def test_ill_add(self):
collector = OutputsCollector(n_devices=2)
foo = tf.zeros([2, 2])
bar = tf.zeros([42])
with self.assertRaisesRegexp(AssertionError, ""):
collector.add_to_collection(name=None, var=None)
with self.assertRaisesRegexp(AssertionError, ""):
collector.add_to_collection(name=None, var=bar)
with self.assertRaisesRegexp(ValueError, ""):
collector.add_to_collection(name=foo, var=bar,
average_over_devices=True)
collector.add_to_collection(name=foo, var=bar,
average_over_devices=True)
collector.add_to_collection(name=foo, var=bar,
average_over_devices=True)
def test_netout_single_device(self):
n_device = 1
collector = OutputsCollector(n_devices=n_device)
for idx in range(n_device):
with tf.name_scope('worker_%d' % idx):
image = tf.ones([2, 32, 32, 32, 1])
foo = tf.zeros([2, 2])
collector.add_to_collection(name='image',
var=image,
collection=NETORK_OUTPUT,
average_over_devices=False)
collector.add_to_collection(name='foo',
var=foo,
collection=NETORK_OUTPUT,
average_over_devices=False)
self.assertDictEqual(collector.output_vars,
{'image': image, 'foo': foo})
def test_netout_mutiple_device(self):
n_device = 4
collector = OutputsCollector(n_devices=n_device)
for idx in range(n_device):
with tf.name_scope('worker_%d' % idx):
image = tf.ones([2, 32, 32, 32, 1])
foo = tf.zeros([2, 2])
bar = tf.zeros([42])
collector.add_to_collection(name='image',
var=image,
collection=NETORK_OUTPUT,
average_over_devices=False)
collector.add_to_collection(name='foo',
var=foo,
collection=NETORK_OUTPUT,
average_over_devices=False)
collector.add_to_collection(name='bar',
var=bar,
collection=NETORK_OUTPUT,
average_over_devices=True)
self.assertEqual(
set(collector.output_vars),
{'image_1', 'image_3', 'image_2',
'image', 'foo_1', 'foo_2', 'foo_3', 'foo', 'bar'})
self.assertEqual(len(collector.output_vars['bar']), n_device)
collector.finalise_output_op()
self.assertIsInstance(collector.output_vars['bar'], tf.Tensor)
def test_add_to_single_device(self):
n_device = 1
collector = OutputsCollector(n_devices=n_device)
for idx in range(n_device):
with tf.name_scope('worker_%d' % idx):
image = tf.ones([2, 32, 32, 32, 1])
foo = tf.zeros([2, 2])
bar = tf.zeros([42])
collector.add_to_collection(name='image',
var=image,
average_over_devices=False)
collector.add_to_collection(name='foo',
var=foo,
average_over_devices=False)
collector.add_to_collection(name='bar',
var=bar,
collection=NETWORK_OUTPUT,
average_over_devices=False)
self.assertDictEqual(collector.variables(collection=CONSOLE),
{'image': image, 'foo': foo})
self.assertDictEqual(collector.variables(collection=NETWORK_OUTPUT),
{'bar': bar})