code: def _collate_target(
      self, samples: List[SpeechToSpeechDatasetItem]
  ) -> torch.Tensor:
      if self.target_is_code:
          target = fairseq_data_utils.collate_tokens(
              [x.target for x in samples],
              self.tgt_dict.pad(),
              self.tgt_dict.eos(),
              left_pad=False,
              move_eos_to_beginning=False,
          )
          # convert stacked units to a single id
          pack_targets = [self.pack_units(x.target) for x in samples]
          prev_output_tokens = fairseq_data_utils.collate_tokens(
              pack_targets,
              self.tgt_dict.pad(),
              self.tgt_dict.eos(),
              left_pad=False,
              move_eos_to_beginning=True,
          )
          target_lengths = torch.tensor(
              [x.size(0) for x in pack_targets], dtype=torch.long
          )
      else:
          target = _collate_frames(
              [x.target for x in samples], is_audio_input=False
          )
          bsz, _, d = target.size()
          prev_output_tokens = torch.cat(
              (target.new_full((bsz, 1, d), 0.0), target[:, :-1, :]),
              dim=1,
          )
          target_lengths = torch.tensor(
              [x.target.size(0) for x in samples], dtype=torch.long
          )
  
      return target, prev_output_tokens, target_lengths
  
imports: import logging
  from dataclasses import dataclass
  from pathlib import Path
  from typing import Dict, List, Optional, Tuple
  import torch
  from fairseq.data import ConcatDataset, Dictionary
  from fairseq.data import data_utils
  from fairseq.data.audio.audio_utils import get_features_or_waveform
  from fairseq.data.audio.data_cfg import S2SDataConfig
  from fairseq.data.audio.speech_to_text_dataset import SpeechToTextDataset, SpeechToTextDatasetCreator, TextTargetMultitaskData, _collate_frames
label_desc: Use image node_id 4 for calling the SpeechToSpeechDataset obj's underlying member method code with example usage: obj._collate_target(samples) and returns: target,  prev_output_tokens,  target_lengths