com.microsoft - PythonOpGrad#

PythonOpGrad - 1 (com.microsoft)#

Version

This version of the operator has been available since version 1 of domain com.microsoft.

Summary

Wrapper of Pytorch’s autograd.Function’s backward implementaiton.

Attributes

inplace: Indicate if the output should reuse input memory. Todo(pengwa): do we really need it? Default value is ?.
input_tensor_ranks: Input ranks of autograd.Function.backward (including only tensor inputs).This attribute is mostly used for input checks for better robustness. Default value is ?.
input_tensor_requires_grads (required): Flags to indicate which inputs have gradients (including only tensor inputs).This attribute is mostly used for input checks for better robustness. Default value is ?.
input_tensor_types: Input types of autograd.Function.backward (including only tensor inputs).This attribute is mostly used for input checks for better robustnes. Default value is ?.
name (required): Name of custom class. Default value is ?.
output_convention (required): A string inidicating autograd.Function.backward outputs’s type.value ‘c’ - non-tensor output; value ‘d’ - tensor output. Default value is ?.
output_tensor_ranks: Output ranks of autograd.Function.backward outputs (including only tensor outputs). Default value is ?.
output_tensor_requires_grads (required): Flags to indicate which outputs have gradients (including only tensor outputs). Default value is ?.
output_tensor_types: Output types of autograd.Function.backward outputs (including only tensor outputs). Default value is ?.

Inputs

Between 2 and 2147483647 inputs.

context (heterogeneous) - TInt64: Address of context created in this operator. It should be generated by the corresponding forward.
inputs (variadic) - T: There are 2*N inputs: N gradient inputs (as inputs of autograd.Function.backward) + N forward run activations of autograd.Function.apply.The N forward run inputs are used as control dependency between PythonOpGrad and PythonOp

Outputs

Between 1 and 2147483647 outputs.

Examples