code: def score_labeling_with_handle(
      func, ground_truth, predictions, use_handle, dtype=np.int32
  ):
      """Test helper to standardize inputs between sklearn and our prims metrics.
  
      Using this function we can pass python lists as input of a test just like
      with sklearn as well as an option to use handle with our metrics.
      """
      a = cp.array(ground_truth, dtype=dtype)
      b = cp.array(predictions, dtype=dtype)
  
      handle, stream = get_handle(use_handle)
  
      return func(a, b, handle=handle)
  
imports: import pytest
  from cuml.internals.mem_type import MemoryType
  from cuml.internals.input_utils import input_to_cuml_array, is_array_like
  from cuml.internals.base import Base
  import cuml
  from sklearn.model_selection import train_test_split
  from sklearn.metrics import mean_squared_error, brier_score_loss
  from sklearn.datasets import make_classification, make_regression
  from sklearn import datasets
  from pylibraft.common.cuda import Stream
  from sklearn.datasets import make_regression
  from numba.cuda.cudadrv.devicearray import DeviceNDArray
  from numbers import Number
  from cuml.internals.safe_imports import gpu_only_import_from
  from itertools import dropwhile
  from copy import deepcopy
  from cuml.internals.safe_imports import cpu_only_import
  import inspect
  from textwrap import dedent, indent
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 17 for calling a global function with example usage: score_labeling_with_handle(func, ground_truth, predictions, use_handle, dtype) and returns: func