Temperature not updating Without opening the ThinQ APP

Hi all,
I've found that my ACs LG did not update the temperature sensors.
If I open the LG ThinQ on the phone it will update automatically on both and in HomeBridge.
This is happening in all AC models?
Thanks
Best Regards

I fixed this issue on v1.7.0, please update

Thanks, works perfect

Hi guys,
I was experiencing the same issue and it still happens after updating to the latest version (v1.8.1).
Did you do something extra to fix it?
Thanks
Roman

@romanarenas is your AC using thinq 1 or thinq 2?

I have the "Enable ThinQ1 support enabled" however I think the ac is  thinq2 since I see this log message: "Start MQTT listener for thinq2 device". Is there a better way to confirm it?

@romanarenas turn on homebridge debug mode and collect some debug logging at startup

Hi,
This problem reappeared.
The temperature cannot be updated unless I enter the LG thinQ App.
Tried versions 1.7.0, 1.8.0 same issue.
Thanks


Jenkins CI apt and yum repos only provides current versions

Platform Ubuntu 12.04.2 & Centos 6.4
Setting default['jenkins']['master']['version'] = "1.555"
I get:
E: Version '1.555' for 'jenkins' was not found
It looks as though Jenkins only shows the current version in their apt repo:
$ apt-cache madison jenkins
   jenkins |      1.557 | http://pkg.jenkins-ci.org/debian/ binary/ Packages
   jenkins | 1.424.6+dfsg-1ubuntu0.2 | http://us.archive.ubuntu.com/ubuntu/ precise-updates/universe amd64 Packages
   jenkins | 1.424.6+dfsg-1ubuntu0.1 | http://security.ubuntu.com/ubuntu/ precise-security/universe amd64 Packages
etc..

This seems most likely an issue that Jenkins doesn't provide anything besides current in the apt repo (and effectively makes package installation unusable as 1.556/7 have a bug with ssh key auth)
I guess I'm opening this bug more for visibility and maybe warn that version and packages cant be used together or am I completely missing something.

This is now a bit of a thorn because Jenkins 2.0 was released and it breaks compatibility with 1.x. Specifically for me, jenkins_plugin 'backup' doesn't work anymore.

superb


Allow filtering/hiding SQL params when using a custom logger implementation

[X] Do only one thing
[ ] Non breaking API changes
[X] Tested

What did this pull request do?
adding a function to interface definition
User Case Description
I have my own implementation of the logger interface, but in my logging I want to hide params when logging in PROD
More
I didn't find a way to set the ParameterizedQueries in config when using my own Logger implementation.

I just saw that params filter is an interface in it self, thank you for the good design I can handle it without this PR


Remove unused variable

A very small fix. If compiling with -Wall -WError it would fail because of the unused variable

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Comparison is base (e93ed4f) 95.28% compared to head (5c1adc5) 97.83%.
Report is 6 commits behind head on main.

:exclamation: Your organization needs to install the Codecov GitHub app to enable full functionality.
Additional details and impacted files
@@            Coverage Diff             @@
##             main      #18      +/-   ##
==========================================
+ Coverage   95.28%   97.83%   +2.54%
==========================================
  Files          16       16
  Lines         276      277       +1
==========================================
+ Hits          263      271       +8
+ Misses         13        6       -7

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.


WebView Overlay

I am trying to implement the webview Overlay to the application, webview is getting added to the camera but it is too very big not matching to the size of camera view..
For live streaming I am using width: 1920 and height: 1080
Not sure what mistake I am doing, any help ?
  var body: some View {
    ZStack {

        let camera = CameraUIView()
        let cameraView = camera.view
        camera.edgesIgnoringSafeArea(.all)

        camera.onAppear {
            rtmpCamera = RtmpCamera(view: cameraView, connectChecker: self)
            rtmpCamera.getStreamClient().setRetries(reTries: 10)
            rtmpCamera.getStreamClient().setAuth(user: "mani", password: "Pr1th1v1")
            rtmpCamera.startPreview(width: 1920, height: 1080)
        }
        camera.onDisappear {
            if (rtmpCamera.isStreaming()) {
                rtmpCamera.stopStream()
            }
            if (rtmpCamera.isOnPreview()) {
                rtmpCamera.stopPreview()
            }
        }

  WebView(url: URL(string: "https://localhost/scoreboard/livescore.html#/123456/preview")!) {
         webView in
          // Handle the WebView after it has loaded
         self.webView = webView

        if !rtmpCamera.isStreaming() && !rtmpCamera.isRecording() {
       // Use the WebView as a filter
        let filterView = ViewFilterRender(view: webView)
          rtmpCamera?.metalInterface.setFilter(baseFilterRender: filterView)
          filterView.setScale(percentX: 100, percentY: 100)
          filterView.translateTo(translation: .CENTER)
      }
  }
 .frame(width: 400, height: 400)
.opacity(0) // Hide the WebView visually, use it only as a filter

My webview code is like this
struct WebView: UIViewRepresentable {
let url: URL
var onWebViewLoaded: ((WKWebView) -> Void)? // Pass WebView reference

class Coordinator: NSObject, WKNavigationDelegate {
    var parent: WebView

    init(parent: WebView) {
        self.parent = parent
    }

    func webView(_ webView: WKWebView, didFinish navigation: WKNavigation!) {
        // Trigger the callback after the WebView has loaded
        parent.onWebViewLoaded?(webView)
    }
}

func makeCoordinator() -> Coordinator {
    return Coordinator(parent: self)
}

func makeUIView(context: Context) -> WKWebView {
    let webView = WKWebView(frame: .zero)

    // Step 1: Set the background to transparent
    webView.backgroundColor = .clear
    webView.isOpaque = false

    // Step 2: Set the web view's content to support transparency in the web page
    let request = URLRequest(url: url)
    webView.load(request)

    webView.navigationDelegate = context.coordinator

    // Modify the page content to have transparent background
    let js = """
    document.body.style.backgroundColor = 'transparent';
    """
    webView.evaluateJavaScript(js, completionHandler: nil)

    return webView
}

func updateUIView(_ uiView: WKWebView, context: Context) {
    // You can update the WebView properties here if needed
}
}

Hello,
This is probably a bug.
Can you share a screenshot as a reference?


Filter bar pill visibility in dark mode

Made the pill background color solid and slightly changed the foreground color. It's more readable now.


Add 'wagtail_update_index' as an alias for the 'update_index' command

Fixes #2447

I'm unable to run the command locally due to an issue with my vagrant-wagtail-develop setup (https://github.com/wagtail/vagrant-wagtail-develop/issues/22), but from a code/docs perspective, this looks spot on.

Okay, local issues sorted, and this is working fine for me. Merge away :)

Thanks @ababic! Now merged in 61e1e4c2f961d854ad8dc679f58174eacdaf940a.


Main menu won't open on Chrome for Android

Describe the bug
On both phanpy.social and dev.phanpy.social viewed on Chrome for Android in portrait orientation, when on any page other than Home, the main menu won't stay open unless at the top of the page and instead scrolls the page upwards with each attempt to open it.
To Reproduce
Steps to reproduce the behavior:

On Chrome for Android in portrait orientation, go to phanpy.social or dev.phanpy.social
Select any view from the main menu other than "Home"
Try to open the main menu; it opens correctly
Scroll down the page, and then slightly up so that the top menu bar shows
Try to open the main menu; it opens but then immediately closes, and the page scrolls slightly up

Expected behavior
The main menu should stay open.
Screenshots
Video showing the behaviour: https://github.com/cheeaun/phanpy/assets/132479092/df247906-26b0-46be-8c27-486c7c57dd75
Smartphone (please complete the following information):

Device: Google Pixel 3
OS: Android 12 (build SP1A.210712.016.C2)
Browser: Chrome (version 113.0.5672.77)

Potential fix deployed in production.

This fixed the issue for me! Many thanks.


RuntimeError in running test_case.py

raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for DeepNano_seq:
Unexpected key(s) in state_dict: "pretrained_model.embeddings.position_ids".
help please? Thanks

Hi Hanlab-OSU,
This bug currently looks as if it is related to huggingface transfermors. Could you please provide more details? For example: does this bug only appear when running test_case.py? Or does it appear when running both test_nai.py and test_ppi_ESM2.py? Are you using the 8M version of the DeepNano-seq model?

It occurs for test_nai.py as well. yes I was using the 8M version of the DeepNano-seq model. Thanks.
##########################在nai数据上测试DeepNano-seq(DScriptData)esm2_t6_8M_UR50D模型：
Some weights of EsmModel were not initialized from the model checkpoint at ./models/esm2_t6_8M_UR50D and are newly initialized: ['esm.pooler.dense.bias', 'esm.pooler.dense.weight']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
Traceback (most recent call last):
File "/home/xx/DeepNano/test_nai.py", line 89, in
model.load_state_dict(weights)
File "/home/xx/miniconda3/lib/python3.12/site-packages/torch/nn/modules/module.py", line 2189, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for DeepNano_seq:
Unexpected key(s) in state_dict: "pretrained_model.embeddings.position_ids".

I finally got it to work by installing the requirement.txt and torch=1.13.1+cu116. Also i need to downgrade numpy to 1.26.4


how do I verify arguments passed to the stub ?

In code below I would like to check the params that I passed to the stubbed function..
const sinon = require('sinon');
var sinonStubPromise = require('sinon-stub-promise');
sinonStubPromise(sinon);
var serviceRequest = require("../../mysql/models")['ServiceRequest'];
var providerRequest = require("../../mysql/models")['ProviderRequest'];
var serviceRequestCreateStub = sinon.stub(serviceRequest, 'create');
var providerRequestCreateStub = sinon.stub(providerRequest, 'create');
...
...
serviceRequestCreateStub.callsFake(function(obj){ /* would like to verify that obj passed in was correct here*/}).returnsPromise().resolves({},true);

I'm not exactly sure what you are trying to do. The documentation for callsFake seems like it just allows you to override the behavior of the stub when invoked.
In order to verify that your stub was called with the correct args, you could do myStub.withArgs(obj).returnsPromise().resolves({}, true).
Hope that helps!

thanks, I got it to work @astephenb
btw I notice that when the args are not called properly that the error message is pretty bad and not very easy to diagnose
providerRequestCreateStub.withArgs({
vroomMessageUuid: messages[0].data.attributes.messageUuid,
recipient: messages[0].data.attributes.to,
timestamp: sinon.match.any,
twilioMessageSid: "12345678"
}).returnsPromise().resolves({},true);
is there anyway to tell it to give a more meaningful error message ? thanks


不能支持gpt4吗？

Have you found the answer to this question please, I would also like to know this.

请问支持gpt4吗


Push to Vimeo live

Streaming to Facebook works ok but I can't get streaming to Vimeo live working.
Any advice or help would be appreciated :)
(the stream keys are not active)
This is my config:
worker_processes auto;
rtmp_auto_push on;
events {}
rtmp {
server {
listen 1935;
listen [::]:1935 ipv6only=on;
    application live {
        live on;
        record off;
    }

    application send {
            live on;
            record off;
            push rtmp://live-api-s.facebook.com:80/rtmp/1878372137817090?ds=1&s_sw=0&s_vt=api-s&a=AThn60865qcGnwB5;
            push rtmp://rtmp-global.cloud.vimeo.com/live/3b5890ea-9542-4717-857d-f3458001bab8?token=6d81e5cc-7c91-4e16-b32c-3450376d70cd;
    }
}

}

I think you can push twice in 1 resource. Maybe
exec_push ffmpeg -i rtmp://localhost/send/$name
              -c:a copy -b:a copy  -c:v copy -b:v copy -f flv <facebook-rtmp-link>
             -c:a copy -b:a copy  -c:v copy -b:v copy -f flv <vimeo-rtmp-link>;

p/s: Remember install ffmpeg and read this for more information https://trac.ffmpeg.org/wiki/Creating%20multiple%20outputs

Hi, and thank you for your suggestions.
Unfortunately, even with only the Vimeo push in the setup, It's not working.

