Convert build plan buttons to links

Checklist

[ ] I tested all changes and all related features with different users (student, tutor, editor, instructor, admin) on the test server https://artemistest.ase.in.tum.de.
[X] Client: I followed the coding and design guidelines.
[ ] Client: I added multiple integration tests (Jest) related to the features (with a high test coverage)
[ ] Client: I documented the TypeScript code using JSDoc style.
[X] Client: I added multiple screenshots/screencasts of my UI changes(https://docs.artemis.ase.in.tum.de/dev/guidelines/language-guidelines/).

Motivation and Context
Links to repositories of programming exercises are links and therefore one can open them directly in a new tab. The build plans, however, are still implemented as buttons that have the annoying property of only being left-clickable.
Description
I removed the directives which were used to generate the links. I added a utils method that creates the links and added for all components a generation on startup which allows me to load the build plan link directly in the href attribute.
Since it's an external link, I added a rel="noreferrer".
Steps for Testing
This testing is only about checking whether all links are actually links (also those that look like buttons).
This includes

Left-click transfers the user to a new tab
Right-click opens the context menu
Middle-click opens the page in the background
Hovering over the link shows the link in the bottom corner
The term "make sure xxx is a link" refers to this.

Exam

Create an exam (no setup needed) with one programming exercise
Make sure that the two build plans (Template, Solution) in the exercise list are links and lead to the correct build plan

Student

Create one programming exercise with the build plan hidden and one with the build plan published
Participate as a student and make sure that the button link to the build plan is hidden for the first exercise
Participate as a student and make sure that the button to the build plan acts as a link and leads to the correct build plan

Course

Select one of the two previously created exercises for you to test
Make sure that the two build plans (Template, Solution) in the exercise list are links and lead to the correct build plan
Enter the exercise details and make sure that the two build plans (Template, Solution) are links and lead to the correct build plan
Navigate to the participations list and make sure that the build plan is a link and leads to the correct student build plan
Get back and navigate to the scores list. Make sure that the build plan button acts as a link and leads to the correct student build plan

Test Coverage
programming-exercise-group-cell.component.ts: 54.55%
programming-exercise-detail.component.ts: 44.14%
programming-exercise.component.ts: 72.53%
programming-exercise.utils.ts: 47.5%
exercise-scores.component.ts: 80.17%
participation.component.ts: 78.03%
course-exercise-details.component.ts: 75.86%
Screenshots
Publish Build Plan Setting on Exercise Creation

Exam Exercise List

Course Exercise List

Exercise Detail View (Course and Exam are the same)

Exercise Participation List (Course and Exam are the same)

Exercise Scores List (Course and Exam are the same)

Student Exercise view with released Build Plan

Client tests fail due to too little test coverage however I only removed tests related to stuff I removed itself.
I'm not quite sure where I could add good tests here regarding my changes. Does someone have a suggestion?

@MaisiKoleni @Olimbia23 Please check the refactoring changes.
Please also verify that the logic didn't change because I don't think the changes require manual testing again.


Replace code owners for shared modules

The GE Test Distribution team is now owning the modules that use the shared code.

@bot-gradle test and merge

Your PR is queued. See the queue page for details.

OK, I've already triggered a build for you.


[FEAT] ...terraform-azurerm-api-management module does not support StandardV2 SKU

Community Note

Please vote on this issue by adding a :thumbsup: reaction to the original issue to help the community and maintainers prioritize this request
Please do not leave "+1" or "me too" comments, they generate extra noise for issue followers and do not help prioritize the request
If you are interested in working on this issue or have submitted a pull request, please leave a comment

Description
Hi,
The module currently does not support deploying an API Management instance with the StandardV2 SKU.
It's giving me following error when set the SKU to StandardV2 in the module's parameters.
│ Error: invalid value for sku_name (This is not a valid Api Management sku name.)
│
│   with module.apim.azurerm_api_management.apim,
│   on ../../modules/terraform-module-azure-api-mgt/r-api-management.tf line 8, in resource "azurerm_api_management" "apim":
│    8:   sku_name        = var.sku_name
Please add support for the StandardV2 SKU in the terraform-azurerm-api-management module.
New or Affected Resource(s)/Data Source(s)
azurerm_api_management
Potential Terraform Configuration
No response
References
No response

Hello, thanks for this issue,
we will look into it.

Can you try to pass: StandardV2_1 in the SKU variable?
However, I found this issue: https://github.com/hashicorp/terraform-provider-azurerm/issues/25445
I think we need to wait the provider to fix this properly.


Installation Problem

I installed the hpyerlearn successfully usingpython setup.py install. It shows:
#### Welcome to Umbra's HyperLearn! ####
#### During installation, code will be compiled down to C / LLVM via Numba. ####
#### This could mean you have to wait...... ####

#### You MUST have a C compiler AND MKL/LAPACK enabled Scipy. ####
#### If you have Anaconda, then you are set to go! ####
running install
running bdist_egg
running egg_info
writing manifest file 'hyperlearn.egg-info/SOURCES.txt'
running install_lib
running build_py
creating build/bdist.linux-x86_64/egg
creating build/bdist.linux-x86_64/egg/hyperlearn
byte-compiling build/bdist.linux-x86_64/egg/hyperlearn/__init__.py to __init__.cpython-37.pyc
creating build/bdist.linux-x86_64/egg/EGG-INFO
copying hyperlearn.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO
copying hyperlearn.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO
copying hyperlearn.egg-info/dependency_links.txt -> build/bdist.linux-x86_64/egg/EGG-INFO
copying hyperlearn.egg-info/not-zip-safe -> build/bdist.linux-x86_64/egg/EGG-INFO
copying hyperlearn.egg-info/requires.txt -> build/bdist.linux-x86_64/egg/EGG-INFO
copying hyperlearn.egg-info/top_level.txt -> build/bdist.linux-x86_64/egg/EGG-INFO
removing 'build/bdist.linux-x86_64/egg' (and everything under it)
creating /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages/hyperlearn-0.0.1-py3.7.egg
Extracting hyperlearn-0.0.1-py3.7.egg to /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
byte-compiling /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages/hyperlearn-0.0.1-py3.7.egg/hyperlearn/__init__.py to __init__.cpython-37.pyc
Adding hyperlearn 0.0.1 to easy-install.pth file

Installed /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages/hyperlearn-0.0.1-py3.7.egg
Processing dependencies for hyperlearn==0.0.1
Searching for Cython==0.29
Best match: Cython 0.29
Adding Cython 0.29 to easy-install.pth file
Installing cygdb script to /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/bin
Installing cython script to /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/bin
Installing cythonize script to /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/bin

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for psutil==5.7.0
Best match: psutil 5.7.0
Adding psutil 5.7.0 to easy-install.pth file

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for numba==0.55.2
Best match: numba 0.55.2
Adding numba 0.55.2 to easy-install.pth file

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for torch==1.6.0
Best match: torch 1.6.0
Adding torch 1.6.0 to easy-install.pth file
Installing convert-caffe2-to-onnx script to /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/bin
Installing convert-onnx-to-caffe2 script to /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/bin

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for pandas==1.3.5
Best match: pandas 1.3.5
Adding pandas 1.3.5 to easy-install.pth file

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for scipy==1.7.3
Best match: scipy 1.7.3
Adding scipy 1.7.3 to easy-install.pth file

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for scikit-learn==1.0.2
Best match: scikit-learn 1.0.2
Adding scikit-learn 1.0.2 to easy-install.pth file

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for torchvision==0.7.0+cu101
Best match: torchvision 0.7.0+cu101
Adding torchvision 0.7.0+cu101 to easy-install.pth file

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for numpy==1.21.6
Best match: numpy 1.21.6
Adding numpy 1.21.6 to easy-install.pth file
Installing f2py script to /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/bin
Installing f2py3 script to /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/bin
Installing f2py3.7 script to /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/bin

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for llvmlite==0.38.1
Best match: llvmlite 0.38.1
Adding llvmlite 0.38.1 to easy-install.pth file

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for setuptools==62.3.2
Best match: setuptools 62.3.2
Adding setuptools 62.3.2 to easy-install.pth file

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for future==0.18.2
Best match: future 0.18.2
Adding future 0.18.2 to easy-install.pth file
Installing futurize script to /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/bin
Installing pasteurize script to /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/bin

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for python-dateutil==2.8.2
Best match: python-dateutil 2.8.2
Adding python-dateutil 2.8.2 to easy-install.pth file

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for pytz==2022.1
Best match: pytz 2022.1
Adding pytz 2022.1 to easy-install.pth file

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for joblib==1.1.0
Best match: joblib 1.1.0
Adding joblib 1.1.0 to easy-install.pth file

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for threadpoolctl==3.1.0
Best match: threadpoolctl 3.1.0
Adding threadpoolctl 3.1.0 to easy-install.pth file

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for Pillow==7.2.0
Best match: Pillow 7.2.0
Adding Pillow 7.2.0 to easy-install.pth file

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Searching for six==1.16.0
Best match: six 1.16.0
Adding six 1.16.0 to easy-install.pth file

Using /home/lksgcc/.pyenv/versions/anaconda3-5.0.1/envs/sgcc36/lib/python3.7/site-packages
Finished processing dependencies for hyperlearn==0.0.1
#### HyperLearn has been installed! ####

#### If you want to compile Numba code, please run:
    >>>>   python numba_compile.py

However, when I import hyperleran, I found there is not any sub method can be found and there is only a hyperlearn-0.0.1-py3.7.egg file in the site-package file. Is there anything wrong during my installation?
Thanks for your reply.

Heyy! Ohhh oops! So we're still in the process of fixing things up - I think I might have accidentally not pushed a newer update.
So currently the package is un-usable as of now - you can join our Discord (link on frontpage) for more updates.
It's been real hectic, so I'll be sure to tell you when it's all polished!


Remove region dependency

Issue #, if available:
7
Description of changes:
Run list_accounts against current region instead of hard-coded us-east-1
By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

Tested successfully

merge completed


CI: Update azure pipelines config path

What does this PR do?
Updates it for consistency across all Lightning-AI repositories.
Before submitting

[x] Was this discussed/approved via a Github issue? (no need for typos and docs improvements)
[x] Did you read the contributor guideline, Pull Request section?
[x] Did you make sure your PR does only one thing, instead of bundling different changes together?
[x] Did you make sure to update the documentation with your changes?
[x] Did you write any new necessary tests? [not needed for typos/docs]
[x] Did you verify new and existing tests pass locally with your changes?
[x] If you made a notable change (that affects users), did you update the CHANGELOG?

PR review

[x] Is this pull request ready for review? (if not, please submit in draft mode)

Anyone in the community is free to review the PR once the tests have passed.
If we didn't discuss your PR in Github issues there's a high chance it will not be merged.
Did you have fun?
Make sure you had fun coding 🙃

@Borda Please update the config file path at the top right of the azure dashboard: https://dev.azure.com/Lightning-AI/lightning Bolts/_build?definitionId=31


schema.ParseString has errors when DataRefs are used

Given this test string
module todo {
	data AnotherType {}
	data CreateListRequest {
		another AnotherType
	}
	data CreateListResponse {}

	// Create a new list
	verb createList(todo.CreateListRequest) CreateListResponse
		calls createList
}

sch, err := schema.ParseString("", testSchema) will fail with the error 5:15: reference to unknown Verb "AnotherType" in the testParsing function

I think we determined this was not a bug?


add first class support for iframe

an appearing idea come to me when I came
across the philosophy of https://posit-dev.github.io/great-tables/articles/intro.html
so can ludic make first class support for iframe so we can embed dynamic table components for e2e fast datascience analysis

Hi @marquisthunder
This seems like a really interesting idea. Ludic already supports the iframe HTML element (from ludic.html import iframe).
Could you please further explain the idea how it could be used? :)
Thank you.


