Commit 9277d100 authored by Bharath Ramsundar's avatar Bharath Ramsundar
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deepchem/molnet/__init__.py

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from deepchem.molnet.load_function.bace_datasets import load_bace_classification, load_bace_regression

from deepchem.molnet.load_function.bbbc_datasets import load_bbbc001, load_bbbc002

from deepchem.molnet.load_function.bbbp_datasets import load_bbbp

from deepchem.molnet.load_function.cell_counting_datasets import load_cell_counting

from deepchem.molnet.load_function.chembl_datasets import load_chembl

from deepchem.molnet.load_function.clearance_datasets import load_clearance

from deepchem.molnet.load_function.clintox_datasets import load_clintox

from deepchem.molnet.load_function.delaney_datasets import load_delaney

from deepchem.molnet.load_function.hiv_datasets import load_hiv

from deepchem.molnet.load_function.hopv_datasets import load_hopv

from deepchem.molnet.load_function.kaggle_datasets import load_kaggle

from deepchem.molnet.load_function.lipo_datasets import load_lipo

from deepchem.molnet.load_function.muv_datasets import load_muv

from deepchem.molnet.load_function.nci_datasets import load_nci

from deepchem.molnet.load_function.pcba_datasets import load_pcba, load_pcba_146, load_pcba_2475

from deepchem.molnet.load_function.pdbbind_datasets import load_pdbbind_grid, load_pdbbind

from deepchem.molnet.load_function.ppb_datasets import load_ppb

from deepchem.molnet.load_function.qm7_datasets import load_qm7

from deepchem.molnet.load_function.qm7_datasets import load_qm7_from_mat, load_qm7b_from_mat

