ONNX Backends for Python/Numpy runtime (compiled)#

Backend class: OnnxInferenceBackend.

<<<

import unittest
import sys
from datetime import datetime
from contextlib import redirect_stdout, redirect_stderr
from io import StringIO
from onnx.backend.test import BackendTest
from onnx import __version__ as onnx_version
from onnxruntime import __version__ as ort_version
from numpy import __version__ as npy_version
import mlprodict.onnxrt.backend_pyc as backend

back_test = BackendTest(backend, __name__)
back_test.include('.*_cpu')
back_test.exclude('.*_blvc_.*')
back_test.exclude('.*_densenet_.*')
back_test.exclude('.*_densenet121_.*')
back_test.exclude('.*_inception_.*')
back_test.exclude('.*_resnet50_.*')
back_test.exclude('.*_shufflenet_.*')
back_test.exclude('.*_squeezenet_.*')
back_test.exclude('.*_vgg19_.*')
back_test.exclude('.*_zfnet512_.*')
globals().update(back_test.enable_report().test_cases)

print('---------------------------------')
print('python', sys.version)
print('onnx', onnx_version)
print('onnxruntime', ort_version)
print('numpy', npy_version)
print('---------------------------------')
print(datetime.now(), "BEGIN")
print('---------------------------------')

buffer = StringIO()
if True:
    with redirect_stdout(buffer):
        with redirect_stderr(buffer):
            res = unittest.main(verbosity=2, exit=False)
else:
    res = unittest.main(verbosity=2, exit=False)

testsRun = res.result.testsRun
errors = len(res.result.errors)
skipped = len(res.result.skipped)
unexpectedSuccesses = len(res.result.unexpectedSuccesses)
expectedFailures = len(res.result.expectedFailures)

print('---------------------------------')
print(datetime.now(), "END")
print('---------------------------------')

print("testsRun=%d errors=%d skipped=%d" % (testsRun, errors, skipped))
print("unexpectedSuccesses=%d expectedFailures=%d" % (
    unexpectedSuccesses, expectedFailures))
ran = testsRun - skipped
print("ratio=%f" % (1 - errors * 1.0 / ran))
print('---------------------------------')
lines = buffer.getvalue().split('\n')
print("\n".join(line for line in lines
      if "skipped 'no matched include pattern'" not in line))

