code: def Selu(
      alpha=1.6732632423543772848170429916717,
      lmbda=1.0507009873554804934193349852946,
  ):
      r"""Returns an `Elu`-like layer with an additional scaling/slope parameter.
  
    .. math::
        f(x) = \left\{ \begin{array}{cl}
            \lambda \cdot \alpha \cdot (e^x - 1) & \text{if}\ x \leq 0, \\
            \lambda \cdot x                      & \text{otherwise}.
        \end{array} \right.
  
    Args:
      alpha: Coefficient multiplying the exponential, for negative inputs.
      lmbda: Coefficient scaling the whole function.
    """
      return Fn(
          "Selu",
          lambda x: lmbda * jnp.where(x > 0, x, alpha * jnp.expm1(x)),
      )
  
imports: from trax import fastmath
  from trax.fastmath import numpy
  from trax.layers import base
  from trax.layers.assert_shape import assert_shape
  from trax.layers.base import Fn
label_desc: Use image node_id 5 for calling a global function with example usage: Selu(alpha, lmbda) and returns: Fn