from deepchem.molnet.load_function.qm8_datasets import load_qm8

from deepchem.molnet.load_function.qm9_datasets import load_qm9

from deepchem.molnet.load_function.sampl_datasets import load_sampl

from deepchem.molnet.load_function.sider_datasets import load_sider

from deepchem.molnet.load_function.sweetlead_datasets import load_sweet

from deepchem.molnet.load_function.tox21_datasets import load_tox21

from deepchem.molnet.load_function.toxcast_datasets import load_toxcast

from deepchem.molnet.load_function.uspto_datasets import load_uspto

from deepchem.molnet.load_function.uv_datasets import load_uv

from deepchem.molnet.load_function.factors_datasets import load_factors

from deepchem.molnet.load_function.kinase_datasets import load_kinase

from deepchem.molnet.load_function.thermosol_datasets import load_thermosol

from deepchem.molnet.load_function.hppb_datasets import load_hppb

from deepchem.molnet.load_function.chembl25_datasets import load_chembl25



from deepchem.molnet.dnasim import simulate_motif_density_localization

from deepchem.molnet.dnasim import simulate_motif_counting

from deepchem.molnet.dnasim import simple_motif_embedding

from deepchem.molnet.dnasim import motif_density

from deepchem.molnet.dnasim import simulate_single_motif_detection



from deepchem.molnet.run_benchmark import run_benchmark

#from deepchem.molnet.run_benchmark_low_data import run_benchmark_low_data

from deepchem.molnet import run_benchmark_models

deepchem/molnet/check_availability.py

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CheckFeaturizer = {

    ('bace_c', 'logreg'): ['ECFP', 1024],

    ('bace_c', 'tf'): ['ECFP', 1024],

    ('bace_c', 'tf_robust'): ['ECFP', 1024],

    ('bace_c', 'rf'): ['ECFP', 1024],

    ('bace_c', 'kernelsvm'): ['ECFP', 1024],

    ('bace_c', 'irv'): ['ECFP', 1024],

    ('bace_c', 'xgb'): ['ECFP', 1024],

    ('bace_c', 'graphconv'): ['GraphConv', 75],

    ('bace_c', 'dag'): ['GraphConv', 75],

    ('bace_c', 'weave'): ['Weave', 75],

    ('bace_c', 'textcnn'): ['Raw', None],

    ('bace_c', 'mpnn'): ['Weave', [75, 14]],

    ('bbbp', 'logreg'): ['ECFP', 1024],

    ('bbbp', 'tf'): ['ECFP', 1024],

    ('bbbp', 'tf_robust'): ['ECFP', 1024],

    ('bbbp', 'rf'): ['ECFP', 1024],

    ('bbbp', 'kernelsvm'): ['ECFP', 1024],

    ('bbbp', 'irv'): ['ECFP', 1024],

    ('bbbp', 'xgb'): ['ECFP', 1024],

    ('bbbp', 'graphconv'): ['GraphConv', 75],

    ('bbbp', 'dag'): ['GraphConv', 75],

    ('bbbp', 'weave'): ['Weave', 75],

    ('bbbp', 'textcnn'): ['Raw', None],

    ('bbbp', 'mpnn'): ['Weave', [75, 14]],

    ('clintox', 'logreg'): ['ECFP', 1024],

    ('clintox', 'tf'): ['ECFP', 1024],

    ('clintox', 'tf_robust'): ['ECFP', 1024],

    ('clintox', 'rf'): ['ECFP', 1024],

    ('clintox', 'kernelsvm'): ['ECFP', 1024],

    ('clintox', 'irv'): ['ECFP', 1024],

    ('clintox', 'xgb'): ['ECFP', 1024],

    ('clintox', 'graphconv'): ['GraphConv', 75],

    ('clintox', 'dag'): ['GraphConv', 75],

    ('clintox', 'weave'): ['Weave', 75],

    ('clintox', 'textcnn'): ['Raw', None],

