tf.nn.softmax

Computes softmax activations.

Main aliases

tf.math.softmax

tf.nn.softmax(
    logits, axis=None, name=None
)

This function performs the equivalent of

softmax = tf.exp(logits) / tf.reduce_sum(tf.exp(logits), axis)

Args
`logits`	A non-empty `Tensor`. Must be one of the following types: `half`, `float32`, `float64`.
`axis`	The dimension softmax would be performed on. The default is -1 which indicates the last dimension.
`name`	A name for the operation (optional).

Returns
A `Tensor`. Has the same type and shape as `logits`.

Raises
`InvalidArgumentError`	if `logits` is empty or `axis` is beyond the last dimension of `logits`.

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Last updated 2021-02-18 UTC.

Args