def __init__(self, link, epoch=10, batch_size=100, visualize=False):
ChainList.__init__(self, link)
self.optimizer = optimizers.AdaDelta()
self.optimizer.setup(self)
self.loss_function = F.mean_squared_error
self.epoch = epoch
self.batch_size = batch_size
self.visualize = visualize
def __init__(self, link, epoch=20, batch_size=100, visualize=True):
ChainList.__init__(self, link)
self.optimizer = optimizers.AdaDelta()
self.optimizer.setup(self)
self.loss_function = F.mean_squared_error
self.epoch = epoch
self.batch_size = batch_size
self.visualize = visualize
def __construct(self):
"""
Instead of __init.
For correspond to gridsearchCV.
"""
self.last_unit = self.n_units[-1]
self.n_units = self.n_units[0:-1]
self.total_layer = len(self.n_units)
ChainList.__init__(self)
self.__collect_child_model()
self.optimizer.setup(self)
self.__constructed = True
def __init__(self, n_units, epoch=10, batch_size=20, visualize=True, is_classification=True, **keywords):
ChainList.__init__(self)
self.n_units = n_units[0:-1]
self.last_unit = n_units[-1]
self.total_layer = len(n_units)
self.set_optimizer()
self.epoch = epoch
self.batch_size = batch_size
self.visualize = visualize
self.is_classification = is_classification
self.pre_trained = False
if 'nobias' in keywords.keys():
self.nobias = keywords['nobias']
else:
self.nobias = False
self.keywords = keywords
self.collect_child_model()
def __init__(self,
n_units,
epoch=10,
batch_size=20,
visualize=True,
is_classification=True,
**keywords):
ChainList.__init__(self)
self.n_units = n_units[0:-1]
self.last_unit = n_units[-1]
self.total_layer = len(n_units)
self.set_optimizer()
self.epoch = epoch
self.batch_size = batch_size
self.visualize = visualize
self.is_classification = is_classification
self.pre_trained = False
if 'nobias' in keywords.keys():
self.nobias = keywords['nobias']
else:
self.nobias = False
self.keywords = keywords
self.collect_child_model()
