googlenet.py 文件源码

def __init__(self):
        super(GoogLeNet, self).__init__(
            conv1=L.Convolution2D(3,  64, 7, stride=2, pad=3),
            conv2_reduce=L.Convolution2D(64,  64, 1),
            conv2=L.Convolution2D(64, 192, 3, stride=1, pad=1),
            inc3a=L.Inception(192,  64,  96, 128, 16,  32,  32),
            inc3b=L.Inception(256, 128, 128, 192, 32,  96,  64),
            inc4a=L.Inception(480, 192,  96, 208, 16,  48,  64),
            inc4b=L.Inception(512, 160, 112, 224, 24,  64,  64),
            inc4c=L.Inception(512, 128, 128, 256, 24,  64,  64),
            inc4d=L.Inception(512, 112, 144, 288, 32,  64,  64),
            inc4e=L.Inception(528, 256, 160, 320, 32, 128, 128),
            inc5a=L.Inception(832, 256, 160, 320, 32, 128, 128),
            inc5b=L.Inception(832, 384, 192, 384, 48, 128, 128),
            loss3_fc=L.Linear(1024, 1000),

            loss1_conv=L.Convolution2D(512, 128, 1),
            loss1_fc1=L.Linear(4 * 4 * 128, 1024),
            loss1_fc2=L.Linear(1024, 1000),

            loss2_conv=L.Convolution2D(528, 128, 1),
            loss2_fc1=L.Linear(4 * 4 * 128, 1024),
            loss2_fc2=L.Linear(1024, 1000)
        )
        self.train = True