code: def selu(x: ArrayLike) -> Array:
      r"""Scaled exponential linear unit activation.
  
    Computes the element-wise function:
  
    .. math::
      \mathrm{selu}(x) = \lambda \begin{cases}
        x, & x > 0\\
        \alpha e^x - \alpha, & x \le 0
      \end{cases}
  
    where :math:`\lambda = 1.0507009873554804934193349852946` and
    :math:`\alpha = 1.6732632423543772848170429916717`.
  
    For more information, see
    `Self-Normalizing Neural Networks
    <https://papers.nips.cc/paper/6698-self-normalizing-neural-networks.pdf>`_.
  
    Args:
      x : input array
  
    Returns:
      An array.
  
    See also:
      :func:`elu`
    """
      alpha = 1.6732632423543772848170429916717
      scale = 1.0507009873554804934193349852946
      return scale * elu(x, alpha)
  
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 12 for calling a global function with example usage: selu(x) and returns: unknown