# SPDX-License-Identifier: Apache-2.0
"""onnx shape inference. Shape inference is not guaranteed to be
complete.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import onnx
import onnx.onnx_cpp2py_export.shape_inference as C
from onnx import ModelProto
from typing import Text, Union
"""Apply shape inference to the provided ModelProto.
Inferred shapes are added to the value_info field of the graph.
If the inferred values conflict with values already provided in the
graph, that means that the provided values are invalid (or there is a
bug in shape inference), and the result is unspecified.
bool check_type: Checks the type-equality for input and output
bool strict_mode: Stricter shape inference, it will throw errors if any;
Otherwise, simply stop if any error
bool data_prop: Enables data propagation for limited operators to perform shape computation
Arguments:
input (Union[ModelProto, Text, bytes], bool, bool, bool) -> ModelProto
Return:
return (ModelProto) model with inferred shape information
"""
[docs]def infer_shapes(model: Union[ModelProto, bytes], check_type: bool = False, strict_mode: bool = False, data_prop: bool = False) -> ModelProto:
if isinstance(model, (ModelProto, bytes)):
model_str = model if isinstance(model, bytes) else model.SerializeToString()
inferred_model_str = C.infer_shapes(model_str, check_type, strict_mode, data_prop)
return onnx.load_from_string(inferred_model_str)
elif isinstance(model, str):
raise TypeError('infer_shapes only accepts ModelProto or bytes,'
'you can use infer_shapes_path for the model path (String).')
else:
raise TypeError('infer_shapes only accepts ModelProto or bytes, '
'incorrect type: {}'.format(type(model)))
[docs]def infer_shapes_path(model_path: Text, output_path: Text = '', check_type: bool = False, strict_mode: bool = False, data_prop: bool = False) -> None:
"""
Take model path for shape_inference same as infer_shape; it support >2GB models
Directly output the inferred model to the output_path; Default is the original model path
"""
if isinstance(model_path, ModelProto):
raise TypeError('infer_shapes_path only accepts model Path (String),'
'you can use infer_shapes for the ModelProto.')
# Directly output the inferred model into the specified path, return nothing
elif isinstance(model_path, str):
# If output_path is not defined, default output_path would be the original model path
if output_path == '':
output_path = model_path
C.infer_shapes_path(model_path, output_path, check_type, strict_mode, data_prop)
else:
raise TypeError('infer_shapes_path only accepts model path (String), '
'incorrect type: {}'.format(type(model_path)))
InferenceError = C.InferenceError