code: def test_errors(self):
      from sklearn.ensemble import RandomForestRegressor
  
      data = dx.datasets.load_fifa()
      X = data.drop(columns=["nationality", "value_eur"]).iloc[1:100, :]
      y = data["value_eur"][1:100]
  
      model = RandomForestRegressor()
      model.fit(X, y)
  
      def predict_function_return_2d(m, d):
          n_rows = d.shape[0]
          prediction = m.predict(d)
          return prediction.reshape((n_rows, 1))
  
      def predict_function_return_3d(m, d):
          n_rows = d.shape[0]
          prediction = m.predict(d)
          return prediction.reshape((n_rows, 1, 1))
  
      def predict_function_return_one_element_array(m, d):
          return np.array(0.2)
  
      warnings.simplefilter("always")
      with warnings.catch_warnings(record=True) as w:
          # Trigger a warning.
          dx.Explainer(
              model,
              X,
              y,
              verbose=False,
              model_type="regression",
              predict_function=predict_function_return_2d,
          )
          assert issubclass(w[-1].category, UserWarning)
  
      with warnings.catch_warnings(record=True) as w:
          # Trigger a warning.
          dx.Explainer(
              model,
              X,
              y,
              verbose=False,
              model_type="regression",
              predict_function=predict_function_return_3d,
          )
          assert issubclass(w[-1].category, UserWarning)
  
      with warnings.catch_warnings(record=True) as w:
          # Trigger a warning.
          dx.Explainer(
              model,
              X,
              y,
              verbose=False,
              model_type="regression",
              predict_function=predict_function_return_one_element_array,
          )
          assert issubclass(w[-1].category, UserWarning)
  
file_path: DALEX/python/dalex/test/test_explainer.py
imports: import unittest
  from sklearn.compose import ColumnTransformer
  from sklearn.impute import SimpleImputer
  from sklearn.neural_network import MLPRegressor
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import StandardScaler, LabelEncoder, OneHotEncoder
  import dalex
  import numpy
  import warnings
label_desc: Use image node_id 3 for calling the ExplainerTest obj's underlying member method code with example usage: obj.test_errors() and returns: prediction, prediction, np