Docker Provider Doesn't allow HTTPS in traefik<->backend in swarm mode

Do you want to request a feature or report a bug?

Bug

What did you do?
So the problem here is that when you try to verify certificates between backend and traefik in swarm. The problem:
'500 Internal Server Error' caused by: x509: cannot validate certificate for <IP_ADDRESS> because it doesn't contain any IP SANs
The issue is that the container's service might exist at the service DNS but the responding container has a different IP due to the Service/Pod system in Swarm/K8s. So the issue is that the IP that the container is presenting from is different than the IP which resolves to the DNS (because of the swarm loadbalancer) so the certificate is being labeled as invalid. There is no easy way to specify what the IP is prior to the containers deployment so we are stuck.

What did you expect to see?
Valid communication from traefik to the backend using the "https" scheme
What did you see instead?
Now I tested this using both a File provider and a Docker label provider in v2.2 and here are the results:

TLS v1.2
TLS v1.3

File Provider
works
not work

Docker
not work.
. not work

So in TLS v1.3 even if I specify the "url" as a dns within the file provider or using Docker it still sees the wrong IP and throws an error. However if I use the file provider and downgrade to v1.2 it works without using the insecureSkipVerify=true. So I think the feature/bug is that we should be able to specify that the Docker service use DNS for the TLS v1.2 case and then we will have to come up with a technical solution for the IP addresses later.

File Provider:
http:
  routers:
    mcf-https:
      entryPoints: ["https"]
      service: mcf-https@file
      tls: {}
      rule: Host(`mcf.mcf.prd.mbx.us.lmco.com`)
  services:
    mcf-https:
      loadBalancer:
        servers:
        - url: https://mcf:9443/

Docker Labels:
        - "traefik.enable=true"
        - "traefik.docker.network=traefik"
        - "traefik.constraint-label=traefik"
        - "traefik.http.routers.router01-https.rule=Host(`<host>`)"
        - "traefik.http.routers.router01-https.entrypoints=https"
        - "traefik.http.routers.router01-https.service=service01"
        - "traefik.http.routers.router01-https.tls=true"
        - "traefik.http.services.service01.loadbalancer.server.port=9000"
        - "traefik.http.services.service01.loadbalancer.server.scheme=https"

If applicable, please paste the log output in DEBUG level (--log.level=DEBUG switch)
'500 Internal Server Error' caused by: x509: cannot validate certificate for <IP_ADDRESS> because it doesn't contain any IP SANs

Hi @Enquier ,
Thanks for your interest in Traefik.
The new feature ServerTransport has been added to Traefik.
It is a way to fine tune the connection between Traefik and the backend.
It is only available on master and will be released in the next minor version.
Could you test it thanks to the traefik/traefik:experimental-master image (only for test purpose) ?
You will have to define the serversTransport with the needed servername/conf in a file like in documentation.
Then you will have to reference this serversTransport thanks to a label like:
- "traefik.http.services.service01.loadbalancer.serversTransport=myServiceTransport@file"

Okay I will take a look

Would it not be possible to add a simple label such as:
        - "traefik.http.services.<whatverthisis>.loadbalancer.tls.insecureskipverify=true"

Thanks

Would it not be possible to add a simple label such as:
        - "traefik.http.services.<whatverthisis>.loadbalancer.tls.insecureskipverify=true"

Thanks

All,
After some experimentation I was able to make this work in v2.4:
I configured the following in docker:

"traefik.http.services.foobar.loadbalancer.serversTransport = foobar@file"

And the following in a dynamic file provider:
http:
serversTransports:
foobar:
serverName: internalServiceCertificateSubject

Glad you solved it! As this was merely a question then, I close that issue :)

I will mention that it was rather difficult to determine the solution. I
would recommend updating the documentation to make it clear that you need
to define the ServersTransports only in a file even if referenced by a
Docker/provider
On Fri, Feb 19, 2021 at 08:55 Manuel Zapf<EMAIL_ADDRESS>wrote:

Glad you solved it! As this was merely a question then, I close that issue
:)
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/traefik/traefik/issues/7454#issuecomment-782164371,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/ABNEWTZQ33WFPOGYZVEAVHDS72CWDANCNFSM4S5CRK3A
.

--
-Chas


⚠ Redacted has degraded performance

In edb7c8f, Redacted ($RED) experienced degraded performance:

HTTP code: 200
Response time: 2970 ms

Resolved: Redacted performance has improved in 58124e4.


mjml-button button with href attribute has in Outlook different height than without href attribute

Hey,
as mjml-button with href evaluates to  html element, and mjml-button without any link evaluates to  html, this two elements have in effect different height, when displayed in Outlook

Hi @tomaszchabinka can you share a live snippet so I can try ?

Hi @tomaszchabinka
Some clients have differents default style for html tags. So you might need to reset it sometimes.
Button with href uses a simple a tag, and without href it uses a p tag.
I'm not able to reproduce on any Outlook so I'm closing the issue.
If you want to reopen please add more info like outlook version, a live snippet as @Kant1-0 asked and a screenshot so we can provide help on this


Normalize line endings to Unix style

Fixing old mistakes of committing windows style line endings in my original SNBT contribution.
The line endings of files are a mix of crlf windows- and lf unix style (se the image below from listing of line endings on the index). This normalizes all files to have lf unix style line endings again.

Left side shows the old mix of eol on the index. Right side shows the new normalized eol.

Thank you for the PR! I will merge it, and then this repository will be archived as MCProtocolLib now uses a different NBT library.


Can I change the Linux Machine ip range or configure a static ip?

Is your feature request related to a problem? Please describe.
The problem I encountered was that a cluster of machines in the same LAN required LAN ip.
But the dhcp network segment in a linux VM is 198.x.x.x, which is not a LAN network segment.
Describe the solution you'd like
I need the ip range which like  10.x.x.x, 172.16.x.x, 192.168.x.x
Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.
Additional context
Add any other context or screenshots about the feature request here.

Duplicate of #218


Improve toml-test integration

Make the scripts executable and add hashbang; this way it can be run a bit easier:
% toml-test -int-as-float ./toml-test-parse.js | tail -n3
toml-test v2023-10-18 [./toml-test-parse.js]: using embedded tests
  valid tests: 163 passed,  3 failed
invalid tests: 342 passed, 13 failed

% toml-test ./toml-test-encode.js -encoder | tail -n2
toml-test v2023-10-18 [./toml-test-encode.js]: using embedded tests
encoder tests: 157 passed,  9 failed

Also add a run-toml-test.bash script to the root, with the correct flags to run the tests and skipping known failures; this way it's easy to test for regressions.
I just added the -int-as-float flag to toml-test, so that you don't get loads of "failed" tests on this. In my reading of the specification ("64-bit signed integers (from −2^63 to 2^63−1) should be accepted") it's not actually required to support the full int64 range. I'll send a PR to clarify the spec on this later.

The Inf thing was fixed: https://github.com/toml-lang/toml-test/pull/143 – I didn't really look at the content of the scripts, but you should be able to remove any exceptions you did for that.
I need to look at the other failures; I just added smol-toml to https://arp242.github.io/toml-test-matrix; one of the reason I made that is so I can have some insight what failures happen with different encoders, and fix/improve toml-test as needed. I'll get round to it ... eventually.


Finished with error: Gradle task assembleDebug failed with exit code 1

I update subspace.yaml and now I get this message when I try tu run app.
flutter run -v
[  +26 ms] executing: [/Users/macbook/Developer/flutter/] git log -n 1 --pretty=format:%H
[  +43 ms] Exit code 0 from: git log -n 1 --pretty=format:%H
[        ] a72edc27064c2cbfbbae17ea1695333e1b3d9595
[        ] executing: [/Users/macbook/Developer/flutter/] git describe --match v*.*.* --first-parent --long --tags
[  +11 ms] Exit code 0 from: git describe --match v*.*.* --first-parent --long --tags
[        ] v1.9.1+hotfix.3-0-ga72edc270
[   +8 ms] executing: [/Users/macbook/Developer/flutter/] git rev-parse --abbrev-ref --symbolic @{u}
[  +11 ms] Exit code 0 from: git rev-parse --abbrev-ref --symbolic @{u}
[        ] origin/beta
[        ] executing: [/Users/macbook/Developer/flutter/] git ls-remote --get-url origin
[   +9 ms] Exit code 0 from: git ls-remote --get-url origin
[        ] https://github.com/flutter/flutter.git
[  +61 ms] executing: [/Users/macbook/Developer/flutter/] git rev-parse --abbrev-ref HEAD
[  +10 ms] Exit code 0 from: git rev-parse --abbrev-ref HEAD
[        ] beta
[ +245 ms] executing: /Users/macbook/Library/Android/sdk/platform-tools/adb devices -l
[  +11 ms] Exit code 0 from: /Users/macbook/Library/Android/sdk/platform-tools/adb devices -l
[        ] List of devices attached
           R58M80LG94Z            device usb:336592896X product:d1eea model:SM_N970F device:d1 transport_id:8
           emulator-5554          device product:sdk_google_phone_x86 model:Android_SDK_built_for_x86 device:generic_x86 transport_id:7
[  +20 ms] executing: /Users/macbook/Developer/flutter/bin/cache/artifacts/libimobiledevice/idevice_id -h
[  +49 ms] /usr/bin/xcrun simctl list --json devices
[ +114 ms] More than one device connected; please specify a device with the '-d <deviceId>' flag, or use '-d all' to act on all devices.
[   +3 ms] /Users/macbook/Library/Android/sdk/platform-tools/adb -s R58M80LG94Z shell getprop
[  +63 ms] ro.hardware = exynos9825
[        ] ro.build.characteristics = phone
[   +1 ms] /Users/macbook/Library/Android/sdk/platform-tools/adb -s emulator-5554 shell getprop
[  +20 ms] ro.hardware = ranchu
[   +2 ms] SM N970F                  • R58M80LG94Z   • android-arm64 • Android 9 (API 28)
[   +1 ms] Android SDK built for x86 • emulator-5554 • android-x86   • Android 5.1.1 (API 22) (emulator)
[  +12 ms] "flutter run" took 555ms.

