docstr: Shapes:
      - x: :math:`[B, C, T]`
      - mask:  :math:`[B, 1, T]`
  
  TODO: Handle the cond input
docstr_tok: ["Shapes",":","-","x",":",":","math",":","`","[","B",",","C",",","T","]","`","-","mask",":",":","math",":","`","[","B",",","1",",","T","]","`","TODO",":","Handle","the","cond","input"]
code: def forward(
      self, x, mask=None, g=None
  ):  # pylint: disable=unused-argument
      """
      Shapes:
          - x: :math:`[B, C, T]`
          - mask:  :math:`[B, 1, T]`
  
      TODO: Handle the cond input
      """
      x = self.fft(x, mask=mask)
      x = self.proj(x)
      return x
  
file_path: TTS/TTS/tts/layers/generic/transformer.py
imports: import torch
  import torch.nn.functional
  from torch import nn
label_desc: Use image node_id 2 for calling the FFTDurationPredictor obj's underlying member method code with example usage: obj.forward(x, mask, g) and returns: x