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75 lines
2.3 KiB
Python
75 lines
2.3 KiB
Python
import asyncio
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import json
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from pathlib import Path
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from aggregation import aggregate
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from eval_runner import EvalRunner
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from workflow import EvalInput, create_workflow
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async def test_fraction_match():
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wf = create_workflow()
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result = await wf.run(EvalInput(groundtruth="3/5", prediction="6/10"))
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assert result.get_outputs()[0] == 1
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print("PASS: test_fraction_match")
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async def test_float_fraction():
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wf = create_workflow()
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result = await wf.run(EvalInput(groundtruth="1/2", prediction="0.5"))
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assert result.get_outputs()[0] == 1
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print("PASS: test_float_fraction")
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async def test_mismatch():
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wf = create_workflow()
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result = await wf.run(EvalInput(groundtruth="3", prediction="5"))
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assert result.get_outputs()[0] == -1
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print("PASS: test_mismatch")
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async def test_batch():
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dataset = [
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EvalInput(groundtruth="3/5", prediction="6/10"),
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EvalInput(groundtruth="1/2", prediction="0.5"),
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EvalInput(groundtruth="3", prediction="5"),
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]
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runner = EvalRunner(
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workflow_factory=create_workflow,
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aggregate_fn=aggregate,
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concurrency=5,
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input_mapping={"values": "processed_results"},
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)
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result = await runner.run(dataset)
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assert result.metrics["num_correct"] == 2
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assert result.metrics["num_exception"] == 1
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print("PASS: test_batch")
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async def test_data_jsonl():
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"""Run eval on every row in data.jsonl"""
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data_path = Path(__file__).parent / "data.jsonl"
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rows = [json.loads(line) for line in data_path.read_text(encoding="utf-8").splitlines() if line.strip()]
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wf = create_workflow()
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for i, row in enumerate(rows):
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result = await wf.run(EvalInput(
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groundtruth=row["groundtruth"],
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prediction=row["prediction"],
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))
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score = result.get_outputs()[0]
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assert isinstance(score, int), f"Row {i}: expected int, got {type(score)}"
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print(f" Row {i}: score={score}")
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print(f"PASS: test_data_jsonl ({len(rows)} rows)")
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async def main():
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await test_fraction_match()
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await test_float_fraction()
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await test_mismatch()
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await test_batch()
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await test_data_jsonl()
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print("\nAll tests passed!")
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if __name__ == "__main__":
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asyncio.run(main())
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