tf.random

TensorFlow 1 version

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Draws samples from a categorical distribution.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.random.categorical

tf.random.categorical(
    logits, num_samples, dtype=None, seed=None, name=None
)

Used in the notebooks

Used in the tutorials
Text generation with an RNN Playing CartPole with the Actor-Critic Method Image captioning with visual attention Federated Learning for Text Generation Wiki40B Language Models

Example:

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

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.
`dtype`	integer type to use for the output. Defaults to int64.
`seed`	A Python integer. Used to create a random seed for the distribution. See `tf.random.set_seed` for behavior.
`name`	Optional name for the operation.

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

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tf.random / Overview

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Used in the notebooks

Example:

Args

Returns