How to solve? I have use image_picker but I found image_picker_ios issue in IOS run time.

Steps to Reproduce

...
...
...

Logs

Logs

//
//  Generated file. Do not edit.
//
// clang-format off
#import "GeneratedPluginRegistrant.h"
#if __has_include(<firebase_core/FLTFirebaseCorePlugin.h>)
#import <firebase_core/FLTFirebaseCorePlugin.h>
#else
@import firebase_core;
#endif
#if __has_include(<firebase_messaging/FLTFirebaseMessagingPlugin.h>)
#import <firebase_messaging/FLTFirebaseMessagingPlugin.h>
#else
@import firebase_messaging;
#endif
#if __has_include(<flutter_inappwebview/InAppWebViewFlutterPlugin.h>)
#import <flutter_inappwebview/InAppWebViewFlutterPlugin.h>
#else
@import flutter_inappwebview;
#endif
#if __has_include(<flutter_local_notifications/FlutterLocalNotificationsPlugin.h>)
#import <flutter_local_notifications/FlutterLocalNotificationsPlugin.h>
#else
@import flutter_local_notifications;
#endif
#if __has_include(<geolocator_apple/GeolocatorPlugin.h>)
#import <geolocator_apple/GeolocatorPlugin.h>
#else
@import geolocator_apple;
#endif
#if __has_include(<google_maps_flutter/FLTGoogleMapsPlugin.h>)
#import <google_maps_flutter/FLTGoogleMapsPlugin.h>
#else
@import google_maps_flutter;
#endif
#if __has_include(<image_picker_ios/FLTImagePickerPlugin.h>)
#import <image_picker_ios/FLTImagePickerPlugin.h>
#else
@import image_picker_ios;
#endif
#if __has_include(<location/LocationPlugin.h>)
#import <location/LocationPlugin.h>
#else
@import location;
#endif
#if __has_include(<package_info_plus/FLTPackageInfoPlusPlugin.h>)
#import <package_info_plus/FLTPackageInfoPlusPlugin.h>
#else
@import package_info_plus;
#endif
#if __has_include(<paytm_allinonesdk/AllInOneSdkPlugin.h>)
#import <paytm_allinonesdk/AllInOneSdkPlugin.h>
#else
@import paytm_allinonesdk;
#endif
#if __has_include(<share_plus/FLTSharePlusPlugin.h>)
#import <share_plus/FLTSharePlusPlugin.h>
#else
@import share_plus;
#endif
#if __has_include(<shared_preferences_ios/FLTSharedPreferencesPlugin.h>)
#import <shared_preferences_ios/FLTSharedPreferencesPlugin.h>
#else
@import shared_preferences_ios;
#endif
#if __has_include(<url_launcher_ios/FLTURLLauncherPlugin.h>)
#import <url_launcher_ios/FLTURLLauncherPlugin.h>
#else
@import url_launcher_ios;
#endif
#if __has_include(<video_player_avfoundation/FLTVideoPlayerPlugin.h>)
#import <video_player_avfoundation/FLTVideoPlayerPlugin.h>
#else
@import video_player_avfoundation;
#endif
#if __has_include(<wakelock/WakelockPlugin.h>)
#import <wakelock/WakelockPlugin.h>
#else
@import wakelock;
#endif
#if __has_include(<webview_flutter_wkwebview/FLTWebViewFlutterPlugin.h>)
#import <webview_flutter_wkwebview/FLTWebViewFlutterPlugin.h>
#else
@import webview_flutter_wkwebview;
#endif
@implementation GeneratedPluginRegistrant

(void)registerWithRegistry:(NSObject*)registry {
[FLTFirebaseCorePlugin registerWithRegistrar:[registry registrarForPlugin:@"FLTFirebaseCorePlugin"]];
[FLTFirebaseMessagingPlugin registerWithRegistrar:[registry registrarForPlugin:@"FLTFirebaseMessagingPlugin"]];
[InAppWebViewFlutterPlugin registerWithRegistrar:[registry registrarForPlugin:@"InAppWebViewFlutterPlugin"]];
[FlutterLocalNotificationsPlugin registerWithRegistrar:[registry registrarForPlugin:@"FlutterLocalNotificationsPlugin"]];
[GeolocatorPlugin registerWithRegistrar:[registry registrarForPlugin:@"GeolocatorPlugin"]];
[FLTGoogleMapsPlugin registerWithRegistrar:[registry registrarForPlugin:@"FLTGoogleMapsPlugin"]];
[FLTImagePickerPlugin registerWithRegistrar:[registry registrarForPlugin:@"FLTImagePickerPlugin"]];
[LocationPlugin registerWithRegistrar:[registry registrarForPlugin:@"LocationPlugin"]];
[FLTPackageInfoPlusPlugin registerWithRegistrar:[registry registrarForPlugin:@"FLTPackageInfoPlusPlugin"]];
[AllInOneSdkPlugin registerWithRegistrar:[registry registrarForPlugin:@"AllInOneSdkPlugin"]];
[FLTSharePlusPlugin registerWithRegistrar:[registry registrarForPlugin:@"FLTSharePlusPlugin"]];
[FLTSharedPreferencesPlugin registerWithRegistrar:[registry registrarForPlugin:@"FLTSharedPreferencesPlugin"]];
[FLTURLLauncherPlugin registerWithRegistrar:[registry registrarForPlugin:@"FLTURLLauncherPlugin"]];
[FLTVideoPlayerPlugin registerWithRegistrar:[registry registrarForPlugin:@"FLTVideoPlayerPlugin"]];
[WakelockPlugin registerWithRegistrar:[registry registrarForPlugin:@"WakelockPlugin"]];
[FLTWebViewFlutterPlugin registerWithRegistrar:[registry registrarForPlugin:@"FLTWebViewFlutterPlugin"]];
}

