MIAD-198 /bulk-alerts (select alert) screen

MIAD-198

Codecov Report
Attention: Patch coverage is 97.61905% with 3 lines in your changes missing coverage. Please review.

Project coverage is 90.61%. Comparing base (762b054) to head (602f787).

Files with missing lines
Patch %
Lines

server/middleware/journeyStateMachine.ts
84.61%
2 Missing :warning:

...erver/middleware/redirectCheckAnswersMiddleware.ts
95.83%
1 Missing :warning:

Additional details and impacted files
@@            Coverage Diff             @@
##             main     #111      +/-   ##
==========================================
+ Coverage   90.12%   90.61%   +0.48%
==========================================
  Files          71       79       +8
  Lines        1702     1822     +120
  Branches      260      284      +24
==========================================
+ Hits         1534     1651     +117
- Misses        164      167       +3
  Partials        4        4

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


Rasa installation error

Rasa Core version: Latest
Python version: 3.7
Operating system (windows, osx, ...): MacOS Mojave
Issue:
I am trying to install rasa_core but I get this error:
Collecting tensorflow==1.10.0 (from rasa_core->-r requirements.txt (line 10))
  Could not find a version that satisfies the requirement tensorflow==1.10.0 (from rasa_core->-r requirements.txt (line 10)) (from versions: )
No matching distribution found for tensorflow==1.10.0 (from rasa_core->-r requirements.txt (line 10))

😕
Can you please tell me what to do?

Solution:
Uninstall Python 3.7 and install any 3.6 distribution.
Tensorflow does not offer a package for 3.7 yet. 😕


docs: fix documentation error

The example given for the stages option was incorrectly formatted and this caused a production bug for us because we used include: instead of stages:! 😄

 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.


How to use FilterLoggerFactory as default ILoggerFactory

I would like to use FilterLoggerFactory as the default ILoggerFactory. I see there is a WithFilter extension method that returns the FilterLoggerFactory but it will not affect the ILoggerFactory registered with DI.
Where is the right place to configure FilterLoggerFactory as the default? I'm thinking it would be with the
WebHostBuilder
public static void Main(string[] args)
{
    var host = new WebHostBuilder()
        .UseKestrel()
        .UseContentRoot(Directory.GetCurrentDirectory())
        .UseLoggerFactory(new FilterLoggerFactory(new LoggerFactory(), new FilterLoggerSettings()))
        .UseStartup<Startup>()
        .Build();

    host.Run();
}

Also, what's the guidance on directly accessing APIs in that have "Internal" in the namespace? In this case Microsoft.Extensions.Logging.Filter.Internal.FilterLoggerFactory.

You could do
public static void Main(string[] args)
{
    var host = new WebHostBuilder()
        .UseKestrel()
        .UseContentRoot(Directory.GetCurrentDirectory())
        .UseLoggerFactory(new LoggerFactory().WithFilter(new FilterLoggerSettings()))
        .UseStartup<Startup>()
        .Build();

    host.Run();
}

In that way you won't access the "internal" class. An alternative is to do it in ConfigureServices:
services.AddSingleton(new LoggerFactory().WithFilter(new FilterLoggerSettings()));

I'm personally not a fan of either of these methods. I would prefer either some way to set it up either

In connection to the call to services.AddLogging() (e.g. services.AddLogging().WithFilter(...) or services.AddLogging(new FilterLoggerSettings()))
Or in Configure(...), while adding loggers (i.e. a method on ILoggerFactory).

The first suggestion is probably the easiest to implement given the current implementation.

Thanks @SimonTouchtech. I really like the:
.UseLoggerFactory(new LoggerFactory().WithFilter(new FilterLoggerSettings()))

I think the suggestion:
services.AddSingleton(new LoggerFactory().WithFilter(new FilterLoggerSettings()));

will not be picked up by the web host since it already created its logger so the filtering will not take effect there.
I'm going to keep the issue open to see if I can get some guidance on the usage of classes in the "Internal" namespace.


#405 - Laravel 11 upgrade

In this PR I have:

updated all dependencies including Laravel to new main version
reorganize app directories
reorganize Laravel structures

Note: we are still waiting for rackbeat/laravel-ui-avatars (https://github.com/Rackbeat/laravel-ui-avatars/pull/15) to update their package. Probably we need to discuss how to handle this here (get rid of the package, use Github replacement or wait).
This should close #405.

With last commit I removed rackbeat/laravel-ui-avatars. I replace it with really simple custom class.

@EwelinaSkrzypacz
If you run app in dev mode (npm run dev), open app via http not https.
If you run app in prod mode (npm run build) https should works.

On dev env I open app via http
On beta env I do nothing - just I made deploy

@EwelinaSkrzypacz
Looks like beta is working after configuring trusted proxies middleware.

Thanks, beta is working right now - I can login and click through application.
But I have one problem - I can't create request (on local env and beta env) because I see 401 error in dev console. It's like request types don't fetch


uproxy ui needs scrollbars (windows, linux, chromebook)

"LEARN MORE ABOUT UPROXY" is not showing up (in frame) when it build in windows

Fixed by #822


Typos and readability suggestions

Thanks so much for this library! And thank you for great documentation! I sat down this evening and enjoyed what I was reading so much that I figured I might as well take a moment to help improve the guide, especially since a pair of fresh eyes are the best way to find little typos and such.  Feel free to revert any of my suggestions, as I know some of them might be considered just an English style choice.

Thank you so much; that's an outstanding contribution to our doc!


Verbose output: KeyError (interface needs to be added)

When having the verbose output enabled I ran into an issue in https://github.com/svenevs/exhale/blob/master/exhale/graph.py#L458. self.kind was interface but this wasn't present in fmt_spec so fmt_spec[self.kind] was giving a KeyError. Better check for that since it's "only" a debug message.

Ahhhh yes interface, the forgotten child.  To be honest I never expected Exhale to be able to support anything but C++, but apparently you've had some potential success with PHP as well as another user with Verilog.
Adding support for .. doxygeninterface:: shouldn't be super difficult, I just need to treat it like "class" and "struct".  I was avoiding some pesky issues with Exhale because I thought I would be able to finish a more hefty rewrite of something but I'm fixing the pesky issues first now, so I'll throw this one in there.  I'll want to fix #28 first though.
I know zero PHP, do you have some brief sample code that demonstrates an interface?  If not I'll add some ugly Java code for the interface test case (ugly because it's been at least 6 years since I've done any Java...).

This is an example of an interface class in PHP:
<?php
/**
 * Magento
 *
 * NOTICE OF LICENSE
 *
 * This source file is subject to the Open Software License (OSL 3.0)
 * that is bundled with this package in the file LICENSE.txt.
 * It is also available through the world-wide-web at this URL:
 * http://opensource.org/licenses/osl-3.0.php
 * If you did not receive a copy of the license and are unable to
 * obtain it through the world-wide-web, please send an email
 * to<EMAIL_ADDRESS>so we can send you a copy immediately.
 *
 * DISCLAIMER
 *
 * Do not edit or add to this file if you wish to upgrade Magento to newer
 * versions in the future. If you wish to customize Magento for your
 * needs please refer to http://www.magento.com for more information.
 *
 * @category    Mage
 * @package     Mage_Api
 * @copyright  Copyright (c) 2006-2017 X.commerce, Inc. and affiliates (http://www.magento.com)
 * @license    http://opensource.org/licenses/osl-3.0.php  Open Software License (OSL 3.0)
 */

/**
 * Web service api server interface
 *
 * @category   Mage
 * @package    Mage_Api
 * @author     Magento Core Team<EMAIL_ADDRESS> */
interface Mage_Api_Model_Server_Adapter_Interface
{
    /**
     * Set handler class name for webservice
     *
     * @param string $handler
     * @return Mage_Api_Model_Server_Adapter_Interface
     */
    function setHandler($handler);

    /**
     * Retrive handler class name for webservice
     *
     * @return string
     */
    function getHandler();

    /**
     * Set webservice api controller
     *
     * @param Mage_Api_Controller_Action $controller
     * @return Mage_Api_Model_Server_Adapter_Interface
     */
    function setController(Mage_Api_Controller_Action $controller);

    /**
     * Retrive webservice api controller
     *
     * @return Mage_Api_Controller_Action
     */
    function getController();

    /**
     * Run webservice
     *
     * @return Mage_Api_Model_Server_Adapter_Interface
     */
    function run();

    /**
     * Dispatch webservice fault
     *
     * @param int $code
     * @param string $message
     */
    function fault($code, $message);

} // Class Mage_Api_Model_Server_Adapter_Interface End

Hey @glamic-ep sorry for forgetting about this.  Thank you for the example PHP snippet!
If I recall correctly, you are no longer planning on using Exhale, you intend to customize the Doxygen HTML?  I was able to get some minimal Fortran support, but for PHP I'd need to actually be a lot more careful about certain things after looking more closely at the language.
If you aren't planning on using Exhale, I will solve this at a much later date.  If you are, then I can add some temporary hacks in just to make it work.

Yes, correct, I have now gone down the Doxygen route. That means there is no immediate need for me to have customized/updated anything. Thanks for your help.

I fall into the same bug and created MR #84

/// @example

Results into
(!) Exhale: could not generate reStructuredText documents :/Traceback (most recent call last):
  File "c:\python39\lib\site-packages\exhale\__init__.py", line 25, in environment_ready
    deploy.explode()
  File "c:\python39\lib\site-packages\exhale\deploy.py", line 423, in explode
    textRoot.toConsole()
  File "c:\python39\lib\site-packages\exhale\graph.py", line 3823, in toConsole
    self.consoleFormat(
  File "c:\python39\lib\site-packages\exhale\graph.py", line 3880, in consoleFormat
    l.toConsole(0, fmt_spec)
  File "c:\python39\lib\site-packages\exhale\graph.py", line 543, in toConsole
    c.toConsole(level + 1, fmt_spec)
  File "c:\python39\lib\site-packages\exhale\graph.py", line 516, in toConsole
    kind=utils._use_color(self.kind, fmt_spec[self.kind], sys.stderr),
KeyError: 'example'


Teardown Lnd Volumes

Pull Request Test Coverage Report for Build 710419690

6 of 6 (100.0%)  changed or added relevant lines in 1 file are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+0.3%) to 81.525%

Totals

Change from base Build 710387426:
0.3%

Covered Lines:
278

Relevant Lines:
341

💛  - Coveralls


Orientation aware

I had to disable this bit to actually get correct width / height
  // Sets screen width and height
    // if (orientation == Orientation.portrait) {
    width = boxConstraints.maxWidth;
    height = boxConstraints.maxHeight;
    // } else {
    //   width = boxConstraints.maxHeight;
    //   height = boxConstraints.maxWidth;
    // }

AS far as I know then LayoutBuilder is orientation aware...ie width is always width and you should not artificially change it.

