text:
REQUEST: New membership for Mr-Linus

GitHub Username
@Mr-Linus
Requirements

[X] I have reviewed the community membership guidelines
[X] I have enabled 2FA on my GitHub account
[X] I am actively contributing to 1 or more Koordinator subprojects
[X] I have two sponsors that meet the sponsor requirements listed in the community membership guidelines
[X] I have spoken to my sponsors ahead of this application, and they have agreed to sponsor my application
[X] I have verified that my sponsors are a reviewer or an approver in at least one OWNERS file within one of the Koordinator GitHub organizations (excluding the contributor-playground)
[ ] OPTIONAL: I have taken the Inclusive Open Source Community Orientation course

Sponsor 1
@hormes
Sponsor 2
@jasonliu747
List of contributions to the Koordinator project

PRs Reviewed / authored
PR38
PR42
PR51

Issues responded to
Issues50

Subprojects  I am involved with
koordinator-sh/koordinator

/cc @jasonliu747 @hormes

+1

+1

Welcome to the Koordinator family and look forward to your contributions.

@Mr-Linus

/close

authors: Mr-Linus hormes jasonliu747

repo: koordinator-sh/koordinator


text:
apis: add Prod overcommit strategy api

Ⅰ. Describe what this PR does

Add the API of the Prod resource overcommitment strategy.
Ⅱ. Does this pull request fix one issue?

Part of #1428.
Ⅲ. Describe how to verify it
Ⅳ. Special notes for reviews
V. Checklist

[ ] I have written necessary docs and comments
[ ] I have added necessary unit tests and integration tests
[ ] All checks passed in make test

/lgtm

/hold

/close for a comprehensive design.

source: gharchive/pull-request

authors: hormes saintube

license_type: permissive

license_source: github-api


text:
Создайте пожалуйста собранный релиз

Здравствуйте. Разместите уже собранный релиз, чтобы не пересобирать его самостоятельно.
Спасибо

Сорри, зашел к Пластинину, а оказалось у него форк.

source: gharchive/issue

license: Unlicense


text:
画面遷移のボタンの２度押しをできないようにする

Issue

fix #264

Overview

launchSingleTopを使用することにより何度も同じ画面に遷移しないようにした

JaCoCo Code Coverage 67.52% :white_check_mark:

Class
Covered
Meta
Status

  Generated by :no_entry_sign: Danger

authors: KSNDBOT kosenda

repo: kosenda/hiragana-converter


text:
kosmosctl dr reports 'command terminated with exit code 1' error

What happened:

What you expected to happen:
kosmosctl connectivity test reports an error, but the network is actually functioning properly.
How to reproduce it (as minimally and precisely as possible):
Anything else we need to know?:
Environment:

Kosmos version: v0.1.7
Others:

/assign @wangyizhi1

repo: kosmos-io/kosmos


text:
feat: support single node model

What type of PR is this?

/kind feature
What does this PR do?

Which issue(s) does this PR fix?

Fixes #225
Special notes for your reviewer:

Does this PR introduce a user-facing change?

make pod support single node model

/approve

/lgtm


text:
Can't type in input fields

This is happened even on Demo App =/
There is an option to enable / disable keyboard with ImGUI?
I'm using LWJGL with OpenGL and GLFW.

Hi, quick info: my machine got broken, I'll be back asap

Sorry, try the update branch: e824187

I just merged it into the master, for info

Hello,
in previous version I was enabled to create the window context using the handler of Lwjgl GLFW implementation (long value). Like this:
lwjglGlfw.init(new GlfwWindow(window.getHandler()), true, GlfwClientApi.OpenGL);
In the new branch this methos isn't available. How can I do the same thing?
Thank you.

sorry, that was broken
233cff5d023d4329b7e82ea375178159d41f487b

Glad you solved.
Thanks for the nice words 👍
Consider closing if solved

Hi! Friendly reminder that there has been no activity here for over a month and this appears to be fixed. If you wish to keep this open, please respond with what still is an issue, or this will be closed in a week. Thanks!

Thank you for your support.

authors: Sylvyrfysh elect86 vfmachado

repo: kotlin-graphics/imgui

license: mit

license_source: bigquery


text:
KotlinTest not harmonious with IntelliJ IDEA

Writing KotlinTest tests in IntelliJ editor works fine. Executing individual KotlinTest files in IntelliJ runs the tests. However trying to run "All Tests" in the test module of an IntelliJ IDEA project with KotlinTest tests results in no tests being found.

It seemed to work for me and these are just standard jUnit tests under the hood. @helmbold does it work for you ?

It works fine here. The only thing I'm missing is the possibility to run a single test method, but I guess that this would require a KotlinTest plug-in for IntelliJ.

Here's an hypothesis: @sksamuel and @helmbold have their tests in the same directory as the source being tested and created their projects using IntelliJ IDEA whereas I have the standard Gradle project structure with source in src/main/kotlin and tests in src/test/kotlin using an IntelliJ IDEA project generated from the Gradle project.

Let's use KotlinTest itself as an example: it has the code separated from tests (src/main/kotlin and src/test/kotlin). It works on my machine.

Me too. In the left hand side "project" pane, I right click on src/test/kotlin (the green icon) and choose "run all tests". Works fine. Is that what you're doing Russel

Part of the hypothesis failed then: file system and module structure not the issue. Run "gradle test" and all the tests run. Run the files individually in IntelliJ IDEA and they run. Right click on package or module and "No tests found". Recreating the project from scratch leads to the same position. Are you both creating projects with the built in Kotlin support rather than with Gradle, if so the the remaining hypothesis is that the Gradle plugin is doing something really weird.

I go to file -> new project from existing sources -> ... import from gradle
I'm running intellij 16 community.
On 21 June 2016 at 08:51, Russel Winder notifications@github.com wrote:

Part of the hypothesis failed then: file system and module structure not
the issue. Run "gradle test" and all the tests run. Run the files
individually in IntelliJ IDEA and they run. Right click on package or
module and "No tests found". Recreating the project from scratch leads to
the same position. Are you both creating projects with the built in Kotlin
support rather than with Gradle, if so the the remaining hypothesis is that
the Gradle plugin is doing something really weird.
—
You are receiving this because you were mentioned.
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on Linux.
On 21 June 2016 at 08:52, Stephen Samuel (Sam) sam@sksamuel.com wrote:

I go to file -> new project from existing sources -> ... import from gradle
I'm running intellij 16 community.
On 21 June 2016 at 08:51, Russel Winder notifications@github.com wrote:

Part of the hypothesis failed then: file system and module structure not
the issue. Run "gradle test" and all the tests run. Run the files
individually in IntelliJ IDEA and they run. Right click on package or
module and "No tests found". Recreating the project from scratch leads to
the same position. Are you both creating projects with the built in Kotlin
support rather than with Gradle, if so the the remaining hypothesis is that
the Gradle plugin is doing something really weird.
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/kotlintest/kotlintest/issues/39#issuecomment-227366309,
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I am running 2016.2 EAP and use the import route it should do the same thing…

@russel Maybe you should file an issue, since it looks like some IntelliJ bug. Could you try IntelliJ 2016.1?

Did you get this sorted  @russel

I see the same behavior as @russel, so I opened https://youtrack.jetbrains.com/issue/IDEA-158136.

@mfriedenhagen Thanks for that, I have voted. Sorry for not acting myself, I have been writing a document and avoiding as much as possible. Document submitted this morning, so no I can get back to doing stuff. Which will probably be kotlinx.maths code using KotlinTest tests.

I got the same issue on elementaryOS, IDEA 2016.2 EAP. Here a screenshot of runing all test in this repo's master: https://www.dropbox.com/s/k1c5bsd3e0yfcov/Screenshot_2016-07-11_16.50.10.png

ah, just found a workaround by learning from Spek code: adding @RunWith() to our test class:
@RunWith(KTestJUnitRunner::class)
class FlatSpecExample : FlatSpec() {
    init {
        "String.length" should "return the length of the string" {
            "sammy".length shouldBe 5
            "".length shouldBe 0
        }
    }
}

and then our test class will be picked up by IDEA's Junit Runner

Aha. the @RunWith thing is working for me.

Well, TestBase is annotated with the RunWith, so this seems not to propagate.

I think I've fixed it (for 2.0 and 1.3). Could you verify it please, @russel , @mfriedenhagen , @hoangtranwork ?

Is there a released version of KotlinTest available with the fix.
(This would be amazingly useful for session at the LJC Open Conference on Saturday 2016-11-26.)

I'll do a release tomorrow night. Remind me :)
On 24 Nov 2016 5:13 p.m., "Russel Winder" notifications@github.com wrote:

Is there a released version of KotlinTest available with the fix.
(This would be amazingly useful for session at the LJC Open Conference on
Saturday 2016-11-26.)
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.

Since nobody reports any issues with my solution, I close it now.

@helmbold As I failed to remind @sksamuel to do a release to test, I haven't actually tested. But the opportunity I had for last Saturday has gone, and went differently to expected. People did though get a blast of proposition based testing and because I have no idea if it is sensible using the various Java/JUnit ports of QuickCheck, I showed using Kotlin and KotlinTest. Speks got a mention from the audience. Hopefully people spotted that Kotlin is way nicer than Java.

@russel It is great that you did something to improve our visibility!

I still need @RunWith(KTestJUnitRunner::class)
Idea 2016.3.1
Kotlin 1.1 m03
kotlintest 1.3.5

Thanks for the feedback, @elect86 . This issue is fixed in 2.0 (dev) only at the moment. We should get this release finally out of the door!

For anyone who arrives at this issue via searching for solutions the problem, as I did, a humble reminder: if you added the test/kotlin directory by hand, don't forget that you have to do "Mark directory as test root."

authors: MrTact elect86 helmbold hoangtranwork mfriedenhagen russel sksamuel

repo: kotlintest/kotlintest


text:
[error] backend port not found: :inotifywait

Hi!
When i run Visualixir
elixir --sname visualixir --hidden -S mix phoenix.server

i see in console:

This is not a problem with visualixir but phoenix in development mode. It
watches for filechanges and uses a couple of backends for this task, in
your case it choose :intofywait which is not available on your system.
Visualixir should run regardless of this message, only when you develop on
it yourself, it might take some time until changes of the files are
realized and acted upon.
To make it work in general you might install *inotify-tools* (Ubuntu
assumed).
Max notifications@github.com schrieb am Do., 17. Nov. 2016 um 12:04 Uhr:

Hi!
When i run Visualixir
elixir --sname visualixir --hidden -S mix phoenix.server
i see in console:
https://camo.githubusercontent.com/3b91453976b5f55c1265c9f3b2ce2a4bdeb77b59/687474703a2f2f7265732e636c6f7564696e6172792e636f6d2f706f73742d6861776b2f696d6167652f75706c6f61642f76313437393338303532332f6563643364633331366430345f3030315f7361336767632e706e67
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/koudelka/visualixir/issues/13, or mute the thread
https://github.com/notifications/unsubscribe-auth/AADmRww_VAoJsZJELHqhpD6DdWM595jWks5q_DSUgaJpZM4K1KiC
.

Tnx!

❤@NobbZ

authors: NobbZ Slavenin koudelka

repo: koudelka/visualixir


text:
Mark returns "400 Bad Request: com.atlassian.confluence.api.service.exceptions.BadRequestException: Content body cannot be converted to new editor format"

What happened?
I have several files that fail to sync to Confluence, returning the following error:
{"statusCode":400,"data":{"authorized":true,"valid":true,"errors":[],"successful":true},"message":"com.atlassian.confluence.api.service.exceptions.BadRequestException: Content body cannot be converted to new editor format"}
2023-09-12 16:14:15.283 FATAL Confluence API returned unexpected status: 400 Bad Request, output: "{\"statusCode\":400,\"data\":{\"authorized\":true,\"valid\":true,\"errors\":[],\"successful\":true},\"message\":\"com.atlassian.confluence.api.service.exceptions.BadRequestException: Content body cannot be converted to new editor format\"}"

What did you expect to happen?
I expected all the files in the GHA job to be properly synced to Confluence, in their specified locations.
** Information (please complete the following information):**

Mark Version (mark --version): 9.9.0
Mark Parameters: --trace
Confluence Version: Cloud
Environment specific Information: Running in GHA

** Logs or other output**
Example log files with the bearer token stripped out:
Device-Details-Errorlog.txt
RC-Caveats-ErrorLog.txt
RC-FAQ-ErrorLog.txt
Additional context
Add any other context about the problem here.

