Trouble getting ICON results #13

Samiepapa · 2022-02-14T02:30:29Z

After installing all packages, I got the results successfully for PIFu and PaMIR.
I faced the runtime error when trying to get the ICON demo result. Could you guide what setting was wrong?

$ python infer.py -cfg ../configs/icon-filter.yaml -gpu 0 -in_dir ../examples -out_dir ../results

Traceback (most recent call last):
  File "infer.py", line 304, in <module>
    verts_pr, faces_pr, _ = model.test_single(in_tensor)
  File "./ICON/apps/ICON.py", line 738, in test_single
    sdf = self.reconEngine(opt=self.cfg,
  File "./.virtualenvs/icon/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "../lib/common/seg3d_lossless.py", line 148, in forward
    return self._forward_faster(**kwargs)
  File "../lib/common/seg3d_lossless.py", line 170, in _forward_faster
    occupancys = self.batch_eval(coords, **kwargs)
  File "../lib/common/seg3d_lossless.py", line 139, in batch_eval
    occupancys = self.query_func(**kwargs, points=coords2D)
  File "../lib/common/train_util.py", line 338, in query_func
    preds = netG.query(features=features,
  File "../lib/net/HGPIFuNet.py", line 285, in query
    smpl_sdf, smpl_norm, smpl_cmap, smpl_ind = cal_sdf_batch(
  File "../lib/dataset/mesh_util.py", line 231, in cal_sdf_batch
    residues, normals, pts_cmap, pts_ind = func(
  File "./.virtualenvs/icon/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "./.virtualenvs/icon/lib/python3.8/site-packages/bvh_distance_queries/mesh_distance.py", line 79, in forward
    output = self.search_tree(triangles, points)
  File "./.virtualenvs/icon/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "./.virtualenvs/icon/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "./.virtualenvs/icon/lib/python3.8/site-packages/bvh_distance_queries/bvh_search_tree.py", line 109, in forward
    output = BVHFunction.apply(
  File "./.virtualenvs/icon/lib/python3.8/site-packages/bvh_distance_queries/bvh_search_tree.py", line 42, in forward
    outputs = bvh_distance_queries_cuda.distance_queries(
RuntimeError: after reduction step 1: cudaErrorInvalidDevice: invalid device ordinal

The text was updated successfully, but these errors were encountered:

Samiepapa · 2022-02-14T02:49:57Z

For the reference, my nvidia version info is as follows.
NVIDIA-SMI 510.47.03 Driver Version: 510.47.03 CUDA Version: 11.6

The Cuda version was set to 11.5.

$ sudo update-alternatives --config cuda
There are 10 choices for the alternative cuda (providing /usr/local/cuda).

  Selection    Path                  Priority   Status
------------------------------------------------------------
* 0            /usr/local/cuda-11.5   115       auto mode

From the previous issues mentioned here, I've changed the CUDA version to 11.0. I faced the different issue as follows.

$ python infer.py -cfg ../configs/icon-filter.yaml -gpu 0 -in_dir ../examples -out_dir ../results
Using /home/yongilcho/.cache/torch_extensions as PyTorch extensions root...
Detected CUDA files, patching ldflags
Emitting ninja build file /home/yongilcho/.cache/torch_extensions/voxelize_cuda/build.ninja...
Building extension module voxelize_cuda...
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
[1/2] /usr/local/cuda/bin/nvcc --generate-dependencies-with-compile --dependency-output voxelize_cuda.cuda.o.d -DTORCH_EXTENSION_NAME=voxelize_cuda -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -isystem /home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include -isystem /home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -isystem /home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/TH -isystem /home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/THC -isystem /usr/local/cuda/include -isystem /home/test/anaconda3/include/python3.8 -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_86,code=sm_86 --compiler-options '-fPIC' -std=c++14 -c /home/yongilcho/reposit/ICON/lib/neural_voxelization_layer/cuda/voxelize_cuda.cu -o voxelize_cuda.cuda.o
FAILED: voxelize_cuda.cuda.o

YuliangXiu · 2022-02-14T08:14:32Z

When did you git clone the code? I updated a new version 9 hours ago. For now, the voxelize_cuda is installed by pip. Please check out requirements.txt. Also, after changing the CUDA version, remember to install the suitable PyTorch compatible with such CUDA.

