HolyWu
commented
2 years ago Can you shed some light on what runtime (onnxruntime, onnxruntime-gpu and onnxruntime-directml) is need for which provider?
CUDA and TensorRT require onnxruntime-gpu, while DirectML requires onnxruntime-directml.
2022-03-19 20:14:30.0977965 [E:onnxruntime:Default, provider_bridge_ort.cc:995 onnxruntime::ProviderLibrary::Get] LoadLibrary failed with error 126 "Das angegebene Modul wurde nicht gefunden." when trying to load "I:\Hybrid\64bit\Vapoursynth\Lib\site-packages\onnxruntime\capi\onnxruntime_providers_cuda.dll" 2022-03-19 20:14:30.0978594 [W:onnxruntime:Default, onnxruntime_pybind_state.cc:535 onnxruntime::python::CreateExecutionProviderInstance] Failed to create CUDAExecutionProvider. Please reference https://onnxruntime.ai/docs/reference/execution-providers/CUDA-ExecutionProvider.html#requirements to ensure all dependencies are met. Vapoursynth preview error: 2022-03-19 20:14:30.3973685 [E:onnxruntime:Default, provider_bridge_ort.cc:995 onnxruntime::ProviderLibrary::Get] LoadLibrary failed with error 126 "Das angegebene Modul wurde nicht gefunden." when trying to load "I:\Hybrid\64bit\Vapoursynth\Lib\site-packages\onnxruntime\capi\onnxruntime_providers_cuda.dll" 2022-03-19 20:14:30.3974014 [W:onnxruntime:Default, onnxruntime_pybind_state.cc:535 onnxruntime::python::CreateExecutionProviderInstance] Failed to create CUDAExecutionProvider. Please reference https://onnxruntime.ai/docs/reference/execution-providers/CUDA-ExecutionProvider.html#requirements to ensure all dependencies are met.
LoadLibrary failed with error 126 means some dependent DLLs are missing, like Visual C++ 2019 runtime, CUDA SDK, or cuDNN. Visit https://github.com/HolyWu/vs-dpir/discussions/19 for installation steps.
When I uninstall 'onnxruntime-gpu', install 'onnxruntime' and use provider=1, no error appears. When I uninstall 'onnxruntime', install 'onnxruntime-directml' and use provider=1, no error appears.
Actually there is a warning message generated, at least when using vspipe, something like Warning: C:\Python39\lib\site-packages\onnxruntime\capi\onnxruntime_inference_collection.py:55: UserWarning: Specified provider 'CUDAExecutionProvider' is not in available provider names.Available providers: 'CPUExecutionProvider'. If you didn't see it then it means the application you are using doesn't capture the messages.
-> Is there a downside of using onnxruntime-directml ?
It's slower compared CUDA and/or TensorRT. DirectML is mainly for AMD and Intel hardwares since they don't support CUDA.
Also using provider=0 and provider=1 doesn't seem to make a difference. From the looks of it cpu&gpu usage both times is the same.
Because ONNX Runtime automatically falls back to use CPU for inferencing when CUDA Execution Provider (provider=1) is not available.
Selur
Can you shed some light on what runtime (onnxruntime, onnxruntime-gpu and onnxruntime-directml) is need for which provider?
When I install 'onnxruntime-gpu' and use provider=1, I get:
(dpir still seems to work) When I uninstall 'onnxruntime-gpu', install 'onnxruntime' and use provider=1, no error appears. When I uninstall 'onnxruntime', install 'onnxruntime-directml' and use provider=1, no error appears. When use provider=3, no error appears and the processing is a lot faster.
-> Is there a downside of using onnxruntime-directml ?
Also using provider=0 and provider=1 doesn't seem to make a difference. From the looks of it cpu&gpu usage both times is the same. Would be nice if you could shed some light on what is used when. :)