Merge pull request #1113 from nitinprakash96/master (281a1e05) · Commits · 钟慕尧 / deepchem

.travis.yml

+3 −1

Original line number	Diff line number	Diff line
		@@ -21,7 +21,9 @@ install:
		script:
		- nosetests --with-flaky -a '!slow' --with-timer --with-coverage --cover-package=deepchem
		-v deepchem --nologcapture
		- find ./deepchem \| grep .py$ \|xargs python -m doctest -v
		- if [ $TRAVIS_PYTHON_VERSION == '3.5']; then
		find ./deepchem \| grep .py$ \|xargs python -m doctest -v;
		fi
		- bash devtools/travis-ci/test_format_code.sh
		after_success:
		- echo $TRAVIS_SECURE_ENV_VARS

+1 −2

Original line number	Diff line number	Diff line
		"""
		Imports all submodules
		"""
		from __future__ import print_function
		from __future__ import division
		from __future__ import unicode_literals

+0 −1

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		"""
		Process an input dataset into a format suitable for machine learning.
		"""
		from __future__ import print_function
		from __future__ import division
		from __future__ import unicode_literals
		import os

+9 −10

Original line number	Diff line number	Diff line
		"""
		Contains wrapper class for datasets.
		"""
		from __future__ import print_function
		from __future__ import division
		from __future__ import unicode_literals
		import json
		@@ -200,9 +199,9 @@ class Dataset(object):

		>>> dataset = NumpyDataset(np.ones((2,2)))
		>>> for x, y, w, id in dataset.itersamples():
		... print(x, y, w, id)
		[1. 1.] [0.] [0.] 0
		[1. 1.] [0.] [0.] 1
		... print(x.tolist(), y.tolist(), w.tolist(), id)
		[1.0 1.0] [0.0] [0.0] 0
		[1.0 1.0] [0.0] [0.0] 1
		"""
		raise NotImplementedError()

		@@ -409,9 +408,9 @@ class NumpyDataset(Dataset):

		>>> dataset = NumpyDataset(np.ones((2,2)))
		>>> for x, y, w, id in dataset.itersamples():
		... print(x, y, w, id)
		[1. 1.] [0.] [0.] 0
		[1. 1.] [0.] [0.] 1
		... print(x.tolist(), y.tolist(), w.tolist(), id)
		[1.0 1.0] [0.0] [0.0] 0
		[1.0 1.0] [0.0] [0.0] 1
		"""
		n_samples = self._X.shape[0]
		return ((self._X[i], self._y[i], self._w[i], self._ids[i])
		@@ -889,9 +888,9 @@ class DiskDataset(Dataset):

		>>> dataset = DiskDataset.from_numpy(np.ones((2,2)), np.ones((2,1)), verbose=False)
		>>> for x, y, w, id in dataset.itersamples():
		... print(x, y, w, id)
		[1. 1.] [1.] [1.] 0
		[1. 1.] [1.] [1.] 1
		... print(x.tolist(), y.tolist(), w.tolist(), id)
		[1.0 1.0] [0.0] [0.0] 0
		[1.0 1.0] [0.0] [0.0] 1
		"""

		def iterate(dataset):

+9 −7

Original line number	Diff line number	Diff line
		"""
		Sample supports from datasets.
		"""
		from __future__ import print_function
		from __future__ import division
		from __future__ import unicode_literals

		import logging
		import time
		import numpy as np
		from deepchem.data import NumpyDataset

		logger = logging.getLogger(__name__)


		def remove_dead_examples(dataset):
		"""Removes compounds with no weight.
		@@ -133,7 +135,7 @@ def get_task_test(dataset, n_episodes, n_test, task, log_every_n=50):
		tests = []
		for episode in range(n_episodes):
		if episode % log_every_n == 0:
		print("Sampling test %d" % episode)
		logger.info("Sampling test %d" % episode)
		inds = ids[episode]
		X_batch = X_task[inds]
		y_batch = np.squeeze(y_task[inds, task])
		@@ -221,7 +223,7 @@ def get_task_support(dataset, n_episodes, n_pos, n_neg, task, log_every_n=50):
		supports = []
		for episode in range(n_episodes):
		if episode % log_every_n == 0:
		print("Sampling support %d" % episode)
		logger.info("Sampling support %d" % episode)
		# No replacement allowed for supports
		pos_ids = np.random.choice(len(pos_mols), (n_pos,), replace=False)
		neg_ids = np.random.choice(len(neg_mols), (n_neg,), replace=False)
		@@ -285,7 +287,7 @@ class EpisodeGenerator(object):
		self.task_num = 0
		self.trial_num = 0
		time_end = time.time()
		print("Constructing EpisodeGenerator took %s seconds" %
		logger.info("Constructing EpisodeGenerator took %s seconds" %
		str(time_end - time_start))

		def __iter__(self):