Entirely possible. This error is a bane to my sanity. Not sure what the cause is though. I have several docs that cannot be synced to Confluence due to this issue.

repo: kovetskiy/mark


text:
Update Settings “general”

Automatically generated by Netlify CMS

👷 Deploy Preview for ruipro processing.

Name
Link

🔨 Latest commit
c1ee029181e3a8913938c0bc14b42ec3197f4131

🔍 Latest deploy log
https://app.netlify.com/sites/ruipro/deploys/62c42e0c2a8b1e0008ee2c78

repo: koyomiyahouya/ripr

license: MIT


text:
Applying a patch doesn't seem to work?

[const jsdiff = require("diff");

let text = `# Markdown
This is some markdown.

Let's find the diffs
`;

let newText = `# Markdown
This is some markdown.

Let's find the diffs and prove it all works.
`;
let diff = jsdiff.structuredPatch("old", "new", text, newText);
let newDoc = jsdiff.applyPatch(text, diff);
console.log(newDoc);

and what I get back is:
/home/nicferrier/jswork/sqlparsing/node_modules/diff/lib/patch/apply.js:111
          delimiter = _hunk.linedelimiters[j];
                                          ^

TypeError: Cannot read property '0' of undefined
    at Object.applyPatch (/home/nicferrier/jswork/sqlparsing/node_modules/diff/lib/patch/apply.js:111:43)

I couldn't find a test that does this... but since structuredPatch is at the heart of all the patch routines that seems a bit odd.
Help?

I did some digging:
const {applyPatch, applyPatches} = require("./lib/patch/apply.js");

const {parsePatch} = require('./lib/patch/parse.js');
const {createPatch, structuredPatch} = require('./lib/patch/create.js');

let text = `# Markdown
This is some markdown.

Let's find the diffs
`;

let newText = `# Markdown
This is some markdown.

Let's find the diffs and prove it all works.
`;

let patch = createPatch("file", text, newText);
console.log("patch", patch);

let parsed = parsePatch(patch);
console.log("parsed", JSON.stringify(parsed, null, 2));

let newDoc = applyPatch(text, parsed);
console.log(newDoc);

let structuredParsed = structuredPatch("old", "new", text, newText);
console.log("structured", JSON.stringify(structuredParsed, null, 2));

This is what the above produces:
patch Index: file
===================================================================
--- file
+++ file
@@ -1,4 +1,4 @@
 # Markdown
 This is some markdown.

-Let's find the diffs
+Let's find the diffs and prove it all works.

parsed [
  {
    "index": "file",
    "oldFileName": "file",
    "oldHeader": "",
    "newFileName": "file",
    "newHeader": "",
    "hunks": [
      {
        "oldStart": 1,
        "oldLines": 4,
        "newStart": 1,
        "newLines": 4,
        "lines": [
          " # Markdown",
          " This is some markdown.",
          " ",
          "-Let's find the diffs",
          "+Let's find the diffs and prove it all works."
        ],
        "linedelimiters": [
          "\n",
          "\n",
          "\n",
          "\n",
          "\n"
        ]
      }
    ]
  }
]
# Markdown
This is some markdown.

Let's find the diffs and prove it all works.

structured {
  "oldFileName": "old",
  "newFileName": "new",
  "hunks": [
    {
      "oldStart": 1,
      "oldLines": 4,
      "newStart": 1,
      "newLines": 4,
      "lines": [
        " # Markdown",
        " This is some markdown.",
        " ",
        "-Let's find the diffs",
        "+Let's find the diffs and prove it all works."
      ]
    }
  ]
}

So the object produced by parsePatch differs from that produced by structuredPatch. That was not my expectation and maybe is the problem.
I can use the parsePatch form right now so I'm good.
Thanks!

Would be great if this was fixed. I was surprised by this as well and the type definitions also indicate this should work.

It looks like linedelimiters is simply not populated when creating a structuredPatch. Populating it makes structuredPatch work.

This is also happening in merge

Appears to be related to #157

@nicferrier @okev  This thread might not be the correct one, but could anyone point me in the direction of how can I represent (with the help of ins and del tags) the diff between two markdown using this structured patch? Also is there a way to determine word changes using this method, as I see that if a line is same with difference in a word the whole line is marked as removed with -.

authors: Xiphe benjamingr deyayan nicferrier okev

repo: kpdecker/jsdiff


text:
Review math inlining

In commit 45a772df73582609cbeb57d69397122bff72db94 I split the math and raycast code into a new library crate, all-is-cubes-base. Unfortunately, I didn’t think at the time about the effect this would have on function inlining. rustc currently has a heuristic for marking small functions inlinable, but it doesn't seem to suffice. After a slapdash addition of #[inline] where it seemed like it would make sense, I get the following notable results in benchmarks:

Bench target
Benchmark name
Effect of inlining on run time

space
space-bulk-mutation/*
-0%..-96%

space
GridAab/iter_for_each
-42%

save
load
-21%

mesh
block/*
-10%..-26%

raytrace
threaded/*
+20%..+29%

mesh
space/*
+7%..+41%

block
evaluate/*
+16%..+56%

raycast
many steps *
+85%

Benchmarks run on my laptop have quite unstable results, but these are huge differences which I am confident are significant. But since they are differences in both directions, we need to break down the #[inline] changes into smaller units to determine what's actually improving performance and what's making it worse.

The above data was collected by running all benchmarks only once. On re-testing, it seems that a lot of the apparent losses (and gains) may have been noise. Sigh.

5c90bca42869f764931d53622ce2939f284fd6e1 puts in the rest of the inlining. In the end, I couldn't find any consistent regression.

repo: kpreid/all-is-cubes


text:
Removed cydia

Hey Guys,
I know i did a mistake and removed Cydia could anyone explain me how i get it back got 10.1.1 on an 5S (got a mac if needed)

Not a code issue please close.
But I will help install this deb of cydia and your all good. apt.saurik.com/debs/cydia_1.1.28_iphoneos-arm.deb

#162 #64

Btw, google it or look on reddit, tons of people have tutorials

install Mobile terminal then do
apt-get install cydia
apt-get update
apt-get upgrade
apt-get auto clean

SSH is

First reset your iPhone so you have the option to press go on Yalu but don't do it yet, now go to your computer and download ifunbox open it then go to quicktoolbox, plug in your iPhone and open USB tunnel. A code should appear if you did it right. Now go to Yalu and click go until you get Cydia. Hope it works for you because it worked for me.

authors: AcedArmy Fremder NickGP cydiasnotthere kpwn modz2014

license: WTFPL


text:
jack not being loaded

from startup logs
[Aug 17 20:11:14] WARNING[1255] loader.c: Error loading module 'app_jack.so': libjack.so.0: cannot open shared object file: No such file or directory
[Aug 17 20:11:14] WARNING[1255] loader.c: Module 'app_jack.so' could not be loaded.

[futel@futel-stage ~]$ ls -l /usr/local/lib/libjack*
lrwxrwxrwx 1 root root      19 Aug 17 19:06 /usr/local/lib/libjacknet.so -> libjacknet.so.0.1.0
lrwxrwxrwx 1 root root      19 Aug 17 19:06 /usr/local/lib/libjacknet.so.0 -> libjacknet.so.0.1.0
-rwxr-xr-x 1 root root  154181 Aug 17 19:06 /usr/local/lib/libjacknet.so.0.1.0
lrwxrwxrwx 1 root root      22 Aug 17 19:06 /usr/local/lib/libjackserver.so -> libjackserver.so.0.1.0
lrwxrwxrwx 1 root root      22 Aug 17 19:06 /usr/local/lib/libjackserver.so.0 -> libjackserver.so.0.1.0
-rwxr-xr-x 1 root root 1046596 Aug 17 19:06 /usr/local/lib/libjackserver.so.0.1.0
lrwxrwxrwx 1 root root      16 Aug 17 19:06 /usr/local/lib/libjack.so -> libjack.so.0.1.0
lrwxrwxrwx 1 root root      16 Aug 17 19:06 /usr/local/lib/libjack.so.0 -> libjack.so.0.1.0
-rwxr-xr-x 1 root root  449999 Aug 17 19:06 /usr/local/lib/libjack.so.0.1.0
[futel@futel-stage ~]$

ldconfig is run by install_misc.yml
but install_jackd is run after than
so it looks like we need to run install_jackd earlier? Or have a ldconfig in a later config recipe.

@kra to be safe we could just run ldconfig at the end of anywhere that needs it...

repo: kra/futel-installation


text:
关于beianx的报错

大佬，为什么修改了beianx的key值，调试框始终有这个报错。

beianx api_v5的接口请求成功 但是返回的结果为空 手动在beianx官网上测试v5接口时却有结果。。。。
不知道问题出在哪？


text:
add an example of a json service

Summary
Interestingly, the Request's json method does not appear in any of the guides. This PR adds an example that uses it and other common json service functionality
Motivation
There does appear to be some confusion as to how to get the json representation of a request as evidenced by the google search results for "Mojolicious parse JSON body". Having a small example in the Tutorial seems like a simple place to start. I have chosen to place it after the GET and POST parameters section and the HTTP section since you need the concept of input parameters and also knowledge of the ->req and ->res methods to establish these concepts. The json stash value doesn't seem to be mentioned directly either but is rather introduced obliquely later, this also gives a nod in that direction.
References
https://groups.google.com/forum/#!topic/mojolicious/_r-tzqKKtGI
https://github.com/kraih/mojo/issues/522#issuecomment-229823654

Afraid i have to give this a 👎 , since the example is out of place and introduces features that are meant to be introduced much later in the tutorial.

Thank you @jberger, I agree that:

Methods that deal with parsing the body of requests (especially JSON) should be appended to the current Mojolicious documentation and
Perhaps the example is out of place given the current structure of the tutorial. However, I don't think there's anything sacred about the tutorial or the general flow of the documentation, which I actually find kind of difficult to navigate from the the perspective of a reference guide.

Sorry for the apparent (yet, unintended) "snark" in previous comments.

The tutorial is not intended as a reference guide. Indeed the problem is that the request's json methos is only described in the class reference documentation. I'm trying to correct the fact that it does not appear in the Guides which is where we want people to be introduced to the concepts.

Closing this pull request for now. While most of us still believe that an example similar to this one should exist in the guides, @dancingfrog's behavior here and on other communication channels has resulted in an exodus of volunteers willing to work on it.

For the record, a similar tutorial was added in https://github.com/kraih/mojo/compare/cebbec8c18ae8dd1d9803f92e0d63616f0244e46...56bb6015d80b8d221630ef99af0dbac1ad363013

authors: dancingfrog jberger kraih

repo: kraih/mojo


text:
Support Debian

It would be useful to support creating Debian clusters as well.
Bootstrap scripts are located here. Beside adding scripts, you will have to code an profile. Profiles are located in the profile package and you can use any existing as the template (e.g. Ubuntu @ Amazon).
If you'd like to learn more about kubicorn project, you can read The Project Walkthrough.
If you have any question, comment on the issue, join us on the #kubicorn channel in the Gophers Slack community or open a PR. We'll always do everything we can to get the PR though.
There's similar issue for Archlinux as well, #221

I will give it a try if this is still up for grab.

                                                                                IIRC somebody is working on this one, but I'm not sure neither I can check it right now

Thx.

hey yea i'm taking a look at this one

This issue is available for work again.

@xmudrii ubuntu's amazon template is now here. link in the description 404s.

Which description? @adnxn

Ubuntu @ Amazon link is broken (the package has been moved). I'll fix this tonight.

