Luckperms & essentials permission doesn't work.

Description

Hello, i have a problem with LuckPerms and essentials. All essentials.PermissionExample doesn't work at all. I made a single rank, with "essentials.kit.daily" or "essentials.msg" (the kit was already created) and player doesn't have access to these command, even if i give them the permission. Tested everything, nothing works. All essenitals permission just doesn't work with Luckperms for some reasons.
Any help?
Sorry for the bad english :(
Reproduction steps

Just do /lp editor
apply and in minecraft or console apply the new perms
Wait until a player do the command
"access denied."

Expected behaviour

Give them the god'damn essentials (commands) permissions!
Environment details

Server type/version: Paper version git-Paper-468 (MC: 1.16.5) (Implementing API version 1.16.5-R0.1-SNAPSHOT)
LuckPerms version: v5.2.106

Any other relevant details

Plugins (30): AntiCreeper, AuctionHouse, BeSocial, BuycraftX, ClearLag, CoreProtect, CustomHeads*, DiscordSRV, dynmap*, Dynmap-Essentials*, Essentials, Essentials_WarpGUI, EssentialsSpawn, GoldenCrates, HolographicDisplays, LockettePro, LuckPerms, NexEngine, NoPlugins, OpenInv, PlaceholderAPI, PlayerParticles, QuickShop, ShopGUIPlus, ShopGUIPlusSilkSpawnersBridge, SilkSpawners, Smelt, Vault, WorldEdit, WorldGuard

According to essentials documentation, lets use your kits example. You will need essentials.kit AND essentials.kits.[kitname]. I think you are just using the wrong permission nodes, contact essentials support on it and sending your editor link so we can see the perm nodes you set will be useful in this case.

According to essentials documentation, lets use your kits example. You will need essentials.kit AND essentials.kits.[kitname]. I think you are just using the wrong permission nodes, contact essentials support on it and sending your editor link so we can see the perm nodes you set will be useful in this case.

The problem is, it's not that.
Because every permission doesn't work so,
essentials.msg
essentials.afk
etc, etc doesn't work at all.

Ok so here are some info youy should provide:

screenshot output of /ess version (run command from console)
send your editor link.
Run /lp verbose command <player> <command> replacing the placeholders appropriately

Make sure LuckPerms is your only permissions plugin installed, other perms plugins will take over if any is present making LP not function.
You can find a very small list of permissions plugins in the [migration page] (https://luckperms.net/wiki/Migration) (keep in mind that it's not an exhaustive list and other perms plugins exist).
If you are unsure whether or not one of your plugins is a permissions plugin you can upload a screenshot of /plugins.

Ok so here are some info youy should provide:

screenshot output of /ess version (run command from console)
send your editor link.
Run /lp verbose command <player> <command> replacing the placeholders appropriately
(edit: also ensure you test with a player that are in the correct permission groups.)

Version Server : 1.16.5-R0.1-SNAPSHOT git-Paper-468 (MC: 1.16.5)

.... [19:10:47 INFO]: Version EssentialsX : 2.19.0-dev+74-36422ab
.... [19:10:47 INFO]: Version LuckPerms : 5.2.106
.... [19:10:47 INFO]: Version PlaceholderAPI : 2.10.9
.... [19:10:47 INFO]: Version Vault : 1.7.3-b131
.... [19:10:47 INFO]: Version EssentialsXSpawn : 2.19.0-dev+74-36422ab

with the lp verbose :
Forcing X to execute command fly and reporting all checks made....

.... [19:11:47 INFO]: [Essentials] L'accès à la commande a été refusé pour X.
.... [19:11:47 INFO]: [LP] VB > X - essentials.mail - undefined
.... [19:11:47 INFO]: [LP] VB > X - essentials.fly - undefined
.... [19:11:47 INFO]: [LP] Command execution complete.

in french : [Essentials] Access to the command has been denied for X.
but she is in the... default group (aka member) which... got the essentials.mail and X is in the Roe group so access to the essentials.fly
it's so wierd!

UPDATE :
I deleted the essentials folder (except the users data + warps)
and the permissions finally works!
Sorry about all of this, i should have deleted the essentials folder in the first place!


Fix breaking test

should not really on instances of Jax array checking dtype and shape instead.

LGTM but how did the code pass CI before (both GitHub and Google internal?)

LGTM but how did the code pass CI before (both GitHub and Google internal?)

Also I didn't get the error when running tests on my local computer. Is it maybe due to some numerical differences with a new jax/jaxlib version (I didn't upgrade packages locally)?

Also I didn't get the error when running tests on my local computer. Is it maybe due to some numerical differences with a new jax/jaxlib version (I didn't upgrade packages locally)?

It's not a numerics issue. It's about the class instance of a device buffer with the new jax release. We should not test that anyway because that's testing against Jax internals

It's not a numerics issue. It's about the class instance of a device buffer with the new jax release. We should not test that anyway because that's testing against Jax internals

So there's a second instance of this? The check is still failing at tests/linen/linen_test.py:133

So there's a second instance of this? The check is still failing at tests/linen/linen_test.py:133

You are right. I overlooked it because somehow the second one didn't trigger locally?! I made a seperate PR for the other failure

You are right. I overlooked it because somehow the second one didn't trigger locally?! I made a seperate PR for the other failure


ncon is not as fast as it could be

I rewrote ncon to use directly the backend methods tensordot, transpose, reshape and some others, and it turns out that it is much faster than our current tn.ncon
D = 800
D1=12
D2 = 10
a = np.random.rand(D1,D,D)
b = np.random.rand(D,D,D2)

print(timeit.timeit(lambda: tn.ncon([a,b],[[-1,1,2,],[1,2,-2]],backend='numpy'), number=100)) #takes ~ 3 seconds
print(timeit.timeit(lambda: ncon([a,b],[[-1,1,2,],[1,2,-2]],backend='numpy'), number=100)) #takes ~ 1 second

Nice! I'm curious why that is the case. Is it the python overhead or is it better contraction methods?

Not sure. I'm using tensordot to contract tensors, and I'm doing nothing fancy. The difference seems to depend on the order of the contracted indices.

Hey guys, for comparison I tested the tn.ncon with numpy backend against my own version of numpy ncon and found similar results to Martin (with the tn.ncon taking 4-5 times longer for the example considered above). I also tested my MATLAB version of ncon and found it to have identical performance to my numpy version in this example (which is not surprising since the tensors in the example are large enough such that almost all of the computation time is spent in matrix-matrix multiplication, so the difference in the language-specific overheads is negligible).
I also tried a different example (that now requires tensor permutations):
D1 = 12
D2 = 10
a = np.random.rand(D,D,D1)
b = np.random.rand(D2,D,D)

print(timeit.timeit(lambda: ncon([a,b],[[1,2,-1],[-2,1,2]]), number=100))
print(timeit.timeit(lambda: tn.ncon([a,b],[[1,2,-1],[-2,1,2]],backend='numpy'), number=100))

In this example the tn.ncon was 12-15 times slower than my numpy ncon, so it seems there is a significant efficiency issue for existing numpy backend for tn.ncon.

That's really strange, especially since all ncon should be doing is calling tensordot...

In Glen's code, the tensors are also really small and there's only 1 multiplication happening. I think it's likely just a ton of python overhead.

Whoops, I forgot to specify but I set D = 800 in my example (so the tensor dimensions are the same as in Martins example, the only difference is a permutation is involved). So these are a 800-by-800-by-12 tensor and a 10-by-800-by-800 tensor, which are large enough such that the relative overhead is minimal.

I noticed that the variance of the runtime of tn.ncon is really high. Some runs are as fast as a simple ncon call, but about half of them are really slow.

This happens actually for all other backends as well, with the expection of the tensorflow backend (I didn't test symmetric backend).

The high variance seems to suggest that it could be related to python overhead, in which case though we should definitely switch to the other version.

No arguments on my end.

I'll prepare a PR. It will still be worth finding out what's causing this. If it's some python overhead in the Node or Edge classes we might want to fix it.

@Thenerdstation congrats btw on you last paper! looks very nice!

Thanks haha. Jensen did basically all of the work, but I had the idea 😎.

I think I have found some hints on this issue.
D = 800
D1=12
D2 = 10
a = np.random.rand(D1,D,D)
b = np.random.rand(D,D,D2)

print(timeit.timeit(lambda: np.tensordot(a,b, [[1,2], [0,1]]), number=100)) #takes ~ 2.7 seconds
print(timeit.timeit(lambda: np.tensordot(a,b, [[2,1], [1,0]]), number=100)) #takes ~ 8.5 seconds

and of course they are the same
np.allclose(np.tensordot(a,b, [[1,2], [0,1]]),np.tensordot(a,b, [[2,1], [1,0]]) ) # True

somehow TN utilize the slow axes arguments in tensordot. But this in general is not an issue from TensorNetwork or python overhead here. It is just weird to see the performance difference in numpy.tensordot with barely the same thing. I guess the possible reason is in the slower case, a transpose is explicitly invoked.

And for the high variance part,
tn.ncon([a,b],[[-1,1,2],[1,2,-2]])

this thing actually gives the tensordot axes as [[1,2], [0,1]] and [[2,1], [1,0]] stochastically... for each run, the tensordot axes can be different.

Aw, that makes a ton of sense.
Do we know what order is consistently faster? We could probably add an optimization of it in contract_between.

Do we know what order is consistently faster?

I am not an expert on this so I am not very sure. But I find this problem persists in opt_einsum and numpy with einsum str instead of ncon interface.
D = 800
D1 = 12
D2 = 10
a = np.random.rand(D1,D,D)
b = np.random.rand(D,D,D2)
print(timeit.timeit(lambda: np.einsum("ijk, jkl->il", a, b, optimize=True), number=100)) # 2.5s
print(timeit.timeit(lambda: np.einsum("ikj, kjl->il", a, b, optimize=True), number=100)) # 19s
print(timeit.timeit(lambda: oe.contract("ijk, jkl->il", a, b), number=100)) # 19s
print(timeit.timeit(lambda: oe.contract("ikj, kjl->il", a, b), number=100)) # 2.5s

I will open an issue in opt_einsum, the authors there are experts on this.

Okay, so its seems that the performance difference between the ncon's here relates to how much tensor permutation is done. Hey @mganahl, this lend itself to an easy way to improve the new numpy version of ncon.  If we consider the examples discussed previously:
D = 800
D1=12
D2 = 10
a = np.random.rand(D1,D,D)
b = np.random.rand(D,D,D2)

print(timeit.timeit(lambda: ncon([a,b],[[-1,1,2,],[1,2,-2]]), number=100))
print(timeit.timeit(lambda: ncon([a,b],[[-1,2,1,],[2,1,-2]]), number=100))

then I find the second line takes ncon several times longer than the first, even though they represent the same contraction. However if I put just a few extra lines into ncon (right before the tensordot call):
ind_order = np.argsort(A_cont)
A_cont = A_cont[ind_order]
B_cont = B_cont[ind_order]

then the problem is fixed, and both of the examples evaluate quickly. These lines ensure that tensordot is called with axes = [[1,2], [0,1]] in both instances, rather than axes = [[2,1], [1,0]] in the second instance. In general, I think it would always be a good idea to have the contracted indices follow the order that the indices appear on one of the tensors (i.e. so that at least one of the lists in axes is in ascending order when presented to tensordot). It may also be worthwhile to experiment to find some heuristics along these lines. For instance, I think it would be better to take the axes order for tensordot from the tensor with largest size, such that the permutation is limited to the smaller of the tensors where-ever possible. It may also be advantageous to switch the input order of the tensors given to tensordot in some circumstances.

