class_docstr: A Loss module that computes loss for WaveGlow
      
code: def input_types(self):
      return {
          "z": NeuralType(
              ("B", "flowgroup", "T"), NormalDistributionSamplesType()
          ),
          "log_s_list": [
              NeuralType(("B", "flowgroup", "T"), VoidType())
          ],  # TODO: Figure out a good typing
          "log_det_W_list": [
              NeuralType(elements_type=VoidType())
          ],  # TODO: Figure out a good typing
          "sigma": NeuralType(optional=True),
      }
  
file_path: NeMo/nemo/collections/tts/losses/waveglowloss.py
imports: import torch
  from nemo.core.classes import Loss, typecheck
  from nemo.core.neural_types.elements import LossType, NormalDistributionSamplesType, VoidType
  from nemo.core.neural_types.neural_type import NeuralType
label_desc: Use image node_id 1 for calling the WaveGlowLoss obj's underlying member method code with example usage: obj.input_types() and returns: dict