com.microsoft - PythonOp#

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 (required): Flags to indicate whether the torch.autograd.apply’s inputs require gradients (including flags for both tensor and non-tensor inputs) 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_requires_grads (required): Flags to indicate which output has gradient 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