From 8fe562a7701ca3192359ca6faac74b1a5846a681 Mon Sep 17 00:00:00 2001 From: Bimba Shrestha Date: Tue, 28 Jan 2020 11:29:43 -0800 Subject: [PATCH] [automated_benchmarking] Make arguments optional and add --dict argument (#1968) * Make arugments optional and add --dict argument * Removing accidental print statement * Change to more likely scenario for dictionary compression benchmark --- tests/Makefile | 2 +- tests/README.md | 33 ++++--- tests/automated_benchmarking.py | 157 ++++++++++++++++++++++++-------- 3 files changed, 140 insertions(+), 52 deletions(-) diff --git a/tests/Makefile b/tests/Makefile index 241e3f2b4..a27f1dd5b 100644 --- a/tests/Makefile +++ b/tests/Makefile @@ -238,7 +238,7 @@ versionsTest: clean $(PYTHON) test-zstd-versions.py automated_benchmarking: clean - $(PYTHON) automated_benchmarking.py golden-compression 1 current 1 "" 60 + $(PYTHON) automated_benchmarking.py checkTag: checkTag.c $(ZSTDDIR)/zstd.h $(CC) $(FLAGS) $< -o $@$(EXT) diff --git a/tests/README.md b/tests/README.md index 05df82e54..23e00767c 100644 --- a/tests/README.md +++ b/tests/README.md @@ -33,21 +33,32 @@ pull requests from the zstd repo and compare facebook:dev to all of them once, c will continuously get pull requests from the zstd repo and run benchmarks against facebook:dev. ``` -Example usage: python automated_benchmarking.py golden-compression 1 current 1 "" 60 +Example usage: python automated_benchmarking.py ``` ``` -usage: automated_benchmarking.py [-h] directory levels mode emails +usage: automated_benchmarking.py [-h] [--directory DIRECTORY] + [--levels LEVELS] [--iterations ITERATIONS] + [--emails EMAILS] [--frequency FREQUENCY] + [--mode MODE] [--dict DICT] -positional arguments: - directory directory with files to benchmark - levels levels to test eg ('1,2,3') - mode 'fastmode', 'onetime', 'current' or 'continuous' - iterations number of benchmark iterations to run - emails email addresses of people who will be alerted upon regression. - Only for continuous mode - frequency specifies the number of seconds to wait before each successive - check for new PRs in continuous mode +optional arguments: + -h, --help show this help message and exit + --directory DIRECTORY + directory with files to benchmark + --levels LEVELS levels to test eg ('1,2,3') + --iterations ITERATIONS + number of benchmark iterations to run + --emails EMAILS email addresses of people who will be alerted upon + regression. Only for continuous mode + --frequency FREQUENCY + specifies the number of seconds to wait before each + successive check for new PRs in continuous mode + --mode MODE 'fastmode', 'onetime', 'current', or 'continuous' (see + README.md for details) + --dict DICT filename of dictionary to use (when set, this + dictioanry will be used to compress the files provided + inside --directory) ``` #### `test-zstd-speed.py` - script for testing zstd speed difference between commits diff --git a/tests/automated_benchmarking.py b/tests/automated_benchmarking.py index a385c21b0..aaa3010df 100644 --- a/tests/automated_benchmarking.py +++ b/tests/automated_benchmarking.py @@ -94,16 +94,19 @@ def clone_and_build(build): return "../zstd" +def parse_benchmark_output(output): + idx = [i for i, d in enumerate(output) if d == "MB/s"] + return [float(output[idx[0] - 1]), float(output[idx[1] - 1])] + + def benchmark_single(executable, level, filename): - tmp = ( + return parse_benchmark_output(( subprocess.run( [executable, "-qb{}".format(level), filename], stderr=subprocess.PIPE ) .stderr.decode("utf-8") .split(" ") - ) - idx = [i for i, d in enumerate(tmp) if d == "MB/s"] - return [float(tmp[idx[0] - 1]), float(tmp[idx[1] - 1])] + )) def benchmark_n(executable, level, filename, n): @@ -129,6 +132,45 @@ def benchmark(build, filenames, levels, iterations): ] +def benchmark_dictionary_single(executable, filenames_directory, dictionary_filename, level, iterations): + cspeeds, dspeeds = [], [] + for _ in range(iterations): + output = subprocess.run([executable, "-qb{}".format(level), "-D", dictionary_filename, "-r", filenames_directory], stderr=subprocess.PIPE).stderr.decode("utf-8").split(" ") + cspeed, dspeed = parse_benchmark_output(output) + cspeeds.append(cspeed) + dspeeds.append(dspeed) + max_cspeed, max_dspeed = max(cspeeds), max(dspeeds) + print( + "Bench (executable={} level={} filenames_directory={}, dictionary_filename={}, iterations={}):\n\t[cspeed: {} MB/s, dspeed: {} MB/s]".format( + os.path.basename(executable), + level, + os.path.basename(filenames_directory), + os.path.basename(dictionary_filename), + iterations, + max_cspeed, + max_dspeed, + ) + ) + return (max_cspeed, max_dspeed) + + +def benchmark_dictionary(build, filenames_directory, dictionary_filename, levels, iterations): + executable = clone_and_build(build) + return [benchmark_dictionary_single(executable, filenames_directory, dictionary_filename, l, iterations) for l in levels] + + +def parse_regressions_and_labels(old_cspeed, new_cspeed, old_dspeed, new_dspeed, baseline_build, test_build): + cspeed_reg = (old_cspeed - new_cspeed) / old_cspeed + dspeed_reg = (old_dspeed - new_dspeed) / old_dspeed + baseline_label = "{}:{} ({})".format( + baseline_build["user"], baseline_build["branch"], baseline_build["hash"] + ) + test_label = "{}:{} ({})".format( + test_build["user"], test_build["branch"], test_build["hash"] + ) + return cspeed_reg, dspeed_reg, baseline_label, test_label + + def get_regressions(baseline_build, test_build, iterations, filenames, levels): old = benchmark(baseline_build, filenames, levels, iterations) new = benchmark(test_build, filenames, levels, iterations) @@ -137,13 +179,8 @@ def get_regressions(baseline_build, test_build, iterations, filenames, levels): for k, filename in enumerate(filenames): old_cspeed, old_dspeed = old[j][k] new_cspeed, new_dspeed = new[j][k] - cspeed_reg = (old_cspeed - new_cspeed) / old_cspeed - dspeed_reg = (old_dspeed - new_dspeed) / old_dspeed - baseline_label = "{}:{} ({})".format( - baseline_build["user"], baseline_build["branch"], baseline_build["hash"] - ) - test_label = "{}:{} ({})".format( - test_build["user"], test_build["branch"], test_build["hash"] + cspeed_reg, dspeed_reg, baseline_build, test_label = parse_regressions_and_labels( + old_cspeed, new_cspeed, old_dspeed, new_dspeed, baseline_build, test_build ) if cspeed_reg > CSPEED_REGRESSION_TOLERANCE: regressions.append( @@ -171,14 +208,58 @@ def get_regressions(baseline_build, test_build, iterations, filenames, levels): ) return regressions -def main(filenames, levels, iterations, builds=None, emails=None, continuous=False, frequency=DEFAULT_MAX_API_CALL_FREQUENCY_SEC): +def get_regressions_dictionary(baseline_build, test_build, filenames_directory, dictionary_filename, levels, iterations): + old = benchmark_dictionary(baseline_build, filenames_directory, dictionary_filename, levels, iterations) + new = benchmark_dictionary(test_build, filenames_directory, dictionary_filename, levels, iterations) + regressions = [] + for j, level in enumerate(levels): + old_cspeed, old_dspeed = old[j] + new_cspeed, new_dspeed = new[j] + cspeed_reg, dspeed_reg, baesline_label, test_label = parse_regressions_and_labels( + old_cspeed, new_cspeed, old_dspeed, new_dspeed, baseline_build, test_build + ) + if cspeed_reg > CSPEED_REGRESSION_TOLERANCE: + regressions.append( + "[COMPRESSION REGRESSION] (level={} filenames_directory={} dictionary_filename={})\n\t{} -> {}\n\t{} -> {} ({:0.2f}%)".format( + level, + filenames_directory, + dictionary_filename, + baseline_label, + test_label, + old_cspeed, + new_cspeed, + cspeed_reg * 100.0, + ) + ) + if dspeed_reg > DSPEED_REGRESSION_TOLERANCE: + regressions.append( + "[DECOMPRESSION REGRESSION] (level={} filenames_directory={} dictionary_filename={})\n\t{} -> {}\n\t{} -> {} ({:0.2f}%)".format( + level, + filenames_directory, + dictionary_filename, + baseline_label, + test_label, + old_dspeed, + new_dspeed, + dspeed_reg * 100.0, + ) + ) + return regressions + + +def main(filenames, levels, iterations, builds=None, emails=None, continuous=False, frequency=DEFAULT_MAX_API_CALL_FREQUENCY_SEC, dictionary_filename=None): if builds == None: builds = get_new_open_pr_builds() while True: for test_build in builds: - regressions = get_regressions( - MASTER_BUILD, test_build, iterations, filenames, levels - ) + if dictionary_filename == None: + regressions = get_regressions( + MASTER_BUILD, test_build, iterations, filenames, levels + ) + else: + regressions = get_regressions_dictionary( + MASTER_BUILD, test_build, filenames, dictionary_filename, levels, iterations + ) body = "\n".join(regressions) if len(regressions) > 0: if emails != None: @@ -198,42 +279,38 @@ def main(filenames, levels, iterations, builds=None, emails=None, continuous=Fal if __name__ == "__main__": parser = argparse.ArgumentParser() - parser.add_argument( - "directory", help="directory with files to benchmark", default="fuzz" - ) - parser.add_argument("levels", help="levels to test eg ('1,2,3')", default="1,2,3") - parser.add_argument( - "mode", help="'fastmode', 'onetime', 'current' or 'continuous'", default="onetime" - ) - parser.add_argument( - "iterations", help="number of benchmark iterations to run", default=5 - ) - parser.add_argument( - "emails", - help="email addresses of people who will be alerted upon regression. Only for continuous mode", - default=None, - ) - parser.add_argument( - "frequency", - help="specifies the number of seconds to wait before each successive check for new PRs in continuous mode", - default=DEFAULT_MAX_API_CALL_FREQUENCY_SEC - ) + + parser.add_argument("--directory", help="directory with files to benchmark", default="golden-compression") + parser.add_argument("--levels", help="levels to test eg ('1,2,3')", default="1") + parser.add_argument("--iterations", help="number of benchmark iterations to run", default="1") + parser.add_argument("--emails", help="email addresses of people who will be alerted upon regression. Only for continuous mode", default=None) + parser.add_argument("--frequency", help="specifies the number of seconds to wait before each successive check for new PRs in continuous mode", default=DEFAULT_MAX_API_CALL_FREQUENCY_SEC) + parser.add_argument("--mode", help="'fastmode', 'onetime', 'current', or 'continuous' (see README.md for details)", default="current") + parser.add_argument("--dict", help="filename of dictionary to use (when set, this dictioanry will be used to compress the files provided inside --directory)", default=None) args = parser.parse_args() - filenames = glob.glob("{}/**".format(args.directory)) + filenames = args.directory levels = [int(l) for l in args.levels.split(",")] mode = args.mode iterations = int(args.iterations) emails = args.emails frequency = int(args.frequency) + dictionary_filename = args.dict + + if dictionary_filename == None: + filenames = glob.glob("{}/**".format(filenames)) + + if (len(filenames) == 0): + print("0 files found") + quit() if mode == "onetime": - main(filenames, levels, iterations, frequency=frequency) + main(filenames, levels, iterations, frequency=frequenc, dictionary_filename=dictionary_filename) elif mode == "current": builds = [{"user": None, "branch": "None", "hash": None}] - main(filenames, levels, iterations, builds, frequency=frequency) + main(filenames, levels, iterations, builds, frequency=frequency, dictionary_filename=dictionary_filename) elif mode == "fastmode": builds = [{"user": "facebook", "branch": "master", "hash": None}] - main(filenames, levels, iterations, builds, frequency=frequency) + main(filenames, levels, iterations, builds, frequency=frequency, dictionary_filename=dictionary_filename) else: - main(filenames, levels, iterations, None, emails, True, frequency=frequency) + main(filenames, levels, iterations, None, emails, True, frequency=frequency, dictionary_filename=dictionary_filename)