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    Batch Normalization(BN)层是一种常用于神经网络的正则化技术,它通过规范化输入数据的均值和方差来加速神经网络的训练过程并提高其准确性。它在深度神经网络中被广泛使用,并已经被证明对于提高训练速度和网络性能非常有效。 具体而言,BN层的作用如下:
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