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d710e56aca
Split the 53 over-threshold dated log entries (Recent decisions, Tried and abandoned) into per-entry persistent-memory.d/<slug>.md detail files, leaving one-line pointers in the index; the 10 short entries stay inline. Startup index drops 60,527 -> 25,256 bytes (492 -> 270 lines); entry bodies move verbatim to on-demand detail files, so a fresh session loads ~25 KB instead of ~60 KB and pulls a detail file only when its pointer is relevant. Top matter (Repo purpose, Tools & conventions, Current state) is unchanged; both archival back-references preserved. CLAUDE.md persistent-memory section now documents the index<->detail read discipline (read the index, pull details on demand, never bulk-read the dir, commit both together). Auto-archival still held every dated entry back (all <30 days old); the July burst begins aging past the 30-day guard ~2026-07-31.
2 lines
1.2 KiB
Markdown
2 lines
1.2 KiB
Markdown
- `[2026-07-14]` **MTP-on-modelopt: NO checkpoint config skips the spec-decode drafter's quant (vLLM 0.24 bug) — 4 config attempts failed before the runtime workaround.** All crashed the same way (`qwen3_5_mtp.py:256` `param_data.shape == loaded_weight.shape` AssertionError — bf16 mtp head loaded into a quantized drafter param): (1) mtp excludes in `config.json` (WRONG file — vLLM modelopt reads `hf_quant_config.json`); (2) specific-unfused mtp names in hf_quant_config; (3) wildcards `mtp*`/`mtp.layers.0*` (`is_layer_skipped` is EXACT-membership, NOT glob — wildcards match nothing); (4) exact fused+unfused names in both `mtp.`/`model.` prefixes. Instrumenting `is_layer_skipped` proved the drafter's exclude list holds ONLY the main model's `linear_attn` entries — the mtp excludes never reach the draft-model quant config. ONLY fix = a mounted `sitecustomize` force-skipping `mtp.*`. LESSON: don't chase checkpoint-config fixes for the mtp-drafter crash; go straight to the runtime patch. Also `nvidia-modelopt[hf]==0.43` (AEON's producer version) is a trap — it pins transformers back to 4.57 which can't load `qwen3_5` at all; use 0.45 + the FusedMoE guard in `quant_modelopt.py`.
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