link: https://developer.nvidia.com/cuda-toolkit-archive
$ sudo chmod +x cuda_{xx.x.xxx_xxx.xx}_linux.run
$ sudo sh cuda_10.2.89_440.33.01_linux.run
link: https://developer.nvidia.com/cuda-toolkit-archive
$ sudo chmod +x cuda_{xx.x.xxx_xxx.xx}_linux.run
$ sudo sh cuda_10.2.89_440.33.01_linux.run
reference links: https://learnml.today/speeding-up-model-with-fusing-batch-normalization-and-convolution-3
import torch
import torchvision
def fuse(conv, bn):
web: https://vulkan.lunarg.com/sdk/home#linux
mv 1.1.130.0 vulkan-1.1.130.0
mv vulkan-1.1.130.0 /usr/local/
github: https://github.com/nanmi/cortex/edit/master/README.md
Cortex is an open source platform for deploying machine learning models—trained with nearly any framework—as production web services.
install • tutorial • docs • examples • we're hiring • email us • chat with us
The project will be updated continuously ......
Pull requests are welcome!
Note: This is not one convertor for all frameworks, but a collection of different converters. Because github is an open source platform, I hope we can help each other here, gather everyone's strength.
Because of these different frameworks, the awesome convertors of deep learning models for different frameworks occur. It should be noted that I did not test all the converters, so I could not guarantee that each was available. But I also hope this convertor collection may help you!