code: def __call__(self, code, dur, f0):
      if self.extra_length == 0:
          code_mask = torch.zeros_like(code).bool()
          dur_mask = torch.zeros_like(dur).bool()
          f0_mask = torch.zeros_like(f0).bool()
          return code, code_mask, dur, dur_mask, f0, f0_mask
  
      code, code_mask = self.shift_one(
          code, 0, self.extra_length, self.pads.code
      )
      dur, dur_mask = self.shift_one(
          dur, self.dur, self.extra_length - self.dur, self.pads.dur
      )
      f0, f0_mask = self.shift_one(
          f0, self.f0, self.extra_length - self.f0, self.pads.f0
      )
      return code, code_mask, dur, dur_mask, f0, f0_mask
  
imports: import json
  import logging
  import os
  import random
  from pathlib import Path
  import numpy
  import torch
  import torch.utils.data
  from .None import data_utils
  from fairseq.data.fairseq_dataset import FairseqDataset
label_desc: Use image node_id 5 for calling the Shifts obj's underlying member method code with example usage: obj.__call__(code, dur, f0) and returns: code,  code_mask,  dur,  dur_mask,  f0,  f0_mask, code,  code_mask,  dur,  dur_mask,  f0,  f0_mask