    ('clintox', 'mpnn'): ['Weave', [75, 14]],

    ('hiv', 'logreg'): ['ECFP', 1024],

    ('hiv', 'tf'): ['ECFP', 1024],

    ('hiv', 'tf_robust'): ['ECFP', 1024],

    ('hiv', 'rf'): ['ECFP', 1024],

    ('hiv', 'kernelsvm'): ['ECFP', 1024],

    ('hiv', 'irv'): ['ECFP', 1024],

    ('hiv', 'xgb'): ['ECFP', 1024],

    ('hiv', 'graphconv'): ['GraphConv', 75],

    ('hiv', 'dag'): ['GraphConv', 75],

    ('hiv', 'weave'): ['Weave', 75],

    ('hiv', 'textcnn'): ['Raw', None],

    ('hiv', 'mpnn'): ['Weave', [75, 14]],

    ('muv', 'logreg'): ['ECFP', 1024],

    ('muv', 'tf'): ['ECFP', 1024],

    ('muv', 'tf_robust'): ['ECFP', 1024],

    ('muv', 'rf'): ['ECFP', 1024],

    ('muv', 'kernelsvm'): ['ECFP', 1024],

    ('muv', 'irv'): ['ECFP', 1024],

    ('muv', 'xgb'): ['ECFP', 1024],

    ('muv', 'graphconv'): ['GraphConv', 75],

    ('muv', 'siamese'): ['GraphConv', 75],

    ('muv', 'attn'): ['GraphConv', 75],

    ('muv', 'res'): ['GraphConv', 75],

    ('muv', 'weave'): ['Weave', 75],

    ('muv', 'textcnn'): ['Raw', None],

    ('muv', 'mpnn'): ['Weave', [75, 14]],

    ('pcba', 'logreg'): ['ECFP', 1024],

    ('pcba', 'tf'): ['ECFP', 1024],

    ('pcba', 'tf_robust'): ['ECFP', 1024],

    ('pcba', 'irv'): ['ECFP', 1024],

    ('pcba', 'xgb'): ['ECFP', 1024],

    ('pcba', 'graphconv'): ['GraphConv', 75],

    ('pcba', 'weave'): ['Weave', 75],

    ('pcba', 'textcnn'): ['Raw', None],

    ('pcba_146', 'logreg'): ['ECFP', 1024],

    ('pcba_146', 'tf'): ['ECFP', 1024],

    ('pcba_146', 'tf_robust'): ['ECFP', 1024],

    ('pcba_146', 'irv'): ['ECFP', 1024],

    ('pcba_146', 'xgb'): ['ECFP', 1024],

    ('pcba_146', 'graphconv'): ['GraphConv', 75],

    ('pcba_146', 'weave'): ['Weave', 75],

    ('pcba_2475', 'logreg'): ['ECFP', 1024],

    ('pcba_2475', 'tf'): ['ECFP', 1024],

    ('pcba_2475', 'tf_robust'): ['ECFP', 1024],

    ('pcba_2475', 'irv'): ['ECFP', 1024],

    ('pcba_2475', 'xgb'): ['ECFP', 1024],

    ('pcba_2475', 'graphconv'): ['GraphConv', 75],

    ('pcba_2475', 'weave'): ['Weave', 75],

    ('sider', 'logreg'): ['ECFP', 1024],

    ('sider', 'tf'): ['ECFP', 1024],

    ('sider', 'tf_robust'): ['ECFP', 1024],

    ('sider', 'rf'): ['ECFP', 1024],

    ('sider', 'kernelsvm'): ['ECFP', 1024],

    ('sider', 'irv'): ['ECFP', 1024],

    ('sider', 'xgb'): ['ECFP', 1024],

    ('sider', 'graphconv'): ['GraphConv', 75],

    ('sider', 'dag'): ['GraphConv', 75],

    ('sider', 'weave'): ['Weave', 75],

    ('sider', 'siamese'): ['GraphConv', 75],

    ('sider', 'attn'): ['GraphConv', 75],

    ('sider', 'res'): ['GraphConv', 75],

    ('sider', 'textcnn'): ['Raw', None],

    ('sider', 'mpnn'): ['Weave', [75, 14]],

    ('tox21', 'logreg'): ['ECFP', 1024],

    ('tox21', 'tf'): ['ECFP', 1024],

    ('tox21', 'tf_robust'): ['ECFP', 1024],

    ('tox21', 'rf'): ['ECFP', 1024],

    ('tox21', 'kernelsvm'): ['ECFP', 1024],

    ('tox21', 'irv'): ['ECFP', 1024],

    ('tox21', 'xgb'): ['ECFP', 1024],

    ('tox21', 'graphconv'): ['GraphConv', 75],

    ('tox21', 'dag'): ['GraphConv', 75],

