Show node metrics if high memory consumption is detected

In case the node is detected to consume a lot of memory, its metric endpoint will be dumped to the log.
The threshold is set to ~8.5Gb.

bors r+


Run "git init" when .git doesn't exist to help GitHub source zip/tar.gz builds

For https://github.com/dotnet/source-build/issues/1646
Download links with this change:
https://github.com/dagood/source-build/archive/49195585d0de06e9a06b8fb005c460035363b2af.zip
https://github.com/dagood/source-build/archive/49195585d0de06e9a06b8fb005c460035363b2af.tar.gz

Thanks for this, @dagood! My local test just finished and it unfortunately failed:
  [  8%] Linking CXX static library libcoreclrpal.a
  /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/ranlib: file: libcoreclrpal.a(context.S.o) has no symbols
  /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/ranlib: file: libcoreclrpal.a(context.S.o) has no symbols
  [  8%] Built target coreclrpal
  make: *** [all] Error 2
  Failed to build CoreCLR component.

  'coreclr' failed during build.
  See '/private/tmp/dotnet-20200805-91052-50bno3/source-build-49195585d0de06e9a06b8fb005c460035363b2af/artifacts/logs/coreclr.log' for more information.
  'corefx' failed during build.
  'msbuild' failed during build.
  'known-good' failed during build.

Build FAILED.

/private/tmp/dotnet-20200805-91052-50bno3/source-build-49195585d0de06e9a06b8fb005c460035363b2af/packages/restored/microsoft.dotnet.arcade.sdk/1.0.0-beta.19359.6/tools/ProjectLayout.props(8,3): warning MSB4011: "/private/tmp/dotnet-20200805-91052-50bno3/source-build-49195585d0de06e9a06b8fb005c460035363b2af/packages/restored/microsoft.dotnet.arcade.sdk/1.0.0-beta.19359.6/tools/RepoLayout.props" cannot be imported again. It was already imported at "/private/tmp/dotnet-20200805-91052-50bno3/source-build-49195585d0de06e9a06b8fb005c460035363b2af/packages/restored/microsoft.dotnet.arcade.sdk/1.0.0-beta.19359.6/tools/Build.proj (52,3)". This is most likely a build authoring error. This subsequent import will be ignored.
/private/tmp/dotnet-20200805-91052-50bno3/source-build-49195585d0de06e9a06b8fb005c460035363b2af/repos/Directory.Build.targets(262,5): error MSB3073: The command "/private/tmp/dotnet-20200805-91052-50bno3/source-build-49195585d0de06e9a06b8fb005c460035363b2af/artifacts/src/coreclr.018cfd06dceb19b6eb1e9217a500fb1071946fcd//build.sh x64 Release skiptests -ignoreWarnings -skipmanagedtools -skiprestore -nopgooptimize msbuildonunsupportedplatform cmakeargs -DCLR_CMAKE_USE_SYSTEM_LIBUNWIND=TRUE /bl /p:ILLinkTrimAssembly=false /p:CheckCDefines=false /p:PackagesDir=/private/tmp/dotnet-20200805-91052-50bno3/source-build-49195585d0de06e9a06b8fb005c460035363b2af/packages/restored/ /p:ContinuousIntegrationBuild=true /p:VersionSuffix="servicing" -warnAsError:0 /v:minimal  /p:DotNetPackageVersionPropsPath=/private/tmp/dotnet-20200805-91052-50bno3/source-build-49195585d0de06e9a06b8fb005c460035363b2af/artifacts/obj/x64/Release/PackageVersions.props /p:DotNetRestoreSourcePropsPath=/private/tmp/dotnet-20200805-91052-50bno3/source-build-49195585d0de06e9a06b8fb005c460035363b2af/artifacts/obj/x64/Release/RestoreSources.props >> /private/tmp/dotnet-20200805-91052-50bno3/source-build-49195585d0de06e9a06b8fb005c460035363b2af/artifacts/logs/coreclr.log 2>&1" exited with code 1. [/private/tmp/dotnet-20200805-91052-50bno3/source-build-49195585d0de06e9a06b8fb005c460035363b2af/repos/coreclr.proj]
    1 Warning(s)
    1 Error(s)

Time Elapsed 00:56:05.92
Build failed (exit code '1').

Here's the contents of coreclr.log.

Thanks for giving it a shot. The first error in the log is:
[  0%] Building C object src/corefx/System.Globalization.Native/CMakeFiles/System.Globalization.Native_Static.dir/pal_calendarData.c.o
In file included from /tmp/dotnet-20200805-91052-50bno3/source-build-49195585d0de06e9a06b8fb005c460035363b2af/artifacts/src/coreclr.018cfd06dceb19b6eb1e9217a500fb1071946fcd/src/corefx/System.Globalization.Native/pal_calendarData.c:10:
In file included from /tmp/dotnet-20200805-91052-50bno3/source-build-49195585d0de06e9a06b8fb005c460035363b2af/artifacts/src/coreclr.018cfd06dceb19b6eb1e9217a500fb1071946fcd/src/corefx/System.Globalization.Native/pal_calendarData.h:8:
In file included from /tmp/dotnet-20200805-91052-50bno3/source-build-49195585d0de06e9a06b8fb005c460035363b2af/artifacts/src/coreclr.018cfd06dceb19b6eb1e9217a500fb1071946fcd/src/corefx/System.Globalization.Native/pal_locale.h:5:
/tmp/dotnet-20200805-91052-50bno3/source-build-49195585d0de06e9a06b8fb005c460035363b2af/artifacts/src/coreclr.018cfd06dceb19b6eb1e9217a500fb1071946fcd/src/corefx/System.Globalization.Native/pal_icushim.h:19:10: fatal error: 'unicode/ucurr.h' file not found
#include <unicode/ucurr.h>
         ^~~~~~~~~~~~~~~~~

Have you gone through the CoreCLR setup instructions, for ICU in particular? Seems like a missing ICU header:
https://github.com/dotnet/coreclr/blob/release/3.1/Documentation/building/osx-instructions.md
or I guess https://github.com/dotnet/runtime/blob/master/docs/workflow/building/coreclr/osx-instructions.md
As a heads up, you might also have a problem if you're trying to build on macOS 11/Big Sur, we aren't able to build there yet. https://github.com/dotnet/runtime/pull/39900 fixes it in a CoreCLR branch but hasn't made it to a release yet.
Also, our macOS PR validation isn't working right now, tracked by https://github.com/dotnet/source-build/issues/1685. I'll be ignoring it to merge this PR. I think it only takes the recent homebrew cmake update to break it. It shows up later (when trying to run) so I don't think that would have caused this compile error.
All of the above isn't source-build related though--I'd suggest trying to build CoreCLR on its own and filing issues on dotnet/runtime to get in contact with the experts.

Have you gone through the CoreCLR setup instructions, for ICU in particular? Seems like a missing ICU header:
https://github.com/dotnet/coreclr/blob/release/3.1/Documentation/building/osx-instructions.md
or I guess https://github.com/dotnet/runtime/blob/master/docs/workflow/building/coreclr/osx-instructions.md

No, I haven't. Thanks, I'll try to add depends_on "icu4c" => :build and depends_on "pkg-config" => :build to the formula. Hopefully that helps.

As a heads up, you might also have a problem if you're trying to build on macOS 11/Big Sur, we aren't able to build there yet. dotnet/runtime#39900 fixes it in a CoreCLR branch but hasn't made it to a release yet.

I'm building on macOS Mojave 10.14.6, so that shouldn't be a problem.

Also, our macOS PR validation isn't working right now, tracked by #1685. I'll be ignoring it to merge this PR. I think it only takes the recent homebrew cmake update to break it. It shows up later (when trying to run) so I don't think that would have caused this compile error. More info at dotnet/runtime#39833.

Interesting. I've declared depends_on "cmake" => :build in the Homebrew formula, so perhaps that's going to break the same way here, then. We'll see.

All of the above isn't source-build related though--I'd suggest trying to build CoreCLR on its own and filing issues on dotnet/runtime to get in contact with the experts.

Thanks. That makes me think: Is a more modular approach to this perhaps better? I'm now trying to add a dotnet formula that does and contains "everything", but perhaps I should start at a lower level and add a dotnet-coreclr formula first, then build on that stepwise until we get a dotnet-sdk formula in working order?
Thoughts?

Thanks. That makes me think: Is a more modular approach to this perhaps better? I'm now trying to add a dotnet formula that does and contains "everything", but perhaps I should start at a lower level and add a dotnet-coreclr formula first, then build on that stepwise until we get a dotnet-sdk formula in working order?

Unfortunately there's no reasonable way in 2.1/3.1 to transport the outputs from one step to the next if built solo. No incrementality in other ways either. But CoreCLR is the roughest in terms of prereqs, so I don't think there's a need to do anything drastic here.


Vnet option

https://github.com/Azure-Samples/ansible-playbooks/blob/946dc2b7d686ec9679e40a2ca4c0a7af79cf15b3/aks_create_scale.yml#
How can I add exist Vnet id

Hi @ramaswin121994 Do you mean attach the existing vnet to the AKS? I don't think AKS service api supports this operation according to the documentation
If you mention the ventSubnetID in the AgentPollProfile, you can set the agent_poll_profile like
      agent_pool_profiles:
        - name: default
          count: 3
          vm_size: Standard_D2_v2
          vnet_subnet_id: "your vnet subnet id"


isolate "channel" variables and unleash extensive output channel support

The biggest limitation in mugene to support non-MIDI output formats / devices / playback engines is that it stricttly limits to 16 channels to produce raw MIDI messages that contain channel as the status byte.
It is required so that an arbitrary track can contain messages that are scattered to more than one channel, as well as supporting multiple tracks bound to one single channel.
The latter is still required, but the former is not necessary for meaningful composition. If we can limit a track to be bound to only one channel, then things become much easier to extend support non-MIDI outputs.
Starting with "mugene 2", there will be some abstract music data structure with "channel mapping" which is generated from mapping definitions in the MML and then adjusted to specific output types. "Audio Processor players" can take the outputs along with the channel mapping and then split tracks and attach to each Audio Processor channel which also has separate instrumental settings (like "state" in VST). The existing SMF support is left as is - expect for channel changes in the middle.

There is no need to take care of that within this compiler. It can keep generating MIDI tracks as is. Channel outputs should be taken care at "MIDI player" level. That's what audio plugin based music data does.


feat: Add support for traffic source attachment

Description

Add support for traffic source attachment

Motivation and Context

This allows users to direct traffic from various networking components (ALB, CLB, VPC Lattice, Gateway LB, etc.) to instances created within the autoscaling group

Breaking Changes

No

How Has This Been Tested?

[x] I have updated at least one of the examples/* to demonstrate and validate my change(s)
[x] I have tested and validated these changes using one or more of the provided examples/* projects
[x] I have executed pre-commit run -a on my pull request

This PR is included in version 7.2.0 :tada:


Add more information about what is applicant-facing vs. internal

In the add screens step, it is unclear whether and what information is shown on the applicant-facing side of things or whether it's internal. Suggestion is to add more information about whether things are applicant-facing or internal.
This could be relevant in other areas as well, the add screens step is just what was noted.

Would love to also get a better understanding for the "Administrative use" use cases, but previous UXers on this project had developed a solution here:

This is for the add questions step, not add screen step but the same logic can apply. I'm especially curious to understand this use case for the add screen step as it currently feels redundant.

@rahaghas @clouser2 I believe the original question from previous admins was around what is shown in the screenshot above -- whether "Screen name" and "Screen description" appears to applicants, or just to the admins. We could use the "Applicant View"/ "Administrative Use" language here, but I think where /how exactly it should appear in the pop-up is the TBD part.
@rahaghas what do you think?

