code: def load_sider(featurizer="ECFP", split="index"):
      current_dir = os.path.dirname(os.path.realpath(__file__))
  
      # Load SIDER dataset
      print("About to load SIDER dataset.")
      dataset_file = os.path.join(current_dir, "./sider.csv.gz")
      dataset = dc.utils.save.load_from_disk(dataset_file)
      print("Columns of dataset: %s" % str(dataset.columns.values))
      print("Number of examples in dataset: %s" % str(dataset.shape[0]))
  
      # Featurize SIDER dataset
      print("About to featurize SIDER dataset.")
      if featurizer == "ECFP":
          featurizer = dc.feat.CircularFingerprint(size=1024)
      elif featurizer == "GraphConv":
          featurizer = dc.feat.ConvMolFeaturizer()
  
      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)
  
      splitters = {
          "index": dc.splits.IndexSplitter(),
          "random": dc.splits.RandomSplitter(),
          "scaffold": dc.splits.ScaffoldSplitter(),
      }
      splitter = splitters[split]
      train, valid, test = splitter.train_valid_test_split(dataset)
  
      return SIDER_tasks, (train, valid, test), transformers
  
file_path: deepchem/examples/sider/sider_datasets.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import unicode_literals
  import os
  import numpy
  import shutil
  import deepchem
label_desc: Use image node_id 1 for calling a global function with example usage: load_sider(featurizer, split) and returns: SIDER_tasks,  train,  valid,  test,  transformers