@end

Hi @vmanjesh
When opening an issue, please try to provide all or some of the information indicated in the template so that we can address this issue properly.

Issue Template
If you are looking for support, please check out our documentation
or consider asking a question on Stack Overflow:
- https://flutter.dev/
- https://api.flutter.dev/
- https://stackoverflow.com/questions/tagged/flutter?sort=frequent

If you have found a bug or if our documentation doesn't have an answer
to what you're looking for, then fill our the template below. Please read
our guide to filing a bug first: https://flutter.dev/docs/resources/bug-reports

Steps to Reproduce

Please tell us exactly how to reproduce the problem you are running into.

Please attach a small application (ideally just one main.dart file) that
reproduces the problem. You could use https://gist.github.com/ for this.

If the problem is with your application's rendering, then please attach
a screenshot and explain what the problem is.

1. ...
2. ...
3. ...

Please tell us which target platform(s) the problem occurs (Android / iOS / Web / macOS / Linux / Windows)
Which target OS version, for Web, browser, is the test system running?
Does the problem occur on emulator/simulator as well as on physical devices?

Target Platform:
Target OS version/browser:
Devices:

Run your application with `flutter run --verbose` and attach all the
log output below between the lines with the backticks. If there is an
exception, please see if the error message includes enough information
to explain how to solve the issue.

Run `flutter analyze` and attach any output of that command below.
If there are any analysis errors, try resolving them before filing this issue.

Finally, paste the output of running `flutter doctor -v` here.

Closing this issue, since no information has been provided. Once you provide more information, please write in the comments and I will reopen it.
Thank you!


[R] configure backtrace and fopen64

Fixes #8595.
This adds -DDMLC_LOG_STACK_TRACE=0 and -DDMLC_USE_FOPEN64=0 to the XGB_RFLAGS pre-processor flags in case the respective features are missing.

I added AC_MSG_NOTICE messages for consistency with how endian detection is recorded in the log.
I ran autoreconf using the same version (2.71) as used previously to keep the configure diff small, but for a clearer picture see the changes in the configure.ac source file.
For testing, I created the R source package directory using python3 tests/ci_build/test_r_package.py --task=pack and installed that on both Ubuntu and Alpine Linux.

Installation now gives the following output on my Ubuntu 22.04 and Alpine Linux 3.20 systems, respectively:
Ubuntu 22.04
configure: Checking if/where backtrace is available
checking whether the C++ compiler works... yes
checking for C++ compiler default output file name... a.out
checking for suffix of executables...
checking whether we are cross compiling... no
checking for suffix of object files... o
checking whether the compiler supports GNU C++... yes
checking whether g++ -std=gnu++17 accepts -g... yes
checking for g++ -std=gnu++17 option to enable C++11 features... none needed
checking for backtrace in -lexecinfo... no
checking for backtrace... yes
configure: Checking whether fopen64 is available
checking for fopen64... yes
configure: Endian detection
checking for stdio.h... yes
checking for stdlib.h... yes
checking for string.h... yes
checking for inttypes.h... yes
checking for stdint.h... yes
checking for strings.h... yes
checking for sys/stat.h... yes
checking for sys/types.h... yes
checking for unistd.h... yes
configure: Checking system endianness as USE_LITTLE_ENDIAN is unset
checking whether byte ordering is bigendian... no
using little endian
configure: creating ./config.status
config.status: creating src/Makevars
config.status: creating config.h
** libs
Makevars:20: -DXGBOOST_STRICT_R_MODE=1
Makevars:20: -DDMLC_LOG_BEFORE_THROW=0
Makevars:20: -DDMLC_ENABLE_STD_THREAD=1
Makevars:20: -DDMLC_DISABLE_STDIN=1
Makevars:20: -DDMLC_LOG_CUSTOMIZE=1
using C compiler: 'gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0'
using C++ compiler: 'g++ (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0'
using C++17
[...]

