code: def add_parameters(parser):
      
      group = parser.add_argument_group('Evaluation arguments')
  
      group.add_argument('--eval-batch-size', type=int, default=1024)
  
      # Datasets
      group.add_argument(
          '--similarity-datasets', type=str,
          default=nlp.data.word_embedding_evaluation.word_similarity_datasets,
          nargs='*',
          help='Word similarity datasets to use for intrinsic evaluation.')
      group.add_argument(
          '--similarity-functions', type=str,
          default=nlp.embedding.evaluation.list_evaluation_functions(
              'similarity'), nargs='+',
          help='Word similarity functions to use for intrinsic evaluation.')
      group.add_argument(
          '--analogy-datasets', type=str, default=['GoogleAnalogyTestSet'],
          nargs='*',
          help='Word similarity datasets to use for intrinsic evaluation.')
      group.add_argument(
          '--analogy-functions', type=str,
          default=nlp.embedding.evaluation.list_evaluation_functions('analogy'),
          nargs='+',
          help='Word analogy functions to use for intrinsic evaluation. ')
  
      ## Analogy evaluation specific arguments
      group.add_argument(
          '--analogy-dont-exclude-question-words', action='store_true',
          help=('Exclude input words from valid output analogies.'
                'The performance of word embeddings on the analogy task '
                'is around 0% accuracy if input words are not excluded.'))
docs: Add evaluation specific parameters to parser.