Coverage for mlos_bench/mlos_bench/tests/config/environments/local/scripts/bench_run.py: 40%

1#!/usr/bin/env python3 

2# 

3# Copyright (c) Microsoft Corporation. 

4# Licensed under the MIT License. 

5# 

6""" 

7Helper script to run the benchmark and store the results and telemetry in CSV files. 

8 

9This is a sample script that demonstrates how to produce the benchmark results 

10and telemetry in the format that MLOS expects. 

11 

12THIS IS A TOY EXAMPLE. The script does not run any actual benchmarks and produces fake 

13data for demonstration purposes. Please copy and extend it to suit your needs. 

14 

15Run: 

16 ./bench_run.py ./output-metrics.csv ./output-telemetry.csv` 

17""" 

18 

19import argparse 

20from datetime import datetime, timedelta 

21 

22import pandas 

23 

24 

25def _main(output_metrics: str, output_telemetry: str) -> None: 

26 

27 # Some fake const data that we can check in the unit tests. 

28 # Our unit tests expect the `score` metric to be present in the output. 

29 df_metrics = pandas.DataFrame( 

30 [ 

31 {"metric": "score", "value": 123.4}, # A copy of `total_time` 

32 {"metric": "total_time", "value": 123.4}, 

33 {"metric": "latency", "value": 9.876}, 

34 {"metric": "throughput", "value": 1234567}, 

35 ] 

36 ) 

37 df_metrics.to_csv(output_metrics, index=False) 

38 

39 # Timestamps are const so we can check them in the tests. 

40 timestamp = datetime(2024, 10, 25, 13, 45) 

41 ts_delta = timedelta(seconds=30) 

42 

43 df_telemetry = pandas.DataFrame( 

44 [ 

45 {"timestamp": timestamp, "metric": "cpu_load", "value": 0.1}, 

46 {"timestamp": timestamp, "metric": "mem_usage", "value": 20.0}, 

47 {"timestamp": timestamp + ts_delta, "metric": "cpu_load", "value": 0.6}, 

48 {"timestamp": timestamp + ts_delta, "metric": "mem_usage", "value": 33.0}, 

49 {"timestamp": timestamp + 2 * ts_delta, "metric": "cpu_load", "value": 0.5}, 

50 {"timestamp": timestamp + 2 * ts_delta, "metric": "mem_usage", "value": 31.0}, 

51 ] 

52 ) 

53 df_telemetry.to_csv(output_telemetry, index=False) 

54 

55 

56if __name__ == "__main__": 

57 parser = argparse.ArgumentParser( 

58 description="Run the benchmark and save the results in CSV files." 

59 ) 

60 parser.add_argument("output_metrics", help="CSV file to save the benchmark results to.") 

61 parser.add_argument("output_telemetry", help="CSV file for telemetry data.") 

62 args = parser.parse_args() 

63 _main(args.output_metrics, args.output_telemetry)