Comments (8)
Here's a summary I've made of all past issues relating to simple-knn and diff-gaussian-rasterization. It eventually worked for me after 4 hours, 10+ reboots, and back-rolling VS2022 Community to an earlier version.
Environment setup issue (github.com)
"diff-gaussian-rasterization" and "simple-knn" not installing properly.
-
Always use the conda terminal and work under the git repo’s directory.
-
CUDA toolkit 11.7 was installed system-wide before all the following took place.
-
VS2022 v17.10.3 fails regardless, whilst v17.6.4 works.
-
Delete these before cloning the repo and creating conda environment again:
C:\Users\YOURNAME.conda\envs\gaussian_splatting
C:\Users\YOURNAME\gaussian-splatting -
Make sure cloning is recursive (otherwise the hyperlinked folders in the github repo doesn’t get cloned):
git clone https://github.com/graphdeco-inria/gaussian-splatting --recursive
-
Need “C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30133\bin\Hostx64\x64” to be in PATH for the build command to find cl.exe
-
Also need C++ devtools ticked in VS installer.
-
CUDA and PyTorch versions need to match: maybe use pip instead of conda. For example, for CUDA 11.7 (11.7.1 works):
conda create -n gaussian_splatting python=3.7
conda activate gaussian_splatting
conda install -c conda-forge vs2022_win-64
pip install torch==1.13.1+cu117 torchvision==0.14.1+cu117 torchaudio==0.13.1 --extra-index-url
https://download.pytorch.org/whl/cu117 (or alternatively? conda install pytorch==1.13.1 torchvision==0.14.1
torchaudio==0.13.1 pytorch-cuda=11.7 -c pytorch -c nvidia)
pip install submodules/diff-gaussian-rasterization
pip install submodules/simple-knn
pip install plyfile
pip install tqdm
-
Note that cudatoolkit version in environment.yml is WRONG. Change it to be 11.7 or 11.8, not 11.6. Some reported problems using 11.8, but some succeeded with it.
-
Check if PyTorch can access CUDA:
(gaussian_splatting) c:\dev\gaussian-splatting>python
>>> import torch
>>> torch.cuda.is_available()
True
(then press Ctrl+Z to exit) -
To restart an aborted installation:
conda env update --file environment.yml --name gaussian_splatting
Edit 2024-06-27:
Environment:
Windows 11 home version
CPU: Intel i7-12700H
GPU: NVIDIA RTX 3070
16GB RAM
x64 system
Windows 11 home version
from gaussian-splatting.
Here's a summary I've made of all past issues relating to simple-knn and diff-gaussian-rasterization. It eventually worked for me after 4 hours, 10+ reboots, and back-rolling VS2022 Community to an earlier version.
Environment setup issue (github.com)
"diff-gaussian-rasterization" and "simple-knn" not installing properly.
- Always use the conda terminal and work under the git repo’s directory.
- CUDA toolkit 11.7 was installed system-wide before all the following took place.
- VS2022 v17.10.3 fails regardless, whilst v17.6.4 works.
- Delete these before cloning the repo and creating conda environment again:
C:\Users\YOURNAME.conda\envs\gaussian_splatting
C:\Users\YOURNAME\gaussian-splatting- Make sure cloning is recursive (otherwise the hyperlinked folders in the github repo doesn’t get cloned):
git clone https://github.com/graphdeco-inria/gaussian-splatting --recursive
- Need “C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30133\bin\Hostx64\x64” to be in PATH for the build command to find cl.exe
- Also need C++ devtools ticked in VS installer.
- CUDA and PyTorch versions need to match: maybe use pip instead of conda. For example, for CUDA 11.7 (11.7.1 works):
conda create -n gaussian_splatting python=3.7
conda activate gaussian_splatting
conda install -c conda-forge vs2022_win-64
pip install torch==1.13.1+cu117 torchvision==0.14.1+cu117 torchaudio==0.13.1 --extra-index-url
https://download.pytorch.org/whl/cu117 (or alternatively? conda install pytorch==1.13.1 torchvision==0.14.1
torchaudio==0.13.1 pytorch-cuda=11.7 -c pytorch -c nvidia)
pip install submodules/diff-gaussian-rasterization
pip install submodules/simple-knn
pip install plyfile
pip install tqdm
- Note that cudatoolkit version in environment.yml is WRONG. Change it to be 11.7 or 11.8, not 11.6. Some reported problems using 11.8, but some succeeded with it.