Thanks for bringing this issue up. This will be fixed on the next version.

Thanks for bringing this up to me. The width and height parameters are used for calculating Adaptive.w and Adaptive.h. I've renamed both of them to adaptiveWidth and adaptiveHeight. This issue is now fixed in the latest version (^2.0.1). width and height parameters are now set with the correct width and height.

if anyone is interested in orientation aware sizer: https://pub.dev/packages/flutter_sizer/versions/1.0.0

@radvansky-tomas Its a really good package. Congrats :tada:
Would it be ok to use some of your improvements in your package? I'm going to experiment with your .dp implementation.

@CoderUni Of course ;) use what you can...I spent couple hours investigating good .dp option...best option would be to use less "magic" numbers...but I could not find proper documentation. Specially when you want to use is across all platforms.
PS. yep thx ,will try to update it with next release


tmt run rerun for discover does not work

If I try to run discover again with previously run id it does not work ....
See below
$ tmt run discover
/var/tmp/tmt/run-011

/ci/test
    discover
        how: fmf
        repository: git://pkgs.devel.redhat.com/tests/systemd
        filter: tags: PoC & distros: rhel-8
        tests: 1 test selected

$ tmt run -i /var/tmp/tmt/run-011 discover
/var/tmp/tmt/run-011

/ci/test

This has been fixed during conversion into dynamic plugins:
> tmt run discover
/var/tmp/tmt/run-093

/plans/docs
    discover
        how: fmf
        url: https://github.com/psss/fmf
        ref: master
        filter: coverage:/stories/docs.*
        summary: 1 test selected

/plans/features
    discover
        how: fmf
        url: https://github.com/psss/fmf
        ref: master
        summary: 6 tests selected

/plans/smoke
    discover
        how: shell
        directory: /home/psss/git/fmf
        summary: 1 test selected

> tmt run -i /var/tmp/tmt/run-093 discover
/var/tmp/tmt/run-093

/plans/docs
    discover
        status: done
        summary: 1 test selected

/plans/features
    discover
        status: done
        summary: 6 tests selected

/plans/smoke
    discover
        status: done
        summary: 1 test selected


error during install setup.py

Hi guys, when I want to install the setup.py
it shows
error: eth-utils 2.0.0 is installed but eth-utils<2.0.0,>=1.9.5 is required by {'web3'}
but I think my eth-utils is 1.9.5

what should I do now?
Thank you very much

Hi @kydchen
One of the (sub-)dependencies of web3 wants a higher version than web3 needs for eth-utils
My workaround is to install with pip instead of setup.py and you should be able to get around that error.
From the root of the honestnft repo simply do pip install .

Hi @kydchen One of the (sub-)dependencies of web3 wants a higher version than web3 needs for eth-utils My workaround is to install with pip instead of setup.py and you should be able to get around that error.
From the root of the honestnft repo simply do pip install .

I‘ll have a try, thank you very much!

You're always welcome to join the Discord https://discord.gg/c2wJuzCh

Having a similar issue
error: eth-utils 1.10.0 is installed but eth-utils<3,>=2.0.0 is required by {'eth-rlp'}

@ricrosales This can be closed


Does pack command incorrectly determine the exe name?

For a console app named like "AcmeImport.Console" the default assembly name will be "AcmeImport.Console"  However, the pack command below looks for "AcmeImport.exe" in the publish directory.  Note the missing ".Console".
[...]windows-x64.warp-packer.exe --arch windows-x64 --input_dir "C:\all\AcmeImport\AcmeImport.Console\dotnetwarp_temp" --exec "AcmeImport.exe" --output "AcmeImport.exe"
My work around was to edit project properties renaming the assembly to "AcmeImport" which results in an exe that the pack command will hit.

Fixed in #24


:robot: Triggering CI on branch 'release-next' after synching to upstream/main

Having the following issue:
the server could not find the requested resource (get eventtypes.eventing.knative.dev)

This is because we run the eventing upstream tests, which use the eventtype v1beta2, but the serverless operator installs eventing v1.9 which does not provide this version of eventtype.
Anyhow these tests are not needed for eventing-istio. Will check on it...


Version 2

Version 2

Description

Major new feature: allow using API builder
Major refactoring and code cleanup (part 1 of 2 ;-) ).
Breaking changes:

probability fields renamed to confidence
parsing methods by input type rather than by document type
removal of license plate API

How Has This Been Tested
Unit tests refactored, updated, and added to!
Types of changes

[x] Docs change / refactoring / dependency upgrade
[ ] Bug fix (non-breaking change which fixes an issue)
[x] New feature (non-breaking change which adds functionality)
[x] Breaking change (fix or feature that would cause existing functionality to change)

Checklist

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

Did the changes in the README took in consideration #47 ?

Did the changes in the README took in consideration #47 ?

Yes. @fakela you can close your PR.


Mark data points labeled as botnet-related by classifier

The classifier will label flows as botnet or non-botnet. This must be exposed through the UI for the final project.
Imported from Georgia Tech github:
{"created_at":"2019-03-31T13:28:27Z","updated_at":"2019-04-07T03:00:04Z","closed_at":"2019-04-07T02:59:54Z","html_url":"https://github.gatech.edu/ekobrin3/2019-Spring-CSE6242-flowgridviz/issues/27","id":75824}

Fixed in v0.10.0
Imported from Georgia Tech github:
{"created_at":"2019-04-07T02:59:54Z","updated_at":"2019-04-07T03:00:04Z","html_url":"https://github.gatech.edu/ekobrin3/2019-Spring-CSE6242-flowgridviz/issues/27#issuecomment-41175","id":41175}


Help : Server graceful shutdown

Hi,
I have really liked the project for my microservices but how can I implement graceful shutdown of server instance. I have tried accessing server.close by implementing (*server.close).store(true, Ordering::Relaxed);
But it says that server.close is a private
Is there any other way to shutdown the server or I am doing anything wrong.

See signal-hook.
I "catch" e.g. the 1st SIGTERM (or SIGINT), set an cond_term: AtomicBool, call unblock() for how many threads there are. In the spawned threads I check the AtomicBool, short before return in the spawned threads another AtomicU8 (th_stop_count_spawned) is counted up for stopping/exiting threads. (If you have more threads than u8::MAX, change the type) (s_num is my server thread number from the for-loop creating the threads)
let thread_builder = std::thread::Builder::new();
let th = thread_builder.spawn(move || {
    debug!("thread init {}", s_num);

    for req in server.incoming_requests() {
        // handle request
        let mut response = response_generate(&req, &req_cfg);
        if let Err(err) = req.respond(response) {
            error!("responding failed: {:?}", err);
        }

        if cond_term.load(Ordering::Relaxed) {
            debug!("thread {} stop graceful", s_num);
            // stop `incoming_requests()` by `signal_hook` condition
            break;
        }
    }

    // this here is called also after `unblock()` of `incoming_requests()`
    if cond_term.load(Ordering::Relaxed) {
        debug!("thread {} stop graceful", s_num);
        let _ = th_stop_count_spawned.fetch_add(1, Ordering::Relaxed);
    } else {
        panic!("unexpected thread abort");
    }
});

On program start I start a mostly sleeping thread like this...
let th = thread_builder.spawn(move || {
        debug!("graceful shutdown thread init");

        while !check_term.load(Ordering::Relaxed) {
            thread::sleep(Duration::from_millis(750));
        }

        info!(
            "graceful server shutdown in up to {} seconds",
            server_shutdown
        );

        for _ in 1..=server_num {
            server.unblock();
        }

        for _ in 0..server_shutdown {
            if th_stop_count_spawned.load(Ordering::Relaxed) >= server_num {
                return;
            }
            thread::sleep(Duration::from_secs(1));
        }

        exit_routine();
    });

server_shutdown is the graceful wait time period in seconds.
check_term is a different Arc::clone from cond_term above.
The return ends this extra thread and the program continues its code after the outside JoinHandle::join().
There I have a Vec with all JoinHandle from all threads and simply block that all threads are joinable.
The exit_routine() is a handler when the graceful wait time (in ~seconds) is over and there would be incoming_request threads left over after this wait time. So to cleanup also some stuff on not graceful shutdown and force a process::exit().


Deploying multiple icebreaker bots to the same RG breaks all but the latest one

The azure logic app fails to get secrets from the key vault - if the permission is manually added it will still fail because the app secret will not be valid (401).

Thank you for submitting this issue, as we work to ensure consistent responses with items logged in our issues list, we are working to address these items that did not get responses. Please let us know if you are still facing this issue and require assistance and we will be happy to discuss. If no further action is needed at moment and no response is received, we will close out the issue in 3 business days. You may also always open a new issue or respond here if something does come back up. Thank you!


add MCP server badge

This PR adds a badge for the mcp-azure-tablestorage server listing in Glama MCP server directory.

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected
Confirm that there are no obvious security issues with dependencies of the server
Extract server characteristics such as tools, resources, prompts, and required parameters.

