- Modified detect_gpu_backends() to perform functional tests on GPUs
- CUDA detection now verifies devices can actually perform tensor operations
- ROCm detection now tests device functionality before counting
- Only NVIDIA GPUs are counted for CUDA, and only functional devices
- Prevents counting of non-working GPUs like old AMD cards misreported as CUDA
- Example: System with old AMD GPU (device 0) + working CUDA GPU (device 1) now correctly shows only the functional CUDA GPU
- Total VRAM calculation now reflects only actually usable GPUs
- Both PyTorch and nvidia-smi/rocm-smi detection paths updated