code: def load_parallel_dataset(
      source_lang,
      target_lang,
      src_bin_path,
      tgt_bin_path,
      source_dictionary,
      target_dictionary,
      split,
      remove_eos_from_source,
      append_eos_to_target=True,
      char_source_dict=None,
      log_verbose=True,
  ):
      corpus = pytorch_translate_data.ParallelCorpusConfig(
          source=pytorch_translate_data.CorpusConfig(
              dialect=source_lang, data_file=src_bin_path
          ),
          target=pytorch_translate_data.CorpusConfig(
              dialect=target_lang, data_file=tgt_bin_path
          ),
          weights_file=None,
      )
  
      if log_verbose:
          print("Starting to load binarized data files.", flush=True)
      validate_corpus_exists(corpus=corpus, split=split)
  
      tgt_dataset = pytorch_translate_data.InMemoryIndexedDataset.create_from_file(
          corpus.target.data_file
      )
      if char_source_dict is not None:
          src_dataset = (
              char_data.InMemoryNumpyWordCharDataset.create_from_file(
                  corpus.source.data_file
              )
          )
      else:
          src_dataset = pytorch_translate_data.InMemoryIndexedDataset.create_from_file(
              corpus.source.data_file
          )
      parallel_dataset = weighted_data.WeightedLanguagePairDataset(
          src=src_dataset,
          src_sizes=src_dataset.sizes,
          src_dict=source_dictionary,
          tgt=tgt_dataset,
          tgt_sizes=tgt_dataset.sizes,
          tgt_dict=target_dictionary,
          remove_eos_from_source=remove_eos_from_source,
          append_eos_to_target=append_eos_to_target,
      )
      return parallel_dataset, src_dataset, tgt_dataset
  
imports: from typing import Optional
  from fvcore.common.file_io import PathManager
  from pytorch_translate.data import char_data, data, weighted_data
label_desc: Use image node_id 1 for calling a global function with example usage: load_parallel_dataset(source_lang, target_lang, src_bin_path, tgt_bin_path, source_dictionary, target_dictionary, split, remove_eos_from_source, append_eos_to_target, char_source_dict, log_verbose) and returns: parallel_dataset,  src_dataset,  tgt_dataset