>>>

    ---------------------------------
    python 3.9.1 (default, Jan 18 2021, 16:35:58) 
    [GCC 8.3.0]
    onnx 1.11.0
    onnxruntime 1.11.0
    numpy 1.21.5
    ---------------------------------
    2022-04-05 07:15:28.466790 BEGIN
    ---------------------------------
    ---------------------------------
    2022-04-05 07:15:57.331689 END
    ---------------------------------
    testsRun=2026 errors=303 skipped=1021
    unexpectedSuccesses=0 expectedFailures=0
    ratio=0.698507
    ---------------------------------
    test_abs_cpu (__main__.OnnxBackendNodeModelTest) ... /var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/npy/xop.py:16: DeprecationWarning: Please use `coo_matrix` from the `scipy.sparse` namespace, the `scipy.sparse.coo` namespace is deprecated.
      from scipy.sparse.coo import coo_matrix
    /var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/_op_numpy_helper.py:8: DeprecationWarning: Please use `coo_matrix` from the `scipy.sparse` namespace, the `scipy.sparse.coo` namespace is deprecated.
      from scipy.sparse.coo import coo_matrix
    /usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py:188: DeprecationWarning: `np.object` is a deprecated alias for the builtin `object`. To silence this warning, use `object` by itself. Doing this will not modify any behavior and is safe. 
    Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
      if ref_outputs[i].dtype == np.object:
    ok
    test_acos_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_acos_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_acosh_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_acosh_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_adagrad_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_adagrad_multiple_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_adam_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_adam_multiple_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_add_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_add_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_add_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_and2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_and3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_and4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_and_bcast3v1d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_and_bcast3v2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_and_bcast4v2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_and_bcast4v3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_and_bcast4v4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmax_default_axis_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmax_default_axis_example_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmax_default_axis_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmax_default_axis_random_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmax_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmax_keepdims_example_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmax_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmax_keepdims_random_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmax_negative_axis_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmax_negative_axis_keepdims_example_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmax_negative_axis_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmax_negative_axis_keepdims_random_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmax_no_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmax_no_keepdims_example_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmax_no_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmax_no_keepdims_random_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmin_default_axis_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmin_default_axis_example_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmin_default_axis_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmin_default_axis_random_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmin_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmin_keepdims_example_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmin_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmin_keepdims_random_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmin_negative_axis_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmin_negative_axis_keepdims_example_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmin_negative_axis_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmin_negative_axis_keepdims_random_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmin_no_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmin_no_keepdims_example_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmin_no_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_argmin_no_keepdims_random_select_last_index_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_asin_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_asin_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_asinh_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_asinh_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_atan_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_atan_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_atanh_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_atanh_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_averagepool_1d_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_averagepool_2d_ceil_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_averagepool_2d_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_averagepool_2d_pads_count_include_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_averagepool_2d_pads_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_averagepool_2d_precomputed_pads_count_include_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_averagepool_2d_precomputed_pads_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_averagepool_2d_precomputed_same_upper_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_averagepool_2d_precomputed_strides_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_averagepool_2d_same_lower_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_averagepool_2d_same_upper_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_averagepool_2d_strides_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_averagepool_3d_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_basic_conv_with_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_basic_conv_without_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_basic_convinteger_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_batchnorm_epsilon_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_batchnorm_epsilon_training_mode_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_batchnorm_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_batchnorm_example_training_mode_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_bernoulli_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_bernoulli_double_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_bernoulli_double_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_bernoulli_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_bernoulli_seed_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_bernoulli_seed_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_bitshift_left_uint16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_bitshift_left_uint32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_bitshift_left_uint64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_bitshift_left_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_bitshift_right_uint16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_bitshift_right_uint32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_bitshift_right_uint64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_bitshift_right_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_cast_BFLOAT16_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_cast_DOUBLE_to_FLOAT16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_cast_DOUBLE_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_cast_FLOAT16_to_DOUBLE_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_cast_FLOAT16_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_cast_FLOAT_to_BFLOAT16_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_cast_FLOAT_to_DOUBLE_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_cast_FLOAT_to_FLOAT16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_cast_FLOAT_to_STRING_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_cast_STRING_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_castlike_BFLOAT16_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_castlike_BFLOAT16_to_FLOAT_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_castlike_DOUBLE_to_FLOAT16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_castlike_DOUBLE_to_FLOAT16_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_castlike_DOUBLE_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_castlike_DOUBLE_to_FLOAT_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_castlike_FLOAT16_to_DOUBLE_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_castlike_FLOAT16_to_DOUBLE_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_castlike_FLOAT16_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_castlike_FLOAT16_to_FLOAT_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_castlike_FLOAT_to_BFLOAT16_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_castlike_FLOAT_to_BFLOAT16_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_castlike_FLOAT_to_DOUBLE_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_castlike_FLOAT_to_DOUBLE_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_castlike_FLOAT_to_FLOAT16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_castlike_FLOAT_to_FLOAT16_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_castlike_FLOAT_to_STRING_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_castlike_FLOAT_to_STRING_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_castlike_STRING_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_castlike_STRING_to_FLOAT_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_ceil_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_ceil_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_celu_cpu (__main__.OnnxBackendNodeModelTest) ... /var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_celu.py:47: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
    Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
      lambda x: pycelu(x, self.alpha), otypes=[numpy.float])
    ok
    test_celu_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_clip_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_clip_default_inbounds_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_clip_default_int8_inbounds_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_clip_default_int8_max_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_clip_default_int8_min_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_clip_default_max_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_clip_default_min_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_clip_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_clip_inbounds_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_clip_outbounds_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_clip_splitbounds_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_compress_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_compress_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_compress_default_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_compress_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_concat_1d_axis_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_concat_1d_axis_negative_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_concat_2d_axis_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_concat_2d_axis_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_concat_2d_axis_negative_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_concat_2d_axis_negative_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_concat_3d_axis_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_concat_3d_axis_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_concat_3d_axis_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_concat_3d_axis_negative_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_concat_3d_axis_negative_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_concat_3d_axis_negative_3_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_constant_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_constant_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_constantofshape_float_ones_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_constantofshape_int_shape_zero_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_constantofshape_int_zeros_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_conv_with_autopad_same_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_conv_with_strides_and_asymmetric_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_conv_with_strides_no_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_conv_with_strides_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_convinteger_with_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_convinteger_without_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_convtranspose_1d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_convtranspose_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_convtranspose_autopad_same_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_convtranspose_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_convtranspose_dilations_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_convtranspose_kernel_shape_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_convtranspose_output_shape_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_convtranspose_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_convtranspose_pads_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_convtranspose_with_kernel_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_cos_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_cos_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_cosh_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_cosh_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_cumsum_1d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_cumsum_1d_exclusive_cpu (__main__.OnnxBackendNodeModelTest) ... /var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_cum_sum.py:50: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
      numpy.cumsum(x[indices_c], axis=axis, out=res[indices_d])
    ok
    test_cumsum_1d_reverse_cpu (__main__.OnnxBackendNodeModelTest) ... /var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_cum_sum.py:43: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
      x = x[rev_indices]
    /var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_cum_sum.py:57: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.
      res = res[rev_indices]
    ok
    test_cumsum_1d_reverse_exclusive_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_cumsum_2d_axis_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_cumsum_2d_axis_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_cumsum_2d_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_depthtospace_crd_mode_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_depthtospace_crd_mode_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_depthtospace_dcr_mode_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_depthtospace_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_dequantizelinear_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_dequantizelinear_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_det_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_det_nd_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_div_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_div_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_div_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_div_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_dropout_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_dropout_default_mask_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_dropout_default_mask_ratio_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_dropout_default_old_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_dropout_default_ratio_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_dropout_random_old_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_dynamicquantizelinear_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_dynamicquantizelinear_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_dynamicquantizelinear_max_adjusted_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_dynamicquantizelinear_max_adjusted_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_dynamicquantizelinear_min_adjusted_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_dynamicquantizelinear_min_adjusted_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_edge_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_einsum_batch_diagonal_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_einsum_batch_matmul_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_einsum_inner_prod_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_einsum_sum_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_einsum_transpose_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_elu_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_elu_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_elu_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_equal_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_equal_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_erf_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_exp_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_exp_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_expand_dim_changed_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_expand_dim_unchanged_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_eyelike_populate_off_main_diagonal_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_eyelike_with_dtype_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_eyelike_without_dtype_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_flatten_axis0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_flatten_axis1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_flatten_axis2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_flatten_axis3_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_flatten_default_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_flatten_negative_axis1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_flatten_negative_axis2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_flatten_negative_axis3_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_flatten_negative_axis4_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_floor_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_floor_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gather_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gather_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gather_2d_indices_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gather_elements_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gather_elements_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gather_elements_negative_indices_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gather_negative_indices_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gathernd_example_float32_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_gathernd_example_int32_batch_dim1_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_gathernd_example_int32_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_gemm_all_attributes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gemm_alpha_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gemm_beta_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gemm_default_matrix_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gemm_default_no_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gemm_default_scalar_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gemm_default_single_elem_vector_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gemm_default_vector_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gemm_default_zero_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gemm_transposeA_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gemm_transposeB_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_globalaveragepool_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_globalaveragepool_precomputed_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_globalmaxpool_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_globalmaxpool_precomputed_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_greater_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_greater_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_greater_equal_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_greater_equal_bcast_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_greater_equal_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_greater_equal_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_gridsample_aligncorners_true_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_gridsample_bicubic_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_gridsample_bilinear_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_gridsample_border_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_gridsample_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_gridsample_nearest_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_gridsample_reflection_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_gridsample_zeros_padding_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_gru_batchwise_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_gru_defaults_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_gru_seq_length_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_gru_with_initial_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_hardmax_axis_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_hardmax_axis_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_hardmax_axis_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_hardmax_default_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_hardmax_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_hardmax_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_hardmax_one_hot_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_hardsigmoid_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_hardsigmoid_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_hardsigmoid_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_hardswish_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_hardswish_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_identity_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_identity_opt_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_identity_sequence_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_if_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_if_opt_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_if_seq_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_instancenorm_epsilon_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_instancenorm_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_isinf_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_isinf_negative_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_isinf_positive_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_isnan_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_leakyrelu_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_leakyrelu_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_leakyrelu_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_less_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_less_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_less_equal_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_less_equal_bcast_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_less_equal_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_less_equal_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_log_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_log_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_logsoftmax_axis_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_logsoftmax_axis_0_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_logsoftmax_axis_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_logsoftmax_axis_1_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_logsoftmax_axis_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_logsoftmax_axis_2_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_logsoftmax_default_axis_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_logsoftmax_default_axis_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_logsoftmax_example_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_logsoftmax_example_1_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_logsoftmax_large_number_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_logsoftmax_large_number_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_logsoftmax_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_logsoftmax_negative_axis_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_loop11_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_loop13_seq_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_loop16_seq_none_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_lrn_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_lrn_default_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_lstm_batchwise_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_lstm_defaults_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_lstm_with_initial_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_lstm_with_peepholes_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_matmul_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_matmul_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_matmul_4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_matmulinteger_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_max_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_max_float16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_max_float32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_max_float64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_max_int16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_max_int32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_max_int64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_max_int8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_max_one_input_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_max_two_inputs_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_max_uint16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_max_uint32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_max_uint64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_max_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_maxpool_1d_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_maxpool_2d_ceil_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_maxpool_2d_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_maxpool_2d_dilations_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_maxpool_2d_pads_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_maxpool_2d_precomputed_pads_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_maxpool_2d_precomputed_same_upper_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_maxpool_2d_precomputed_strides_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_maxpool_2d_same_lower_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_maxpool_2d_same_upper_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_maxpool_2d_strides_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_maxpool_2d_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_maxpool_3d_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_maxpool_with_argmax_2d_precomputed_pads_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_maxpool_with_argmax_2d_precomputed_strides_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_maxunpool_export_with_output_shape_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_maxunpool_export_without_output_shape_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_mean_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_mean_one_input_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_mean_two_inputs_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_min_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_min_float16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_min_float32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_min_float64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_min_int16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_min_int32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_min_int64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_min_int8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_min_one_input_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_min_two_inputs_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_min_uint16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_min_uint32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_min_uint64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_min_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_mod_broadcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_mod_int64_fmod_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_mod_mixed_sign_float16_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_mod_mixed_sign_float32_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_mod_mixed_sign_float64_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_mod_mixed_sign_int16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_mod_mixed_sign_int32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_mod_mixed_sign_int64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_mod_mixed_sign_int8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_mod_uint16_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_mod_uint32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_mod_uint64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_mod_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_momentum_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_momentum_multiple_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_mul_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_mul_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_mul_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_mul_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_mvn_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_mvn_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_neg_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nesterov_momentum_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nllloss_NC_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NC_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nllloss_NCd1_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1_mean_weight_negative_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nllloss_NCd1_mean_weight_negative_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1_weight_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nllloss_NCd1_weight_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1_weight_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nllloss_NCd1_weight_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2_no_weight_reduction_mean_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nllloss_NCd1d2_no_weight_reduction_mean_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2_reduction_mean_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2_reduction_mean_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2_reduction_sum_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2_reduction_sum_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2_with_weight_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2_with_weight_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2_with_weight_reduction_mean_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nllloss_NCd1d2_with_weight_reduction_mean_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2_with_weight_reduction_sum_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2_with_weight_reduction_sum_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2_with_weight_reduction_sum_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2_with_weight_reduction_sum_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2d3_none_no_weight_negative_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2d3_none_no_weight_negative_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2d3_sum_weight_high_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2d3_sum_weight_high_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2d3d4d5_mean_weight_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nllloss_NCd1d2d3d4d5_mean_weight_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2d3d4d5_none_no_weight_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nllloss_NCd1d2d3d4d5_none_no_weight_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_nonmaxsuppression_center_point_box_format_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nonmaxsuppression_flipped_coordinates_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nonmaxsuppression_identical_boxes_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nonmaxsuppression_limit_output_size_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nonmaxsuppression_single_box_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nonmaxsuppression_suppress_by_IOU_and_scores_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nonmaxsuppression_suppress_by_IOU_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nonmaxsuppression_two_batches_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nonmaxsuppression_two_classes_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_nonzero_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_not_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_not_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_not_4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_onehot_negative_indices_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_onehot_with_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_onehot_with_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_onehot_without_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_optional_get_element_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_optional_get_element_sequence_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_optional_has_element_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_optional_has_element_empty_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_or2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_or3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_or4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_or_bcast3v1d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_or_bcast3v2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_or_bcast4v2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_or_bcast4v3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_or_bcast4v4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_pow_bcast_array_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_pow_bcast_scalar_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_pow_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_pow_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_pow_types_float32_int32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_pow_types_float32_int64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_pow_types_float32_uint32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_pow_types_float32_uint64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_pow_types_float_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_pow_types_int32_float32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_pow_types_int32_int32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_pow_types_int64_float32_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_pow_types_int64_int64_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_pow_types_int_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_prelu_broadcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_prelu_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_qlinearconv_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_qlinearmatmul_2D_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_qlinearmatmul_3D_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_quantizelinear_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_quantizelinear_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_range_float_type_positive_delta_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_range_float_type_positive_delta_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_range_int32_type_negative_delta_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_range_int32_type_negative_delta_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_reciprocal_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reciprocal_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_l1_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_l1_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_l1_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_l1_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_l1_keep_dims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_l1_keep_dims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_l1_negative_axes_keep_dims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_l1_negative_axes_keep_dims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_l2_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_l2_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_l2_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_l2_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_l2_keep_dims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_l2_keep_dims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_l2_negative_axes_keep_dims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_l2_negative_axes_keep_dims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_log_sum_asc_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_log_sum_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_log_sum_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_log_sum_desc_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_log_sum_exp_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_log_sum_exp_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_log_sum_exp_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_log_sum_exp_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_log_sum_exp_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_log_sum_exp_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_log_sum_exp_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_log_sum_exp_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_log_sum_negative_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_max_default_axes_keepdim_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_max_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_max_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_max_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_max_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_max_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_max_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_max_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_mean_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_mean_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_mean_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_mean_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_mean_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_mean_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_mean_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_mean_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_min_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_min_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_min_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_min_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_min_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_min_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_min_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_min_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_prod_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_prod_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_prod_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_prod_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_prod_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_prod_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_prod_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_prod_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... /var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_reduce_sum.py:75: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.
      return (numpy.sum(data, axis=axes if axes else None,
    ok
    test_reduce_sum_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_empty_axes_input_noop_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_empty_axes_input_noop_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_square_default_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_square_default_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_square_do_not_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_square_do_not_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_square_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_square_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_square_negative_axes_keepdims_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reduce_sum_square_negative_axes_keepdims_random_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reflect_pad_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_relu_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reshape_allowzero_reordered_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_reshape_extended_dims_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reshape_negative_dim_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reshape_negative_extended_dims_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reshape_one_dim_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reshape_reduced_dims_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reshape_reordered_all_dims_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reshape_reordered_last_dims_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reshape_zero_and_negative_dim_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_reshape_zero_dim_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_resize_downsample_scales_cubic_A_n0p5_exclude_outside_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_downsample_scales_cubic_align_corners_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_downsample_scales_cubic_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_downsample_scales_linear_align_corners_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_downsample_scales_linear_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_downsample_scales_nearest_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_downsample_sizes_cubic_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_downsample_sizes_linear_pytorch_half_pixel_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_downsample_sizes_nearest_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_downsample_sizes_nearest_tf_half_pixel_for_nn_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_tf_crop_and_resize_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_upsample_scales_cubic_A_n0p5_exclude_outside_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_upsample_scales_cubic_align_corners_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_upsample_scales_cubic_asymmetric_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_upsample_scales_cubic_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_upsample_scales_linear_align_corners_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_upsample_scales_linear_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_upsample_scales_nearest_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_upsample_sizes_cubic_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_upsample_sizes_nearest_ceil_half_pixel_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_upsample_sizes_nearest_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_upsample_sizes_nearest_floor_align_corners_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_reversesequence_batch_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_reversesequence_time_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_rnn_seq_length_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_roialign_aligned_false_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_roialign_aligned_true_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_round_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_scan9_sum_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_scan_sum_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_scatter_elements_with_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_scatter_elements_with_duplicate_indices_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_scatter_elements_with_negative_indices_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_scatter_elements_without_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_scatter_with_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_scatter_without_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_scatternd_add_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_scatternd_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_scatternd_multiply_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_NCd1_mean_weight_negative_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_NCd1_mean_weight_negative_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_NCd1_mean_weight_negative_ii_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_NCd1_mean_weight_negative_ii_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_NCd1d2d3_none_no_weight_negative_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_NCd1d2d3_none_no_weight_negative_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_NCd1d2d3_none_no_weight_negative_ii_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_NCd1d2d3_sum_weight_high_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_NCd1d2d3_sum_weight_high_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_NCd1d2d3_sum_weight_high_ii_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_NCd1d2d3_sum_weight_high_ii_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_NCd1d2d3d4d5_mean_weight_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_NCd1d2d3d4d5_mean_weight_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_NCd1d2d3d4d5_mean_weight_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_NCd1d2d3d4d5_mean_weight_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_NCd1d2d3d4d5_none_no_weight_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_NCd1d2d3d4d5_none_no_weight_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_NCd1d2d3d4d5_none_no_weight_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_NCd1d2d3d4d5_none_no_weight_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_3d_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_3d_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_3d_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_no_weight_ii_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_no_weight_ii_3d_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_mean_no_weight_ii_3d_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_no_weight_ii_3d_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_mean_no_weight_ii_4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_no_weight_ii_4d_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_mean_no_weight_ii_4d_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_no_weight_ii_4d_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_mean_no_weight_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_no_weight_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_mean_no_weight_ii_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_no_weight_ii_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_mean_weight_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_weight_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_mean_weight_ii_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_weight_ii_3d_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_mean_weight_ii_3d_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_weight_ii_3d_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_mean_weight_ii_4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_weight_ii_4d_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_mean_weight_ii_4d_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_weight_ii_4d_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_mean_weight_ii_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_weight_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_mean_weight_ii_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_weight_ii_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_mean_weight_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_mean_weight_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sce_none_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_none_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_none_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_none_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_none_weights_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_none_weights_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_none_weights_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_none_weights_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_sum_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_sum_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_sum_log_prob_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sce_sum_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_selu_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_selu_default_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_selu_example_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_sequence_insert_at_back_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sequence_insert_at_front_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_shape_clip_end_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_shape_clip_start_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_shape_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_shape_end_1_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_shape_end_negative_1_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_shape_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_shape_start_1_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_shape_start_1_end_2_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_shape_start_1_end_negative_1_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_shape_start_negative_1_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_shrink_hard_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_shrink_soft_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sigmoid_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sigmoid_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sign_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_simple_rnn_batchwise_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_simple_rnn_defaults_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_simple_rnn_with_initial_bias_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_sin_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sin_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sinh_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sinh_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_size_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_size_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_slice_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_slice_default_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_slice_default_steps_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_slice_end_out_of_bounds_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_slice_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_slice_neg_steps_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_slice_negative_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_slice_start_out_of_bounds_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_softmax_axis_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_softmax_axis_0_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_softmax_axis_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_softmax_axis_1_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_softmax_axis_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_softmax_axis_2_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_softmax_default_axis_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_softmax_default_axis_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_softmax_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_softmax_example_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_softmax_large_number_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_softmax_large_number_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_softmax_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_softmax_negative_axis_expanded_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_softplus_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_softplus_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_softsign_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_softsign_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_spacetodepth_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_spacetodepth_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_split_equal_parts_1d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_split_equal_parts_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_split_equal_parts_default_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_split_variable_parts_1d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_split_variable_parts_2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_split_variable_parts_default_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_split_zero_size_splits_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sqrt_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sqrt_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_squeeze_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_squeeze_negative_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_strnormalizer_export_monday_casesensintive_lower_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_strnormalizer_export_monday_casesensintive_nochangecase_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_strnormalizer_export_monday_casesensintive_upper_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_strnormalizer_export_monday_empty_output_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_strnormalizer_export_monday_insensintive_upper_twodim_cpu (__main__.OnnxBackendNodeModelTest) ... FAIL
    test_strnormalizer_nostopwords_nochangecase_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sub_bcast_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sub_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sub_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sub_uint8_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sum_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sum_one_input_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_sum_two_inputs_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tan_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tan_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tanh_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tanh_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tfidfvectorizer_tf_batch_onlybigrams_skip0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tfidfvectorizer_tf_batch_onlybigrams_skip5_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tfidfvectorizer_tf_batch_uniandbigrams_skip5_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tfidfvectorizer_tf_only_bigrams_skip0_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_tfidfvectorizer_tf_onlybigrams_levelempty_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_tfidfvectorizer_tf_onlybigrams_skip5_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_tfidfvectorizer_tf_uniandbigrams_skip5_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_thresholdedrelu_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_thresholdedrelu_default_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_thresholdedrelu_example_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_tile_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_tile_precomputed_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_top_k_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_top_k_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_top_k_smallest_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_training_dropout_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_training_dropout_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_training_dropout_default_mask_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_training_dropout_mask_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_training_dropout_zero_ratio_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_training_dropout_zero_ratio_mask_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_transpose_all_permutations_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_transpose_all_permutations_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_transpose_all_permutations_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_transpose_all_permutations_3_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_transpose_all_permutations_4_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_transpose_all_permutations_5_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_transpose_default_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tril_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tril_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tril_one_row_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tril_out_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tril_out_pos_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tril_pos_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tril_square_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tril_square_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_tril_zero_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_triu_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_triu_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_triu_one_row_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_triu_out_neg_out_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_triu_out_pos_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_triu_pos_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_triu_square_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_triu_square_neg_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_triu_zero_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_unique_not_sorted_without_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_unique_sorted_with_axis_3d_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_unique_sorted_with_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_unique_sorted_with_negative_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_unique_sorted_without_axis_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_unsqueeze_axis_0_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_unsqueeze_axis_1_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_unsqueeze_axis_2_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_unsqueeze_axis_3_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_unsqueeze_negative_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_unsqueeze_three_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_unsqueeze_two_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_unsqueeze_unsorted_axes_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_upsample_nearest_cpu (__main__.OnnxBackendNodeModelTest) ... ERROR
    test_where_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_where_long_example_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_xor2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_xor3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_xor4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_xor_bcast3v1d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_xor_bcast3v2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_xor_bcast4v2d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_xor_bcast4v3d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_xor_bcast4v4d_cpu (__main__.OnnxBackendNodeModelTest) ... ok
    test_AvgPool1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_AvgPool1d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_AvgPool2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_AvgPool2d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_AvgPool3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_AvgPool3d_stride1_pad0_gpu_input_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_AvgPool3d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_BatchNorm1d_3d_input_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_BatchNorm2d_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_BatchNorm2d_momentum_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_BatchNorm3d_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_BatchNorm3d_momentum_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_ConstantPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv1d_dilated_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv1d_groups_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv1d_pad1_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv1d_pad1size1_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv1d_pad2_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv1d_pad2size1_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv1d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv2d_depthwise_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv2d_depthwise_padded_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv2d_depthwise_strided_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv2d_depthwise_with_multiplier_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv2d_dilated_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv2d_groups_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv2d_groups_thnn_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv2d_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv2d_padding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv2d_strided_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv3d_dilated_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv3d_dilated_strided_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv3d_groups_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv3d_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv3d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Conv3d_stride_padding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_ConvTranspose2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_ConvTranspose2d_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_ELU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Embedding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Embedding_sparse_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_GLU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_GLU_dim_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_LeakyReLU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_LeakyReLU_with_negval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Linear_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Linear_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_LogSoftmax_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_MaxPool1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_MaxPool1d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_MaxPool1d_stride_padding_dilation_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
    test_MaxPool2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_MaxPool2d_stride_padding_dilation_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ok
    test_MaxPool3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_MaxPool3d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_MaxPool3d_stride_padding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_PReLU_1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_PReLU_1d_multiparam_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_PReLU_2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_PReLU_2d_multiparam_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_PReLU_3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_PReLU_3d_multiparam_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_PixelShuffle_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_PoissonNLLLLoss_no_reduce_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_ReLU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_ReflectionPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_ReplicationPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_SELU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Sigmoid_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Softmax_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Softmin_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Softplus_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Softsign_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_Tanh_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_ZeroPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_log_softmax_dim3_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_log_softmax_lastdim_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_softmax_functional_dim3_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_softmax_lastdim_cpu (__main__.OnnxBackendPyTorchConvertedModelTest) ... ERROR
    test_operator_add_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_add_size1_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_add_size1_right_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_add_size1_singleton_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_addconstant_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_addmm_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_basic_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_chunk_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_clip_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_concat2_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_conv_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_convtranspose_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_exp_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_flatten_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_index_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_max_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_maxpool_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_min_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_mm_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_non_float_params_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_pad_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_params_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_permute2_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_pow_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_reduced_mean_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_reduced_mean_keepdim_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_reduced_sum_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_reduced_sum_keepdim_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_repeat_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_repeat_dim_overflow_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_selu_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_sqrt_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_symbolic_override_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_symbolic_override_nested_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_operator_view_cpu (__main__.OnnxBackendPyTorchOperatorModelTest) ... ERROR
    test_bvlc_alexnet_cpu (__main__.OnnxBackendRealModelTest) ... ERROR
    test_densenet121_cpu (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_densenet121_.*"'
    test_densenet121_cuda (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_densenet121_.*"'
    test_inception_v1_cpu (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_inception_.*"'
    test_inception_v1_cuda (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_inception_.*"'
    test_inception_v2_cpu (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_inception_.*"'
    test_inception_v2_cuda (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_inception_.*"'
    test_resnet50_cpu (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_resnet50_.*"'
    test_resnet50_cuda (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_resnet50_.*"'
    test_shufflenet_cpu (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_shufflenet_.*"'
    test_shufflenet_cuda (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_shufflenet_.*"'
    test_squeezenet_cpu (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_squeezenet_.*"'
    test_squeezenet_cuda (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_squeezenet_.*"'
    test_vgg19_cpu (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_vgg19_.*"'
    test_vgg19_cuda (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_vgg19_.*"'
    test_zfnet512_cpu (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_zfnet512_.*"'
    test_zfnet512_cuda (__main__.OnnxBackendRealModelTest) ... skipped 'matched exclude pattern ".*_zfnet512_.*"'
    test_expand_shape_model1_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
    test_expand_shape_model2_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
    test_expand_shape_model3_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
    test_expand_shape_model4_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
    test_gradient_of_add_and_mul_cpu (__main__.OnnxBackendSimpleModelTest) ... ERROR
    test_gradient_of_add_cpu (__main__.OnnxBackendSimpleModelTest) ... ERROR
    test_sequence_model1_cpu (__main__.OnnxBackendSimpleModelTest) ... ERROR
    test_sequence_model2_cpu (__main__.OnnxBackendSimpleModelTest) ... ERROR
    test_sequence_model3_cpu (__main__.OnnxBackendSimpleModelTest) ... ERROR
    test_sequence_model4_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
    test_sequence_model5_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
    test_sequence_model6_cpu (__main__.OnnxBackendSimpleModelTest) ... ERROR
    test_sequence_model7_cpu (__main__.OnnxBackendSimpleModelTest) ... ERROR
    test_sequence_model8_cpu (__main__.OnnxBackendSimpleModelTest) ... ERROR
    test_shrink_cpu (__main__.OnnxBackendSimpleModelTest) ... ERROR
    test_sign_model_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
    test_single_relu_model_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
    test_strnorm_model_monday_casesensintive_lower_cpu (__main__.OnnxBackendSimpleModelTest) ... FAIL
    test_strnorm_model_monday_casesensintive_nochangecase_cpu (__main__.OnnxBackendSimpleModelTest) ... FAIL
    test_strnorm_model_monday_casesensintive_upper_cpu (__main__.OnnxBackendSimpleModelTest) ... FAIL
    test_strnorm_model_monday_empty_output_cpu (__main__.OnnxBackendSimpleModelTest) ... FAIL
    test_strnorm_model_monday_insensintive_upper_twodim_cpu (__main__.OnnxBackendSimpleModelTest) ... FAIL
    test_strnorm_model_nostopwords_nochangecase_cpu (__main__.OnnxBackendSimpleModelTest) ... ok
    
