tf.raw_ops.RandomPoissonV2
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Outputs random values from the Poisson distribution(s) described by rate.
View aliases
Compat aliases for migration
See
Migration guide for
more details.
tf.compat.v1.raw_ops.RandomPoissonV2
tf.raw_ops.RandomPoissonV2(
shape,
rate,
seed=0,
seed2=0,
dtype=tf.dtypes.int64
,
name=None
)
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
Args |
shape
|
A Tensor . Must be one of the following types: int32 , int64 .
1-D integer tensor. Shape of independent samples to draw from each
distribution described by the shape parameters given in rate.
|
rate
|
A Tensor . Must be one of the following types: half , float32 , float64 , int32 , int64 .
A tensor in which each scalar is a "rate" parameter describing the
associated poisson distribution.
|
seed
|
An optional int . Defaults to 0 .
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
|
An optional int . Defaults to 0 .
A second seed to avoid seed collision.
|
dtype
|
An optional tf.DType from: tf.half, tf.float32, tf.float64, tf.int32, tf.int64 . Defaults to tf.int64 .
|
name
|
A name for the operation (optional).
|
Returns |
A Tensor of type dtype .
|
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Last updated 2024-04-26 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.raw_ops.RandomPoissonV2\n\n\u003cbr /\u003e\n\nOutputs random values from the Poisson distribution(s) described by rate.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.raw_ops.RandomPoissonV2`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/RandomPoissonV2)\n\n\u003cbr /\u003e\n\n tf.raw_ops.RandomPoissonV2(\n shape,\n rate,\n seed=0,\n seed2=0,\n dtype=../../tf/dtypes#int64,\n name=None\n )\n\nThis op uses two algorithms, depending on rate. If rate \\\u003e= 10, then\nthe algorithm by Hormann is used to acquire samples via\ntransformation-rejection.\nSee \u003chttp://www.sciencedirect.com/science/article/pii/0167668793909974\u003e\n\nOtherwise, Knuth's algorithm is used to acquire samples via multiplying uniform\nrandom variables.\nSee Donald E. Knuth (1969). Seminumerical Algorithms. The Art of Computer\nProgramming, Volume 2. Addison Wesley\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `shape` | A `Tensor`. Must be one of the following types: `int32`, `int64`. 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`. Must be one of the following types: `half`, `float32`, `float64`, `int32`, `int64`. A tensor in which each scalar is a \"rate\" parameter describing the associated poisson distribution. |\n| `seed` | An optional `int`. Defaults to `0`. 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` | An optional `int`. Defaults to `0`. A second seed to avoid seed collision. |\n| `dtype` | An optional [`tf.DType`](../../tf/dtypes/DType) from: `tf.half, tf.float32, tf.float64, tf.int32, tf.int64`. Defaults to [`tf.int64`](../../tf#int64). |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor` of type `dtype`. ||\n\n\u003cbr /\u003e"]]