SparseReorder

tensorflow C++ API

tensorflow::ops::SparseReorder

Reorders a SparseTensor into the canonical, row-major ordering.

Summary

Note that by convention, all sparse ops preserve the canonical ordering along increasing dimension number. The only time ordering can be violated is during manual manipulation of the indices and values vectors to add entries.

Reordering does not affect the shape of the SparseTensor.

If the tensor has rank R and N non-empty values, input_indices has shape [N, R], input_values has length N, and input_shape has length R.

Arguments:

• scope: A Scope object
• input_indices: 2-D. N x R matrix with the indices of non-empty values in a SparseTensor, possibly not in canonical ordering.
• input_values: 1-D. N non-empty values corresponding to input_indices.
• input_shape: 1-D. Shape of the input SparseTensor.

Returns:

• Output output_indices: 2-D. N x R matrix with the same indices as input_indices, but in canonical row-major ordering.
• Output output_values: 1-D. N non-empty values corresponding to output_indices.

SparseReorder 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 sp_indices: connect Input node.
• Input sp_values: connect Input node.
• Input sp_shape: connect Input node.
• Input dense: connect Input node.

Return:

• Output output: Output object of SparseDenseCwiseMul class object.

Result:

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

Using Method