I think we can just add some text above the fields that either says "This information will be visible to applicants" or "This information is for administrative use only and will not be visible to applicants" depending on which it is

The "Screen name" and "Screen description" fields are for administrative use only. I believe the proposal for this specific issue would then be to add similar language to what we use for "Create / edit program" of "The following fields will only be visible to administrators."
As I understand, there may be a larger effort around reorganizing these UIs. If we want to incorporate new patterns, that'd likely b the correct avenue.
I can implement the above-described proposal and leave it up to @glorialiou / @rahaghas whether we need more effort on this or whether we should incorporate it into future redesign of the UI.
Work estimate: <1 hour.

That sounds good! Thanks Brett.


Win2019 execution fails while downloading the package

Description
Its for windows 2019 deployment and it was working fine earlier but the build has been failing for the last 4 attempt as PS exited with 1.
Platforms affected

[X] Azure DevOps
[ ] GitHub Actions

Virtual environments affected

[ ] Ubuntu 18.04
[ ] Ubuntu 20.04
[ ] Ubuntu 22.04
[ ] macOS 10.15
[ ] macOS 11
[ ] macOS 12
[X] Windows Server 2019
[ ] Windows Server 2022

Image version and build link
Powershell exited with code 1.
Is it regression?
no
Expected behavior
Installation success and continue execution
Actual behavior
2022-06-13T23:10:57.7689492Z ==> vhd: Machine successfully restarted, moving on
2022-06-13T23:10:57.7717080Z ==> vhd: Provisioning with Powershell...
2022-06-13T23:10:57.7733255Z ==> vhd: Provisioning with powershell script: C:\a\1\s\virtual-environments\images\win/scripts/Installers/Install-VS.ps1
2022-06-13T23:11:11.3248304Z     vhd: Downloading Bootstrapper ...
2022-06-13T23:11:11.3268697Z     vhd: Downloading package from: https://aka.ms/vs/16/release/vs_Enterprise.exe to path C:\Users\INSTAL~1\AppData\Local\Temp\vs_Enterprise.exe .
2022-06-13T23:11:11.3289423Z     vhd: Package downloaded successfully in 0.19 seconds
2022-06-13T23:11:11.3315705Z     vhd: Enable short name support on Windows needed for Xamarin Android AOT, defaults appear to have been changed in Azure VMs
2022-06-13T23:11:12.6377683Z     vhd: Starting Install ...
2022-06-13T23:12:52.2094985Z     vhd: [1b4c:00a2][2022-06-13T23:12:31] Package 'Microsoft.VC.<IP_ADDRESS>.Premium.Tools.HostX86.TargetX86.base,version=14.29.30142' failed to download from 'https://download.visualstudio.microsoft.com/download/pr/f0356831-8920-401d-ab11-813875c90d50/f036a3d9827afcb8f7437efab69a9dda475c8ead88d0d6dc43ffd3d2c3ac0d69/Microsoft.VC.<IP_ADDRESS>.Premium.Tools.HostX86.TargetX86.base.vsix'. One or more errors occurred., Signature: PackageId=Microsoft.VC.<IP_ADDRESS>.Premium.Tools.HostX86.TargetX86.base;PackageAction=DownloadPackage;ReturnCode=0x80131500
2022-06-13T23:12:52.2101450Z     vhd: [1b4c:0006][2022-06-13T23:12:42] Error 0x8013153b: Failed install: The operation was canceled.
2022-06-13T23:12:52.2119229Z     vhd:    at Microsoft.VisualStudio.Setup.InstallOperation.Run(CancellationToken token)
2022-06-13T23:12:52.2141916Z     vhd:    at Microsoft.VisualStudio.Setup.Engine.RunOperation(InstallOperation installOperation, CancellationToken token, ExecuteAction action, ITelemetryOperation telemetryOperation)
2022-06-13T23:12:52.2154171Z     vhd:
2022-06-13T23:12:52.2173018Z     vhd: Non zero exit code returned by the installation process : 1
2022-06-13T23:12:52.5208568Z ==> vhd: Provisioning step had errors: Running the cleanup provisioner, if present...
2022-06-13T23:12:52.5221680Z ==> vhd:
2022-06-13T23:12:52.5236943Z ==> vhd: Deleting individual resources ...
Repro steps
While running the pipeline execution, Package Microsoft.VC.<IP_ADDRESS>.Premium.Tools.HostX86.TargetX86.base,version=14.29.30142' failed to download

Nothing we can help with a flaky network connection.


Add Tiny ImageNet dataset

Describe the dataset
Add Tiny ImageNet dataset to Hub. So this would work.
import hub
ds = hub.load("username/tiny-imagenet")

Here's a tutorial for uploading datasets using Hub.

hey, I would like to that. Please assign it to me

Hey, please assign this to me ( :

Hi @Satyam-kumar-yadav! Assigned you to this issue. Thanks for your willingness to contribute! Let me know if you have any questions, and please star our package while you're at it. :)

Hey @mikayelh! Please check the ImageNet dataset  . My doubt is if you have provided the correct link or not. :)

Hey @Satyam-kumar-yadav, thank you so much for flagging this! :) I've updated link to the entire ImageNet dataset. We'd appreciate if you converted that, but if it is too big of a dataset (may take forever to upload), you can go ahead with the TinyImagenet version (here). Let me know which one will you choose!

Yeah I will go with Tinylmagenet version only. :)

I've updated the issue name to reflect your choice. Thanks a lot for volunteering! :)

Hi, @Satyam-kumar-yadav ! Hope this finds you well. Dropping a note to check in on you an ask if you need a hand with uploading the dataset. Feel free to ask us in the GitHub Discussions (we have beta access!) or our dedicated Slack channel. Thanks a mil!

Hey @Satyam-kumar-yadav, hope this finds you well! I see you've removed your assignment. It is totally fine - just wanted to ask what was the reason behind it? Was the task too challenging? Thanks a lot!

Yeah, I found it quite challenging to do, and I am also not good at it so rather than doing this bigger one I would like to work on some smaller sections. I will be happy if you can help me to get started with it.

Thanks a lot, @Satyam-kumar-yadav. Can you let me know what exactly was the part that was complicated?
I'm tagging @AbhinavTuli in the thread to follow-up regarding this, and maybe suggest a smaller task.

Hey @mikayelh , can I work on this?

Hi, @Abhilasha06! Thanks a lot for volunteering - we appreciate it a lot Assigned you the task - if you ever need a hand with uploading the dataset, feel free to ask us in the GitHub Discussions (we have beta access!) or our dedicated Slack channel. If you haven't already - please star our package. Thanks a mil!

Hey @Abhilasha06, do you need any assistance with uploading the dataset? We've just released v1 of Hub, which makes uploading even easier. If you need any help, feel free to join our Community Slack to ask questions!

Closing this due to inactivity, will reopen if theres widespread interest.


Running tcod application disabled KDE compositor effects

A tcod application seems to be disabling compositor effects as long as it's running. The effect is visible here:

I thought that maybe SDL is responsible for such undesirable behaviour so I tried to make a minimal SDL example to reproduce this behaviour:
#include <iostream>
#include <SDL2/SDL.h>

int main(int argc, char** argv) {
    if(SDL_Init(SDL_INIT_VIDEO) != 0) {
        std::cerr << "failed to init: " << SDL_GetError() << std::endl;
        return 1;
    }
    SDL_Window* win = SDL_CreateWindow("Hello world", 0, 0, 800, 600, SDL_WINDOW_SHOWN);
    SDL_Renderer *ren = SDL_CreateRenderer(win, -1, SDL_RENDERER_ACCELERATED | SDL_RENDERER_PRESENTVSYNC);

    bool quit = false;
    SDL_Event e;

    while(!quit) {
        SDL_RenderClear(ren);
        while(SDL_PollEvent(&e)) {
            switch(e.type) {
                case SDL_QUIT:
                    quit = true;
                    break;
            }
        }

        SDL_RenderPresent(ren);
    }
    SDL_DestroyRenderer(ren);
    SDL_DestroyWindow(win);
    SDL_Quit();

    return 0;
}

And to my surprise, the same build of the code one time disables compositor, and another time it doesn't... It seems to just be completely random.
I compile the code with g++ main.cpp -lSDL2. I'm using the OpenGL 3.1 compositor in KDE.
Do you happen to know what could be causing the issue? I'd happily look into that, should you give me a few pointers where to start.

I don't think anyone here will be able to help, we are just providing a rust interface to tcod.
Your best bet would be to take it to the SDL forums and see what they say.

Yeah, I'm afraid I don't really have anything useful to say here either, sorry!
We've written the bindings to libtcod and as far as most of the people working on them, SDL is basically a libtcod's implementation detail. I certainly don't have knowledge that could help here and I haven't used KDE for over a decade.

Thanks for responses! I guess then, as this is not an issue with libtcod itself but rather with its dependency, there's nothing to fix here and the issue can be closed.


ci: Update checkout action

Fixes #
Proposed Changes

:warning: Please install the  to ensure uploads and comments are reliably processed by Codecov.
Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 98.82%. Comparing base (40c2419) to head (30ee621).
Report is 2 commits behind head on main.

Additional details and impacted files


Make resource server paths configurable

Closes everest-engineering/lhotse#7

This makes the most commonly modified parameters configurable. It doesn't address all the hard coded values and no longer feels urgent since we have to migrate to Spring's new authorisation server at some point so this will all be rewritten :-P


WIP: Add zoom.us video conferencing support

This is a WIP commit for #10979.
Currently implemented:

[x] Adding settings for Zoom credentials.
[x] Updating backend model for Zoom.
[x] Endpoint for Zoom URL creation.
[x] Inserting Zoom URL into message.

To-do:

[ ] Verification of credential inputs (other than just if they are empty).
[ ] Fix an issue with credentials in settings not updating when re-loaded.
[ ] Rebasing against master.
[ ] Add tests for Zoom.

GIF of inserting URL:

I did a rebase + migration rename for the first commit.  I think the backend commit is looking pretty close to mergable; what I'd do to complete it is:

Add unit tests for both the realm API and the; you can use httpretty to mock the HTTP response results.
I think for validating the provided credentials, we should perhaps just call get_zoom_video_call_url and not return the URL; since that confirms end-to-end that we can use that endpoint.  (Could potentially do that passing in a hand-patched copy of the realm object).

Also, just wanted to say this is really nice initial work :)

@shubhamdhama do you have ideas for how to make the settings UI part of this cleaner?


Incompatible with latest version of Analyzer

None of the recent versions of the Angular package are compatible with the latest version of the Analyzer package 0.39.2+1.
pub get update shows:

Because angular >= depends on analyzer ^0.37.0 and auge_web depends on analyzer ^0.39.2+1, angular >=6.0.0-alpha+1 is forbidden.
So, because auge_web depends on angular ^6.0.0-alpha+1, version solving failed.

Dart SDK Version (dart --version)
2.7
AngularDart Version
6.0.0-alpha+1
Whether you are using Windows, macOS, or Linux
Windows
Whether you are using Chrome, Safari, Firefox, Edge
Chrome

As mentioned in https://github.com/dart-lang/angular/issues/1860#issuecomment-565643006, you can use dependency_overrides to override the analyzer constraint.

@leonsenft: FYI: While the overrides may work in many cases, there were a few non-trivial changes between package:analyzer 0.37 and 0.39, and for a non-angular use-case we had breaking changes when doing the override.