This badge helps your users to quickly asses that the MCP server is safe, server capabilities, and instructions for installing the server.

realized the project is missing a license
https://docs.github.com/en/communities/setting-up-your-project-for-healthy-contributions/adding-a-license-to-a-repository
Would you mind adding one?
We will automatically pick up the change (we scan every repo every 6 hours)

realized the project is missing a license
https://docs.github.com/en/communities/setting-up-your-project-for-healthy-contributions/adding-a-license-to-a-repository
Would you mind adding one?
We will automatically pick up the change (we scan every repo every 6 hours)

There is a license now and the pr is merged

Thanks! are you on the MCP Discord?
Let me know your Discord username and I will give you a special flair that's only for MCP server authors.

Thanks! are you on the MCP Discord?
Let me know your Discord username and I will give you a special flair that's only for MCP server authors.

ChristianP#4487
How do I update the NPM link on the page?
The package is not same name as on git..

Thanks! are you on the MCP Discord?
Let me know your Discord username and I will give you a special flair that's only for MCP server authors.

ChristianP#4487
How do I update the NPM link on the page?
The package is not same name as on git..

It picks it up automatically from package.json every 6 hours.


Add support of CMake to check compiler flag and runtime dependencies

Signed-off-by: Anthony Fieroni<EMAIL_ADDRESS>

Excellent work.  Thank you!


Run dependencyGuard task during CI

Run the dependencyGuard task during CI, which will fail if there are detected changes.
Also update the Renovate config to run the dependencyGuardBaseline task, otherwise the auto-generated PRs would fail.
Change-Id: If5f2b18a4c765bd38a3353df2adaaa91cf1739c3

@jdkoren Looks like we're missing the dependabot configuration to run dependencyGuardBaseline for automated updates.
Also minor point, please don't force push as it messes up the commit and comment history.


ui: snapped panels should stick to borders on viewport resize

And they should maintain proportional coverage over the viewport, maintaining distance from other adjacent panels.

I ended up implementing anchor based layouts, for more complex UI scenarios.
I will also add constraints (min max size for layout geometries).
After constraints are in, you should be able to attach a panel to a guide.
If the guide moves, whatever is attached should move with it.
depends on https://github.com/tweakoz/orkid/issues/94


fix: make setting name an extra steps

Checklist:

[x] I have read freeCodeCamp's contribution guidelines.
[x] My pull request has a descriptive title (not a vague title like Update index.md)
[x] My pull request targets the main branch of freeCodeCamp.
[x] I have tested these changes either locally on my machine, or GitPod.

Closes #43358, #41040

I am not entirely sure what we agreed on for these issue's, but here is a way to do it.

I am not entirely sure what you are suggesting here @ShaunSHamilton,
Are you suggesting not adding an extra step and adding a flash message instead?

Are you suggesting not adding an extra step and adding a flash message instead?

I am suggesting two options:

Remove the name step entirely, because it is not a technical requirement to claim a certificate (we just added it, because Campers were getting confused with their username showing up on their cert)
What I mentioned above as the needed logic:

name not set -> Cannot claim certificate (needs to be checked on user record during verification)
name === private -> Certificate hidden (cannot be viewed by anyone) -> Flash message explaining it needs to be made public (same as certifications === private)

For 2, essentially, we are enforcing the requirement for name to be set and public. Currently, it is not enforced - a Camper can claim a certificate without doing prior.
Hope this is clear. If not, we are probably best hoping on a call with whoever else wants, and discussing for a finality.

I get this message after removing the steps for claiming the cert.

Sorry if I'm late to the conversation here - I was trying to take a look at this, here's some things I noticed:
In this PR, the cert claiming widget shows 4 steps:
Complete the following steps to claim and view your Responsive Web Design Certification
-Accept our Academic Honesty Policy
-Complete Responsive Web Design Certification Projects
-Set your profile settings to public
-Set your certification settings to public

If a name is required to claim or view a cert, I think it should be included in the steps. I don't think a name should be required to claim a cert since it hasn't been required in the past and you can just set your name to an empty string afterwards. If it's an empty string, uncheck the step. I think the only things required to claim a cert should be the honesty agreement and the required projects. The step for entering your name can be what it was - Set your name, and make it public. If there isn't a name set, the link takes you to the place to add a name - if it is set, it can take you to the privacy setting.
The name should have the same message in the privacy settings as the profile and certification:
Your certifications will be disabled, if set to private.
We should not fall back to usernames if a name is private. Names need to be public to view a cert.
My opinion anyway. Seems like that would close both the issues.

Hey @ShaunSHamilton,
I would like to hear your opinion on this above message.

I suggest we organise a meeting with Quincy, and hash out the future for the privacy settings. Until then, this PR should be blocked.

I was not at the meeting, but I got a lot from the notes. Let me know what I missed.


docs: Grammar and formatting changes

Just some changes that I noticed would be helpful.

@b-zurg - thanks for it :)


Change auth strategy to using find_or_create_token endpoint

Like discussed in in #484 this simplifies authentication by using the find_or_create_token-endpoint and removing all other auth-endpoints. If all is good users should not notice this change besides when their tokens expire, then they should now just be re-created (I couldn't test that because I had no expired tokens available for testing that).
Closes #484
Fixes #764

Pull Request (PR) draft checklist - click to expand

[x] Please review our
contributing documentation
before getting started.
[x] Ensure an issue exists representing the problem being solved in this PR.
[x] Populate a descriptive title. For example, instead of "Updated README.md", use a
title such as "Add testing details to the contributor section of the README".
[x] Populate the body of the pull request with:

A clear description of the change you are proposing.
Links to any issues resolved by this PR with text in the PR description, for
example closes #1. See
GitHub docs - Linking a pull request to an issue.

[x] Update CHANGELOG.md with details about your change in a section titled
## Unreleased. If such a section does not exist, please create one. Follow
Common Changelog for your additions.
[x] Update the documentation and/or the README.md with details of changes to the
earthaccess interface, if any. Consider new environment variables, function names,
decorators, etc.

Click the "Ready for review" button at the bottom of the "Conversation" tab in GitHub
once these requirements are fulfilled. Don't worry if you see any test failures in
GitHub at this point!

Pull Request (PR) merge checklist - click to expand
Please do your best to complete these requirements! If you need help with any of these
requirements, you can ping the @nsidc/earthaccess-support team in a comment and we
will help you out!

[ ] Add unit tests for any new features.
[x] Apply formatting and linting autofixes. You can add a GitHub comment in this Pull
Request containing "pre-commit.ci autofix" to automate this.
[x] Ensure all automated PR checks (seen at the bottom of the "conversation" tab) pass.
[ ] Get at least one approving review.

📚 Documentation preview 📚: https://earthaccess--782.org.readthedocs.build/en/782/

Oh, didn't have those errors locally and will check what went wrong there.

I am not sure about this and could just initialize with an empty dict to make mypy happy. The rest also failed on main for me I think.

@fwfichtner, you can safely ignore the failing integration tests. They are all tests that will pass once the PR is merged. We still don't know why this is happening, but we've seen it a few recent PRs.
Regarding the failing unit tests, I'll comment in the code.

@mfisher87 and/or @betolink, either of you care to take a quick look at this PR before I merge it?

I'm not going to be able to take a close look at this in the short term. Funding & time-management struggles :weary:

Thanks for the review @chuckwondo

@chuckwondo thanks for merging! fyi I just got my funding confirmed yesterday; it's not much, but I'm out of "am I funded for this at all?" space now :)


Adjust plugin.zsh file to run on zsh 5.1 in mSYS2.

I have fixed the missing brackets in plugin.zsh file. Now it works flawlessly under msys2 on Windows.
I have closed the other pull request as, being frank, I didn't know how to add a somthing from a different branch to it.

Thanks! 👍


[Feature Request] how can i intergrate interworx with boxbilling

What is the idea?
Feature requeshow can i intergrate boxbilling with interworx
Why would this be beneficial
Benefits

Hi @donaldchada, appreciate the feature request.
I can't say this won't be implemented at some point. But development assistance would be welcome if you have any skills.


Fix typos in README.md

Great thanks! Please note that we currently move this topic into an own community extension: https://github.com/camunda/camunda-process-test-coverage


message_feed: Improve edited/moved tooltip.

[x] Change the text to:
First line: Last {moved/edited} [date/time]. [note: no parens around date, don't capitalize date unless required by rules of English, i.e., "today", not "Today"]
Second line, shown only if edit history is enabled in the organization: Click to view edit history.

Fixes: #23075
Screenshots and screen captures:

Before:

After:

Self-review checklist

[ ] Self-reviewed the changes for clarity and maintainability
(variable names, code reuse, readability, etc.).

Communicate decisions, questions, and potential concerns.

[x] Explains differences from previous plans (e.g., issue description).
[x] Highlights technical choices and bugs encountered.
[x] Calls out remaining decisions and concerns.
[ ] Automated tests verify logic where appropriate.

Individual commits are ready for review (see commit discipline).

[x] Each commit is a coherent idea.
[x] Commit message(s) explain reasoning and motivation for changes.

Completed manual review and testing of the following:

[x] Visual appearance of the changes.
[x] Responsiveness and internationalization.
[x]  Strings and tooltips.
[x] End-to-end functionality of buttons, interactions and flows.
[x] Corner cases, error conditions, and easily imagined bugs.

@zulipbot add "buddy review"

@zulipbot add "mentor review" remove "buddy review"

@yogesh-sirsat , this PR has completed the buddy review process, could you please review the PR, thanks :)

I tested the PR locally, according to issue #23075, we need to show the second line only when the message edit history is enabled in settings right, but when I disable message edit history, it doesn't show that tippy at all, it's little confusing here, @palashb01 did you discussed this with Alya?

Hey @yogesh-sirsat  , thanks a lot for reviewing the PR. However, I implemented it exactly as mentioned in issue #23075, and the tooltip (without the second line) still appears even after disabling the message edit history in the settings. I am also attaching a demo video. Could you please verify it once and let me know if any changes are required? Thanks! :)

@palashb01 Do you refresh the page after saving the changes in settings?

@palashb01 Do you refresh the page after saving the changes in settings?

No I didn't

Then can you address, is that issue from your changes in this PR, or its already there(we can post a new issue in this case)?

@yogesh-sirsat I just verified that this is not the issue due to this PR, it's present on the main branch also so I feel like we should create a new issue for this and maybe I can just go ahead and pick it up.

