class_docstr: This constructs a simple bag of words model.
  
  It contains a encoder for encoding candidates and context.
code: def __init__(self, opt, dictionary):
      super().__init__()
      self.hidden_dim = opt.get("hidden_dim", 512)
      self.dict = dictionary
      self.encoder = nn.EmbeddingBag(len(self.dict), self.hidden_dim)
  
file_path: ParlAI/parlai/agents/examples/tra.py
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  from parlai.core.torch_ranker_agent import TorchRankerAgent
  import torch
  from torch import nn
label_desc: Use image node_id 1 to create a new ExampleBagOfWordsModel object from inherited base classes: nn with example: obj = ExampleBagOfWordsModel(opt, dictionary)