本文整理汇总了Python中pylearn2.utils.serial.to_string函数的典型用法代码示例。如果您正苦于以下问题:Python to_string函数的具体用法?Python to_string怎么用?Python to_string使用的例子?那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了to_string函数的6个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_save_load_save
def test_save_load_save():
"""
Test that a monitor can be saved, then loaded, and then the loaded
copy can be saved again.
This only tests that the serialization and deserialization processes
don't raise an exception. It doesn't test for correctness at all.
"""
model = DummyModel(1)
monitor = Monitor.get_monitor(model)
num_examples = 2
num_features = 3
num_batches = 1
batch_size = 2
dataset = DummyDataset(num_examples, num_features)
monitor.add_dataset(dataset=dataset,
num_batches=num_batches, batch_size=batch_size)
vis_batch = T.matrix()
mean = vis_batch.mean()
data_specs = (monitor.model.get_input_space(),
monitor.model.get_input_source())
monitor.add_channel(name='mean', ipt=vis_batch, val=mean, dataset=dataset,
data_specs=data_specs)
saved = to_string(monitor)
monitor = from_string(saved)
saved_again = to_string(monitor)
示例2: test_deserialize
def test_deserialize():
# Test that a monitor can be deserialized
model = DummyModel(1)
monitor = Monitor.get_monitor(model)
x = to_string(monitor)
monitor = from_string(x)
y = to_string(monitor)
示例3: test_serialize_twice
def test_serialize_twice():
# Test that a monitor can be serialized twice
# with the same result
model = DummyModel(1)
monitor = Monitor.get_monitor(model)
x = to_string(monitor)
y = to_string(monitor)
assert x == y
示例4: test_prereqs_multidataset
def test_prereqs_multidataset():
# Test that prereqs are run on the right datasets
NUM_DATASETS = 4
NUM_FEATURES = 3
model = DummyModel(NUM_FEATURES)
monitor = Monitor.get_monitor(model)
prereq_counters = []
datasets = []
for i in xrange(NUM_DATASETS):
batch_size = i + 1
num_examples = batch_size
dataset = DummyDataset(num_examples = num_examples,
num_features = NUM_FEATURES)
dataset.X[:] = i
datasets.append(dataset)
monitor.add_dataset(dataset, 'sequential', batch_size=batch_size)
prereq_counters.append(sharedX(0.))
channels = []
for i in xrange(NUM_DATASETS):
monitor.add_channel(name = str(i),
ipt = model.input_space.make_theano_batch(),
val = prereq_counters[i],
dataset = datasets[i],
prereqs = [ ReadVerifyPrereq(i, prereq_counters[i]) ],
data_specs=(model.get_input_space(), model.get_input_source()))
channels.append(monitor.channels[str(i)])
for channel in channels:
assert len(channel.val_record) == 0
monitor()
for channel in channels:
assert channel.val_record == [1]
monitor()
for channel in channels:
assert channel.val_record == [1,2]
# check that handling all these datasets did not
# result in them getting serialized
to_string(monitor)
示例5: test_valid_after_serialize
def test_valid_after_serialize():
# Test that serializing the monitor does not ruin it
BATCH_SIZE = 2
num_examples = 2 * BATCH_SIZE
NUM_FEATURES = 3
model = DummyModel(NUM_FEATURES)
monitor = Monitor.get_monitor(model)
monitoring_dataset = DummyDataset(num_examples=num_examples, num_features=NUM_FEATURES)
monitoring_dataset.yaml_src = ""
monitor.add_dataset(monitoring_dataset, "sequential", batch_size=BATCH_SIZE)
to_string(monitor)
monitor.redo_theano()
示例6: test_dont_serialize_dataset
def test_dont_serialize_dataset():
# Test that serializing the monitor does not serialize the dataset
BATCH_SIZE = 2
num_examples = 2 * BATCH_SIZE
NUM_FEATURES = 3
model = DummyModel(NUM_FEATURES)
monitor = Monitor.get_monitor(model)
monitoring_dataset = DummyDataset(num_examples = num_examples,
num_features = NUM_FEATURES)
monitoring_dataset.yaml_src = ""
monitor.add_dataset(monitoring_dataset, 'sequential', batch_size=BATCH_SIZE)
monitor()
to_string(monitor)