MapChangeListener interface for android

Adds MapChangeListener for android platform:
- onRegionWillChangeAnimated
- onRegionIsChanging
- onRegionDidChangeAnimated
- onViewComplete

Adds begin/end interfaces for touch gesture responder interfaces:

[x] Pan Responder

[x] generic logic to determine begin/end for pan gestures.

[x] Shove Responder
[x] Scale Responder
[x] Rotate Responder

Provides mechanism to set mapChangeListener from client via MapController.

[ ] Handle mapIsChanging calls for when map is animating due to camera animation. (Will be handled in a subsequent PR)

For Pan, I still am finalizing my thoughts to have a generic way to detect begin and end pan gestures, without putting too much map logic to TouchInput what I had before and reverted in my last commit.

Ok Updated to include pan beginning and end logic and to call apt map change events associated with these. Also updated some docs.
This also fixes couple of issues with Pan Gestures:

Pan Gestures once detected was never removed from the detectedGestures list
SingleTap gesture can now respond aptly, probably because of the above.

Ahh thanks, totally forgot about Npe :(
On Mon, Sep 10, 2018 at 7:28 PM Matt Blair<EMAIL_ADDRESS>wrote:

@matteblair requested changes on this pull request.
The approach here looks good, but there are a lot of spots where methods
are called directly on the (nullable) mapChangeListener without checking
for nullity. Run the demo without setting a mapChangeListener and it'll be
easy to find them from the NPE stack traces ;)
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#1386: Additional global parameter that can be set to change the typi…

Ticketnummer: #1386
controller.setTypingDelayFactor();
Adjust the speed of the typing delay by setting a factor. The typing delay determines the time that the bot takes, to reply to a message. By default, the factor is set to 1, using a predefined calculation for the typing delay, that takes the message length into account. In order to increase or decrease the typing delay, the factor can be changed. For example, the default typing delay can be doubled by setting the factor to 2.
For example:
// double the time of the typing delay
controller.setTypingDelayFactor(2);

@schmitzl I think that since this only affects the web adapter, it should be part of that file, not in Core.
I try to avoid putting anything in core that doesn't apply to all platforms.
Can you define the function and variable in Web.js instead?
Also, please add a note about this to the docs page for the web connector that is contained in this other repo

@benbrown Thank you for the feedback. I implemented the changes and created a pull request for the docs (https://github.com/howdyai/botkit-docs/pull/9).

Great, I will re-review! Thanks contributing!

oops @schmitzl it doesn't look like your new changes have been pushed to this PR yet

@benbrown Sorry, wrong branch! I hope you can view the changes now.


Fix problems discovered by @phpstan

The only hard one was if ( ! count($args) > 3)

if you disable loading of Patchwork.php you can continue with
vendor/bin/phpstan analyse -l 4
be aware of https://github.com/phpstan/phpstan/issues/1482

Have I made a mistake? Test are red 🔴

Codecov Report

Merging #70 into master will not change coverage.
The diff coverage is 100%.

@@            Coverage Diff            @@
##             master      #70   +/-   ##
=========================================
  Coverage     91.54%   91.54%
  Complexity      316      316
=========================================
  Files            28       28
  Lines           781      781
=========================================
  Hits            715      715
  Misses           66       66

Impacted Files
Coverage Δ
Complexity Δ

src/Name/Exception/InvalidCallable.php
88.88% <ø> (ø)
3 <0> (ø)
:arrow_down:

src/Name/Exception/InvalidName.php
86.95% <ø> (ø)
9 <0> (ø)
:arrow_down:

src/Expectation/Expectation.php
93.44% <ø> (ø)
28 <0> (ø)
:arrow_down:

src/Name/Exception/InvalidClosureParam.php
53.33% <ø> (ø)
3 <0> (ø)
:arrow_down:

src/Expectation/FunctionStub.php
92.77% <ø> (ø)
30 <0> (ø)
:arrow_down:

src/Expectation/EscapeHelper.php
100% <ø> (ø)
5 <0> (ø)
:arrow_down:

src/Name/FunctionName.php
100% <ø> (ø)
11 <0> (ø)
:arrow_down:

src/Name/CallbackStringForm.php
85% <ø> (ø)
29 <0> (ø)
:arrow_down:

src/Container.php
100% <100%> (ø)
10 <0> (ø)
:arrow_down:

src/Hook/HookStorage.php
92.95% <100%> (ø)
38 <0> (ø)
:arrow_down:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 547dff7...043a5d7. Read the comment docs.

Thanks a lot for your work.
As you already said you were able to find a bug.
Most of the doc bloc fixes were also were also very fine, and I definetevely want ot merge those.
For some other I commented why I would like to keep what I have.
That said, I also want ot write a unit test for the bug you discovered.
Because I want to do a release today (while I have some time) I think it is faster if I refuse this PR and do myself a commit with most of the changes you suggested, but will make sure to credit you where due.
Thanks a lot for your work, I really appreaciate it.

I understand you points.
When I (secretly) develop code daily I use PHPStan to check my work - I'm not an IDE user.


Added stock feature to see the stock price of a company

Integrate Stock API into Personal Robot Butler Script
Overview
This pull request integrates a Stock Market API into the Alexis Python script. This feature allows users to fetch the stock price of a company.
Update
Extended the main command loop to include a "stock" command, which triggers the Stock Market API to retrieve data about a company's stock price.
Usage
Users can retrieve the stock price of a company by inputting the command "stock" in the script interface.

This PR is associated with the issue #1

Looks good thanks!


Batch uploading images?

Hello,
I downloaded a bunch of images from various image boards but I haven't found a way to batch-upload them to Boorunaut.
Is there a way to do that, and also tag them automatically?
In my downloads folder, there are images (e.g. 123.jpg), and a 123.txt file containing all the tags. Automatically using that .txt file for the tags would be great!

There isn't a way to do this yet, but it's a great feature to have!
I'll create a feature request for this later, but the project is not
actively maintained until I get some time to dive in it
Em sex., 6 de set. de 2024 20:37, pbz134 @.***>
escreveu:

Hello,
I downloaded a bunch of images from various image boards but I haven't
found a way to batch-upload them to Boorunaut.
Is there a way to do that, and also tag them automatically?
In my downloads folder, there are images (e.g. 123.jpg), and a 123.txt
file containing all the tags. Automatically using that .txt file for the
tags would be great!
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There isn't a way to do this yet, but it's a great feature to have! I'll create a feature request for this later, but the project is not actively maintained until I get some time to dive in it Em sex., 6 de set. de 2024 20:37, pbz134 @.> escreveu:
…
Hello, I downloaded a bunch of images from various image boards but I haven't found a way to batch-upload them to Boorunaut. Is there a way to do that, and also tag them automatically? In my downloads folder, there are images (e.g. 123.jpg), and a 123.txt file containing all the tags. Automatically using that .txt file for the tags would be great! — Reply to this email directly, view it on GitHub <#186>, or unsubscribe https://github.com/notifications/unsubscribe-auth/ABZBUNUV2EFS5KRUROWSP2DZVI4FPAVCNFSM6AAAAABNZONTV2VHI2DSMVQWIX3LMV43ASLTON2WKOZSGUYTCMZRHA3DONA . You are receiving this because you are subscribed to this thread.Message ID: @.>

Thanks a lot!
I would really need this feature I have checked out quite a few Booru remakes but they either don't support Windows or are worse in functionality than I want them to be.


Add check that components sockets don't contain forbidden chars

Since input sockets are meant to be passed as parameters to a component's run method they must be valid Python identifiers.
Similarly output sockets must be declared using the @component.output_types(<socket_name>=<type>) decorator so they must respect the same requirement.
We can leverage str.isidentifier() and keyword.iskeyword(<string>) to validate the socket name.

Let's not forget to add a note about this in the documentation


Doesn't work if the app is running from a remote machine

Hello friends,
Here is my case, I'm running an app in a docker container which is hosted from a remote VPS:

The app is running with --inspect=8080.
The container exposes port 8080

So let's assume that the VPS host is 123.30.xxx.xxx, 8080 is exposed to 33129, it means that the debugger uri should be:
https://chrome-devtools-frontend.appspot.com/serve_file/@60cd6e859b9f557d2312f5bf532f6aec5f284980/inspector.html?experiments=true&v8only=true&ws=123.30.xxx.xxx:33129/8c3a0c56-74f0-48ee-abca-feecea95f08f

... but http://123.30.xxx.xxx:33129/json/list responds:
[
  {
    "description": "node.js instance",
    "devtoolsFrontendUrl": "https://chrome-devtools-frontend.appspot.com/serve_file/@60cd6e859b9f557d2312f5bf532f6aec5f284980/inspector.html?experiments=true&v8only=true&ws=localhost:8080/8c3a0c56-74f0-48ee-abca-feecea95f08f",
    "faviconUrl": "https://nodejs.org/static/favicon.ico",
    "id": "8c3a0c56-74f0-48ee-abca-feecea95f08f",
    "title": "/code/node_modules/pm2/lib/ProcessContainerFork.js",
    "type": "node",
    "url": "file:///code/node_modules/pm2/lib/ProcessContainerFork.js",
    "webSocketDebuggerUrl": "ws://localhost:8080/8c3a0c56-74f0-48ee-abca-feecea95f08f"
  }
]

The point is in the devtoolsFrontendUrl:

chrome-devtools-frontend.appspot.com/serve_file/@60cd6e859b9f557d2312f5bf532f6aec5f284980/inspector.html?experiments=true&v8only=true&ws=123.30.xxx.xxx:33129/8c3a0c56-74f0-48ee-abca-feecea95f08f
chrome-devtools-frontend.appspot.com/serve_file/@60cd6e859b9f557d2312f5bf532f6aec5f284980/inspector.html?experiments=true&v8only=true&ws=localhost:8080/8c3a0c56-74f0-48ee-abca-feecea95f08f

Therefore the extension doesn't work in my case. I'm not sure whether debugging remotely in other cases works well or not, please tell me your opinion, I can make a PR when this problem is clear and solved.
Thank you.

The /json/list endpoint comes from the V8 Inspector in Node core. The front end URL makes sense because the Node application is running on localhost:8080 as far as it knows.
That said, the extension could probably just replace the front end host and port with its own options.


generators.json is missing from the installed package

Version
0.5.0
Bug Description
When I use the ng add ng-primitives command it'll install the package but returns an error at the end.

When checking node_modules, the generators.json file is indeed missing:

Steps to Reproduce
No response
Reproduction
No response

Thank you for the report, this should now be resolved in v0.5.1

Awesome! Thanks for the quick fix!

No problem 😊


Campaign Collections are missing content on front end

Content is not being output properly on Campaign Collections. The following fields/field collections aren't working as intended:

field_intro_title
field_intro
field_faq
field_gallery

Not sure if other content is being displayed properly or not.
example: https://www.dosomething.org/volunteer/step-game
Potentially related to #5714

It looks like it's because the fields are translatable and I disabled fallback, was this displaying correctly before @mikefantini?

Hmmm @angaither I actually think it may be because that node is unpublished. @sergii-tkachenko didn't you run a script to fix this for published nodes?
It's working properly on https://www.dosomething.org/volunteer/seniors-and-smartphones

This issue also exists on thor:
https://thor.dosomething.org/volunteer/step-game

Ok so for Collection nodes the fix @sergii-tkachenko did was this: https://github.com/DoSomething/phoenix/pull/5691 and he executed it here: https://github.com/DoSomething/phoenix/issues/5724.
It seems like this just needs to be done again for unpublished nodes.
Are you able to take this on @sergii-tkachenko?
cc: @angaither

@mikefantini Ah, sorry again for the confusion. It did not excluded unpublished nodes, that was a fix FOR unpublished nodes.


