Draws samples from a categorical distribution.Source:
This function takes as input
logits, a 2-D input tensor with shape
(batch_size, num_classes). Each row of the input represents a categorical
distribution, with each column index containing the log-probability for a
The function will output a 2-D tensor with shape (batch_size, num_samples),
where each row contains samples from the corresponding row in
Each column index contains an independent samples drawn from the input
2-D Tensor with shape (batch_size, num_classes). Each row should define a categorical distibution with the unnormalized log-probabilities for all classes.
Int, the number of independent samples to draw for each row of the input. This will be the second dimension of the output tensor's shape.
Optional dtype of the output tensor.
An R integer or instance of
random_seed_generator(). Used to make the behavior of the initializer deterministic. Note that an initializer seeded with an integer or
NULL(unseeded) will produce the same random values across multiple calls. To get different random values across multiple calls, use as seed an instance of