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4 Commits
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b353a7c863
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Integrate RAM cache with model RAM management (#13173)
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7810f49702
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comfy aimdo 0.2.11 + Improved RAM Pressure release strategies - Windows speedups (#12925)
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* Implement seek and read for pins Source pins from an mmap is pad because its its a CPU->CPU copy that attempts to fully buffer the same data twice. Instead, use seek and read which avoids the mmap buffering while usually being a faster read in the first place (avoiding mmap faulting etc). * pinned_memory: Use Aimdo pinner The aimdo pinner bypasses pytorches CPU allocator which can leak windows commit charge. * ops: bypass init() of weight for embedding layer This similarly consumes large commit charge especially for TEs. It can cause a permanement leaked commit charge which can destabilize on systems close to the commit ceiling and generally confuses the RAM stats. * model_patcher: implement pinned memory counter Implement a pinned memory counter for better accounting of what volume of memory pins have. * implement touch accounting Implement accounting of touching mmapped tensors. * mm+mp: add residency mmap getter * utils: use the aimdo mmap to load sft files * model_management: Implement tigher RAM pressure semantics Implement a pressure release on entire MMAPs as windows does perform faster when mmaps are unloaded and model loads free ramp into fully unallocated RAM. Make the concept of freeing for pins a completely separate concept. Now that pins are loadable directly from original file and don' touch the mmap, tighten the freeing budget to just the current loaded model - what you have left over. This still over-frees pins, but its a lot better than before. So after the pins are freed with that algorithm, bounce entire MMAPs to free RAM based on what the model needs, deducting off any known resident-in-mmap tensors to the free quota to keep it as tight as possible. * comfy-aimdo 0.2.11 Comfy aimdo 0.2.11 * mm: Implement file_slice path for QT * ruff * ops: put meta-tensors in place to allow custom nodes to check geo |
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361b9a82a3
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fix pinning with model defined dtype (#12208)
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pinned memory was converted back to pinning the CPU side weight without any changes. Fix the pinner to use the CPU weight and not the model defined geometry. This will either save RAM or stop buffer overruns when the types mismatch. Fix the model defined weight caster to use the [ s.weight, s.bias ] interpretation, as xfer_dest might be the flattened pin now. Fix the detection of needing to cast to not be conditional on !pin. |
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f8acd9c402
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Reduce RAM usage, fix VRAM OOMs, and fix Windows shared memory spilling with adaptive model loading (#11845) |