Add nullcheck  during favorite protocol determination

Add nullcheck  during favorite protocol determination. fix for #1237

Thanks!


Issue with rendering complex PDFs in Designer component on Vercel

Describe the bug
When uploading certain PDFs in the Designer component, the PDF content is not displayed properly on the live server (deployed on Vercel). It appears as blank in the interface, but the same PDF is displayed properly on localhost. When the PDF is flattened prior to uploading, it displays correctly in all environments.
To Reproduce
Steps to reproduce the behavior:

Fork pdfme/playground
Deploy on Vercel
Upload a complex PDF in the Designer component
PDF content appears blank

Expected behavior
All PDFs, regardless of complexity, should be rendered correctly in the Designer component on both localhost and the live server.
Your Environment
Local Environment
The PDFs are correctly displayed on the local development environment.

Live Environment
The issue arises when the project is deployed on Vercel. Complex PDFs appear blank in the Designer component.

Your Error Log
There is no error appearing on the live server.

Additional context
ScreenShots:
Deployed Version (Vercel):

Local Server:

Hi @DevRSC
I'll check this problem.

Hi @DevRSC
Fixed pdfme version 1.2.3.
Thank you.


❓ Is it impossible to add a custom columns to getNodesHierarchyQueryBuilder()?

I've build a working custom getChildrenHierachy() function:
    public function getChildrenHierachyByCategoryIDs($categoryIDs)
    {
        $qb = $this->getNodesHierarchyQueryBuilder();
            $qb->andWhere('node.id in (:categoryIDs)')
            ->setParameter('categoryIDs', $categoryIDs)
        ;

        $aComponents = $qb->getQuery()->getResult(\Doctrine\ORM\Query::HYDRATE_ARRAY);

        return $this->buildTreeArray($aComponents);
    }

Now I want to add a custom column to the result:
    public function getChildrenHierachyByCategoryIDs($categoryIDs, $highlightCategories)
    {
        $qb = $this->getNodesHierarchyQueryBuilder();
        $qb->addSelect('CASE WHEN(node.id = 5) THEN 1 ELSE 0 END') // 5 = test value
            ->andWhere('node.id in (:categoryIDs)')
            ->setParameter('categoryIDs', $categoryIDs)
        ;

        $aComponents = $qb->getQuery()->getResult(\Doctrine\ORM\Query::HYDRATE_ARRAY);

        return $this->buildTreeArray($aComponents);
    }

The runnable query itself (that Symfony is generating) is working perfectly!
But I get an error from return $this->buildTreeArray($aComponents); with the message:

Notice: Undefined index: level

(Full message:
Uncaught PHP Exception ErrorException: "Notice: Undefined index: level" at /PROJECT/vendor/gedmo/doctrine-extensions/lib/Gedmo/Tree/RepositoryUtils.php line 146)
Is it impossible to add custom data to the getNodesHierarchyQueryBuilder()?

I think the issue is related to you not aliasing your statement result. (Apologies for the lack of time to try and reproduce.) Your $aComponents items should each have an index with the name of the column you defined as the TreeLevel (usually it's level or lvl -- in your case it appears to be level).
Maybe you can confirm that this index exists in your items in the working query, and then doesn't when adding in the new statement?
And to fix, you can try adding as my_result (or whatever you want to name that "column") after the END part of your statement to assign it a name to use in the result.
And since this is just a guess, please update if that isn't the case. Any more stack traces or data dumps you can add will help.


pull request for e2e test at 02/04/2017 09:15:07

:white_check_mark: Validation status: passed
For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.


Remove Gradle and Maven plugins duplicated doc reference

Removed unnecessary Gradle and Maven plugins documentation reference from introduction as it is already referenced on the line above and on the Quickstart section.

Hi @wilder , we appreciate your contribution! However, after discussions with the team, we believe keeping the README in the current format helps users find what they need to in the most efficient manner. We welcome you to make further contributions in the future and recommend starting with filing an issue so others can discuss potential solutions as well.

@coollog Sure!
Thank you.


feat: add product for kse and ks

add product for kse and ks

test result
run in kubernetes

result send to cloud

/lgtm
/approve


MM-10776: Adds support for new API endpoint to update team or channel…

… member scheme roles.
Summary
Provides access to new API endpoints to update a channel and team member's scheme roles.
Ticket Link
MM-10776
Checklist

[x] Ran make check-style to check for style errors (required for all pull requests)
[x] Ran make test to ensure unit tests passed
[x] Ran make flow to ensure type cheking passed
[x] Added or updated unit tests (required for all new features)
[x] All new/modified APIs include changes to the drivers

Test Information
Chrome 67.0.3396.62, macOS 10.13.5

@mkraft Maybe the destination branch must be release-5.0

@jespino It hasn't been cut yet so we should be good.


Handle use effect re-renders for exploration tool

@Carifio24 There were a few things that were at play, so I ended up just making a copy of your branch so I could highlight them more easily. Feel free to copy over what you want and close this, or just pull it in (my formatter got aggressive when I pushed this up, so I there's minor pep-related changes that got included which might be annoying).

I would suggest we try and keep component_state stuff in the top-level Page file, just to ensure page-level state stays with the page it goes with and doesn't get buried in separate individual components. You'll notice I moved the ComponentState back to the __init__.py file and just passed in the relevant piece to the IntroSlideshow component.
The IntroSlideshow component should also be a solara.component itself, since we use it as such (have use_reactive variables, etc.), and it's also important for certain solara context-sensitive issues.
I'm not actually super sure why the use_effect wasn't working, but it seems that just wrapping it in its own solara component (ExplorationToolComponent at the top of the IntroSlideshow file) seemed to solve the issue. I'll try and ping Maarten about why this might be, but for now, at least we know some possible solutions if we come across this issue.

@nmearl Awesome, thank you! I'll merge this in (the formatter changes are more to my liking as well). Yeah, I was not really a fan of putting the coordinates into the ComponentState, but since that was working in Stage 1, I was trying to mimic that setup to see if it helped when I got stuck. I actually thought IntroSlideshow was already a solara.component, but I really should've checked that in the course of trying to work this out (oops!)


Scrollbar not draggable in Chrome overlay-scrollbar

Hi Team,
I am from chrome team and currently working on overlay-scrollbar and it will land soon. I recently got a bug report about CodeMirror. https://bugs.chromium.org/p/chromium/issues/detail?id=707337
For this issue, I have 2 solutions to fix:

use overflow: auto and not hide the default scrollbars. Can you also tell me the reason for CodeMirror create another scrollbars and hide the default scrollbars. I will fix it if it is a chrome related issue.
fix the calculation of zeroWitdh https://github.com/codemirror/CodeMirror/blob/master/src/display/scrollbars.js#L114

Thank you.

Also we will use this 2 flags to enable overlay scrollbar. --enable-overlay-scrollbar --enable-prefer-compositing-to-lcd-text

Can you also tell me the reason for CodeMirror create another scrollbars and hide the default scrollbars.

See http://marijnhaverbeke.nl/blog/a-pathological-scrolling-model.html

fix the calculation of zeroWitdh

What is wrong with zeroWidth?

What is wrong with zeroWidth?
It set pointer-events none when we enabled overlay scrollbar. That makes scrollbar not draggable.

It briefly re-enables pointer events when you scroll, which works for OS X-style scrollbars -- but maybe your overlay scrollbar works differently? Is it constantly visible? How does it prevent interfering with mouse events that want to interact with the content on the right of the viewport?

Yes, we have some different with Mac-Overlay-Scrollbar. Mouse near or hover will not fade out the scrollbar.

Do they handle pointer events on the whole bar, or only the handle? What if the user wants to interact with the content under it?

Do they handle pointer events on the whole bar, or only the handle?
The whole bar.
What if the user wants to interact with the content under it?
Need to move mouse far from scrollbar.

Need to move mouse far from scrollbar.

I don't understand. If the content is below the scrollbar, you can't interact with it when you're far away from the scrollbar.

move mouse far away then scrollbar fade out then you can interact with it.

Is there any way for CodeMirror to figure out whether a given scrollbar is faded in or out?

No. we don't.

That's going to make it difficult to do the right thing when the user interacts with the pixels covered by the scrollbar element.

Maybe we can enable custom scrollbar on ChromeOS since we will only make overlay scrollbar by default on CrOS soon.
I think the fake scrollbar not really improve the scroll proformance. At least on Chrome, the fake scrollbar will make the scroll happends on main thread not cc thread.

I think the fake scrollbar not really improve the scroll proformance.

It isn't about scroll performance, as you can read in that blog post I linked, it's about preventing the user from scrolling content that hasn't been drawn into view. I.e. regular scroll events aren't synchronous, so we need the fake scrollbar to be able to respond to scrolling before the main content is redrawn.

There is a spec for scrollbar gutter. But no browser support it at this time. https://drafts.csswg.org/css-overflow/#scollbar-gutter-property

Does attached patch help for you? I found I could enable these scrollbars with a flag, so I could test them on Linux. The hack that was in place for OS X scrollbars almost worked for Chrome's, and with attached tweak it worked for me (I didn't test Chrome OS, since I don't have a device that runs it).

Yes, The Linux with flag "--enable-overlay-scrollbar --enable-prefer-compositing-to-lcd-text" will have same behavious with ChromeOS. It works better now. Still have some issue, I'll work on it. Thank you.


merge the candidates table column questionnaire_response conflict

so i didn't notice that there is a new column being added in candidates table. Just update my side and merged.
In the future, if table schema changes, please remember to update the import_candidates script.


MORE STYLING

Created a separate page, stockDisplay.html, for the tables.

Kinnesh PR thanks for the work


treat some regexp as a comment start

In jsx, expression like /^/*$/ is treated as a comment start

This issue was moved to Microsoft/TypeScript#7295


undefined symbol: nvds_msg2p_generate_multiple_new

I'm getting the following error when running with [sink1] enabled.

Is this a dependency issue caused by DS 6.0?

Hi Mimnsi,
Thank you for reporting the issue. I will update the repo for ds 6.0.

Hello,
Added the support for ds6.0. Please check ds_6.0 branch.

Sorry I ddint get.Do you mean install Deepstream 6.0 again or there is some specific link

Hello,
Added the support for ds6.0. Please check ds_6.0 branch.

Awesome, Thank you so much!

Sorry I ddint get.Do you mean install Deepstream 6.0 again or there is some specific link

I have DS 6 on my system and the repo was built for 5.0 so there were dependency issues earlier. They updated the repo to support DS 6 so it should work now. We have to use the other branch now instead of the master.

I have tried it inside deepstream-l4t tag 6.1-triton and I still have this issue using branch ds_6.0


In-app messaging popup(Android).java

Step 1: Describe your environment

Android device: mi y2
Android OS version: 8.1

Step 2: Describe the problem:
Steps to reproduce:
Question 1:-
In this popup the background color is not shown. It is always white (infact I changed the color on firebase console as per guidelines ). How can I change the background color?
Question 2:-
In this popup is always triggering in splash screen. I want it to trigger in main activity. How to do it?

