jax.nn.relu#
- jax.nn.relu(x) = <jax._src.custom_derivatives.custom_jvp object>[source]#
Rectified linear unit activation function.
Computes the element-wise function:
\[\mathrm{relu}(x) = \max(x, 0)\]except under differentiation, we take:
\[\nabla \mathrm{relu}(0) = 0\]For more information see Numerical influence of ReLU’(0) on backpropagation.
- Parameters:
x (
Union
[Array
,ndarray
,bool_
,number
,bool
,int
,float
,complex
]) – input array- Return type:
- Returns:
An array.
Example
>>> jax.nn.relu(jax.numpy.array([-2., -1., -0.5, 0, 0.5, 1., 2.])) Array([0. , 0. , 0. , 0. , 0.5, 1. , 2. ], dtype=float32)
See also