100% CPU usage reading from 115200 baud serial port

This may be a general node.js issue, but I'm keen to learn the experts opinion on this. We are using nodejs on an Arduino YUN (MIPS 400 MHz). The serial port sends data at 115200 baud (fully saturated).
When I run a simple serial program to just receive the data from the serial port (and do nothing with it), it maxes out the CPU at 100% (about 70% user, 30% system according to top):
'use strict';

var port = '/dev/ttyATH0';

var SerialPort = require("serialport").SerialPort;
var rs = new SerialPort(port, {
  baudrate: 115200,
  buffersize: 1024
});

rs.on('open', function () {
  console.log('port opened!');
});

rs.on('data', function (data) {
  // console.log(data);
});

The problem is, the program needs headroom to do a lot more than that and a simple ~14KB/s serial connection maxing out a 400Mhz CPU doesn't seem entirely right to me.
Sure enough, a simple cat /dev/ttyATH0 > /dev/null (note that this works on my system as the dev is configured for 115200 baud by default) results in around 15% CPU usage. cat /dev/ttyATH0 > /dev/ttyATH0 (piping RX to TX) works at around 5% (possibly due to saving kernel->user space copies).
So I dug deeper and tried to work with node.js fs and a statically allocated buffer.
var fs = require('fs');
fs.open(port, 'r', function (err, fd) {
  console.log('port opened! ' + err);

  var buffer = new Buffer(8),
    read;

  function readCb(err, bytesRead, buffer) {
    console.log(bytesRead);
    process.nextTick(read); // continue reading
  }

  read = function () {
    fs.read(fd, buffer, 0, buffer.length, null, readCb);
  };

  read();
});

Same results, 100% cpu according to top.
Now, I'm totally surprised by this. Increasing the buffer sizes didn't help in both cases either. Is there an inherent reason why Serialport/nodejs is so slow in just fetching the data from the serial port? Are there any performance tips you can offer? Or is the CPU usage reported by top just way off? (I believe this is not so, my investigations started because we were seeing massive lags in processing the serial data, to the tune of 10-20 seconds).
I assume @voodootikigod et. al. might have some insights to share from all those robot projects. Or is everyone using this on beefier hardware? (But still, doesn't seem right to me to max out a 400Mhz CPU for a measly serial port).

I think I might have ran into a similar problem where reading from the serialport at 115200 is showing high cpu load on a Mac (130% in activity monitor on latest MBP), but only when embedded in an Electron app. Running the same serialport code with just iojs showed 2% cpu. The current Electron shell uses iojs v2.2 and that's also the version I tested with.
Any idea how serialport could behave differently in combination with Electron?

@JohannesRudolph I've been having similar problems getting 100% cpu usage with node-serialport, except I'm doing only writing in my case. (On a RaspberyPi 2 connecting to a Teensy 3.1). Could you share how you configured the port with stty so that you could use fs? It sounds like you were able to configure the device with node-serialport then use fs on it; how did you get that working? I can't find anything in the docs about how to get the fd from node-serialport to use in fs.
Thanks.

@gregfriedland I'm using child_process to to invoke stty -Fand pass it a hex version of the settings, see the manpage of stty for details. After that I just do fs.open('/dev/ttyXX', 'w', function (err, fd) {...

Any news on this?
I am facing this issue when sending big data over serialport

@reconbot I am running serialport on 2 platforms to create a communication channel:

rPi 2 model B
OSX Yosemite (windows to come)
The communication is mode through the USB control cable connected on the rPI GPIO (baudrate 115200)

@reconbot sorry for the very late answer!
First https://github.com/EmergingTechnologyAdvisors/node-serialport/pull/808 did not help. I am using 4.0.7 and still seeing the issue.
I actually created a second issue because it gives different details. I actually think that sending evens for every 1 or 2 bytes might be the reason for the high CPU usage.
Also about 5.0.0.beta3. I gave it a quick run but serialport was crashing too often (on both sides) so i had to switch back to 4.0.7 because i was in production.
So i will try and give it another run

@reconbot I will ! But i run serialport through electron and the crash report was not helping at all!


GestureRecognizer never removed.

Hey @marcosgriselli
This condition always false.
 if let swipe = panRecognizer {
       view.removeGestureRecognizer(swipe)
}

Solution:
    fileprivate struct AssociatedKey {
        static var swipeGestureKey = "kSwipeableTabBarControllerGestureKey"
    }
....

    func prepareGestureRecognizer(inView view: UIView) {

        panRecognizer = objc_getAssociatedObject(view, &AssociatedKey.swipeGestureKey) as? UIPanGestureRecognizer

        if let swipe = panRecognizer {
            view.removeGestureRecognizer(swipe)
        }

        panRecognizer = UIPanGestureRecognizer(target: self, action: #selector(SwipeInteractor.handlePan(_:)))
        panRecognizer?.delegate = self
        panRecognizer?.isEnabled = true
        view.addGestureRecognizer(panRecognizer!)
        objc_setAssociatedObject(view, &AssociatedKey.swipeGestureKey, panRecognizer, .OBJC_ASSOCIATION_RETAIN_NONATOMIC)
    }

Please check.

@EvgeniyGT Want so submit a PR? I'd gladly review and merge it :).


Expose Relevant Exception On Multiple Operation Mutate When ExtensionFeedItem ResourceNotFound

When mutating a list of ExtensionFeedItems where operations size > 1, if one or more of the operations contains a resource name that is not found a relevant error message is not returned. The error exposed is:
message: "Multiple errors in \342\200\230details\342\200\231. First error: An internal error has occurred., at operations[0]"

When the operations list is distilled down to a single item and a mutate of the offending resource_name is attempted the relevant exception is returned:
message: "Resource was not found., at operations[0].update.resource_name"

try( final ExtensionFeedItemServiceClient extensionFeedItemServiceClient = googleAdsClient.getLatestVersion().createExtensionFeedItemServiceClient() ) {

    final MutateExtensionFeedItemsRequest request = MutateExtensionFeedItemsRequest.newBuilder()
        .setCustomerId( "456" )
        .addAllOperations( operations )
        .setPartialFailure( true )
        .build();

    final MutateExtensionFeedItemsResponse mutateExtensionFeedItemsResponse = extensionFeedItemServiceClient.mutateExtensionFeedItems( request );
}

Mutate attempt with multiple operations:
Request
-------
MethodName: google.ads.googleads.v5.services.ExtensionFeedItemService/MutateExtensionFeedItems
Endpoint: googleads.googleapis.com:443
Headers: {developer-token=REDACTED, login-customer-id=123, x-goog-api-client=gl-java/1.8.0_161 gapic/ gax/1.57.0 grpc/1.30.0}
Body: customer_id: "456"
operations {
  update {
    resource_name: "customers/456/extensionFeedItems/001"
    sitelink_feed_item {
      /* values */
    }
    extension_type: SITELINK
  }
  update_mask {
    paths: "resource_name"
    paths: "extension_type"
    paths: "sitelink_feed_item.link_text"
    paths: "sitelink_feed_item.final_urls"
  }
}
operations {
  update {
    resource_name: "customers/456/extensionFeedItems/002"
    sitelink_feed_item {
      /* values */
    }
    extension_type: SITELINK
  }
  update_mask {
    paths: "resource_name"
    paths: "extension_type"
    paths: "sitelink_feed_item.link_text"
    paths: "sitelink_feed_item.final_urls"
  }
}

Response
--------
Headers: Metadata(content-disposition=attachment,content-type=application/grpc,request-id=rOCYtlHQp_s2i0ZDIjkcBg,date=Thu, 10 Sep 2020 16:03:46 GMT,alt-svc=h3-29=":443"; ma=2592000,h3-27=":443"; ma=2592000,h3-T051=":443"; ma=2592000,h3-T050=":443"; ma=2592000,h3-Q050=":443"; ma=2592000,h3-Q046=":443"; ma=2592000,h3-Q043=":443"; ma=2592000,quic=":443"; ma=2592000; v="46,43")
Body: results {
}
results {
}
results {
}
partial_failure_error {
  code: 13
  message: "Multiple errors in \342\200\230details\342\200\231. First error: An internal error has occurred., at operations[0]"
  details {
    type_url: "type.googleapis.com/google.ads.googleads.v5.errors.GoogleAdsFailure"
    value: "\n7\n\002P\002\022\037An internal error has occurred.\"\020\022\016\n\noperations\022\000\n9\n\002P\002\022\037An internal error has occurred.\"\022\022\020\n\noperations\022\002\b\001\n9\n\002P\002\022\037An internal error has occurred.\"\022\022\020\n\noperations\022\002\b\002"
  }
}

Mutate attempt with a single operation:
Request
-------
MethodName: google.ads.googleads.v5.services.ExtensionFeedItemService/MutateExtensionFeedItems
Endpoint: googleads.googleapis.com:443
Headers: {developer-token=REDACTED, login-customer-id=123, x-goog-api-client=gl-java/1.8.0_161 gapic/ gax/1.57.0 grpc/1.30.0}
Body: customer_id: "456"
operations {
  update {
    resource_name: "customers/456/extensionFeedItems/002"
    sitelink_feed_item {
      /* values */
    }
    extension_type: SITELINK
  }
  update_mask {
    paths: "resource_name"
    paths: "extension_type"
    paths: "sitelink_feed_item.link_text"
    paths: "sitelink_feed_item.final_urls"
  }
}

Response
--------
Headers: Metadata(content-disposition=attachment,content-type=application/grpc,request-id=JYbyNwFjlSsbsWpqYrCn7g,date=Thu, 10 Sep 2020 16:05:36 GMT,alt-svc=h3-29=":443"; ma=2592000,h3-27=":443"; ma=2592000,h3-T051=":443"; ma=2592000,h3-T050=":443"; ma=2592000,h3-Q050=":443"; ma=2592000,h3-Q046=":443"; ma=2592000,h3-Q043=":443"; ma=2592000,quic=":443"; ma=2592000; v="46,43")
Body: results {
}
partial_failure_error {
  code: 3
  message: "Resource was not found., at operations[0].update.resource_name"
  details {
    type_url: "type.googleapis.com/google.ads.googleads.v5.errors.GoogleAdsFailure"
    value: "\nN\n\0028\003\022\027Resource was not found.\032\002*\000\"+\022\016\n\noperations\022\000\022\b\n\006update\022\017\n\rresource_name"
  }
}