Alpine Linux v3.20
configure: Checking if/where backtrace is available
checking whether the C++ compiler works... yes
checking for C++ compiler default output file name... a.out
checking for suffix of executables...
checking whether we are cross compiling... no
checking for suffix of object files... o
checking whether the compiler supports GNU C++... yes
checking whether g++ -std=gnu++17 accepts -g... yes
checking for g++ -std=gnu++17 option to enable C++11 features... none needed
checking for backtrace in -lexecinfo... no
checking for backtrace... no
configure: Checking whether fopen64 is available
checking for fopen64... no
configure: Endian detection
checking for stdio.h... yes
checking for stdlib.h... yes
checking for string.h... yes
checking for inttypes.h... yes
checking for stdint.h... yes
checking for strings.h... yes
checking for sys/stat.h... yes
checking for sys/types.h... yes
checking for unistd.h... yes
configure: Checking system endianness as USE_LITTLE_ENDIAN is unset
checking whether byte ordering is bigendian... no
using little endian
configure: creating ./config.status
config.status: creating src/Makevars
config.status: creating config.h
** libs
Makevars:20: -DDMLC_LOG_STACK_TRACE=0
Makevars:20: -DDMLC_USE_FOPEN64=0
Makevars:20: -DXGBOOST_STRICT_R_MODE=1
Makevars:20: -DDMLC_LOG_BEFORE_THROW=0
Makevars:20: -DDMLC_ENABLE_STD_THREAD=1
Makevars:20: -DDMLC_DISABLE_STDIN=1
Makevars:20: -DDMLC_LOG_CUSTOMIZE=1
using C compiler: 'gcc (Alpine 13.2.1_git20240309) 13.2.1 20240309'
using C++ compiler: 'g++ (Alpine 13.2.1_git20240309) 13.2.1 20240309'
using C++17
[...]

cc @jameslamb

I have manually checked the compilation is working:
FROM alpine:latest

RUN apk add R R-dev git g++

RUN \
    R -e 'install.packages(c("Matrix", "jsonlite", "data.table"), repos="https://mirror.las.iastate.edu/CRAN/", Ncpus = parallel::detectCores())'

RUN \
    mkdir ws && cd ws && \
    git clone --recursive https://github.com/bastistician/xgboost.git && \
    cd xgboost && git checkout musl-compatible

RUN \
    cd ws/xgboost/R-package && \
    MAKEFLAGS=-j$(nproc) R CMD INSTALL .

Haven't run any test yet due to failure to install testthat (ps compilation error).

Thanks for the @. I know this was already merged, but I just reviewed (and double-checked how these flags affect dmlc-core)... these changes look good to me.


[Bug] The selection move to the beginning of the block when editing text in a custom block component

Currently in my implementation, I render the editor
<Editor
  ...
  blockRendererFn={(contentBlock) => {
    const type = contentBlock.getType();
    if (type === 'unstyled') {
      return {
        component: Block,
        editable: true,
        props: { position },
      };
    }
  }}
/>

And my Block component
const BlockWrapper = styled.div`
  margin-left: ${(props) => `${props.left}px`};
  font-size: 12px;
  padding-bottom: 30px;

  @media (max-width: 576px) {
    margin-left: 0;
    margin-top: ${(props) => `${props.top}px`};
  }
`;

export default function Block({ blockProps: { position }, block }) {
  return (
    <BlockWrapper {...position}>
      {block.getText()}
    </BlockWrapper>
  );
}

I want to use styled-components to style the component, so I don't use blockStyleFn

Any comment?

Any comments or solutions

Have the same problem with moving selection to the beginning of line;
Made the issue, but didn't retrieve the answers to resolve;

Same problem when trying to force selection to the beginning of the first block


[bug] Email connected account USDC approval not working

Link to minimal reproducible example
https://github.com/orgs/reown-com/discussions/3335
Summary
It worked until yesterday. Now when I start a transaction with Wagmi I see this window without doing anything.

List of related npm package versions
"react": "^18.3.1",
"react-dom": "^18.3.1",
"@reown/appkit": "~1.5.2",
"@reown/appkit-adapter-wagmi": "~1.5.2"

It is resolved now


550 errors readme

closes #550

 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.

Thanks!


feat(react): add support for react18

:tada: This PR is included in version 3.35.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:

:tada: This PR is included in version 4.0.0-beta.4 :tada:
The release is available on:

npm package (@beta dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


Encode ground items and projectiles in region updates

Region#encode currently skips ground items and projectiles and so updates for these wont be sent.
public Set<RegionUpdateMessage> encode(int height) {
	Set<RegionUpdateMessage> additions = entities.values().stream()
		.flatMap(Set::stream) // TODO fix this to work for ground items + projectiles
		.filter(entity -> entity instanceof DynamicGameObject && entity.getPosition().getHeight() == height)
		.map(entity -> ((GroupableEntity) entity).toUpdateOperation(this, EntityUpdateType.ADD).toMessage())
		.collect(Collectors.toSet());

	ImmutableSet.Builder<RegionUpdateMessage> builder = ImmutableSet.builder();
	builder.addAll(additions).addAll(updates.get(height)).addAll(removedObjects.get(height));
	return builder.build();
}

Also make sure owner/dropper/creator sees his items first.