    ======================================================================
    ERROR: test_adagrad_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Adagrad' from domain 'ai.onnx.preview.training' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_adagrad_multiple_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Adagrad' from domain 'ai.onnx.preview.training' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_adam_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Adam' from domain 'ai.onnx.preview.training' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_adam_multiple_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Adam' from domain 'ai.onnx.preview.training' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_basic_convinteger_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'ConvInteger' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_bernoulli_seed_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "_mt19937.pyx", line 178, in numpy.random._mt19937.MT19937._legacy_seeding
    TypeError: 'float' object cannot be interpreted as an integer
    
    During handling of the above exception, another exception occurred:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 6, in compiled_run
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_random.py", line 85, in _run
        state = self._get_state(self.seed)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_random.py", line 66, in _get_state
        state = numpy.random.RandomState(seed=self.seed)
      File "mtrand.pyx", line 185, in numpy.random.mtrand.RandomState.__init__
      File "_mt19937.pyx", line 166, in numpy.random._mt19937.MT19937._legacy_seeding
      File "_mt19937.pyx", line 186, in numpy.random._mt19937.MT19937._legacy_seeding
    TypeError: Cannot cast scalar from dtype('float64') to dtype('int64') according to the rule 'safe'
    
    ======================================================================
    ERROR: test_bernoulli_seed_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "_mt19937.pyx", line 178, in numpy.random._mt19937.MT19937._legacy_seeding
    TypeError: 'float' object cannot be interpreted as an integer
    
    During handling of the above exception, another exception occurred:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 6, in compiled_run
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_random.py", line 155, in _run
        state = self._get_state(self.seed)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_random.py", line 66, in _get_state
        state = numpy.random.RandomState(seed=self.seed)
      File "mtrand.pyx", line 185, in numpy.random.mtrand.RandomState.__init__
      File "_mt19937.pyx", line 166, in numpy.random._mt19937.MT19937._legacy_seeding
      File "_mt19937.pyx", line 186, in numpy.random._mt19937.MT19937._legacy_seeding
    TypeError: Cannot cast scalar from dtype('float64') to dtype('int64') according to the rule 'safe'
    
    ======================================================================
    ERROR: test_cast_BFLOAT16_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 187, in _init
        self.graph_ = self.to_sequence(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 595, in to_sequence
        variables[obj.name] = _var_as_dict(obj)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 362, in _var_as_dict
        elem_type = _elem_type_as_str(t.elem_type)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 292, in _elem_type_as_str
        raise NotImplementedError(  # pragma: no cover
    NotImplementedError: elem_type '16' is unknown
    fields:
    ['__abs__',
     '__add__',
     '__and__',
     '__bool__',
     '__ceil__',
     '__class__',
     '__delattr__',
     '__dir__',
     '__divmod__',
     '__doc__',
     '__eq__',
     '__float__',
     '__floor__',
     '__floordiv__',
     '__format__',
     '__ge__',
     '__getattribute__',
     '__getnewargs__',
     '__gt__',
     '__hash__',
     '__index__',
     '__init__',
     '__init_subclass__',
     '__int__',
     '__invert__',
     '__le__',
     '__lshift__',
     '__lt__',
     '__mod__',
     '__mul__',
     '__ne__',
     '__neg__',
     '__new__',
     '__or__',
     '__pos__',
     '__pow__',
     '__radd__',
     '__rand__',
     '__rdivmod__',
     '__reduce__',
     '__reduce_ex__',
     '__repr__',
     '__rfloordiv__',
     '__rlshift__',
     '__rmod__',
     '__rmul__',
     '__ror__',
     '__round__',
     '__rpow__',
     '__rrshift__',
     '__rshift__',
     '__rsub__',
     '__rtruediv__',
     '__rxor__',
     '__setattr__',
     '__sizeof__',
     '__str__',
     '__sub__',
     '__subclasshook__',
     '__truediv__',
     '__trunc__',
     '__xor__',
     'as_integer_ratio',
     'bit_length',
     'conjugate',
     'denominator',
     'from_bytes',
     'imag',
     'numerator',
     'real',
     'to_bytes']
    -----
    <class 'int'>.
    
    ======================================================================
    ERROR: test_cast_FLOAT_to_BFLOAT16_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 187, in _init
        self.graph_ = self.to_sequence(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 605, in to_sequence
        outputs[obj.name] = _var_as_dict(obj)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 362, in _var_as_dict
        elem_type = _elem_type_as_str(t.elem_type)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 292, in _elem_type_as_str
        raise NotImplementedError(  # pragma: no cover
    NotImplementedError: elem_type '16' is unknown
    fields:
    ['__abs__',
     '__add__',
     '__and__',
     '__bool__',
     '__ceil__',
     '__class__',
     '__delattr__',
     '__dir__',
     '__divmod__',
     '__doc__',
     '__eq__',
     '__float__',
     '__floor__',
     '__floordiv__',
     '__format__',
     '__ge__',
     '__getattribute__',
     '__getnewargs__',
     '__gt__',
     '__hash__',
     '__index__',
     '__init__',
     '__init_subclass__',
     '__int__',
     '__invert__',
     '__le__',
     '__lshift__',
     '__lt__',
     '__mod__',
     '__mul__',
     '__ne__',
     '__neg__',
     '__new__',
     '__or__',
     '__pos__',
     '__pow__',
     '__radd__',
     '__rand__',
     '__rdivmod__',
     '__reduce__',
     '__reduce_ex__',
     '__repr__',
     '__rfloordiv__',
     '__rlshift__',
     '__rmod__',
     '__rmul__',
     '__ror__',
     '__round__',
     '__rpow__',
     '__rrshift__',
     '__rshift__',
     '__rsub__',
     '__rtruediv__',
     '__rxor__',
     '__setattr__',
     '__sizeof__',
     '__str__',
     '__sub__',
     '__subclasshook__',
     '__truediv__',
     '__trunc__',
     '__xor__',
     'as_integer_ratio',
     'bit_length',
     'conjugate',
     'denominator',
     'from_bytes',
     'imag',
     'numerator',
     'real',
     'to_bytes']
    -----
    <class 'int'>.
    
