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
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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.
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static <V extends TNumber> RandomPoisson<V> | |
static RandomPoisson<TInt64> | |
Output<V> |
output()
A tensor with shape `shape + shape(rate)`.
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static RandomPoisson.Options |
seed(Long seed)
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static RandomPoisson.Options |
seed2(Long seed2)
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Inherited Methods
Constants
public static final String OP_NAME
The name of this op, as known by TensorFlow core engine
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 |
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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 |
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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. |
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public static RandomPoisson.Options seed2 (Long seed2)
Parameters
seed2 | A second seed to avoid seed collision. |
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