In a practical calculation (contracting a binary MERA) changing the ncon to ensure that for each call to tensordot that one of the axes is always in ascending order, as described above, results in about a 10% speedup. This seems definitely worthwhile to do!

yeah, seems pretty easy also. We'd need to change this section to account for the better order.
https://github.com/google/TensorNetwork/blob/72360d6b0ec91b2b5b7e0c04fcc1641908def50b/tensornetwork/network_components.py#L1983
@gevenbly, do you wanna give it a try? It could be a nice first PR to the library. :)

@refraction-ray you're also welcome to give it a crack.

@Thenerdstation, I think that Martin is already preparing a PR for the ncon, so we should wait for this. As far as I understand, ensuring this could be just a 1-line fix to ensure that tensordot always has a sequential order for axes, i.e. if we replace:
backend.tensordot(node1.tensor, node2.tensor, [axes1, axes2])

with instead:
ind_order = argsort(axes1)
backend.tensordot(node1.tensor, node2.tensor, [axes1[ind_order], axes2[ind_order]])

then it should do the trick.


XCFramework and/or SPM Support

Is it possible to get a release with an XCFramework or, even better,  SPM support?

Is it possible to get a release with an XCFramework or, even better, SPM support?

Thank you for your feedback. SPM is part of our current plan and we will support this feature recently.

@zeinber awesome. Thanks for getting back to me so quickly. Is there an ETA on getting SPM support at all? We're wanting to start using this library and potentially move to the paid version in the near future if it meets our needs.

Sorry, I can't give you an exact time at the moment.
We will try it on the free version first. You can continue to follow our github. It is expected that this function will be supported in version v1.5


[Bug]: first time use notification shows up after every update

Need to update the current firstload.lock implementation to use vscode.ExtensionContext.globalState instead, which would avoid showing the notification after every minor update.

Fixed in v1.1.24


Crest does not support Domain Reload option

Disabling domain reload breaks Crest currently.

Oh #417 fixed this, so closing.


Support Apache Kylin in EngineSpec

Codecov Report

Merging #4925 into master will decrease coverage by 0.04%.
The diff coverage is 80%.

@@            Coverage Diff             @@
##           master    #4925      +/-   ##
==========================================
- Coverage   77.12%   77.08%   -0.05%
==========================================
  Files          44       44
  Lines        8539     8549      +10
==========================================
+ Hits         6586     6590       +4
- Misses       1953     1959       +6

Impacted Files
Coverage Δ

superset/db_engine_specs.py
52.47% <80%> (-0.23%)
:arrow_down:

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Question: Devise Validateable ... why only validate on a changed email and not always?

https://github.com/plataformatec/devise/blob/517010e2c543920c43378e527ddb62e1bc6eb490/lib/devise/models/validatable.rb#L33
https://github.com/plataformatec/devise/blob/517010e2c543920c43378e527ddb62e1bc6eb490/lib/devise/models/validatable.rb#L36
Looking through the validatable module I see that the validation for email only fires when the email field has been modified.  While this probably covers 99% of the normal cases, it seems like it could leave open a situation where a model is created valid and it becomes invalid because another record is created/updated (perhaps an STI model that doesn't have the same validation enabled, or a bug updates a different record).
It seems that the safest thing to do would be to just not use the email_updated? condition at all and just validate uniqueness all the time.  Is there a non-obvious advantage to the current approach?

Hello @olbrich, thanks for the issue.
I'm not sure what were the historic motivations, but we do have a unique constraint in the migration template, so the only way that duplicated objects could be created is if the migration was modified, which probably means that the application has more complex requirements - and probably validations too.
Changing this behavior would also be backwards incompatible, so we'd need a strong reason to change it. Do you see other reasons why this should be changed?

I'm closing this issue because it had no recent activity.
If you're still facing this on the latest version, please open a new one with all the information requested in the template.
Thank you!

@tegon thanks for the response, sorry I missed it at the time.  I suspect the reason for setting up the validation this way is to minimize the number of database queries needed, since the validates_uniqueness_of will require generate one.


Add react native example

@LinusU I tried creating a react native example using the steps you described in https://github.com/uuidjs/uuid/commit/719e1b4d7c8bcf5093f886dfa8cc9144a04ca1cd
The resulting code is in this PR.
However I get the same error described in #389
yarn run ios produces the following console output:
yarn run v1.22.0
$ react-native run-ios
error Could not find the following native modules: react-native-get-random-values. Did you forget to run "pod install" ?
info Found Xcode workspace "reactnative.xcworkspace"
info Launching iPhone 11 (iOS 13.3)
info Building (using "xcodebuild -workspace reactnative.xcworkspace -configuration Debug -scheme reactnative -destination id=24B666A2-136E-4DCB-AB78-E7D2EA82417D")
..............................................
info Installing "/Users/***/Library/Developer/Xcode/DerivedData/reactnative-bektbbjsunfriaarkvypeymxguti/Build/Products/Debug-iphonesimulator/reactnative.app"
info Launching "org.reactjs.native.example.reactnative"
success Successfully launched the app on the simulator
✨  Done in 76.66s.

Should I worry about
error Could not find the following native modules: react-native-get-random-values. Did you forget to run "pod install" ?

?
And then the simulator looks like this:

Any idea?

error Could not find the following native modules: react-native-get-random-values. Did you forget to run "pod install" ?

It seems like the auto-linking didn't run 🤔
This can be fixed by running pod install in the ios directory.
It would be very interesting to know why it didn't happen automatically 🤔

Thanks @LinusU, running pod install did the trick!

How do I test this?  I haven't worked with react-native yet and have limited time to climb whatever that learning curve is.  Should we find someone more qualified to review this (looking at you, @LinusU) and add him/her to this org?
(Putting on my Devil's Advocate hat) Is this necessary?  It's a lot of code and files for a niche platform.  It's also a slippery slope  (e.g. should we have comparable code bases for Jitter, Titanium, Electron, etc.)   Could we offload this problem to a different project/repo.  For example, "For react-native support please refer to the documentation at https://github.com/LinusU/react-native-get-random-values".  The underlying issue here is, after all, not really a uuid problem.

(@LinusU: My apologies. I'm not trying to pick on you.  Just wearing my curmudgeon hat. :-) )

How do I test this?  I haven't worked with react-native yet and have limited time to climb whatever that learning curve is.  Should we find someone more qualified to review this (looking at you, @LinusU) and add him/her to this org?

See https://github.com/uuidjs/uuid/blob/14307d8962181b54bfdb04fa67c65c0208654a26/examples/reactnative/README.md
Should be as easy as:
npm install
npm run ios

in the example directory.
I would of course also be happy to invite @LinusU to this org if he wants that 😉 .

(Putting on my Devil's Advocate hat) Is this necessary?  It's a lot of code and files for a niche platform.  It's also a slippery slope  (e.g. should we have comparable code bases for Jitter, Titanium, Electron, etc.)   Could we offload this problem to a different project/repo.  For example, "For react-native support please refer to the documentation at https://github.com/LinusU/react-native-get-random-values".  The underlying issue here is, after all, not really a uuid problem.

Hmm, the 7.0.0 release broke stuff for 2 use cases: bundling with Node.js (resolved) and React Native. My motivation to add examples for both use cases was to simply ensure that both cases are solved.
I see the point that it does add a lot of code and that this potentially means more maintenance effort. On the other hand these examples were necessary for myself to ultimately ensure that my code changes did not break certain use cases/platforms so I would need those examples in the future anyways (unless I want to risk breaking stuff for React Native users with future releases). Handling the bug reports, reproducing the issues etc. also meant maintenance effort. So I'm not sure if it would change anything if we simply moved that code into a different repo 🤷♂ ?

I would of course also be happy to invite @LinusU to this org if he wants that 😉 .

I'd be happy to! and to help with reviewing!

It's a lot of code and files for a niche platform

Yeah, it's a bit unfortunate that an empty React Native app still has quite a few files 😅. One potential way forward could be to have this in a separate repo, e.g. uuids/react-native-example.

Should be as easy as:

$ npm run ios

><EMAIL_ADDRESS>ios /Users/kieffer/projects/uuid/examples/reactnative
> react-native run-ios

info Found Xcode workspace "reactnative.xcworkspace"
2020-03-02 10:29:56.540 simctl[71879:1171794] CoreSimulator detected version change.  Framework version (681.17.2) does not match existing job version (681.17).  Attempting to remove the stale service in order to add the expected version.
error Could not get the simulator list from Xcode. Please open Xcode and try running project directly from there to resolve the remaining issues. Run CLI with --verbose flag for more details.
SyntaxError: Unexpected token I in JSON at position 0
    at JSON.parse (<anonymous>)
    at runOnSimulator (/Users/kieffer/projects/uuid/examples/reactnative/node_modules/@react-native-community/cli-platform-ios/build/commands/runIOS/index.js:130:23)
    at Object.runIOS [as func] (/Users/kieffer/projects/uuid/examples/reactnative/node_modules/@react-native-community/cli-platform-ios/build/commands/runIOS/index.js:100:12)
    at Command.handleAction (/Users/kieffer/projects/uuid/examples/reactnative/node_modules/react-native/node_modules/@react-native-community/cli/build/index.js:182:23)
    at Command.listener (/Users/kieffer/projects/uuid/examples/reactnative/node_modules/commander/index.js:315:8)
    at Command.emit (events.js:209:13)
    at Command.parseArgs (/Users/kieffer/projects/uuid/examples/reactnative/node_modules/commander/index.js:651:12)
    at Command.parse (/Users/kieffer/projects/uuid/examples/reactnative/node_modules/commander/index.js:474:21)
    at setupAndRun (/Users/kieffer/projects/uuid/examples/reactnative/node_modules/react-native/node_modules/@react-native-community/cli/build/index.js:255:24)
    at Object.run (/Users/kieffer/projects/uuid/examples/reactnative/node_modules/react-native/node_modules/@react-native-community/cli/build/index.js:202:11)
*** SNIP ***

(eyeroll.gif)

😁 hehe, definitely know that feeling!
I'd be happy to test and review this

OK, so how should we proceed with the examples? So far we already have 6 examples in here: https://github.com/uuidjs/uuid/tree/master/examples
Two of them (browser-rollup and browser-webpack) are being used in the Browserstack tests, so it makes sense to have them in this repo. If we wanted to provide a regression test for the node-webpack case it would make sense to use the example as well, similar reasoning could go for the browser-umd build: These examples could all be used in regression tests, I just haven't set up such tests yet.
So the outlier seems to be somewhat the react-native example, right?
I don't have a strong opinion on this topic so please help me find the best option 🤷♂ 😉 !

