.. _l-onnx-doccom.microsoft-PythonOp: ======================== com.microsoft - PythonOp ======================== .. contents:: :local: .. _l-onnx-opcom-microsoft-pythonop-1: PythonOp - 1 (com.microsoft) ============================ **Version** * **name**: `PythonOp (GitHub) `_ * **domain**: **com.microsoft** * **since_version**: **1** * **function**: * **support_level**: * **shape inference**: This version of the operator has been available **since version 1 of domain com.microsoft**. **Summary** Wrapper of Pytorch's autograd.Function implementation. **Attributes** * **inplace**: Indicate if the output should reuse input memory. Default value is ``?``. * **input_convention** (required): input_convention[i]==c means a non-tensor argument. input_convention[i]==d means a tensor. Default value is ``?``. * **input_float_scalar_positions**: Default value is ``?``. * **input_float_scalars**: Python float arguments. Default value is ``?``. * **input_float_tuple_begins**: Default value is ``?``. * **input_float_tuple_positions**: Default value is ``?``. * **input_float_tuples**: Default value is ``?``. * **input_int_scalar_positions**: Default value is ``?``. * **input_int_scalars**: Python int arguments. Default value is ``?``. * **input_int_tuple_begins**: Default value is ``?``. * **input_int_tuple_positions**: Default value is ``?``. * **input_int_tuples**: Python int-tuple arguments. Default value is ``?``. * **input_pointer_scalar_positions**: Default value is ``?``. * **input_pointer_scalars**: Default value is ``?``. * **input_requires_grads**: Flags to indicate whether the torch.autograd.apply's inputs require gradients (including flags for both tensor and non-tensor inputs). If not provided, all value in the vector is 0,which means all inputs don't require grad. Frontend needs this info to call into torch correctly. Default value is ``?``. * **input_tensor_ranks** (required): Input tensors' ranks of autograd.Function.apply. Default value is ``?``. * **input_tensor_types** (required): Input types of autograd.Function.apply. Default value is ``?``. * **name** (required): Name of custom class. Default value is ``?``. * **output_tensor_ranks** (required): Output tensors' ranks of autograd.Function.apply. Default value is ``?``. * **output_tensor_types** (required): Output types of autograd.Function.apply. Default value is ``?``. * **training_mode**: Indicate if the model is exported in training_mode, by default, False. Default value is ``?``. **Inputs** Between 1 and 2147483647 inputs. * **inputs** (variadic) - **T**: Module outputs to be returned to pytorch. **Outputs** Between 2 and 2147483647 outputs. * **context** (heterogeneous) - **TInt64**: Address of context created in this operator. It can be used in backward. * **outputs** (variadic) - **T**: Outputs returned from pytorch. **Examples**