With a nondescript error message of "An internal error has occurred" in the first instance it is very difficult to troubleshoot what the actual problem is.
Also, going back to the original error message of:
message: "Multiple errors in \342\200\230details\342\200\231. First error: An internal error has occurred., at operations[0]"

... the offending operation was not even at index 0, and in fact if operation[0] had been attempted on its own the mutate would succeed.
I believe I've seen this on various objects besides ExtensionFeedItems before but this is the object I have in front of me today.
Clarity on what partial_failure = true means in cases like this would also be helpful, as all operations failed when there was only one offending operation.
Thanks
Pete
Java Client Library : com.google.api-ads:google-ads:9.0.0

Hi Pete, thank you for flagging this for us. This is an issue with the core API and not specific to the client library for Java. I have filed a bug with the eng team to make these error messages clearer in the case of multiple operations because I agree the case you identified is difficult to troubleshoot. Seeing as this is not an issue with the client library for Java, I am going to close this issue here. However, feel free to reply here for an update.


wait for vmi-killer pod to start before moving on

Signed-off-by: Ashley Schuett<EMAIL_ADDRESS>
What this PR does / why we need it:
This test occasionally fails with
Waited for 60 seconds on the event stream to match a specific event: event type Warning, reason = Stopped
We should wait for the vmi-killer pod to be running before we wait for the VMI warning event of type stopped. In some cases the vmi-killer pod might take more time run which will then take time away from waiting for the VMI to produce a stopped event.
If you take a look at the events you will see that there was an issue creating the vmi-killer pod, which then had to be killed and recreated. This made it so there wasn't enough time for the VMI to crash and produce the Stopped warning event.
Failed test: https://prow.apps.ovirt.org/view/gcs/kubevirt-prow/pr-logs/pull/kubevirt_kubevirt/3797/pull-kubevirt-e2e-k8s-1.17/1298977455377223680
Events: https://storage.googleapis.com/kubevirt-prow/pr-logs/pull/kubevirt_kubevirt/3797/pull-kubevirt-e2e-k8s-1.17/1298977455377223680/artifacts/k8s-reporter/1_events.log
Release note:
NONE

/lgtm
/approve


Introduce verbose output

Helm currently has it's normal output and output with --debug messages. This is a proposal to introduce another level between normal and debug output.
kubectl, using klog, has the ability to set a verbosity level. This level is not clearly defined so users have to work it out. But, there are multiple levels. I wouldn't recommend we have that experience.
Homebrew, the mac package manager, has two levels. --verbose and --debug that can be layered on to the normal output. Verbose prints more information about what's happening while debug prints details you'd need if you want to debug something.
This feature request suggests the same idea for Helm. For example, if you used --verbose on helm install it would tell you what's happening as it locates the chart, downloads it, renders the templates, pushes them, etc. I wouldn't need to give lots of internal values and details that debug should supply.
Thoughts?

The level of output I'd like to see is for helm to log any action it specifically takes.  For example, CRUD resource, run hook, wait for objects.  The specific use case I would need this for is building UIs around helm in which I'm installing a chart and want to give some level of output to the user to indicate things are progressing.  Right now, correct me if I'm wrong, nothing it printed until the chart is installed and then notes are outputted.  So if --wait is passed this is a long delay of no output.

Seems like a step in the right direction.  I have a project that deploys an "umbrella" chart, and (by no fault of helm) it takes a long time to complete.  It would be helpful for helm to share information along the lines of "found the chart", "kubernetes has updated the resources, just waiting for them to align", and "yep, all done, thanks".

I would welcome --verbose too. It is also the first argument I try before running into 'help' failure output and consulting the docs. A lots of user-irrelevant content. If it printed the line it finds error on, it would help a lot too since line numbers usually do not match with bigger projects that use some advanced templating...


StochJuMP being called

when trying to solve one of the examples, I get the following:
ERROR: LoadError: LoadError: ArgumentError: Module StochJuMP not found in current path.
Run Pkg.add("StochJuMP") to install the StochJuMP package.
Stacktrace:
[1] _require(::Symbol) at ./loading.jl:435
[2] require(::Symbol) at ./loading.jl:405
[3] include_from_node1(::String) at ./loading.jl:576
while loading /home/gavelasq/.julia/v0.6/DSPsolver/src/DSPsolver.jl, in expression starting on line 5
while loading /home/gavelasq/Documents/structJuMP_example.jl, in expression starting on line 1

A quick answer is that this package is no longer used for DSP. Please check the package: https://github.com/kibaekkim/Dsp.jl.gi
I will resolve the issue later.

using Dsp I get this error:
ERROR: LoadError: LoadError: error compiling Type: could not load library "libDsp"
libDsp.so: cannot open shared object file: No such file or directory
Stacktrace:
[1] include_from_node1(::String) at ./loading.jl:576
while loading /home/gavelasq/.julia/v0.6/Dsp/src/Dsp.jl, in expression starting on line 23
while loading /home/gavelasq/Documents/structJuMP_example.jl, in expression starting on line 1
Also, the only file I have in the lib folder is README.md.

You need to clone and compile DSP, a c libarary. Please visit and check this: https://github.com/Argonne-National-Laboratory/DSP
Please feel free to issue any relevant tickets there.


Create Admin app

A microservice for configuring and managing bots in the cloud (AWS).
A REST API will be provided for clients to configure, start/stop bots.
This work will be done in a new GitHub project.

Closing this - duplicate of #29.


[ParksOnTheAirBridge] Fix links

Some of the links still go to pota.us

Good idea, thanks for the review

Nice


Copilot+ ARM64 : System.BadImageFormatException: at is not a valid Win32 application.

Describe the bug
System.BadImageFormatException: at is not a valid Win32 application.
My app is compiled and packaged for ARM64.
Yet a customer installed the ARM64 version from the MS Store, but the app crash on start with the message above in the Logs.
Steps to reproduce the bug
Install an ARM64 app from the MS Store on a Copilot+ laptop.
Expected behavior
The app should work, just like apps on the Apple, Android, Linux , PS, Nintendo and Xbox stores.
Screenshots
No response
NuGet package version
WinUI 3 - Windows App SDK 1.5.5: 1.5.240627000
Windows version
Windows 11 (22H2): Build 22621
Additional context
No response

Error from the LOG
Application: myapp.exe
CoreCLR Version: 7.0.1724.11508
.NET Version: 7.0.17
Description: The process was terminated due to an unhandled exception.
Exception Info: System.TypeInitializationException: The type initializer for 'WinRT.ActivationFactory1' threw an exception.  ---> System.BadImageFormatException:  is not a valid Win32 application. (0x800700C1)    at System.Runtime.InteropServices.Marshal.ThrowExceptionForHR(Int32 errorCode)    at WinRT.BaseActivationFactory..ctor(String typeNamespace, String typeFullName)    at WinRT.ActivationFactory1..ctor()
at WinRT.ActivationFactory1..cctor()    --- End of inner exception stack trace ---    at WinRT.ActivationFactory1.As(Guid iid)
at Microsoft.Windows.AppLifecycle.AppInstance.Make___objRef_global__Microsoft_Windows_AppLifecycle_IAppInstanceStatics()
at Microsoft.Windows.AppLifecycle.AppInstance.get__objRef_global__Microsoft_Windows_AppLifecycle_IAppInstanceStatics()
at Microsoft.Windows.AppLifecycle.AppInstance.GetCurrent()
at myapp.Program.isOpenNewInstance()
at myapp.Program.Main(String[] args)
Faulting application name: myapp.exe, version: <IP_ADDRESS>, time stamp: 0x65ce0000
Faulting module name: KERNELBASE.dll, version: 10.0.26100.1301, time stamp: 0x0780347f
Exception code: 0xe0434352
Fault offset: 0x00000000001ae0d8
Faulting process id: 0x8320
Faulting application start time: 0x1DAECE781C9B78D
Faulting application path: C:\Program Files\WindowsApps\myappSolutionsinc.myapp_<IP_ADDRESS>_arm64__efag6vr1nbgqc\myapp.exe
Faulting module path: C:\Windows\System32\KERNELBASE.dll
Report Id: 9ae688fc-2ef3-4328-93d6-d035c962eee4
Faulting package full name: myappSolutionsinc.myapp_<IP_ADDRESS>_arm64__efag6vr1nbgqc
Faulting package-relative application ID: App

The log hints at this happening around AppInstance.GetCurrent. But in a test application, I don't see it happening.
https://github.com/user-attachments/assets/3fb1f46c-fe53-496b-8ab3-cef0b483e53c
As you can see through Visual Studio, the ARM64 versions of the libraries are loading when I call AppInstance.GetCurrent. So this doesn't seem to happen naturally. What does your application's code around that point?
Also, it is possible that the log has lost information. The way it is starting and stopping code blocks indicates that the log has backticks `` in it. This would mean that there is some generics in the log. The .NET metadata uses the backtick for that purpose. It is possible that the log has lost some time information because of how websites normally handle < and >.

Sadly your video does not load.
Upgraded the project manually to .net8 and updated everything (framework and vs studio).
Thanks for the info, will investigate further, but it looks like the ARM64 app is trying to load something that is not ARM64.
No wonder that the biggest and hottest project on the internet do not and may never have a windows version : ladybird (the next browser) and zed (the next vs code). I should not have to fight for everything. MS tools should do their job like Xcode and Android Studio do.
Steve Balmer loved the developers and MS were the best 15 years ago for developers, now they are the worst. At 62% of the desktop market and going down every months, Windows must treat the remaining developers with respect.

Debugging with loader snaps enabled should find which binary is trying to be loaded with the incorrect format:

Get a copy of the ARM64 version of gflags.exe, such as from the Windows SDK.
In an Admin command prompt, run gflags.exe /i myapp.exe +sls to show loader snaps.
Launch the app under a native debugger. (Launching from Visual Studio with "Enable native code debugging" enabled works for this. Another option is using WinDbg, using the "Launch app package" option if it is a packaged app or "Launch executable" if unpackaged.)

