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Hello Everyone!
I'M Using Clearml, Yolo V8 And Clearml Gpu Compute (For Orchestration).
The Issue Is That I Can'T Find A Compatibility To Use Gpu During Yolo Training (On A Remote Instance, Not Local). My Local Machine Is Macbook On M2 Chip - Maybe It'S
Thank you for the reply @<1523701070390366208:profile|CostlyOstrich36> . I will try the image.
The initial issue was next:
CUDA initialization: The NVIDIA driver on your system is too old (found version 11040). Please update your GPU driver by downloading and installing a new version from the URL:
Alternatively, go to:
to install a PyTorch version that has been compiled with your version of the CUDA driver. (Triggered internally at ../c10/cuda/CUDAFunctions.cpp:108.)
I identified that torch==2.1.0
is not compatible with nvidia/cuda:11.4.3-cudnn8-runtime-ubuntu20.04
image - it's default image provided by ClearML GPU Compute.
After that I tried the nvidia/cuda:12.1.0-cudnn8-runtime-ubuntu20.04
and got next error:
UserWarning: CUDA initialization: Unexpected error from cudaGetDeviceCount(). Did you run some cuda functions before calling NumCudaDevices() that might have already set an error? Error 804: forward compatibility was attempted on non supported HW (Triggered internally at ../c10/cuda/CUDAFunctions.cpp:108.)
Googling the problem I found that it's usual pain to find compatible versions of cuda, pytorch and gpu. So, I need some advice how to resolve this compatibility issue to be able to use GPU power.
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Answers
11 months ago
11 months ago