class_docstr: Calculate negative log likelihodd for sequence input, also applies label smoothing (if set).
class_docstr_tok: ["Calculate","negative","log","likelihodd","for","sequence","input",",","also","applies","label","smoothing","(","if","set",")","."]
docstr: Returns definitions of module output ports.
          
docstr_tok: ["Returns","definitions","of","module","output","ports","."]
code: def output_types(self):
      """Returns definitions of module output ports."""
      return {"loss": NeuralType(elements_type=LossType())}
  
file_path: NeMo/nemo/collections/common/losses/smoothed_cross_entropy.py
imports: from typing import Optional
  import torch
  from nemo.core.classes import Exportable, Loss, NeuralModule, typecheck
  from nemo.core.neural_types import LabelsType, LogprobsType, LossType, MaskType, NeuralType
label_desc: Use image node_id 2 for calling the SmoothedNLLLoss obj's underlying member method code with example usage: obj.output_types() and returns: dict