register clintox dataset in benchmark.py

from chembl.chembl_datasets import load_chembl

from gdb7.gdb7_datasets import load_gdb7

from sampl.sampl_datasets import load_sampl

from clintox.clintox_datasets import load_clintox

def benchmark_loading_datasets(hyper_parameters, 

                               dataset='tox21', model='tf', split=None,

      hyper parameters including dropout rate, learning rate, etc.

  dataset: string, optional (default='tox21')

      choice of which dataset to use, should be: tox21, muv, sider, 

      toxcast, pcba, delaney, kaggle, nci

      toxcast, pcba, delaney, kaggle, nci, clintox

  model: string,  optional (default='tf')

      choice of which model to use, should be: rf, tf, tf_robust, logreg,

      graphconv, tf_regression, graphconvreg

      path of result file

  """

  if dataset in ['muv', 'pcba', 'tox21', 'sider', 'toxcast']:

  if dataset in ['muv', 'pcba', 'tox21', 'sider', 'toxcast', 'clintox']:

    mode = 'classification'

  elif dataset in ['kaggle', 'delaney', 'nci', 'pdbbind', 'chembl', 

                   'gdb7', 'sampl']:

                       'kaggle': load_kaggle, 'delaney': load_delaney,

                       'pdbbind': load_pdbbind_grid,

                       'chembl': load_chembl, 'gdb7': load_gdb7,

                       'sampl': load_sampl}

                       'sampl': load_sampl, 'clintox': load_clintox}

  print('-------------------------------------')

  print('Benchmark %s on dataset: %s' % (model, dataset))

           'tf_regression, graphconvreg')

  parser.add_argument('-d', action='append', dest='dataset_args', default=[], 

      help='Choice of dataset: tox21, sider, muv, toxcast, pcba, ' + 

           'kaggle, delaney, nci, pdbbindi, chembl, gdb7')

           'kaggle, delaney, nci, pdbbindi, chembl, gdb7, clintox')

  args = parser.parse_args()

  #Datasets and models used in the benchmark test

  splitters = args.splitter_args

    models = ['tf', 'tf_robust', 'logreg', 'graphconv', 

              'tf_regression', 'graphconvreg']

  if len(datasets) == 0:

    datasets = ['tox21', 'sider', 'muv', 'toxcast', 'pcba', 

    datasets = ['tox21', 'sider', 'muv', 'toxcast', 'pcba', 'clintox',

                'delaney', 'nci', 'kaggle', 'pdbbind', 'chembl', 'gdb7']

  #input hyperparameters

  for split in splitters:

    for dataset in datasets:

      if dataset in ['tox21', 'sider', 'muv', 'toxcast', 'pcba']:

      if dataset in ['tox21', 'sider', 'muv', 'toxcast', 'pcba', 'clintox']:

        for model in models:

          if model in ['tf', 'tf_robust', 'logreg', 'graphconv']:

            benchmark_loading_datasets(