code: def generate_non_autoregressive(
      self, encoder_out: Dict[str, Tensor], tgt_tokens
  ):
      decoder_out_tuple = self.model.decoder(tgt_tokens, encoder_out)
      (
          tgt_tokens,
          token_probs,
          token_logits,
      ) = self.model.decoder.get_probs(decoder_out_tuple)
      return tgt_tokens, token_probs, token_logits
  
imports: from enum import Enum
  from typing import Dict, Optional, Tuple
  import torch
  from pytext.common.constants import TORCH_VERSION
  from pytext.config import ConfigBase
  from pytext.models.module import Module
  from pytext.torchscript.vocab import ScriptVocabulary
  from torch import Tensor
label_desc: Use image node_id 11 for calling the MaskedSequenceGenerator obj's underlying member method code with example usage: obj.generate_non_autoregressive(encoder_out, tgt_tokens) and returns: tgt_tokens,  token_probs,  token_logits