class_docstr: Style MelGAN disciminator module.
docstr: Calculate forward propagation.
  
  Args:
      x (Tensor): Input tensor (B, 1, T).
  
  Returns:
      List: List of discriminator outputs, #items in the list will be
          equal to repeats * #discriminators.
docstr_tok: ["Calculate","forward","propagation",".","Args",":","x","(","Tensor",")",":","Input","tensor","(","B",",","1",",","T",")",".","Returns",":","List",":","List","of","discriminator","outputs",",","#","items","in","the","list","will","be","equal","to","repeats","*","#","discriminators","."]
code: def forward(self, x: torch.Tensor) -> List[torch.Tensor]:
      """Calculate forward propagation.
  
      Args:
          x (Tensor): Input tensor (B, 1, T).
  
      Returns:
          List: List of discriminator outputs, #items in the list will be
              equal to repeats * #discriminators.
  
      """
      outs = []
      for _ in range(self.repeats):
          outs += self._forward(x)
  
      return outs
  
imports: import copy
  import logging
  import math
  from typing import Any, Dict, List, Optional
  import numpy
  import torch
  import torch.nn.functional
  from espnet2.gan_tts.melgan import MelGANDiscriminator
  from espnet2.gan_tts.melgan.pqmf import PQMF
  from espnet2.gan_tts.style_melgan.tade_res_block import TADEResBlock
label_desc: Use image node_id 2 for calling the StyleMelGANDiscriminator obj's underlying member method code with example usage: obj.forward(x) and returns: outs