Samiepapa · 2022-02-14T08:32:39Z

Thanks for your quick feedback. I will update the code and check it again.
Anyway, I can find the pythorch (1.8.2) install site, https://pytorch.org/get-started/locally/, only for CUDA11.1.

pip3 install torch==1.8.2+cu111 torchvision==0.9.2+cu111 torchaudio==0.8.2 -f https://download.pytorch.org/whl/lts/1.8/torch_lts.html

Could you know any other install command for CUDA11.0 ?

Samiepapa · 2022-02-14T09:17:27Z

I faced one issue when installing all packages in "requirements.txt."
When setting cuda version to be 11.0, I can not install the packages due to some errors.

Building wheel for bvh-distance-queries (setup.py) ... error
  ERROR: Command errored out with exit status 1:
   command: /home/test/.virtualenvs/icon/bin/python3 -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-req-build-_j98v0fe/setup.py'uild-_j98v0fe/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(bdist_wheel -d /tmp/pip-wheel-a0u0j7ca
       cwd: /tmp/pip-req-build-_j98v0fe/
  Complete output (180 lines):
  running bdist_wheel
  running build
  running build_py
  creating build
  creating build/lib.linux-x86_64-3.8
  creating build/lib.linux-x86_64-3.8/bvh_distance_queries
  copying bvh_distance_queries/bvh_search_tree.py -> build/lib.linux-x86_64-3.8/bvh_distance_queries
  copying bvh_distance_queries/__init__.py -> build/lib.linux-x86_64-3.8/bvh_distance_queries
  copying bvh_distance_queries/mesh_distance.py -> build/lib.linux-x86_64-3.8/bvh_distance_queries
  running build_ext
  building 'bvh_distance_queries_cuda' extension
  creating /tmp/pip-req-build-_j98v0fe/build/temp.linux-x86_64-3.8
  creating /tmp/pip-req-build-_j98v0fe/build/temp.linux-x86_64-3.8/src
  Emitting ninja build file /tmp/pip-req-build-_j98v0fe/build/temp.linux-x86_64-3.8/build.ninja...
  Compiling objects...
  Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
  [1/2] /usr/local/cuda/bin/nvcc --generate-dependencies-with-compile --dependency-output /tmp/pip-req-build-_j98v0fe/build/temp.linux-x86_64-3.8/src/bvh_cualenvs/icon/lib/python3.8/site-packages/torch/include -I/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/torch/csrc/api/includeon/lib/python3.8/site-packages/torch/include/TH -I/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/THC -Iinclude -Icuda-samples/nvs/icon/lib/python3.8/site-packages/torch/include -I/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -I/ib/python3.8/site-packages/torch/include/TH -I/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/THC -I/usr/local/cuda/include -I/nclude -I/home/test/anaconda3/include/python3.8 -c -c /tmp/pip-req-build-_j98v0fe/src/bvh_cuda_op.cu -o /tmp/pip-req-build-_j98v0fe/build/temp.linux-xDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-TIMINGS=0 -DDEBUG_PRINT=0 -DERROR_CHECKING=1 -DNUM_THREADS=256 -DPROFILING=0 -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_UILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=bvh_distance_queries_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_86,code=compute_86 -gencode=arch=
  FAILED: /tmp/pip-req-build-_j98v0fe/build/temp.linux-x86_64-3.8/src/bvh_cuda_op.o
  /usr/local/cuda/bin/nvcc --generate-dependencies-with-compile --dependency-output /tmp/pip-req-build-_j98v0fe/build/temp.linux-x86_64-3.8/src/bvh_cuda_ops/icon/lib/python3.8/site-packages/torch/include -I/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -I/ho/python3.8/site-packages/torch/include/TH -I/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/THC -Iinclude -Icuda-samples/Commonon/lib/python3.8/site-packages/torch/include -I/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -I/home/yhon3.8/site-packages/torch/include/TH -I/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/y -I/home/test/anaconda3/include/python3.8 -c -c /tmp/pip-req-build-_j98v0fe/src/bvh_cuda_op.cu -o /tmp/pip-req-build-_j98v0fe/build/temp.linux-x86_64-HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-optionS=0 -DDEBUG_PRINT=0 -DERROR_CHECKING=1 -DNUM_THREADS=256 -DPROFILING=0 -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIBBI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=bvh_distance_queries_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_86,code=compute_86 -gencode=arch=comput
  nvcc fatal   : Unsupported gpu architecture 'compute_86'