@zulipbot remove "mentor review"
@zulipbot add "maintainer review"

Overall this is looking good, Palash, but see my concerns especially about internationalization here.

@karlstolley I have updated the code with your suggestions, could you please review the PR, thanks :)

@karlstolley , I have updated the code, could you please review the PR, thanks :)

Added a comment, otherwise LGTM!

LGTM!

Merged, thanks @palashb01!


iOS crash after update 2.5.0

I run my project in debug mode and throw this exception:
System.ExecutionEngineException: Attempting to JIT compile method 'Airbnb.Lottie.LOTAnimationView:PlayWithCompletion (Airbnb.Lottie.LOTAnimationCompletionBlock)' while running in aot-only mode.

Are you using Net Standard?
I have the same problem.

Yes, I am using netstandard 2.0

I'm getting a similar issue after upgrading. My error is
Error MT2101: Can't resolve the reference 'System.Void ObjCRuntime.BlockLiteral::SetupBlockUnsafe(System.Delegate,System.Delegate)', referenced from the method
'System.Void Airbnb.Lottie.LOTAnimationView::PlayFromFrame(Foundation.NSNumber,Foundation.NSNumber,Airbnb.Lottie.LOTAnimationCompletionBlock)'
in 'Xamarin.iOS, Version=<IP_ADDRESS>, Culture=neutral, PublicKeyToken=84e04ff9cfb79065'. (MT2101)

My code that produces this is as follows:
LOTAnimationView spinner = LOTAnimationView.AnimationNamed("loaderRingSpinning");
spinner.Frame = new CGRect(new CGPoint(), SpinnerViewContainer.Frame.Size);
spinner.ContentMode = SpinnerViewContainer.ContentMode;
SpinnerViewContainer.AddSubview(spinner);

I've the same issue on my iOS App.
I'm not using .Net Standard ...
Below a screenshot of error logged on MS App Center :

Are you using a device or simulator?
What version of iOS?

Simulator and devices ...
We are using iOS 11.2

I had the exact same problem and was forced to remove any Lottie from my project because of deadlines. I hope you guys manage to fix this so I can add it back at some point. :)

I roll back to 2.1.5 and works fine!

Same issue here, reverted to 2.1.5 works fine

Hi @ankidave and @mprieur18 I was able to reproduce this bug setting Link behavior to Link Framework SDKs Only.
I built this NuGet package  Com.Airbnb.iOS.Lottie.<IP_ADDRESS>-beta1.zip  on my machine.  Please download and rename this file to Com.Airbnb.iOS.Lottie.<IP_ADDRESS>-beta1.nupkg
Can you check if this version fix the problem?

your Nuget fix the problem for me. thanks !

@fabionuno Your <IP_ADDRESS>-beta1 works. What is the next step or ETA on the official one?

@fabionuno did you change anything? What can I do?

@martijn00 Nothing was changed. I just built the project in VS4Mac

@fabionuno weird, i could just compile everything again and release a new version?

@martijn00 Could you please give that a go?

@khle We are testing a new version to release as soon as possible.

@khle I have tested the current package Lottie iOS <IP_ADDRESS> with VS4Mac 7.4 and everything is working fine.
If you are using VS4Mac 7.3.3 can you update to 7.4 and check if it fix the error

You can fix this by updating to VS4Mac 7.4.

Still breaks on appcenter builds :(. I had to roll back to 2.4.1

@mshenoy83 Does AC have 7.4 or some earlier version of VSMac ?

No idea to be frank, but here are the Mono and Xcode versions being used.

2.5.1 still getting
MTOUCH : error MT2101: Can't resolve the reference 'System.Void ObjCRuntime.BlockLiteral::SetupBlockUnsafe(System.Delegate,System.Delegate)', referenced from the method 'System.Void Airbnb.Lottie.LOTAnimationView::PlayFromFrame(Foundation.NSNumber,Foundation.NSNumber,Airbnb.Lottie.LOTAnimationCompletionBlock)'

same here: appcenter fails to build with 2.5.1
2018-03-21T10:00:22.6225950Z (_CompileToNative target) ->
2018-03-21T10:00:22.6476210Z   MTOUCH : error MT2101: Can't resolve the reference 'System.Void ObjCRuntime.BlockLiteral::SetupBlockUnsafe(System.Delegate,System.Delegate)', referenced from the method 'System.Void Airbnb.Lottie.LOTAnimationView::PlayFromFrame(Foundation.NSNumber,Foundation.NSNumber,Airbnb.Lottie.LOTAnimationCompletionBlock)' in 'Xamarin.iOS, Version=<IP_ADDRESS>, Culture=neutral, PublicKeyToken=84e04ff9cfb79065'.

Is there a fix for this? After updating to iOS 11.2 and configuring AppCenter to use the latest Xcode and Mono builds, I'm still blocked by this issue. Other than backporting, I'm not sure what to do here. Builds work fine locally against the latest stable channel but fails in AC.

We have the same issue with 2.5 as well (RELEASE on vs AC).


Global for filenames

This PR remove the remaining big variability for nitc when generating separate files: the path of nit module in runtime error messages.
When compiling a same module but from different current working directories, the relative path of the module changed. Thus causing unnecessary difference in the generated C source code that made ccache unhappy.
Before
$ ccache -C
$ time nitc src/nitc.nit
user	2m8.264s
$ cd src
$ time nitc nitc.nit
user	2m8.676s

After
$ ccache -C
$ time nitc src/nitc.nit
user	2m9.180s
$ cd src
$ time nitc nitc.nit
user	0m9.812s

Note: some files are still different after the PR

main.c because it contains the real filepath
c_function_hash.c same
_ffi.? because the pragma lines indicate the original relative file

Note 2: .nit_compile directories are still created by default in the current directory and let unclean. cf #792

+1

+1


global flutter >  which flutter

@YangLang116 can you explain a bit the motivation behind this change?

@YangLang116 can you explain a bit the motivation behind this change?

1、There's no need to specify a "PATH"
2、’which flutter‘ means default flutter path。However, When calling ’fvm flutter ...‘ command, should try to use the version maintained by FVM

@all-contributors please add @YangLang116 for code

@YangLang116 I had to make some changes but will bring this functionality manually. Will keep this open until I bring it in.


Hooking in a custom CSS-file should include choice of media (screen/print)

Expected behaviour
I want to load a new stylesheet within my plugin:
$this->hook->on('template:layout:css', 'plugins/Css/skin.css');
sets the usage to media="screen". I would like to choose which type of media the css is for.
Something like:
$this->hook->on('template:layout:css', 'plugins/Css/skin.css', 'print');
resulting in
<link rel="stylesheet" href="/kanboard/plugins/css/style.css?1450287310" media="print">
Actual behaviour
media="screen" is set automatically.

I tried sending both, value for the hook and the media-type in an array in the Plugin.php:
$this->hook->on('template:layout:css', array('value' => 'plugins/qm/css/style.css', 'media' => 'print'));
In Helper/Asset::css I have to check if the $filename is an array an then split it into $filename and $media:
    if (is_array($filename))
    {
        $media = $filename['media'];
        $filename = $filename['value'];
    }

Could this be a way?

You can also use the template hook template:layout:head to inject any html tag in the head section.

OK, THX!


retdec-unpacker prints "No matching plugins found for 'gc'"

##### Trying to unpack lib.so into lib.so-unpacked.tmp by using generic unpacker...
RUN: /usr/local/bin/retdec-unpacker lib.so -o lib.so-unpacked.tmp
No matching plugins found for 'gc'
##### Unpacking by using generic unpacker: nothing to do

Thanks for retdec :)
Which plugging do I need and how do I install it?
Thank you

The message you see is just an error of the unpacker but not the whole decompilation. If unpacking fails, decompilations still continues so you shouldn't worry about it. If you have any problems with the decompilation itself then please provide rest of the log messages.

Closing due to inactivity. As @metthal has written, if you have any issues with the decompilation itself, then please re-open and provide logs from the decompilation.

Running phase: Unpacking ( 0.02s ) No matching plugins found for 'GCC 4.9.1' Running phase: Initialization ( 0.06s )
I got this when trying do decompile, retdec-decompiler stops and exits.
What can I do?


upgrade github.com/onsi/ginkgo to v2

Hi Fabric,
In recent I noticed ginkgo released v2 version.
Do we have any plan to do the package upgrade?
some en... benefits from the upgrade, it's vscode plugin of the ginkgo then can be used.

Thanks and regards
Sam

closed via #3498  and checked at https://github.com/hyperledger/fabric/blob/main/go.mod#L26


Struct public API audit

From the get-go struct was planned to be both a useful developer tool, and a library with friendly API for use in larger tools and more complex environments.
This task is to review the current API available in struct, in order to ensure it's fit for purpose as a library as well as a development tool.
Proposed tasks:

[ ] Ensure any publicly accessible APIs are fully documented
[ ] Ensure any APIs and types not intended for public use are properly annotated as such and have appropriate access modifiers
[ ] Assess how internal classes can be simplified to make working with them as easy as possible, e.g. builders and factories

@lyptt I'm going to start a scaffolding tool, I could use to verify this.

Allow to pass version in as string and not version class
Default to empty array when targets, variants and configurations aren’t parsed in
Have constant for latest spec version
Target requires 8 things to be passed in the constructor, we should have sensible defaults to most of these. We can remove profiles argument as we will be inferring, type and platform may be needed but potentially we could let developer set these later and throw assertion if they try to write without setting these for their sanity.

There is a lot of weird quirks and non-obviousness when using profiles.
We should hide these from the API consumer as detailed in #67 to make things easier :)

@jcampbell05 There's a few things here now covered by recent changes:

[x] Have constant for latest spec version
[x] There is a lot of weird quirks and non-obviousness when using profiles. We should hide these from the API consumer as detailed in #67 to make things easier

Remaining items are:

[ ] Allow to pass version in as string and not version class
[ ] Default to empty array when targets, variants and configurations aren’t parsed in

Fixed in 2.0.0.


