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twister: footprint: Improve command-line arguments

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Improve Twister command line arguments for memory footprint:

 * group and order footprint arguments meaningfully,
 * clearer help descriptions,
 * resolve logical inconsistences for combinations of arguments,
   in particular:
   `--last-metrics` now forces `--enable-size-report`,
   `--show-footprint` now controls only detailed log output of
       footprint deltas in comparison modes.
 * align twister tests accordingly.

Signed-off-by: Dmitrii Golovanov <dmitrii.golovanov@intel.com>
This commit is contained in:
Dmitrii Golovanov 2024-04-01 22:41:13 +02:00 • committed by Carles Cufí
commit 2ef6b98b98
4 changed files with 112 additions and 78 deletions
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22
scripts/pylib/twister/twisterlib/reports.py
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@ -404,7 +404,7 @@ class Reporting:
logger.debug("running footprint_reports")
deltas = self.compare_metrics(report)
warnings = 0
if deltas and show_footprint:
if deltas:
for i, metric, value, delta, lower_better in deltas:
if not all_deltas and ((delta < 0 and lower_better) or
(delta > 0 and not lower_better)):
@ -417,15 +417,19 @@ class Reporting:
if not all_deltas and (percentage < (footprint_threshold / 100.0)):
continue
logger.info("{:<25} {:<60} {}{}{}: {} {:<+4}, is now {:6} {:+.2%}".format(
i.platform.name, i.testsuite.name, Fore.YELLOW,
"INFO" if all_deltas else "WARNING", Fore.RESET,
metric, delta, value, percentage))
if show_footprint:
logger.log(
logging.INFO if all_deltas else logging.WARNING,
"{:<25} {:<60} {} {:<+4}, is now {:6} {:+.2%}".format(
i.platform.name, i.testsuite.name,
metric, delta, value, percentage))
warnings += 1
if warnings:
logger.warning("Deltas based on metrics from last %s" %
("release" if not last_metrics else "run"))
logger.warning("Found {} footprint deltas to {} as a baseline.".format(
warnings,
(report if not last_metrics else "the last twister run.")))
def synopsis(self):
cnt = 0
@ -456,13 +460,13 @@ class Reporting:
f"{example_instance.testsuite.source_dir_rel} -T {example_instance.testsuite.id}")
logger.info("-+" * 40)
def summary(self, results, unrecognized_sections, duration):
def summary(self, results, ignore_unrecognized_sections, duration):
failed = 0
run = 0
for instance in self.instances.values():
if instance.status == "failed":
failed += 1
elif instance.metrics.get("unrecognized") and not unrecognized_sections:
elif not ignore_unrecognized_sections and instance.metrics.get("unrecognized"):
logger.error("%sFAILED%s: %s has unrecognized binary sections: %s" %
(Fore.RED, Fore.RESET, instance.name,
str(instance.metrics.get("unrecognized", []))))