input: Write a python function to train a RandomForestClassifier and make predictions.
  assert train_and_predict_rf(X_train, y_train, X_test, max_depth=5, random_state=0, n_estimators=100) == y_pred_expected
  assert train_and_predict_rf(X_train_2, y_train_2, X_test_2, max_depth=3, random_state=1, n_estimators=50) == y_pred_expected_2
  assert train_and_predict_rf(X_train_3, y_train_3, X_test_3, max_depth=None, random_state=42, n_estimators=200) == y_pred_expected_3
output: def train_and_predict_rf(X_train, y_train, X_test, max_depth, random_state, n_estimators):
      from sklearn.ensemble import RandomForestClassifier
      
      model = RandomForestClassifier(max_depth=max_depth, random_state=random_state, n_estimators=n_estimators)
      model.fit(X_train, y_train)
      y_pred = model.predict(X_test)
      
      return y_pred