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enuSpace-tensorflow Manual

FusedPadConv2D

tensorflow C++ API

tensorflow::ops::FusedPadConv2D

Performs a padding as a preprocess during a convolution.

Summary

Similar to FusedResizeAndPadConv2d, this op allows for an optimized implementation where the spatial padding transformation stage is fused with the im2col lookup, but in this case without the bilinear filtering required for resizing. Fusing the padding prevents the need to write out the intermediate results as whole tensors, reducing memory pressure, and we can get some latency gains by merging the transformation calculations. The data_format attribute forConv2Disn’t supported by this op, and ‘NHWC’ order is used instead. Internally this op uses a single per-graph scratch buffer, which means that it will block if multiple versions are being run in parallel. This is because this operator is primarily an optimization to minimize memory usage.

Arguments:

  • scope: A Scope object
  • input: 4-D with shape[batch, in_height, in_width, in_channels].
  • paddings: A two-column matrix specifying the padding sizes. The number of rows must be the same as the rank ofinput.
  • filter: 4-D with shape[filter_height, filter_width, in_channels, out_channels].
  • strides: 1-D of length 4. The stride of the sliding window for each dimension ofinput. Must be in the same order as the dimension specified with format.
  • padding: The type of padding algorithm to use.

Returns:

FusedPadConv2D 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 paddings: connect Input node.
  • Input filter: connect Input node.
  • StringPiece mode: Input mode in value. ex) REFLECT
  • ArraySlice< int> strides_: Input _strides in value ex)1,3,2,1
  • StringPiece mode: Input mode in value. ex) SAME

Return:

  • Output output: Output object of FusedPadConv2D class object.

Result:

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

Using Method