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)
  
file_path: TTS/TTS/encoder/models/base_encoder.py
imports: import numpy
  import torch
  import torchaudio
  from coqpit import Coqpit
  from torch import nn
  from TTS.encoder.losses import AngleProtoLoss, GE2ELoss, SoftmaxAngleProtoLoss
  from TTS.utils.generic_utils import set_init_dict
  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