code: def forward(self, x):
      assert len(x.size()) == 2
  
      x = torch.nn.functional.pad(x.unsqueeze(1), (1, 0), "reflect")
      return torch.nn.functional.conv1d(x, self.filter).squeeze(1)
  
imports: import torch
  import torchaudio
  from torch import nn
  from torch.nn import Conv1d, ConvTranspose1d
  from torch.nn import functional
  from torch.nn.utils.parametrizations import weight_norm
  from torch.nn.utils.parametrize import remove_parametrizations
  from TTS.utils.io import load_fsspec
label_desc: Use image node_id 2 for calling the PreEmphasis obj's underlying member method code with example usage: obj.forward(x) and returns: torch