- Check if PyTorch can access CUDA:
(gaussian_splatting) c:\dev\gaussian-splatting>python
>>> import torch
>>> torch.cuda.is_available()
True
(then press Ctrl+Z to exit)- To restart an aborted installation:
conda env update --file environment.yml --name gaussian_splatting
Edit 2024-06-27:
Environment: Windows 11 home version CPU: Intel i7-12700H GPU: NVIDIA RTX 3070 16GB RAM x64 system Windows 11 home version
Thanks for this detailed description of your troubleshooting.
-
Could you talk a bit about how you downgrade to VS2022 v17.6.4? I am unable to find a way to downgrade the software from anything other than v17.10.3 which it installs by default.
-
Could you also mention where you got the“C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30133\bin\Hostx64\x64” folder from? I am unable to add it to PATH since it doesn't exist on my computer.
from gaussian-splatting.
Thanks for your reply! I tried your tips, but sadly to no avail. However, this line caught my attention :
nvcc fatal : Unsupported gpu architecture 'compute_89'
I believe I have to update the nvcc to a newer version, so that it supports my compute architecture. At the moment, this is not possible. When it does I'll let you know if it worked 👍
from gaussian-splatting.
Here's a summary I've made of all past issues relating to simple-knn and diff-gaussian-rasterization. It eventually worked for me after 4 hours, 10+ reboots, and back-rolling VS2022 Community to an earlier version.
Environment setup issue (github.com)
"diff-gaussian-rasterization" and "simple-knn" not installing properly.
- Always use the conda terminal and work under the git repo’s directory.
- CUDA toolkit 11.7 was installed system-wide before all the following took place.
- VS2022 v17.10.3 fails regardless, whilst v17.6.4 works.
- Delete these before cloning the repo and creating conda environment again:
C:\Users\YOURNAME.conda\envs\gaussian_splatting
C:\Users\YOURNAME\gaussian-splatting- Make sure cloning is recursive (otherwise the hyperlinked folders in the github repo doesn’t get cloned):
git clone https://github.com/graphdeco-inria/gaussian-splatting --recursive
- Need “C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30133\bin\Hostx64\x64” to be in PATH for the build command to find cl.exe
- Also need C++ devtools ticked in VS installer.
- CUDA and PyTorch versions need to match: maybe use pip instead of conda. For example, for CUDA 11.7 (11.7.1 works):
conda create -n gaussian_splatting python=3.7
conda activate gaussian_splatting
conda install -c conda-forge vs2022_win-64
pip install torch==1.13.1+cu117 torchvision==0.14.1+cu117 torchaudio==0.13.1 --extra-index-url
https://download.pytorch.org/whl/cu117 (or alternatively? conda install pytorch==1.13.1 torchvision==0.14.1
torchaudio==0.13.1 pytorch-cuda=11.7 -c pytorch -c nvidia)
pip install submodules/diff-gaussian-rasterization
pip install submodules/simple-knn
pip install plyfile
pip install tqdm
- Note that cudatoolkit version in environment.yml is WRONG. Change it to be 11.7 or 11.8, not 11.6. Some reported problems using 11.8, but some succeeded with it.
- Check if PyTorch can access CUDA:
(gaussian_splatting) c:\dev\gaussian-splatting>python
>>> import torch
>>> torch.cuda.is_available()
True
(then press Ctrl+Z to exit)- To restart an aborted installation:
conda env update --file environment.yml --name gaussian_splatting
Edit 2024-06-27:
Environment: Windows 11 home version CPU: Intel i7-12700H GPU: NVIDIA RTX 3070 16GB RAM x64 system Windows 11 home versionThanks for this detailed description of your troubleshooting.
- Could you talk a bit about how you downgrade to VS2022 v17.6.4? I am unable to find a way to downgrade the software from anything other than v17.10.3 which it installs by default.
- Could you also mention where you got the“C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30133\bin\Hostx64\x64” folder from? I am unable to add it to PATH since it doesn't exist on my computer.
Same issue here. It seems like Microsoft does not allow you to downgrade the Visual Studio C compiler without a paid subscription. v17.10.3 is the latest and that's all you get the Community bundle. If you have Visual Studio installed, there should be either a 2019 or 2022 folder at C:\Program Files (x86)\Microsoft Visual Studio\
Update: The rasterization submodule did build properly for me using the VS 2019 compiler here:
https://visualstudio.microsoft.com/thank-you-downloading-visual-studio/?sku=Community&rel=16
from gaussian-splatting.
Here's a summary I've made of all past issues relating to simple-knn and diff-gaussian-rasterization. It eventually worked for me after 4 hours, 10+ reboots, and back-rolling VS2022 Community to an earlier version.
Environment setup issue (github.com)
"diff-gaussian-rasterization" and "simple-knn" not installing properly.
