mirror of
https://github.com/rndlabsoy/fly-brain-full.git
synced 2026-09-10 11:20:43 +02:00
erojasoficial-byte
c1d089dc3b
138,639 LIF neurons (FlyWire v783, GPU/PyTorch) connected to NeuroMechFly v2 (MuJoCo) with compound-eye vision, olfaction, gustation, somatosensation, courtship song, virtual flight, and proboscis extension. Includes benchmark suite (Brian2, Brian2CUDA, PyTorch, NEST GPU), project website, and technical papers (EN/ES).
51 lines
2.6 KiB
Bash
51 lines
2.6 KiB
Bash
# wsl --unregister Ubuntu-22.04
|
|
wsl --install -d Ubuntu-22.04
|
|
|
|
sudo apt update
|
|
sudo apt upgrade -y
|
|
sudo apt install software-properties-common
|
|
sudo add-apt-repository ppa:ubuntu-toolchain-r/test
|
|
sudo apt update
|
|
sudo apt install gcc-11 g++-11
|
|
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-11 11
|
|
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-11 11
|
|
sudo update-alternatives --config gcc
|
|
sudo update-alternatives --config g++
|
|
gcc --version
|
|
|
|
# # Source 1: https://developer.nvidia.com/cuda-12-5-0-download-archive?target_os=Linux&target_arch=x86_64&Distribution=WSL-Ubuntu&target_version=2.0&target_type=deb_local
|
|
# # Source 2: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/#post-installation-actions
|
|
wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-wsl-ubuntu.pin
|
|
sudo mv cuda-wsl-ubuntu.pin /etc/apt/preferences.d/cuda-repository-pin-600
|
|
wget https://developer.download.nvidia.com/compute/cuda/12.5.0/local_installers/cuda-repo-wsl-ubuntu-12-5-local_12.5.0-1_amd64.deb
|
|
sudo dpkg -i cuda-repo-wsl-ubuntu-12-5-local_12.5.0-1_amd64.deb
|
|
sudo cp /var/cuda-repo-wsl-ubuntu-12-5-local/cuda-*-keyring.gpg /usr/share/keyrings/
|
|
sudo apt-get update
|
|
sudo apt-get -y install cuda-toolkit-12-5 # NOTE: we had an older CUDA installed (I believe v11.5), we may need to revert back to it
|
|
echo '' >> ~/.bashrc # Make CUDA paths permanent by adding to ~/.bashrc
|
|
echo '# CUDA paths' >> ~/.bashrc
|
|
echo 'export PATH=${PATH}:/usr/local/cuda-12.5/bin' >> ~/.bashrc
|
|
echo 'export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/cuda-12.5/lib64' >> ~/.bashrc
|
|
nvcc --version
|
|
|
|
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
|
|
bash ./Miniconda3-latest-Linux-x86_64.sh
|
|
source ~/.bashrc
|
|
conda --version
|
|
|
|
# cd /mnt/c/Users/YOUR_USERNAME/GitHub/fly-brain
|
|
conda env create -f environment.yml
|
|
conda activate brian2cuda
|
|
python -c "import brian2cuda; brian2cuda.example_run()"
|
|
# python fly-brain/code/example-benchmark.py
|
|
|
|
conda deactivate
|
|
conda create --name flybody -c conda-forge -y python=3.10 pip cudatoolkit=11.8.0 ipython ipykernel jupyterlab notebook ffmpeg
|
|
conda activate flybody
|
|
pip install -e fly-body[ray]
|
|
mujoco fly-body/flybody/fruitfly/assets/floor.xml
|
|
|
|
# Optionally, test training a simple DMPO policy for the flybody MuJoCo environment
|
|
# CUDNN_PATH=$(dirname $(python -c "import nvidia.cudnn;print(nvidia.cudnn.__file__)"))
|
|
# export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CONDA_PREFIX/lib/:$CUDNN_PATH/lib # NOTE: this is temporary, run it at least once when starting a new terminal
|
|
# python fly-body/flybody/train_dmpo_ray.py --test |