code: def _treelite_fil_accuracy_score(y_true, y_pred):
      """Function to get correct accuracy for FIL (returns class index)"""
      # convert the input if necessary
      y_pred1 = (
          y_pred.copy_to_host()
          if cuda.devicearray.is_cuda_ndarray(y_pred)
          else y_pred
      )
      y_true1 = (
          y_true.copy_to_host()
          if cuda.devicearray.is_cuda_ndarray(y_true)
          else y_true
      )
  
      y_pred_binary = input_utils.convert_dtype(y_pred1 > 0.5, np.int32)
      return cuml.metrics.accuracy_score(y_true1, y_pred_binary)
  
imports: from cuml.manifold import UMAP
  from cuml.benchmark import datagen
  from cuml.common.device_selection import using_device_type
  from cuml.internals.device_type import DeviceType
  from cuml.internals.global_settings import GlobalSettings
  from cuml.internals.safe_imports import cpu_only_import, gpu_only_import, gpu_only_import_from, safe_import
  import sklearn.ensemble
  import pickle
  import os
  import cuml
  from cuml.internals import input_utils
  from time import perf_counter
label_desc: Use image node_id 17 for calling a global function with example usage: _treelite_fil_accuracy_score(y_true, y_pred) and returns: cuml