@Dnyaneshwar1926 this sounds like it's an issue with the In-App Messaging SDK so I will transfer this over to that repo.  Can you please also provide the code you're using (if any) to launch the pop up?


Consume from Vs Code

How can an artifact be downloaded and used in VS Code? Why do the examples only show Visual Studio?

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 899a78d6-9d08-7744-108d-10add2ba7e2c
Version Independent ID: 6ab31e96-fed8-4335-ed81-b97663d8300f
Content: Consume NuGet packages in Visual Studio
Content Source: docs/artifacts/nuget/consume.md
Product: devops
Technology: devops-artifacts
GitHub Login: @elbatk
Microsoft Alias: elbatk

Thanks for your question. It looks like you're working through an issue with your scenario or implementation, rather than an issue with the documentation. Here are a few options where you might consider asking your question:

Azure DevOps on Stack Overflow
Azure DevOps Support Bot


Complete UI mockup

Do we agree that this is just part of Issue #28 ? Or do we need some more clarification


Matt main

Removing secret and access keys from CORTX-Flask-MediaViewer integration
Signed-off-by: hessio<EMAIL_ADDRESS>Describe your changes in brief
Changes

[ ] Why is this change required? What problem does it solve?
[ ] If proposing a new change then please raise an issue first

How Has This Been Tested? (Optional)

[ ] Please describe in detail how you tested your changes.
[ ] Include details of your testing environment, and the tests you ran to
[ ] How your change affects other areas of the code, etc.

Screenshots (if appropriate)
Checklist

[ ] tested locally
[ ] added new dependencies
[ ] updated the docs
[ ] added a test

View rendered doc/integrations/CORTX-Flask-MediaViewer/README.md

@hessio, can you fix the Codacy issues & signed-off your commits as DCO is failing

fix Codacy issues & signed-off your commits as DCO is failing

@hessio, Codacy check is still failing

@hessio, it has conflicts so please fix

@hessio, it has conflicts so please fix

Conflicts are resolved, the Codacy issues are bugs please check Codacy rules as they are bugs in Codacy

Thank you for your pull request and welcome to our community. We could not parse the GitHub identity of the following contributors: root. This is most likely caused by a git client misconfiguration; please make sure to:

check if your git client is configured with an email to sign commits git config --list | grep email
If not, set it up using git config --global user.email<EMAIL_ADDRESS>Make sure that the git commit email is configured in your GitHub account settings, see https://github.com/settings/emails

@hessio, look like you haven't configured your git config username & email on your local server

Duplicate


No More Bean Overriding

Changelog:

No longer registering a custom Validator instance.
Keeping the bean overriding feature disabled.

Codecov Report

Merging #70 into master will increase coverage by <.01%.
The diff coverage is n/a.

@@             Coverage Diff              @@
##             master      #70      +/-   ##
============================================
+ Coverage     90.43%   90.43%   +<.01%
+ Complexity      260      257       -3
============================================
  Files            32       31       -1
  Lines           627      617      -10
  Branches         77       77
============================================
- Hits            567      558       -9
+ Misses           32       31       -1
  Partials         28       28

Impacted Files
Coverage Δ
Complexity Δ

.../me/alidg/errors/conf/ErrorsAutoConfiguration.java
92.59% <ø> (+1.96%)
13 <0> (-1)
:arrow_down:

...dg/errors/conf/ServletErrorsAutoConfiguration.java
100% <ø> (ø)
3 <0> (ø)
:arrow_down:

...g/errors/conf/ReactiveErrorsAutoConfiguration.java
100% <ø> (ø)
2 <0> (ø)
:arrow_down:

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404 error on running bot on local host

I'm trying to run a microsoft bot locally using iis express, however whenever I run the bot the browser of choice shows up giving me a 404 error and the following details
Module | IIS Web Core
MapRequestHandler
StaticFile
0x80070002
I've tried changing numerous settings within the iis manager to no avail. I can run a very basic bot framework succesfully. Also, this code works on other computers I know for fact so it seems to an problem with a setting somewhere opposed to the code itself
I've also tried setting allowallmodules to true in the web.config which is a solution is saw often

Hi @OBrien1510. I'm closing this issue. Please ask your question in the appropriate repo:

Create Bot Builder SDK V3 (.NET or Javascript) issue
Create Bot Builder SDK V4 .NET issue
Create Bot Builder SDK V4 Javascript issue
Create Bot Builder SDK V4 Java issue
Create Bot Builder SDK V4 Python issue

Also consider:

"How To" questions should be submitted on Stack Overflow.


accept numbers created with new-operator

Add support for numbers created with new Number constructor function:
isPositive(new Number(1))
//=> true

Thanks :).


JCodec 0.2.5 tag not present for release

Maven Central repository updates for version 0.2.5 is dated June 16 2019 however there are not commits around that time. There is also no tag or release in the repository for 0.2.5 (or 0.2.4).

The following pull request had been approved, which implies that 0.25 had been built and released on Maven repo.
stacks13:patch-1


Undo loop optimization

Undo https://github.com/microsoft/python-language-server/pull/1686. Basically fork right before the PR then cherry pick changes on top. Also removes caching services.
Fixes #1988 and probably some others - to be verified.
Some tests became less stable due to old loop resolution issues.

This is great. Many thanks. I hope #1988 can be fixed soon.

There seem to be some regressions in the __all__ handling. Might be something that was over-reverted, since I know the loop dependency stuff was using it to some extent.

Minimized differences and ported fixes from PRs that were not taken due to compatibility problems with old code.

What happened to __all__? Yes, loop resolution can definitely affect that. Theoretically it is possible to build off commit right before the loop one and compare if behavior is the same.

If you run the whole test suite, many of the __all__ related tests fails.

Ran full stack, mine's are clean except one import ordering (it uses os and path which have loops, I guess I need to update the test).

Those LS results appear to be cached; if I run them I get:

Those I not cached, they turn this way when you re-run individual tests. HoverSpanCheck was a known problem, typically passes on re-run. In MissingImports SymbolOrdering2 failed, very long test. Fixed.
What fails for you in highlight and imports? Are you on 3.8 or higher?

Well, this is embarrassing. I'm still on your undo branch. I didn't see that this PR was being made from a branch on the repo itself rather than a fork. I'll retest.

Yeah, now that I run the actual code it passes... 😄
I'll spot check this on some real code.

This should be off my fork, u2 branch

Is these anything that can be done on Code comment level so this bug will not be introduced again? Are these regression tests possible?


Mark days with- or without notes differently in the calendar.

Mark days with- or without notes differently in the calendar.
I replaced rednotebook with Joplin for it’s markdown abilities and got it nearly completely replaced by using calendar and journal add-on.
In rednotebook it is really nice feature to get the empty vs. non-empty days previewed in the calendar differently and jump over empty days in the keyboard navigation.

Thanks for the suggestion.
Most calendar plugins in other note taking apps have this feature. So this will eventually be added in the future.

Added dots to calendar dates to indicate days where notes were created.
This feature was added in 1.0.0-pre-release-5.
Still need to implement the jumping between non-empty days via keyboard navigation.

Can jump non-empty days via keyboard navigation now. Will be released in next update.


Add sitemap checker script

Created a sitemap checker script that will scan all URLs in the pulumi.com sitemap and attempt to request them on the www-reg-staging.pulumi-dev.io site.
Worth noting--it runs quite slowly (obviously). On my machine it probably took somewhere around 30ish minutes to run, so it might be worth running this concurrently. I'm not certain what we'd like our constraints to be there. cc: @EvanBoyle @cnunciato
Issue
Fixes #56
4xx pages
Running this script produced these errors:
403 https://www-reg-staging.pulumi-dev.io/blog/azure-container-solutions/
403 https://www-reg-staging.pulumi-dev.io/blog/pulumi-kubernetes-operator-1-0/
000 https://www-reg-staging.pulumi-dev.io/docs/reference/pkg/azure-native/datafactory/getexposurecontrolfeaturevalue/
403 https://www-reg-staging.pulumi-dev.io/docs/reference/pkg/azure-native/automation/getpython2package/
000 https://www-reg-staging.pulumi-dev.io/docs/reference/pkg/gcp/securitycenter/notificationconfig/
403 https://www-reg-staging.pulumi-dev.io/docs/reference/pkg/azure-native/automation/python2package/

It's worth noting that both of those 000 codes mean cUrl failed to execute--and could be caused by either a timeout (likely) or an inability to resolve the DNS. Both of those pages are 301 redirects that appear to work when I request them manually.

Just a thought, it'd be sweet if this had a verbose mode that gave you a sense of what the script is doing, since it takes so long to run it.

... also, not for now but for a V2 kind of thing, you might think about doing this as a Node script instead, just for the additional flexibility and maintainability. I know for my part, doing things like this in Bash can quickly become a lot more trouble than it's worth! 😄


rtop Windows Support: Convert bash wrapper to ocaml

Fixes #2167
I think the file should be named something other than rtop.ml but I can't get dune to work with anything else.

This fails when there is no ~/.utoprc file:

Fatal error: exception Unix.Unix_error(Unix.ENOENT, "open", "/…/.utoprc")


execute multiple commands into a prepared statement

How To execute multiple commands into a prepared statement In yii2
I am  using postgresql.
when I call a function like..

SELECT proc_customer_request('cities_cur','REGISTRATION','05E000~1'); FETCH ALL IN "cities_cur"

What do you get instead?
SQLSTATE[42601]: Syntax error: 7 ERROR: cannot insert multiple commands into a prepared statement The SQL being executed was: SELECT proc_customer_request('cities_cur','REGISTRATION','05E000~1');  FETCH ALL IN "cities_cur"
Additional info
$connection = \Yii::$app->db;
$sql ="SELECT proc_customer_request('cities_cur','REGISTRATION','05E000~1');  FETCH ALL IN "cities_cur";
$result = $connection->createCommand($sql)->queryAll();

Please Help me to This.

Q
A

Yii version
2

Operating system
ubundu

Your problem is related to PDO rather than to Yii. Check out this answer: http://stackoverflow.com/a/6461110/3584248

hi,
I already checked that but it shows an error PDO not found.
how to use
$db=new  PDO(); in yii2 and I am using postgresql.
i checked the php.ini file and enabled the extension for pdo and pgsql. and when run phpinfo(); it shows PDO and pgsql are enabled.
Please help me to do this..

I apologize if I reopen this issue but I don't know if is exactly a PDO or a PostgreSQL problem.
On MySQL/MariaDB works fine. For instance, I need to read some sql files, one of them auth_item.sql for RBAC. On migration, works on MariaDB but not works on PostgreSQL. I haven't tested on SQL Server (I can't make work the driver) but that's the issue.


The issue regarding concurrent processing with multiple GPU cards

What is the issue?
Premise:
There are 4 GPU cards in the Linux server, and OLLAMA_SCHED_SPREAD=1 is set, with the aim of improving the model's inference efficiency through concurrent processing on multiple GPU cards.
My Scenario:
In the same process, I wish to sequentially call 3 different LLM models to handle the same task (such as summarizing long text), with the intention that users can see the different content summarized by the 3 different LLM models and compare the processing effects of different models.
After the process runs, it can be observed that each model runs on multiple GPU cards, but there are the following issues:

After the first model finishes running, the second model reports an OOM error, and the third model sometimes succeeds and sometimes fails.
Is this issue because after the first model finishes running, all GPU resources are not released completely, and the second model fails due to lack of GPU resources when it continues to run, while the third model succeeds if the GPU resources have been released, and fails if the GPU resources are still not completely released?
If OLLAMA_SCHED_SPREAD=1 is not set, all three models will run successfully because ollama will use different GPU cards to handle the requests of the three models separately, but this method is slower because each model uses a single GPU card for processing.

