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 .
|