I use OBS as a client and when I stream directly to vimeo everything works.
But when I try to use Nginx as a stream splitter for both Facebook and
Vimeo it fails.
I'm not sure I understand what you mean by  checking the secure or private
setting of Vimeo.
Do you mean the security settings for access to the broadcast on Vimeo?
On Fri, Aug 17, 2018 at 6:06 PM, Nguyễn Hiển<EMAIL_ADDRESS>wrote:

Oh. I see requirement this. How about your config ?
Codec H.264
Output resolution of 1920 x 1080 (maximum)
Frame rate of 60 fps (maximum)
Key frame interval of 2 seconds
And maybe you need check setting secure or private of Vimeo.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/arut/nginx-rtmp-module/issues/1306#issuecomment-413912944,
or mute the thread
https://github.com/notifications/unsubscribe-auth/ABm0nFoIzCpu5_EPnAdNspT3rYb69e8Dks5uRuoIgaJpZM4V-pFf
.

Do you mean the security settings for access to the broadcast on Vimeo? -> I'm not sure for it.
I also have problem with ffmpeg transcoding in nginx-rtmp. Sometimes ffmpeg not work although log of nginx show for me it receive data. But not transcoding it. Are you try use nginx-rtmp + ffmpeg for redirect something and install ffmpeg in your (local) vps ?
P/s: I think you should remove some key or link in your question.

I'm not really trying to do anything fancy.
My main goal was to relay my videostream to two services at the same time.
No transcoding, just a basic forward of data.
And don't worry the keys are altered and would be of no use anyways as they
are one-time keys.
:)
On Fri, Aug 17, 2018 at 7:38 PM, Nguyễn Hiển<EMAIL_ADDRESS>wrote:

Do you mean the security settings for access to the broadcast on Vimeo?
-> I'm not sure for it.
I also have problem with ffmpeg transcoding in nginx-rtmp. Sometimes
ffmpeg not work although log of nginx show for me it receive data. But not
transcoding it. Are you try use nginx-rtmp + ffmpeg for redirect something
and install ffmpeg in your (local) vps ?
P/s: I think you should remove some key or link in your question.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/arut/nginx-rtmp-module/issues/1306#issuecomment-413937552,
or mute the thread
https://github.com/notifications/unsubscribe-auth/ABm0nCDg69t5kydmFff7Ksq-cc7PQm0bks5uRv96gaJpZM4V-pFf
.

You can try again with
buflen 5s; # in scope server


changes to the info/rules interface

added some spacing between lines so it does not look like a giant wall of text as much

The adding of paragraphs to each item is semantically questionable, complicates the DOM, and - in the case of contained sub-lists - is incorrect.
This would probably be better implemented in CSS which is the appropriate place to implement purely visual changes such as this. This could be as a general change to the display of ordered list items or using a class.

Will do. Haven't had much time to work on this lately but shouldn’t take long

Closed due to inactivity.


ClusterOperatorStatusController: Add WaitForCacheSync

Without this PR, during upgrades, components that utilize the ClusterOperatorStatusController
(authentication and service-ca) will see a glitch in reporting cluster operator version
during upgrades.  Instead of deleting cluster operator from cluster when not found via
operatorClient, wait for the operatorClient informer to catch up.

/lgtm

/approve


Updated code for dynamic banner and playlist for a better user experi…

…ence

First thing, PLEASE READ THIS: ReactPlay Code Review Checklist

Fixes https://github.com/reactplay/react-play/issues/1064
Fixes https://github.com/reactplay/react-play/pull/1075
Description
The current playlist has 5 steps we can count to display the playlist page.
2 of these steps are repeated.
With some modification, we can take these 2 steps.
*Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.
Take of randomIndex, as it's a value just use to get a random index, no need to use a state for it, and we can just add it
in the display banner. It seems to have an incidence on the homepage as if we let it and console.log in the component, we can have a console.log less without this useState.
Sometimes, on the website, we have a "loading..." that can be on the page. It's because the banner is not found, and the code goes to the catch error.
As the loading is not set to false here, the message keeps showing itself.
The code resolves this issue too.
The logic with if/else in the component is to be sure that if a condition is not met, no render is done.
So you can't have the loader and at the same time the dynamic banner if no play.
No typecasting, the plays are directly defined as an array, and not null so we have no problem using the length properties on it.
Redefine the key in the map for the playlist as the index is not a good practice and leed to some errors.
Take off the fragment in the map as they are not needed.
Fixes # (issue)
Type of change
Please delete options that are not relevant.

[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)
[ ] This change requires a documentation update

How Has This Been Tested?
1/ Downloaded the last version of ReactPlay online to work with.
2/ Made modifications in src/common/playlists./PlayList.jsx and DynamicBanner.jsx. Dynamic banner is only used in PlayList
3/ Compared result behavior with the online website (view screencast ) before change with online/local and after modifications on local.
Please describe the tests that you ran to verify your changes. Provide instructions so we can reproduce.
Compared behavior of online websites with local.
Tested search with name and filters.
Go back from play.
Cancel Search by name ( click on X ).
Checklist:

[X] I have performed a self-review of my own code
[X] I have commented my code, particularly in hard-to-understand areas
[ ] I have made corresponding changes to the documentation
[X] My changes generate no new warnings and fewer react error
[X] I have added tests that prove my fix is effective or that my feature works
[ ] New and existing unit tests pass locally with my changes
[ ] Any dependent changes have been merged and published in downstream modules

Screenshots or example output
https://watch.screencastify.com/v/4Ysc9Fud8vz3zz1ICqeK

This brach has conflicts error. PLease resolve it

@Angra974 , Build is failing, can you check?

@Angra974 , Build is failing, can you check?

Look where the change was made. No relation with code in plays.

The branch need to be updated from main

I'm on some push tonight. Will refresh this one.

Closed the PR as i started a new one. Get the plays mixed in the push so i created a clean one.


ShlomiShitrit/issue18 - add custom messages

Fix #18

add custome messages for:

"Enter 1 to continue"
Result messages

Also:

Add as many intro messages as wanted
Option to change the display name of attribute

I think the option to change the display name of an attribute should be in another issue, I will open one now,
The rest tasks have been done.
Waiting for  your review @nadavWeisler


[feature request] Close image viewer on 'Esc' click and when we click out of image bounds

Hi!
I'm using your library in my project and it works great. Thank you for the great work here 😁
Is there any chance we could have support for dismissing the gallery view when we press the 'ESC' key or when we click on the lightbox, outside of the image bounds?
Thanks!

Hi
Thanks for the feedback @ruialmeida51 👌
Sure, I'm a bit busy lately, but I will add it soon...

I'll keep an eye out for the issue. Take your time!
For now I'm listening to the 'ESC' key in the page and dismissing the image viewer as a workaround. Can't do much about clicking outside of the image to dismiss tho, I'm still too fresh in front-end development to be able to properly change the lib's source code haha 😄
Thanks for getting back to me! 😁

That's a good temporary solution for now. ￼
But I will let you know when I have done it.

@MostafaMDZH, thanks for this project.
It helps a lot to be honest.
I stumbled upon this project today and was thinking about the same problem that this issue has raised,
And totally understand you may not be free to update this personal project of yours. Do you want a helping hand I would love to look at it and address the feature requests in this issue. Those are the same features that I wish this project had.


Allow object to be passed to sqlite.openDatabase

This is to support the location option that the sqlite plugin supports.
See https://github.com/brodysoft/Cordova-SQLitePlugin#opening-a-database

Ahh same work has been done in #653


Add support for dry-system 0.20.0

👋 Hi all,
Follow up on discussion on dry-rb discourse
This PR makes all necessary changes to support latest dry-rb stack (namely, dry-system 0.20.0)

Removed all methods from Dry::Rails::Container that were removed from Dry::Sytem::Container
Removed unused config options
Changed old dry-configurable syntax (include default: key)
Changed old syntax to new component_dirs.add instead of auto_register!
~Wrap adding new dir-s in rescue in spec-s, seems like .add is a bit more strict than auto_register!~ 🤔

☝ changed the approach here, check below

Clean-up specs a bit because it didn't make sense to test functionality that now is in dry-system, kept specs that check if configuration still works as expected, but I'm not re-testing what's already (I guess 😅) tested in underlying gems
Removed MRI 2.5 and JRuby from CI workflow, not used in dry-system as well, and dry-rails requires >=2.6.0

Thanks for the feedback 🙇♂

Tested with my company app, everything work like a charm and removes all deprecation warning :heart_eyes:

BTW, this fixes the problem
require "dry/system/loader/autoloading"

Dry::Rails.container do
  config.component_dirs.add "app/operations" do |dir|
    dir.loader = Dry::System::Loader::Autoloading
  end
end

@timriley Hey! Is there anything we can help with to push this forward?

@pusewicz 👋🏻 I'll help with getting this merged in and released

@pusewicz done https://github.com/dry-rb/dry-rails/releases/tag/v0.4.0

@zlw & @solnic Thanks!


feat(cat): add cat

Implemented
  -A, --show-all            equivalent to -vET
  -b, --number-nonblank     Number the lines, but don't count blank lines, override -n
  -e                        equivalent to -vE
  -E, --show-ends           display $ at end of each line
  -n, --number              Number the output lines, starting at 1.
  -s, --sqeeze-blank        Squeeze multiple adjacent empty lines, causing the output to be single spaced
  -t                        Print tab characters as ‘^I’. Implies the -v option to display non-printing characters
  -T                        equivalent to -vT
  -u                        (ignored)
  --help                    display this help and exit
  --version                 output version information and exit

not yet
  -v, --show-nonprinting    use ^ and M- notation, except for LFD and TAB

Known Issues
stdin  doesn't handle 'line by line'

@JalonSolov resolved


Texture::loadFromImage() result is discarded in Font.cpp and Texture.cpp

Hi.
There're a few cases in Font.cpp and Texture.cpp where there's no checking whether or not the method
Texture::loadFromImage

returns true, for example:
 //in Font.cpp
 texture.loadFromImage(image);
 page.texture.loadFromImage(newImage);

 //in Texture.cpp, copy-ctor
 if (copy.m_texture)
    loadFromImage(copy.copyToImage());

Was it intentional?