My requirements are as follows:

If OLLAMA_SCHED_SPREAD=1 is set, how can GPU resources be quickly released after the first model finishes running to ensure that subsequent models do not fail due to insufficient GPU resources?
If solution 1 cannot be met, what methods can be used to improve model inference efficiency through concurrent processing on multiple GPU cards?

Other Questions (without setting OLLAMA_SCHED_SPREAD=1):
Ollama defaults to OLLAMA_NUM_PARALLEL=4, and if a single GPU card cannot meet the resources for 4 concurrent processes, ollama automatically sets PARALLEL=1. At this time, if a single GPU card can meet the resources needed for PARALLEL=1, one GPU card performs inference; and if a single GPU card cannot meet the resources needed for PARALLEL=1, ollama automatically uses 4 GPU cards to process, is this an automatic and default mechanism?
Summary:
The overall requirement is how to improve the efficiency of concurrent inference when there are multiple GPU cards, thereby enhancing the user experience.
OS
Linux
GPU
Nvidia
CPU
Intel
Ollama version
0.3.14

When you get an OOM error, is all VRAM allocated?  Server logs and the output of nvidia-smi will aid in debugging.

Hi @rick-github
I have analyzed the relevant logs and placed the log files in this issue, and I have also copied them in issue #7146. Please close either one of them.
Thank you for your reply. I have conducted the following two tests, and I am unsure how to handle some issues, so I need your further assistance.
1. Overall Situation Description
1.1 In the same process, three models are sequentially called through the API interface to handle the content summarization task. The models include llama3.1:8b, glm4:9b, llama3.2:latest, and each model has the following parameters set:
"num_ctx": 121000,
"num_predict": 9000

1.2. If the environment variable Environment="OLLAMA_SCHED_SPREAD=1" is not set, all three models will run successfully in sequence, but the inference time is relatively long.
Log file ollama2.log
ollama2.log
1.3. After setting Environment="OLLAMA_SCHED_SPREAD=1".
In order to improve the inference efficiency of the three models and to fully utilize four GPU cards for concurrent processing, I set the environment variable Environment="OLLAMA_SCHED_SPREAD=1" as you instructed. However, after multiple tests, the first model runs successfully every time, the second model fails almost every time, and the third model sometimes succeeds and sometimes fails.
Log file ollama1.log
ollama1.log
1.4. In the ollama1.log log, the first model succeeds, and the second and third both fail.
Model 2 API Error Log as followed
{"message":"Request failed with status code 500","data":{"error":"llama runner process has terminated: error:failed to create context with model '/usr/share/ollama/.ollama/models/blobs/sha256-b506a070d1152798d435ec4e7687336567ae653b3106f73b7b4ac7be1cbc4449'"}}

Model 3 API Error Log as followed
{"message":"Request failed with status code 500","data":{"error":"an unknown error was encountered while running the model CUDA error: out of memory\n current device: 3, in function alloc at /go/src/github.com/ollama/ollama/llm/llama.cpp/ggml/src/ggml-cuda.cu:376\n cuMemCreate(&handle, reservesize, &prop, 0)\n/go/src/github.com/ollama/ollama/llm/llama.cpp/ggml/src/ggml-cuda.cu:102: CUDA error"}}

1.5 Analysis of ollama1.log log
According to your previous instructions, I interpreted the log information in ollama1.log and conducted an analysis. There are some areas where I do not understand or may have misunderstood, and I hope for your assistance.
Note: The following analysis and most of the logs are from ollama1.log. Only in sections 4.5.1 and 5.5 did I compare the relevant information from ollama2.log
2. Four GPU cards, the available resources are 23.3 GiB, 23.3 GiB, 16.8 GiB, 9.7 GiB, as follows,
October 19 22:19:29 gpu ollama[60399]: time=2024-10-19T22:19:29.629+08:00 level=DEBUG source=memory.go:103 msg=evaluating library=cuda gpu_count=4 available="[23.3 GiB 23.3 GiB 16.8 GiB 9.7 GiB]"

3. First Model: llama3.1:8b
3.1 By default, OLLAMA_NUM_PARALLEL=4, the required resources are partial_offload="32.3 GiB" full_offload="32.3 GiB", but none of the GPU cards can meet this requirement. As follows,
October 19 22:19:29 gpu ollama[60399]: time=2024-10-19T22:19:29.629+08:00 level=DEBUG source=memory.go:170 msg="gpu has too little memory to allocate any layers" id=GPU-ac079011-c45b-de29-f2e2-71b2e5d2d7f4 library=cuda variant=v12 compute=8.0 driver=12.2 name="NVIDIA A30" total="23.5 GiB" available="23.3 GiB" minimum_memory=479199232 layer_size="2.0 GiB" gpu_zer_overhead="0 B" partial_offload="32.3 GiB" full_offload="32.3 GiB"
October 19 22:19:29 gpu ollama[60399]: time=2024-10-19T22:19:29.629+08:00 level=DEBUG source=memory.go:170 msg="gpu has too little memory to allocate any layers" id=GPU-1a5993d8-1f60-3ecd-b80f-55ca9f1e95d2 library=cuda variant=v12 compute=8.0 driver=12.2 name="NVIDIA A30" total="23.5 GiB" available="23.3 GiB" minimum_memory=479199232 layer_size="2.0 GiB" gpu_zer_overhead="0 B" partial_offload="32.3 GiB" full_offload="32.3 GiB"
October 19 22:19:29 gpu ollama[60399]: time=2024-10-19T22:19:29.629+08:00 level=DEBUG source=memory.go:170 msg="gpu has too little memory to allocate any layers" id=GPU-6b83f2f6-dc65-7feb-5e02-0cd0087995e8 library=cuda variant=v12 compute=8.0 driver=12.2 name="NVIDIA A30" total="23.5 GiB" available="16.8 GiB" minimum_memory=479199232 layer_size="2.0 GiB" gpu_zer_overhead="0 B" partial_offload="32.3 GiB" full_offload="32.3 GiB"
October 19 22:19:29 gpu ollama[60399]: time=2024-10-19T22:19:29.629+08:00 level=DEBUG source=memory.go:170 msg="gpu has too little memory to allocate any layers" id=GPU-ad4cba93-ee35-2ea2-dba7-7b5772a098ce library=cuda variant=v12 compute=8.0 driver=12.2 name="NVIDIA A30" total="23.5 GiB" available="9.7 GiB" minimum_memory=479199232 layer_size="2.0 GiB" gpu_zer_overhead="0 B" partial_offload="32.3 GiB" full_offload="32.3 GiB"
October 19 22:19:29 gpu ollama[60399]: time=2024-10-19T22:19:29.630+08:00 level=DEBUG source=memory.go:312 msg="insufficient VRAM to load any model layers"

3.2 From the following log, it can be observed that OLLAMA automatically sets parallel=1, and the required resources are required="55.3 GiB" (I do not understand why the required resources are 55.3G at this time, which is greater than the 32.3G shown in 3.1? Additionally, does the parallel=1 in the following log indicate that the four concurrent processes have been reduced to one, and since it has been reduced to parallel=1, why does it require more resources), as follows
October 19 22:19:29 gpu ollama[60399]: time=2024-10-19T22:19:29.630+08:00 level=INFO source=sched.go:730 msg="new model will fit in available VRAM, loading" model=/usr/share/ollama/.ollama/models/blobs/sha256-8eeb52dfb3bb9aefdf9d1ef24b3bdbcfbe82238798c4b918278320b6fcef18fe library=cuda parallel=1 required="55.3 GiB"

3.3 The model runs on four GPU cards. As follows.
Question: If Environment="OLLAMA_SCHED_SPREAD=1" is not set, why does this model still run on four GPU cards (which does not meet my expectation), while the other two models only run on one GPU card (which meets the expectation), and for this part, you can refer to the log file ollama2.log
October 19 22:19:29 gpu ollama[60399]: time=2024-10-19T22:19:29.632+08:00 level=INFO source=memory.go:326 msg="offload to cuda" layers.requested=-1 layers.model=33 layers.offload=33 layers.split=10,11,11,1 memory.available="[23.3 GiB 23.3 GiB 16.8 GiB 9.7 GiB]" memory.gpu_overhead="0 B" memory.required.full="55.3 GiB" memory.required.partial="55.3 GiB" memory.required.kv="14.8 GiB" memory.required.allocations="[14.9 GiB 15.5 GiB 15.3 GiB 9.7 GiB]" memory.weights.total="18.4 GiB" memory.weights.repeating="18.0 GiB" memory.weights.nonrepeating="411.0 MiB" memory.graph.full="8.1 GiB" memory.graph.partial="8.1 GiB"

3.4 The first model works normally, as follows:
October 19 22:19:34 gpu ollama[60399]: DEBUG [launch_slot_with_data] slot is processing task | slot_id=0 task_id=2 tid="139958483587072" timestamp=1729347574
October 19 22:19:34 gpu ollama[60399]: DEBUG [update_slots] slot progression | ga_i=0 n_past=0 n_past_se=0 n_prompt_tokens_processed=58174 slot_id=0 task_id=2 tid="139958483587072" timestamp=1729347574
October 19 22:19:34 gpu ollama[60399]: DEBUG [update_slots] kv cache rm [p0, end) | p0=0 slot_id=0 task_id=2 tid="139958483587072" timestamp=1729347574
October 19 22:21:05 gpu ollama[60399]: DEBUG [print_timings] prompt eval time     =   44130.26 ms / 58174 tokens (    0.76 ms per token,  1318.23 tokens per second) | n_prompt_tokens_processed=58174 n_tokens_second=1318.2337027993692 slot_id=0 t_prompt_processing=44130.263 t_token=0.7585908309554096 task_id=2 tid="139958483587072" timestamp=1729347665
October 19 22:21:05 gpu ollama[60399]: DEBUG [print_timings] generation eval time =   47231.63 ms /   640 runs   (   73.80 ms per token,    13.55 tokens per second) | n_decoded=640 n_tokens_second=13.55024251017226 slot_id=0 t_token=73.7994171875 t_token_generation=47231.627 task_id=2 tid="139958483587072" timestamp=1729347665
October 19 22:21:05 gpu ollama[60399]: DEBUG [print_timings]           total time =   91361.89 ms | slot_id=0 t_prompt_processing=44130.263 t_token_generation=47231.627 t_total=91361.89 task_id=2 tid="139958483587072" timestamp=1729347665
October 19 22:21:05 gpu ollama[60399]: DEBUG [update_slots] slot released | n_cache_tokens=58814 n_ctx=121024 n_past=58813 n_system_tokens=0 slot_id=0 task_id=2 tid="139958483587072" timestamp=1729347665 truncated=false
October 19 22:21:05 gpu ollama[60399]: DEBUG [log_server_request] request | method="POST" params={} path="/completion" remote_addr="<IP_ADDRESS>" remote_port=55272 status=200 tid="139956475393792" timestamp=1729347665
October 19 22:21:05 gpu ollama[60399]: DEBUG [process_single_task] slot data | n_idle_slots=1 n_processing_slots=0 task_id=645 tid="139958483587072" timestamp=1729347665
October 19 22:21:06 gpu ollama[60399]: DEBUG [log_server_request] request | method="POST" params={} path="/tokenize" remote_addr="<IP_ADDRESS>" remote_port=55274 status=200 tid="139956467001088" timestamp=1729347666
October 19 22:21:06 gpu ollama[60399]: [GIN] 2024/10/19 - 22:21:06 | 200 |         1m38s |    <IP_ADDRESS> | POST     "/api/generate"

