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yesMohanHere
c0c329a2f1
- Bump gsplat to >=1.5.3 (sm_120-capable release line) and nerfacc to >=0.5.3 - Drop EOL Python 3.8/3.9: requires-python >=3.10, CI publish/doc workflows - torch.load(..., weights_only=False) for torch>=2.6 checkpoint compatibility - Use torch.amp custom_fwd/custom_bwd with device_type="cuda" (torch>=2.4 API) - Replace deprecated PIL private encoder API in pil_to_numpy with np.asarray (fixes Pillow>=11 compatibility) - Docs: add Torch 2.8+ / CUDA 12.8 install tab for Blackwell GPUs Tested on RTX 5060 (sm_120) with torch 2.11.0+cu128: splatfacto and nerfacto train end-to-end and ns-render produces correct output.