Cloud interface

Hi, I have 1 fronius inverter on my home assistant network and another that is remote. I was hoping to connect both to HA using the one integration. Are there any plans to add the solar web api to this python bridge repo? I could not find much already on github relating to the fronius solar web api other than this repo in Go that can use either interface https://github.com/tgulacsi/fronius.

There are no plans, but anyone is welcome to contribute something like this :)

I've had a go at an initial interface, but then realised it is not supported in my country so have no way  of testing it :(
https://github.com/drc38/python-fronius-web
If it works then it shouldn't be too difficult to incorporate.

Fronius have now enabled api access for me so when I am able to clone your repo I'll submit a PR to incorporate the cloud api

An initial HACS integration for cloud polling of the Fronius is available here https://github.com/drc38/Fronius_solarweb


Add flag to trust rev-proxy header for TLS.

When behind a reverse-proxy that is handling TLS, we need to generate the
correct references and links so that resources can be included and there are no
links back to the http site. To accomplish this, we add a flag to the tls config
that says to trust the X-Forwarded-Proto header and doesn't require a key or
cert.

I can adjust the error handling logic to make tls-rev-proxy mutually exclusive with the other flags if you would prefer.
If you want to see my blog in action it's up and running at https://kylebutt.page/ behind nginx

Thanks! uploaded as clckwrks 0.26.4.


sails debug is not compiling importer.less

Any changes made to the importer.less is not getting reflected when running sails in debug mode.
Works well when: sails lift
Doesn't work when: sails debug
Sails version: 0.11.4
node version: 4.2.2
OS: Mac 10.11.1

Thanks for the heads up, @skavinvarnan.  We'll take a look and attempt to reproduce ASAP.

Hi @skavinvarnan, there are known issues with sails debug and Grunt on Sails v0.11.  It's been patched in the upcoming release, so your options are to use the beta version of Sails (npm install -g sails@beta) or patch your 0.11 version by replacing your Sails' /lib/hooks/grunt/index.js file with the contents of https://raw.githubusercontent.com/balderdashy/sails/88ffc0ed9949f8c74ea390efb5610b0e378fa02c/lib/hooks/grunt/index.js.


Optimized interpreter

There are some inefficiencies in this interpreter, and I was able to optimize it using some features described in the 9899:201x standard.
This may break backwards comparability with legacy compilers, but I think the performance and readability enhancements are worth it.

Thank you for your interest in the HW project!
Unfortunately, legacy support is very important to the HW project, and your pull request will not be accepted at this time.


the discord link is not working

i tried to click on the discord link but it's not working

Discord is still under work


Support model (the classifier) as positional argument in BalancedModel(...)

For consistency with TunedModel, EnsembleModel, IteratedModel, etc.
julia> BalancedModel(ConstantClassifier())
ERROR: MethodError: no method matching BalancedModel(::ConstantClassifier)

One could simply add BalancedModel(model; kwargs...) = BalancedModel(; model, kwargs...) but for a slightly more robust implementation, mimic https://github.com/JuliaAI/MLJIteration.jl/blob/b12c0bc284fd61136924767cfd2a219f98e9aab0/src/constructors.jl#L189

Have just merged #18 which introduces this feature.


Corrects region width problem

I believe this problem was created by merging one of my last Pull Request.  It's no longer in the master.

I can't I deleted my fork after the merge. If you want to apply the change yourself I don't mind. If I remember correctly the pull request was only two lines of code in updateRender of wavesurfer.regions file:
var fillParentNoScroll = (!this.wavesurfer.params.scrollParent && this.wavesurfer.params.fillParent);
var width = fillParentNoScroll ? this.wavesurfer.drawer.getWidth() : this.wrapper.scrollWidth;

The problem is that below this lines there is the old declaration of width.

Merged, thanks!

Thanks to you to for this great project!


Empty copyright in apache license

https://github.com/alexcrichton/toml-rs/blob/master/LICENSE-APACHE#L189
With empty copyright it is just template, isn`t it?

I believe it is intentional (though not required to be included per the definition of "License").  The full text of the license is from here. It instructs the person on the receiving end of the license how to apply the license correctly to their derivative work.  It can be removed, or kept, I don't think it matters.

Yeah I think this is correct as is. Not every project that the person receiving this license will apply it to will have the same copyright year / owner.


Single function entry

lw-rasterizer mixes processing in both worker and non-worker code. It also handles communication between worker and non-worker. This complicates LW4 integration. Could you change it to do this?

A single function entry point for the algorithm. Caller passes in options, image (I can give you either an Image object or a data-url), and progress callbacks. Function returns when done. The function can't spawn a worker since that forces async operation.
Function won't care if it's called inside a worker or the main thread.

Right now, LW4 doesn't have worker support. When I add it, the entire CAM flow will execute in a single worker. That worker will call into lw-rasterizer. The CAM flow executes operations in sequence; it expects each operation to either run to completion or fail before returning.

I just realized that workers can't use Image objects. Maybe 2 functions?

F1: accepts the image object and options, returns data that F2 needs
F2: what I described above.

Go for a ES6 module ;)

You want me to turn it into an ES6 module?

Sorry I always express myself so badly. I will do it.

New module at https://github.com/lautr3k/lw.raster-to-gcode no more WebWorker but an nonBlocking setting when set to true use a setTimeout to avoid blocking the UI.


Telegram Bot should send response back as a reply

This is especially useful when it is used in groups

Thanks!


CPU Govnor

Describe the bug
When i change CPU power to performance, it doesn't work after i reboot
What did you expect to happen?
I expected the CPU to run at Max MHz, because games like Dota 2 Street Fighter 6 and MK1 need CPU to run at max frequency or it wil cause stutter when spells and skills are used
Output of rpm-ostree status
No response
Hardware
i5-6500
RX 6400 RX 580 RX 6600 and RX 5600
Extra information or context
The Commands i entered
sudo cpupower frequency-set -g performance
sudo systemctl enable cpupower

Changes to cpu frequency don't survive reboots -- stock behavior.


Adapt Oxy.Framework modules to NuGet publishing

Adapt Oxy.Framework modules to NuGet publishing to simplify future integration with CI and publishing to nuget.org.
Tutorial: https://docs.microsoft.com/en-us/nuget/create-packages/creating-a-package

Done.


assetPrefix

how to config the assetPrefix?

This plugin has a separate config for that because some users will upload their images to a different service (e.g. S3) than all other assets. You can use the imagesPublicPath for that.
Example:
// next.config.js
const withOptimizedImages = require('next-optimized-images');

module.exports = withOptimizedImages({
  imagesPublicPath: 'https://my.cdn.com/_next/static/images/'
});

But as I'm now writing this, I think the normal assetPrefix should be supported by default and this setting should be an optional overwrite. I'll definitely include assetPrefix support it in the next version, until then, the imagesPublicPath can be used.


.cat() with Buffers

the .cat() method isn't working with buffers as input.
" does not exist     at Function.input (/node_modules/node-pdftk/index.js:88:68)     at pdftk.input.stamp.output.then.catch.then.buffer (/index.js:108:6)     at <anonymous>
when outputting the used buffers as files and then cat, it works as expected.
pdftk     .input({         A: fs.readFileSync('./page1.pdf'),         B: './page2.pdf',     })     .cat('A B')

Oops - it looks like I completely missed the functionality to handle buffers when using handles.
A fix for this is in. See #8 or re-install from npm (version 1.2.2). Thanks for bringing this to my attention!


Change sprockets version dependency

For now there is available sprockets release candidate version, so we can skip version 3 for this and just leave >= 2 version.

@jfirebaugh sorry for this ping pong, but I think it is more correct to just leave '>= 2' version for sprockets.

Yeah I agree with @gkopylov. Should have done this with my earlier PR. :)

It would also be nice if the gem got a new release based on the latest code. :)

Hi @jfirebaugh, bumping this just in case.

Hi @jfirebaugh, just bumping this. Hoping this gets merged and an updated gem version released. :smile:

Can you change it to  >= 2, < 4? The next major change will likely break again.

Done.

Oh, seems that there is no new version of libv8 on travis-ci. Ok, I'll change it to a bit older one.

@jfirebaugh it is passed now. Sorry for long delay :-)

@jfirebaugh, @gkopylov, any news on this one?

@vast this PR is ready to merge. We are only waiting @jfirebaugh to merge it.

Thanks, committed as f399ebbec0e77c76de5ee05cb958bd8e14476ed4.
Anyone on this thread interested in taking over maintenance of skim? I would like to hand the project off to someone.

@jfirebaugh okay, let's give it a try!
Personally I've lost keen interest in SPA after great news about Rails 5 and Turbolinks 3, however I have some projects which is using BackboneJS and skim, so I'll keep supporting this.
Nevertheless SPA frameworks(especially Backbone) will get their niche and we will need a good template engine for them, so I am interested in taking over maintenance of skim.


Fix Argo CD installation namespace for a 4.6 cluster

The operator will decide the namespace based on the version of the cluster it is running in.
Expected behavior
4.6 Cluster: Backend service in openshift-pipelines-app-delivery and argocd in openshift-gitops namespace
4.7 Cluster: Both backend service and argocd in openshift-gitops namespace
How to test:

Install argocd operator
Observe if argocd is installed in openshift-gitops namespace
If it's a 4.6 cluster, the backend will be deployed in openshift-pipelines-app-delivery namespace else it'll get deployed in openshift-gitops namespace

/lgtm
/approve

/lgtm
/approve


Gauge should handle multiple structured log entries properly.

Expected behavior
Gauge's runner or plugin writes two structured log entries and Gauge prints them accordingly.
Example:
{"logLevel":"debug","message":"log debug message"}
{"logLevel":"info","message":"log info message"}

Above log entries should be printed as below.

When log level is set to debug
  log debug message
  log info message

When log level is set to info
  log info message

Actual behavior
Gauge does not process them correctly and prints them as follow regardless of the log level.
Example:
      {"logLevel":"debug","message":"log debug message"}
      {"logLevel":"info","message":"log info message"}

Gauge version
Gauge version: 1.0.6
Commit Hash: df8d663d

This has been verified with version: 1.0.6.nightly-2019-07-16


Latest version blank page.

Latest version get a blank page.
Wordle is not working anymore with the latest docker version.

Heya,
Sorry about that, looks like there was a regression upstream.
I'm just making a new build which should resolve.
https://drone.modem7.com/modem7/react-wordle/59/1/3
Once that's completed, you should be able to pull down a new version and have it working.

@mariushosting please try now!

Thanks it's perfectly working right now!


