tf.compat.v1.random.stateless_multinomial

Draws deterministic pseudorandom samples from a multinomial distribution. (deprecated)

tf.compat.v1.random.stateless_multinomial(
    logits, num_samples, seed, output_dtype=tf.dtypes.int64, name=None
)

This is a stateless version of tf.random.categorical: if run twice with the same seeds and shapes, it will produce the same pseudorandom numbers. The output is consistent across multiple runs on the same hardware (and between CPU and GPU), but may change between versions of TensorFlow or on non-CPU/GPU hardware.

Example:

# samples has shape [1, 5], where each value is either 0 or 1 with equal
# probability.
samples = tf.random.stateless_categorical(
    tf.math.log([[0.5, 0.5]]), 5, seed=[7, 17])

Args
logits	2-D Tensor with shape [batch_size, num_classes]. Each slice [i, :] represents the unnormalized log-probabilities for all classes.
num_samples	0-D. Number of independent samples to draw for each row slice.
seed	A shape [2] Tensor, the seed to the random number generator. Must have dtype int32 or int64. (When using XLA, only int32 is allowed.)
output_dtype	integer type to use for the output. Defaults to int64.
name	Optional name for the operation.

Returns
The drawn samples of shape [batch_size, num_samples].