Coverage for mlprodict/onnxrt/ops_cpu/op_concat.py: 100%

1# -*- encoding: utf-8 -*- 

2# pylint: disable=E0203,E1101,C0111 

3""" 

4@file 

5@brief Runtime operator. 

6""" 

7import numpy 

8from ...onnx_tools.onnx2py_helper import guess_numpy_type_from_dtype 

9from ._op import OpRun 

10from ..shape_object import ShapeObject 

11 

12 

13class Concat(OpRun): 

14 

15 atts = {'axis': 0} 

16 python_inputs = ['*inputs'] 

17 

18 def __init__(self, onnx_node, desc=None, **options): 

19 OpRun.__init__(self, onnx_node, desc=desc, 

20 expected_attributes=Concat.atts, 

21 **options) 

22 

23 def _preprocess(self, a): 

24 if len(a.shape) == 0: 

25 raise RuntimeError( # pragma: no cover 

26 "Concat: one input has an empty shape: %r." % a) 

27 if self.axis >= len(a.shape): 

28 new_shape = a.shape + (1, ) * (self.axis + 1 - len(a.shape)) 

29 return a.reshape(new_shape) 

30 return a 

31 

32 def _run(self, *args): # pylint: disable=W0221 

33 targs = tuple(self._preprocess(a) for a in args) 

34 return (numpy.concatenate(targs, self.axis), ) 

35 

36 def _infer_shapes(self, *args): # pylint: disable=W0221 

37 return (args[0].concat_columns(self.axis, *(args[1:])), ) 

38 

39 def _infer_types(self, *args): # pylint: disable=W0221 

40 args = [guess_numpy_type_from_dtype(a) for a in args] 

41 res = (ShapeObject._infer_merged_type(*args, use_dtype=False), ) 

42 return res 

43 

44 def _infer_sizes(self, *args, **kwargs): 

45 res = self.run(*args, **kwargs) 

46 return (dict(temp=0), ) + res 

47 

48 def to_python(self, inputs): 

49 return "import numpy", "return numpy.concatenate(inputs, axis=axis)"