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https://github.com/wassname/grpo_proj2.git
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wassname
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The fp32+CPU smoke never walked the fast/full bf16+cuda path, so the whole device/dtype class was invisible to the only gate. The GPU path had in fact never run end-to-end. Seven bugs, each masked by fp32+CPU: - svd cache key: numpy has no bf16 -> hash via .view(uint8) - svd save: safetensors needs contiguous cpu tensors - svd cache-hit: load_file returns cpu -> .to(W) for device+dtype - delta_S/delta_S_hack created on cpu -> device=lin.weight.device (else the forward hook mixes cpu/cuda) - V_hack is fp32 (svd) but grads are bf16 -> cast to delta_S's space - completion_nll fed cpu ids to the cuda model in extraction - extraction orientation vote D@V.T mixed bf16 D with fp32 V Smoke is now tiny-random on GPU in bf16 (same device+dtype as fast/full), so this class stays caught. All arms (none/erase/route) and extraction paths (miss/hit/refresh) green: cin_t~0.31-0.41, cout~0 (one_sided identity). Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
73 lines
3.1 KiB
Makefile
73 lines
3.1 KiB
Makefile
set shell := ["bash", "-cu"]
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# Substrate model for real runs (spec §H4). Smoke uses the tiny-random Qwen3.
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MODEL := "Qwen/Qwen3-4B"
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TINY_MODEL := "llamafactory/tiny-random-qwen3" # qwen3 arch, ~6M params, smoke only
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TRAIN := "uv run python -m projected_grpo.train"
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default:
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@just --list
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# Grader gate (no model): hack x mode diagonal. exploited fires iff the matching
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# exploit is present AND the strict oracle rejects. An always-pass grader fails
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# the off-diagonal assert. Wired into smoke so marker drift fails loud.
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check:
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uv run python -m projected_grpo.rewards
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# Self-contained teacher-pool fixture: canned hack/clean completions graded by the
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# real grader and frozen. Injects reward variance (teacher hacks pass ~1.25,
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# tiny-random student ~0) so the GRPO backward / projection / cin paths fire.
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build-pool:
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uv run python -m projected_grpo.build_pool --pool-dir=out/pools/teacher_pool
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# Smoke = the ONLY gate: same harness as production (train.py), tiny-random on GPU
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# in bf16 (same device+dtype as fast/full, so the cuda+bf16 path is actually covered).
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# beartype on so jaxtyping signatures get runtime-checked. 30 steps fires the
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# every-25-step save_ckpt path. erase writes g_proj; cache-miss extracts v_hack.
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smoke *ARGS: build-pool check
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BEARTYPE=1 {{ TRAIN }} smoke --intervention=erase \
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--v-hack-path=out/vhack/v_hack_smoke.safetensors \
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--teacher-pool-dir=out/pools/teacher_pool --mix-ratio=0.5 {{ ARGS }}
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# Vanilla arm: V loaded for the measure_only diagnostic (cin), grad left untouched.
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smoke-vanilla *ARGS: build-pool
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BEARTYPE=1 {{ TRAIN }} smoke --intervention=none \
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--v-hack-path=out/vhack/v_hack_smoke.safetensors \
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--teacher-pool-dir=out/pools/teacher_pool --mix-ratio=0.5 {{ ARGS }}
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# Routing arm: parks the hack-ward grad in δS_hack, ablates at eval. Fires the
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# two-param optimizer path, periodic ablated-eval, online v_hack refresh + the
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# basis_overlap guard, and the final kept-vs-ablated BLUF.
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smoke-route *ARGS: build-pool
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BEARTYPE=1 {{ TRAIN }} smoke --intervention=route \
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--v-hack-path=out/vhack/v_hack_smoke.safetensors \
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--teacher-pool-dir=out/pools/teacher_pool --mix-ratio=0.5 \
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--eval-ablate-every=10 --eval-n-prompts=2 --vhack-refresh-every=10 {{ ARGS }}
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# The trio = every code path the full run walks. Run before any real run.
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smoke-all: smoke smoke-vanilla smoke-route results
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# Run smoke twice: first warms the v_hack cache (miss), second hits it (cache-hit
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# branch). Catches save/scope bugs that only manifest in one.
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smoke-both:
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rm -f out/vhack/v_hack_smoke.safetensors
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just smoke
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just smoke
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# Aggregate logs/run_{arm}_s{seed}.log into one last-5-step table.
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results:
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uv run python scripts/results.py
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# Real runs (Qwen3-4B, GPU). v_hack auto-extracts on cache-miss inside train.
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full-vanilla *ARGS:
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{{ TRAIN }} full --intervention=none {{ ARGS }}
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full *ARGS:
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{{ TRAIN }} full --intervention=erase {{ ARGS }}
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fast-vanilla *ARGS:
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{{ TRAIN }} fast --intervention=none --teacher-pool-dir=out/pools/teacher_pool {{ ARGS }}
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fast *ARGS:
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{{ TRAIN }} fast --intervention=erase --teacher-pool-dir=out/pools/teacher_pool {{ ARGS }}
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