The loader snaps will spew a lot of information to the debug output as it is searching for and loading dlls. Hopefully this will show which dll failed to load when the invalid format error was hit.

I updated my app to .net 8.0 with the latest build tools and sdk
Another customer called me because the app does not start on his Lenovo copilot+
How is it possible that I did everything exactly like MS wanted : Use only their WinUI3/Win32/WindowsAppSdk and compiled to arm64 with the latest VS Studio, the app was once again approved by the MS store employees who are supposed to test the app and yet it does not work. But these old apps from the 90's compiled in x86 32 bits are running????
Wake up MS!!!! Fix your s... you are destroying your customers confidence in your copilot+ thing (and also me the dev).

I don't have an overpriced Copilot+ Laptop, so I cannot test on it. I can only check for the error in the MS log.

1000
0
2
100
0
0x8000000000000000

6494

Application
LAPTOP-GHSG3R51

-
myapp.exe
<IP_ADDRESS>
66960000
KERNELBASE.dll
10.0.26100.1455
f4a3a16d
e0434352
00000000001ae0d8
0x49a4
0x1daf330791e5027
C:\Program Files\WindowsApps\myappSolutionsinc.myapp_<IP_ADDRESS>_arm64__efag6vr1nbgqc\myapp.exe
C:\Windows\System32\KERNELBASE.dll
f1e2ba5a-6a80-4623-8eb0-b73717c3a08b
myappSolutionsinc.myapp_<IP_ADDRESS>_arm64__efag6vr1nbgqc
App

1026
0
2
0
0
0x80000000000000

6493

Application
LAPTOP-GHSG3R51

-
Application: myapp.exe CoreCLR Version: 8.0.824.36612 .NET Version: 8.0.8 Description: The process was terminated due to an unhandled exception. Exception Info: System.TypeInitializationException: The type initializer for 'WinRT.ActivationFactory`1' threw an exception. ---> System.BadImageFormatException: is not a valid Win32 application. (0x800700C1) at System.Runtime.InteropServices.Marshal.ThrowExceptionForHR(Int32 errorCode) at WinRT.BaseActivationFactory..ctor(String typeNamespace, String typeFullName) at WinRT.ActivationFactory`1..ctor() at WinRT.ActivationFactory`1..cctor() --- End of inner exception stack trace --- at WinRT.ActivationFactory`1.As(Guid iid) at Microsoft.Windows.AppLifecycle.AppInstance.Make___objRef_global__Microsoft_Windows_AppLifecycle_IAppInstanceStatics() at Microsoft.Windows.AppLifecycle.AppInstance.get__objRef_global__Microsoft_Windows_AppLifecycle_IAppInstanceStatics() at Microsoft.Windows.AppLifecycle.AppInstance.GetCurrent() at myapp.Program.isOpenNewInstance() at myapp.Program.Main(String[] args)

Update : All our customers who bought a Windows Copilot+ have returned it to the store because our Windows ARM64 app does not run on Copilot+ laptops. And now we tell our customers that our Windows ARM64 app (approved by MS on the MS App Store) does not run on Copilot+ Windows PC. Its a good thing that our 20 000+ customers are moving away from Windows to macOS, iOS and Android (Chromebook) everyday. Note that our customers must use our app to work, otherwise they can't work at all.
Once again MS has abandoned support for their own products right after releasing them (exactly like Windows Mixed Reality). Since we are the only one in the world making app for modern Windows and modern Hardware and MS does not want to help us, we may have to abandon the Windows version of our app and ask users to install the Android version on their Windows 11.
Warning, do no buy Windows Copilot+ laptops, they are not even compatible with apps made specifically for them.

So I got a Windows ARM to test and the problem was that I needed to set the target in the xml project settings to arm64. Now the app run on my Windows ARM, but once on the MS App Store and installed by the MS App Store, the app crash on start again. We have no choice to tell our users not to buy a Copilot+ laptop for now. The  MS Tools and MS Store do not work for ARM. It has nothing to do with the code, maybe an obscure project setting in hidden xml files??? I guess people who still use Windows in 2024 kind of deserve the Microsoft Experience.  Hey Windows users : you made your bed, you sleep in it.

Debugging with loader snaps enabled should find which binary is trying to be loaded with the incorrect format:

Get a copy of the ARM64 version of gflags.exe, such as from the Windows SDK.
In an Admin command prompt, run gflags.exe /i myapp.exe +sls to show loader snaps.
Launch the app under a native debugger. (Launching from Visual Studio with "Enable native code debugging" enabled works for this. Another option is using WinDbg, using the "Launch app package" option if it is a packaged app or "Launch executable" if unpackaged.)

The loader snaps will spew a lot of information to the debug output as it is searching for and loading dlls. Hopefully this will show which dll failed to load when the invalid format error was hit.

Please follow these instructions to get more info on where the failure is coming from. This way, we can better assist you.

I just don't have time to work on that for now, maybe in a few months.
The reality is that a WinUI3 project compiled for ARM will run on an ARM windows, but once downloaded from the store, it crashes on start without a single line of code being executed. So I removed the ARM version from the store and now the x64 get installed on ARM computers and for now, that is good enough for the inferior windows platform.


Perform code coverage in CI and update badge

[ ] get token from https://codecov.io/gh/public-awesome/stakebird
[ ] add Drone plugin http://plugins.drone.io/drone-plugins/drone-codecov/
[ ] add badge to README

Maybe not related to the issue but adding golangci-lint to the build step could be nice as well


Octopus throwing error when deleting expired tokens

Message: undefined method `delete_if' for "{}":String Did you mean? delete delete!

I have already submitted a pull request to take care of it.
https://github.com/lynndylanhurley/devise_token_auth/pull/762


Resolve existing CI issues, new wheels for OSX, improvements for Windows wheels

This PR resolves #738, and adds new CI functionality. In order for this PR to work, Travis and AppVeyor will need new environment variables PYPI_API_ENDPOINT=https://pypi.org/pypi (note the lack of a final forward slash in that URL).
By using conda's "pinned" dependencies, this PR builds wheels for

Windows: Python 3.6 and 3.7,
OSX: Python 2.7, 3.6, and 3.7.

The wheels for OSX are entirely new. The Python 3.7 wheel for Windows is new.
I attempted to have wheels build for python 3.5 on Windows and OSX. This failed because of a (somewhat obscure?) packaged called readme_renderer, which seems to be required for uploading wheels to PyPI. Using the conda channels we currently have, there is no appropriate version of readme_renderer which exists for Python 3.5. In the next major improvements to CI testing, I will move away from conda install ... for managing packages, and instead work with pip. Hopefully that will allow us to build python 3.5 wheels.

Pinging @akshayka , @SteveDiamond

This is great! LGTM.

@SteveDiamond, this should be ready to merge once the Travis and AppVeyor have the environment variables PYPI_API_ENDPOINT=https://pypi.org/pypi (note the lack of a final forward slash in that URL).

I added the variable. Thanks for doing this!


turn off / restart module

Hi. Could you add the module "turn off / restart" (and maybe the option to perform the action after n seconds)?

This is a nice idea, but it would require root access.
Including root required functionality will be a bigger task and requires more testing effort.
Thank you for your ideas!


Add hotcorner extension

Description

Screencast

Checklist

[x] I read the extension guidelines
[x] I read the documentation about publishing
[x] I ran npm run build and tested this distribution build in Raycast
[x] I checked that files in the assets folder are used by the extension itself
[x] I checked that assets used by the README are placed outside of the metadata folder

Hi 👋
I was not able to get this to work, tried setting a few things and the screen blinked, but when checking in Hot Corners everything was as before

I'm on Sonoma if that changes anything?

Hi, @pernielsentikaer
Since the extension uses Shell Commands (in the code started with "defaults write") to change the function of hot corners, so user have to give Raycast permission on System Events (It's under Privacy & Security - Automation - Raycast).
The reason of screen blinks is the command requires restarting the dock to take effect. The restart of the dock is accompanied by screen blink. It seems this is unavoidable.

Seems to work for some of it, but most of the things are shuffled around - launchpad started the screensaver so the recording ended so made two recordings instead
https://github.com/raycast/extensions/assets/38033107/0bf89782-b3e2-41c7-8eaa-dcb43da69470
https://github.com/raycast/extensions/assets/38033107/6565b43c-decc-4bba-8284-e127ca935995

Thanks for your patience. I've fixed the bug and now hot corner options are totally aligned with the options in system preference.
Also, in the latest commit, i've add a little help doc after "Disable All Corners" in the list, which helps user to address the issue with automation permission.
please review again,
thanks.


Avoid back button trap by using replaceState

This tool is awesome! Nice work Corey!
I was testing it out and noticed that if you change your colors a number of times, then you have to use the back button an equal number of times to exit back out of the website.
I think it would be better if you only had to use the back button once to exit, regardless of how many changes you'd made.
I think this could be achieved by changing pushState to replaceState in updatePath. If I opened a PR for that would you be open to merging it in?
Thanks!

Hells yeah, let's do it

Sweet, I'll get started on that! 🤘

Just opened a PR! 😀


Feature/non confidential unit tests

Working on #1162 and simplfying testing

Coverage decreased (-0.8%) to 69.741% when pulling d4770becfda32f9dfbedd6f158ba107970556a71 on feature/non_confidential_unit_tests into 21b5194b2e8eb98ec06ee7c8d81e8df73129e390 on develop.

