[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

diff --git a/tests/Makefile b/tests/Makefile
index 241e3f2b4128e6e58bfc0a97499f4b028148279f..a27f1dd5bb76f1b79df22cfe7831351c128a9173 100644 (file)
--- 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 05df82e540a95908b4afa2f7281bb6aeb0ae46ee..23e00767c39041ce849e2d1eeba05e244512e51b 100644 (file)
--- 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 a385c21b098d1638e352628a0e7e7f62623756d9..aaa3010dff2c641e7c2da770943465e7dc091c3c 100644 (file)
--- 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)