class_docstr: Transformer Ranker Agent.
  
  Implementation of a TorchRankerAgent, where the model is a Transformer
code: def _vectorize_memories(self, obs):
      # TODO: move this to Torch Ranker Agent
      raise NotImplementedError(
          "Abstract class: user must implement this function to use memories"
      )
  
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 5 for calling the TransformerRankerAgent obj's underlying member method code with example usage: obj._vectorize_memories(obs) without return types