FYI, the number of tests run by Maven seems consistent (I moved some tests from unit tests to integration tests since they made more sense that way) but cobertura/coveralls seems to be counting it a bit differently


Expansions to sleep functionality

Expansions to sleep functionality

Implementation of the Sadeh and Galland sleep detection algorithms (see #427). More specifically, I added the zero-crossing count calculation needed for these algorithms to g.applymetrics, and function g.sib.det now allows for chosing how sleep, I call it sustained inactivity bouts = SIB, should be detected: vanHees2015 (default), Sadeh1994, and Galland2012.
When working with hip-worn accelerometer data GGIR attempts to estimate time in bed, if argument sensor.location is set to "hip". For this the code uses the horizontal orientation (defined as: -45 < angle < 45) of the longitudinal sensor axis as indicator for potential lying time.. Next, it uses the last steps of the HDCZA algorithm to identify the longest lying episode in the day.  In the code this new algorithm is referred to as "HorAngle".
Function g.sib.det code has been restructured such that SPT, Time in Bed and SIB detection happen in newly created functions called: HASIB (Heuristic Algorithms for Sustained Inactivity Bout detection) and HASPT (Heuristic Algorithms for Sleep Period Time detection). I did this to improve the readability of function g.sib.det. As a result I was able to simplify the handling of single and multi-day recordings (see #398).
GGIR is now able to handle both the old basic sleeplog format and a more advanced sleeplog format which facilitates nap and nonwear entries by calendar date. See code updates to g.loadlog and g.part4. These self-reported naps and nonwear are now used in g.part5, where it is used to export the start and end times of the accelerometer-detected sustained inactivity bouts, as well as the start and end times of the self-reported naps and nonwear to csv report to aid nap analysis (see #418). For the moment it just stores the information, later this year I may expand this with complementary functionality to do actual nap behaviour analysis.

Minor updates related to the above.

Part 4 is now able to handle time in bed diaries/algorithms, and if they are used it will automatically generate sleep latency and sleep efficiency estimates.
Part 4 report now includes guider estimates also in 'cleaned' report, previously these were only stored in the full report, but now the guider can also represent time in bed it makes sense to also show this to the user in the cleaner report.
WASO and NOA (Number of awakenings) added to the part 4 report
Work on GGIR vignette text, function documentation, and unit tests to reflect all these changes.
Effort made to shorten function g.part4 which is one of the longest functions in GGIR. I moved about 75 lines from g.part4 code to a newly created g.part4_extractid.

Checklist before merging:

[x] Existing tests still work (check by running the test suite, e.g. from RStudio).
[x] Added tests (if you added functionality) or fixed existing test (if you fixed a bug).
[x] Updated or expanded the documentation.
[x] Updated release notes in inst/NEWS.Rd with a user-readable summary. Please, include references to relevant issues or PR discussions.
[x] Added your name to the contributors lists in the DESCRIPTION and CITATION.cff files.

Codecov Report

Merging #445 (23196a9) into master (88dc210) will increase coverage by 0.06%.
The diff coverage is 75.56%.

:exclamation: Current head 23196a9 differs from pull request most recent head f379edf. Consider uploading reports for the commit f379edf to get more accurate results

@@            Coverage Diff             @@
##           master     #445      +/-   ##
==========================================
+ Coverage   74.66%   74.72%   +0.06%
==========================================
  Files          83       87       +4
  Lines       10084    10497     +413
==========================================
+ Hits         7529     7844     +315
- Misses       2555     2653      +98

Impacted Files
Coverage Δ

R/g.part5.addfirstwake.R
17.50% <12.50%> (ø)

R/g.analyse.R
79.46% <25.00%> (-0.36%)
:arrow_down:

R/g.part1.R
70.66% <50.00%> (+0.06%)
:arrow_up:

R/g.part4_extractid.R
50.00% <50.00%> (ø)

R/g.part5.R
72.33% <52.77%> (-1.11%)
:arrow_down:

R/g.sib.det.R
66.66% <62.90%> (-7.77%)
:arrow_down:

R/g.shell.GGIR.R
85.35% <65.78%> (-1.81%)
:arrow_down:

R/HASPT.R
66.66% <66.66%> (ø)

R/g.part4.R
72.33% <74.77%> (+0.76%)
:arrow_up:

R/g.part5.fixmissingnight.R
67.85% <75.00%> (-0.78%)
:arrow_down:

... and 13 more

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I know it is summer time, and you all may be enjoying your summer break. So there is no major rush to this PR.
@l-k- this is the PR I announced in #398. Would you mind reviewing this? It comes with more code updates then you may be interested in, but it would be great if you could at least check that your issue relating to 1 night recordings has been addressed. I tried to send you a review request above, but somehow I could not select your GitHub tag l-k-.
@m-patterson These changes should have no impact on your default GGIR usage. All of this relates to new optional variations to how GGIR can be used.
@jhmigueles I remember you worked with ActiGraph's implementation of the Sadeh algorithm. You may be interested to know that GGIR now also has an  implementation. If you could try this out on your data and let me know if estimates look plausible that would be great.

@vincentvanhees -- got the notification, very happy to review this!

On a local test set, I received this error at part4 of the algorithm:

The config.csv file was not create, but here are my settings used:

On another note, when I source functions, I add these functions in order to run the external function calling:

However, there seemed to be an error with the 'resample' function:

and here:

error at part4 of the algorithm:

Thanks, this should be fixed now. I forgot to declare a default value for object addlegend at the top, in case do.visual = FALSE.

config.csv file was not created

I am not able to reproduce this. The config file is created in g.shell.GGIR. So, if this function is run it should normally produce the file. Let me know if it keeps doing this.

However, there seemed to be an error with the 'resample' function:

Thanks for spotting. I previously expanded the resample function to have the option to do nearest neighbor interpolation as opposed to linear interpolation (still the default). This to enable research on the possible role of the resampling/interpolation approach. The nearest neighbor algorithm uses std::round which only works with C++11. I have no rewritten the resample.cpp function to avoid this dependency on C++11.

The changes work for me, everything looks good now

All working well now

Not sure if this is only a problem local to my machine, but when I try to run .cwa files on this branch I get the following error:

The code works fine when I run my local Verisense files, which are saved as .csv

I am merging this pull request now. It has successfully been tested in four different datasets, which led to various minor correction. So, it is time for this to be part of a GitHub release.


Cannot reach network outside host

Hello guys,
I would to ask you about the problem of reaching servers outside the host from my containers. My containers reach nothing else then local network on my host & docker networks. I would be pleased if you could go through this issue and give me some advice. Thank you for replies.
Ping results:
❌ <IP_ADDRESS>
❌ google.com
✔ <IP_ADDRESS>
✔ <IP_ADDRESS>
✔ public IP of the server
Output:
letsencrypt-nginx-proxy-companion | 2020/12/10 12:17:19 Received event start for container 25e2c44dd50a
nginx-proxy                | dockergen.1 | 2020/12/10 12:17:19 Received event start for container 25e2c44dd50a
nginx-proxy                | dockergen.1 | 2020/12/10 12:17:19 Generated '/etc/nginx/conf.d/default.conf' from 3 containers
letsencrypt-nginx-proxy-companion | 2020/12/10 12:17:24 Debounce minTimer fired
letsencrypt-nginx-proxy-companion | 2020/12/10 12:17:24 Generated '/app/letsencrypt_service_data' from 3 containers
letsencrypt-nginx-proxy-companion | 2020/12/10 12:17:24 Running '/app/signal_le_service'
letsencrypt-nginx-proxy-companion | [Thu Dec 10 12:17:30 UTC 2020] Please refer to https://curl.haxx.se/libcurl/c/libcurl-errors.html for error code: 6
letsencrypt-nginx-proxy-companion | [Thu Dec 10 12:17:30 UTC 2020] Can not init api.
letsencrypt-nginx-proxy-companion | [Thu Dec 10 12:17:30 UTC 2020] Please refer to https://curl.haxx.se/libcurl/c/libcurl-errors.html for error code: 6
letsencrypt-nginx-proxy-companion | [Thu Dec 10 12:17:30 UTC 2020] Can not init api.
letsencrypt-nginx-proxy-companion | [Thu Dec 10 12:17:31 UTC 2020] Create account key ok.
letsencrypt-nginx-proxy-companion | [Thu Dec 10 12:17:31 UTC 2020] Create account key ok.
letsencrypt-nginx-proxy-companion | [Thu Dec 10 12:17:31 UTC 2020] Registering account: https://acme-v02.api.letsencrypt.org/directory
letsencrypt-nginx-proxy-companion | [Thu Dec 10 12:17:31 UTC 2020] Registering account: https://acme-v02.api.letsencrypt.org/directory
letsencrypt-nginx-proxy-companion | [Thu Dec 10 12:17:36 UTC 2020] Please refer to https://curl.haxx.se/libcurl/c/libcurl-errors.html for error code: 6
letsencrypt-nginx-proxy-companion | [Thu Dec 10 12:17:36 UTC 2020] Please refer to https://curl.haxx.se/libcurl/c/libcurl-errors.html for error code: 6
letsencrypt-nginx-proxy-companion | [Thu Dec 10 12:17:37 UTC 2020] Could not get nonce, let's try again.
all containers are attached to network: nginx-proxy (driver: bridge)
iptables:
ipt.log
ipt-legacy.log
bridged network - FAILS
host network:
root@hooman:/home/wajda# docker run -it --network=host alpine
/ # ping google.com
PING google.com (2a00:1450:400c:c0c::8b): 56 data bytes
64 bytes from 2a00:1450:400c:c0c::8b: seq=0 ttl=104 time=759.309 ms
64 bytes from 2a00:1450:400c:c0c::8b: seq=1 ttl=104 time=15.081 ms
64 bytes from 2a00:1450:400c:c0c::8b: seq=2 ttl=104 time=7.704 ms
64 bytes from 2a00:1450:400c:c0c::8b: seq=3 ttl=104 time=8.538 ms
64 bytes from 2a00:1450:400c:c0c::8b: seq=4 ttl=104 time=9.345 ms
64 bytes from 2a00:1450:400c:c0c::8b: seq=5 ttl=104 time=9.716 ms
64 bytes from 2a00:1450:400c:c0c::8b: seq=6 ttl=104 time=8.758 ms
^C
--- google.com ping statistics ---
7 packets transmitted, 7 packets received, 0% packet loss
round-trip min/avg/max = 7.704/116.921/759.309 ms
/ #

ipt-legacy.log
ipt.log
iptables

The problem was with debian 10 (Buster). It uses nftables that blocked traffic from the container. 2 options are available
1- switch back to iptables $ sudo update-alternatives --config iptables then restart docker
2- configure nftables with docker >HERE<


[Feature Request] - Show all tabs in taskbar when hovering

Description:
Show all the tabs that are open when hovering over Sets in the taskbar. (Additionally, when hovering only UWP apps show in the hover previews, as can be seen in the screenshot below).
Screenshot:

Version Info:
Edition Windows 11 Pro Insider Preview
Version 22H2
Installed on 2022-10-19
OS build 25227.1000
Experience Windows Feature Experience Pack 1000.25227.1000.0

I would rate this difficulty: impossible but yes good idea

Notes on concepts needed for implementation

We can set add window into the taskbar hover icon
However, that window must either be the desktop window itself or be owned by the process because of some security Microsoft placed
We can technically create a new hidden window and then copy the content of a specific window, however, I'm not sure if it worth the performance cost.