    ======================================================================
    ERROR: test_castlike_BFLOAT16_to_FLOAT_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 187, in _init
        self.graph_ = self.to_sequence(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 595, in to_sequence
        variables[obj.name] = _var_as_dict(obj)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 362, in _var_as_dict
        elem_type = _elem_type_as_str(t.elem_type)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 292, in _elem_type_as_str
        raise NotImplementedError(  # pragma: no cover
    NotImplementedError: elem_type '16' is unknown
    fields:
    ['__abs__',
     '__add__',
     '__and__',
     '__bool__',
     '__ceil__',
     '__class__',
     '__delattr__',
     '__dir__',
     '__divmod__',
     '__doc__',
     '__eq__',
     '__float__',
     '__floor__',
     '__floordiv__',
     '__format__',
     '__ge__',
     '__getattribute__',
     '__getnewargs__',
     '__gt__',
     '__hash__',
     '__index__',
     '__init__',
     '__init_subclass__',
     '__int__',
     '__invert__',
     '__le__',
     '__lshift__',
     '__lt__',
     '__mod__',
     '__mul__',
     '__ne__',
     '__neg__',
     '__new__',
     '__or__',
     '__pos__',
     '__pow__',
     '__radd__',
     '__rand__',
     '__rdivmod__',
     '__reduce__',
     '__reduce_ex__',
     '__repr__',
     '__rfloordiv__',
     '__rlshift__',
     '__rmod__',
     '__rmul__',
     '__ror__',
     '__round__',
     '__rpow__',
     '__rrshift__',
     '__rshift__',
     '__rsub__',
     '__rtruediv__',
     '__rxor__',
     '__setattr__',
     '__sizeof__',
     '__str__',
     '__sub__',
     '__subclasshook__',
     '__truediv__',
     '__trunc__',
     '__xor__',
     'as_integer_ratio',
     'bit_length',
     'conjugate',
     'denominator',
     'from_bytes',
     'imag',
     'numerator',
     'real',
     'to_bytes']
    -----
    <class 'int'>.
    
    ======================================================================
    ERROR: test_castlike_BFLOAT16_to_FLOAT_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 187, in _init
        self.graph_ = self.to_sequence(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 595, in to_sequence
        variables[obj.name] = _var_as_dict(obj)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 362, in _var_as_dict
        elem_type = _elem_type_as_str(t.elem_type)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 292, in _elem_type_as_str
        raise NotImplementedError(  # pragma: no cover
    NotImplementedError: elem_type '16' is unknown
    fields:
    ['__abs__',
     '__add__',
     '__and__',
     '__bool__',
     '__ceil__',
     '__class__',
     '__delattr__',
     '__dir__',
     '__divmod__',
     '__doc__',
     '__eq__',
     '__float__',
     '__floor__',
     '__floordiv__',
     '__format__',
     '__ge__',
     '__getattribute__',
     '__getnewargs__',
     '__gt__',
     '__hash__',
     '__index__',
     '__init__',
     '__init_subclass__',
     '__int__',
     '__invert__',
     '__le__',
     '__lshift__',
     '__lt__',
     '__mod__',
     '__mul__',
     '__ne__',
     '__neg__',
     '__new__',
     '__or__',
     '__pos__',
     '__pow__',
     '__radd__',
     '__rand__',
     '__rdivmod__',
     '__reduce__',
     '__reduce_ex__',
     '__repr__',
     '__rfloordiv__',
     '__rlshift__',
     '__rmod__',
     '__rmul__',
     '__ror__',
     '__round__',
     '__rpow__',
     '__rrshift__',
     '__rshift__',
     '__rsub__',
     '__rtruediv__',
     '__rxor__',
     '__setattr__',
     '__sizeof__',
     '__str__',
     '__sub__',
     '__subclasshook__',
     '__truediv__',
     '__trunc__',
     '__xor__',
     'as_integer_ratio',
     'bit_length',
     'conjugate',
     'denominator',
     'from_bytes',
     'imag',
     'numerator',
     'real',
     'to_bytes']
    -----
    <class 'int'>.
    
    ======================================================================
    ERROR: test_castlike_FLOAT_to_BFLOAT16_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 187, in _init
        self.graph_ = self.to_sequence(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 595, in to_sequence
        variables[obj.name] = _var_as_dict(obj)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 362, in _var_as_dict
        elem_type = _elem_type_as_str(t.elem_type)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 292, in _elem_type_as_str
        raise NotImplementedError(  # pragma: no cover
    NotImplementedError: elem_type '16' is unknown
    fields:
    ['__abs__',
     '__add__',
     '__and__',
     '__bool__',
     '__ceil__',
     '__class__',
     '__delattr__',
     '__dir__',
     '__divmod__',
     '__doc__',
     '__eq__',
     '__float__',
     '__floor__',
     '__floordiv__',
     '__format__',
     '__ge__',
     '__getattribute__',
     '__getnewargs__',
     '__gt__',
     '__hash__',
     '__index__',
     '__init__',
     '__init_subclass__',
     '__int__',
     '__invert__',
     '__le__',
     '__lshift__',
     '__lt__',
     '__mod__',
     '__mul__',
     '__ne__',
     '__neg__',
     '__new__',
     '__or__',
     '__pos__',
     '__pow__',
     '__radd__',
     '__rand__',
     '__rdivmod__',
     '__reduce__',
     '__reduce_ex__',
     '__repr__',
     '__rfloordiv__',
     '__rlshift__',
     '__rmod__',
     '__rmul__',
     '__ror__',
     '__round__',
     '__rpow__',
     '__rrshift__',
     '__rshift__',
     '__rsub__',
     '__rtruediv__',
     '__rxor__',
     '__setattr__',
     '__sizeof__',
     '__str__',
     '__sub__',
     '__subclasshook__',
     '__truediv__',
     '__trunc__',
     '__xor__',
     'as_integer_ratio',
     'bit_length',
     'conjugate',
     'denominator',
     'from_bytes',
     'imag',
     'numerator',
     'real',
     'to_bytes']
    -----
    <class 'int'>.
    
    ======================================================================
    ERROR: test_castlike_FLOAT_to_BFLOAT16_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 187, in _init
        self.graph_ = self.to_sequence(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 595, in to_sequence
        variables[obj.name] = _var_as_dict(obj)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 362, in _var_as_dict
        elem_type = _elem_type_as_str(t.elem_type)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 292, in _elem_type_as_str
        raise NotImplementedError(  # pragma: no cover
    NotImplementedError: elem_type '16' is unknown
    fields:
    ['__abs__',
     '__add__',
     '__and__',
     '__bool__',
     '__ceil__',
     '__class__',
     '__delattr__',
     '__dir__',
     '__divmod__',
     '__doc__',
     '__eq__',
     '__float__',
     '__floor__',
     '__floordiv__',
     '__format__',
     '__ge__',
     '__getattribute__',
     '__getnewargs__',
     '__gt__',
     '__hash__',
     '__index__',
     '__init__',
     '__init_subclass__',
     '__int__',
     '__invert__',
     '__le__',
     '__lshift__',
     '__lt__',
     '__mod__',
     '__mul__',
     '__ne__',
     '__neg__',
     '__new__',
     '__or__',
     '__pos__',
     '__pow__',
     '__radd__',
     '__rand__',
     '__rdivmod__',
     '__reduce__',
     '__reduce_ex__',
     '__repr__',
     '__rfloordiv__',
     '__rlshift__',
     '__rmod__',
     '__rmul__',
     '__ror__',
     '__round__',
     '__rpow__',
     '__rrshift__',
     '__rshift__',
     '__rsub__',
     '__rtruediv__',
     '__rxor__',
     '__setattr__',
     '__sizeof__',
     '__str__',
     '__sub__',
     '__subclasshook__',
     '__truediv__',
     '__trunc__',
     '__xor__',
     'as_integer_ratio',
     'bit_length',
     'conjugate',
     'denominator',
     'from_bytes',
     'imag',
     'numerator',
     'real',
     'to_bytes']
    -----
    <class 'int'>.
    
    ======================================================================
    ERROR: test_clip_default_inbounds_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        (y, ) = n0_clip_11(x, , )
                              ^
    SyntaxError: invalid syntax
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        x = dict_inputs['x']
        (y, ) = n0_clip_11(x, , )
        return {
            'y': y,
        }
    
    ======================================================================
    ERROR: test_clip_default_int8_inbounds_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        (y, ) = n0_clip_11(x, , )
                              ^
    SyntaxError: invalid syntax
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        x = dict_inputs['x']
        (y, ) = n0_clip_11(x, , )
        return {
            'y': y,
        }
    
    ======================================================================
    ERROR: test_clip_default_int8_max_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        (y, ) = n0_clip_11(x, , max)
                              ^
    SyntaxError: invalid syntax
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        x = dict_inputs['x']
        max = dict_inputs['max']
        (y, ) = n0_clip_11(x, , max)
        return {
            'y': y,
        }
    
    ======================================================================
    ERROR: test_clip_default_max_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        (y, ) = n0_clip_11(x, , max)
                              ^
    SyntaxError: invalid syntax
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        x = dict_inputs['x']
        max = dict_inputs['max']
        (y, ) = n0_clip_11(x, , max)
        return {
            'y': y,
        }
    
    ======================================================================
    ERROR: test_convinteger_with_padding_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'ConvInteger' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_convinteger_without_padding_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'ConvInteger' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_depthtospace_crd_mode_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'DepthToSpace' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_depthtospace_crd_mode_example_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'DepthToSpace' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_depthtospace_dcr_mode_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'DepthToSpace' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_depthtospace_example_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'DepthToSpace' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_dynamicquantizelinear_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1755, in _build_compile_run
        raise NotImplementedError(
    NotImplementedError: Not implemented for models including functions.
    
    ======================================================================
    ERROR: test_dynamicquantizelinear_max_adjusted_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1755, in _build_compile_run
        raise NotImplementedError(
    NotImplementedError: Not implemented for models including functions.
    
    ======================================================================
    ERROR: test_dynamicquantizelinear_min_adjusted_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1755, in _build_compile_run
        raise NotImplementedError(
    NotImplementedError: Not implemented for models including functions.
    
    ======================================================================
    ERROR: test_gathernd_example_float32_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GatherND' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_gathernd_example_int32_batch_dim1_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GatherND' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_gathernd_example_int32_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GatherND' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_globalmaxpool_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GlobalMaxPool' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_globalmaxpool_precomputed_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GlobalMaxPool' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_gridsample_aligncorners_true_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GridSample' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_gridsample_bicubic_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GridSample' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_gridsample_bilinear_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GridSample' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_gridsample_border_padding_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GridSample' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_gridsample_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GridSample' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_gridsample_nearest_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GridSample' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_gridsample_reflection_padding_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GridSample' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_gridsample_zeros_padding_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GridSample' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_gru_batchwise_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GRU' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_gru_defaults_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GRU' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_gru_seq_length_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GRU' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_gru_with_initial_bias_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'GRU' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_hardswish_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1755, in _build_compile_run
        raise NotImplementedError(
    NotImplementedError: Not implemented for models including functions.
    
    ======================================================================
    ERROR: test_identity_opt_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 187, in _init
        self.graph_ = self.to_sequence(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 595, in to_sequence
        variables[obj.name] = _var_as_dict(obj)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 419, in _var_as_dict
        dtype['optional'] = _var_as_dict(optional)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 488, in _var_as_dict
        raise NotImplementedError(  # pragma: no cover
    NotImplementedError: Unable to guess which object it is type is <class 'onnx.onnx_ml_pb2.Optional'> value is 'elem_type {\n  sequence_type {\n    elem_type {\n      tensor_type {\n        elem_type: 1\n        shape {\n          dim {\n            dim_value: 5\n          }\n        }\n      }\n    }\n  }\n}\n'.
    
    ======================================================================
    ERROR: test_if_opt_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 187, in _init
        self.graph_ = self.to_sequence(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 605, in to_sequence
        outputs[obj.name] = _var_as_dict(obj)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 419, in _var_as_dict
        dtype['optional'] = _var_as_dict(optional)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 488, in _var_as_dict
        raise NotImplementedError(  # pragma: no cover
    NotImplementedError: Unable to guess which object it is type is <class 'onnx.onnx_ml_pb2.Optional'> value is 'elem_type {\n  sequence_type {\n    elem_type {\n      tensor_type {\n        elem_type: 1\n        shape {\n          dim {\n            dim_value: 5\n          }\n        }\n      }\n    }\n  }\n}\n'.
    