OK, so how should we proceed with the examples? So far we already have 6 examples

Is the purpose of examples to provide documentation to users?  Or is it, really, to serve as test cases for CI?  I would argue the latter.  Yes, they're probably occasionally useful to users (maybe?), but I see that as being of secondary interest (despite the "examples" directory name).
Thus, I'd suggest we stick with the "used as part of our CI" as the barrier to entry for /examples.
Regarding react-native specifically... sorry, but I'm not just not seeing where the value here is.  It's not part of our CI (nor should it be, imho).  Nor is it an interesting example for readers. It's a metric shit-ton of files for building an empty app to verify that two-lines of JS do what they're supposed to do, and that are already documented elsewhere.
IMHO, we've already addressed this.  We investigated, we found the problem, and we've updated the project to provide clear guidance on what to do for anyone who runs into it.

OK, I'm almost convinced we should not include this example now 😉
How about making the docs a bit more explicit then by just explicitly writing out the 2 lines that do the magic? #396

I have archived this example in https://github.com/ctavan/uuid-example-react-native and will now close this PR.


Begin explicit serialization functionality

Codecov Report

Merging #113 (a877274) into main (58cf108) will decrease coverage by 1.08%.
The diff coverage is 57.57%.

@@            Coverage Diff             @@
##             main     #113      +/-   ##
==========================================
- Coverage   75.47%   74.38%   -1.09%
==========================================
  Files          29       31       +2
  Lines        1672     1761      +89
  Branches      237      253      +16
==========================================
+ Hits         1262     1310      +48
- Misses        297      333      +36
- Partials      113      118       +5

Impacted Files
Coverage Δ

...exvanyo/composelife/patterns/OscillatorPatterns.kt
100.00% <ø> (ø)

...om/alexvanyo/composelife/patterns/OtherPatterns.kt
100.00% <ø> (ø)

...lexvanyo/composelife/patterns/StillLifePatterns.kt
100.00% <ø> (ø)

...m/alexvanyo/composelife/wear/GameOfLifeRenderer.kt
59.32% <ø> (ø)

...xvanyo/composelife/model/CellStateSerialization.kt
43.07% <43.07%> (ø)

...otlin/com/alexvanyo/composelife/model/CellState.kt
75.00% <66.66%> (-8.88%)
:arrow_down:

...oselife/parameterizedstring/ParameterizedString.kt
100.00% <100.00%> (ø)

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Styling of switchers is broken

Issue description:
After recent updates switcher controls look weird. The label is not fully visible and covered by the switcher.

Hello and thank you for reporting this issue.
We are closing most open GitHub issues with the release of Kirki 4 to start fresh with this major release.
If you are still running into issues after you have tested your theme with Kirki 4, please let us know so we can reopen the issue.
Please note that Kirki 3 is no longer actively supported. Moving forward, we will only provide support the very latest version of Kirki.
Thank you for your understanding.
Best,
David


osd: fix container reboot

It's sad but we can not rely on the prepare container anymore since the
log are flushed after reboot. So inpecting the container does not return
anything.
Now, instead we use a ephemeral container to look up for the
journal/block.db/block.wal (depending if filestore or bluestore) and
build the activate command accordingly.
Signed-off-by: Sébastien Han<EMAIL_ADDRESS>

jenkins test luminous-ansible2.3-bluestore_docker_dedicated_journal

jenkins test luminous-ansible2.3-bluestore_docker_dmcrypt_journal_collocation

jenkins test luminous-ansible2.3-docker_dedicated_journal

jenkins test luminous-ansible2.3-docker_dmcrypt_journal_collocation

jenkins test luminous-ansible2.3-docker_dmcrypt_journal_collocation

jenkins test jenkins test luminous-ansible2.3-docker_dmcrypt_journal_collocation

jenkins test luminous-ansible2.3-docker_dmcrypt_journal_collocation

jenkins test luminous-ansible2.3-docker_dmcrypt_journal_collocation

jenkins test luminous-ansible2.3-docker_dedicated_journal

jenkins test luminous-ansible2.3-bluestore_docker_dedicated_journal

jenkins test luminous-ansible2.3-bluestore_docker_dmcrypt_journal_collocation

jenkins test luminous-ansible2.3-bluestore_docker_dedicated_journal

jenkins test luminous-ansible2.3-bluestore_docker_dedicated_journal

jenkins test luminous-ansible2.3-docker_dedicated_journal

jenkins test luminous-ansible2.3-bluestore_docker_dmcrypt_journal_collocation

jenkins test luminous-ansible2.3-docker_dmcrypt_journal_collocation

jenkins test luminous-ansible2.3-docker_dmcrypt_journal_collocation

jenkins test luminous-ansible2.3-bluestore_docker_dmcrypt_journal_collocation

jenkins test luminous-ansible2.3-bluestore_docker_dedicated_journal

jenkins test luminous-ansible2.3-bluestore_docker_dmcrypt_journal_collocation

jenkins test luminous-ansible2.3-docker_dedicated_journal

jenkins test luminous-ansible2.3-docker_cluster

jenkins test luminous-ansible2.3-cluster

jenkins test luminous-ansible2.3-cluster

jenkins test luminous-ansible2.3-docker_cluster

jenkins test luminous-ansible2.3-docker_cluster

jenkins test luminous-ansible2.3-centos7_cluster

jenkins test luminous-ansible2.3-docker_cluster

jenkins test luminous-ansible2.3-docker_dedicated_journal

jenkins test luminous-ansible2.3-bluestore_docker_dmcrypt_journal_collocation

jenkins test luminous-ansible2.3-bluestore_docker_dedicated_journal

jenkins test luminous-ansible2.3-docker_dmcrypt_journal_collocation

jenkins test luminous-ansible2.3-docker_cluster

jenkins test luminous-ansible2.3-centos7_cluster

jenkins test luminous-ansible2.3-centos7_cluster

jenkins test luminous-ansible2.3-centos7_cluster

jenkins test luminous-ansible2.3-docker_cluster

test in priority:
jenkins test luminous-ansible2.3-docker_dmcrypt_journal_collocation
jenkins test luminous-ansible2.3-bluestore_docker_dedicated_journal
jenkins test luminous-ansible2.3-docker_dedicated_journal
jenkins test luminous-ansible2.3-bluestore_docker_dmcrypt_journal_collocation

waits for https://github.com/ceph/ceph-docker/pull/789


Tag error banner with analyses that are blocking

When biom artifacts in the processing workflow are blocked from deletion due to their presence in an analysis, the error banner should say which analysis(es) are blocking it so the user can track it down.

Closing in favor of: https://github.com/biocore/qiita/issues/2228

Agree


Bad usernames could crash the server

During a test round, some very long usernames caused the server to crash. I don't know if it's just the length or also special characters.

With basically every combination I couldn't get any crashes. Even a combination of ' " ` didn't crash anything.
Also the input tells me to limit the number of letters to 13.-ish for the name.


Crash Upon Dismissal

Not really sure what I'm doing wrong, but couldn't find anybody having the same issues. I'm presenting the image controller as described in the README. Getting several different crashes, always when dismissing the image.
    UIViewController *vcToShowFrom = ((AppDelegate*)[[UIApplication sharedApplication] delegate]).mainNavigationController.visibleViewController;

    JTSImageInfo *imageInfo = [[JTSImageInfo alloc] init];
    imageInfo.imageURL = url;
    imageInfo.referenceRect = vcToShowFrom.view.bounds;
    imageInfo.referenceView = vcToShowFrom.view;

    JTSImageViewController *imageViewer = [[JTSImageViewController alloc]
                                           initWithImageInfo:imageInfo
                                           mode:JTSImageViewControllerMode_Image
                                           backgroundStyle:JTSImageViewControllerBackgroundOption_None];

    [imageViewer showFromViewController:vcToShowFrom transition:JTSImageViewControllerTransition_FromOriginalPosition];```

Crash 1:
-[UITransitionView didAddSubview:]: message sent to deallocated instance 0x15f671e40
Crash 2:
[CATransaction synchronize] called within transaction

I had the same issue and it appear to happen when i calculated tableviewcell height from an attributed string in heightForRowAtIndexPath. i fixed this by caching the heights when it first loads.

Thanks! That fixed the problem!


RFID icon

Icon Request

Icon name: RFID
Tags of this icon: Device
Use case: for app that use RFID technology
Screenshots of similar icons:

https://remixicon.com/icon/rfid-line


fix #394 instance needs to be fully qualified and not abstract

@iocanel sorry about this, ran through the snapshot again with fabric8 and saw a situation where the instance type is fully qualified and the type with the same name is not, which led to a compilation error.  So this needs to be fully qualified.  A simple reproducer didn't seem to induce the behavior though.

After this I was able to successfully align fabric8 to a new sundrio.


react redux is supported?

I'm challenging react, redux server side rendering.
Do hypernova-react support react, redux?
if supported, please tell me integrated code.

sorry.
I can.

class Show extends React.Component {
render() {
return (

ok

);
}
}
export default renderReact(
'show',
Show,
);


Remove trailing empty lines

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prow/istio-unit-tests.sh
7b36d55f46b4045d0f43a132c57563c47cc8fc2d
link
/test istio-unit-tests

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@wattli: The following tests failed, say /retest to rerun them all:

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7b36d55f46b4045d0f43a132c57563c47cc8fc2d
link
/test istio-unit-tests

prow/istio-presubmit.sh
7b36d55f46b4045d0f43a132c57563c47cc8fc2d
link
/test istio-presubmit

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high impact :-)

It's sort of 'fixit'

@wattli: The following tests failed, say /retest to rerun them all:

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7b36d55f46b4045d0f43a132c57563c47cc8fc2d
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/test istio-presubmit

prow/istio-unit-tests.sh
be72046efa92424aaef8137a7bd6b849457607ea
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/test istio-unit-tests

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be72046efa92424aaef8137a7bd6b849457607ea
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prow/istio-presubmit.sh
be72046efa92424aaef8137a7bd6b849457607ea
link
/test istio-presubmit

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[Enhancement] Add ability to Tag environments and warn users of sensitive operations

Sometime people would use it to access production or other sensitive environments. we must add an option to mark/tag environments, with color, or any other solution.
additionally, tag production as "read only" might be a good idea.

We added the colors.
@roikatz shouldn't the user have readonly credentials then?

@deniswsrosa  - Not necessarily, it might be easy to change files with that utility, so at least have the option to set a toggle for an environment to be read only, to be on the safe side.

Work is in progress. This feature will be available in the next release


issue solved

Description
Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.
Do not include any personal data.
Fixes # (issue)
Checklist

[ ] I followed the guidelines in our Contributing document
[ ] I added an explanation of my changes

Additional notes (optional)

Not sure what issue this is solving, thanks for sharing though!


