text:
VOD did not download at end of stream

Describe the bug
VOD did not download.
To Reproduce
Steps to reproduce the behavior:

Set channel to download VOD at end of stream (Note: I did add this channel while this stream was already live. Then I restarted the container.)
VOD does not download.

Expected behavior
VOD should download.
Screenshots

Logs
2024-03-16 00:47:41 | automator.end | info | Stream end
-- | -- | -- | --
2024-03-16 00:47:41 | automator.end | info | Stream offline for arilyna
2024-03-16 00:47:41 | clientBroker.notify | info | (streamOffline) arilyna has gone offline!:
2024-03-16 00:47:41 | clientBroker.notify | warn | No body specified
2024-03-16 00:47:41 | automator.end | warn | Stream offline notification for arilyna but channel is not capturing.
2024-03-16 00:47:41 | route.channels.download | error | Failed to fetch video data: GQL requests are disabled. Check your config.
2024-03-16 00:47:41 | tw.vod.downloadVideo | info | Prepare to download VOD 2092207347
2024-03-16 00:47:41 | tw.vod.downloadVideo | info | Downloading VOD 2092207347...
2024-03-16 00:47:42 | helper.execAdvanced | success | Spawned process 88 for download_vod_2092207347
2024-03-16 00:47:42 | job.save | info | Save job download_vod_2092207347 with PID 88 to /usr/local/share/twitchautomator/data/cache/pids/download_vod_2092207347.json
2024-03-16 00:47:42 | helper.execAdvanced | info | Attached to all streams for process 88 for download_vod_2092207347
2024-03-16 00:47:43 | job.clear | info | Clear job download_vod_2092207347 with PID 88
2024-03-16 00:47:43 | job.clear | success | Job download_vod_2092207347 removed from jobs list
2024-03-16 00:47:43 | helper.execAdvanced | error | Process 88 for download_vod_2092207347 exited with code 1
2024-03-16 00:47:43 | automator.getStartDate | error | No start date for arilyna
2024-03-16 00:47:43 | automator.getStartDate | error | No start date for arilyna
2024-03-16 00:47:43 | automator.vodBasenameTemplate | error | Invalid start date:
2024-03-16 00:47:43 | automator.getStartDate | error | No start date for arilyna
2024-03-16 00:47:43 | automator.getVodID | error | No VOD ID for arilyna
2024-03-16 00:47:43 | automator.end | error | Error downloading VOD at end: {year}.{month}.{day}_Arilyna_𝕧𝕚𝕕𝕖𝕠𝕘𝕒𝕞𝕖 𝕞𝕦𝕤𝕚𝕔 🌙 !HelloFresh_[false] (Failed to download vod: Process 88 for download_vod_2092207347 exited with code 1)

Server:

OS or Docker: Docker for Mac 4.28.0

it seems like that video is deleted, are you sure it existed when the stream ended?

Thank you for your quick reply.
Interesting. No, I am not sure that it existed when the stream ended. I'm new to LiveStreamDVR, so I'll see how it goes with a livestream that's currently happening (with a different streamer) and let you know if the problem persists.
That does point out to me the advantage of capturing rather than downloading once the stream is over, though.

It did it again. This time I can see that the broadcast is indeed available. I just noticed the error about not having GQL enabled. The message advises to do it at my own risk, so I didn't enable it. But would that solve my problem?
2024-03-16 22:26:38 | clientBroker.notify | warn | No body specified
-- | -- | -- | --
2024-03-16 22:26:38 | automator.end | warn | Stream offline notification for sashagrey but channel is not capturing.
2024-03-16 22:26:38 | route.channels.download | error | Failed to fetch video data: GQL requests are disabled. Check your config.
2024-03-16 22:26:57 | tw.vod.downloadVideo | info | Prepare to download VOD 2092956221
2024-03-16 22:26:57 | tw.vod.downloadVideo | info | Downloading VOD 2092956221...
2024-03-16 22:26:57 | helper.execAdvanced | success | Spawned process 103 for download_vod_2092956221
2024-03-16 22:26:57 | job.save | info | Save job download_vod_2092956221 with PID 103 to /usr/local/share/twitchautomator/data/cache/pids/download_vod_2092956221.json
2024-03-16 22:26:57 | helper.execAdvanced | info | Attached to all streams for process 103 for download_vod_2092956221
2024-03-16 22:26:59 | job.clear | info | Clear job download_vod_2092956221 with PID 103
2024-03-16 22:26:59 | job.clear | success | Job download_vod_2092956221 removed from jobs list
2024-03-16 22:26:59 | helper.execAdvanced | error | Process 103 for download_vod_2092956221 exited with code 1
2024-03-16 22:26:59 | automator.getStartDate | error | No start date for sashagrey
2024-03-16 22:26:59 | automator.getStartDate | error | No start date for sashagrey
2024-03-16 22:26:59 | automator.vodBasenameTemplate | error | Invalid start date:
2024-03-16 22:26:59 | automator.getStartDate | error | No start date for sashagrey
2024-03-16 22:26:59 | automator.getVodID | error | No VOD ID for sashagrey
2024-03-16 22:26:59 | automator.end | error | Error downloading VOD at end: {year}.{month}.{day}_sashagrey_COSPLAY !POBOX UNBOXING !TTS !PATREON_[false] (Failed to download vod: Process 103 for download_vod_2092956221 exited with code 1)

@MrBrax
It did it again. This time I can see that the livestream is indeed available. I just noticed the error about not having GQL enabled. The message advises to do it at my own risk, so I didn't enable it. But would that solve my problem?
2024-03-16 22:26:38 | clientBroker.notify | warn | No body specified
-- | -- | -- | --
2024-03-16 22:26:38 | automator.end | warn | Stream offline notification for sashagrey but channel is not capturing.
2024-03-16 22:26:38 | route.channels.download | error | Failed to fetch video data: GQL requests are disabled. Check your config.
2024-03-16 22:26:57 | tw.vod.downloadVideo | info | Prepare to download VOD 2092956221
2024-03-16 22:26:57 | tw.vod.downloadVideo | info | Downloading VOD 2092956221...
2024-03-16 22:26:57 | helper.execAdvanced | success | Spawned process 103 for download_vod_2092956221
2024-03-16 22:26:57 | job.save | info | Save job download_vod_2092956221 with PID 103 to /usr/local/share/twitchautomator/data/cache/pids/download_vod_2092956221.json
2024-03-16 22:26:57 | helper.execAdvanced | info | Attached to all streams for process 103 for download_vod_2092956221
2024-03-16 22:26:59 | job.clear | info | Clear job download_vod_2092956221 with PID 103
2024-03-16 22:26:59 | job.clear | success | Job download_vod_2092956221 removed from jobs list
2024-03-16 22:26:59 | helper.execAdvanced | error | Process 103 for download_vod_2092956221 exited with code 1
2024-03-16 22:26:59 | automator.getStartDate | error | No start date for sashagrey
2024-03-16 22:26:59 | automator.getStartDate | error | No start date for sashagrey
2024-03-16 22:26:59 | automator.vodBasenameTemplate | error | Invalid start date:
2024-03-16 22:26:59 | automator.getStartDate | error | No start date for sashagrey
2024-03-16 22:26:59 | automator.getVodID | error | No VOD ID for sashagrey
2024-03-16 22:26:59 | automator.end | error | Error downloading VOD at end: {year}.{month}.{day}_sashagrey_COSPLAY !POBOX UNBOXING !TTS !PATREON_[false] (Failed to download vod: Process 103 for download_vod_2092956221 exited with code 1)

is it still broken? this could have been streamlink being out of date

I'll have to find some time to test it out. I kind of gave up so I haven't used it. Will report back.

repo: MrBrax/LiveStreamDVR


text:
/subs error with last code.

Another error when going to /subs (with the last commit available):

[error] 42#42: *323 FastCGI sent in stderr: "PHP message: PHP Fatal error:  Uncaught TypeError: Argument 1 passed to App\TwitchHelper::getChannelData() must be of the type string, bool given, called in /var/www/twitchautomator/src/Controller/SubController.php on line 68 and defined in /var/www/twitchautomator/src/TwitchHelper.php:388

IIRC, this happens when the oauth is not correct, somewhere in the code it returns a boolean.

i think i fixed this

i think i fixed this

source: gharchive/issue

authors: KurtzPT MrBrax

repo: MrBrax/TwitchAutomator

license: MIT

license_type: permissive

license_source: github-api


text:
请问现在还能用这个工具混淆jspatch过审吗？

谢谢。

不行.要用的话还得把JSPatch.js的文件混淆才行.
现在Apple对dlopen和dlsym的调用都查的很严.还是有些风险的，可以试试看jspatch平台上的最新版本看看.记得他们是吧JSPatch.js文件都混淆了的
发自我的 iPhone

在 2018年5月3日，23:08，Xi Lin notifications@github.com 写道：
谢谢。
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub, or mute the thread.

好的，谢谢！

@xilin
我以前有存jspatch 1.7.2版本的sdk，你要的话我可以给你。

太好了，我的邮箱是linxi60@gmail.com
非常感谢！

@MrChens 你好,我们现在正在做JSPatch的混淆,能给我也发一份1.7.2版本的sdk吗

@MrChens 你好,我们现在正在做JSPatch的混淆,能给我也发一份1.7.2版本的sdk吗

可以，我回去找一下看看。

@MrChens 你好,我们现在正在做JSPatch的混淆,能给我也发一份1.7.2版本的sdk吗

@yibyli 可以，我回去找一下看看。

@MrChens 你好,我们现在正在做JSPatch的混淆,能给我也发一份1.7.2版本的sdk吗

@yibyli 找到了，怎么给你？

@MrChens 请您发到这个邮箱: yibyli@foxmail.com,多谢!

您好，我也需要一份JSPatch 1.7.2的版本，可以发给我吗，谢谢
邮箱：873098673@qq.com

您好，我也需要一份JSPatch 1.7.2的版本，可以发给我吗，谢谢
邮箱：873098673@qq.com
已经删除了，你问一下其他人看看

您好，我也需要一份JSPatch 1.7.2的版本，可以发给我吗，谢谢
邮箱：873098673@qq.com

@LitDragon 不好意思，已经删除很久了，你问一下其他人看看

您好，我也需要一份JSPatch 1.7.2的版本，可以发给我吗，谢谢
邮箱：873098673@qq.com

@LitDragon 不好意思，已经删除很久了，你问一下其他人看看

没事，谢谢回复

authors: LitDragon MrChens xilin yibyli

repo: MrChens/codeObfuscated


text:
Alldebrid debrid search not working

Hello,
Basically debrid search is not working for alldebrid at all, it's erroring the catalog and it's also not picking up any of my "saved links" or "torrents" I have in my cloud.
I've tested with real debrid and that one has no issue.
Love the app, is it possible to get this fixed? Lemme know if you need help testing. Thanks!!

Same here, the addon isn't showing any results even though they're in my links history.  I'm not sure if this addon has just been abandoned or what.  It's too bad because this is necessary in conjunction with DMM to play through Stremio, otherwise you're limited to Torrentio's results which are often insufficient.

Is this issue still there for AllDebrid?

It works now!
Thank you!

authors: DevonCM oathzed


text:
cfgspawnabletypes.xml problem

i was able to open the xml once then it would not open any more. tried to reinstall both the xml and the editor but it did not help. I am able to use it for the other xml files just not the spawnabltypes one any idea on what i should do?