    ('tox21', 'weave'): ['Weave', 75],

    ('tox21', 'siamese'): ['GraphConv', 75],

    ('tox21', 'attn'): ['GraphConv', 75],

    ('tox21', 'res'): ['GraphConv', 75],

    ('tox21', 'textcnn'): ['Raw', None],

    ('tox21', 'mpnn'): ['Weave', [75, 14]],

    ('toxcast', 'logreg'): ['ECFP', 1024],

    ('toxcast', 'tf'): ['ECFP', 1024],

    ('toxcast', 'tf_robust'): ['ECFP', 1024],

    ('toxcast', 'rf'): ['ECFP', 1024],

    ('toxcast', 'kernelsvm'): ['ECFP', 1024],

    ('toxcast', 'irv'): ['ECFP', 1024],

    ('toxcast', 'xgb'): ['ECFP', 1024],

    ('toxcast', 'graphconv'): ['GraphConv', 75],

    ('toxcast', 'weave'): ['Weave', 75],

    ('toxcast', 'textcnn'): ['Raw', None],

    ('toxcast', 'mpnn'): ['Weave', [75, 14]],

    ('bace_r', 'tf_regression'): ['ECFP', 1024],

    ('bace_r', 'rf_regression'): ['ECFP', 1024],

    ('bace_r', 'krr'): ['ECFP', 1024],

    ('bace_r', 'xgb_regression'): ['ECFP', 1024],

    ('bace_r', 'graphconvreg'): ['GraphConv', 75],

    ('bace_r', 'dag_regression'): ['GraphConv', 75],

    ('bace_r', 'weave_regression'): ['Weave', 75],

    ('bace_r', 'textcnn_regression'): ['Raw', None],

    ('chembl', 'tf_regression'): ['ECFP', 1024],

    ('chembl', 'rf_regression'): ['ECFP', 1024],

    ('chembl', 'krr'): ['ECFP', 1024],

    ('chembl', 'xgb_regression'): ['ECFP', 1024],

    ('chembl', 'graphconvreg'): ['GraphConv', 75],

    ('chembl', 'weave_regression'): ['Weave', 75],

    ('clearance', 'tf_regression'): ['ECFP', 1024],

    ('clearance', 'rf_regression'): ['ECFP', 1024],

    ('clearance', 'krr'): ['ECFP', 1024],

    ('clearance', 'xgb_regression'): ['ECFP', 1024],

    ('clearance', 'graphconvreg'): ['GraphConv', 75],

    ('clearance', 'dag_regression'): ['GraphConv', 75],

    ('clearance', 'weave_regression'): ['Weave', 75],

    ('delaney', 'tf_regression'): ['ECFP', 1024],

    ('delaney', 'rf_regression'): ['ECFP', 1024],

    ('delaney', 'krr'): ['ECFP', 1024],

    ('delaney', 'xgb_regression'): ['ECFP', 1024],

    ('delaney', 'graphconvreg'): ['GraphConv', 75],

    ('delaney', 'dag_regression'): ['GraphConv', 75],

    ('delaney', 'weave_regression'): ['Weave', 75],

    ('delaney', 'mpnn'): ['Weave', [75, 14]],

    ('delaney', 'textcnn_regression'): ['Raw', None],

    ('hopv', 'tf_regression'): ['ECFP', 1024],

    ('hopv', 'rf_regression'): ['ECFP', 1024],

    ('hopv', 'krr'): ['ECFP', 1024],

    ('hopv', 'xgb_regression'): ['ECFP', 1024],

    ('hopv', 'graphconvreg'): ['GraphConv', 75],

    ('hopv', 'dag_regression'): ['GraphConv', 75],

    ('hopv', 'weave_regression'): ['Weave', 75],

    ('lipo', 'tf_regression'): ['ECFP', 1024],

    ('lipo', 'rf_regression'): ['ECFP', 1024],

    ('lipo', 'krr'): ['ECFP', 1024],

    ('lipo', 'xgb_regression'): ['ECFP', 1024],

    ('lipo', 'graphconvreg'): ['GraphConv', 75],

    ('lipo', 'dag_regression'): ['GraphConv', 75],

    ('lipo', 'weave_regression'): ['Weave', 75],

    ('lipo', 'mpnn'): ['Weave', [75, 14]],

    ('lipo', 'textcnn_regression'): ['Raw', None],

    ('nci', 'tf_regression'): ['ECFP', 1024],