4. Second Model: glm4:9b
4.1 After the first model ends, perhaps because the GPU resources have not been completely released at this time (I am not sure if this is the reason), the available resources of each GPU cannot meet the model's needs of partial_offload="30.9 GiB" full_offload="30.9 GiB".
October 19 22:21:09 gpu ollama[60399]: time=2024-10-19T22:21:09.039+08:00 level=DEBUG source=server.go:1044 msg="stopping llama server"
October 19 22:21:09 gpu ollama[60399]: time=2024-10-19T22:21:09.039+08:00 level=DEBUG source=server.go:1050 msg="waiting for llama server to exit"
October 19 22:21:09 gpu ollama[60399]: time=2024-10-19T22:21:09.290+08:00 level=DEBUG source=gpu.go:358 msg="updating system memory data" before.total="125.4 GiB" before.free="108.2 GiB" before.free_swap="3.7 GiB" now.total="125.4 GiB" now.free="108.5 GiB" now.free_swap="3.7 GiB"
October 19 22:21:09 gpu ollama[60399]: CUDA driver version: 12.2
October 19 22:21:10 gpu ollama[60399]: time=2024-10-19T22:21:10.002+08:00 level=DEBUG source=server.go:1054 msg="llama server stopped"
October 19 22:21:10 gpu ollama[60399]: time=2024-10-19T22:21:10.003+08:00 level=DEBUG source=sched.go:380 msg="runner released" modelPath=/usr/share/ollama/.ollama/models/blobs/sha256-8eeb52dfb3bb9aefdf9d1ef24b3bdbcfbe82238798c4b918278320b6fcef18fe
October 19 22:21:10 gpu ollama[60399]: time=2024-10-19T22:21:10.220+08:00 level=DEBUG source=gpu.go:406 msg="updating cuda memory data" gpu=GPU-ad4cba93-ee35-2ea2-dba7-7b5772a098ce name="NVIDIA A30" overhead="0 B" before.total="23.5 GiB" before.free="8.8 GiB" now.total="23.5 GiB" now.free="9.7 GiB" now.used="13.8 GiB"
October 19 22:21:10 gpu ollama[60399]: time=2024-10-19T22:21:10.510+08:00 level=DEBUG source=gpu.go:406 msg="updating cuda memory data" gpu=GPU-6b83f2f6-dc65-7feb-5e02-0cd0087995e8 name="NVIDIA A30" overhead="0 B" before.total="23.5 GiB" before.free="16.1 MiB" now.total="23.5 GiB" now.free="16.8 GiB" now.used="6.7 GiB"
October 19 22:21:10 gpu ollama[60399]: time=2024-10-19T22:21:10.778+08:00 level=DEBUG source=gpu.go:406 msg="updating cuda memory data" gpu=GPU-ac079011-c45b-de29-f2e2-71b2e5d2d7f4 name="NVIDIA A30" overhead="0 B" before.total="23.5 GiB" before.free="7.1 GiB" now.total="23.5 GiB" now.free="23.3 GiB" now.used="232.9 MiB"
October 19 22:21:11 gpu ollama[60399]: time=2024-10-19T22:21:11.017+08:00 level=DEBUG source=gpu.go:406 msg="updating cuda memory data" gpu=GPU-1a5993d8-1f60-3ecd-b80f-55ca9f1e95d2 name="NVIDIA A30" overhead="0 B" before.total="23.5 GiB" before.free="6.5 GiB" now.total="23.5 GiB" now.free="23.3 GiB" now.used="232.9 MiB"

4.4 However, the available resources of each GPU card still cannot meet the needs of the second model.
 As follows,
Question: At this time, OLLAMA_NUM_PARALLEL=4, why doesn't it automatically set OLLAMA_NUM_PARALLEL=1 like the first model? And assess whether any one of the GPU cards can meet the resources required by OLLAMA_NUM_PARALLEL=1?
October 19 22:21:12 gpu ollama[60399]: time=2024-10-19T22:21:12.114+08:00 level=INFO source=memory.go:326 msg="offload to cuda" layers.requested=-1 layers.model=41 layers.offload=41 layers.split=12,12,12,5 memory.available="[23.3 GiB 23.3 GiB 16.8 GiB 9.7 GiB]" memory.gpu_overhead="0 B" memory.required.full="43.1 GiB" memory.required.partial="43.1 GiB" memory.required.kv="4.6 GiB" memory.required.allocations="[11.1 GiB 11.3 GiB 11.1 GiB 9.5 GiB]" memory.weights.total="8.9 GiB" memory.weights.repeating="8.4 GiB" memory.weights.nonrepeating="485.6 MiB" memory.graph.full="7.8 GiB" memory.graph.partial="7.8 GiB"

4.5.1 The following information is from ollama2.log, and it can be observed that when OLLAMA_SCHED_SPREAD=1 is not set, this model eventually runs on one of the GPU cards and ultimately succeeds.
I don't understand why these errors occurred, allocating 8574.52 MiB on device 3: cudaMalloc failed: out of memory. From the above logs, it seems that the available resources on device 3 should be sufficient.
10月 19 22:21:15 gpu ollama[60399]: llama_new_context_with_model: pipeline parallelism enabled (n_copies=4)
10月 19 22:21:15 gpu ollama[60399]: ggml_backend_cuda_buffer_type_alloc_buffer: allocating 8574.52 MiB on device 3: cudaMalloc failed: out of memory
10月 19 22:21:15 gpu ollama[60399]: ggml_gallocr_reserve_n: failed to allocate CUDA3 buffer of size<PHONE_NUMBER>
10月 19 22:21:15 gpu ollama[60399]: llama_new_context_with_model: failed to allocate compute buffers
10月 19 22:21:16 gpu ollama[60399]: llama_init_from_gpt_params: error: failed to create context with model '/usr/share/ollama/.ollama/models/blobs/sha256-b506a070d1152798d435ec4e7687336567ae653b3106f73b7b4ac7be1cbc4449'
10月 19 22:21:16 gpu ollama[60399]: ERROR [load_model] unable to load model | model="/usr/share/ollama/.ollama/models/blobs/sha256-b506a070d1152798d435ec4e7687336567ae653b3106f73b7b4ac7be1cbc4449" tid="140035751489536" timestamp=1729347676
10月 19 22:21:16 gpu ollama[60399]: terminate called without an active exception
10月 19 22:21:16 gpu ollama[60399]: time=2024-10-19T22:21:16.326+08:00 level=INFO source=server.go:621 msg="waiting for server to become available" status="llm server error"
10月 19 22:21:16 gpu ollama[60399]: time=2024-10-19T22:21:16.515+08:00 level=DEBUG source=server.go:428 msg="llama runner terminated" error="signal: aborted"
10月 19 22:21:16 gpu ollama[60399]: time=2024-10-19T22:21:16.576+08:00 level=ERROR source=sched.go:455 msg="error loading llama server" error="llama runner process has terminated: error:failed to create context with model '/usr/share/ollama/.ollama/models/blobs/sha256-b506a070d1152798d435ec4e7687336567ae653b3106f73b7b4ac7be1cbc4449'"
10月 19 22:21:16 gpu ollama[60399]: time=2024-10-19T22:21:16.577+08:00 level=DEBUG source=sched.go:458 msg="triggering expiration for failed load" model=/usr/share/ollama/.ollama/models/blobs/sha256-b506a070d1152798d435ec4e7687336567ae653b3106f73b7b4ac7be1cbc4449
10月 19 22:21:16 gpu ollama[60399]: time=2024-10-19T22:21:16.577+08:00 level=DEBUG source=sched.go:360 msg="runner expired event received" modelPath=/usr/share/ollama/.ollama/models/blobs/sha256-b506a070d1152798d435ec4e7687336567ae653b3106f73b7b4ac7be1cbc4449
10月 19 22:21:16 gpu ollama[60399]: time=2024-10-19T22:21:16.577+08:00 level=DEBUG source=sched.go:375 msg="got lock to unload" modelPath=/usr/share/ollama/.ollama/models/blobs/sha256-b506a070d1152798d435ec4e7687336567ae653b3106f73b7b4ac7be1cbc4449
10月 19 22:21:16 gpu ollama[60399]: time=2024-10-19T22:21:16.577+08:00 level=DEBUG source=gpu.go:358 msg="updating system memory data" before.total="125.4 GiB" before.free="109.8 GiB" before.free_swap="3.7 GiB" now.total="125.4 GiB" now.free="109.8 GiB" now.free_swap="3.7 GiB"
10月 19 22:21:16 gpu ollama[60399]: [GIN] 2024/10/19 - 22:21:16 | 500 | 10.016638054s |    <IP_ADDRESS> | POST     "/api/generate"

4.7 Upon checking the logs through the frontend application, the API interface returned the following error message (this should be due to the errors mentioned above):
{"message":"Request failed with status code 500","data":{"error":"llama runner process has terminated: error:failed to create context with model '/usr/share/ollama/.ollama/models/blobs/sha256-b506a070d1152798d435ec4e7687336567ae653b3106f73b7b4ac7be1cbc4449'"}

5. Third Model: llama3.2:latest
5.1 At this point, the resources of the four GPU cards have been completely released. By default, OLLAMA_NUM_PARALLEL=4, and the required resources are partial_offload="24.9 GiB" full_offload="24.9 GiB", but none of the individual GPU cards can meet the required resources.
Question 1: Why does parallel=1 require more resources, 43.7G, memory.required.full="43.7 GiB", while only 24.9G was needed in 5.1?
Question 2: Why do models 1 and 3 automatically downgrade from parallel=4 to parallel=1, but the second model does not automatically adjust to parallel=1?
10月 19 22:21:19 gpu ollama[60399]: time=2024-10-19T22:21:19.065+08:00 level=DEBUG source=memory.go:103 msg=evaluating library=cuda gpu_count=4 available="[23.3 GiB 23.3 GiB 16.8 GiB 9.7 GiB]"
10月 19 22:21:19 gpu ollama[60399]: time=2024-10-19T22:21:19.065+08:00 level=INFO source=sched.go:730 msg="new model will fit in available VRAM, loading" model=/usr/share/ollama/.ollama/models/blobs/sha256-dde5aa3fc5ffc17176b5e8bdc82f587b24b2678c6c66101bf7da77af9f7ccdff library=cuda parallel=1 required="43.7 GiB"
10月 19 22:21:19 gpu ollama[60399]: time=2024-10-19T22:21:19.065+08:00 level=INFO source=server.go:103 msg="system memory" total="125.4 GiB" free="109.7 GiB" free_swap="3.7 GiB"
10月 19 22:21:19 gpu ollama[60399]: time=2024-10-19T22:21:19.065+08:00 level=DEBUG source=memory.go:103 msg=evaluating library=cuda gpu_count=4 available="[23.3 GiB 23.3 GiB 16.8 GiB 9.7 GiB]"
10月 19 22:21:19 gpu ollama[60399]: time=2024-10-19T22:21:19.066+08:00 level=INFO source=memory.go:326 msg="offload to cuda" layers.requested=-1 layers.model=29 layers.offload=29 layers.split=8,9,8,4 memory.available="[23.3 GiB 23.3 GiB 16.8 GiB 9.7 GiB]" memory.gpu_overhead="0 B" memory.required.full="43.7 GiB" memory.required.partial="43.7 GiB" memory.required.kv="12.9 GiB" memory.required.allocations="[11.4 GiB 11.7 GiB 11.4 GiB 9.3 GiB]" memory.weights.total="14.5 GiB" memory.weights.repeating="14.2 GiB" memory.weights.nonrepeating="308.2 MiB" memory.graph.full="6.2 GiB" memory.graph.partial="6.2 GiB"