#0      throwToolExit (package:flutter_tools/src/base/common.dart:28:3)
#1      RunCommand.validateCommand (package:flutter_tools/src/commands/run.dart:281:7)
<asynchronous suspension>
#2      FlutterCommand.verifyThenRunCommand (package:flutter_tools/src/runner/flutter_command.dart:465:11)
<asynchronous suspension>
#3      FlutterCommand.run.<anonymous closure> (package:flutter_tools/src/runner/flutter_command.dart:407:33)
<asynchronous suspension>
#4      AppContext.run.<anonymous closure> (package:flutter_tools/src/base/context.dart:154:29)
<asynchronous suspension>
#5      _rootRun (dart:async/zone.dart:1124:13)
#6      _CustomZone.run (dart:async/zone.dart:1021:19)
#7      _runZoned (dart:async/zone.dart:1516:10)
#8      runZoned (dart:async/zone.dart:1463:12)
#9      AppContext.run (package:flutter_tools/src/base/context.dart:153:18)
<asynchronous suspension>
#10     FlutterCommand.run (package:flutter_tools/src/runner/flutter_command.dart:397:20)
#11     CommandRunner.runCommand (package:args/command_runner.dart:197:27)
<asynchronous suspension>
#12     FlutterCommandRunner.runCommand.<anonymous closure> (package:flutter_tools/src/runner/flutter_command_runner.dart:402:21)
<asynchronous suspension>
#13     AppContext.run.<anonymous closure> (package:flutter_tools/src/base/context.dart:154:29)
<asynchronous suspension>
#14     _rootRun (dart:async/zone.dart:1124:13)
#15     _CustomZone.run (dart:async/zone.dart:1021:19)
#16     _runZoned (dart:async/zone.dart:1516:10)
#17     runZoned (dart:async/zone.dart:1463:12)
#18     AppContext.run (package:flutter_tools/src/base/context.dart:153:18)
<asynchronous suspension>
#19     FlutterCommandRunner.runCommand (package:flutter_tools/src/runner/flutter_command_runner.dart:356:19)
<asynchronous suspension>
#20     CommandRunner.run.<anonymous closure> (package:args/command_runner.dart:112:25)
#21     new Future.sync (dart:async/future.dart:224:31)
#22     CommandRunner.run (package:args/command_runner.dart:112:14)
#23     FlutterCommandRunner.run (package:flutter_tools/src/runner/flutter_command_runner.dart:242:18)
#24     run.<anonymous closure>.<anonymous closure> (package:flutter_tools/runner.dart:63:22)
<asynchronous suspension>
#25     _rootRun (dart:async/zone.dart:1124:13)
#26     _CustomZone.run (dart:async/zone.dart:1021:19)
#27     _runZoned (dart:async/zone.dart:1516:10)
#28     runZoned (dart:async/zone.dart:1500:12)
#29     run.<anonymous closure> (package:flutter_tools/runner.dart:61:18)
<asynchronous suspension>
#30     AppContext.run.<anonymous closure> (package:flutter_tools/src/base/context.dart:154:29)
<asynchronous suspension>
#31     _rootRun (dart:async/zone.dart:1124:13)
#32     _CustomZone.run (dart:async/zone.dart:1021:19)
#33     _runZoned (dart:async/zone.dart:1516:10)
#34     runZoned (dart:async/zone.dart:1463:12)
#35     AppContext.run (package:flutter_tools/src/base/context.dart:153:18)
<asynchronous suspension>
#36     runInContext (package:flutter_tools/src/context_runner.dart:59:24)
<asynchronous suspension>
#37     run (package:flutter_tools/runner.dart:50:10)
#38     main (package:flutter_tools/executable.dart:65:9)
<asynchronous suspension>
#39     main (file:///Users/macbook/Developer/flutter/packages/flutter_tools/bin/flutter_tools.dart:8:3)
#40     _startIsolate.<anonymous closure> (dart:isolate-patch/isolate_patch.dart:303:32)
#41     _RawReceivePortImpl._handleMessage (dart:isolate-patch/isolate_patch.d

[✓] Flutter (Channel beta, v1.9.1+hotfix.3, on Mac OS X 10.14.6 18G95, locale pl-PL)
    • Flutter version 1.9.1+hotfix.3 at /Users/macbook/Developer/flutter
    • Framework revision a72edc2706 (5 days ago), 2019-09-25 15:41:01 -0700
    • Engine revision b863200c37
    • Dart version 2.5.0

[✓] Android toolchain - develop for Android devices (Android SDK version 29.0.2)
    • Android SDK at /Users/macbook/Library/Android/sdk
    • Android NDK location not configured (optional; useful for native profiling support)
    • Platform android-29, build-tools 29.0.2
    • Java binary at: /Applications/Android Studio.app/Contents/jre/jdk/Contents/Home/bin/java
    • Java version OpenJDK Runtime Environment (build 1.8.0_202-release-1483-b49-5587405)
    • All Android licenses accepted.

[✓] Xcode - develop for iOS and macOS (Xcode 11.0)
    • Xcode at /Applications/Xcode.app/Contents/Developer
    • Xcode 11.0, Build version 11A420a
    • CocoaPods version 1.7.5

[✓] Android Studio (version 3.5)
    • Android Studio at /Applications/Android Studio.app/Contents
    • Flutter plugin version 39.0.3
    • Dart plugin version 191.8423
    • Java version OpenJDK Runtime Environment (build 1.8.0_202-release-1483-b49-5587405)

[✓] IntelliJ IDEA Community Edition (version 2019.2.2)
    • IntelliJ at /Applications/IntelliJ IDEA CE.app
    • Flutter plugin version 39.0.5
    • Dart plugin version 192.6603.23

[✓] VS Code (version 1.38.0)
    • VS Code at /Applications/Visual Studio Code.app/Contents
    • Flutter extension version 3.4.1

[✓] Connected device (2 available)
    • SM N970F                  • R58M80LG94Z   • android-arm64 • Android 9 (API 28)
    • Android SDK built for x86 • emulator-5554 • android-x86   • Android 5.1.1 (API 22) (emulator)

• No issues found!

I had met this error too.

This maybe helpful:
flutter clean
adb uninstall com.your.app.id

Remove the -v and you'll see the log it's trying to show:
"[ +114 ms] More than one device connected; please specify a device with the '-d ' flag, or use '-d all' to act on all devices."


added support for ingress in k8s 1.22+

Duplicates #27.

Fixes #19.

Any updates on when will this be merged?

Waiting for the author to respond.
As a general rule, I don't merge MRs without some due diligence in communication from the author, particularly after feedback is given and left unaddressed.

Seems that the author (@devfaz) hasn't been active in the last few months.
This PR is crucial, cause it makes the chart usable for all the latest k8s versions.
Is there something else we can do about it?

@ElArtista  thx for the trigger...
Even if I dont get why my missing answer is not allowing any merge.
LMGTFY: https://kubernetes.io/blog/2019/07/18/api-deprecations-in-1-16/
So it will no longer work with k8s <1.16, but start working for k8s >= 1.22.
For the future I would suggest to handle new commiters a bit more friendly, than - maybe - they will continue to try improving the code. Thats how opensource works - we all provide work/time for free and should appricate each others work as much as possible.

Closing, as the author is in violation of contribution guidelines.


Localization isn't working

if let bundleURL = podBundle.URLForResource("MBPhotoPicker", withExtension: "bundle") fails

cocoapods 1.0.1


Device hangs when running appetizer trace replay

Hi,
I record the trace on system A and when I run replay on system B, the device hangs, I have to reboot the device manaully, because the device appears offline when I run adb devices
Can you suggest what is wrong?

make sure you dont have STF or alike running or managing the device in question.
adb shell ps | grep minitouch to check if there is any process running minitouch. If so, there should be some testing frameworks/tools using minitouch that conflicts with replaykit.
If not, please report further details about the device, like model, root?, Android version, and adb shell getevent -lp results.

Thanks for your feedback.
I do have stf running
Is there a way to run both stf and replaykit ?

I have another problem
I am using the code in test-appetizer-toolkit-replays.sh as is
I invoke the shell script for another python script, the app launches waits a few seconds and then exits without any errors.
When I run only the shell script, it works flawlessly, it replays all of the events in the trace file

You need to remove the device from STF's control.
As for the script, I suspect your shell sets some environment variables (e.g., PATH) that makes replaykit work. But in the python case, processes launched from subprocess does not have the same environment variables as the shell. To workaround, 1. set shell=True when opening replaykit from Python 2. make a symbolic link in /usr/bin/ or similar locations for adb.


How to convert the trained tensorflow model to numpy format

How to convert the trained tensorflow model to numpy format that you provided in the DoReFa demo? thanks.

./scripts/dump-model-params.py --meta train_log/alexnet-dorefa/graphxxxx.meta train_log/alexnet-dorefa/model-xxx output.npy

Hi,can you help me with my problem during using dump-model-params?
(tensorflow) xxxxx-Precision-Tower-7910:~/tensorflow/DoReFa-Net$ ./dump-model-params.py --meta train_log/alexnet-dorefa1118-000755/graph-1118-000802.meta train_log/alexnet-dorefa1118-000755/model out.npy
Failed to load OpenCL runtime (expected version 1.1+)
Traceback (most recent call last):
File "./dump-model-params.py", line 35, in
init = get_model_loader(args.model)
File "/home/xxxxx/.local/lib/python2.7/site-packages/tensorpack/tfutils/sessinit.py", line 261, in get_model_loader
return SaverRestore(filename)
File "/home/xxxx/.local/lib/python2.7/site-packages/tensorpack/tfutils/sessinit.py", line 106, in init
model_path = get_checkpoint_path(model_path)
File "/home/xxxx/.local/lib/python2.7/site-packages/tensorpack/tfutils/varmanip.py", line 167, in get_checkpoint_path
assert tf.gfile.Exists(model_path) or tf.gfile.Exists(model_path + '.index'), model_path
AssertionError: train_log/alexnet-dorefa1118-000755/model

I said model-xxx, not model.

What xxx stands for?

model-xxx means files whose names start with model-.

Thank you for your patience. 👍

look like .npy not supported now?

The script itself has documented how to use it. It now uses npz.

@ppwwyyxx : Does tensorpack support reading the *.pb files? If not, could you recommend other tools that can also extract the nets' weights to numpy arrays? Many thanks in advance!

You should in general read a file by referring to the library that creates the file.
Specifically, if you mean "pb files" created by tensorflow, then tensorflow will have the tool to read it, not tensorpack.


No Scope available on non-versioned controllers

Given:
ASP.NET Core 5 API App using Windsor
When using Microsoft API versioning (Startup.cs line 29) the controller is only working when the request is using the versioned url "/api/v1/weatherforecast". When using the non-versioned url "/weatherforecast" services resolved inplace creates a InvalidOperationException "No Scope available"
This was working with ASP.NET Core 2.2.
AspCoreVersionedApis.zip

HI @twenzel
preferred way to resolve in your code is to use IServiceProvider not container directly. Especially with scoped services. ASP.NET runtime contols the lifetime of the scope.
For your code:
public WeatherForecastController(ILogger<WeatherForecastController> logger, IUserService userService, IServiceProvider serviceProvider)
{
	_logger = logger;
	_userService = userService ?? throw new ArgumentNullException(nameof(userService));
	_serviceProvider = serviceProvider;
}

[HttpGet]
public IEnumerable<WeatherForecast> Get()
{
	var service = _serviceProvider.GetRequiredService<IScopedService>();
	var service1 = _serviceProvider.GetRequiredService<ITransientService>();

	var rng = new Random();
	return Enumerable.Range(1, 5).Select(index => new WeatherForecast
	{
		Date = DateTime.Now.AddDays(index),
		TemperatureC = rng.Next(-20, 55),
		Summary = Summaries[rng.Next(Summaries.Length)]
	})
	.ToArray();
}

Hi Guys,
I'm experiencing the same issue. I have a POST request, then my code calls Container.BeginScope().
The scope seems to be ok, as I don't receive any exception.
When I try to resolve a scoped service I get error 'System.InvalidOperationException: 'No scope available'
'.
Do you have any suggestion?
Best regards

@StefanoVuerich ,
i am wondering why do you need to manually call Container.BeginScope()? The pipeline should start scope via CreateScope automatically

@ltines ,
our old implementation was calling Container.Beginscope() to be able to resolve scoped services.
What is the piece of the pipeline you are referring when you say 'The pipeline should start scope via CreateScope automatically' ?


