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CJohn
33921fcc51
并发 run_all 会触发 workqueue Concurrent access，导致后端进程中断。 为 matrix parallel 内核加进程锁，前端对 run_all 做 pending 去重。
60 lines
1.7 KiB
Python
60 lines
1.7 KiB
Python
"""Numba parallel kernels must stay safe under concurrent callers."""
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from __future__ import annotations
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import threading
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from concurrent.futures import ThreadPoolExecutor
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import numpy as np
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import pytest
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from app.backtest.numba_runtime import run_numba_parallel
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def test_run_numba_parallel_serializes_concurrent_calls():
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"""Two threads must not overlap inside the parallel critical section."""
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active = 0
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max_active = 0
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lock = threading.Lock()
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def work() -> int:
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nonlocal active, max_active
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with lock:
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active += 1
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max_active = max(max_active, active)
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try:
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total = 0
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for i in range(20_000):
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total += i
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return total
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finally:
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with lock:
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active -= 1
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with ThreadPoolExecutor(max_workers=8) as pool:
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list(pool.map(lambda _: run_numba_parallel(work), range(16)))
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assert max_active == 1
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@pytest.mark.skipif(
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__import__("importlib").util.find_spec("numba") is None,
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reason="numba not installed on this platform",
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)
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def test_valid_shift_kernel_survives_concurrent_threads():
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"""Regression for workqueue 'Concurrent access has been detected' crashes."""
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from app.backtest.matrix import valid_shift
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rng = np.random.default_rng(0)
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values = rng.normal(size=(64, 32)).astype(np.float32)
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values[::7, ::3] = np.nan
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def once() -> np.ndarray:
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return valid_shift(values, 3)
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with ThreadPoolExecutor(max_workers=4) as pool:
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results = list(pool.map(lambda _: once(), range(8)))
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baseline = results[0]
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for other in results[1:]:
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np.testing.assert_allclose(baseline, other, equal_nan=True)
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