Overriding analyzer is not the magic solution as it breaks some others packages on build. In my project, I tried many times but impossible to use analyzer> 0.38.3 Hope you'll  upgrade Angular to be compatible with analyzer 0.39+ soon

@leonsenft trying to update to analyzer ^0.39.0 with dependency_overrides fails on webdev build with the following error:
[SEVERE] ../../../.pub-cache/hosted/pub.dartlang.org/angular-6.0.0-alpha+1/lib/src/compiler/analyzed_class.dart:64:15: Error: The method 'isEquivalentTo' isn't defined for the class 'DartType'. - 'DartType' is from 'package:analyzer/dart/element/type.dart' ('../../../.pub-cache/hosted/pub.dartlang.org/analyzer-0.39.8/lib/dart/element/type.dart').Try correcting the name to the name of an existing method, or defining a method named 'isEquivalentTo'.  return type.isEquivalentTo(string);
Unhandled exception:
Bad state: Unable to start build daemon.
#0      _handleDaemonStartup (package:build_daemon/client.dart:82:5)
<asynchronous suspension>
#1      BuildDaemonClient.connect (package:build_daemon/client.dart:183:11)
<asynchronous suspension>
#2      connectClient (package:webdev/src/daemon_client.dart:17:23)
#3      _startBuildDaemon (package:webdev/src/serve/dev_workflow.dart:26:18)
#4      DevWorkflow.start (package:webdev/src/serve/dev_workflow.dart:194:24)
#5      ServeCommand.run (package:webdev/src/command/serve_command.dart:101:27)
<asynchronous suspension>
#6      CommandRunner.runCommand (package:args/command_runner.dart:197:27)
#7      _CommandRunner.runCommand (package:webdev/src/webdev_command_runner.dart:38:24)
#8      CommandRunner.run.<anonymous closure> (package:args/command_runner.dart:112:25)
#9      new Future.sync (dart:async/future.dart:224:31)

Angular (5.3.1)
We can't update builder libraries with important fixes for us because they depend on the latest analyzer version. And angular doesn't compile with this analyzer version.
[SEVERE] angular:angular on lib/src/smth.dart: Unhandled exception in the AngularDart compiler!
Please report a bug: https://github.com/dart-lang/angular/issues/newBad state: Provider.useFactory must be a Function, but got type Smth Function() instead with type element null
...

This topic is getting more and more pressure every day. Developers outside of Google are from now on basically bound to the SDK version <dart-sdk 2.14.0-91.0.dev because angular 6.0.1 depends on analyzer ^0.40.0
See also https://github.com/dart-lang/sdk/issues/46482
dependency_overrides:
  analyzer: ^1.0.0

Working dir: D:\dart-apps\webV\gdv\gdv_app
"D:\dart-sdk\dart-sdk 2.14.0-241.0.dev\bin\dart.exe" pub get
Resolving dependencies...
Because analyzer >=1.0.0 depends on package_config ^2.0.0 and angular_compiler 1.0.1 depends on package_config ^1.9.3, analyzer >=1.0.0 is incompatible with angular_compiler 1.0.1.
And because angular 6.0.1 depends on angular_compiler 1.0.1 and no versions of angular match >6.0.1 <7.0.0, analyzer >=1.0.0 is incompatible with angular ^6.0.1.
So, because gdv_app depends on both angular ^6.0.1 and analyzer ^1.0.0, version solving failed.


[BUG] Typo when running deployment dry run

Describe the bug
Small typo when running deployment
To Reproduce
Steps to reproduce the behavior:

Run seedfarmer apply <path_to_deployment.yaml>  --dry-run
Look at the output table header reads "Deployemnt" instead of "Deployment"

Screenshots

Corrected and merged.  Will be in the next patch release


New version: Jackett.Jackett version 0.22.391

Pull request has been created with WinGet Releaser :rocket:
Microsoft Reviewers: Open in CodeFlow

/azp run

/azp run


Fix docs build and optimize host register

This PR includes following updates:

Fix ./build.sh docs
Add related cleanup for ./build.sh clean
Slightly optimize for memset before cudaHostRegister to speedup host continuous type of WholeMemory

/ok to test


Remove ServiceIdentifier attribute from ServiceBinding for "user-provided" instances

Context
We figured it would be counter-intuitive to have service identifiers "user-provided" for user-provided service bindings originating from BTP CF VCAP_SERVICES environment variable.

Release Notes
<TODO: Insert release notes>

Definition of Done

[ ] Feature scope is implemented
[ ] Feature scope is tested
[ ] Feature scope is documented
[ ] Release notes are created

Closed for another solution


Updating aws-sdk dependency

Without explicitly setting aws-sdk version. using the gem resulted in conflicts with using the aws-sdk-sqs directly (which i'm using in separate part of my project)
Bundler could not find compatible versions for gem "aws-sdk-core":
 In snapshot (Gemfile.lock):
    aws-sdk-core (= 3.29.0)
  In Gemfile:
    active_elastic_job was resolved to 2.0.1, which depends on
      aws-sdk (~> 2) was resolved to 2.0.1.pre, which depends on
        aws-sdk-resources (= 2.0.1.pre) was resolved to 2.0.1.pre, which depends on
          aws-sdk-core (= 2.0.1)
    aws-sdk-sqs was resolved to 1.7.0, which depends on
      aws-sdk-core (>= 3.26.0, ~> 3)
Running `bundle update` will rebuild your snapshot from scratch, using only
the gems in your Gemfile, which may resolve the conflict.

I've managed to fix this, and deploy the whole setup in my AWS staging environment which works well now.
Another note, initially i went for FIFO queue but that needed more dependencies that wasn't supported by default, so I've have added a note in the README to make it easier for others

Thank you @tawan for the awesome library,  took some time to setup but works well so far.  i believe this pull request can be helpful to others

from the build failures for this pull requests and others, it seems the test environment doesn't have AWS_REGION  set.
tests are confirmed to be working locally using
EXCEPT_DEPLOYED=true bundle exec rspec spec
and in the docker environment
docker run -e EXCEPT_DEPLOYED=true -v $(pwd):/usr/src/app active-elastic-job-dev bundle exec rspec spec```

note: working with ruby 2.5.1

Are we sure AWS_REGION is set properly in CI ?

thanks @joeyparis


bash-4.3: fix patches hashes

Without this bash will not be made.

Thanks! Can you submit this against staging, since it will cause a mass rebuild?
See also #11398 and #11418

This is already in staging (https://github.com/NixOS/nixpkgs/commit/3c437a643fff579909702229c1a8521600feba16).

Sweet!

Forgive the naive question, but how do I get from a fresh install of Nix to a git-HEAD-based one without running into this? (I've verified I do have 3c437a6 in my checkout.)

@mikesperber this is fixed on master


Regression: Image no longer decoded correctly

This image
tiny.zip
should be decoded as

but since 768b16b70b5a1d1315dda29ccc3777761a9b5a31 it seems to be decoded as

Feel free to use the images under any license.

Thanks for reporting! Seems to have been an issue in the color transform code


Documentation for ARM Template is missing resource type.

The JSON supplied does not include the resource type, is this in the WAF resource? looking at the arm template schema for application gateway, it seems not. In order to use the supplied JSON for anything, some context needs to be provided.

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

ID: 7f37e9d2-9044-93ba-8ce5-cd9cc3dc64fc
Version Independent ID: 4c03470f-1e5e-62d1-fbf2-4386e3712fe6
Content: Create and use v2 custom rules - Azure Web Application Firewall
Content Source: articles/web-application-firewall/ag/create-custom-waf-rules.md
Service: web-application-firewall
GitHub Login: @vhorne
Microsoft Alias: victorh

@RIKIKU, Appreciate your feedback. Here the doc is more towards explaining the WAF configurations in Application Gateway, so the ARM schema snippets are cropped/sampled to just WAF configuration for quick view and understanding. Here is the complete template of Microsoft Application Gateway to modify resources under it accordingly.

@SubhashVasarapu-MSFT,
I appreciate your reply and making it possible to submit feedback on this documentation.
I think your comment has actually illustrated my point here. The customRules property is not a part of the Application gateway schema. If I follow the link you provided and use my browser to search for "customRules"  it seems this is not a property of the App Gateway template.
After quite a lot of searching, I did eventually find ApplicationGatewayWebApplicationFirewallPolicies which I suggest is the JSON in this document.  This is a whole other resource where the only thing it has in common with the application gateway template is the namespace.
It was very difficult to find the firewall policies resource and I suggest that a link should be provided from this document to the ApplicationGatewayWebApplicationFirewallPolicies template document, or the resource type should be included in the JSON snippets to aid in locating the rest of the template.

Link added to ApplicationGatewayWebApplicationFirewallPolicies
#please-close


Added Eduroam wifi example to network manager docs

Created an additional base WPA2 enterprise example for Eduroam with network manager.
Change-type: patch
Signed-off-by: Alex Bucknall<EMAIL_ADDRESS>

@balena-ci retest

@balena-ci retest

@balena-ci retest

I will get this merged!


empty argument -dll when using only one dll

there seems to be a bug intruduced with issue #3
https://github.com/tr8dr/.Net-Bridge/blob/f39b85db51476d5935be54ab4a4b5d5bb14d3118/src/R/rDotNet/R/Driver.R#L78

Do you have a suggestion as to how to fix?   I am not sure how to reproduce this.

not yet; Yesterday, I patched the CRAN version into the GitHub (I assumed
CRAN 0.9.1) and run into the multiple DLL last issues. I will check on
Friday.
Best wishes
Christian
On Wed, May 29, 2019 at 9:48 PM Jonathan Shore<EMAIL_ADDRESS>wrote:

Do you have a suggestion as to how to fix? I am not sure how to reproduce
this.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/tr8dr/.Net-Bridge/issues/8?email_source=notifications&email_token=ABFMYY62KPK2OG2KUCU34ILPX3MYJA5CNFSM4HQSQ4K2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGODWQOJFA#issuecomment-497083540,
or mute the thread
https://github.com/notifications/unsubscribe-auth/ABFMYY7SZUYU4CFMWOQSNGLPX3MYLANCNFSM4HQSQ4KQ
.


Auto-updater

Make this optional, and ask when first opened before making any network requests.
Add an option to settings "Check for updates"
Show a banner when updates are available. Check a file at simplewebserver.org/versions.json

@ethanaobrien Instead of building an auto updater into the program, I think we should instead just check if there is a new version available, and make the user go and download the new version to update. We should make sure the installer replaces an old version if it's already installed. The Windows / macOS store will already take care of automatic updates for us. So we would only have the update checker built in to the manual install version. How does this sound?

Yes, I agree. I think we should only do this on the manual install version. Are we going to do an exe release that installs to appdata or programdata?

Haven't you already figured out how to make a windows installer? AppData is only for storage files, we should definitely not install program files there.

Sorry, I meant Program Files. I have figured out how to make one that will publish to the windows store.

I forgot that we'd need a separate apple developer account for the macOS App Store. Nevermind about that.
App data local or roaming?

local. electron stores the save data in the roaming folder and the app in the local folder

Okay, makes sense, that sounds good.

There is room for future improvement here, with code signing. But I'm closing for now.


Bugfix/issue 230 jacobian transposed

Submisison Checklist

[X] Run unit tests: ./runTests.py src/test/unit
[X] Run cpplint: make cpplint
[X] Declare copyright holder and open-source license: see below

Summary:
align jacobian with common definition, i.e. to return a NxM matrix for a R^N -> R^M function
Intended Effect:
Currently the output would the transposed MxN
How to Verify:
Run current tests for stan/math/rev/mat/functor/jacobian.hpp
Side Effects:
All user code using the functions now get the correct (but different) sized matrices.
Documentation:
Reviewer Suggestions:
@syclik @bob-carpenter
Copyright and Licensing
Please list the copyright holder for the work you are submitting (this will be you or your assignee, such as a university or company): Sebastian Weber
By submitting this pull request, the copyright holder is requiring to license the submitted work under the following licenses:

Code: BSD 3-clause (https://opensource.org/licenses/BSD-3-Clause)
Documentation: CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/)

Uh, default says it failed, but there aren't any failed tests.  @syclik --- any idea what's up here?
Also, what this really needs is a test to make sure we're doing this the right way around.  In general, whenever there's a bug, the first thing to do is write a test that fails in the current implementation.  Then fix it so the new implementation passes.