Provide images as argument via iOS Shortcuts

Rather than selecting images within Pythonista, would like to be able to select images in another app and send them to the script vis the iOS Share Sheet.

This isn't currently possible in iOS, because Apple is too intuitive and innovative. (what other reason could there be, right?)


error while creating mount source path

The issue has been previously submitted here:
https://github.com/linuxserver/docker-tautulli/issues/44
but submitter solved it by uninstalling the snap package (which doesn't solve the issue)
today I also run into the same problem using snap package.
Works fine with docker ubuntu artful repo.
Doesn't work if I use snap package.
Please look into this and make them compatible.

To add more info to anyone who runs into this issue, it's because the snap package is adhering to the default permissions/privileges that snap packages are granted. Some other snaps get around this issue by instructing users to install with the --classic flag passed in - but imitating the legacy permissions defeats the purpose of the security scoping done in snaps.
For reference:
docker-compose.yaml
version: '3'
services:
    my_service:
        volumes:
            - ~/.hidden_folder:/root/.hidden_folder
...

$ docker.compose up
$ docker inspect container_id
...
"Mounts": [
    {
        "Type": "bind",
        "Source": "/home/my_user/snap/docker/179/.hidden_folder",
        "Destination": "/root/.hidden_folder",
        "Mode": "rw",
        "RW": true,
        "Propogation": "rprivate"
    }
...

@GS-JS  so what i'm hearing is that a snap may be a bad fit for a docker deliver method?

@cacois I'm not familiar enough with Ubuntu/Docker/Snap enough to say for sure that this, or other Docker+Snap issues, is a show-stopper - apologies. Maybe Docker+Snap actually warrants the --classic flag to function appropriately.

Closing all issues and pull requests since this repo is getting archived (see notice at the top of README).


Fix POSIX API write file bug

What changes are proposed in this pull request?
All the output stream operations should be synchronized to prevent concurrent operations and able to get correct written size in Fuse.getattr.
Why are the changes needed?
Previously Fuse.write() didn't synchronize the write file operation and host the assumption that all write will be sequential and is guaranteed by the application which is not true.
Does this PR introduce any user facing changes?
NA

Access pattern:

BytesWritten will be updated sequentially (synchronized on the output stream write operations)
BytesWritten value will be read concurrently

same thread: write()-getattr()-write()-getattr(), use "volatile long mBytesWritten" to make sure the getattr can always get the correct bytes writtem.
other threads (e.g. ls commands) getattr() at any time, the result can be a little outdated or incorrect. Don't want to use synchronized block around outputStream.getBytesWritten() to slow down the write operations.

Error: 8.675 [ERROR]   Run 2: DistributedCommandsStatsTest.testDistributedLoadCancelStats:151 » Timeout Time...
20:29:18.675 [INFO]

WIP may rewrite this PR


Download button fails

There is something wrong in the code. I will try to fix it asap.

I found the problem, the download button is downloading a base64 string the length of 127 @Google doc pages. Where the canvas only has the base64 string the length of.... super short.
The download button is not appending the data instead of setting: it is overwriting. So that isn't the problem.
The solution might fall in as setting the download button href to the data from the canvas instead of what it is doing.

It seems to be working now on the computer I just tested it with which is different than the other 2 computers plus different times of day (other 2 were at same time).

Yeah, it is working now.


CUDA seems only be used in python dlib not linux c++

Hi,
I have used mmod dlib detection. When it's used via python, the GPU is automatically used. However, when it's used via c++, it seems the GPU is not used and the speed is quite slow. The same linux box with CUDA installed. The dlib path is also included. Please advice. Thank you.

Help is more likely if you can provide:

The commands you used to build dlib
The output of those commands

In my experience, the best way of installing dlib is via cmake as a shared library so it can be referenced from your own program's CMakeLists file.
Once you have installed CUDA and cuDNN, and completed the post-install instructions correctly (by adding relevent things to the PATH and LD_LIBRARY_PATH), cmake will automatically detect CUDA and cuDNN and build dlib to us them.
An example cmake command to build dlib as a shared library with CUDA and cuDNN support is:
cmake -DCMAKE_C_COMPILER=/usr/bin/gcc-8 -DCMAKE_CXX_COMPILER=/usr/bin/g++-8 -DUSE_AVX_INSTRUCTIONS=ON -DBUILD_SHARED_LIBS=1 -DCUDA_HOST_COMPILER=/usr/bin/gcc-8 ../

You should see from the output whether or not dlib has then successfully picked up the configuration of CUDA and cuDNN, and if not why not (the output really is very helpful in telling you what you haven't done).
For example, you should see something like:
-- Found CUDA: /usr (found suitable version "10.1", minimum required is "7.5")
-- Looking for cuDNN install...
-- Found cuDNN: /usr/lib/x86_64-linux-gnu/libcudnn.so
-- Building a CUDA test project to see if your compiler is compatible with CUDA...
-- Building a cuDNN test project to check if you have the right version of cuDNN installed...
-- Enabling CUDA support for dlib.  DLIB WILL USE CUDA

Then you can build:
cmake --build . --config Release


chore: release mailtools v0.1.1

#17  👈
main

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Join @BlankParticle and the rest of your teammates on  Graphite

Merge activity

Apr 7, 1:16 AM EDT: @BlankParticle merged this pull request with Graphite.


Python 3.6.8 and Tensorflow 1.12.0 not working on windows 2008 R2

Please make sure that this is a build/installation issue. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:build_template
System information

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Windows 2008 R2 64-bit
TensorFlow installed from (source or binary): source (pip install tensorflow)
TensorFlow version: 1.12.0
Python version: 3.6.8
Installed using virtualenv? pip? conda?: pip
GPU model and memory: 4GB RAM

Describe the problem
I'm trying to import the tensorflow 1.12.0 library in python 3.6.8 but at the initial stage itself in getting following error.
Please help me out with the same.
Provide the exact sequence of commands / steps that you executed before running into the problem
Successfully installed tensorflow-1.12.0
C:\Tensorflow\models\research>python
Python 3.6.8 (tags/v3.6.8:3c6b436a57, Dec 24 2018, 00:16:47) [MSC v.1916 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.

import tensorflow as tf
Traceback (most recent call last):
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\p
ython\pywrap_tensorflow.py", line 58, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\p
ython\pywrap_tensorflow_internal.py", line 28, in
_pywrap_tensorflow_internal = swig_import_helper()
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\p
ython\pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\imp.py", line 243, in load
_module
return load_dynamic(name, filename, file)
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\imp.py", line 343, in load
_dynamic
return _load(spec)
ImportError: DLL load failed with error code -1073741795

During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "", line 1, in
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow_
init_.py", line 24, in
from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\p
ython_init_.py", line 49, in
from tensorflow.python import pywrap_tensorflow
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\p
ython\pywrap_tensorflow.py", line 74, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\p
ython\pywrap_tensorflow.py", line 58, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\p
ython\pywrap_tensorflow_internal.py", line 28, in
_pywrap_tensorflow_internal = swig_import_helper()
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\p
ython\pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\imp.py", line 243, in load
_module
return load_dynamic(name, filename, file)
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\imp.py", line 343, in load
_dynamic
return _load(spec)
ImportError: DLL load failed with error code -1073741795
Any other info / logs
Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.

Tensorflow installation logs if required
C:\Tensorflow\models\research>pip install tensorflow
Collecting tensorflow
Using cached https://files.pythonhosted.org/packages/05/cd/c171d2e33c0192b04560ce864c26eba83fed888
fe5cd9ded661b2702f2ae/tensorflow-1.12.0-cp36-cp36m-win_amd64.whl
Requirement already satisfied: keras-applications>=1.0.6 in c:\users\administrator\appdata\local\pro
grams\python\python36\lib\site-packages (from tensorflow) (1.0.7)
Requirement already satisfied: absl-py>=0.1.6 in c:\users\administrator\appdata\local\programs\pytho
n\python36\lib\site-packages (from tensorflow) (0.7.0)
Requirement already satisfied: tensorboard<1.13.0,>=1.12.0 in c:\users\administrator\appdata\local\p
rograms\python\python36\lib\site-packages (from tensorflow) (1.12.2)
Requirement already satisfied: numpy>=1.13.3 in c:\users\administrator\appdata\local\programs\python
\python36\lib\site-packages (from tensorflow) (1.16.1)
Requirement already satisfied: wheel>=0.26 in c:\users\administrator\appdata\local\programs\python\p
ython36\lib\site-packages (from tensorflow) (0.33.1)
Requirement already satisfied: grpcio>=1.8.6 in c:\users\administrator\appdata\local\programs\python
\python36\lib\site-packages (from tensorflow) (1.18.0)
Requirement already satisfied: astor>=0.6.0 in c:\users\administrator\appdata\local\programs\python
python36\lib\site-packages (from tensorflow) (0.7.1)
Requirement already satisfied: termcolor>=1.1.0 in c:\users\administrator\appdata\local\programs\pyt
hon\python36\lib\site-packages (from tensorflow) (1.1.0)
Requirement already satisfied: protobuf>=3.6.1 in c:\users\administrator\appdata\local\programs\pyth
on\python36\lib\site-packages (from tensorflow) (3.6.1)
Requirement already satisfied: six>=1.10.0 in c:\users\administrator\appdata\local\programs\python\p
ython36\lib\site-packages (from tensorflow) (1.12.0)
Requirement already satisfied: keras-preprocessing>=1.0.5 in c:\users\administrator\appdata\local\pr
ograms\python\python36\lib\site-packages (from tensorflow) (1.0.9)
Requirement already satisfied: gast>=0.2.0 in c:\users\administrator\appdata\local\programs\python\p
ython36\lib\site-packages (from tensorflow) (0.2.2)
Requirement already satisfied: h5py in c:\users\administrator\appdata\local\programs\python\python36
\lib\site-packages (from keras-applications>=1.0.6->tensorflow) (2.9.0)
Requirement already satisfied: markdown>=2.6.8 in c:\users\administrator\appdata\local\programs\pyth
on\python36\lib\site-packages (from tensorboard<1.13.0,>=1.12.0->tensorflow) (3.0.1)
Requirement already satisfied: werkzeug>=0.11.10 in c:\users\administrator\appdata\local\programs\py
thon\python36\lib\site-packages (from tensorboard<1.13.0,>=1.12.0->tensorflow) (0.14.1)
Requirement already satisfied: setuptools in c:\users\administrator\appdata\local\programs\python\py
thon36\lib\site-packages (from protobuf>=3.6.1->tensorflow) (40.6.2)
Installing collected packages: tensorflow
Successfully installed tensorflow-1.12.0

@akrana I think for some reason, tensorflow was not installed correctly. I had this issue earlier and resolved it. Please uninstall python and tensorflow Then reinstall using the instructions here. Thanks!