Ohhhhh here in the issue. Okay, fixed :)

authors: adnxn ellenkorbes recollir xmudrii

repo: kris-nova/kubicorn


text:
not working com nested array

Array
[
{
    'config_vimbo': [
        {
            _id: '1',
            title: 'Estrutura FrontEnd - Códigos',
            path: '/apps/general-settings/frontend-structure-code',
            hidden: 'this._rolesService.hide.isNotVimbo()'
        },
        {
            _id: '2',
            title: 'Unidade de medidas CTE',
            path: '/apps/general-settings/units-measurement-cte',
            hidden: 'this._rolesService.hide.isNotVimbo()'
        }
    ]
},
{
    'Sua equipe': [
        {
            _id: '1',
            title: 'Gerencie usuários e permissões',
            path: '/apps/general-settings/user-business',
            hidden: '!this._rolesService.modules.canView("configuracao")'
        }
    ]
},
{
    'Ajustes da sua conta': [
        {
            _id: '1',
            title: 'Unidades de medidas',
            path: '/apps/general-settings/units-measurement',
            hidden: '!this._rolesService.modules.canView("configuracao")'
        }
    ]
}]

Config
var options = {
  caseSensitive: true,
  shouldSort: true,
  threshold: 0.6,
  location: 0,
  distance: 100,
  maxPatternLength: 32,
  minMatchCharLength: 1,
  keys: [
    "title",
    "config_vimbo.title",
    "Sua equipe.title",
    "Ajustes da sua conta.title"
  ]
};
var fuse = new Fuse(list, options); // "list" is the item array
var result = fuse.search("unid");

Result
[
  {
    "config_vimbo": [
      {
        "_id": "1",
        "title": "Estrutura FrontEnd - Códigos",
        "path": "/apps/general-settings/frontend-structure-code",
        "hidden": "this._rolesService.hide.isNotVimbo()"
      },
      {
        "_id": "2",
        "title": "Unidade de medidas CTE",
        "path": "/apps/general-settings/units-measurement-cte",
        "hidden": "this._rolesService.hide.isNotVimbo()"
      }
    ]
  },
  {
    "Ajustes da sua conta": [
      {
        "_id": "1",
        "title": "Unidades de medidas",
        "path": "/apps/general-settings/units-measurement",
        "hidden": "!this._rolesService.modules.canView(\"configuracao\")"
      }
    ]
  }
]

In config_vimbo id 1 is left over, does not match the search

Unless I am misunderstanding the question, this is behaving as expected. The algorithm is matching the title of config_vimbo -> id:2  -> title:"Unidade de medidas CTE". This item is a sub-item of config_vimbo, and Fuse returns the entire object in which a match is found.

yes, but because Id 1 is coming, it should not return, since it does not correspond to the research.

authors: GlauberF krisk

repo: krisk/Fuse


text:
prototype name in nested forms

Is possible to inherit parents prototype name into childrens prototype in multiple nested form collections?
If I have users with multiple addresses, and address can have multiple cars. Car form prototype looks like this:

  Brand
  <input class="form-control" name="addresses[0][cars][__NAME__][brand]" type="text" id="addresses[0][cars][__NAME__][brand]">

This would be better this way:

  Brand
  <input class="form-control" name="addresses[__ADDRESS_NAME__][cars][__CAR_NAME__][brand]" type="text" id="addresses[__ADDRESS_NAME__][cars][__CAR_NAME__][brand]">

Yeah, I agree it's better. Didn't think of that. Will work on it during this week, because i'ts a bigger issue. Thanks for reporting.

Thank you! I will keep an eye on your project!

@lordjancso
I fixed this, finally got some time to analyze it properly. At this moment it's only on dev branch, because i'm planning to release 1.6. If you can, pull the dev version and test it out.

Cool, I will test it soon. Should I close this now?

Close it after you test it and it works fine.

authors: kristijanhusak lordjancso


text:
Created an endpoint for tracking all Icelandic torrent sites, list maintained by kjarni.cc

Tracks up-status, sll, domain, inviteOnly.

Made one commit and then 4 more to clean up my mistakes

Travis looks like he isn't complaining about me

Don't merge this yet, apparently its running on a laptop, and a random port

Closed due to inactivity. Please create a new pull request if you have some changes.

authors: HermannBjorgvin kristjanmik

repo: kristjanmik/apis


text:
Disable firewall checks if Little Snitch or Netbarrier are installed

They're a replacement for macOS' firewall, so it stands to reason that the firewall would be disabled.
I couldn't spot a way to set some sort of global flag in the hjson, and then not run certain tests if a flag is / isn't set - is that something that should be done elsewhere?

They're a replacement for macOS' firewall, so it stands to reason that the firewall would be disabled.

Excellent idea. I don't have Little Snitch or Netbarrier installed on a test machine; do you know what commands can be used to check whether they are installed?

I couldn't spot a way to set some sort of global flag in the hjson, and then not run certain tests if a flag is / isn't set - is that something that should be done elsewhere?

That's a neat idea. In general, there is an awful lot of copied/pasted code with small changes in the Hjson currently.
One way to do this would be to turn a lot of this reusable code into bash functions that take arguments, and which always get prepended to commands. This would provide a little API that config checks can call and make the test expressions relatively brief and simple.

Excellent idea. I don't have Little Snitch or Netbarrier installed on a test machine; do you know what commands can be used to check whether they are installed?

I have machines with both, I'll check Netbarrier tomorrow but for Little Snitch it's just a matter of checking to see whether the Little Snitch Daemon process is running. So pgrep "Little Snitch Daemon" would work, it'll either return the PID or it'll return nothing (if it's not running).

One way to do this would be to turn a lot of this reusable code into bash functions that take arguments, and which always get prepended to commands. This would provide a little API that config checks can call and make the test expressions relatively brief and simple.

This should probably be broken out into a new issue, but I agree, that seems to make a lot of sense.

@fluffypony as for your suggestion about an API and keeping commands conditional, these will be satisfied by issues https://github.com/kristovatlas/osx-config-check/issues/85 and https://github.com/kristovatlas/osx-config-check/issues/107

@kristovatlas awesome, great job:)

This is partially satisfied by https://github.com/kristovatlas/osx-config-check/issues/77
@fluffypony if you want to look into NetBarrier I'd find that help. In the meantime, I consider this sufficiently satisfied for the next milestone.

authors: fluffypony kristovatlas

repo: kristovatlas/osx-config-check


text:
Icon request: Mixer

URL of the site or app : https://mixer.com/
Logo resources for the icon : https://github.com/mixer/branding-kit/blob/master/svg/MixerMerge_Dark.svg

Here's the icon,
https://github.com/krisu5/aegis-icons/blob/master/PNG/Mixer.png


text:
Arrow function: bad formatting when converting from multiline single expression

Hey! First of all, thanks for this extension. I've longed for an arrow function refactoring like the one provided here. I've lost count of the number of times I've switched back and forth.
--
Given:
const foo = () => (
    1
);

If I use the refactoring to convert this single expression function to a block, I get:
const foo = () => {
        return (
    1
);
    };

Is there something we could do to fix the formatting here?

Hi, thanks. Glad that it's of use to you.
Refactorix could invoke one of the two VS Code commands "Format Selection" / "Format Document" after a refactoring has been made. "Format Selection" is kind of hard  to detect the new range and one has to alter the selection before invoking the command which could flicker.
I suggest a new configurable Refactorix option "Format Document on Refactoring" (default is false to preserve backward compatibility). Would that suffice your needs?

@krizzdewizz When I read through the source code, it seemed like you were doing some work to retain indentation—I'm guessing this has limits though? I agree this is probably a job better handled by another tool.

I suggest a new configurable Refactorix option "Format Document on Refactoring" (default is false to preserve backward compatibility). Would that suffice your needs?

I think so. I use Prettier so that will just format the new function in addition to everything else, but there shouldn't be any changes elsewhere.
Maybe we should hang on to this and see what other people’s needs are.

authors: OliverJAsh krizzdewizz

repo: krizzdewizz/vscode-refactorix


text:
update

pull

test


text:
Dependabot Investigation

Ignore the PR content, I only want to talk to dependabot.

@dependabot help

@dependabot show org.apache.zookeeper:zookeeper ignore conditions


text:
Fix broken unit test

I think these assertions were just incorrect following a refactoring.

Ha, had missed that PR (just enabled notifications), and looked into this just locally, arriving at the same conclusion :) Thanks, @tombentley!

authors: gunnarmorling tombentley

repo: kroxylicous/kproxy


text:
Translations: add italian translation

Add italian translation as requested on issue #30

Thanks a lot for the translation :)


text:
[Core feature request] continue-on-error for steps

What feature do you need?
https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepscontinue-on-error
Do you have an example usage?
- id: "execute_action"
  uses: "./"
  with:
    "distribution": "${{ matrix.distribution.user-id }}"
  continue-on-error: true
- run: "if '${{ steps.execute_action.outcome }}' NEQ 'failure' exit 1\n"
  shell: "cmd"

Is there any way to manually work-around this except for generating the YAML and then doing a string replace in the result?
I didn't find a way to customize this, as an extension function on Action is used to generate the uses string so cannot be overridden and specifying an own uses in _customArguments unfortunately leads to duplicate key instead of overridden.

The intended way to work around it is to use _customArguments, but as you've already noticed in #292, now it doesn't work as expected. Thanks for pointing it out, we'll address it!

Ah, bullshit, my question was intended for #288.
I moved it there.
This is perfectly work-aroundable using _customArguments.


text:
Adding arewecompressedyet.com

Came across this in a discussion thread on LinkedIn as an example of a good and thorough video quality analysis tool. Let me know if there are any issues with how I've written it up, wasn't sure if link to site code should be separate entry or not so I left it in the description.

@tiffsequence i love it, thanks for opening the PR!

authors: krzemienski tiffsequence

repo: krzemienski/awesome-video


text:
macOS support

Am I missing something or am I currently on my own and would have to implement macOS support myself?

I don't do much OSX development so didn't have time to implement it but the generic principle would work and I don't imagine this would require a huge amount of effort to add OSX version

Thanks @krzysztofzablocki for all your work! I would love to add macOS support, but as yet lack enough of an understanding of this project to be able to add it. I hope this will change and that I can find the time. :)

repo: krzysztofzablocki/KZPlayground


text:
fix: escaping reserved variable names

See https://github.com/SwiftGen/StencilSwiftKit/blob/master/Sources/Filters.swift#L15
The reason for this change is that when we try to generate property with the same name, or use it without self. we loose it's escaping (SourceKitten/SourceKite returns it unescaped), and generated code does not compile

          1 Error

:no_entry_sign:
Any changes to library code need a summary in the Changelog.

  Generated by :no_entry_sign: danger

authors: SourceryBot ilyapuchka

repo: krzysztofzablocki/Sourcery


text:
Tatt bort oppbevaringssted i arkivmelding opprett

Ref issue #178

Ta bort fra metadatakatalog.xsd også?

Ta bort fra metadatakatalog.xsd også?

Det kan vi hvis vi tar bort oppbevaringssted bort i arkivstruktur.xsd også.
Som medfører at det forsvinner fra de meldingstyper som bruker arkivstruktur.xsd.
Er det ønskelig?

Ja, evt. avvikende fysisk plassering vil neppe håndteres via Fiks Arkiv. Fiks Arkiv vil håndtere elektronisk arkivering. Det får heller legges til om det dukker opp et fagsystem med dette behovet. Men da måtte det ha vært med i alle meldingene.
Så jeg mener at dette kan tas fullstendig bort.