Finally, I succeeded to install all packages in requirements.txt with Cuda version 11.5.
After installing all packages, I can see the same issue mentioned first even though I changed the cuda version 11.0.

Traceback (most recent call last):
  File "infer.py", line 310, in <module>
    verts_pr, faces_pr, _ = model.test_single(in_tensor)
  File "/home/test/reposit/ICON/apps/ICON.py", line 738, in test_single
    sdf = self.reconEngine(opt=self.cfg,
  File "/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "../lib/common/seg3d_lossless.py", line 148, in forward
    return self._forward_faster(**kwargs)
  File "../lib/common/seg3d_lossless.py", line 170, in _forward_faster
    occupancys = self.batch_eval(coords, **kwargs)
  File "../lib/common/seg3d_lossless.py", line 139, in batch_eval
    occupancys = self.query_func(**kwargs, points=coords2D)
  File "../lib/common/train_util.py", line 338, in query_func
    preds = netG.query(features=features,
  File "../lib/net/HGPIFuNet.py", line 285, in query
    smpl_sdf, smpl_norm, smpl_cmap, smpl_ind = cal_sdf_batch(
  File "../lib/dataset/mesh_util.py", line 255, in cal_sdf_batch
    residues, normals, pts_cmap, pts_ind = func(
  File "/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/test/.virtualenvs/icon/lib/python3.8/site-packages/bvh_distance_queries/mesh_distance.py", line 79, in forward
    output = self.search_tree(triangles, points)
  File "/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/home/test/.virtualenvs/icon/lib/python3.8/site-packages/bvh_distance_queries/bvh_search_tree.py", line 109, in forward
    output = BVHFunction.apply(
  File "/home/test/.virtualenvs/icon/lib/python3.8/site-packages/bvh_distance_queries/bvh_search_tree.py", line 42, in forward
    outputs = bvh_distance_queries_cuda.distance_queries(
RuntimeError: after reduction step 1: cudaErrorInvalidDevice: invalid device ordinal

YuliangXiu · 2022-02-14T09:34:47Z

Thanks for your quick feedback. I will update the code and check it again. Anyway, I can find the pythorch (1.8.2) install site, https://pytorch.org/get-started/locally/, only for CUDA11.1.
pip3 install torch==1.8.2+cu111 torchvision==0.9.2+cu111 torchaudio==0.8.2 -f https://download.pytorch.org/whl/lts/1.8/torch_lts.html
Could you know any other install command for CUDA11.0 ?

cudatookit==11.1 can works well on cuda 11.0, no worry

YuliangXiu · 2022-02-14T09:37:37Z

I faced one issue when installing all packages in "requirements.txt." When setting cuda version to be 11.0, I can not install the packages due to some errors.

