code: def build_model(cls, args, task):
      model = BertRanker(args, task)
      return DiscriminativeNMTReranker(args, model)
  
imports: from dataclasses import dataclass, field
  import os
  import torch
  import torch.nn
  from fairseq import utils
  from fairseq.dataclass import ChoiceEnum, FairseqDataclass
  from fairseq.models import BaseFairseqModel, register_model
  from fairseq.models.roberta.model import RobertaClassificationHead
  from fairseq.modules import LayerNorm, TransformerSentenceEncoder, TransformerSentenceEncoderLayer
label_desc: Use image node_id 1 for calling the DiscriminativeNMTReranker obj's underlying member method code with example usage: obj.build_model(cls, args, task) and returns: DiscriminativeNMTReranker