org.tensorflow.op.random

Class RandomPoisson<V extends Number>

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.random.RandomPoisson<V>

Type Parameters:

V - data type for output() output

All Implemented Interfaces:

Op, Operand<V>

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

Outputs random values from the Poisson distribution(s) described by rate.

This op uses two algorithms, depending on rate. If rate >= 10, then the algorithm by Hormann is used to acquire samples via transformation-rejection. See http://www.sciencedirect.com/science/article/pii/0167668793909974.

Otherwise, Knuth's algorithm is used to acquire samples via multiplying uniform random variables. See Donald E. Knuth (1969). Seminumerical Algorithms. The Art of Computer Programming, Volume 2. Addison Wesley

Nested Class Summary

Nested Classes

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

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

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

Factory method to create a class wrapping a new RandomPoisson 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 rate.

rate - A tensor in which each scalar is a "rate" parameter describing the associated poisson distribution.

dtype -

options - carries optional attributes values

Returns:

a new instance of RandomPoisson

create

public static <T extends Number,U extends Number> RandomPoisson<Long> create(Scope scope,
                                                                             Operand<T> shape,
                                                                             Operand<U> rate,
                                                                             RandomPoisson.Options... options)

Factory method to create a class wrapping a new RandomPoisson operation using default output types.

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 rate.

rate - A tensor in which each scalar is a "rate" parameter describing the associated poisson distribution.

options - carries optional attributes values

Returns:

a new instance of RandomPoisson

seed

public static RandomPoisson.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 RandomPoisson.Options seed2(Long seed2)

Parameters:

seed2 - A second seed to avoid seed collision.

output

public Output<V> output()

A tensor with shape `shape + shape(rate)`. Each slice `[:, ..., :, i0, i1, ...iN]` contains the samples drawn for `rate[i0, i1, ...iN]`.

asOutput

public Output<V> 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<V extends Number>

See Also:

OperationBuilder.addInput(Output)