|  View source on GitHub | 
Soft shrink function.
tfa.activations.softshrink(
    x: tfa.types.TensorLike,
    lower: tfa.types.Number = -0.5,
    upper: tfa.types.Number = 0.5
) -> tf.Tensor
Computes soft shrink function:
\[ \mathrm{softshrink}(x) = \begin{cases} x - \mathrm{lower} & \text{if } x < \mathrm{lower} \\ x - \mathrm{upper} & \text{if } x > \mathrm{upper} \\ 0 & \text{otherwise} \end{cases}. \]
Usage:
x = tf.constant([-1.0, 0.0, 1.0])tfa.activations.softshrink(x)<tf.Tensor: shape=(3,), dtype=float32, numpy=array([-0.5, 0. , 0.5], dtype=float32)>
| Args | |
|---|---|
| x | A Tensor. Must be one of the following types:bfloat16,float16,float32,float64. | 
| lower | float, lower bound for setting values to zeros. | 
| upper | float, upper bound for setting values to zeros. | 
| Returns | |
|---|---|
| A Tensor. Has the same type asx. |