code: def is_object_dtype(arr_or_dtype):
      """
      Check whether an array-like or dtype is of the object dtype.
  
      Parameters
      ----------
      arr_or_dtype : array-like or dtype
          The array-like or dtype to check.
  
      Returns
      -------
      boolean
          Whether or not the array-like or dtype is of the object dtype.
  
      Examples
      --------
      >>> from cudf.api.types import is_object_dtype
      >>> import numpy as np
      >>> is_object_dtype(object)
      True
      >>> is_object_dtype(int)
      False
      >>> is_object_dtype(np.array([], dtype=object))
      True
      >>> is_object_dtype(np.array([], dtype=int))
      False
      >>> is_object_dtype([1, 2, 3])
      False
      """
      if isinstance(arr_or_dtype, cudf.BaseIndex):
          return arr_or_dtype._is_object()
      elif isinstance(arr_or_dtype, cudf.Series):
          return pd_types.is_object_dtype(
              arr_or_dtype=arr_or_dtype.dtype
          )
      else:
          return pd_types.is_object_dtype(arr_or_dtype=arr_or_dtype)
  
imports: from __future__ import annotations
  from collections import abc
  from functools import wraps
  from inspect import isclass
  from typing import List, Union
  import cupy
  import numpy
  import pandas
  from pandas.api import types
  import cudf
  from cudf.core._compat import PANDAS_GE_150
  from cudf.core.dtypes import _BaseDtype, dtype, is_categorical_dtype, is_decimal32_dtype, is_decimal64_dtype, is_decimal128_dtype, is_decimal_dtype, is_interval_dtype, is_list_dtype, is_struct_dtype
label_desc: Use image node_id 11 for calling a global function with example usage: is_object_dtype(arr_or_dtype) and returns: arr_or_dtype, pd_types, pd_types