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enuSpace-tensorflow Manual

SparseAdd

tensorflow C++ API

tensorflow::ops::SparseAdd

Adds two SparseTensor objects to produce another SparseTensor

Summary

The input SparseTensor objects’ indices are assumed ordered in standard lexicographic order. If this is not the case, before this step run SparseReorder to restore index ordering.

By default, if two values sum to zero at some index, the output SparseTensor would still include that particular location in its index, storing a zero in the corresponding value slot. To override this, callers can specify thresh, indicating that if the sum has a magnitude strictly smaller than thresh, its corresponding value and index would then not be included. In particular, thresh == 0 (default) means everything is kept and actual thresholding happens only for a positive value.

In the following shapes, nnz is the count after taking thresh into account.

Arguments:

  • scope: A Scope object
  • a_indices: 2-D. The indices of the first SparseTensor, size [nnz, ndims] Matrix.
  • a_values: 1-D. The values of the first SparseTensor, size [nnz] Vector.
  • a_shape: 1-D. The shape of the first SparseTensor, size [ndims] Vector.
  • b_indices: 2-D. The indices of the second SparseTensor, size [nnz, ndims] Matrix.
  • b_values: 1-D. The values of the second SparseTensor, size [nnz] Vector.
  • b_shape: 1-D. The shape of the second SparseTensor, size [ndims] Vector.
  • thresh: 0-D. The magnitude threshold that determines if an output value/index pair takes space.

Returns:

SparseAdd 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 a_indices: connect Input node.
  • Input a_values: connect Input node.
  • Input a_shape: connect Input node.
  • Input b_indices: connect Input node.
  • Input b_values: connect Input node.
  • Input b_shape: connect Input node.
  • Input thresh: connect Input node.

Return:

  • Output sum_indices: Output object of SparseAdd class object.
  • Output sum_values: Output object of SparseAdd class object.
  • Output sum_shape: Output object of SparseAdd class object.

Result:

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

Using Method