def test(self):
from deepy.dataset import HeartScaleDataset
from deepy.conf import NetworkConfig
from deepy import NeuralLayer
import logging
logging.basicConfig(level=logging.INFO)
conf = NetworkConfig(input_size=13)
conf.layers = [NeuralLayer(10), NeuralLayer(5), NeuralLayer(1, 'linear')]
ff = NeuralRegressor(conf)
t = SGDTrainer(ff)
train_set = [(np.array([[1,2,3,4,5,6,7,8,9,10,11,12,13]]), np.array([[1,0]]))]
a = [HeartScaleDataset(single_target=True).train_set()]
b = [HeartScaleDataset(single_target=True).valid_set()]
for k in list(t.train(a, b)):
pass
print k
def __init__(self, input_dim, config=None, input_tensor=None):
logging.info(DEEPY_MESSAGE)
self.network_config = config if config else NetworkConfig()
self.input_dim = input_dim
self.input_tensor = input_tensor
self.parameter_count = 0
self.parameters = []
self.free_parameters = []
self.training_updates = []
self.updates = []
self.input_variables = []
self.target_variables = []
self.training_callbacks = []
self.testing_callbacks = []
self.epoch_callbacks = []
self.layers = []
self._hidden_outputs = []
self.training_monitors = []
self.testing_monitors = []
self.setup_variables()
self.train_logger = TrainLogger()
if self.network_config.layers:
self.stack(self.network_config.layers)
import time
import logging
import numpy as np
from deepy.layers.recurrent import RecurrentLayer, RecurrentNetwork
from deepy.conf import NetworkConfig, TrainerConfig
from deepy.utils.functions import FLOATX
from deepy import SGDTrainer
logging.basicConfig(level=logging.INFO)
if __name__ == '__main__':
net_conf = NetworkConfig(input_size=6)
net_conf.layers = [RecurrentLayer(size=10, activation='sigmoid', bptt=True)]
trainer_conf = TrainerConfig()
trainer_conf.learning_rate = 0.03
trainer_conf.weight_l2 = 0.0001
trainer_conf.hidden_l2 = 0.0001
trainer_conf.monitor_frequency = trainer_conf.validation_frequency = trainer_conf.test_frequency = 1
network = RecurrentNetwork(net_conf)
trainer = SGDTrainer(network)
data = np.array([[1,0,0,0,0,0],
[0,1,0,0,0,0],
[0,0,1,0,0,0],
[0,0,0,1,0,0],
import time
import logging
import numpy as np
from deepy.conf import NetworkConfig, TrainerConfig
from deepy.utils.functions import FLOATX
from deepy import NeuralLayer, SGDTrainer, AutoEncoder
logging.basicConfig(level=logging.INFO)
if __name__ == '__main__':
net_conf = NetworkConfig(input_size=6)
net_conf.layers = [NeuralLayer(3, 'sigmoid'), NeuralLayer(6, 'softmax')]
trainer_conf = TrainerConfig()
trainer_conf.learning_rate = 0.03
trainer_conf.weight_l2 = 0.0001
trainer_conf.hidden_l2 = 0.0001
trainer_conf.monitor_frequency = trainer_conf.validation_frequency = trainer_conf.test_frequency = 1000
network = AutoEncoder(net_conf)
trainer = SGDTrainer(network)
data = np.array([[1,0,0,0,0,0],
[0,1,0,0,0,0],
[0,0,1,0,0,0],
[0,0,0,1,0,0],