Building wheel for bvh-distance-queries (setup.py) ... error
  ERROR: Command errored out with exit status 1:
   command: /home/test/.virtualenvs/icon/bin/python3 -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-req-build-_j98v0fe/setup.py'uild-_j98v0fe/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(bdist_wheel -d /tmp/pip-wheel-a0u0j7ca
       cwd: /tmp/pip-req-build-_j98v0fe/
  Complete output (180 lines):
  running bdist_wheel
  running build
  running build_py
  creating build
  creating build/lib.linux-x86_64-3.8
  creating build/lib.linux-x86_64-3.8/bvh_distance_queries
  copying bvh_distance_queries/bvh_search_tree.py -> build/lib.linux-x86_64-3.8/bvh_distance_queries
  copying bvh_distance_queries/__init__.py -> build/lib.linux-x86_64-3.8/bvh_distance_queries
  copying bvh_distance_queries/mesh_distance.py -> build/lib.linux-x86_64-3.8/bvh_distance_queries
  running build_ext
  building 'bvh_distance_queries_cuda' extension
  creating /tmp/pip-req-build-_j98v0fe/build/temp.linux-x86_64-3.8
  creating /tmp/pip-req-build-_j98v0fe/build/temp.linux-x86_64-3.8/src
  Emitting ninja build file /tmp/pip-req-build-_j98v0fe/build/temp.linux-x86_64-3.8/build.ninja...
  Compiling objects...
  Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
  [1/2] /usr/local/cuda/bin/nvcc --generate-dependencies-with-compile --dependency-output /tmp/pip-req-build-_j98v0fe/build/temp.linux-x86_64-3.8/src/bvh_cualenvs/icon/lib/python3.8/site-packages/torch/include -I/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/torch/csrc/api/includeon/lib/python3.8/site-packages/torch/include/TH -I/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/THC -Iinclude -Icuda-samples/nvs/icon/lib/python3.8/site-packages/torch/include -I/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -I/ib/python3.8/site-packages/torch/include/TH -I/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/THC -I/usr/local/cuda/include -I/nclude -I/home/test/anaconda3/include/python3.8 -c -c /tmp/pip-req-build-_j98v0fe/src/bvh_cuda_op.cu -o /tmp/pip-req-build-_j98v0fe/build/temp.linux-xDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-TIMINGS=0 -DDEBUG_PRINT=0 -DERROR_CHECKING=1 -DNUM_THREADS=256 -DPROFILING=0 -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_UILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=bvh_distance_queries_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_86,code=compute_86 -gencode=arch=
  FAILED: /tmp/pip-req-build-_j98v0fe/build/temp.linux-x86_64-3.8/src/bvh_cuda_op.o
  /usr/local/cuda/bin/nvcc --generate-dependencies-with-compile --dependency-output /tmp/pip-req-build-_j98v0fe/build/temp.linux-x86_64-3.8/src/bvh_cuda_ops/icon/lib/python3.8/site-packages/torch/include -I/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -I/ho/python3.8/site-packages/torch/include/TH -I/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/THC -Iinclude -Icuda-samples/Commonon/lib/python3.8/site-packages/torch/include -I/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/torch/csrc/api/include -I/home/yhon3.8/site-packages/torch/include/TH -I/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/include/THC -I/usr/local/cuda/include -I/home/y -I/home/test/anaconda3/include/python3.8 -c -c /tmp/pip-req-build-_j98v0fe/src/bvh_cuda_op.cu -o /tmp/pip-req-build-_j98v0fe/build/temp.linux-x86_64-HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-optionS=0 -DDEBUG_PRINT=0 -DERROR_CHECKING=1 -DNUM_THREADS=256 -DPROFILING=0 -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIBBI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=bvh_distance_queries_cuda -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_86,code=compute_86 -gencode=arch=comput
  nvcc fatal   : Unsupported gpu architecture 'compute_86'

Finally, I succeeded to install all packages in requirements.txt with Cuda version 11.5. After installing all packages, I can see the same issue mentioned first even though I changed the cuda version 11.0.