Disable audio for notifications not working

I'm using Franz 5.0.0-beta.14 on macOS High Sierra. I keep on hearing a sound when I receive a WhatsApp message despite having disabled audio by clicking the bell on the left down corner. What I want is to receive a notification but without sound.

In fact, it still happens in 5.0.0-beta.15.607

Still happens 5.0.0-beta.17, at least in Google Hangouts

Still happens in Version 5.0.0-beta.18 in Messenger (for one). I worked around it by setting Messenger's internal options to not play sound (not ideal, because sometimes I want sound).

Major annoyance...

Same problem.
Franz 5 Beta on a Macbook Pro OSX (Sierra & now Mojave) with Whatsapp.
No matter what settings I use: it always beeps. It's driving me nuts.
I'm using an external audio interface for sound, not system sound.


Vehicle updates remove stops

Vehicle updates currently implemented by clearing the entire annotation layer and adding in all the updates
Re-do vehicle updates that doesn't involve clearing all of the annotations.

Resolved in new PR #43


Move away from grunt-saucelabs

grunt-saucelabs is the last thing stopping us dropping grunt as a dependency altogether. I'd like to get this done before we ship the second beta.
The solution to this should probably use https://docs.travis-ci.com/user/sauce-connect/

Agreed. I was looking at it too the other day. If you make any progress, feel free to CC me to have a quick look.


Clarify docstring for ReplacePrefixMatch.

Make example text clearer and add table of replacement cases.
What type of PR is this?
/kind documentation
Optionally add one or more of the following kinds if applicable:
/area conformance
What this PR does / why we need it:
The docstring is a bit unclear, and edge cases are not explicitly defined.
Which issue(s) this PR fixes:
Fixes https://github.com/kubernetes-sigs/gateway-api/issues/2078
Does this PR introduce a user-facing change?:

NONE

Thanks @briantkennedy! Do you mind running make generate to get the presubmits to pass? Otherwise this LGTM.

Thanks @briantkennedy!
/lgtm
/approve


Example for MicrosoftTeams and unavailable params

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New-CsOnlineSession from the Module MicrosoftTeams links here now.
Comparing the command New-CsOnlineSession (Skype) with the Teams variant, a few parameters are not available.
Added a note for each of these.
Also added Example 4 (which would have helped me) establishing a connection to both.
This one may not not be essential (establishing a connection with the command from the Teams module calls Connect-MicrosoftTeams in the background anyway, but running it first enables a semi single-sign-on (Dialog is still shown if logged into more than one Tenant, but no additional credentials are required).

Created PR from my fork as I do not have Commit rights from the master branch.
Apologies if this is not the intended way (still familiarising myself more with git)

@get-itips agreed.

@DEberhardt

@DEberhardt

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removed 2 parameters, but left Username and Example 4 for now.
how should we proceed?

removed 2 parameters, but left Username and Example 4 for now.
how should we proceed?

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I'm not fully convinced to add this example, and I think we can also remove -Username parameter (but leave it is not an issue for me).
What do you think @get-itips @tseward?

While I appreciate David's contribution, my vote is
The example, I think, fits better in https://github.com/MicrosoftDocs/OfficeDocs-SkypeForBusiness/pull/6405 as this repo holds more procedural examples/guides.
To remove all parameters not present in the cmdlet as of today.

I'm not fully convinced to add this example, and I think we can also remove -Username parameter (but leave it is not an issue for me).
What do you think @get-itips @tseward?

While I appreciate David's contribution, my vote is
The example, I think, fits better in https://github.com/MicrosoftDocs/OfficeDocs-SkypeForBusiness/pull/6405 as this repo holds more procedural examples/guides.
To remove all parameters not present in the cmdlet as of today.

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This should do then.
Example 4 removed, Parameters not present in MicrosoftTeams removed.

This should do then.
Example 4 removed, Parameters not present in MicrosoftTeams removed.

David, we are reaching the approval :)
are you familiar with PlatyPS ?
It is telling me that new parameters are present:
New-CsOnlineSession [-Credential <PSCredential>] [-OverrideAdminDomain <String>]
 [-OverridePowerShellUri <String>] [-TeamsEnvironmentName <String>] [-SessionOption <PSSessionOption>]
 [<CommonParameters>]

David, we are reaching the approval :)
are you familiar with PlatyPS ?
It is telling me that new parameters are present:
New-CsOnlineSession [-Credential <PSCredential>] [-OverrideAdminDomain <String>]
 [-OverridePowerShellUri <String>] [-TeamsEnvironmentName <String>] [-SessionOption <PSSessionOption>]
 [<CommonParameters>]

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I know of the beaked Module, but haven't used the PlatyPS yet myself. 😄
Just double-checked the parameters with Get-help New-CsOnlineSession and corrected the order of the Syntax.
I have 5 Parameters in MicrosoftTeams (v1.1.10-preview)

I know of the beaked Module, but haven't used the PlatyPS yet myself. 😄
Just double-checked the parameters with Get-help New-CsOnlineSession and corrected the order of the Syntax.
I have 5 Parameters in MicrosoftTeams (v1.1.10-preview)

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@Kateyanne Please merge this PR. Thanks.

@Kateyanne Please merge this PR. Thanks.

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Adding support for --token-usage/-t flag

Fixes #7
Thank you for making the process easier by adding the code for parsing the --token-usage/-t  option flag argument from the command line in codeMage.py!
Implementation
I started implementing the feature by adding an if-statement that checks if the option flag was provided to translator.py. At first, if condition was met, my code was simply printing out the token information (that has been extracted from the completion object) to stdout,  however, after the first round of testing, I noticed that the token amounts are always equal to 0.

After printing out the completion object, I've realized that completion token details are not being returned by the chosen model (completion_token_details=None).

That is why I added another check to see if completion token details are present in the response. Now, if details about the token usage are present, they get printed to stderr, else - the users will see a message saying that model didn't give any token usage details.

Examples
Running the command with a model that provides token usage details (openai/gpt-3.5-turbo)

Running the command with a model that doesn't

To take advantage of the token usage feature, you can consider allowing users to specify the model of choice, or switching to a model that gives token usage details in its responses.
Changes
Apart from adding the code block with if-statements, I've imported sys at the top of translator.py for printing to stderr, added the info about the new option at the bottom of the README.md.

and updated the help info for flag option in codeMage.py

Instead of using print(), I think you need to use sys.stderr.write("This is an stderr")

I have changed all of the print() statements to sys.stderr.write()

Thank you so much your contirubution. I merged it to my main branch. It looks really good.
And Yes, I checked that my LLM API for some reason doesn't support the token usage.
I will probably implement the support for other models


Add export notation for typescript module

Upon trying to use this library in a typescript project with esnext as the module type my IDE (IntelliJ Ultiimate) found the following typescript error:
TS2306: File<EMAIL_ADDRESS>is not a module.

The above error appeared when attempting to import the library via:
import chunkedDc from "@saltyrtc/chunked-dc";

Or
import {ReliableOrderedChunker, ReliableOrderedUnchunker} from "@saltyrtc/chunked-dc";

After looking around for a solution, the eventual fix was to include this export line suggested by this SO answer with the typescript documentation on how it exports a single object to be compatible with CommonJS and AMD.

@threema-danilo Would you like to take a look if this is fine?
In general though, this project could use a typing revamp... but chore. :slightly_smiling_face:

Sorry for the long delay and thanks for the bump. I think this looks good, I'll merge this and will also do some dependency maintenance 🙂

Uh, I merged too early (because CI was broken) 😕 When running node_modules/.bin/tsc --noEmit I get a lot of Cannot find namespace 'chunkedDc' errors.
I'll try to see if I can find a solution that can be implemented in reasonable time without breaking everything. Otherwise, I may revert the change until we (or a contributor) find time to revamp the entire typing setup. Right now we're using old-style namespaces, which should not be mixed with modules.

Yeah, I played around with different options, but by mixing namespaces and modules we seem to break some stuff.
The clean solution would be:

Get rid of the namespaces
Use modules, export all public APIs
Generate the types instead of writing them by hand

For now, I'll simply revert the commit. Sorry!


Same as Issue #3, but it somewhat works I guess

As in Issue #3 it says in my console "The addon with the id 'staffchat' was not found."
But staffchat works on one side though, if i write /sc  on my mc server it gets sent to the configured discord channel but the other way around doesn't work for some reason

Could you turn on debug in the Spicord config and tell me if it gives you any errors?

for some reason it works now, i restarted the server and after checking github i enabled debug on spicord but didn'T reload it yet, still apparently seems to work now
magically solved itself i guess

I've tested it myself and found the issue.
It tried to get something from the bot before the bot actually started.
I used onLoad instead of onReady which means that the bot may sometimes not be ready yet.
I'll upload a fix in a little bit.


doc: move governance to stage 2

As there is no need for board, budgetary, or legal approval
I believe this proposal can immediately go to stage 3
If there are no objections I'll modify this PR to do so.

