code: def __init__(
      self,
      split: str,
      is_train_split: bool,
      cfg: S2TJointDataConfig,
      audio_paths: List[str],
      n_frames: List[int],
      src_texts: Optional[List[str]] = None,
      tgt_texts: Optional[List[str]] = None,
      speakers: Optional[List[str]] = None,
      src_langs: Optional[List[str]] = None,
      tgt_langs: Optional[List[str]] = None,
      ids: Optional[List[str]] = None,
      tgt_dict: Optional[Dictionary] = None,
      src_dict: Optional[Dictionary] = None,
      pre_tokenizer=None,
      bpe_tokenizer=None,
      src_pre_tokenizer=None,
      src_bpe_tokenizer=None,
      append_eos: Optional[bool] = True,
      alignment: Optional[List[str]] = None,
      use_src_lang_id: Optional[int] = 0,
  ):
      super().__init__(
          split,
          is_train_split,
          cfg,
          audio_paths,
          n_frames,
          src_texts=src_texts,
          tgt_texts=tgt_texts,
          speakers=speakers,
          src_langs=src_langs,
          tgt_langs=tgt_langs,
          ids=ids,
          tgt_dict=tgt_dict,
          pre_tokenizer=pre_tokenizer,
          bpe_tokenizer=bpe_tokenizer,
          append_eos=append_eos,
      )
  
      self.src_dict = src_dict
      self.src_pre_tokenizer = src_pre_tokenizer
      self.src_bpe_tokenizer = src_bpe_tokenizer
      self.alignment = None
      self.use_src_lang_id = use_src_lang_id
      if alignment is not None:
          self.alignment = [
              [float(s) for s in sample.split()] for sample in alignment
          ]
  
imports: import logging
  from pathlib import Path
  from typing import Dict, List, NamedTuple, Optional
  import torch
  from fairseq.data import ConcatDataset, Dictionary, ResamplingDataset
  from fairseq.data import data_utils
  from fairseq.data.audio.speech_to_text_dataset import S2TDataConfig, SpeechToTextDataset, SpeechToTextDatasetCreator
label_desc: Use image node_id 1 to create a new SpeechToTextJointDataset object from inherited base classes: SpeechToTextDataset with example: obj = SpeechToTextJointDataset(split, is_train_split, cfg, audio_paths, n_frames, src_texts, tgt_texts, speakers, src_langs, tgt_langs, ids, tgt_dict, src_dict, pre_tokenizer, bpe_tokenizer, src_pre_tokenizer, src_bpe_tokenizer, append_eos, alignment, use_src_lang_id)