    ======================================================================
    ERROR: test_instancenorm_epsilon_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'InstanceNormalization' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_instancenorm_example_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'InstanceNormalization' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_loop16_seq_none_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 187, in _init
        self.graph_ = self.to_sequence(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 595, in to_sequence
        variables[obj.name] = _var_as_dict(obj)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 419, in _var_as_dict
        dtype['optional'] = _var_as_dict(optional)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 488, in _var_as_dict
        raise NotImplementedError(  # pragma: no cover
    NotImplementedError: Unable to guess which object it is type is <class 'onnx.onnx_ml_pb2.Optional'> value is 'elem_type {\n  sequence_type {\n    elem_type {\n      tensor_type {\n        elem_type: 1\n        shape {\n        }\n      }\n    }\n  }\n}\n'.
    
    ======================================================================
    ERROR: test_lrn_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'LRN' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_lrn_default_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'LRN' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_lstm_batchwise_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'LSTM' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_lstm_defaults_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'LSTM' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_lstm_with_initial_bias_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'LSTM' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_lstm_with_peepholes_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'LSTM' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_matmulinteger_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'MatMulInteger' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_max_example_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 8, in compiled_run
    TypeError: _run() takes 3 positional arguments but 4 were given
    
    ======================================================================
    ERROR: test_max_one_input_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 6, in compiled_run
    TypeError: _run() missing 1 required positional argument: 'b'
    
    ======================================================================
    ERROR: test_maxunpool_export_with_output_shape_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'MaxUnpool' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_maxunpool_export_without_output_shape_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'MaxUnpool' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_min_example_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 8, in compiled_run
    TypeError: _run() takes 3 positional arguments but 4 were given
    
    ======================================================================
    ERROR: test_min_one_input_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 6, in compiled_run
    TypeError: _run() missing 1 required positional argument: 'b'
    
    ======================================================================
    ERROR: test_momentum_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Momentum' from domain 'ai.onnx.preview.training' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_momentum_multiple_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Momentum' from domain 'ai.onnx.preview.training' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_mvn_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1755, in _build_compile_run
        raise NotImplementedError(
    NotImplementedError: Not implemented for models including functions.
    
    ======================================================================
    ERROR: test_nesterov_momentum_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Momentum' from domain 'ai.onnx.preview.training' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_nllloss_NCd1_ii_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 7, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_nllloss_NCd1_mean_weight_negative_ii_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 8, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_nllloss_NCd1_weight_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 8, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_nllloss_NCd1_weight_ii_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 8, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_nllloss_NCd1d2_no_weight_reduction_mean_ii_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 7, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_nllloss_NCd1d2_with_weight_reduction_mean_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 8, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_nllloss_NCd1d2d3d4d5_mean_weight_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 8, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_nonmaxsuppression_center_point_box_format_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'NonMaxSuppression' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_nonmaxsuppression_flipped_coordinates_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'NonMaxSuppression' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_nonmaxsuppression_identical_boxes_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'NonMaxSuppression' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_nonmaxsuppression_limit_output_size_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'NonMaxSuppression' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_nonmaxsuppression_single_box_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'NonMaxSuppression' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_nonmaxsuppression_suppress_by_IOU_and_scores_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'NonMaxSuppression' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_nonmaxsuppression_suppress_by_IOU_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'NonMaxSuppression' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_nonmaxsuppression_two_batches_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'NonMaxSuppression' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_nonmaxsuppression_two_classes_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'NonMaxSuppression' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_nonzero_example_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'NonZero' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_onehot_negative_indices_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'OneHot' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_onehot_with_axis_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'OneHot' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_onehot_with_negative_axis_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'OneHot' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_onehot_without_axis_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'OneHot' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_optional_get_element_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 187, in _init
        self.graph_ = self.to_sequence(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 595, in to_sequence
        variables[obj.name] = _var_as_dict(obj)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 419, in _var_as_dict
        dtype['optional'] = _var_as_dict(optional)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 488, in _var_as_dict
        raise NotImplementedError(  # pragma: no cover
    NotImplementedError: Unable to guess which object it is type is <class 'onnx.onnx_ml_pb2.Optional'> value is 'elem_type {\n  tensor_type {\n    elem_type: 1\n    shape {\n      dim {\n        dim_value: 4\n      }\n    }\n  }\n}\n'.
    
    ======================================================================
    ERROR: test_optional_get_element_sequence_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 187, in _init
        self.graph_ = self.to_sequence(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 595, in to_sequence
        variables[obj.name] = _var_as_dict(obj)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 419, in _var_as_dict
        dtype['optional'] = _var_as_dict(optional)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 488, in _var_as_dict
        raise NotImplementedError(  # pragma: no cover
    NotImplementedError: Unable to guess which object it is type is <class 'onnx.onnx_ml_pb2.Optional'> value is 'elem_type {\n  sequence_type {\n    elem_type {\n      tensor_type {\n        elem_type: 6\n        shape {\n          dim {\n            dim_value: 4\n          }\n        }\n      }\n    }\n  }\n}\n'.
    
    ======================================================================
    ERROR: test_optional_has_element_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 187, in _init
        self.graph_ = self.to_sequence(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 595, in to_sequence
        variables[obj.name] = _var_as_dict(obj)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 419, in _var_as_dict
        dtype['optional'] = _var_as_dict(optional)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 488, in _var_as_dict
        raise NotImplementedError(  # pragma: no cover
    NotImplementedError: Unable to guess which object it is type is <class 'onnx.onnx_ml_pb2.Optional'> value is 'elem_type {\n  tensor_type {\n    elem_type: 1\n    shape {\n      dim {\n        dim_value: 4\n      }\n    }\n  }\n}\n'.
    
    ======================================================================
    ERROR: test_optional_has_element_empty_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 187, in _init
        self.graph_ = self.to_sequence(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 595, in to_sequence
        variables[obj.name] = _var_as_dict(obj)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 419, in _var_as_dict
        dtype['optional'] = _var_as_dict(optional)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 488, in _var_as_dict
        raise NotImplementedError(  # pragma: no cover
    NotImplementedError: Unable to guess which object it is type is <class 'onnx.onnx_ml_pb2.Optional'> value is 'elem_type {\n  tensor_type {\n    elem_type: 6\n    shape {\n    }\n  }\n}\n'.
    
    ======================================================================
    ERROR: test_qlinearmatmul_2D_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'QLinearMatMul' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_qlinearmatmul_3D_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'QLinearMatMul' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_range_float_type_positive_delta_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 317, in preprocess_parameters
        sess = rt_class(v['value'], runtime=runtime,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 187, in _init
        self.graph_ = self.to_sequence(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 595, in to_sequence
        variables[obj.name] = _var_as_dict(obj)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 488, in _var_as_dict
        raise NotImplementedError(  # pragma: no cover
    NotImplementedError: Unable to guess which object it is type is <class 'onnx.onnx_ml_pb2.ValueInfoProto'> value is 'name: "prev"\n'.
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 221, in setup_runtime
        self.preprocess_parameters(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 323, in preprocess_parameters
        raise RuntimeError(
    RuntimeError: Unable to instantiate a node of type 'Loop' and name ''.
    
    ======================================================================
    ERROR: test_range_int32_type_negative_delta_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 317, in preprocess_parameters
        sess = rt_class(v['value'], runtime=runtime,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 187, in _init
        self.graph_ = self.to_sequence(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 595, in to_sequence
        variables[obj.name] = _var_as_dict(obj)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnx_tools/onnx2py_helper.py", line 488, in _var_as_dict
        raise NotImplementedError(  # pragma: no cover
    NotImplementedError: Unable to guess which object it is type is <class 'onnx.onnx_ml_pb2.ValueInfoProto'> value is 'name: "prev"\n'.
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 221, in setup_runtime
        self.preprocess_parameters(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 323, in preprocess_parameters
        raise RuntimeError(
    RuntimeError: Unable to instantiate a node of type 'Loop' and name ''.
    
    ======================================================================
    ERROR: test_reshape_allowzero_reordered_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 213, in _init
        raise RuntimeError(  # pragma: no cover
    RuntimeError: Wrong ONNX file, one input or output has an empty shape: name: "data"
    type {
      tensor_type {
        elem_type: 1
        shape {
          dim {
            dim_value: 0
          }
          dim {
            dim_value: 3
          }
          dim {
            dim_value: 4
          }
        }
      }
    }
    .
    
    ======================================================================
    ERROR: test_resize_downsample_scales_cubic_A_n0p5_exclude_outside_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_downsample_scales_cubic_align_corners_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_downsample_scales_cubic_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_downsample_scales_linear_align_corners_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_downsample_scales_linear_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_downsample_scales_nearest_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_downsample_sizes_cubic_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_downsample_sizes_linear_pytorch_half_pixel_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_downsample_sizes_nearest_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_downsample_sizes_nearest_tf_half_pixel_for_nn_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_tf_crop_and_resize_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_upsample_scales_cubic_A_n0p5_exclude_outside_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_upsample_scales_cubic_align_corners_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_upsample_scales_cubic_asymmetric_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_upsample_scales_cubic_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_upsample_scales_linear_align_corners_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_upsample_scales_linear_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_upsample_scales_nearest_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_upsample_sizes_cubic_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_upsample_sizes_nearest_ceil_half_pixel_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_upsample_sizes_nearest_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_upsample_sizes_nearest_floor_align_corners_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_resize_upsample_sizes_nearest_round_prefer_ceil_asymmetric_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Resize' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_reversesequence_batch_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'ReverseSequence' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_reversesequence_time_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'ReverseSequence' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_rnn_seq_length_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 118, in load_op
        return cl(onnx_node, desc=desc, runtme=runtime, **options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_rnn.py", line 156, in __init__
        CommonRNN.__init__(self, onnx_node, desc=desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_rnn.py", line 40, in __init__
        self.f1 = self.choose_act(self.activations[0],
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_rnn.py", line 57, in choose_act
        raise RuntimeError(  # pragma: no cover
    RuntimeError: Unknown activation function 'tanh'.
    
    ======================================================================
    ERROR: test_roialign_aligned_false_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'RoiAlign' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_roialign_aligned_true_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'RoiAlign' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_scan_sum_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        (y, z, ) = n0_scan(, initial, x)
                           ^
    SyntaxError: invalid syntax
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        initial = dict_inputs['initial']
        x = dict_inputs['x']
        (y, z, ) = n0_scan(, initial, x)
        return {
            'y': y,
            'z': z,
        }
    
    ======================================================================
    ERROR: test_scatter_elements_without_axis_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 8, in compiled_run
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_scatter_elements.py", line 78, in _run
        res = scatter_elements(data, indices, updates, axis=self.axis)
    AttributeError: 'ScatterElements' object has no attribute 'axis'
    
    ======================================================================
    ERROR: test_scatter_with_axis_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Scatter' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_scatter_without_axis_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Scatter' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_scatternd_add_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'ScatterND' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_scatternd_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'ScatterND' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_scatternd_multiply_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'ScatterND' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_sce_NCd1_mean_weight_negative_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 15, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_NCd1_mean_weight_negative_ii_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 16, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_NCd1d2d3d4d5_mean_weight_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 15, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_NCd1d2d3d4d5_mean_weight_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 16, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_mean_no_weight_ii_3d_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 14, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_mean_no_weight_ii_3d_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 15, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_mean_no_weight_ii_4d_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 14, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_mean_no_weight_ii_4d_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 15, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_mean_no_weight_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 14, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_mean_no_weight_ii_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 15, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_mean_weight_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 15, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_mean_weight_ii_3d_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 15, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_mean_weight_ii_3d_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 16, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_mean_weight_ii_4d_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 15, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_mean_weight_ii_4d_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 16, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_mean_weight_ii_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 15, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_mean_weight_ii_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 16, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_sce_mean_weight_log_prob_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 16, in compiled_run
    TypeError: cannot unpack non-iterable numpy.float32 object
    
    ======================================================================
    ERROR: test_shrink_hard_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Shrink' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_shrink_soft_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Shrink' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_simple_rnn_batchwise_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 118, in load_op
        return cl(onnx_node, desc=desc, runtme=runtime, **options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_rnn.py", line 156, in __init__
        CommonRNN.__init__(self, onnx_node, desc=desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_rnn.py", line 40, in __init__
        self.f1 = self.choose_act(self.activations[0],
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_rnn.py", line 57, in choose_act
        raise RuntimeError(  # pragma: no cover
    RuntimeError: Unknown activation function 'tanh'.
    
    ======================================================================
    ERROR: test_simple_rnn_defaults_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 118, in load_op
        return cl(onnx_node, desc=desc, runtme=runtime, **options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_rnn.py", line 156, in __init__
        CommonRNN.__init__(self, onnx_node, desc=desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_rnn.py", line 40, in __init__
        self.f1 = self.choose_act(self.activations[0],
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_rnn.py", line 57, in choose_act
        raise RuntimeError(  # pragma: no cover
    RuntimeError: Unknown activation function 'tanh'.
    