[TSK-281] Changes in file saving and Input Parameter

For saving the tweets I have utilized the username which is available from the tweets scraped. Plus I have added uuid incase the username are same and consecutive. For timeframe since we are only getting dates they wont be helpful so I have used local time at which the tweets are scraped to further distinct them after saving.
In twitter while scraping we could actually use any query and start/end dates while using CLI.
example:-
python twitter_api_scraper.py --query "Hurricane" --start_date "2024-01-01" --end_date "2024-01-31".
For running it using server.py, I have added the new POST endpoint for inputing query, start date and end date.
Now the hardcoded parameters are on the augmentation part where currently its using Wildfire as default even when there is different query. @sk-ram can you take a look on how you can modify augmentation part of code.

@sk-ram could you undo your changes here and move them to a separate PR for #9

@iamMihirT @sk-ram can you make sure that this PR is only fixing the file naming scheme. Remove any other changes and send a separate PR. I want to release this in 2.0 milestone which will go live on Wednesday. Thanks!

@alebg, could you review this pull request?

@alebg, could you review this pull request?

@ydamit, could you please review it?

Closing in favor of #10


Fix/loader on iframe

There was a bug warning that the contact form was not displayed on firefox. This might be due a temporary problem on the target website (out of our reach) or due to a long time waiting. For this case I added a loader so the user doesn´t feel its broken.

Extra:

Fix overview page dots. Remove the one at the end of the title and add the one after the number.

Only one suggestion: could you increase space between loading spinner and Subscribe to our newsletter (...) text?

This was centered and working in all browsers. Maybe you hadn't pushed


x-envoy-upstream-service-time is more large than expected respond time

Describe the bug
We are using seldon-core + ambassador 1.14.3 to build our services.
But recently we found that some respond time from ambassador is too long.
the upstream pod after ambassador just calc n + 1 and return result, and it cost less than 1ms.
As we had the ambassador debug logs below.
[2022-06-16 09:17:38.187][209][debug][http] [source/common/http/conn_manager_impl.cc:254] [C39] new stream
[2022-06-16 09:17:38.187][209][debug][http] [source/common/http/conn_manager_impl.cc:886] [C39][S17049628811525024967] request headers complete (end_stream=false):
':authority', '<IP_ADDRESS>:30080'
':path', '/seldon.protos.Model/Predict'
':method', 'POST'
':scheme', 'http'
'content-type', 'application/grpc'
'te', 'trailers'
'user-agent', 'grpc-java-netty/1.45.1'
'seldon', 'rmd0006'
'namespace', 'mlmodel'
'x-client-trace-id', 'b9e3dcef490f494b96ecbb20b1ff9417'
'grpc-accept-encoding', 'gzip'
'grpc-timeout', '2999982u'

[2022-06-16 09:17:38.187][209][debug][router] [source/common/router/router.cc:425] [C39][S17049628811525024967] cluster 'cluster_rmd0006_groovy_mlmodel_9501_mlmodel' match for URL '/seldon.protos.Model/Predict'
[2022-06-16 09:17:38.187][209][debug][router] [source/common/router/router.cc:582] [C39][S17049628811525024967] router decoding headers:
':authority', '<IP_ADDRESS>:30080'
':path', '/seldon.protos.Model/Predict'
':method', 'POST'
':scheme', 'http'
'content-type', 'application/grpc'
'te', 'trailers'
'user-agent', 'grpc-java-netty/1.45.1'
'seldon', 'rmd0006'
'namespace', 'mlmodel'
'x-client-trace-id', 'b9e3dcef490f494b96ecbb20b1ff9417'
'grpc-accept-encoding', 'gzip'
'grpc-timeout', '2999982u'
'x-forwarded-for', '<IP_ADDRESS>'
'x-forwarded-proto', 'http'
'x-envoy-internal', 'true'
'x-request-id', '330a778e-f9e9-4ace-a6d7-530efe466b97'
'x-envoy-expected-rq-timeout-ms', '3000'

[2022-06-16 09:17:38.187][209][debug][router] [source/common/router/upstream_request.cc:359] [C39][S17049628811525024967] pool ready
[2022-06-16 09:17:38.187][209][debug][http] [source/common/http/filter_manager.cc:778] [C39][S17049628811525024967] request end stream

here we use tcpdump & wireshark trace tcp with upstream pod, it just cost 1ms as expect.

but from logs below , we saw that stream is end after 39ms.
[2022-06-16 09:17:38.227][209][debug][router] [source/common/router/router.cc:1174] [C39][S17049628811525024967] upstream headers complete: end_stream=false
[2022-06-16 09:17:38.227][209][debug][http] [source/common/http/conn_manager_impl.cc:1501] [C39][S17049628811525024967] encoding headers via codec (end_stream=false):
':status', '200'
'content-type', 'application/grpc'
'grpc-encoding', 'identity'
'grpc-accept-encoding', 'gzip'
'x-envoy-upstream-service-time', '39'
'date', 'Thu, 16 Jun 2022 09:17:37 GMT'
'server', 'envoy'

[2022-06-16 09:17:38.227][209][debug][http] [source/common/http/conn_manager_impl.cc:1517] [C39][S17049628811525024967] encoding trailers via codec:
'grpc-status', '0'

The ambassador respond time is more large than service pod respond time.
To Reproduce
Steps to reproduce the behavior:

Go to '...'
Click on '....'
Scroll down to '....'
See error

Expected behavior
A clear and concise description of what you expected to happen.
Versions (please complete the following information):

Ambassador: [e.g. 0.32.1]
Kubernetes environment [e.g. Minikube, bare metal, Google Kubernetes Engine]
Version [e.g. 1.8.1]

Additional context
Add any other context about the problem here.

Has latency been a problem with your deployment?  As I understand there can be various reasons for this x-envoy-upstream-service-time value and it doesn't seem excessive.  Do you perhaps have a large number of Mappings?

We suspect Envoy’s value includes network latency and can vary depending on your network and number of Mappings.


feat(Jenkinsfile.release): creates artifact with correct buildinfo

This PR creates a ready-to-be-copied buildinfo.json to speed up the bump-process and make it "less manual", whoever creates a bump doesnt have to check for the correct sha or something, just fire up the jenkinsjob and copy & paste the buildoinfo to DCOS.
In the Future we want to automate this even more - step by step 👍

run integration tests

Alfred test this

run system tests


Synologydsm: Error if NAS is not running

If the NAS is switched off, I get the following error:

File "/home/user/.local/lib/python3.7/site-packages/homeassistant/components/synologydsm/sensor.py", line 115, in run_setup
for disk in config.get(CONF_DISKS, api.storage.disks):
TypeError: 'NoneType' object is not iterable

I fixed this in my installation by adding this code:
        # Handle all volumes
        if config.get(CONF_VOLUMES, api.storage.volumes) != None:      # <======
          for volume in config.get(CONF_VOLUMES, api.storage.volumes):
            sensors += [SynoNasStorageSensor(
                api, variable, _STORAGE_VOL_MON_COND[variable], volume)
                        for variable in monitored_conditions
                        if variable in _STORAGE_VOL_MON_COND]

        # Handle all disks
        if config.get(CONF_DISKS, api.storage.disks) != None:         # <======
          for disk in config.get(CONF_DISKS, api.storage.disks):
            sensors += [SynoNasStorageSensor(
                api, variable, _STORAGE_DSK_MON_COND[variable], disk)
                        for variable in monitored_conditions
                        if variable in _STORAGE_DSK_MON_COND]

thanks,I find here also need to add
    if self.var_id in network_sensors or self.var_id in memory_sensors:
        attr = getattr(self._api.utilisation, self.var_id)(False)
        if attr != None:   # <======
            if self.var_id in network_sensors:
                return round(attr / 1024.0, 1)
            if self.var_id in memory_sensors:
                return round(attr / 1024.0 / 1024.0, 1)
    else:
        return getattr(self._api.utilisation, self.var_id)

@martin3000 I'm also getting this error. Could you submit a pull request with your changes? Modifying the core should not be the solution 🙈


Version 0.1.8 is not published on CocoaPods trunck

[!] Unable to satisfy the following requirements:

- `AFNetworking-RACExtensions (~> 0.1.8)` required by `Podfile`

I'd like to second this. Publishing the last version would be very helpful. Thanks.

This issue and #35 are duplicates.
@kastiglione Shall we give the people what they want?

Oh please

Any updates on this?

I pull request, update to 0.1.8
https://github.com/CocoaPods/Specs/pull/13061

Um has anyone claimed this pod?

For those who needs 0.1.8, add this to your Podfile
pod 'AFNetworking-RACExtensions', :git => 'https://github.com/CodaFi/AFNetworking-RACExtensions.git', :commit => '108d9bdf08a644c754e48f4a4896f7a23841dce7'

Q: Why can't I use :tag => '0.1.8'?
A: Because the podspec file under tag 0.1.8 points to tag 0.1.6.
Q: Why do I need to specify the :commit?
A: Because podspec got updated and points to tag 0.1.8 in this commit.
Q: What if I don't specify the :commit?
A: Then you will get the latest master, which may be or may not be what you want.

Ping @kastiglione @tonyarnold, please help.
Or, can you add me as a contributor? I can help in the future.
http://guides.cocoapods.org/making/getting-setup-with-trunk#adding-other-people-as-contributors

@chiahsien I'm not an admin here. Why not open a pull request?

@kastiglione
Cocoapods doesn't accept pull request for newer podspec anymore.
The only way to submit podspec is to use pod trunk.

You can see my previous life link for more information about pod trunk.

@chiahsien:

"For those who needs 0.1.8, add this to your Podfile..."

Thanks for the tip. In my case, this pod is a dependency on an internal development pod; I don't want to have to fork the spec repo just for this, nor do I want my team to have to manage that burden.
Getting the spec updated is still really important to us, though.

@chiahsien I'm not an admin of this project. I'm not an owner/admin of the podspec. I don't know if there's anything I can do for you.

@kastiglione I don't remember signing up as an admin either, so that leaves @tonyarnold

If someone else wants to claim the pod, go for it — no offense intended to @CodaFi but I haven't used this library in a long time. I wouldn't be testing it properly even if I did put the podspec together.

@CodaFi Maybe you are the owner even though you didn't sign up?
Can you try to claim it then add me to the contributor list?
http://guides.cocoapods.org/making/getting-setup-with-trunk#claiming-an-existing-library

Well I'll be damned.  I am an admin, apparently.  I'll remove you (or remove yourself) from the list then @tonyarnold, I completely understand where you're coming from.  Thanks for taking the time that you did maintaining this crazy thing.

@chiahsien Do you have an email you would like me to use to add you to the contributors list?

@CodaFi chiahsien AT gmail.com, thank you!

I've just pushed 0.1.8 to the trunk.
I really can't apologize enough for the delay.

@chiahsien Done!

@chiahsien I'm going to remove that comment to keep your email private.

Thank you all for your efforts!


