org.tensorflow.op.random

Class RandomGamma<U extends Number>

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.random.RandomGamma<U>

Type Parameters:

U - data type for output() output

All Implemented Interfaces:

Op, Operand<U>

@Operator(group="random")
public final class RandomGamma<U extends Number>
extends PrimitiveOp
implements Operand<U>

Outputs random values from the Gamma distribution(s) described by alpha.

This op uses the algorithm by Marsaglia et al. to acquire samples via transformation-rejection from pairs of uniform and normal random variables. See http://dl.acm.org/citation.cfm?id=358414

Nested Class Summary

Nested Classes

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

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

Modifier and Type	Method and Description
Output<U>	asOutput() Returns the symbolic handle of a tensor.
static <U extends Number,T extends Number> RandomGamma<U>	create(Scope scope, Operand<T> shape, Operand<U> alpha, RandomGamma.Options... options) Factory method to create a class wrapping a new RandomGamma operation.
Output<U>	output() A tensor with shape `shape + shape(alpha)`.
static RandomGamma.Options	seed(Long seed)
static RandomGamma.Options	seed2(Long seed2)

Methods inherited from class org.tensorflow.op.PrimitiveOp

equals, hashCode, op, toString

Methods inherited from class java.lang.Object

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

Method Detail

create

public static <U extends Number,T extends Number> RandomGamma<U> create(Scope scope,
                                                                        Operand<T> shape,
                                                                        Operand<U> alpha,
                                                                        RandomGamma.Options... options)

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

Parameters:

scope - current scope

shape - 1-D integer tensor. Shape of independent samples to draw from each distribution described by the shape parameters given in alpha.

alpha - A tensor in which each scalar is a "shape" parameter describing the associated gamma distribution.

options - carries optional attributes values

Returns:

a new instance of RandomGamma

seed

public static RandomGamma.Options seed(Long seed)

Parameters:

seed - If either `seed` or `seed2` are set to be non-zero, the random number generator is seeded by the given seed. Otherwise, it is seeded by a random seed.

seed2

public static RandomGamma.Options seed2(Long seed2)

Parameters:

seed2 - A second seed to avoid seed collision.

output

public Output<U> output()

A tensor with shape `shape + shape(alpha)`. Each slice `[:, ..., :, i0, i1, ...iN]` contains the samples drawn for `alpha[i0, i1, ...iN]`. The dtype of the output matches the dtype of alpha.

asOutput

public Output<U> asOutput()

Description copied from interface: Operand

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.

Specified by:

asOutput in interface Operand<U extends Number>

See Also:

OperationBuilder.addInput(Output)