resnet.py 文件源码

def two_conv_layer(x, nb_channels, kernel_size=3, stride=1, l2_reg=1e-4,
                   first=False):
    if first: # Skip BN-Relu
        out = x
    else:
        out = BatchNormalization()(x)
        out = Activation('relu')(out)
    out = Convolution2D(nb_channels, kernel_size, kernel_size,
                        subsample=(stride, stride),
                        border_mode='same', init='he_normal',
                        W_regularizer=l2(l2_reg), bias=False)(out)
    out = BatchNormalization()(out)
    out = Activation('relu')(out)
    out = Convolution2D(nb_channels, kernel_size, kernel_size,
                        border_mode='same', init='he_normal',
                        W_regularizer=l2(l2_reg), bias=False)(out)
    return out