Draws samples from a multinomial distribution. (deprecated)
tf.compat.v1.multinomial(
    logits, num_samples, seed=None, name=None, output_dtype=None
)
   # 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. | 
| seed | A Python integer. Used to create a random seed for the distribution. See tf.random.set_seedfor behavior. | 
| name | Optional name for the operation. | 
| output_dtype | The integer type of the output: int32orint64. Defaults toint64. | 
| Returns | |
|---|---|
| The drawn samples of shape [batch_size, num_samples]. | 
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Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
    https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/compat/v1/multinomial