docstr: `ivy.Container` instance method variant of `ivy.is_complex_dtype`.
  This method simply wraps the function, and so the docstring for
  `ivy.is_complex_dtype` also applies to this method with minimal
  changes.
  
  Parameters
  ----------
  self : ivy.Container
      The `ivy.Container` instance to call `ivy.is_complex_dtype` on.
  
  key_chains : Union[List[str], Dict[str, str]]
      The key-chains to apply or not apply the method to.
      Default is ``None``.
  
  to_apply : bool
      Boolean indicating whether to apply the
      method to the key-chains. Default is ``False``.
  
  prune_unapplied : bool
      Boolean indicating whether to prune the
      key-chains that were not applied. Default is ``False``.
  
  map_sequences : bool
      Boolean indicating whether to map method
      to sequences (list, tuple). Default is ``False``.
  
  Returns
  -------
  ret : bool
      Boolean of whether the input is of a complex dtype.
  
  Examples
  --------
  >>> x = ivy.is_complex_dtype(ivy.complex64)
  >>> print(x)
  True
  
  >>> x = ivy.is_complex_dtype(ivy.int64)
  >>> print(x)
  False
  
  >>> x = ivy.is_complex_dtype(ivy.float32)
  >>> print(x)
  False
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code: def is_complex_dtype(
      self: 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,
  ) -> ivy.Container:
      """`ivy.Container` instance method variant of `ivy.is_complex_dtype`.
      This method simply wraps the function, and so the docstring for
      `ivy.is_complex_dtype` also applies to this method with minimal
      changes.
  
      Parameters
      ----------
      self : ivy.Container
          The `ivy.Container` instance to call `ivy.is_complex_dtype` on.
  
      key_chains : Union[List[str], Dict[str, str]]
          The key-chains to apply or not apply the method to.
          Default is ``None``.
  
      to_apply : bool
          Boolean indicating whether to apply the
          method to the key-chains. Default is ``False``.
  
      prune_unapplied : bool
          Boolean indicating whether to prune the
          key-chains that were not applied. Default is ``False``.
  
      map_sequences : bool
          Boolean indicating whether to map method
          to sequences (list, tuple). Default is ``False``.
  
      Returns
      -------
      ret : bool
          Boolean of whether the input is of a complex dtype.
  
      Examples
      --------
      >>> x = ivy.is_complex_dtype(ivy.complex64)
      >>> print(x)
      True
  
      >>> x = ivy.is_complex_dtype(ivy.int64)
      >>> print(x)
      False
  
      >>> x = ivy.is_complex_dtype(ivy.float32)
      >>> print(x)
      False
      """
      return self._static_is_complex_dtype(
          self,
          key_chains=key_chains,
          to_apply=to_apply,
          prune_unapplied=prune_unapplied,
          map_sequences=map_sequences,
      )
  
imports: from typing import Optional, Union, List, Dict, Tuple, Callable
  import ivy
  from ivy.data_classes.container.base import ContainerBase
label_desc: Use image node_id 28 for calling the _ContainerWithDataTypes obj's underlying member method code with example usage: obj.is_complex_dtype(key_chains, to_apply, prune_unapplied, map_sequences) and returns: self