T
- data type for output()
output@Operator(group="sparse") public final class SparseSoftmax<T extends Number> extends PrimitiveOp implements Operand<T>
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.
operation
Modifier and Type | Method and Description |
---|---|
Output<T> |
asOutput()
Returns the symbolic handle of a tensor.
|
static <T extends Number> |
create(Scope scope,
Operand<Long> spIndices,
Operand<T> spValues,
Operand<Long> spShape)
Factory method to create a class wrapping a new SparseSoftmax operation.
|
Output<T> |
output()
1-D.
|
equals, hashCode, op, toString
public static <T extends Number> SparseSoftmax<T> create(Scope scope, Operand<Long> spIndices, Operand<T> spValues, Operand<Long> spShape)
scope
- current scopespIndices
- 2-D. `NNZ x R` matrix with the indices of non-empty values in a
SparseTensor, in canonical ordering.spValues
- 1-D. `NNZ` non-empty values corresponding to `sp_indices`.spShape
- 1-D. Shape of the input SparseTensor.public Output<T> asOutput()
Operand
Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.
asOutput
in interface Operand<T extends Number>
OperationBuilder.addInput(Output)
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