authors: jarleborsheim sturtzel

repo: ks-no/fiks-arkiv-specification


text:
Error: Model with name BERTSeqClassification does not exist

/kind bug
What steps did you take and what happened:
Followed Doc to deploy bert sequence classifier with torchserve on Kserve.
kubectl get pod
NAME                                                              READY   STATUS    RESTARTS   AGE
sklearn-irisv2-predictor-default-00001-deployment-6476cfcdjjpws   2/2     Running   0          3h19m
torchserve-bert-v2-predictor-default-00001-deployment-5676v48gp   2/2     Running   0          9m37s

kubectl describe pod torchserve-bert-v2-predictor-default-00001-deployment-5676v48gp
Name:             torchserve-bert-v2-predictor-default-00001-deployment-5676v48gp
Namespace:        default
Priority:         0
Service Account:  default
Node:             kind-control-plane/172.18.0.3
Start Time:       Wed, 30 Nov 2022 00:56:33 +0530
Labels:           app=torchserve-bert-v2-predictor-default-00001
                  component=predictor
                  pod-template-hash=5676596ddd
                  service.istio.io/canonical-name=torchserve-bert-v2-predictor-default
                  service.istio.io/canonical-revision=torchserve-bert-v2-predictor-default-00001
                  serviceEnvelope=kservev2
                  serving.knative.dev/configuration=torchserve-bert-v2-predictor-default
                  serving.knative.dev/configurationGeneration=1
                  serving.knative.dev/configurationUID=35c2e5c5-e54b-42ad-98cd-8181f7c304af
                  serving.knative.dev/revision=torchserve-bert-v2-predictor-default-00001
                  serving.knative.dev/revisionUID=09ae5676-7bdf-456f-ac91-a54128317f88
                  serving.knative.dev/service=torchserve-bert-v2-predictor-default
                  serving.knative.dev/serviceUID=84917927-1410-4f13-bb51-3dd81520d7a5
                  serving.kserve.io/inferenceservice=torchserve-bert-v2
Annotations:      autoscaling.knative.dev/class: kpa.autoscaling.knative.dev
                  autoscaling.knative.dev/minScale: 1
                  internal.serving.kserve.io/storage-initializer-sourceuri: gs://first_praveen_bucket/gcp
                  serving.knative.dev/creator: system:serviceaccount:kserve:kserve-controller-manager
Status:           Running
IP:               10.244.0.29
IPs:
  IP:           10.244.0.29
Controlled By:  ReplicaSet/torchserve-bert-v2-predictor-default-00001-deployment-5676596ddd
Init Containers:
  storage-initializer:
    Container ID:  containerd://0a502498a9a3b0d309ae4c7f9f1e93e4e6c79eb9477ede9edeef127c4e11de63
    Image:         kserve/storage-initializer:v0.9.0-rc0
    Image ID:      docker.io/kserve/storage-initializer@sha256:6cad6a39917c118c08eca833a16d347abf4b96342e00ddaf1535561077808192
    Port:          <none>
    Host Port:     <none>
    Args:
      gs://first_praveen_bucket/gcp
      /mnt/models
    State:          Terminated
      Reason:       Completed
      Exit Code:    0
      Started:      Wed, 30 Nov 2022 00:56:34 +0530
      Finished:     Wed, 30 Nov 2022 00:58:02 +0530
    Ready:          True
    Restart Count:  0
    Limits:
      cpu:     1
      memory:  1Gi
    Requests:
      cpu:        100m
      memory:     100Mi
    Environment:  <none>
    Mounts:
      /mnt/models from kserve-provision-location (rw)
      /var/run/secrets/kubernetes.io/serviceaccount from kube-api-access-k7rbd (ro)
Containers:
  kserve-container:
    Container ID:  containerd://8a3794ffc838712991c43622821bc7cac51d4be6820461f6d54b81c75fe7f7e7
    Image:         index.docker.io/pytorch/torchserve-kfs@sha256:43c1c14b2768c0cd73ce40e23da0a56176532b3c0fcb8b2217c087da3054c372
    Image ID:      docker.io/pytorch/torchserve-kfs@sha256:43c1c14b2768c0cd73ce40e23da0a56176532b3c0fcb8b2217c087da3054c372
    Port:          8080/TCP
    Host Port:     0/TCP
    Args:
      torchserve
      --start
      --model-store=/mnt/models/model-store
      --ts-config=/mnt/models/config/config.properties
    State:          Running
      Started:      Wed, 30 Nov 2022 00:58:02 +0530
    Ready:          True
    Restart Count:  0
    Limits:
      cpu:     1
      memory:  2Gi
    Requests:
      cpu:     1
      memory:  2Gi
    Environment:
      TS_SERVICE_ENVELOPE:  kservev2
      PORT:                 8080
      K_REVISION:           torchserve-bert-v2-predictor-default-00001
      K_CONFIGURATION:      torchserve-bert-v2-predictor-default
      K_SERVICE:            torchserve-bert-v2-predictor-default
    Mounts:
      /mnt/models from kserve-provision-location (ro)
      /var/run/secrets/kubernetes.io/serviceaccount from kube-api-access-k7rbd (ro)
  queue-proxy:
    Container ID:   containerd://a071b637707b0573b27f5ee7e6e1c174c7d4ec9dd79d1de3c7122208ed0f2095
    Image:          gcr.io/knative-releases/knative.dev/serving/cmd/queue@sha256:a40f6e84de1a0d145d27084a94cc7fa221159e75cafde7d332ac8f4f0aed58fb
    Image ID:       gcr.io/knative-releases/knative.dev/serving/cmd/queue@sha256:a40f6e84de1a0d145d27084a94cc7fa221159e75cafde7d332ac8f4f0aed58fb
    Ports:          8022/TCP, 9090/TCP, 9091/TCP, 8012/TCP, 8112/TCP
    Host Ports:     0/TCP, 0/TCP, 0/TCP, 0/TCP, 0/TCP
    State:          Running
      Started:      Wed, 30 Nov 2022 00:58:02 +0530
    Ready:          True
    Restart Count:  0
    Requests:
      cpu:      25m
    Readiness:  http-get http://:8012/ delay=0s timeout=1s period=10s #success=1 #failure=3
    Environment:
      SERVING_NAMESPACE:                 default
      SERVING_SERVICE:                   torchserve-bert-v2-predictor-default
      SERVING_CONFIGURATION:             torchserve-bert-v2-predictor-default
      SERVING_REVISION:                  torchserve-bert-v2-predictor-default-00001
      QUEUE_SERVING_PORT:                8012
      QUEUE_SERVING_TLS_PORT:            8112
      CONTAINER_CONCURRENCY:             0
      REVISION_TIMEOUT_SECONDS:          300
      SERVING_POD:                       torchserve-bert-v2-predictor-default-00001-deployment-5676v48gp (v1:metadata.name)
      SERVING_POD_IP:                     (v1:status.podIP)
      SERVING_LOGGING_CONFIG:
      SERVING_LOGGING_LEVEL:
      SERVING_REQUEST_LOG_TEMPLATE:      {"httpRequest": {"requestMethod": "{{.Request.Method}}", "requestUrl": "{{js .Request.RequestURI}}", "requestSize": "{{.Request.ContentLength}}", "status": {{.Response.Code}}, "responseSize": "{{.Response.Size}}", "userAgent": "{{js .Request.UserAgent}}", "remoteIp": "{{js .Request.RemoteAddr}}", "serverIp": "{{.Revision.PodIP}}", "referer": "{{js .Request.Referer}}", "latency": "{{.Response.Latency}}s", "protocol": "{{.Request.Proto}}"}, "traceId": "{{index .Request.Header "X-B3-Traceid"}}"}
      SERVING_ENABLE_REQUEST_LOG:        false
      SERVING_REQUEST_METRICS_BACKEND:   prometheus
      TRACING_CONFIG_BACKEND:            none
      TRACING_CONFIG_ZIPKIN_ENDPOINT:
      TRACING_CONFIG_DEBUG:              false
      TRACING_CONFIG_SAMPLE_RATE:        0.1
      USER_PORT:                         8080
      SYSTEM_NAMESPACE:                  knative-serving
      METRICS_DOMAIN:                    knative.dev/internal/serving
      SERVING_READINESS_PROBE:           {"tcpSocket":{"port":8080,"host":"127.0.0.1"},"successThreshold":1}
      ENABLE_PROFILING:                  false
      SERVING_ENABLE_PROBE_REQUEST_LOG:  false
      METRICS_COLLECTOR_ADDRESS:
      CONCURRENCY_STATE_ENDPOINT:
      CONCURRENCY_STATE_TOKEN_PATH:      /var/run/secrets/tokens/state-token
      HOST_IP:                            (v1:status.hostIP)
      ENABLE_HTTP2_AUTO_DETECTION:       false
    Mounts:
      /var/run/secrets/kubernetes.io/serviceaccount from kube-api-access-k7rbd (ro)
Conditions:
  Type              Status
  Initialized       True
  Ready             True
  ContainersReady   True
  PodScheduled      True
Volumes:
  kube-api-access-k7rbd:
    Type:                    Projected (a volume that contains injected data from multiple sources)
    TokenExpirationSeconds:  3607
    ConfigMapName:           kube-root-ca.crt
    ConfigMapOptional:       <nil>
    DownwardAPI:             true
  kserve-provision-location:
    Type:        EmptyDir (a temporary directory that shares a pod's lifetime)
    Medium:
    SizeLimit:   <unset>
QoS Class:       Burstable
Node-Selectors:  <none>
Tolerations:     node.kubernetes.io/not-ready:NoExecute op=Exists for 300s
                 node.kubernetes.io/unreachable:NoExecute op=Exists for 300s
Events:
  Type     Reason     Age                    From               Message
  ----     ------     ----                   ----               -------
  Normal   Scheduled  10m                    default-scheduler  Successfully assigned default/torchserve-bert-v2-predictor-default-00001-deployment-5676v48gp to kind-control-plane
  Normal   Pulled     10m                    kubelet            Container image "kserve/storage-initializer:v0.9.0-rc0" already present on machine
  Normal   Created    10m                    kubelet            Created container storage-initializer
  Normal   Started    10m                    kubelet            Started container storage-initializer
  Normal   Pulled     8m56s                  kubelet            Container image "index.docker.io/pytorch/torchserve-kfs@sha256:43c1c14b2768c0cd73ce40e23da0a56176532b3c0fcb8b2217c087da3054c372" already present on machine
  Normal   Created    8m56s                  kubelet            Created container kserve-container
  Normal   Started    8m56s                  kubelet            Started container kserve-container
  Normal   Pulled     8m56s                  kubelet            Container image "gcr.io/knative-releases/knative.dev/serving/cmd/queue@sha256:a40f6e84de1a0d145d27084a94cc7fa221159e75cafde7d332ac8f4f0aed58fb" already present on machine
  Normal   Created    8m56s                  kubelet            Created container queue-proxy
  Normal   Started    8m56s                  kubelet            Started container queue-proxy
  Warning  Unhealthy  8m44s (x4 over 8m54s)  kubelet            Readiness probe failed: Get "http://10.244.0.29:8012/": context deadline exceeded (Client.Timeout exceeded while awaiting headers)

Port Forward for testing purpose
INGRESS_GATEWAY_SERVICE=$(kubectl get svc --namespace istio-system --selector="app=istio-ingressgateway" --output jsonpath='{.items[0].metadata.name}')
kubectl port-forward --namespace istio-system svc/${INGRESS_GATEWAY_SERVICE} 8080:80
start another terminal
export INGRESS_HOST=localhost
export INGRESS_PORT=8080
What did you expect to happen:
What's the InferenceService yaml:
apiVersion: serving.kserve.io/v1beta1
kind: InferenceService
metadata:
  name: "torchserve-bert-v2"
spec:
  predictor:
    pytorch:
      protocolVersion: v2
      storageUri: <GCP model path>
**GCP model path contains-
├── config
│   ├── config.properties
├── model-store
│   ├── BERTSeqClassification.mar**

Anything else you would like to add:
Request Input file-> bert_v2.json
{
  "id": "d3b15cad-50a2-4eaf-80ce-8b0a428bd298",
  "inputs": [{
    "name": "4b7c7d4a-51e4-43c8-af61-04639f6ef4bc",
    "shape": -1,
    "datatype": "BYTES",
    "data": "{\"text\":\"Bloomberg has decided to publish a new report on the global economy.\", \"target\":1}"
  }
  ]
}

Inference request URL
SERVICE_HOSTNAME=$(kubectl get inferenceservice torchserve-bert-v2 -o jsonpath='{.status.url}' | cut -d "/" -f 3)

curl -v \
  -H "Host: ${SERVICE_HOSTNAME}" \
  -H "Content-Type: application/json" \
  -d @./bert_v2.json \
  http://${INGRESS_HOST}:${INGRESS_PORT}/v2/models/BERTSeqClassification/infer

