def METHOD_NAME():
  """Load SIDER datasets. Does not do train/test split"""
  # Featurize SIDER dataset
  print("About to featurize SIDER dataset.")
  current_dir = os.path.dirname(os.path.realpath(__file__))
  dataset_file = os.path.join(current_dir, "../sider/sider.csv.gz")
  featurizer = dc.feat.ConvMolFeaturizer()
  dataset = dc.utils.save.load_from_disk(dataset_file)
  SIDER_tasks = dataset.columns.values[1:].tolist()
  print("SIDER tasks: %s" % str(SIDER_tasks))
  print("%d tasks in total" % len(SIDER_tasks))
  loader = dc.data.CSVLoader(
      tasks=SIDER_tasks, smiles_field="smiles", featurizer=featurizer)
  dataset = loader.featurize(dataset_file)
  print("%d datapoints in SIDER dataset" % len(dataset))
  # Initialize transformers
  transformers = [dc.trans.BalancingTransformer(dataset=dataset)]
  print("About to transform data")
  for transformer in transformers:
    dataset = transformer.transform(dataset)
  return SIDER_tasks, dataset, transformers