LGTM


Callbacks don't work when passed unitialized

For example:
class Foo(inferno.callbacks.Callback):
    def on_epoch_end(self, net, **kwargs):
        pass

net = NeuralNet(..., callbacks=[Foo])

Error:
Traceback (most recent call last):
  File "train.py", line 189, in <module>
    pl.fit(corpus.train[:1000], corpus.train[:1000])
  File "/home/ottonemo/anaconda3/lib/python3.6/site-packages/sklearn/model_selection/_search.py", line 945, in fit
    return self._fit(X, y, groups, ParameterGrid(self.param_grid))
  File "/home/ottonemo/anaconda3/lib/python3.6/site-packages/sklearn/model_selection/_search.py", line 550, in _fit
    base_estimator = clone(self.estimator)
  File "/home/ottonemo/anaconda3/lib/python3.6/site-packages/sklearn/base.py", line 69, in clone
    new_object_params[name] = clone(param, safe=False)
  File "/home/ottonemo/anaconda3/lib/python3.6/site-packages/sklearn/base.py", line 57, in clone
    return estimator_type([clone(e, safe=safe) for e in estimator])
  File "/home/ottonemo/anaconda3/lib/python3.6/site-packages/sklearn/base.py", line 57, in <listcomp>
    return estimator_type([clone(e, safe=safe) for e in estimator])
  File "/home/ottonemo/anaconda3/lib/python3.6/site-packages/sklearn/base.py", line 67, in clone
    new_object_params = estimator.get_params(deep=False)
TypeError: get_params() missing 1 required positional argument: 'self'

Probable cause: get_params recursively inspects all attributes of the wrapper instance including self.callbacks which still contains the uninitialized callbacks. It then calls get_params which does not work as it is not a static method.

I couldn't reproduce it:
def test_get_params_with_uninit_callbacks(self, net_cls, module_cls):
    from inferno.callbacks import EpochTimer

    net = net_cls(
        module_cls,
        callbacks=[EpochTimer, ('other_timer', EpochTimer)],
    )
    # does not raise
    net.get_params()
    net.initialize()
    net.get_params()

Was this accidentally fixed?

Okay, this is how to reproduce it:
        net = net_cls(
            module_cls,
            callbacks=[EpochTimer, ('other_timer', EpochTimer)],
        )
        net = clone(net)

That problem cannot be easiliy fixed it seems. We could not return callbacks when get_params is called on NeuralNet, thus avoiding the recursive clone call on the un-initialized callbacks. However, that would mean that the cloned object does not have the callbacks anymore!
Specifically, the problem occurs on all attributes that are un-initialized and have the get_params method (which sklearn looks for). At the moment, this only applies to the callbacks.
I believe this is one further argument in favor of requiring everything to be initialized (see #13 )

I believe this is one further argument in favor of requiring everything to be initialized (see #13 )

Yeah. I think this is a WONTFIX in favor of #13.

Agree

Came here  to report the same bug.
Doesn't passing callbacks initialized break sklearn compatibility ? the inner state of the callbacks will change during training, which contradicts: These initial arguments (or parameters) are always remembered by the estimator.
A workaround to this could be to store the instanced callbacks in a special container that inherits from lists ?
    pass```

(I quickly that this does preserve `clone` and `initialize_callbacks` methods)

This is still a slight modification of the input argument but it seems acceptable.

Indeed [the type checking in `clone` is strict](https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/base.py#L49)

Thanks for chiming in.

Doesn't passing callbacks initialized break sklearn compatibility ? the inner state of the callbacks will change during training, which contradicts: These initial arguments (or parameters) are always remembered by the estimator.

I don't think that skorch callbacks violate this the way they are implemented. It is true that they change their state and it is also true that this mutates the initial arguments. However, once training starts again or the network is initialized the callbacks are re-set to their initial state exactly the way they were initalized (via the .initialize() method of the callback). If a callback has internal state it is implemented the sklearn way (self.foo_ for the changing parameter, self.foo for the initial parameter) to avoid this problem.
In my problem there is no issue but maybe I'm overlooking something. Is there a particular reason that you are reporting this right now?

Just to add to @githubnemo's comment, think of callbacks as an sklearn pipeline. When you fit the pipeline, the estimators are mutated. However, their __init__ arguments remain untouched.  This behaviour is the same behaviour as callbacks have. And analogously, pipelines don't allow to pass uninitialized estimators.
For that reason, I would leave the restriction except if you can show us a situation where this is undesired.

Thank you for the clarification, I understand your points. I think it is debatable whether this is compatible with the sklearn coding guidelines or not. I'd like to add a few more remarks including my usecases.
Before that, the issue for me is not strictly that the current NeuralNet does not support uninstanciated callbacks, it is that objects passed as input are mutated. If it were possible to clone the callbacks in initialize_callbacks before use it would also solve the issues.

think of callbacks as an sklearn pipeline
except sklearn.pipeline.Pipeline (and FeatureUnion) do not inherit from BaseEstimator, it's a different beast (a _BaseComposition). I'd imagine that a NeuralNet is not a composition, but an estimator (and a meta estimator).

I see two practical issues with instanciated callbacks passed as arguments:

in some cases, sklearn relies in hashing the input arguments stored as attributes to get a unique index of the estimator, for caching purpose. While I think that the caching utility in sklearn is really rough, current NeuralNet is not compatible with it, because the hash will differs before and after training. It's not a problem with sklearn' metaestimators because instanciated estimators are hashable and always cloned before use.
it's harder to keep track of objects attached to callbacks when trying to clean things. I've had usecases where the references in callbacks and the references in callbacks_ diverged (because I saved and loaded callbacks) and it took me some time to understand why the RAM wouldn't empty (because of references attached in callbacks.

(On a side not, speaking of references to old objects that should be flushed, it is not good to store a reference to the optimizer in LR schedulers like ReduceLROnPlateau, because if the optimizer is reinitialized during training, the reference in the scheduler is not updated. For my use I've rewritten those callbacks to avoid such an issue, in general I think that, for all objects that should remain synchronized or that might weight in RAM, it should be carefully ensured that only one reference exist at all time, and this reference is attached to an attribute of the current NeuralNet instance, and any interaction with those objects are done with this unique reference)

As you already said, this is not about callbacks being uninitialized but rather about potential side-effects.
Let's discuss this in a separate issue #434.

it is not good to store a reference to the optimizer in LR schedulers like ReduceLROnPlateau

I agree with you that storing references is problematic and should be avoided when possible. In this case,
there is not much we can do about it, though, since it is the PyTorch API we are dealing with, not skorch's. We also take care to make sure that only the latest reference is used when creating the scheduler before training to avoid such issues. If there is an issue that we have overlooked, please report it so we can work on a solution.


More updates

Most of the "backend" stuff is now complete and we can begin working on the "frontend", as in the stuff users of the library are going to utilise.
There are also still ~85 doc-missing warnings from StyleCop.

Merging, there are no warnings from StyleCop other than the documentation stuff.


*: implement the datablock projection

Codecov Report

Merging #22 into master will increase coverage by 0.12%.
The diff coverage is 66.66%.

@@            Coverage Diff            @@
##           master     #22      +/-   ##
=========================================
+ Coverage   83.18%   83.3%   +0.12%
=========================================
  Files         100     100
  Lines        9633    9565      -68
=========================================
- Hits         8013    7968      -45
+ Misses       1380    1365      -15
+ Partials      240     232       -8

Impacted Files
Coverage Δ

src/transforms/transform_orderby.go
66.66% <0%> (ø)
:arrow_up:

src/transforms/transform_projection.go
72.22% <0%> (+2.77%)
:arrow_up:

src/executors/executor_tvf.go
82.45% <0%> (+2.45%)
:arrow_up:

src/transforms/transform_filter.go
82.35% <100%> (+4.57%)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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Fix ring_exchange RS to support CUDA graph capture

@vasunvidia Could you make the change to main and not directly to release branch. Let's also replace all instances of at::cuda::getDefaultCUDAStream in com_gemm_overlap.h to at::cuda::getCurrentCUDAStream?

@vasunvidia Could you make the change to main and not directly to release branch. Let's also replace all instances of at::cuda::getDefaultCUDAStream in com_gemm_overlap.h to at::cuda::getCurrentCUDAStream?

Made the changes and created new PR https://github.com/NVIDIA/TransformerEngine/pull/811


[FEATURE REQUEST] ...Add hashtag capabilities

Is your feature request related to a problem? Please describe.
No
Describe the solution you'd like
I've submitted this same idea to YNAB, and after reading many forums it looks like many others have submitted the same idea over the last couple of years. It does not look like YNAB as done anything towards it so now I am submitting the idea to toolkit for ynab. It would be really nice if you can add a hastag and be able to filter reports by the hashtag. For example, I and my wife both have a vehicle, it would be nice to be able to just have 1 fuel subcategory, as well as 1 maintenance subcategory. Then in the description I would put #myvehicle or #wifesvehicle when ever I fueled up or did maintenance. That way I can see how much I spent on fuel or maintenance or see how much I spent on each vehicle total. I think mint.com has this feature also Spendee also has this feature if you want to check either one of those apps/websites out to get an idea of what I am suggesting. The reason I am not using either one those applications for this feature is because YNAB is just so much better and easier to use already. I think adding this feature would make YNAB the ultimate budgeting tool.
Describe alternatives you've considered
Still adding the hashtag in the memo, this makes it easy to search what I want and can select them to see a total, but I still can't filter reports by hashtag.

We use Trello to track Feature Requests so that users can vote on what they'd like to see next. This is crucial for us since there are so many requests and so little time amongst those of us who work on the Toolkit.
Your feature request has been added here and will need to be manually sorted.
This issue can now be closed.


DialogTrigger in popover should accept function as 2nd child

Closes https://github.com/adobe/react-spectrum/issues/985
✅ Pull Request Checklist:

[x] Included link to corresponding React Spectrum GitHub Issue.
[x] Added/updated unit tests and storybook for this change (for new code or code which already has tests).
[x] Filled out test instructions.
[N/A?] Updated documentation (if it already exists for this component).
[N/A?] Looked at the Accessibility Practices for this feature - Aria Practices

📝 Test Instructions:
Open the Storybook for DialogTrigger popover, verify that contents are visible, try to close it with the cancel button, verify it's closed

Merging can be performed automatically once the requested changes are addressed

looks like i'll need another review from @dannify 🙏


switch namespace to kube-system and define rbac SA

switch namespace to kube-system and define rbac SA as of 'kubernetes-dashboard'

Switching namespace makes sense. Nice hint.
What k8s version do you use? My problem is, that the service account kubernetes-dashboard (I use version 1.9.2) does not have access rights to the default namespace. Did you change something?
I had the same problem with the rbac. My approach was to grant cluster admin rights to the service account kube-system:default.
So running this command solves my problem. This bypasses the rbac in a way, but I can live with it. If you have a better approach, please share.
kubectl create clusterrolebinding kube-system-default-admin   --clusterrole=cluster-admin   --serviceaccount=kube-system:default


How to add our own json file ?

