qrnn.py 文件源码

def __init__(self, in_size, out_size, kernel_size=2, attention=False,
                 decoder=False):
        if kernel_size == 1:
            super().__init__(W=Linear(in_size, 3 * out_size))
        elif kernel_size == 2:
            super().__init__(W=Linear(in_size, 3 * out_size, nobias=True),
                             V=Linear(in_size, 3 * out_size))
        else:
            super().__init__(
                conv=L.ConvolutionND(1, in_size, 3 * out_size, kernel_size,
                                     stride=1, pad=kernel_size - 1))
        if attention:
            self.add_link('U', Linear(out_size, 3 * in_size))
            self.add_link('o', Linear(2 * out_size, out_size))
        self.in_size, self.size, self.attention = in_size, out_size, attention
        self.kernel_size = kernel_size