5.3 According to the above analysis, the available resources of the four GPU cards (23.3 GiB 23.3 GiB 16.8 GiB 9.7 GiB) can meet the model's resource requirement of 43.7G, why does the third model suddenly report an OOM error.
10月 19 22:21:46 gpu ollama[60399]: CUDA error: out of memory

and
10月 19 22:21:47 gpu ollama[60399]: No symbol table is loaded.  Use the "file" command.
10月 19 22:21:47 gpu ollama[60399]: [Inferior 1 (process 60845) detached]
10月 19 22:21:47 gpu ollama[60399]: time=2024-10-19T22:21:47.580+08:00 level=DEBUG source=server.go:1044 msg="stopping llama server"
10月 19 22:21:47 gpu ollama[60399]: time=2024-10-19T22:21:47.581+08:00 level=DEBUG source=server.go:1050 msg="waiting for llama server to exit"
10月 19 22:21:47 gpu ollama[60399]: time=2024-10-19T22:21:47.908+08:00 level=DEBUG source=server.go:428 msg="llama runner terminated" error="signal: aborted"
10月 19 22:21:47 gpu ollama[60399]: time=2024-10-19T22:21:47.908+08:00 level=DEBUG source=server.go:1054 msg="llama server stopped"
10月 19 22:21:47 gpu ollama[60399]: [GIN] 2024/10/19 - 22:21:47 | 500 | 30.138749435s |    <IP_ADDRESS> | POST     "/api/generate"

5.4 Upon checking the logs through the frontend application, the API interface returned the following error message:
{"message":"Request failed with status code 500","data":{"error":"an unknown error was encountered while running the model CUDA error: out of memory\n current device: 3, in function alloc at /go/src/github.com/ollama/ollama/llm/llama.cpp/ggml/src/ggml-cuda.cu:376\n cuMemCreate(&handle, reservesize, &prop, 0)\n/go/src/github.com/ollama/ollama/llm/llama.cpp/ggml/src/ggml-cuda.cu:102: CUDA error"}

5.5 The following log is from ollama2.log, and it can be observed that the model eventually runs on a single GPU card and ultimately succeeds. (Different from 5.2 and 5.3 above)
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.192+08:00 level=DEBUG source=memory.go:103 msg=evaluating library=cuda gpu_count=1 available="[23.3 GiB]"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.193+08:00 level=DEBUG source=memory.go:170 msg="gpu has too little memory to allocate any layers" id=GPU-1a5993d8-1f60-3ecd-b80f-55ca9f1e95d2 library=cuda variant=v12 compute=8.0 driver=12.2 name="NVIDIA A30" total="23.5 GiB" available="23.3 GiB" minimum_memory=479199232 layer_size="1.9 GiB" gpu_zer_overhead="0 B" partial_offload="24.9 GiB" full_offload="23.1 GiB"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.193+08:00 level=DEBUG source=memory.go:312 msg="insufficient VRAM to load any model layers"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.193+08:00 level=DEBUG source=memory.go:103 msg=evaluating library=cuda gpu_count=1 available="[16.8 GiB]"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.197+08:00 level=DEBUG source=memory.go:170 msg="gpu has too little memory to allocate any layers" id=GPU-6b83f2f6-dc65-7feb-5e02-0cd0087995e8 library=cuda variant=v12 compute=8.0 driver=12.2 name="NVIDIA A30" total="23.5 GiB" available="16.8 GiB" minimum_memory=479199232 layer_size="1.9 GiB" gpu_zer_overhead="0 B" partial_offload="24.9 GiB" full_offload="23.1 GiB"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.198+08:00 level=DEBUG source=memory.go:312 msg="insufficient VRAM to load any model layers"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.198+08:00 level=DEBUG source=memory.go:103 msg=evaluating library=cuda gpu_count=1 available="[9.7 GiB]"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.199+08:00 level=DEBUG source=memory.go:170 msg="gpu has too little memory to allocate any layers" id=GPU-ad4cba93-ee35-2ea2-dba7-7b5772a098ce library=cuda variant=v12 compute=8.0 driver=12.2 name="NVIDIA A30" total="23.5 GiB" available="9.7 GiB" minimum_memory=479199232 layer_size="1.9 GiB" gpu_zer_overhead="0 B" partial_offload="24.9 GiB" full_offload="23.1 GiB"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.199+08:00 level=DEBUG source=memory.go:312 msg="insufficient VRAM to load any model layers"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.199+08:00 level=DEBUG source=memory.go:103 msg=evaluating library=cuda gpu_count=1 available="[4.3 GiB]"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.200+08:00 level=DEBUG source=memory.go:170 msg="gpu has too little memory to allocate any layers" id=GPU-ac079011-c45b-de29-f2e2-71b2e5d2d7f4 library=cuda variant=v12 compute=8.0 driver=12.2 name="NVIDIA A30" total="23.5 GiB" available="4.3 GiB" minimum_memory=479199232 layer_size="1.9 GiB" gpu_zer_overhead="0 B" partial_offload="24.9 GiB" full_offload="23.1 GiB"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.200+08:00 level=DEBUG source=memory.go:312 msg="insufficient VRAM to load any model layers"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.200+08:00 level=DEBUG source=memory.go:103 msg=evaluating library=cuda gpu_count=1 available="[23.3 GiB]"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.202+08:00 level=INFO source=sched.go:714 msg="new model will fit in available VRAM in single GPU, loading" model=/usr/share/ollama/.ollama/models/blobs/sha256-dde5aa3fc5ffc17176b5e8bdc82f587b24b2678c6c66101bf7da77af9f7ccdff gpu=GPU-1a5993d8-1f60-3ecd-b80f-55ca9f1e95d2 parallel=1 available=24986779648 required="21.6 GiB"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.202+08:00 level=DEBUG source=sched.go:249 msg="new model fits with existing models, loading"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.202+08:00 level=INFO source=server.go:103 msg="system memory" total="125.4 GiB" free="109.1 GiB" free_swap="3.7 GiB"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.202+08:00 level=DEBUG source=memory.go:103 msg=evaluating library=cuda gpu_count=1 available="[23.3 GiB]"
10月 20 00:14:41 gpu ollama[1265]: time=2024-10-20T00:14:41.203+08:00 level=INFO source=memory.go:326 msg="offload to cuda" layers.requested=-1 layers.model=29 layers.offload=29 layers.split="" memory.available="[23.3 GiB]" memory.gpu_overhead="0 B" memory.required.full="21.6 GiB" memory.required.partial="21.6 GiB" memory.required.kv="12.9 GiB" memory.required.allocations="[21.6 GiB]" memory.weights.total="14.5 GiB" memory.weights.repeating="14.2 GiB" memory.weights.nonrepeating="308.2 MiB" memory.graph.full="5.8 GiB" memory.graph.partial="6.2 GiB"

6 I monitor the GPU operation by executing the command gpustat -i 1, as follows:
6.1 If the environment variable is set as Environment="OLLAMA_SCHED_SPREAD=1" (as shown in ollama1.log, model 1 runs successfully, while models 2 and 3 fail)
All three models run on GPUs 1, 2, and 3 (which is basically as expected), but I do not know why GPU 0 has not been used or is only occasionally occupied.
6.2 If the environment variable is not set as Environment="OLLAMA_SCHED_SPREAD=1" (as shown in ollama2.log, all three models run successfully)
First model: It runs on GPUs 1, 2, and 3. I do not know why GPU 1 has not been used or is only occasionally occupied, and I am unclear why this model can still run on multiple GPU cards without setting the environment variable Environment="OLLAMA_SCHED_SPREAD=1".
Second model: It runs only on GPU 2 (as expected).
Third model: It runs only on GPU 3 (as expected).

The reason we don't default to OLLAMA_SCHED_SPREAD=1 is because most users see slower performance due to CPU bottlenecks when a model could load in a single GPU.  Have you analyzed the performance to determine that OLLAMA_SCHED_SPREAD=1 does actually increase performance in your setup?
Our current scheduling algorithm does have some difficulty dealing with GPUs that have very different VRAM sizes.  I believe that coupled with under-estimating VRAM requirements for large context size is likely leading us to try to put too many layers on the smallest GPU when there's ample room on the larger GPU, which also explains why turning spread on causes this problem to get worse.

Due to the setting OLLAMA_SCHED_SPREAD=1 causing all GPU resources not to be released in a timely manner, resulting in other requests failing due to lack of GPU resources for a period of time, I have canceled this setting.
Furthermore, following the guidance of @rick-github, I have set the following environment variables: OLLAMA_NUM_PARALLEL=1, OLLAMA_FLASH_ATTENTION=1, and GGML_CUDA_ENABLE_UNIFIED_MEMORY=1.
---Original---
From: "Daniel @.>
Date: Wed, Oct 23, 2024 05:30 AM
To: @.>;
Cc<EMAIL_ADDRESS>Subject: Re: [ollama/ollama]  The issue regarding concurrent processing withmultiple GPU cards (Issue #7253)
The reason we don't default to OLLAMA_SCHED_SPREAD=1 is because most users see slower performance due to CPU bottlenecks when a model could load in a single GPU.  Have you analyzed the performance to determine that OLLAMA_SCHED_SPREAD=1 does actually increase performance in your setup?
Our current scheduling algorithm does have some difficulty dealing with GPUs that have very different VRAM sizes.  I believe that coupled with under-estimating VRAM requirements for large context size is likely leading us to try to put too many layers on the smallest GPU when there's ample room on the larger GPU, which also explains why turning spread on causes this problem to get worse.
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@SDAIer it sounds like you have a working setup now, is that correct?

what is your question？
---Original---
From: "Daniel @.>
Date: Thu, Oct 31, 2024 00:13 AM
To: @.>;
Cc<EMAIL_ADDRESS>Subject: Re: [ollama/ollama]  The issue regarding concurrent processing withmultiple GPU cards (Issue #7253)
@SDAIer it sounds like you have a working setup now, is that correct?
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ok，I will close this issue. Thanks guys @rick-github @dhiltgen


Add gitlab-ci usage

Description
I wanted to integrate safety into our gitlab ci suite, but didn't know how. It would be nice to add it to the readme, since it's quite popular.

Related: #145


fix: pycode environment produced an error

Fixes: #66. The issue was a in for loop inside tree_sitter_latex_external_scanner_scan(). I also added a test on environments.txt.

