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persona_topk: log j-thoughts as positive:/negative: (was pos>neg/neg>pos)

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Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
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wassname
2026-07-10 20:35:29 +08:00
co-authored by Claudypoo
parent 07759f73ce
commit d52b7ece7d
1 changed files with 7 additions and 4 deletions
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jsteer/jacobian.py
+7 -4
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@@ -289,10 +289,13 @@ class Jacobian:
diff = logits_pos - logits_neg # [vocab]
top_pos = diff.topk(k) # pos evokes > neg
top_neg = (-diff).topk(k) # neg evokes > pos
for name, sel in (("pos>neg", top_pos), ("neg>pos", top_neg)):
toks = [tok.decode([i]) for i in sel.indices.tolist()]
logger.info(f"persona_topk {name} top-{k}: {toks}") # SHOULD be persona-
# specific words now, not generic \n/the; generic here => contrast is null.
toks_pos = [tok.decode([i]) for i in top_pos.indices.tolist()]
toks_neg = [tok.decode([i]) for i in top_neg.indices.tolist()]
# SHOULD be persona-specific words (positive vs negative affect here), not
# generic \n/the; generic on both sides means the contrast is null.
logger.info(f"j-thoughts (content of mental workspace, top-{k})\n"
f" positive: {toks_pos}\n"
f" negative: {toks_neg}")
w = (W_U[top_pos.indices].float().mean(0)
- W_U[top_neg.indices].float().mean(0)).cpu()
cfg = JacobianPersonaTopkC(layers=self._steer_layers(layers))