SparseReduceMax

tensorflow C++ API

tensorflow::ops::SparseReduceMax

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 particular, this Op also returns a denseTensorinstead of a sparse one.

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:

• Output:R-K-D. The reduced Tensor.

SparseReduceMax 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.
• SparseReduceMax ::Attrs attrs : Input attrs in value. ex) keep_dims= false;

Return:

• Output output: Output object of SparseReduceMax class object.

Result:

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

Using Method