I think that the part regarding the Vapoursynth + pip install and related modules should be provide the same output contained in the file "Hybrid_torch_addon.7z" that you sent to me (with the exception of folder vsgan_models). So I think that I can skip these steps (unless you think that your archive is not reliable to perform this test).
Now to create my CUDA setup I used the following files:
cuda_11.4.3_472.50_win10.exe
cudnn-11.4-windows-x64-v8.2.2.26.zip
TensorRT-8.0.3.4.Windows10.x86_64.cuda-11.3.cudnn8.2.zip
and I already wrote with this setup vs-dpir and onnxruntime is working perfectly.
Theoretically should be enough:
delete the env variable CUDA_PATH, CUDA_PATH_V11_4
rename "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.4" in "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.4_fake" (just to don't deinstall CUDA)
reboot the PC
now just to be sure, copy all dlls in "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.4_fake\bin" in "D:\Programs\Hybrid\64bit\Vapoursynth\Lib\site-packages\onnxruntime\capi"
I think that in the past I already tested a configuration like it, but I will perform this test again tomorrow.
In meanwhile I found the following code in the source directory of onnxruntime (file: onnxruntime_pybind_state.cc)
#ifdef USE_CUDA
// If the environment variable 'CUDA_UNAVAILABLE' exists, then we do not load cuda. This is set by _ld_preload for the manylinux case
// as in that case, trying to load the library itself will result in a crash due to the way that auditwheel strips dependencies.
if (Env::Default().GetEnvironmentVar("ORT_CUDA_UNAVAILABLE").empty()) {
if (auto* cuda_provider_info = TryGetProviderInfo_CUDA()) {
const CUDAExecutionProviderInfo info = GetCudaExecutionProviderInfo(cuda_provider_info,
provider_options_map);
// This variable is never initialized because the APIs by which it should be initialized are deprecated, however they still
// exist are are in-use. Neverthless, it is used to return CUDAAllocator, hence we must try to initialize it here if we can
// since FromProviderOptions might contain external CUDA allocator.
external_allocator_info = info.external_allocator_info;
return cuda_provider_info->CreateExecutionProviderFactory(info)->CreateProvider();
} else {
if (!Env::Default().GetEnvironmentVar("CUDA_PATH").empty()) {
ORT_THROW("CUDA_PATH is set but CUDA wasn't able to be loaded. Please install the correct version of CUDA and cuDNN as mentioned in the GPU requirements page (https://onnxruntime.ai/docs/reference/execution-providers/CUDA-ExecutionProvider.html#requirements), make sure they're in the PATH, and that your GPU is supported.");
}
}
}
LOGS_DEFAULT(WARNING) << "Failed to create " << type << ". Please reference https://onnxruntime.ai/docs/reference/execution-providers/CUDA-ExecutionProvider.html#requirements to ensure all dependencies are met.";
#endif
It seems that if the environment variable CUDA_PATH is not found the CUDA library is not loaded. But first the module try to initialize CUDA in any case if is not defined the environment variable ORT_CUDA_UNAVAILABLE.
