code: def parse_decoder_inputs(self, decoder_inputs):
      # (B, n_mel_channels, T_out) -> (B, T_out, n_mel_channels)
      decoder_inputs = decoder_inputs.transpose(1, 2)
      decoder_inputs = decoder_inputs.view(
          decoder_inputs.size(0),
          int(decoder_inputs.size(1) / self.n_frames_per_step),
          -1,
      )
      # (B, T_out, n_mel_channels) -> (T_out, B, n_mel_channels)
      decoder_inputs = decoder_inputs.transpose(0, 1)
      return decoder_inputs
  
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 7 for calling the Decoder obj's underlying member method code with example usage: obj.parse_decoder_inputs(decoder_inputs) and returns: decoder_inputs