How do batch normalization layers behave differently during training vs inference in Keras?

During training, BatchNorm uses batch statistics; during inference, it uses moving averages.

BatchNorm maintains running mean and variance during training. At inference time, it switches to these accumulated statistics. Mismatch between training and inference distributions can cause performance degradation.