Link Search Menu Expand Document

Dilation2DBackpropInput


tensorflow C++ API

tensorflow::ops::Dilation2DBackpropInput

Computes the gradient of morphological 2-D dilation with respect to the input.


Summary

Arguments:

  • scope: A Scope object
  • input: 4-D with shape[batch, in_height, in_width, depth].
  • filter: 3-D with shape[filter_height, filter_width, depth].
  • out_backprop: 4-D with shape[batch, out_height, out_width, depth].
  • strides: 1-D of length 4. The stride of the sliding window for each dimension of the input tensor. Must be: [1, stride_height, stride_width, 1].
  • rates: 1-D of length 4. The input stride for atrous morphological dilation. Must be: [1, rate_height, rate_width, 1].
  • padding: The type of padding algorithm to use.

Returns:

  • Output: 4-D with shape[batch, in_height, in_width, depth].

Dilation2DBackpropInput block

Source link : https://github.com/EXPNUNI/enuSpaceTensorflow/blob/master/enuSpaceTensorflow/tf_nn.cpp

Argument:

  • Scope scope : A Scope object (A scope is generated automatically each page. A scope is not connected.)
  • Input input: connect Input node.
  • Input filter: connect Input node.
  • Input out_backprop: connect Input node.
  • gtl::ArraySlice< int > strides: Input strides in value ex)1,2,2,1
  • gtl::ArraySlice< int > rates: Input strides in value ex)1,2,2,1
  • StringPiece padding: Input paddingin value ex)SAME
  • Dilation2DBackpropInput::Attrs attrs : Input attrs in value. ex) data_format_ = NHWC;

Return:

  • Output in_backprop : Output object of Dilation2DBackpropInput class object.

Result:

  • std::vector(Tensor) result_in_backprop : Returned object of executed result by calling session.

Using Method