An implementation of SENet, proposed in Squeeze-and-Excitation Networks by Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu
https://arxiv.org/abs/1709.01507
For the Pytorch implementation, you can refer to wang-xinyu/senet.pytorch.
// 1. generate se_resnet50.wts from [wang-xinyu/senet.pytorch](https://github.com/wang-xinyu/senet.pytorch)
// 2. put se_resnet50.wts into tensorrtx/senet
// 3. build and run
cd tensorrtx/senet
mkdir build
cd build
cmake ..
make
sudo ./se_resnet -s // serialize model to plan file i.e. 'se_resnet50.engine'
sudo ./se_resnet -d // deserialize plan file and run inference
// 4. see if the output is same as [wang-xinyu/senet.pytorch]