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SparseReduceMaxSparse


tensorflow C++ API

tensorflow::ops::SparseReduceMaxSparse

Computes the max of elements across dimensions of a SparseTensor.


Summary

This Op takes a SparseTensor and is the sparse counterpart totf.reduce_max(). In contrast toSparseReduceMax, this Op returns a SparseTensor.

Reducessp_inputalong the dimensions given inreduction_axes. Unlesskeep_dimsis true, the rank of the tensor is reduced by 1 for each entry inreduction_axes. Ifkeep_dimsis true, the reduced dimensions are retained with length 1.

Ifreduction_axeshas no entries, all dimensions are reduced, and a tensor with a single element is returned. Additionally, the axes can be negative, which are interpreted according to the indexing rules in Python.

Arguments:

  • scope: A Scope object
  • input_indices: 2-D.N x Rmatrix with the indices of non-empty values in a SparseTensor, possibly not in canonical ordering.
  • input_values: 1-D.Nnon-empty values corresponding toinput_indices.
  • input_shape: 1-D.Shape of the input SparseTensor.
  • reduction_axes: 1-D. Length-Kvector containing the reduction axes.

Optional attributes (seeAttrs):

keep_dims: If true, retain reduced dimensions with length 1.

Returns:


SparseReduceMaxSparse block

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

Argument:

  • Scope scope : A Scope object (A scope is generated automatically each page. A scope is not connected.)
  • Input input_indices: connect Input node.
  • Input input_values: connect Input node.
  • Input input_shape: connect Input node.
  • Input reduction_axes: connect Input node.
  • SparseReduceMaxSparse ::Attrs attrs : Input attrs in value. ex) keep_dims= false;

Return:

  • Output output_indices: Output object of SparseReduceMaxSparse class object.
  • Output output_values: Output object of SparseReduceMaxSparse class object.
  • Output output_shape: Output object of SparseReduceMaxSparse class object.

Result:

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

Using Method