code: def test_rf_memory_leakage(
      small_clf, datatype, fil_sparse_format, n_iter
  ):
      use_handle = True
  
      X, y = small_clf
      X = X.astype(datatype)
      y = y.astype(np.int32)
      X_train, X_test, y_train, y_test = train_test_split(
          X, y, train_size=0.8, random_state=0
      )
      # Create a handle for the cuml model
      handle, stream = get_handle(use_handle, n_streams=1)
  
      # Warmup. Some modules that are used in RF allocate space on the device
      # and consume memory. This is to make sure that the allocation is done
      # before the first call to get_memory_info.
      base_model = curfc(handle=handle)
      base_model.fit(X_train, y_train)
      handle.sync()  # just to be sure
      free_mem = cuda.current_context().get_memory_info()[0]
  
      def test_for_memory_leak():
          cuml_mods = curfc(handle=handle)
          cuml_mods.fit(X_train, y_train)
          handle.sync()  # just to be sure
          # Calculate the memory free after fitting the cuML model
          delta_mem = (
              free_mem - cuda.current_context().get_memory_info()[0]
          )
          assert delta_mem == 0
  
          for i in range(2):
              cuml_mods.predict(
                  X_test,
                  predict_model="GPU",
                  fil_sparse_format=fil_sparse_format,
              )
              handle.sync()  # just to be sure
              # Calculate the memory free after predicting the cuML model
              delta_mem = (
                  free_mem - cuda.current_context().get_memory_info()[0]
              )
              assert delta_mem == 0
  
      for i in range(n_iter):
          test_for_memory_leak()
  
imports: import treelite
  from sklearn.model_selection import train_test_split
  from sklearn.datasets import fetch_california_housing, make_classification, make_regression, load_iris, load_breast_cancer
  from sklearn.metrics import accuracy_score, mean_squared_error, mean_tweedie_deviance
  from sklearn.ensemble import RandomForestRegressor
  from sklearn.ensemble import RandomForestClassifier
  import cuml.internals.logger
  from cuml.testing.utils import get_handle, unit_param, quality_param, stress_param
  from cuml.metrics import r2_score
  from cuml.ensemble import RandomForestRegressor
  from cuml.ensemble import RandomForestClassifier
  import cuml
  from cuml.internals.safe_imports import gpu_only_import_from
  import os
  import json
  import random
  from cuml.internals.safe_imports import cpu_only_import
  import pytest
  import warnings
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 19 for calling a global function with example usage: test_rf_memory_leakage(small_clf, datatype, fil_sparse_format, n_iter) without return types