code: def relu(x: ArrayLike) -> Array:
      r"""Rectified linear unit activation function.
  
      Computes the element-wise function:
  
      .. math::
        \mathrm{relu}(x) = \max(x, 0)
  
      except under differentiation, we take:
  
      .. math::
        \nabla \mathrm{relu}(0) = 0
  
      For more information see
      `Numerical influence of ReLU’(0) on backpropagation
      <https://openreview.net/forum?id=urrcVI-_jRm>`_.
  
      Args:
        x : input array
  
      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:
        :func:`relu6`
  
      """
      return jnp.maximum(x, 0)
  
imports: from __future__ import annotations
  from functools import partial
  import operator
  import numpy
  from typing import Any
  import jax
  import jax.numpy
  from jax import custom_jvp
  from jax import lax
  from jax._src import config
  from jax._src import core
  from jax._src import dtypes
  from jax._src import util
  from jax._src.core import AxisName
  from jax._src.numpy import util
  from jax._src.typing import Array, ArrayLike
  from jax._src.ops.special import logsumexp
label_desc: Use image node_id 1 for calling a global function with example usage: relu(x) and returns: jnp