tf.keras.activations.softmax

View source on GitHub

The softmax activation function transforms the outputs so that all values are in

range (0, 1) and sum to 1. It is often used as the activation for the last layer of a classification network because the result could be interpreted as a probability distribution. The softmax of x is calculated by exp(x)/tf.reduce_sum(exp(x)).

Arguments
x Input tensor.
axis Integer, axis along which the softmax normalization is applied.
Returns
Tensor, output of softmax transformation (all values are non-negative and sum to 1).
Raises
ValueError In case dim(x) == 1.

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/keras/activations/softmax