googlenet.py 文件源码

def inceptionC(self, input_layer, nfilt):
        # Corresponds to figure 6 in the paper
        l1 = self.bn_conv(input_layer, num_filters=nfilt[0][0], filter_size=1)

        l2 = self.bn_conv(input_layer, num_filters=nfilt[1][0], filter_size=1)
        l2 = self.bn_conv(l2, num_filters=nfilt[1][1], filter_size=(1, 7), pad=(0, 3))
        l2 = self.bn_conv(l2, num_filters=nfilt[1][2], filter_size=(7, 1), pad=(3, 0))

        l3 = self.bn_conv(input_layer, num_filters=nfilt[2][0], filter_size=1)
        l3 = self.bn_conv(l3, num_filters=nfilt[2][1], filter_size=(7, 1), pad=(3, 0))
        l3 = self.bn_conv(l3, num_filters=nfilt[2][2], filter_size=(1, 7), pad=(0, 3))
        l3 = self.bn_conv(l3, num_filters=nfilt[2][3], filter_size=(7, 1), pad=(3, 0))
        l3 = self.bn_conv(l3, num_filters=nfilt[2][4], filter_size=(1, 7), pad=(0, 3))

        l4 = Pool2DLayer(
            input_layer, pool_size=3, stride=1, pad=1, mode='average_exc_pad')
        l4 = self.bn_conv(l4, num_filters=nfilt[3][0], filter_size=1)

        return ConcatLayer([l1, l2, l3, l4])