code: def ensure_float(arr):
      """
      Ensure that an array object has a float dtype if possible.
  
      Parameters
      ----------
      arr : array-like
          The array whose data type we want to enforce as float.
  
      Returns
      -------
      float_arr : The original array cast to the float dtype if
                  possible. Otherwise, the original array is returned.
      """
      if is_extension_array_dtype(arr.dtype):
          if is_float_dtype(arr.dtype):
              arr = arr.to_numpy(
                  dtype=arr.dtype.numpy_dtype, na_value=np.nan
              )
          else:
              arr = arr.to_numpy(dtype="float64", na_value=np.nan)
      elif issubclass(arr.dtype.type, (np.integer, np.bool_)):
          arr = arr.astype(float)
      return arr
  
imports: from __future__ import annotations
  from typing import Any, Callable
  import warnings
  import numpy
  from pandas._libs import Interval, Period, algos, lib
  from pandas._libs.tslibs import conversion
  from pandas._typing import ArrayLike, DtypeObj
  from pandas.core.dtypes.base import _registry
  from pandas.core.dtypes.dtypes import CategoricalDtype, DatetimeTZDtype, ExtensionDtype, IntervalDtype, PeriodDtype
  from pandas.core.dtypes.generic import ABCIndex
  from pandas.core.dtypes.inference import is_array_like, is_bool, is_complex, is_dataclass, is_decimal, is_dict_like, is_file_like, is_float, is_hashable, is_integer, is_interval, is_iterator, is_list_like, is_named_tuple, is_nested_list_like, is_number, is_re, is_re_compilable, is_scalar, is_sequence
label_desc: Use image node_id 1 for calling a global function with example usage: ensure_float(arr) and returns: arr