Texture::loadFromImage can only fail if the size is either (0, 0) or greater than the maximum texture size supported by the GPU.
Now let's analyze the cases where it is not checked:

Texture copy constructor: if the source texture is valid, then obviously creating a texture with the same size is valid too, therefore loadFromImage can't fail; another point is that we wouldn't have any way to signal a failure in a constructor without exceptions :)

Font, texture.loadFromImage: the size is 2x2, which is not zero and way less than the maximum supported size -> cannot fail

Font, page.texture.loadFromImage: the size is checked against the maximum supported size, so again, it cannot fail


Infinite loop when files have the same name but only differ in casing

Bug description
If two files have the same name but only differ in casing, (e.g: Gamemanager.cs.meta & GameManager.cs.meta), it will trigger a loop where Unity will attempt to import the files, print a warning/error, and repeat.
How to reproduce

Copy a file in the project and give it an identical name, with different casing (e.g: Gamemanager.cs.meta & GameManager.cs.meta)
Run tests with unity-test-runner

Expected behavior

Ideally, the test runner will simply ignore one of the files, or support case-sensitive file names, and continue as normal
Alternately, the test runner would quit with an error when this error is encountered
If possible, worst case: Detect that no progress is being made, and cancel the test with an error

Additional details
In my case, this happened due to renaming a class and its associated file.
Assets/GotoGames/Components/Utils/GameobjectExtensions.cs → Assets/GotoGames/Components/Utils/GameObjectExtensions.cs
(Note the "o" of Gameobject becoming an "O": GameObject)
The meta file was correctly renamed, but a new meta file with the old name was also added to the commit. I did not catch this new addition, and pushed this to the repo.
The test process ran for six hours before being killed by GitHub actions, filling a log file with 46 Megabytes worth of:
    Assets/GotoGames/Components/Utils/GameobjectExtensions.cs.meta
    Assets/GotoGames/Components/Utils/GameObjectExtensions.cs.meta
Case sensitive file systems are not fully supported, please move or rename these files.
(Filename: ./Modules/AssetDatabase/Editor/V2/SourceAssetDB.cpp Line: 829)

The following files have the same name but only differ in casing and will be ignored:
    Assets/GotoGames/Components/Utils/GameobjectExtensions.cs.meta
    Assets/GotoGames/Components/Utils/GameObjectExtensions.cs.meta
Case sensitive file systems are not fully supported, please move or rename these files.
(Filename: ./Modules/AssetDatabase/Editor/V2/SourceAssetDB.cpp Line: 829)

The following files have the same name but only differ in casing and will be ignored:
    Assets/GotoGames/Components/Utils/GameobjectExtensions.cs.meta
    Assets/GotoGames/Components/Utils/GameObjectExtensions.cs.meta
Case sensitive file systems are not fully supported, please move or rename these files.
(Filename: ./Modules/AssetDatabase/Editor/V2/SourceAssetDB.cpp Line: 829)```

I don't know if this is a game-ci issue or a Unity issue, the real fix might need to come from up-stream


test/mdc2test.c: Remove unused OSSL_PROVIDER

Since the 'prov' is not used after initialization,
it should be better to remove it.
Signed-off-by: Jiasheng Jiang<EMAIL_ADDRESS>
Checklist

[ ] documentation is added or updated
[ ] tests are added or updated

This is wrong. The OSSL_PROVIDER_load() has a side effect of loading the provider into the library context.


[Feature Request]: Ignore specific CSS properties

Hi, and thanks for the helpful extension!
This is more of an idea/feature request.
It would be great to have a setting to ignore specific properties.
I'm working on a project where we don't replace some properties with their respective logical ones (e.g., min-width, max-width)
Having an ignore list would help reduce the warnings in the problems list and leverage the replacement of all functionality more efficiently.

@patriziosotgiu
I just released a new version that adds a configuration setting called ignoreList that lets you ignore certain css properties.  Install the update and let me know what you think.


Using system-wide 125% scaling makes java applications bloated.

Platform: Windows 10
Architecture: x64
I set my windows dpi on the (recommended) 125%, since i have a 15" laptop with 1920:1080 resolution. Everything is tiny if I don't do this.
https://i.imgur.com/qLBYCcM.png
If I open the prepackaged runelite.exe (a client for a game written in java), which has java included, without touching the dpi settings, it blows it up to 125%, which is what should happen, but not what I want.
If I select the bottom checkmark, and set it to "application", it goes back to regular crisp 100%.
https://i.imgur.com/a3gDszE.png
But if I use the runelite.jar file, and it uses my computer's java installation, which is currently AdoptOpenJdk 13, I can't have it go to 100%. It's always 125%.
Highdpi setting changed runelite.exe in front, highdpi settings for "java.exe" and "javaw.exe" changed runelite.jar in the back: https://i.imgur.com/V9nzXm8.png
Compatibility settings on both are the same.
I can change the size of the .jar one, but that just crops the client: https://i.imgur.com/n6mBoql.png
This happens with every .jar file. I'm at my wit's end.
Another piece of information is that it used to work with an earlier version of java. (Might be java 8)
But newer applications required at least java 11, and that's where I am now.

@JeljoGb Have you tried with the adoptopenjdk.net/upstream.html build?

Could you explain to me how I should install that?
I tried opening the .jar with the javaw.exe in that package, but that did nothing.
Do I have to put the files somewhere specific?

@jerboaa - should the javaw from the upstream builds just work out of the box?  I'd have thought so.

Could you explain to me how I should install that?

Download the zip and extract it somewhere. Then use the full path to bin/java.exe -jar <jar>?

I tried opening the .jar with the javaw.exe in that package, but that did nothing.

Sorry, I'm not a Windows person. @stooke might be able to help with that. Not sure what javaw.exe is.

Do I have to put the files somewhere specific?

I don't think so.

@jerboaa - should the javaw from the upstream builds just work out of the box? I'd have thought so.

Not sure what javaw is, sorry.


Different ways to create Objects in Java

We ask that you please be patient as our team works through approving and publishing all articles/tutorials in a timely manner. Allow 1-3 days for a topic to be reviewed and/or approved - allow 3-7 days for an articles to be reviewed and/or published.
Be sure to visit our Resources Page for tools, resources, and example articles to go over.
NOTE: (Please ensure that you have only one open issue + linked pull request at a time. This will ensure that we complete the article in a timely manner from inception to publishing.)
NOTE: We tend to stray away or tend not to publish reviews/comparisons of commercial product offerings.
We're looking for the first 2-3 paragraphs of the article that appropriately summarize what your article will be about.
Proposed title of article
Different ways to create objects in Java
Introduction paragraph (2-3 paragraphs):
Java is an object-oriented language, everything revolve around the object. We know that without creating and instantiating object there is no use of creating a class.
An object represents runtime entity of a class and is essential to call variables and methods of the class. In this article, we will discuss 5 different ways to create an Object in Java :

Using a new keyword - This is the most popular way of creating an object in java , almost every Java Developer knows this methodology.
Using newInstance() method of Class class
Using newInstance() method of Constructor class
Using Object Deserialization
Using clone() method

Key takeaways:

What is an object and its characteristics
Different ways to create an object
Discussing each method of creating an object with examples

References:
N/A

@mosesmwangi442 seems like a helpful topic - lets please be sure it add value beyond what is in the official docs and that it does not overlap with any existing EngEd articles or incoming topic suggestions (if you haven't already). - approved


{BUG} ATEM Module "Null" Status, cannot edit, unusable

Programming companion all of yesterday. Came back on this morning and none of the buttons I programmed were working. Looked at the GUI, showed my atem module as "null". Every time I try to edit the instance, or edit a button, I get a javascript error window that says cannot read instance of null. I am version 2.2.0.

This looks like a bug in the core of companion. It looks like your config has gotten into an invalid state, and companion is not currently able to recover from this.

This looks like a bug in the core of companion. It looks like your config has gotten into an invalid state, and companion is not currently able to recover from this.


Pre-release PR

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

486 of 600 (81.0%)  changed or added relevant lines in 39 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage decreased (-1.5%) to 89.932%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

pygod/metrics/metrics.py
18
19
94.74%

pygod/test/test_anomalous.py
65
66
98.48%

pygod/test/test_radar.py
65
66
98.48%

pygod/test/test_basic_nn.py
26
29
89.66%

pygod/models/anomalous.py
62
67
92.54%

pygod/models/gaan.py
65
70
92.86%

pygod/models/radar.py
62
67
92.54%

pygod/utils/utility.py
4
23
17.39%

pygod/models/scan.py
21
95
22.11%

Totals

Change from base Build<PHONE_NUMBER>:
-1.5%

Covered Lines:
3591

Relevant Lines:
3993

💛  - Coveralls


Investigate use of pxshm in CmiAlloc

Original issue: https://charm.cs.illinois.edu/redmine/issues/1478

Currently, when the runtime is built with pxshm support, we use an extra copy into a posix shared memory buffer when we know that the recipient is on the same host but not the same OS process. We can potentially avoid that if we can just make all messages be allocated in posix shared memory to begin with

Original date: 2017-10-31 04:16:34

CMA doesn't require registration of any kind, and we are moving toward using it rather than pxshm.


🐛 [Bug] An wrong function call for torch._C._jit_to_tensorrt on spec in tutorial code.

Bug Description
This is a bug in a tutorial below.

Web: https://nvidia.github.io/TRTorch/tutorials/use_from_pytorch.html
Original ReST doc: https://github.com/NVIDIA/TRTorch/blob/51a2043217a3f6c93f393169961750733c0d26ec/docsrc/tutorials/use_from_pytorch.rst

To compile a model, torch._C._jit_to_tensorrt() is called with two parameters, script_model._c and spec.
But, a following error happened.
Traceback (most recent call last):
  File "simple.py", line 34, in <module>
    main()
  File "simple.py", line 27, in main
    trt_model = torch._C._jit_to_tensorrt(script_model._c, spec)
RuntimeError: The following operation failed in the TorchScript interpreter.
Traceback of TorchScript (most recent call last):
  File "<string>", line 6, in __setstate__
                self.__processed_module = state[1]
                self.__create_backend()
                self.__handles = self.__backend.compile(self.__processed_module, self.__method_compile_spec)
                                 ~~~~~~~~~~~~~~~~~~~~~~ <--- HERE

RuntimeError: isGenericDict() INTERNAL ASSERT FAILED at "/opt/python/cp36-cp36m/lib/python3.6/site-packages/torch/include/ATen/core/ivalue_inl.h":830, please report a bug to PyTorch. Expected GenericDict but got Object

This error looks like caused by wrong parameter. In test code (https://github.com/NVIDIA/TRTorch/blob/b93627ecc7bb7123d2e32aff9d762dd0e6bc3166/tests/py/test_to_backend_api.py), this API is called with a different parameter like below. It looks like making additional dict with forward key is necessary.
trt_model = torch._C._jit_to_tensorrt(script_model._c, {'forward': spec})

To Reproduce
Steps to reproduce the behavior:

Launch NGC TRT container, nvcr.io/nvidia/tensorrt:20.03-py3.
Install required libraries

pip install https://github.com/NVIDIA/TRTorch/releases/download/v0.1.0/trtorch-0.1.0-cp36-cp36m-linux_x86_64.whl torchvision==0.7.0

Run each step described in the tutorial.

