Problems with CUDA implementation #44
Description
Hello,
I get the following error:
device: cuda:0
C:\Users\Public\PythonProjects\point2mesh\models\layers\mesh.py:201: UserWarning: Using torch.cross without specifying the dim arg is deprecated.
Please either pass the dim explicitly or simply use torch.linalg.cross.
The default value of dim will change to agree with that of linalg.cross in a future release. (Triggered internally at C:\cb\pytorch_1000000000000\work\aten\src\ATen\native\Cross.cpp:67.)
face_normals = torch.cross(vs[faces[:, 1]] - vs[faces[:, 0]],
Traceback (most recent call last):
File "main.py", line 29, in <module>
part_mesh = PartMesh(mesh, num_parts=options.get_num_parts(len(mesh.faces)), bfs_depth=opts.overlap)
File "C:\Users\Public\PythonProjects\point2mesh\models\layers\mesh.py", line 356, in __init__
m, vs_index = self.main_mesh.submesh(vs_index)
File "C:\Users\Public\PythonProjects\point2mesh\models\layers\mesh.py", line 320, in submesh
return PartMesh.create_submesh(vs_index, self)
File "C:\Users\Public\PythonProjects\point2mesh\models\layers\mesh.py", line 433, in create_submesh
faces_mask = vs_mask[mesh.faces].sum(dim=-1) > 0
RuntimeError: indices should be either on cpu or on the same device as the indexed tensor (cpu)
If I deactivate cuda with
torch.cuda.is_available = lambda : False
the program runs, albeit very slowly.
Cuda is apparently available.
>>>torch.cuda.device_count()
1
>>>torch.cuda.current_device()
0
>>>torch.cuda.device(0)
<torch.cuda.device object at 0x000001CCA8D36190>
>>>torch.cuda.get_device_name(0)
'NVIDIA GeForce RTX 4060 Laptop GPU'
conda list
(point2mesh) PS C:\Users\Public\PythonProjects\point2mesh> conda list
# packages in environment at C:\Users\Public\Anaconda\envs\point2mesh:
#
# Name Version Build Channel
atomicwrites 1.4.1 pypi_0 pypi
attrs 25.3.0 pypi_0 pypi
blas 1.0 mkl
brotli-python 1.0.9 py38hd77b12b_8
ca-certificates 2025.2.25 haa95532_0
certifi 2024.8.30 py38haa95532_0
charset-normalizer 3.3.2 pyhd3eb1b0_0
colorama 0.4.6 py38haa95532_0
cuda-cccl 12.9.27 0 nvidia
cuda-cccl_win-64 12.9.27 0 nvidia
cuda-cudart 12.1.105 0 nvidia
cuda-cudart-dev 12.1.105 0 nvidia
cuda-cupti 12.1.105 0 nvidia
cuda-libraries 12.1.0 0 nvidia
cuda-libraries-dev 12.1.0 0 nvidia
cuda-nvrtc 12.1.105 0 nvidia
cuda-nvrtc-dev 12.1.105 0 nvidia
cuda-nvtx 12.1.105 0 nvidia
cuda-opencl 12.9.19 0 nvidia
cuda-opencl-dev 12.9.19 0 nvidia
cuda-profiler-api 12.9.19 0 nvidia
cuda-runtime 12.1.0 0 nvidia
cuda-version 12.9 3 nvidia
filelock 3.13.1 py38haa95532_0
freetype 2.13.3 h0620614_0