    ======================================================================
    ERROR: test_simple_rnn_with_initial_bias_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 118, in load_op
        return cl(onnx_node, desc=desc, runtme=runtime, **options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_rnn.py", line 156, in __init__
        CommonRNN.__init__(self, onnx_node, desc=desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_rnn.py", line 40, in __init__
        self.f1 = self.choose_act(self.activations[0],
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_rnn.py", line 57, in choose_act
        raise RuntimeError(  # pragma: no cover
    RuntimeError: Unknown activation function 'tanh'.
    
    ======================================================================
    ERROR: test_slice_start_out_of_bounds_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 213, in _init
        raise RuntimeError(  # pragma: no cover
    RuntimeError: Wrong ONNX file, one input or output has an empty shape: name: "y"
    type {
      tensor_type {
        elem_type: 1
        shape {
          dim {
            dim_value: 20
          }
          dim {
            dim_value: 0
          }
          dim {
            dim_value: 5
          }
        }
      }
    }
    .
    
    ======================================================================
    ERROR: test_softplus_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Softplus' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_softplus_example_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Softplus' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_softsign_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Softsign' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_softsign_example_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Softsign' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_spacetodepth_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'SpaceToDepth' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_spacetodepth_example_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'SpaceToDepth' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_tfidfvectorizer_tf_only_bigrams_skip0_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 6, in compiled_run
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_tfidfvectorizer.py", line 54, in _run
        return (res.reshape((x.shape[0], -1)), )
    ValueError: cannot reshape array of size 7 into shape (12,newaxis)
    
    ======================================================================
    ERROR: test_tfidfvectorizer_tf_onlybigrams_levelempty_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 6, in compiled_run
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_tfidfvectorizer.py", line 54, in _run
        return (res.reshape((x.shape[0], -1)), )
    ValueError: cannot reshape array of size 3 into shape (12,newaxis)
    
    ======================================================================
    ERROR: test_tfidfvectorizer_tf_onlybigrams_skip5_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 6, in compiled_run
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_tfidfvectorizer.py", line 54, in _run
        return (res.reshape((x.shape[0], -1)), )
    ValueError: cannot reshape array of size 7 into shape (12,newaxis)
    
    ======================================================================
    ERROR: test_tfidfvectorizer_tf_uniandbigrams_skip5_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 320, in run
        outputs = list(prepared_model.run(inputs))
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 83, in run
        outs = self._session.run(feeds)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 875, in run
        return self._run(inputs, clean_right_away=False,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 312, in _run_sequence_runtime_compiled
        return self._run_compiled(  # pylint: disable=E1101
      File "<string>", line 6, in compiled_run
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/op_tfidfvectorizer.py", line 54, in _run
        return (res.reshape((x.shape[0], -1)), )
    ValueError: cannot reshape array of size 7 into shape (12,newaxis)
    
    ======================================================================
    ERROR: test_thresholdedrelu_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'ThresholdedRelu' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_thresholdedrelu_default_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'ThresholdedRelu' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_thresholdedrelu_example_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'ThresholdedRelu' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_tile_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Tile' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_tile_precomputed_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Tile' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_tril_zero_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 213, in _init
        raise RuntimeError(  # pragma: no cover
    RuntimeError: Wrong ONNX file, one input or output has an empty shape: name: "x"
    type {
      tensor_type {
        elem_type: 7
        shape {
          dim {
            dim_value: 3
          }
          dim {
            dim_value: 0
          }
          dim {
            dim_value: 5
          }
        }
      }
    }
    .
    
    ======================================================================
    ERROR: test_triu_zero_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 213, in _init
        raise RuntimeError(  # pragma: no cover
    RuntimeError: Wrong ONNX file, one input or output has an empty shape: name: "x"
    type {
      tensor_type {
        elem_type: 7
        shape {
          dim {
            dim_value: 0
          }
          dim {
            dim_value: 5
          }
        }
      }
    }
    .
    
    ======================================================================
    ERROR: test_unique_not_sorted_without_axis_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Unique' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_unique_sorted_with_axis_3d_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Unique' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_unique_sorted_with_axis_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Unique' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_unique_sorted_with_negative_axis_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Unique' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_unique_sorted_without_axis_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Unique' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_upsample_nearest_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Upsample' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_AvgPool1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_unsqueeze_1(0)
        (2, ) = n1_averagepool(1)
        (3, ) = n2_squeeze_1(2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_AvgPool1d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_unsqueeze_1(0)
        (2, ) = n1_averagepool(1)
        (3, ) = n2_squeeze_1(2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_AvgPool2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_averagepool(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_AvgPool2d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_averagepool(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_AvgPool3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_averagepool(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_AvgPool3d_stride1_pad0_gpu_input_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_averagepool(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_AvgPool3d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_averagepool(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_BatchNorm1d_3d_input_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 9
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # init: 3 (3)
        # init: 4 (4)
        # inputs
        0 = dict_inputs['0']
        (5, ) = n0_batchnormalization_14(0, 1, 2, 3, 4)
        return {
            '5': 5,
        }
    
    ======================================================================
    ERROR: test_BatchNorm2d_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 9
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # init: 3 (3)
        # init: 4 (4)
        # inputs
        0 = dict_inputs['0']
        (5, ) = n0_batchnormalization_14(0, 1, 2, 3, 4)
        return {
            '5': 5,
        }
    
    ======================================================================
    ERROR: test_BatchNorm2d_momentum_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 9
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # init: 3 (3)
        # init: 4 (4)
        # inputs
        0 = dict_inputs['0']
        (5, ) = n0_batchnormalization_14(0, 1, 2, 3, 4)
        return {
            '5': 5,
        }
    
    ======================================================================
    ERROR: test_BatchNorm3d_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 9
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # init: 3 (3)
        # init: 4 (4)
        # inputs
        0 = dict_inputs['0']
        (5, ) = n0_batchnormalization_14(0, 1, 2, 3, 4)
        return {
            '5': 5,
        }
    
    ======================================================================
    ERROR: test_BatchNorm3d_momentum_eval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 9
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # init: 3 (3)
        # init: 4 (4)
        # inputs
        0 = dict_inputs['0']
        (5, ) = n0_batchnormalization_14(0, 1, 2, 3, 4)
        return {
            '5': 5,
        }
    
    ======================================================================
    ERROR: test_ConstantPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_pad(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_Conv1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv1d_dilated_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv1d_groups_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv1d_pad1_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv1d_pad1size1_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv1d_pad2_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv1d_pad2size1_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv1d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv2d_depthwise_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv2d_depthwise_padded_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv2d_depthwise_strided_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv2d_depthwise_with_multiplier_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv2d_dilated_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv2d_groups_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv2d_groups_thnn_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv2d_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # inputs
        0 = dict_inputs['0']
        (2, ) = n0_conv(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_Conv2d_padding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv2d_strided_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv3d_dilated_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv3d_dilated_strided_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv3d_groups_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv3d_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # inputs
        0 = dict_inputs['0']
        (2, ) = n0_conv(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_Conv3d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Conv3d_stride_padding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_conv(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_ConvTranspose2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_convtranspose(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_ConvTranspose2d_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # inputs
        0 = dict_inputs['0']
        (2, ) = n0_convtranspose(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_ELU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_elu(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_Embedding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # inputs
        0 = dict_inputs['0']
        (2, ) = n0_gather(1, 0)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_Embedding_sparse_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # inputs
        0 = dict_inputs['0']
        (2, ) = n0_gather(1, 0)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_GLU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, 2, ) = n0_split_2(0)
        (3, ) = n1_sigmoid(2)
        (4, ) = n2_mul(1, 3)
        return {
            '4': 4,
        }
    
    ======================================================================
    ERROR: test_GLU_dim_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, 2, ) = n0_split_2(0)
        (3, ) = n1_sigmoid(2)
        (4, ) = n2_mul(1, 3)
        return {
            '4': 4,
        }
    
    ======================================================================
    ERROR: test_LeakyReLU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_leakyrelu(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_LeakyReLU_with_negval_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_leakyrelu(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_Linear_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 7
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # init: 2 (2)
        # inputs
        0 = dict_inputs['0']
        (3, ) = n0_gemm(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_Linear_no_bias_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # inputs
        0 = dict_inputs['0']
        (2, ) = n0_transpose(1)
        (3, ) = n1_matmul(0, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_LogSoftmax_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_logsoftmax(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_MaxPool1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_maxpool(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_MaxPool1d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_maxpool(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_MaxPool2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_maxpool(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_MaxPool3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_maxpool(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_MaxPool3d_stride_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_maxpool(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_MaxPool3d_stride_padding_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_maxpool(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_PReLU_1d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # inputs
        0 = dict_inputs['0']
        (2, ) = n0_prelu(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_PReLU_1d_multiparam_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # inputs
        0 = dict_inputs['0']
        (2, ) = n0_prelu(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_PReLU_2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # inputs
        0 = dict_inputs['0']
        (2, ) = n0_prelu(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_PReLU_2d_multiparam_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # inputs
        0 = dict_inputs['0']
        (2, ) = n0_prelu(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_PReLU_3d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # inputs
        0 = dict_inputs['0']
        (2, ) = n0_prelu(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_PReLU_3d_multiparam_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # inputs
        0 = dict_inputs['0']
        (2, ) = n0_prelu(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_PixelShuffle_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_constant_12()
        (2, ) = n1_reshape_5(0, 1)
        (3, ) = n2_transpose(2)
        (4, ) = n3_constant_12()
        (5, ) = n4_reshape_5(3, 4)
        return {
            '5': 5,
        }
    
    ======================================================================
    ERROR: test_PoissonNLLLLoss_no_reduce_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_constant_12()
        (2, ) = n1_exp(0)
        (3, ) = n2_mul(1, 0)
        (4, ) = n3_sub(2, 3)
        return {
            '4': 4,
        }
    
    ======================================================================
    ERROR: test_ReLU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_relu(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_ReflectionPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_pad(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_ReplicationPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_pad(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_SELU_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_selu(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_Sigmoid_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_sigmoid(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_Softmax_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_softmax(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_Softmin_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_neg(0)
        (2, ) = n1_softmax(1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_Softplus_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Softplus' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_Softsign_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_abs(0)
        (2, ) = n1_constant_12()
        (3, ) = n2_add(1, 2)
        (4, ) = n3_div(0, 3)
        return {
            '4': 4,
        }
    
    ======================================================================
    ERROR: test_Tanh_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_tanh(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_ZeroPad2d_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_pad(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_log_softmax_dim3_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_logsoftmax(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_log_softmax_lastdim_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_logsoftmax(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_softmax_functional_dim3_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_softmax(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_softmax_lastdim_cpu (__main__.OnnxBackendPyTorchConvertedModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_softmax(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_operator_add_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        1 = dict_inputs['1']
        (2, ) = n0_add(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_operator_add_size1_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        1 = dict_inputs['1']
        (2, ) = n0_add(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_operator_add_size1_right_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        1 = dict_inputs['1']
        (2, ) = n0_add(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_operator_add_size1_singleton_broadcast_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        1 = dict_inputs['1']
        (2, ) = n0_add(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_operator_addconstant_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_constant_12()
        (2, ) = n1_add(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_operator_addmm_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        1 = dict_inputs['1']
        2 = dict_inputs['2']
        (3, ) = n0_gemm(0, 1, 2)
        (4, ) = n1_gemm(0, 1, 3)
        return {
            '4': 4,
        }
    
    ======================================================================
    ERROR: test_operator_basic_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        1 = dict_inputs['1']
        (2, ) = n0_add(0, 1)
        (3, ) = n1_mul(0, 2)
        (4, ) = n2_tanh(3)
        (5, ) = n3_sigmoid(4)
        (6, ) = n4_neg(5)
        return {
            '6': 6,
        }
    
    ======================================================================
    ERROR: test_operator_chunk_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, 2, ) = n0_split_2(0)
        return {
            '1': 1,
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_operator_clip_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_clip_6(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_operator_concat2_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        1 = dict_inputs['1']
        (2, ) = n0_concat(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_operator_conv_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # inputs
        0 = dict_inputs['0']
        (2, ) = n0_conv(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_operator_convtranspose_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # inputs
        0 = dict_inputs['0']
        (2, ) = n0_convtranspose(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_operator_exp_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_exp(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_operator_flatten_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_flatten(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_operator_index_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_slice_1(0)
        (2, ) = n1_squeeze_1(1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_operator_max_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        1 = dict_inputs['1']
        (2, ) = n0_max(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_operator_maxpool_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_maxpool(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_operator_min_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        1 = dict_inputs['1']
        (2, ) = n0_min(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_operator_mm_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        1 = dict_inputs['1']
        (2, ) = n0_constant_12()
        (3, ) = n1_gemm(0, 1, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_operator_non_float_params_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # inputs
        0 = dict_inputs['0']
        (2, ) = n0_add(0, 1)
        (3, ) = n1_mul(0, 2)
        return {
            '3': 3,
        }
    
