1b53106907
The recipe runs DM on lottie files with tracing enabled. DM will grab 25 samples evenly distributed across the timeline and the trace will be outputted with Animation entry points. The output of the trace is then parsed and written into perf.json for perf.skia.org ingestion. Example resultant perf.json: https://isolateserver.appspot.com/browse?namespace=default-gzip&digest=31f605ad3c9047f2889893654d57344502794371&as=perf.json Recipe would run on android devices. Bug: skia:8884 Change-Id: I70715febf2bfbd7b1f8fcbd872cb4709638eabd7 Reviewed-on: https://skia-review.googlesource.com/c/skia/+/201472 Commit-Queue: Ravi Mistry <rmistry@google.com> Reviewed-by: Eric Boren <borenet@google.com> |
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.. | ||
android_compile.expected | ||
calmbench.expected | ||
check_generated_files.expected | ||
compile.expected | ||
compute_buildstats.expected | ||
compute_test.expected | ||
housekeeper.expected | ||
infra.expected | ||
perf_canvaskit.expected | ||
perf_pathkit.expected | ||
perf_skottietrace.expected | ||
perf.expected | ||
recreate_skps.expected | ||
skpbench.expected | ||
skqp_test.expected | ||
test_canvaskit.expected | ||
test_lottie_web.expected | ||
test_pathkit.expected | ||
test_skqp_emulator.expected | ||
test.expected | ||
update_go_deps.expected | ||
upload_buildstats_results.expected | ||
upload_calmbench_results.expected | ||
upload_dm_results.expected | ||
upload_nano_results.expected | ||
upload_skiaserve.expected | ||
android_compile.py | ||
calmbench.py | ||
check_generated_files.py | ||
compile.py | ||
compute_buildstats.py | ||
compute_test.py | ||
housekeeper.py | ||
infra.py | ||
perf_canvaskit.py | ||
perf_pathkit.py | ||
perf_skottietrace.py | ||
perf.py | ||
README.md | ||
recreate_skps.py | ||
skpbench.py | ||
skqp_test.py | ||
test_canvaskit.py | ||
test_lottie_web.py | ||
test_pathkit.py | ||
test_skqp_emulator.py | ||
test.py | ||
update_go_deps.py | ||
upload_buildstats_results.py | ||
upload_calmbench_results.py | ||
upload_dm_results.py | ||
upload_nano_results.py | ||
upload_skiaserve.py |
Skia Recipes
These are the top-level scripts which run inside of Swarming tasks to perform all of Skia's automated testing.
To run a recipe locally:
$ python infra/bots/recipes.py run --workdir=/tmp/<workdir> <recipe name without .py> key1=value1 key2=value2 ...
Each recipe may have its own required properties which must be entered as key/value pairs in the command.
When you change a recipe, you generally need to re-train the simulation test:
$ python infra/bots/recipes.py test train
Or:
$ cd infra/bots; make train
The test generates expectations files for the tests contained within each recipe which illustrate which steps would run, given a particular set of inputs. Pay attention to the diffs in these files when making changes to ensure that your change has the intended effect.