The code looks fine, by the way.

It fails this test: ./runTests.py test/unit/math/mix/mat/functor/autodiff_test.cpp
Not sure what's up with it yet.
Re: Jenkins -- I'm still trying to figure out how to aggregate tests to the project so it shows the right message from GitHub.

Hi!
I checked matters and the test needed an update as the to be tested output from the jacobian function is now transposed (sorry, I should have caught this myself, but I was not able to decipher the error messages here). The tests are now successful. However, I had to apply a workaround which I have seen to be necessary when working with NESTED AD things:
The AD nested calculations are WRONG if the AD stack is not initialized. This is why I instantiate a var dummy variable within the test before the jacobian call is done. My guess is that this was not necessary before this patch due to the change from set_zero_all_adjoints() to set_zero_all_adjoints_nested().
My guess is that the set_zero_all_adjoints_nested() may have an issue.
For the purpose of this pull request I guess we have 3 options:

Fix the nested system (if my understanding here is correct and we have an issue here and not a misuse from my end)
change set_zero_all_adjoints_nested() to set_zero_all_adjoints() in the jacobian function and remove the dummy variable in the test
leave things as they are

@bob-carpenter : Just for the future: You are pointing towards test-driven development. For this specific case the already existing test was actually wrong. So if I were to redo this again, would it have been ok to CHANGE the existing test which tests for the wrongly transposed output to the correct behavior. That way the old test would be changed, but this would trigger the mis-behavior. Would this be ok from a test-driven dev perspective?

Whoa... there is another jacobian function lingering in stan math somewhere which returns a transposed Jacobian. The test code for the
jacobian(f,x,fx_rev,J_rev);
function still tests for the transposed Jacobian - but I have no clue where this is coming from.

Found it. The "fwd" version was what I was looking for. I adapted the test and corrected the fwd jacobian version. BTW, there is another jacobian implementation around in the test system, but that one is ok as far as I can tell.

Thanks, Sebastian; this is good to go.   It looks like all the tests passed on Jenkins and then some aggregator got messed up --- GitHub is obscuring the bottom half of my screen with an annoying overlay modal dialog message about localization I can't remove.

All the tests actually passed. Merging.


Support tsconfig paths in spack.

So that setting paths in options.jsc.paths in spack.config.js is respected when resolving modules.

@kdy1, I though this would solve my problem with aliasing builtin modules but it doesn't work so I think spack needs to introduce the concept of aliases.
For example, I have a dependency that requires the node builtin module stream but I am building for the browser so I want to use stream-browserify instead. Currently, paths do not allow me to do that as I get this error:
not processed by tsc resolver because base module is in node_modules

Can we add an alias configuration to spack.config.js that would just do a straight rewriting of a module source on a match:
alias: {
  stream: "stream-browserify",
  fs: "localstorage-fs"
}

I think we could add this to NodeModulesResolver, would that work?

@kdy1, I have added the alias functionality which is helping me a lot step through my build errors. One small detail I changed is that I figured it would be better to allow different aliases per target runtime environment for isomorphic builds, so the config now looks like:
alias: {
  browser: {
    stream: "stream-browserify"
  }
}

The downside is that if somebody wants the same aliases for node and the browser some duplication is required but I think it is better to allow them to be configured individually.
I think this can be merged now if you approve :+1:

Cool @kdy1, all done :+1:


Many drivers are dependent on eh2 traits

We already were aware of twai, see #1123, but upon switching to eh1 by default, I had to hack in this commit: https://github.com/esp-rs/esp-hal/pull/1313/commits/121dca7e2201ef59657a5f3bd476612aaecc80a1. All of these fixme's and now public functions exist because they were only usable via the eh02 traits.
They need fixing so that

They work without any eh feature
The new APIs are documented

tracking

[x] #1355
[x] #1367
[x] #1372
[x] #1391
[x] https://github.com/esp-rs/esp-hal/pull/1392
[x] https://github.com/esp-rs/esp-hal/pull/1386

@MabezDev is working on GPIO, I have opened PRs for the remaining peripherals.

If we've missed anything please let me know but otherwise this appears to be complete.


Add weights, move files: Tasks>AdminClust>MemCPU

Partially addresses #8398.
Preview: https://deploy-preview-8635--kubernetes-io-master-staging.netlify.com/docs/tasks/administer-cluster/manage-resources/memory-default-namespace/
This is one of several PRs that I will submit to get the Tasks left nav in order.

/assign @chenopis

/cc @kubernetes/sig-docs-pr-reviews

@steveperry-53 @chenopis @Bradamant3 @zacharysarah Please don't hold off on getting this and my other PRs merged. I'm working on the Tasks left nav in a sequence of PRs, each of which does a small part of the overall joj. So please move this and my other Tasks PRs forward. We can tackle the mixing of individual topics with folders at a later time.

@steveperry-53 Makes sense! Will do!
/approve
/lgtm


Need to stand up YARN Application Timeline Server

We should be deploying the YARN Application Timeline Server. Further investigation should go into TEZ-8. Lastly, as noted in #64, should YARN Proxy be properly deployed?

This is fixed in PR #150

I have submitted the initial version of code  and it's in-progress.

fixed in #717


bump to 5.0.3

LGTM

@ph what is the status on this?

@talevy I think this PR was not actually needed since master was already at 5.0.3 but we had forgotten to publishing it. I did a sanity check on the 5.0.3 gems and I can confirm it has the jars in it.
/t/logstash-output-kafka-5.0.3 ❯❯❯ find . | grep .jar                                                                                ⏎
./lib/logstash-output-kafka_jars.rb
./vendor/jar-dependencies
./vendor/jar-dependencies/runtime-jars
./vendor/jar-dependencies/runtime-jars/kafka-clients-<IP_ADDRESS>.jar
./vendor/jar-dependencies/runtime-jars/log4j-1.2.17.jar
./vendor/jar-dependencies/runtime-jars/lz4-1.3.0.jar
./vendor/jar-dependencies/runtime-jars/slf4j-api-1.7.21.jar
./vendor/jar-dependencies/runtime-jars/slf4j-log4j12-1.7.13.jar
./vendor/jar-dependencies/runtime-jars/snappy-java-<IP_ADDRESS>.jar


Screen scrolling madness with 2.0

Hey,
Love the ability to reset the database when required.  I'm back to using Prompta, thanks!
However, with 2.0 I notice that something screwy happens with vertical scrolling as soon as the chat is longer than a single page.
This is on latest macOS (14.0) using DMG (it seems fine when using the chat.prompta.dev).
Screen recording attached because it's hard to explain.
https://github.com/iansinnott/prompta/assets/130651/f67172a8-4f6b-4b46-8d0a-028c9669ef71

thanks @adamshand the video is very helpful. let me see if i can repro

Was unable to reproduce that oddness. I'm also on mac (arm), are you sure you're on the latest version. i just pushed https://github.com/iansinnott/prompta/releases/tag/v2.0.1 which adds the version string to the UI in the settings panel.
If you're still able to repro can you think of anything else that might be different in your env?

Pretty sure I was on the latest version, but just downloaded 2.0.1 and it's still doing the same thing.

I'm running Sonoma (14.0) which might be a problem?  Other than that I'm on a fairly standard M2 MacBook Air.

Hm, possibly. I'm not running Sonoma so while it should work it's entirely untested. When you tried in the browser was it safari?
The desktop version is essentially a safari window without the chrome.

Ah yes.  I tested in Brave previously.  Just tried Safari and it also does the weird vertical scrolling thing.


#5 Changed deprecated YellowBox (as of RN 0.63) to use LogBox

Hey here's a pull request for issue #5, thanks for the great package

Thanks for the pull request

I just released this with 0.2.0


[Bug]: Horse image is not properly displayed in dark mode

Is there an existing issue for this?

[X] I have searched the existing issues

Describe the bug
When we open horse under animal option in dark mode the hairs of the horse gets merged with the background and they are not visible.
Expected behavior
everytime we open horse in dark mode
Add ScreenShots

On which device are you experiencing this bug?
Android
Record

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

please assign this issue to me

i need to upload new horse.svg file kindly give me push request

Hi! I would like to work on this issue (#182) regarding the horse image not displaying properly in dark mode. I will ensure to test the changes thoroughly in both light and dark modes. Thank you for the opportunity!


Add templates for new poster and publications

Would be nice to have templates along with the instructions of #72

Having templates would only introduce repeated code: one time on the README.md and other one on the template itself.
I think it's better to just copy paste the instructions from the README.md.


support new version of pgspecial

Describe your changes
Update psycopg version and pgspecial version
Issue number
Closes #367
Checklist before requesting a review

[x] Performed a self-review of my code
[x] Formatted my code with pkgmt format
[x] Added tests (when necessary).
[x] Added docstring documentation and update the changelog (when needed)

:books: Documentation preview :books:: https://jupysql--622.org.readthedocs.build/en/622/

@edublancas The CI/Integration test fails for this PR. I can connect the database locally. Do you have any idea why that happen?

@tl3119: you have to get comfortable with reading error logs, it's a good skill.
sure, I can help, based on the logs, the error seems this:

AttributeError: 'psycopg2.extensions.connection' object has no attribute 'pgconn'

looks like this is a problem with psycopg2, perhaps since you upgraded the version, it's now incompatible with either our code or the new pgspecial version.
I'd recommend running the tests locally until you can reproduce it. then you can debug to see what's causing the problem


Show indirect relationships (e.g., grandparent/grandchild nodes if a parent/child has been removed via filtering)

Implemented on dag branch


Ipmiview: 2.11.0 -> 2.12.0

Motivation for this change
Update version to latest. Old version no longer exists.
Things done

[x] Tested using sandboxing
(nix.useSandbox on NixOS,
or option build-use-sandbox in nix.conf
on non-NixOS)
Built on platform(s)

[x] NixOS
[ ] macOS
[ ] Linux

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

The package does build now after bumping the version, however when using the program and attempting to launch a console with ipmi I get the error

Cannot run program “java” error=2, No such file or directory

I attempted to fix it and looked around but was unable to find the cause of the error. It seems that it's trying to launch the wrong "java". I don't know if this error existed before because I was never able to use the previous version.

You can use strace -f -e execve <yourprogram> in order to find out, which java it is looking for.

@Mic92 I Just get it failing to run at all with strace.
strace -f -e execve IPMIView
execve("/run/current-system/sw/bin/IPMIView", ["IPMIView"], [/* 89 vars */]) = -1 ENOEXEC (Exec format error)
strace: exec: Exec format error
+++ exited with 1 +++

The wrapper was bogus. Please try again.

@Mic92 No luck, same error.

OK, wrapper let me run strace. Thanks @Mic92 I'm looking through the output now.

