TensorFlow 2 version
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The softmax activation function transforms the outputs so that all values are in
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Compat aliases for migration
See Migration guide for more details.
tf.compat.v1.keras.activations.softmax, `tf.compat.v2.keras.activations.softmax`
tf.keras.activations.softmax(
x, axis=-1
)
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.
|