Error with reddit-parser

I am getting an error while training my own reddit data from this website, https://files.pushshift.io/reddit/comments/
2017-8.
Trying it the first time:
Traceback (most recent call last):
File "reddit_parse.py", line 258, in
main()
File "reddit_parse.py", line 37, in main
parse_main(args)
File "reddit_parse.py", line 91, in parse_main
args.print_subreddit, args.min_conversation_length)
File "reddit_parse.py", line 242, in write_comment_cache
output_file.write(output_string + '\n')
File "reddit_parse.py", line 151, in write
self.file_reference.write(data)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\encodings\cp1252.py", line 19, in encode
return codecs.charmap_encode(input,self.errors,encoding_table)[0]
UnicodeEncodeError: 'charmap' codec can't encode character '\U0001f602' in position 404: character maps to
Second time, I added 'encoding=utf8' to line 151:
Traceback (most recent call last):
File "reddit_parse.py", line 258, in
main()
File "reddit_parse.py", line 37, in main
parse_main(args)
File "reddit_parse.py", line 91, in parse_main
args.print_subreddit, args.min_conversation_length)
File "reddit_parse.py", line 242, in write_comment_cache
output_file.write(output_string + '\n')
File "reddit_parse.py", line 151, in write
self.file_reference.write(data, encoding='utf8')
TypeError: write() takes no keyword arguments
Python 3.6.8
Tensorflow 1.9.0
Could someone please help me?

I personally could never get it to work, so I ended up just programming my own.

Could you send me the code? I have no idea how to do parsing.

Let me take a look at your data set and I might be able to help you out.

Ok. Thanks a lot. You're awesome.

Thanks, we will keep in touch.

May be of some use?
https://www.youtube.com/watch?v=dvOnYLDg8_Y&list=PLQVvvaa0QuDdc2k5dwtDTyT9aCja0on8j

Thanks, that might help. the data seems to be a similar layout.

Might be json format
https://www.reddit.com/r/datasets/comments/3bxlg7/i_have_every_publicly_available_reddit_comment/

Yep, got that.I just downloaded some testing data to look at and start coding. This parser shouldn't be too complicated.

Thanks SO much.
On Sun, 1 Sep 2019 at 19:12, DSMJR<EMAIL_ADDRESS>wrote:

Yep, got that.I just downloaded some testing data to look at and start
coding. This parser shouldn't be too complicated.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
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or mute the thread
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.

No problem.

Some of the datasets on that website are corrupted after extraction. I didn't find any corrupted ones in the "daily" directory. Done with the parser, if you have any errors with it, do tell. I also included my cornell corpus parser, if you are interested. And also a link to a pre-parsed reddit dataset.
Parser ----  https://drive.google.com/file/d/1YgDZrQGJXZybXAo_5_4SZXycBFUJ3jCo/view?usp=sharing
pre-parsed data ---- https://drive.google.com/uc?id=1s77S7COjrb3lOnfqvXYfn7sW_x5U1_l9&export=download
cornell corpus ---- https://www.cs.cornell.edu/~cristian/Cornell_Movie-Dialogs_Corpus.html

You're the best. What data did you pre-parse?

It was the pre-parsed data in the README of this project. It seemed to be decent data in case you weren't aware it👍.

I'm sorry, I'm getting an error while parsing. It seems to just be a simple unicode decode error;
Traceback (most recent call last):
File "C:/Users/16175/Documents/chatbot-rnn/reddit-parse/parser.py", line 19, in
for i in file:                                       #
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\codecs.py", line 321, in decode
(result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xe5 in position 10: invalid continuation byte

I'm parsing RC_2017-08 (around 15 gigs)

let me take a look

Strange I used "RC_2005-12" (because it was the smallest in size and I wanted to get data quickly to test) and I didn't have any problems with it.

Huh. I'm going to check out the difference between the files. :\

Nevermind. I got it to work by changing the encoding to latin1. I'm not sure if it will cause problems in the future, though. Some people say that some encoding makes the output gibberish. Anyway, new error:
Traceback (most recent call last):
File "C:/Users/16175/Documents/chatbot-rnn/reddit-parse/parser.py", line 30, in
f = f[1]  #
IndexError: list index out of range

add print(f) just above that line to see what data is in the variable.

['BZh91AY&SYåØ;\x90\x06Úvß€\x7f\x90\x7fÿÿúÿÿÿÿÿÿÿÿb³Gß[ì0õ\xa0\x1a\x00h\x1a\x00ÑX\x14}\x06ûX\x01è\x00¢|Ã)õ÷O\x1dÜ\x0fT¥\x00\x02¨RJÐ\x00\x00Á4\x03Az,[\x00:\x1e¤\x0e@\x02€h:\x00\x1d"h\x01vtª«°\n']
Traceback (most recent call last):
File "C:/Users/16175/Documents/chatbot-rnn/reddit-parse/parser.py", line 31, in
f = f[1]  #
IndexError: list index out of range
I need to get some sleep. See you tomorrow.

I Think that might be a consequence of changing encoding. I'm downloading your dataset (RC_2017-08) to see.

On line 8 (file = open(filename, 'r', encoding='utf8')) change 'r' to 'rb'
also make sure you change encoding back to utf8.

I downloaded the file (RC_2017-08) https://files.pushshift.io/reddit/comments/RC_2017-08.bz2
and no errors. Do we have the same file?

Where did you download it? Link I provided?

Yes, we have the same file. Did you change anything in the code from the zip you sent me?

No changes.

What did you enter for file name?

oh, and also. What python are you using?

I can't find a reason why it doesn't work, it should work. How big is your file extracted and un-extracted?

file name : "RC_2017-08"

7.38 extracted, not sure how big unextracted (got deleted)

Ok looks to be the same file.

I re-downloaded the zip, utf8, invalid continuation byte.

python 3.7.2. It shouldn't make a difference.

how are you running code? I am using pycharm built-in. Are you using terminal?

I'm using terminal

ok. using cmd now. What did you enter for file name (parser is in reddit_parse directory)

Whatever file you downloaded and extracted name. I used RC_2017-08

alright.

Traceback (most recent call last):
File "parser.py", line 19, in
for i in file:                                       #
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\codecs.py", line 321, in decode
(result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xe5 in position 10: invalid continuation byte

with terminal

it is so weird. Try on line 8 change the open() mode from "r" to "rt"

and if that doesn't work get rid of encoding=utf-8 on the same line

file = open(filename, 'rt') or file = open(filename, 'rt', encoding = 'utf-8')

got rid of utf8;
Traceback (most recent call last):
File "C:/Users/16175/Documents/chatbot-rnn/reddit-parse/parser.py", line 19, in
for i in file:                                       #
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\encodings\cp1252.py", line 23, in decode
return codecs.charmap_decode(input,self.errors,decoding_table)[0]
UnicodeDecodeError: 'charmap' codec can't decode byte 0x90 in position 13: character maps to

did you try doing file = open(filename, 'rt', encoding = 'utf-8')

Traceback (most recent call last):
File "C:/Users/16175/Documents/chatbot-rnn/reddit-parse/parser.py", line 19, in
for i in file:                                       #
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\codecs.py", line 321, in decode
(result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xe5 in position 10: invalid continuation byte

try to change encoding to ISO-8859-1

Traceback (most recent call last):
File "C:/Users/16175/Documents/chatbot-rnn/reddit-parse/parser.py", line 29, in
f = f[1]                                         #
IndexError: list index out of range

open your data file with a text editor and turn off word wrap. does the first line look "weird".

what's word wrap? is notepad ok?

notepad is fine. word wrap make all line line up instead of wrapping around your screen

Wait you said RC_2017-08 is about 7GB un-exracted.

which first line? #?

and no, not weird

at least i don't think so

no, extracted 7gb

My RC_2017 is about 7GB extracted and 50GB unextracted

rc_2017-08? or whole year?

 My bz2 is 7gb. Did you extract the bz2?

I didn't. The readme says not to

Yes for the parser. Then txt file that comes from the parser can be directly trained on

So you extracted RC_2017-08.bz2, correct?

correct

extracting now

how long did it take you to extract

extract then parse the extracted file. Then file that comes from the parser I made can go straight into the training folder for the AI.

with 7zip about 10mins

I'm using winrar. I'll let it extract, I need to go to a BBQ

I assume BBQ means Barbecue?

winrar will do just fine.

Yes. Do you prefer 7zip or winrar?

7zip.

I use 7zip or peazip interchangeably

It should most definitely work. once it is extracted.👍

Barbecue got canceled. ): How long will it take to parse? And, also, if you want, I can sub to your youtube channel and like your videos if you have one as a thank you.

I don't have a youtube channel but I do have a lot of cool scripts and programs on my github. I don't know how long it will take to parse definitely 1 hour plus. does the parser work once extracted?

Does the parser work now?

I have output.txt. The parser works. Do I put it in data?