Response
*   Trying 127.0.0.1:8080...
* Connected to localhost (127.0.0.1) port 8080 (#0)
> POST /v2/models/BERTSeqClassification/infer HTTP/1.1
> Host: torchserve-bert-v2.default.example.com
> User-Agent: curl/7.84.0
> Accept: */*
> Content-Type: application/json
> Content-Length: 271
>
* Mark bundle as not supporting multiuse
< HTTP/1.1 404 Not Found
< content-length: 66
< content-type: application/json; charset=UTF-8
< date: Tue, 29 Nov 2022 19:34:59 GMT
< server: istio-envoy
< x-envoy-upstream-service-time: 9
<
* Connection #0 to host localhost left intact
{"error": "Model with name BERTSeqClassification does not exist."}%

kubectl logs torchserve-bert-v2-predictor-default-00001-deployment-5676v48gp
Defaulted container "kserve-container" out of: kserve-container, queue-proxy, storage-initializer (init)
WARNING: sun.reflect.Reflection.getCallerClass is not supported. This will impact performance.
2022-11-29T19:28:20,943 [INFO ] main org.pytorch.serve.servingsdk.impl.PluginsManager - Initializing plugins manager...
2022-11-29T19:28:22,146 [INFO ] main org.pytorch.serve.ModelServer -
Torchserve version: 0.6.0
TS Home: /usr/local/lib/python3.8/dist-packages
Current directory: /home/model-server
Temp directory: /home/model-server/tmp
Number of GPUs: 0
Number of CPUs: 7
Max heap size: 4494 M
Python executable: /usr/bin/python
Config file: /mnt/models/config/config.properties
Inference address: http://0.0.0.0:8085
Management address: http://0.0.0.0:8086
Metrics address: http://0.0.0.0:8082
Model Store: /mnt/models/model-store
Initial Models: N/A
Log dir: /home/model-server/logs
Metrics dir: /home/model-server/logs
Netty threads: 4
Netty client threads: 0
Default workers per model: 7
Blacklist Regex: N/A
Maximum Response Size: 6553500
Maximum Request Size: 6553500
Limit Maximum Image Pixels: true
Prefer direct buffer: false
Allowed Urls: [file://.*|http(s)?://.*]
Custom python dependency for model allowed: false
Metrics report format: prometheus
Enable metrics API: true
Workflow Store: /mnt/models/model-store
Model config: N/A
2022-11-29T19:28:22,256 [INFO ] main org.pytorch.serve.servingsdk.impl.PluginsManager -  Loading snapshot serializer plugin...
2022-11-29T19:28:22,656 [INFO ] main org.pytorch.serve.snapshot.SnapshotManager - Started restoring models from snapshot {"name":"startup.cfg","modelCount":1,"models":{"bert":{"1.0":{"defaultVersion":true,"marName":"BERTSeqClassification.mar","minWorkers":1,"maxWorkers":5,"batchSize":2,"maxBatchDelay":500,"responseTimeout":60}}}}
2022-11-29T19:28:22,850 [INFO ] main org.pytorch.serve.snapshot.SnapshotManager - Validating snapshot startup.cfg
2022-11-29T19:28:22,925 [INFO ] main org.pytorch.serve.snapshot.SnapshotManager - Snapshot startup.cfg validated successfully
[I 221129 19:28:24 __main__:75] Wrapper : Model names ['bert'], inference address http//0.0.0.0:8085, management address http://0.0.0.0:8086, model store /mnt/models/model-store
[I 221129 19:28:24 TorchserveModel:54] kfmodel Predict URL set to 0.0.0.0:8085
[I 221129 19:28:24 TorchserveModel:56] kfmodel Explain URL set to 0.0.0.0:8085
[I 221129 19:28:24 TSModelRepository:30] TSModelRepo is initialized
[I 221129 19:28:24 model_server:150] Registering model: bert
[I 221129 19:28:24 model_server:123] Listening on port 8080
[I 221129 19:28:24 model_server:125] Will fork 1 workers
[I 221129 19:28:24 model_server:128] Setting max asyncio worker threads as 11
2022-11-29T19:28:46,328 [DEBUG] main org.pytorch.serve.wlm.ModelVersionedRefs - Adding new version 1.0 for model bert
2022-11-29T19:28:46,330 [DEBUG] main org.pytorch.serve.wlm.ModelVersionedRefs - Setting default version to 1.0 for model bert
2022-11-29T19:28:46,331 [DEBUG] main org.pytorch.serve.wlm.ModelVersionedRefs - Setting default version to 1.0 for model bert
2022-11-29T19:28:46,332 [INFO ] main org.pytorch.serve.wlm.ModelManager - Model bert loaded.
2022-11-29T19:28:46,333 [DEBUG] main org.pytorch.serve.wlm.ModelManager - updateModel: bert, count: 1
2022-11-29T19:28:46,530 [DEBUG] W-9000-bert_1.0 org.pytorch.serve.wlm.WorkerLifeCycle - Worker cmdline: [/usr/bin/python, /usr/local/lib/python3.8/dist-packages/ts/model_service_worker.py, --sock-type, unix, --sock-name, /home/model-server/tmp/.ts.sock.9000]
2022-11-29T19:28:46,627 [INFO ] main org.pytorch.serve.ModelServer - Initialize Inference server with: EpollServerSocketChannel.
2022-11-29T19:28:48,722 [INFO ] main org.pytorch.serve.ModelServer - Inference API bind to: http://0.0.0.0:8085
2022-11-29T19:28:48,725 [INFO ] main org.pytorch.serve.ModelServer - Initialize Management server with: EpollServerSocketChannel.
2022-11-29T19:28:48,733 [INFO ] main org.pytorch.serve.ModelServer - Management API bind to: http://0.0.0.0:8086
2022-11-29T19:28:48,735 [INFO ] main org.pytorch.serve.ModelServer - Initialize Metrics server with: EpollServerSocketChannel.
2022-11-29T19:28:48,739 [INFO ] main org.pytorch.serve.ModelServer - Metrics API bind to: http://0.0.0.0:8082
Model server started.
2022-11-29T19:28:52,241 [WARN ] pool-3-thread-1 org.pytorch.serve.metrics.MetricCollector - worker pid is not available yet.
2022-11-29T19:28:53,466 [INFO ] pool-3-thread-1 TS_METRICS - CPUUtilization.Percent:40.0|#Level:Host|#hostname:torchserve-bert-v2-predictor-default-00001-deployment-5676v48gp,timestamp:1669750133
2022-11-29T19:28:53,523 [INFO ] pool-3-thread-1 TS_METRICS - DiskAvailable.Gigabytes:229.0811767578125|#Level:Host|#hostname:torchserve-bert-v2-predictor-default-00001-deployment-5676v48gp,timestamp:1669750133
2022-11-29T19:28:53,525 [INFO ] pool-3-thread-1 TS_METRICS - DiskUsage.Gigabytes:38.98243713378906|#Level:Host|#hostname:torchserve-bert-v2-predictor-default-00001-deployment-5676v48gp,timestamp:1669750133
2022-11-29T19:28:53,527 [INFO ] pool-3-thread-1 TS_METRICS - DiskUtilization.Percent:14.5|#Level:Host|#hostname:torchserve-bert-v2-predictor-default-00001-deployment-5676v48gp,timestamp:1669750133
2022-11-29T19:28:53,529 [INFO ] pool-3-thread-1 TS_METRICS - MemoryAvailable.Megabytes:13237.20703125|#Level:Host|#hostname:torchserve-bert-v2-predictor-default-00001-deployment-5676v48gp,timestamp:1669750133
2022-11-29T19:28:53,530 [INFO ] pool-3-thread-1 TS_METRICS - MemoryUsed.Megabytes:4136.36328125|#Level:Host|#hostname:torchserve-bert-v2-predictor-default-00001-deployment-5676v48gp,timestamp:1669750133
2022-11-29T19:28:53,532 [INFO ] pool-3-thread-1 TS_METRICS - MemoryUtilization.Percent:26.4|#Level:Host|#hostname:torchserve-bert-v2-predictor-default-00001-deployment-5676v48gp,timestamp:1669750133
2022-11-29T19:28:55,315 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG - Listening on port: /home/model-server/tmp/.ts.sock.9000
2022-11-29T19:28:55,318 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG - [PID]59
2022-11-29T19:28:55,322 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG - Torch worker started.
2022-11-29T19:28:55,323 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG - Python runtime: 3.8.0
2022-11-29T19:28:55,329 [DEBUG] W-9000-bert_1.0 org.pytorch.serve.wlm.WorkerThread - W-9000-bert_1.0 State change null -> WORKER_STARTED
2022-11-29T19:28:55,515 [INFO ] W-9000-bert_1.0 org.pytorch.serve.wlm.WorkerThread - Connecting to: /home/model-server/tmp/.ts.sock.9000
2022-11-29T19:28:55,948 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG - Connection accepted: /home/model-server/tmp/.ts.sock.9000.
2022-11-29T19:28:56,424 [INFO ] W-9000-bert_1.0 org.pytorch.serve.wlm.WorkerThread - Flushing req. to backend at: 1669750136359
2022-11-29T19:28:57,594 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG - model_name: bert, batchSize: 2
2022-11-29T19:29:01,332 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG - generated new fontManager
2022-11-29T19:29:04,773 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG - Transformers version 4.11.0
2022-11-29T19:29:04,801 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG - Backend worker process died.
2022-11-29T19:29:04,802 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG - Traceback (most recent call last):
2022-11-29T19:29:04,827 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG -   File "/usr/local/lib/python3.8/dist-packages/ts/model_service_worker.py", line 210, in <module>
2022-11-29T19:29:04,829 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG -     worker.run_server()
2022-11-29T19:29:04,832 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG -   File "/usr/local/lib/python3.8/dist-packages/ts/model_service_worker.py", line 181, in run_server
2022-11-29T19:29:04,834 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG -     self.handle_connection(cl_socket)
2022-11-29T19:29:04,837 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG -   File "/usr/local/lib/python3.8/dist-packages/ts/model_service_worker.py", line 139, in handle_connection
2022-11-29T19:29:04,838 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG -     service, result, code = self.load_model(msg)
2022-11-29T19:29:04,839 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG -   File "/usr/local/lib/python3.8/dist-packages/ts/model_service_worker.py", line 104, in load_model
2022-11-29T19:29:04,840 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG -     service = model_loader.load(
2022-11-29T19:29:04,842 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG -   File "/usr/local/lib/python3.8/dist-packages/ts/model_loader.py", line 151, in load
2022-11-29T19:29:04,843 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG -     initialize_fn(service.context)
2022-11-29T19:29:04,833 [INFO ] epollEventLoopGroup-5-1 org.pytorch.serve.wlm.WorkerThread - 9000 Worker disconnected. WORKER_STARTED
2022-11-29T19:29:04,846 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG -   File "/home/model-server/tmp/models/053bb446d6094183a82b99d6f359f99d/Transformer_handler_generalized.py", line 71, in initialize
2022-11-29T19:29:04,847 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG -     self.model = torch.jit.load(model_pt_path, map_location=self.device)
2022-11-29T19:29:04,922 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG -   File "/usr/local/lib/python3.8/dist-packages/torch/jit/_serialization.py", line 162, in load
2022-11-29T19:29:04,924 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG -     cpp_module = torch._C.import_ir_module(cu, str(f), map_location, _extra_files)
2022-11-29T19:29:04,925 [INFO ] W-9000-bert_1.0-stdout MODEL_LOG - RuntimeError: version_ <= kMaxSupportedFileFormatVersionINTERNAL ASSERT FAILED at "../caffe2/serialize/inline_container.cc":147, please report a bug to PyTorch. Attempted to read a PyTorch file with version 10, but the maximum supported version for reading is 9. Your PyTorch installation may be too old.
2022-11-29T19:29:04,945 [DEBUG] W-9000-bert_1.0 org.pytorch.serve.wlm.WorkerThread - System state is : WORKER_STARTED
2022-11-29T19:29:04,946 [DEBUG] W-9000-bert_1.0 org.pytorch.serve.wlm.WorkerThread - Backend worker monitoring thread interrupted or backend worker process died.
java.lang.InterruptedException: null
   at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.reportInterruptAfterWait(AbstractQueuedSynchronizer.java:2056) ~[?:?]
   at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:2133) ~[?:?]
   at java.util.concurrent.ArrayBlockingQueue.poll(ArrayBlockingQueue.java:432) ~[?:?]
   at org.pytorch.serve.wlm.WorkerThread.run(WorkerThread.java:189) [model-server.jar:?]
   at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:515) [?:?]
   at java.util.concurrent.FutureTask.run(FutureTask.java:264) [?:?]
   at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128) [?:?]
   at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628) [?:?]
   at java.lang.Thread.run(Thread.java:829) [?:?]
2022-11-29T19:29:05,849 [WARN ] W-9000-bert_1.0 org.pytorch.serve.wlm.BatchAggregator - Load model failed: bert, error: Worker died.
2022-11-29T19:29:05,850 [DEBUG] W-9000-bert_1.0 org.pytorch.serve.wlm.WorkerThread - W-9000-bert_1.0 State change WORKER_STARTED -> WORKER_STOPPED
2022-11-29T19:29:05,927 [WARN ] W-9000-bert_1.0 org.pytorch.serve.wlm.WorkerLifeCycle - terminateIOStreams() threadName=W-9000-bert_1.0-stderr
2022-11-29T19:29:05,929 [WARN ] W-9000-bert_1.0 org.pytorch.serve.wlm.WorkerLifeCycle - terminateIOStreams() threadName=W-9000-bert_1.0-stdout
2022-11-29T19:29:05,934 [INFO ] W-9000-bert_1.0 org.pytorch.serve.wlm.WorkerThread - Retry worker: 9000 in 1 seconds.

