tf.random_poisson

tf.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 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.set_random_seed for behavior.
• name: Optional name for the operation.

Returns:

• samples: a Tensor of shape tf.concat(shape, tf.shape(lam)) with values of type dtype.