Sounds like an syntax error to me. I would suggest to open it with a proper XML editor. One which can tell you when it's not properly.

Is there one you would recommend I'm new to editing code for games.On Mar 28, 2021 2:18 PM, MrX13415 @.***> wrote:
Sounds like an syntax error to me. I would suggest to open it with a proper XML editor. One which can tell you when it's not properly.
—You are receiving this because you authored the thread.Reply to this email directly, view it on GitHub, or unsubscribe.

My recommodation for an universal TextEditor, especially if you are interested in learning more in this direction like actual coding or so: Visual Studio Code from Microsoft. (Avaliable on all Platforms and it's free.) To be able to check Sytnax errors you need to install an extension via the integrated extension manager. (You can basically add all kind of language or file support like this.)
I'm using this extension: https://marketplace.visualstudio.com/items?itemName=qub.qub-xml-vscode
Others my also work. To view potential problems make sure, the "Problems" pane at the bottom is visible. You can activate it via the menu "View" > "Problems".

For editing the types.xml you can also use this online tool: http://dayztypes.pro/
My software works too, but I haven't real found time to update it and make it better.

everytime I pressed load and tried loading in types it would just close the application


text:
Prefix for imported secrets

I'm pulling secrets from Vault from multiple secret paths.  Unfortunately, some of those secrets uniquely named.  Could we get a new option to insert a prefix/parentPath into the secrets imported at the path?
e.g. something like:
{
    "ConnectionString": "secret value",
    "Option1": "secret value 2",
}

with code like:
config.AddVaultConfiguration(
        () => new VaultOptions(
            "htpp://localhost:8200",
            new KerberosAuthMethodInfo(),
            reloadOnChange: true,
            reloadCheckIntervalSeconds: 60),
        "azure/signalr",
        "secret", prefix: "SignalR" );

would mean the ConnectionString value would be accessible under Configuration[SignalR:ConnectionString]

@almostjulian please check the BasePath in VaultConfigurationSource. It should do what you want:
 // act
 ConfigurationBuilder builder = new ConfigurationBuilder();
 builder.AddVaultConfiguration(
     () => new VaultOptions("http://localhost:8200", "root"),
     "SignalR", // <---- this is base path, basically the prefix
     "secret", // <---- this is the mount point
     this._logger);

So, do you want to import from Vault with a prefix, or read keys with a certain prefix, I think that's what I don't get at the moment :)

Ok, I see. That is something possible. I don't have much time but can do some stuff over the weekend. Feel free to submit your PR if you can.

Sure thing, I'll try to submit something later this week before the weekend.

Apologies for the delay, I've created #53 for this

Released in 1.0.2 https://github.com/MrZoidberg/VaultSharp.Extensions.Configuration/releases/tag/1.0.2

authors: MrZoidberg almostjulian


text:
Mudblazor Table Row Click

Bug type
Component
Component name
MudTable
What happened?

My requirement was edit the record only when edit button was clicked and not on rowclick. I tried that. Im facing issue with that Row Click.
Lets say I have 3 rows in Table. I'm randomly clicking the 3rd row and then I click on 2nd row Edit icon (for editing the row). When I place the cursor on textbox it automatically closing. Sometimes it is duplicating the value

Expected behavior
Expected is it should allow me to edit even though I clicked on random rows it should not have the reference of that row
Reproduction link
https://github.com/Pavithra1062/Blazor/blob/3ab24cc67e256128d82b41f5995f039f05f80900/Index.razor
Reproduction steps

Create MudTable with Readonly as True.
Enable Row edit during add or edit icon click
Make ReadOnly False based on Row edit
Keep track of item being edited
click on random row and click on edit icon of another row and try to edit
Place the cursor on Textbox

Relevant log output
No response
Version (bug)
5.1.5
Version (working)
No response
What browsers are you seeing the problem on?
Chrome, Microsoft Edge
On what operating system are you experiencing the issue?
Windows
Pull Request

[ ] I would like to do a Pull Request

Code of Conduct

[X] I agree to follow this project's Code of Conduct

Can you share a sample code showing the issue in https://try.mudblazor.com , please?

Please access url mentioned in Reproduction link

Im unable to run this code in trymudblazor.

Can you share a sample code showing the issue in https://try.mudblazor.com , please?

Can you share a sample code showing the issue in https://try.mudblazor.com , please?

please check url mentioned in reproduction link.

I've created a try.mudblazor based on you link to start an investigation:
https://try.mudblazor.com/snippet/cumllQvvqqcPPhDK
I'll take a look as soon as I can.

I'm seeing the same thing. I think what's happening here is the the RowClick event is executing some Javascript which immedately removes the focus from a row in the table. This has two side-effects:

If you put an edit box in a MudTd in the table, when you click on it to edit the text, the row click-handler immediately removes focus from that edit box.
If a user tries to select the text in a cell to copy to the clipboard, as soon as they release the mouse, the onclick event fires, removing focus from the table. It's incredibly frustrating.

If I open developer tools and disable/remove the onclick handler for the generated TR, the problem is solved. This also used to work when I first implemented my MudTable last year - it's only recently that it's broken.
I'm going to look into a workaround to stop the click handler firing, but in the meantime I thought this info might be helpful.

v6.1.6 fixes this, MudTable now has a SelectOnRowClick bool property.

v6.1.6 fixes this, MudTable now has a SelectOnRowClick bool property.

Do I understand correctly that this issue can be closed?

v6.1.6 fixes this, MudTable now has a SelectOnRowClick bool property.

Do I understand correctly that this issue can be closed?

Re-reading the lot again, I think I mentioned the SelectOnRowClick parameter as a hint to possibly solve this issue.
Only @Pavithra1062 can give us a conclusive answer.

I will close the issue. @Pavithra1062 let me know if the issue is still present for MudBlazor v6+ and there is no workaround for it, I will reopen.

authors: HClausing Pavithra1062 ScarletKuro Webreaper Yomodo

repo: MudBlazor/MudBlazor


text:
MudDatePicker inside a MudCard DateChanged event issue

Bug type
Component
Component name
MudDatePicker
What happened?
When putting a MudDatePicker in a MudCard the MudDatePicker does not update the text of field upon the DateChanged event. When you don't put that same form in a card it works as expected.
Expected behavior
MudDatePicker text of field upon DateChanged event even when in MudCard.
Reproduction link
https://try.mudblazor.com/snippet/wkGmOgusepWkoghk
Reproduction steps
Put MudDatePicker in MudCard and change the date. More info is in the try it link posted.
Relevant log output
No response
Version (bug)
6.0.11-dev.4
Version (working)
No response
What browsers are you seeing the problem on?
Chrome
On what operating system are you experiencing the issue?
Windows
Pull Request

[ ] I would like to do a Pull Request

Code of Conduct

[X] I agree to follow this project's Code of Conduct

Working in latest versions.

authors: danielchalmers zoborowi


text:
Changes in MudFocusTrap.razor destroy our content

Bug type
Component
Component name
MudFocusTrap
What happened?
Adding this container in the "MudFocusTrap.razor" destroys the entire content of our dialog, especially when we set the content to 100% height.

Expected behavior
This container, which we cannot control, compresses our content to a height of 72 pixels.
Reproduction link
https://try.mudblazor.com/snippet/wOcnkFYhqcUbXUtK
Reproduction steps

Run the project.
With the new container, the content is no longer 100% in height.
With the previous version, the content is 100% high.

Relevant log output
No response
Version (bug)
6.1.7
Version (working)
6.1.6
What browsers are you seeing the problem on?
Microsoft Edge
On what operating system are you experiencing the issue?
Linux
Pull Request

[ ] I would like to do a Pull Request

Code of Conduct

[X] I agree to follow this project's Code of Conduct

Fixed in upcoming v7.0.0-preview2.

authors: danielchalmers peerem


text:
MudMenu overlay issue in sticky element

Bug type
Component
Component name
MudMenu
What happened?
When a MudMenu is defined on a sticky cell (position: sticky) in a table row, opening the menu create an overlay that cover everything but the sticky cell after the menu.
Expected behavior
The overlay div covers everything but the menu,
Reproduction link
https://try.mudblazor.com/snippet/wEcHkyuVnVykRptC
Reproduction steps
Just click on a three-dot button, the overlay will appear (made red to make evident the behaviuor), and see the some cell are not below the overlay
Relevant log output
No response
Version (bug)
6.2.0
Version (working)
No response
What browsers are you seeing the problem on?
Firefox, Chrome
On what operating system are you experiencing the issue?
Windows
Pull Request

[ ] I would like to do a Pull Request

Code of Conduct

[X] I agree to follow this project's Code of Conduct

I think I found a solution in a StackOverflow.
So to apply this you first need to find out which parent of your overlay element has position: sticky and then just apply a high enough z-index to this element.
In your case, it's a bit harder, as the respective parent element is the th element, but you have to set the higher z-index to only the one th that is parent of the currently open menu, and not to all of them.

Hi @ar-schraml , I'd like to try your suggestion but as you wrote it's harder to do it programmatically.
Instead with last version of MudBlazor (6.17.0 as I write) I can use the new event IsOpenChanged to know if the menu is open or not and then apply a class to a container (eg. body) and with some simple css disable pointer events on elements under the overlay.
I wrote a new example here
https://try.mudblazor.com/snippet/mYwekRYhxxItTmWJ
the sticky elements are still over the overlay, but now you cannot click them, and only overlay and popover are clickable.
In my project I defined all the event callback and handler manually just to intercept the event and add or remove the class.
It would be nice if MudMenu would add/remove the class automatically (I dont know if it's an hard change).

authors: arschraml tantuffah


text:
NavMenu: Fix border stle for RTL layout

Fixed the border style alignment of the NavMenu
Description
Border style was set to right edge by using
border-right-style: solid; border-right-width: 2px;
It's now fixed by using inline styles of the border:
border-inline-end-style: solid; border-inline-end-width: 2px;
How Has This Been Tested?
visually
Types of changes

[x] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)

Before:

After:

[x] The PR is submitted to the correct branch (dev).
[x] My code follows the code style of this project.
[ ] I've added relevant tests.

Hi team,
I'm new to MudBlazor
I appreciate you for the great job
As I'm working mostly on RTL projects, I see some issues at this area around MudBlazor.
If I'm allowed, I can work on some of these issues as much as I can.

@vrassouli can you please check my PR why it's failing to build & Test, I've just changed a single line in CSS and it's not a breaking change. It would be very helpful for me if you can help. Thanks
https://github.com/MudBlazor/MudBlazor/pull/4451

I checked it, but founding nothing!
By adding your changes to my local repo, all test get passed without errors! can not understand what is wrong with the pipeline

@vrassouli okay thank you.

source: gharchive/pull-request

authors: vrassouli zubairkhakwani


text:
Fix Mistaken CSS Reordering

Description
Fixes: https://github.com/MudBlazor/MudBlazor/issues/8144
Fixes: https://github.com/MudBlazor/MudBlazor/pull/7948#issuecomment-1992474850
This returns the old reordering in MudBlazor.scss file which was broken with MudToggleGroup PR.
How Has This Been Tested?

Types of changes

[x] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)

Checklist:

[x] The PR is submitted to the correct branch (dev).
[x] My code follows the code style of this project.
[ ] I've added relevant tests.

Fixes the DatePicker visual crash.

