class_docstr: Bert BiEncoder that computes classification metrics (F1, precision, recall)
code: def train_step(self, batch):
      output = super().train_step(batch)
      preds = output["text"]
      self._update_confusion_matrix(preds, batch.labels)
      return output
  
imports: from parlai.agents.bert_ranker.bi_encoder_ranker import BiEncoderRankerAgent
  from projects.style_gen.modules import ClassificationMixin
label_desc: Use image node_id 1 for calling the BertRankerClassifierAgent obj's underlying member method code with example usage: obj.train_step(batch) and returns: output