class_docstr: Equivalent of bert_ranker/crossencoder but does not rely on an external library
  (hugging face).
class_docstr_tok: ["Equivalent","of","bert_ranker\/crossencoder","but","does","not","rely","on","an","external","library","(","hugging","face",")","."]
code: def build_model(self, states=None):
      return CrossEncoderModule(self.opt, self.dict, self.NULL_IDX)
  
file_path: ParlAI/parlai/agents/transformer/crossencoder.py
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  from .modules import TransformerEncoder
  from parlai.core.torch_ranker_agent import TorchRankerAgent
  from .transformer import TransformerRankerAgent
  from parlai.utils.torch import concat_without_padding
  import torch
label_desc: Use image node_id 2 for calling the CrossencoderAgent obj's underlying member method code with example usage: obj.build_model(states) and returns: CrossEncoderModule