lhk229
a48d70d9f7
Config-only tuning of the temporary CPU lane (no pipeline/code change). Query chunk 512 trims ViTMatte's attention transient ~0.9 GB at 2048x2048 (8.0 -> 7.1 GB peak working set) with bitwise-identical output; 256 gives nothing more. The remaining ~7.1 GB floor is attributed to ViTMatte's detail-capture decoder (backbone stage peaks 4.6 GB, decoder 7.1 GB, pymatting only 0.08 GB), so it is not further reducible by attention chunking -- noted for a possible future decoder-tiling pass. Accepted as-is for the 8 GB box. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
32 lines
1.4 KiB
YAML
32 lines
1.4 KiB
YAML
# Urgent CPU-only lane: fp32, birefnet segmentation, NO cross-check, NO anime-seg.
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#
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# This is the lightest production path: base ViTMatte + one BiRefNet@1024, ~14-15s
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# per 1.5 MP image on CPU. It needs ONLY these two weights provisioned --
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# BiRefNet_HR-matting (cross-check) and anime-seg are never loaded.
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#
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# Tuned for an 8 GB box (~7 GB for the service). Measured peak working set:
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# 2048x1152 (2.4 MP) ~5.6 GB | 2048x2048 (4.2 MP) ~7.1 GB.
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# The 2048x2048 peak is a floor set by ViTMatte's own dense compute, not the
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# attention (shrinking the chunk below 512 does not lower it further). Set
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# MemoryMax=8G with a hard 4 MP input cap (BGFILTER_MAX_IMAGE_PIXELS default),
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# or cap inputs tighter if you need more headroom.
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#
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# Anything omitted here inherits the built-in defaults (identical to default.yaml).
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model:
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device: cpu
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precision: fp32 # fp32 only: this lane targets non-bf16 CPUs
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# Query chunk of 512 (vs the 2048 default) trims ViTMatte's attention transient
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# ~0.9 GB at 2048x2048 (8.0 -> 7.1 GB) for ~1 s more compute; 256 gives nothing
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# more. Exact/bitwise-identical output -- purely a memory-vs-speed knob.
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attn_query_chunk: 512
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segmentation:
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enabled: true
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backend: birefnet # the only backend this lane uses
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device: cpu
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precision: fp32
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cross_check:
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enabled: false # no second-opinion HR-matting pass (the big cost/mem sink)
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