tf.math.softplus | TensorFlow v2.16.1 (original) (raw)
tf.math.softplus
Computes elementwise softplus: softplus(x) = log(exp(x) + 1).
View aliases
Main aliases
tf.math.softplus(
features, name=None
)
Used in the notebooks
| Used in the guide | Used in the tutorials |
|---|---|
| Introduction to gradients and automatic differentiation | TFP Probabilistic Layers: Regression Gaussian Process Latent Variable Models Bayesian Modeling with Joint Distribution |
softplus is a smooth approximation of relu. Like relu, softplus always takes on positive values.
Example:
import tensorflow as tf
tf.math.softplus(tf.range(0, 2, dtype=tf.float32)).numpy()
array([0.6931472, 1.3132616], dtype=float32)
| Args | |
|---|---|
| features | Tensor |
| name | Optional: name to associate with this operation. |
| Returns |
|---|
| Tensor |
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Last updated 2024-04-26 UTC.