dropout_rate=0,
activation=activation.tanh),
#MaxPool(size=2, stride=2),
ConvToFullyConnected(),
FullyConnected(size=64, activation=activation.tanh),
FullyConnected(size=10, activation=None, last_layer=True)
]
# -------------------------------------------------------
# Train with BP
# -------------------------------------------------------
model = Model(
layers=layers,
num_classes=10,
optimizer=GDMomentumOptimizer(lr=3 * 1e-2, mu=0.9),
)
print("\nRun training:\n------------------------------------")
stats = model.train(data_set=data,
method='bp',
num_passes=num_iteration,
batch_size=64)
loss, accuracy = model.cost(*data.test_set())
print("\nResult:\n------------------------------------")
print('loss on test set: {}'.format(loss))
print('accuracy on test set: {}'.format(accuracy))
print("\nTrain statisistics:\n------------------------------------")
MaxPool(size=2, stride=2),
Convolution((8, 3, 3, 3), stride=1, padding=1, dropout_rate=0, activation=activation.tanh, weight_initializer=initializer[0]),
MaxPool(size=2, stride=2),
Convolution((16, 8, 3, 3), stride=1, padding=1, dropout_rate=0, activation=activation.tanh, weight_initializer=initializer[1]),
MaxPool(size=2, stride=2),
Convolution((32, 16, 3, 3), stride=1, padding=1, dropout_rate=0, activation=activation.tanh, weight_initializer=initializer[2]),
MaxPool(size=2, stride=2),
ConvToFullyConnected(),
FullyConnected(size=64, activation=activation.tanh),
FullyConnected(size=10, activation=None, last_layer=True)
]
model = Model(
layers=layers,
num_classes=10,
optimizer=GDMomentumOptimizer(lr=1e-3, mu=0.9),
)
print("\n\n------------------------------------")
print("Initialize: {}".format(initializer))
print("\nRun training:\n------------------------------------")
stats = model.train(data_set=data, method='dfa', num_passes=num_passes, batch_size=50)
loss, accuracy = model.cost(*data.test_set())
print("\nResult:\n------------------------------------")
print('loss on test set: {}'.format(loss))
print('accuracy on test set: {}'.format(accuracy))
FullyConnected(size=num_hidden_units,
activation=activation.tanh,
fb_weight_initializer=initializer),
FullyConnected(size=num_hidden_units,
activation=activation.tanh,
fb_weight_initializer=initializer),
FullyConnected(size=num_hidden_units,
activation=activation.tanh,
fb_weight_initializer=initializer),
FullyConnected(size=10, activation=None, last_layer=True)
]
model = Model(
layers=layers,
num_classes=10,
optimizer=GDMomentumOptimizer(lr=lr, mu=0.9),
regularization=0.001,
# lr_decay=0.5,
# lr_decay_interval=100
)
print("\n\n------------------------------------")
print("Initialize: {}".format(initializer))
print("\nRun training:\n------------------------------------")
data = mnist_dataset.load('dataset/mnist')
stats = model.train(data_set=data,
method='dfa',
num_passes=3,