I'm using a CLI for my project here
I've managed to create a YAML/JSON that is working fine with your extension.
However, in order to run it, I have to add this json to generic.json.gz and hack catchFetcher.js to download that gz file instead of yours:
    fetchAllCurated(kind = 'general', isForcing = false) {
        return __awaiter(this, void 0, void 0, function* () {
            console.log("[CacheFetcher.fetchAllCurated] Started running...");
            const url = `https://github.com/vdesabou/kafka-docker-playground/raw/master/scripts/cli/general.json.gz`;

I'm wondering if there could be a better way to do that ?
Any thoughts ?

Current implementation can load individual JSON via "Shell Completion: Load Command Spec (experimental)". It loads matching JSON if available here: https://github.com/yamaton/h2o-curated-data/tree/main/experimental/json
So, if you are okay to do some hack, please overwrite the url in downloadCommandToCache to point to your JSON location like you did. It's a bit simpler.
Another quick and easy solution is to add your command spec to  https://github.com/yamaton/h2o-curated-data. I'm open to any solutions.

I used the experimental trick, working like a charm!
Thanks 😊


Crash on viewing module details for a module with an absent optional dependency

What you were trying to do
Test to see if the Health module would exhibit any weirdness with the ModuleTestingEnvironment module not present (optional dependency)
What actually happened
Game crashed when I tried to get module details (in the advanced game start screen) for Health (and I suspect any other combination of an optional dependency for a module not present)
How to reproduce

Have a workspace with an optional dependency, such as Health on the MTE (groovyw module recurse CoreSampleGameplay)
Delete the MTE from your workspace
Run the game and select Health via the Module Details button

Expecting a simple bit of hardening in the related display logic will be enough to bypass the crash: if a modue has an optional dependency that's not present just mark it as not present or don't allow the user to retrieve details on it.
Log details and game version
19:34:49.736 [pool-3-thread-1] INFO  o.t.e.module.ModuleListDownloader - Retrieved 184 entries
19:35:05.276 [main] ERROR o.terasology.engine.TerasologyEngine - Uncaught exception, attempting clean game shutdown
java.lang.NullPointerException: null
	at org.terasology.rendering.nui.layers.mainMenu.moduleDetailsScreen.ModuleDetailsScreen$11.draw(ModuleDetailsScreen.java:321)
	at org.terasology.rendering.nui.layers.mainMenu.moduleDetailsScreen.ModuleDetailsScreen$11.draw(ModuleDetailsScreen.java:306)
	at org.terasology.rendering.nui.itemRendering.AbstractItemRenderer.draw(AbstractItemRenderer.java:30)

We even do a null check in that method, but ignore it two lines later 🙄 will provide a quick fix, without extensive testing though...


Add failing test to FastAPI router

Description
For now... This PR is just proving that the default behavior doesn't work. :eyes:

Types of Changes

[ ] Core
[X] Bugfix
[ ] New feature
[X] Enhancement/optimization
[ ] Documentation

Issues Fixed or Closed by This PR

Default behavior should not raise an exception.

Checklist

[X] My code follows the code style of this project.
[ ] My change requires a change to the documentation.
[ ] I have updated the documentation accordingly.
[ ] I have read the CONTRIBUTING document.
[X] I have added tests to cover my changes.
[X] I have tested the changes and verified that they work and don't break anything (as well as I can manage).

I need to check what I've made wrong. I'll check later.
In the meantime, let me know which of the 3 last commits you prefer:

https://github.com/strawberry-graphql/strawberry/pull/2217/commits/660a74c15858669bad8d25a7e11a467a816531ab
https://github.com/strawberry-graphql/strawberry/pull/2217/commits/5f2b000eab3f7fedd55f0d4102762e305a216c87
https://github.com/strawberry-graphql/strawberry/pull/2217/commits/ac32575f89a1526c3ba9e7bd2d95d59713f58797

Choosing a path for the user may be a breaking change, as order matters... But it's unlikely, I guess? Anyway, let me know, and I'll fix the tests. :+1:


AttributeError: 'NoneType' object has no attribute 'items' in wandb_config.

wandb --version && python --version && uname

Weights and Biases version: 0.8.18
Python version: 3.7
Operating System: Linux

Description
My wandb run randomly crashes for a few runs (Traceback included). This doesn't happen all the time but randomly like 1 out of 3 time a script is run. If this helps, I am running my code on compute nodes which do not have access to internet. I plan to save my run logs locally and run wandb sync from login nodes which have access to internet to sync them online.
TRACE
wandb: Tracking run with wandb version 0.8.18
Traceback (most recent call last):
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/site-packages/wandb/internal_cli.py", line 106, in
main()
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/site-packages/wandb/internal_cli.py", line 98, in main
headless(args)
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/site-packages/wandb/internal_cli.py", line 54, in headless
util.sentry_reraise(e)
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/site-packages/wandb/util.py", line 92, in sentry_reraise
six.reraise(type(exc), exc, sys.exc_info()[2])
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/site-packages/six.py", line 693, in reraise
raise value
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/site-packages/wandb/internal_cli.py", line 36, in headless
run = wandb.wandb_run.Run.from_environment_or_defaults()
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/site-packages/wandb/wandb_run.py", line 247, in from_environment_or_defaults
config = Config.from_environment_or_defaults()
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/site-packages/wandb/wandb_config.py", line 87, in from_environment_or_defaults
return Config(config_paths=conf_paths, wandb_dir=wandb.wandb_dir(), run_dir=run_dir)
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/site-packages/wandb/wandb_config.py", line 54, in init
self.set_run_dir(run_dir)
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/site-packages/wandb/wandb_config.py", line 181, in set_run_dir
self._load_values()
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/site-packages/wandb/wandb_config.py", line 151, in _load_values
self._load_file(path)
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/site-packages/wandb/wandb_config.py", line 134, in _load_file
for key, val in loaded.items():
AttributeError: 'NoneType' object has no attribute 'items'
Traceback (most recent call last):
File "experiments/natural_language/dataset_experiments.py", line 36, in
is_natural_lang_exp=True)
File "/lustre03/project/6008064/karora/quant_exp_bias/experiments/util.py", line 62, in initialize_experiments
sync_tensorboard=False)
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/site-packages/wandb/init.py", line 1067, in init
_init_headless(run)
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/site-packages/wandb/init.py", line 277, in _init_headless
success, _ = server.listen(30)
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/site-packages/wandb/wandb_socket.py", line 46, in listen
self.connect()
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/site-packages/wandb/wandb_socket.py", line 40, in connect
self.connection, addr = self.socket.accept()
File "/home/karora/miniconda3/envs/quant_exp/lib/python3.7/socket.py", line 212, in accept
fd, addr = self._accept()
socket.timeout: timed out
(END)

This might be caused by large git api calls that are timing out.  Can you try running with WANDB_DISABLE_CODE=true

Thanks @vanpelt .
I'll try it out.
I just wanted to ascertain that AttributeError is happening due to socket timing out.

Yeah, the error is really mis leading.  I'll look into the attributeerror bug, but I think the root cause is something else.

Hey @kushalarora
In the past year we've majorly reworked the CLI and UI for Weights & Biases. We're closing issues older than 6 months. Please comment to reopen.


Remote Tunnel - ChromeOS's Penguin: Can't Install Extension on Remote Host

Remote Tunnel - ChromeOS's Penguin: Can't Install Extension on Remote Host
Does this issue occur when all extensions are disabled?: Can't test

VS Code Version: VSCode-Web (ui) + (host) /
Visual Studio Code
Version: 1.86.1
Commit: 31c37ee8f63491495ac49e43b8544550fbae4533
Date: 2024-02-07T09:07:19.849Z (3 days ago)
Browser: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Code/1.86.1 Chrome/118.0.5993.159 Electron/27.2.3 Safari/537.36
OS Version:
(OS) ChromeOS Flex - Version 122.0.6261.30 (Official Build) beta (64-bit)
(Crostini)
PRETTY_NAME="Debian GNU/Linux 12 (bookworm)"
NAME="Debian GNU/Linux"
VERSION_ID="12"
VERSION="12 (bookworm)"
VERSION_CODENAME=bookworm
ID=debian

Steps to Reproduce:
On ChromeOS

Enable Linux
Install VSCode Desktop (.deb)
Note: I didn't tested with VSCode CLI but can't risk breaking my local VSCode Desktop
Install Remote-Tunnel and Login
Go to VSCode Web
Open Remote Host and Log into the VSCode Desktop instance
Try to install any extension on remote host
Here is a test with GitHub Pull Request, but the same behavior applies to any other workspace extension

✔ Installed

Yet no extension has been installed on remote host

This issue should be transferred to https://github.com/microsoft/vscode-remote-release
Sorry @aeschli, can you do it?
I found that repository after creating that issue there, sorry for the inconvenience.

Try to install any extension on remote host

Can you please share following log when you try to install the extension - F1 > Open View... > Remote

@sandy081, well, now I can't even sign into "Remote - Tunnels"

Output - GitHub Authentication
2024-02-20 20:39:06.408 [info] Logging in for the following scopes: read:org user:email
2024-02-20 20:39:06.464 [info] Trying without local server... (read:org user:email)
2024-02-20 20:39:07.712 [info] Exchanging code for token...
2024-02-20 20:39:07.964 [error] Failed to fetch
2024-02-20 20:39:07.966 [error] Error: No auth flow succeeded.
	at t.GitHubServer.login (https://assets.github.dev/stable/8b3775030ed1a69b13e4f4c628c612102e30a681/extensions/github-authentication/dist/browser/extension.js#vscode-extension:3:186680)
	at async t.GitHubAuthenticationProvider.createSession (https://assets.github.dev/stable/8b3775030ed1a69b13e4f4c628c612102e30a681/extensions/github-authentication/dist/browser/extension.js#vscode-extension:3:183165)

However, I'm still signed in without apparent problem with the GitHub extension

https://github.com/microsoft/vscode/issues/204914#issuecomment-1954931556

Please file a separate issue for not able to connecting to the tunne;

However, my Extension doesn't get automatically installed, yet, i have ticked "sync this extesion"

Can you please share your settings sync log - F1 > Open View > Settings Sync

Separate issue filled: https://github.com/microsoft/vscode/issues/205747
It will take time, since I hard-reseted my computer.
I'll let you know

Closing this as there is nothing heard from the author.

