tf.keras.activations.softmax | TensorFlow v2.16.1 (original) (raw)
tf.keras.activations.softmax
Stay organized with collections Save and categorize content based on your preferences.
Softmax converts a vector of values to a probability distribution.
tf.keras.activations.softmax(
x, axis=-1
)
The elements of the output vector are in range [0, 1] and sum to 1.
Each input vector is handled independently. The axis argument sets which axis of the input the function is applied along.
Softmax 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 each vector x is computed asexp(x) / sum(exp(x)).
The input values in are the log-odds of the resulting probability.
| Args | |
|---|---|
| x | Input tensor. |
| axis | Integer, axis along which the softmax is applied. |
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2024-06-07 UTC.