Contribution "Gravity sim of 3 bodies"

Demo -> https://editor.p5js.org/Lets_A_Code/sketches/_swz04pem

Duplicate of #2334


Embeddable Isolated Story

Is your feature request related to a problem? Please describe.
I'd like to request the isolated embed feature that Storybook provides: https://storybook.js.org/docs/sharing/embed
This provides the ability to strip away the wrapping UI and present a isolated component story which can be embedded in
Describe the solution you'd like
Replication of the Storybook feature set, specifically: https://storybook.js.org/docs/sharing/embed#embed-a-story-without-the-toolbar where viewMode=story is set as a URL param.
This would hide the separator (resizer), aside (nav & search), and header/footer (addons)

Describe alternatives you've considered
I could create my own decorator that looks at the URL for a specific param and then apply styles to hide Ladle UI, but this feels like a feature set that others are going to want and should be built into Ladle

I'm sorry, I somehow completely missed the fact that there's already a fullscreen mode that accomplishes this


Prisma Cloud Scan fails for DAPR dashboard deployment

Describe the proposal
Prisma Cloud Scan fails for following parameters for DAPR dashboard deployment

Mount container's root filesystem as read only
Do not disable default seccomp profile
Restrict container from acquiring additional privileges

I am not able to find relevant support to resolve the same in latest dapr dashboard 0.15.0 helm chart
Expect following feature support in the helm chart:
securityContext:
  allowPrivilegeEscalation: false
  readOnlyRootFilesystem: false
  seccompProfile:
    type: RuntimeDefault

Hi Team
Any updates / comments on this ?


Add error messaging for page weight issues

Having weight assigned to each page is an important part of Quire as it determines the necessary reading order of a Quire publication. We should add error handling into the footer-buttons.html and navbar.html partials to double-check for three weight-related requirements:

All pages have a specified weight
All page weights are greater than zero
All page weights are unique

Below is some sample code that could be further refined. And there should be some discussion about when we should be using Hugo's errorf (which stops the build process and posts the message text) versus warnf (which posts the message text but allows the build to continue). https://gohugo.io/functions/errorf/
{{ $pageWeights := "" }}
{{ range $pages }}

  {{ if .Weight }}

    {{ if eq .Weight "0" }}
    {{ errorf "Your %q page weight is zero. Make it 1 or greater to ensure page navigation links work properly." .Path }}
    {{ end }}

    {{ if in (string $pageWeights) (string .Weight) }}
    {{ errorf "Your %q file has the same page weight as another page in your project. Please make sure all page weights are unique." .Path }}
    {{ else }}
    {{ $pageWeights = delimit (slice $pageWeights .Weight) ", " }}
    {{ end }}

  {{ else }}

    {{ errorf "Your %q page doesn’t have an assigned weight. Please assigne a unique weight greater than zero to ensure your project pages are ordered correctly." .Path }}

   {{ end }}

{{ end }}

Closed with PR #169


How to setup larger timeout?

My IBM-I server is small / very resource limited and seems that because of that when is retrieving file lists I always get "Connection to XXXX has timed out".
How can I setup a larger timeout?

Right now it is hardcoded to 35000ms, but perhaps it is your iBM i system timing out your SSH connection?

Verify the TCP keepalive on the iSeries (CHGTCPA). - TCP keep alive
Any timeout settings in the sshd_config

Hi @worksofliam
I just found out that the problem is when "liblist" runs qsh is returning exit code 9 but "timeout", "end" and "error" events  are mapped to "disconnected" function - I will look deeper into why my IBM-I is returning exit code other than 0 (FWIW is OS 7.1), also get deeper into how to work with VS plugins and add a different function for error.

This is likely the same issue as https://github.com/halcyon-tech/vscode-ibmi/issues/389.
Also, for the record, we do not formally support 7.1. I will help where I can though.

@worksofliam
Thanks - next time I will extend my search to closed issues.
Seems that the open utilities aren't well configured, looks like I will have to continue using PDM/SEU on that host.
I'm closing the issue.


[Issue] targetSDK 31: Manifest merger fails

While trying to raise targetSDK of Omega, we have faced the error message:
Manifest merger failed : android:exported needs to be explicitly specified for <activity>...
And after long researching and digging for the reason(s), it seems that the manifest part of the libTaskbar (gets merged to the other projects' manifests) is missing the attribute in each single component.
Solving this should be relatively easy through adding android:exported="true/false" to each component.
Tell me if I can help out on this. Cheers!

Thanks for bringing this to my attention. I've been meaning to get a new release of Taskbar / libtaskbar out anyway, I'll get this done by this weekend.
Does libtaskbar need to target API 31 as well?  I was planning on staying on 30 for now, but should be able to bump it up to 31 if needed.

This should now be fixed for the next release, which I'm still hoping to get out by the end of the weekend.


Support for AirQ

Description:
Discuss with Alexey about supporting AirQ in webUI so we can continue fw project

Some units need to be fixed


find definition in menu as shortcut

Hi,
in menus/connect-kdb-q.cson I can see the KDB-Q menu entries

Connect to a server
Exec Line
Exec selection

but I cannot find "Find definition" and "Find reference" which are also part of the KDB-Q menu which confuses me a bit.
My goal is to add a shortcut to "Find definition" and "Find reference" in keymaps/connect-kdb-q.cson but I guess there would have to be a new event to be registered in connect-kdb-q
Thanks

Hi,
This is because Find definition and reference are in autocomplete-kdb-q.
You can add any shortcut in your main cfg I think using the cmd name.
WBR, Andrey Kozyrev.
2018-07-23 13:29 GMT+03:00 MaxHoefl<EMAIL_ADDRESS>
Hi,
in menus/connect-kdb-q.cson I can see the KDB-Q menu entries

Connect to a server
Exec Line
Exec selection

but I cannot find "Find definition" and "Find reference" which are also
part of the KDB-Q menu which confuses me a bit.
My goal is to add a shortcut to "Find definition" and "Find reference" in
keymaps/connect-kdb-q.cson but I guess there would have to be a new event
to be registered in connect-kdb-q
Thanks
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.


Suppress keyword argument warnings in Ruby 2.7

This PR suppresses the following keyword argument warnings when using Ruby 2.7.
/Users/koic/src/github.com/dry-rb/dry-configurable/lib/dry/configurable/settings/argument_parser.rb:41:
warning: The last argument is used as the keyword parameter
/Users/koic/src/github.com/dry-rb/dry-configurable/lib/dry/configurable/settings/argument_parser.rb:44:
warning: for `options' defined here

And this PR fixes the following and other testing errors occurred by warning gem.
% ruby -v
ruby 2.7.0dev (2019-09-14T09:21:37Z master 39c37acf86) [x86_64-darwin17]
% bundle exec rake
(snip)

  143) Dry::Configurable when included with a constructor in the base
       class allows to configure class instances
     Failure/Error: Warning.process { |w| raise RuntimeError, w }

     RuntimeError:
       /Users/koic/src/github.com/dry-rb/dry-configurable/lib/dry/configurable/settings/argument_parser.rb:41:
warning: The last argument is used as the keyword parameter
     # ./spec/spec_helper.rb:21:in `block in <top (required)>'
     # ./lib/dry/configurable/settings/argument_parser.rb:41:in `call'

cf. https://bugs.ruby-lang.org/issues/14183

thanks, this should work


KAFKA-17193: Pin all external GitHub Actions to the specific git hash

Backporting https://github.com/apache/kafka/pull/17461 to 3.8
More detailed description of your change,
if necessary. The PR title and PR message become
the squashed commit message, so use a separate
comment to ping reviewers.
Summary of testing strategy (including rationale)
for the feature or bug fix. Unit and/or integration
tests are expected for any behaviour change and
system tests should be considered for larger changes.
Committer Checklist (excluded from commit message)

[ ] Verify design and implementation
[ ] Verify test coverage and CI build status
[ ] Verify documentation (including upgrade notes)

@chia7712 or @mumrah do you have a second to review this one?
I need to generate the docker images and it fails.


color_threshold colors are incorrect when also configuring the y-axis.

Checklist

[x] I updated the card to the latest version available
[x] I cleared the cache of my browser
[x] I verified that I'm really running the lastest version in my browser console
[x] I checked if there is another issue opened with the same problem

Describe the bug
The gradient applied by color_threshold appears to be calculated over the range of sensor values, rather than the actual y-axis values. So they are correct if the y-axis is auto-generated, but incorrect if the y-axis scale is configured with a specific minimum, or if another series is also displayed. The screenshots below demonstrate this best.
Version of the card
Version: 2.1.2
To Reproduce
This is the configuration I used:
type: custom:apexcharts-card
experimental:
  color_threshold: true
header:
  show: true
  title: Humidity
  show_states: true
  colorize_states: true
graph_span: 24h
yaxis:
  - min: 0
    max: ~50
    decimals: 0
    align_to: 10
series:
  - entity: sensor.ams_humidity
    color: lightblue
    type: area
    stroke_width: 1
    color_threshold:
      - value: 0
        color: white
      - value: 15
        color: cyan
      - value: 30
        color: green
      - value: 30
        color: red
      - value: 40
        color: black
        opacity: 1

Screenshots
This screenshot shows it working correctly.
Note that color_threshold is set with overlapping values at 30, to create a hard division between green and red at 30.
The resulting gradient goes from a light green, through the hard transition to red, and up to a little bit of black.

This screenshot is the exact same data and configuration, except the a y-axis set for 0 to ~50.
You can see that it gets the exact same gradient applied. The hard division happens around 14 instead of 30, and the low-end colors don't appear.

This screenshot adds another series which extends the axis, instead of configuring it manually.
Again the same gradient is applied. Notice that the hard division happens around 27.5.

Expected behavior
I expect the color gradient to match the configured values, regardless of y-axis scale.
Desktop:

Browser: Chrome
Version: 128.0.6613.84

Smartphone:

Device: Samsung Galaxy S21 Ultra
OS: Android 14
Browser: Home Assistant App
Version 2024.07.3-full

Additional context
N/A

I was also facing this bug, so I did a little bit debugging and I want to share my findings in case someone else finds them useful:
Apparently the apexcharts library only supports relative coordinates as the colorStops used for the gradient filling. Since the color_threshold property uses absolute coordinates, they need to be transfered into relative coordinates first which is done by the _computeFillColorStops function. To do that, the colors of the minimum and maximum value of the yaxis are determined as they consitute 0 and 100% in the relative coordinates and then the colors between are interpolated.
These border values are determined in lines 929 and 930 of apexcharts-card.ts and the problem is that it is assumed that the border values of a series match the border values of the yaxis which is obviously not the case when the borders of the yaxis are customized. I don't know how to fix the problem properly as I have quite some trouble understanding the datastructures used, but I was able to find a workaround for at least the cases with only a single yaxis:
let min = this._graphs?.[serie.index]?.min;
let max = this._graphs?.[serie.index]?.max;
if (min === undefined || max === undefined) return [];
const yaxis = Array.isArray(this._config?.apex_config?.yaxis) ? this._config?.apex_config?.yaxis?.[0] : this._config?.apex_config?.yaxis;
if (yaxis?.min !== undefined) min = typeof yaxis.min === 'number' ? yaxis.min : yaxis.min(min);
if (yaxis?.max !== undefined) max = typeof yaxis.max === 'number' ? yaxis.max : yaxis.max(max);


Is anything besides sha256_shani worthwhile on x64?

