docstr: ivy.Container static method variant of ivy.selu. This method simply
  wraps the function, and so the docstring for ivy.selu also applies to
  this method with minimal changes.
  
  Parameters
  ----------
  x
      input container.
  key_chains
      The key-chains to apply or not apply the method to. Default is ``None``.
  to_apply
      If True, the method will be applied to key_chains, otherwise key_chains
      will be skipped. Default is ``True``.
  prune_unapplied
      Whether to prune key_chains for which the function was not applied.
      Default is ``False``.
  map_sequences
      Whether to also map method to sequences (lists, tuples).
      Default is ``False``.
  out
      optional output container, for writing the result to. It must have a shape
      that the inputs broadcast to.
  
  Returns
  -------
  ret
      a container with the scaled exponential linear unit activation function
      applied element-wise.
  
  Examples
  --------
  >>> x = ivy.Container(a=ivy.array([1.0, -1.2]), b=ivy.array([0.4, -0.2]))
  >>> y = ivy.Container.static_selu(x)
  >>> print(y)
  {
      a: ivy.array([1.05070102, -1.22856998]),
      b: ivy.array([0.42028043, -0.31868932])
  }
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code: def static_selu(
      x: Union[ivy.Array, ivy.NativeArray, ivy.Container],
      /,
      *,
      key_chains: Optional[
          Union[List[str], Dict[str, str], ivy.Container]
      ] = None,
      to_apply: Union[bool, ivy.Container] = True,
      prune_unapplied: Union[bool, ivy.Container] = False,
      map_sequences: Union[bool, ivy.Container] = False,
      out: Optional[ivy.Container] = None,
  ) -> ivy.Container:
      """ivy.Container static method variant of ivy.selu. This method simply
      wraps the function, and so the docstring for ivy.selu also applies to
      this method with minimal changes.
  
      Parameters
      ----------
      x
          input container.
      key_chains
          The key-chains to apply or not apply the method to. Default is ``None``.
      to_apply
          If True, the method will be applied to key_chains, otherwise key_chains
          will be skipped. Default is ``True``.
      prune_unapplied
          Whether to prune key_chains for which the function was not applied.
          Default is ``False``.
      map_sequences
          Whether to also map method to sequences (lists, tuples).
          Default is ``False``.
      out
          optional output container, for writing the result to. It must have a shape
          that the inputs broadcast to.
  
      Returns
      -------
      ret
          a container with the scaled exponential linear unit activation function
          applied element-wise.
  
      Examples
      --------
      >>> x = ivy.Container(a=ivy.array([1.0, -1.2]), b=ivy.array([0.4, -0.2]))
      >>> y = ivy.Container.static_selu(x)
      >>> print(y)
      {
          a: ivy.array([1.05070102, -1.22856998]),
          b: ivy.array([0.42028043, -0.31868932])
      }
      """
      return ContainerBase.cont_multi_map_in_function(
          "selu",
          x,
          key_chains=key_chains,
          to_apply=to_apply,
          prune_unapplied=prune_unapplied,
          map_sequences=map_sequences,
          out=out,
      )
  
imports: from typing import Union, Optional, List, Dict, Literal
  import ivy
  from ivy.data_classes.container.base import ContainerBase
label_desc: Use image node_id 11 for calling the _ContainerWithActivationExperimental obj's underlying member method code with example usage: obj.static_selu() and returns: ContainerBase