RandomPoisson

public final class RandomPoisson

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 Classes

class RandomPoisson.Options Optional attributes for RandomPoisson

Constants

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

Public Methods

Output<V>	asOutput() Returns the symbolic handle of the tensor.
static <V extends TNumber> RandomPoisson<V>	create(Scope scope, Operand<? extends TNumber> shape, Operand<? extends TNumber> rate, Class<V> dtype, Options... options) Factory method to create a class wrapping a new RandomPoisson operation.
static RandomPoisson<TInt64>	create(Scope scope, Operand<? extends TNumber> shape, Operand<? extends TNumber> rate, 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)

Inherited Methods

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

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.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`.

From interface org.tensorflow.Operand

abstract Output<V extends TNumber>	asOutput() Returns the symbolic handle of the tensor.
abstract V extends TNumber	asTensor() Returns the tensor at this operand.
abstract Shape	shape() Returns the (possibly partially known) shape of the tensor referred to by the `Output` of this operand.
abstract Class<V extends TNumber>	type() Returns the tensor type of this operand

From interface org.tensorflow.ndarray.Shaped

abstract int	rank()
abstract Shape	shape()
abstract long	size() Computes and returns the total size of this container, in number of values.

Constants

public static final String OP_NAME

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

Constant Value: "RandomPoissonV2"

Public Methods

public Output<V> asOutput ()

Returns the symbolic handle of the 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 RandomPoisson<V> create (Scope scope, Operand<? extends TNumber> shape, Operand<? extends TNumber> rate, Class<V> dtype, 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.
options	carries optional attributes values

Returns

a new instance of RandomPoisson

public static RandomPoisson<TInt64> create (Scope scope, Operand<? extends TNumber> shape, Operand<? extends TNumber> rate, 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

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]`.

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.

public static RandomPoisson.Options seed2 (Long seed2)

Parameters

seed2	A second seed to avoid seed collision.