When I try to train, error:
Preprocessing file 1/5 (data/reddit\output 1.bz2)... Traceback (most recent call last):
File "C:/Users/16175/Documents/chatbot-rnn/train.py", line 193, in
main()
File "C:/Users/16175/Documents/chatbot-rnn/train.py", line 49, in main
train(args)
File "C:/Users/16175/Documents/chatbot-rnn/train.py", line 56, in train
data_loader = TextLoader(args.data_dir, args.batch_size, args.seq_length)
File "C:\Users\16175\Documents\chatbot-rnn\utils.py", line 40, in init
self._preprocess(self.input_files[i], self.tensor_file_template.format(i))
File "C:\Users\16175\Documents\chatbot-rnn\utils.py", line 111, in _preprocess
data = file_reference.read()
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\codecs.py", line 321, in decode
(result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x92 in position 934: invalid start byte

I'm following you. :)

New error while training:
C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\framework\dtypes.py:532: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
Couldn't find data/reddit\data1.npz. Preprocessing...
Preprocessing the following files:

data/reddit\output 1.bz2
data/reddit\output 2.bz2
data/reddit\output 3.bz2
data/reddit\output 4.bz2
data/reddit\output 5.bz2
data/reddit\output.txt
Saving vocab file
Saved vocab (vocab size: 128)
Preprocessing file 1/6 (data/reddit\output 1.bz2)... Traceback (most recent call last):
File "train.py", line 193, in
main()
File "train.py", line 49, in main
train(args)
File "train.py", line 56, in train
data_loader = TextLoader(args.data_dir, args.batch_size, args.seq_length)
File "C:\Users\16175\Documents\chatbot-rnn\utils.py", line 40, in init
self._preprocess(self.input_files[i], self.tensor_file_template.format(i))
File "C:\Users\16175\Documents\chatbot-rnn\utils.py", line 111, in _preprocess
data = file_reference.read()
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\codecs.py", line 321, in decode
(result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x92 in position 934: invalid start byte

Hold on let me look at this.

show lines 105 and 106 in utils.py.

    self.vocab = dict(zip(self.chars, range(len(self.chars))))

def _preprocess(self, input_file, tensor_file):
    if input_file.endswith(".bz2"):
        file_reference = bz2.open(input_file, mode='rt', encoding='utf8')

Change: file_reference = bz2.open(input_file, mode='rt', encoding='utf8') to
          file_reference = bz2.open(input_file, mode='rt', encoding="utf-8", errors="replace")

And:
Change: file_reference = io.open(input_file, mode='rt', encoding='utf8') to,
          file_reference = io.open(input_file, mode='rt', encoding="utf-8", errors="replace")

Couldn't find data/reddit\data1.npz. Preprocessing...
Preprocessing the following files:

data/reddit\output 1.bz2
data/reddit\output 2.bz2
data/reddit\output 3.bz2
data/reddit\output 4.bz2
data/reddit\output 5.bz2
data/reddit\output.txt
Saving vocab file
Saved vocab (vocab size: 128)
Preprocessing file 1/6 (data/reddit\output 1.bz2)... done (0.0 seconds)
Preprocessing file 2/6 (data/reddit\output 2.bz2)... done (0.0 seconds)
Preprocessing file 3/6 (data/reddit\output 3.bz2)... done (0.0 seconds)
Preprocessing file 4/6 (data/reddit\output 4.bz2)... done (0.0 seconds)
Preprocessing file 5/6 (data/reddit\output 5.bz2)... done (0.0 seconds)
Preprocessing file 6/6 (data/reddit\output.txt)... done (1.9 seconds)
Processed input data: 9,831,058 characters loaded (1.9 seconds)
Total batch count: 6,156
Building the model
Total trainable parameters: 228,120,704
loading tensor data file 0

stays like this forever

it should start to train if you wait a while.

Does it work?

How long is a 'while'?

I don't know, how long have you been running it?

And I also forgot to ask you what the specs are on your computer.

Sorry, I kept it like that for 40 minutes, I'm using tensorflow-gpu with an i7 9700K, GTX 1060 6GB and 16GB RAM.

It looks like with your data set you have '228,120,704' of Trainable values (that's a lot) it may take a while to process. There is no reason for a stall like that, I would just let it run until we see some results.👍

ran it for 40 minutes, i7 9th gen, 16 Ram, gtx 1060 tf 1.9 gpu

I'll let it run overnight

I think running it over night is a good idea. I can't think of any reason why it wouldn't be working. I think it is just going to take a while to first process your datasets. I am interested to hear what it is doing in the morning. This has been a long issue I am glad I've been able to help so far.

You are the reason I didn't just search for some pre parsed data ( ͡° ͜ʖ ͡°)

Ha. I am happy to help. python is a VERY amazing language.

Friend thinks JavaScript is better; writes an alphazero RL bot
"nevermind python is better"

Javascript is a good language BUT python is way better.

Loading vocab file...
Loading sizes file...
Total batch count: 6,156
Building the model
Total trainable parameters: 228,120,704
loading tensor data file 0
Saved model to models/new_save\model.ckpt (epoch fraction 0.000).
Traceback (most recent call last):
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py", line 1322, in _do_call
return fn(*args)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py", line 1307, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py", line 1409, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[4096,2048] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[Node: gradients/rnnlm_1/while/rnnlm/partitioned_multi_rnn_cell/cell_2_0/gru_cell/MatMul_1_grad/MatMul_1 = MatMul[T=DT_FLOAT, transpose_a=true, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](gradients/rnnlm_1/while/rnnlm/partitioned_multi_rnn_cell/cell_2_0/gru_cell/MatMul_1_grad/MatMul_1/StackPopV2, gradients/rnnlm_1/while/rnnlm/partitioned_multi_rnn_cell/cell_2_0/gru_cell/Tanh_grad/TanhGrad)]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
     [[Node: gradients/rnnlm_1/while/rnnlm/partitioned_multi_rnn_cell/cell_0_2/gru_cell/BiasAdd/Enter_grad/b_acc_3/_71 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_765_g...ad/b_acc_3", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]

Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "train.py", line 193, in
main()
File "train.py", line 49, in main
train(args)
File "train.py", line 155, in train
train_loss, state, _, summary = sess.run(outputs, feed)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py", line 900, in run
run_metadata_ptr)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py", line 1135, in _run
feed_dict_tensor, options, run_metadata)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py", line 1316, in _do_run
run_metadata)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\client\session.py", line 1335, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[4096,2048] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[Node: gradients/rnnlm_1/while/rnnlm/partitioned_multi_rnn_cell/cell_2_0/gru_cell/MatMul_1_grad/MatMul_1 = MatMul[T=DT_FLOAT, transpose_a=true, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](gradients/rnnlm_1/while/rnnlm/partitioned_multi_rnn_cell/cell_2_0/gru_cell/MatMul_1_grad/MatMul_1/StackPopV2, gradients/rnnlm_1/while/rnnlm/partitioned_multi_rnn_cell/cell_2_0/gru_cell/Tanh_grad/TanhGrad)]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
     [[Node: gradients/rnnlm_1/while/rnnlm/partitioned_multi_rnn_cell/cell_0_2/gru_cell/BiasAdd/Enter_grad/b_acc_3/_71 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_765_g...ad/b_acc_3", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]

Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
Caused by op 'gradients/rnnlm_1/while/rnnlm/partitioned_multi_rnn_cell/cell_2_0/gru_cell/MatMul_1_grad/MatMul_1', defined at:
File "train.py", line 193, in
main()
File "train.py", line 49, in main
train(args)
File "train.py", line 88, in train
model = Model(args)
File "C:\Users\16175\Documents\chatbot-rnn\model.py", line 228, in init
grads, _ = tf.clip_by_global_norm(tf.gradients(self.cost, tvars),
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\gradients_impl.py", line 532, in gradients
gate_gradients, aggregation_method, stop_gradients)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\gradients_impl.py", line 701, in _GradientsHelper
lambda: grad_fn(op, *out_grads))
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\gradients_impl.py", line 396, in _MaybeCompile
return grad_fn()  # Exit early
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\gradients_impl.py", line 701, in
lambda: grad_fn(op, *out_grads))
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\math_grad.py", line 1049, in _MatMulGrad
grad_b = gen_math_ops.mat_mul(a, grad, transpose_a=True)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 4567, in mat_mul
name=name)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\framework\ops.py", line 3414, in create_op
op_def=op_def)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\framework\ops.py", line 1740, in init
self._traceback = self._graph._extract_stack()  # pylint: disable=protected-access
...which was originally created as op 'rnnlm_1/while/rnnlm/partitioned_multi_rnn_cell/cell_2_0/gru_cell/MatMul_1', defined at:
File "train.py", line 193, in
main()
[elided 1 identical lines from previous traceback]
File "train.py", line 88, in train
model = Model(args)
File "C:\Users\16175\Documents\chatbot-rnn\model.py", line 177, in init
initial_state=self.initial_state, scope='rnnlm')
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\rnn.py", line 618, in dynamic_rnn
dtype=dtype)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\rnn.py", line 815, in _dynamic_rnn_loop
swap_memory=swap_memory)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 3209, in while_loop
result = loop_context.BuildLoop(cond, body, loop_vars, shape_invariants)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 2941, in BuildLoop
pred, body, original_loop_vars, loop_vars, shape_invariants)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 2878, in _BuildLoop
body_result = body(*packed_vars_for_body)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 3179, in
body = lambda i, lv: (i + 1, orig_body(*lv))
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\rnn.py", line 786, in _time_step
(output, new_state) = call_cell()
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\rnn.py", line 772, in
call_cell = lambda: cell(input_t, state)
File "C:\Users\16175\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\python\ops\rnn_cell_impl.py", line 232, in call
return super(RNNCell, self).call(inputs, state)
ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[4096,2048] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[Node: gradients/rnnlm_1/while/rnnlm/partitioned_multi_rnn_cell/cell_2_0/gru_cell/MatMul_1_grad/MatMul_1 = MatMul[T=DT_FLOAT, transpose_a=true, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](gradients/rnnlm_1/while/rnnlm/partitioned_multi_rnn_cell/cell_2_0/gru_cell/MatMul_1_grad/MatMul_1/StackPopV2, gradients/rnnlm_1/while/rnnlm/partitioned_multi_rnn_cell/cell_2_0/gru_cell/Tanh_grad/TanhGrad)]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
     [[Node: gradients/rnnlm_1/while/rnnlm/partitioned_multi_rnn_cell/cell_0_2/gru_cell/BiasAdd/Enter_grad/b_acc_3/_71 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_765_g...ad/b_acc_3", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]

Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

I put output.txt and output 1.bz2-output 5.bz2 in a reddit folder inside data. Is that correct?

Yes you had them in the right spot. This OOM error might be an easy fix.

Show me line 30 and 24.

