tf.compat.v1.random_poisson
Draws shape samples from each of the given Poisson distribution(s).
tf.compat.v1.random_poisson(
lam, shape, dtype=tf.dtypes.float32, seed=None, name=None
)
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 type dtype. 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 of the output: float16, float32, float64, int32 or int64. |
seed |
A Python integer. Used to create a random seed for the distributions. See tf.random.set_seed for behavior. |
name |
Optional name for the operation. |
| Returns | |
|---|---|
samples |
a Tensor of shape tf.concat([shape, tf.shape(lam)], axis=0) with values of type dtype. |
© 2020 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/versions/r2.3/api_docs/python/tf/compat/v1/random_poisson