pytorchTest

A basic toy example project of using pytorch in c++, and using c++ to extend pytorch operations

Requires G++11

For ubuntu older than 21.10, run following first

sudo add-apt-repository 'deb http://mirrors.kernel.org/ubuntu jammy main universe'
sudo apt-get update

Then, install the default gcc/g++ of ubuntu22.04

sudo apt-get install gcc g++ cmake python3 python3-pip

Requires Torch

You may refer to https://pytorch.org/get-started/locally/ for mor details, following are the minimal requirements

(Optional) Cuda-based torch

You may wish to install cuda for faster pre-training on models, following is a reference procedure. Please refer to https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#ubuntu

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.0-1_all.deb
sudo dpkg -i cuda-keyring_1.0-1_all.deb
sudo apt-get update
sudo apt-get install cuda
sudo apt-get install nvidia-gds
sudo apt-get install libcudnn8 libcudnn8-dev libcublas*

Then you may have to reboot for enabling cuda.

(Required) Install pytorch

sudo apt-get install python3 python3-pip

(w/ CUDA):

pip3 install torch torchvision torchaudio

(w/o CUDA)

pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cpu

How to build

(CUDA-related is only necessary if your pytorch has cuda, but it's harmless if you don't have cuda.)

Build in shell

export CUDACXX=/usr/local/cuda/bin/nvcc
mkdir build && cd build
cmake -DCMAKE_PREFIX_PATH=`python3 -c 'import torch;print(torch.utils.cmake_prefix_path)'` ..
make 

Tips for build in Clion

There are bugs in the built-in cmake of Clion, so you can not run -DCMAKE_PREFIX_PATH=python3 -c 'import torch;print(torch.utils.cmake_prefix_path)'. Following may help:

• Please run 'import torch;print(torch.utils.cmake_prefix_path)' manually first, and copy the path
• Paste the path to -DCMAKE_PREFIX_PATH=
• Manually set the environment variable CUDACXX as "/usr/local/cuda/bin/nvcc" in Clion's cmake settings

Test

• run pytorch in c++: ./example-app
• run our own extension in python python3 pythonTest.py

Local generation of the documents

You can also re-generate them locally, if you have the doxygen and graphviz. Following are how to install them in ubuntu 21.10/22.04

sudo apt-get install doxygen
sudo apt-get install graphviz

Then, you can do

mkdir doc
doxygen Doxyfile

to get the documents in doc/html folder, and start at index.html

Known issues

1. If you use Torch with cuda, the nvcc will refuse to work as it doesn't support c++20 yet. Therefore, we disabled the global requirement check of C++ 20, and only leave an "-std=c++20" option for g++. This will be fixed after nvidia can support c++20 in cuda.