Unable to connect to Redis Datasource via Grafana Cloud

Summary
Hello! Unable to connect to any of my Redis 7 instance pools on my VPS either by localhost ports or via Unix socket. Any help appreciated!
Relevant information
I have a small 48 core 6GB CentoOS 7/Virtuozzo WHM/Cpanel based cloud VPS with several small Redis Server v7.0.10 instances, each is fully working that I use for my various Apache vhosts/websites.
Each instance or pool runs under SystemD and binds to <IP_ADDRESS>.1, they are currently un-passworded and are available via port and Unix sockets:

localhost:6379

localhost:6380

localhost:6381

… to

localhost:6386

/var/lib/redis/redis.sock

/var/lib/redis/redis2.sock

/var/lib/redis/redis3.sock

… to

/var/lib/redis/redis8.sock

I have installed the 3 related Redis plugins on my free Grafana Cloud:

Redis Datasource redis-datasource (v2.1.1)
Redis Application redis-app (v2.2.1)
Redis Explorer redis-explorer-app (v2.1.1)

When trying to connect to any instance via either localhost:6379 or redis://localhost:6379 etc, I get this error message via the Datasource Standalone tab:
getInstance error: dial tcp <IP_ADDRESS>:6379: connect: connection refused

If I try the Unix socket connection method, I get this on the Datasource Socket tab:
getInstance error: dial unix /var/lib/redis/redis.sock: connect: no such file or directory
I can’t find any similar messages in my Apache or CSF/LFD firewall logs related to it.
I have ACL user names created (one for Grafana to eventually use) but all currently set as nopass so I’m leaving the ACL option disabled and not entering any usernames or passwords.
However when I try using the other Redis infrastructure plugin v0.0.3, that comes with the Redis Dashboard for Prometheus Redis Exporter 1.x it works fine and connects immediately. However that one doesn’t support multiple instances so it’s not ideal.

(BTW, the links to the demo Dashboard on the Datasource overview page are broken, I get a message saying Dashboard not found).
Many thanks!
redis-cli -s /var/lib/redis/redis.sock
redis /var/lib/redis/redis.sock> info
# Server
redis_version:7.0.10
redis_git_sha1:00000000
redis_git_dirty:0
redis_build_id:5aad47f03c937350
redis_mode:standalone
os:Linux 3.10.0-1160.53.1.vz7.185.3 x86_64
arch_bits:64
monotonic_clock:POSIX clock_gettime
multiplexing_api:epoll
atomicvar_api:c11-builtin
gcc_version:8.3.1
process_id:21033
process_supervised:systemd
run_id:2ef8b39e737fa80e0b60f1e9fdb6e97bec8a04dd
tcp_port:6379
server_time_usec:1682515275648506
uptime_in_seconds:419166
uptime_in_days:4
hz:10
configured_hz:10
lru_clock:4793675
executable:/usr/bin/redis-server
config_file:/etc/redis/redis.conf
io_threads_active:0

# Clients
connected_clients:1
cluster_connections:0
maxclients:1000
client_recent_max_input_buffer:8
client_recent_max_output_buffer:0
blocked_clients:0
tracking_clients:0
clients_in_timeout_table:0

# Memory
used_memory:690744
used_memory_human:674.55K
used_memory_rss:9777152
used_memory_rss_human:9.32M
used_memory_peak:1199184
used_memory_peak_human:1.14M
used_memory_peak_perc:57.60%
used_memory_overhead:394768
used_memory_startup:392784
used_memory_dataset:295976
used_memory_dataset_perc:99.33%
allocator_allocated:903392
allocator_active:1323008
allocator_resident:10326016
total_system_memory:6442450944
total_system_memory_human:6.00G
used_memory_lua:31744
used_memory_vm_eval:31744
used_memory_lua_human:31.00K
used_memory_scripts_eval:0
number_of_cached_scripts:0
number_of_functions:0
number_of_libraries:0
used_memory_vm_functions:32768
used_memory_vm_total:64512
used_memory_vm_total_human:63.00K
used_memory_functions:184
used_memory_scripts:184
used_memory_scripts_human:184B
maxmemory:16777216
maxmemory_human:16.00M
maxmemory_policy:allkeys-lru
allocator_frag_ratio:1.46
allocator_frag_bytes:419616
allocator_rss_ratio:7.80
allocator_rss_bytes:9003008
rss_overhead_ratio:0.95
rss_overhead_bytes:-548864
mem_fragmentation_ratio:14.63
mem_fragmentation_bytes:9108704
mem_not_counted_for_evict:0
mem_replication_backlog:0
mem_total_replication_buffers:0
mem_clients_slaves:0
mem_clients_normal:1800
mem_cluster_links:0
mem_aof_buffer:0
mem_allocator:jemalloc-5.2.1
active_defrag_running:0
lazyfree_pending_objects:0
lazyfreed_objects:0

# Persistence
loading:0
async_loading:0
current_cow_peak:0
current_cow_size:0
current_cow_size_age:0
current_fork_perc:0.00
current_save_keys_processed:0
current_save_keys_total:0
rdb_changes_since_last_save:0
rdb_bgsave_in_progress:0
rdb_last_save_time:1682096109
rdb_last_bgsave_status:ok
rdb_last_bgsave_time_sec:-1
rdb_current_bgsave_time_sec:-1
rdb_saves:0
rdb_last_cow_size:0
rdb_last_load_keys_expired:2420
rdb_last_load_keys_loaded:0
aof_enabled:0
aof_rewrite_in_progress:0
aof_rewrite_scheduled:0
aof_last_rewrite_time_sec:-1
aof_current_rewrite_time_sec:-1
aof_last_bgrewrite_status:ok
aof_rewrites:0
aof_rewrites_consecutive_failures:0
aof_last_write_status:ok
aof_last_cow_size:0
module_fork_in_progress:0
module_fork_last_cow_size:0

# Stats
total_connections_received:8544
total_commands_processed:21556
instantaneous_ops_per_sec:0
total_net_input_bytes:908396
total_net_output_bytes:38403251
total_net_repl_input_bytes:0
total_net_repl_output_bytes:0
instantaneous_input_kbps:0.00
instantaneous_output_kbps:0.00
instantaneous_input_repl_kbps:0.00
instantaneous_output_repl_kbps:0.00
rejected_connections:0
sync_full:0
sync_partial_ok:0
sync_partial_err:0
expired_keys:0
expired_stale_perc:0.00
expired_time_cap_reached_count:0
expire_cycle_cpu_milliseconds:14440
evicted_keys:0
evicted_clients:0
total_eviction_exceeded_time:0
current_eviction_exceeded_time:0
keyspace_hits:0
keyspace_misses:0
pubsub_channels:0
pubsub_patterns:0
pubsubshard_channels:0
latest_fork_usec:0
total_forks:0
migrate_cached_sockets:0
slave_expires_tracked_keys:0
active_defrag_hits:0
active_defrag_misses:0
active_defrag_key_hits:0
active_defrag_key_misses:0
total_active_defrag_time:0
current_active_defrag_time:0
tracking_total_keys:0
tracking_total_items:0
tracking_total_prefixes:0
unexpected_error_replies:0
total_error_replies:894
dump_payload_sanitizations:0
total_reads_processed:30100
total_writes_processed:21560
io_threaded_reads_processed:0
io_threaded_writes_processed:0
reply_buffer_shrinks:285
reply_buffer_expands:2

# Replication
role:master
connected_slaves:0
master_failover_state:no-failover
master_replid:23ca5cb3a45af59f0241225f80ae086b36ba4814
master_replid2:0000000000000000000000000000000000000000
master_repl_offset:241104
second_repl_offset:-1
repl_backlog_active:0
repl_backlog_size:1048576
repl_backlog_first_byte_offset:0
repl_backlog_histlen:0

# CPU
used_cpu_sys:171.736551
used_cpu_user:381.038902
used_cpu_sys_children:0.000000
used_cpu_user_children:0.000000
used_cpu_sys_main_thread:171.732740
used_cpu_user_main_thread:381.037618

# Modules

# Errorstats
errorstat_ERR:count=894

# Cluster
cluster_enabled:0

# Keyspace
redis /var/lib/redis/redis.sock>

Hi @TheOldMan2000 - I'm taking over maintenance of this plugin - so forgive me if I'm missing some critical context here.
This sounds like your trying to connect to your Redis instance (on your 48 core 6GB Centos machines) from your Grafana cloud account.
I might be missing something here, but I don't think your VPS and your free grafana instance are going to run on the same machine. So trying to connect via localhost:6379/<IP_ADDRESS>:6379 (or for that matter a unix socket) simply isn't going to work. Now if you installed Grafana on your VPS and ran it from there, sure that should work as they would be on the same server. But as it stands you would need either a DNS name or IP address that the plugin can reach out to in order to connect to Redis.

Hello @slorello89
Thank you for the suggestions. I’m unsure but I assumed it would work because Grafana Agent was running on the same VPS, and I have no problem at all with the other Redis plugin for Grafana Cloud, as seen in the image above.

Hi @TheOldMan2000 - Sorry for the delayed response, I looked into it wrt the grafana agent, I don't see any indication that the Grafana Agent can use this plugin (unless I'm dramatically wrong about something - if so please feel free to correct me), so you would need to use the external-IP/hostname for your Redis instance from Grafana Cloud in order to access it. Accessing Redis on localhost:6379 from Grafana Cloud will not work since it's not there.
Connect to the real host/ip and make sure your firewall is opened up and it should just work.


NPD: Remove get start point

Based on https://github.com/kubernetes/node-problem-detector/pull/31 to enable the presubmit test.
This PR addressed https://github.com/kubernetes/node-problem-detector/issues/3#issuecomment-246431485 to remove the unnecessary getStartPoint function.
With this change @AdoHe should be able to use simple tail library directly.

rebase first, then we are ready to go.

@dchen1107 Rebased, apply LGTM based on https://github.com/kubernetes/node-problem-detector/pull/32#issuecomment-246492744.


Insert query fails silently after upgrading to 4.6

EdgeDB Version: 4.6+0632dff
EdgeDB CLI Version: 4.1.0+03ae624
OS Version: Linux Mint 21.3

Steps to Reproduce:

Migrate the provided schema on an EdgeDB 4.6 instance
Run query:

select (insert people::Person {
  first_name:= "Test",
  last_name:= "TEST"
}) { * }
# Returns an empty set

Running only the insert statement also return an empty set.
Checking the database content confirms that the item was not inserted.
Insertion of other object types seems to work, although I only tested a few of them.
Everything works as expected on v4.5.

Schema:

Schema definition files: https://gist.github.com/lsdch/22ea6f875e7df4481e73da26dd0ca891
Migration file: https://gist.github.com/lsdch/cca2800c7ab63f431d1fe3ab2d818298

Thanks for the report!
This issue is a knock-on effect of https://github.com/edgedb/edgedb/issues/7061.
Because the cardinality of the current_user global gets inferred incorrectly in queries, we perform some optimizations that are unsound when dealing with something of optional cardinality.
This will be fixed in 4.7 by reverting #6613 and in 5.x by https://github.com/edgedb/edgedb/pull/7062


[❗🔨 build]:  update of setup-node action due to break of cache support

As a new version of setup-node was released we need to update it due to the cut of support of the currently active version.
Please update all of the workflows listed in the project (.github/workflows)
** Statement of issue **
The github workflow builds failed with the following message:

Environment

GitHub Actions

Priority : Citical

CC: @exadel-inc/esl-core-team as you also work on other DMTP projects, be aware of that issue, it sounds actual for almost all of our projects.

:tada: This issue has been resolved in version 4.0.0-beta.8 :tada:
The release is available on:

npm package (@beta dist-tag)
GitHub release

Your semantic-release bot :package::rocket:

:tada: This issue has been resolved in version 4.0.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


Fix typo

Fix authorization typo.

I closed it because the title and description were very inappropriate. I corrected them.

Thanks!


Image inside the headset shakes/jitters heavily during head movement with Nvidia GPUs

This is a known issue as pointed out in the discord server, so i thought i would create one here on GitHub. On nvidia hardware, the image inside the headset jitters or shakes heavily on the Linux Build of ALVR server. This will not happen on windows. Someone pointed out this has to do with Nvidia GPUs on Linux not having support for async reprojection in the drivers.
Maybe somebody smarter than me, can come up with their own workaround to get the posing correct to make the experience more comfortable for the user wearing the HMD on Nvidia.

