Help protect the Great Barrier Reef with TensorFlow on Kaggle Join Challenge


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Draws shape samples from each of the given Poisson distribution(s).

lam is the rate parameter describing the distribution(s).


samples = tf.random.poisson([10], [0.5, 1.5])
# samples has shape [10, 2], where each slice [:, 0] and [:, 1] represents
# the samples drawn from each distribution

samples = tf.random.poisson([7, 5], [12.2, 3.3])
# samples has shape [7, 5, 2], where each slice [:, :, 0] and [:, :, 1]
# represents the 7x5 samples drawn from each of the two distributions

shape A 1-D integer Tensor or Python array. The shape of the output samples to be drawn per "rate"-parameterized distribution.
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.
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.compat.v1.set_random_seed for behavior.
name Optional name for the operation.

samples a Tensor of shape tf.concat([shape, tf.shape(lam)], axis=0) with values of type dtype.