code: def add_common_args(parser):
      """
      Add command line arguments for this agent.
      """
      TorchRankerAgent.add_cmdline_args(parser, partial_opt=None)
      parser = parser.add_argument_group("Bert Ranker Arguments")
      parser.add_argument(
          "--add-transformer-layer",
          type="bool",
          default=False,
          help="Also add a transformer layer on top of Bert",
      )
      parser.add_argument(
          "--pull-from-layer",
          type=int,
          default=-1,
          help="Which layer of Bert do we use? Default=-1=last one.",
      )
      parser.add_argument(
          "--out-dim",
          type=int,
          default=768,
          help="For biencoder, output dimension",
      )
      parser.add_argument(
          "--topn",
          type=int,
          default=10,
          help="For the biencoder: select how many elements to return",
      )
      parser.add_argument(
          "--data-parallel",
          type="bool",
          default=False,
          help="use model in data parallel, requires "
          "multiple gpus. NOTE This is incompatible"
          " with distributed training",
      )
      parser.add_argument(
          "--bert-aggregation",
          type=str,
          default="first",
          choices=["first", "max", "mean"],
          help="How do we transform a list of output into one",
      )
      parser.set_defaults(
          label_truncate=300,
          text_truncate=300,
          learningrate=0.00005,
          eval_candidates="inline",
          candidates="batch",
          dict_maxexs=0,  # skip building dictionary
      )
  
file_path: ParlAI/parlai/agents/bert_ranker/helpers.py
imports: from parlai.core.torch_ranker_agent import TorchRankerAgent
  from parlai.utils.torch import neginf
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: add_common_args(parser) without return types