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trajectory plot (steer/heal zigzag + trait-coherence pareto) + barrier-vs-nll gradient pressure log

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- plot.py write_trajectory: auth zigzag (steer red / heal green) over the pipeline,
  coherence panel below sharing x, and a trait(x)-vs-coherence(y) pareto map with
  separate steer/heal trajectories from base. PNG via kaleido + interactive html.
  Fixed coherence axes to [0.83,1.01] so ~0.001 noise does not fill the panel.
- run.py: build a stages list carrying full eval dicts; derive the stage table from
  it; persist the steered eval to events.jsonl; render trajectory at end of run.
- heal.py: log g_bar/g_nll = ||grad barrier|| / ||grad sft|| at each logged step.
  >>1 = barrier over-tight (undoing trait); 0 = inert.

Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
This commit is contained in:
wassname
2026-06-04 17:21:10 +08:00
parent 0bdd84293a
commit 933ce38b0b
5 changed files with 320 additions and 22 deletions
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name = "six"
version = "1.17.0"
@@ -2288,6 +2458,7 @@ dependencies = [
{ name = "einops" },
{ name = "iso-kl-figure" },
{ name = "jaxtyping" },
{ name = "kaleido" },
{ name = "loguru" },
{ name = "numpy" },
{ name = "plotly" },
@@ -2313,6 +2484,7 @@ requires-dist = [
{ name = "einops" },
{ name = "iso-kl-figure", editable = "docs/vendor/isokl_steering_calibration" },
{ name = "jaxtyping" },
{ name = "kaleido", specifier = ">=1.3.0" },
{ name = "loguru" },
{ name = "numpy" },
{ name = "plotly" },