Buckets:
| """Self-check for pilot.py without a GPU: python scripts/test_pilot.py""" | |
| import csv | |
| import os | |
| import sys | |
| import tempfile | |
| sys.path.insert(0, os.path.dirname(__file__)) | |
| import pilot as p | |
| BASE = dict(fictional_rule="R", narrative="N", question="Q", gold_rationale="", changed_feature="", | |
| same_answer_as_base="", written_by="test", review_status="APPROVED", notes="") | |
| def case(fam, var, lang, task, gold): | |
| return dict(BASE, family_id=fam, variant_id=var, language=lang, task_type=task, gold_answer=gold) | |
| def write(rows): | |
| fd, path = tempfile.mkstemp(suffix=".csv") | |
| os.close(fd) | |
| with open(path, "w", encoding="utf-8", newline="") as f: | |
| w = csv.DictWriter(f, fieldnames=p.CASE_COLUMNS) | |
| w.writeheader() | |
| w.writerows(rows) | |
| return path | |
| # parsing | |
| assert p.parse_answer("<think>ANSWER: CONFIRMED_ACTIVE</think>\nok\nANSWER: INSUFFICIENT_EVIDENCE", "status") == ("INSUFFICIENT_EVIDENCE", "ok") | |
| assert p.parse_answer("**ANSWER:** CONFIRMED_NOT_ACTIVE", "status") == ("CONFIRMED_NOT_ACTIVE", "ok") | |
| # CONFIRMED_ACTIVE must not match inside CONFIRMED_NOT_ACTIVE | |
| assert p.parse_answer("ANSWER: CONFIRMED_NOT_ACTIVE", "status")[0] == "CONFIRMED_NOT_ACTIVE" | |
| assert p.parse_answer("no label here", "status") == ("", "no_answer_line") | |
| assert p.parse_answer("ANSWER: maybe", "status") == ("maybe", "invalid") | |
| assert p.parse_answer("ANSWER: e2, E1 ,E3", "order") == ("E2, E1, E3", "ok") | |
| # loading: unapproved rows skipped, bad labels rejected | |
| rows = [case("F1", "base", "fr", "status", "CONFIRMED_ACTIVE"), | |
| dict(case("F1", "base", "darija_fr", "status", "CONFIRMED_ACTIVE"), review_status="PENDING_HUMAN_REVIEW")] | |
| assert [c["case_id"] for c in p.load_cases(write(rows))] == ["F1-base-fr"] | |
| try: | |
| p.load_cases(write([case("F1", "base", "fr", "status", "ACTIVE")])) | |
| raise AssertionError("bad gold label accepted") | |
| except ValueError: | |
| pass | |
| # metrics: both languages of F1 base+contrast, format A | |
| def row(fam, var, lang, task, gold, parsed, manual=""): | |
| c = case(fam, var, lang, task, gold) | |
| st = "ok" | |
| return dict(c, prompt_format="A", parsed_answer=parsed, parse_status=st, | |
| auto_correct=p.auto_score(c, parsed, st), manual_verdict=manual) | |
| rs = [row("F1", "base", "fr", "status", "CONFIRMED_ACTIVE", "CONFIRMED_ACTIVE"), | |
| row("F1", "contrast", "fr", "status", "INSUFFICIENT_EVIDENCE", "INSUFFICIENT_EVIDENCE"), | |
| row("F1", "base", "darija_fr", "status", "CONFIRMED_ACTIVE", "CONFIRMED_ACTIVE"), | |
| row("F1", "contrast", "darija_fr", "status", "INSUFFICIENT_EVIDENCE", "CONFIRMED_ACTIVE"), | |
| row("S1", "sanity", "fr", "extract", "Tlemcen", "Tlemcen", manual="CORRECT"), | |
| row("S1", "sanity", "darija_fr", "extract", "Tlemcen", "Alger")] | |
| m = p.metrics(rs) | |
| assert m["overall"] == "4/5", m | |
| assert m["unjudged"] == 1, m | |
| assert m["by_language"] == {"darija_fr": "1/2", "fr": "3/3"}, m | |
| assert m["contrast_consistency"] == "1/2", m | |
| assert m["cross_language_both_correct"] == "1/2", m | |
| assert m["cross_language_same_answer"] == "1/2", m | |
| # glossary goes right before the story, once, in both formats; no glossary leaves the prompt unchanged | |
| c = case("F4", "base", "darija_fr", "order", "E1, E2") | |
| for fmt in ("A", "B"): | |
| g = p.build_prompt(c, fmt, glossary="psk = because") | |
| assert g.count("psk = because") == 1 and g.index("psk = because") < g.index("N"), (fmt, g) | |
| assert p.build_prompt(c, fmt) == p.build_prompt(c, fmt, glossary=None) | |
| fd, gpath = tempfile.mkstemp(suffix=".txt"); os.close(fd) | |
| open(gpath, "w", encoding="utf-8").write("# comment\npsk = TODO\n") | |
| try: | |
| p.load_glossary(gpath) | |
| raise AssertionError("TODO glossary accepted") | |
| except ValueError: | |
| pass | |
| open(gpath, "w", encoding="utf-8").write("# comment\npsk = because\n9bel ma = before\n") | |
| assert p.load_glossary(gpath) == "psk = because\n9bel ma = before" | |
| print("all checks passed") | |
Xet Storage Details
- Size:
- 3.94 kB
- Xet hash:
- 978d001b4fc6b54add4e3e8bf6a22f0a423807ca058031a68644bf6dfa38302f
·
Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.