Checking now

Double checked file order and downloaded PR to visually test DatePicker

Thank you @mckaragoz and @mikes-gh !

authors: henon mckaragoz mikes-gh


text:
Really fix form_name_feedback

This fixes a bug reported by Huafang and caused by my PR the other day:form_name_feedback is printing double feedback.
To reproduce:

Create an obs, propose the name Grifola frondosa, and click "Create". There will be double suggestions:

On any obs, propose the name Grifola frondosa, and click "Propose". There will be double suggestions. Pick one, and then commit the form. On show obs reload, it will flash "There are problems with the name..." although this is no longer true.

This PR also tries to fix what i was trying to fix originally, which is that form_name_feedback updates the flash too late for it to be picked up by a Turbo update. The naming error flash messages are now added upstream, either in NamingParams#name_missing? or ObservationsController::Validators#validate_name.
Everything seems to work as before, except:

The current "Missing name" flash message, which was only fired on Naming forms, is now replaced with the "There is a problem with the name", as on Observation forms. It seems to be superfluous because I think it only ever appears alongside "There is a problem".
Depending if there are valid_names offered, form_name_feedback sends the flash message "There is a problem..." either as a warning or an error. But because "Missing name" is a flash error and not a warning, it is always shown as an error. There is currently (on main) effectively no difference between the flash messages currently shown in a modal naming form - both "Missing name" and "There is a problem..." are shown as a flash_error, even though they may be registered differently. The same seems to be true on the Observation form, but i haven't tested every case.
Naming flash messages no longer appear inappropriately on the next page load.

coverage: 94.587% (-0.002%) from 94.589%
when pulling d049a06bb42995fde62164c2db3ed4480e540fd4 on nimmo-form-name-feedback-flash
into a493c9579a02c530ce02d65a10655da5f3e84e64 on main.

@JoeCohen I think i should go ahead and merge this, it's definitely an improvement. Please let me know if you discover anything wrong, though.

Oh nevermind, I can't deploy it anyway.
You can merge and deploy if it seems ok!

authors: coveralls nimmolo

repo: MushroomObserver/mushroom-observer


text:
有人退群 退群监控其他群之前的退群信息也都会显示

Issue示例

MacOS版本 : 10.15.5
微信版本 : 2.4.x
小助手版本 : 2.4.1
BUG描述 :有人退群 退群监控其他群之前的退群信息也都会显示
操作场景 : 有人退群 退群监控其他群之前的退群信息也都会显示
方便的话提供日志, 截图或者视频(可选)

已经移除

repo: MustangYM/WeChatExtension-ForMac


text:
1.0.1

优化了一部分配置
具体见readme对应版本

检查一遍  暂未发现问题


text:
Add encryption conform EIP1024

This is a draft PR
Encryption is needed to have MEWwalletKit conform to EIP1024. This is a first draft with bugs (the new unit test testEncode() crashes at two different places seemingly random (unknown object release and an out-of-bounds index).
Questions for the maintainers:

Is the current approach the right one?
What is the best way to debug the code calling NaCl?

Hey @ronaldmannak,

Is the current approach the right one?

Everything should be fine, since it's aligned with decryption, except that I don't think that we need to have public visibility of key sizes

crashes at two different places seemingly random

It's mostly because of wrong buffer sizes (encryption buffer should have 32 extra bytes, while encrypted data - 16). Let me double-check that and I'll comment what needs to be fixed
P.S. Also, FYI, we're moving repos to a new location https://github.com/mewwallet/, but it's ok to finish this PR here (since it's not "deprecated" yet) and I'll merge it into mewwallet one

In addition to https://github.com/MyEtherWallet/mew-wallet-ios-kit/pull/7 and key sizes
I think it better to have helper function, like generateNonce inside of twetnacl package, and do not think about that in mew-wallet-kit

Thanks @Foboz. I've updated the code. The unit test encrypts w/o error, but then throws an internal error code upon decryption. It looks like encryption is still not correct. Did I update everything correctly?

@Foboz Thanks for the second review, I appreciate it. The code now seems to work and is ready for review. I've added new unit tests as well. I will update the MEWwalletKit API next.

Hi @ronaldmannak, thanks for the update. Looks great! However, do you think that we really need to have keys size in public? If so, I would prefer to update that part before merge

@Foboz My bad, I forgot to change those back. Done.

Hey @ronaldmannak, sorry for being silent. I'm making last checks and will merge

authors: Foboz ronaldmannak

repo: MyEtherWallet/mew-wallet-ios-tweetnacl


text:
Make improvements to db dump tool

Print effects given the txn digest
Print deserialized Move object layout when printing an object
Print all versions  (with move layout) of an object given an id

@sadhansood is this still something you'd like to pursue? If not, let's close the issue. Thanks!

authors: sadhansood stefan-mysten

repo: MystenLabs/sui


text:
[move-ide] Added support for init function auto-completion

Description
This PR adds preliminary support for auto-completing init function definition. It contains the beginning of the proposed fine-grain error recovery in the parser, currently only implemented for function definitions. The gist of the idea is that we parse function definition as much as we can, and regardless of whether the parsing was fully successful or not, we still return a correct function Function AST node if we can (i.e., if we correctly parse attributes, fun keyword, and function name).
In particular, this would generate a correct Function AST node, for function ini even though its definition is incomplete:
module 0x0::some_module {
    fun ini
}

What this allows us to do, is context-sensitive auto-completion for init functions using LSP concept of snippets. In particular, when triggering auto-completion in the code fragment above right after ini, the IDE will recognize that we are trying to auto-complete a function whose name starts with ini and will offer a code snippet expanding this to a full init function definition (we will be able to omit sui::tx_context prefix once auto-imports are in place):
module 0x0::some_module {
    fun init(ctx: &mut sui::tx_context::TxContext) {
    }
}

Furthermore, if the module contains a struct definition being a one-time-witness candidate, the IDE will be smart enough to recognize this and offer an expanded snippet:
module 0x0::some_module {
    struct SOME_MODULE has drop {}
    fun init(witness: SOME_MODULE, ctx: &mut sui::tx_context::TxContext) {
    }
}

Finally, this snippet will not be offered for all identifiers with a given prefix, only those that represent function definitions. In particular, it will not do it for local variable declaration in the following code fragment:
module 0x0::some_module {
    fun foo() {
        let ini
    }
}

The main current limitation is that at this point auto-completion must be preceded by a save (to rebuild symbols information in the LSP server) and manual re-triggering of the auto-completion command. In order to support a smooth user experience, we need to add support for the compiler to use a virtual file system (files stored in memory).
Test Plan
Added a compiler test and a symbolicator test for this feature.

If your changes are not user-facing and do not break anything, you can skip the following section. Otherwise, please briefly describe what has changed under the Release Notes section.
Type of Change (Check all that apply)

[ ] protocol change
[x] user-visible impact
[ ] breaking change for a client SDKs
[ ] breaking change for FNs (FN binary must upgrade)
[ ] breaking change for validators or node operators (must upgrade binaries)
[ ] breaking change for on-chain data layout
[ ] necessitate either a data wipe or data migration

Release notes
Developers might see more compiler diagnostics as selected parsing errors no longer prevent compilation and diagnostics from the compiler reaching later compilation stages where additional diagnostics may be generated.

I will take a deeper look tomorrow, but most of these parser errors look really suspicious, like something has gone wrong with the thing that is supposed to consume tokens until the start of the next module member

Generally speaking, the weird errors were a consequence of not passing the error back to top level (recent change) to avoid modifying function signatures (return types). In other words, once a partial function was constructed (partial due to parsing error at some point during function parsing), it was returned to as a valid module member and since no info about the error was passes, next member's parsing was immediately attempted (which would result in another immediate error on the next token).
The current version compromises on this design a bit and  keeps "error state" in the parsing context for the parser to skip tokens when error is encountered and yet a member is parsed (partially) correctly. This way at least we don't have to keep this state in the AST nor propagate it via return types.

Superseded by https://github.com/MystenLabs/sui/pull/17137 and https://github.com/MystenLabs/sui/pull/16673


text:
iPad issue: Help layer shows wrong help-texts.

Help layers help-texts show "edit board"-texts even when I have no edit board-button (i'm a guest).
////////CONTRIBOARD TESTING, 24.7.2015////////
Contriboard (SUT) versions:
Client version v1.2.100
API version v0.4.38
IMG version v0.1.10
Testing environment:
Heli (1 kpl iPad iOS 8.3 (12F69) Flowdock -> Apple web-view)
////////CONTRIBOARD TESTING, 24.7.2015////////

Duplicate of #246

Duplicate #246 Closed now
Client versio	v1.2.118
API versio	v0.4.42
IMG versio	v0.1.10

authors: HelSu narsuman tanelih

license: mit

license_source: bigquery


text:
NComm Version 1.0

After using NComm in a few personal projects I realized the project structure and API were lacking in a few ways.  Therefore, I decided to make a large number of major changes to the organization and API of NComm which I am dubbing the official 1.0.0 release.  I doubt there will be any major breaking changes in the near future so I am declaring NComm 1.0.0 stable and any major breaking changes will only be merged in NComm 2.0.0.

NComm 1.0.0 here we go!


text:
難読化されたコードをコンパイルできる形へ自動調整する

概要

tigressにおいて，main関数が実装されていないコードを難読化すると自動的に void main() が追加されてしまい，難読化されたコードを別のコードと組み合わせてコンパイルすることができなくなってしまう．

調整事項
コンパイルできる形への調整のために発見した必要事項

void 型を返す main 関数を削除
extern で宣言している関数を削除
struct timeval の定義を削除
malloc または rand が含まれる場合は cstdlib ライブラリを使用する
定義前に宣言している独自 enum を削除

実装方法

(Best) C言語パーサーで対象のコードをパースした後，必要な形に調整して対象のコードを再構成する
(Good) 1行ごとにコードを読み取り，不要な箇所を削除して対象のコードを再構成する

C言語パーサーを実装するのが困難だったため，(Good)の方法で実装を行う予定

printfが含まれる場合は cstdioライブラリを使用する

AddO系統の難読化されたコードにおいてrand()による値の初期化を行っている箇所も削除していた．関数内のコードは基本的には削除しない

repo: NAIST-SE/ObfusEval


text:
decide on the final stack

@ibes
Let's start with what you think is a great starting point - and in the process we can change and experiment and find out what could be even better...
OK?

yes - will fixate the decission between Mix (as it is in the current repo) or wpack.io today by checking the repo

We have a startpoint now 💯

authors: ibes michael-voit

repo: NANU-Wandel-Wege-entdecken/NANU-website


text:
Add page redirection to login when no permissions available

This is to handle the case when a user with a role that has no permissions. They should now be redirected to the login page where an appropriate error is displayed.
This also prevents the bug where the error is shown on the login page regardless if permissions are present.

Any tips on how to test this? Is there an easy way to create a user with no permissions?

