Running setup.py install for mesh-mesh-intersection ... error about shapy HOT 6 CLOSED

I was able to successfully build the package on Windows 11, Python 3.10.11 and CUDA 11.8 by following these steps:

1. For any CUDA version after 11.6, CUDA Samples ARE NOT included in the CUDA Toolkit download. So you must download CUDA Samples from https://github.com/NVIDIA/cuda-samples. Make sure to download the right branch for your CUDA version i.e. 11.8 etc.

2. The CUDA_SAMPLES_INC must point to the folder that contains "helper_math.h". In the 11.8 samples, it is located in the Common folder

NOTE if you are running windows and follow the given install instructions:
unix shell => export CUDA_SAMPLES_INC=$(pwd)/include
windows cmd => set CUDA_SAMPLES_INC= path/to/helper_math.h

I myself got frustrated and hard coded it into line 58 of setup.py like this:

cuda_samples_inc = r'C:/Program Files/NVIDIA Corporation/CUDA Samples/v11.8/Common' mesh_mesh_intersect_src_files = [ 'src/mesh_mesh_intersect.cpp', 'src/mesh_mesh_intersect_cuda_op.cu'] mesh_mesh_intersect_include_dirs = torch.utils.cpp_extension.include_paths() + [ osp.abspath('include'), cuda_samples_inc]

3. open mesh-mesh-intersection/include/aabb.hpp and at line 34 delete __align__(32)

4. open mesh-mesh-intersection/include/triangle.hpp and at line 33 delete __align__(48)

• credit to chatgpt for deducing the __align__ command is causing flag errors

5. open mesh-mesh-intersection/src/mesh_mesh_intersect_cuda_op.cu
   here you will search out every instance of "long" and replace it with “int64_t”
   I recommend ctrl+f and search "long"
   NOTE do NOT change "long2" in line 133 and 135!!!

*credit to VictoryCoorg for the "long" fix https://forums.developer.nvidia.com/t/strange-link-error-seen-by-multiple-people-while-building-pytorch-cpp-cuda-extensions/145261/2

If my instructions are hard to follow, I will make a video showing the steps and update back.

from shapy.

@CumaOzavci The packages I installed are almost the latest releases, except for numpy and omegaconf.
This is my requirements.txt:

chumpy
imageio
jpeg4py
joblib
kornia
loguru
matplotlib
numpy==1.21.5
omegaconf==2.0.6
open3d
Pillow
PyOpenGL
pyrender
scikit-image
scikit-learn
scipy
smplx
tqdm
trimesh
yacs
fvcore
nflows
PyYAML

from shapy.

Ive been stuck on this same issue for the last week. Ive seemingly tried everything. I will share the solution if/when I get it to install.

from shapy.

@TheChildishMillennial Thank you for your reply. I also successfully ran SHAPY, but I finally build the Package on Ubuntu22.04, Python3.10.12, CUDA11.8.
I also tried it on Windows at first, but I encountered the problem you answered above and didn’t know how to solve it, so I converted to Linux. Thank you very much for answering the question！ This will definitely help many people.

from shapy.

@tillen1001 can you share your library versions for your setup. I could not install due to library conflicts in same setup.

from shapy.

@tillen1001 can you share your library versions for your setup. I could not install due to library conflicts in same setup.

Package Version

absl-py 2.0.0
addict 2.4.0
aiohttp 3.9.1
aiosignal 1.3.1
ansi2html 1.9.1
asttokens 2.4.1
async-timeout 4.0.3
attrs 23.2.0
blinker 1.7.0
cachetools 5.3.2
certifi 2023.11.17
cffi 1.16.0
charset-normalizer 3.3.2
chumpy 0.70
click 8.1.7
comm 0.2.1
ConfigArgParse 1.7
contourpy 1.2.0
cycler 0.12.1
dash 2.14.2
dash-core-components 2.0.0
dash-html-components 2.0.0
dash-table 5.0.0
decorator 5.1.1
exceptiongroup 1.2.0
executing 2.0.1
fastjsonschema 2.19.1
filelock 3.13.1
Flask 3.0.0
fonttools 4.47.0
freetype-py 2.4.0
frozenlist 1.4.1
fsspec 2023.12.2
fvcore 0.1.5.post20221221
google-auth 2.26.1
google-auth-oauthlib 1.2.0
grpcio 1.60.0
idna 3.6
imageio 2.33.1
importlib-metadata 7.0.1
iopath 0.1.10
ipython 8.20.0
ipywidgets 8.1.1
itsdangerous 2.1.2
jedi 0.19.1
Jinja2 3.1.2
joblib 1.3.2
jpeg4py 0.1.4
jsonschema 4.20.0
jsonschema-specifications 2023.12.1
jupyter_core 5.7.1
jupyterlab-widgets 3.0.9
kiwisolver 1.4.5
kornia 0.7.1
lazy_loader 0.3
lightning-utilities 0.10.0
loguru 0.7.2
Markdown 3.5.1
MarkupSafe 2.1.3
matplotlib 3.8.2
matplotlib-inline 0.1.6
mesh-mesh-intersection 0.2.0
mpmath 1.3.0
multidict 6.0.4
nbformat 5.9.2
nest-asyncio 1.5.8
networkx 3.2.1
nflows 0.14
numpy 1.21.5
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 12.3.101
nvidia-nvtx-cu12 12.1.105
oauthlib 3.2.2
omegaconf 2.0.6
open3d 0.18.0
opencv-python 4.9.0.80
packaging 23.2
pandas 2.0.3
parso 0.8.3
pexpect 4.9.0
pillow 10.2.0
pip 22.0.2
platformdirs 4.1.0
plotly 5.18.0
portalocker 2.8.2
prompt-toolkit 3.0.43
protobuf 4.23.4
ptyprocess 0.7.0
pure-eval 0.2.2
pyasn1 0.5.1
pyasn1-modules 0.3.0
pycparser 2.21
pyglet 2.0.10
Pygments 2.17.2
PyOpenGL 3.1.0
pyparsing 3.1.1
pyquaternion 0.9.9
pyrender 0.1.45
python-dateutil 2.8.2
pytorch-lightning 2.1.3
pytz 2023.3.post1
PyWavelets 1.4.1
PyYAML 6.0.1
referencing 0.32.1
requests 2.31.0
requests-oauthlib 1.3.1
retrying 1.3.4
rpds-py 0.16.2
rsa 4.9
scikit-image 0.21.0
scikit-learn 1.3.2
scipy 1.10.1
setuptools 59.6.0
shape-attributes 0.2.0
six 1.16.0
smplx 0.1.28
stack-data 0.6.3
sympy 1.12
tabulate 0.9.0
tenacity 8.2.3
tensorboard 2.15.1
tensorboard-data-server 0.7.2
termcolor 2.4.0
threadpoolctl 3.2.0
tifffile 2023.12.9
torch 2.1.0+cu118
torchaudio 2.1.0+cu118
torchmetrics 1.2.1
torchvision 0.16.0+cu118
tqdm 4.66.1
traitlets 5.14.1
trimesh 4.0.8
triton 2.1.0
typing_extensions 4.9.0
tzdata 2023.4
urllib3 2.1.0
wcwidth 0.2.13
Werkzeug 3.0.1
widgetsnbextension 4.0.9
yacs 0.1.8
yarl 1.9.4
zipp 3.17.0

from shapy.