- Always use the conda terminal and work under the git repo’s directory.
- CUDA toolkit 11.7 was installed system-wide before all the following took place.
- VS2022 v17.10.3 fails regardless, whilst v17.6.4 works.
- Delete these before cloning the repo and creating conda environment again:
C:\Users\YOURNAME.conda\envs\gaussian_splatting
C:\Users\YOURNAME\gaussian-splatting- Make sure cloning is recursive (otherwise the hyperlinked folders in the github repo doesn’t get cloned):
git clone https://github.com/graphdeco-inria/gaussian-splatting --recursive
- Need “C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30133\bin\Hostx64\x64” to be in PATH for the build command to find cl.exe
- Also need C++ devtools ticked in VS installer.
- CUDA and PyTorch versions need to match: maybe use pip instead of conda. For example, for CUDA 11.7 (11.7.1 works):
conda create -n gaussian_splatting python=3.7
conda activate gaussian_splatting
conda install -c conda-forge vs2022_win-64
pip install torch==1.13.1+cu117 torchvision==0.14.1+cu117 torchaudio==0.13.1 --extra-index-url
https://download.pytorch.org/whl/cu117 (or alternatively? conda install pytorch==1.13.1 torchvision==0.14.1
torchaudio==0.13.1 pytorch-cuda=11.7 -c pytorch -c nvidia)
pip install submodules/diff-gaussian-rasterization
pip install submodules/simple-knn
pip install plyfile
pip install tqdm
- Note that cudatoolkit version in environment.yml is WRONG. Change it to be 11.7 or 11.8, not 11.6. Some reported problems using 11.8, but some succeeded with it.
- Check if PyTorch can access CUDA:
(gaussian_splatting) c:\dev\gaussian-splatting>python
>>> import torch
>>> torch.cuda.is_available()
True
(then press Ctrl+Z to exit)- To restart an aborted installation:
conda env update --file environment.yml --name gaussian_splatting
Edit 2024-06-27:
Environment: Windows 11 home version CPU: Intel i7-12700H GPU: NVIDIA RTX 3070 16GB RAM x64 system Windows 11 home version
you are my hero
from gaussian-splatting.
Here's a summary I've made of all past issues relating to simple-knn and diff-gaussian-rasterization. It eventually worked for me after 4 hours, 10+ reboots, and back-rolling VS2022 Community to an earlier version.
Environment setup issue (github.com)
"diff-gaussian-rasterization" and "simple-knn" not installing properly.
- Always use the conda terminal and work under the git repo’s directory.
- CUDA toolkit 11.7 was installed system-wide before all the following took place.
- VS2022 v17.10.3 fails regardless, whilst v17.6.4 works.
- Delete these before cloning the repo and creating conda environment again:
C:\Users\YOURNAME.conda\envs\gaussian_splatting
C:\Users\YOURNAME\gaussian-splatting- Make sure cloning is recursive (otherwise the hyperlinked folders in the github repo doesn’t get cloned):
git clone https://github.com/graphdeco-inria/gaussian-splatting --recursive
- Need “C:\Program Files (x86)\Microsoft Visual Studio\2019\Community\VC\Tools\MSVC\14.29.30133\bin\Hostx64\x64” to be in PATH for the build command to find cl.exe
- Also need C++ devtools ticked in VS installer.
- CUDA and PyTorch versions need to match: maybe use pip instead of conda. For example, for CUDA 11.7 (11.7.1 works):
conda create -n gaussian_splatting python=3.7
conda activate gaussian_splatting
conda install -c conda-forge vs2022_win-64
pip install torch==1.13.1+cu117 torchvision==0.14.1+cu117 torchaudio==0.13.1 --extra-index-url
https://download.pytorch.org/whl/cu117 (or alternatively? conda install pytorch==1.13.1 torchvision==0.14.1
torchaudio==0.13.1 pytorch-cuda=11.7 -c pytorch -c nvidia)
pip install submodules/diff-gaussian-rasterization
pip install submodules/simple-knn
pip install plyfile
pip install tqdm
- Note that cudatoolkit version in environment.yml is WRONG. Change it to be 11.7 or 11.8, not 11.6. Some reported problems using 11.8, but some succeeded with it.
- Check if PyTorch can access CUDA:
(gaussian_splatting) c:\dev\gaussian-splatting>python
>>> import torch
>>> torch.cuda.is_available()
True
(then press Ctrl+Z to exit)- To restart an aborted installation:
conda env update --file environment.yml --name gaussian_splatting
Edit 2024-06-27:
Environment: Windows 11 home version CPU: Intel i7-12700H GPU: NVIDIA RTX 3070 16GB RAM x64 system Windows 11 home version
Hi! I have tried to do multiple checks in order to be sure that I was following every detail.
