code: def _init_classifier(self):
      num_hidden = self.config.text_embedding.num_hidden
      num_choices = registry.get(
          self._datasets[0] + "_num_final_outputs"
      )
      dropout = self.config.classifier.dropout
      self.classifier = WeightNormClassifier(
          num_hidden, num_choices, num_hidden * 2, dropout
      )
  
file_path: mmf/mmf/models/ban.py
imports: import torch
  from mmf.common.registry import registry
  from mmf.models.base_model import BaseModel
  from mmf.modules.embeddings import BiLSTMTextEmbedding
  from mmf.modules.layers import BCNet, BiAttention, FCNet, WeightNormClassifier
  from torch import nn
label_desc: Use image node_id 7 for calling the BAN obj's underlying member method code with example usage: obj._init_classifier() without return types