Package org.tensorflow.op.sparse

Class SparseReduceSumSparse<T>

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.sparse.SparseReduceSumSparse<T>

Type Parameters:

T - data type for outputValues() output

All Implemented Interfaces:

Op

@Operator(group="sparse")
public final class SparseReduceSumSparse<T>
extends PrimitiveOp

Computes the sum of elements across dimensions of a SparseTensor.

This Op takes a SparseTensor and is the sparse counterpart to `tf.reduce_sum()`. In contrast to SparseReduceSum, this Op returns a SparseTensor.

Reduces `sp_input` along the dimensions given in `reduction_axes`. Unless `keep_dims` is true, the rank of the tensor is reduced by 1 for each entry in `reduction_axes`. If `keep_dims` is true, the reduced dimensions are retained with length 1.

If `reduction_axes` has no entries, all dimensions are reduced, and a tensor with a single element is returned. Additionally, the axes can be negative, which are interpreted according to the indexing rules in Python.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	SparseReduceSumSparse.Options	Optional attributes for SparseReduceSumSparse

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

Modifier and Type	Method	Description
static <T> SparseReduceSumSparse<T>	create(Scope scope, Operand<java.lang.Long> inputIndices, Operand<T> inputValues, Operand<java.lang.Long> inputShape, Operand<java.lang.Integer> reductionAxes, SparseReduceSumSparse.Options... options)	Factory method to create a class to wrap a new SparseReduceSumSparse operation to the graph.
static SparseReduceSumSparse.Options	keepDims(java.lang.Boolean keepDims)
Output<java.lang.Long>	outputIndices()
Output<java.lang.Long>	outputShape()
Output<T>	outputValues()

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from class org.tensorflow.op.PrimitiveOp

equals, hashCode, toString

Method Detail

create

public static <T> SparseReduceSumSparse<T> create(Scope scope,
                                                  Operand<java.lang.Long> inputIndices,
                                                  Operand<T> inputValues,
                                                  Operand<java.lang.Long> inputShape,
                                                  Operand<java.lang.Integer> reductionAxes,
                                                  SparseReduceSumSparse.Options... options)

Factory method to create a class to wrap a new SparseReduceSumSparse operation to the graph.

Parameters:

scope - current graph scope

inputIndices - 2-D. `N x R` matrix with the indices of non-empty values in a SparseTensor, possibly not in canonical ordering.

inputValues - 1-D. `N` non-empty values corresponding to `input_indices`.

inputShape - 1-D. Shape of the input SparseTensor.

reductionAxes - 1-D. Length-`K` vector containing the reduction axes.

options - carries optional attributes values

Returns:

a new instance of SparseReduceSumSparse

keepDims

public static SparseReduceSumSparse.Options keepDims(java.lang.Boolean keepDims)

Parameters:

keepDims - If true, retain reduced dimensions with length 1.

outputIndices

public Output<java.lang.Long> outputIndices()

outputValues

public Output<T> outputValues()

outputShape

public Output<java.lang.Long> outputShape()