    ('nci', 'rf_regression'): ['ECFP', 1024],

    ('nci', 'krr'): ['ECFP', 1024],

    ('nci', 'xgb_regression'): ['ECFP', 1024],

    ('nci', 'graphconvreg'): ['GraphConv', 75],

    ('nci', 'weave_regression'): ['Weave', 75],

    ('ppb', 'tf_regression'): ['ECFP', 1024],

    ('ppb', 'rf_regression'): ['ECFP', 1024],

    ('ppb', 'krr'): ['ECFP', 1024],

    ('ppb', 'xgb_regression'): ['ECFP', 1024],

    ('ppb', 'graphconvreg'): ['GraphConv', 75],

    ('ppb', 'dag_regression'): ['GraphConv', 75],

    ('ppb', 'weave_regression'): ['Weave', 75],

    ('sampl', 'tf_regression'): ['ECFP', 1024],

    ('sampl', 'rf_regression'): ['ECFP', 1024],

    ('sampl', 'krr'): ['ECFP', 1024],

    ('sampl', 'xgb_regression'): ['ECFP', 1024],

    ('sampl', 'graphconvreg'): ['GraphConv', 75],

    ('sampl', 'dag_regression'): ['GraphConv', 75],

    ('sampl', 'weave_regression'): ['Weave', 75],

    ('sampl', 'mpnn'): ['Weave', [75, 14]],

    ('sampl', 'textcnn_regression'): ['Raw', None],

    ('kaggle', 'tf_regression'): [None, 14293],

    ('kaggle', 'rf_regression'): [None, 14293],

    ('kaggle', 'krr'): [None, 14293],

    ('pdbbind', 'tf_regression'): ['grid', 2052],

    ('pdbbind', 'rf_regression'): ['grid', 2052],

    ('pdbbind', 'krr'): ['grid', 2052],

    ('pdbbind', 'graphconvreg'): ['GraphConv', 75],

    ('qm7', 'tf_regression'): ['ECFP', 1024],

    ('qm7', 'rf_regression'): ['ECFP', 1024],

    ('qm7', 'krr'): ['ECFP', 1024],

    ('qm7', 'krr_ft'): ['CoulombMatrix', 1024],

    ('qm7', 'textcnn_regression'): ['Raw', None],

    ('qm7', 'graphconvreg'): ['GraphConv', 75],

    ('qm7', 'weave_regression'): ['Weave', 75],

    ('qm7', 'tf_regression_ft'): ['CoulombMatrix', [23, 23]],

    ('qm7', 'dtnn'): ['CoulombMatrix', [23, 23]],

    ('qm7', 'ani'): ['BPSymmetryFunctionInput', [23, 4]],

    ('qm7b', 'tf_regression_ft'): ['CoulombMatrix', [23, 23]],

    ('qm7b', 'krr_ft'): ['CoulombMatrix', 1024],

    ('qm7b', 'dtnn'): ['CoulombMatrix', [23, 23]],

    ('qm8', 'tf_regression'): ['ECFP', 1024],

    ('qm8', 'rf_regression'): ['ECFP', 1024],

    ('qm8', 'krr'): ['ECFP', 1024],

    ('qm8', 'graphconvreg'): ['GraphConv', 75],

    ('qm8', 'tf_regression_ft'): ['CoulombMatrix', [26, 26]],

    ('qm8', 'krr_ft'): ['CoulombMatrix', 1024],

    ('qm8', 'dtnn'): ['CoulombMatrix', [26, 26]],

    ('qm8', 'ani'): ['BPSymmetryFunctionInput', [26, 4]],

    ('qm8', 'mpnn'): ['MP', [70, 8]],

    ('qm8', 'weave_regression'): ['Weave', 75],

    ('qm8', 'textcnn_regression'): ['Raw', None],

    ('qm9', 'tf_regression'): ['ECFP', 1024],

    ('qm9', 'rf_regression'): ['ECFP', 1024],

    ('qm9', 'krr'): ['ECFP', 1024],

    ('qm9', 'graphconvreg'): ['GraphConv', 75],

    ('qm9', 'tf_regression_ft'): ['CoulombMatrix', [29, 29]],

    ('qm9', 'krr_ft'): ['CoulombMatrix', 1024],

    ('qm9', 'dtnn'): ['CoulombMatrix', [29, 29]],

    ('qm9', 'ani'): ['BPSymmetryFunctionInput', [29, 4]],

    ('qm9', 'mpnn'): ['MP', [70, 8]],

    ('qm9', 'weave_regression'): ['Weave', 75],

    ('qm9', 'textcnn_regression'): ['Raw', None]