My repro code is below. Note that I modified the tutorial code to use FP32 for test.
import torch
import trtorch
import torchvision.models as models

def main():
    model = models.mobilenet_v2(pretrained=True)
    script_model = torch.jit.script(model)

    spec = {
        "forward": trtorch.TensorRTCompileSpec({
            "input_shapes": [[1, 3, 300, 300]],
            "op_precision": torch.float32,
            "refit": False,
            "debug": False,
            "strict_types": False,
            "allow_gpu_fallback": True,
            "device_type": "gpu",
            "capability": trtorch.EngineCapability.default,
            "num_min_timing_iters": 2,
            "num_avg_timing_iters": 1,
            "max_batch_size": 0,
        })
    }
    # trt_model = torch._C._jit_to_tensorrt(script_model._c, {'forward': spec})
    trt_model = torch._C._jit_to_tensorrt(script_model._c, spec)

    x = torch.randn((1, 3, 300, 300)).to('cuda').to(torch.float32)
    print(trt_model.forward(x))

if __name__ == '__main__':
    main()

Expected behavior
No exception.
Environment

Build information about the TRTorch compiler can be found by turning on debug messages

PyTorch Version (e.g., 1.0): 1.6.0
CPU Architecture: Intel(R) Core(TM) i7-6850K
OS (e.g., Linux): Ubuntu 18.04.5 LTS (host) / Ubuntu 18.04.4 LTS (container)
How you installed PyTorch (conda, pip, libtorch, source): pip
Build command you used (if compiling from source): N/A
Are you using local sources or building from archives: N/A
Python version: 3.6.9
CUDA version: 10.2.89
GPU models and configuration: TitanX (Pascal)
Any other relevant information: N/A

Additional context
N/A

It seems like to me there might be some confusing variable names. spec in the test is of type trtorch.TensorRTCompileSpec, torch._C._jit_to_tensorrt takes a torch._C.ScriptModule and a Dictionary { str : torch.TensorRTCompileSpec }. So in the test we need to make a dictionary {'forward': spec}. Hence
trt_model = torch._C._jit_to_tensorrt(script_model._c, {'forward': spec})

spec in the docs unless I am misreading it is itself a Dictionary { str : trtorch.TensorRTCompileSpec } so we should be able to call it with
trt_model = torch._C._jit_to_tensorrt(script_model._c, spec)

as shown in the documentation (https://nvidia.github.io/TRTorch/tutorials/use_from_pytorch.html).
It would probably be a good idea to change the name of one of these to avoid confusion.

It seems like to me there might be some confusing variable names. spec in the test is of type trtorch.TensorRTCompileSpec, torch._C._jit_to_tensorrt takes a torch._C.ScriptModule and a Dictionary { str : torch.TensorRTCompileSpec }. So in the test we need to make a dictionary {'forward': spec}. Hence
trt_model = torch._C._jit_to_tensorrt(script_model._c, {'forward': spec})

spec in the docs unless I am misreading it is itself a Dictionary { str : trtorch.TensorRTCompileSpec } so we should be able to call it with
trt_model = torch._C._jit_to_tensorrt(script_model._c, spec)

as shown in the documentation (https://nvidia.github.io/TRTorch/tutorials/use_from_pytorch.html).
It would probably be a good idea to change the name of one of these to avoid confusion.

Let me add one comment about spec in the test code.
It is defined like below therefore current torch._C._jit_to_tensorrt seems to take a Dictionary { str : { str : torch.TensorRTCompileSpec }} instead of simple { str : torch.TensorRTCompileSpec }.
https://github.com/NVIDIA/TRTorch/blob/b93627ecc7bb7123d2e32aff9d762dd0e6bc3166/tests/py/test_to_backend_api.py#L14-L29
Is that expected?

Let me add one comment about spec in the test code.
It is defined like below therefore current torch._C._jit_to_tensorrt seems to take a Dictionary { str : { str : torch.TensorRTCompileSpec }} instead of simple { str : torch.TensorRTCompileSpec }.
https://github.com/NVIDIA/TRTorch/blob/b93627ecc7bb7123d2e32aff9d762dd0e6bc3166/tests/py/test_to_backend_api.py#L14-L29
Is that expected?

Yeah there was an issue with an expected nested dict. It should be fixed now in master. Note the API in PyTorch has changed in 1.7 to trt_model = torch._C._jit_to_backend("tensorrt", script_model, spec)

Yeah there was an issue with an expected nested dict. It should be fixed now in master. Note the API in PyTorch has changed in 1.7 to trt_model = torch._C._jit_to_backend("tensorrt", script_model, spec)


Doesn't work with express

It is a very interesting idea of super fast http server :). But unfortunately it is crashes on every request on different places. I'm using node v8.9.4.
When I try to use turbo-http with express everything is crashed.
$ npm i express-generator -g
$ mkdir turbu;
$ cd turbo
$ express
  create : .
   create : ./package.json
   create : ./app.js
   create : ./public
   create : ./routes
   create : ./routes/index.js
   create : ./routes/users.js
   create : ./views
   create : ./views/index.jade
   create : ./views/layout.jade
   create : ./views/error.jade
   create : ./bin
   create : ./bin/www
   create : ./public/javascripts
   create : ./public/images
   create : ./public/stylesheets
   create : ./public/stylesheets/style.css

$ npm i @mafintosh/turbo-http

I Changed in bin/www: http -> @mafintosh/turbo-http.
And after start and making request I see:
coderaiser@cloudcmd:~/2$ node bin/www
(node:12532) Warning: N-API is an experimental feature and could change at any time.
/home/coderaiser/2/node_modules/finalhandler/index.js:130
      req.socket.destroy()
                 ^

TypeError: req.socket.destroy is not a function
    at Immediate.<anonymous> (/home/coderaiser/2/node_modules/finalhandler/index.js:130:18)
    at Immediate._onImmediate (/home/coderaiser/2/node_modules/express/lib/router/index.js:635:15)
    at runCallback (timers.js:791:20)
    at tryOnImmediate (timers.js:751:5)
    at processImmediate [as _immediateCallback] (timers.js:722:5)

When I try to use turbo-http in edward error was:
/home/coderaiser/edward/node_modules/send/index.js:613
  var ranges = req.headers.range
                           ^

TypeError: Cannot read property 'range' of undefined
    at SendStream.send (/home/coderaiser/edward/node_modules/send/index.js:613:28)
    at /home/coderaiser/edward/node_modules/send/index.js:775:12
    at FSReqWrap.oncomplete (fs.js:153:5)

When I try to use it with cloudcmd I got:
coderaiser@cloudcmd:~/cloudcmd$ node bin/cloudcmd.js
(node:12906) Warning: N-API is an experimental feature and could change at any time.
url: http://localhost:31337/
_stream_readable.js:718
  if (state.pipesCount === 0)
            ^

TypeError: Cannot read property 'pipesCount' of undefined
    at Request.Readable.unpipe (_stream_readable.js:718:13)
    at unpipe (/home/coderaiser/cloudcmd/node_modules/unpipe/index.js:47:12)
    at send (/home/coderaiser/cloudcmd/node_modules/finalhandler/index.js:289:3)
    at Immediate.<anonymous> (/home/coderaiser/cloudcmd/node_modules/finalhandler/index.js:135:5)
    at Immediate._onImmediate (/home/coderaiser/cloudcmd/node_modules/express/lib/router/index.js:635:15)
    at runCallback (timers.js:791:20)
    at tryOnImmediate (timers.js:751:5)
    at processImmediate [as _immediateCallback] (timers.js:722:5)

Would be great to have ability to use turbo-http with express :)

The API is different in places from Node.js core. It most likely will never be fully compatible for perf reasons. What should happen (ideally...) would be for new cool JSON api frameworks to be built on top :)

@mafintosh @lukeed I'm currently testing both polka & turbo-http with Nest. Cool stuff 🙂

@coderaiser I started writing theodore which uses turbo-http and has a similar api as express. Of course it's missing a bunch of stuff, but does the basics right now.

@lukeed -A little late on this one but how did that testing with polka go?
I gave it a run with rayo and I was able to pass some basic tests, will do some more testing in the next couple of days and report back... Curious to hear your findings though.

@aichholzer how did the tests go? Any numbers to show? I especially would love to see how much responses per second can be generated on a 512MB RAM 1 Core benchmark environment

It seems that ranges aren't implemented yet.


Elarian documentation tutorial

The customer Number is returned as Null following the syntax provided

Alternative

Content has been updated, nice catch 👍🏿


open project cannot open embedded link

Should be able to parse the embedded link id and open it. Needed for Windows 10.

Fixed by issue #124


Migrate to Whatsapp-web.js Module, baileys Depreciated, in that state baileys module will more likely make your account get banned by WA

Can we Migrate this project to use Whatsapp-web.js because of baileys discontinuation

Can we Migrate this project to use Whatsapp-web.js because of baileys discontinuation

no migration, just use `"@adiwajshing/baileys": "github:WhiskeySockets/Baileys", change in your package.json.
I know it's not allready, but, it's the recomendation. or... if you need more stable using 4.4.0 but it's not a recomendation.


The maker does not reconnect after losing the WebSocket connection to BitMEX

When the maker loses connection to the WebSocket, it does not try to reconnect. As a result, we do not send any limit orders anymore.
Only the scheduled restart fixes that.
{"timestamp":"2023-07-05T21:22:15.109143768Z","level":"DEBUG","fields":{"message":"Received new quote","bid":"30436","ask":"30436.5","timestamp":"2023-07-05 21:22:00.0 +00:00:00","symbol":"btcusd"},"target":"maker::trading::bitmex_client"}
{"timestamp":"2023-07-05T21:22:15.109175842Z","level":"DEBUG","fields":{"message":"Received new quote Quote { timestamp: \"2023-07-05T21:22:00Z\", bid: 30436, ask: 30436.5 }"},"target":"maker::trading"}
{"timestamp":"2023-07-05T21:23:11.387348853Z","level":"DEBUG","fields":{"message":"Received close frame: Some(CloseFrame { code: Away, reason: \"CloudFlare WebSocket proxy restarting\" })","log.target":"tungstenite::protocol","log.module_path":"tungstenite::protocol","log.file":"/home/runner/.cargo/registry/src/index.crates.io-6f17d22bba15001f/tungstenite-0.18.0/src/protocol/mod.rs","log.line":556},"target":"tungstenite::protocol"}
{"timestamp":"2023-07-05T21:23:11.387384049Z","level":"DEBUG","fields":{"message":"Replying to close with Frame { header: FrameHeader { is_final: true, rsv1: false, rsv2: false, rsv3: false, opcode: Control(Close), mask: None }, payload: [3, 233, 67, 108, 111, 117, 100, 70, 108, 97, 114, 101, 32, 87, 101, 98, 83, 111, 99, 107, 101, 116, 32, 112, 114, 111, 120, 121, 32, 114, 101, 115, 116, 97, 114, 116, 105, 110, 103] }","log.target":"tungstenite::protocol","log.module_path":"tungstenite::protocol","log.file":"/home/runner/.cargo/registry/src/index.crates.io-6f17d22bba15001f/tungstenite-0.18.0/src/protocol/mod.rs","log.line":573},"target":"tungstenite::protocol"}

this might be the sole reason we need scheduled restarts? 😔

This log has been recorded just recently:
{"timestamp":"2023-07-13T04:59:50.864804022Z","level":"DEBUG","fields":{"message":"Received close frame: Some(CloseFrame { code: Normal, reason: \"Bye\" })","log.target":"tungstenite::protocol","log.module_path":"tungstenite::protocol","log.file":"/home/runner/.cargo/registry/src/index.crates.io-6f17d22bba15001f/tungstenite-0.18.0/src/protocol/mod.rs","log.line":556},"target":"tungstenite::protocol"}

Is this reproducible locally or no?

