old_contents: # coding=utf-8
  # Copyright 2018 The HuggingFace Inc. team.
  #
  # Licensed 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.
  """ Conditional generation class. """
  
  
  class Seq2SeqModel(object):
      def __init__(self):
          # need to use from_pretrained to initialize
          raise NotImplementedError
  
      @classmethod
      def from_pretrained(cls, encoder, decoder):
          # Here we should call AutoModel to initialize the models depending
          # on the pretrained models taken as an input.
          # For a first iteration we only work with Bert.
          raise NotImplementedError
  
      def __call__(self):
          # allows to call an instance of the class
          # model = Seq2Seq(encode='bert', decoder='bert')
          raise NotImplementedError
  
      def process(self):
          # alternative API to __call__ it is more explicit.
          raise NotImplementedError
  
new_contents: # coding=utf-8
  # Copyright 2018 The HuggingFace Inc. team.
  #
  # Licensed 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.
  """ Conditional generation class. """
  
  
  class Seq2SeqModel(object):
      def __init__(self):
          raise EnvironmentError(
              """Seq2Seq is designed to be instantiated using the
          `Seq2Seq.from_pretrained(encoder_name_or_path, decoder_name_or_path)` method."""
          )
  
      @classmethod
      def from_pretrained(cls, encoder_name, decoder_name):
          # Here we should call AutoModel to initialize the models depending
          # on the pretrained models taken as an input.
          # For a first iteration we only work with Bert.
          raise NotImplementedError
  
      def __call__(self):
          # allows to call an instance of the class
          # model = Seq2Seq(encode='bert', decoder='bert')
          raise NotImplementedError
  
      def process(self):
          # alternative API to __call__ it is more explicit.
          raise NotImplementedError
  
subject: raise exception when class initialized with __init__