code: def forward(self, *args, **kwargs):
      if self.training:
          return self.train_forward(**kwargs)
      return self.infer(**kwargs)
  
imports: import torch
  from torch.autograd import Variable
  from torch.nn import functional
  from nemo.collections.tts.modules.submodules import Attention, ConvNorm, LinearNorm, Prenet
  from nemo.collections.tts.parts.utils.helpers import get_mask_from_lengths
  from nemo.core.classes import NeuralModule, typecheck
  from nemo.core.neural_types.elements import EmbeddedTextType, LengthsType, LogitsType, MelSpectrogramType, SequenceToSequenceAlignmentType
  from nemo.core.neural_types.neural_type import NeuralType
  from nemo.utils import logging
label_desc: Use image node_id 4 for calling the Decoder obj's underlying member method code with example usage: obj.forward() and returns: self, self