tf.random_poisson
tf.random_poisson
tf.random_poisson
random_poisson( lam, shape, dtype=tf.float32, seed=None, name=None )
Defined in tensorflow/python/ops/random_ops.py
.
Draws shape
samples from each of the given Poisson distribution(s).
lam
is the rate parameter describing the distribution(s).
Example:
samples = tf.random_poisson([0.5, 1.5], [10]) # samples has shape [10, 2], where each slice [:, 0] and [:, 1] represents # the samples drawn from each distribution
samples = tf.random_poisson([12.2, 3.3], [7, 5]) # samples has shape [7, 5, 2], where each slice [:, :, 0] and [:, :, 1] # represents the 7x5 samples drawn from each of the two distributions
Args:
-
lam
: A Tensor or Python value or N-D array of typedtype
.lam
provides the rate parameter(s) describing the poisson distribution(s) to sample. -
shape
: A 1-D integer Tensor or Python array. The shape of the output samples to be drawn per "rate"-parameterized distribution. -
dtype
: The type oflam
and the output:float16
,float32
, orfloat64
. -
seed
: A Python integer. Used to create a random seed for the distributions. Seetf.set_random_seed
for behavior. -
name
: Optional name for the operation.
Returns:
-
samples
: aTensor
of shapetf.concat(shape, tf.shape(lam))
with values of typedtype
.
© 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/python/tf/random_poisson