I was curious if anyone has managed to compile pytorch to get Deepstack working with older cards where Compute Compatability is <= 3.5?
I have successfully compiled pytorch as per: GitHub - pytorch/pytorch: Tensors and Dynamic neural networks in Python with strong GPU acceleration
and copied the “torch” directory under Deepstack/windows_packages but get the following error:
Traceback (most recent call last):
File "C:\DeepStack\intelligencelayer\shared\detection.py", line 21, in <module>
File "C://DeepStack\windows_packages\torch\__init__.py", line 135, in <module>
OSError: [WinError 126] The specified module could not be found. Error loading "C://DeepStack\windows_packages\torch\lib\backend_with_compiler.dll" or one of its dependencies.
Any ideas how to get this working?
Just got this working with the Deepstack-GPU-2022.01.1 installer!
So much faster on my older machine.
The problem above was because not all of the libs were copied over from my compile directory.
So I just needed to copy the contents of the folder: pytorch-1.10.1\pytorch\build\lib
into the C://DeepStack\windows_packages\torch\lib
and the error message went away, but then I had to do the same with torchvision.
This is with
Driver Version: 472.98
CUDA Version: 11.4
CUDNN: 8.2.4 (cudnn-11.4-windows-x64-v126.96.36.199.zip)
Thanks for reporting this @loopy12 . We will review the Windows GPU build again to figure out what could be wrong that caused the PyTorch build to be missing.
With “older” (aka MUCH cheaper) cards such as the GT710 being the go-to for tinkerers and testers, could I ask the inclusion of these compiled kernel images with Deepstack’s GPU version?
@OlafenwaMoses To clarify, the installer works fine, but does not include support for the older cards due to pytorch dropping support for Compute<=3.5 in their builds by default but can be included by compiling. So I compiled pytorch with the support and got it working by copying the compiled libs over the Deepstack-GPU installer and it worked.
Thanks for sharing this @loopy12 . To address issues with running DeepStack on different generations of GPUs, we are working on doing the following in future releases
- the default :gpu tag will support latest GPUs and CUDA version
- there will be other GPU tags for older CUDA versions
Great! I can confirm that Deepstack works well on the GT710 and is about ~3-4x superior in performance over my running the CPU version.