TPUPartitionedInput

public final class TPUPartitionedInput

An op that groups a list of partitioned inputs together. This op

Nested Classes

class

TPUPartitionedInput.Options

Optional attributes for TPUPartitionedInput

Public Methods

Output <T>	asOutput () Returns the symbolic handle of a tensor.
static <T> TPUPartitionedInput <T>	create ( Scope scope, Iterable< Operand <T>> inputs, Options... options) Factory method to create a class wrapping a new TPUPartitionedInput operation.
Output <T>	output () A handle which represents the full shape of partitioned tensors.
static TPUPartitionedInput.Options	partitionDim (Long partitionDim)

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 org.tensorflow.Operand

abstract Output <T>

asOutput () Returns the symbolic handle of a tensor.

Public Methods

public Output <T> asOutput ()

Returns the symbolic handle of a tensor.

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.

public static TPUPartitionedInput <T> create ( Scope scope, Iterable< Operand <T>> inputs, Options... options)

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

Parameters

scope	current scope
inputs	A list of partitioned inputs which must have the same shape.
options	carries optional attributes values

Returns

• a new instance of TPUPartitionedInput

public Output <T> output ()

A handle which represents the full shape of partitioned tensors.

public static TPUPartitionedInput.Options partitionDim (Long partitionDim)

Parameters

partitionDim	An integer describles which dimension is partitioned. -1 means those inputs are replicated.