code: def test_data_creator(self):
      def get_x_y(size, config):
          values = np.random.randn(size, 4)
          df = pd.DataFrame(values, columns=["f1", "f2", "f3", "t"])
          selected_features = config["features"]
          x = df[selected_features].to_numpy()
          y = df["t"].to_numpy()
          return x, y
  
      from functools import partial
  
      train_data_creator = partial(get_x_y, 20)
      val_data_creator = partial(get_x_y, 5)
      config = {
          "n_estimators": 5,
          "max_depth": 2,
          "tree_method": "hist",
      }
      model_builder = XGBoostModelBuilder(
          model_type="regressor", cpus_per_trial=1, **config
      )
      model = model_builder.build(config={"features": ["f1", "f2"]})
      model.fit_eval(
          train_data_creator,
          validation_data=val_data_creator,
          metric="mae",
      )
  
file_path: BigDL/python/orca/test/bigdl/orca/automl/xgboost/test_xgbregressor.py
imports: from bigdl.orca.test_zoo_utils import ZooTestCase
  import numpy
  import pandas
  import os
  from numpy.testing import assert_array_almost_equal
  from bigdl.orca.automl.xgboost.XGBoost import XGBoost, XGBoostModelBuilder
  import pytest
label_desc: Use image node_id 6 for calling the TestXgbregressor obj's underlying member method code with example usage: obj.test_data_creator() and returns: x,  y