I do not use my Chromebook anymore due to obstacles being thrown in my way such as this one
Please close as not planned instead @sandy081


Question about the OpenAI model endpoint names

Hi @alice9210,
We are evaluating our agent work on Android Control and have some promising results. Since the performance can be slightly affected by difference of GPT-4 endpoints, could I ask the specific endpoint name used in the paper?
Is it gpt-4-turbo-2024-04-09?

Thanks!

Yes that is correct. We used gpt-4-turbo-2024-04-09.
Hope that helps!


Requested feature_data_ size 536907080 doesn't match 1960; Feature generation failed;

Click to expand!
Issue Type
Bug
Have you reproduced the bug with TF nightly?
Yes
Source
source
Tensorflow Version
V2.8
Custom Code
Yes
OS Platform and Distribution
No response
Mobile device
No response
Python version
No response
Bazel version
No response
GCC/Compiler version
No response
CUDA/cuDNN version
No response
GPU model and memory
No response
Current Behaviour?
Hello Together,
I'm having a Problem with the micro_speech example for arduino from this repo: https://github.com/tensorflow/tflite-micro-arduino-examples/tree/main/examples/micro_speech
When trying to use this example with a new trained model from this jupyter noteboobk: https://github.com/tensorflow/tflite-micro/tree/main/tensorflow/lite/micro/examples/micro_speech/train
I always get the same error message:
Requested feature_data_ size 536907080 doesn't match 1960
Feature generation failed
The only thing i changed in the notebook was the tensorflow version. This is because this notebook was using 1.x Version which is no longer supported by colab and i changed it to work with the latest 2.x version
Can anyone help here?
Greetings,
Patrick
Standalone code to reproduce the issue
https://github.com/tensorflow/tflite-micro-arduino-examples/tree/main/examples/micro_speech

 https://github.com/tensorflow/tflite-micro/tree/main/tensorflow/lite/micro/examples/micro_speech/train

Relevant log output
No response

Hi @Svobi27
I was able to run the example after making some changes for TF 2.x version. Please find the gist here.
Thanks.

Hello @pjpratik
Thanks for the response!
I tried the arduino example with the model from your notebook but i still get the same error message unfortunatly...

@Svobi27
I see that at a ticket #2709 has been opened in TFLite Micro repo.
Could you please close this issue as it being tracked there?
Thanks.

Hi @Svobi27
As mentioned earlier,  this issue can be closed here and the issue: https://github.com/tensorflow/tflite-micro/issues/2079 can be opened since it is related to TFLite Micro.
Thanks.

Sorry missunderstood! reopened the issue again in the TFLite Micro repo

Thanks for opening the issue in TFLite Micro repro. Closing it here.


Choose the palette

How do people feel about this colour palette?

colour-palette.pdf

I am closing this issue as we have agreed on the colour palette above and created this app using these colours as a guide.


Remove "metadata filter by" from the record

Is your feature request related to a problem? Please describe.
Filter by metadata from records is not really useful now it's available from the main filter bar.
Describe the solution you'd like
Remove the filter action:

Checkbox
Apply/cancel button
Aligned metadata presentation to metadata info
Maintain separated metadata info and record info as two items in the falafel menu

Describe alternatives you've considered
Additional context
#1911

This issue will be tackled when we'll implement the "info records". What do you think @leiyre ? we don't save time doing this one first?

@Amelie-V I think both issues can be tackled at the same time, because they are closely related.


Task overlapped with armnn delegate

We should have a cmake for this project  and allow pure linux  to  run and   build a libneutralnetwork.so directly.  tensroflow lite nnapi delegate will dlopen libnutralnetwork.so  in pure linux environment (non-android)
There is no need for a duplicated and separated delegate for tensorflow lite.
https://github.com/ARM-software/armnn/tree/branches/armnn_20_11/delegate

I think for non-Android, using a direct delegate is quite a bit simpler to set up than getting NNNAPI and the NN HAL driver service to work.
Using the direct delegate will also work on older Android devices where NNAPI is not present, or an old version, so it can have advantages even on Android. Especially for third-party applications which are not in control of which versions of NN HAL drivers have been installed.
What advantages do you see NNAPI having over using a direct delegate?

I think for non-Android, using a direct delegate is quite a bit simpler to set up than getting NNNAPI and the NN HAL driver service to work.
Using the direct delegate will also work on older Android devices where NNAPI is not present, or an old version, so it can have advantages even on Android. Especially for third-party applications which are not in control of which versions of NN HAL drivers have been installed.
What advantages do you see NNAPI having over using a direct delegate?

1.) We don't need to modify the application to use nnapi. e.g.
I can just download tensorflow lite prebuilt benchmark tool to test the performance without any application code changes.
2.) We don't need a NN HAL driver service on non-Andoird.
All need is android-nn-driver to generate a libneuralnetworks.so for dlopen by the tensorflow lite.
tensorflow lite already support native linux nnapi.
3.) I don't think the setup will be harder when using nnapi instead of direct delegate. We nly need to build and install  ibneuralnetworks.so to /usr/lib, the tensorflow lite will dlopen it if it is found automatiacally.
4.) There are still unimplemented layers/support in android-nn-driver and direct delegate.
The andoirdd-nn-drvier implementation seems to be more completed though.
Right now , if the layer cannot be run in the GPU, it will fallback to CPU, and a single model can be break down into multiple parts . The model can still be run, but will end up with very poor performance due to latency and transfer of data between gpu/cpu for those cpu fallback layers. We should focus the development time on implementation those un-implementation layer first.  Right now I am doing a benchmark using direct  delegate , but the performance is very poor because of those unimplemented layers.  While all those layers are supported by Qualcomm/MediaTek/Hisilicon. Thse are the models I am currently testing with:
https://ai-benchmark.com/tests.html
5.) For older Android support , application can call or use armnn directly.

1.) We don't need to modify the application to use nnapi. e.g.
I can just download tensorflow lite prebuilt benchmark tool to test the performance without any application code changes.
2.) We don't need a NN HAL driver service on non-Andoird.
All need is android-nn-driver to generate a libneuralnetworks.so for dlopen by the tensorflow lite.
tensorflow lite already support native linux nnapi.
3.) I don't think the setup will be harder when using nnapi instead of direct delegate. We nly need to build and install  ibneuralnetworks.so to /usr/lib, the tensorflow lite will dlopen it if it is found automatiacally.
4.) There are still unimplemented layers/support in android-nn-driver and direct delegate.
The andoirdd-nn-drvier implementation seems to be more completed though.
Right now , if the layer cannot be run in the GPU, it will fallback to CPU, and a single model can be break down into multiple parts . The model can still be run, but will end up with very poor performance due to latency and transfer of data between gpu/cpu for those cpu fallback layers. We should focus the development time on implementation those un-implementation layer first.  Right now I am doing a benchmark using direct  delegate , but the performance is very poor because of those unimplemented layers.  While all those layers are supported by Qualcomm/MediaTek/Hisilicon. Thse are the models I am currently testing with:
https://ai-benchmark.com/tests.html
5.) For older Android support , application can call or use armnn directly.

There is nothing  wrong have a direct delegate and an nnapi backend for nnapi deleage.
But we  need to maintain 2 different codebase, and leave the user confuse about which one to use. I just want to have a positive discussion here only.
There are  something need to be done for android-nn-driver to build for pure linux.
since pure linux don't have libneuralnetwork_common,   we need to write/copy those  api ANeuralNetworksModel_  from libneuralnetwork_common for pure linux implementation.
Also need a wrapper for android logging mechanism in pure linux environment.

There is nothing  wrong have a direct delegate and an nnapi backend for nnapi deleage.
But we  need to maintain 2 different codebase, and leave the user confuse about which one to use. I just want to have a positive discussion here only.
There are  something need to be done for android-nn-driver to build for pure linux.
since pure linux don't have libneuralnetwork_common,   we need to write/copy those  api ANeuralNetworksModel_  from libneuralnetwork_common for pure linux implementation.
Also need a wrapper for android logging mechanism in pure linux environment.

@MatthewARM FYI Google already have out of Android (chrome os support for nnapi) which should be able to use in pure linux directly.
https://chromium.googlesource.com/chromiumos/platform2/+/master/nnapi

While I agree that NNAPI could be made to work on (non-Android) Linux, it doesn't seem to be a supported or promoted option within the NNAPI project, for example I've not seen any official guides on how to set it up.
So for the moment the path of least resistance for the Arm NN project is to have an NNAPI driver for Android system integrators, and a TensorFlow Lite delegate for other kinds of deployment.


Run make vet in CI

currently make vet fails on the repo:
./firewall_test.go:140:7: github.com/slackhq/nebula/firewall.Packet composite literal uses unkeyed fields
./firewall_test.go:315:7: github.com/slackhq/nebula/firewall.Packet composite literal uses unkeyed fields
./firewall_test.go:374:7: github.com/slackhq/nebula/firewall.Packet composite literal uses unkeyed fields
./firewall_test.go:460:7: github.com/slackhq/nebula/firewall.Packet composite literal uses unkeyed fields
./control.go:75:2: misuse of unbuffered os.Signal channel as argument to signal.Notify
./control.go:76:2: misuse of unbuffered os.Signal channel as argument to signal.Notify

This PR adds a make vet step to each of the test jobs. I'll add fixups for the simple go vet errors.

It appears that the remaining go vet errors are in
https://github.com/slackhq/nebula/blob/1a7c57501140d326224872675dcd9193b266783e/control.go#L78-L80
It seems that updating it to  sigChan := make(chan os.Signal, 1) would cause the channel to be buffered, and remove the vet error. I'm not sure what value would be correct. From reading it seems that channels are essentially queues? So a value of 1 or 2 would probably be sufficient since we just want to catch one of those values and shutdown?

@wadey mind merging this for me since I don't have merge perms atm?