Wraps _pytorch_softsplat and _pytorch_costvol with torch.compile
for ~6x speedup on ROCm/non-cupy setups. Falls back to eager
execution gracefully if compilation fails.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
cupy.cuda.get_cuda_path() can return None when CUDA_HOME is not set
and cupy can't auto-detect it. Fall back to /usr/local/cuda.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Make cupy import optional (try/except), replace @cupy.memoize with a
dict cache, add _pytorch_softsplat() using scatter_add for bilinear
splatting, and update forward() dispatch to fall back to PyTorch when
cupy is unavailable or tensor is on CPU.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Integrates GIMM-VFI alongside existing BIM/EMA/SGM models. Key feature: generates
all intermediate frames in one forward pass (no recursive 2x passes needed for 4x/8x).
- Vendor gimm_vfi_arch/ from kijai/ComfyUI-GIMM-VFI with device fixes
- Two variants: RAFT-based (~80MB) and FlowFormer-based (~123MB)
- Auto-download checkpoints from HuggingFace (Kijai/GIMM-VFI_safetensors)
- Three new nodes: Load GIMM-VFI Model, GIMM-VFI Interpolate, GIMM-VFI Segment Interpolate
- single_pass toggle: True=arbitrary timestep (default), False=recursive like other models
- ds_factor parameter for high-res input downscaling
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Ethanfel