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

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.