SparseSlice

public final class SparseSlice

Slice a `SparseTensor` based on the `start` and `size`.

For example, if the input is

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

Graphically the output tensors are:

sparse_slice([0, 0], [2, 4]) = shape = [2, 4] [ a ] [b c ]

sparse_slice([0, 4], [2, 3]) = shape = [2, 3] [ d e ] [ ]

String OP_NAME The name of this op, as known by TensorFlow core engine

static <T extends TType> SparseSlice<T>	create(Scope scope, Operand<TInt64> indices, Operand<T> values, Operand<TInt64> shape, Operand<TInt64> start, Operand<TInt64> size) Factory method to create a class wrapping a new SparseSlice operation.
Output<TInt64>	outputIndices()
Output<TInt64>	outputShape() A list of 1-D tensors represents the shape of the output sparse tensors.
Output<T>	outputValues() A list of 1-D tensors represents the values of the output sparse tensors.

From class org.tensorflow.op.RawOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Return this unit of computation as a single `Operation`.
final String	toString()

From class java.lang.Object

From interface org.tensorflow.op.Op

abstract ExecutionEnvironment	env() Return the execution environment this op was created in.
abstract Operation	op() Return this unit of computation as a single `Operation`.

Constants

The name of this op, as known by TensorFlow core engine

Constant Value: "SparseSlice"

Factory method to create a class wrapping a new SparseSlice operation.

scope	current scope
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.
start	1-D. tensor represents the start of the slice.
size	1-D. tensor represents the size of the slice. output indices: A list of 1-D tensors represents the indices of the output sparse tensors.

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

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