models.py 文件源码

def __init__(self, n, h, in_size, in_channels, embed_size, block_size):
        super().__init__(
            l0=L.Convolution2D(in_channels, n, 3, stride=1, pad=1),
            ln=L.Linear(None, h))

        self.n_blocks = int(log2(in_size / embed_size)) + 1
        self.block_size = block_size

        for i in range(self.n_blocks):
            n_in = (i + 1) * n
            n_out = (i + 2) * n if i < self.n_blocks - 1 else n_in
            for j in range(block_size - 1):
                self.add_link('c{}'.format(i * block_size + j),
                              L.Convolution2D(n_in, n_in, 3, stride=1, pad=1))
            self.add_link('c{}'.format(i * block_size + block_size - 1),
                          L.Convolution2D(n_in, n_out, 3, stride=1, pad=1))