No, unfortunately there's no way to create a user without permissions yet. The easiest way is to temporarily override the event.locals.permissibleQueries value being set in hook.server.ts to just being {}.

authors: AaronPlave duranb

repo: NASA-AMMOS/aerie-ui


text:
Update parent LID integrity checking to fix bug introduced for collection integrity checking

I forget - was that error deliberately removed? I think validate should catch such errors, but maybe I missed/forgot some discussion.
Here's the current validate, followed by the build 9b's validate, with the error that 9b caught about 10 lines from the bottom. Hmmm, I couldn't attach a 160k zip. I uploaded it to pds-gamma:/home/rchen/bundleLID.zip
% validate -R pds4.bundle -t bundleLID/
PDS Validate Tool Report
Configuration:
Version                       1.17.3
Date                          2019-10-22T18:48:45Z
Parameters:
Targets                       [file:/Users/rchen/Desktop/bundleLID/]
Rule Type                     pds4.bundle
Severity Level                WARNING
Recurse Directories           true
File Filters Used             [*.xml, .XML]
Data Content Validation       on
Product Level Validation      on
Allow Unlabeled Files         false
Max Errors                    100000
Registered Contexts File      /PDS4tools/validate/resources/registered_context_products.json
Product Level Validation Results
PASS: file:/Users/rchen/Desktop/bundleLID/bundle_1.xml
Oct 22, 2019 11:48:50 AM com.sun.xml.bind.v2.runtime.reflect.opt.AccessorInjector
INFO: The optimized code generation is disabled
PASS: file:/Users/rchen/Desktop/bundleLID/data_derived/sol149b.xml
.........
PASS: file:/Users/rchen/Desktop/bundleLID/data_derived/sol149a.xml
PASS: file:/Users/rchen/Desktop/bundleLID/data_derived/data_derived_collection_1.xml
PDS4 Bundle Level Validation Results
PASS: file:/Users/rchen/Desktop/bundleLID/data_derived/data_derived_collection_1.xml
PASS: file:/Users/rchen/Desktop/bundleLID/bundle_1.xml
PASS: file:/Users/rchen/Desktop/bundleLID/data_derived/sol149b.xml
PASS: file:/Users/rchen/Desktop/bundleLID/data_derived/sol149a.xml
Validation complete.
Summary:
0 error(s)
0 warning(s)
End of Report
%
%
%
% /PDS4.9b.tools/validate-1.15.0/bin/validate -R pds4.bundle -f -t bundleLID/
PDS Validate Tool Report
Configuration:
Version                       1.15.0
Date                          2019-10-22T18:49:52Z
Parameters:
Targets                       [file:/Users/rchen/Desktop/bundleLID/]
Rule Type                     pds4.bundle
Severity Level                WARNING
Recurse Directories           true
File Filters Used             [.xml, *.XML]
Force Mode                    on
Data Content Validation       on
Allow Unlabeled Files         false
Max Errors                    100000
Registered Contexts File      /PDS4.9b.tools/validate-1.15.0/resources/registered_context_products.json
Product Level Validation Results
PASS: file:/Users/rchen/Desktop/bundleLID/bundle_1.xml
WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by com.sun.xml.bind.v2.runtime.reflect.opt.Injector$1 (file:/PDS4.9b.tools/validate-1.15.0/lib/jaxb-impl-2.2.4.jar) to method java.lang.ClassLoader.defineClass(java.lang.String,byte[],int,int)
WARNING: Please consider reporting this to the maintainers of com.sun.xml.bind.v2.runtime.reflect.opt.Injector$1
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release
PASS: file:/Users/rchen/Desktop/bundleLID/data_derived/sol149b.xml
PASS: file:/Users/rchen/Desktop/bundleLID/data_derived/sol149a.xml
PASS: file:/Users/rchen/Desktop/bundleLID/data_derived/data_derived_collection_1.xml
PDS4 Bundle Level Validation Results
FAIL: file:/Users/rchen/Desktop/bundleLID/data_derived/data_derived_collection_1.xml
ERROR  [error.integrity.missing_parent_prefix]   Member LID urn:nasa:pds:phx_ra:data_777:sol149b does not begin with parent LID urn:nasa:pds:phx_ra:data_derived
PASS: file:/Users/rchen/Desktop/bundleLID/bundle_1.xml
PASS: file:/Users/rchen/Desktop/bundleLID/data_derived/sol149b.xml
PASS: file:/Users/rchen/Desktop/bundleLID/data_derived/sol149a.xml
Summary:
1 error(s)
0 warning(s)
Message Types:
1            error.integrity.missing_parent_prefix
End of Report

@rchenatjpl great catch. about to merge a change to show this.
btw, when referencing data on our systems, we should probably try not to reference file paths since that can be a security concern. either send it to me over slack or say something like "home directory on pds-gamma". i know it is silly, but just to cover our bases.

Ok, I'll try to remember.
On 10/22/19, 13:43, "Jordan Padams" notifications@github.com wrote:
@rchenatjpl <https://github.com/rchenatjpl> great catch. about to merge
 a change to show this.
btw, when referencing data on our systems, we should probably try not to reference file paths since that can be a security concern. either send it to me over slack or say something like "home directory on pds-gamma". i know it is silly, but just to cover
 our bases.
—
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unsubscribe <https://github.com/notifications/unsubscribe-auth/ANPP7XGOCHAXT6BC7W2ZB6DQP5QXXANCNFSM4JDUJWZQ>.
[
{
"@context": "http://schema.org",
"@type": "EmailMessage",
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"target": "https://github.com/NASA-PDS-Incubator/validate/issues/146?email_source=notifications\u0026email_token=ANPP7XETE33Z73MZXISJXXLQP5QXXA5CNFSM4JDUJWZ2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEB7EIUY#issuecomment-545145939",
"url": "https://github.com/NASA-PDS-Incubator/validate/issues/146?email_source=notifications\u0026email_token=ANPP7XETE33Z73MZXISJXXLQP5QXXA5CNFSM4JDUJWZ2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEB7EIUY#issuecomment-545145939",
"name": "View Issue"
},
"description": "View this Issue on GitHub",
"publisher": {
"@type": "Organization",
"name": "GitHub",
"url": "https://github.com"
}
}
]

authors: jordanpadams rchenatjpl

repo: NASA-PDS-Incubator/validate


text:
adding seasonal weighting to lat/lonplots and vertical levels

From @nusbaume :
Fixes #121
Addresses #132

@nusbaume feel free to push. I am in a "stable" state now. Good to go!

repo: NCAR/ADF


text:
calculate anomalies & detrend

This has to be a common function.  at last try the esmlab wrapper wasn't working.  Maybe GeoCAT has something?

esmlab is working!  the dataset has to include timebounds to work properly
ds_anom = esmlab.core.anomaly(ds_last, clim_freq='mon', time_coord_name='time')

@jhamman if you have any time to see what I'm doing wrong with apply_ufunc in this code I'd appreciate it.  Also away this week and you're at the hackathon, so fine to wait a week...


text:
Fix bug in validator

@kshefchek This should tidy up the error reporting and make it much easier to handle errors.

@kshefchek this is ready for review and merge.

Thanks @kshefchek . Suggestions incorporated.

repo: NCATS-Tangerine/kgx


text:
Create Page Enhancements

Fixes https://github.com/NEAR-DevHub/neardevhub-bos/issues/596
Fixes https://github.com/NEAR-DevHub/neardevhub-bos/issues/501

Added Submit button on Preview page
Many UI enhancements, including better mobile UI and disabled submit button when there is no title and description

@itexpert120 could you please share a preview link of the UI changes you've made with every PR? This will speed up the review process.

@Tguntenaar Added preview

repo: NEAR-DevHub/neardevhub-bos


text:
Fix the threshold, support Weight type

@race-of-sloths include

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Since it an asap bug if it is ready to merge you should merge it.

@race-of-sloths score 3

authors: Megha-Dev-19 Tguntenaar race-of-sloths


text:
Data upload fails with projects containing jdx and jdf files

This is due to space (prefix) in the file names that are being uploaded. Please ensure that the file names have no trailing empty spaces. Also, nmrXiv webapp will trim the name when processing them, so this should be resolved. Also, please attach a file that you have tried for us to test and confirm if everything is working fine as intended.

Uploading projects with trailing space and jdx and jdf files is working now


text:
Improve crosswalk from schema.org to oai_dc

Since OAI-PMH mandates the metadataPrefix oai_dc, there is a crosswalk
from schema.org to oai_dc via xslt in json_container2oai_dc.xslt
=> The crosswalk is currently very minimalistic and needs improvement.
This ressource gives background on crosswalks: https://doi.org/10.5281/zenodo.4420116
The minimalistic example we have is
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:json="http://denbi.de/schemas/json-container" xmlns:map="http://www.w3.org/2005/xpath-functions/map" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ https://www.openarchives.org/OAI/2.0/oai_dc.xsd http://purl.org/dc/elements/1.1/ https://www.radar-service.eu/schemas/dc.xsd">
  <dc:identifier>https://massbank.eu/MassBank/RecordDisplay?id=MSBNK-Eawag-EQ358855#HHZIURLSWUIHRB-UHFFFAOYSA-N</dc:identifier>
  <dc:identifier>DOI</dc:identifier>
  <oai_dc:title>Nilotinib</oai_dc:title>
</oai_dc:dc>

I will have a look at it with Sandra!

Hi, to reproduce the issue / task, I have the following code snippet:
./any-jsonld2json_container.sh data/MSBNK-Eawag-EA00040-MolecularEntity.json | java -jar /usr/share/java/Saxon-HE-9.9.1.5.jar -xsl:json_container2oai_dc.xslt -s:-
which will create the following almost-oai_dc XML output:
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/"
           xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"
           xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
           xmlns:map="http://www.w3.org/2005/xpath-functions/map"
           xmlns:json="http://denbi.de/schemas/json-container"
           xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ https://www.openarchives.org/OAI/2.0/oai_dc.xsd http://purl.org/dc/elements/1.1/ https://www.radar-service.eu/schemas/dc.xsd">
   <dc:identifier>https://massbank.eu/MassBank/RecordDisplay?id=MSBNK-Eawag-EA000401#OUSYWCQYMPDAEO-UHFFFAOYSA-N</dc:identifier>
   <dc:identifier>DOI</dc:identifier>
   <oai_dc:title>Metamitron-desamino</oai_dc:title>
</oai_dc:dc>

I'd like to ask for two things from @febach or @stefanbozic or someone else:

please provide here in the issue a command line to validate that oai_dc XML output, and see what is actually broken. Maybe with an xmllint call against a oai_dc XSD ? And where to find that XSD ?
please suggest a fix to https://github.com/NFDI4Chem/oai4schemas/blob/main/json_container2oai_dc.xslt so that the validation succeeds.

Thanks in advance,
yours, Steffen

authors: febach sneumann


text:
feat(schematics): add v19 ng update migration

PR Checklist
Please check if your PR fulfills the following requirements:

[x] The commit message follows our guidelines: https://github.com/NG-ZORRO/ng-zorro-antd/blob/master/CONTRIBUTING.md#commit
[ ] Tests for the changes have been added (for bug fixes / features)
[ ] Docs have been added / updated (for bug fixes / features)

PR Type
What kind of change does this PR introduce?

[ ] Bugfix
[ ] Feature
[ ] Code style update (formatting, local variables)
[x] Refactoring (no functional changes, no api changes)
[ ] Build related changes
[ ] CI related changes
[ ] Documentation content changes
[ ] Application (the showcase website) / infrastructure changes
[x] Other... Please describe:

What is the current behavior?

Issue Number: N/A
What is the new behavior?

