tf.random.categorical
Draws samples from a categorical distribution.
tf.random.categorical(
logits, num_samples, dtype=None, seed=None, name=None
)
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]. |