So it's looking for iKVM.jar, where should I put it? I tried wrapping it but it didn't work.
I tried this:
      makeWrapper $out/jre/bin/java $out/bin/iKVM.jar \
        --add-flags "-jar $out/iKVM.jar"

and this:
      makeWrapper $out/jre/bin/java $out/share/java/iKVM.jar \
        --add-flags "-jar $out/iKVM.jar"

[pid 32358] execve("/home/john/.local/bin/java", ["java", "-Djava.library.path=.", "-jar", "iKVM.jar", "<IP_ADDRESS>", "ADMIN", "Aoy9g1j", "null", "5900", "623", "0", "0"], [/* 91 vars */]) = -1 ENOENT (No such file or directory)
[pid 32358] execve("/home/john/.node_modules/bin/java", ["java", "-Djava.library.path=.", "-jar", "iKVM.jar", "<IP_ADDRESS>", "ADMIN", "Aoy9g1j", "null", "5900", "623", "0", "0"], [/* 91 vars */]) = -1 ENOENT (No such file or directory)
[pid 32358] execve("/home/john/bin/java", ["java", "-Djava.library.path=.", "-jar", "iKVM.jar", "<IP_ADDRESS>", "ADMIN", "Aoy9g1j", "null", "5900", "623", "0", "0"], [/* 91 vars */]) = -1 ENOENT (No such file or directory)
[pid 32358] execve("/run/wrappers/bin/java", ["java", "-Djava.library.path=.", "-jar", "iKVM.jar", "<IP_ADDRESS>", "ADMIN", "Aoy9g1j", "null", "5900", "623", "0", "0"], [/* 91 vars */]) = -1 ENOENT (No such file or directory)
[pid 32358] execve("/run/wrappers/bin/java", ["java", "-Djava.library.path=.", "-jar", "iKVM.jar", "<IP_ADDRESS>", "ADMIN", "Aoy9g1j", "null", "5900", "623", "0", "0"], [/* 91 vars */]) = -1 ENOENT (No such file or directory)
[pid 32358] execve("/home/john/.nix-profile/bin/java", ["java", "-Djava.library.path=.", "-jar", "iKVM.jar", "<IP_ADDRESS>", "ADMIN", "Aoy9g1j", "null", "5900", "623", "0", "0"], [/* 91 vars */]) = -1 ENOENT (No such file or directory)
[pid 32358] execve("/home/john/.nix-profile/sbin/java", ["java", "-Djava.library.path=.", "-jar", "iKVM.jar", "<IP_ADDRESS>", "ADMIN", "Aoy9g1j", "null", "5900", "623", "0", "0"], [/* 91 vars */]) = -1 ENOENT (No such file or directory)
[pid 32358] execve("/home/john/.nix-profile/lib/kde4/libexec/java", ["java", "-Djava.library.path=.", "-jar", "iKVM.jar", "<IP_ADDRESS>", "ADMIN", "Aoy9g1j", "null", "5900", "623", "0", "0"], [/* 91 vars */]) = -1 ENOENT (No such file or directory)
[pid 32358] execve("/nix/var/nix/profiles/default/bin/java", ["java", "-Djava.library.path=.", "-jar", "iKVM.jar", "<IP_ADDRESS>", "ADMIN", "Aoy9g1j", "null", "5900", "623", "0", "0"], [/* 91 vars */]) = -1 ENOENT (No such file or directory)
[pid 32358] execve("/nix/var/nix/profiles/default/sbin/java", ["java", "-Djava.library.path=.", "-jar", "iKVM.jar", "<IP_ADDRESS>", "ADMIN", "Aoy9g1j", "null", "5900", "623", "0", "0"], [/* 91 vars */]) = -1 ENOENT (No such file or directory)
[pid 32358] execve("/nix/var/nix/profiles/default/lib/kde4/libexec/java", ["java", "-Djava.library.path=.", "-jar", "iKVM.jar", "<IP_ADDRESS>", "ADMIN", "Aoy9g1j", "null", "5900", "623", "0", "0"], [/* 91 vars */]) = -1 ENOENT (No such file or directory)
[pid 32358] execve("/run/current-system/sw/bin/java", ["java", "-Djava.library.path=.", "-jar", "iKVM.jar", "<IP_ADDRESS>", "ADMIN", "Aoy9g1j", "null", "5900", "623", "0", "0"], [/* 91 vars */]) = -1 ENOENT (No such file or directory)
[pid 32358] execve("/run/current-system/sw/sbin/java", ["java", "-Djava.library.path=.", "-jar", "iKVM.jar", "<IP_ADDRESS>", "ADMIN", "Aoy9g1j", "null", "5900", "623", "0", "0"], [/* 91 vars */]) = -1 ENOENT (No such file or directory)
[pid 32358] execve("/run/current-system/sw/lib/kde4/libexec/java", ["java", "-Djava.library.path=.", "-jar", "iKVM.jar", "<IP_ADDRESS>", "ADMIN", "Aoy9g1j", "null", "5900", "623", "0", "0"], [/* 91 vars */]) = -1 ENOENT (No such file or directory)
[pid 32358] +++ exited with 255 +++
[pid 32296] --- SIGCHLD {si_signo=SIGCHLD, si_code=CLD_EXITED, si_pid=32358, si_uid=1000, si_status=255, si_utime=0, si_stime=0} ---

The problem is not iKVM.jar, but you need to extend the PATH of IPMIView in the wrapper to include $out/jre/bin/

Well, that helped, Now at least the error is gone but when I click the button to launch the KVM console nothing happens.
strace shows the following when I launch the KVM console:
[pid 16934] execve("/nix/store/fypifsmnf4yxqjs328dzd12h6j2v8sgq-IPMIView-20151223/jre/bin/java", ["java", "-Djava.library.path=.", "-jar", "iKVM.jar", "<IP_ADDRESS>", "ADMIN", "REDACTED", "null", "5900", "623", "0", "0"], [/* 90 vars */]) = 0
[pid 16934] +++ exited with 1 +++
[pid 16909] --- SIGCHLD {si_signo=SIGCHLD, si_code=CLD_EXITED, si_pid=16934, si_uid=1000, si_status=1, si_utime=0, si_stime=0} ---

I have no motherboard to debug this further. You could check the network traffic.

@Mic92 I was wondering if I might need to set the classpath as was done here, but I wasn't sure what to set it to. Do you think that might be it? I don't know much about java, but it seems to be having trouble launching iKVM.jar.

I suspect that the strace output of:
"java", "-Djava.library.path=.", "-jar", "iKVM.jar", "<IP_ADDRESS>", "ADMIN", "REDACTED", "null", "5900", "623", "0", "0"

is already correct.

OK, thanks for your help.

I guess if you're happy with it this could be committed, could it not? With the commit it at least works other than the KVM console.

For the record: I never got the KVM console to work inside the Nix package.
It has to do with library loading, something among set LD_LIBRARY_PATH to $out

patchelf of libiKVM64.so (a JNI library) has no effect:
$ ldd libiKVM64.so
 linux-vdso.so.1 (0x00007ffd45569000)
 libstdc++.so.6 => not found
 libm.so.6 => /nix/store/l48biijfr1j6d5kdg911051x2phfjrz7-glibc-2.25/lib/libm.so.6 (0x00007fd80a72d000)
 libgcc_s.so.1 => /nix/store/l48biijfr1j6d5kdg911051x2phfjrz7-glibc-2.25/lib/libgcc_s.so.1 (0x00007fd80a517000)
 libc.so.6 => /nix/store/l48biijfr1j6d5kdg911051x2phfjrz7-glibc-2.25/lib/libc.so.6 (0x00007fd80a178000)
 /nix/store/l48biijfr1j6d5kdg911051x2phfjrz7-glibc-2.25/lib64/ld-linux-x86-64.so.2 (0x00007fd80f369000)

There suppose to be something like --set-rpath "${gcc-unwrapped.lib}/lib64" instead of --set-rpath "${gcc.cc}/lib"

Fixed in 41740ec0395059d426a4b3676c45cd886d2249ad thanks


Custom fields

Needed for Great Oak truck issue

Approach 1

Add UserPropertySet model/table much like Community/Cluster, with hard-coded columns like can_use_truck
In Community, have a field called enabled_user_properties, editable only by superadmins, where you whitelist all the UserPropertySet fields that are applicable to this community
Then you still get to use Rails validation, etc., and it's so much less confusing than Approach 2

Approach 2

See notes in Evernote
User should be able to have custom data values
The custom data schema can be defined per-community (see the Per-community Settings issue)
Values should be stored as JSONB
This issue would entail just the backend
Acceptance tests:

Can set schema for a particular community (just use JSON, treat as a text blob setting?)
Having done this, with a user from that community, can CRUD custom values using convenient, form-friendly methods
If schema is changed later, this is handled gracefully
Performance should be good, minimize queries to load all this up, perhaps no need to check schema except when editing user

Originally created by Tom Smyth at 2015-12-31 02:37, migrated from redmine-#3896

Subject changed from Community settings to Settings/custom fields

By Tom Smyth at 2016-04-26 23:48

Priority changed from 3 to 2

By Tom Smyth at 2016-01-04 08:05

Category set to Public Release

By Tom Smyth at 2016-05-22 21:44

Priority changed from 2 to 4

By Tom Smyth at 2016-09-08 06:05

Description updated (diff)

By Tom Smyth at 2016-10-23 18:35

Subject changed from Settings/custom fields to Custom fields

Description updated (diff)
Category deleted ( ~~ Public Release~~ )
Estimate changed from 3.00 h to 8.00 h

By Tom Smyth at 2016-10-23 18:16


window variable

If use webpack entry built, it does not write variables on the window?

I see #14 .


Fix docs for index

Clarify storage of timestamps and refs in the index

/cc @Gouthamve

Thanks!


win1251 real specs

Coverage decreased (-0.02%) when pulling 190c8ce83b0274fa69c75961134828c47d48bcf2 on win1251 into a9da685f882ce1bad3cb1ff2bd0367c88ba4dc3f on master.

Changes Unknown when pulling 4b45ddf40232a37d5c48407434197fbc39d96a0a on win1251 into ** on master**.

Changes Unknown when pulling 3993cab62b3205f92f0d2f307b7d3f81ecd34c91 on win1251 into ** on master**.

Coverage decreased (-0.02%) when pulling d5e504e7e82df5c326ee5d64367fcacb7dbc0988 on win1251 into 648bfa0ea0280c65735201fc87c3f56218f7fe59 on master.

Coverage decreased (-0.02%) when pulling d5e504e7e82df5c326ee5d64367fcacb7dbc0988 on win1251 into 648bfa0ea0280c65735201fc87c3f56218f7fe59 on master.

Coverage decreased (-0.02%) when pulling d5e504e7e82df5c326ee5d64367fcacb7dbc0988 on win1251 into 648bfa0ea0280c65735201fc87c3f56218f7fe59 on master.

Coverage decreased (-0.02%) when pulling d5e504e7e82df5c326ee5d64367fcacb7dbc0988 on win1251 into 648bfa0ea0280c65735201fc87c3f56218f7fe59 on master.

Coverage decreased (-0.02%) when pulling d5e504e7e82df5c326ee5d64367fcacb7dbc0988 on win1251 into 648bfa0ea0280c65735201fc87c3f56218f7fe59 on master.


Session gets stuck and shows connected/connecting

After a few days, the WhatsApp instance stops responding sometimes it's stuck on "connecting" or "connected" without any response.
The only ways you can enable it is to delete and add again or restart the server.
Is there a way I can monitor the instance and watch if the variable is still in the session array, that way I can restart it without deleting or restarting the app?

If the device, where whatsapp is installed, is not online within 72 hours whatsapp, and the web becomes online, it disconnects automatically.
What I do here is restart every day via cron
Or you can also use npm restart.


Cards 8 and 9 not rendering on (some?) mobile phones

On my mobile phone, in either desktop or mobile phone view, cards 8 and 9 of the Celtic cross reading do not render properly.
Chrome 92.0.4515.131
Android 11; Pixel 3a Build/RQ30A.210704.001

On further inspection, you can see a little frowny face for the two cards that aren't rendering. I think this is a graphic produced by PIXI when it fails to render. I suspect this is a memory exhaustion issue, maybe related to creating too many WebGL contexts.
See here.