Thanks!


feat: adding pip to base image

Adding pip as requested by https://github.com/actions-runner-controller/actions-runner-controller/pull/536
Binaries are searched in PATH order, as a result including this shouldn't break anything as the actions/setup-python action bolts onto the front of the PATH. The Python env configured by the action should always be resolved over the built in python and pip installs due to this, see below for evidence.
I have also removed the python-is-python3 package as we are now symlinking pip manually. I thought it was more consistent if we were symlinking both the interpreter and pip rather than letting a package do it for interpreter and manually doing it for pip.

@toast-gear this PR seems to just not add things installed with pip to the path, is there a reason for that?
#536 did that with ENV PATH="${HOME}/.local/bin:${PATH}", which isn't a great solution but should reliably work afaik.
ENV PATH="${PATH}:${HOME}/.local/bin" should also work.

pip doesn't install packages in ~/.local/bin? Adding ${HOME}/.local/bin to the PATH wouldn't achieve this?

I don't know about this, I just know I tested it with a few random pip things and they all worked with the PATH change I did above, while they didn't without, so I assumed thats how everything worked?
I also looked some things up back then, and I think I found two paths for pip stuff, not four.
I did find this ~/.local/lib/python3.8/site-packages path as a relevant one, however after some looking into this I decided it probably wasn't needed, tho I can't remember why.

I think packages get installed in the User Site Directory location by default which is python version specific
You are also able to install into User Script Directory however I'm struggling to actually do this? Have you got an example?

An example would be meson, I am using this as an example because I use it in the project I basically use as a test for self hosted runners atm.
I don't really use self hosted runners much yet, because the things I wanted it for aren't ready yet, and some not even started.
Anyways when running pip install meson, that should install meson, however running meson after that tells me meson isn't on the path.
However with the path set it works on a self hosted runner.

Did you test on GitHub Actions? It's super interesting that the HOME var seems to be getting set to /github/home, we don't actively set it in the Dockerfile

I'm sorry, I seem to have missed the notification for this.

Did you test on GitHub Actions?

Yes, I did. Both that, and on a local kind cluster.
For the local kind cluster, I let acceptance set it up, and then ran the pip commands using kubectl.


perRead Invalid option '?'

Hello,
perRead doesn't seem to be working; I'm getting "Invalid option ?"
MethylDackel perRead Homo_sapiens_assembly19.fasta methylation.bam
Invalid option '?'
Usage: MethylDackel perRead [OPTIONS] <ref.fa>

Do you maybe have some hidden special character in the command? What version are you using?

It's not a hidden character (I typed everything out).
MethylDackel --version
0.5.2 (using HTSlib version 1.12-7-g088096f)
On Thu, Jun 3, 2021 at 2:49 AM Devon Ryan @.***> wrote:

Do you maybe have some hidden special character in the command? What
version are you using?
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Reply to this email directly, view it on GitHub
https://github.com/dpryan79/MethylDackel/issues/115#issuecomment-853617911,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AAK2EWZQXS5B3LPREUWCLKLTQ4QV3ANCNFSM456YYIJQ
.

--
Neva Cherniavsky Durand, Ph.D. | she, her, hers
Assistant Professor |  Molecular and Human Genetics
Aiden Lab | Baylor College of Medicine
www.aidenlab.org

I reinstalled and am no longer getting this error.


MAINTAINERS: Create dedicated entries for 3rd party toolchains

Fixes: #63738
Create dedicated entries for ARC MWDT, arm compiler 6, and one Api toolchains.
This helps contributors to identify whom to contact in case of issues related to those toolchains.
The Zephyr SDK, cross-compile, and other GCC based compilers are covered as part of the general cmake/toolchain,compiler,linker,bintools entry in the MAINTAINERS file.

Would not close #63738 with this alone

Agree, but it's still a fix targeting #63738.
So we just have to remember to re-open #63738 when this PR is merged.


pws: Init at 1.0.6

Things done

[x] Tested using sandboxing (nix-build --option build-use-chroot true or nix.useChroot on NixOS)
Built on platform(s)

[x] NixOS
[ ] OS X
[ ] Linux

[ ] Tested compilation of all pkgs that depend on this change using nix-shell -p nox --run "nox-review wip"
[x] Tested execution of all binary files (usually in ./result/bin/)
[x] Fits CONTRIBUTING.md.

pws is a CLI utility for storing passwords securely. It needs either xsel or xclip to work.

I'm not sure what you've meant with the first task on the TODO list (my first contribution here) - I've executed nix-build --option build-use-chroot true -A pws -I nixpkgs=/vagrant on my nixbox and it generated package successfuly, result/bin/pws works fine.
I have NixOS on vagrant using https://github.com/zimbatm/nixbox
I've also tested whole flow manually on this nixbox (so, I've added pws package through /etc/nixos/configuration.nix, and then I've tested whether it work in Xfce).
Not yet sure what's going on with this nix-shell check from the checklist, if it's needed, I'll try to dive in this soon.

@swistak35 the nox step is most likely redundant here; adding a new package shouldn't affect other packages.
The purpose of building in a sandbox is to identify implicit assumptions about the build environment. If you're using nix-daemon (e.g., on NixOS), passing build-use-sandbox via nix-build is ignored, afaik.


Add ignore property to meshmodels

Description
This PR adds a new property "ignore" in MeshModels construct which will be false by default and can be set to true to signify that a particular model should be ignored and this property can be set by the user.
This PR fixes #
Notes for Reviewers
Signed commits

[ ] Yes, I signed my commits.

merge conflict

Must be schema-driven. A PR and release of meshery/schemas must be done first.

@MUzairS15 will you ensure that this happens?

Must be schema-driven. A PR and release of meshery/schemas must be done first.

@leecalcote https://github.com/meshery/schemas/pull/50

Please don’t use the meshmodels term any longer.


Merge v1.0.0-alpha.12 into staging

Prerequisites
If this PR changes PHP code or dependencies:

[ ] I've run composer format and fixed any code formatting issues.
[ ] I've run composer analyze and addressed any static analysis issues.
[ ] I've run php artisan test and ensured that all tests pass.
[ ] I've run composer localize to update localization source files and committed any changes.

If this PR changes CSS or JavaScript code or dependencies:

[ ] I've run npm run lint and fixed any linting issues.
[ ] I've run npm run build and ensured that CSS and JavaScript assets can be compiled.

We don't have merge commits enabled in this Repo so closing and will push up directly.


update elasticsearch to 7.13.2

closes CRJI/EIC#749

will keep for reference in future upgrade; we will probably shift to opensearch


Update en.json

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Does this PR depend on any recent backend work? If so, please include the PR number from the iit-backend repo and associated Airtable ticket link.
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QA checklist: complete all parts relevant to your ticket changes
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Check in French

Cycle through all pages in French for any glaring omissions

Thanks @floraguolr. FYI next time just edit all the jsons for all 3 languages in 1 PR instead of separating by file. Also I think the French translation was fine as it was, it doesn't really make sense how it is now. Let's leave it as "Base de données à jour jusqu'à". Check with @grbdeveaux but should be fine

Yes the French phrasing is good. The most correct phrasing would be this:
"Base de données à jour jusqu'au"
"au" instead of "à"

Don't forget to update German (just use google translate for now). After that, it's good to merge!


Create issue template for not working games and game suggestions

I saw on some other GitHub projects there are some templates for issues and you just need to fill in the information as there are basically some prompts. I hope you understand what I'm trying to say (my brain is on low battery right now), I'll even attach a link to the documentation from GitHub related to the issue templates.
https://docs.github.com/en/communities/using-templates-to-encourage-useful-issues-and-pull-requests/configuring-issue-templates-for-your-repository

done


stop gameloop when game over

Refactor-4: the snake still moves when the game is over. Maybe I did something wrong in another function, otherwise this PR makes gameloop stop when the game is over.

Indeed, the snake never stops unless CTRL+C is pressed. This is because in the "once-upon-a-time-implementation" (This repo was originaly writen as a graphical user interface with SDL)  the event handling was different. The current version does not try to check gameover field. I will change it in other branches too. Thanks for the feedback

Ok, thanks for the explanation.
Indeed, we have to press CTRL+C to terminate the execution but, in my implementation, I stop the snake when the game is over (so the executable is still running but I can see more easily that the game is finished and the final state of the game).
I think it's a matter of personal preference, so feel free to ignore/close the PR.

Well, clearly stoping the execution is the right thing to do... hahaha It can be a good exercise to include in the refactor-1.md. I'll think about it. Let's keep this PR open meanwhile

@juliendehos . Thanks for contributing. I've merge this and modified the snake-fury-exercise (and all solution branches) branch so now the game loop stops when is game over. Also, modified refactor-5.md which has the very same problem.


Kaminari integration with empty result sets ends up dividing by zero

I am trying to use Tire with Mongoid and recently committed Kaminari support. Looks like if you have a chain like this
MyModel.page(1).per(10).tire.search(params[:q])

then Kaminari support ends up dividing by zero. The problematic line is this one
(@options[:size].to_i + @options[:from].to_i) / @options[:size].to_i

I am not sure I understand the intent here. If page is not known and result set is empty, the best we can do is to default to 1. Then it is 0 / 1 and things work as expected.
Is my understanding correct? I would be happy to submit a PR if someone can explain me what the :size option is.

@mlitwiniuk: Yeah, that's the way to go, the code is insanely using all the instance var instead of the accessor method. Will change that all.

@michaelklishin: Please check the current master, the issue should be fixed.


Sometimes my image in cirleImageView is zoomed

ex.: https://i.imgur.com/KP7vZRi.jpg
I am using picasso with .noFade() to download images directly into cirleImageView.
It's strange. Any suggestions?

That is indeed strange. I guess it also is outdated by now. Please re-open if it still is an issue.


Move to hickory-dns

[x] This needs to be moved to https://github.com/hickory-dns
[ ] The current trust dns docker image needs to be deleted too
[ ] And the upload account attacked to the new org

@williamdes, let me invite you to Hickory DNS, then do you want to move the repo, or me?

@williamdes, let me invite you to Hickory DNS, then do you want to move the repo, or me?

Thank you for inviting me!
Done, I moved it
Only  https://github.com/trust-dns/trust-dns-docs left
Can you do the Docker image deleting or moving part?

see #3, I think I have all the integration keys setup properly for the new repo. I can delete the old repo.

see #3, I think I have all the integration keys setup properly for the new repo. I can delete the old repo.

Nice, the docker hub repo yes go ahead

before I delete that, do you think there are any concerns about it breaking users of the existing docker image? there's not a security issue here, so is there another way to specify the next version is a different name?

before I delete that, do you think there are any concerns about it breaking users of the existing docker image? there's not a security issue here, so is there another way to specify the next version is a different name?

No, there is no good way..
This leads to situations like this one: https://github.com/phpmyadmin/docker/issues/363
Or this one: https://hub.docker.com/r/bitwardenrs/server
I bet there is not that much Docker users now since we never advertised it as existant 🤞🏻


Background images

Hi and thank you for that nice script. Is it possible to lazyload backgroundimages?
thank you

See issues #6 and #21

Now supported natively in version 2.0.0


typo: Double word "the"

@nschonni : Thanks for your contribution! The author, @vhorne, has been notified to review your proposed change.

#sign-off


Update sha256 for minikube 0.20.0

After making all changes to the cask:

[x] brew cask audit --download {{cask_file}} is error-free.
[x] brew cask style --fix {{cask_file}} reports no offenses.
[x] The commit message includes the cask’s name and version.

