GoogLeNet (Inception v1) model architecture from "Going Deeper with Convolutions" http://arxiv.org/abs/1409.4842`_.
For the details, you can refer to pytorchx/googlenet
Following tricks used in this googlenet:
- MaxPool2d(ceil_mode=True), ceilmode=True, which is not supported in Tensorrt4, we use a padding layer before maxpool to solve this problem.
- Batchnorm layer, implemented by scale layer.
// 1. generate googlenet.wts from [pytorchx/googlenet](https://github.com/wang-xinyu/pytorchx/tree/master/googlenet)
// 2. put googlenet.wts into tensorrtx/googlenet
// 3. build and run
cd tensorrtx/googlenet
mkdir build
cd build
cmake ..
make
sudo ./googlenet -s // serialize model to plan file i.e. 'googlenet.engine'
sudo ./googlenet -d // deserialize plan file and run inference
// 4. see if the output is same as pytorchx/googlenet