To be accurate, in order to match video frames with a position, the linux build relies on a hack and unwinds the stack in vkQueuePresent in order to find a TrackedDevicePose_t object and associates it to the video frame.
Unfortunately, this trick only works with async reprojection, which is not supported on nvidia drivers. In the non-async codepath, the TrackedDevicePose_t objects do not seem to match the image.

happened to me on windows 10 with an rx 580, fixed it by tinkering with the settings a little to find a sweet spot

@rullinoiz Unfortunately this is a Linux specific issue that cannot be solved by messing with a few settings, because of how the Linux driver is written we have to change actual code to fix this

Same exact thing occurring on an AMD Radeon 6800XT

Apparently this will be fixed in driver 470 https://www.gamingonlinux.com/2021/06/nvidia-driver-470-for-linux-to-include-support-for-async-reprojection

Same exact thing occurring on an AMD Radeon 6800XT

I have the same issue I believe with a RX 580.

happened to me on windows 10 with an rx 580, fixed it by tinkering with the settings a little to find a sweet spot

What settings?

Installing the 470 nvidia beta drivers for linux fixed this for me

Installing the 470 nvidia beta drivers for linux fixed this for me

What distro are you using? I still get the jitter even with the 470 driver installed

Manjaro linux, linux 5.12 kernel (linux-tkg-pds)
alvr settings are 75% resolution, 72hz, reduce color banding on, throttled udp

Manjaro linux, linux 5.12 kernel (linux-tkg-pds)
alvr settings are 75% resolution, 72hz, reduce color banding on, throttled udp

I can confirm that this is still an issue.
I am on Manjaro with kernel 5.12.19-1 and nvidia driver version 470.57.02 with the same settings as you on v16-rc2, the jitter is still there.

Installing the 470 nvidia beta drivers for linux fixed this for me

Using Arch and on Nvidia driver 470 but it's not better for me.

Disabling async reprojection reduce shaking a lot.
It's located at ~/.steam/steam/config/steamvr.vrsettings :
{
   "steamvr" : {
      "enableLinuxVulkanAsync" : false
   }
}

Still seems to be an issue with driver version 510.47.03 and NVENC.

Is the last release (https://github.com/alvr-org/ALVR/releases/tag/v18.0.0) supposed to fix it?

Sounds great, I'll test this ASAP.

Fixed on ALVR v18.0.0


Add refreshing of the hubspot data

For:

https://github.com/hypothesis/report/issues/39

I'm self approving this one


authentication error

authentication error, nothing happens after scanning the code and when executing another request it tells me that there is a token error
{"status": false, "err": "Wrong token authentication"}

am I having the same problem, any news?

I think this is the main cause
WA_AUTOMATE_VERSION   '1.9.57 UPDATE AVAILABLE: 1.9.74'
WA_AUTOMATE is outdated in whats2API.
We are missing a lot of bug fixes.

@joaomirandasa

just update it, they will fix all

just update it, they will fix all

it Worked! Thanks!

just update it, they will fix all

How  can I do this, @indrajatmiko ?
Can you point me some directions?
TIA

It worked! Thanks

How to update it?

just update it, they will fix all

How to update it?

npm update

Thanks alot @impozzible

I am still facing the same issue and getting this as the response:
{
"status": false,
"err": "Wrong token authentication"
}

I am still facing the same issue and getting this as the response:
{
"status": false,
"err": "Wrong token authentication"
}


Improve .dbc

Changed PP status in 0x3B4 to Intel and 2-bit
Removed overlap in 0x432 for SOC and Voltage setpoint

Thank you


Wrong spring cloud connectors core coordinates

The commit to upgrade to Spring Boot 2 changed two things with the spring-cloud-core artifact:

A version was explicitly set. Please refrain from doing that as it likely to break dependency management of app using the starter
The dependency used to be optional and isn't anymore. Is that an oversight?

The name of this artifact was changed as "spring-cloud-core" is very generic. The new name is spring-cloud-connectors-core and is managed by Spring Boot 2 so you shouldn't need to specify a version.

Thank you for pointing out, created a PR with the proposed changes


Unmarshaling error

As part of my research I am setting up FastFabric-1.4 to run some experiments and followed the documentation in your git. I am facing a few issues and it would be great if you could guide me in the process.
I am able to run around 500 transactions with FastFabric but beyond that unmarshaling fails on the peers. I used the same chaincode and client scripts available in this git. The exact error is shown below. Since the error only occurs when I increase the number of transactions I assume that my FastFabric setup is correct. Is this an expected error if the system cannot sustain the transaction throughput?  Do you have any suggestions for resolving this? Maybe I need to change some configurations based on my server specifications (blockBufferSize,  maxBlockCountToStore etc).
[gossip.channel] HandleMessage -> WARN 0c9 Data update contains an invalid message: Failed unmarshaling GossipMessage from envelope: unexpected EOF
github.com/hyperledger/fabric/gossip/gossip/channel.(*gossipChannel).HandleMessage
/home/ubuntu/go/src/github.com/hyperledger/fabric/gossip/gossip/channel/channel.go:658
github.com/hyperledger/fabric/gossip/gossip.(*gossipServiceImpl).handleMessage
/home/ubuntu/go/src/github.com/hyperledger/fabric/gossip/gossip/gossip_impl.go:378
github.com/hyperledger/fabric/gossip/gossip.(*gossipServiceImpl).acceptMessages
/home/ubuntu/go/src/github.com/hyperledger/fabric/gossip/gossip/gossip_impl.go:332
runtime.goexit
/usr/local/go/src/runtime/asm_amd64.s:1581
Further, even with less than 500 transactions the orderer returns an EOF error to the clients. Despite this error the transactions are successfully committed to the blockchain, so is it fine to ignore this error?
error: [Orderer.js]: sendBroadcast - on error: "Error: 2 UNKNOWN: EOF\n    at Object.exports.createStatusError (/home/ubuntu/go/src/github.com/hyperledger/fabric/fastfabric/scripts/client/node_modules/grpc/src/common.js:91:15)\n    at ClientDuplexStream._emitStatusIfDone (/home/ubuntu/go/src/github.com/hyperledger/fabric/fastfabric/scripts/client/node_modules/grpc/src/client.js:233:26)\n    at ClientDuplexStream._receiveStatus (/home/ubuntu/go/src/github.com/hyperledger/fabric/fastfabric/scripts/client/node_modules/grpc/src/client.js:211:8)\n    at Object.onReceiveStatus (/home/ubuntu/go/src/github.com/hyperledger/fabric/fastfabric/scripts/client/node_modules/grpc/src/client_interceptors.js:1311:15)\n    at InterceptingListener._callNext (/home/ubuntu/go/src/github.com/hyperledger/fabric/fastfabric/scripts/client/node_modules/grpc/src/client_interceptors.js:568:42)\n    at InterceptingListener.onReceiveStatus (/home/ubuntu/go/src/github.com/hyperledger/fabric/fastfabric/scripts/client/node_modules/grpc/src/client_interceptors.js:618:8)\n    at /home/ubuntu/go/src/github.com/hyperledger/fabric/fastfabric/scripts/client/node_modules/grpc/src/client_interceptors.js:1127:18"

Hi, I have issues with setting the network up on one local machine. Maybe you can help me?


Add files via upload

Adding request pull for MY.TCCD.EDU

@Raigekijin This domain is blacklisted because the college allows to register an email address there even if you are not a student of the college. If you are the student of this college, please apply with official document ("OFFICIAL DOCUMENT" tab at https://www.jetbrains.com/shop/eform/students).


Tooltip Added for all icons in Share Card

Issue(s)
https://github.com/middlewarehq/unwrapped/issues/62
Acceptance Criteria fulfillment

[x] Should Have Tootip on Copy Button
[x] Should Have Tootip on Share on X Button
[x] Should Have Tootip on Share on LinkedIn Button
[ ] Should Have Tootip on Download Button

Proposed changes (including videos or screenshots)
The requirement of having a tooltip on each of the button can be easily fullfilled by using react-tooltip package(already present in the project). This Tooltip is aligned with the current design of the app, and is useful to communicate proper functionality of the feature.

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

Hi @dhruvagarwal , Please check this PR, I am happy to contribute more, as I found this project very intresting and inspirational.
Thanks

Thanks @RounakJoshi09 for your contribution. Looks good to me but I'll let @jayantbh have a look at it and approve as he deems fit.

Thanks for the contribution @RounakJoshi09.  Reviewed your PR, and it LGTM! Merging it.


Support developing applications that use multiple individual containers

Jaguar works by loading the application into a separate container, but it only runs one at a time. We start installing the program here https://github.com/toitlang/jaguar/blob ... r.toit#L49 (this is what kills the old version of the program) and we start running it here https://github.com/toitlang/jaguar/blob ... r.toit#L60.
This issue is suggesting to implement a new feature to load the applications into individual containers identified by the name: <App name> from https://docs.toit.io/platform/apps/appspec/#the-specification-file
Inspired by https://esp32.com/viewtopic.php?f=2&t=24941#p88621

Being able to develop apps that run across multiple containers using Jaguar seem useful.

@krzychb Finally made some progress with this. Once #228 lands, you can install multiple containers and have them run side by side using:
$ jag container install hello examples/hello.toit
$ jag container install http examples/http/http.toit
$ jag container list
718b6ac6-860c-58af-8ef7-f694e7284dc6: jaguar
0b777bc9-d58c-56b2-a030-1738f48888b1: hello
6173c8b0-be07-5b2e-852a-1e9cc5847a3a: http

Thank you @kasperl!


Azure Stack Edge Pro GPU link for GPU inferencing takes to Azure ML deployment docs for FPGA

Is this link wrong?
Original text:
Inference with Azure Machine Learning - With Azure Stack Edge Pro GPU, you can run ML models to get quick results that can be acted on before the data is sent to the cloud. The full data set can optionally be transferred to continue to retrain and improve your ML models. For more information, see how to use Deploy Azure ML hardware accelerated models on Azure Stack Edge Pro GPU.
Perhaps it should link instead to the following?
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-deploy-inferencing-gpus
ASE Pro GPU should support GPU inferencing on AKS clusters, I would expect...

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

ID: 2cdd1fa7-d4d9-bf20-3359-7b51386e8107
Version Independent ID: 9a2c3027-89d9-c936-3f13-3eb37a2481df
Content: Microsoft Azure Stack Edge Pro with GPU overview
Content Source: articles/databox-online/azure-stack-edge-gpu-overview.md
Service: databox
Sub-service: edge
GitHub Login: @alkohli
Microsoft Alias: alkohli

@nswitanek Thanks for the question! We are investigating and will update you shortly.


[unstable release]

Background
This PR adds the changes added from @robin-drexler 's PR:  remove customer-account docs #38269 and @hheyhhay  PR: update build-docs to shopify-dev path #38473 to unstable for the 2024-10 release
Solution
This unstable release should only have changes from the two PRs mentioned above.
🎩

...