Double-click, too?

It'd be great to be able to differentiate a double-click-input from a single click on any given selection, too.

Why? Can you give an example of a (system) app that uses this pattern?

Run a script/visit link OR copy literal script/link contents to the clipboard (eg AKAlias run script or copy to clipboard).
Visit link A OR visit link B (eg Github notifications view or mark-as-read).

Are you aware of the alternate parameter? Tutorial: https://getbitbar.com/plugins/Tutorial/alternate_options.sh


chore: release master

:robot: I have created a release beep boop
ck3oop-ui: 0.1.1
0.1.1 (2024-06-18)
Features

Fake feat (68e50e9)
Fake feat (a666e07)
Fake feat (9fc2da5)
rust-core: Mod file parsing (03ce8e1)

ck3oop-core-js: 0.1.1
0.1.1 (2024-06-18)
Features

Fake feat (9fc2da5)

ck3oop-ui-js: 0.1.1
0.1.1 (2024-06-18)
Features

Fake feat (9fc2da5)

Dependencies

The following workspace dependencies were updated

dependencies

ck3oop-core-js bumped from ^0.1.0 to ^0.1.1

ck3oop-core-rs: 0.1.1
0.1.1 (2024-06-18)
Features

Fake feat (a666e07)
rust-core: Mod file parsing (03ce8e1)

ck3oop-ui-rs: 0.0.2
Dependencies

The following workspace dependencies were updated

dependencies

ck3oop-core-rs bumped from 0.1.0 to 0.1.1

This PR was generated with Release Please. See documentation.

:robot: Created releases:

ck3oop-ui-v0.1.1
ck3oop-core-js-v0.1.1
ck3oop-ui-js-v0.1.1
ck3oop-core-rs-v0.1.1
ck3oop-ui-rs-v0.0.2
:sunflower:


Updating with keybase-installer fails

On Debian unstable, I am unable to update keybase.
When I run keybase-installer as myself, it fails because it cannot unlink /usr/local/lib/node_modules/keybase:
npm ERR! error rolling back Error: EACCES: permission denied, unlink '/usr/local/lib/node_modules/keybase'

When I run keybase-installer as root, it fails with the following output:
[matijs@walnut] sudo keybase-installer
info: Made temporary directory: /tmp/keybase_install_BWlzfd5n7n_Cu8QE0gaiyg
info: Using keyset version v1
info: Fetching URL https://dist.keybase.io/sig/files/1/index.asc
info: cleaning up tmpdir /tmp/keybase_install_BWlzfd5n7n_Cu8QE0gaiyg
error: exit code 2
warn: gpg: key 7F9E8BFA: public key "Keybase.io Index Signing (v1<EMAIL_ADDRESS>imported
warn: gpg: failed to create temporary file '/root/.gnupg/.#lk0x00005587eb757490.walnut.7322': No such file or directory
warn: gpg: can't connect to the agent: No such file or directory
warn: gpg: Total number processed: 1
warn: gpg:               imported: 1
warn: gpg: no ultimately trusted keys found

mkdir /root/.gnupgp as root
On Fri, Oct 16, 2015 at 8:14 AM, Matijs van Zuijlen <
<EMAIL_ADDRESS>wrote:

On Debian unstable, I am unable to update keybase.
When I run keybase-installer as myself, it fails because it cannot unlink
/usr/local/lib/node_modules/keybase:
npm ERR! error rolling back Error: EACCES: permission denied, unlink '/usr/local/lib/node_modules/keybase'
When I run keybase-installer as root, it fails with the following output:
[matijs@walnut] sudo keybase-installer
info: Made temporary directory: /tmp/keybase_install_BWlzfd5n7n_Cu8QE0gaiyg
info: Using keyset version v1
info: Fetching URL https://dist.keybase.io/sig/files/1/index.asc
info: cleaning up tmpdir /tmp/keybase_install_BWlzfd5n7n_Cu8QE0gaiyg
error: exit code 2
warn: gpg: key 7F9E8BFA: public key "Keybase.io Index Signing (v1<EMAIL_ADDRESS>imported
warn: gpg: failed to create temporary file '/root/.gnupg/.#lk0x00005587eb757490.walnut.7322': No such file or directory
warn: gpg: can't connect to the agent: No such file or directory
warn: gpg: Total number processed: 1
warn: gpg:               imported: 1
warn: gpg: no ultimately trusted keys found
—
Reply to this email directly or view it on GitHub
https://github.com/keybase/node-installer/issues/72.

Thanks, that worked!


Self labels test keeps failing

The integration test for self-labelling keeps failing in CI.
Logs
See also https://github.com/strideynet/bsky-furry-feed/actions/runs/5916587573/job/16044028143?pr=148
    logger.go:130: 2023-08-20T09:31:13.476Z	ERROR	failed to handle repo commit	{"error": "create (at://did:plc:c1e1ee347119cd4f/app.bsky.feed.post/3k5exq62yqer): handling record create: handling app.bsky.feed.post create: creating post: executing CreateCandidatePost query: failed to encode args[6]: unable to encode &bsky.FeedPost{LexiconTypeID:\"app.bsky.feed.post\", CreatedAt:\"2023-08-20T09:31:13.386Z\", Embed:(*bsky.FeedPost_Embed)(nil), Entities:[]*bsky.FeedPost_Entity(nil), Facets:[]*bsky.RichtextFacet(nil), Labels:(*bsky.FeedPost_Labels)(0xc000584c90), Langs:[]string(nil), Reply:(*bsky.FeedPost_ReplyRef)(nil), Text:\"paws paws paws\"} into text format for jsonb (OID 3802): json: error calling MarshalJSON for type *bsky.FeedPost_Labels: cannot marshal empty enum"}

...

    ingester_test.go:280:
        	Error Trace:	/home/runner/work/bsky-furry-feed/bsky-furry-feed/ingester/ingester_test.go:282
        	            				/opt/hostedtoolcache/go/1.21.0/x64/src/runtime/asm_amd64.s:1650
        	Error:      	Received unexpected error:
        	            	no rows in result set
    ingester_test.go:280:
        	Error Trace:	/home/runner/work/bsky-furry-feed/bsky-furry-feed/ingester/ingester_test.go:280
        	Error:      	Condition never satisfied
        	Test:       	TestFirehoseIngester/waiting_for_posts/self_labels

Caused by https://github.com/bluesky-social/indigo/issues/281


Getting error on locate command

sudipta@Sudipta-Sen-W1FJVTJHQX  ~  python3env  subarulink locate                                                                                 ✔  4275  09:18:43
Traceback (most recent call last):
  File "/Users/sudipta/python3env/bin/subarulink", line 8, in <module>
    sys.exit(main())
  File "/Users/sudipta/python3env/lib/python3.9/site-packages/subarulink/app/cli.py", line 715, in main
    LOOP.run_until_complete(cli.single_command(args.command, args.vin, cli.config))
  File<EMAIL_ADDRESS>line 647, in run_until_complete
    return future.result()
  File "/Users/sudipta/python3env/lib/python3.9/site-packages/subarulink/app/cli.py", line 555, in single_command
    print(f"Longitude:\t{self.car_data['status'].get('longitude')}")
KeyError: 'status'
Unclosed client session
client_session: <aiohttp.client.ClientSession object at 0x103b4a2e0>
Unclosed connector
connections: ['[(<aiohttp.client_proto.ResponseHandler object at 0x103b730a0>, 17.977914666)]']
connector: <aiohttp.connector.TCPConnector object at 0x103b4a310>

Is this Unclosed connector going to drain the battery?

No, it won't drain the battery or do anything to affect your car. I'll try to fix the bug soon (I renamed some constants recently and it looks like I didn't incorporate them into the CLI)

Bug should be fixed now in v0.7.5

Yeah it's fixed. Thank you.


You are receiving this because you authored the thread.Message ID:
@.***>


Update the workflows to match covalent devops

[ ] I have added the tests to cover my changes.
[x] I have updated the documentation, VERSION, and CHANGELOG accordingly.
[x] I have read the CONTRIBUTING document.

@venkatBala once this is merged into develop, open a PR which merges develop-covalent into develop.

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you all sign our Contributor License Agreement before we can accept your contribution.1 out of 2 committers have signed the CLA.:white_check_mark: venkatBala:x: wjcunningham7You have signed the CLA already but the status is still pending? Let us recheck it.


Update to Latest Node 8 LTS

Update Node 8 image to 8.12.
closes #65

 Thank you for your submission, we really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

Could you update NPM as well, to 6.4.1?

@rybon, absolutely. Done.

that's great update @juancarlosfarah can you also update info in README.md in folder https://github.com/cypress-io/cypress-docker-images/tree/master/base please?

@bahmutov, not a problem! Just updated the info.

great, @juancarlosfarah I am landing this and will start the docker hub build

Done, it has built hub image
 ---> Running in 856d32026169

v8.12.0

Removing intermediate container 856d32026169

 ---> 1190c97ed76d

Step 5/6 : RUN npm -v

 ---> Running in 7a9e63261e8c

6.4.1

Removing intermediate container 7a9e63261e8c

 ---> 6636a135f4e3

Step 6/6 : RUN yarn -v

 ---> Running in 382d34c4b2b7

1.9.4


[Feature Request]: Improve status of workbench when pod is unschedulable

Feature description
When attempting to start a workbench, if the pod is unschedulable the workbench appears to be "Starting" for a long time with no feedback to the user on what the issue is.
Pods not being scheduled could happen for many different reasons including GPU's not being available, CPU/Memory not being available, quota limits, issues with PVCs such as a RWO pvc already being mounted to another Workbench, etc.
The dashboard should provide more context to what is happening with the pod.
A few different options...

Instead of only displaying "Starting" and "Running" map the display directly the pods status and show things like "ContainerCreating", "Pending", etc.
Expose specific events on the workbench page that you want the user to see.
Provide a link directly to the pod events or details that allows a user to inspect what is going on.

Describe alternatives you've considered
No response
Anything else?
No response

This looks to be solved with https://github.com/opendatahub-io/odh-dashboard/issues/749 -- Which should be in ODH 1.4.1 Operator.
We include an underline now on the Starting... to indicate it is clickable for more information on the starting. When there is an error we add an error (!) with a tooltip saying what happened. It is also clickable and will grant more information as well.


[Trivial] fix dependency for fedora

Not sure if this is a typo or package name is changed, but libclang-dev does not exist on dns packages. Change to the correct name and verified on Fedora 38.

Codecov Report

Merging #1908 (230d8b2) into main (d616ebf) will increase coverage by 0.02%.
The diff coverage is n/a.

:exclamation: Current head 230d8b2 differs from pull request most recent head 73bdd11. Consider uploading reports for the commit 73bdd11 to get more accurate results

Additional details and impacted files
@@            Coverage Diff             @@
##             main    #1908      +/-   ##
==========================================
+ Coverage   67.33%   67.36%   +0.02%
==========================================
  Files         126      126
  Lines       14265    14265
==========================================
+ Hits         9606     9610       +4
+ Misses       4659     4655       -4


Reduce timeout module.

Module checks should not take more than seconds. We spend 5 min retrying the module check when the requests time out.

Could you please explain why this change was made, either in a comment or in a PR description? Thanks

Added to the description.