Additionally, if updating a cask:

[x] If the sha256 changed but the version didn’t,
provide public confirmation by the developer: https://github.com/kubernetes/minikube/pull/1631

Hi folks, why CI build failed?

They seem to have failed because this is only a change to the SHA256, I assume as a fail-safe to require the "public confirmation by the developer" step

LGTM

When will this be merged?

They seem to have failed because this is only a change to the SHA256, I assume as a fail-safe to require the "public confirmation by the developer" step

Bingo.

When will this be merged?

When the team gets around to it. Please refrain from such comments; the PR is 3 hours old. We’re also human and deserve to rest.

@vitorgalvao sorry i didnt mean that. I am new to homebrew and cask community. Just wanted to know the estimated ETA from other members.


Chrome autofill broken

Hi,
We're using this plugin in our VueJs app and noticed something was off.
Whenever you enter a number manually everything works as expected.
But when you use the autofill in chrome the hidden fields stay empty.
This means our users will see the fields being filled in but nothing is saved.
To combat this we wanted to use  autocomplete='off' but this is not passed onto the hidden input fields.
Any ideas of what we might be able to do?
And thank you for all the work put into this plugin, much appreciated!

I have the same issue

@YamenSharaf We went with a autocomplete="off" on a form element surrounding the input fields. That did the job for not allowing autocomplete.
But we're considering removing vue-tel-input in the future as a lot of our customers complain about not having autocomplete.

@Agilix I thought this is something that should be trivial, so I made a PR here to address this issue. Hope it gets merged soon
https://github.com/EducationLink/vue-tel-input/pull/63

Thanks guys, I merged PR from @YamenSharaf, please update to v2.0.14.


Incorporate Bathymetry as a Context Set for DeepSensor

Sure! Below is a GitHub issue outlining the task for incorporating bathymetry as a context set in the DeepSensor model. This includes getting the bathymetry data, formatting it for DeepSensor, and training the model with the new context set. The main supervisor will provide assistance with obtaining the bathymetry data.

Task Description:
Integrate bathymetry data as a new context set for the DeepSensor model. This task involves obtaining bathymetry data, formatting it appropriately for DeepSensor, and training the model with this new context set to enhance the spatial network design for environmental monitoring.
Checklist:

Obtain Bathymetry Data:

[x] @DaniJonesOcean: obtain relevant bathymetry data for the Great Lakes.
[x] Ensure the data covers the necessary spatial and temporal resolutions required for the DeepSensor model.

Format Bathymetry Data for DeepSensor:

[x] Preprocess the bathymetry data to align with the required input format for DeepSensor.
[ ] Create a context set that includes bathymetry data, ensuring consistency with existing context sets used in the model.

Train DeepSensor with the New Context Set:

[ ] Configure the DeepSensor environment to include the new bathymetry context set.
[ ] Train the DeepSensor model using the updated context set that includes bathymetry.
[ ] Monitor the training process and document any improvements or challenges observed.
[ ] Evaluate the model's performance with the new context set and compare it to the baseline model without bathymetry.

Documentation and Reporting:

[ ] Create a Jupyter notebook to document the entire process of incorporating bathymetry data, including code, preprocessing steps, and results.
[ ] Save the trained model and relevant output files.
[ ] Upload the Jupyter notebook, formatted bathymetry data, and trained model to the shared GitHub repository under an appropriate directory.

@eredding02 I've created a new bathymetry file that will hopefully work with DeepSensor:
https://github.com/CIGLR-ai-lab/GreatLakes-TempSensors/blob/main/notebooks/debugging/interpolated_bathymetry.nc
I'll also share it with you via Google Drive and Colab. When you get a chance, give it a try and let me know how it goes!

@eredding02 I pretty much consider this done, aside from the bit of extra plotting that you mentioned.
The "documentation and reporting" steps are captured in our Milestone 5 tasks, so they are kind of duplicated here.
Once you have some comparison plots (spatial, time series) so we can see some differences between training with bathymetry and training without bathymetry, we can close this issue.


November 2024 Enhancements

Added function to send email for endpoints that will expire soon to creator of entries
Added VLAN and dACL options to Authorization Templates
Added VLAN and dACL to DB procedure for ISE to fetch values to use as dynamic attributes in Authorization Profiles
Corrected update behavior that didn't take into account per user psk setting in Authorization Templates
Schema v5

Fixes #52 #56 #57


[SPARK-39770][SQL][AVRO] Support Avro schema evolution

What changes were proposed in this pull request?
Support avro schema evolution by merging the schemas of all avro files and turning this into the reader's schema.
Why are the changes needed?
Avro does not yet support schema evolution
Does this PR introduce any user-facing change?
It adds a parameter schemaEvolution to AvroOptions which defaults to false keeping the current behavior as the default
How was this patch tested?
Added test to AvroSuite for schema merging
Added SchemaMergeSpec to test the schema merging machinery

+CC @xkrogen, @shardulm94


Add concurrency setting to example Docker Conda Store config file

I think this got overlooked in #250

Thanks Chris. A little more context. I added this specifically because running docker compose up from examples/docker was erroring out. The error message suggested that something was expecting concurrency to be defined... just so you know in case that's unexpected behavior


some small changes

link to live stream blog on conf page
add IRC link to contact page and doc contrib gif to contrib page
update cloudu logo

all working on staging.


Move to CancellationToken, Use spawn instead of exec, Add output channel for logging

Part 1 of split up of PR #145

I don't have tslint setup (as it's deprecated, see discussion to move to eslint), otherwise a lot of these minor changes could be automatically fixed while typing.


How to convert pytorch_model.bin weights into faceid.bin style?

The following code is used to convert the old version of IP-adapter,
`import torch
ckpt = "checkpoint-50000/pytorch_model.bin"
sd = torch.load(ckpt, map_location="cpu")
image_proj_sd = {}
ip_sd = {}
for k in sd:
if k.startswith("unet"):
pass
elif k.startswith("image_proj_model"):
image_proj_sd[k.replace("image_proj_model.", "")] = sd[k]
elif k.startswith("adapter_modules"):
ip_sd[k.replace("adapter_modules.", "")] = sd[k]
torch.save({"image_proj": image_proj_sd, "ip_adapter": ip_sd}, "ip_adapter.bin")`
However, the faceid includes the lora weights, so how to revise above codes to convert pytorch_model.bin weights into faceid.bin style?

Hi, may I ask how to solve this problem

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fix: remove HTML lookbehind regex, skip tests

Checklist:

[x] I have read freeCodeCamp's contribution guidelines.
[x] My pull request has a descriptive title (not a vague title like Update index.md)

Removes (commented out with a note) the lookbehind regex for Safari compatibility.
Added .skip to the HTML tests.
Prettier formatting (trailing commas, single quotes).

I thought it might be best to comment out the code. I can remove it if needed.
Related issue: https://github.com/freeCodeCamp/freeCodeCamp/issues/42101

@ojeytonwilliams Sorry for the late reply. That all sounds good to me.

By the way, were the format changes just prettier defaults? If so, I can set that up for the repo.

Should be. Does setting it up for the repo just mean adding a prettier config?

@ojeytonwilliams Sorry for the late reply. That all sounds good to me.

Cool, I'll remind myself how to publish to npm and get that done.

Should be. Does setting it up for the repo just mean adding a prettier config?

More or less, yeah.  The eslint config needs updating so they don't fight each other, but that's about it.  I'll quickly set that up and you can see what I mean.

@lasjorg there we go. I'm 99% sure I didn't break anything with the merge, but could you just give this a quick look?

@ojeytonwilliams what happened to the formatting? All the single quotes are now double quotes.
I rarely set up ESLint/Prettier in projects. I usually just use whatever the boilerplate or framework gives me and then the VS Code extensions. So I tend to forget everything about it. Do we not need a config? Like eslint-plugin-prettier and a config file? I thought eslint-config-prettier just turned rules off.

I applied the prettier formatting in https://github.com/freeCodeCamp/strip-comments/pull/6 and then merged that in here. So, this PR doesn't change formatting relative to that.

Do we not need a config? Like eslint-plugin-prettier and a config file? I thought eslint-config-prettier just turned rules off.

Yeah, that's exactly right. The config just leaves formatting to prettier.
There are a couple of ways of integrating eslint and prettier. You can use eslint-plugin-prettier, or just eslint-config-prettier. This way (without the plugin) means you can completely ignore formatting when you're coding. prettier kicks in when you ask your editor to format or when you try to commit.
I quite like it, compared to the plugin, because it means that eslint warnings are more likely a actual problem and not just something prettier will fix. Either way's fine with me, though.

Maybe I'm just misunderstanding something here. But when I try to format (auto on saving, or Alt + Shift + F) nothing happens with the quotes. Other formating does work (like if I make a mess and save it, it fixes it). But it doesn't seem to be changing the quotes back to single quotes.
If I run prettier against a file
npx prettier --write "./lib/Node.js"
All that happens is that it switches the line endings to LF from CRLF and again it does not change the quotes.

Anyway, it doesn't really matter for this PR so I guess I should just merge it. Everything else seems fine.

Thanks for confirming, I'll handle publishing now that this is in.
Re: prettier. I'm not sure where the discrepancy is coming from.  If you're curious there's info to be had from npm run format -- --loglevel=debug, but I don't think we need to worry until there's a conflict.

@ojeytonwilliams I figured it out. It is the .editorconfig file that does it.
Part of Prettier log in VS Code:
["INFO" - 19.23.25] Detected local configuration (i.e. .prettierrc or .editorconfig), VS Code configuration will not be used
At one point, I was going to ask if we should remove .editorconfig, now I think we probably should.

BTW, if we publish to npm should the README be updated? Not sure how you are supposed to handle forks that make changes to the original. I know you bumped the version but do we need to do anything else?


Update ReadMe - avoid repetition with website and update reseach focus

The readme for this repository hasn't been updated in some time. The goal of this issue is to delete old content that is already presented in other public mediums (e.g. our shiny new website!) and to update the research focus to align with the team's new objectives.
First, we will discuss what content should be in the readme, and then we will update it accordingly.
cc @vkalghatgi @dmc314

Discussion #14 - if you have any ideas about what changes we should do to the content of the readme


Clarify what is the default of :eof-value in read-json-supplier

Tiny PR to mention that the default eof-value is :eof (was missing in the docs).
Let me know if the wording should be something different !

This looks great to me - thanks.


Create a contextual filter/search widget for landing page content

💡 Description

@edwardbarraza I think this is done, no?

@edwardbarraza checking back here. I think this is done?

@anilnatha ☝

yes this is done


Confusing instructions for creation of MessageBody C

In Step 4 of Update the Module with Custom Code , the user is instructed to "Add the MessageBody class" and is then instructed to paste in code for a class named FileEvent.  This is a bit confusing, perhaps it could be worded a bit differently?

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: ded0d4cd-5b54-69ab-75fd-027b7c9ce424
Version Independent ID: 1f5aa92e-050a-74b9-7c77-a527e32ab7c4
Content: C# IoT Edge module for Azure Data Box Edge
Content Source: articles/databox-online/data-box-edge-create-iot-edge-module.md
Service: databox
Sub-service: edge
GitHub Login: @alkohli
Microsoft Alias: alkohli

@toolboc I marked this feedback as duplicate, and re-assigned the previous for doc-enhancement. Thanks again for you valuable feedback.
We will now proceed to close this thread. If there are further questions regarding this matter, please reopen it and we will gladly continue the discussion.