Checklist

[x] I have :tophat:'d these changes
[x] I have updated relevant documentation

/snapit


unverified users can login using the password-reset flow

Bug Report
unverified users can login using the password-reset flow.
Steps to Reproduce

create a user in an auth collection which has "verify" enabled
use "forgot-password" to receive a password reset token for this user
use "reset-password" to set a new password for the user

--> the user is automatically logged in, although not being verified
--> the user is still not able to login using the login form, because he is not verified
Other Details
the expected behavior would be that an unverified user cannot gain access to the application.
Possible Solutions and Thoughts:
a) do not allow reset-password for unverified users
this could solve the problem, but the password-reset functionality seems currently to be the only way to prevent locked out users which did not receive or have lost their verification email. that means that if this option is implemented, a resendVerificationEmail() functionality is required from my point of view.
from my understanding, it is currently not possible to configure this behavior over the payload config, as there is no beforePasswordReset hook which could throw an error if the user is not verified. maybe there are ways to configure it i have not thought of?
b) do not perform auto-login after password-reset
this would definitely have a negative impact on the user experience. it could be limited to unverified users, but it could get hard for users to understand why they are not able to login with their updated credentials. this would require an explicit login error message.
and again, the problem with lost verification emails must be solved somehow.
c) trigger beforeLogin and afterLogin hooks after password is reset
this could make it possible to configure the desired behavior over the payload config: if an error is thrown in beforeLogin, the user is not automatically logged in.
it would be nice to have an additional parameter in the hooks to be able to distinguish between "normal logins" and "password-reset" logins.
d) auto-verify on password reset
one could argue that if the user was able to receive the forgot-password email, the user is implicitly verified. then the _verified flag should automatically be set to true on password-reset if the collection has "verify" activated.
from my understanding this is currently not configurable over the payload config because there is no afterPasswordReset hook and the afterLogin hook is not triggered.
--
ps: thank you so much: payload is an amazing project! keep up the excellent work!

Hey @berndb — this is a great catch. And thank you for the compliments! Payload is just getting started. LOTS more in store, especially in the next ~30 days. Keep an eye out.
I've implemented your suggestion in D. It's great.
PR will be merged and this will be released likely tomorrow!


upload: Removing attachment from text disallows attaching the file again

This is how to reproduce the error:

Press the 'attach file' button in the compose box.
Select a file to attach. This will upload the file to the server and place a link in the compose box.
Don't press send, discard the message.
Now try to send a message with the same attachment.

When you select a file using the attach file button, nothing will happen (a link should have been placed in the compose box instead).

@zulipbot label "area: markdown" "bug" "bite size" "help wanted"

Sounds like a jquery-filedrop bug, not a backend bug.

@zulipbot claim

Looks like the issue here is that after the upload is finished, the file list isn't cleared correctly, so when the same file is uploaded, it does not trigger the .change() event handler.
I've set up a working change. Will commit in the morning.


Update service.yaml

What this PR does / why we need it: Fix a typo in service.yaml
Which issue this PR fixes (optional, in fixes #<issue number>(, fixes #<issue_number>, ...) format, will close that issue when PR gets merged):  n/a
Special notes for your reviewer:

Thanks for the pull request. Please sign the CLA and increment the version in Chart.yaml.

@kti-rob bump

@kti-rob Can you also bump the Chart.yaml version please?

/assign

Opened new request: #7198
/close

/close in favour of #7198


CB-5768 Add entitlement and enable feature flag for IDBroker mapping validation

Adds IDBroker mapping validation as an entitlement and defaults the feature flag of environment request to true for IDBroker mapping validation. This lays the way to enable this per tenant in CDP in case there are issues with SimulatePrincipalPolicy due to IAM limits or other AWS issues (altus found that SimulatePrincipalPolicy is not always accurate).

Rebased to resolve merge conflict with master.


runtime: checkdead fires due to suspected race in the Go runtime when GOMAXPROCS=1 on AWS [1.19 backport]

@prattmic requested issue #59600 to be considered for backport to the next 1.19 minor release.

@gopherbot Please open a backport issue to 1.20.
Quoting @SuperQ :

Is it possible to get this bugfix backported to 1.20? It is affecting users of Prometheus monitoring as we default GOMAXPROCS=1 for the node_exporter to reduce problems with data races in the Linux kernel.

Quoting @prattmic:

@gopherbot Please open a backport to 1.19. This issue is not new in 1.20, and potentially affects users with GOMAXPROCS=1.

On closer look, I think that this issue is new in 1.20. Specifically, the issue was due to a critical section in injectglist where we allocate a P, unlock sched.lock (allowing checkdead to run), and then later in startm lock sched.lock again to actually start the M to use the P.
This was introduced in https://go-review.googlesource.com/c/go/+/389014/8/src/runtime/proc.go#3186. Prior to that CL, the P was acquired in startm with sched.lock held the whole time.
Thus I believe we can retract this cherry-pick request.

Yes, we only noticed the issue with 1.20.


Do you consider to release the training code?

Hi, thanks for your work!
Could you release the training code? My implementation cannot reach the performance reported in your paper.
Thanks in advance!

Hi, thanks for your work!
Could you release the training code? My implementation cannot reach the performance reported in your paper.
Thanks in advance!

Sorry to reply you later. I am a little busy recently, and the code is not ready yet.

code for ablation will come soon.
code for seg: https://github.com/pppppM/mmsegmentation/tree/laoyong_cvpr
code for detection: https://github.com/pppppM/mmdetection

===================================================
run this code:【https://drive.google.com/file/d/15BdezuKf4pdDwk9KhhEeCLkS1CmCdxya/view?usp=sharing】
The mIou (no flip and scale) of original student(PSPNet-RN18) is 71.2
./tools/dist_train_distill.sh ./configs/pspnet/distill-pspnet_r101-to-pspnet_r18-d8_512x1024_40k_cityscape-ocw-0.0-v1.py None 1 45680
After distillation only by CW loss, the mIou (no flip and scale) of original student(PSPNet-RN18) is 74.7.
./tools/dist_train_distill.sh ./configs/pspnet/distill-pspnet_r101-to-pspnet_r18-d8_512x1024_40k_cityscape-ocw-40.0-v1.py None 1 45682

@drilistbox Thanks for your prompt reply and experimental details!

Hi, have you reproduced the training phase? Is it possible to share your code?

hi, thanks for your attention, more detail please refer https://github.com/irfanICMLL/TorchDistiller/tree/main/SemSeg-distill.

hi, thanks for your attention, more detail please refer https://github.com/irfanICMLL/TorchDistiller/tree/main/SemSeg-distill.

Thanks a lot.


Cleanups

Minimal changes - most are codespell or clang-format changes

Merged as a part of the 1.0 release.


OutOfOrderGattCallbackException: Unexpected response type OnCharacteristicWrite received

I work on Android. Have been using this lib for more than one year. And now I got the case when I catch OutOfOrderGattCallbackException. The full text is OutOfOrderGattCallbackException: Unexpected response type OnCharacteristicWrite received. The scenario is pretty simple: there are two characteristics. One I use to write byte arrays on a device, the second one is read the status of this "writing". And in one moment I get this exception. I found it is source code but its cause is not clear for me. Why do I get it?

What version of Kable are you using?
OutOfOrderGattCallbackException occurs when the underlying bluetooth callback provided Kable with an unexpected response.
More specifically, Kable ensures that every I/O operation happens within a lock. For example, when a write request is initiated, the lock prevents other I/O operations until Kable gets a write response. If an unexpected response is received, i.e. receiving a read response callback when we had just performed a write request, then OutOfOrderGattCallbackException would be thrown.
In most cases, this should not occur. I haven't seen the Android system giving unexpected responses, but that is what that exception is intended to inform you of (that failure case).
There is some complexity around cancellation handling, so it is possible that the internal Kable bookkeeping has a bug.
I would need more detailed logs to know more, and to help further.

We came upon this issue with version 0.23.0.

@grabbe-bryghtlabs can you provide logs to help debug the issue?

This is a snippet
2024-04-09 11:24:35.854 28595-28632 oplus_bt_s..._ble_event com.android.bluetooth                I  report_stack_ble_gatt_read_write_operation_event enter 2024-04-09 11:24:35.854 28595-28632 BtGatt.GattService      com.android.bluetooth                D  onWriteCharacteristic() - increasing permit for address=DC:DA:0C:15:1F:A6 2024-04-09 11:24:35.855 28595-28632 oplus_bt_s..._ble_event com.android.bluetooth                I  stack_ble_gatt_read_write_operation_event_report address=dc:**:**:**:1f:a6 2024-04-09 11:24:36.062 28595-28916 BtGatt.GattService      com.android.bluetooth                D  writeCharacteristic() - trying to acquire permit. 2024-04-09 11:24:36.100 28595-28795 bt_bta_gattc            com.android.bluetooth                D  Handling write response type: 2: handle 0x000c 2024-04-09 11:24:36.100 28595-28632 oplus_bt_s..._ble_event com.android.bluetooth                I  report_stack_ble_gatt_read_write_operation_event enter 2024-04-09 11:24:36.101 28595-28632 BtGatt.GattService      com.android.bluetooth                D  onWriteCharacteristic() - increasing permit for address=DC:DA:0C:15:1F:A6 2024-04-09 11:24:36.103 28595-28632 oplus_bt_s..._ble_event com.android.bluetooth                I  stack_ble_gatt_read_write_operation_event_report address=dc:**:**:**:1f:a6 2024-04-09 11:24:38.906  1299-6353  ANDR-PERF-LM<EMAIL_ADDRESS>E  AdaptiveLaunch: writeToDataBase() 64: Meter aborted or could not get meter data for this run 2024-04-09 11:24:41.413  1299-1358  ANDR-PERF-LM<EMAIL_ADDRESS>W  FeatureState: writeState() 188: GameOptimization: State transition not allowed 2024-04-09 11:24:42.440  1299-6353  ANDR-PERF-LM<EMAIL_ADDRESS>E  AdaptiveLaunch: writeToDataBase() 64: Meter aborted or could not get meter data for this run 2024-04-09 11:24:44.800  1299-1358  ANDR-PERF-LM<EMAIL_ADDRESS>W  FeatureState: writeState() 188: GameOptimization: State transition not allowed 2024-04-09 11:24:45.012  1299-1358  ANDR-PERF-LM<EMAIL_ADDRESS>W  FeatureState: writeState() 188: GameOptimization: State transition not allowed 2024-04-09 11:24:46.051  1299-1358  ANDR-PERF-LM<EMAIL_ADDRESS>W  FeatureState: writeState() 188: GameOptimization: State transition not allowed 2024-04-09 11:24:48.988 17668-17668 BLEBoard                usap64                               E  Failed to send data, timeout                                                                                com.juul.kable.GattRequestRejectedException                                                                                at com.juul.kable.BluetoothDeviceAndroidPeripheral$write$$inlined$execute$1.invokeSuspend(Connection.kt:80)                                                                                at kotlin.coroutines.jvm.internal.BaseContinuationImpl.resumeWith(ContinuationImpl.kt:33)                                                                                at kotlinx.coroutines.DispatchedTask.run(DispatchedTask.kt:106)                                                                                at android.os.Handler.handleCallback(Handler.java:958)                                                                                at android.os.Handler.dispatchMessage(Handler.java:99)                                                                                at android.os.Looper.loopOnce(Looper.java:257)                                                                                at android.os.Looper.loop(Looper.java:368)                                                                                at android.os.HandlerThread.run(HandlerThread.java:67)

@grabbe-bryghtlabs thanks! I'll also need Kable logs leading up to the issue. With level Events or Data.

Thanks! The very first line of those logs show a write to a characteristic but then shortly after you see the exception from Kable stating that it received a descriptor response.
Is there any chance you can provide more of the logs leading up to the crash?
I'm trying to understand what data was sent to Android and what sequence Android is responding in. Thanks again.

