code: def _build_word_embedding(self):
      self.text_processor = registry.get(
          self._datasets[0] + "_text_processor"
      )
      self.vocab = self.text_processor.vocab
      self.vocab_size = self.vocab.get_size()
      self.word_embedding = self.vocab.get_embedding(
          torch.nn.Embedding, embedding_dim=self.config.embedding_dim
      )
      self.text_embeddings_out_dim = self.config.embedding_dim
  
file_path: mmf/mmf/models/butd.py
imports: import torch
  from mmf.common.registry import registry
  from mmf.models.pythia import Pythia
  from mmf.modules.layers import ClassifierLayer
label_desc: Use image node_id 4 for calling the BUTD obj's underlying member method code with example usage: obj._build_word_embedding() without return types