Loading README.md +5 −1 Original line number Diff line number Diff line Loading @@ -353,6 +353,9 @@ Scaffold splitting |qm7b |MT-NN regression |Index |0.931 |0.803 | | |MT-NN regression |Random |0.923 |0.884 | | |MT-NN regression |Stratified |0.934 |0.884 | |qm9 |MT-NN regression |Index |0.733 |0.791 | | |MT-NN regression |Random |0.811 |0.823 | | |MT-NN regression |Stratified |0.843 |0.818 | |kaggle |MT-NN regression |User-defined|0.748 |0.452 | |Dataset |Model |Splitting |Train score/MAE(kcal/mol)|Valid score/MAE(kcal/mol)| Loading Loading @@ -385,7 +388,7 @@ Number of tasks and examples in the datasets |chembl(5thresh) |691 |23871 | |qm7 |1 |7165 | |qm7b |14 |7211 | |qm9 |15 |133885 | Time needed for benchmark test(~20h in total) Loading Loading @@ -442,6 +445,7 @@ Time needed for benchmark test(~20h in total) |chembl |MT-NN regression |200 |9000 | |qm7 |MT-NN regression |10 |400 | |qm7b |MT-NN regression |10 |600 | |qm9 |MT-NN regression |220 |10000 | |kaggle |MT-NN regression |2200 |3200 | Loading examples/benchmark.py +16 −12 Original line number Diff line number Diff line Loading @@ -19,7 +19,7 @@ Giving regression performances of: Random forest(rf_regression), Graph convolution regression(graphconvreg) on datasets: delaney(ESOL), nci, kaggle, pdbbind, qm7, qm7b, chembl, sampl(FreeSolv) qm7, qm7b, qm9, chembl, sampl(FreeSolv) time estimation listed in README file Loading Loading @@ -52,6 +52,7 @@ from delaney.delaney_datasets import load_delaney from pdbbind.pdbbind_datasets import load_pdbbind_grid from chembl.chembl_datasets import load_chembl from qm7.qm7_datasets import load_qm7_from_mat, load_qm7b_from_mat from qm9.qm9_datasets import load_qm9 from sampl.sampl_datasets import load_sampl from clintox.clintox_datasets import load_clintox from hiv.hiv_datasets import load_hiv Loading @@ -74,7 +75,7 @@ def benchmark_loading_datasets(hyper_parameters, dataset: string, optional (default='tox21') choice of which dataset to use, should be: tox21, muv, sider, toxcast, pcba, delaney, kaggle, nci, clintox, hiv, pdbbind, chembl, qm7, qm7b, sampl qm7, qm7b, qm9, sampl model: string, optional (default='tf') choice of which model to use, should be: rf, tf, tf_robust, logreg, irv, graphconv, tf_regression, rf_regression, graphconvreg Loading @@ -87,7 +88,8 @@ def benchmark_loading_datasets(hyper_parameters, if dataset in ['muv', 'pcba', 'tox21', 'sider', 'toxcast', 'clintox', 'hiv']: mode = 'classification' elif dataset in [ 'kaggle', 'delaney', 'nci', 'pdbbind', 'chembl', 'qm7', 'qm7b', 'sampl' 'kaggle', 'delaney', 'nci', 'pdbbind', 'chembl', 'qm7', 'qm7b', 'qm9', 'sampl' ]: mode = 'regression' else: Loading Loading @@ -122,18 +124,18 @@ def benchmark_loading_datasets(hyper_parameters, if not model in ['tf_regression', 'rf_regression']: return if dataset in ['qm7']: featurizer = None # qm7 is already featurized if dataset in ['qm7', 'qm7b', 'qm9']: featurizer = None # qm7, qm7b, qm9 is already featurized if split in ['scaffold', 'butina']: return # qm7 accept index and random splitter return # qm7, qm7b, qm9 accept index and random splitter if not model in ['tf_regression']: return if split in ['year']: if not dataset in ['chembl']: return if split in ['indice', 'stratified']: if not dataset in ['qm7', 'qm7b']: if split in ['stratified']: if not dataset in ['qm7', 'qm7b', 'qm9']: return elif not split in [None, 'index', 'random', 'scaffold', 'butina']: raise ValueError('Splitter function not supported') Loading @@ -151,6 +153,7 @@ def benchmark_loading_datasets(hyper_parameters, 'chembl': load_chembl, 'qm7': load_qm7_from_mat, 'qm7b': load_qm7b_from_mat, 'qm9': load_qm9, 'sampl': load_sampl, 'clintox': load_clintox, 'hiv': load_hiv Loading @@ -171,14 +174,14 @@ def benchmark_loading_datasets(hyper_parameters, train_dataset, valid_dataset, test_dataset = all_dataset fit_transformers = [] if dataset in ['qm7', 'qm7b']: if dataset in ['qm7', 'qm7b', 'qm9']: fit_transformers = [dc.trans.CoulombFitTransformer(train_dataset)] time_finish_loading = time.time() # time_finish_loading-time_start is the time(s) used for dataset loading if dataset in ['kaggle', 'pdbbind']: n_features = train_dataset.get_data_shape()[0] elif dataset in ['qm7', 'qm7b']: elif dataset in ['qm7', 'qm7b', 'qm9']: n_features = list(train_dataset.get_data_shape()) # dataset has customized features Loading Loading @@ -788,7 +791,8 @@ if __name__ == '__main__': dest='dataset_args', default=[], help='Choice of dataset: tox21, sider, muv, toxcast, pcba, ' + 'kaggle, delaney, nci, pdbbind, chembl, sampl, qm7, qm7b, clintox, hiv') 'kaggle, delaney, nci, pdbbind, chembl, sampl, qm7, qm7b, qm9, clintox, hiv' ) parser.add_argument( '-t', action='store_true', Loading @@ -814,7 +818,7 @@ if __name__ == '__main__': if len(datasets) == 0: datasets = [ 'tox21', 'sider', 'muv', 'toxcast', 'pcba', 'clintox', 'hiv', 'sampl', 'delaney', 'nci', 'kaggle', 'pdbbind', 'chembl', 'qm7b' 'delaney', 'nci', 'kaggle', 'pdbbind', 'chembl', 'qm7b', 'qm9' ] #input hyperparameters Loading examples/qm9/__init__.py 0 → 100644 +0 −0 Empty file added. examples/qm9/qm9_datasets.py +3 −0 Original line number Diff line number Diff line Loading @@ -17,6 +17,9 @@ def load_qm9(featurizer=None, split='random'): print("About to featurize qm9 dataset.") current_dir = os.path.dirname(os.path.realpath(__file__)) dataset_file = os.path.join(current_dir, "./gdb9.sdf") if not os.path.exists(dataset_file): os.system('sh ' + current_dir + '/get_qm9.sh') qm9_tasks = [ "A", "B", "C", "mu", "alpha", "homo", "lumo", "gap", "r2", "zpve", "cv", "u0_atom", "u298_atom", "h298_atom", "g298_atom" Loading Loading
README.md +5 −1 Original line number Diff line number Diff line Loading @@ -353,6 +353,9 @@ Scaffold splitting |qm7b |MT-NN regression |Index |0.931 |0.803 | | |MT-NN regression |Random |0.923 |0.884 | | |MT-NN regression |Stratified |0.934 |0.884 | |qm9 |MT-NN regression |Index |0.733 |0.791 | | |MT-NN regression |Random |0.811 |0.823 | | |MT-NN regression |Stratified |0.843 |0.818 | |kaggle |MT-NN regression |User-defined|0.748 |0.452 | |Dataset |Model |Splitting |Train score/MAE(kcal/mol)|Valid score/MAE(kcal/mol)| Loading Loading @@ -385,7 +388,7 @@ Number of tasks and examples in the datasets |chembl(5thresh) |691 |23871 | |qm7 |1 |7165 | |qm7b |14 |7211 | |qm9 |15 |133885 | Time needed for benchmark test(~20h in total) Loading Loading @@ -442,6 +445,7 @@ Time needed for benchmark test(~20h in total) |chembl |MT-NN regression |200 |9000 | |qm7 |MT-NN regression |10 |400 | |qm7b |MT-NN regression |10 |600 | |qm9 |MT-NN regression |220 |10000 | |kaggle |MT-NN regression |2200 |3200 | Loading
examples/benchmark.py +16 −12 Original line number Diff line number Diff line Loading @@ -19,7 +19,7 @@ Giving regression performances of: Random forest(rf_regression), Graph convolution regression(graphconvreg) on datasets: delaney(ESOL), nci, kaggle, pdbbind, qm7, qm7b, chembl, sampl(FreeSolv) qm7, qm7b, qm9, chembl, sampl(FreeSolv) time estimation listed in README file Loading Loading @@ -52,6 +52,7 @@ from delaney.delaney_datasets import load_delaney from pdbbind.pdbbind_datasets import load_pdbbind_grid from chembl.chembl_datasets import load_chembl from qm7.qm7_datasets import load_qm7_from_mat, load_qm7b_from_mat from qm9.qm9_datasets import load_qm9 from sampl.sampl_datasets import load_sampl from clintox.clintox_datasets import load_clintox from hiv.hiv_datasets import load_hiv Loading @@ -74,7 +75,7 @@ def benchmark_loading_datasets(hyper_parameters, dataset: string, optional (default='tox21') choice of which dataset to use, should be: tox21, muv, sider, toxcast, pcba, delaney, kaggle, nci, clintox, hiv, pdbbind, chembl, qm7, qm7b, sampl qm7, qm7b, qm9, sampl model: string, optional (default='tf') choice of which model to use, should be: rf, tf, tf_robust, logreg, irv, graphconv, tf_regression, rf_regression, graphconvreg Loading @@ -87,7 +88,8 @@ def benchmark_loading_datasets(hyper_parameters, if dataset in ['muv', 'pcba', 'tox21', 'sider', 'toxcast', 'clintox', 'hiv']: mode = 'classification' elif dataset in [ 'kaggle', 'delaney', 'nci', 'pdbbind', 'chembl', 'qm7', 'qm7b', 'sampl' 'kaggle', 'delaney', 'nci', 'pdbbind', 'chembl', 'qm7', 'qm7b', 'qm9', 'sampl' ]: mode = 'regression' else: Loading Loading @@ -122,18 +124,18 @@ def benchmark_loading_datasets(hyper_parameters, if not model in ['tf_regression', 'rf_regression']: return if dataset in ['qm7']: featurizer = None # qm7 is already featurized if dataset in ['qm7', 'qm7b', 'qm9']: featurizer = None # qm7, qm7b, qm9 is already featurized if split in ['scaffold', 'butina']: return # qm7 accept index and random splitter return # qm7, qm7b, qm9 accept index and random splitter if not model in ['tf_regression']: return if split in ['year']: if not dataset in ['chembl']: return if split in ['indice', 'stratified']: if not dataset in ['qm7', 'qm7b']: if split in ['stratified']: if not dataset in ['qm7', 'qm7b', 'qm9']: return elif not split in [None, 'index', 'random', 'scaffold', 'butina']: raise ValueError('Splitter function not supported') Loading @@ -151,6 +153,7 @@ def benchmark_loading_datasets(hyper_parameters, 'chembl': load_chembl, 'qm7': load_qm7_from_mat, 'qm7b': load_qm7b_from_mat, 'qm9': load_qm9, 'sampl': load_sampl, 'clintox': load_clintox, 'hiv': load_hiv Loading @@ -171,14 +174,14 @@ def benchmark_loading_datasets(hyper_parameters, train_dataset, valid_dataset, test_dataset = all_dataset fit_transformers = [] if dataset in ['qm7', 'qm7b']: if dataset in ['qm7', 'qm7b', 'qm9']: fit_transformers = [dc.trans.CoulombFitTransformer(train_dataset)] time_finish_loading = time.time() # time_finish_loading-time_start is the time(s) used for dataset loading if dataset in ['kaggle', 'pdbbind']: n_features = train_dataset.get_data_shape()[0] elif dataset in ['qm7', 'qm7b']: elif dataset in ['qm7', 'qm7b', 'qm9']: n_features = list(train_dataset.get_data_shape()) # dataset has customized features Loading Loading @@ -788,7 +791,8 @@ if __name__ == '__main__': dest='dataset_args', default=[], help='Choice of dataset: tox21, sider, muv, toxcast, pcba, ' + 'kaggle, delaney, nci, pdbbind, chembl, sampl, qm7, qm7b, clintox, hiv') 'kaggle, delaney, nci, pdbbind, chembl, sampl, qm7, qm7b, qm9, clintox, hiv' ) parser.add_argument( '-t', action='store_true', Loading @@ -814,7 +818,7 @@ if __name__ == '__main__': if len(datasets) == 0: datasets = [ 'tox21', 'sider', 'muv', 'toxcast', 'pcba', 'clintox', 'hiv', 'sampl', 'delaney', 'nci', 'kaggle', 'pdbbind', 'chembl', 'qm7b' 'delaney', 'nci', 'kaggle', 'pdbbind', 'chembl', 'qm7b', 'qm9' ] #input hyperparameters Loading
examples/qm9/qm9_datasets.py +3 −0 Original line number Diff line number Diff line Loading @@ -17,6 +17,9 @@ def load_qm9(featurizer=None, split='random'): print("About to featurize qm9 dataset.") current_dir = os.path.dirname(os.path.realpath(__file__)) dataset_file = os.path.join(current_dir, "./gdb9.sdf") if not os.path.exists(dataset_file): os.system('sh ' + current_dir + '/get_qm9.sh') qm9_tasks = [ "A", "B", "C", "mu", "alpha", "homo", "lumo", "gap", "r2", "zpve", "cv", "u0_atom", "u298_atom", "h298_atom", "g298_atom" Loading