I suppose I can just pull out my ethernet cable :wink:


Issue with program containing Float32List

What happened?
I created the following program in Dart Pad:
import 'dart:typed_data' ;
import 'dart:math';

extension type Vector3(Float32List storage) {

  Vector3.zero() : storage = new Float32List.fromList([0.0, 0.0, 0.0]);

  double get length => sqrt(storage[0] * storage[0] + storage[1] * storage[1] + storage[2] * storage[2]);

}

void main() {
  final v0 = new Vector3.zero();

   print(v0.length);
}

It runs with the Dart VM on Dart SDK version: 3.3.1 (stable) (Wed Mar 6 13:09:19 2024 +0000) on "macos_arm64" . However it fails with an error in Dart Pad:
Uncaught TypeError: typed_data.Float32List.fromList is not a function, error: TypeError: typed_data.Float32List.fromList is not a function

Steps to reproduce problem

Paste the code above
Press run

Additional info
Browser
Browser: Chrome
Version: Based on Dart SDK 3.0.0 and Flutter SDK 3.19.2
Are you using any extensions/plugins that affect website behavior
(particularly those that affect iframes, such as ad blockers)?
Are there any warnings or errors in your browser's JavaScript console?
If so, paste them below:
VM302:64 Uncaught TypeError: typed_data.Float32List.fromList is not a function
    at Object.Vector3$124constructor$35zero [as Vector3|constructor#zero] (<anonymous>:64:40)
    at Object.main$0 [as main] (<anonymous>:74:46)
    at Object.main$ [as main] (<anonymous>:54:10)
    at <anonymous>:113:26
    at Object.execCb (require.js:5:16727)
    at e.check (require.js:5:10499)
    at e.<anonymous> (require.js:5:12915)
    at require.js:5:1542
    at require.js:5:13376
    at each (require.js:5:1020)
    at e.emit (require.js:5:13344)
    at e.check (require.js:5:11058)
    at e.enable (require.js:5:13242)
    at e.init (require.js:5:9605)
    at a (require.js:5:8305)
    at Object.completeLoad (require.js:5:15962)
    at HTMLScriptElement.onScriptLoad (require.js:5:16882)

Machine
Operating system: MacOS
Version: 13.4
Your code
What code was in the editor, if any, when the failure occurred? You
can paste it in below:
import 'dart:typed_data' ;
import 'dart:math';

extension type Vector3(Float32List storage) {

  Vector3.zero() : storage = new Float32List.fromList([0.0, 0.0, 0.0]);

  double get length => sqrt(storage[0] * storage[0] + storage[1] * storage[1] + storage[2] * storage[2]);

}

void main() {
  final v0 = new Vector3.zero();

   print(v0.length);
}

DartPad's output
Did DartPad print anything to the console pane? If so, paste it below:
Uncaught TypeError: typed_data.Float32List.fromList is not a function, error: TypeError: typed_data.Float32List.fromList is not a function

If you were running Flutter code, you can also paste an image of the
Flutter output directly into this bug report.

Thanks for letting me know, than it will probably land soon 🙂


drivers: modem: support for binary data over uart iface

Is your feature request related to a problem? Please describe.
I would like to be able to send and receive binary data when using the modem subsystem. As I understand it cmd_handler_process_rx_buf() inside drivers/modem/modem_cmd_handler.c strips all carriage returns and line feeds from the uart interface. This means any incoming binary data is truncated if it contains either of those hex values.
Describe the solution you'd like
Perhaps a way to temporarily disable this functionality for binary response commands?
Additional context
Here's a failing implementation of Iridium's AT+SBRB command. The incoming binary gets truncated at the first CR or LF resulting in incomplete data.
MODEM_CMD_DEFINE(on_cmd_sbdrb_read)
{
    struct modem_sbd_data *dev_data = CONTAINER_OF(data, struct modem_sbd_data,
                               cmd_handler_data);

    uint16_t sbdrb_len;
    size_t net_buf_len;

    // get first two bytes of buffer, representing packet len
    net_buf_linearize(dev_data->sbdrb_buf, 2, data->rx_buf, 0, 2);

    // swap byte endianness
    sbdrb_len = sys_get_be16(dev_data->sbdrb_buf);

    // try to pull the rest of the sbdrb message
    net_buf_len = net_buf_linearize(dev_data->sbdrb_buf, sizeof(dev_data->sbdrb_buf),
                    data->rx_buf, 0, sbdrb_len);
    dev_data->sbdrb_buf_len = net_buf_len;

    // sbdrb_len != net_buf_len when a /r or /n is within the binary response

    modem_cmd_handler_set_error(data, 0);
    k_sem_give(&dev_data->sem_response);

    return 0;
}

...
struct modem_cmd sbdrb_resp_cmds[] = {MODEM_CMD("", on_cmd_sbdrb_read, 0U, "")};

    ret = modem_cmd_send(&data->ctx.iface, &data->ctx.cmd_handler, sbdrb_resp_cmds, 1U,
                 "AT+SBDRB", &data->sem_response, MDM_CMD_AT_TIMEOUT);
    if (ret < 0) {
        LOG_ERR("AT+SBDRB returned [%d]", ret);
        return ret;
    }
...

Got a hand from @bjarki-trackunit in the Zephyr discord saying

With the modem iface in modem_context.h, you can read the raw data without passing it to the command handler. See https://github.com/zephyrproject-rtos/zephyr/blob/fb9a6af7004bcdb5bcdadde19898cf9aae8b9449/drivers/modem/quectel-bg9x.c#L849-L858 you can expand you rx receiver thread to pass the binary data to some handler when waiting for binary data, instead of the command handler, which happens within the helper function modem_cmd_handler_process() does

Looks to answer my question - closing


[Bug]: improvement need's in Footer Section

Is there an existing issue for this?

[X] I have searched the existing issues

Describe the bug
In the footer section at the bottom of the newsletter section, Subscribe button looks odd, I think we can

improve that button's UI
Expected behavior

[X] I have read the Contributing Guidelines
[X] I'm a GSSOC'24 contributor
[X] I have starred the repository

@Suman373 Please review my issue. If it is valid, please add the labels gssoc24 extend and Hacktoberfest and assign it to me.

Is there an existing issue for this?

[x]  I have searched the existing issues

Describe the bug
In the footer section at the bottom of the newsletter section, Subscribe button looks odd, I think we can
 improve that button's UI
Expected behavior

* [x]  I have read the Contributing Guidelines
* [x]  I'm a GSSOC'24 contributor
* [x]  I have starred the repository

Hello @officeneerajsaini, Go for it
All the Best


Notification bar stays visible while playing a video

Most videos are 16:9, so are most screens, so I guess the notification area should be hidden in the player.

fixed with version v0.9.17

whoops. wrong issue...


Markdown Preview

Can someone pls help me find a way to increase the height of the html widget?

I'll take a look sometime soon. Does the height value not work?

Yea, the parameter does nothing. You can set the width with the place call, but not the height

I can't close the preview...

Yes thats missing

This close button is only temporary, and will be replaced by a button in a dropdown when the new menu bar is done


Is there a way to reference the viewport's position?

It appears "position: fixed" doesn't work in GSS as it did in regular CSS.
I've made a header that I need to be at the top of the window, always, and it makes full use of GSS to center buttons, logo etc.
Is there any property I can use that would take into account the scroll position of the viewport?

$scroll-top

Thank you a ton for the reply! It seems there's some lag associated with it though, as sometimes when I scroll the window down and up, the header moves out of position for a few miliseconds. Is there really no way to perfectly reproduce the effect one would get with "position: fixed" in regular css? How would a gss user make one of those headers that stick to the top of the window?


Move nation question to the end of the flow

What
The question regarding which nation has been moved to the final question.
This question was the first question in the flow.

Changed logic in the application controller that sets the def first_question_path...  to  /need-help-with path.
We also checked the session exists (def check_first_question_answered) via checking the first path, so was updated.
When the final question is submitted, we persisted the answers to the database. This previously had some complexity as the last question would change depending on which checkboxes were selected.
Given that the /nation question should be shown to all users, we can go back to only persisting the data in that controller... which meant removing from all of the other places it was added to

How to review
Ensure the flow has been correctly implemented, including back links.
Links
https://trello.com/c/57lE8k8g/694-move-the-where-do-you-want-information-about-question-to-the-end-of-the-flow

@leenagupte Coverage is falling because I deleted some tested lines.
Previous the untested methods were, say for example, 1 out 10 lines (10%). If I delete 5 tested lines, then the untested line is now 1 out 5 so the file is now 20% untested :(
That's what caused my comment in slack about removing the untested method set_session_history


Question about Using ConvTranspose for Upsampling

Hello,
I'm trying to use caffe2's ConvTranpose and set stride > 1 for resolution upsampling.
What is the algorithm of the upsampling ? (bilinear, nearest neighbor, or just fill 0)
i.e. the algorithm of deriving the white grid value in the figure in follow link (which is the case of transpose convolution with 3x3 kernel and stride = 2).
https://i.stack.imgur.com/f2RiP.gif
Thanks

I have the same question. I'm trying to implement an autoencoder using ConvTranspose, but there is no unpooling or upsample operation. How to do that?

I did this by performing 2 conv_transpose operations, the first one for the deconvolution itself and the second one for upscaling (using kernel=2 and stride=2):
upconv1 = brew.conv_transpose(model, in_blob, "upconv1", dim_in=64, dim_out=1, kernel=3, pad=1)
upsample1 = brew.conv_transpose(model, upconv1, "upsample1", dim_in=1, dim_out=1, kernel=2, stride=2)

Maybe UpsampleNearestOp  is what you need~


Odigos uninstall command: count Enter as a yes response when prompted

In Odigos CLI, when running odigos uninstall the user is prompted to confirm the uninstall.
We should treat pressing Enter as writing y.
Current state:
➜ odigos uninstall
About to uninstall Odigos from namespace odigos-system
Are you sure? [Y/n]:
Aborting uninstall

Desired:
➜ odigos uninstall
About to uninstall Odigos from namespace odigos-system
Are you sure? [Y/n]:
Uninstalling Odigos Deployments                   ✔
Uninstalling Odigos DaemonSets                    ✔
Uninstalling Odigos ConfigMaps                    ✔
Uninstalling Odigos CRDs                          ✔
Uninstalling Odigos RBAC                          ✔
Uninstalling Odigos Secrets                       ✔
Uninstalling Namespace odigos-system              ✔
Waiting for namespace to be deleted               ✔
Rolling back odigos changes to pods               ✔

Hello @edeNFed  This looks like a good first issue for me -  couple of years experience as a devops/platform engineer and golang hacker after hours I am very much interested in the project.

Great @SzymonSt good to hear 😀 let me know if you need any help

might help with testing after fix @SzymonSt

Hi @werstatyw I've created a PR and tested in on both linux and windows compilations. If you wish to do any more tests please go ahead. BTW I was thinking that such critical actions as uninstallig odigos stack/ maybe editing some resources in future shouldn't be yes by default. What we could do is to extend Ask method to support both cases when Y is default and N is default as well. What do you think @edeNFed ?


The buttons on the VKB Gladiator MkII are incorrect

Forum post

Fixed by commit https://github.com/richardbuckle/EDRefCard/commit/7ac2b1e1d35b35d0a163177728353273e3aa27dc


[tokenizer] Avoid unittest polluting cache directory.

