code: def ensure_dtype_objs(
      dtype: DtypeArg | dict[Hashable, DtypeArg] | None
  ) -> DtypeObj | dict[Hashable, DtypeObj] | None:
      """
      Ensure we have either None, a dtype object, or a dictionary mapping to
      dtype objects.
      """
      if isinstance(dtype, defaultdict):
          # "None" not callable  [misc]
          default_dtype = pandas_dtype(dtype.default_factory())  # type: ignore[misc]
          dtype_converted: defaultdict = defaultdict(
              lambda: default_dtype
          )
          for key in dtype.keys():
              dtype_converted[key] = pandas_dtype(dtype[key])
          return dtype_converted
      elif isinstance(dtype, dict):
          return {k: pandas_dtype(dtype[k]) for k in dtype}
      elif dtype is not None:
          return pandas_dtype(dtype)
      return dtype
  
imports: from __future__ import annotations
  from collections import defaultdict
  from typing import TYPE_CHECKING
  import warnings
  import numpy
  from pandas._libs import lib, parsers
  from pandas.compat._optional import import_optional_dependency
  from pandas.errors import DtypeWarning
  from pandas.util._exceptions import find_stack_level
  from pandas.core.dtypes.common import pandas_dtype
  from pandas.core.dtypes.concat import concat_compat, union_categoricals
  from pandas.core.dtypes.dtypes import CategoricalDtype
  from pandas.core.indexes.api import ensure_index_from_sequences
  from pandas.io.common import dedup_names, is_potential_multi_index
  from pandas.io.parsers.base_parser import ParserBase, ParserError, is_index_col
label_desc: Use image node_id 2 for calling a global function with example usage: ensure_dtype_objs(dtype) and returns: dtype, dtype_converted, unknown, pandas_dtype