VGG 11-layer model (configuration "A") from "Very Deep Convolutional Networks For Large-Scale Image Recognition" https://arxiv.org/pdf/1409.1556.pdf
For the Pytorch implementation, you can refer to pytorchx/vgg
VGG's architecture is simple, just some conv, relu, maxpool, and fc layers.
// 1. generate vgg.wts from [pytorchx/vgg](https://github.com/wang-xinyu/pytorchx/tree/master/vgg)
// 2. put vgg.wts into tensorrtx/vgg
// 3. build and run
cd tensorrtx/vgg
mkdir build
cd build
cmake ..
make
sudo ./vgg -s // serialize model to plan file i.e. 'vgg.engine'
sudo ./vgg -d // deserialize plan file and run inference
// 4. see if the output is same as pytorchx/vgg