Using slim to perform batch normalization
Run python mnist_bn.py --phase=train to train.
Run python mnist_bn.py --phase=test to test.
It should achieve an accuracy of ~99.3% or higher on test set.
I've added accuracy, cross_entropy and batch normalization paramters into summary. Use tensorboard --logdir=/log to explore the learning curve and parameter distributions!