densenet.py 文件源码

def addLayer(previousLayer, nChannels, nOutChannels, dropRate, blockNum):

    bn = BatchNormalization(name = 'denseb_BatchNorm_{}'.format(blockNum) , axis = 1)(previousLayer)

    relu = Activation('relu', name ='denseb_relu_{}'.format(blockNum))(bn)

    conv = Convolution2D(nOutChannels, 3, 3, border_mode='same', name='denseb_conv_{}'.format(blockNum))(relu)

    if dropRate is not None:

        dp = Dropout(dropRate, name='denseb_dropout_{}'.format)(conv)

        return merge([dp, previousLayer], mode='concat', concat_axis=1)

    else:

        return merge([conv, previousLayer], mode='concat', concat_axis=1)