(alpha=1.6732632423543772848170429916717,
         lmbda=1.0507009873554804934193349852946)
return Fn('Selu', lambda x: lmbda * jnp.where(x > 0, x, alpha * jnp.expm1(x)))
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.
r"""Returns an `Elu`-like layer with an additional scaling/slope parameter.
r Returns an Elu - like layer with an additional scaling / slope parameter .
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)))
def Selu ( alpha = 1.6732632423543772848170429916717 , lmbda = 1.0507009873554804934193349852946 ) : return Fn ( 'Selu' , lambda x : lmbda * jnp . where ( x > 0 , x , alpha * jnp . expm1 ( x ) ) )