Hello,
I did uninstall the Python 3.6.8, reinstall Python.
Uninstall tensorflow, reinstall it. Still I was facing same issue
I degraded the python to 3.6.6 and reinstall tensorflow, Im still facing the issue as follow

C:\Users\Administrator>pip uninstall tensorflow
Uninstalling tensorflow-1.12.0:
  Would remove:
    c:\users\administrator\appdata\local\programs\python\python36\lib\site-packa
ges\tensorflow-1.12.0.dist-info\*
    c:\users\administrator\appdata\local\programs\python\python36\lib\site-packa
ges\tensorflow\*
    c:\users\administrator\appdata\local\programs\python\python36\scripts\freeze
_graph.exe
    c:\users\administrator\appdata\local\programs\python\python36\scripts\saved_
model_cli.exe
    c:\users\administrator\appdata\local\programs\python\python36\scripts\tensor
board.exe
    c:\users\administrator\appdata\local\programs\python\python36\scripts\tflite
_convert.exe
    c:\users\administrator\appdata\local\programs\python\python36\scripts\toco.e
xe
    c:\users\administrator\appdata\local\programs\python\python36\scripts\toco_f
rom_protos.exe
Proceed (y/n)? y
  Successfully uninstalled tensorflow-1.12.0
C:\Users\Administrator>pip install tensorflow
Collecting tensorflow
Downloading https://files.pythonhosted.org/packages/bf/58/34bfa8fa17f863333611
72b3b502e805195180f19a7496ad0f6149138d55/tensorflow-1.13.1-cp36-cp36m-win_amd64.
whl (63.1MB)
100% |████████████████████████████████| 63.1MB 69kB/s
Requirement already satisfied: numpy>=1.13.3 in c:\users\administrator\appdata\l
ocal\programs\python\python36\lib\site-packages (from tensorflow) (1.16.1)
Collecting tensorflow-estimator<1.14.0rc0,>=1.13.0 (from tensorflow)
Downloading https://files.pythonhosted.org/packages/bb/48/13f49fc3fa0fdf916aa1
419013bb8f2ad09674c275b4046d5ee669a46873/tensorflow_estimator-1.13.0-py2.py3-non
e-any.whl (367kB)
100% |████████████████████████████████| 368kB 6.6MB/s
Requirement already satisfied: grpcio>=1.8.6 in c:\users\administrator\appdata\l
ocal\programs\python\python36\lib\site-packages (from tensorflow) (1.18.0)
Requirement already satisfied: keras-applications>=1.0.6 in c:\users\administrat
or\appdata\local\programs\python\python36\lib\site-packages (from tensorflow) (1
.0.7)
Requirement already satisfied: gast>=0.2.0 in c:\users\administrator\appdata\loc
al\programs\python\python36\lib\site-packages (from tensorflow) (0.2.2)
Requirement already satisfied: termcolor>=1.1.0 in c:\users\administrator\appdat
a\local\programs\python\python36\lib\site-packages (from tensorflow) (1.1.0)
Requirement already satisfied: wheel>=0.26 in c:\users\administrator\appdata\loc
al\programs\python\python36\lib\site-packages (from tensorflow) (0.33.1)
Requirement already satisfied: astor>=0.6.0 in c:\users\administrator\appdata\lo
cal\programs\python\python36\lib\site-packages (from tensorflow) (0.7.1)
Requirement already satisfied: six>=1.10.0 in c:\users\administrator\appdata\loc
al\programs\python\python36\lib\site-packages (from tensorflow) (1.12.0)
Requirement already satisfied: absl-py>=0.1.6 in c:\users\administrator\appdata
local\programs\python\python36\lib\site-packages (from tensorflow) (0.7.0)
Requirement already satisfied: protobuf>=3.6.1 in c:\users\administrator\appdata
\local\programs\python\python36\lib\site-packages (from tensorflow) (3.6.1)
Requirement already satisfied: keras-preprocessing>=1.0.5 in c:\users\administra
tor\appdata\local\programs\python\python36\lib\site-packages (from tensorflow) (
1.0.9)
Collecting tensorboard<1.14.0,>=1.13.0 (from tensorflow)
Downloading https://files.pythonhosted.org/packages/fa/7b/3ee06856ec30d5136cd2
002408df1d111fcff269f3691147dbf3b8dc0ba2/tensorboard-1.13.0-py3-none-any.whl (3.
2MB)
100% |████████████████████████████████| 3.2MB 6.6MB/s
Collecting mock>=2.0.0 (from tensorflow-estimator<1.14.0rc0,>=1.13.0->tensorflow
)
Downloading https://files.pythonhosted.org/packages/e6/35/f187bdf23be87092bd0f
1200d43d23076cee4d0dec109f195173fd3ebc79/mock-2.0.0-py2.py3-none-any.whl (56kB)
100% |████████████████████████████████| 61kB 3.9MB/s
Requirement already satisfied: h5py in c:\users\administrator\appdata\local\prog
rams\python\python36\lib\site-packages (from keras-applications>=1.0.6->tensorfl
ow) (2.9.0)
Requirement already satisfied: setuptools in c:\users\administrator\appdata\loca
l\programs\python\python36\lib\site-packages (from protobuf>=3.6.1->tensorflow)
(40.6.2)
Requirement already satisfied: werkzeug>=0.11.15 in c:\users\administrator\appda
ta\local\programs\python\python36\lib\site-packages (from tensorboard<1.14.0,>=1
.13.0->tensorflow) (0.14.1)
Requirement already satisfied: markdown>=2.6.8 in c:\users\administrator\appdata
\local\programs\python\python36\lib\site-packages (from tensorboard<1.14.0,>=1.1
3.0->tensorflow) (3.0.1)
Collecting pbr>=0.11 (from mock>=2.0.0->tensorflow-estimator<1.14.0rc0,>=1.13.0-

tensorflow)
Downloading https://files.pythonhosted.org/packages/8c/7f/fed53b379500fd889707
d1f6e61c2a35e12f2de87396894aff89b017d1d6/pbr-5.1.2-py2.py3-none-any.whl (107kB)
100% |████████████████████████████████| 112kB 6.6MB/s
Installing collected packages: pbr, mock, tensorflow-estimator, tensorboard, ten
sorflow
Found existing installation: tensorboard 1.12.2
Uninstalling tensorboard-1.12.2:
Successfully uninstalled tensorboard-1.12.2
Successfully installed mock-2.0.0 pbr-5.1.2 tensorboard-1.13.0 tensorflow-1.13.1
tensorflow-estimator-1.13.0

C:\Users\Administrator>python
Python 3.6.6 (v3.6.6:4cf1f54eb7, Jun 27 2018, 03:37:03) [MSC v.1900 64 bit (AMD6
4)] on win32
Type "help", "copyright", "credits" or "license" for more information.

import tensorflow as tf
Traceback (most recent call last):
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-p
ackages\tensorflow\python\pywrap_tensorflow.py", line 58, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-p
ackages\tensorflow\python\pywrap_tensorflow_internal.py", line 28, in
_pywrap_tensorflow_internal = swig_import_helper()
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-p
ackages\tensorflow\python\pywrap_tensorflow_internal.py", line 24, in swig_impor
t_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, descript
ion)
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\imp.py
", line 243, in load_module
return load_dynamic(name, filename, file)
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\imp.py
", line 343, in load_dynamic
return _load(spec)
ImportError: DLL load failed with error code -1073741795

During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "", line 1, in
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-p
ackages\tensorflow_init_.py", line 24, in
from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-im
port
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-p
ackages\tensorflow\python_init_.py", line 49, in
from tensorflow.python import pywrap_tensorflow
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-p
ackages\tensorflow\python\pywrap_tensorflow.py", line 74, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-p
ackages\tensorflow\python\pywrap_tensorflow.py", line 58, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-p
ackages\tensorflow\python\pywrap_tensorflow_internal.py", line 28, in
_pywrap_tensorflow_internal = swig_import_helper()
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\site-p
ackages\tensorflow\python\pywrap_tensorflow_internal.py", line 24, in swig_impor
t_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, descript
ion)
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\imp.py
", line 243, in load_module
return load_dynamic(name, filename, file)
File "C:\Users\Administrator\AppData\Local\Programs\Python\Python36\lib\imp.py
", line 343, in load_dynamic
return _load(spec)
ImportError: DLL load failed with error code -1073741795
Failed to load the native TensorFlow runtime.
See https://www.tensorflow.org/install/errors
for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

@akrana Looking at the error log, I see the tensorflow was not uninstalled completely for some reason. Did you follow the instructions I provided? Could you follow that and let me know if that solved installation issue? Thanks!

I think it was resolved. I am closing the issue. Please open a new ticket when new information is available. Thanks!

m


added documentation for #78 and 213e9a8

Q
A

Bug fix?
no

New feature?
no

API breaks?
no

Deprecations?
no

Related tickets
Additional documentation for #78 (213e9a8) and banzaicloud/banzai-charts#528

License
Apache 2.0

What's in this PR?
I added additional documentation for the s3_endpoint variable and will be submitting another PR to the banzaicloud/banzai-charts.
Why?
I want to use Wasabi instead of Amazon, and noticed the feature existed but appeared undocumented.

 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.Daniel Bodnar seems not to be a GitHub user. You need a GitHub account to be able to sign the CLA. If you have already a GitHub account, please add the email address used for this commit to your account.You have signed the CLA already but the status is still pending? Let us recheck it.

Signed the CLA and submitted an issue (#92). Let me know if there's anything else ya need me to do.


feat: add react/no-unsafe lint rule

This pull request adds the react/no-unsafe lint rule, validating the nonexistence of legacy lifecycle methods deemed unsafe by the React team.
References #341

Thank you! I committed some suggestions that just change the URLs to a hyperlink tag.


Editor - Problem with multiple data grid fields on screen

I'm trying to add a new optional property at project level that will use a data grid to enter info. If the glossary is also added the fields start to play up during editing. It looks like there's some conflict with having more than one field of this type on screen at a time.
Issues include:

Add a new row to one of the properties & then it appears in both.
Move off the page and back again and the contents of the 1st field has been replaced with that of the 2nd one.
The submit button on the edit record dialog stops working. The data doesn't save and the dialog doesn't close.

These don't happen all the time but quite often and it never happens when there's only one data grid on the screen during editing.

This causes issues when including both glossary & variables together in a project.


Remove "Powered by Google" violates GDSC guidelines!!

https://github.com/dscbkbiet/dscbkbiet.github.io/blob/3ae7445ffce89ff3301aa905b053ef48d5e2e964/src/components/Home.js#L32
Remove Powered by Google violates GDSC guidelines!!

Done


proposal: Automated, per-endpoint mTLS

Related issue: #977

TBH I was thinking about implementing something like this via https://github.com/thanos-io/thanos/pull/2226 i.e. attach this kind of configuration to the store configuration however this works too, probably a bit more flexible when you can detach one from another


Utility for tracking total time spent on JIT compilations

It'd be great if there was some convenient jax util that could keep track of the total time spent on jit compilations/recompilations.
I can kind of approximate by timing the first runs for each jitted function for each set of input shapes but that seems unclean and possibly inaccurate.

