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!