支持在 ng update ng-zorro-antd 时迁移下列 Breaking changes API

input-number #8901

entrypoint: ng-zorro-antd/input-number -> ng-zorro-antd/input-number-legacy
NzInputNumberModule -> NzInputNumberLegacyModule
NzInputNumberComponent -> NzInputNumberLegacyComponent

card #8741

迁移移除的 @Input nzBorderless 到 nzBordered

在 ng add 时

添加 providers 时，使用 provideNzI18n 替代 NZ_I18N
使用模板生成代码时

standalone 模式下移除 standalone: true
非 standalone 模式下增加 standalone: false

整理 ./schematics/ng-upgrade 下的代码组织结构 （参考 cdk）

本地验证
# build schematics
cd path/to/ng-zorro-antd
npx gulp build:schematics
cp ./components/package.json ./publish
sed -i "" -e 's/"version": "18.2.1"/"version": "19.0.0"/' ./publish/package.json

# symlink
npm ln

# ng update
cd path/to/project
npm ln ng-zorro-antd
ng update ng-zorro-antd --migrate-only --to 19.0.0 --from 18.2.1

Does this PR introduce a breaking change?

[ ] Yes
[x] No

Other information

晚点我加下 #8741 的迁移

ready to review

reviewed

repo: NG-ZORRO/ng-zorro-antd


text:
Feature/ccm 5363 recipient data

Description
Adds an environment-specific key to ensure that each environment can generate distinct hashes.
Provides a temporary query that shows that the key can be propagated from SSM into Athena via the step function.
Context
In future this will allow us to hash a patient NHS number for reports with minimal risk of precomputation attacks.
Type of changes

[ ] Refactoring (non-breaking change)
[x] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would change existing functionality)
[ ] Bug fix (non-breaking change which fixes an issue)

Checklist

[ ] I am familiar with the contributing guidelines
[x] I have followed the code style of the project
[ ] I have added tests to cover my changes
[ ] I have updated the documentation accordingly
[ ] This PR is a result of pair or mob programming

Sensitive Information Declaration
To ensure the utmost confidentiality and protect your and others privacy, we kindly ask you to NOT including PII (Personal Identifiable Information) / PID (Personal Identifiable Data) or any other sensitive data in this PR (Pull Request) and the codebase changes. We will remove any PR that do contain any sensitive information. We really appreciate your cooperation in this matter.

[x] I confirm that neither PII/PID nor sensitive data are included in this PR and the codebase changes.

Support for environment-specific hash keys in queries.

repo: NHSDigital/nhs-notify-reporting


text:
Related work

rephrase sentence on related work

PR looks good to me! :) I just had one minor nit-picky comment but am otherwise happy to get this merged :)

authors: Edenhofer roth-jakob

repo: NIFTy-PPL/JAXbind


text:
Dark Theme(#11)

Have added dark theme to the app. Issue: #11

Issue already resolved. 👍

authors: nivethsaran roshniRam


text:
Indicate which route is 'best' if multiple routes are available due to add-path

If a peer sends more than one route for a specific prefix, indicate which is best (if available in JSON output).

there isn't a best route. closing this one.

license: ISC


text:
Term中score和selfscore是什么？怎么计算出来的？

现在着重在看NLP这部分，可是里面很多地方没有注释，来咨询一下：
1）walkPath()中的relationMap是什么？？我Debug一直是null，好像没什么用的样子
2）Term结构体中有一个score和selfscore是什么？感觉和最后统计出的newword的freq有关？？那我是否可以自己给这个score赋值？？

ngram 中庸的。。。selfscore是本身分数。。score是vterbi 中记录路径的分数。
最好不要修改分数。。。newword  freq好像是依赖这个我也给忘记了

历史终将不了了之

authors: ansjsun kylinzlkz


text:
Add chapter on using bash

Add chapter on using bash
Closes #215

Ah, one other useful command to add may be who. I use that on remote servers a lot to check whether I'm not disturbing anyone by hogging the full machine ;)

authors: bouweandela egpbos

repo: NLeSC/guide


text:
questions about routinator syncs certificates

hello，
I installed routinator on my Ubuntu system，and try to use it to synchronize RPKI repositories. I found that it takes about 10 minutes to synchronize the entire  RPKI repositories and verify the certificates，is 10 minutes normal? I'd like to know how long this software will take to synchronize all RPKI repositories and validate all certificates respectively.
Whether the software will traverse all repositories during an update cycle? Is it traversing all of the RPKI certificates from the five RIRs' root certificates (default trust anchor) to leaf certificates to  synchronize RPKI repositories？

Typically the first validation run will take between 10 and 20 minutes, so what you're seeing is quite normal. In subsequent runs only the deltas will be processed so that is much quicker, typically around a minute or two.
Relying party software will connect to the five RIR trust anchors and traverse the entire RPKI tree, which currently consists of about 25 individual repositories. That means fetching data is the slowest part of the validation process.
You can learn more about this on rpki.readthedocs.io or discuss experiences on our mailing list.

authors: AlexanderBand syysumuro

repo: NLnetLabs/routinator


text:
Event Log not creating custom folder

I have a requirement where in we want our event logs to be written to a custom folder in Event Logs, however when i am specifying layout in NLog.config file it is directing it to Application folder.
Looked into source code , and looks like this is how it is implemented.
My exact requirement is to log events from my application is below manner:

Any pointers from any one on how to achieve it.
Thanks in advance.
Uploaded image again...Tx

Your image does not displayed. Could you upload it again?

Are you looking for something like this: http://stackoverflow.com/questions/5171155/creating-an-application-and-event-logs-in-the-applications-and-services-logs-s

Yes something like this but i want to write logs to it using NLog logger and want to set up the same using nlog config file.

You need to specifiy source and log in the configuration.
Event Log Target wiki page can guide you to do this.
To find out which value is required, you can look at the MSDN page. Because source and log values are the same thing that defined MSDN page
Please try and inform us. If it will not work for you, I will take a look again.

Yup using the guidelines specified on wiki page, i am not able to get the folder i have mentioned in first post, also i specify layout of message in nlog config file it ignores the value given in "log" configuration and directs it to application folder in event log.
This is the config file value i have set:

Could you post your full NLog config at here?

<!--
add your targets here
See https://github.com/nlog/NLog/wiki/Targets for possible targets.
See https://github.com/nlog/NLog/wiki/Layout-Renderers for the possible layout renderers.
-->

<!--Writing events to the a file with the date in the filename.-->

<!--size 100 kb and max archive files can be 2-->
<target name="eventlog" xsi:type="EventLog"  machineName="." source="mysource1" log="mylog1"  layout="${longdate} | ${guid} |${logger} | ${level} | ${message} | ${exception:format=ToString}"/>

<!--Write all events with minimal level of Debug (So Debug, Info, Warn, Error and Fatal, but not Trace)  to "f"-->
<logger name="*" minlevel="Debug" writeTo="eventlog" />

@UgurAldanmaz are you looking at this?

bump @UgurAldanmaz

@dev-4488 I guess this is still an issue?

Yes it is, any pointers on how to fix it or when it will be fixed??

I will look at this, but I need some more info to understand the issue.
As far I understand you would like to write to "mylog1/operation" (logname), is that correct?
So if you set
 target name="eventlog" xsi:type="EventLog"  machineName="." source="mysource1" log="mylog1/operation"  layout="${longdate} | ${guid} |${logger} | ${level} | ${message} | ${exception:format=ToString}"/>

that won't work?

Yes you are correct, because if you specify Layout for an event log target it will start putting logged events information in default folder i.e. Application.

I'm not sure if I fully understand you.
But you like to use a Layout for the log name?
e.g.
<target log="${test}" >

Nope, i am using below xml to write to event logs:

<target name="eventlog" xsi:type="EventLog"  machineName="." source="mysource1" log="mylog1"  layout="${longdate} | ${guid} |${logger} | ${level} | ${message} | ${exception:format=ToString}"/>

However the log information is going to Application folder in Event Viewer rather than to a custom folder "mylog1".

Ah, so this is https://github.com/NLog/NLog/issues/950 ?

Yes.... :)  is there any solution for it ??

Well I can't reproduce it.
But if you willing to help, you can test if you can write to the log just with some c# statements (without nlog) . If that's working, we will move the working code into NLog.

Closing this as it's a duplicate of #950

repo: NLog/NLog


text:
Replaced MutableUnsafeAttribute with ThreadAgnosticImmutableAttribute

[ ] Waiting for NLog v5.3

I don't like the word "unsafe", and since the attribute is just a restriction of the original ThreadAgnosticAttribute, then I think [ThreadAgnosticImmutable] is better (Only ThreadAgnostic when LogEvent-state is immutable)

It could be interesting if the layout precalculate was a little smarter. Right now if having a JsonLayout that includes ThreadId, then the entire JsonLayout must be precalculated by the application-thread, and cannot be deferred to async-background-thread.
It could be neat if JsonLayout Precalculate was to recognize that less than 5 SimpleLayout needed to perfrom Thread-context-capture, then instead of rendering the entire Json-Document on the application-thread. Then it would "just" precalculate those 5 SimpleLayout-results.
It could also be interesting if the JsonLayout was able to recognize whether it should precalculate, when it detects that it must IncludeEventProperties = true, but only if the LogEventInfo-properties are "volatile" / "not-immutable". This should be combined with the coming optimization where NLog.Extensions.Logging doesn't provider format-Parameters-array, but only the LogEvent-properties-collection.


text:
[5pt] Stage-Based CatFIM bug where the branch 0 dem_adj_elevation is used

A bug is occurring in Stage-Based CatFIM where the wrong dem_adj_elevation value is being used. The goal is to use the value from the branch that is not branch 0, but there is a flaw in the logic. Related to Vlab 115987.
Current behavior
Overinundating some reaches, such as LDYN6.
Expected behavior
Correct inundation.
Screenshots

The bug occurs in generate_categorical_fim.py on line 331. The wrong dem_adj_elevation value is being used because of a flaw in the pandas logic.

I addressed the bug for site LDYN6. Screenshot below. Will now do a full run.

repo: NOAA-OWP/inundation-mapping


text:
Add ADCP Scal and EIN

EIN could be combined with VEL in many cases

what about if a depth has been qc'd out of one?

SCAL can be added to all pretty easily but as a seperate dataset (tabular)

There is already a "table" that reads all .nc files in the directory and puts it in a tabular format... however, it grabs all depths from the gridded data too which is unnecessary.  Modify to get just SCAL

new CF flavored netcdf files starting 2020 will have this


text:
Event text going outside of the box

https://github.com/NPBruce/valkyrie-store/issues/1

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authors: MrCraigen NPBruce

repo: NPBruce/valkyrie


text:
Table row shading with wxWidgets 3.1.5

Mentioned in https://github.com/NREL/wex/pull/135 and SAM #883
windows-display-issues-from-paul.pdf

Fixed with wex pull requests 138 and 139
https://github.com/NREL/wex/pull/138
https://github.com/NREL/wex/pull/139

repo: NREL/SAM


text:
Update data JSON from Haystack v3 to Haystack v4

Update the input data configuration JSON to Haystack version 4. Affects...

Data intake Python code (maybe? TBD)
tests/data/README.md (describes format)
tests/data/Synthetic Site/Synthetic Site Config.json

Updating all SkySpark-related issues to high priority

repo: NREL/Wattile


text:
Feature/update reqs and add simple test

This pull requests adds/improves some software components ahead of the v1 changes.
It addresses: Issue #34 and Issue #31 , changes include:

Removing unused requirements
Adding semantic versioning using compatible release specifier
Adds a first pytest, which just declares an empty py-sim but can test everything imports
Adds a continuous integration workflow for automatic testing
Removes un-used requirements.txt
Adds vs-code items to gitignore

Pulling to main to cause the ci to go into effect and can back merge to develop after
Pull request closes #34 and closes #31

I ran the tests locally (and I think this pull request ran the tests too), but yeah, might also be different after merging...

repo: NREL/hercules


text:
Add an est_time plan tool

eta_time(scan([det], motor, 1, 10, 10)) would be cool. This would be a simulator that uses whatever it can find out about the hardware to estimate how long a plan would take to run and, say, return a number of seconds. It would not touch any hardware.

