shuyueW1991
commented
5 months ago The following yml file content is what I run successfully with python3.8n with cuda 12.1:
` name: feature3dgs_v channels:
- conda-forge dependencies:
- _libgcc_mutex=0.1=conda_forge
- _openmp_mutex=4.5=2_gnu
- bzip2=1.0.8=hd590300_5
- ca-certificates=2024.6.2=hbcca054_0
- ld_impl_linux-64=2.40=hf3520f5_7
- libffi=3.4.2=h7f98852_5
- libgcc-ng=13.2.0=h77fa898_10
- libgomp=13.2.0=h77fa898_10
- libnsl=2.0.1=hd590300_0
- libsqlite=3.46.0=hde9e2c9_0
- libuuid=2.38.1=h0b41bf4_0
- libxcrypt=4.4.36=hd590300_1
- libzlib=1.3.1=h4ab18f5_1
- ncurses=6.5=h59595ed_0
- openssl=3.3.1=h4ab18f5_0
- pip=24.0=pyhd8ed1ab_0
- python=3.8.19=hd12c33a_0_cpython
- readline=8.2=h8228510_1
- tk=8.6.13=noxft_h4845f30_101
- wheel=0.43.0=pyhd8ed1ab_1
- xz=5.2.6=h166bdaf_0
- pip:
- certifi==2024.6.2
- charset-normalizer==3.3.2
- contourpy==1.1.1
- cycler==0.12.1
- filelock==3.15.1
- fonttools==4.53.0
- fsspec==2024.6.0
- idna==3.7
- importlib-resources==6.4.0
- jinja2==3.1.4
- joblib==1.4.2
- kiwisolver==1.4.5
- markupsafe==2.1.5
- matplotlib==3.7.5
- mpmath==1.3.0
- networkx==3.1
- numpy==1.24.4
- nvidia-cublas-cu12==12.1.3.1
- nvidia-cuda-cupti-cu12==12.1.105
- nvidia-cuda-nvrtc-cu12==12.1.105
- nvidia-cuda-runtime-cu12==12.1.105
- nvidia-cudnn-cu12==8.9.2.26
- nvidia-cufft-cu12==11.0.2.54
- nvidia-curand-cu12==10.3.2.106
- nvidia-cusolver-cu12==11.4.5.107
- nvidia-cusparse-cu12==12.1.0.106
- nvidia-nccl-cu12==2.18.1
- nvidia-nvjitlink-cu12==12.5.40
- nvidia-nvtx-cu12==12.1.105
- packaging==24.1
- pillow==10.3.0
- plyfile==1.0.3
- pyparsing==3.1.2
- python-dateutil==2.9.0.post0
- requests==2.32.3
- scikit-learn==1.3.2
- scipy==1.10.1
- setuptools==69.5.1
- six==1.16.0
- sympy==1.12.1
- threadpoolctl==3.5.0
- torch==2.1.0
- torchaudio==2.1.0
- torchvision==0.16.0
- tqdm==4.66.4
- triton==2.1.0
- typing-extensions==4.12.2
- urllib3==2.2.2
- zipp==3.19.2
`
Hope this helps!!
SummerRiver3D
Great job! However, when I was running your training and testing code, I encountered problems that have been reported in other issues, and I believe these are caused by inconsistent environments. I would like to know the versions of your CUDA, GCC, G++, PyTorch, and other related environmental information.