Traceback (most recent call last):
  File "infer.py", line 310, in <module>
    verts_pr, faces_pr, _ = model.test_single(in_tensor)
  File "/home/test/reposit/ICON/apps/ICON.py", line 738, in test_single
    sdf = self.reconEngine(opt=self.cfg,
  File "/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "../lib/common/seg3d_lossless.py", line 148, in forward
    return self._forward_faster(**kwargs)
  File "../lib/common/seg3d_lossless.py", line 170, in _forward_faster
    occupancys = self.batch_eval(coords, **kwargs)
  File "../lib/common/seg3d_lossless.py", line 139, in batch_eval
    occupancys = self.query_func(**kwargs, points=coords2D)
  File "../lib/common/train_util.py", line 338, in query_func
    preds = netG.query(features=features,
  File "../lib/net/HGPIFuNet.py", line 285, in query
    smpl_sdf, smpl_norm, smpl_cmap, smpl_ind = cal_sdf_batch(
  File "../lib/dataset/mesh_util.py", line 255, in cal_sdf_batch
    residues, normals, pts_cmap, pts_ind = func(
  File "/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/test/.virtualenvs/icon/lib/python3.8/site-packages/bvh_distance_queries/mesh_distance.py", line 79, in forward
    output = self.search_tree(triangles, points)
  File "/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/test/.virtualenvs/icon/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/home/test/.virtualenvs/icon/lib/python3.8/site-packages/bvh_distance_queries/bvh_search_tree.py", line 109, in forward
    output = BVHFunction.apply(
  File "/home/test/.virtualenvs/icon/lib/python3.8/site-packages/bvh_distance_queries/bvh_search_tree.py", line 42, in forward
    outputs = bvh_distance_queries_cuda.distance_queries(
RuntimeError: after reduction step 1: cudaErrorInvalidDevice: invalid device ordinal

Probably, you could have a loot at

I showed the full process to set it up in Ubuntu with anaconda.

Current BVH only supports CUDA<=11.0, this is a version modified from
torch-mesh-isect, I have no idea when Vassilis will update it to support the latest CUDA.

Samiepapa · 2022-02-14T10:58:02Z

Okay. Thanks a lot.
I will check the Colab setting.
BTW, Is it limited to Ubuntu18.04 like Colab ?

YuliangXiu · 2022-02-14T11:01:03Z

Okay. Thanks a lot. I will check the Colab setting. BTW, Is it limited to Ubuntu18.04 like Colab ?

Nope, it works well on Ubuntu 20.04.

jaymefosa · 2022-02-16T14:22:11Z

getting the same issue with various versions of Pytorch and Cuda 11.0

bvh samples seem to run for the most part (some other issues with Kornia arise)

YuliangXiu · 2022-02-16T14:41:58Z

@jaymefosa

Here is the PyTorch version I used for ICON

Please re-install (uninstall, install) the bvh or PyTorch3D if you changed the version of PyTorch, because these libs are dependent on PyTorch.

guayabas · 2022-02-19T21:00:10Z

Another hint to solve the CUDA version issue is to define the environmental variable TORCH_CUDA_ARCH_LIST="8.0" (in .bashrc for example) before installing pytorch-related packages

cuda 11.0 requires arch 8.0 (https://arnon.dk/matching-sm-architectures-arch-and-gencode-for-various-nvidia-cards/) but python setuptools can give arch 8.6 as default if using cuda 11.1 breaking things between pytorch3d, bvh, etc. which is that annoying 'invalid device ordinal'

YuliangXiu · 2022-03-07T02:52:56Z

@jaymefosa @Samiepapa, I have replaced the bvh-distance-queries with PyTorch3D+Kaolin, thus you don't need to install it anymore. Also, the CUDA version is not limited to 11.0.

YuliangXiu closed this as completed Feb 24, 2022

YuliangXiu added bug Something isn't working CUDA or OpenGL CUDA related issues and removed bug Something isn't working labels May 21, 2022

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Trouble getting ICON results #13

Trouble getting ICON results #13

Samiepapa commented Feb 14, 2022

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jaymefosa commented Feb 16, 2022

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Trouble getting ICON results #13

Trouble getting ICON results #13

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Samiepapa commented Feb 14, 2022

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