Cannot read propery 'STATE_NONE' of undefined

import TrackPlayer from 'react-native-track-player';
could not importing TrackPlayer

To solve this I had to do this https://github.com/react-native-kit/react-native-track-player/wiki/Installation#ios-library-not-found-for--lswiftcoreaudio-for-architecture-x86_64
Then I restarted the bundler and everything was ok. We could do something like this in lib/index.js on lines 12-14 to catch something like this and provide at least a helpful message:
if (!TrackPlayer) {
  console.error("FATAL: FAILED TO LOAD TrackPlayer from NativeModules, did you enable swift in this project? https://github.com/react-native-kit/react-native-track-player/wiki/Installation#ios-library-not-found-for--lswiftcoreaudio-for-architecture-x86_64");
}

I had this error on iOS. As @jimthedev mentioned, I went ahead and created the dummy.swift file within Xcode and that fixed it. https://github.com/react-native-kit/react-native-track-player/wiki/Installation#ios-library-not-found-for--lswiftcoreaudio-for-architecture-x86_64

I looked at the console output after running react-native run-ios and found some errors, including PCH was compiled with module cache path.... I fixed it by going XCode - Product - Clean and then
running rm -r ios/build.
https://stackoverflow.com/questions/15463179/how-to-fix-pch-error

What if you have the same issue on Android ?


Review of overview section

Looking at the following sentence: "When a new system of record is registered via the data agnostic or onboarding application, it should create the required folders on the containers in the raw, enriched and standardized data layers. "
Few things require review.

if naming convention is important then standardized is not a layer according to the chart above this sentence , it's a container, so is this meant to be "curated" ?
the sentence seems to be missing something before or after "data agnostic"
I would imagine that it's unlikely that a new SOR will need a folder in all 3 layers up front, definitely one for ingestion/raw and maybe another for enriched but by the time it's left raw, it may become something completely different being joined to another SOR perhaps.

Looking at the following paragraph there seems to be a mix/ambiguity of terms between folders vs containers and layers and zones which the guidance is applicable to:
"Each data product should have two folders in the curated data lake layer over which the data product team should have ownership.
At the standardized container, in the enriched zone, there would be two folders per source system divided by classification. This will allow the team to store data with different security and data classification separately and different security access can be assigned to them. The container would contain a general folder, for confidential or below, and a sensitive personal data folder. Access will be controlled, by access control lists (ACLs). By having these two folders, you can choose to create a dataset with all the personal data removed located in the general folder. You can then have another dataset with all personal data in the sensitive personal data folder."
The sentence "A child file's access control list (ACL) files do not have a default ACL. " I think is meant to read "A child file's access control list (ACL) do not have a default ACL. "
The sentence " You might choose to store the data in its original format, such as JSON or .CSV. But there might be scenarios where it makes sense to store it as a column in compressed format..." should perhaps read " You might choose to store the data in its original format, such as JSON or CSV, but there might be also scenarios where it is more cost effective to store the contents of the file as a column in a compressed file format..."
Thanks

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

ID: b1a9e844-d37a-9ca3-37b4-62a8e5a216f9
Version Independent ID: b1a9e844-d37a-9ca3-37b4-62a8e5a216f9
Content: Provision three Azure Data Lake Storage Gen2 accounts for each data landing zone - Cloud Adoption Framework
Content Source: docs/scenarios/data-management/best-practices/data-lake-zones.md
Service: cloud-adoption-framework
Sub-service: scenario
GitHub Login: @mboswell
Microsoft Alias: mboswell

Great feedback @hurtn
#assign: @mboswell
#label:"data management and analytics"

The following users don't have valid GitHub IDs, or are not collaborators on this repo: bel"data managemen

#assign: @mboswell

edits made and updated

#please-close


Fix multiprocessing X display collisions by utilizing flock

Fixes: #16 & #15, makes #14 obsolete
I've run into this issue as well.
This change uses fcntl.flock to create a lock file, ensuring multi-process safe display IDs.
It includes a test case, however I've not yet tested it using a production load. I expect to in the next week or so.
Let me know if you have any questions. Hopefully this change puts all concurrency issues to rest.

Have done some more testing and fixed a nasty multi-threading issue. This is working fine for me and has been stress-tested with lots of concurrency.

I just came across one stray issue. I will look into it and try to understand why this could have happened.
PermissionError: [Errno 13] Permission denied: '/tmp/.X23405-lock'

LGTM :+1:
@fuhrysteve , thanks for the patch! (and extra thanks for including an accompanying test)

PermissionError: [Errno 13] Permission denied: '/tmp/.X23405-lock'

did you find out anything about this?  I'd like to get that figured out before merging your PR.

hmmm.. your branch has failing tests under Python3.2 and pypy 2.7.  You can run tests across all versions with tox.

I just removed Python3.2 support and pushed a change for that to master
pypy 2.7 is failing to install mock.  Needs more investigation.

I'll take a look more later on today.

@cgoldberg I'm not sure what caused the PermissionError. It could be due to an issue I had with closing the file in an earlier version of this. I haven't been able to reproduce it again, though.
Here's the relevant portion of the stack from when it occurred:
PermissionError: [Errno 13] Permission denied: '/tmp/.X23405-lock'
    File "xxxx.py", line nn, in __enter__
    self.xvfb.start()
  File "xvfbwrapper/xvfbwrapper.py", line 63, in start
    self.new_display = self._get_next_unused_display()
  File "xvfbwrapper/xvfbwrapper.py", line 122, in _get_next_unused_display
    self._lock_display_file = open(tempfile_path.format(rand), 'w')

Ok, that seems to fix the issue for pypy. As for python 3.2, this looks like a pip compatibility issue. I think pip 8.x dropped support for python 3.2 since they tried to remove the u string prefix in it, but brought it back in python 3.3. I suggest just dropping support for 3.2.. let me know if you disagree and I'll revert

Looks like you beat me to the punch upstream with dropping 3.2! Rebased that out

either travis or launchpad seems to be having some network connectivity issues. I believe these tests will pass if we retry the build later.

Still no idea what caused that PermissionError. At this point I suspect it's either an environment issue on my end, or a bug in an earlier version of this where I was closing & deleting the file in BlockingIOError (which was a defect that somewhat hilariously defeated the whole purpose of this change).

@fuhrysteve i finally had the time to do a more proper review, and your new changes are excellent... clean robust code and tests.  tbh I'm not used to FOSS contributions that well done.  Some PR's can be painful to review or reject.  so thanks a bunch.  I'm going to merge this PR as-is.
p.s.
sorry I sat in this for nearly 2 weeks.  life interrupted ;)
I'll plan to do a new release containing this pretty soon.

Thanks @cgoldberg!


New selection box implementation for component groups

Pull Request Description
Task link.
[ci no changelog needed]
This PR implements a new selection box that will replace an old (not really working) one in the component browser. The old selection box wasn't working well with the headers of the component groups, so we were forced to make a much harder implementation.
The new implementation duplicates some visual components and places them in a separate layer. Then, a rectangular mask cuts off everything that is not "selected". This way:

We have more control over what the selected entries should look like.
We can easily support the multi-layer structure of the component groups with headers.
We avoid problems with nested masks that our renderer doesn't support at the moment.

To be more precise, we duplicate the following:

Background of the component group becomes the "fill" of the selection.
Entries text and icons - we can alter them easily.
Header background and header text. By placing them in separate scene layers we ensure correct rendering order.

https://user-images.githubusercontent.com/6566674/173657899-1067f538-4329-44f9-9dc2-78c8a4708b5a.mp4
Important Notes

This PR implements the base of our future selection mechanism, selecting entries with a mouse and keyboard still has several issues that will be fixed in the future tasks.
The scrolling behavior will also be improved in future tasks. Right we only restrict the selection box position so that it never leaves the borders of the component group.
I added a new function to add shapes to new layers in a non-exclusive way (we had only add_exclusive) before. I have no idea how we didn't use this feature before even though we mention it a lot in the docs.
The demo scene restricts the position of the selection box for one-column component groups but does not for the wide component group.

Checklist
Please include the following checklist in your PR:

[x] The documentation has been updated if necessary.
[x] All code conforms to the
Scala,
Java,
and
Rust
style guides.
All code has been tested:

[x] Unit tests have been written where possible.
[x] If GUI codebase was changed: Enso GUI was tested when built using BOTH
./run ide dist and ./run ide watch.

QA acceptance passed, merging it now.


how can we make index_key available for splunk-objects?

Just like in spunk-logging,  how can we make index_key available for splunk-objects?
Basically, i want to redirect the splunk objects to diferent index based on the variable index_key.  Thanks.

@beth2016 that is not currently supported. You may want to head over to https://github.com/splunk/fluent-plugin-kubernetes-objects and submit a feature request.

You will need to use the jq_transformer to add the index field as part of the filters before they get sent with the hec plugin, similar to how we use it to set the source, etc.
    <filter kube.**>
      @type jq_transformer
      jq '.record.index = "my_index" | .record'
    </filter>

similar to
https://github.com/splunk/splunk-connect-for-kubernetes/blob/7292e173e4fdc496e92ba4ebc3a187abb62e0a37/manifests/splunk-kubernetes-objects/configMap.yaml#L39-L42

@matthewmodestino   Thanks.   I will give that a try.  You are awesome.


Why not implement this in Pytorch?

Pytorch has a mps backend but it is kind of frugal.

This is a question we get asked a lot. Before I get started on why, let me say we like PyTorch a lot, we use it often, and much of our higher-level neural net library was inspired by it.

Apple silicon first
First and foremost, we wanted to design MLX for Apple silicon. This means among other things taking advantage of unified memory. When you make an array in MLX you do not have to specify what device it resides on, you just make it. Operations run on devices without needing to copy arrays. For example:
a = mx.random.normal((100,))
b = mx.random.normal((100,))
mx.add(a, b, stream=mx.cpu)
mx.add(a, b, stream=mx.gpu)

There are no copies of either a or b even though the operations are running on different devices. Furthermore, MLX will run those operations in parallel since they can be run on different devices, and there are no dependencies between them. This seemingly small change to the programming model would be very difficult to implement in PyTorch. And we hope that it will open the door to new and interesting algorithms (for machine learning or otherwise).
Alternative Design and API
We do some things differently than PyTorch. For example, our array API mirrors NumPy, which we think is important. Our function transformations are composable like Jax. Computations are lazy, which can be really useful. But graphs are still built dynamically, which makes debugging easy and changing the sizes of array arguments to functions trivial.
These are all features that we wanted to include. We had the luxury of picking the best from all the frameworks we've used and worked on in the past and combining them into something new.
Simple, Flexible, Baggage-Free
Like everything else in this world, machine learning frameworks obey the second law of thermodynamics — they have a tendency towards increasing entropy.  Since AI is still changing rapidly, as frameworks age they get more complex and are harder to improve, and adapt. We believe that a new framework like ours, which is still (relatively) pretty simple and hackable, might be a good starting point for people looking to explore new ideas.
For example, tracing through the MLX stack to find or change how things work is doable, even for researchers without extensive experience in framework engineering. Similarly, you can easily add custom Metal (GPU) kernels to try out new ideas or optimizations.
More Exploration, More Diversity
Historically the success of different machine learning paradigms has been pretty tied to the available hardware.  It's hard to argue with the fact that the success of deep learning depended a lot on its coevolution with GPUs. Apple silicon has some new and interesting characteristics that may benefit new algorithms. But we need frameworks, i.e. MLX,  that let us explore that. In general we think that more diversity for ML researchers both on the hardware side and the supporting software is always a good thing.
Oh, and also @andresy really likes writing array frameworks 😉

This is a good start for Mac studio users!

No  means to offend you, but most of the deep learning enthusiasts around me really love using PyTorch on "Mac OS ".
So, here's the situation:
  1. When we need to quickly verify our deep learning algorithms, we use SSH to remotely connect to a server with a PyTorch environment on Mac OS. Then, we debug locally. Once successful, we utilize the GPU on the server for training.

  2.Currently, most projects and top-tier open-source projects are based on the PyTorch framework. Personally, I really don't want to rewrite projects that have already been open-sourced using your framework.

