org.tensorflow.op.core

Class SparseSplit<T>

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.core.SparseSplit<T>

Type Parameters:

T - data type for outputValues() output

All Implemented Interfaces:

Op

@Operator
public final class SparseSplit<T>
extends PrimitiveOp

Split a `SparseTensor` into `num_split` tensors along one dimension.

If the `shape[split_dim]` is not an integer multiple of `num_split`. Slices `[0 : shape[split_dim] % num_split]` gets one extra dimension. For example, if `split_dim = 1` and `num_split = 2` and the input is

input_tensor = shape = [2, 7] [ a d e ] [b c ]

Graphically the output tensors are:

output_tensor[0] = shape = [2, 4] [ a ] [b c ]

output_tensor[1] = shape = [2, 3] [ d e ] [ ]

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

Modifier and Type	Method and Description
static <T> SparseSplit<T>	create(Scope scope, Operand<Long> splitDim, Operand<Long> indices, Operand<T> values, Operand<Long> shape, Long numSplit) Factory method to create a class to wrap a new SparseSplit operation to the graph.
List<Output<Long>>	outputIndices()
List<Output<Long>>	outputShape() A list of 1-D tensors represents the shape of the output sparse tensors.
List<Output<T>>	outputValues() A list of 1-D tensors represents the values of the output sparse tensors.

Methods inherited from class org.tensorflow.op.PrimitiveOp

equals, hashCode, toString

Methods inherited from class java.lang.Object

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

Method Detail

create

public static <T> SparseSplit<T> create(Scope scope,
                                        Operand<Long> splitDim,
                                        Operand<Long> indices,
                                        Operand<T> values,
                                        Operand<Long> shape,
                                        Long numSplit)

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

Parameters:

scope - current graph scope

splitDim - 0-D. The dimension along which to split. Must be in the range `[0, rank(shape))`.

indices - 2-D tensor represents the indices of the sparse tensor.

values - 1-D tensor represents the values of the sparse tensor.

shape - 1-D. tensor represents the shape of the sparse tensor. output indices: A list of 1-D tensors represents the indices of the output sparse tensors.

numSplit - The number of ways to split.

Returns:

a new instance of SparseSplit

outputIndices

public List<Output<Long>> outputIndices()

outputValues

public List<Output<T>> outputValues()

A list of 1-D tensors represents the values of the output sparse tensors.

outputShape

public List<Output<Long>> outputShape()

A list of 1-D tensors represents the shape of the output sparse tensors.