fix: add pynvml fallback for unified memory architectures (e.g., GB10) - #22
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foreverlms merged 1 commit intoJun 7, 2026
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On unified memory architectures like NVIDIA GB10 (DGX Spark), pynvml.nvmlDeviceGetMemoryInfo() raises NVMLError_NotSupported because there is no dedicated GPU memory. This change wraps the pynvml call in a try/except and falls back to torch.cuda.get_device_properties().total_memory when pynvml fails. If CUDA is also unavailable, defaults to 128GB. Co-authored-by: Claude
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NVIDIA#22) On unified memory architectures like NVIDIA GB10 (DGX Spark), pynvml.nvmlDeviceGetMemoryInfo() raises NVMLError_NotSupported because there is no dedicated GPU memory. This change wraps the pynvml call in a try/except and falls back to torch.cuda.get_device_properties().total_memory when pynvml fails. If CUDA is also unavailable, defaults to 128GB. Co-authored-by: Claude Co-authored-by: Kun Ling <kun.lingcc@foxmail.com>
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On unified memory architectures like NVIDIA GB10 (DGX Spark), pynvml.nvmlDeviceGetMemoryInfo() raises NVMLError_NotSupported because there is no dedicated GPU memory.
This change wraps the pynvml call in a try/except and falls back to torch.cuda.get_device_properties().total_memory when pynvml fails. If CUDA is also unavailable, defaults to 128GB.
Co-authored-by: Claude