tf.nn.log_softmax

Computes log softmax activations.

Main aliases

tf.math.log_softmax

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

Used in the tutorials
Training with Orbit

For each batch i and class j we have

logsoftmax = logits - log(reduce_sum(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 as `logits`. Same shape as `logits`.

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

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Last updated 2024-04-26 UTC.

Args