code: def load(self, config, dataset_type, *args, **kwargs):
      self.config = config
  
      split_dataset_from_train = self.config.get("split_train", False)
      if split_dataset_from_train:
          config = self._modify_dataset_config_for_split(config)
  
      annotations = self._read_annotations(config, dataset_type)
      if annotations is None:
          return None
  
      datasets = []
      for imdb_idx in range(len(annotations)):
          dataset_class = self.dataset_class
          dataset = dataset_class(config, dataset_type, imdb_idx)
          datasets.append(dataset)
  
      dataset = MMFConcatDataset(datasets)
      if split_dataset_from_train:
          dataset = self._split_dataset_from_train(
              dataset, dataset_type
          )
  
      self.dataset = dataset
      return self.dataset
  
imports: import collections
  import os
  import typing
  import warnings
  from copy import deepcopy
  import mmf.utils.download
  import torch
  from mmf.datasets.base_dataset_builder import BaseDatasetBuilder
  from mmf.datasets.concat_dataset import MMFConcatDataset
  from mmf.datasets.subset_dataset import MMFSubset
  from mmf.utils.configuration import get_global_config, get_mmf_env, get_zoo_config
  from mmf.utils.general import get_absolute_path
  from omegaconf import open_dict
label_desc: Use image node_id 11 for calling the MMFDatasetBuilder obj's underlying member method code with example usage: obj.load(config, dataset_type) and returns: self, None