class_docstr: Classifier based on Transformer.
class_docstr_tok: ["Classifier","based","on","Transformer","."]
code: def build_model(self):
      _check_positional_embeddings(self.opt)
      num_classes = len(self.class_list)
      self.base_model = TransformerMemNetModel(self.opt, self.dict)
      return TransformerLinearWrapper(
          self.base_model.context_encoder, num_classes
      )
  
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  from parlai.core.agents import Agent
  from parlai.utils.torch import padded_3d
  from parlai.core.torch_classifier_agent import TorchClassifierAgent
  from parlai.core.torch_ranker_agent import TorchRankerAgent
  from parlai.core.torch_generator_agent import TorchGeneratorAgent
  from parlai.utils.misc import recursive_getattr, warn_once
  from parlai.utils.logging import logging
  from parlai.utils.fsdp import should_use_fsdp
  from .modules import TransformerMemNetModel, TransformerGeneratorModel, TransformerLinearWrapper
  import torch
label_desc: Use image node_id 2 for calling the TransformerClassifierAgent obj's underlying member method code with example usage: obj.build_model() and returns: TransformerLinearWrapper