So, I wrote this little Nim program:
{.passL: "-lhashtree -lcrypto".}
proc sha256_1_sse*(o, i: pointer; n: uint64) {.importc,header:"hashtree.h".}
proc sha256_1_avx*(o, i: pointer; n: uint64) {.importc,header:"hashtree.h".}
proc sha256_4_avx*(o, i: pointer; n: uint64) {.importc,header:"hashtree.h".}
proc sha256_8_avx2*(o, i: pointer; n: uint64) {.importc,header:"hashtree.h".}
proc sha256_16_avx512*(o, i: pointer; n: uint64) {.importc,header:"hashtree.h".}
proc sha256_shani*(o, i: pointer; n: uint64) {.importc,header:"hashtree.h".}
proc SHA256(i:pointer, n:uint64, o:pointer){.importc, header: "openssl/sha.h".}
import std/[random, stats, times, math], cligen/strUt

type Kind* = enum ssl, sse, a1, a4, a28, a5, ni

proc sh64B(kind: Kind; o, i: pointer) =
  case kind
  of ssl: SHA256(i, 64, o)
  of sse: sha256_1_sse(o, i, 1) # Count is of 64B blocks!
  of a1:  sha256_1_avx(o, i, 1)
  of a4:  sha256_4_avx(o, i, 1)
  of a28: sha256_8_avx2(o, i, 1)
  of a5:  sha256_16_avx512(o, i, 1)
  of ni:  sha256_shani(o, i, 1)

proc benchK(k: Kind, x: seq[int64], bN=128, mN=4, aN=8) =
  var o: array[32, byte]    # Output hash/digest
  var s = 0
  var ra: RunningStat
  for a in 0 ..< aN:        # Average loop
    var rm: RunningStat
    for m in 0 ..< mN:      # Minimum loop
      let t0 = epochTime()
      for b in 0 ..< bN:    # 64B block loop
        sh64B k, o[0].addr, x[8*(b+mN*(m+aN*a))].unsafeAddr
        try: s += cast[ptr int](o[0].addr)[]
        except OverflowDefect: discard # Allow overflow
      rm.push epochTime() - t0
    ra.push rm.min*1e9      # Times in nanoseconds
  let scl = 1.0/bN.float
  let sigDt = ra.standardDeviation*scl/ra.n.float.sqrt
  echo k, " ", fmtUncertain(ra.mean*scl, sigDt), " ", s

proc bench*(kinds: seq[Kind], bN=256, mN=4, aN=8) =
  var x: seq[int64]
  for j in 1 .. 8*bN*mN*aN: x.add rand(Natural.high)
  for k in kinds: benchK(k, x, bN, mN, aN)

when isMainModule:
  when defined(release): randomize()
  when defined(linux): import cligen/osUt; setAffinity()
  import cligen; dispatch bench

and I tried it on 3 CPUs - all on bare metal Linux; No virtual machine/cloud/etc. and I got:
<EMAIL_ADDRESS>./nbench sse a1 a4 a28 ssl
sse 275.90 +- 0.22 -4855863120176234208
a1  277.07 +- 0.16 -4855863120176234208
a4  284.8  +- 5.3  -4855863120176234208
a28 278.00 +- 0.16 -4855863120176234208
ssl 259.14 +- 0.22 -4855863120176234208

<EMAIL_ADDRESS>./nbench sse a1 a4 a28 ni ssl
sse 340.55 +- 0.15 -4055874101654296147
a1  714.12 +- 0.13 -4055874101654296147
a4  716.39 +- 0.13 -4055874101654296147
a28 719.29 +- 0.15 -4055874101654296147
ni  63.64  +- 0.15 -4055874101654296147
ssl 108.24 +- 0.13 -4055874101654296147

i7-1270P$ ./nbench sse a1 a4 a28 ni ssl
sse 256.00 +- 0.11 -1773879145443525967
a1  257.5  +- 1.3  -1773879145443525967
a4  256.23 +- 0.11 -1773879145443525967
a28 256.81 +- 0.14 -1773879145443525967
ni  41.21  +- 0.14 -1773879145443525967
ssl 68.1   +- 2.4  -1773879145443525967

At least from these preliminary results, it seems like when an x64 CPU supports SHA-NI extensions, you can get about a 1.7X boost.  However, when it does not support those extensions then whatever other things openssl (vsn-1.1.1t) is doing are "better enough" to more than compensate for the work savings of your approach.  Is this consistent with other testing/user reports you have seen?  Is true avx512 some breakthrough here?  Looking at how much the sha-ni extensions beat 8_avx2 makes it seem unlikely.
In light of all that, might it make sense to simplify to just an SHA-NI branch?  At least on x64?

I don't understand Nim but my guess from that code is that you're hashing small trees, in which case this assembly is essentially the same as openssl's (which was also taken from Intel's). You can look at the benchmarks in the REAMDE.md for a x64 without shani support and AVX2 being 5 times faster than openssl. Shani is still faster than that. Only AVX512 beats shani (and it's comparable to it) on large trees.

You are right.  Those above are just one-at-a-time results. { My battling with the assembler infinite recursion must have addled my brain. ;-) }  Just to correct the record, in case any future onlooker is curious, this is an updated (and somewhat enhanced) Nim usage:
{.passL: "-lhashtree -lcrypto".} # May also need "-L" if uninstalled
proc sha256_1_sse*(o, i: pointer; n: uint64) {.importc,header:"hashtree.h".}
proc sha256_1_avx*(o, i: pointer; n: uint64) {.importc,header:"hashtree.h".}
proc sha256_4_avx*(o, i: pointer; n: uint64) {.importc,header:"hashtree.h".}
proc sha256_8_avx2*(o, i: pointer; n: uint64) {.importc,header:"hashtree.h".}
proc sha256_16_avx512*(o,i: pointer; n: uint64) {.importc,header:"hashtree.h".}
proc sha256_shani*(o, i: pointer; n: uint64) {.importc,header:"hashtree.h".}
proc SHA256(i:pointer, n:uint64, o:pointer){.importc, header: "openssl/sha.h".}

template pua(T: typedesc): untyped = ptr UncheckedArray[T]
type
  Kind*   = enum ssl, sse, a1, a4, a28, a5, ni  #XXX --> AUTO
  Block*  = array[64, byte]     # Inputs
  Digest* = array[32, byte]     # Outputs

proc sha256_64Bs*(kind: Kind; o: pua Digest; i: pua Block; bN: int) =
  ## A batch interface to sha256 hashing of `bN` 64 Byte blocks.
  case kind   #XXX Test CpuPlatform in {amd64, arm64} & cpuid
  of ssl: (for b in 0 ..< bN: SHA256(i[b].addr, 64, o[b].addr))
  of sse: sha256_1_sse(    o[0].addr, i[0].addr, bN.uint64)
  of a1:  sha256_1_avx(    o[0].addr, i[0].addr, bN.uint64)
  of a4:  sha256_4_avx(    o[0].addr, i[0].addr, bN.uint64)
  of a28: sha256_8_avx2(   o[0].addr, i[0].addr, bN.uint64)
  of a5:  sha256_16_avx512(o[0].addr, i[0].addr, bN.uint64)
  of ni:  sha256_shani(    o[0].addr, i[0].addr, bN.uint64)

when isMainModule:                # A demo/bench/test program
  import std/[random, stats, times, math], cligen/strUt, cligen

  proc benchK(k: Kind, x: seq[uint64], bN=256, mN=5, aN=10, cold=false) =
    var o = newSeq[Digest](bN)    # Output hash/digests
    var s = 0u64
    var ra: RunningStat
    for a in 0 ..< aN:            # Average loop
      var rm: RunningStat
      for m in 0 ..< mN:          # Minimum loop
        let t0 = epochTime()
        sha256_64Bs k, cast[pua Digest](o[0].addr),
                    cast[pua Block](x[8*(mN*(m + aN*a))].unsafeAddr), bN
        rm.push epochTime() - t0  # Note time & below accum chksum
        for b in 0 ..< bN: s += cast[ptr uint64](o[b][0].addr)[]
      ra.push (if cold: rm.max else: rm.min) # Avg(Most(Times))
    let scale = 1e9/bN.float      # Want amortized nanosec per hash
    let sigDt = ra.standardDeviation*scale/ra.n.float.sqrt
    echo k, " ", fmtUncertain(ra.mean*scale, sigDt), " ", s

  proc bench*(kinds: seq[Kind], bN=256, mN=5, aN=10, cold=false) =
    ## Small bench CLI for Potuz' asm hashtree lib largely to get at auto (but
    ## likely static unless we go ATLAS route) method choice on various CPUs.
    var x: seq[uint64]            # Pre-generated rand data
    for j in 1 .. 8*bN*mN*aN: x.add randState.next
    for k in kinds: benchK(k, x, bN, mN, aN)

  when defined(release): randomize()
  when defined(linux): import cligen/osUt; setAffinity() # lessen CPU migration
  dispatch bench, help={"bN":"block count", "mN":"most loop", "aN":"avg loop",
                        "cold": "average max times not min"}

with new results like this (all times in nsec/64B block):
<EMAIL_ADDRESS>./nbench sse a1 a4 a28 ssl
sse 276.14 +- 0.88<PHONE_NUMBER>6429409582
a1  274.46 +- 0.13<PHONE_NUMBER>6429409582
a4  108.78 +- 0.12<PHONE_NUMBER>6429409582
a28 58.86  +- 0.18<PHONE_NUMBER>6429409582
ssl 255.83 +- 0.13<PHONE_NUMBER>6429409582

<EMAIL_ADDRESS>./nbench sse a1 a4 a28 ni ssl
sse 336.301 +- 0.088<PHONE_NUMBER>6840592016
a1  709.48  +- 0.12<PHONE_NUMBER>6840592016
a4  145.75  +- 0.15<PHONE_NUMBER>6840592016
a28 146.59  +- 0.14<PHONE_NUMBER>6840592016
ni  40.42   +- 0.14<PHONE_NUMBER>6840592016
ssl 104.96  +- 0.13<PHONE_NUMBER>6840592016

i7-1270P$ ./nbench sse a1 a4 a28 ni ssl
sse 254.81 +- 0.14<PHONE_NUMBER>556970637
a1  255.00 +- 0.12<PHONE_NUMBER>556970637
a4  109.99 +- 0.95<PHONE_NUMBER>556970637
a28 54.67  +- 0.13<PHONE_NUMBER>556970637
ni  41.44  +- 0.89<PHONE_NUMBER>556970637
ssl 65.5   +- 1.4<PHONE_NUMBER>556970637

So, maybe worth dropping the avx_x1 which seems perf risky on some AMD (and needing no more CPU features than avx_x4 anyway, AFICT) and just hard coding a sequence of avx512 || ni || avx2 || avx || sse || ssl.
I don't have avx512 to test on, but I know there is huge impl variation.  Might conceivably be more robust to start at ni if the max boost from avx512 relative to that is only 1.16X.. unless one does ATLAS-style build|run-time benchmarking to select.  { Mostly just explaining my code comment. }

Nice, thanks for the benches, indeed I often wonder about avx1. I thought at some point some processor may implement it while not supporting the opcodes in avx4, but that doesn't seem to be the case. Might as well drop it and fallback to pure sse


Creation of unity tests for the “Logging Messages” endpoint

Title: Implement Unit Testing and GitHub Action Integration
Story:
As a software developer on the project,
I want to add unit tests to our existing Java codebase,
So that we can ensure the code's correctness and maintainability,
And I want these tests to run automatically inside a GitHub Action,
With the test results reported as comments on the associated pull request,
To facilitate code review and continuous integration.
Acceptance Criteria:

The existing Java codebase should be reviewed to identify critical components and areas that require unit testing.

