Something went wrong. Try again.
End-to-end Tinker model training and serving with Eve.
Something went wrong. Try again.
1.7 kB · 49 lines
Python
at main
1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950from __future__ import annotations
import jsonimport stat
import pytest
from training.recipes import get_recipefrom training.run import _write_private_json, build_batches, oversample_cases, promotion_result
def test_batches_are_deterministic_and_complete() -> None: first = build_batches(item_count=10, steps=5, batch_size=4, seed=7) second = build_batches(item_count=10, steps=5, batch_size=4, seed=7) assert first == second assert len(first) == 5 assert all(len(batch) == 4 for batch in first)
def test_oversampling_repeats_only_selected_validation_weakness() -> None: train = get_recipe("capability-placement").generate_cases()["train"] expanded = oversample_cases(train, ("skill", "library", "subagent"), factor=3) assert len(expanded) == len(train) + 2 * 24 assert sum(case.kind == "skill" for case in expanded) == 24 assert sum(case.kind == "library" for case in expanded) == 24 assert sum(case.kind == "subagent" for case in expanded) == 24 assert sum(case.kind == "tool" for case in expanded) == 8
@pytest.mark.parametrize( ("baseline", "candidate", "passed"), [ (0.10, 0.90, True), (0.60, 0.85, False), (0.10, 0.70, False), ],)def test_promotion_requires_absolute_quality_and_gain( baseline: float, candidate: float, passed: bool) -> None: result = promotion_result(baseline, candidate, minimum_accuracy=0.8, minimum_gain=0.3) assert result["passed"] is passed
def test_private_json_writer_uses_mode_0600(tmp_path) -> None: path = tmp_path / "nested" / "receipt.json" _write_private_json(path, {"ok": True}) assert json.loads(path.read_text()) == {"ok": True} assert stat.S_IMODE(path.stat().st_mode) == 0o600