llm-atlas/experiments/k3/attnres_local_path/README.md

Attention Residuals local mixer-path diagnostics

This directory implements preregistered protocol llm-atlas-k3-attnres-local-path-v1.

It is a targeted follow-up to Round 06. It exact-replays the same depth-32 Block training and keeps the learned forward unchanged while switching source value-gradient coefficients only at frozen mixer scopes. It is not a Kimi K3 checkpoint run, a trainable variant, an additive attribution, or a reproduction of unpublished Figure 5 telemetry.

Frozen environment

Python /home/wuyang/.pyenv/versions/3.10.14/envs/navi-router-cu128/bin/python
PyTorch 2.11.0+cu128
GPU NVIDIA GeForce RTX 5090
CUBLAS_WORKSPACE_CONFIG=:4096:8

The preregistration was committed as 6911efc before the runner or any result file existed.

Step-0 smoke

CUBLAS_WORKSPACE_CONFIG=:4096:8 \
/home/wuyang/.pyenv/versions/3.10.14/envs/navi-router-cu128/bin/python \
  experiments/k3/attnres_local_path/train.py \
  --run-kind smoke \
  --seed 2026073001 \
  --cache-dir /home/wuyang/.cache/llm-atlas/k3-attnres-gradient-scale-v1 \
  --data-manifest experiments/k3/attnres_gradient/manifest.json \
  --parent-manifest experiments/k3/attnres_spike/manifest.json \
  --manifest experiments/k3/attnres_local_path/manifest.json \
  --output /home/wuyang/.cache/llm-atlas/k3-attnres-local-path-v1/smoke/seed-2026073001.json

The first smoke passed all 14-mode forward-identity, selector, Round 06 endpoint, initialization-negative-control, parent-learned, and loss-scale gates. Its canonical content hash is f708200f4fb122f61f30b97393839382a2094a71a8ea5d48cf47fb7fa094e69b.

Formal cells use the same command with --run-kind formal, one of the three manifest seeds, and a new output path. The independent seed-2026073001 run uses --run-kind replay.

Only analyze.py may calculate the global log gap, sufficiency/restoration scores, and preregistered gates. The site consumes its frozen aggregate rather than reimplementing thresholds in TypeScript.