miss out one convolutional layer in VGG16

[zlin3000]

In vgg.py, block 3 only contains 2 conv layers and 1 pool layer. However, from the paper, it shows there should be 3 conv layers and 1 pool layer in block 3.

Ref: https://arxiv.org/pdf/1409.1556v6.pdf