fvcore 0.1.5.post20221221 pyhd8ed1ab_0 conda-forge
gmpy2 2.1.2 py38h7f96b67_0
icc_rt 2022.1.0 h6049295_2
idna 3.7 py38haa95532_0
intel-openmp 2025.0.0 haa95532_1164
jinja2 3.1.4 py38haa95532_0
jpeg 9e h827c3e9_3
khronos-opencl-icd-loader 2024.05.08 h8cc25b3_0
lcms2 2.16 hb4a4139_0
lerc 4.0.0 h5da7b33_0
libcublas 12.1.0.26 0 nvidia
libcublas-dev 12.1.0.26 0 nvidia
libcufft 11.0.2.4 0 nvidia
libcufft-dev 11.0.2.4 0 nvidia
libcurand 10.3.10.19 0 nvidia
libcurand-dev 10.3.10.19 0 nvidia
libcusolver 11.4.4.55 0 nvidia
libcusolver-dev 11.4.4.55 0 nvidia
libcusparse 12.0.2.55 0 nvidia
libcusparse-dev 12.0.2.55 0 nvidia
libdeflate 1.22 h5bf469e_0
libffi 3.4.4 hd77b12b_1
libjpeg-turbo 2.0.0 h196d8e1_0
libnpp 12.0.2.50 0 nvidia
libnpp-dev 12.0.2.50 0 nvidia
libnvjitlink 12.1.105 0 nvidia
libnvjitlink-dev 12.1.105 0 nvidia
libnvjpeg 12.1.1.14 0 nvidia
libnvjpeg-dev 12.1.1.14 0 nvidia
libpng 1.6.39 h8cc25b3_0
libtiff 4.5.1 h44ae7cf_1
libuv 1.48.0 h827c3e9_0
libwebp-base 1.3.2 h3d04722_1
lz4-c 1.9.4 h2bbff1b_1
markupsafe 2.1.3 py38h2bbff1b_0
mkl 2023.2.0 h6a75c08_49573 conda-forge
mkl-service 2.4.0 py38h2bbff1b_1
mkl_fft 1.3.8 py38h2bbff1b_0
mkl_random 1.2.4 py38h59b6b97_0
more-itertools 10.5.0 pypi_0 pypi
mpc 1.1.0 h7edee0f_1
mpfr 4.0.2 h62dcd97_1
mpir 3.0.0 hec2e145_1
mpmath 1.3.0 py38haa95532_0
networkx 3.1 py38haa95532_0
numpy 1.24.3 py38h79a8e48_1
numpy-base 1.24.3 py38h8a87ada_1
openjpeg 2.5.2 hae555c5_0
openssl 3.0.16 h3f729d1_0
packaging 25.0 pypi_0 pypi
pillow 10.4.0 py38h827c3e9_0
pip 24.2 py38haa95532_0
pluggy 0.13.1 pypi_0 pypi
portalocker 2.3.0 py38haa95532_1
py 1.11.0 pypi_0 pypi
pysocks 1.7.1 py38haa95532_0
pytest 5.4.2 pypi_0 pypi
python 3.8.20 h8205438_0
pytorch 2.2.2 py3.8_cuda12.1_cudnn8_0 pytorch
pytorch-cuda 12.1 hde6ce7c_6 pytorch
pytorch-mutex 1.0 cuda pytorch
pywin32 305 py38h2bbff1b_0
pyyaml 6.0.2 py38h827c3e9_0
requests 2.32.3 py38haa95532_0
setuptools 75.1.0 py38haa95532_0
six 1.16.0 pyhd3eb1b0_1
sqlite 3.45.3 h2bbff1b_0
sympy 1.13.3 py38haa95532_0
tabulate 0.9.0 py38haa95532_0
tbb 2021.8.0 h59b6b97_0
termcolor 2.1.0 py38haa95532_0
torchaudio 2.2.2 pypi_0 pypi
torchvision 0.17.2 pypi_0 pypi
tqdm 4.66.5 py38h9909e9c_0
trimesh 4.5.3 pyhd8ed1ab_0 conda-forge
typing_extensions 4.11.0 py38haa95532_0
urllib3 2.2.3 py38haa95532_0
vc 14.42 haa95532_5
vs2015_runtime 14.42.34433 hbfb602d_5
wcwidth 0.2.13 pypi_0 pypi
wheel 0.44.0 py38haa95532_0
win_inet_pton 1.1.0 py38haa95532_0
xz 5.6.4 h4754444_1
yacs 0.1.6 pyhd3eb1b0_1
yaml 0.2.5 he774522_0
zlib 1.2.13 h8cc25b3_1
zstd 1.5.6 h8880b57_0
Is there a fix to get cuda running?