def infer_shapes(model: Union[ModelProto, bytes],
check_type: bool = False,
strict_mode: bool = False,
data_prop: bool = False) -> ModelProto:
"""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.
Arguments:
model (Union[ModelProto, bytes], bool, bool, bool) -> ModelProto
check_type (bool): Checks the type-equality for input and output
strict_mode (bool): Stricter shape inference, it will throw errors if any;
Otherwise, simply stop if any error
data_prop (bool): Enables data propagation for limited operators to perform shape computation
Returns:
(ModelProto) model with inferred shape information
"""
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)))
def infer_shapes(model, check_type=False): # type: (ModelProto,bool) -> ModelProto
if not isinstance(model, ModelProto):
raise ValueError('Shape inference only accepts ModelProto, '
'incorrect type: {}'.format(type(model)))
model_str = model.SerializeToString()
inferred_model_str = C.infer_shapes(model_str, check_type)
return onnx.load_from_string(inferred_model_str)
def infer_shapes(model): # type: (ModelProto) -> ModelProto
if not isinstance(model, ModelProto):
raise ValueError('Shape inference only accepts ModelProto, '
'incorrect type: {}'.format(type(model)))
model_str = model.SerializeToString()
inferred_model_str = C.infer_shapes(model_str)
return onnx.load_from_string(inferred_model_str)
def infer_shapes(model, check_type=False): # type: (ModelProto, bool) -> ModelProto
if isinstance(model, ModelProto):
model_str = model.SerializeToString()
inferred_model_str = C.infer_shapes(model_str, check_type)
return onnx.load_from_string(inferred_model_str)
elif isinstance(model, string_types):
raise TypeError('infer_shapes only accepts ModelProto,'
'you can use infer_shapes_path for the model path (String).')
else:
raise TypeError('infer_shapes only accepts ModelProto, '
'incorrect type: {}'.format(type(model)))
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)))