docstr: Args:
      encoded_utterance: [CLS] token hidden state from BERT encoding of the utterance
docstr_tok: ["Args",":","encoded_utterance",":","[","CLS","]","token","hidden","state","from","BERT","encoding","of","the","utterance"]
code: def forward(self, encoded_utterance):
      """
      Args:
          encoded_utterance: [CLS] token hidden state from BERT encoding of the utterance
      """
  
      # Project the utterance embeddings.
      utterance_embedding = self.utterance_proj(encoded_utterance)
      utterance_embedding = self.activation(utterance_embedding)
  
      logits = self.layer1(utterance_embedding)
      return logits
  
file_path: NeMo/nemo/collections/nlp/modules/dialogue_state_tracking/sgd_decoder.py
imports: from typing import Dict, Optional
  import torch
  from torch import nn
  from nemo.core.classes import NeuralModule, typecheck
  from nemo.core.neural_types import LogitsType, NeuralType
label_desc: Use image node_id 2 for calling the LogitsQA obj's underlying member method code with example usage: obj.forward(encoded_utterance) and returns: logits