    ======================================================================
    ERROR: test_operator_pad_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_pad(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_operator_params_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 6
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # init: 1 (1)
        # inputs
        0 = dict_inputs['0']
        (2, ) = n0_add(0, 1)
        (3, ) = n1_mul(0, 2)
        (4, ) = n2_tanh(3)
        (5, ) = n3_sigmoid(4)
        (6, ) = n4_neg(5)
        return {
            '6': 6,
        }
    
    ======================================================================
    ERROR: test_operator_permute2_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_transpose(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_operator_pow_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        1 = dict_inputs['1']
        (2, ) = n0_pow(0, 1)
        return {
            '2': 2,
        }
    
    ======================================================================
    ERROR: test_operator_reduced_mean_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_reducemean(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_operator_reduced_mean_keepdim_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_reducemean(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_operator_reduced_sum_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_reducesum_1(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_operator_reduced_sum_keepdim_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_reducesum_1(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_operator_repeat_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Tile' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_operator_repeat_dim_overflow_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Tile' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_operator_selu_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_selu(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_operator_sqrt_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_sqrt(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_operator_symbolic_override_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'InstanceNormalization' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_operator_symbolic_override_nested_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        1 = dict_inputs['1']
        2 = dict_inputs['2']
        (3, ) = n0_sum(0, 1, 2)
        (4, ) = n1_neg(0)
        (5, ) = n2_neg(1)
        return {
            '3': 3,
            '4': 4,
            '5': 5,
        }
    
    ======================================================================
    ERROR: test_operator_view_cpu (__main__.OnnxBackendPyTorchOperatorModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1791, in _build_compile_run
        obj = compile(final_code, "<string>", 'exec')
      File "<string>", line 5
        0 = dict_inputs['0']
        ^
    SyntaxError: cannot assign to literal
    
    The above exception was the direct cause of the following exception:
    
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 294, in _init
        _, fct, code = self._build_compile_run('debug' in self.runtime)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 1793, in _build_compile_run
        raise SyntaxError(
      File "<string>", line None
    SyntaxError: Unable to compile
    #####
    def compiled_run(dict_inputs, yield_ops=None):
        if yield_ops is not None:
            raise NotImplementedError('yields_ops should be None.')
        # inputs
        0 = dict_inputs['0']
        (1, ) = n0_flatten(0)
        return {
            '1': 1,
        }
    
    ======================================================================
    ERROR: test_bvlc_alexnet_cpu (__main__.OnnxBackendRealModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'LRN' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_gradient_of_add_and_mul_cpu (__main__.OnnxBackendSimpleModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Gradient' from domain 'ai.onnx.preview.training' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_gradient_of_add_cpu (__main__.OnnxBackendSimpleModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Gradient' from domain 'ai.onnx.preview.training' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_sequence_model1_cpu (__main__.OnnxBackendSimpleModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'SequenceEmpty' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_sequence_model2_cpu (__main__.OnnxBackendSimpleModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'SequenceErase' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_sequence_model3_cpu (__main__.OnnxBackendSimpleModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'SequenceErase' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_sequence_model6_cpu (__main__.OnnxBackendSimpleModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'SplitToSequence' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_sequence_model7_cpu (__main__.OnnxBackendSimpleModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'SplitToSequence' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_sequence_model8_cpu (__main__.OnnxBackendSimpleModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'SplitToSequence' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    ERROR: test_shrink_cpu (__main__.OnnxBackendSimpleModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 295, in run
        prepared_model = self.backend.prepare(model, device)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 221, in prepare
        return cls.prepare(binm, device, **kwargs)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 202, in prepare
        inf = cls.create_inference_session(model)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/backend.py", line 256, in create_inference_session
        return OnnxInference(model, runtime='python_compiled')
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 142, in __init__
        self._init(existing_functions)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference.py", line 260, in _init
        node.setup_runtime(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 260, in setup_runtime
        raise e
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/onnx_inference_node.py", line 243, in setup_runtime
        self.ops_ = load_op(self.onnx_node, desc=self.desc,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops.py", line 36, in load_op
        return lo(onnx_node, desc=desc, options=options)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_doc/sphinxdoc/source/mlprodict/onnxrt/ops_cpu/__init__.py", line 85, in load_op
        raise MissingOperatorError(  # pragma no cover
    mlprodict.onnxrt.excs.MissingOperatorError: Operator 'Shrink' from domain '' has no runtime yet. Available list:
     - Abs Acos Acosh Add And ArgMax ArgMin ArrayFeatureExtractor Asin Asinh
    Atan Atanh AveragePool BatchNormalization Bernoulli Binarizer BitShift
    BroadcastGradientArgs CDist Cast CastLike CategoryMapper Ceil Celu
    Clip ComplexAbs Compress Concat ConcatFromSequence Constant
    ConstantOfShape Conv ConvTranspose Cos Cosh CumSum DEBUG
    DequantizeLinear Det DictVectorizer Div Dropout Einsum Elu Equal Erf
    Exp Expand EyeLike FFT FFT2D FeatureVectorizer Flatten Floor
    FusedMatMul Gather GatherElements Gemm GlobalAveragePool Greater
    GreaterOrEqual HardSigmoid Hardmax Identity If Imputer IsInf IsNaN
    LabelEncoder LeakyRelu Less LessOrEqual LinearClassifier
    LinearRegressor Log LogSoftmax Loop LpNormalization MatMul Max MaxPool
    Mean Min Mod Mul Neg NegativeLogLikelihoodLoss Normalizer Not
    OneHotEncoder OpRun Or PRelu Pad Pow QLinearConv QuantizeLinear RFFT
    RNN RandomNormal RandomNormalLike RandomUniform RandomUniformLike
    Range Reciprocal ReduceL1 ReduceL2 ReduceLogSum ReduceLogSumExp
    ReduceMax ReduceMean ReduceMin ReduceProd ReduceSum ReduceSumSquare
    Relu Reshape Round SVMClassifier SVMClassifierDouble SVMRegressor
    SVMRegressorDouble Scaler Scan ScatterElements Selu SequenceAt
    SequenceConstruct SequenceInsert Shape Sigmoid Sign Sin Sinh Size
    Slice Softmax SoftmaxCrossEntropyLoss SoftmaxGrad Solve Split Sqrt
    Squeeze StringNormalizer Sub Sum Tan Tanh TfIdfVectorizer Tokenizer
    TopK Transpose TreeEnsembleClassifier TreeEnsembleClassifierDouble
    TreeEnsembleRegressor TreeEnsembleRegressorDouble Trilu Unsqueeze
    Where Xor YieldOp ZipMap
    
    ======================================================================
    FAIL: test_bernoulli_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 4 / 10 (40%)
    Max absolute difference: 1.
    Max relative difference: 1.
     x: array([0., 1., 0., 1., 1., 1., 1., 1., 1., 1.])
     y: array([0., 1., 1., 0., 0., 1., 0., 1., 1., 1.])
    
    ======================================================================
    FAIL: test_bernoulli_double_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 3 / 10 (30%)
    Max absolute difference: 1.
    Max relative difference: 1.
     x: array([0., 1., 0., 0., 0., 1., 1., 1., 1., 0.])
     y: array([0., 1., 1., 0., 0., 1., 0., 1., 1., 1.])
    
    ======================================================================
    FAIL: test_bernoulli_double_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 7 / 10 (70%)
    Max absolute difference: 1.
    Max relative difference: 1.
     x: array([0., 1., 0., 1., 1., 0., 1., 0., 0., 1.])
     y: array([0., 1., 1., 0., 0., 1., 0., 1., 1., 1.])
    
    ======================================================================
    FAIL: test_bernoulli_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 7 / 10 (70%)
    Max absolute difference: 1.
    Max relative difference: 1.
     x: array([1., 0., 0., 0., 0., 0., 1., 0., 0., 1.])
     y: array([0., 1., 1., 0., 0., 1., 0., 1., 1., 1.])
    
    ======================================================================
    FAIL: test_cast_FLOAT_to_STRING_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 187, in assert_similar_outputs
        np.testing.assert_equal(outputs[i].dtype, ref_outputs[i].dtype)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 425, in assert_equal
        raise AssertionError(msg)
    AssertionError: 
    Items are not equal:
     ACTUAL: dtype('<U32')
     DESIRED: dtype('O')
    
    ======================================================================
    FAIL: test_castlike_FLOAT_to_STRING_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 189, in assert_similar_outputs
        np.testing.assert_array_equal(outputs[i], ref_outputs[i])
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 934, in assert_array_equal
        assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Arrays are not equal
    
    Mismatched elements: 12 / 12 (100%)
     x: array([[0.9767611026763916, 0.6048455238342285, 0.7392635941505432,
            0.03918779268860817],
           [0.28280696272850037, 0.12019655853509903, 0.296140193939209,...
     y: array([['0.9767611', '0.6048455', '0.7392636', '0.039187793'],
           ['0.28280696', '0.12019656', '0.2961402', '0.11872772'],
           ['0.31798318', '0.41426298', '0.064147495', '0.6924721']],
          dtype=object)
    
    ======================================================================
    FAIL: test_castlike_FLOAT_to_STRING_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 187, in assert_similar_outputs
        np.testing.assert_equal(outputs[i].dtype, ref_outputs[i].dtype)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 425, in assert_equal
        raise AssertionError(msg)
    AssertionError: 
    Items are not equal:
     ACTUAL: dtype('<U32')
     DESIRED: dtype('O')
    
    ======================================================================
    FAIL: test_convtranspose_autopad_same_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    (shapes (1, 2, 7, 7), (1, 2, 6, 6) mismatch)
     x: array([[[[ 0.,  0.,  1.,  1.,  3.,  2.,  2.],
             [ 0.,  0.,  1.,  1.,  3.,  2.,  2.],
             [ 3.,  3.,  8.,  5., 12.,  7.,  7.],...
     y: array([[[[ 0.,  0.,  1.,  1.,  3.,  2.],
             [ 0.,  0.,  1.,  1.,  3.,  2.],
             [ 3.,  3.,  8.,  5., 12.,  7.],...
    
    ======================================================================
    FAIL: test_convtranspose_output_shape_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    (shapes (1, 2, 9, 7), (1, 2, 10, 8) mismatch)
     x: array([[[[ 0.,  0.,  1.,  1.,  3.,  2.,  2.],
             [ 0.,  0.,  1.,  1.,  3.,  2.,  2.],
             [ 0.,  0.,  1.,  1.,  3.,  2.,  2.],...
     y: array([[[[ 0.,  0.,  1.,  1.,  3.,  2.,  2.,  0.],
             [ 0.,  0.,  1.,  1.,  3.,  2.,  2.,  0.],
             [ 0.,  0.,  1.,  1.,  3.,  2.,  2.,  0.],...
    
    ======================================================================
    FAIL: test_dynamicquantizelinear_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 2 / 6 (33.3%)
    Max absolute difference: 255
    Max relative difference: 9.808
     x: array([153, 255,   0,  25, 221, 178], dtype=uint8)
     y: array([153, 255,   0,  26, 221, 179], dtype=uint8)
    
    ======================================================================
    FAIL: test_dynamicquantizelinear_max_adjusted_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 1 / 6 (16.7%)
    Max absolute difference: 255
    Max relative difference: 2.656
     x: array([191, 121, 172,  95,  42,   0], dtype=uint8)
     y: array([191, 121, 172,  96,  42,   0], dtype=uint8)
    
    ======================================================================
    FAIL: test_dynamicquantizelinear_min_adjusted_expanded_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 7 / 12 (58.3%)
    Max absolute difference: 255
    Max relative difference: 3.984
     x: array([[ 63, 133,  82, 159],
           [212, 255,  95, 165],
           [248, 255, 191, 149]], dtype=uint8)
     y: array([[ 64, 134,  83, 159],
           [213, 255,  96, 166],
           [249, 255, 191, 149]], dtype=uint8)
    
    ======================================================================
    FAIL: test_eyelike_without_dtype_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 187, in assert_similar_outputs
        np.testing.assert_equal(outputs[i].dtype, ref_outputs[i].dtype)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 425, in assert_equal
        raise AssertionError(msg)
    AssertionError: 
    Items are not equal:
     ACTUAL: dtype('float32')
     DESIRED: dtype('int32')
    
    ======================================================================
    FAIL: test_isinf_negative_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 3 / 6 (50%)
     x: array([False, False,  True, False, False,  True])
     y: array([False, False, False, False,  True, False])
    
    ======================================================================
    FAIL: test_isinf_positive_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 3 / 6 (50%)
     x: array([False, False, False, False,  True, False])
     y: array([False, False,  True, False, False,  True])
    
    ======================================================================
    FAIL: test_logsoftmax_default_axis_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 60 / 60 (100%)
    Max absolute difference: 1.374
    Max relative difference: 0.679
     x: array([[[-0.63786 , -2.150428, -0.994332, -0.32463 , -0.607985],
            [-1.424634, -1.600497, -1.821713, -2.462304, -2.064944],
            [-2.257869, -1.096312, -1.212032, -2.443848, -2.031679],...
     y: array([[[-1.488776, -2.852671, -2.27409 , -1.011935, -1.38527 ],
            [-1.222501, -1.24969 , -2.048422, -2.09656 , -1.78918 ],
            [-2.184687, -0.874457, -1.567693, -2.207056, -1.884868],...
    
