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wassnameandClaude Opus 4.7
646edfc7af
Deletes 7 source files that were superseded but never removed: run.py, grad_proj.py, extract_vhack.py (older twin-NLL extractor), grpo_smoke.py, grpo_proj_smoke.py (smoke harnesses replaced by train.py "smoke" subcommand), phase2_analyze.py (pilot is past), probe_uat.py (UAT pipeline is past). Drops matching justfile recipes (vhack-check, phase2-analyze, probe-uat) and the BASE constant that pointed at run.py. Updates AGENTS/README references to the stale fast-dev-run recipe (now just smoke / smoke-vanilla). Verified by running just smoke-vanilla --steps=2 end-to-end. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
73 lines
3.0 KiB
Markdown
73 lines
3.0 KiB
Markdown
# AGENTS.md — projected_grpo
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**This is novel ML research.** Not in your training data. Extrapolate carefully.
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## Project in one paragraph
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Test whether SVD-basis gradient projection against an extracted hack-direction
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reduces reward-hack rate in GRPO on Nanda's LeetCode benchmark. Differs from
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Rebound (Wu & Tang 2026) by intervening at the *gradient* level rather than the
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*advantage* level. Differs from AntiPaSTO (the user's prior work) by using
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unpaired GRPO rollouts rather than paired-preference contrast.
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Inherit global rules from `~/.claude/CLAUDE.md`.
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## Workflow
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- Read [docs/spec.md](spec.md) for the preregistered plan.
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- Read [docs/brainstorm/extracted_prefs.md](docs/brainstorm/extracted_prefs.md) for design rationale.
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- New sweep arms get recipes in [justfile](justfile) with `# H:` hypothesis comments.
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- `just smoke` before any real run (~1-2 min, beartype on, real pipeline on tiny inputs).
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- Real runs go through `pueue` on the 96GB GPU box. Label each job with `why:` and `resolve:`.
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- Head [docs/RESEARCH_JOURNAL.md](docs/RESEARCH_JOURNAL.md) for latest results.
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- No `tests/` dir; `smoke` is the correctness gate.
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## External dependencies
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`external/rl-rewardhacking/` is Ariahw's repo (verl-based GRPO + LeetCode dataset
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+ reward hacking monitors). We import from it; we do NOT modify it. Sync with
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`just sync-external`.
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## Code style
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- `einops` for reshape, `einsum` for contractions
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- `jaxtyping` on function inputs/outputs only
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- `polars` v1 API; `loguru`; `tabulate` for log tables
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- Single-letter dims: `b s h d r` (batch/seq/head/dim/rank)
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- Capital suffix for projected spaces: `gS` = gradient in SVD top-m basis
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- Greek letters/symbols for math-heavy code (cos α, ||g||)
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## Tensor shapes glossary
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- `v_hack`: `Float[Tensor, "d"]` — single direction in residual stream
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- `V_m`: `Float[Tensor, "d m"]` — top-m right singular vectors of W
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- `g`: `Float[Tensor, "d_out d_in"]` for a weight grad; flatten to `"D"` for projection
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- `cos_align`: `Float[Tensor, ""]` — scalar
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## Compression over accretion
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Every edit should reduce entropy. If you add something, remove something else.
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| Smell | Fix |
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| Defensive guards (`if x is None`) | Let it crash, fix root cause |
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| Magic constants | Name it or derive from spec.md |
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| Two loss variants | Pick one, delete other |
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| Stubs / canned modes | Delete; smoke uses real model |
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## Don't
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- Don't add losses without removing equivalent complexity. Gradient projection
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is a *constraint*, not a competing objective.
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- Don't use defensive programming. Fail fast, crash loudly.
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- Don't fabricate numbers in journal entries or table prototypes. Mark TODO.
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- Don't run real GRPO to test syntax errors. Use `just smoke`.
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- Don't modify `external/rl-rewardhacking/` — it's a third-party pin.
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## Decision points (live)
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- **H4 fallback**: if Qwen3.5-2B hack rate <30% at step 200, swap to Qwen3-4B
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with num_generations=4, batch=64. See spec.md.
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- **verl fallback**: if verl breaks on single 96GB, swap to TRL GRPOTrainer.
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- **Layer choice for SVD/v_hack**: TBD during smoke; default 60-75% depth per Wu-Tang.
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