tf.random.stateless_multinomial

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

This is a stateless version of tf.random.categorical: if run twice with the same seeds, 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] integer Tensor of seeds to the random number generator.
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].

© 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/r1.15/api_docs/python/tf/random/stateless_multinomial