Environment:

Istio Version:
Knative Version:
KServe Version:
Kubeflow version:
Cloud Environment:[k8s_istio/istio_dex/gcp_basic_auth/gcp_iap/aws/aws_cognito/ibm]
Minikube/Kind version:
Kubernetes version: (use kubectl version):
OS (e.g. from /etc/os-release):

pytorch version mismatch was there. Created pytorch trace model with torch 1.13 and inside kserve torch version was 1.11 so it was creating issue while loading the trace model inside kserve environments.

repo: kserve/kserve


text:
No matches for kind InferenceService

/kind bug
What steps did you take and what happened:
I was trying to follow the Getting-started documentation.

Installed kind
Installed kubectl
Installed the KServe "Quickstart" environment by the following command

curl -s "https://raw.githubusercontent.com/kserve/kserve/release-0.10/hack/quick_install.sh" | bash

In the next step created a namespace called kserve-test and then tried to create an InferenceService via the following command
kubectl apply -n kserve-test -f - <<EOF
apiVersion: "serving.kserve.io/v1beta1"
kind: "InferenceService"
metadata:
  name: "sklearn-iris"
spec:
  predictor:
    model:
      modelFormat:
        name: sklearn
      storageUri: "gs://kfserving-examples/models/sklearn/1.0/model"
EOF

I got the below error
error: resource mapping not found for name: "sklearn-iris" namespace: "" from "inferenceservice.yaml": no matches for kind "InferenceService" in version "serving.kserve.io/v1beta1"
ensure CRDs are installed first

What did you expect to happen:

Expected a resource with kind InferenceService
I think namespace is also missing from the resource spec.

What's the InferenceService yaml:
apiVersion: "serving.kserve.io/v1beta1"
kind: "InferenceService"
metadata:
  name: "sklearn-iris"
spec:
  predictor:
    model:
      modelFormat:
        name: sklearn
      storageUri: "gs://kfserving-examples/models/sklearn/1.0/model"

Anything else you would like to add:
[Miscellaneous information that will assist in solving the issue.]
Environment:

Istio Version: 1.15.0
Knative Version:
KServe Version:
Kubeflow version: 1.26.3
Cloud Environment:[k8s_istio/istio_dex/gcp_basic_auth/gcp_iap/aws/aws_cognito/ibm]: local
Minikube/Kind version: v0.18.0
Kubernetes version: (use kubectl version): 1.26.3
OS (e.g. from /etc/os-release):

@dunefro The install probably failed for some reason, you might want to check if everything is installed successfully

@yuzisun I am having a similar install issue on Mac, with latest Docker, Kind and KServe quickstart.      Here is the log, the issue(s) is at the bottom,..."ensure CRDs are installed first"
namespace/istio-system created
✔ Istio core installed
✔ Istiod installed
✔ Ingress gateways installed
✔ Installation complete                                                         Making this installation the default for injection and validation.
Thank you for installing Istio 1.15.  Please take a few minutes to tell us about your install/upgrade experience!  https://forms.gle/SWHFBmwJspusK1hv6
😀 Successfully installed Istio
customresourcedefinition.apiextensions.k8s.io/certificates.networking.internal.knative.dev created
customresourcedefinition.apiextensions.k8s.io/configurations.serving.knative.dev created
customresourcedefinition.apiextensions.k8s.io/clusterdomainclaims.networking.internal.knative.dev created
customresourcedefinition.apiextensions.k8s.io/domainmappings.serving.knative.dev created
customresourcedefinition.apiextensions.k8s.io/ingresses.networking.internal.knative.dev created
customresourcedefinition.apiextensions.k8s.io/metrics.autoscaling.internal.knative.dev created
customresourcedefinition.apiextensions.k8s.io/podautoscalers.autoscaling.internal.knative.dev created
customresourcedefinition.apiextensions.k8s.io/revisions.serving.knative.dev created
customresourcedefinition.apiextensions.k8s.io/routes.serving.knative.dev created
customresourcedefinition.apiextensions.k8s.io/serverlessservices.networking.internal.knative.dev created
customresourcedefinition.apiextensions.k8s.io/services.serving.knative.dev created
customresourcedefinition.apiextensions.k8s.io/images.caching.internal.knative.dev created
namespace/knative-serving created
clusterrole.rbac.authorization.k8s.io/knative-serving-aggregated-addressable-resolver created
clusterrole.rbac.authorization.k8s.io/knative-serving-addressable-resolver created
clusterrole.rbac.authorization.k8s.io/knative-serving-namespaced-admin created
clusterrole.rbac.authorization.k8s.io/knative-serving-namespaced-edit created
clusterrole.rbac.authorization.k8s.io/knative-serving-namespaced-view created
clusterrole.rbac.authorization.k8s.io/knative-serving-core created
clusterrole.rbac.authorization.k8s.io/knative-serving-podspecable-binding created
serviceaccount/controller created
clusterrole.rbac.authorization.k8s.io/knative-serving-admin created
clusterrolebinding.rbac.authorization.k8s.io/knative-serving-controller-admin created
clusterrolebinding.rbac.authorization.k8s.io/knative-serving-controller-addressable-resolver created
customresourcedefinition.apiextensions.k8s.io/images.caching.internal.knative.dev unchanged
customresourcedefinition.apiextensions.k8s.io/certificates.networking.internal.knative.dev unchanged
customresourcedefinition.apiextensions.k8s.io/configurations.serving.knative.dev unchanged
customresourcedefinition.apiextensions.k8s.io/clusterdomainclaims.networking.internal.knative.dev unchanged
customresourcedefinition.apiextensions.k8s.io/domainmappings.serving.knative.dev unchanged
customresourcedefinition.apiextensions.k8s.io/ingresses.networking.internal.knative.dev unchanged
customresourcedefinition.apiextensions.k8s.io/metrics.autoscaling.internal.knative.dev unchanged
customresourcedefinition.apiextensions.k8s.io/podautoscalers.autoscaling.internal.knative.dev unchanged
customresourcedefinition.apiextensions.k8s.io/revisions.serving.knative.dev unchanged
customresourcedefinition.apiextensions.k8s.io/routes.serving.knative.dev unchanged
customresourcedefinition.apiextensions.k8s.io/serverlessservices.networking.internal.knative.dev unchanged
customresourcedefinition.apiextensions.k8s.io/services.serving.knative.dev unchanged
secret/serving-certs-ctrl-ca created
secret/knative-serving-certs created
image.caching.internal.knative.dev/queue-proxy created
configmap/config-autoscaler created
configmap/config-defaults created
configmap/config-deployment created
configmap/config-domain created
configmap/config-features created
configmap/config-gc created
configmap/config-leader-election created
configmap/config-logging created
configmap/config-network created
configmap/config-observability created
configmap/config-tracing created
poddisruptionbudget.policy/activator-pdb created
deployment.apps/activator created
service/activator-service created
deployment.apps/autoscaler created
service/autoscaler created
deployment.apps/controller created
service/controller created
deployment.apps/domain-mapping created
deployment.apps/domainmapping-webhook created
service/domainmapping-webhook created
poddisruptionbudget.policy/webhook-pdb created
deployment.apps/webhook created
service/webhook created
validatingwebhookconfiguration.admissionregistration.k8s.io/config.webhook.serving.knative.dev created
mutatingwebhookconfiguration.admissionregistration.k8s.io/webhook.serving.knative.dev created
mutatingwebhookconfiguration.admissionregistration.k8s.io/webhook.domainmapping.serving.knative.dev created
secret/domainmapping-webhook-certs created
validatingwebhookconfiguration.admissionregistration.k8s.io/validation.webhook.domainmapping.serving.knative.dev created
validatingwebhookconfiguration.admissionregistration.k8s.io/validation.webhook.serving.knative.dev created
secret/webhook-certs created
resource mapping not found for name: "activator" namespace: "knative-serving" from "https://github.com/knative/serving/releases/download/knative-v1.7.0/serving-core.yaml": no matches for kind "HorizontalPodAutoscaler" in version "autoscaling/v2beta2"
ensure CRDs are installed first
resource mapping not found for name: "webhook" namespace: "knative-serving" from "https://github.com/knative/serving/releases/download/knative-v1.7.0/serving-core.yaml": no matches for kind "HorizontalPodAutoscaler" in version "autoscaling/v2beta2"

@jbottum I think you are using kubernetes 1.26 or above in which autoscaling/v2beta2 is removed in favour of autoscaling/v2. You should downgrade the kubernetes or upgrade the knative.

@sivanantha321 thanks, I will try that.

That worked, with Kind using K8s 1.25, use these instructions, https://kind.sigs.k8s.io/docs/user/configuration/#kubernetes-version to build the yaml and this version: kindest/node:v1.25.9@sha256:c08d6c52820aa42e533b70bce0c2901183326d86dcdcbedecc9343681db45161

Works for me too.

authors: dunefro jbottum sivanantha321 tiansiyuan yuzisun


text:
vLLM engine crashes when --num-scheduler-steps > 1 and max_tokens is undefined

/kind bug
What steps did you take and what happened:

Create an InferenceService with the Hugging Face server + vLLM backend, and use an LLM as the model
Enable vLLM's multistep scheduling (--num-scheduler-steps > 1), which is recommended as of v0.6.0 to improve performance
Make a request to /openai/v1/chat/completions without setting max_tokens -> ERROR
Subsequent requests will fail (kserve.errors.ModelNotReady: Model with name ... is not ready) as well, even with max_tokens set

Traceback (most recent call last):
  File "/prod_venv/lib/python3.10/site-packages/vllm/engine/async_llm_engine.py", line 48, in _log_task_completion
    return_value = task.result()
  File "/prod_venv/lib/python3.10/site-packages/vllm/engine/async_llm_engine.py", line 733, in run_engine_loop
    result = task.result()
  File "/prod_venv/lib/python3.10/site-packages/vllm/engine/async_llm_engine.py", line 673, in engine_step
    request_outputs = await self.engine.step_async(virtual_engine)
  File "/prod_venv/lib/python3.10/site-packages/vllm/engine/async_llm_engine.py", line 340, in step_async
    outputs = await self.model_executor.execute_model_async(
  File "/prod_venv/lib/python3.10/site-packages/vllm/executor/gpu_executor.py", line 185, in execute_model_async
    output = await make_async(self.driver_worker.execute_model
  File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
    result = self.fn(*self.args, **self.kwargs)
  File "/prod_venv/lib/python3.10/site-packages/vllm/worker/worker_base.py", line 327, in execute_model
    output = self.model_runner.execute_model(
  File "/prod_venv/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
    return func(*args, **kwargs)
  File "/prod_venv/lib/python3.10/site-packages/vllm/worker/multi_step_model_runner.py", line 458, in execute_model
    outputs = self._final_process_outputs(model_input,
  File "/prod_venv/lib/python3.10/site-packages/vllm/worker/multi_step_model_runner.py", line 308, in _final_process_outputs
    output_proc_callback()
  File "/prod_venv/lib/python3.10/site-packages/vllm/engine/llm_engine.py", line 984, in _process_model_outputs
    self.output_processor.process_outputs(
  File "/prod_venv/lib/python3.10/site-packages/vllm/engine/output_processor/multi_step.py", line 120, in process_outputs
    self._process_seq_outputs(seq, valid_samples,
  File "/prod_venv/lib/python3.10/site-packages/vllm/engine/output_processor/multi_step.py", line 144, in _process_seq_outputs
    remaining_tokens = sampling_params.max_tokens - (seq.get_output_len() +
TypeError: unsupported operand type(s) for -: 'NoneType' and 'int'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/prod_venv/lib/python3.10/site-packages/starlette/_exception_handler.py", line 51, in wrapped_app
    await app(scope, receive, sender)
  File "/prod_venv/lib/python3.10/site-packages/starlette/routing.py", line 73, in app
    response = await f(request)
  File "/prod_venv/lib/python3.10/site-packages/fastapi/routing.py", line 301, in app
    raw_response = await run_endpoint_function(
  File "/prod_venv/lib/python3.10/site-packages/fastapi/routing.py", line 212, in run_endpoint_function
    return await dependant.call(**values)
  File "/kserve/kserve/protocol/rest/openai/endpoints.py", line 123, in create_chat_completion
    completion = await self.dataplane.create_chat_completion(
  File "/kserve/kserve/protocol/rest/openai/dataplane.py", line 100, in create_chat_completion
    return await model.create_chat_completion(completion_request)
  File "/kserve/kserve/protocol/rest/openai/openai_chat_adapter_model.py", line 218, in create_chat_completion
    Completion, await self.create_completion(completion_request)
  File "/huggingfaceserver/huggingfaceserver/vllm/vllm_model.py", line 83, in create_completion
    return await self.openai_serving_completion.create_completion(request)
  File "/huggingfaceserver/huggingfaceserver/vllm/vllm_completions.py", line 197, in create_completion
    raise OpenAIError(str(e))

