class_docstr: Wrapper class for data config YAML
class_docstr_tok: ["Wrapper","class","for","data","config","YAML"]
docstr: Subword tokenizer to apply on source text after pre-tokenization.
  Returning a dictionary with `bpe` providing the tokenizer name and
  the other items providing the tokenizer-specific arguments.
  Tokenizers are defined in `fairseq.data.encoders.*`
docstr_tok: ["Subword","tokenizer","to","apply","on","source","text","after","pre-tokenization",".","Returning","a","dictionary","with","`","bpe","`","providing","the","tokenizer","name","and","the","other","items","providing","the","tokenizer-specific","arguments",".","Tokenizers","are","defined","in","`","fairseq.data.encoders",".","*","`"]
code: def src_bpe_tokenizer(self) -> Dict:
      """Subword tokenizer to apply on source text after pre-tokenization.
      Returning a dictionary with `bpe` providing the tokenizer name and
      the other items providing the tokenizer-specific arguments.
      Tokenizers are defined in `fairseq.data.encoders.*`"""
      return self.config.get("src_bpe_tokenizer", {"bpe": None})
  
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 3 for calling the S2TJointDataConfig obj's underlying member method code with example usage: obj.src_bpe_tokenizer() and returns: self