tf.compat.v1.math.softmax

Computes softmax activations. (deprecated arguments)

tf.compat.v1.math.softmax(
    logits, axis=None, name=None, dim=None
)

This function performs the equivalent of

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

See: https://en.wikipedia.org/wiki/Softmax_function

Example usage:

tf.nn.softmax([-1, 0., 1.])
<tf.Tensor: shape=(3,), dtype=float32,
numpy=array([0.09003057, 0.24472848, 0.66524094], dtype=float32)>

logits A non-empty Tensor, or an object whose type has a registered Tensor conversion function. Must be one of the following types: half,float32, float64. See also convert_to_tensor
axis The dimension softmax would be performed on. The default is -1 which indicates the last dimension.
name A name for the operation (optional).
dim Deprecated alias for axis.

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

InvalidArgumentError if logits is empty or axis is beyond the last dimension of logits.
TypeError If no conversion function is registered for logits to Tensor.
RuntimeError If a registered conversion function returns an invalid value.