docstr: Determine whether arrays in the container contain any nans, as well as infs or
  -infs if specified.
  
  Parameters
  ----------
  x
      The container to check for nans.
  include_infs
      Whether to include infs and -infs in the check. Default is True.
  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``.
  
  Returns
  -------
      Whether the container has any nans, applied either leafwise or across the
      entire container.
  
  Examples
  --------
  >>> x = ivy.Container(a=ivy.array([1, 2]), b=ivy.array([float('nan'), 2]))
  >>> y = ivy.Container.static_has_nans(x)
  >>> print(y)
  {
      a: false,
      b: true
  }
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code: def _static_has_nans(
      x: ivy.Container,
      /,
      *,
      include_infs: Union[bool, ivy.Container] = True,
      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,
  ) -> ivy.Container:
      """
      Determine whether arrays in the container contain any nans, as well as infs or
      -infs if specified.
  
      Parameters
      ----------
      x
          The container to check for nans.
      include_infs
          Whether to include infs and -infs in the check. Default is True.
      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``.
  
      Returns
      -------
          Whether the container has any nans, applied either leafwise or across the
          entire container.
  
      Examples
      --------
      >>> x = ivy.Container(a=ivy.array([1, 2]), b=ivy.array([float('nan'), 2]))
      >>> y = ivy.Container.static_has_nans(x)
      >>> print(y)
      {
          a: false,
          b: true
      }
      """
      return ContainerBase.cont_multi_map_in_function(
          "has_nans",
          x,
          include_infs=include_infs,
          key_chains=key_chains,
          to_apply=to_apply,
          prune_unapplied=prune_unapplied,
          map_sequences=map_sequences,
      )
  
imports: from numbers import Number
  from typing import Any, Union, List, Dict, Iterable, Optional, Callable
  from ivy.data_classes.container.base import ContainerBase
  import ivy
label_desc: Use image node_id 23 for calling the _ContainerWithGeneral obj's underlying member method code with example usage: obj._static_has_nans() and returns: ContainerBase