}



CheckSplit = {

    'bace_c': ['random', 'scaffold'],

    'bace_r': ['random', 'scaffold'],

    'bbbp': ['random', 'scaffold'],

    'chembl': ['index', 'random', 'scaffold', 'year'],

    'clearance': ['index', 'random', 'scaffold'],

    'clintox': ['index', 'random', 'scaffold'],

    'delaney': ['index', 'random', 'scaffold'],

    'hiv': ['index', 'random', 'scaffold', 'butina'],

    'hopv': ['index', 'random', 'scaffold', 'butina'],

    'kaggle': ['index'],  # already splitted, no splitter required

    'lipo': ['index', 'random', 'scaffold'],

    'muv': ['index', 'random', 'scaffold', 'task'],

    'nci': ['index', 'random', 'scaffold'],

    'pcba': ['index', 'random', 'scaffold'],

    'pcba_146': ['index', 'random', 'scaffold'],

    'pcba_2475': ['index', 'random', 'scaffold'],

    'pdbbind': ['index', 'random', 'time'],

    'ppb': ['index', 'random', 'scaffold'],

    'qm7': ['index', 'random', 'stratified'],

    'qm7b': ['index', 'random', 'stratified'],

    'qm8': ['index', 'random', 'stratified'],

    'qm9': ['index', 'random', 'stratified'],

    'sampl': ['index', 'random', 'scaffold'],

    'sider': ['index', 'random', 'scaffold', 'task'],

    'tox21': ['index', 'random', 'scaffold', 'butina', 'task'],

    'toxcast': ['index', 'random', 'scaffold']

}

deepchem/molnet/dnasim.py

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deepchem/molnet/preset_hyper_parameters.py

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#!/usr/bin/env python2

# -*- coding: utf-8 -*-

"""

Created on Tue Mar  7 00:07:10 2017



@author: zqwu

"""

