tf.nn.softmax

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Computes softmax activations.

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.