I think you will measure it using the tensorflow profiler
https://www.tensorflow.org/tensorboard/tensorboard_profiling_keras
It will show up as PjRtStreamExecutorClient::Compile traceme due to
https://cs.opensource.google/tensorflow/tensorflow/+/master:tensorflow/compiler/xla/pjrt/pjrt_stream_executor_client.cc;l=2105?q=PjRtStreamExecutorClient::Compile tensorflow

Thanks for the information and pointers. I figured I could use a profiler to measure it but I thought it would be nicer to just have an easy utility as part of jax (especially for users that lack experience running/understanding the output of a profiler).
Side note: Having something like a decorator that users can use to mark functions they want to specifically target and measure seemed useful as well.
I'll close this issue for now and if others desire this more, they can re open it.


Are you killing the project?

The roadmap is short and you haven’t release anything in over 2 months? Are you terminating the project?  You have not fixed Managed exceptions and that have been a issue since day one? We was changing from RayGun to AppCenter but if you are not dedicated and stop development we will change back again.

Dokumentoplysninger
⚠ Undlad at redigere denne sektion. Det er påkrævet til docs.microsoft.com ➟ GitHub-problemlinkning.

ID: 62690a4a-94f3-21cb-a674-d297e557ca62
Version Independent ID: 3adaeac7-e034-5b5b-19c5-1c0151a7264c
Content
Content Source
Service: vs-appcenter

@mbertelsen we're regularly releasing features for this product, we released new features and a new version of the SDK just last week.  This project is under active development.
I apologize for the short roadmap, but we're in the process of tightening up some infrastructure capabilities right now and getting ready for GDPR is a focus as well.


glib ulong inconsistent on windows

Describe the bug
It is known that on win64 platform, unsigned long is 4 bytes; on linux64 platform, it is 8 bytes. Some functions like g_bit_nth_lsf_impl accepts gulong as a parameter, whose type is not redefined like guinit64 on windows. It could lead to problems if a ginit64 variable is passed to such function.
Environment

OS:  Windows and Linux
Compiler: MSVC and gcc

To Reproduce
Sample program:
#include <glib.h>
#include <glib/gprintf.h>

int main() {
    guint64 elem =<PHONE_NUMBER>;
    gint offset = g_bit_nth_lsf(elem, -1);
    g_printf("%d\n", offset);
}

We compile and run the above code on Linux and Windows respectively.
The build pipeline for linux is available at here.
The program on linux outputs an integer 32.
We compile and run the same problem on windows, available at here using vcpkg unofficial glib library. The program source code is the same. But the output is -1 on windows, which is different.
This kind of difference could lead to program crash when porting existing codes from linux to windows.
Additional context
None

vcpkg uses the glib library from gnome and adds an unofficial cmake wrapper to make it easier to integrate into build systems.  While unfortunate, this looks like an issue with glib and not vcpkg itself.  For this reason I am closing the issue.  If there is something you think vcpkg could do to help this then feel free to reopen the issue and let us know.


New sample script: Clean your development tenant Group and Sites

Docs

Author
Patrick Lamber

Original Post
No post yet

Description
Shows how to delete all Microsoft 365 Groups and SPO sites from your development tenant. Use it when you want to have a fresh start.

Keywords
Development Maintenance

Hi @waldekmastykarz and @garrytrinder,
the script is ready to be pushed soon. I just would like to use the JMESPath for filtering. The script
is here.
Could somebody of you tell me how to achieve this filter with JMESPath?
$allSites = m365 spo site classic list -o json | ConvertFrom-Json
$allSites = $allSites | where { $_.Template.IndexOf("STS#") -gt -1 -or $_.Template.IndexOf("SITEPAGEPUBLISHING#") -gt -1 }

The syntax I am used to use in the Azure CLI throws me an exception. I thought of using this filter:
-f "[?contains(template,'STS#') or contains(template,'SITEPAGEPUBLISHING#')]"

Thank you

Your JMESPath query seems to be working just fine if I test it at https://jmespath.org/. Are you saying you're testing it with Azure CLI or did you mean CLI for Microsoft 365?

It fails when used in our CLI with that criteria

I can repro it. Let me have a look

You were almost there. You need to replace or with ||. That works in the CLI.

I knew it. Its me ;)

JMESPath queries are right up there with regex and time zones 😄

@waldekmastykarz:
Maybe its not just me.
Tried this one on Windows:
m365 spo site classic list -o json -f "[?contains(Template,'STS#')]"

What I am doing wrong?
br,
Patrick

Finally got it.
m365 spo site classic list -o json --query "[?contains(Template,'SITEPAGEPUBLISHING') || contains(Template,'STS')]"
Thank you for your help

Was it the # that was breaking in PowerShell?

Me using the -f parameter instead of --query 🤫


how to properly use napari-s3zarr ?

Hi @tlambert03 , Hi @GenevieveBuckley ,
I just tried to use your napari-s3zarr package and I'm not sure how I should use it.
At EPFL we have our own S3 storage, where I dropped a zarr.
I have the the read-only bucket "hash", the access key and secret key but I'm not sure what I should do with them !
From the s3 I get the zarr link is https://s3.epfl.ch/12092-127a2c5216de10513f28977152b492d9/Test_zarr/ome-tiff.companion.ome_lvl_0.ome.zarr/
I saw in s3zarr.py that the path should start withs3: so I tried with :
napari s3:12092-127a2c5216de10513f28977152b492d9/Test_zarr/ome-tiff.companion.ome_lvl_0.ome.zarr/
also tried
napari s3:s3.epfl.ch/12092-127a2c5216de10513f28977152b492d9/Test_zarr/ome-tiff.companion.ome_lvl_0.ome.zarr/
napari opens, popup to select , napari builtins, napari-ome-zarr or s3zarr which I selected and then get the  error :
(ome_ngff) C:\Users\guiet>napari s3:s3.epfl.ch/12092-127a2c5216de10513f28977152b492d9/Test_zarr/ome-tiff.companion.ome_lvl_0.ome.zarr/
Traceback (most recent call last):
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\_qt\qt_viewer.py", line 830, in _qt_open
    self.viewer.open(
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\components\viewer_model.py", line 1024, in open
    layers = self._open_or_raise_error(
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\components\viewer_model.py", line 1146, in _open_or_raise_error
    raise MultipleReaderError(
napari.errors.reader_errors.MultipleReaderError: Multiple plugins found capable of reading s3:s3.epfl.ch/12092-127a2c5216de10513f28977152b492d9/Test_zarr/ome-tiff.companion.ome_lvl_0.ome.zarr/. Select plugin from {'s3zarr': 's3zarr', 'napari': 'napari builtins', 'napari-ome-zarr': 'napari-ome-zarr'} and pass to reading function e.g. `viewer.open(..., plugin=...)`.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\runpy.py", line 197, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\runpy.py", line 87, in _run_code
    exec(code, run_globals)
  File "C:\Users\guiet\.conda\envs\ome_ngff\Scripts\napari.exe\__main__.py", line 7, in <module>
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\__main__.py", line 561, in main
    _run()
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\__main__.py", line 341, in _run
    viewer._window._qt_viewer._qt_open(
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\_qt\qt_viewer.py", line 848, in _qt_open
    handle_gui_reading(filenames, self, stack, **kwargs)
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\_qt\dialogs\qt_reader_dialog.py", line 199, in handle_gui_reading
    open_with_dialog_choices(
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\_qt\dialogs\qt_reader_dialog.py", line 292, in open_with_dialog_choices
    qt_viewer.viewer.open(paths, stack=stack, plugin=plugin_name, **kwargs)
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\components\viewer_model.py", line 1014, in open
    self._add_layers_with_plugins(
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\components\viewer_model.py", line 1216, in _add_layers_with_plugins
    layer_data, hookimpl = read_data_with_plugins(
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\plugins\io.py", line 114, in read_data_with_plugins
    raise ValueError(
ValueError: Plugin 's3zarr' does not support file(s) ['C:\\Users\\guiet\\s3:s3.epfl.ch\\12092-127a2c5216de10513f28977152b492d9\\Test_zarr\\ome-tiff.companion.ome_lvl_0.ome.zarr']

But as I'm discovering both zarr and s3 , I'm not really sure what i should try next...
Thank you in advance for your answer,
Best,
Romain

Hey @romainGuiet, thanks for your note.

I saw in s3zarr.py that the path should start withs3: so I tried with :
napari s3:12092-127a2c5216de10513f28977152b492d9/Test_zarr/ome-tiff.companion.ome_lvl_0.ome.zarr/

You were on the right track there by looking at that file, but note also that it asserts that path.endswith(".zarr") ... and your path does not... it ends with .zarr/.  So you should try removing that.  (if that works for you, you could make a pr that converts this to path.rstrip("/").endswith(".zarr"):)

Hi @tlambert03 ,
thank you for your swift answer.

You were on the right track there by looking at that file, but note also that it asserts that path.endswith(".zarr")

I think it's a different issue, because if I run without or with the /
napari s3:12092-127a2c5216de10513f28977152b492d9/Test_zarr/ome-tiff.companion.ome_lvl_0.ome.zarr
or
napari s3:12092-127a2c5216de10513f28977152b492d9/Test_zarr/ome-tiff.companion.ome_lvl_0.ome.zarr/
in both case I have the pop up window which proposes s3zaar

so my guess is that it passes the endswith() test because if I run while adding /0/:
napari s3:12092-127a2c5216de10513f28977152b492d9/Test_zarr/ome-tiff.companion.ome_lvl_0.ome.zarr/0/
(cf will reply on forum.iamge.sc ) the popup doesn't contain s3zarr and the error is different and becomes :
(ome_ngff) C:\Users\guiet>napari s3:12092-127a2c5216de10513f28977152b492d9/Test_zarr/ome-tiff.companion.ome_lvl_0.ome.zarr/0/
Traceback (most recent call last):
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\components\viewer_model.py", line 1126, in _open_or_raise_error
    added = self._add_layers_with_plugins(
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\components\viewer_model.py", line 1216, in _add_layers_with_plugins
    layer_data, hookimpl = read_data_with_plugins(
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\plugins\io.py", line 104, in read_data_with_plugins
    raise ValueError(
ValueError: There is no registered plugin named 'napari-ome-zarr'.
Names of plugins offering readers are: {'s3zarr'}

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\_qt\qt_viewer.py", line 830, in _qt_open
    self.viewer.open(
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\components\viewer_model.py", line 1024, in open
    layers = self._open_or_raise_error(
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\components\viewer_model.py", line 1135, in _open_or_raise_error
    raise ReaderPluginError(
napari.errors.reader_errors.ReaderPluginError: Tried opening with napari-ome-zarr, but failed.

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\runpy.py", line 197, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\runpy.py", line 87, in _run_code
    exec(code, run_globals)
  File "C:\Users\guiet\.conda\envs\ome_ngff\Scripts\napari.exe\__main__.py", line 7, in <module>
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\__main__.py", line 561, in main
    _run()
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\__main__.py", line 341, in _run
    viewer._window._qt_viewer._qt_open(
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\_qt\qt_viewer.py", line 838, in _qt_open
    handle_gui_reading(
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\_qt\dialogs\qt_reader_dialog.py", line 188, in handle_gui_reading
    readers = prepare_remaining_readers(paths, plugin_name, error)
  File "C:\Users\guiet\.conda\envs\ome_ngff\lib\site-packages\napari\_qt\dialogs\qt_reader_dialog.py", line 243, in prepare_remaining_readers
    raise ReaderPluginError(
napari.errors.reader_errors.ReaderPluginError: Tried to read s3:12092-127a2c5216de10513f28977152b492d9/Test_zarr/ome-tiff.companion.ome_lvl_0.ome.zarr/0/ with plugin napari-ome-zarr, because it was associated with that file extension/because it is the only plugin capable of reading that path, but it gave an error. Try associating a different plugin or installing a different plugin for this kind of file.

