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# 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 to `sp_indices`.
• sp_shape: 1-D. Shape of the input SparseTensor.

Returns:

• `Output`: 1-D. The `NNZ` values for the result `SparseTensor`.

### Constructors and Destructors

`SparseSoftmax(const ::tensorflow::Scope & scope, ::tensorflow::Input sp_indices, ::tensorflow::Input sp_values, ::tensorflow::Input sp_shape)`

### Public attributes

`operation`
`Operation`
`output`
`::tensorflow::Output`

### Public functions

`node() const `
`::tensorflow::Node *`
`operator::tensorflow::Input() const `
`operator::tensorflow::Output() const `

## Public attributes

### operation

`Operation operation`

### output

`::tensorflow::Output output`

## 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 `
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