code: def forward(
      self,
      logits: Tuple[torch.Tensor, torch.Tensor],
      context: Dict[str, torch.Tensor],
  ) -> Tuple[List[Dict[str, float]], List[List[Dict[str, float]]]]:
      d_logits, w_logits = logits
      if "token_indices" in context:
          w_logits = query_word_reprs(
              w_logits, context["token_indices"]
          )
  
      d_results = self.doc_scores(d_logits)
      w_results = self.word_scores(w_logits, context)
      return d_results, w_results
  
imports: from typing import Any, Dict, List, Optional, Tuple, Union
  import torch
  import torch.nn
  from caffe2.python import core
  from pytext.common.constants import DatasetFieldName
  from pytext.data.utils import Vocabulary
  from pytext.models.module import create_module
  from pytext.utils.usage import log_class_usage
  from torch import jit
  from .doc_classification_output_layer import ClassificationOutputLayer
  from .output_layer_base import OutputLayerBase
  from .utils import query_word_reprs
  from .word_tagging_output_layer import CRFOutputLayer, WordTaggingOutputLayer
label_desc: Use image node_id 2 for calling the IntentSlotScores obj's underlying member method code with example usage: obj.forward(logits, context) and returns: d_results,  w_results