I am running 11.7.1 cuda.
VS 2022 17.6.4
git 2.45.2
pytorch for 11.7
copied the path in the environment variables
I use the last anaconda and everytime I delete the environment and reboot
Changed 11.6 to 11.7 in the environment yml file
any ideas?
thanks!
a.
This is the error:
Processing c:\users\alessandro\gaussian-splatting\submodules\diff-gaussian-rasterization
Preparing metadata (setup.py) ... done
Building wheels for collected packages: diff-gaussian-rasterization
Building wheel for diff-gaussian-rasterization (setup.py) ... error
error: subprocess-exited-with-error
× python setup.py bdist_wheel did not run successfully.
│ exit code: 1
╰─> [5 lines of output]
running bdist_wheel
running build
running build_py
running build_ext
error: [WinError 2] The system cannot find the file specified
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
ERROR: Failed building wheel for diff-gaussian-rasterization
Running setup.py clean for diff-gaussian-rasterization
Failed to build diff-gaussian-rasterization
Installing collected packages: diff-gaussian-rasterization
Running setup.py install for diff-gaussian-rasterization ... error
error: subprocess-exited-with-error
× Running setup.py install for diff-gaussian-rasterization did not run successfully.
│ exit code: 1
╰─> [11 lines of output]
running install
C:\Users\Alessandro\anaconda3\envs\gaussian_splatting\lib\site-packages\setuptools\command\install.py:37: SetuptoolsDeprecationWarning: setup.py install is deprecated. Use build and pip and other standards-based tools.
setuptools.SetuptoolsDeprecationWarning,
running build
running build_py
creating build
creating build\lib.win-amd64-cpython-37
creating build\lib.win-amd64-cpython-37\diff_gaussian_rasterization
copying diff_gaussian_rasterization_init_.py -> build\lib.win-amd64-cpython-37\diff_gaussian_rasterization
running build_ext
error: [WinError 2] The system cannot find the file specified
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
error: legacy-install-failure
× Encountered error while trying to install package.
╰─> diff-gaussian-rasterization
note: This is an issue with the package mentioned above, not pip.
hint: See above for output from the failure.
from gaussian-splatting.
I get this error, does anyone know how to fix it. I'm using windows 11, VS v2022 , and CUDA 11.8.
× python setup.py bdist_wheel did not run successfully.
│ exit code: 1
╰─> [9 lines of output]
running bdist_wheel
running build
running build_py
creating build
creating build\lib.win-amd64-cpython-37
creating build\lib.win-amd64-cpython-37\diff_gaussian_rasterization
copying diff_gaussian_rasterization_init_.py -> build\lib.win-amd64-cpython-37\diff_gaussian_rasterization
running build_ext
error: [WinError 2] The system cannot find the file specified
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
ERROR: Failed building wheel for diff_gaussian_rasterization
error: subprocess-exited-with-error
from gaussian-splatting.
I had exactly the same problem, which I managed to solve by following the steps below. I used CUDA 12.5 and the equivalent PyTorch
Apparently this error is related to problems with the compilation settings related to CUDA, Check and set the compilers and some flags for CUDA.
Check the current settings (I recommend that you save the current configuration to revert to the previous state if necessary)
echo $TORCH_CUDA_ARCH_LIST
echo $TORCH_NVCC_FLAGS
Set the compilers (may be different for you)
export TORCH_CUDA_ARCH_LIST="7.0"
export TORCH_NVCC_FLAGS="-D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__"
Apparently you didn't get this error, but after running the above command I got a C/C++ FLT_MAX
error, apparently the compiler wasn't identifying the function and I had to include it manually in the simple_knn.cu file.
#include <cfloat>
This may or may not have helped, but I installed a specific version of CMake (3.18.4), which worked for the CUDA and PyTorch versions installed.
After that I cleared the cache,
pip cache purge
I reinstalled some dependencies,
pip install --upgrade setuptools wheel torch
and installed the module by running pip install .
inside the /submodules/simple_knn/
directory.
After these steps I advise you to reinstall diff-gaussian-rasterization module.
pip uninstall diff_gaussian_rasterization
pip install diff_gaussian_rasterization
And install the module in the same way, running pip install .
Following these steps I was able to solve this error, from what I understand about CUDA, PyTorch and CMake, you have to find the perfect match between your versions and your OS environment, I had to reinstall different versions of CUDA and CMake until I got them to work. These dependencies have serious compatibility problems.
from gaussian-splatting.
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from gaussian-splatting.