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745627a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 | """Pytest plugin: per-test wall time (setup/call/teardown) and peak CUDA memory, written as JSONL.
Load with `-p profile_plugin` (directory on PYTHONPATH). Output path: $PROFILE_OUT. Extra metadata copied into every
row: $PROFILE_META (JSON object). Peak memory covers the PyTorch allocator of the pytest process only (not vLLM servers
or `accelerate launch` subprocesses).
"""
import json
import os
import pytest
import torch
_rows = []
_meta = json.loads(os.environ.get("PROFILE_META", "{}"))
@pytest.hookimpl(hookwrapper=True)
def pytest_runtest_protocol(item, nextitem):
row = {"nodeid": item.nodeid, "file": item.nodeid.split("::")[0], "outcome": "passed"}
item._profile_row = row
torch.cuda.reset_peak_memory_stats()
yield
row["peak_alloc_mib"] = torch.cuda.max_memory_allocated() / 2**20
row["peak_reserved_mib"] = torch.cuda.max_memory_reserved() / 2**20
row["total_s"] = sum(row.get(f"{when}_s", 0.0) for when in ("setup", "call", "teardown"))
_rows.append({**_meta, **row})
@pytest.hookimpl(hookwrapper=True)
def pytest_runtest_makereport(item, call):
outcome = yield
report = outcome.get_result()
row = item._profile_row
row[f"{report.when}_s"] = report.duration
if report.outcome != "passed" and row["outcome"] == "passed":
row["outcome"] = report.outcome if report.when == "call" or report.skipped else "error"
def pytest_sessionfinish(session, exitstatus):
with open(os.environ["PROFILE_OUT"], "w") as f:
for row in _rows:
f.write(json.dumps(row) + "\n")
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