-
Notifications
You must be signed in to change notification settings - Fork 47
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
update dependency versions and fix broken tests #66
Conversation
* move codecov report to github action * enable artifact caching * disable fail-fast because Github Action doesn't support allow_failures yet
Julia 1.6 has made a lot of changes to `show`. Two of the most "breaking change" among it is 1) that `Array{T, 2}` is now shown as `Matrix{T}` and 2) that `RGB{Normed{UInt8, 8}}` is now shown as its alias `RGB{N0f8}` FixedPointNumbers and Colors/ColorTypes have made similar changes, too. This update is not perfect because the reference is hard coded into test cases and it's very likely to break in future. But given that how `op` is shown isn't of high priority here, here I just save myself some time and copy & paste the results so as to make tests pass.
aggfun and mapfun might not support `Gray{N0f8}` well, this is a patch to make sure things goes well here wrt type stability.
Benchmark resultJudge resultBenchmark Report for /home/runner/work/Augmentor.jl/Augmentor.jlJob Properties
ResultsA ratio greater than
Benchmark Group ListHere's a list of all the benchmark groups executed by this job:
Julia versioninfoTarget
Baseline
Target resultBenchmark Report for /home/runner/work/Augmentor.jl/Augmentor.jlJob Properties
ResultsBelow is a table of this job's results, obtained by running the benchmarks.
Benchmark Group ListHere's a list of all the benchmark groups executed by this job:
Julia versioninfo
Baseline resultBenchmark Report for /home/runner/work/Augmentor.jl/Augmentor.jlJob Properties
ResultsBelow is a table of this job's results, obtained by running the benchmarks.
Benchmark Group ListHere's a list of all the benchmark groups executed by this job:
Julia versioninfo
Runtime information
|
For failed
show
tests, I didn't spend much time revisiting theshow
codes, just relaxes the test to make sure it passes.For type instability related to
mean(x)
, I directly promote theeltype
to its float type because floats are more robust and is more likely to be handled correctly. This won't change much for typical machine learning workflows as data is mostly stored inFloat32
. See also JuliaGraphics/ColorVectorSpace.jl#134 (comment)closes #57 closes #60