515bda6811
- fill in a couple switches to allow software to rasterize gray8
- add a gray8 config to DM so we can test it
- enable this config on some bots
Today we draw gray8 using SkRasterPipeline, loading it as {g,g,g,1}
and storing using the same fixed luma math as SkLumaColorFilter.
One day it'd be nice to use the color space's luma vector if present.
Can we support this on GPU?
Change-Id: I4ee661c8bd5f33f5db2433ffb6e1bc2483af8397
Reviewed-on: https://skia-review.googlesource.com/92681
Reviewed-by: Brian Osman <brianosman@google.com>
Commit-Queue: Mike Klein <mtklein@chromium.org>
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| .. | ||
| bookmaker.expected | ||
| bundle_recipes.expected | ||
| calmbench.expected | ||
| check_generated_files.expected | ||
| compile.expected | ||
| ct_skps.expected | ||
| housekeeper.expected | ||
| infra.expected | ||
| perf.expected | ||
| recreate_skps.expected | ||
| skpbench.expected | ||
| test.expected | ||
| update_meta_config.expected | ||
| upload_calmbench_results.expected | ||
| upload_coverage_results.expected | ||
| upload_dm_results.expected | ||
| upload_nano_results.expected | ||
| upload_skiaserve.expected | ||
| bookmaker.py | ||
| bundle_recipes.py | ||
| calmbench.py | ||
| check_generated_files.py | ||
| compile.py | ||
| ct_skps.py | ||
| housekeeper.py | ||
| infra.py | ||
| perf.py | ||
| README.md | ||
| recreate_skps.py | ||
| skpbench.py | ||
| test.py | ||
| update_meta_config.py | ||
| upload_calmbench_results.py | ||
| upload_coverage_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 run --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.