Kevin Gilper
07d2f0b763
New docs/deepstack-layers/ is the authoritative, reproducible account of the 12 layers values, at three separated confidence levels: 1. Structure (verified from code): the values are gains on 12 equal deepstack chunks - features from 12 successive Qwen3-VL encoder-depth bands. Shown in kg_krea_v9/clip_hooks.py (the deepstack feature list) and conditioning.py (the 12-way width split). 2. Semantics (convergent evidence): analyze_tables.py reads the live tables and shows the four independently-tuned appearance tables (style/palette/material/lighting) agree chunk-for-chunk - 0-4 carry structure (monotonic depth ramp, all suppress), 5-6 transition, 7/8/10 carry appearance (all spike, chunk 8 strongest, then 10, then 7). Four tables tuned for four different jobs converging is the measurement encoded as data, not an assertion. 3. Precise response curve (fresh measurement): generate_sweep.py is a turnkey single-chunk-spike sweep (the paper's section 16.4 method), emitting each spike as a V10 custom recipe validated against the real node code. Dry-run works anywhere; rendering needs the V10 nodes on a ComfyUI box (single-chunk tables are not V9-expressible), so the measured-verdict table is staged pending a V10-equipped render box. SCORING.md defines the rubric. Cross-linked from technical paper 5.2, the recipe guide, and custom_recipes/README. Tooling lives under docs/ (excluded from registry packs by .comfyignore). sweep_out/ is gitignored.
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Scoring the deepstack sweep
After generate_sweep.py --server ... renders the grid, score every spike
render against the control (<ref>__sweep-control.png) to determine what
each chunk carries. The control and the spike share prompt, seed, reference,
strength, pooled channel, and all other chunks - so any visible difference is
attributable to the spiked chunk alone.
Procedure
For each reference (subject, palette) and each chunk L:
-
Open
<ref>__sweep-control.pngand<ref>__sweep-chunk-LL-gain-4.pngside by side. -
Judge which single aspect changed most relative to the control, and how strongly (none / subtle / clear / dominant):
Aspect What to look for structure subject shape, pose, layout, spatial composition shifting toward the reference palette overall color cast, hue relationships moving toward the reference texture surface/material grain, finish, micro-detail lighting light direction, contrast, glow, shadow, mood (none) no meaningful change from control -
Record:
chunk L -> <aspect> (<strength>). If two aspects move together, record both with the dominant one first.
Recording
Fill the verdict table in README.md - one row per chunk, with the verdict from each reference and a consensus column. A determination is "solidified" when:
- both references agree on each chunk's dominant aspect, and
- the measured structure->transition->appearance ordering matches the convergent-table prediction (chunks 0-4 structure, 5-6 transition, 7/8/10 appearance with 8 strongest), OR any disagreement is documented with its consequence for the tables.
If a scoring pass is done by an agent, have a second independent agent score the same grid blind and reconcile; note both in the record.
Optional: multi-level confirmation
Re-run with --gains 2 4 6 to confirm each chunk's response is monotonic in
gain (a real carrier gets stronger with a bigger spike; noise does not). Note
the gain at which each chunk's effect first becomes clearly visible.