ReadVariableXlaSplitND

public final class ReadVariableXlaSplitND

Splits resource variable input tensor across all dimensions.

An op which splits the resource variable input tensor based on the given num_splits attribute, pads slices optionally, and returned the slices. Slices are returned in row-major order.

This op may be generated via the TPU bridge.

For example, with `input` tensor:

[[0, 1, 2],
  [3, 4, 5],
  [6, 7, 8]]

`num_splits`:

[2, 2]

and `paddings`:

[1, 1]

the expected `outputs` is:

[[0, 1],
  [3, 4]]
 [[2, 0],
  [5, 0]]
 [[6, 7],
  [0, 0]]
 [[8, 0],
  [0, 0]]

Nested Classes

class ReadVariableXlaSplitND.Options Optional attributes for ReadVariableXlaSplitND

Public Methods

static <T> ReadVariableXlaSplitND<T>	create(Scope scope, Operand<?> resource, Class<T> T, Long N, List<Long> numSplits, Options... options) Factory method to create a class wrapping a new ReadVariableXlaSplitND operation.
Iterator<Operand<T>>	iterator()
List<Output<T>>	outputs()
static ReadVariableXlaSplitND.Options	paddings(List<Long> paddings)

Inherited Methods

From class org.tensorflow.op.PrimitiveOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Returns the underlying `Operation`
final String	toString()

From class java.lang.Object

boolean	equals(Object arg0)
final Class<?>	getClass()
int	hashCode()
final void	notify()
final void	notifyAll()
String	toString()
final void	wait(long arg0, int arg1)
final void	wait(long arg0)
final void	wait()

From interface java.lang.Iterable

void	forEach(Consumer<? super T> arg0)
abstract Iterator<Operand<T>>	iterator()
Spliterator<Operand<T>>	spliterator()

Public Methods

public static ReadVariableXlaSplitND<T> create (Scope scope, Operand<?> resource, Class<T> T, Long N, List<Long> numSplits, Options... options)

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

Parameters

scope	current scope
resource	Resource variable of input tensor to split across all dimensions. } out_arg { name: "outputs" description: <
numSplits	Number of ways to split per dimension. Shape dimensions must be evenly divisible.
options	carries optional attributes values

Returns

a new instance of ReadVariableXlaSplitND

public Iterator<Operand<T>> iterator ()

public List<Output<T>> outputs ()

public static ReadVariableXlaSplitND.Options paddings (List<Long> paddings)

Parameters

paddings	Optional list of right paddings per dimension of input tensor to apply before splitting. This can be used to make a dimension evenly divisible.