code: def is_float_dtype(arr_or_dtype) -> bool:
      """
      Check whether the provided array or dtype is of a float dtype.
  
      Parameters
      ----------
      arr_or_dtype : array-like or dtype
          The array or dtype to check.
  
      Returns
      -------
      boolean
          Whether or not the array or dtype is of a float dtype.
  
      Examples
      --------
      >>> from cudf.api.types import is_float_dtype
      >>> import numpy as np
      >>> import cudf
      >>> is_float_dtype(str)
      False
      >>> is_float_dtype(int)
      False
      >>> is_float_dtype(float)
      True
      >>> is_float_dtype(np.array(['a', 'b']))
      False
      >>> is_float_dtype(cudf.Series([1, 2]))
      False
      >>> is_float_dtype(cudf.Index([1, 2.]))
      True
      """
      if isinstance(arr_or_dtype, cudf.BaseIndex):
          return arr_or_dtype._is_floating()
      return _wrap_pandas_is_dtype_api(pd_types.is_float_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 12 for calling a global function with example usage: is_float_dtype(arr_or_dtype) and returns: _wrap_pandas_is_dtype_api, arr_or_dtype