LocallyDenseLayer.py 文件源码

def __init__(self, incoming, num_units, cell_num, W=lasagne.init.GlorotUniform(),
                 b=lasagne.init.Constant(0.), nonlinearity=nonlinearities.rectify,
                 name=None, **kwargs):
        super(LocallyDenseLayer, self).__init__(incoming, name)
        self.nonlinearity = (nonlinearities.identity if nonlinearity is None
                             else nonlinearity)

        self.num_units = num_units

        num_inputs = int(np.prod(self.input_shape[1:]))
        self.cell_input_size = num_inputs / cell_num
        self.cell_size = self.num_units / cell_num

        if isinstance(W, lasagne.init.Initializer):
            W = [W for i in range(0, cell_num)]

        if isinstance(b, lasagne.init.Initializer):
            b = [b for i in range(0, cell_num)]

        self._dense_layers = []
        self.W = []
        self.b = []

        # Creating m number of tied dense layers
        for i in range(cell_num):
            self._dense_layers.append(TiedDenseLayer(CutLayer(incoming, cell_num),
                                                     self.cell_size, W[i], b[i], nonlinearity, **kwargs))

            self.W.append(self._dense_layers[-1].W)
            self.b.append(self._dense_layers[-1].b)