This is after updating to 0.31.0

I have a vague suspicion that maybe you have two Peripheral objects for the same connection?
Can you look through how you're creating the peripheral and if there is a way you possible have multiple objects (rather than references to the same object).
I'm guessing that is why multiple I/O operations are occurring at once.
If you're having trouble isolating such a situation in your code, let me know, and I can add additional logging that will confirm/deny my suspicion.

The way it is built out we have a single scan job and one instance of a peripheral.  I don't think that would be the case.  If there is a way that I can provide more logging, please let me know.  I can run through the same scenario in an isolated environment this evening.

I have some theories of what might be going wrong. I'll try to add some necessary logging to validate soon. Thanks for being patient.

Just let me know what I can do.  I appreciate your attentiveness

I'm also finding this exception cropping up when using WithResponse

Just wanted to confirm that I've seen this happen to around 5 of our customers.
Fatal Exception: com.juul.kable.OutOfOrderGattCallbackException: Unexpected response type OnCharacteristicWrite received
       at com.juul.kable.BluetoothDeviceAndroidPeripheral.read(BluetoothDeviceAndroidPeripheral.kt:782)
       at com.juul.kable.BluetoothDeviceAndroidPeripheral$read$1.invokeSuspend(:15)
       at kotlin.coroutines.jvm.internal.BaseContinuationImpl.resumeWith(ContinuationImpl.kt:33)
       at kotlinx.coroutines.DispatchedTask.run(DispatchedTask.kt:104)
       at kotlinx.coroutines.internal.LimitedDispatcher$Worker.run(LimitedDispatcher.kt:111)
       at kotlinx.coroutines.scheduling.TaskImpl.run(Tasks.kt:99)
       at kotlinx.coroutines.scheduling.CoroutineScheduler.runSafely(CoroutineScheduler.kt:584)
       at kotlinx.coroutines.scheduling.CoroutineScheduler$Worker.executeTask(CoroutineScheduler.kt:811)
       at kotlinx.coroutines.scheduling.CoroutineScheduler$Worker.runWorker(CoroutineScheduler.kt:715)
       at kotlinx.coroutines.scheduling.CoroutineScheduler$Worker.run(CoroutineScheduler.kt:702)```

Our current setup has peripherals cached in a map by their advertisement identifier (mac address), so there shouldn't be a case where we are using the same peripheral in two different spots.

Just wanted to confirm that I've seen this happen to around 6 of our customers. There are several thousand using the latest build, so the volume is relatively low.
Fatal Exception: com.juul.kable.OutOfOrderGattCallbackException: Unexpected response type OnCharacteristicWrite received
       at com.juul.kable.BluetoothDeviceAndroidPeripheral.read(BluetoothDeviceAndroidPeripheral.kt:782)
       at com.juul.kable.BluetoothDeviceAndroidPeripheral$read$1.invokeSuspend(:15)
       at kotlin.coroutines.jvm.internal.BaseContinuationImpl.resumeWith(ContinuationImpl.kt:33)
       at kotlinx.coroutines.DispatchedTask.run(DispatchedTask.kt:104)
       at kotlinx.coroutines.internal.LimitedDispatcher$Worker.run(LimitedDispatcher.kt:111)
       at kotlinx.coroutines.scheduling.TaskImpl.run(Tasks.kt:99)
       at kotlinx.coroutines.scheduling.CoroutineScheduler.runSafely(CoroutineScheduler.kt:584)
       at kotlinx.coroutines.scheduling.CoroutineScheduler$Worker.executeTask(CoroutineScheduler.kt:811)
       at kotlinx.coroutines.scheduling.CoroutineScheduler$Worker.runWorker(CoroutineScheduler.kt:715)
       at kotlinx.coroutines.scheduling.CoroutineScheduler$Worker.run(CoroutineScheduler.kt:702)

Our current setup has peripherals cached in a map by their advertisement identifier (mac address), so there shouldn't be a case where we are using the same peripheral in two different spots. For what it's worth, our peripherals are generally connected to and disconnected from throughout the day. In either case, I can try to put some defense around our I/O operations. Would it be preferable to just reconnect the peripheral if this happens, or is this a recoverable scenario during a connection?

Not sure about your scenario, but I've had this come up when updating firmware on a BLE device and it gets bricked.  We have another process to force our firmware to update, but it's a bit cumbersome and it would be nice to figure out why it's happening and if I can do anything to guard against it.  We also have the peripheral in memory in a singleton.  For general calls I have things wrapped in a retry with delay.

I don't have a reliable way of reproducing this, but #749 should fix this (and it slated to be included in the upcoming 0.35.0 release).


Screenshot duplicates on a every test run

I create a simple test and run him several times
Test code
it('Load page corrctly', () => {
    cy.server();
    cy.route(/models\/\S+/).as('fetchMockData');

    cy.visit('/');
    cy.wait('@fetchMockData').its('status').should('eq', 200);

    cy.getByTestId('canvas').compareSnapshot('/compare/canvas');
});

All it's ok, but I saw in a project tree some screensots for this test

When I try to call cypress run I got this message
  (Screenshots)

  -  /tests/e2e/screenshots/open-page.spe      (689x688)
     c.js/compare/canvas-actual.png

and all files expect canvas-actual.png was deleted.
Cypress uses canvas-actual.png but a last generated file is canvas-actual (2).png.
Could you please explain how it works?

Also about additional files - filename (1/2 ...).png - can I  just add them to a .gitignore or I need call cypress run after every update my tests for removing these additional files?

@SchDen I have this same issue with duplicate filenames, but you closed this without mentioning a solution? 🤔

Hi @MattTreichelYeah , I just moved to https://github.com/meinaart/cypress-plugin-snapshots. It's easier to use

Yeah except cypress-plugin-snapshots is no longer maintained and relies on you having a pretty old cypress version installed.


qasm() mistranslate the operator QuantumCircuit.ecr

Environment

Qiskit Terra version: 0.36.1
Python version: 3.7.4
Operating system: Windows

What is happening?
The circuit shown below can be translated into OpenQASM successfully,but there exists two rzx gates.The one and only difference between two rzx gates is the parameter of rz gate,one is -pi/4,and another is pi/4.
Here is the error message.
OPENQASM 2.0;
include "qelib1.inc";
gate rzx(param0) q0,q1 { h q1; cx q0,q1; rz(-pi/4) q1; cx q0,q1; h q1; }
gate rzx(param0) q0,q1 { h q1; cx q0,q1; rz(pi/4) q1; cx q0,q1; h q1; }
gate ecr q0,q1 { rzx(pi/4) q0,q1; x q0; rzx(-pi/4) q0,q1; }
qreg q[2];
ecr q[0],q[1];

Traceback (most recent call last):
  File "20220518.py", line 8, in <module>
    another_circuit.from_qasm_str(qasm_str)
  File "D:\Anaconda3\lib\site-packages\qiskit\circuit\quantumcircuit.py", line 2334, in from_qasm_str
    return _circuit_from_qasm(qasm)
  File "D:\Anaconda3\lib\site-packages\qiskit\circuit\quantumcircuit.py", line 4667, in _circuit_from_qasm
    ast = qasm.parse()
  File "D:\Anaconda3\lib\site-packages\qiskit\qasm\qasm.py", line 53, in parse
    return qasm_p.parse(self._data)
  File "D:\Anaconda3\lib\site-packages\qiskit\qasm\qasmparser.py", line 1137, in parse
    self.parser.parse(data, lexer=self.lexer, debug=self.parse_deb)
  File "D:\Anaconda3\lib\site-packages\ply\yacc.py", line 333, in parse
    return self.parseopt_notrack(input, lexer, debug, tracking, tokenfunc)
  File "D:\Anaconda3\lib\site-packages\ply\yacc.py", line 1120, in parseopt_notrack
    p.callable(pslice)
  File "D:\Anaconda3\lib\site-packages\qiskit\qasm\qasmparser.py", line 612, in p_gate_decl_2
    self.update_symtab(program[0])
  File "D:\Anaconda3\lib\site-packages\qiskit\qasm\qasmparser.py", line 78, in update_symtab
    prev.file,
qiskit.qasm.exceptions.QasmError: "Duplicate declaration for gate 'rzx' at line 4, file .\nPrevious occurrence at line 3, file "

How can we reproduce the issue?
from qiskit import QuantumCircuit

circuit = QuantumCircuit(2)
circuit.ecr(0, 1)
qasm_str = circuit.qasm()
print(qasm_str)
another_circuit = QuantumCircuit(2)
another_circuit.from_qasm_str(qasm_str)
print(another_circuit)

What should happen?
An expected OpenQASM code about QuantumCircuit.ecr is something like this.
gate rzx(param0) q0,q1 { h q1; cx q0,q1; rz(param0) q1; cx q0,q1; h q1; }
gate ecr q0,q1 { rzx(pi/4) q0,q1; x q0; rzx(-pi/4) q0,q1; }

Any suggestions?
No response

Thanks for the report.  Sorry this is a bit bugged out - we have some problems with the OQ 2 exporter when dealing with gates that can take arbitrary parameters but are only used with exact angles, as you've seen.
I unfortunately can't promise that this will be a top priority for the internal team because we're busy with a lot of new features for OpenQASM 3.0 support, but we'd be happy to accept PRs from other people about this issue.

I have a fix for this which is just to include RZX as an atomic gate in qelib1.inc. Is this a suitable approach?

For linking purposes, I gave the reason we can't add rzx to qelib1.inc here https://github.com/Qiskit/qiskit-terra/pull/8534#pullrequestreview-1074567054.


From_sql_queryable_simple_projection_composed isn't portable

It sends the following SQL:
SELECT *
FROM Products
WHERE Discontinued <> 1
AND ((UnitsInStock + UnitsOnOrder) < ReorderLevel)

PostgreSQL issues:

Identifiers must be quoted (to preserve case)
Discontinued is a bool, which needs to be checked with = TRUE

The first is easy enough, for the second you can either remove the WHERE clause altogether, or expose an overridable property that would provide the SQL.

Duplicate of #9228


Redis tableName should be case-sensitive

When configuring Redis tableName option, upper-case chars are automatically treated as lower-case, so only lower-case keys are found when querying the table.
For example, I have 2 keys in Redis:

Test:1 with value 1
test:2 with value 2

redis/test.json
{
    "tableName": "Test",
    "schemaName": "default",
    "key": {
        "dataFormat": "raw",
        "fields": [
            {
                "name": "id",
                "mapping": "5",
                "type": "VARCHAR"
            }
        ]
    },
    "value": {
        "dataFormat": "raw",
        "fields": [
            {
                "name": "col",
                "type": "VARCHAR"
            }
        ]
    }
}

redis.properties
connector.name=redis
redis.table-names=Test
redis.database-index=0
redis.nodes=localhost:6379
redis.key-prefix-schema-table=true

Query
SELECT * FROM redis.default.test;

Problem: Only the second (lower-case) key will be returned.
Presto v334
Redis v4.0.11

Currently, all schema, table and column names in Presto are always lowercase.
We are working on getting this right under https://github.com/prestosql/presto/issues/17.
Before that is completed, there is unfortunately no way to access redis "tables" that differ in case only.
If the name is not in lower-case, and an all-lower-case name does not exist, it is still possible to do a match,
and we do so in a bunch of connectors (probably not in Redis).


increased mitochondrial DNA content

Add new term:
increased mitochondrial DNA content (child of abnormal mitochondrial chromosome morphology MP:0011638)
DEF: greater than expected amount of DNA contained within the mirochondria of a eukaryotic cell
SYN: increased mitochondrial genome size
SYN: increased mtDNA amount
SYN: increased mtDNA content
SYN: increased mitochondrial DNA level

Added increased mitochondrial DNA content MP:0030937 and all synonyms suggested above.


