code: def load_dataset(hparams):
      dataset_splits = {}
      data_folder = hparams["data_save_folder"]
      for split_id in DATASET_SPLITS:
          split_path = hparams[f"{split_id}_json"]
          dataset_split = (
              sb.dataio.dataset.DynamicItemDataset.from_json(
                  split_path, replacements={"data_root": data_folder}
              )
          )
          dataset_split = apply_sort(hparams, dataset_split)
          dataset_splits[split_id] = dataset_split
      return dataset_splits
  
imports: import logging
  import sys
  import torch
  import speechbrain
  import os
  from collections import namedtuple
  from audiomnist_prepare import prepare_audiomnist
  from hyperpyyaml import load_hyperpyyaml
  from torchaudio import functional
  from speechbrain.dataio.dataio import length_to_mask, write_audio
  from speechbrain.dataio.dataset import apply_overfit_test
  from speechbrain.utils import data_utils
  from speechbrain.utils.train_logger import plot_spectrogram
  from enum import Enum
  from speechbrain.utils.distributed import run_on_main
  from speechbrain.utils.data_utils import dict_value_combinations, dist_stats, masked_mean, masked_min, masked_max, masked_std, match_shape
label_desc: Use image node_id 3 for calling a global function with example usage: load_dataset(hparams) and returns: dataset_splits