This is an old one, but want to add my encouragement. This would be really useful for us, it would of course probably assume a fixed time for motor moves which wion't be so accurate but a great start.

Can you help us brainstorm what we would need to know from the hardware, to first order? In my mind, a "zeroth-order solution" would make blunt assumptions like "All motors take 1 second to move, period." I imagine we would need:

movable hardware to report a an ETA to a given position like motor.eta(5) or temp.eta(273)
detectors to consistently exposure their exposure time through a consistently-named attribute, and (better yet) give us some estimate of the overhead time (triggering time - acquiring time)

Maybe we should develop software loops for empirically measuring these things and storing the relevant data in a cached file somewhere.

I agree getting an accurate measure of the time taken for the motors is difficult. For the detectors, almost all have a 'aquisition period' variable and this could be mapped to a consistently named attribute in the setup file, or if the variable is not present then a estimate could be hard-wired.
For the motors, a standard motor record from a delta tau has a 'motor velocity' attribute (in units/s) already, which can be used to give a time estimate for a move of x units. Non-motor record motors may need to introduce a hard-wired estimate like the detectors without aquisition time in the setup.

Just thought I’d add, I am happy to discuss in person if it helps, just throw something on my calender

We can't prioritize this until after our "1.0" deadline (a week from Wednesday) but I think we can draft something usable not long after that.

So I will wait to progress much on this until Dan is back. But this morning I did some testing at SIX in order to see if we could get an accurate eta for a 'move' and for a 'count'. I think it is possible but a little more work needs to be done.
for 'move':
using the motor.velocity and motor.settle_time, along with the distance to move runs into an issue in that there is a on defined 'settle time' built into the motion that depends on the travel distance. if I determine this extra 'settle' time empirically and add it to the eta then for all moves of this distance I get an eta to within 1% (longer moves have reduced error). I tested with several travel distances (with different extra settle times), and about 10 motors (each with there own extra settle time values) and it does seem accurate to within 1%. This extra settle time is clearly observed in CSS (watching the move indicator) so is not associated with any bluesky/ophyd overheads. I will talk to John Sinsheimer and see if this extra settle time can be determined a-priori or not.
for 'count':
using the det.aquire_time gives a pretty poor indication in itself ( ~ 10%). The remaining error is overhead from count (a fixed value independent of the number of points ~ 3.6s, detector independent) and from the individual reads (a fixed value depending on the number of counts  ~ 0.275s, detector independent). The first is probably associated with the stage and unstage, while the second is associated with the time lag between asking for a read and processing the liveplot/livetable update. I can see from the CSS page that these values are not related to he detector acquisition time, and they do not vary with acquisition time. My thoughts on this is that we could get more accurate over time with these values by calculating, and storing, these time lags after each stop document (or similar).
What are peoples thoughts?

I have an update on the motor issue above regarding the extra settle time that is related to the distance moved. After speaking with John Sinsheimer it appears this was a setup mistake in the delta tau. After John fixed the issues I did more testing, and the settle time and velocities now do a good job of estimating the time (< 1% accuracy). There are a few outliers, where the PV velocity differs from the measured velocity resulting in 1-50% time errors, but these are bought under control by using the measured velocity. And the final outlier case are the virtual motor axes, where it is impossible without knowing the motion equations between real and virtual motions to accurately estimate the time to move. So I think the solution here is to take the PV velocity as a starting point, but to measure and average after each move of an axis a velocity which will make the estimating tool more accurate as time goes on.

So a quick update on this, the summarize_plan analogy is written, and undergoing testing. We are working on the lower level stuff.

A preliminary set of code to do this is presented in PR #1048 and NSLS-II/Ophyd PR # 567

We plan to do this, but the feature is too complex to be designed via GitHub Issues. We will write up a Bluesky Enhancement Proposal to lay out the planned design.

authors: awalter-bnl danielballan

repo: NSLS-II/bluesky


text:
Data storage server down

This is a urgent issue. The GPFS server is down. Bluesky scan engine couldn't access to storage directory, we cannot run any scan now.

Petkus is aware of the problem and is working on it.
-matt
On Wed, 1 Feb 2017, xiaojinghuang wrote:

This is a urgent issue. The GPFS server is down. Bluesky scan engine couldn't access to storage
directory, we cannot run any scan now.
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Can you access the GPFS server via any other method on the workstation?  Can you IOCs see the GPFS?
My guess is not as nothing at the python layer knows about GPFS, it is simply a path in the file system.  I also do not think that the RE directly writes to the GPFS, the detector IOCs should be doing that them selves.
You should contact someone from Rob's group about this.

The server is back online now. Thanks a lot.

authors: cowanml tacaswell xiaojinghuang

repo: NSLS-II/ophyd


text:
Different Results when I do inference on onnx file using TRT engine vs inference using pth file

I am able to train and validate using a custom dataset (bunch of npy files and corresponding annotations). I am using pointpillars model. The results look accurate on the point cloud using the demp.py file (visualization using pth)
For my eval example 000000.npy,
I get the following results using demo.py:
pred_dicts[0]['pred_scores']  tensor([0.8475, 0.4954, 0.4725, 0.4603], device='cuda:0')
pred_dicts[0]['pred_boxes']  tensor([[  9.6669,   1.1732,   2.1426,   0.2856,   0.5018,   3.1349,   6.2874],
[  9.8581, -10.6740,   2.0632,   0.4447,   0.4504,   2.5857,   6.2749],
[ 24.9824, -10.4977,   3.1227,   0.2673,   0.4696,   3.1857,   6.2983],
[ 24.8274,   1.3483,   2.7095,   0.2326,   0.4953,   3.1487,   6.3119]],
device='cuda:0')
However, when I do inference using the generated onnx file using the TRT engine, I get the following:
50.8117 -6.56379 1.9568 0.256044 0.501621 2.79036 6.28261 0 0.860124
48.4368 -14.8604 2.06768 0.442814 0.450666 2.58379 6.27543 0 0.499151
42.9857 -14.6852 3.1227 0.267265 0.469636 3.18565 6.29831 0 0.472531
45.4026 -6.38253 2.70948 0.232621 0.495276 3.14874 6.31186 0 0.460299
After I analyzed the numbers, I see the confidence numbers are almost the same. Even the box dimensions are same across both. Even the z dimensions match. However, I see a huge disparity in x and y coordinates. Can someone please help me out?
I have attached another comparison as well:

Hey, can someone please help me out with this? I am using npy files for TFRT inference instead of bin files. Not sure if that is causing any issue? When I compared the .npy data being loaded in python vs data loaded in the main.cpp, I see 32 additional bytes when the main.cpp file loads the same npy file. I accounted for this but that did not fix my issue, unfortunately!

@byte-deve , I would really appreciate your input here.

repo: NVIDIA-AI-IOT/CUDA-PointPillars


text:
[Task] Run Merlin notebook tests from Systems repo

Description
When we make changes in systems we will want to run the example notebooks in the Merlin repo using the current branch of systems. This will ensure that any changes to systems will not break the end-to-end demos/integration tests, which has been an issue lately and came up in our retrospective.
The process will be:

Create a python venv using tox
Check out the main branch of Merlin and install
Check out the PR branch of systems and install
Run Merlin integration tests (notebooks)

Since the notebooks include making inference on triton, this will have to run on the Jenkins machine, not in the CPU-only Github actions test.

First PR towards this was getting tox working on jenkins: https://github.com/NVIDIA-Merlin/systems/pull/180

Finished here: https://github.com/NVIDIA-Merlin/systems/pull/183

repo: NVIDIA-Merlin/Merlin


text:
[Task] Add Tensorflow version for getting-started and end-to-end example notebooks

Description

[x] Tensorflow support and example notebooks were asked by several people at the RecSys'21. Need to add example notebooks for that.
[x]  Test if currently we can serve a session-based model trained with Tensorflow to Triton.

closing with https://github.com/NVIDIA-Merlin/Transformers4Rec/pull/341


text:
caffe BGR issue

hey,
After I trained the model successfully, I tried to test one image, and I found it does not do channel swap. So I am a little confused.
Here is my understanding:
Inside caffe, if you let caffe do decoding on the image, it will always be BGR format(by opencv). And I did not see any code inside digits, which will convert loaded images into BGR mode. Therefore,
digits create db -----> with encoded images
caffe train the db ------> with BGR format
digits test one image -------> with RGB format
So the final result won't work as expected.
Did I miss anything?

Rats. I intentionally avoided swapping channels because it's annoying and because I want the datasets to be consumable by different deep-learning frameworks which don't require the channel swap. It was all working fine until I added the JPEG compression.
I think the right thing to do is to do the channel swap at inference time only if the dataset was encoded and chalk this up to a caffe "bug".
Thanks very much for bringing this to my attention, @dxj19831029.

repo: NVIDIA/DIGITS


text:
About manual pre-processing.

I trained my network in DIGITS. And deploy it my c++ framework with DIGITS caffemodel. And result is 1.X % worse than DIGITS result. I think reason is in the image preprocessing step.
I used gray image.
resize it by cv::resize()    {here, default option is INTER_LINEAR and DIGITS use image = scipy.misc.imresize(image, (height, width), 'bilinear') is it different?}
I used mean image subtraction.
so load mean.binaryproto.
And resized image convert to CV_32FC1.
And subtract them.
I think problem can occur at resize step.
And if it is problem, I want know how can I implement c++ classifier with DIGITS caffemodel.

Sorry for the slow response!
If you're using a different resizing method then the model performance will almost certainly not be "worse" - you'll just get different results for the same images. It sounds like you already have a C++ classifier with a DIGITS caffemodel - you don't really need to match DIGITS's output in order to have a working system.
However, it's nice to be able to verify that you're not doing anything wrong. So let's see if we can figure out your problem.
From OpenCV's documentation:

INTER_LINEAR - a bilinear interpolation (used by default)

That sounds like it should be the same as scipy's "bilinear" to me. So I doubt the resizing algorithm is your problem.

And resized image convert to CV_32FC1.

My guess is that you are converting your image to BGR, while the mean image is in RGB (or vice versa).
Try using the classification example under /examples/classification/ and see if you can reproduce the results there. If so, check these functions to see how DIGITS resizes images and how Caffe's caffe.io.Transformer gets set up.

authors: lukeyeager oanoelsis


text:
question about data files for the xlnet example

Where could I download data files for running the example  ?  Thanks.
int main(int argc, char** argv)
{
    string input_name = "./data/data.npz";
    string model_name = "./data/model.npz";
    string check_name = "./data/output.npz";

    if (argc != 11) {
        printf("[ERROR] ./bin/xlnet_correctness_example batch_size num_layers seq_len "
               "head_num size_per_head num_token input_name model_name check_name "
               "data_type 0: fp32, 1: fp16, 2: bf16\n");
        printf("e.g., ./bin/xlnet_correctness_example 8 12 128 12 64 32000 "
               "./data/data.npz ./data/model.npz ./data/output.npz 0\n");
        return 0;
    }

These files are prepared in these steps: https://github.com/NVIDIA/FasterTransformer/blob/main/docs/xlnet_guide.md#verify-the-correctness

authors: byshiue zjin-lcf

repo: NVIDIA/FasterTransformer


text:
Very limited LoRA Functionality

So I noticed that we can add a single LoRA to the TRT model. Problems here are:

It is only ever a single LoRA at any given time, and you have to build a new TRT model for each.
The implemented LoRA always seems to be at full (1.0) strength.

