def __init__(self, root_path):
"""Initialize paths and loggers of the model."""
# Storage director of the model and its snapshots
self.root_path = root_path
self.model_path = os.path.join(self.root_path, self.Model_Filename)
utils.remove_if_exists(self.model_path)
# Set logging output...
for name in ["neon.util.persist"]:
dslogger = logging.getLogger(name)
dslogger.setLevel(40)
print 'Epochs: %d Batch-Size: %d' % (self.max_epochs, self.batch_size)
def __init__(self, root_path, lrate=0.01, batch_size=30, max_epochs=10):
"""Initialize paths and loggers of the model."""
# Storage director of the model and its snapshots
self.root_path = root_path
self.model_name = os.path.basename(self.root_path)
self.model_path = os.path.join(self.root_path, self.Model_Filename)
utils.remove_if_exists(self.model_path)
# Training settings
self.lrate = lrate
self.batch_size = batch_size
self.max_epochs = max_epochs
# Set logging output...
for name in ["neon.util.persist"]:
dslogger = logging.getLogger(name)
dslogger.setLevel(40)
print "[%s] Epochs: %d Batch-Size: %d" % (self.model_name, self.max_epochs, self.batch_size)
def __init__(self, root_path, lrate=0.01, batch_size=30, max_epochs=10):
"""Initialize paths and loggers of the model."""
# Storage director of the model and its snapshots
self.root_path = root_path
self.model_name = os.path.basename(self.root_path)
self.model_path = os.path.join(self.root_path, self.Model_Filename)
utils.remove_if_exists(self.model_path)
# Training settings
self.lrate = lrate
self.batch_size = batch_size
self.max_epochs = max_epochs
# Set logging output...
for name in ["neon.util.persist"]:
dslogger = logging.getLogger(name)
dslogger.setLevel(40)
print "[%s] Epochs: %d Batch-Size: %d" % (self.model_name, self.max_epochs, self.batch_size)
