def METHOD_NAME(data_dir=None, subset="core"):
  """Featurizes pdbbind according to provided featurization"""
  tasks = ["active-site"]
  current_dir = os.path.dirname(os.path.realpath(__file__))
  data_dir = os.path.join(current_dir, "%s_pockets" % (subset))
  if os.path.exists(data_dir):
    return dc.data.DiskDataset(data_dir), tasks
  pdbbind_dir = os.path.join(current_dir, "../pdbbind/v2015")
  # Load PDBBind dataset
  if subset == "core":
    labels_file = os.path.join(pdbbind_dir, "INDEX_core_data.2013")
  elif subset == "refined":
    labels_file = os.path.join(pdbbind_dir, "INDEX_refined_data.2015")
  elif subset == "full":
    labels_file = os.path.join(pdbbind_dir, "INDEX_general_PL_data.2015")
  else:
    raise ValueError("Only core, refined, and full subsets supported.")
  print("About to load contents.")
  if not os.path.exists(labels_file):
    raise ValueError("Run ../pdbbind/get_pdbbind.sh to download dataset.")
  contents_df = load_pdbbind_labels(labels_file)
  ids = contents_df["PDB code"].values
  y = np.array([float(val) for val in contents_df["-logKd/Ki"].values])
  # Define featurizers
  pocket_featurizer = dc.feat.BindingPocketFeaturizer()
  ligand_featurizer = dc.feat.CircularFingerprint(size=1024)
  # Featurize Dataset
  all_features = []
  all_labels = []
  missing_pdbs = []
  all_ids = []
  time1 = time.time()
  for ind, pdb_code in enumerate(ids):
    print("Processing complex %d, %s" % (ind, str(pdb_code)))
    pdb_subdir = os.path.join(pdbbind_dir, pdb_code)
    if not os.path.exists(pdb_subdir):
      print("%s is missing!" % pdb_subdir)
      missing_pdbs.append(pdb_subdir)
      continue
    features, labels = compute_binding_pocket_features(
        pocket_featurizer, ligand_featurizer, pdb_subdir, pdb_code)
    if features is None:
      print("Featurization failed!")
      continue
    all_features.append(features)
    all_labels.append(labels)
    ids = np.array(["%s%d" % (pdb_code, i) for i in range(len(labels))])
    all_ids.append(ids)
  time2 = time.time()
  print("TIMING: PDBBind Pocket Featurization took %0.3f s" % (time2-time1))
  X = np.vstack(all_features)
  y = np.concatenate(all_labels)
  w = np.ones_like(y)
  ids = np.concatenate(all_ids)
  dataset = dc.data.DiskDataset.from_numpy(X, y, w, ids, data_dir=data_dir)
  return dataset, tasks