class_docstr: Transformer Ranker Agent.
  
  Implementation of a TorchRankerAgent, where the model is a Transformer
class_docstr_tok: ["Transformer","Ranker","Agent",".","Implementation","of","a","TorchRankerAgent",",","where","the","model","is","a","Transformer"]
docstr: Encode candidates.
docstr_tok: ["Encode","candidates","."]
code: def encode_candidates(self, padded_cands):
      """
      Encode candidates.
      """
      _, cands = self.model(xs=None, mems=None, cands=padded_cands)
  
      return cands
  
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 7 for calling the TransformerRankerAgent obj's underlying member method code with example usage: obj.encode_candidates(padded_cands) and returns: cands