Description
Brief description of what this PR is about

If this change is a backward incompatible change, why must this change be made?
Interesting edge cases to note here

Codecov Report
Base: 72.08% // Head: 71.55% // Decreases project coverage by -0.53% :warning:

Coverage data is based on head (52608ef) compared to base (bb5073f).
Patch coverage: 73.63% of modified lines in pull request are covered.

Additional details and impacted files
@@             Coverage Diff              @@
##             master    #2228      +/-   ##
============================================
- Coverage     72.08%   71.55%   -0.54%
- Complexity     5126     6341    +1215
============================================
  Files           473      631     +158
  Lines         21970    28071    +6101
  Branches       2351     2988     +637
============================================
+ Hits          15838    20087    +4249
- Misses         4925     6522    +1597
- Partials       1207     1462     +255

Impacted Files
Coverage Δ

api/src/main/java/ai/djl/modality/cv/Image.java
69.23% <ø> (-4.11%)
:arrow_down:

...rc/main/java/ai/djl/modality/cv/MultiBoxPrior.java
76.00% <ø> (ø)

...rc/main/java/ai/djl/modality/cv/output/Joints.java
71.42% <ø> (ø)

.../main/java/ai/djl/modality/cv/output/Landmark.java
100.00% <ø> (ø)

...main/java/ai/djl/modality/cv/output/Rectangle.java
72.41% <0.00%> (ø)

...i/djl/modality/cv/translator/BigGANTranslator.java
21.42% <0.00%> (-5.24%)
:arrow_down:

.../modality/cv/translator/ImageFeatureExtractor.java
0.00% <0.00%> (ø)

.../ai/djl/modality/cv/translator/YoloTranslator.java
27.77% <0.00%> (+18.95%)
:arrow_up:

...ain/java/ai/djl/modality/cv/util/NDImageUtils.java
59.21% <0.00%> (ø)

api/src/main/java/ai/djl/modality/nlp/Decoder.java
63.63% <ø> (ø)

... and 564 more

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.

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Remove 0 balance accounts in account collection db

[ ] check 0 balance accounts when sync from tools/sync.js and tools/richlist.js

Duplicate of https://github.com/ethereumclassic/explorer/issues/299


feat: Enhance Hotels Route with City Query Parameter Support

Description:
Issue Summary:
Currently, the application supports navigating to the /hotels route with a city specified through internal state management, such as when a user searches for "Pune" from the homepage. However, this approach does not update the URL with the search parameters, limiting direct URL navigation and bookmarking capabilities. To improve usability and direct access, we aim to introduce support for URL query parameters, specifically for city selection.
Objective:
Enable the /hotels route to accept a city query parameter in the URL, allowing users to directly navigate to a pre-filtered list of hotels based on the city. This feature should support both direct URL entry (e.g., /hotels?city=pune) and navigation from within the application, enhancing flexibility and user experience.
Implementation Steps:

Query Parameter Support:

Modify the hotels route to parse the city query parameter from the URL. This involves checking the URL for any city parameters upon route loading.

Prioritize Query Parameter:

Adjust the logic within the /hotels route to first check for a city query parameter. If present, use this parameter as the locationInputValue to filter the hotel listings.
If the city query parameter is not present, then fallback to using the existing state variable (locationInputValue) as the source for the city filter.
There is already a useEffect on location, can we use that ? search for "const location = useLocation()" and see if we can use that, else you can implement as per your requirements.

Hello, I want to help here, I already clone the project and added the feature, I still need to write tests

Hello, I want to help here, I already cloned the project and added the feature, I still need to write tests

Thank you!


chore: updating dependabot file to support gha, python and docker packages

Hi @wadeBarnes , this is ready for review now


Setup qhy183 camera driver with indi-server

Submited pull request https://github.com/NixOS/nixpkgs/pull/200472

need to work on https://github.com/NixOS/nixpkgs/issues/200154 and https://github.com/NixOS/nixpkgs/issues/200152


lua tcp socket read timed out in error message

Hi
we are using this module for propagating worker event
but when we use it
it shows "lua tcp socket read timed out" in error message frequently
how could we avoid these messages

This may be helpful:
https://github.com/openresty/lua-nginx-module#lua_socket_log_errors


37117 CDTDatastore:getAllDocuments returns a conflicting document twice

What:
In some cases, CDTDatastore:getAllDocuments returns a conflicting document twice, although each document is based on a different conflicting revision.
Why:
CDTDatastore:getAllDocuments uses TD_Database:getDocsWithIDs:options: to get all documents in a datastore. It first prepares the options:
    struct TDQueryOptions query = {.limit = (unsigned int)self.database.documentCount,
                                   .inclusiveEnd = YES,
                                   .skip = 0,
                                   .descending = NO,
                                   .includeDocs = YES,
                                   .content = contentOptions};

And then it calls the method:
        NSDictionary *dictResults = [self.database getDocsWithIDs:nil options:&query];

But TD_Database:getDocsWithIDs:options: reads the revisions, not the documents, and returns the winning revisions. The limit set by CDTDatastore:getAllDocuments refers to the total number of documents in the datastore but if there are conflicting documents, the number of revisions will be bigger than the number of documents. For example:

In the datastore there is one conflicting document with 2 revisions.
CDTDatastore:getAllDocuments set the limit to 1 because there is only 1 document.
CDTDatastore:getAllDocuments calls TD_Database:getDocsWithIDs:options: with limit equal to 1, so TD_Database:getDocsWithIDs:options: reads only one revision and returns it as a document.
CDTDatastore:getAllDocuments updates the options and set skip to 1 because we already read one document (well, that is what we think) and calls  again TD_Database:getDocsWithIDs:options:. This time TD_Database:getDocsWithIDs:options: reads the second revision for the conflicting document and returns it as a new document.

We end with 2 documents although there is only 1 document in the datastore.
How:
Do not limit the query, replace:
    struct TDQueryOptions query = {.limit = (unsigned int)self.database.documentCount,
                                   .inclusiveEnd = YES,
                                   .skip = 0,
                                   .descending = NO,
                                   .includeDocs = YES,
                                   .content = contentOptions};

With:
    struct TDQueryOptions query = {.limit = UINT_MAX,
                                   .inclusiveEnd = YES,
                                   .skip = 0,
                                   .descending = NO,
                                   .includeDocs = YES,
                                   .content = contentOptions};

Tests:
To test this change we create documents with 2 conflicting revisions. So the key to force the error is to create an odd number of documents. For example:

I create 3 documents with 2 conflicting revision
The first time CDTDatastore:getAllDocuments calls TD_Database:getDocsWithIDs:options:, this last method will get 3 revisions: 2 for the first conflicting document and 1 for other conflicting document. It will return 2 documents.
The second time CDTDatastore:getAllDocuments calls TD_Database:getDocsWithIDs:options:,  TD_Database:getDocsWithIDs:options: will get the second revision for the document mentioned before and another 2 revisions for other conflicting document. It will return again 2 documents.

reviewer @alfinkel
reviewer @rhyshort
NOTICE: Although this change fixes the problem it is not a complete solution. The real problem is not the LIMIT but the way TD_Database:getDocsWithIDs:options: uses it. We already implemented a new version of this method here, however we chose this path that is less invasive.
Check BugzID 37117 for more details about the design and how it has evolved until the current point.

+1

+1


build: add emotion and styled-system

Fixes #624
Wasn't so sure about this https://emotion.sh/docs/install#with-babel-plugin-emotion, so I haven't included it in this PR.

If you’re using Create React App, you can use the Babel macro

There are some optimisations which aren’t possible with Babel Macros, so if it’s possible, we still recommend using babel-plugin-emotion

I'd love to do away with the rewire, but I think we need it to apply some
extra webpack to leaflet, which is needed because leaflet and Adobe
tracking compete for the same global.
Insert vomit emoji here
On Tue, 5 May 2020, 7:23 pm Steve Burtenshaw<EMAIL_ADDRESS>wrote:

@stphnnnn commented on this pull request.
In config-overrides.js
https://github.com/neontribe/gbptm/pull/625#discussion_r420315950:

return config;
},

 return config;

}
),
};

I wonder if we should do away with react-rewired- app entirely to reduce
the number of dependencies and deviation from a standard create react app
application.
We could use the:

JSX pragma when we need to use the css prop (unless styled-system
relies on it?)
It looks like with import leaflet everywhere it's needed so we don't
need the ProvidePlugin for that

What do you think @falconx https://github.com/falconx?
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
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frozen in place after character creation?

https://streamable.com/3zb2lj i am having an issue with my server where my character is frozen in place after creation however after a relog or /logout the character works 100%. I'm not sure if it has anything to do with my multicharacter script or whether someone here is the issue. Would anyone by chance know a possible fix to this. I have proceeded to contact the developer of the multicharacter script to ask the same questions but haven't received a response.

@Monkerai what multicharacter are you using?

im using staxzs-multicharacter.

@Monkerai I don't own that multicharacter so can't say what's causing the issue. If you could contact me on Discord and show me how it works and what's the code, I'll be able to help you out

Solved


develop a standard report that describes, for each script/widget, which IDs are NOT in portal

this should be something suitable for sending on to providers of annotation features

note, this should be validated against "current list of extant genes/etc." so that obsolete ensembl IDs are not ok, too.

queries for getting present vocabulary terms
# all gene IDs in the current release, sorted
https://app.nih-cfde.org/ermrest/catalog/1/attribute/CFDE:gene/id@sort(id)

# all gene IDs known by the registry (submission system), sorted
# note the only change was replacing the catalog ID "1" with "registry"
https://app.nih-cfde.org/ermrest/catalog/registry/attribute/CFDE:gene/id@sort(id)

These can be visited in the browser or via command-line  withcurl or wget. You do not need to deal with login credentials or anything.
You can also add a query parameter to the end of the URL ?accept=csv  if you would prefer a basic CSV text listing instead of the default JSON representation. You can also swap out different vocabulary table names in place of the "gene" table in the URLs, and you can change the hostname if you want to do the equivalent query to app-dev or app-staging instead of app...


Adds additional context for the triggered build

This allows the merged build PR to run as if it's a PR build, additionally GITHUB_MERGED_PR_BUILD_TYPE is exposed for consumers

This isn't required as the BUILDKITE_PULL_REQUEST variable doesn't make it to the triggered build


[1.6.9] Failed building wheel for uamqp

UAMQP Package Version: 1.6.9
Operating System: macOS 14.4 (23E214)
Python Version:   3.8.18, 3.9.18, 3.11.6

Describe the bug
Failed to install directly with pip:
pip install uamqp

      ...
      uamqp/c_uamqp.c:65557:146: error: incompatible function pointer types passing 'void (void *, enum MESSAGE_RECEIVER_STATE_TAG, enum MESSAGE_RECEIVER_STATE_TAG)' to parameter of type 'ON_MESSAGE_RECEIVER_STATE_CHANGED' (aka 'void (*)(const void *, enum MESSAGE_RECEIVER_STATE_TAG, enum MESSAGE_RECEIVER_STATE_TAG)') [-Wincompatible-function-pointer-types]
              __pyx_t_1 = ((struct __pyx_vtabstruct_5uamqp_7c_uamqp_cMessageReceiver *)__pyx_v_receiver->__pyx_vtab)->create(__pyx_v_receiver, __pyx_v_link, __pyx_f_5uamqp_7c_uamqp_on_message_receiver_state_changed, ((void *)__pyx_v_callback_context)); if (unlikely(!__pyx_t_1)) __PYX_ERR(7, 23, __pyx_L1_error)
                                                                                ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
      ...
      35 warnings and 1 error generated.
      error: command '/usr/bin/clang' failed with exit code 1
      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
  ERROR: Failed building wheel for uamqp
Failed to build uamqp
ERROR: Could not build wheels for uamqp, which is required to install pyproject.toml-based projects

To Reproduce
Steps to reproduce the behavior:

Create virtual env with desired python version
Install package with pip install uamqp or pip install uamqp==1.6.9

Expected behavior
Package should be installed.
Additional context
Installation of version 1.6.8 works fine.
Release 1.6.9 is blocking installation of requirements for azure collection.

