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tensorflow::ops::RandomPoissonV2
#include <random_ops.h>
Outputs random values from the Poisson distribution(s) described by rate.
Summary
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:
- scope: A Scope object
- 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.
Optional attributes (see Attrs
):
- 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: A second seed to avoid seed collision.
Returns:
Output
: A tensor with shape shape + shape(rate)
. Each slice [:, ..., :, i0, i1, ...iN]
contains the samples drawn for rate[i0, i1, ...iN]
.
Public static functions
|
Dtype(DataType x)
|
|
Seed(int64 x)
|
|
Seed2(int64 x)
|
|
Public attributes
Public functions
node
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
Public static functions
Dtype
Attrs Dtype(
DataType x
)
Seed
Attrs Seed(
int64 x
)
Seed2
Attrs Seed2(
int64 x
)
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Last updated 2020-04-20 UTC.
[null,null,["Last updated 2020-04-20 UTC."],[],[],null,["# tensorflow::ops::RandomPoissonV2 Class Reference\n\ntensorflow::ops::RandomPoissonV2\n================================\n\n`#include \u003crandom_ops.h\u003e`\n\nOutputs random values from the Poisson distribution(s) described by rate.\n\nSummary\n-------\n\nThis op uses two algorithms, depending on rate. If rate \\\u003e= 10, then the algorithm by Hormann is used to acquire samples via transformation-rejection. See \u003chttp://www.sciencedirect.com/science/article/pii/0167668793909974\u003e.\n\nOtherwise, 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\n\nArguments:\n\n- scope: A [Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- shape: 1-D integer tensor. Shape of independent samples to draw from each distribution described by the shape parameters given in rate.\n- rate: A tensor in which each scalar is a \"rate\" parameter describing the associated poisson distribution.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/random-poisson-v2/attrs#structtensorflow_1_1ops_1_1_random_poisson_v2_1_1_attrs)):\n\n- 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.\n- seed2: A second seed to avoid seed collision.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): A tensor with shape `shape + shape(rate)`. Each slice `[:, ..., :, i0, i1, ...iN]` contains the samples drawn for `rate[i0, i1, ...iN]`.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [RandomPoissonV2](#classtensorflow_1_1ops_1_1_random_poisson_v2_1ac6781b746b5d655d44cf7298d0ec0e8d)`(const ::`[tensorflow::Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` shape, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` rate)` ||\n| [RandomPoissonV2](#classtensorflow_1_1ops_1_1_random_poisson_v2_1affe491853f03c22d0d69fe155380690d)`(const ::`[tensorflow::Scope](/versions/r1.15/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` shape, ::`[tensorflow::Input](/versions/r1.15/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` rate, const `[RandomPoissonV2::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/random-poisson-v2/attrs#structtensorflow_1_1ops_1_1_random_poisson_v2_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|-----------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_random_poisson_v2_1a8a6d22a45ef402122008fd37ae60584a) | [Operation](/versions/r1.15/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [output](#classtensorflow_1_1ops_1_1_random_poisson_v2_1aacc4e0f70e7215919fd2ed050cc778ec) | `::`[tensorflow::Output](/versions/r1.15/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|-----------------------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_random_poisson_v2_1a2c4c1c5791ce65536c0711c345c5104f)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_random_poisson_v2_1a680111c81759da8f485b7c57830a97c8)`() const ` | ` ` ` ` |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_random_poisson_v2_1ab0e8e0cee5576ad5d628eb26db934fc6)`() const ` | ` ` ` ` |\n\n| ### Public static functions ||\n|---------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------|\n| [Dtype](#classtensorflow_1_1ops_1_1_random_poisson_v2_1a16ea2843b7cb14092e392a1634d5f9d3)`(DataType x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/random-poisson-v2/attrs#structtensorflow_1_1ops_1_1_random_poisson_v2_1_1_attrs) |\n| [Seed](#classtensorflow_1_1ops_1_1_random_poisson_v2_1a4923276f993adff27a39549f725e140c)`(int64 x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/random-poisson-v2/attrs#structtensorflow_1_1ops_1_1_random_poisson_v2_1_1_attrs) |\n| [Seed2](#classtensorflow_1_1ops_1_1_random_poisson_v2_1a3db3d3b1dcf6fd61014a43d46719c992)`(int64 x)` | [Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/random-poisson-v2/attrs#structtensorflow_1_1ops_1_1_random_poisson_v2_1_1_attrs) |\n\n| ### Structs ||\n|----------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::RandomPoissonV2::Attrs](/versions/r1.15/api_docs/cc/struct/tensorflow/ops/random-poisson-v2/attrs) | Optional attribute setters for [RandomPoissonV2](/versions/r1.15/api_docs/cc/class/tensorflow/ops/random-poisson-v2#classtensorflow_1_1ops_1_1_random_poisson_v2). |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### output\n\n```text\n::tensorflow::Output output\n``` \n\nPublic functions\n----------------\n\n### RandomPoissonV2\n\n```gdscript\n RandomPoissonV2(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input shape,\n ::tensorflow::Input rate\n)\n``` \n\n### RandomPoissonV2\n\n```gdscript\n RandomPoissonV2(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input shape,\n ::tensorflow::Input rate,\n const RandomPoissonV2::Attrs & attrs\n)\n``` \n\n### node\n\n```gdscript\n::tensorflow::Node * node() const \n``` \n\n### operator::tensorflow::Input\n\n```gdscript\n operator::tensorflow::Input() const \n``` \n\n### operator::tensorflow::Output\n\n```gdscript\n operator::tensorflow::Output() const \n``` \n\nPublic static functions\n-----------------------\n\n### Dtype\n\n```carbon\nAttrs Dtype(\n DataType x\n)\n``` \n\n### Seed\n\n```text\nAttrs Seed(\n int64 x\n)\n``` \n\n### Seed2\n\n```text\nAttrs Seed2(\n int64 x\n)\n```"]]