mirror of
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wassnameandClaudypoo
d5876a46d3
Second external review (gpt-5.5, correctness-focused) on the post-cleanup tree. Found no off-by-one/double-flip in the ordinal canonicalization+keying. Fixed the parts I agreed with and could verify on the path the experiment uses: - read.py: NaN-safe answer-token renorm. p_a/pmass poisons the profile with NaN when pmass underflows to 0 at coherence collapse -- exactly when pmass should just flag it. softmax(logp_allowed) is identical when pmass>0 and stable at collapse. - maps.ipsative_pca: move SVD sign-stabilization INTO the helper so it and plot_ipsative_pca share one orientation (saved coords could otherwise mirror the figure). - instrument: assert ordinal answer_space is ['1'..scale_max] IN ORDER (reduce_ordinal weights by position; a reordered space silently inverts E) -- was length-only. - instrument.per_item_categorical: assert per-item dimension/sign agree across frames and frames are distinct, instead of silently averaging under rows[0]'s metadata. - pyproject: move matplotlib+textalloc to an optional `maps` extra; evals stay headless. - tests: drop imports of the deleted reduce_nominal/expected_value, inline the expectation, remove the now-impossible nominal-reducer test. Deferred (flagged to maintainer): two NaN/window issues in guided.py's forced-choice rollout (nominal evaluate() path) -- not exercised by this experiment, can't smoke-test, and the NaN-as-collapse-signal there is a deliberate design. Verified: experiment smoke green on all 4 instruments (no assert false-fires), 6 pure unit tests pass, headless import clean, 16pf map renders. Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
45 lines
1.0 KiB
TOML
45 lines
1.0 KiB
TOML
[project]
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name = "tiny-mfv"
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version = "0.1.0"
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description = "Tiny moral-foundations vignettes eval (Clifford 2015 classic + paraphrase configs) for steering checkpoints."
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requires-python = ">=3.11"
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dependencies = [
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"transformers>=5.7",
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"torch",
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"accelerate",
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"pandas",
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"loguru",
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"python-dotenv",
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"tyro",
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"openai>=1.40",
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"httpx",
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"tqdm",
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"tabulate",
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"datasets",
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"numpy",
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]
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[project.optional-dependencies]
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# tinymfv.maps (culture-map + range viz) only; `import tinymfv` and the evals stay headless,
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# numeric-only consumers (steering-lite) skip this. Install with `pip install tiny-mfv[maps]`.
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maps = [
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"matplotlib>=3.8",
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"textalloc>=1.2.3", # non-overlapping label placement on the maps
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]
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[dependency-groups]
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dev = [
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"openrouter-wrapper",
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"scipy>=1.17.1",
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]
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[tool.uv.sources]
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openrouter-wrapper = { git = "https://github.com/wassname/openrouter_wrapper" }
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[tool.hatch.build.targets.wheel]
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packages = ["src/tinymfv"]
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