code: def load_muv_convmol():
      """Load MUV datasets. Does not do train/test split"""
      # Load MUV dataset
      print("About to load MUV dataset.")
      current_dir = os.path.dirname(os.path.realpath(__file__))
      dataset_file = os.path.join(
          current_dir, "../../datasets/muv.csv.gz"
      )
      # Featurize MUV dataset
      print("About to featurize MUV dataset.")
      featurizer = dc.feat.ConvMolFeaturizer()
      MUV_tasks = sorted(
          [
              "MUV-692",
              "MUV-689",
              "MUV-846",
              "MUV-859",
              "MUV-644",
              "MUV-548",
              "MUV-852",
              "MUV-600",
              "MUV-810",
              "MUV-712",
              "MUV-737",
              "MUV-858",
              "MUV-713",
              "MUV-733",
              "MUV-652",
              "MUV-466",
              "MUV-832",
          ]
      )
  
      loader = dc.data.CSVLoader(
          tasks=MUV_tasks, smiles_field="smiles", featurizer=featurizer
      )
      dataset = loader.featurize(dataset_file)
  
      # Initialize transformers
      transformers = [dc.trans.BalancingTransformer(dataset=dataset)]
      print("About to transform data")
      for transformer in transformers:
          dataset = transformer.transform(dataset)
  
      return MUV_tasks, dataset, transformers
  
file_path: deepchem/examples/low_data/datasets.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import unicode_literals
  import os
  import sys
  import shutil
  import tempfile
  import numpy
  import deepchem
label_desc: Use image node_id 5 for calling a global function with example usage: load_muv_convmol() and returns: MUV_tasks,  dataset,  transformers