#include <random_ops.h>
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
Arguments:
Optional attributes (see Attrs
):
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.Returns:
Output
: A tensor with shape shape + shape(rate)
. Each slice [:, ..., :, i0, i1, ...iN]
contains the samples drawn for rate[i0, i1, ...iN]
. Constructors and Destructors | |
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RandomPoissonV2(const ::tensorflow::Scope & scope, ::tensorflow::Input shape, ::tensorflow::Input rate) | |
RandomPoissonV2(const ::tensorflow::Scope & scope, ::tensorflow::Input shape, ::tensorflow::Input rate, const RandomPoissonV2::Attrs & attrs) |
Public attributes | |
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output |
Public functions | |
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node() const | ::tensorflow::Node * |
operator::tensorflow::Input() const | |
operator::tensorflow::Output() const |
Public static functions | |
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Dtype(DataType x) | |
Seed(int64 x) | |
Seed2(int64 x) |
Structs | |
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tensorflow::ops::RandomPoissonV2::Attrs | Optional attribute setters for RandomPoissonV2. |
::tensorflow::Output output
RandomPoissonV2( const ::tensorflow::Scope & scope, ::tensorflow::Input shape, ::tensorflow::Input rate )
RandomPoissonV2( const ::tensorflow::Scope & scope, ::tensorflow::Input shape, ::tensorflow::Input rate, const RandomPoissonV2::Attrs & attrs )
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output() const
Attrs Dtype( DataType x )
Attrs Seed( int64 x )
Attrs Seed2( int64 x )
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/cc/class/tensorflow/ops/random-poisson-v2.html