docstr: `ivy.Container` instance method variant of `ivy.result_type`. This
  method simply wraps the function, and so the docstring for
  `ivy.result_type` also applies to this method with minimal changes.
  
  Parameters
  ----------
  self
      input container from which to cast.
  arrays_and_dtypes
      an arbitrary number of input arrays and/or dtypes.
  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
  -------
  ret
      the dtype resulting from an operation involving the input arrays and dtypes.
  
  Examples
  --------
  >>> x = ivy.Container(a = ivy.array([3, 3, 3]))
  >>> print(x.a.dtype)
  int32
  
  >>> y = ivy.Container(b = ivy.float64)
  >>> print(x.result_type(y))
  {
      a: {
          b: float64
      }
  }
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code: def result_type(
      self: ivy.Container,
      *arrays_and_dtypes: 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.result_type`. This
      method simply wraps the function, and so the docstring for
      `ivy.result_type` also applies to this method with minimal changes.
  
      Parameters
      ----------
      self
          input container from which to cast.
      arrays_and_dtypes
          an arbitrary number of input arrays and/or dtypes.
      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
      -------
      ret
          the dtype resulting from an operation involving the input arrays and dtypes.
  
      Examples
      --------
      >>> x = ivy.Container(a = ivy.array([3, 3, 3]))
      >>> print(x.a.dtype)
      int32
  
      >>> y = ivy.Container(b = ivy.float64)
      >>> print(x.result_type(y))
      {
          a: {
              b: float64
          }
      }
      """
      return self._static_result_type(
          self,
          *arrays_and_dtypes,
          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 30 for calling the _ContainerWithDataTypes obj's underlying member method code with example usage: obj.result_type() and returns: self