Basically the issue is vllm/engine/output_processor/multi_step.py requires SamplingParams.max_tokens to be set.
What did you expect to happen:
We should be able to omit max_tokens without facing any errors.
What's the InferenceService yaml:
apiVersion: serving.kserve.io/v1beta1
kind: InferenceService
metadata:
  name: llama3
spec:
  predictor:
    model:
      args:
      - --model_name=llama3
      - --model_id=meta-llama/Llama-3.1-8B-Instruct
      - --max-model-len=16384
      - --num-scheduler-steps=8
      env:
      - name: HF_TOKEN
        value: ...
      image: kserve/huggingfaceserver:latest
      modelFormat:
        name: huggingface
      resources:
        limits:
          cpu: "4"
          memory: 16Gi
          nvidia.com/gpu: "1"
        requests:
          cpu: "2"
          nvidia.com/gpu: "1"

Anything else you would like to add:
Without multistep scheduling, this works fine, there won't be any error if we don't specify max_tokens.
Potential Fix
There's an upstream issue on vLLM, which was already fixed. I believe the reason why it's not also fixed yet in KServe is because KServe wrote its own frontend (huggingfaceserver/huggingfaceserver/vllm) for vLLM, and the fix on vLLM was to their own frontend (vllm/entrypoints/openai), in particular to the to_sampling_params function. If the fix was to the vLLM engine then KServe would've gotten the fix too after upgrading the version.
I believe both frontends are similar enough though that this would be a simple fix to port over to KServe. I can have a PR up quickly.
Environment:

Istio Version: v1.20.3
Knative Version: v1.13.1
KServe Version: latest
Cloud Environment: k8s_istio
Kubernetes version: (use kubectl version): v1.29.7-eks-a18cd3a

@kevinmingtarja hi, would you mind to send the PR?

@kevinmingtarja hi, would you mind sending the PR?

yep, I just made a PR for the fix!

authors: kevinmingtarja spolti


text:
Siyuan upgrade node version in dockerfile

The changed are verified via successful docker build using the new Dockerfile.

That is even more confusing :-D but at least there is a PR with all fixes.

Can you rebase to master and fix the tests?

@markwinter can you help out here as well?

authors: juliusvonkohout tiansiyuan

repo: kserve/models-web-app


text:
Windows usage

Tying to use this on windows but getting an error.

I was not able to run with lpw start but I have done the "pip install lpw"
I then clone the project run as described on Local Development.

When I attach the pcap I get this error.

RuntimeError: There is no current event loop in thread 'ScriptRunner.scriptThread'. Traceback: File "C:\Users\taduo\AppData\Local\Programs\Python\Python312\Lib\site-packages\streamlit\runtime\scriptrunner\script_runner.py", line 535, in _run_script     exec(code, module.__dict__) File "C:\Users\taduo\Documents\gitprojects\local-packet-whisperer\bin\lpw_main.py", line 120, in <module>     initLLM(pcap_data=getPcapData(input_file=f'{packetFile.name}', filter=filters, decode_info=decodes))                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\taduo\Documents\gitprojects\local-packet-whisperer\bin\lpw_packet.py", line 17, in getPcapData     cap : ps.FileCapture = ps.FileCapture(input_file=input_file, display_filter=filter)                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\taduo\AppData\Local\Programs\Python\Python312\Lib\site-packages\pyshark\capture\file_capture.py", line 38, in __init__     super(FileCapture, self).__init__(display_filter=display_filter, only_summaries=only_summaries, File "C:\Users\taduo\AppData\Local\Programs\Python\Python312\Lib\site-packages\pyshark\capture\capture.py", line 88, in __init__     self._setup_eventloop() File "C:\Users\taduo\AppData\Local\Programs\Python\Python312\Lib\site-packages\pyshark\capture\capture.py", line 170, in _setup_eventloop     current_eventloop = asyncio.get_event_loop_policy().get_event_loop()                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\taduo\AppData\Local\Programs\Python\Python312\Lib\asyncio\events.py", line 702, in get_event_loop     raise RuntimeError('There is no current event loop in thread %r.'

Same here, I don't know how to solve

Thanks for trying this in windows. I haven't tested this in Windows so your issue helps.
Can you share the following info:

Windows version
Python version
Pip version
How did you install lpw?
do pip3 freeze > reqs.txt and attach it here

Fixed this issue. Update to LPW 0.1.3
pip install --upgrade lpw  or pip install lpw==0.1.3

Hi,
Nice to hear from you.
I still face the same issue, the information is as follows:

Windows version: windows 10 profesional
Python version: 3.12.0
Pip version: 24.0
How did you install lpw? pip install lpw==0.1.3
do pip3 freeze > reqs.txt and attach it here

altair==5.3.0
anyio==4.4.0
appdirs==1.4.4
attrs==23.2.0
blinker==1.8.2
cachetools==5.3.3
certifi==2024.6.2
charset-normalizer==3.3.2
click==8.1.7
colorama==0.4.6
gitdb==4.0.11
GitPython==3.1.43
h11==0.14.0
httpcore==1.0.5
httpx==0.25.2
idna==3.7
importlib_metadata==7.1.0
Jinja2==3.1.4
jsonschema==4.22.0
jsonschema-specifications==2023.12.1
lpw==0.1.3
lxml==5.2.2
markdown-it-py==3.0.0
MarkupSafe==2.1.5
mdurl==0.1.2
numpy==1.26.4
ollama==0.1.6
packaging==23.2
pandas==2.2.2
pillow==10.3.0
protobuf==4.25.3
pyarrow==16.1.0
pydeck==0.9.1
Pygments==2.18.0
pyshark==0.6
python-dateutil==2.9.0.post0
pytz==2024.1
referencing==0.35.1
requests==2.32.3
rich==13.7.1
rpds-py==0.18.1
scapy==2.5.0
setuptools==70.1.0
six==1.16.0
smmap==5.0.1
sniffio==1.3.1
streamlit==1.31.1
tenacity==8.4.1
termcolor==2.4.0
toml==0.10.2
toolz==0.12.1
tornado==6.4.1
typing_extensions==4.9.0
tzdata==2024.1
tzlocal==5.2
urllib3==2.2.2
validators==0.28.3
watchdog==4.0.1
zipp==3.19.2

My Web

Whole error msg
RuntimeError: There is no current event loop in thread 'ScriptRunner.scriptThread'. Traceback: File "E:\PacketWhisperer\Python312\Lib\site-packages\streamlit\runtime\scriptrunner\script_runner.py", line 535, in _run_script     exec(code, module.__dict__) File "E:\PacketWhisperer\local-packet-whisperer-main\local-packet-whisperer-main\bin\lpw_main.py", line 120, in <module>     initLLM(pcap_data=getPcapData(input_file=f'{packetFile.name}', filter=filters, decode_info=decodes))                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\PacketWhisperer\local-packet-whisperer-main\local-packet-whisperer-main\bin\lpw_packet.py", line 17, in getPcapData     cap : ps.FileCapture = ps.FileCapture(input_file=input_file, display_filter=filter)                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\PacketWhisperer\Python312\Lib\site-packages\pyshark\capture\file_capture.py", line 38, in __init__     super(FileCapture, self).__init__(display_filter=display_filter, only_summaries=only_summaries, File "E:\PacketWhisperer\Python312\Lib\site-packages\pyshark\capture\capture.py", line 88, in __init__     self._setup_eventloop() File "E:\PacketWhisperer\Python312\Lib\site-packages\pyshark\capture\capture.py", line 170, in _setup_eventloop     current_eventloop = asyncio.get_event_loop_policy().get_event_loop()                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\user\AppData\Local\Programs\Python\Python312\Lib\asyncio\events.py", line 698, in get_event_loop     raise RuntimeError('There is no current event loop in thread %r.'
Thank you very much!

@Shannon0708 the error response shows old version. Line 17 in lpw_packet.py is different in 0.1.3 . I suggest removing the package and try again.
pip uninstall lpw
pip install lpw
Or better follow https://github.com/kspviswa/local-packet-whisperer/tree/main?tab=readme-ov-file#local-development

authors: Shannon0708 kspviswa taduo

repo: kspviswa/local-packet-whisperer


text:
多次play stop 直播串流後，觸發failed to setup EAGLContext導致串流無法播放

錯誤訊息為failed to setup EAGLContext
正常播放的log
2018-04-16 09:39:31.802460+0800 [1800:922812] OK setup GL
2018-04-16 09:39:31.806145+0800 [1800:922812] ------ Player Configuration ------
2018-04-16 09:39:31.806192+0800 [1800:922812] sdk version = 2.9.0.1
2018-04-16 09:39:31.806203+0800 [1800:922812] shouldAutoplay = 1
2018-04-16 09:39:31.806212+0800 [1800:922812] shouldLoop = 0
2018-04-16 09:39:31.806220+0800 [1800:922812] shouldMute = 0
2018-04-16 09:39:31.806227+0800 [1800:922812] shouldHideVideo = 0
2018-04-16 09:39:31.806234+0800 [1800:922812] decodeMode = 2
2018-04-16 09:39:31.806257+0800 [1800:922812] bufferTimeMax = 2.000000
2018-04-16 09:39:31.806270+0800 [1800:922812] scalingMode = 3
2018-04-16 09:39:31.806278+0800 [1800:922812] prepareTimeout = 10
2018-04-16 09:39:31.806286+0800 [1800:922812] readTimeout = 30
2018-04-16 09:39:31.806293+0800 [1800:922812] ------ Player Configuration end ------
發生錯誤的log
2018-04-16 09:39:33.787736+0800 [1800:922812] failed to setup EAGLContext
2018-04-16 09:39:33.794615+0800 [1800:922812] ------ Player Configuration ------
2018-04-16 09:39:33.794708+0800 [1800:922812] sdk version = 2.9.0.1
2018-04-16 09:39:33.794740+0800 [1800:922812] shouldAutoplay = 1
2018-04-16 09:39:33.794764+0800 [1800:922812] shouldLoop = 0
2018-04-16 09:39:33.794786+0800 [1800:922812] shouldMute = 1
2018-04-16 09:39:33.794807+0800 [1800:922812] shouldHideVideo = 0
2018-04-16 09:39:33.794829+0800 [1800:922812] decodeMode = 2
2018-04-16 09:39:33.794850+0800 [1800:922812] bufferTimeMax = 2.000000
2018-04-16 09:39:33.794875+0800 [1800:922812] scalingMode = 3
2018-04-16 09:39:33.794896+0800 [1800:922812] prepareTimeout = 10
2018-04-16 09:39:33.794915+0800 [1800:922812] readTimeout = 30
2018-04-16 09:39:33.794943+0800 [1800:922812] ------ Player Configuration end ------
一但觸發
failed to setup EAGLContext 怎麼播放都是白屏，請問該如何解決

最後改用 reset 取代 stop 功能，app關閉才銷毀播放器避開這問題，failed to setup EAGLContext真的沒人碰到嗎?

不清楚你之前的代码是怎么做的，stop后播放器会销毁，应该把播放器对象设置为nil，再次播放时需要重新初始化播放器，然后再播放
如果是正常使用过程中要切换播放的视频的话，比较推荐使用reset的方式来修改url然后播放的，这样少了一个播放器的重新申请和初始化的步骤

stop后 我有確實的把播放器对象设置为nil   反覆呼叫個約70~80次之後會出現這問題，我後來改的方法就是你所提的到reset的方式


text:
Update code for consistency

With #18 merged with master, the item names should be updated too.

Race -> Ancestry
Style -> Facet
I tried doing this on my end, which made all my created items disappear. I think this is because they aren't registering for the new names. This might need some macros to update the existing item names to the new ones.
So, I humbly request your help!
Appreciated!

