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
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], [0,0,0,0,1,0],
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], [0,0,0,0,1,0],