class_docstr: Style MelGAN generator module.
docstr: Perform inference.
  
  Args:
      c (Tensor): Input tensor (T, in_channels).
  
  Returns:
      Tensor: Output tensor (T ** prod(upsample_scales), out_channels).
docstr_tok: ["Perform","inference",".","Args",":","c","(","Tensor",")",":","Input","tensor","(","T",",","in_channels",")",".","Returns",":","Tensor",":","Output","tensor","(","T","*","*","prod","(","upsample_scales",")",",","out_channels",")","."]
code: def inference(self, c: torch.Tensor) -> torch.Tensor:
      """Perform inference.
  
      Args:
          c (Tensor): Input tensor (T, in_channels).
  
      Returns:
          Tensor: Output tensor (T ** prod(upsample_scales), out_channels).
  
      """
      c = c.transpose(1, 0).unsqueeze(0)
  
      # prepare noise input
      noise_size = (
          1,
          self.in_channels,
          math.ceil(c.size(2) / self.noise_upsample_factor),
      )
      noise = torch.randn(*noise_size, dtype=torch.float).to(
          next(self.parameters()).device
      )
      x = self.noise_upsample(noise)
  
      # NOTE(kan-bayashi): To remove pop noise at the end of audio, perform padding
      #    for feature sequence and after generation cut the generated audio. This
      #    requires additional computation but it can prevent pop noise.
      total_length = c.size(2) * self.upsample_factor
      c = F.pad(c, (0, x.size(2) - c.size(2)), "replicate")
  
      # This version causes pop noise.
      # x = x[:, :, :c.size(2)]
  
      for block in self.blocks:
          x, c = block(x, c)
      x = self.output_conv(x)[..., :total_length]
  
      return x.squeeze(0).transpose(1, 0)
  
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 6 for calling the StyleMelGANGenerator obj's underlying member method code with example usage: obj.inference(c) and returns: x