Best
R

Would you have a s3 dataset link that I could test ? So I could check if the issue is not due to my dataset or s3 settings ?
Best,
Romain

Ok, in that case, I'd recommend just trying to use dask.array.from_zarr directly to see what the error is (sorry the exception messages are useless)
Note that this plugin is essentially just a one liner that calls https://docs.dask.org/en/stable/generated/dask.array.from_zarr.html
return [(da.from_zarr(path, storage_options={"anon": True}),)]


fix: skeleton: use lighter colors in skeleton

SUMMARY:
fix: skeleton: use lighter colors in skeleton
GITHUB ISSUE (Open Source Contributors)
JIRA TASK (Eightfold Employees Only):
CHANGE TYPE:

[ ] Bugfix Pull Request
[ ] Feature Pull Request

TEST COVERAGE:

[ ] Tests for this change already exist
[ ] I have added unittests for this change

TEST PLAN:

Codecov Report

:exclamation: No coverage uploaded for pull request base (main@44dcb7a). Click here to learn what that means.
Patch has no changes to coverable lines.

Additional details and impacted files
@@           Coverage Diff           @@
##             main     #478   +/-   ##
=======================================
  Coverage        ?   84.99%
=======================================
  Files           ?      749
  Lines           ?    16048
  Branches        ?     5495
=======================================
  Hits            ?    13640
  Misses          ?     2347
  Partials        ?       61

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

:umbrella: View full report at Codecov.
:loudspeaker: Do you have feedback about the report comment? Let us know in this issue.


Virtual slides ignore initialSlide in the beginning

Check that this is really a bug

[X] I confirm

Reproduction link
https://github.com/nolimits4web/swiper/issues/2755
Bug description
https://github.com/nolimits4web/swiper/issues/2755
Hell, the problem is still relevant.
Expected Behavior
No response
Actual Behavior
No response
Swiper version
8.0.5
Platform/Target and Browser Versions
Chrome latest
Validations

[X] Follow our Code of Conduct
[X] Read the docs.
[X] Check that there isn't already an issue that request the same feature to avoid creating a duplicate.
[X] Make sure this is a Swiper issue and not a framework-specific issue

Would you like to open a PR for this bug?

[ ] I'm willing to open a PR

As you don't provide up to date live example and other details, I assume there is no such issue, as you can see it works here perfectly https://codesandbox.io/s/swiper-virtual-slides-forked-zsdwq


labwc-menu-generator: init at unstable-2023-10-31

Description of changes
Add labwc-menu-generator
Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
24.05 Release Notes (or backporting 23.05 and 23.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

Add a :+1: reaction to pull requests you find important.

This pull request has been mentioned on NixOS Discourse. There might be relevant details there:
https://discourse.nixos.org/t/prs-ready-for-review/3032/3223

The project has a t directory for Perl's prove tests. I've tested locally and they succeed by adding perl to nativeCheckInputs. Any reason not to have doCheck = true;?


Read version for docker image from text file

Description
The latest version of rl-baselines3-zoo is 2.3.0, but the tag on docker is still 2.2.0a1 - this updates build_docker.sh so it tags it correctly.
Motivation and Context

[x] I have raised an issue to propose this change (required for new features and bug fixes) - https://github.com/DLR-RM/rl-baselines3-zoo/issues/455

Types of changes

[X] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to change)
[ ] Documentation (update in the documentation)

Checklist:

[X] I've read the CONTRIBUTION guide (required)
[X] I have updated the changelog accordingly (required).
I didn't think the CHANGLOG needed to be updated for this - ie, if I put it in the 2.3.0 section, the note would be something like, "made docker tag 2.3.0", which seems unnecessary
[ ] My change requires a change to the documentation.
[ ] I have updated the tests accordingly (required for a bug fix or a new feature).
[ ] I have updated the documentation accordingly.
[X] I have reformatted the code using make format (required)
[X] I have checked the codestyle using make check-codestyle and make lint (required)
[X] I have ensured make pytest and make type both pass. (required)

Note: we are using a maximum length of 127 characters per line

The latest version of rl-baselines3-zoo is 2.3.0, but the tag on docker is still 2.2.0a1 - this updates build_docker.sh so it tags it correctly.

Actually this version is for the base image, which defined in https://github.com/DLR-RM/stable-baselines3/blob/master/scripts/build_docker.sh
The latest version for SB3 docker image is 2.2.0a1: https://hub.docker.com/r/stablebaselines/stable-baselines3/tags


Give a more helpful error message for certain decorators with too many arguments

Right now this only works for single-signature decorators that accept no arguments. We could improve this to cases where

there are too many arguments from the decorated entity for every signature and
the min arg count is 0 for every signature

We now give a more helpful error message when

a decorator receives too many arguments and
0 arguments could be given

This comes up for me all the time in Angular where I end up forgetting to invoke the decorator:
@Component({ /*... */ })
class FooComponent {
  @Input foo: string; // Oops, I meant @Input(), not @Input
}

This should be marked as breaking change. the recommendation is to add rest args in the signature.

@dotnet-bot test please

This should be marked as breaking change. the recommendation is to add rest args in the signature.

😕 Why? These decorators could never have succeeded as they would receive too many arguments.


Argument list too long invoking action via docker container

I'm running into an "argument list too long" error when trying to connect actions in a sequence, and the first action emits a very large JSON dictionary (this * 5)
Environment details:

Bluemix

Steps to reproduce the issue:

Create an OpenWhisk action github-user-aggregator that emits a JSON doc like this one -- however instead of 100 users, it has 500 users.
Create another OpenWhisk action (clobber-document) that runs in a docker container.  Here is the dockerfile and here is the code.  I'm creating the action via wsk action create clobber-document --docker myusername/clobber-document
Connect the two actions in a sequence so that the clobber-document action receives the JSON doc emitted by the github-user-aggregator action, and tries to write it to the db

Provide the actual results and outputs:
$ wsk activation logs 437465b647cf4d75995dd1367e307bc6
2017-07-08T23:26:15.031740914Z stdout: [Errno 7] Argument list too long
2017-07-08T23:26:15.032487263Z stdout: XXX_THE_END_OF_A_WHISK_ACTIVATION_XXX
2017-07-08T23:26:15.032503216Z stderr: XXX_THE_END_OF_A_WHISK_ACTIVATION_XXX

Provide the expected results and outputs:
Expected it to write/update the db
Additional information you deem important:

Happens every time
Is bash involved in passing the arguments around somewhere?  Where is the code where the python shim invokes the /action/exec executable in the docker container?  Is it just a matter of using shell=false in the python subprocess command?  (assuming that's being used)
I think switching to the Custom Go Handler described in James Thomas' blog post might workaround the problem, since it would avoid shelling out.

Hey @tleyden,
This looks like an internal kernel limit (MAX_ARG_STRLEN) on the maximum length of an argument.
https://stackoverflow.com/questions/29801975/why-is-the-subprocess-popen-argument-length-limit-smaller-than-what-the-os-repor
That file you referenced as the argument list is ~100KB, which means you're trying to pass 500KB.
I can think of a few ways around this.....

Use an object store to write the data to. Pass the key as the output of the action, rather than the raw data. This is a common pattern to pass large amounts of data between actions once you get above a certain size.

Use the Apache Kafka integration as a message queue for invoking actions from these messages. Push the individual items onto the queue and then connect the receiving functions as a trigger feed source. They will be invoked on demand.

Use a fan-out and wait approach rather than a sequence. Have the action which produces this JSON manually split up and invoke the actions using the client SDK. The parent action will fire off the worker requests and then return once they have all returned. The disadvantage of this style is that you'll pay twice for the execution time, as the parent action will have to block waiting on the responses.

Thanks @jthomas -- I'll close the ticket since it looks like an inherent limitation rather than an actual issue.
Wouldn't implementing the REST handler to receive the OpenWhisk invocation directly in Go also fix the issue?  Any other known issues with that approach?
I'm referring to the approach you mentioned in your blog post:

Using the Docker SDK for OpenWhisk relies on a Node.js application to handle the platform HTTP requests, spawning a process to execute the user binary file.
Implementing the HTTP API, described above, in Go would allow us to remove the Node.js handler from the image. Compiling the Go Action source with the HTTP API handler into a single binary and using an Alpine Linux base image will dramatically reduce the image size.

That's correct, you could just do that.


improvement(highlights): send notification to action item assignee

When assigning action item in Highlights Widget,
assignee will get Argus Notification with
link to the view and action details.
closes: https://github.com/scylladb/argus/issues/500

example notification:


Correct imports

Hi!
I added some requirements that were needed to me run the project.
I also add the specific version of each one.
Added ignore swp and swo vim files to .gitignore.
After the requirements.txt update, I was able to run the project.

Awesome, thanks for contributing!


componentDidUpdate is not triggered when one of the props is changed

Just noticed this bug for one of our components. The props are as follows:
export type GenericMechanicsProps<T> = {
  // ...5 props here...
  exerciseId: string;
  // 20 props here
};

The render() function is as follows:
render() {
    console.log('RENDER', this.props.exerciseId);

    return (
      <Background isActive={...}>
        <FlexLayout
          main={this.props.renderMainLayout(...)}
          footer={this.renderFooterLayout()}
        />
        {this.renderOverlay()}
      </Background>
    );
  }

The componentDidUpdate is just a logger:
componentDidUpdate(oldProps: GenericMechanicsProps<T>) {
    console.log('DID UPDATE');
}

Background is just a styled-component div element
FlexLayout is again a simple thing
renderOverlay() renders an overlay UI element.
Here's the console.log:

RENDER dda22843-9c1c-42be-9ee8-5f3f8af358af
RENDER 6921462c-b5f8-4f23-a922-c790957d8d93
DID UPDATE
RENDER e4d15e83-f64f-4b52-babb-755ba445c554

I was expecting DID UPDATE to happen but it didn't. Is there anything I can help with debugging this issue?

Nope, my bad. It was not triggered because the component was unmounted and then mounted again.


[RUSH] Porting necessary rush changes from main

common/config - from main
eng/scripts - location update - resulting from pnpm-config.json

Followup of https://github.com/Azure/azure-sdk-for-js/pull/24782#issuecomment-1426420432

/check-enforcer evaluate

/check-enforcer evaluate

/azp run js - storage - ci

/check-enforcer override

failure is known and unrelated. linux and mac passing.


Update fails with no very clear error message

me@host:~$ /isodevice/Applications/AppImageUpdate-171-b380930-x86_64.AppImage /isodevice/Applications/Firefox-latest.glibc2.3.4-x86_64.AppImage
AppImageUpdate version 1-alpha (commit b380930), build 171 built on 2017-11-27 17:25:25 UTC
Checking for updates...
... done
Starting update...
Updating from Bintray via ZSync
open: Permission denied
zsync2: Failed to parse .zsync file!
zsync2: Reading and/or parsing .zsync file failed!
Update failed

I'm receiving the same error message when using the latest version of AppImageUpdate to update itself:
Fetching release information for tag "continuous" from GitHub API.
Updating from GitHub Releases via ZSync
zsync2: Failed to parse .zsync file!
zsync2: Reading and/or parsing .zsync file failed!


