tensorflow:: ops:: SparseReorder
#include <sparse_ops.h>
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
.
Args:
- 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 toinput_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 tooutput_indices
.
Constructors and Destructors |
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SparseReorder(const ::tensorflow::Scope & scope, ::tensorflow::Input input_indices, ::tensorflow::Input input_values, ::tensorflow::Input input_shape)
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Public attributes |
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operation
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output_indices
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output_values
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Public attributes
operation
Operation operation
output_indices
::tensorflow::Output output_indices
output_values
::tensorflow::Output output_values
Public functions
SparseReorder
SparseReorder( const ::tensorflow::Scope & scope, ::tensorflow::Input input_indices, ::tensorflow::Input input_values, ::tensorflow::Input input_shape )