densenet.py 文件源码

 复制代码def addTransition(previousLayer, nChannels, nOutChannels, dropRate, blockNum):

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

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

    conv = Convolution2D(nOutChannels, 1, 1, border_mode='same', name='tr_conv_{}'.format(blockNum))(relu)

    if dropRate is not None:

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

        avgPool = AveragePooling2D(pool_size=(2, 2))(dp)

    else:
        avgPool = AveragePooling2D(pool_size=(2, 2))(conv)

    return avgPool