I am installing Apache-Superset after installation getting this error

I installed apache-superset and when try to initialize the db with command superset db upgrade I prompts this error how can I resolve this issue? I also asked  on stackoverflow  but since yesterday no one answered please help.
Traceback (most recent call last):
  File "c:\users\user\appdata\local\programs\python\python37\lib\runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "c:\users\user\appdata\local\programs\python\python37\lib\runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "C:\Apache\apache\Scripts\superset.exe\__main__.py", line 4, in <module>
  File "C:\Apache\apache\lib\site-packages\superset\__init__.py", line 18, in <module>
    from flask import current_app, Flask
  File "C:\Apache\apache\lib\site-packages\flask\__init__.py", line 14, in <module>
    from jinja2 import escape
  File "C:\Apache\apache\lib\site-packages\jinja2\__init__.py", line 12, in <module>
    from .environment import Environment
  File "C:\Apache\apache\lib\site-packages\jinja2\environment.py", line 25, in <module>
    from .defaults import BLOCK_END_STRING
  File "C:\Apache\apache\lib\site-packages\jinja2\defaults.py", line 3, in <module>
    from .filters import FILTERS as DEFAULT_FILTERS  # noqa: F401
  File "C:\Apache\apache\lib\site-packages\jinja2\filters.py", line 13, in <module>
    from markupsafe import soft_unicode
ImportError: cannot import name 'soft_unicode' from 'markupsafe' (C:\Apache\apache\lib\site-packages\markupsafe\__init__.py)

Closing this as it's a help request rather than a bug report. Not to diminish your problem though, I'd be happy to move this to a Q&A discussion if you'd like, or I welcome you to bring the conversation to the #debug-together channel on Slack


Object stops despite bounce set to 1 when Continuous CD is on

Godot version
4.1
System information
Windows 11
Issue description
When Continuous CD is on, object stops despite bounce 1:
https://youtu.be/bsOe_VxWv2M
Steps to reproduce
Open project
Minimal reproduction project
Godot_continuous_cd.zip

Couldn't see an issue in the MRP.

After hitting the ball against the wall, it loses all speed and does not bounce.
https://drive.google.com/file/d/1D4BywwfueCxzpjoKjTiGctCnvawV8Uhr/view?usp=sharing

I actually ran into this myself. I've got a small repro project here: https://www.dropbox.com/scl/fi/ulr35fwrx8czgqhhpawgd/break-it.zip?rlkey=r8r5bme76g6y33g8aaa21lh6b&dl=0. Press space to launch the ball and notice the velocity changes on bounce despite the bounce value being set to 1. I've also toggled off CCD in which case the velocity is maintained but the ball can penetrate through the walls.
I'm going to try digging into the code myself but I am not sure what I'm looking for so no guarantees I can actually find a fix for it.


Preview content doesn't scroll with CodeEditor, "Sticky Preview"

This is due to a recent change that made it so the CodeEditor doesn't scroll with overflow. This is fine, but the preview content should move with the code editor, otherwise you can't code and see the preview at the same time
In this video, the preview should follow the user as they scroll down the page (be "sticky")
https://github.com/user-attachments/assets/a1e7d2ed-0991-4549-aa5f-40a83d8b9395

fixed


add updated zipformer onnx export

#1094

[x] nonstreaming onnx export (export-onnx.py)
[x] onnx_pretrained.py
[x] streaming onnx export (export-onnx-streaming.py)
[x] onnx_pretrained-streaming.py

@kakashidan
Please see https://github.com/kakashidan/icefall/pull/1

@kakashidan
Please see kakashidan#1

OK. I've merged the PR and checked that nonstreaming onnx version works well.

All good for some files, not so good for others, something with factor 2 subsampling:
onnxruntime.capi.onnxruntime_pybind11_state.RuntimeException: [ONNXRuntimeError] : 6 : RUNTIME_EXCEPTION : Non-zero status code returned while running Reshape node. Name:'/encoder/encoders.1/downsample/Reshape' Status Message: /onnxruntime_src/onnxruntime/core/providers/cpu/tensor/reshape_helper.h:40 onnxruntime::ReshapeHelper::ReshapeHelper(const onnxruntime::TensorShape&, onnxruntime::TensorShapeVector&, bool) gsl::narrow_cast<int64_t>(input_shape.Size()) == size was false. The input tensor cannot be reshaped to the requested shape. Input shape:{293,101,256}, requested shape:{147,2,101,256}

All good for some files, not so good for others, something with factor 2 subsampling:
onnxruntime.capi.onnxruntime_pybind11_state.RuntimeException: [ONNXRuntimeError] : 6 : RUNTIME_EXCEPTION : Non-zero status code returned while running Reshape node. Name:'/encoder/encoders.1/downsample/Reshape' Status Message: /onnxruntime_src/onnxruntime/core/providers/cpu/tensor/reshape_helper.h:40 onnxruntime::ReshapeHelper::ReshapeHelper(const onnxruntime::TensorShape&, onnxruntime::TensorShapeVector&, bool) gsl::narrow_cast<int64_t>(input_shape.Size()) == size was false. The input tensor cannot be reshaped to the requested shape. Input shape:{293,101,256}, requested shape:{147,2,101,256}

Are you testing the non-streaming version? Could you share the complete command the the wave you are using?

 I suppose it depends on feature length, it can not divide by 2 if file lenght is odd.

How long is your test wave?  I suppose it depends on feature length, it can not divide by 2 if file lenght is odd.

I reproduced the same problem when I use some other audios. I'll check why this could happened

Please find the fix in #965
It can save your life.

I tested it, it worked for most files, but on some I also have the issue above with the reshaping error.
I patched the zipformer.py file, but I still get the error on some files. (the broken files are all over 30s).
It does not require retraining, right, just the patch before the export ?

@csukuangfj thanks a lot, looks better now!
@joazoa looks like another IF construction in the code needs proper handling

(the broken files are all over 30s).

@joazoa  Are you still having this error after applying the changes from #965

@kakashidan
Please follow
https://github.com/k2-fsa/icefall/blob/c0de78d3c0ea04a08d849e37a8e22ff48a5e087a/egs/librispeech/ASR/pruned_transducer_stateless7/zipformer.py#L904-L913
to change
https://github.com/k2-fsa/icefall/blob/c0de78d3c0ea04a08d849e37a8e22ff48a5e087a/egs/librispeech/ASR/zipformer/zipformer.py#L1304
max_len limits the input audio length.
(Please replace is_jit_tracing() with torch.jit.is_tracing())

may be better to recreate it each time, in scripting mode?
On Tuesday, June 6, 2023, danfu @.***> wrote:

@.**** commented on this pull request.
In egs/librispeech/ASR/zipformer/zipformer.py
https://github.com/k2-fsa/icefall/pull/1108#discussion_r1218828685:

@@ -1305,6 +1305,12 @@ def init(
) -> None:
"""Construct a CompactRelPositionalEncoding object."""
super(CompactRelPositionalEncoding, self).init()

   if torch.jit.is_tracing:

       # 10k frames correspond to ~100k ms, e.g., 100 seconds, i.e.,

OK
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may be better to recreate it each time, in scripting mode?
…
On Tuesday, June 6, 2023, danfu @.> wrote: @.* commented on this pull request. ------------------------------ In egs/librispeech/ASR/zipformer/zipformer.py <#1108 (comment)>: > @@ -1305,6 +1305,12 @@ def init( ) -> None: """Construct a CompactRelPositionalEncoding object.""" super(CompactRelPositionalEncoding, self).init() + if torch.jit.is_tracing: + # 10k frames correspond to ~100k ms, e.g., 100 seconds, i.e., OK — Reply to this email directly, view it on GitHub <#1108 (comment)>, or unsubscribe https://github.com/notifications/unsubscribe-auth/AAZFLO5PQVANSAVFIIHEZK3XJ2QMBANCNFSM6AAAAAAYWJ4VSQ . You are receiving this because you are subscribed to this thread.Message ID: @.***>

Yes, it is feasible for torch.jit.script(), but for torch.jit.is_tracing(), it can trace only what it sees during the execution.
For instance, if there is an if ... else statement, then only one branch is kept during the trace; the other is discarded and does not exist in the final exported model.

From https://pytorch.org/docs/stable/onnx.html#torch.onnx.export,

If model is not a torch.jit.ScriptModule nor a torch.jit.ScriptFunction, this runs model once in order to convert it to a TorchScript graph to be exported (the equivalent of torch.jit.trace()). Thus this has the same limited support for dynamic control flow as torch.jit.trace().

I just tried to pass a torch.jit.script() model to torch.onnx.export() so that it won't use torch.jit.trace() internally.
However, it throws the following error:
Traceback (most recent call last):
  File "./zipformer/export-onnx.py", line 621, in <module>
    main()
  File "/star-fj/fangjun/py38/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 28, in decorate_context
    return func(*args, **kwargs)
  File "./zipformer/export-onnx.py", line 563, in main
    export_encoder_model_onnx(
  File "./zipformer/export-onnx.py", line 301, in export_encoder_model_onnx
    torch.onnx.export(
  File "/star-fj/fangjun/py38/lib/python3.8/site-packages/torch/onnx/__init__.py", line 316, in export
    return utils.export(model, args, f, export_params, verbose, training,
  File "/star-fj/fangjun/py38/lib/python3.8/site-packages/torch/onnx/utils.py", line 107, in export
    _export(model, args, f, export_params, verbose, training, input_names, output_names,
  File "/star-fj/fangjun/py38/lib/python3.8/site-packages/torch/onnx/utils.py", line 724, in _export
    _model_to_graph(model, args, verbose, input_names,
  File "/star-fj/fangjun/py38/lib/python3.8/site-packages/torch/onnx/utils.py", line 497, in _model_to_graph
    graph = _optimize_graph(graph, operator_export_type,
  File "/star-fj/fangjun/py38/lib/python3.8/site-packages/torch/onnx/utils.py", line 151, in _optimize_graph
    torch._C._jit_pass_lower_all_tuples(graph)
RuntimeError: tuple index with non-constant index

Here are my changes by modifying the latest commit of this PR up to now:
diff --git a/egs/librispeech/ASR/zipformer/export-onnx.py b/egs/librispeech/ASR/zipformer/export-onnx.py
index fea669f..5bc1dac 100755
--- a/egs/librispeech/ASR/zipformer/export-onnx.py
+++ b/egs/librispeech/ASR/zipformer/export-onnx.py
@@ -296,6 +296,8 @@ def export_encoder_model_onnx(
     x = torch.zeros(1, 100, 80, dtype=torch.float32)
     x_lens = torch.tensor([100], dtype=torch.int64)

+    encoder_model = torch.jit.script(encoder_model)
+
     torch.onnx.export(
         encoder_model,
         (x, x_lens),
diff --git a/egs/librispeech/ASR/zipformer/zipformer.py b/egs/librispeech/ASR/zipformer/zipformer.py
index 85ebdb5..08f3784 100644
--- a/egs/librispeech/ASR/zipformer/zipformer.py
+++ b/egs/librispeech/ASR/zipformer/zipformer.py
@@ -1305,7 +1305,7 @@ class CompactRelPositionalEncoding(torch.nn.Module):
     ) -> None:
         """Construct a CompactRelPositionalEncoding object."""
         super(CompactRelPositionalEncoding, self).__init__()
-        if torch.jit.is_tracing:
+        if torch.jit.is_tracing():
             # 10k frames correspond to ~100k ms, e.g., 100 seconds, i.e.,
             # It assumes that the maximum input won't have more than
             # 10k frames.

