Adding in run-all-benchmarks file

"""

@author: Bharath Ramsundar 

"""

import os

import time

import sys

import pandas as pd

import numpy as np

import tempfile

from scipy.stats import truncnorm

from benchmark import benchmark_loading_datasets

np.random.seed(123)

base_dir = tempfile.mkdtemp()

out_path='.'

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

#datasets = ['muv', 'nci', 'tox21', 'sider', 'toxcast']

datasets = ['tox21']

hps = {}

hps['tf'] = [{'dropouts': [0.25], 'learning_rate': 0.001,

              'layer_sizes': [1000], 'batch_size': 50, 'nb_epoch': 10}]

hps['tf_robust'] = [{'dropouts': [0.5], 'bypass_dropouts': [0.5],

                     'learning_rate': 0.001,

                     'layer_sizes': [500], 'bypass_layer_sizes': [100],

                     'batch_size': 50, 'nb_epoch': 10}]

hps['logreg'] = [{'learning_rate': 0.001, 'penalty': 0.05, 

                  'penalty_type': 'l1', 'batch_size': 50, 'nb_epoch': 10}]

hps['graphconv'] = [{'learning_rate': 0.001, 'n_filters': 64,

                     'n_fully_connected_nodes': 128, 'batch_size': 50,

                     'nb_epoch': 10}]

for model in models:

  for dataset in datasets:

    print("Benchmarking %s on dataset %s" % (model, dataset))

    benchmark_loading_datasets(base_dir, hps, dataset_name=dataset,

                               model=model, reload=True,

                               verbosity='high', out_path=out_path)