def __init__(self):
X1 = T.tensor4()
X2 = T.tensor4()
X = [X1, X2]
Y = [T.ivector()]
model = Model()
#conv1
model.add(Conv(filter_shape = (32, 3, 3, 3), regularizers = {'W': l1(0.0001)}, w_shared = True, n_inputs = 2))
model.add(Conv(filter_shape = (32, 32, 2, 2), regularizers = {'W': l1(0.0001)}, w_shared = True, n_inputs = 2))
model.add(Pooling(pool_size = (2,2)))
model.add(Activation(mode = 'tanh'))
#conv2
model.add(Conv(filter_shape = (32, 32, 3, 3), regularizers = {'W': l1(0.0001)}, w_shared = True, n_inputs = 2))
model.add(Pooling(pool_size = (2,2)))
model.add(Activation(mode = 'tanh'))
#abs_diff
model.add(Abs_diff())
#conv3
model.add(Conv(filter_shape = (32, 32, 3, 3), regularizers = {'W': l1(0.0001)}, w_shared = True))
model.add(Pooling(pool_size = (2,2)))
model.add(Activation(mode = 'tanh'))
model.add(Flatten())
self.f = theano.function(X, model.f(X, is_train = True))
model.add(Fully((2880, 512)))
model.add(Activation(mode = 'tanh'))
model.add(Dropout(0.5))
model.add(Fully((512, 2)))
model.add(Activation(mode = 'softmax'))
model.build(CostFunc.nll, RMSprop(), X, Y)
self.model = model
