code: def to_new_backend(
      x: Union[ivy.Array, ivy.NativeArray, Iterable],
      native: bool = True,
      nested: bool = False,
      include_derived: Optional[Dict[str, bool]] = None,
      cont_inplace: bool = False,
      to_ignore: Optional[Union[type, Tuple[type]]] = None,
  ) -> Union[ivy.Array, ivy.NativeArray, Iterable]:
      """Return the input array converted to new backend framework form if it is
      an `ivy.Array`, `ivy.NativeArray` or NativeVariable instance. If nested is
      set, the check is applied to all nested leaves of tuples, lists and dicts
      contained within ``x``.
  
      Parameters
      ----------
      x
          The input to maybe convert.
      native
          Whether to return the new array as a `ivy.NativeArray`, NativeVariable
          or an `ivy.Array`. Default is ``True``.
      nested
          Whether to apply the conversion on arguments in a nested manner. If so, all
          dicts, lists and tuples will be traversed to their lowest leaves in search of
          ivy.Array instances. Default is ``False``.
      include_derived
          Whether to also recursive for classes derived from tuple, list and dict.
          Default is ``False``.
      cont_inplace
          Whether to update containers in place. Default is ``False``
      to_ignore
          Types to ignore when deciding whether to go deeper into the nest or not
  
      Returns
      -------
       ret
          the input in the new backend framework form in the case of array instances.
      """
      if nested:
          return ivy.nested_map(
              lambda x: _to_new_backend(
                  x,
                  native=native,
                  inplace=cont_inplace,
                  to_ignore=to_ignore,
              ),
              x,
              include_derived,
              shallow=False,
          )
      return _to_new_backend(
          x, native=native, inplace=cont_inplace, to_ignore=to_ignore
      )
  
file_path: ivy/ivy/data_classes/array/conversions.py
imports: import numpy
  from typing import Any, Union, Tuple, Dict, Iterable, Optional
  import ivy
label_desc: Use image node_id 9 for calling a global function with example usage: to_new_backend(x, native, nested, include_derived, cont_inplace, to_ignore) and returns: _to_new_backend, ivy