Just managed to use torch.jit.script() to export the positional encoding module, while the remaining modules are exported using torch.jit.trace().
Please see https://github.com/kakashidan/icefall/pull/2

Now the exported model does not constrain the length of the input wave. The only constraint is user's RAM.

@csukuangfj @kakashidan Any update regarding exporting streaming version?

@csukuangfj @kakashidan Any update regarding exporting streaming version?

I think it is almost finished, right? @kakashidan

Hello and sorry for the late update:
I got it master to work with icefall and with sherpa-onnx-python.
sherpa-onnx - C  worked with the initial patches on this issue  (but could not deal with audio over 18s).
The master branch does not work for  sherpa-onnx - C , the new ones fail with Unsupported model_type: zipformer2. (reported here: https://github.com/k2-fsa/sherpa-onnx/issues/174 , just wanted to point out that the initial new zipformer patches caused no problems for sherpa-onnx, but the merge in master has).
I also tried it with triton, but ran into some issues with "model 'encoder', configuration expects 5 inputs, model provides 2 for offline model and 102 / 99 in case of streaming model.
Should triton work with the existing export script or does it require an additional triton flag ? (I saw some of the other export scripts have a separate function for triton export, but i think for ziperformer 2 this is not needed)
Would anybody have a template for the triton zipformer2 config that I can try ?

the new ones fail with Unsupported model_type: zipformer2. (reported here: https://github.com/k2-fsa/sherpa-onnx/issues/174

The streaming zipformer2 has not been supported in sherpa-onnx yet.
But the non-streaming zipformer2 should already have been supported in sherpa-onnx without any code changes from the sherpa-onnx side.

just wanted to point out that the initial new zipformer patches caused no problems for sherpa-onnx, but the merge in master has

Could you show the error log? Are you referring to the streaming version or non-streaming version?

For the triton part, @yuekaizhang could you have a look?

I did a fresh install of k2, icefall, sherpa-onnx, exported the large non streaming zipformer2 with librispeech/ASR/zipformer/export-onnx.py
When i use sherpa-onnx i get this error:
Creating recognizer ...
/home/sherpa-onnx/sherpa-onnx/csrc/offline-recognizer-impl.cc:Create:88
Unsupported model_type: zipformer2
We support only the following model types at present:

Non-streaming transducer models from icefall
Non-streaming Paraformer models from FunASR
EncDecCTCModelBPE models from NeMo

zipformer/onnx_pretrained.py works fine.

@joazoa

I did a fresh install of k2, icefall, sherpa-onnx, exported the large non streaming zipformer2 with librispeech/ASR/zipformer/export-onnx.py

It should be fixed in https://github.com/k2-fsa/sherpa-onnx/pull/180
Could you update your sherpa-onnx and try it again?
(You need to re-compile your sherpa-onnx after updating the code)

Wow you are fast! I can confirm that this is now fixed.

@yuekaizhang  This is the error when i try triton with the zipformer2: (I used the script for the old zipformer offline).
Traceback (most recent call last):
File "./client.py", line 665, in
asyncio.run(main())
File "/usr/lib/python3.8/asyncio/runners.py", line 44, in run
return loop.run_until_complete(main)
File "/usr/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete
return future.result()
File "./client.py", line 610, in main
ans_list = await asyncio.gather(*tasks)
File "./client.py", line 354, in send
response = await triton_client.infer(
File "/usr/local/lib/python3.8/dist-packages/tritonclient/grpc/aio/init.py", line 677, in infer
raise_error_grpc(rpc_error)
File "/usr/local/lib/python3.8/dist-packages/tritonclient/grpc/_utils.py", line 62, in raise_error_grpc
raise get_error_grpc(rpc_error) from None
tritonclient.utils.InferenceServerException: [StatusCode.INTERNAL] in ensemble 'transducer', onnx runtime error 1: Non-zero status code returned while running Where node. Name:'/encoder/0/layers.0/self_attn_weights/Wher$
' Status Message: /encoder/0/layers.0/self_attn_weights/Where: condition operand cannot broadcast on dim 2 Condition Shape: {1,1,137}, X Shape: {}, Y Shape: {4,1,496,496}

@yuekaizhang This is the error when i try triton with the offline zipformer2: (I used the script for the old zipformer offline). Traceback (most recent call last): File "./client.py", line 665, in asyncio.run(main()) File "/usr/lib/python3.8/asyncio/runners.py", line 44, in run return loop.run_until_complete(main) File "/usr/lib/python3.8/asyncio/base_events.py", line 616, in run_until_complete return future.result() File "./client.py", line 610, in main ans_list = await asyncio.gather(*tasks) File "./client.py", line 354, in send response = await triton_client.infer( File "/usr/local/lib/python3.8/dist-packages/tritonclient/grpc/aio/init.py", line 677, in infer raise_error_grpc(rpc_error) File "/usr/local/lib/python3.8/dist-packages/tritonclient/grpc/_utils.py", line 62, in raise_error_grpc raise get_error_grpc(rpc_error) from None tritonclient.utils.InferenceServerException: [StatusCode.INTERNAL] in ensemble 'transducer', onnx runtime error 1: Non-zero status code returned while running Where node. Name:'/encoder/0/layers.0/self_attn_weights/Wher$ ' Status Message: /encoder/0/layers.0/self_attn_weights/Where: condition operand cannot broadcast on dim 2 Condition Shape: {1,1,137}, X Shape: {}, Y Shape: {4,1,496,496}

I think we have not confirmed and tested zipformer2 yet. @wd929, right?
For zipformer (statless7) triton recipe, you may try this latest one https://github.com/k2-fsa/sherpa/blob/master/triton/scripts/build_librispeech_pruned_transducer_stateless7_offline.sh.
I am expecting the recent changes of zipformer related onnx codes would not trigger errors in the triton recipe.

That is the script I used to export the offline zipformer2.
I only changed these:
ENCODER_LAYERS=2,2,4,5,4,2
ENCODER_DIM=512
CNN_MODULE_KERNEL=31,31,15,15,15,31
the client works (for the same offline model)  when i add --streaming --chunk_size 32
When i remove the streaming, i get the error above.

That is the script I used to export the offline zipformer2. I only changed these: ENCODER_LAYERS=2,2,4,5,4,2 ENCODER_DIM=512 CNN_MODULE_KERNEL=31,31,15,15,15,31
the client works (for the same offline model) when i add --streaming --chunk_size 32 When i remove the streaming, i get the error above.

I think this recipe is for offlien ASR. It should not work with --streaming options. We or someone who are interested would make a PR to support zipformer2 offline ASR with a script build_librispeech_zipformer2_offline.sh.

Yes, the recipe is for the offline. Weirdly, the client works with the offline model in streaming mode but not in offline mode.


Add a verified badge to a user if the user .chain name/akAddress is gotten from superhero wallet

This is quite different from #172

I changed avatars logic and now user without wallet, but with ak or .chain name wont have avatar.
But user with wallet and the same name will. So, we dont need bage anymore.

Found bug. walletSynced prop is not enough for verifying users, we should use one more parameter.


Static auto completion fix #262

Problems hide in extracting HaxeVarDefenition part (no field information except name) from HaxeVarDefenition instead returning original  HaxeVarDefenition (needs only for name and statc check) HaxeResolveUtil.getNamedSubComponents.
https://github.com/TiVo/intellij-haxe/issues/262

@romanmikhailov,  Hi! and thanks for your help.  I must be missing something, though, because this change seems to introduce a boolean variable that is set to true in all cases, and checked once (if ( && ...)).  Since it is always true, there is no functionality change that I can see.  Can you explain how this change fixes the problem?

Exuse my mistake. Not full push.

Hi Roman! Thanks for help, are you sure that it's a fix for #262? Because it was reported that completion for methods was not shown. Your fix seems to be related to fields.

@as3boyan Hi. It's fix for both methods and fields autocompletion.

Closed as already implemented in https://github.com/TiVo/intellij-haxe/pull/265


(GH-177) Add open command

Description
To allow the re-opening of a milestone, that might have been closed as
part of an aborted release.  This will help with the exercising of the
integration tests for GitReleaseManager.
Related Issue
Fixes #177
Motivation and Context
Adding this command allows for reverting an action that can be done by GRM.  In the same way that we can discard a created release, we can now re-open a closed milestone.
How Has This Been Tested?
Tested on Friday Lunch Time Stream, using the FakeRepository on the GitTools Organisation.
Screenshots (if appropriate):
Checklist:

[x] My code follows the code style of this project.
[x] My change requires a change to the documentation.
[ ] I have updated the documentation accordingly.
[x] I have read the CONTRIBUTING document.
[ ] I have added tests to cover my changes.
[ ] All new and existing tests passed.

@gep13 your changes have been merged, thanks for your contribution 👍


doc: drop the --production flag for installing windows-build-tools

Checklist

[x] documentation is changed or added
[x] commit message follows commit guidelines

Description of change

Drop --production from the install instructions for windows-build-tools. The --production flag isn't needed here, as "not installing devDependencies" is already implied when npm installing a module by name.
(This was probably copy-pasted a while ago from windows-build-tools' README.md, which has since been updated to drop the --production flag from its install instructions: https://github.com/felixrieseberg/windows-build-tools/commit/4420dc848b74cdc70784ce00a1253d10465b1cb0)

Why should we still recommend Windows Build Tools?  It’s current release installs legacy Python reached its end of life On 1/1/2020 (242 days ago).  The Microsoft Store install of Python is a much better/safer/easier way to go and it will auto update like when Python 3.9 is released next month.

Hmm. As I see it, windows-build-tools is a one-liner on the command-line to get Visual Studio Build Tools. Much easier than tracking down the installer and selecting the right components. (It's surprisingly easy to not select the right ones/difficult to get it right).
It's also the only obvious way to get Visual Studio older than 2019 at the moment, that I'm aware of. Some projects hit corner cases and bugs with Visual Studio 2019 and need the older 2017 or 2015 that one can get with windows-build-tools.
As a Windows user, I'm much more interested in the C++ compiler toolchain (from Visual Studio). Python installation is coincidentally included, but if it could be disabled in windows-build-tools I personally would disable it. For what it's worth: If you already have Python 2.7 on your system, it usually skips installing another copy.

merged @ e98bb16


Why is there a difference between the VolRecon and SparseNeus when computing "iter_cos" from "true_cos" in renderer.py?

Hi, thanks for your great work!
I understand why true_cos in your implementaion is $-1$ because of SRDF.
ButI notice that, in your implementation, iter_cos in $renderer.py$ equals $1.5\cdot$true_cos when cos_anneal_ratio is equal to $1$, but $\cdot 1.5$ exceeds the upper bound of the cos function, which is different from implementation between NeuS and SparseNeus. I wonder if there are some reasons why you designed this.
Looking forward to your reply!
Note:
In VolRecon:
iter_cos = -(-true_cos * 0.5 + 0.5 * (1.0 - cos_anneal_ratio) - true_cos * cos_anneal_ratio)

In SparseNeus & NeuS:
iter_cos = -(F.relu(-true_cos * 0.5 + 0.5) * (1.0 - cos_anneal_ratio) + F.relu(-true_cos) * cos_anneal_ratio)

Hi, thanks for pointing this out! this looks like a bug. we will look into that. you can use the code from NeuS.