This seems to be a major downside currently as this heavily limits what I can do with any given model. As long as I am just using baseline SD checkpoints this is no problem, but as soon as I introduce a LoRA to the generation process, this becomes messy, and depending on the LoRa, unusable. As soon as I want to have multiple LoRAs, it basically is impossible.

I'm working on improving this. Currently, we require an ONNX model containing the applied weights to refit the engine just in time. And in the short term, I don't see a workaround for this.....
For now, there are two options:

Use the default LoRA embeddings and export the ONNX model JIT. This takes approx. 40s for SD1.5 model.
Extend the current LoRA exporter to support multiple LoRA and strength.

I understood the second option, but not the first. What do you mean "default LoRA embeddings"?
By default a checkpoint has no embedding, so what specifically did you mean by default, and how does that relate to variable LoRA strength configuration when fusing the checkpoint and LoRA weights?
As a side-note, fantastic work on this extension Luca, much appreciated!
Your side-project has led to a sale of 2 x 4090 cards and a 3080 already, so I hope your employer allows you some paid time to work on this project :)

What do you mean "default LoRA embeddings"?

I am not sure what the correct terminology would be, but I intended the <loraName:Scale> syntax in the prompt.
After some more thought, I think this is my preferred way of doing things:

LoRA checkpoints still need to be exported through the TensorRT tab. Export in this case means layout and weight transformation, so no TensorRT compile for each LoRA checkpoint.
At inference, the <loraName:Scale> syntax can be used (given the LoRAs you want to use have been exported)

I appreciate the positive feedback!

When does the TensorRT compilation happen in the above two-step procedure?

The compilation happens during the export of the base model. I'm working on a POC right now to see how feasible this is. If everything goes smoothly (which it never does) I could have something in a few hours hacked together.

LoRA checkpoints still need to be exported through the TensorRT tab. Export in this case means layout and weight transformation, so no TensorRT compile for each LoRA checkpoint.

and

The compilation happens during the export of the base model.

Does this mean that only the base model (checkpoint) needs to be TRT compiled, and that you can use the lora ranks and weights as-is without creating TRT variants of them?
The statement "no TensorRT compile for each LoRA checkpoint" led me to believe the latter.
Or I may have misunderstood, and you meant there could be two separate compiles, one for the base checkpoint and another for the LoRA ranks and weights separately.
Either way, you seem to indicate there may be a way around the L x W x C (#loras x #weights-for-lora-fusing x #base-checkpoints) combinatorial explosion of number of exported onnx and trt models the current scheme requires, so am I interpreting you answer to mean there may be a way to fuse the lora weights (be they compiled or not) with the compiled base checkpoint "engine" dynamically (at inference time)?

Does this mean that only the base model (checkpoint) needs to be TRT compiled, and that you can use the lora ranks and weights as-is without creating TRT variants of them?

Yesn't - Long explanation:
The engine export consists of two steps:

ONNX export
TensorRT engine compilation

TensorRT requires ONNX as an intermediate representation to lower the graphs IR. Therfore, we cannot leverage torch checkpoints directly, but need to lower them through ONNX. This also applies to LoRA checkpoints.
Therefore LoRA checkpoints still need to be exported. But this only requires step 1 (ONNX export) rather than the actual compilation. We'll leverage the compiled base models and apply LoRA then.

Here is an end-to-end example assuming you start from scratch:
I have SD 1.5 installed and two random LoRAs (BarbieCore, pk_trainer768_V1)

I need to export the base model (SD1.5) to TensorRT (ONNX Export + Compile)
I need to export my LoRA checkpoints (ONNX Export only)

From here LoRA should work as (native) in the UI using prompts like:  <lora:BarbieCore:0.7>  <lora:pk_trainer768_V1:1> A pixel image of a man with a sword Barbiecore
I hope this clarifies things, and isn't more confusing than before :D

Here is a screenshot of how it looks like at inference. This also allows the SD Unet dropdown to be set to automatic.

Limitations

Applying the LoRA is pretty slow at the moment (~10s). But when using the same scales and loras this is being cached.
There is probably still a ton of bugs
LoRA TensorRT format is not as filesize efficient

I pushed my PoC to lora_v2 in case you dare to test it.

I pushed my PoC to lora_v2 in case you dare to test it.

I did, and it worked flawlessly. My hat's off to you. Awesome job!

Applying the LoRA is pretty slow at the moment (~10s). But when using the same scales and loras this is being cached.

Yes, but unless someone rotates a bunch of different LoRAs in and out constantly in the XYZ plot, it shouldn't be a problem.
The initial load of a new lora took about what you describe, but once loaded, I could tweak the weights without that initial pause. Started rendering instantly. The main use case for varying weights a lot is likely the XYZ plot, and I'm happy to report that it iterates over different weights in the same lora(s) at full throttle.
I'm still a bit perplexed that there was no discernable performance impact (regression), since only the base checkpoint is TRT compiled, and the LoRA ranks and weights seem not to (unless you do on-the-fly compilation during loading at inference time). Haven't had time to look at the code change yet.
For anyone else wanting to use this:

Go into the extension directory and check out the lora_v2 branch.
Delete any fused checkpoint + lora tensorrt and ONNX files that you may have created earlier for the combinations. You can keep the ONNX and TRT models for the base checkpoint itself, since the code change doesn't seem to affect those.
Apply the LoRAs as usual with SD-webUI, and enjoy the 2x rendering speedup.

I am happy to hear it works on a machine other than mine :D I also tested LyCORIS, and for me, it seemed to have worked fine.
One general disclaimer: This is a work in progress, and there might be breaking changes before it finds its way into the main branch.

On the fly Lora... IT WORKS!!!
With my limited testing on 3 different loras, here is my feedback:
The loras have small amount of effect on the generated images. That is, the loras seems to work, but they are not as effective as when i use them without TensorRT.
Here is an example: link
I do not know if there is an issue from my side, cause I do get an error when trying to generate images with TensorRT + Lora.
Here is the error I get:
Apllying LoRAs: ['lora:TheRockV3:1']███████████████████████████████████████████████████| 30/30 [00:04<00:00,  7.89it/s]
*** Error running process: C:\stable-diffusion-webui\extensions\Stable-Diffusion-WebUI-TensorRT\scripts\trt.py
    Traceback (most recent call last):
      File "C:\stable-diffusion-webui\modules\scripts.py", line 623, in process
        script.process(p, *script_args)
      File "C:\stable-diffusion-webui\extensions\Stable-Diffusion-WebUI-TensorRT\scripts\trt.py", line 191, in process
        self.get_loras(p)
      File "C:\stable-diffusion-webui\extensions\Stable-Diffusion-WebUI-TensorRT\scripts\trt.py", line 229, in get_loras
        modelmanager.available_models()[lora_name][0]["filepath"],
    KeyError: 'TheRockV3'

---
Loading TensorRT engine: C:\stable-diffusion-webui\models\Unet-trt\realisticVisionV51_v51VAE_f4744654_cc86_sample=1x4x64x64+2x4x64x64+8x4x96x96-timesteps=1+2+8-encoder_hidden_states=1x77x768+2x77x768+8x154x768.trt

Loaded Profile: 0
        sample = [(1, 4, 64, 64), (2, 4, 64, 64), (8, 4, 96, 96)]
        timesteps = [(1,), (2,), (8,)]
        encoder_hidden_states = [(1, 77, 768), (2, 77, 768), (8, 154, 768)]
        latent = [(-1946122960), (-1946120097), (-1946121115)]

100%|██████████████████████████████████████████████████████████████████████████████████| 30/30 [00:03<00:00,  8.04it/s]
Total progress: 100%|██████████████████████████████████████████████████████████████████| 30/30 [00:03<00:00,  7.95it/s]
Total progress: 100%|██████████████████████████████████████████████████████████████████| 30/30 [00:03<00:00,  8.44it/s]

+1, I've also managed to get it working. Amazing stuff, now I need only ControlNet to completely move over to TensorRT.
I started with a fresh installation with only this extension and besides my incompetence, there were no issues.
The resulting image is the exact same with and without TensorRt unet enabled.
Do you think there would be major work needed before this can be merged?

Go into the extension directory and check out the lora_v2 branch.

I'm still rather new to anything github. How do I switch branches?  Can't seem to get it to work.

Hi, So I've been testing out your Lora_v2 branch and while inpainting I've been getting an error about a missing attribute as highlighted below.
*** Error running before_process: /content/stable-diffusion-webui/extensions/Stable-Diffusion-WebUI-TensorR/scripts/trt.py
    Traceback (most recent call last):
      File "/content/stable-diffusion-webui/modules/scripts.py", line 615, in before_process
        script.before_process(p, *script_args)
      File "/content/stable-diffusion-webui/extensions/Stable-Diffusion-WebUI-TensorR/scripts/trt.py", line 129, in before_process
        if p.enable_hr:
    AttributeError: 'StableDiffusionProcessingImg2Img' object has no attribute 'enable_hr'

I have seen this play out with a couple other extensions previously you may want to consider using something like getattr() to see if the attribute has a value and if it is not set return a default value. You could do somethinng like the following where you previously have accessed it:
    def before_process(self, p, *args):  # 1
        # Check divisibilty
        if p.width % 64 or p.height % 64:
            gr.Error("Target resolution must be divisible by 64 in both dimensions.")

		enable_hr = getattr(p, 'enable_hr', False)
        if enable_hr:
            hr_w = int(p.width * p.hr_scale)
            hr_h = int(p.height * p.hr_scale)
            if hr_w % 64 or hr_h % 64:
                gr.Error(
                    "HIRES Fix resolution must be divisible by 64 in both dimensions. Please change the upscale factor or disable HIRES Fix."
                )

That should achieve the same results as you were intending.

I pushed my PoC to lora_v2 in case you dare to test it.

So to make sure, is lora_v2 basically dev branch?
And do you have any tips to not need 30 2GB for every resolution/aspect ratio variable known to man? xD As currently i got 30 different ones as from the gist i got, a more dynamic res one will allow more different resolution, but not as fast.

So to make sure, is lora_v2 basically dev branch?

lora_v2 has commits on top of the dev branch which allows loading multiple loras and changing lora weights. You have to convert the lora to TensorRT but do not need to specify a resolution.

And do you have any tips to not need 30 2GB for every resolution/aspect ratio variable known to man? xD As currently i got 30 different ones as from the gist i got, a more dynamic res one will allow more different resolution, but not as fast.

I would create one dynamic if you use multiple resolutions and aspect ratios. Here's an example for SD 1.5 for generations from 512-768 (any aspect ratio) with hires fix up to 2x.

I do not know what the optimal field does so I set it to match the max (if anyone has an explanation, please share). It still has a big speed improvement over not using TensorRT.

How do I indicate on the TensorRT tab that I want the Lora to make an "ONNX Export only"?
Moreover, what's the obvious thing to check if I've:

updated to lora_v2
built TRT and ONNX for my preferred model at my preferred resolutions
exported Loras from the TensorRT tab
selected Automatic in the SD_unet selector in the UI
added <lora:X> to the prompt
and the Loras are not being applied at inference?