import deepchem



hps = {}

hps['tf'] = {

    'layer_sizes': [1500],

    'weight_init_stddevs': [0.02],

    'bias_init_consts': [1.],

    'dropouts': [0.5],

    'penalty': 0.1,

    'penalty_type': 'l2',

    'batch_size': 50,

    'nb_epoch': 10,

    'learning_rate': 0.001

}



hps['tf_robust'] = {

    'layer_sizes': [1500],

    'weight_init_stddevs': [0.02],

    'bias_init_consts': [1.],

    'dropouts': [0.5],

    'bypass_layer_sizes': [200],

    'bypass_weight_init_stddevs': [0.02],

    'bypass_bias_init_consts': [1.],

    'bypass_dropouts': [0.5],

    'penalty': 0.1,

    'penalty_type': 'l2',

    'batch_size': 50,

    'nb_epoch': 10,

    'learning_rate': 0.0005

}

hps['logreg'] = {

    'penalty': 1.,

    'penalty_type': 'l2',

}

hps['irv'] = {

    'penalty': 0.,

    'batch_size': 50,

    'nb_epoch': 10,

    'learning_rate': 0.001,

    'n_K': 10

}

hps['graphconv'] = {

    'batch_size': 64,

    'nb_epoch': 40,

    'learning_rate': 0.0005,

    'n_filters': 64,

    'n_fully_connected_nodes': 128,

    'seed': 123

}

hps['dag'] = {

    'batch_size': 64,

    'nb_epoch': 50,

    'learning_rate': 0.0005,

    'n_graph_feat': 30,

    'default_max_atoms': 60,

    'seed': 123

}

hps['weave'] = {

    'batch_size': 64,

    'nb_epoch': 40,

    'learning_rate': 0.0005,

    'n_graph_feat': 128,

    'n_pair_feat': 14,

    'seed': 123

}

hps['textcnn'] = {

    'batch_size': 64,

    'nb_epoch': 40,

    'learning_rate': 0.0005,

    'n_embedding': 75,

    'filter_sizes': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20],

    'num_filters': [100, 200, 200, 200, 200, 100, 100, 100, 100, 100, 160, 160],

    'seed': 123

}

hps['rf'] = {'n_estimators': 500}

hps['kernelsvm'] = {'C': 1.0, 'gamma': 0.05}

hps['xgb'] = {

    'max_depth': 5,

    'learning_rate': 0.05,

    'n_estimators': 3000,

    'gamma': 0.,

    'min_child_weight': 5,

    'max_delta_step': 1,

    'subsample': 0.53,

    'colsample_bytree': 0.66,

    'colsample_bylevel': 1,

    'reg_alpha': 0,

    'reg_lambda': 1,

    'scale_pos_weight': 1,

    'base_score': 0.5,

    'seed': 2016,

    'early_stopping_rounds': 100

}



hps['tf_regression'] = {

    'layer_sizes': [1000, 1000],

    'weight_init_stddevs': [0.02, 0.02],

    'bias_init_consts': [1., 1.],

    'dropouts': [0.25, 0.25],

    'penalty': 0.0005,

    'penalty_type': 'l2',

    'batch_size': 128,

    'nb_epoch': 50,

    'learning_rate': 0.0008

}

hps['tf_regression_ft'] = {

    'layer_sizes': [400, 100, 100],

    'weight_init_stddevs': [0.05, 0.1, 0.1],

    'bias_init_consts': [0., 0., 0.],

    'dropouts': [0.01, 0.01, 0.01],

    'penalty': 0.,

    'penalty_type': 'l2',

    'batch_size': 25,

    'nb_epoch': 50,

    'learning_rate': 0.001,

    'fit_transformers': deepchem.trans.CoulombFitTransformer

}

hps['rf_regression'] = {'n_estimators': 500}

hps['krr'] = {'alpha': 1e-3}

hps['krr_ft'] = {'alpha': 1e-3}

hps['graphconvreg'] = {

    'batch_size': 128,

    'nb_epoch': 100,

    'learning_rate': 0.0005,

    'n_filters': 128,

    'n_fully_connected_nodes': 256,

    'seed': 123

}

hps['dtnn'] = {

    'batch_size': 64,

    'nb_epoch': 100,

    'learning_rate': 0.001,

    'n_embedding': 50,

    'n_distance': 170,

    'seed': 123

}

hps['dag_regression'] = {

    'batch_size': 64,

    'nb_epoch': 100,

    'learning_rate': 0.0005,

    'n_graph_feat': 30,

    'default_max_atoms': 60,

    'seed': 123

}

hps['weave_regression'] = {

    'batch_size': 64,

    'nb_epoch': 100,

    'learning_rate': 0.0005,

    'n_graph_feat': 128,

    'n_pair_feat': 14,

    'seed': 123

}

hps['textcnn_regression'] = {

    'batch_size': 64,

    'nb_epoch': 100,

    'learning_rate': 0.0005,

    'n_embedding': 75,

    'filter_sizes': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20],

    'num_filters': [100, 200, 200, 200, 200, 100, 100, 100, 100, 100, 160, 160],

    'seed': 123

}

hps['ani'] = {

    'batch_size': 32,

    'nb_epoch': 100,

    'learning_rate': 0.00005,

    'layer_structures': [20, 10, 10],

    'seed': 123

}

hps['mpnn'] = {

    'batch_size': 16,

    'nb_epoch': 50,

    'learning_rate': 0.001,

    'T': 2,

    'M': 5,

    'seed': 123

}



hps['xgb_regression'] = {

    'max_depth': 5,

    'learning_rate': 0.05,

    'n_estimators': 3000,

    'gamma': 0.,

    'min_child_weight': 5,

    'max_delta_step': 1,

    'subsample': 0.53,

    'colsample_bytree': 0.66,

    'colsample_bylevel': 1,

    'reg_alpha': 0,

    'reg_lambda': 1,

    'scale_pos_weight': 1,

    'base_score': 0.5,

    'seed': 2016,

    'early_stopping_rounds': 100

}



hps['siamese'] = {

    'n_pos': 1,

    'n_neg': 1,

    'test_batch_size': 128,

    'n_filters': [64, 128, 64],

    'n_fully_connected_nodes': [128],

    'nb_epochs': 1,

    'n_train_trials': 2000,

    'n_eval_trials': 20,

    'learning_rate': 1e-4

}

hps['res'] = {

    'n_pos': 1,

    'n_neg': 1,

    'test_batch_size': 128,

    'n_filters': [64, 128, 64],

    'n_fully_connected_nodes': [128],

    'max_depth': 3,

    'nb_epochs': 1,

    'n_train_trials': 2000,

    'n_eval_trials': 20,

    'learning_rate': 1e-4

}

hps['attn'] = {

    'n_pos': 1,

    'n_neg': 1,

    'test_batch_size': 128,

    'n_filters': [64, 128, 64],

    'n_fully_connected_nodes': [128],

    'max_depth': 3,

    'nb_epochs': 1,

    'n_train_trials': 2000,

    'n_eval_trials': 20,

    'learning_rate': 1e-4

}

deepchem/molnet/run_benchmark.py

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