bvandeusen
e6f128c894
Step 2 of milestone #128. _hygiene_excluded_ids (training_data.py) is the one shared predicate: images carrying any system tag are dropped from every OTHER concepts head training — not positives (a rough wip tagged as a character drags the head toward generic-sketch) and not rejection or sampled negatives (a wip OF character X is not evidence against X). A system tags own head trains on them unfiltered; that is what makes auto-flagging banners work. Selection is split out of train_head as the sklearn-free head_training_ids so CI (no sklearn) can pin the behavior. CCIP: reference prototypes skip hygiene-tagged images — a faceless wip figure region must never become an identity reference — and the ref cache signature now counts hygiene applications, since tagging an image wip changes the reference set without touching character/region counts. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
126 lines
4.4 KiB
Python
126 lines
4.4 KiB
Python
"""Training hygiene (#128): system-tagged images are ABSENT from other
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concepts' training data and from CCIP reference prototypes.
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sklearn only exists in the ml image, so these pin head_training_ids (the
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sklearn-free selection split out of train_head) rather than a full fit —
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the exclusion lives entirely in that selection.
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"""
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import pytest
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from sqlalchemy import insert, select
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from backend.app.models import ImageRecord, ImageRegion, Tag, TagKind
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from backend.app.models.tag import image_tag
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from backend.app.services.ml import ccip
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from backend.app.services.ml.heads import head_training_ids
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from backend.app.services.ml.training_data import _hygiene_excluded_ids
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from backend.app.services.tag_service import TagService
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pytestmark = pytest.mark.integration
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_CFG = {"min_positives": 2, "neg_ratio": 1}
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async def _system_wip(db) -> Tag:
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return (await db.execute(
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select(Tag).where(Tag.is_system.is_(True), Tag.name == "wip")
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)).scalar_one()
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async def _img(db, sha, *, embedded=True):
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rec = ImageRecord(
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path=f"/images/{sha}.jpg", sha256=sha, size_bytes=1, mime="image/jpeg",
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width=1, height=1, origin="imported_filesystem",
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integrity_status="unknown",
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siglip_embedding=([0.1] * 1152 if embedded else None),
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)
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db.add(rec)
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await db.flush()
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return rec
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async def _apply(db, image_id, tag_id):
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await db.execute(insert(image_tag).values(
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image_record_id=image_id, tag_id=tag_id, source="manual",
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))
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@pytest.mark.asyncio
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async def test_hygiene_excluded_ids(db):
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wip = await _system_wip(db)
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flagged = await _img(db, "a" * 64)
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await _img(db, "b" * 64)
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await _apply(db, flagged.id, wip.id)
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excluded = await db.run_sync(lambda s: _hygiene_excluded_ids(s))
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assert excluded == {flagged.id}
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@pytest.mark.asyncio
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async def test_head_selection_drops_hygiene_from_both_sides(db):
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"""A wip-tagged image of concept X is neither a positive NOR a sampled
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negative for X — it is absent entirely."""
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wip = await _system_wip(db)
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concept = await TagService(db).find_or_create("concept_x", TagKind.general)
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clean_a = await _img(db, "a" * 64)
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clean_b = await _img(db, "b" * 64)
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flagged_pos = await _img(db, "c" * 64) # X + wip: dropped positive
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negative_pool = await _img(db, "d" * 64) # untagged: legit negative
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flagged_pool = await _img(db, "e" * 64) # wip only: must not be sampled
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for img in (clean_a, clean_b, flagged_pos):
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await _apply(db, img.id, concept.id)
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await _apply(db, flagged_pos.id, wip.id)
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await _apply(db, flagged_pool.id, wip.id)
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ids = await db.run_sync(lambda s: head_training_ids(s, concept.id, _CFG))
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assert ids is not None
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pos_ids, neg_ids = ids
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assert set(pos_ids) == {clean_a.id, clean_b.id}
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assert negative_pool.id in neg_ids
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assert flagged_pos.id not in neg_ids
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assert flagged_pool.id not in neg_ids
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@pytest.mark.asyncio
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async def test_system_tags_own_head_keeps_hygiene_positives(db):
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"""The wip head itself trains ON wip-tagged images — that's what makes
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auto-flagging work."""
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wip = await _system_wip(db)
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one = await _img(db, "a" * 64)
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two = await _img(db, "b" * 64)
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await _img(db, "c" * 64) # negative pool
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await _apply(db, one.id, wip.id)
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await _apply(db, two.id, wip.id)
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ids = await db.run_sync(lambda s: head_training_ids(s, wip.id, _CFG))
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assert ids is not None
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pos_ids, _ = ids
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assert set(pos_ids) == {one.id, two.id}
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@pytest.mark.asyncio
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async def test_ccip_references_skip_hygiene_images(db):
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"""A wip's figure region must never become an identity prototype, even on
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a single-character image."""
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ccip._REF_CACHE.update(sig=None, refs=None)
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wip = await _system_wip(db)
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char = await TagService(db).find_or_create("Char A", TagKind.character)
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clean = await _img(db, "a" * 64)
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flagged = await _img(db, "b" * 64)
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for img, slot in ((clean, 0), (flagged, 1)):
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vec = [0.0] * 768
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vec[slot] = 1.0
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db.add(ImageRegion(
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image_record_id=img.id, kind="figure",
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rx=0.0, ry=0.0, rw=1.0, rh=1.0,
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ccip_embedding=vec, embedding_version="ccip-test",
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))
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await _apply(db, img.id, char.id)
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await _apply(db, flagged.id, wip.id)
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await db.commit()
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refs = await ccip.character_references(db)
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vectors = refs.get(char.id, [])
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assert len(vectors) == 1
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assert float(vectors[0][0]) == pytest.approx(1.0)
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assert float(vectors[0][1]) == pytest.approx(0.0)
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