I might understand your approach, but I sincerely hope your team can consider the perspective of developers who use Mac OS and are passionate about deep learning."

I hope that this repo will gain traction among developers who are focused on device-based inference apps.

I think there's certainly space for something like this. Some people (including me) realised that Apple Silicon, today, is the most affordable option for having a proper amount of memory with machine learning. Compare a maxed out Mac Studio M2 Ultra with 192GB ram , it's 8K or so , with a Nvidia A100 40GB, it's already 20-25K, you would need 4 or 5 to match the amount of RAM! I know, that computation also matters and is somewhat slower on the Mac GPU, but considering the cost difference that's easily compensated by e.g. buying 2 and distributing the learning.
So far I've successfully used this approach with tensorflow-mac . However, an Apple-Silicon native framework that optimises  the use of unified memory is awesome. Also, I do like the simplicity and compactness of the framework.
I do hope this won't reduce the effort Apple spends on tf-mac and PyTorch MPS compatibility, but I think there's no reason all of this can be combined. Great effort!

Hello, friend:
I'm glad you've realized this. Apple indeed has the advantage of unified memory. This is a crucial foundation for diversifying the entire field of deep learning. When I first read the approach you presented, it excited me. However, the more I think about it, the more something seems amiss.
Let's put aside the field of deep learning and delve into another topic. Apple, as a company, has certainly diversified the entire IT world. They've created one of the three major operating systems: Windows, Linux, and macOS.
Windows operating system supports both Intel and AMD chips. While profiting themselves, they've shared some profits with other companies, allowing them to gain as well. Simultaneously, software like PyTorch and TensorFlow supports this kind of hardware.
Linux is open-source and fully supported by PyTorch and TensorFlow.
macOS: When using Intel chips, PyTorch and TensorFlow are supported. After discontinuing Intel chips and embarking on their own chip journey, they've laid the groundwork for diversifying deep learning, from software to hardware, utilizing their in-house products.
I'm eagerly anticipating how MLX will perform on the Mac Studio M3. Have you noticed that despite having 36GB of RAM, the highest supported ROM on the Mac M3 Pro is only 512GB? If you take a moment to review historical events, monopolies often result in outcomes that aren't too consumer-friendly.
If they truly aim to diversify deep learning, simply being compatible with PyTorch would suffice.
Sometimes, it's not just about what's said; it's equally important to observe what actions are taken.

That's an interesting perspective, but I respectfully disagree with it :).
In the machine learning space, Apple is David & NVidia is Goliath. Their objective is not necessarily to "diversify the deep learning space". Their objective could be, become an important player in this space, and deliver a great value. Only by doing that, by the way, they'll be able to reach that objective. Nvidia has the near-monopoly in this space, not apple.
Based on that, continue your thinking: how can Apple be strong player in this space? Using their traditional model: full vertical integration! Hardware & software optimised hand in hand to create one awesome user experience. That's what MLX is for machine learning. My point on unified memory is specifically about the fact that PyTorch is from the ground up conceived with a separated memory space and copies all around. Maybe unified memory can be "forced" into it, but it would probably be a suboptimal experience overall. In the MLX world things around unified memory are trivially simple, as I've noticed when trying it out.
I'm owning a machine learning team and program in my organisation, and the decision to go with Apple Silicon has saved me about 200K over 2 years (2023 and 2024 projected) and the 2 years after that I expect to save 500K. And this is for a relatively small team/machine learning setup. Models are being trained & being run, I'm getting the value now.
Again, respectfully, I think if you go deeper than the surface on some of the things you mention, you'll see that they turn out to be not as dire as you say. For example, the M3 Pro having 128GB of RAM (you said 512GB of ROM but I suppose you mistyped?). In any case, that's normal because of 2 factors: the memory bandwidth and speed in Apple Silicon is (close to) GPU grade, which is the only way unified memory can work. This memory needs a large bus, controller, ... Depending on the M3 model, this bus is smaller or bigger, and looking at the M2: the M2 PRO has 96GB limit, the M2ultra 192GB (which is what we have). That's not a coincidence: the M2ultra is basically 2 M2's combined. So, the limits stem from the nature of the chips specifications and is not artificial rather it's more inherent. In the end, as I mentioned, the cost is an order of magnitude lower these days for Apple Silicon compared to Nvidia, of course for this application taking the heaviest Apple Silicon there is, is a must. And, for the M3: of course the M3 ultra will still have to be brought out. By the way: in the Mac Studio example, there's also a super speed well integrated 8TB local data (SSD) option, which, when I compared to cloud computing and Azure SSD costs are an order of magnitude faster (again) and an order of magnitude cheaper as well!
Additionally, as someone else remarked, having mlx as an open source library will allow the community of PyTorch to more easily connect that to metal.
So, rather than hypothesising how Apple could go from a detail in the machine learning market to a monopoly (that would be quite a turnaround) and practice unfair behaviour in that market, for now they are upcoming in the space, need to prove a lot, and will only grow when they provide value.
For me, on the hardware level, they've made an almost unbelievable advance in value for money. And, true to their strategy, if they can combine this with a nice integrated software stack that offers simplicity and synergy, they will become a potential great player in that market. It'll also depend if they decide to start offering servers /dedicated ML products etc, that's to be seen.
From an overall market influence perspective, I think you can go to the bank on having one impact before everything else: if Apple goes from "negligible" to being "a small player in deep learning space", Nvidia will be required to adjust their pricing. This is probably the first tangible market impact there would be. Nvidia's prices are ridiculous, their consumer GPU's artificially limited in memory, their server GPU's have more memory (still not very impressive) but are costed beyond any reasonable amount (25K for a 40GB card?). Let alone, that they are purchasable anywhere. This Nvidia near-monopoly is because of their great CUDA and software stack overall.
So, in summary - this will only improve things, you can only judge on what you see, and what you see is Apple trying to deliver more value in this space, I don't see how that can be a bad thing :).
Now I'll go back to porting my latest model to MLX, the first results are awesome, works fluently, super easy to translate, there's a nice data pipeline as well, ... this is just a pleasure to use!

I have to say, Apple is really lucky to have users like you.  :)

Thanks all for this , you guys truly gave a new opportunity to Apple. And thanks for all the good arguments. Happy to have made a good choice buying a silicon machine even before this was out. And god knows I did have a lot of reason not to trust Apple anymore !

@chumingqian, it's not luck. For all there many shortcomings, Apple has long offered users things that weren't available elsewhere. People who get caught up in specs tend to be blind to it, and put it down to "marketing."

[...] so it seems like the envisioned future of this library is to develop apps that run natively on MacOS. It's a bit of a shame, because it will be much harder to use this software on other architectures.

@wisefool769 There are multiple options if you want software that runs on other architectures. What would be the point in another framework that runs on other architectures when that limits what's possible (in terms of some combination of performance, memory efficiency and development velocity) on Apple's unified memory architecture?
I hope Apple invests in getting MPS support in PyTorch to the point where GPU accelerated LLM training with existing PyTorch toolkits requires no extra effort on the part of end users. I also hope that between internal and external developers, MLX gets to the point where people think twice before grabbing something from the PyTorch toolbox.

I hold the same question in my mind, why not combine with Torch.  I think one thing that will obstruct MLX development is the Apple silicon, which is also its target audience .  As a Kaggler, sometime I will debug code locally and then run the result using GPU provided by Kaggle. Using PyTorch, I can easily switch between MPS/GPU using  torch.device( 'mps' if torch.backends.mps.is_available() else 'cuda') , no need to modify the code. However, using MLX I may need to rewrite the code and not  efficient as a result.    However, I love this package much since it is the one to unleash the full power of Apple silicon for Deep Learning.

Related: https://github.com/keras-team/keras/issues/18961
FYI: The new Keras allows you to mix-and-match PyTorch, JAX, and TensorFlow.

What would be the point in another framework that runs on other architectures when that limits what's possible

I would love to better understand how PyTorch is limiting, beyond a greater level of bureaucracy from committing to an established project.

Architecturewise pythorch cannot deal with unified memory easily so it’s not the best option at all for silicon architecture. Moreover You can still use pythorch and MLC if you like. NVidia did exactly the same thing with Cuda and now nobody complains. Unified memory is the way to have cheaper AI computing and in ten years everyone will use it like everyone use Cuda today. Maintaining parallel dev is the standard as technologies evolve. Break are necessary to pass new levels or we would still have x86 32b.

As MLX is designed for the lazy computation and unified memory. I guess that should have some relationship with the paper [LLM in flash] (http://export.arxiv.org/abs/2312.11514).

Maybe my question is stupid but, what if instead of making MLX compatible with PyTorch we tried to make cuda compatible with a simplified version of MLX ? This way we could use almost the same code everywhere ?

what if instead of making MLX compatible with PyTorch we tried to make cuda compatible with a simplified version of MLX

Interesting question. Most of the METAL backend is abstracted nicely so you can currently compile MLX for CPU only mode. That also means adding another back-end is very possible. With CUDA the main issue I see is how you deal with the unified memory programming model. We don't want to change the API, so what happens in the following:
c = mx.matmul(a, b, stream=mx.gpu) # CUDA gpu in this case
# c is in GPU RAM at this point
d = mx.sine(c, stream=mx.cpu) # Does this silently copy c?

I'm not sure if we have any other option except an implicit copy as adding operations to move arrays between memory spaces to the core API is probably not a good idea.

It’s necessary for Apple to have its own easy-to-use framework for Apple Silicon because all third-party frameworks have to consider the compatibility of other platforms, let alone most of them prioritize the development/optimization for other platforms.

An alternative frugal  kit of openai/triton, CUDA  is also necessary  for Apple silicon to support the other akin computional fields, like as bioinformatics, computional chemistry.

Is it possible to convert MLX trained model to other frameworks for inference like TFLite, PyTorch mobile, ONX, CoreML for iOS? How easy it is to convert models from MLX to PyTorch or TensorFlow?

@ramkumarkoppu It's not in https://github.com/onnx/onnxmltools, but there is an open issue here https://github.com/ml-explore/mlx/issues/290 requesting this feature

Ivy (which is like babel from the NodeJS ecosystem) is also working on adding MLX as a supported framework https://github.com/unifyai/ivy/issues/27458. It should be pretty easy to transpile models across all major frameworks in 2024 soon.

AMD/Nvidia is also working on shared memory, that is different from unified memory that means that you use your ram as GPU memory, because with recent kernels of linux, your memory is HMM https://www.kernel.org/doc/html/v5.0/vm/hmm.html
Also AMD has some new APU's and Nvidia with Nvidia Grace have the same idea from apple, unified memory in all system.
It could be amazing that if exists a decorator to convert all pytorch code to mlx.

adding operations to move arrays between memory spaces to the core API is probably not a good idea

FWIW, the array API standard has to_device as a method of the array object.

"I thought that the unified memory system on the M-series chips would reduce copying overheads. Perhaps this is not yet the case from a software perspective (e.g. PyTorch and TensorFlow are not designed for Apple Silicon).
Maybe newer frameworks designed for Apple Silicon such as MLX will better utilise the unified memory system. This will require further investigation."
-- from the article
https://towardsdatascience.com/apple-m3-machine-learning-speed-test-f1346e23a1b2

Is it possible to use the MLX compiled/trained models with other frameworks like torch?
I.e., can I run an MLX model on Cuda afterwards?

Speaking of which, it would be very convenient if there was the invention of a pytorch to MLX code converter, similar to how it exists for language to langauge conversions

Lowering Triton to a Metal backend?


Consider using old-style figs for numbers in results/in general to avoid them jumping out as large like capital letters

Our base font has this as an alternate.

These are particularly jarring in text like news item titles.

This was surprisingly easy with the widely supported font-variant-numeric.
851bc338.