class_docstr: MelGAN generator module.
docstr: Calculate forward propagation.
  
  Args:
      c (Tensor): Input tensor (B, channels, T).
  
  Returns:
      Tensor: Output tensor (B, 1, T ** prod(upsample_scales)).
docstr_tok: ["Calculate","forward","propagation",".","Args",":","c","(","Tensor",")",":","Input","tensor","(","B",",","channels",",","T",")",".","Returns",":","Tensor",":","Output","tensor","(","B",",","1",",","T","*","*","prod","(","upsample_scales",")",")","."]
code: def forward(self, c: torch.Tensor) -> torch.Tensor:
      """Calculate forward propagation.
  
      Args:
          c (Tensor): Input tensor (B, channels, T).
  
      Returns:
          Tensor: Output tensor (B, 1, T ** prod(upsample_scales)).
  
      """
      return self.melgan(c)
  
imports: import logging
  from typing import Any, Dict, List
  import numpy
  import torch
  from espnet2.gan_tts.melgan.residual_stack import ResidualStack
label_desc: Use image node_id 2 for calling the MelGANGenerator obj's underlying member method code with example usage: obj.forward(c) and returns: self