If you do not know the root cause of the problem / bug, and wish someone to help you, please
post according to this template:
🐛 Bugs / Unexpected behaviors
Compilation error when trying to install from source:
C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.8/include\cub/device/dispatch/dispatch_segmented_sort.cuh(338): error: invalid combination of type specifiers
C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.8/include\cub/device/dispatch/dispatch_segmented_sort.cuh(338): error: expected an identifier
C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.8/include\cub/device/dispatch/dispatch_segmented_sort.cuh(379): error: expected a member name
3 errors detected in the compilation of "C:/Users/Haofan Lu/AppData/Local/Temp/3/pip-req-build-ejxxne68/pytorch3d/csrc/pulsar/cuda/renderer.create_selector.gpu.cu".
renderer.create_selector.gpu.cu
....
C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.8/include\cub/device/dispatch/dispatch_segmented_sort.cuh(338): error: invalid combination of type specifiers
C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.8/include\cub/device/dispatch/dispatch_segmented_sort.cuh(338): error: expected an identifier
C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.8/include\cub/device/dispatch/dispatch_segmented_sort.cuh(379): error: expected a member name
3 errors detected in the compilation of "C:/Users/Haofan Lu/AppData/Local/Temp/3/pip-req-build-ejxxne68/pytorch3d/csrc/pulsar/cuda/renderer.backward_dbg.gpu.cu".
renderer.backward_dbg.gpu.cu
...
C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.8/include\cub/device/dispatch/dispatch_segmented_sort.cuh(338): error: invalid combination of type specifiers
C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.8/include\cub/device/dispatch/dispatch_segmented_sort.cuh(338): error: expected an identifier
C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.8/include\cub/device/dispatch/dispatch_segmented_sort.cuh(379): error: expected a member name
3 errors detected in the compilation of "C:/Users/Haofan Lu/AppData/Local/Temp/3/pip-req-build-ejxxne68/pytorch3d/csrc/pulsar/cuda/renderer.backward.gpu.cu".
renderer.backward.gpu.cu
...
C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.8/include\cub/device/dispatch/dispatch_segmented_sort.cuh(338): error: invalid combination of type specifiers
C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.8/include\cub/device/dispatch/dispatch_segmented_sort.cuh(338): error: expected an identifier
C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.8/include\cub/device/dispatch/dispatch_segmented_sort.cuh(379): error: expected a member name
3 errors detected in the compilation of "C:/Users/Haofan Lu/AppData/Local/Temp/3/pip-req-build-ejxxne68/pytorch3d/csrc/pulsar/cuda/renderer.forward.gpu.cu".
renderer.forward.gpu.cu
NOTE: Please look at the existing list of Issues tagged with the label 'bug`. Only open a new issue if this bug has not already been reported. If an issue already exists, please comment there instead..
Instructions To Reproduce the Issue:
OS: Windows Server 2019
NVCC: 11.7 & 11.8 (Both tested and found the same error)
C++ compiler: MSVC 2019 C++ Desktop Development
Python: 3.9.0
Pytorch: 1.13.1
Please include the following (depending on what the issue is):
Any changes you made (git diff) or code you wrote
None
If you do not know the root cause of the problem / bug, and wish someone to help you, please post according to this template:
🐛 Bugs / Unexpected behaviors
Compilation error when trying to install from source:
NOTE: Please look at the existing list of Issues tagged with the label 'bug`. Only open a new issue if this bug has not already been reported. If an issue already exists, please comment there instead..
Instructions To Reproduce the Issue:
OS: Windows Server 2019 NVCC: 11.7 & 11.8 (Both tested and found the same error) C++ compiler: MSVC 2019 C++ Desktop Development Python: 3.9.0 Pytorch: 1.13.1 Please include the following (depending on what the issue is):
git diff
) or code you wrote NonePlease also simplify the steps as much as possible so they do not require additional resources to run, such as a private dataset.