[BUG] - Tooltip shouldBlockScroll doesn't work

NextUI Version
2.4.2
Describe the bug
Tooltip's prop shouldBlockScroll doesn't work as intended, scroll is not blocked and I can still scroll content below tooltip
Your Example Website or App
https://codesandbox.io/p/devbox/great-haslett-83r6xg?workspaceId=3d68e848-d3a4-4835-979a-3a4880722b13
Steps to Reproduce the Bug or Issue
You can check this behaviour on sandbox, I've attached
Expected behavior
When i pass shouldBlockScroll={true} to Tooltip component, it should block scroll below. As it works in Dropdown component, for example
Screenshots or Videos
No response
Operating System Version
macOS
Browser
Chrome

Seems the entire logic is missing

@yevhenzar  I believe first you should  retry after correcting the spell,

@abhinandan-verma I tried already.

reopening - the PR involves breaking change. will reschedule in v2.5.0.


/arrangement fix, confirm booth-related services

tickets must be adapted to comply with the new panel requirements

final output should be as follows


How to build a parallel CNN using the same MLP in top with keras?

Somethings like this:
model = Sequential()
model.add(Convolution2D(nb_filters1, nb_conv, nb_conv, border_mode='valid', input_shape=(1, img_rows, img_cols)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(nb_pool, nb_pool)))
model.add(Convolution2D(nb_filters2, nb_conv, nb_conv))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(nb_pool, nb_pool)))
model.add(Dropout(0.25))
model2 = Sequential()
model2.add(Convolution2D(nb_filters1, nb_conv, nb_conv, border_mode='valid', input_shape=(1, img_rows, img_cols)))
model2.add(Activation('relu'))
model2.add(MaxPooling2D(pool_size=(nb_pool, nb_pool)))
model2.add(Convolution2D(nb_filters2, nb_conv, nb_conv))
model2.add(Activation('relu'))
model2.add(MaxPooling2D(pool_size=(nb_pool, nb_pool)))
model2.add(Dropout(0.25))
model/model2.add(Flatten())
model/model2.add(Dense(512))
model/model2.add(Activation('softmax'))
Anybody can help me?

Please make sure that the boxes below are checked before you submit your issue. Thank you!
[+] Check that you are up-to-date with the master branch of Keras. You can update with:
pip install git+git://github.com/fchollet/keras.git --upgrade --no-deps
[+] If running on Theano, check that you are up-to-date with the master branch of Theano. You can update with:
pip install git+git://github.com/Theano/Theano.git --upgrade --no-deps
[?] Provide a link to a GitHub Gist of a Python script that can reproduce your issue (or just copy the script here if it is short). --> My model is pretty simple and the question is about general possibility of pretraining Embedding layer :)


#51 helloworld

Why:
Closes #51
What's being changed:
Check off the following:

[x] I have reviewed my changes in staging (look for "Automatically generated comment" and click Modified to view your latest changes).
[x] For content changes, I have completed the self-review checklist.

Hey @zikpefu
Thanks for your contributions to this open source project 😃
This PR will be reviewed and merged shortly

Preview : https://codinasion--pr36-dev-igku8tg2.web.app/programme/hello-world/
(expires Tue, 29 Mar 2022 08:11:27 GMT)

LIVE : https://codinasion.web.app/programme/hello-world/


Appstudio update rhtap-demo-component-nqhx

Pipelines as Code configuration proposal
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creating pipelinerun rhtap-demo-component-nqhx-on-pull-request- in namespace rhtap-demo-dev-nums-tenant has failed.
Tekton Controller has reported this error: the namespace of the provided object does not match the namespace sent on the request

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Tekton Controller has reported this error: the namespace of the provided object does not match the namespace sent on the request


Add spdm_requester_size check before use

Fix: #2736

One thing I noticed is that the zeroing of the send / receive (scratch) buffers are handled inconsistently between messages. I'll file a separate issue for that.


Consider treating check-jsonschema as an "official" more featureful CLI

Huge Disclaimer: I'm the author/maintainer of check-jsonschema so obviously I think it's great and we should all use it. 😉
There are a number of issues which revolve around making the jsonschema CLI more featureful.
I think it's nice to have a built-in CLI, but that it's also nice to keep the complexity of this project low and have a clear separation of concerns.
check-jsonschema currently takes care of the following features which I do not believe should be features of jsonschema:

providing a pre-commit hook (see also #857 and related)
supporting YAML as a format (solves #582)
downloading and caching schemas specified as HTTP(S) URLs
vendoring a set of known schemas as part of the package, to support offline usage (e.g. in pre-commit.ci)
some controls over format validation

Because the version number of check-jsonschema moves independently from jsonschema, it's not necessary to do a jsonschema release in order to update the pre-commit hook config or add CLI-only features. And it's not necessary to think about a major version bump in order to  change the CLI in a breaking way.
Many CLI features, like #889, could be handled by check-jsonschema, allowing this project to ignore them.
The most significant downside I know of is that check-jsonschema has very rudimentary output formatting. It's nowhere near as nice as the jsonschema CLI (yet!).
Here are some ideas I've had about what we can do if this is interesting:

listing check-jsonschema in the "Community" section of the readme
adding a link somewhere in the docs
creating a github org (py-jsonschema?) and putting both projects under it

I'm also willing to make changes in check-jsonschema if there is some milestone the project must meet (other than popularity) in order to be considered.

Hi. Thanks for the ticket. I'll leave longer comments, but a quick one is that the CLI is functionality I didn't want to add in the first place :), I wanted someone doing it as an additional package, so I'm definitely open to the idea.
What needs to change or how probably are longer and require some investigating, but yeah thanks definitely worth discussing.

I don't want to pollute the issue tracker here, but I've been working on trying to make sure check-jsonschema covers all of the use-cases which have been raised about the CLI on this project.
@Julian, with your permission, I'd like to add replies to the following issues suggesting that they use check-jsonschema to see if it satisfies their needs:

#913
"format" validation is enabled by default in check-jsonschema
#889
I've added a --check-metaschema flag, and accepted the complexity it adds.
#669
The local file loading behavior in check-jsonschema uses a RefResolver where the ref-base is the filename. I think that will satisfy this user.
#582
As I'm trying to build a tool for validating yaml files like .readthedocs.yml, this is one of my primary features.

I believe that all of these (and probably some closed issues too) could be considered "solved" by this.

I'm trying to balance how much self-promotion is appropriate here, vs how useful it would be to tell people about the tool. Please let me know if it seems like I'm crossing the line! It's hard to figure out. 😅

Thanks! So far how you've gone about this is perfect, so don't worry :)
I'm thinking perhaps we take things the org route -- I'll create a python-jsonschema org, and add you to it. We can then discuss any changes, but at least it gets things underway. -- Which apologies I still haven't really taken a close look, so the only thing I'm not 100% thrilled yet about is the precise name, but it seems jsonschema-cli is unfortunately taken :/
But yeah let me create the org.
Until then, definitely feel free to promote on those issues!

I'll create a python-jsonschema org, and add you to it. We can then discuss any changes

Woohoo! We'll figure out more later, I'm sure.

Which apologies I still haven't really taken a close look

No need to apologize! I'm not expecting your review -- though obviously I'd appreciate it.
check-jsonschema is staying in 0.x versions until I'm confident that the code isn't going to need (another) major rewrite. So there's plenty of time for you to look in the future if you want.

the only thing I'm not 100% thrilled yet about is the precise name, but it seems jsonschema-cli is unfortunately taken :/

We could try to reclaim that name, but I must admit that I don't really like "jsonschema-cli".
I like some verb in there like check or validate OR something which isn't hyphenated at all like rustc or jq (I just can't come up with a good one for this).
We can revisit later: I'm not super strongly attached to the current name -- we can look at doing a name-change in the future if it seems worth it.
The only thing I think is important is to have the package name and command name match because it's easier for people to learn and use.

v0.15.0 of check-jsonschema added a lot of what I felt was missing, so I'm now thinking about what it takes to consider this issue closed.
I think the next stage is to start closing any outstanding issues for the CLI component and pointing them at check-jsonschema.
We can close this issue or keep it open -- either is fine by me.


XLA leads to core dump

System information
output of tf_env_collect.sh
Tensorflow
Tensorflow compiled from the source v1.3.0(9e76bf3)
with cuda, with xla, without mpi, without mkl
OS
CentOS 7
out put of uname -a:
Linux zhanghao 3.10.0-514.26.2.el7.x86_64 #1 SMP Tue Jul 4 15:04:05 UTC 2017 x86_64 x86_64 x86_64 GNU/Linux
python
Python 2.7.13 |Intel Corporation| (default, Apr 27 2017, 15:33:46)
[GCC 4.8.2 20140120 (Red Hat 4.8.2-15)] on linux2
Bezel
Build label: 0.5.2
Build target: bazel-out/local-fastbuild/bin/src/main/java/com/google/devtools/build/lib/bazel/BazelServer_deploy.jar
Build time: Tue Jun 27 13:27:03 2017<PHONE_NUMBER>)
Build timestamp:<PHONE_NUMBER>
Build timestamp as int:<PHONE_NUMBER>
GPU
CUDA 8.0 cuDNN 6.0.21
GPU: GeForce GTX 950M
Describe the problem
core dump when use xla with gpu,
BTW, if use cpu only, xla won't lead to core dump
Source code
This is code to reproduce the bug
import tensorflow as tf
import sys
D = 2
A = tf.random_normal(shape=[D, D, 2], dtype=tf.float32,name="A")
B = tf.random_normal(shape=[D, D, 2], dtype=tf.float32, name="B")
E = tf.ones(shape=[D], dtype=tf.float32, name="EBA")
H = tf.reshape(tf.constant([[0.25,0,0,0],[0,-0.25,0.5,0],[0,0.5,-0.25,0],[0,0,0,0.25]],
                           dtype=tf.float32),[2,2,2,2],name="Hamiltonian")
EA = tf.multiply(A,tf.reshape(E,[D,1,1]))
AB = tf.tensordot(EA,B,[[1],[0]],name="AB")
S, U, V = tf.svd(tf.reshape(AB,[2*D,2*D]))
UU = tf.transpose(tf.multiply(tf.reshape(U[:,:D],[D,2,D]),tf.reshape(E,[D,1,1])),[0,2,1],name="nA")
data = UU / tf.reduce_max(UU)
config = tf.ConfigProto()
if len(sys.argv)>1:
    config.graph_options.optimizer_options.global_jit_level = tf.OptimizerOptions.ON_1
sess = tf.Session(config=config)
sess.run(tf.global_variables_initializer())
print sess.run(data)

save as MPS.py and run python MPS.py and get:
2017-08-29 20:51:54.856662: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:893] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2017-08-29 20:51:54.857232: I tensorflow/core/common_runtime/gpu/gpu_device.cc:955] Found device 0 with properties:
name: GeForce GTX 950M
major: 5 minor: 0 memoryClockRate (GHz) 1.124
pciBusID 0000:0a:00.0
Total memory: 3.95GiB
Free memory: 3.92GiB
2017-08-29 20:51:54.857292: I tensorflow/core/common_runtime/gpu/gpu_device.cc:976] DMA: 0
2017-08-29 20:51:54.857301: I tensorflow/core/common_runtime/gpu/gpu_device.cc:986] 0:   Y
2017-08-29 20:51:54.857312: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1045] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 950M, pci bus id: 0000:0a:00.0)
[[[ 0.64684284 -0.48666194]
  [-0.56722689 -0.19181968]]