30: parser.add_argument('--batch_size', type=int, default=40,
24: parser.add_argument('--num_blocks', type=int, default=2,

Change line 30 to: parser.add_argument('--batch_size', type=int, default=10,

Loading vocab file...
Loading sizes file...
Total batch count: 24,629
Found a previous checkpoint. Overwriting model description arguments to:
model: gru, block_size: 2048, num_blocks: 3, num_layers: 3
Building the model
Total trainable parameters: 228,120,704
Loading saved parameters
Resuming from global epoch fraction 0.000, total trained time: 0:00:00, learning rate: 9.999999747378752e-06
loading tensor data file 0
0 / 24,629 (epoch 0.000 / 50), loss 4.845 (avg 4.845), 9.393s
1 / 24,629 (epoch 0.000 / 50), loss 4.834 (avg 4.840), 1.797s
2 / 24,629 (epoch 0.000 / 50), loss 4.833 (avg 4.837), 1.845s
3 / 24,629 (epoch 0.000 / 50), loss 4.815 (avg 4.832), 1.804s
4 / 24,629 (epoch 0.000 / 50), loss 4.813 (avg 4.828), 1.798s
5 / 24,629 (epoch 0.000 / 50), loss 4.795 (avg 4.822), 1.801s
6 / 24,629 (epoch 0.000 / 50), loss 4.788 (avg 4.818), 1.799s
7 / 24,629 (epoch 0.000 / 50), loss 4.768 (avg 4.811), 1.795s
8 / 24,629 (epoch 0.000 / 50), loss 4.765 (avg 4.806), 1.796s
9 / 24,629 (epoch 0.000 / 50), loss 4.751 (avg 4.801), 1.795s
10 / 24,629 (epoch 0.000 / 50), loss 4.716 (avg 4.793), 1.801s
11 / 24,629 (epoch 0.000 / 50), loss 4.702 (avg 4.786), 1.798s
12 / 24,629 (epoch 0.000 / 50), loss 4.674 (avg 4.777), 1.804s
loading tensor data file 1
Saved model to models/new_save\model.ckpt (epoch fraction 0.001).
Traceback (most recent call last):
File "train.py", line 193, in
main()
File "train.py", line 49, in main
train(args)
File "train.py", line 140, in train
x, y = data_loader.next_batch()
File "C:\Users\16175\Documents\chatbot-rnn\utils.py", line 192, in next_batch
self._load_preprocessed((self.tensor_index + 1) % self.input_file_count)
File "C:\Users\16175\Documents\chatbot-rnn\utils.py", line 154, in _load_preprocessed
ydata[-1] = xdata[0]
IndexError: index 0 is out of bounds for axis 0 with size 0

In the directory models/new_save delete all the data in that folder.

This time
Total trainable parameters: 152,080,512
is something wrong?

No vocab file found. Preprocessing...
Preprocessing the following files:

data/reddit\output 1.bz2
data/reddit\output 2.bz2
data/reddit\output 3.bz2
data/reddit\output 4.bz2
data/reddit\output 5.bz2
data/reddit\output.txt
Saving vocab file
Saved vocab (vocab size: 128)
Preprocessing file 1/6 (data/reddit\output 1.bz2)... done (0.0 seconds)
Preprocessing file 2/6 (data/reddit\output 2.bz2)... done (0.0 seconds)
Preprocessing file 3/6 (data/reddit\output 3.bz2)... done (0.0 seconds)
Preprocessing file 4/6 (data/reddit\output 4.bz2)... done (0.0 seconds)
Preprocessing file 5/6 (data/reddit\output 5.bz2)... done (0.0 seconds)
Preprocessing file 6/6 (data/reddit\output.txt)... done (1.9 seconds)
Processed input data: 9,831,058 characters loaded (1.9 seconds)
Total batch count: 24,629
Building the model
Total trainable parameters: 152,080,512
loading tensor data file 0
0 / 24,629 (epoch 0.000 / 50), loss 4.853 (avg 4.853), 5.785s
1 / 24,629 (epoch 0.000 / 50), loss 4.843 (avg 4.848), 1.208s
2 / 24,629 (epoch 0.000 / 50), loss 4.838 (avg 4.845), 1.209s
3 / 24,629 (epoch 0.000 / 50), loss 4.825 (avg 4.840), 1.210s
4 / 24,629 (epoch 0.000 / 50), loss 4.816 (avg 4.835), 1.207s
5 / 24,629 (epoch 0.000 / 50), loss 4.802 (avg 4.830), 1.204s
6 / 24,629 (epoch 0.000 / 50), loss 4.789 (avg 4.824), 1.212s
7 / 24,629 (epoch 0.000 / 50), loss 4.778 (avg 4.818), 1.208s
8 / 24,629 (epoch 0.000 / 50), loss 4.765 (avg 4.812), 1.205s
9 / 24,629 (epoch 0.000 / 50), loss 4.754 (avg 4.806), 1.208s
10 / 24,629 (epoch 0.000 / 50), loss 4.731 (avg 4.800), 1.209s
11 / 24,629 (epoch 0.000 / 50), loss 4.714 (avg 4.792), 1.211s
12 / 24,629 (epoch 0.000 / 50), loss 4.694 (avg 4.785), 1.203s
loading tensor data file 1
Saved model to models/new_save\model.ckpt (epoch fraction 0.001).
Traceback (most recent call last):
File "train.py", line 193, in
main()
File "train.py", line 49, in main
train(args)
File "train.py", line 140, in train
x, y = data_loader.next_batch()
File "C:\Users\16175\Documents\chatbot-rnn\utils.py", line 192, in next_batch
self._load_preprocessed((self.tensor_index + 1) % self.input_file_count)
File "C:\Users\16175\Documents\chatbot-rnn\utils.py", line 154, in _load_preprocessed
ydata[-1] = xdata[0]
IndexError: index 0 is out of bounds for axis 0 with size 0

This time
Total trainable parameters: 152,080,512
is something wrong?

no it's normal.

And you got rid of all the files that the program made previously?

yes.

I didn't delete anything and tried again and it works now! :/

i'm gonna keep this open until the model is fully trained, k?

Ok sounds good. I guess it resolved itself. if it is resolved then don't forget to mark the issue closed.

Glad I could help!

How much loss is acceptable?

depends on how well it does in inference mode. The lower the better.

Glad I could help! Enjoy.

I think it deserves a new issue, but error with training:
https://github.com/pender/chatbot-rnn/issues/60


feat: vue-input-otp

Why vue-input-otp, does the one from radix-vue not fitting? 🤔

noticed a bug yaa.. seems like clicking on other input doesn't focus on them.. need to click multiple time then only able to focus other.
https://github.com/radix-vue/shadcn-vue/assets/59365435/07615058-37c3-4296-b9de-78ec1371080d

https://github.com/wobsoriano/vue-input-otp/issues/9

hey @wobsoriano a vuejs + svelte version is on input-otp roadmap.
I'll wait for the react lib to become stable (no significant issues opened in ~10-15 days) and then finally start working in the vanilla JS core so that we can export to another libraries such as vuejs and svelte. sounds good?

@guilhermerodz that sounds like a plan! For the meantime, I'll keep the vue-input-otp package in sync with the React version until your Svelte and Vue versions are released :) Once they're ready, I'll gladly include a link to your repository.


feat: warn if bail is used in watch mode

This PR contains a:

[ ] bugfix
[x] new feature
[ ] code refactor
[ ] test update
[ ] typo fix
[ ] metadata update

Motivation / Use-Case
When running in watch mode, if the bail option is set, the process would exit on the first error. This PR introduces a warning to tell the user about the possible termination of its process.
This has been discussed on webpack repository: https://github.com/webpack/webpack/issues/6498
Breaking Changes
no
Additional Info

How should I detect the --bail argument? argv is not available within compiler.js. Should I move the overall logic?

@ooflorent ping


NavbarLogo doesn't have width and height attribute

🐛 Bug Report
Prerequisites

[X] I'm using the latest version of Docusaurus.
[X] I have tried the npm run clear or yarn clear command.
[X] I have tried rm -rf node_modules yarn.lock package-lock.json and re-installing packages.
[X] I have tried creating a repro with https://new.docusaurus.io
[X] I have read the console error message carefully (if applicable)

Description
The img tag in the NavbarLogo attribute in docusaurus.config.js file to add Logo to Navbar doesn't have any option/prop to set the height and width of the logo. Because of this, the Lighthouse Report fails and suggests to add width and height to the logo image.
Have you read the Contributing Guidelines on issues?
Yes, I have Read it.
Steps to reproduce

Run Lighthouse test on any docusaurus powered website
See the diagnostics message that suggests to add width and height attribute
Also in inspect element, width and height attributes are missing.

Expected behavior
There should be props for this in order to add height and width to image along with defaults.
Screen Shot

Your environment

Docusaurus version used: latest
Environment name and version (e.g. Chrome 78.0.3904.108, Node.js 10.17.0): Chrome 87
Operating system and version (e.g. Ubuntu 20.04.2 LTS): Windows 10

I am new to the community and willing to contribute towards this issue. Please let me know more insights upon this. Would like to take this up!

As a further request: can we make all images within a Markdown file have the height (and width, maybe) attribute as well? Is it possible to fetch this data when we convert them to require calls?
This ensures that there's no layout shift as the images load.


Incorrect segmentation on a thoracic healthy patient

Information
Contrast: T1w
Region: Thoracic
Pathology: Healthy
SCT model: https://github.com/sct-pipeline/contrast-agnostic-softseg-spinalcord/releases/download/v2.4/model_soft_bin_20240425-170840.zip
Issue
In my pipeline, I register the T1w image (0.9x0.9x5mm) to another acquisition (0.5x0.5x5mm) then performed the segmentation

Segmentation completely fails

I tried to segment the original image as well. This went better, but it stopped in lower slices

Incomplete segmentation in lower slices in the original acquisition

This is strange, the cord is well contrasted. @NathanMolinier can you give it a try with TotalSpineSeg?

hey @po09i, how urgent is this? I believe the newer model (unreleased yet) will work better on the 2nd image for sure. I was planning to make a pre-release of the newer model by the end of this week. I would say v2.4 model is old now

It is not urgent at all, the segmentation on the second image covers more than the FOV of the image I need it registered to. So this is more of a feedback than something I need help with :)

This is the output of TotalSpineSeg on the registered image

hey @po09i, I just made a pre-release of the latest model I was referring to, please do try it out if you have time! Note that you might to update the model URL in SCT's codebase in order to access the model via SCT.

