tf.multinomial
tf.multinomial
tf.multinomial
multinomial( logits, num_samples, seed=None, name=None )
Defined in tensorflow/python/ops/random_ops.py
.
See the guide: Constants, Sequences, and Random Values > Random Tensors
Draws samples from a multinomial distribution.
Example:
# samples has shape [1, 5], where each value is either 0 or 1 with equal # probability. samples = tf.multinomial(tf.log([[10., 10.]]), 5)
Args:
-
logits
: 2-D Tensor with shape[batch_size, num_classes]
. Each slice[i, :]
represents the log-odds for all classes. -
num_samples
: 0-D. Number of independent samples to draw for each row slice. -
seed
: A Python integer. Used to create a random seed for the distribution. Seetf.set_random_seed
for behavior. -
name
: Optional name for the operation.
Returns:
The drawn samples of shape [batch_size, num_samples]
.
© 2017 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/api_docs/python/tf/multinomial