A unit testing framework, such as JUnit, should be selected and integrated into the project.

Unit tests should be created for identified components and functionalities, ensuring good code coverage.

A GitHub Action workflow should be created and configured to run the unit tests on each push to the repository and on pull request events.

The GitHub Action should be set up to post the test results as comments on the associated pull request, indicating success or failure and providing details on any failed tests.

The unit tests should include both positive and negative test cases to cover different scenarios.

A README or documentation should be updated to provide instructions on how to run the tests locally and how to interpret the GitHub Action test results.

The unit tests and GitHub Action workflow should be added as part of a feature branch or pull request and reviewed by team members for correctness and effectiveness.

Any identified issues or bugs should be addressed and resolved.

Once the unit tests and GitHub Action are working as expected, they should be merged into the main codebase.

Definition of Done:

Unit tests cover critical components and functionalities in the codebase.
The GitHub Action workflow is successfully configured and reports test results on pull requests.
README/documentation is updated with relevant information.
Code changes are reviewed and approved by team members.
All identified issues and bugs are resolved.
The unit tests and GitHub Action are merged into the main codebase.

This user story outlines the steps required to add unit tests, integrate them with a GitHub Action, and ensure that the test results are reported back to pull requests, thereby improving code quality and continuous integration in the project.


Azure pipelines

Pull Request Test Coverage Report for Build 227

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage decreased (-0.2%) to 70.422%

Totals

Change from base Build 226:
-0.2%

Covered Lines:
3807

Relevant Lines:
5406

💛  - Coveralls

Codecov Report

Merging #77 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master      #77   +/-   ##
=======================================
  Coverage   71.58%   71.58%
=======================================
  Files          16       16
  Lines         901      901
=======================================
  Hits          645      645
  Misses        256      256

Continue to review full report at Codecov.

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Document internal code architecture

Probably also related to #1331. Perhaps in the same document?
Yeah, I think so. Closing as a dupe.


Worker didn't clean up space it used in docker disk when exit.

Alluxio Version:
2.7.2 + fluid v0.6
Describe the bug
When worker exit, it doesn't clean corresponding block on docker disk, cause disk become full:
root@jssz-main-cv-train-15:~ # du -h --max-depth=1 /data/docker/alluxio/ai/
0	/data/docker/alluxio/ai/xg-lid
489G	/data/docker/alluxio/ai/xingui-lid      <- this one is already deleted
375G	/data/docker/alluxio/ai/audf-1
863G	/data/docker/alluxio/ai/
root@jssz-main-cv-train-15:~ # df -h /data/docker/
Filesystem      Size  Used Avail Use% Mounted on
/dev/nvme0n1    1.5T  1.5T   20K 100% /data/docker
And the worker is no longer running:
root@jssz-main-cv-train-15:~ # docker ps | grep alluxio-worker
23af46fe6ea8        hub.bilibili.co/ops-coeus/alluxio-with-hdfs            "/entrypoint.sh work…"   3 days ago          Up 3 days                               k8s_alluxio-worker_audf-1-worker-mlgsc_ai_062c1835-7721-4752-8607-820f9c660752_0

Fluid uses
timeout -t 60 alluxio fs free -f path

to clean the Alluxio cache
Two possibilities here:

timeout -t 60 is not enough for clearing data in Alluxio
alluxio fs free -f /path didn't actually clear all data in worker storage

@ssz1997 can you help resolve the problem of how to cleanup worker disk data in the Kubernetes environment?

Depending on how you delete worker, especially in Fluid env, there may be different behaviors.
The fluid way is to delete the whole cluster by running kubectl delete alluxioruntime, which would run alluxio fs free /. As Lu pointed out, even this way might not clean up all the data. But I think this is not the root cause here.
If you directly delete worker daemonset by running kubectl delete daemonset xxxx-worker, the data will not be deleted. Even after you delete pv and pvc created by Fluid, the data will still be there because the default pv reclaim policy provided by Fluid is Retain. The only way to delete these data in this case is to purge the data directly from the disk. See https://kubernetes.io/docs/concepts/storage/persistent-volumes/#retain. Not to mention Fluid will recreate the pv and the pvc.
For other ways to exit worker, we may have to see case by case whether the data is cleaned up.


RFC: Removal of "internal" content types.

Internal content types are used for the "internal link" and "external link" forms.
Ostensibly they allow the user to customize these forms.
They have the following issues:

RLP (resource locator) tag is used to nominate the field which should be used as the "reference" to the linked thing.
view,  controller , etc elements serve no purpose. The internal types are used only to represent forms.
The name of the property with the linked resource is mutable -- it would be better if this was a constant.
They require that the "template" is changed if the "state" of the node is changed to be a redirect (internal or external). This causes issues and we had to introduce the originTemplate property as a work-around.

In their defense:

They allow users to customize the forms  (but what use cases are there for this?)

I propose:

We drop these types and let the redirect by an integral part of a document and the forms become immutable.

/cc @wachterjohannes @chirimoya @danrot

I also think that we should drop this, I don't see any value in making this configureable.

The "internal" flag is also used for "excerpt". I am not sure what the implications of removing this are for that.

i think for the internal and external link its ok to drop it! but the excerpt should be customizable! perhaps we should think about dans idea to extract the "form" configuration out of the XML-Template to make it abstracter and let the usecase of the excerpt could then be done with an abstract "form"

@dantleech i have started with the fix for that and there i have a problem with the excerpt template:
https://github.com/sulu-io/sulu/pull/1040

This also causes a serious bug in the copy language function. If a language is copied for an internal link, the new copied page has no URL at all, and is not accessible on the website.

i have tested it now with current develop branch: the copied internal-link will be displayed in navigation and smart-content (smart-content ignores link-title => i will fix that today) in both are the right url without redirect!

@i have removed milestone because its not absolutely necessary to do that before 1.0! all related bugs are fixed! but still it should be done because its really a "shit" construct (=

ping @wachterjohannes @danrot

the only "internal" content-template which we use currently is the "excerpt" template which should be extensible. With our page-template system it is at least "overwritable". We have currently no possibility to migrate this to another feature. We  should really think about implementing a "form" template which could be used for this


@conda-forge-admin, add noarch: python

Issue:

Environment (conda list):

$ conda list

Details about  conda and system ( conda info ):

$ conda info

Hi! This is the friendly automated conda-forge-webservice.
I just wanted to let you know that I made the recipe noarch: python in conda-forge/entrypoints-feedstock#20.


Ignore invalid /Encoding-entries when parsing fonts (issue 14821)

In the referenced PDF document the fonts have /Encoding-entries that are Streams (containing completely bogus data), which are thus obviously not valid here.
Hence, only when ignoreErrors is set, we'll now ignore these corrupt /Encoding-entries and fallback to the existing code to try and infer a usable encoding.
Given that this is clearly a case of corrupt PDF documents, there's no guarantee that this will "fix" all such cases, however it's the best that we do here and shouldn't really be worse than ignoring an entire font.

/botio-linux preview

/botio test

Thank you for doing this!


Support [UnionType, InterfaceType] on one C# type

Is your feature request related to a problem? Please describe.
Simpler declaration in pure-code first of a base type that can act as a union and an interface.
Describe the solution you'd like
Support both attributes, creating a schema type for each. One would obviously need to specify an explicit name to be unique from the default derived from the annotated class/interface.
[UnionType, InterfaceType(Name = "Animalable")]
public interface IAnimal { }

// Startup
.AddType<IAnimal>()
.AddType<Dog>()
.AddType<Cat>()

Order would matter, in a similar way to below when hooked up via startup. e.g. pure code first uses of IAnimal would be typed in the schema (by default) as the type of the first attribute.
Describe alternatives you've considered
Below is the way to do it now (order matters).
public interface IAnimal { }

// Startup
.AddUnionType<IAnimal>()
.AddInterfaceType<IAnimal>(d => d.Name("Animalable"))
.AddType<Dog>()
.AddType<Cat>()

(doesn't work though, on v10.5 anyway, see comment below)
Additional context
Really just a nice-to-have, not a priority at all.

It actually seems like (at least on v10) the alternative workaround above doesn't ever add the types into the interface, so that's a bummer.

@benmccallum we have reviewed this and will not implement this. We think it is to much work for such a small use-case. We however will cover your use-case in a better way with the new mutation error type generation that use stage 6a of the errors guide.

No worries @michaelstaib , I think the workaround works on v11 anyway as I did that the other day, so it's fine. It was more an issue when that didn't on V10.


Validation: Test IPv6 support

@Mierdin would you be able to test IPv6 support in your environment?
I did some preliminary tests and it appears to work as designed, remember that IPv6 addresses have to be wrapped in brackets [ ]
Thanks!

Example of working version:

closing, abandoned


feature: use autocompletion for better search results

Hey, we'd love to open a new ticket to suggest autocompletion upon some observations we made. :)
To solve this problem of not knowing how different people think differently when using tags/categories (for search and definition), maybe autocompletion would help to list all existent tags/categories?
What do you think? :)
Best,
Thuy
cc @acid
Cases to recap:

when typing "Anti-Rassismus" in search input field, then no results are found
when typing "Antirassimus" in search input field, then 10 results are found

when typing "Rassismus" in search input field, then the 11 profiles shown here are not the same and not included in the search for "Anti-Rassimus" or "Antirassismus" even though these 2 words contain "Rassimus"

Belongs to #439


[2pt]  Display reserved rockets in My profile - Filters

Render a list of all reserved rockets (use filter()) on the "My profile" page.

https://github.com/inspecta/react-group-project-1/pull/37


Is this repo still active?

I would not mind rewriting this plugin to avoid crashes, but I'd prefer a response before beginning.

Looks like there's a second plugin on the plugin hub under the name "House Thieving Varlamore", so I guess it's fine to let this one die.


[Off-canvas] Bug iOS translateX

Hi,
If you check the following zurb doc on an  iPhone (i have tried on iPhone 6) and click on the open right menu, you can see a bug. The menu expand too much (x2) et come back in the normal expand state.
http://foundation.zurb.com/sites/docs/off-canvas.html
Have you got a solution ?
Thanks,
Guillaume

Can you link an image? this is what I'm getting right now on an iPhone 6s.

You can try on a iPhone 6 ( the menu left is more fluid than the right). Try also iPhone 4 Safari (iOS 7.1.2).
I can’t send you a photo : the final state is good. just the translate movement of the menu is not fluid and too large
Thanks
Le 27 janvier 2016 à 18:46:55, Chris Oyler<EMAIL_ADDRESS>a écrit:
Can you link an image? this is what I'm getting right now on an iPhone 6s.
—
Reply to this email directly or view it on GitHub.