Fixed


text:
KTOR-7748 Generate a server project from OpenAPI specification

https://youtrack.jetbrains.com/issue/KTOR-7748

@antonarhipov, could you also check?

@vnikolova, please check the docs

@Stexxe, thanks for the PR.
Could you tell me if you thought how we would generate openAPI clients for ktor clients?

I tried this:
anton@macbook-pro tmp % ./ktor-cli/ktor openapi -o ktor-project openapi.yml
Error downloading OpenAPI utility. Please try again later.
For more details, see the log: /Users/anton/.ktor/run.log.
anton@macbook-pro tmp % less /Users/anton/.ktor/run.log:
2024/11/22 18:25:34 16: fetch OpenAPI JAR: unexpected response status 404 from the server:

404 - Path /org/openapitools/openapi-generator-cli/7.10.0-SNAPSHOT/openapi-generator-cli-7.10.0-20241106.082455-66.jar not found in local storage of repository "Snapshots" [id=snapshots]
...

I tried this:
anton@macbook-pro tmp % ./ktor-cli/ktor openapi -o ktor-project openapi.yml Error downloading OpenAPI utility. Please try again later. For more details, see the log: /Users/anton/.ktor/run.log.
anton@macbook-pro tmp % less /Users/anton/.ktor/run.log:
2024/11/22 18:25:34 16: fetch OpenAPI JAR: unexpected response status 404 from the server:
404 - Path /org/openapitools/openapi-generator-cli/7.10.0-SNAPSHOT/openapi-generator-cli-7.10.0-20241106.082455-66.jar not found in local storage of repository "Snapshots" [id=snapshots] ...

That's strange. I cannot reproduce it at the moment. Can you please try again?

authors: Stexxe antonarhipov e5l

repo: ktorio/ktor-cli


text:
Expose Event Router metrics

This PR exposes the metrics port of the event tailer.
It is up to users to scrape them or not.
On large "moving" clusters, the cardinality of the metrics can be huge.

@h4wkmoon thanks for the contribution!
Please signoff your commit with your email address as reported by the DCO check:
https://github.com/kube-logging/logging-operator/pull/1629/checks?check_run_id=20192975222
Also please run make fmt as described in https://github.com/kube-logging/logging-operator/blob/master/CONTRIBUTING.md#opening-a-pull-request-pr

repo: kube-logging/logging-operator


text:
Api::patch should only allow modifications to a subset type

This can be done using some ideas from #143. However, it is made complicated by the json patch format that sits on top of it.
This is why we should try to do it for Api::apply #174 as a starting point (which is likely what most future controllers will use in the future any because patch can be difficult to use directly).

I think this idea is probably a bit too ambitious, particularly when seeing how brittle the serialization can be when looking back at the recent k8s-openapi option unpacking experiment.
Going to close this issue. I don't think we have a clear way to do this, nor is it necessary to do this. If that changes, we can open a new issue.

Well, an analogue of this was actually done in client-go now under KEP-2155 :: generated apply configuration types, so it might be worth re-examining if we want to pick up #649. But will wait on discussion therein before re-opening this (particularly with other work on protobuf serialization).

repo: kube-rs/kube-rs


text:
fix: print manifests to stdout

Fixes https://github.com/kube-vip/kube-vip/issues/749

Hi @thebsdbox this need your attention since it fixed manifest generating in issue in 0.7.0 caused by this https://github.com/kube-vip/kube-vip/pull/746
Created follow up issue to add e2e for that https://github.com/kube-vip/kube-vip/issues/751

authors: Wielewout lubronzhan

repo: kube-vip/kube-vip


text:
add support for amazon linux 2022 (AL2022)

Feature Request
Short Description
KubeArmor could support amazon linux 2022.
Is your feature request related to a problem? Please describe the use case.
The OS is still in preview state and soon will be implemented across all aws services and it's good to have a support for that in the future.
Link: https://docs.aws.amazon.com/linux/al2022/ug/what-is-amazon-linux.html
Link: https://github.com/amazonlinux/amazon-linux-2022
Describe the solution you'd like
Create a support for amazon linux 2022.

This is a duplicate of #1005.

authors: nyrahul yasin-cs-ko-ak

repo: kubearmor/KubeArmor


text:
AWS China Support

Pricing api endpoint is different from other in aws china.
It's
https://pricing.cn-north-1.amazonaws.com.cn/offers/v1.0/cn/index.json

Hi @ywyt738, thanks for reporting this issue! We'll look into supporting AWS China's pricing correctly right away.

Not yet.

Do you publish a patch version?

@ywyt738 I believe Fang shared an update, but we're starting to investigate solutions this week!

@ywyt738 I am working on this issue this week and want to ensure that we are correctly detecting your AWS region and using that to route to the correct pricing api endpoint. Would it be possible for you to send the response of the /api/allNodes endpoint off Kubecost on our slack channel?

@Sean-Holcomb This is cost-model container's log
+ kubectl logs -f kubecost-cost-analyzer-7966c8c7f-d8zhc cost-model
I0413 05:53:42.259340       1 router.go:808] Starting cost-model (git commit "1.77.1")
I0413 05:53:42.259415       1 router.go:829] Prometheus/Thanos Client Max Concurrency set to 5
I0413 05:53:42.266932       1 router.go:842] Retrieved a prometheus config file from: http://monitor-stack-prometheus-server.monitor.svc
I0413 05:53:42.267835       1 router.go:862] Using scrape interval of 60.000000
I0413 05:53:42.270786       1 router.go:880] Success: retrieved the 'up' query against prometheus at: http://monitor-stack-prometheus-server.monitor.svc
I0413 05:53:42.272665       1 clustercache.go:92] NAMESPACE: kubecost
I0413 05:53:42.482027       1 watchcontroller.go:195] Starting *v1.Namespace controller
I0413 05:53:42.482064       1 watchcontroller.go:195] Starting *v1.Node controller
I0413 05:53:42.482086       1 watchcontroller.go:195] Starting *v1.Pod controller
I0413 05:53:42.482162       1 watchcontroller.go:195] Starting *v1.Service controller
I0413 05:53:42.482219       1 watchcontroller.go:195] Starting *v1.ConfigMap controller
I0413 05:53:42.482241       1 watchcontroller.go:195] Starting *v1.DaemonSet controller
I0413 05:53:42.482288       1 watchcontroller.go:195] Starting *v1.Deployment controller
I0413 05:53:42.482334       1 watchcontroller.go:195] Starting *v1.StatefulSet controller
I0413 05:53:42.482346       1 watchcontroller.go:195] Starting *v1.ReplicaSet controller
I0413 05:53:42.482431       1 watchcontroller.go:195] Starting *v1.PersistentVolume controller
I0413 05:53:42.482446       1 watchcontroller.go:195] Starting *v1.StorageClass controller
I0413 05:53:42.483385       1 provider.go:398] Found ProviderID starting with "aws", using AWS Provider
I0413 05:53:42.491382       1 router.go:931] No pricing-configs configmap found at installtime, using existing configs: configmaps "pricing-configs" not found
I0413 05:53:42.499744       1 router.go:939] No app-configs configmap found at installtime, using existing configs: configmaps "app-configs" not found
I0413 05:53:42.507573       1 router.go:939] No product-configs configmap found at installtime, using existing configs: configmaps "product-configs" not found
I0413 05:53:42.517800       1 log.go:47] [Info] Mapping customAlertsConfig to legacy alert configs
I0413 05:53:42.517969       1 log.go:47] [Info] Alerts disabled through cost-analyzer/values.yaml
I0413 05:53:42.526261       1 router.go:939] No saved-report-configs configmap found at installtime, using existing configs: configmaps "saved-report-configs" not found
I0413 05:53:42.527120       1 awsprovider.go:594] starting download of "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonEC2/current/cn-north-1/index.json", which is quite large ...

https://github.com/kubecost/cost-model/pull/770
We've got https://github.com/kubecost/cost-model/pull/770 in review to address this! Thanks for that report!

Hi @ywyt738 this is available in our nightly builds!  let us know if we can get you anything else here. https://github.com/kubecost/docs/blob/ef803156421396b0db30a655d1240244a9346931/release-process.md#nightly-releases

@AjayTripathy I begin to use the nightly version.(cost-model:CM-c2aecb2_KCM-d6fd871)
now log is below:
I0417 02:10:23.301371       1 router.go:310] Error returned to client: empty data for range: [2021-04-16T02:10:23+0000, 2021-04-17T02:10:23+0000)
I0417 02:10:51.502842       1 costmodel.go:946] Error getting node pricing. Error: Could not fetch data for "i-02b78cbc2745170ff"
I0417 02:10:51.503007       1 costmodel.go:946] Error getting node pricing. Error: Could not fetch data for "i-09d93069025ac3cff"
I0417 02:10:51.503093       1 costmodel.go:946] Error getting node pricing. Error: Could not fetch data for "i-0cc98726ec79a3a3a"
I0417 02:10:51.503183       1 costmodel.go:946] Error getting node pricing. Error: Could not fetch data for "i-0859bd1ff8b972bd9"
I0417 02:10:51.503247       1 costmodel.go:946] Error getting node pricing. Error: Could not fetch data for "i-0de0b6fc45ff8efb7"
I0417 02:10:51.503316       1 costmodel.go:946] Error getting node pricing. Error: Could not fetch data for "i-0e182711713bad3b3"
I0417 02:10:51.505248       1 costmodel.go:946] Error getting node pricing. Error: Could not fetch data for "i-0cc98726ec79a3a3a"
I0417 02:10:51.505386       1 costmodel.go:946] Error getting node pricing. Error: Could not fetch data for "i-0859bd1ff8b972bd9"

@ywyt738 Looks like you made it a little further along and that you have Kubecost up and running now. I have identified what I think is the issue with these new logs, and I am working on a fix.

@ywyt738 I added in 773 which I think will fix your problem. Please give the nightly build another try and share your results. The feedback is very helpful and is appreciated

@Sean-Holcomb I have upgraded to CM-0dd46e0_KCM-2b163cd. It works good.
Is the price unit on the frontend USD or CNY?

@ywyt738 Awesome, I am glad to hear it! The price unit should now be CNY. You can actually change the display unit of Kubecost changing this option from USD to CNY which should make things on the UI a little more clear. I am going to close this ticket for now. Please let us know if you encounter any other issues

repo: kubecost/cost-model


text:
feat: add integration tests for pipeline cronjob

Signed-off-by: João Vanzuita joao@kubeshop.io

we got it merged here https://github.com/kubefirst/kubefirst/pull/322

repo: kubefirst/kubefirst


text:
GKE node auto-provisioning not scaling down

While using kubeflow 1.0, 1.2, 1.3 I have noticed that sometimes nodes do not scale down.
AFAIU this happens because of node auto-provisioning. Nodes are scaled up and in some cases kube-system pods might start running on them, preventing them from scaling down.

One option to consider is to put a taint on the nodepool that you want to be able to scale to 0. That way system pods will not be able to run on those nodes, so they won't block scale-down. Downside is you'll need to add a toleration to all the pods that you want to run on this nodepool (this can be automated with mutating admission webhook). This is a very useful pattern if you have a nodepool with particularly expensive nodes.
Alternatively you can create PDBs for all non-daemonset system pods. Note: restarting some system pods can cause various types of disruption to your cluster, which is why CA does not restart them by default (ex. restarting metrics-server will break all HPAs in your cluster for a few minutes). It's up to you to decide which disruptions you're ok with.

https://github.com/kubernetes/autoscaler/issues/2377#issuecomment-618275429
Not sure if relevant but maybe these lines require an update?
https://github.com/kubeflow/gcp-blueprints/blob/1d41c6ca7fc904d91dfcfb44e61e42435801e72c/kubeflow/common/cluster/upstream/cluster.yaml#L32-L37
Currently I'm considering to cancel the node auto-provisioning although it would be nice to have this working as expected.
Any ideas how to fix this?

A known problem is Istio Sidecars
https://istio.io/latest/docs/ops/common-problems/injection/#cluster-is-not-scaled-down-automatically
We need to add cluster-autoscaler.kubernetes.io/safe-to-evict": "true" for all the pods with istio sidecar and are safe to evict.

We could add this to known services for users, welcome contributions!

authors: Bobgy Shaked

repo: kubeflow/gcp-blueprints