class_docstr: Combines decoder_embedding with the tokens_head layer to simulate the classifier in NemoNMT
class_docstr_tok: ["Combines","decoder_embedding","with","the","tokens_head","layer","to","simulate","the","classifier","in","NemoNMT"]
code: def output_types(self) -> Optional[Dict[str, NeuralType]]:
      return {"log_probs": NeuralType(("B", "T", "D"), ChannelType())}
  
imports: import random
  from typing import Dict, List, Optional
  import torch
  import torch.nn.functional
  from nemo.collections.nlp.modules.common.megatron.utils import build_position_ids
  from nemo.core.classes.exportable import Exportable
  from nemo.core.neural_types import ChannelType, EncodedRepresentation, MaskType, NeuralType
label_desc: Use image node_id 8 for calling the TokensHeadEmb obj's underlying member method code with example usage: obj.output_types() and returns: dict