Is it that I need to delete the onnx loras?

I am getting an error when trying to convert a lora to trt:
[W] 'colored' module is not installed, will not use colors when logging. To enable colors, please install the 'colored' module: python3 -m pip install colored [E] ONNX-Runtime is not installed, so constant folding may be suboptimal or not work at all. Consider installing ONNX-Runtime: I:\sd.webui\system\python\python.exe -m pip install onnxruntime [!] Module: 'onnxruntime.tools.symbolic_shape_infer' is required but could not be imported. Note: Error was: No module named 'onnxruntime' You can set POLYGRAPHY_AUTOINSTALL_DEPS=1 in your environment variables to allow Polygraphy to automatically install missing modules. [W] colored module is not installed, will not use colors when logging. To enable colors, please install the colored module: python3 -m pip install colored [W] Inference failed. You may want to try enabling partitioning to see better results. Note: Error was: No module named 'onnxruntime' [!] Module: 'onnxruntime.tools.symbolic_shape_infer' is required but could not be imported. Note: Error was: No module named 'onnxruntime' You can set POLYGRAPHY_AUTOINSTALL_DEPS=1 in your environment variables to allow Polygraphy to automatically install missing modules. [W] colored module is not installed, will not use colors when logging. To enable colors, please install the colored module: python3 -m pip install colored [W] Inference failed. You may want to try enabling partitioning to see better results. Note: Error was: No module named 'onnxruntime' [!] Module: 'onnxruntime.tools.symbolic_shape_infer' is required but could not be imported. Note: Error was: No module named 'onnxruntime' You can set POLYGRAPHY_AUTOINSTALL_DEPS=1 in your environment variables to allow Polygraphy to automatically install missing modules. Exported to ONNX. Traceback (most recent call last): File "I:\sd.webui\system\python\lib\site-packages\gradio\routes.py", line 488, in run_predict output = await app.get_blocks().process_api( File "I:\sd.webui\system\python\lib\site-packages\gradio\blocks.py", line 1431, in process_api result = await self.call_function( File "I:\sd.webui\system\python\lib\site-packages\gradio\blocks.py", line 1103, in call_function prediction = await anyio.to_thread.run_sync( File "I:\sd.webui\system\python\lib\site-packages\anyio\to_thread.py", line 33, in run_sync return await get_asynclib().run_sync_in_worker_thread( File "I:\sd.webui\system\python\lib\site-packages\anyio_backends_asyncio.py", line 877, in run_sync_in_worker_thread return await future File "I:\sd.webui\system\python\lib\site-packages\anyio_backends_asyncio.py", line 807, in run result = context.run(func, *args) File "I:\sd.webui\system\python\lib\site-packages\gradio\utils.py", line 707, in wrapper response = f(*args, **kwargs) File "I:\sd.webui\webui\extensions\Stable-Diffusion-WebUI-TensorRT\ui_trt.py", line 247, in export_lora_to_trt if len(available_trt_unet[base_name]) == 0: KeyError: 'revAnimated_v122'

Just a quick question about this log, is installing ONNX-Runtime necessary, a good thing? to omit that error or have faster compile times?

When I switched to the Lora_v2 branch and converted it to TensorRT, I encountered the following error while using it.
 Error running process: J:\x\stable-diffusion-webui\extensions\Stable-Diffusion-WebUI-TensorRT\scripts\trt.py     Traceback (most recent call last):       File "J:\x\stable-diffusion-webui\modules\scripts.py", line 710, in process         script.process(p, *script_args)       File "J:\x\stable-diffusion-webui\extensions\Stable-Diffusion-WebUI-TensorRT\scripts\trt.py", line 191, in process         self.get_loras(p)       File "J:\x\stable-diffusion-webui\extensions\Stable-Diffusion-WebUI-TensorRT\scripts\trt.py", line 238, in get_loras         refit_dict = apply_loras(base_path, lora_pathes, lora_scales)       File "J:\x\stable-diffusion-webui\extensions\Stable-Diffusion-WebUI-TensorRT\scripts\lora.py", line 32, in apply_loras         add_to_map(refit_dict, name, n.outputs[0].values)     AttributeError: 'Variable' object has no attribute 'values'

When I switched to the Lora_v2 branch and converted it to TensorRT, I encountered the following error while using it.
Error running process: J:\x\stable-diffusion-webui\extensions\Stable-Diffusion-WebUI-TensorRT\scripts\trt.py
    Traceback (most recent call last):
      File "J:\x\stable-diffusion-webui\modules\scripts.py", line 710, in process
        script.process(p, *script_args)
      File "J:\x\stable-diffusion-webui\extensions\Stable-Diffusion-WebUI-TensorRT\scripts\trt.py", line 191, in process
        self.get_loras(p)
      File "J:\x\stable-diffusion-webui\extensions\Stable-Diffusion-WebUI-TensorRT\scripts\trt.py", line 238, in get_loras
        refit_dict = apply_loras(base_path, lora_pathes, lora_scales)
      File "J:\x\stable-diffusion-webui\extensions\Stable-Diffusion-WebUI-TensorRT\scripts\lora.py", line 32, in apply_loras
        add_to_map(refit_dict, name, n.outputs[0].values)
    AttributeError: 'Variable' object has no attribute 'values'

Hello everybody
Do you know if it's normal that it's create 1 single TRT file per lora and per checkpoint ? The size of each trt file generated is 1,6 Go
Inside the folder models\Unet-trt
Do you know if I can do an optimization ?
Because if I have 15 loras and 3 checkpoints. No problem to take time to generate it. But it will take too much space on the hard drive...
Thank you

getattr(p, 'enable_hr', False)

Why the error will happen? I alse came to it. We have an wrong version for the extension?

I'm working on improving this. Currently, we require an ONNX model containing the applied weights to refit the engine just in time. And in the short term, I don't see a workaround for this.....
For now, there are two options:

Use the default LoRA embeddings and export the ONNX model JIT. This takes approx. 40s for SD1.5 model.
Extend the current LoRA exporter to support multiple LoRA and strength.

I found an issue for the lora on switching engine which one lora based on A model onnx can't fit in B model because of mismatching shape channel. Any solution or advice about it?

Hello everybody
Do you know if it's normal that it's create 1 single TRT file per lora and per checkpoint ? The size of each trt file generated is 1,6 Go Inside the folder models\Unet-trt Do you know if I can do an optimization ?
Because if I have 15 loras and 3 checkpoints. No problem to take time to generate it. But it will take too much space on the hard drive...
Thank you

perhaps it's normal. If you don't care about the time of inference, perhaps you can cal lora at runtime.

tweak

Hi guys! Would you mind to share the method to use one lora on different base model as pytorch?

authors: CoolCuda DuckersMcQuack FerLuisxd Sniper199999 ThisIsNetsu bigmover contentis devjo intoempty mort666 qybing szokolai-mate worksforme

repo: NVIDIA/Stable-Diffusion-WebUI-TensorRT


text:
Support for Zephyr 7B model

Hi Nvidia Team,
Please add the support for Zepyhr 7B model.
https://huggingface.co/HuggingFaceH4/zephyr-7b-alpha

Thanks for your suggestion.
Let me add it to the list of models that were requested and we will keep you posted.
Juney

Hi @TheCodeWrangler  we have not tested Zephyr so cannot comment. If you do, definitely let us know!

I am hoping to understand what makes a new arch. work/not work with tensorRT-LLM to compile .engine files.

TensorRT-LLM is invariant to hyper-parameters, but not architectural changes. ie, if you want to change the number of layers or heads, that's fine, but if you want to replace GQA with SWA or layernorm with RMSnorm, that requires code changes. You can check out the args of the models you're interested in to see which hyperparams are exposed.

I have heard that the architecture of Zephyr is very similar to LLama. Does tensorRT-LLM not work currently on Zephyr?
I am hoping to understand what makes a new arch. work/not work with tensorRT-LLM to compile .engine files.

Have you tested it?

I have tested a trained Zephyr 7b model extensively today, with no success at all.
I've used an ensemble repository, debugged to see the in- and outputs, however, the generated TensorRT engine doesn't seem to respond when fed the input tokens from the preprocessor/tokenizer.
This I have tested with 2 way Tensor parallelism + 2 way pipeline parallelism, 2 way Tensor parallelism and no parallelism at all, all running on a DGX.
The Engine does actually respond when querying it with the run.py script, which does strike me as odd, so I may have an issue with the actual model setup, so further investigation may be required.

After another round of testing today, the same engine suddenly does seem to work, to the point where I can't replicate the empty response anymore... So I guess there is at least some level of compatibility?

As more and more new models enter the market, we have prepared comprehensive instructions for TRT-LLM developers on adapting to new models of interest. We encourage our community developers to expand the range of supported models, fostering an open ecosystem with rapid iterations.
Please try following these instructions and let us know if you encounter any issues during the adaptation process. We greatly appreciate your dedication.

@laikhtewari

authors: AdamzNV KatarinaMah juney-nvidia ncomly-nvidia nv-guomingz rishabh279 teis-e

repo: NVIDIA/TensorRT-LLM


text:
Incorrect error message when shape is not suitable for fp8 casting

Version: latest stable
import torch
import transformer_engine.pytorch as te
from transformer_engine.common import recipe

# Set dimensions.
in_features = 767
out_features = 3072
hidden_size = 2048

# Initialize model and inputs.
model = te.Linear(in_features, out_features, bias=True)
inp = torch.randn(hidden_size, in_features, device="cuda")

# Create an FP8 recipe. Note: All input args are optional.
fp8_recipe = recipe.DelayedScaling(
    margin=0, interval=1, fp8_format=recipe.Format.E4M3)

# Enable autocasting for the forward pass
with te.fp8_autocast(enabled=True, fp8_recipe=fp8_recipe):
    out = model(inp)

loss = out.sum()
loss.backward()

The error message is
AssertionError: Tensor dimensions are not compatible for FP8 execution: (2048 % 8 != 0, 767 % 16 != 0)

But it is obvious that 2048 % 8 == 0.
https://github.com/NVIDIA/TransformerEngine/blob/b8eea8aaa94bb566c3a12384eda064bda8ac4fd7/transformer_engine/pytorch/utils.py#L216-L224
This function should be improved, as the comment says.

767 % 16 != 0. We should clarify that both conditions are required.

repo: NVIDIA/TransformerEngine


text:
[PyTorch][duplicate][CI] FP8 cuda graphs

This PR adds the following features (high-level):

make_graphed_callables API similar to the PyTorch API with some additional arguments for FP8 usage. Support for fp8 weight caching via existing is_first_microbatchargument is also retained.
Restructuring and amax reduction logic with a simpler design and handling of various parallelisms with minimal book-keeping compared to the previous approach.
Forward and backward amaxes are reduced within the scope of current iteration, solving numerous bugs w.r.t. checkpointing and removing the need to save global buffers.
Support for nested/multiple FP8 autocast contexts with different recipes and distributed groups.
Amax reductions are module independent and happen at at autocast level. This also resolves numerous bugs and allows for support for MoE/LoRA like models.
Redesign of transposes for Float8Tensor that makes the transposes persistent for graph capture. Also fixes use cases for the vanilla optimizers (non fp8-distopt).
The scaling inverses for weight tensors are no longer frozen when caching weights across microbatches.

/te-ci pytorch