 [[ 0.34154066  0.77098727]
  [ 1.         -0.0881796 ]]]

and then run python MPS.py -, and get:
2017-08-29 20:52:18.127327: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:893] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2017-08-29 20:52:18.127719: I tensorflow/core/common_runtime/gpu/gpu_device.cc:955] Found device 0 with properties:
name: GeForce GTX 950M
major: 5 minor: 0 memoryClockRate (GHz) 1.124
pciBusID 0000:0a:00.0
Total memory: 3.95GiB
Free memory: 3.92GiB
2017-08-29 20:52:18.127780: I tensorflow/core/common_runtime/gpu/gpu_device.cc:976] DMA: 0
2017-08-29 20:52:18.127789: I tensorflow/core/common_runtime/gpu/gpu_device.cc:986] 0:   Y
2017-08-29 20:52:18.127799: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1045] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 950M, pci bus id: 0000:0a:00.0)
2017-08-29 20:52:18.319392: I tensorflow/compiler/xla/service/platform_util.cc:58] platform CUDA present with 1 visible devices
2017-08-29 20:52:18.319435: I tensorflow/compiler/xla/service/platform_util.cc:58] platform Executor present with 1 visible devices
2017-08-29 20:52:18.319739: I tensorflow/compiler/xla/service/platform_util.cc:58] platform Host present with 8 visible devices
2017-08-29 20:52:18.320615: I tensorflow/compiler/xla/service/service.cc:187] XLA service 0x7f59008c0350 executing computations on platform CUDA. Devices:
2017-08-29 20:52:18.320640: I tensorflow/compiler/xla/service/service.cc:195]   StreamExecutor device (0): GeForce GTX 950M, Compute Capability 5.0
2017-08-29 20:52:18.474432: F tensorflow/compiler/xla/util.cc:183] Check failed: p1.size() == p2.size() (3 vs. 0)
[1]    14077 abort (core dumped)  python MPS.py -

@learyg Could you take a look at this XLA assertion failure coredump?

For what it is worth, I think I'm observing the same problem with our models. The bug seems to be present in both tensorflow 1.2.1 and 1.3.0, no matter how they were compiled - I have tested with a couple of variants. CUDA 8, CuDNN 6 and 1080Ti.
If useful I can upload a frozen version of one of these models.

Same here

It has been 14 days with no activity and the awaiting tensorflower label was assigned. Please update the label and/or status accordingly.

Sorry for the seriously long delay, will try to repro. It's also helpful if you use TF_XLA_FLAGS="--xla_dump_computations_to=/tmp/" as a prefix on your cmdline and post the protobuf binary that appears as a result along with the git revision (the XLA compilation can be replayed directly with https://github.com/tensorflow/tensorflow/blob/e210cb140a60a74d5e9ce3bf9ebedb21b4910f1c/tensorflow/compiler/xla/tools/replay_computation.cc ).

well, lastest tensorflow doesn't have this problem for this code indeed. but the following code still reproduces the similar core dump.
import tensorflow as tf
import sys
D = 2
A = tf.random_normal(shape=[D, D, 2], dtype=tf.float32,name="A")
B = tf.random_normal(shape=[D, D, 2], dtype=tf.float32, name="B")
if len(sys.argv)%2:
    fun = tf.random_normal
else:
    fun = tf.ones
E = fun(shape=[D], dtype=tf.float32, name="EBA")
H = tf.reshape(tf.constant([[0.25,0,0,0],[0,-0.25,0.5,0],[0,0.5,-0.25,0],[0,0,0,0.25]],
                           dtype=tf.float32),[2,2,2,2],name="Hamiltonian")
EA = tf.multiply(A,tf.reshape(E,[D,1,1]))
AB = tf.tensordot(EA,B,[[1],[0]],name="AB")
S, U, V = tf.svd(tf.reshape(AB,[2*D,2*D]))
UU = tf.transpose(tf.multiply(tf.reshape(U[:,:D],[D,2,D]),tf.reshape(E,[D,1,1])),[0,2,1],name="nA")
data = UU / tf.reduce_max(UU)
config = tf.ConfigProto()
if len(sys.argv)>2:
    config.graph_options.optimizer_options.global_jit_level = tf.OptimizerOptions.ON_1
sess = tf.Session(config=config)
sess.run(tf.global_variables_initializer())
print sess.run(data)

the only difference is changing tf.ones to tf.random_normal.
all of python2 main.py, python2 main.py -, python2 main.py - - - run correctly
but python2 main.py - - still core dump
:)

Thanks for the bug report, @hzhangxyz.
Can you please file a separate bug and cc me and bixia@?  I don't expect this is the same issue as before, even though it looks very similar from your end.
It would be helpful if you could include the new log output in the new bug.  The first one wasn't a proper core dump but was instead an assertion failure; those log messages are useful to us.
Thanks again.


Changed test assert into a warning.

tests/test_tools.py::test_sorting was failing on my local machine. It is not clear to me that the test makes sense unless you are choosing between two different implementations for performance reasons. I suggest @mloubout takes a look at this lines of code (git blame) - my suggested fix is to convert this to a warning and changed to higher precision timer.

Why/when did this slow down.

Nothing changed other than the fact that if I run this on my desktop:
Linux kimogila 5.4.0-53-generic #59-Ubuntu SMP Wed Oct 21 09:38:44 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux
Python 3.8.5
gcc version 9.3.0 (Ubuntu 9.3.0-17ubuntu1~20.04)
I am not convinced this was a valid test in the first place - but I opted to set it to a warning rather than deleting this part of the test.

It's odd it fails on your maching, no_key should be like 10 times faster. Did nokey get slower or key get faster?

It's odd it fails on your maching, no_key should be like 10 times faster. Did nokey get slower or key get faster? THis is there because we were relying too much on key which was making src/rec processing crazy slow, this test was there to make sure the no-key sorting, that defaults to numpy since this change, was indeed faster and this was not useless extra sorting branches.

So it might be the underlying packages as I'm running a more recent linux distribution than is used in the tests (ubuntu 10.04, numpy 1.17.4).
I'm not sure it's worth investigating a lot of time diving into this - would need to run cprofile for the two cases on different systems. For this PR all that is to be decided is whether this really should be a failing test or warning. I'm advocating for the latter because I don't see this as a effective means of performance regression - and this change in performance is down to the env rather than having anything got to do with Devito.

I'm not sure it's worth investigating a lot of time diving into this

I disagree. The sorting speed was a major issue with MPI so if it got slower we need to know and fix it.

I'm not sure it's worth investigating a lot of time diving into this

I disagree. The sorting speed was a major issue with MPI so if it got slower we need to know and fix it.

What part of what I said are you disagreeing with?
Why do you think one method got slower? How do you know it's not that the other implementation has gotten faster?
Looking at more detail, this is what you are testing:
t2 - t1 < 0.5 * (t1 - t0)
where t1-t0 is the wall time for sort_key = filter_ordered(array, key=key) and where t2 - t1 is the wall time for sort_nokey = filter_ordered(array). So you are expecting the nokey variant be to at least twice as fast as the key variant. Now looking at the actual timings i get on my machine:
0.5*(t1 - t0) =  0.001161813735961914
(t2 - t1)     =  0.0014281272888183594
So this test is failing because of a difference 0.00026 seconds. ... this is not the kind of thing you can measure to any reliability. I tested this manually in a loop - some times it fails and other times it passes.

If we rewrite the test to run a multiple experiments then we can mostly eliminate the jitter. But it remains a fragile test that needs rethinking.
def test_sorting():
key = lambda x: x
array = np.random.rand(10000)
start = time.perf_counter()
for i in range(100):
    sort_key = filter_ordered(array, key=key)
t0 = time.perf_counter() - start

start = time.perf_counter()
for i in range(100):
    sort_nokey = filter_ordered(array)
t1 = time.perf_counter() - start

assert t1 < 0.5 * t0
assert sort_key == sort_nokey

Why do you think one method got slower? How do you know it's not that the other implementation has gotten faster?

That's my point, we need to know which one it is. If sort_key = filter_ordered(array, key=key) got faster then it's perfectly fine, if sort_nokey = filter_ordered(array) got slower enough to make this fail then we have a problem. I'm not saying this doesn't need update/fix, I'm just saying we need to know which of the two cases it is.

Damn rabbit holes...
So - the test as it stands is crap and needs fixing... period.
However, I took a look at the performance issue were trying to solve. It boils down to the fact that numpy.unique give you sorted values whether you asked for them or not and in this particular case you needed to keep the ordering. The popular solution to this is to simply use pandas.unique instead which does not sort and has the added benefit of being much faster due to it's lower computational complexity.
This does mean we incur pandas as a core dependency (previously it was in requirements-optional.txt. However, I believe that this is justified in that pandas is pretty much everywhere these days and there are numerous opportunities where we could pandas methods rather than numpy when they are superior.

I'm happy with pandas, thought about adding it too wasn't sure if was worth it.
Another nitpicky comment sorry.

Your nitpicking ultimately led us to find the source of the original problem and propose a potential better fix. So don't say sorry when you are right!
If this PR is merged then we should look to see where else in Devito there might be performance/feature opportunities. I seem to remember that I also considered it for resampling data.

@ggorman as we agreed yesterday, we should split the performance side of this test and move it to an ASV test

@FabioLuporini I stepped back from that direction as I later realised that the test was more fundamentally flawed. I rewrote the test and rebased on master.
Details:
Updated test to use an array of random integers with a fixed seed rather
than random floats with random seed to that the test:
* is deterministic between runs
* duplicate keys are in fact created so unique actually does something.
Additionally, the tic/toc timings are now over multiple calls to the
function so that the variance is reduced.

I think, however, it was still a good idea to move the timing part to ASV

Are you saying that should be part of this PR?

yeah why not it's a small PR after all


Use new unit test fixture for nodepool control tests

Removes most of the StatefulSet Update code. Instead we (for now) only create missing pilots and update when the replica count needs to be increased.
Later the statefulset creation will be done by the CreateNodePool  actions.
Also makes the nodepool control gracefully handle the situation where the statefulset lister doesn't yet have latest statefulsets.

Release note:
NONE

/retest


A beginners' tutorial in pure Ruby?

A lot of students new to Ruby (and not knowing Rails) are looking out for some tutorial on how to use dalli with maybe the activerecord gem but the code being in pure Ruby. Anyone game for writing this for them?
Much appreciated.

This really doesn't make sense to me.  The documentation on how to use Dalli::Client is reasonably clear, and a good Ruby programmer should be able to understand Dalli based on existing documentation.  I don't see what such a tutorial would add.  If needed, someone should write it as a blog post.