I am facing the same issue but for all versions of uampq with Python 3.11.8 on a Macbook with Sonoma 14.4.1 and an M3 chip.

Hi everyone, are yall using uAMQP with either the  eventhub or servicebus python sdks ? If thats the case we are wanting users to move over to the new versions of the SDK that uses a pure python based AMQP library
As such this library never officially supported ARM and didn't have wheels pushed out for it. We are just pushing out small updates overall as this library is no longer in active maintenance.

~I have the same issue with Python 3.8.17 on an M1 Macbook with Sonoma 14.2.1~
Edit: I followed the recommendation and updated my Azure SDK

Which one? Because I installed cmake, but it doesn't work

@rtrive are you using the Azure Event Hub or Service Bus SDKs? Those also used uAMQP but now are using a new python based on. Upgrading those most likely fixed the issue for them

UAMQP Package Version: 1.6.9
Operating System: macOS 14.4 (23E214)
Python Version:   3.12.2
M1

have the same problem with 1.6.8 and 1.6.9
Same error:
uamqp/c_uamqp.c:112510:55: error: no member named 'ob_digit' in 'struct _longobject'
                  const digit* digits = ((PyLongObject*)x)->ob_digit;
                                        ~~~~~~~~~~~~~~~~~~  ^
      uamqp/c_uamqp.c:112651:55: error: no member named 'ob_digit' in 'struct _longobject'
                  const digit* digits = ((PyLongObject*)x)->ob_digit;
                                        ~~~~~~~~~~~~~~~~~~  ^
      fatal error: too many errors emitted, stopping now [-ferror-limit=]
      294 warnings and 20 errors generated.
      error: command '/usr/bin/clang' failed with exit code 1
      [end of output]

thank you

UAMQP Package Version: 1.6.9
Operating System: Sonoma 14.4.1
Python Version: 3.11.6
M2
It is possible to build with this flag:
CFLAGS="-Wno-error=incompatible-function-pointer-types" pip install uamqp==1.6.9
Not sure if there are side effects, but I only require to install uampq as a dependency of azure-iot-hub, and it doesn't seems to affect the functionality I need.
With Python 3.12 this workaround doesn't work.

UAMQP Package Version: 1.6.9 Operating System: Sonoma 14.4.1 Python Version: 3.11.6 M2
It is possible to build with this flag: CFLAGS="-Wno-error=incompatible-function-pointer-types" pip install uamqp==1.6.9
Not sure if there are side effects, but I only require to install uampq as a dependency of azure-iot-hub, and it doesn't seems to affect the functionality I need.
With Python 3.12 this workaround doesn't work.

This worked for me installing the latest version. Thanks!
CFLAGS="-Wno-error=incompatible-function-pointer-types" pip3 install uamqp

UAMQP Package Version: 1.6.9 Operating System: Sonoma 14.4.1 Python Version: 3.11.6 M2
It is possible to build with this flag: CFLAGS="-Wno-error=incompatible-function-pointer-types" pip install uamqp==1.6.9
Not sure if there are side effects, but I only require to install uampq as a dependency of azure-iot-hub, and it doesn't seems to affect the functionality I need.
With Python 3.12 this workaround doesn't work.

This worked for me installing the latest version. Thanks!
CFLAGS="-Wno-error=incompatible-function-pointer-types" pip3 install uamqp

This works with on python 3.11 for me:
UAMQP Package Version: 1.6.9
Operating System: macOS 14.4 (23E214)
Python Version: 3.11.9
M1
brew install llvm@14
PATH=/opt/homebrew/opt/llvm@14/bin:$PATH pip install uamqp

3.12 - still haven't found a solution


JSON Format Invalid

Release: https://github.com/codepb/jquery-template/archive/1.5.0.tar.gz
File: bower.json
in the "ignore" field, there has no comma and the end of array.

where is the issue sorry? It looks fine here: https://github.com/codepb/jquery-template/blob/master/bower.json

It's in the tar.gz files, i dont know why it in here, and build error? the repository part too, there no comma.

You are correct. Not sure why that would be the case. I'll investigate

How do I get to that file through the interface?

updated version, fixed in 1.5.1


Homemade evaluation script not working properly + Eval dataset not available

Hi all,
I am very interested in your table detection model and wanted to check it by myself. I encountered different diffculties trying to do so and wanted to get some help.
1 - Eval dataset not available
I used an Azure VM to load the dataset and explore it. In your README.md, it is explicitly stated that the detection dataset is in PubTables-1M-Image_Page_Detection_PASCAL_VOC.tar.gz, and there should be 4 folders inside: images, train, test and val. However, when I opened the archive, there were only 2 folders: images and train, and three textfiles: train_filelist.txt, test_filelist.txt and val_filelist.txt containing the path to the XML annotation files.
test_filelist.txt and val_filelist.txt are clearly referencing files that are in /test/ and /val/, even if those folders don't exist. I verified that the test and val annotations were not all in the train folder, and they are not.
I don't know where to find the test and val annotations, you've probably changed the dataset since the readme was written, and it would be nice to update it.
2 - Homemade inference script not working
Because I didn't have the eval dataset, I evaluated the detection model on some samples from the train dataset (I know, big warning because the model saw them during the training, but I just wanted to see good  results, because I struggle to use the detection model).
Here is my code:
First, I instanciate the model and load the weights (that I downloaded through the link in the README.md)
import os
import xml.etree.ElementTree as ET
from PIL import Image, ImageDraw

from torchvision import transforms
import torchvision.transforms.functional as F

import torch
from detr.models.position_encoding import PositionEmbeddingSine
from detr.models.detr import DETR
from detr.models.transformer import Transformer
from detr.models.backbone import Backbone, Joiner

position_embedding = PositionEmbeddingSine(128)
backbone = Backbone("resnet18", False, False, False)
backbone_model = Joiner(backbone, position_embedding)
backbone_model.num_channels = backbone.num_channels
backbone = backbone_model

transformer = Transformer(
    d_model=256,
    dropout=0.1,
    nhead=8,
    dim_feedforward=2048,
    num_encoder_layers=6,
    num_decoder_layers=6,
    normalize_before=True,
    return_intermediate_dec=True,
)

model = DETR(
    backbone,
    transformer,
    num_classes=2,
    num_queries=15,
    aux_loss=False,
)

weights = torch.load("~/Projects/table-parsing/models/pubtables1m_detection_detr_r18.pth", map_location=torch.device('cpu'))
model.load_state_dict(weights)

I consider this part successful because I am greeted by a <All keys matched successfully> message. If i would have instantiated the model incorrectly, I would have the usual Missing key(s) or Unexpected key(s) warnings from pytorch.
Secondly, I created a simple pipeline to reproduce the image preprocessing done in the repo:
convert_tensor = transforms.ToTensor()
mean = torch.tensor([0.485, 0.456, 0.406])
std = torch.tensor([0.229, 0.224, 0.225])
final_size = 800
max_size = 1333

def detr_pipeline(image):

    # Resizing image
    w, h = image.size
    min_original_size = float(min((w, h)))
    max_original_size = float(max((w, h)))
    if max_original_size / min_original_size * final_size > max_size:
        size = int(round(max_size * min_original_size / max_original_size))
    else:
        size = final_size

    if (w <= h and w == size) or (h <= w and h == size):
        new_h, new_w = h, w
    elif w < h:
        new_w = size
        new_h = int(size * h / w)
    else:
        new_h = size
        new_w = int(size * w / h)

    rescaled_image = F.resize(image, (new_h, new_w))
    image_tensor = convert_tensor(rescaled_image)

    # Normalizing image
    image_tensor = image_tensor - torch.broadcast_to(mean.unsqueeze(-1).unsqueeze(-1), image_tensor.shape)
    image_tensor = image_tensor / torch.broadcast_to(std.unsqueeze(-1).unsqueeze(-1), image_tensor.shape)

    # Inference
    output = model([image_tensor])
    return output

The hardcoded means and stds come from detr.datasets.coco.make_coco_transforms
Finally, I used this pipeline to evaluate 20 examples from the training set
dataset_path = "~/Data/PubTables1M-Detection-PASCAL-VOC"
annotation_folder = "train"

train_annotations = []
with open(os.path.join(dataset_path, "train_filelist.txt")) as file:
    for line in file:
        train_annotations.append(line[:-1])

found_examples = 0
current = 0

while found_examples < 20:
    ann = train_annotations[current]
    current += 1
    xml_path = os.path.join(dataset_path, ann)
    assert os.path.isfile(xml_path), 'Annotation not found'
    data = ET.parse(xml_path)
    root = data.getroot()
    image_path = os.path.join(dataset_path, "images", root[1].text)
    if not os.path.isfile(image_path):
        print(f"Skipping {root[1].text}, as file doesn't exist")
        continue
    else:
        print(image_path)
    found_examples += 1
    with Image.open(image_path) as im:
        outputs = detr_pipeline(im)
        bboxes, logits = outputs['pred_boxes'], outputs['pred_logits']
        probas_per_class = logits.softmax(-1)[:, :, :-1]
        objects_to_keep = probas_per_class.max(-1).values > 0.5
        pred_boxes = bboxes[objects_to_keep]

        draw = ImageDraw.Draw(im)
        for elem in root:
            if elem.tag == "object":
                x0, y0, xmax, ymax = [float(i.text) for i in elem.getchildren()[-1].getchildren()]
                draw.rectangle(
                    (x0, y0, xmax, ymax),
                    outline="blue",
                    width=3,
                )
        for box in pred_boxes:
                centre_x, centre_y, width, height = box
                x0 = int(im.size[0] * (centre_x - width / 2))
                y0 = int(im.size[1] * (centre_y - height / 2))
                x1 = int(im.size[0] * (centre_x + width / 2))
                y1 = int(im.size[1] * (centre_y + height / 2))
                draw.rectangle(
                    [x0, y0, x1, y1],
                    outline="red",
                    width=3
                )
        im.save(os.path.join("~/Desktop/output/table", root[1].text))

Note that here, I put a confidence threshold of 0.5, which is very low compared to some other DeTr model, where usually they consider a 0.9 confidence level. Hence I expect to have some false positive results.
Also, I want to point out that there are many annotation files that reference an image that is not in the image folder (that's why I used a while loop and not a for loop.
But when I look at the results, none of them are correct, here are a few samples (the annotations are in blue and the predictions are in red):

It is very weird, considering the model saw these samples during the training. I tried removing the preprocessing, but it doesn't change the results very much, it still looks completely random. Could you please help me with this inference script? What am I doing wrong here?

