fixing test failure and bug (024e587a) · Commits · 钟慕尧 / deepchem

deepchem/molnet/run_benchmark_low_data.py

+1 −1

Original line number	Diff line number	Diff line
		@@ -135,7 +135,7 @@ def run_benchmark_low_data(datasets,
		output_line = [dataset, str(split), mode, 'valid', i]
		for task in valid_score[i][0]:
		output_line.extend(
		[task.valid_score[i][0][task], valid_score[i][1][task]])
		[task, valid_score[i][0][task], valid_score[i][1][task]])
		output_line.extend(
		['time_for_running', time_finish_fitting - time_start_fitting])
		writer.writerow(output_line)

deepchem/molnet/tests/test_molnet.py

+9 −8

Original line number	Diff line number	Diff line
		@@ -10,6 +10,7 @@ import unittest
		import numpy as np
		import pandas as pd
		import deepchem as dc
		import tempfile
		import csv


		@@ -27,7 +28,7 @@ class TestMolnet(unittest.TestCase):
		datasets = ['delaney']
		model = 'graphconvreg'
		split = 'random'
		out_path = self.current_dir
		out_path = tempfile.mkdtemp()
		dc.molnet.run_benchmark(
		datasets, str(model), split=split, out_path=out_path)
		with open(os.path.join(out_path, 'results.csv'), 'r') as f:
		@@ -42,26 +43,26 @@ class TestMolnet(unittest.TestCase):
		def test_qm7_multitask(self):
		"""Tests molnet benchmarking on qm7 with multitask network."""
		datasets = ['qm7']
		model = 'tf_regression'
		model = 'tf_regressioni_ft'
		split = 'random'
		out_path = self.current_dir
		out_path = tempfile.mkdtemp()
		dc.molnet.run_benchmark(
		datasets, str(model), split=split, out_path=out_path)
		with open(os.path.join(out_path, 'results.csv'), 'r') as f:
		reader = csv.reader(f)
		for lastrow in reader:
		pass
		assert lastrow[-4] == model + '_ft'
		assert lastrow[-4] == model
		assert lastrow[-5] == 'valid'
		assert float(lastrow[-3]) > 0.95
		os.remove(os.path.join(out_path, 'results.csv'))

		def test_tox21_multitask(self):
		"""Tests molnet benchmarking on tox21 with multitask network."""
		datasets = ['tox21']
		def test_clintox_multitask(self):
		"""Tests molnet benchmarking on clintox with multitask network."""
		datasets = ['clintox']
		model = 'tf'
		split = 'random'
		out_path = self.current_dir
		out_path = tempfile.mkdtemp()
		dc.molnet.run_benchmark(
		datasets, str(model), split=split, out_path=out_path, test=True)
		with open(os.path.join(out_path, 'results.csv'), 'r') as f:

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