    ======================================================================
    FAIL: test_loop11_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    (shapes (1,), (5, 1) mismatch)
     x: array([13.], dtype=float32)
     y: array([[-1.],
           [ 1.],
           [ 4.],...
    
    ======================================================================
    FAIL: test_maxpool_2d_uint8_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 187, in assert_similar_outputs
        np.testing.assert_equal(outputs[i].dtype, ref_outputs[i].dtype)
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 425, in assert_equal
        raise AssertionError(msg)
    AssertionError: 
    Items are not equal:
     ACTUAL: dtype('float64')
     DESIRED: dtype('uint8')
    
    ======================================================================
    FAIL: test_mod_int64_fmod_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 2 / 6 (33.3%)
    Max absolute difference: 3
    Max relative difference: 3.
     x: array([ 0, -2,  5,  0,  2,  3])
     y: array([ 0,  1,  5,  0, -1,  3])
    
    ======================================================================
    FAIL: test_mod_mixed_sign_float16_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 4 / 6 (66.7%)
    Max absolute difference: 3.4
    Max relative difference: 20.67
     x: array([ 1.998, -3.002,  5.   , -1.998,  3.002,  3.   ], dtype=float16)
     y: array([-0.10156,  0.3984 ,  5.     ,  0.10156, -0.3984 ,  3.     ],
          dtype=float16)
    
    ======================================================================
    FAIL: test_mod_mixed_sign_float32_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 4 / 6 (66.7%)
    Max absolute difference: 3.4
    Max relative difference: 21.
     x: array([ 2., -3.,  5., -2.,  3.,  3.], dtype=float32)
     y: array([-0.1,  0.4,  5. ,  0.1, -0.4,  3. ], dtype=float32)
    
    ======================================================================
    FAIL: test_mod_mixed_sign_float64_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 4 / 6 (66.7%)
    Max absolute difference: 3.4
    Max relative difference: 21.
     x: array([ 2., -3.,  5., -2.,  3.,  3.])
     y: array([-0.1,  0.4,  5. ,  0.1, -0.4,  3. ])
    
    ======================================================================
    FAIL: test_quantizelinear_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 1 / 6 (16.7%)
    Max absolute difference: 255
    Max relative difference: 1.962
     x: array([128, 129, 129, 255,   1,   0], dtype=uint8)
     y: array([128, 129, 130, 255,   1,   0], dtype=uint8)
    
    ======================================================================
    FAIL: test_scatter_elements_with_duplicate_indices_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 1 / 5 (20%)
    Max absolute difference: 3.1
    Max relative difference: 0.596
     x: array([[1. , 2.1, 3. , 4. , 5. ]], dtype=float32)
     y: array([[1. , 5.2, 3. , 4. , 5. ]], dtype=float32)
    
    ======================================================================
    FAIL: test_selu_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 28 / 60 (46.7%)
    Max absolute difference: 3.689
    Max relative difference: 0.667
     x: array([[[ 5.292157,  1.200472,  2.936214,  6.722679,  5.602674],
            [-1.247332,  2.850265, -0.280919, -0.196141,  1.231796],
            [ 0.432131,  4.362821,  2.283113,  0.365025,  1.33159 ],...
     y: array([[[ 5.292157,  1.200472,  2.936214,  6.722679,  5.602674],
            [-3.741995,  2.850265, -0.842756, -0.588423,  1.231796],
            [ 0.432131,  4.362821,  2.283113,  0.365025,  1.33159 ],...
    
    ======================================================================
    FAIL: test_selu_default_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 28 / 60 (46.7%)
    Max absolute difference: 0.078
    Max relative difference: 0.048
     x: array([[[ 1.853492,  0.420446,  1.028361,  2.354509,  1.962245],
            [-1.043557,  0.998259, -0.235026, -0.164098,  0.431416],
            [ 0.151347,  1.528007,  0.799623,  0.127844,  0.466368],...
     y: array([[[ 1.853492,  0.420446,  1.028361,  2.354509,  1.962245],
            [-1.096467,  0.998259, -0.246942, -0.172418,  0.431416],
            [ 0.151347,  1.528007,  0.799623,  0.127844,  0.466368],...
    
    ======================================================================
    FAIL: test_selu_example_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 1 / 3 (33.3%)
    Max absolute difference: 2.528
    Max relative difference: 0.667
     x: array([-1.264241,  0.      ,  3.      ], dtype=float32)
     y: array([-3.792723,  0.      ,  3.      ], dtype=float32)
    
    ======================================================================
    FAIL: test_shape_end_1_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    (shapes (3,), (1,) mismatch)
     x: array([3, 4, 5])
     y: array([3])
    
    ======================================================================
    FAIL: test_shape_end_negative_1_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    (shapes (3,), (2,) mismatch)
     x: array([3, 4, 5])
     y: array([3, 4])
    
    ======================================================================
    FAIL: test_shape_start_1_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    (shapes (3,), (2,) mismatch)
     x: array([3, 4, 5])
     y: array([4, 5])
    
    ======================================================================
    FAIL: test_shape_start_1_end_2_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    (shapes (3,), (1,) mismatch)
     x: array([3, 4, 5])
     y: array([4])
    
    ======================================================================
    FAIL: test_shape_start_1_end_negative_1_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    (shapes (3,), (1,) mismatch)
     x: array([3, 4, 5])
     y: array([4])
    
    ======================================================================
    FAIL: test_shape_start_negative_1_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    (shapes (3,), (1,) mismatch)
     x: array([3, 4, 5])
     y: array([5])
    
    ======================================================================
    FAIL: test_softmax_default_axis_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 191, in assert_similar_outputs
        np.testing.assert_allclose(
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1530, in assert_allclose
        assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Not equal to tolerance rtol=0.001, atol=1e-07
    
    Mismatched elements: 60 / 60 (100%)
    Max absolute difference: 0.359
    Max relative difference: 2.949
     x: array([[[0.528422, 0.116434, 0.369971, 0.722795, 0.544447],
            [0.240596, 0.201796, 0.161748, 0.085238, 0.126825],
            [0.104573, 0.334101, 0.297592, 0.086826, 0.131115],...
     y: array([[[0.225649, 0.05769 , 0.10289 , 0.363515, 0.250256],
            [0.294493, 0.286594, 0.128938, 0.122878, 0.167097],
            [0.112513, 0.417088, 0.208526, 0.110024, 0.151849],...
    
    ======================================================================
    FAIL: test_strnormalizer_export_monday_casesensintive_lower_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 189, in assert_similar_outputs
        np.testing.assert_array_equal(outputs[i], ref_outputs[i])
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 934, in assert_array_equal
        assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Arrays are not equal
    
    (shapes (4,), (3,) mismatch)
     x: array(['', 'tuesday', 'wednesday', 'thursday'], dtype=object)
     y: array(['tuesday', 'wednesday', 'thursday'], dtype=object)
    
    ======================================================================
    FAIL: test_strnormalizer_export_monday_casesensintive_nochangecase_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 189, in assert_similar_outputs
        np.testing.assert_array_equal(outputs[i], ref_outputs[i])
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 934, in assert_array_equal
        assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Arrays are not equal
    
    (shapes (4,), (3,) mismatch)
     x: array(['', 'tuesday', 'wednesday', 'thursday'], dtype=object)
     y: array(['tuesday', 'wednesday', 'thursday'], dtype=object)
    
    ======================================================================
    FAIL: test_strnormalizer_export_monday_casesensintive_upper_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 189, in assert_similar_outputs
        np.testing.assert_array_equal(outputs[i], ref_outputs[i])
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 934, in assert_array_equal
        assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Arrays are not equal
    
    (shapes (4,), (3,) mismatch)
     x: array(['', 'TUESDAY', 'WEDNESDAY', 'THURSDAY'], dtype=object)
     y: array(['TUESDAY', 'WEDNESDAY', 'THURSDAY'], dtype=object)
    
    ======================================================================
    FAIL: test_strnormalizer_export_monday_empty_output_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 189, in assert_similar_outputs
        np.testing.assert_array_equal(outputs[i], ref_outputs[i])
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 934, in assert_array_equal
        assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Arrays are not equal
    
    (shapes (2,), (1,) mismatch)
     x: array(['', ''], dtype=object)
     y: array([''], dtype=object)
    
    ======================================================================
    FAIL: test_strnormalizer_export_monday_insensintive_upper_twodim_cpu (__main__.OnnxBackendNodeModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 189, in assert_similar_outputs
        np.testing.assert_array_equal(outputs[i], ref_outputs[i])
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 934, in assert_array_equal
        assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Arrays are not equal
    
    (shapes (1, 6), (1, 4) mismatch)
     x: array([['MONDAY', 'TUESDAY', 'WEDNESDAY', 'MONDAY', 'TUESDAY',
            'WEDNESDAY']], dtype=object)
     y: array([['TUESDAY', 'WEDNESDAY', 'TUESDAY', 'WEDNESDAY']], dtype=object)
    
    ======================================================================
    FAIL: test_strnorm_model_monday_casesensintive_lower_cpu (__main__.OnnxBackendSimpleModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 189, in assert_similar_outputs
        np.testing.assert_array_equal(outputs[i], ref_outputs[i])
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 934, in assert_array_equal
        assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Arrays are not equal
    
    (shapes (4,), (3,) mismatch)
     x: array(['', 'tuesday', 'wednesday', 'thursday'], dtype=object)
     y: array(['tuesday', 'wednesday', 'thursday'], dtype=object)
    
    ======================================================================
    FAIL: test_strnorm_model_monday_casesensintive_nochangecase_cpu (__main__.OnnxBackendSimpleModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 189, in assert_similar_outputs
        np.testing.assert_array_equal(outputs[i], ref_outputs[i])
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 934, in assert_array_equal
        assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Arrays are not equal
    
    (shapes (4,), (3,) mismatch)
     x: array(['', 'tuesday', 'wednesday', 'thursday'], dtype=object)
     y: array(['tuesday', 'wednesday', 'thursday'], dtype=object)
    
    ======================================================================
    FAIL: test_strnorm_model_monday_casesensintive_upper_cpu (__main__.OnnxBackendSimpleModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 189, in assert_similar_outputs
        np.testing.assert_array_equal(outputs[i], ref_outputs[i])
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 934, in assert_array_equal
        assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Arrays are not equal
    
    (shapes (4,), (3,) mismatch)
     x: array(['', 'TUESDAY', 'WEDNESDAY', 'THURSDAY'], dtype=object)
     y: array(['TUESDAY', 'WEDNESDAY', 'THURSDAY'], dtype=object)
    
    ======================================================================
    FAIL: test_strnorm_model_monday_empty_output_cpu (__main__.OnnxBackendSimpleModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 189, in assert_similar_outputs
        np.testing.assert_array_equal(outputs[i], ref_outputs[i])
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 934, in assert_array_equal
        assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Arrays are not equal
    
    (shapes (2,), (1,) mismatch)
     x: array(['MONDAY', 'MONDAY'], dtype=object)
     y: array([''], dtype=object)
    
    ======================================================================
    FAIL: test_strnorm_model_monday_insensintive_upper_twodim_cpu (__main__.OnnxBackendSimpleModelTest)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 265, in device_test_func
        return test_func(*args, device=device, **kwargs)
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 321, in run
        self.assert_similar_outputs(ref_outputs, outputs,
      File "/usr/local/lib/python3.9/site-packages/onnx/backend/test/runner/__init__.py", line 189, in assert_similar_outputs
        np.testing.assert_array_equal(outputs[i], ref_outputs[i])
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 934, in assert_array_equal
        assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
      File "/var/lib/jenkins/workspace/mlprodict/mlprodict_UT_39_std/_venv/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 763, in assert_array_compare
        raise AssertionError(msg)
    AssertionError: 
    Arrays are not equal
    
    (shapes (1, 6), (1, 4) mismatch)
     x: array([['MONDAY', 'TUESDAY', 'WEDNESDAY', 'MONDAY', 'TUESDAY',
            'WEDNESDAY']], dtype=object)
     y: array([['TUESDAY', 'WEDNESDAY', 'TUESDAY', 'WEDNESDAY']], dtype=object)
    
    ----------------------------------------------------------------------
    Ran 2026 tests in 28.789s
    
    FAILED (failures=44, errors=303, skipped=1021)