docstr: ivy.Container static method variant of ivy.logsigmoid. This method
  simply wraps the function, and so the docstring for ivy.logsigmoid also
  applies to this method with minimal changes.
  
  Parameters
  ----------
  input
      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``.
  complex_mode
      optional specifier for how to handle complex data types. See
      ``ivy.func_wrapper.handle_complex_input`` for more detail.
  
  Returns
  -------
      Container with Log-sigmoid applied to the leaves.
  
  Examples
  --------
  >>> a = ivy.array([1, 0, 0.9])
  >>> b = ivy.array([0.1, 2, -0.9])
  >>> x = ivy.Container(a=a, b=b)
  >>> z = ivy.Container.static_logsigmoid(x)
  >>> print(z)
  {
      a: ivy.array([-0.31326169, -0.69314718, -0.34115386]),
      b: ivy.array([-0.64439666, -0.126928, -1.24115384])
  }
  
  >>> a = ivy.array([0.3, 2.5, 4.9])
  >>> b = ivy.array([0.1, 1.2, -9.])
  >>> x = ivy.Container(a=a, b=b)
  >>> z = ivy.Container.static_logsigmoid(x)
  >>> print(z)
  {
      a: ivy.array([-0.55435526, -0.07888974, -0.00741899]),
      b: ivy.array([-0.64439666, -0.26328245, -9.00012302])
  }
docstr_tok: ["ivy.Container","static","method","variant","of","ivy.logsigmoid",".","This","method","simply","wraps","the","function",",","and","so","the","docstring","for","ivy.logsigmoid","also","applies","to","this","method","with","minimal","changes",".","Parameters","--","--","--","--","--","input","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","``",".","complex_mode","optional","specifier","for","how","to","handle","complex","data","types",".","See","``","ivy.func_wrapper.handle_complex_input","``","for","more","detail",".","Returns","--","--","--","-","Container","with","Log-sigmoid","applied","to","the","leaves",".","Examples","--","--","--","--",">",">",">","a","=","ivy.array","(","[","1",",","0",",","0.9","]",")",">",">",">","b","=","ivy.array","(","[","0.1",",","2",",","-0.9","]",")",">",">",">","x","=","ivy.Container","(","a=a",",","b=b",")",">",">",">","z","=","ivy.Container.static_logsigmoid","(","x",")",">",">",">","print","(","z",")","{","a",":","ivy.array","(","[","-0.31326169",",","-0.69314718",",","-0.34115386","]",")",",","b",":","ivy.array","(","[","-0.64439666",",","-0.126928",",","-1.24115384","]",")","}",">",">",">","a","=","ivy.array","(","[","0.3",",","2.5",",","4.9","]",")",">",">",">","b","=","ivy.array","(","[","0.1",",","1.2",",","-9",".","]",")",">",">",">","x","=","ivy.Container","(","a=a",",","b=b",")",">",">",">","z","=","ivy.Container.static_logsigmoid","(","x",")",">",">",">","print","(","z",")","{","a",":","ivy.array","(","[","-0.55435526",",","-0.07888974",",","-0.00741899","]",")",",","b",":","ivy.array","(","[","-0.64439666",",","-0.26328245",",","-9.00012302","]",")","}"]
code: def static_logsigmoid(
      input: 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,
      complex_mode: Literal["split", "magnitude", "jax"] = "jax",
  ) -> ivy.Container:
      """ivy.Container static method variant of ivy.logsigmoid. This method
      simply wraps the function, and so the docstring for ivy.logsigmoid also
      applies to this method with minimal changes.
  
      Parameters
      ----------
      input
          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``.
      complex_mode
          optional specifier for how to handle complex data types. See
          ``ivy.func_wrapper.handle_complex_input`` for more detail.
  
      Returns
      -------
          Container with Log-sigmoid applied to the leaves.
  
      Examples
      --------
      >>> a = ivy.array([1, 0, 0.9])
      >>> b = ivy.array([0.1, 2, -0.9])
      >>> x = ivy.Container(a=a, b=b)
      >>> z = ivy.Container.static_logsigmoid(x)
      >>> print(z)
      {
          a: ivy.array([-0.31326169, -0.69314718, -0.34115386]),
          b: ivy.array([-0.64439666, -0.126928, -1.24115384])
      }
  
      >>> a = ivy.array([0.3, 2.5, 4.9])
      >>> b = ivy.array([0.1, 1.2, -9.])
      >>> x = ivy.Container(a=a, b=b)
      >>> z = ivy.Container.static_logsigmoid(x)
      >>> print(z)
      {
          a: ivy.array([-0.55435526, -0.07888974, -0.00741899]),
          b: ivy.array([-0.64439666, -0.26328245, -9.00012302])
      }
      """
      return ContainerBase.cont_multi_map_in_function(
          "logsigmoid",
          input,
          key_chains=key_chains,
          to_apply=to_apply,
          prune_unapplied=prune_unapplied,
          map_sequences=map_sequences,
          complex_mode=complex_mode,
      )
  
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 9 for calling the _ContainerWithActivationExperimental obj's underlying member method code with example usage: obj.static_logsigmoid() and returns: ContainerBase