docstr: c : (B, C, T_in).
  Tensor: (B, C, T_upsampled),
docstr_tok: ["c",":","(","B",",","C",",","T_in",")",".","Tensor",":","(","B",",","C",",","T_upsampled",")",","]
code: def forward(self, c):
      """
      c : (B, C, T_in).
      Tensor: (B, C, T_upsampled),
      """
      c_ = self.conv_in(c)
      c = (
          c_[:, :, : -self.aux_context_window]
          if self.use_causal_conv
          else c_
      )
      return self.upsample(c)
  
file_path: TTS/TTS/vocoder/layers/upsample.py
imports: import torch
  from torch.nn import functional
label_desc: Use image node_id 2 for calling the ConvUpsample obj's underlying member method code with example usage: obj.forward(c) and returns: self