Hi,
For issue 1, I suggest trying to unzip again. This issue is a duplicate of #36.
For issue 2, I have not looked at your code but looking at the output it looks like you're selecting and outputting the no-object class instead of the table and table-rotated classes. In DETR, the confidence score for the no-object/background class is output at the last class index.
However, another possibility is the image size. At inference time the image should be scaled to have a maximum length (width or height) of 800 to match what we do in our paper.
Hope these suggestions help you.
Best,
Brandon

Hi @bsmock
Thanks a lot for your quick answer.
I indeed had an issue unzipping the archive and I'm currently working on fixing it.
I understand that reading all the code is time-consuming. Nevertheless, I'd like to draw your attention on two points:

In this part in the detr pipeline, I almost copy-pasted the repo preprocessing code to resize the image at 800 with a max size of 1333:

w, h = image.size
min_original_size = float(min((w, h)))
max_original_size = float(max((w, h)))
if max_original_size / min_original_size * final_size > max_size:
    size = int(round(max_size * min_original_size / max_original_size))
else:
    size = final_size

if (w <= h and w == size) or (h <= w and h == size):
    new_h, new_w = h, w
elif w < h:
    new_w = size
    new_h = int(size * h / w)
else:
    new_h = size
    new_w = int(size * w / h)

rescaled_image = F.resize(image, (new_h, new_w))
image_tensor = convert_tensor(rescaled_image)

So the image is indeed rescaled to 800 pixels (width or height).

I found in src.main.py the following class map, which I assume is the table-detection one:

class_map = {'table': 0, 'table rotated': 1, 'no object': 2}

Therefore, in the code I wrote above, I used:
probas_per_class = logits.softmax(-1)[:, :, :-1]

I drop the last column that contains the 'no object`. Just to check that it wasn't swapped with another column, I tried dropping alternatively column 0 , 1 and 2, to check if one was better than another, but all the results seem random (even if keeping column 2 seems to create much more random results).
Hoping that you can help me with my problem
Benoit

@BenoitdeKersabiec  were you able to rectify the issue

Hey @zackwylde-cmd
I was able to rectify the issue with the dataset. I don't know why but it was the 'Import to Azur VM' functionality that was not working. I downloaded the dataset locally and all the files were there.
About the model, I couldn't make it work. I can't see the issue with my inference script and I didn't received an answer here

@bsmock, @zackwylde-cmd
I found the issue in my inference script. As usual, a small oversight lead to weird results.
I forgot to set the model to eval mode with model.eval() after loading it. Just adding this lead to logical results. Everything else in the inference script is working. I am closing the issue.

Hi @yellowjs0304
The inference code pretty much the concatenation of what's above.
for one specific image, if I flatten the code, you can do
import torch
from detr.models.position_encoding import PositionEmbeddingSine
from torchvision import transforms
import torchvision.transforms.functional as F
import os
from PIL import Image, ImageDraw
import json
from tqdm import tqdm
from detr.models.detr import DETR
from detr.models.transformer import Transformer
from detr.models.backbone import Backbone, Joiner
import numpy as np
import random

# ---- Instantiating the model ---- #
position_embedding = PositionEmbeddingSine(128, normalize=True)
backbone = Backbone("resnet18", False, False, False)
backbone_model = Joiner(backbone, position_embedding)
backbone_model.num_channels = backbone.num_channels
backbone = backbone_model

transformer = Transformer(
    d_model=256,
    dropout=0.1,
    nhead=8,
    dim_feedforward=2048,
    num_encoder_layers=6,
    num_decoder_layers=6,
    normalize_before=True,
    return_intermediate_dec=True,
)

model = DETR(
    backbone,
    transformer,
    num_classes=2,
    num_queries=15,
    aux_loss=False,
)

weights = torch.load("./pubtables1m_detection_detr_r18.pth", map_location=torch.device('cpu')) # Change weight path here
model.load_state_dict(weights)
model.eval()

convert_tensor = transforms.ToTensor()
mean = torch.tensor([0.485, 0.456, 0.406])
std = torch.tensor([0.229, 0.224, 0.225])
final_size = 800
max_size = 1333

def detr_pipeline(image):
    image = Image.open(image)

    # Resizing image
    width, height = image.size
    current_max_size = max(width, height)
    scale = final_size / current_max_size
    resized_image = image.resize((int(round(scale * width)), int(round(scale * height))))
    image_tensor = convert_tensor(resized_image)

    # Normalizing image
    image_tensor = F.normalize(image_tensor, mean=mean, std=std)

    # Inference
    output = model([image_tensor])
    return output

outputs = detr_pipeline("image.jpg) # Change image path here
bboxes, logits = outputs['pred_boxes'], outputs['pred_logits']
prob_per_class = logits.softmax(-1)[:, :, :-1]
pred_confidence = prob_per_class.max(-1).values > 0.5
pred_boxes = bboxes[pred_confidence]

The last variable pred_boxes contains the normalized boxes coordinates for tables with a confidence > .5

@BenoitdeKersabiec Thank you for kindly reply~! It'll really helpful!


What's the best way of load-balancing nb2kg to more than 1 server?

A very simple use case. Scale notebook server horizontally, i.e. on multiple hosts. Use a simple round-robin load-balancing method. Ideally plug this load balancer into kernel-gateway itself, or if easier, into nb2kg.
What would be the best approach?

I'm not sure how round-robin load-balancing can work with kernels which inherently hold state in RAM, unless that state is replicated across all kernels.

@rs2 - You might be interested in looking at the recently opened incubator project - Jupyter Enterprise Gateway.  The DistributedProcessProxy implements this exact behavior.
Closing this issue since this isn't something that NB2KG is designed to do.

@kevin-bates :+1:


Training Time of GraphCast

Hello,
I am reproducing GraphCast training phases, and it seems to take dramatically more time on Phase 3 (autoregressive phase) than on Phase 1 and 2.
Is it possible to share the approximated time taken for each training Phases 1, 2, and 3 of GraphCast?
Also, the model seems to use a LOT of device memory on phase 3. Is there any tips on reducing device memory usage during training?
Thank you.

Thanks for your message!

Is it possible to share the approximated time taken for each training Phases 1, 2, and 3 of GraphCast?

Out of the approximately 4 weeks that it took to train the model, phase 3 was about 11 days. Phase 1 and Phase 2 took time proportional to the relative number of training steps in each.

Also, the model seems to use a LOT of device memory on phase 3.

Yes, this is indeed hard to work around. At the time we were limited to 32GB of device memory per training example using TPUv4  and we had to leverage various gradient check-pointing strategies. With today's TPUv5 it should be a lot easier to get it to fit.
Typically if you can 1-step part of training training fit in 32GB by adding some hk.remat options (e.g. TPUv4), then you should be able to fit the 12AR part of training on the TPU v5, so long as you set this to True for the autoregressive training.

Thank you for the detailed and fast reply! That helped a lot.


Kafka producer and consumer, checkstyle

Signed-off-by: Lukas Kral<EMAIL_ADDRESS>This PR adds base for our test-clients:

kafka producer and consumer
checkstyle and suppressions
image building
travis

Do you really need a structure with so many levels?

How we discussed offline, we want to add HTTP clients (and maybe more in the future) to this repo, so from my POV the structure is correct.


feat: Collisions, forces and gravity with Bullet

Implementation of the features described
New test script as example of the functionalities

Functions for movement tested:

AngularFactor
AngularVelocity
LinearVelocity
ApplyCentralImpulse

Changes seem great. I tested loading the scene and starting play mode everything works fine here, physics seem to work great. Then I try to delete objects from hierarchy and also works but when I try to put the cube inside the charachter or otherwise it crashes I don't know if it's only happening to me or is a bug.

It happens to me too, I've checked the stack and in theory it has nothing to do with physics, so it seems out of this scope (?)

Thank you @totisama!


Images flicker

Everything works fine with the example code but if I replace <Text> with <Image> (which loads images from local uris), then as soon as the drag ends, the image flickers for a blink of eye. I've only tested it on iOS.
Say I drag item A from index 0 to index 3. As soon as I release, the image from item A will appear first at index 0 and then at index 3.
I can see that when the dragging ends my component re-renders only once. I also tried wrapping <Image> with useMemo() without any luck (which is I guess is expected since there are no more than 1 re-renderings anyhow).
Any help would be greatly appreciated.

Ok, I found the issue. It was a silly mistake using index as the keyExtractor. Using a unique key solves the problem.

I had the same mistake (I used a sample from readme), you saved me @gsavvid !!! thank you!


dse: Improve aliases detection

If there are two expressions such as:
A = 0.05*v[t, x, y, z + 2] + 0.05*v[t, x, y, z + 5]
B = 0.05*v[t, x, y, z + 3] + 0.05*v[t, x, y, z]

then they won't be detected as aliases iff they are compared in the following way:

A's first indexed (v[t, x, y, z + 2]) with B's first indexed (v[t, x, y, z + 3]) and A's second indexed (v[t, x, y, z + 5] with B's second indexed (v[t, x, y, z ]).

However, if the comparison is swapped (A's first indexed with B's second indexed and A's second indexed with B's first indexed), then a common distance along z is determined (2) and A and B are detected as aliases.
The aliases detection engine should be improved and become independent of the order in which the indexeds with common coefficients (0.05 in this case) are returned by retrieve_indexed. Perhaps do some sort of deterministic ordering?
This, however, only appears in TTI SO=16 with kernel=shifted.
The price to pay are more flops and more memory consumption (w.r.t. to cases in which things work smoothly, such as SO={4, 8, 12})

This has gone through several revisions already; most recently in https://github.com/opesci/devito/pull/816


[BUG] extract core logic; restructure the project

Describe the bug

Currently there are a lot things shared among CLI features.
CLI knows and decides a lot of things.

Partially implemented.


The datepicker on users/profile/edit produces the wrong date

Selecting a date using the datepicker on the users/profile/edit page enters the wrong date into the "Date of Birth" field (e.g. ThuThu-JulJul-2022202220222022). The following screen recording demonstrates the issue:
https://user-images.githubusercontent.com/11529449/181415666-ed236e71-0e8e-4b86-83de-328bcd5894b7.mov
Browser: Google Chrome Version 103.0.5060.134 (Official Build) (arm64)

The scenario "User should see errors for dob in future" in the cucumber test features/users/users.feature would have caught this bug. I'm going to disable this test in an upcoming PR, but they should be re-enabled as part of this ticket.

Resolved by https://github.com/Australian-Genomics/CTRL/pull/47.


Does Differential Expression work with Spatial Data?

Context:
gDoc thread
In the PoC, we noticed that diff exp doesn't work in spatial mode, but we are unsure why. Emanuele wonders if it's because diff exp only works with certain embeddings
DoD:

We want diff exp to work in spatial mode, where a user can select two groups of cells and run diff exp. So the outcome of the spike should pin point where the gap is, so we can correctly estimate the effort it'll take to make diff exp work with spatial mode

Hey team! Please add your planning poker estimate with Zenhub @kaloster @seve

@dsadgat @niknak33 we expect all 8 "prep" and "spike" tickets to be done by Friday 2/23, so it'll be done mid sprint of Feb 20 to March 4 one!

@niknak33 will also communicate the due date in gantt chart (THANK YOU!)

@atarashansky suggested cellxgene launch spatial2.h5ad --debug to look at the trace!

Somehow diff exp is working now
Private Zenhub Video