Note that you might to update the model URL in SCT's codebase in order to access the model via SCT.

no, this is bad practice-- we should not encourage ppl to manually edit hard-coded path in SCT. @naga-karthik please update the URL with your model and submit a PR on SCT, thanks

Maybe Naga meant to download the pre-release as now possible using -custom-url:
sct_deepseg -install seg_sc_contrast_agnostic -custom-url https://github.com/sct-pipeline/contrast-agnostic-softseg-spinalcord/releases/download/v2.5/model_contrast-agnostic_20240930-1002.zip
sct_deepseg -i <IMAGE> -task seg_sc_contrast_agnostic

I tried @naga-karthik / @valosekj 's suggestion and got this error:

Terminal dump

sct_deepseg -i ./ax4_thoracic_off/nav_output/derivatives/anat_reg.nii.gz -task seg_sc_contrast_agnostic -o ./ax4_thoracic_off/nav_output/derivatives/anat_reg_seg.nii.gz -qc ./ax4_thoracic_off/nav_output/derivatives/qc

--
Spinal Cord Toolbox (git-master-8589f9d108a638592cdff56d9971f831373d31be)

sct_deepseg -i ./ax4_thoracic_off/nav_output/derivatives/anat_reg.nii.gz -task seg_sc_contrast_agnostic -o ./ax4_thoracic_off/nav_output/derivatives/anat_reg_seg.nii.gz -qc ./ax4_thoracic_off/nav_output/derivatives/qc
--

Using custom model from URL 'https://github.com/sct-pipeline/contrast-agnostic-softseg-spinalcord/releases/download/v2.5/model_contrast-agnostic_20240930-1002.zip'.
Traceback (most recent call last):
  File "spinalcordtoolbox/spinalcordtoolbox/scripts/sct_deepseg.py", line 400, in <module>
    main(sys.argv[1:])
  File "spinalcordtoolbox/spinalcordtoolbox/scripts/sct_deepseg.py", line 309, in main
    im_lst, target_lst = inference.segment_non_ivadomed(path_model, model_type, input_filenames, thr,
  File "spinalcordtoolbox/spinalcordtoolbox/deepseg/inference.py", line 121, in segment_non_ivadomed
    net = create_net(path_model, device)
  File "spinalcordtoolbox/spinalcordtoolbox/deepseg/monai.py", line 128, in create_nnunet_from_plans
    model.load_state_dict(checkpoint)
  File "spinalcordtoolbox/python/envs/venv_sct/lib/python3.9/site-packages/torch/nn/modules/module.py", line 2153, in load_state_dict
    raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for PlainConvUNet:
	size mismatch for encoder.stages.4.0.convs.0.conv.weight: copying a param with shape torch.Size([384, 256, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 256, 3, 3, 3]).
	size mismatch for encoder.stages.4.0.convs.0.conv.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.4.0.convs.0.norm.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.4.0.convs.0.norm.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.4.0.convs.0.all_modules.0.weight: copying a param with shape torch.Size([384, 256, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 256, 3, 3, 3]).
	size mismatch for encoder.stages.4.0.convs.0.all_modules.0.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.4.0.convs.0.all_modules.1.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.4.0.convs.0.all_modules.1.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.4.0.convs.1.conv.weight: copying a param with shape torch.Size([384, 384, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3, 3]).
	size mismatch for encoder.stages.4.0.convs.1.conv.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.4.0.convs.1.norm.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.4.0.convs.1.norm.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.4.0.convs.1.all_modules.0.weight: copying a param with shape torch.Size([384, 384, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3, 3]).
	size mismatch for encoder.stages.4.0.convs.1.all_modules.0.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.4.0.convs.1.all_modules.1.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.4.0.convs.1.all_modules.1.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.5.0.convs.0.conv.weight: copying a param with shape torch.Size([384, 384, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3, 3]).
	size mismatch for encoder.stages.5.0.convs.0.conv.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.5.0.convs.0.norm.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.5.0.convs.0.norm.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.5.0.convs.0.all_modules.0.weight: copying a param with shape torch.Size([384, 384, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3, 3]).
	size mismatch for encoder.stages.5.0.convs.0.all_modules.0.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.5.0.convs.0.all_modules.1.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.5.0.convs.0.all_modules.1.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.5.0.convs.1.conv.weight: copying a param with shape torch.Size([384, 384, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3, 3]).
	size mismatch for encoder.stages.5.0.convs.1.conv.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.5.0.convs.1.norm.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.5.0.convs.1.norm.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.5.0.convs.1.all_modules.0.weight: copying a param with shape torch.Size([384, 384, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3, 3]).
	size mismatch for encoder.stages.5.0.convs.1.all_modules.0.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.5.0.convs.1.all_modules.1.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for encoder.stages.5.0.convs.1.all_modules.1.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.4.0.convs.0.conv.weight: copying a param with shape torch.Size([384, 256, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 256, 3, 3, 3]).
	size mismatch for decoder.encoder.stages.4.0.convs.0.conv.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.4.0.convs.0.norm.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.4.0.convs.0.norm.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.4.0.convs.0.all_modules.0.weight: copying a param with shape torch.Size([384, 256, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 256, 3, 3, 3]).
	size mismatch for decoder.encoder.stages.4.0.convs.0.all_modules.0.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.4.0.convs.0.all_modules.1.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.4.0.convs.0.all_modules.1.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.4.0.convs.1.conv.weight: copying a param with shape torch.Size([384, 384, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3, 3]).
	size mismatch for decoder.encoder.stages.4.0.convs.1.conv.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.4.0.convs.1.norm.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.4.0.convs.1.norm.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.4.0.convs.1.all_modules.0.weight: copying a param with shape torch.Size([384, 384, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3, 3]).
	size mismatch for decoder.encoder.stages.4.0.convs.1.all_modules.0.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.4.0.convs.1.all_modules.1.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.4.0.convs.1.all_modules.1.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.5.0.convs.0.conv.weight: copying a param with shape torch.Size([384, 384, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3, 3]).
	size mismatch for decoder.encoder.stages.5.0.convs.0.conv.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.5.0.convs.0.norm.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.5.0.convs.0.norm.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.5.0.convs.0.all_modules.0.weight: copying a param with shape torch.Size([384, 384, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3, 3]).
	size mismatch for decoder.encoder.stages.5.0.convs.0.all_modules.0.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.5.0.convs.0.all_modules.1.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.5.0.convs.0.all_modules.1.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.5.0.convs.1.conv.weight: copying a param with shape torch.Size([384, 384, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3, 3]).
	size mismatch for decoder.encoder.stages.5.0.convs.1.conv.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.5.0.convs.1.norm.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.5.0.convs.1.norm.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.5.0.convs.1.all_modules.0.weight: copying a param with shape torch.Size([384, 384, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3, 3]).
	size mismatch for decoder.encoder.stages.5.0.convs.1.all_modules.0.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.5.0.convs.1.all_modules.1.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.encoder.stages.5.0.convs.1.all_modules.1.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.stages.0.convs.0.conv.weight: copying a param with shape torch.Size([384, 768, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 640, 3, 3, 3]).
	size mismatch for decoder.stages.0.convs.0.conv.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.stages.0.convs.0.norm.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.stages.0.convs.0.norm.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.stages.0.convs.0.all_modules.0.weight: copying a param with shape torch.Size([384, 768, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 640, 3, 3, 3]).
	size mismatch for decoder.stages.0.convs.0.all_modules.0.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.stages.0.convs.0.all_modules.1.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.stages.0.convs.0.all_modules.1.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.stages.0.convs.1.conv.weight: copying a param with shape torch.Size([384, 384, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3, 3]).
	size mismatch for decoder.stages.0.convs.1.conv.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.stages.0.convs.1.norm.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.stages.0.convs.1.norm.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.stages.0.convs.1.all_modules.0.weight: copying a param with shape torch.Size([384, 384, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3, 3]).
	size mismatch for decoder.stages.0.convs.1.all_modules.0.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.stages.0.convs.1.all_modules.1.weight: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.stages.0.convs.1.all_modules.1.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.transpconvs.0.weight: copying a param with shape torch.Size([384, 384, 1, 2, 2]) from checkpoint, the shape in current model is torch.Size([320, 320, 1, 2, 2]).
	size mismatch for decoder.transpconvs.0.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([320]).
	size mismatch for decoder.transpconvs.1.weight: copying a param with shape torch.Size([384, 256, 2, 2, 2]) from checkpoint, the shape in current model is torch.Size([320, 256, 2, 2, 2]).
	size mismatch for decoder.seg_layers.0.weight: copying a param with shape torch.Size([1, 384, 1, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 320, 1, 1, 1]).

*I shortened some paths

@po09i Oopsi, I realized that the model architecture was also slightly updated with v2.5. Hence the size mismatch errors you got. I created a PR on the SCT repo and tested it on an image myself. If you could please try it again (usage instructions in the PR), it should work fine now!

@naga-karthik I used the newer version (2024_09_30) and similarly did not get any segmentation of the spinal cord :/


Copy in chrome dev tools not working

Only reproduces on mac. Works on win and linux.

F1 > developer tools
Try to copy any text via cmd + c
Text is not copied 🐛

Started appearing about the time we merged the menu work so our suscipion is that is the cause.
Also note that when doing cmd + c, chrome dev tools is expecting there is a copy command under the edit menu (which we do have)
Assigning to July since this is hurting a bit of team's productivity.
fyi @jrieken

Ah, this happens because on macOS, you must register the role of the action in the menubar. In the old code it was done statically like sohttps://github.com/Microsoft/vscode/blob/1dfc5e557209371715f655691b1235b6b26a06be/src/vs/code/electron-main/menus.ts#L548
This is only done for cut, copy, paste and on macOS so we could just add a function to menubar.ts to check the actionid and add the role. otherwise, the menuregistry would need to be extended, but I don't see that as worth it. What do you think?

@sbatten great thanks for the explanation. Yeah let's solve it like that, it is a bit of a special action.

Thanks, this now works great -> verified