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
def __init__(self): X1 = T.tensor4() X2 = T.tensor4() X = [X1, X2] Y = [T.ivector()] model = Model() #conv1 model.add(Conv(filter_shape = (25, 3, 5, 5), w_shared = True, n_inputs = 2)) model.add(Pooling(pool_size = (2,2))) model.add(Activation(mode = 'tanh')) #conv2 model.add(Conv(filter_shape = (25, 25, 3, 3), 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 = (25, 25, 3, 3), w_shared = True)) model.add(Pooling(pool_size = (2,2))) model.add(Activation(mode = 'tanh')) model.add(Flatten()) model.add(Fully((25*18*5, 500))) model.add(Activation(mode = 'tanh')) model.add(Fully((500, 2))) model.add(Activation(mode = 'softmax')) model.build(CostFunc.nll, RMSprop(), X, Y) self.model = model