tensorflow::
ops::
SparseSoftmax
#include <sparse_ops.h>
Applies softmax to a batched N-D
SparseTensor
.
Summary
The inputs represent an N-D SparseTensor with logical shape
[..., B, C]
(where
N >= 2
), and with indices sorted in the canonical lexicographic order.
This op is equivalent to applying the normal
tf.nn.softmax()
to each innermost logical submatrix with shape
[B, C]
, but with the catch that
the implicitly zero elements do not participate
. Specifically, the algorithm is equivalent to the following:
(1) Applies
tf.nn.softmax()
to a densified view of each innermost submatrix with shape
[B, C]
, along the size-C dimension; (2) Masks out the original implicitly-zero locations; (3) Renormalizes the remaining elements.
Hence, the
SparseTensor
result has exactly the same non-zero indices and shape.
Args:
- scope: A Scope object
-
sp_indices: 2-D.
NNZ x R
matrix with the indices of non-empty values in a SparseTensor, in canonical ordering. -
sp_values: 1-D.
NNZ
non-empty values corresponding tosp_indices
. - sp_shape: 1-D. Shape of the input SparseTensor.
Returns:
-
Output
: 1-D. TheNNZ
values for the resultSparseTensor
.
Constructors and Destructors |
|
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SparseSoftmax
(const ::
tensorflow::Scope
& scope, ::
tensorflow::Input
sp_indices, ::
tensorflow::Input
sp_values, ::
tensorflow::Input
sp_shape)
|
Public attributes |
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operation
|
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output
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Public functions |
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node
() const
|
::tensorflow::Node *
|
operator::tensorflow::Input
() const
|
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operator::tensorflow::Output
() const
|
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Public attributes
Public functions
SparseSoftmax
SparseSoftmax( const ::tensorflow::Scope & scope, ::tensorflow::Input sp_indices, ::tensorflow::Input sp_values, ::tensorflow::Input sp_shape )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const