code: def _build_cpu_skl_classifier(m, data, args, tmpdir):
      """Loads the SKLearn classifier and returns it"""
  
      max_leaf_nodes = args["max_leaf_nodes"]
      n_estimators = args["n_estimators"]
      n_feature = data[0].shape[1]
      train_size = data[0].shape[0]
      model_name = (
          f"skl_{max_leaf_nodes}_{n_estimators}_{n_feature}_"
          + f"{train_size}.model.pkl"
      )
      model_path = os.path.join(tmpdir, model_name)
  
      skl_model = pickle.load(open(model_path, "rb"))
      return skl_model
  
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 14 for calling a global function with example usage: _build_cpu_skl_classifier(m, data, args, tmpdir) and returns: skl_model