nerfstudio-project
Why Was Installing tiny-cuda-nn & Nerfstudio on My RTX 3060 Such a Nightmare? (And How I Finally Fixed It)
Installing tiny-cuda-nn & Nerfstudio on Windows (RTX 3060 + CUDA 11.8)
After spending over 48 hours troubleshooting, I finally got tiny-cuda-nn and Nerfstudio installed successfully. Here's what worked for me.
System Specs & Versions
- GPU: NVIDIA RTX 3060
- CUDA Version: 11.8
- Visual Studio Version: VS 2019 v17.8 (Worked!)
- Python Version: 3.8
Issues Faced & Fixes
1️⃣ TCNN_CUDA_ARCHITECTURES Error
Issue: Compilation failure due to missing CUDA architectures.
Fix: Set the CUDA architecture to 86:
set TCNN_CUDA_ARCHITECTURES=86
2️⃣ VS 2022 v17.10+ Not Working
Issue: CUDA (11.8) requires _MSC_VER < 1910 || _MSC_VER >= 1940, but VS 2022 sets _MSC_VER = 1940.
Fix: Removed VS 2022 v17.10+ and installed VS 2022 Fall 2023 LTSC (v17.8).
Either during installation of tinycudann or nerfstudio using pip, if it fails because of an error message mentioning Rust/Cargo, download and execute the installer from rustup.rs and try again.
3️⃣ CMake and cl Not Recognized
Issue: Running cmake or cl returned "not recognized as a command."
Fix: Manually added the following paths to the system PATH:
set PATH=C:\Program Files\Microsoft Visual Studio\2022\Enterprise\Common7\IDE\CommonExtensions\Microsoft\CMake\CMake\bin;%PATH%
set PATH=C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\VC\Tools\MSVC\14.38.33130\bin\Hostx64\x86;%PATH%
Then activated the MSVC environment:
call "C:\Program Files\Microsoft Visual Studio\2022\BuildTools\VC\Auxiliary\Build\vcvars64.bat"
4️⃣ Conda Environment Variables Not Set
Issue: CUDA was not detected properly inside Conda.
Fix: Manually set the following environment variables before installation:
set CUDAVER=11.8
set CUDA_HOME=%CONDA_PREFIX%
set CUDA_ROOT=%CONDA_PREFIX%
set PATH=%CONDA_PREFIX%\Library\bin;%PATH%
set LD_LIBRARY_PATH=%CONDA_PREFIX%\Library\lib;%LD_LIBRARY_PATH%
set LD_LIBRARY_PATH=%CONDA_PREFIX%\Library\lib64;%LD_LIBRARY_PATH%
set CUDA_HOST_COMPILER=C:\Program Files\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.3X.X\bin\Hostx64\x64\cl.exe
💡 To make these settings permanent, add them to your System Environment Variables.
5️⃣ Created a Conda Environment for Nerfstudio
conda create --name nerfstudio -y python=3.8
conda activate nerfstudio
python -m pip install --upgrade pip
6️⃣ Installed PyTorch with CUDA 11.8
pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 -f https://download.pytorch.org/whl/torch_stable.html
7️⃣ Installed tiny-cuda-nn via GitHub
Initially, the installation failed. However, after running:
pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch
it finally worked.
8️⃣ Installed Nerfstudio
pip install nerfstudio
🎉 Success!
Now, both tiny-cuda-nn and Nerfstudio are working perfectly! Hopefully, this helps someone else facing similar issues. 🚀
