code: def _generate_permuted_indexes(self, dataset_length):
      generator = torch.Generator()
      generator.manual_seed(self.config.get("split_train.seed", 123456))
      return torch.randperm(dataset_length, generator=generator)
  
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 13 for calling the MMFDatasetBuilder obj's underlying member method code with example usage: obj._generate_permuted_indexes(dataset_length) and returns: torch