text: #
  # Licensed to the Apache Software Foundation (ASF) under one or more
  # contributor license agreements.  See the NOTICE file distributed with
  # this work for additional information regarding copyright ownership.
  # The ASF licenses this file to You under the Apache License, Version 2.0
  # (the "License"); you may not use this file except in compliance with
  # the License.  You may obtain a copy of the License at
  #
  #    http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  #
  
  from typing import NoReturn
  from typing import Union
  
  from raydp.utils import df_type_check
  
  
  class SparkEstimatorInterface:
      def fit_on_spark(self,
                       df: Union["pyspark.sql.DataFrame", "koalas.DataFrame"],
                       **kwargs) -> NoReturn:
          """
          Fit the model on the df. The df should be ether spark DataFrame or koalas DataFrame.
          """
          df_type_check(df)
  
      def evaluate_on_spark(self,
                            df: Union["pyspark.sql.DataFrame", "koalas.DataFrame"],
                            **kwargs) -> NoReturn:
          """
          Evaluate on the trained model. The df should be ether spark DataFrame or koalas
          DataFrame. This should be called after call fit.
          """
          df_type_check(df)
  