code: def load_a_dataset(
      self,
      split,
      data_path,
      src,
      src_dict,
      tgt,
      tgt_dict,
      combine,
      prepend_bos=False,
      langpairs_sharing_datasets=None,
      data_category=None,
      **extra_kwargs,
  ):
      dataset_impl = self.args.dataset_impl
      upsample_primary = self.args.upsample_primary
      left_pad_source = self.args.left_pad_source
      left_pad_target = self.args.left_pad_target
      max_source_positions = self.args.max_source_positions
      max_target_positions = self.args.max_target_positions
      load_alignments = self.args.load_alignments
      truncate_source = self.args.truncate_source
      src_dataset_transform_func = self.src_dataset_tranform_func
      tgt_dataset_transform_func = self.tgt_dataset_tranform_func
      enable_lang_ids = self.args.enable_lang_ids
      lang_dictionary = self.lang_dict
      src_langtok_spec, tgt_langtok_spec = extra_kwargs["langtok_spec"]
  
      src_langtok = self.get_encoder_langtok(src, tgt, src_langtok_spec)
      tgt_langtok = self.get_decoder_langtok(tgt, tgt_langtok_spec)
      logger.info(
          f"{data_category}:{src}-{tgt} src_langtok: {src_langtok}; tgt_langtok: {tgt_langtok}"
      )
  
      langpair_ds = self.load_langpair_dataset(
          data_path,
          split,
          src,
          src_dict,
          tgt,
          tgt_dict,
          combine,
          dataset_impl,
          upsample_primary,
          left_pad_source,
          left_pad_target,
          max_source_positions,
          max_target_positions,
          prepend_bos,
          load_alignments,
          truncate_source,
          src_dataset_transform_func=lambda dataset: src_dataset_transform_func(
              src, tgt, dataset, src_langtok_spec
          ),
          tgt_dataset_transform_func=lambda dataset: tgt_dataset_transform_func(
              src, tgt, dataset, tgt_langtok_spec
          ),
          src_lang_id=_lang_id(lang_dictionary, src)
          if enable_lang_ids and lang_dictionary is not None
          else None,
          tgt_lang_id=_lang_id(lang_dictionary, tgt)
          if enable_lang_ids and lang_dictionary is not None
          else None,
          langpairs_sharing_datasets=langpairs_sharing_datasets,
      )
      # TODO: handle modified lang toks for mined data and dae data
      if self.args.lang_tok_replacing_bos_eos:
          ds = self.alter_dataset_langtok(
              langpair_ds,
              src_eos=self.get_source_dictionary(src).eos()
              if src
              else self.get_target_dictionary(tgt).eos(),
              src_lang=src,
              tgt_eos=self.get_target_dictionary(tgt).eos(),
              tgt_lang=tgt,
              src_langtok_spec=src_langtok_spec,
              tgt_langtok_spec=tgt_langtok_spec,
          )
      else:
          ds = langpair_ds
      return ds
  
imports: import itertools
  import json
  import logging
  import math
  import os
  from collections import OrderedDict, defaultdict
  from argparse import ArgumentError
  from fairseq import utils
  from fairseq.data import AppendTokenDataset, ConcatDataset, Dictionary, LanguagePairDataset, PrependTokenDataset, SampledMultiDataset, SampledMultiEpochDataset, StripTokenDataset, TransformEosLangPairDataset, TruncateDataset, data_utils, indexed_dataset
  from fairseq.data.multilingual.multilingual_utils import EncoderLangtok, LangTokSpec, LangTokStyle, augment_dictionary, get_lang_tok
  from fairseq.data.multilingual.sampled_multi_dataset import CollateFormat
  from fairseq.file_io import PathManager
  from fairseq.utils import FileContentsAction, csv_str_list, eval_str_dict
label_desc: Use image node_id 23 for calling the MultilingualDatasetManager obj's underlying member method code with example usage: obj.load_a_dataset(split, data_path, src, src_dict, tgt, tgt_dict, combine, prepend_bos, langpairs_sharing_datasets, data_category) and returns: ds