code: def load_uv(shard_size):
      """Loads uv datasets. Generates if not stored already."""
      UV_tasks = ["logTIC"] + ["w__%d" % i for i in range(210, 401)]
  
      current_dir = os.path.dirname(os.path.realpath(__file__))
      raw_train_dir = os.path.join(current_dir, "raw_train_dir")
      train_dir = os.path.join(current_dir, "train_dir")
      valid_dir = os.path.join(current_dir, "valid_dir")
      test_dir = os.path.join(current_dir, "test_dir")
  
      if (
          os.path.exists(raw_train_dir)
          and os.path.exists(train_dir)
          and os.path.exists(valid_dir)
          and os.path.exists(test_dir)
      ):
          print("Reloading existing datasets")
          raw_train_dataset = dc.data.DiskDataset(raw_train_dir)
          train_dataset = dc.data.DiskDataset(train_dir)
          valid_dataset = dc.data.DiskDataset(valid_dir)
          test_dataset = dc.data.DiskDataset(test_dir)
      else:
          print("Featurizing datasets")
          (
              raw_train_dataset,
              train_dataset,
              valid_dataset,
              test_dataset,
          ) = gen_uv(
              UV_tasks,
              raw_train_dir,
              train_dir,
              valid_dir,
              test_dir,
              shard_size=shard_size,
          )
  
      transformers = get_transformers(raw_train_dataset)
      return (
          UV_tasks,
          (train_dataset, valid_dataset, test_dataset),
          transformers,
      )
  
file_path: deepchem/examples/uv/UV_datasets.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import unicode_literals
  import os
  import shutil
  import time
  import numpy
  import deepchem
  from uv_features import uv_descriptors
label_desc: Use image node_id 5 for calling a global function with example usage: load_uv(shard_size) and returns: UV_tasks,  train_dataset,  valid_dataset,  test_dataset,  transformers