Merge pull request #474 from ktaneishi/chembl_adme_fix (e745b56e) · Commits · 钟慕尧 / deepchem

examples/adme/run_benchmarks.py

+5 −4

Original line number	Diff line number	Diff line
		@@ -4,6 +4,7 @@
		from __future__ import print_function
		from __future__ import division
		from __future__ import unicode_literals
		from builtins import range

		import os
		import numpy as np
		@@ -23,13 +24,13 @@ LMBDA = 1e-4

		def retrieve_datasets():
		os.system(
		'wget %s' %
		'wget -c %s' %
		'https://s3-us-west-1.amazonaws.com/deep-crystal-california/az_logd.csv')
		os.system(
		'wget %s' %
		'wget -c %s' %
		'https://s3-us-west-1.amazonaws.com/deep-crystal-california/az_hppb.csv')
		os.system(
		'wget %s' %
		'wget -c %s' %
		'https://s3-us-west-1.amazonaws.com/deep-crystal-california/az_clearance.csv'
		)

		@@ -144,7 +145,7 @@ model, train, val, test, transformers = experiment(
		if MODEL == 'GraphConv':
		best_val_score = 0.0
		train_score = 0.0
		for l in xrange(0, MAX_EPOCH):
		for l in range(0, MAX_EPOCH):
		model.fit(train, nb_epoch=1)
		latest_train_score = model.evaluate(train, [metric],
		transformers)['mean-pearson_r2_score']

+1 −1

Original line number	Diff line number	Diff line
		@@ -29,7 +29,7 @@ graph_model = dc.nn.SequentialGraph(n_feat)
		graph_model.add(dc.nn.GraphConv(128, n_feat, activation='relu'))
		graph_model.add(dc.nn.BatchNormalization(epsilon=1e-5, mode=1))
		graph_model.add(dc.nn.GraphPool())
		graph_model.add(dc.nn.GraphConv(128, 64, activation='relu'))
		graph_model.add(dc.nn.GraphConv(128, 128, activation='relu'))
		graph_model.add(dc.nn.BatchNormalization(epsilon=1e-5, mode=1))
		graph_model.add(dc.nn.GraphPool())
		# Gather Projection