I'm seeing 2d transforms work in that browser http://caniuse.com/#feat=transforms2d
The Sass version runs autoprefixer. Can you make sure the vendor prefixes are there in your compiled CSS?

@guoni, I'm having issues reproducing this as well. For now, I'm going to close this.
However, if you want to reopen it using the new issues template, that would be extremely helpful: https://github.com/zurb/foundation-sites/blob/develop/.github/ISSUE_TEMPLATE.md
Thanks!


Deadlock detected

Deadlock detected. Resetting KV cache and recomputing requests. Consider limiting number of concurrent requests or decreasing max lengths of prompts/generations.

Constantly see this issue when running below on a A100(40GiB) for llama2-7b.
    import mii
    from deepspeed.inference import RaggedInferenceEngineConfig, DeepSpeedTPConfig
    from deepspeed.inference.v2.ragged import DSStateManagerConfig

    tp_config = DeepSpeedTPConfig(tp_size=tensor_parallel)
    mgr_config = DSStateManagerConfig(max_ragged_batch_size=1024,
                                      max_ragged_sequence_count=1024)
    inference_config = RaggedInferenceEngineConfig(tensor_parallel=tp_config,
                                                   state_manager=mgr_config)
    llm = mii.serve(
        model,
        deployment_name='mii',
        tensor_parallel=tensor_parallel,
        inference_engine_config=inference_config,
        replica_num=1,
        task='text-generation'
    )
    outputs = llm.generate(prompts,
                           do_sample=False,
                           top_p=1.0,
                           max_new_tokens=max_new_tokens)

The deadlock is caused when we detect that we are not making any progress on any of the generation tasks. This can happen for a few reasons, including lots of concurrent generation requests, very long sequences, or limited GPU memory. Our current solution for this will hurt performance if you are seeing it often. How many requests are you sending to the server at once time?
Also, I believe @tohtana is working on an improved solution to this problem.

I am sending a few hundred requests within one batch.

I am sending a few hundred requests within one batch.

If these requests are generating lots of tokens, then sending this many at once will definitely cause the deadlock situation. If you can send the requests in smaller batches, that would avoid the problem. However, I will let @tohtana comment on any upcoming changes that will allow users to send large batches of requests at once!

vLLM implements swapping (Chapter 4.5 of vLLM paper) as an alternative to recomputing if no space could be allocated for KV cache of new tokens. Would MII implement KV cache swapping?

Hi, any update on this issue.
I am also getting same issue even with a batch size 1 (using 2 x A100 80GB) but when I am using a single A100 80GB I am able to run even with higher batches

@canamika27 I think #403 resolved the issue. Can you try the latest version?

@tohtana  -- Deadlock issue is solved with latest deepspeed version but again I got a new error :
assert last_r is not None, "Function to clear the KV cache is invoked, but no request consumes KV cache"
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
The batch size is 1
The batch size is 1
The total time is 3.23 secs
The batch size is 1
The total time is 4.21 secs
The batch size is 1
The total time is 3.15 secs
The batch size is 1
The total time is 3.15 secs
The batch size is 1
Traceback (most recent call last):
File "/home/AutoAWQ/Digi_human/TP_DP/Deepspeed/test_deepspeed.py", line 37, in
response = pipe(prompts, max_new_tokens=256)
File "/home/anaconda3/envs/mlc/lib/python3.10/site-packages/mii/batching/ragged_batching.py", line 550, in call
self.schedule_requests()
File "/home/anaconda3/envs/mlc/lib/python3.10/site-packages/mii/batching/ragged_batching.py", line 334, in schedule_requests
self.reset_request_status()
File "/home/anaconda3/envs/mlc/lib/python3.10/site-packages/mii/batching/ragged_batching.py", line 359, in reset_request_status
assert last_r is not None, "Function to clear the KV cache is invoked, but no request consumes KV cache"
AssertionError: Function to clear the KV cache is invoked, but no request consumes KV cache
[2024-02-26 00:11:22,782] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 766664
[2024-02-26 00:11:25,008] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 766665

@tohtana -- Thanks !! Deadlock issue is solved with latest Deepspeed version but again I got a new error : assert last_r is not None, "Function to clear the KV cache is invoked, but no request consumes KV cache"
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. The batch size is 1 The batch size is 1 The total time is 3.23 secs The batch size is 1 The total time is 4.21 secs The batch size is 1 The total time is 3.15 secs The batch size is 1 The total time is 3.15 secs The batch size is 1 Traceback (most recent call last): File "/home/AutoAWQ/Digi_human/TP_DP/Deepspeed/test_deepspeed.py", line 37, in response = pipe(prompts, max_new_tokens=256) File "/home/anaconda3/envs/mlc/lib/python3.10/site-packages/mii/batching/ragged_batching.py", line 550, in call self.schedule_requests() File "/home/anaconda3/envs/mlc/lib/python3.10/site-packages/mii/batching/ragged_batching.py", line 334, in schedule_requests self.reset_request_status() File "/home/anaconda3/envs/mlc/lib/python3.10/site-packages/mii/batching/ragged_batching.py", line 359, in reset_request_status assert last_r is not None, "Function to clear the KV cache is invoked, but no request consumes KV cache" AssertionError: Function to clear the KV cache is invoked, but no request consumes KV cache [2024-02-26 00:11:22,782] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 766664 [2024-02-26 00:11:25,008] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 766665
One Observation from my end : I am currently using 2 x A100 80GB systems & my prompts are approx 1000-2000 tokens, so when I am reducing my prompt length till 200 tokens it seems to be working with batch size 1 but not for higher batches. It seems we cannot run large prompts. This issue is happening only when I am using 2 gpus , with 1 GPU I am able to run with big batches & long prompts.

I got the same error.

@tohtana -- Thanks !! Deadlock issue is solved with latest Deepspeed version but again I got a new error : assert last_r is not None, "Function to clear the KV cache is invoked, but no request consumes KV cache"
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. The batch size is 1 The batch size is 1 The total time is 3.23 secs The batch size is 1 The total time is 4.21 secs The batch size is 1 The total time is 3.15 secs The batch size is 1 The total time is 3.15 secs The batch size is 1 Traceback (most recent call last): File "/home/AutoAWQ/Digi_human/TP_DP/Deepspeed/test_deepspeed.py", line 37, in response = pipe(prompts, max_new_tokens=256) File "/home/anaconda3/envs/mlc/lib/python3.10/site-packages/mii/batching/ragged_batching.py", line 550, in call self.schedule_requests() File "/home/anaconda3/envs/mlc/lib/python3.10/site-packages/mii/batching/ragged_batching.py", line 334, in schedule_requests self.reset_request_status() File "/home/anaconda3/envs/mlc/lib/python3.10/site-packages/mii/batching/ragged_batching.py", line 359, in reset_request_status assert last_r is not None, "Function to clear the KV cache is invoked, but no request consumes KV cache" AssertionError: Function to clear the KV cache is invoked, but no request consumes KV cache [2024-02-26 00:11:22,782] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 766664 [2024-02-26 00:11:25,008] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 766665
One Observation from my end : I am currently using 2 x A100 80GB systems & my prompts are approx 1000-2000 tokens, so when I am reducing my prompt length till 200 tokens it seems to be working with batch size 1 but not for higher batches. It seems we cannot run large prompts. This issue is happening only when I am using 2 gpus , with 1 GPU I am able to run with big batches & long prompts.

same error

@tohtana -- Thanks !! Deadlock issue is solved with latest Deepspeed version but again I got a new error : assert last_r is not None, "Function to clear the KV cache is invoked, but no request consumes KV cache"
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. The batch size is 1 The batch size is 1 The total time is 3.23 secs The batch size is 1 The total time is 4.21 secs The batch size is 1 The total time is 3.15 secs The batch size is 1 The total time is 3.15 secs The batch size is 1 Traceback (most recent call last): File "/home/AutoAWQ/Digi_human/TP_DP/Deepspeed/test_deepspeed.py", line 37, in response = pipe(prompts, max_new_tokens=256) File "/home/anaconda3/envs/mlc/lib/python3.10/site-packages/mii/batching/ragged_batching.py", line 550, in call self.schedule_requests() File "/home/anaconda3/envs/mlc/lib/python3.10/site-packages/mii/batching/ragged_batching.py", line 334, in schedule_requests self.reset_request_status() File "/home/anaconda3/envs/mlc/lib/python3.10/site-packages/mii/batching/ragged_batching.py", line 359, in reset_request_status assert last_r is not None, "Function to clear the KV cache is invoked, but no request consumes KV cache" AssertionError: Function to clear the KV cache is invoked, but no request consumes KV cache [2024-02-26 00:11:22,782] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 766664 [2024-02-26 00:11:25,008] [INFO] [launch.py:316:sigkill_handler] Killing subprocess 766665
One Observation from my end : I am currently using 2 x A100 80GB systems & my prompts are approx 1000-2000 tokens, so when I am reducing my prompt length till 200 tokens it seems to be working with batch size 1 but not for higher batches. It seems we cannot run large prompts. This issue is happening only when I am using 2 gpus , with 1 GPU I am able to run with big batches & long prompts.

I have the same problem.

Any Update on this? I am also getting the same error.

同样的错误，请问有解决方案吗

Any workaround for the new problem? @arashb Sorry for ping, can you help?
I just want to do inference serially, but got this error after exactly 3 pipeline calls. Stably repro with mixtral8x7b on two machines.


[Bugfix] Fix bias for 0-dim tensors in gemm

Description
For te_gemm and te_grouped_gemm,

If grad == false, we should do nothing to bias.
If grad == true, we should calculate grad_bias here.

Type of change

[ ] Documentation change (change only to the documentation, either a fix or a new content)
[x] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] Infra/Build change
[ ] Code refractor

Checklist:

[ ] I have read and followed the contributing guidelines
[ ] The functionality is complete
[ ] I have commented my code, particularly in hard-to-understand areas
[ ] I have made corresponding changes to the documentation
[ ] My changes generate no new warnings
[ ] I have added tests that prove my fix is effective or that my feature works
[ ] New and existing unit tests pass locally with my changes

/te-ci pytorch

/te-ci pytorch

/te-ci pytorch

I'll merge this PR since the CI passes except for a doc test failing with irrelevant error.


Fix issues with overflow for responsive stacked view

Fixes https://github.com/gregnb/mui-datatables/issues/312.

Coverage remained the same at 75.953% when pulling 51b263aa7e233828ab717266f6808422b8a85d7b on bugfix/issue-312-responsive-stacked-overflow into 47f844d013b7652928d1aaaef63f626c97455c28 on master.


Link to 2FA should go straight to 2FA settings in a new tab

I tried to pay an expense and saw this:

When I clicked account settings it jumped me to the main profile settings screen in the same window. Instead, it should link directly to the 2FA section, and it should be in a new tab so I don't lose the expense I was paying.

Ping @sbinlondon