code: def test_no_x_train_and_validation_sets():
      print("AutoML run with x not provided with train and valid")
      ds = import_dataset()
      aml = H2OAutoML(
          project_name="py_aml2",
          stopping_rounds=3,
          stopping_tolerance=0.001,
          stopping_metric="AUC",
          max_models=max_models,
          seed=1234,
      )
      aml.train(
          y=ds.target,
          training_frame=ds.train,
          validation_frame=ds.valid,
      )
      assert aml.project_name == "py_aml2", "Project name is not set"
      assert aml.stopping_rounds == 3, "stopping_rounds is not set to 3"
      assert (
          aml.stopping_tolerance == 0.001
      ), "stopping_tolerance is not set to 0.001"
      assert (
          aml.stopping_metric == "AUC"
      ), "stopping_metrics is not set to `AUC`"
      assert aml.max_models == 2, "max_models is not set to 2"
      assert aml.seed == 1234, "seed is not set to `1234`"
      log_df = aml.event_log.as_data_frame()
      warn_messages = log_df[log_df["level"] == "WARN"]["message"]
      assert warn_messages.str.startswith(
          "User specified a validation frame with cross-validation still enabled"
      ).any(), "a warning should have been raised for using a validation frame with CV enabled"
      print("Check leaderboard")
      print(aml.leaderboard)
  
file_path: h2o-3/h2o-py/tests/testdir_algos/automl/pyunit_automl_input.py
imports: import sys, os
  import h2o
  from h2o.automl import H2OAutoML
  from tests import pyunit_utils
  from _automl_utils import import_dataset
label_desc: Use image node_id 3 for calling a global function with example usage: test_no_x_train_and_validation_sets() without return types