old_contents: #!/usr/bin/env python
  
  # Copyright (c) Facebook, Inc. and its affiliates.
  # This source code is licensed under the MIT license found in the
  # LICENSE file in the root directory of this source tree.
  
  from parlai.scripts.train_model import setup_args, TrainLoop
  
  if __name__ == '__main__':
      parser = setup_args()
      parser.set_defaults(
          task='wizard_of_wikipedia:generator:random_split',
          model='projects.wizard_of_wikipedia.generator.agents:EndToEndAgent',
          model_file='/tmp/end2end_generator/model',
          dict_lower=True,
          dict_tokenizer='bpe',
          n_layers=5,
          n_heads=2,
          dropout=0.20,
          ffn_size=512,
          embeddingsize=256,
          log_every_n_secs=10,
          validation_patience=12,
          validation_metric='ppl',
          validation_metric_mode='min',
          validation_every_n_epochs=0.5,
          n_positions=128,
          truncate=128,
          max_knowledge=32,
          knowledge_alpha=0.95,
          knowledge_truncate=32,
          learningrate=5e-4,
          warmup_updates=5000,
          clip=0.1,
          lr_scheduler='invsqrt',
          embedding_type='fasttext',
          beam_size=1,
          skip_generation=False,
          batchsize=64,
      )
      TrainLoop(parser.parse_args()).train()
  
new_contents: #!/usr/bin/env python
  
  # Copyright (c) Facebook, Inc. and its affiliates.
  # This source code is licensed under the MIT license found in the
  # LICENSE file in the root directory of this source tree.
  
  from parlai.scripts.train_model import setup_args, TrainLoop
  
  if __name__ == '__main__':
      parser = setup_args()
      parser.set_defaults(
          task='wizard_of_wikipedia:generator:random_split',
          model='projects.wizard_of_wikipedia.generator.agents:EndToEndAgent',
          model_file='/tmp/end2end_generator/model',
          dict_lower=True,
          dict_tokenizer='bpe',
          n_layers=5,
          n_heads=2,
          dropout=0.20,
          ffn_size=512,
          embedding_size=256,
          log_every_n_secs=10,
          validation_patience=12,
          validation_metric='ppl',
          validation_metric_mode='min',
          validation_every_n_epochs=0.5,
          n_positions=128,
          truncate=128,
          max_knowledge=32,
          knowledge_alpha=0.95,
          knowledge_truncate=32,
          learningrate=5e-4,
          warmup_updates=5000,
          clip=0.1,
          lr_scheduler='invsqrt',
          embedding_type='fasttext',
          beam_size=1,
          skip_generation=False,
          batchsize=64,
      )
      TrainLoop(parser.parse_args()).train()
  
subject: Update train_end2end.py (#1671)