docstr: ivy.Container instance method variant of ivy.split. This method
  simply wraps the function, and so the docstring for ivy.split also
  applies to this method with minimal changes.
  
  Parameters
  ----------
  self
      array to be divided into sub-arrays.
  copy
      boolean indicating whether or not to copy the input array.
      If True, the function must always copy.
      If False, the function must never copy and must
      raise a ValueError in case a copy would be necessary.
      If None, the function must reuse existing memory buffer if possible
      and copy otherwise. Default: ``None``.
  num_or_size_splits
      Number of equal arrays to divide the array into along the given axis if an
      integer. The size of each split element if a sequence of integers
      or 1-D array. Default is to divide into as many 1-dimensional arrays
      as the axis dimension.
  axis
      The axis along which to split, default is ``0``.
  with_remainder
      If the tensor does not split evenly, then store the last remainder entry.
      Default is ``False``.
  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
  -------
      list of containers of sub-arrays.
  
  Examples
  --------
  >>> x = ivy.Container(a=ivy.array([2, 1, 5, 9]), b=ivy.array([3, 7, 2, 11]))
  >>> y = x.split(num_or_size_splits=2)
  >>> print(y)
  [{
      a: ivy.array([2, 1]),
      b: ivy.array([3, 7])
  }, {
      a: ivy.array([5, 9]),
      b: ivy.array([2, 11])
  }]
code: def split(
      self: ivy.Container,
      /,
      *,
      copy: Optional[Union[bool, ivy.Container]] = None,
      num_or_size_splits: Optional[
          Union[
              int,
              Sequence[int],
              ivy.Array,
              ivy.NativeArray,
              ivy.Container,
          ]
      ] = None,
      axis: Union[int, ivy.Container] = 0,
      with_remainder: Union[bool, ivy.Container] = False,
      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,
  ) -> List[ivy.Container]:
      """ivy.Container instance method variant of ivy.split. This method
      simply wraps the function, and so the docstring for ivy.split also
      applies to this method with minimal changes.
  
      Parameters
      ----------
      self
          array to be divided into sub-arrays.
      copy
          boolean indicating whether or not to copy the input array.
          If True, the function must always copy.
          If False, the function must never copy and must
          raise a ValueError in case a copy would be necessary.
          If None, the function must reuse existing memory buffer if possible
          and copy otherwise. Default: ``None``.
      num_or_size_splits
          Number of equal arrays to divide the array into along the given axis if an
          integer. The size of each split element if a sequence of integers
          or 1-D array. Default is to divide into as many 1-dimensional arrays
          as the axis dimension.
      axis
          The axis along which to split, default is ``0``.
      with_remainder
          If the tensor does not split evenly, then store the last remainder entry.
          Default is ``False``.
      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
      -------
          list of containers of sub-arrays.
  
      Examples
      --------
      >>> x = ivy.Container(a=ivy.array([2, 1, 5, 9]), b=ivy.array([3, 7, 2, 11]))
      >>> y = x.split(num_or_size_splits=2)
      >>> print(y)
      [{
          a: ivy.array([2, 1]),
          b: ivy.array([3, 7])
      }, {
          a: ivy.array([5, 9]),
          b: ivy.array([2, 11])
      }]
      """
      return self._static_split(
          self,
          copy=copy,
          num_or_size_splits=num_or_size_splits,
          axis=axis,
          with_remainder=with_remainder,
          key_chains=key_chains,
          to_apply=to_apply,
          prune_unapplied=prune_unapplied,
          map_sequences=map_sequences,
      )
  
imports: from typing import Optional, Union, List, Tuple, Dict, Iterable, Sequence
  from numbers import Number
  import ivy
  from ivy.data_classes.container.base import ContainerBase
label_desc: Use image node_id 6 for calling the _ContainerWithManipulation obj's underlying member method code with example usage: obj.split() and returns: self