4cd1437dda39ad067f139ecc1d0ab1f41947e1ac,onnx_coreml/_transformers.py,ReshapeInitTensorFuser,__call__,#ReshapeInitTensorFuser#Any#,250

Before Change

                continue
            if shape_name not in node.input_tensors:
                continue
            assert len(node.parents) == 0

            removed.append(node)
            output_name = node.outputs[0]

After Change

                    if parent.op_type != "Constant":
                        is_non_constant_parent = True
                        break
            if is_non_constant_parent:
                continue

            removed.append(node)
            output_name = node.outputs[0]

            tensor = node.input_tensors[tensor_name]
            if "shape" in node.attrs:
                shape = tuple(node.attrs["shape"])
            else:
                shape = node.input_tensors[shape_name] // type: ignore

            // ONNX spec supports setting dimension to "0", in which case
            // it should be taken from old dimension.
            // This isn"t supported in numpy, so don"t transform.
            // TODO Should we support this case?
            if any([s == 0 for s in shape]):
                continue

            reshaped_tensor = tensor.reshape(shape)

Instances