Also make sure owner/dropper/creator sees his items first.

Yeah, this involves sending a separate frame (SendTileItemMessage). Probably want to introduce some sort of repository/manager for the items

Ground items are finished in #372


'bool' object is not callable

I want to call model with experiment option but bool cuda variable is confused with cuda function in experiment.py file.

Maybe fixed with that: https://github.com/TNTLFreiburg/braindecode/commit/730abfa04ca3d2f9bb0d60a6045abdde491ebcfb ?


Apply link is not accessible

Put a direct button to join us (https://sefglobal.org/apply/)

@Piumal1999 could you please add this to the navigation

Ok

Done pr #167

@jayasanka-sack please review pr #167


Dockerize

Added Dockerfile and a script that starts the crawler.

An automated docker build would be great on hub.docker.com, but it's up to you @fhamborg.
If it's done then the readme should contain some reference to it.
docker run -d -v <config>:/news-please/newsplease/config/ <your-docker-name>/news-please

yea, thats a good idea, but im wondering if the start script can be improved, because currently it would start crawling articles from the example articles. what do you think?
thanks for your pull request! :-)

That's while it should mount a folder when the docker starts.
-v <config>:/news-please/newsplease/config/
You can place your own config.cfg and sitelist.hjson into that  folder, and it will be loaded by the crawler.

i havent used docker before, beside adding this information to the readme, is there anything to do (changes in the code, etc)?

No, it's working well without any changes in the codebase. :)
But a docker build would be necessary to provide an image.

https://hub.docker.com/
login or create an account
Create / Create Automated Build / Github / Select the project, and the default settings are fine
On the dashboard, select the project, navigate to the Build Settings tab, and trigger a build. You have to do this now, because there are no new commits in the repo.

This is great! I'm just missing the info on the readme or the wiki to enjoy all the power of news-please dockerized. Thanks!

Okay, the docker is created now. https://hub.docker.com/r/fhamborg/news-please/ Thanks @ntlf for your help!

@sakinho I'm not really familiar with docker yet, what info would be helpful to you in the readme?

I think it would be useful to know that docker version exists and the commands to create the image and the commands to execute news-please.
Also I think is key in documentation (in general) a way to execute news-please all the time, everyday, in order to get a lot of news. I have red we can demonize RSS Crawler, but it would be nice to demonize all news please or at least execute ir several times a day easily.

Currently, I neither have the time available to add that nor do we need the docker image in our group. However, if you'd like to contribute, I'd be very happy to merge a pull request that adds this info to the readme and/or provides additional functionality so that the dockerized news-please works out of the box for the use cases you mentioned.


ValidateUpdateItem Date Time FieldValue formats

I'd like to request a bit more information on the AddValidateUpdateItemUsingPath/ValidateUpdateListItem REST endpoints in regards to Date/Time fields.
I know that supplying an ISO formatted string to the FieldValue property in the FormValues object will result in an error. It seems you need to know the format that the endpoint will accept.
Depending on your locale settings in your SPWeb object, the format may be "DD/MM/YYYY hh:mm" or "MM/DD/YYYY hh:mm AM/PM" and possibly other variations (e.g., the date separator might need to be '-').
Given the information supplied by ClientFormSchema for a date time field, I don't know how to format the value in a reliable generic way that the API will always accept. Just for reference, here's the ClientFormSchema for a date/time field
CalendarType: 1
ClientValidationFormula: null
ClientValidationMessage: null
DefaultValue: "[today]"
DefaultValueFormatted: "18/11/2019 16:0"
DefaultValueTyped: "/Date(1574121600000)/"
Description: ""
Direction: "none"
DisplayFormat: 1
FieldType: "DateTime"
FirstDayOfWeek: 1
FirstWeekOfYear: 2
Hidden: false
HijriAdjustment: 0
HoursMode24: true
HoursOptions: Array(24)
0: "00:"
1: "01:"
2: "02:"
3: "03:"
4: "04:"
5: "05:"
6: "06:"
7: "07:"
8: "08:"
9: "09:"
10: "10:"
11: "11:"
12: "12:"
13: "13:"
14: "14:"
15: "15:"
16: "16:"
17: "17:"
18: "18:"
19: "19:"
20: "20:"
21: "21:"
22: "22:"
23: "23:"
length: 24
__proto__: Array(0)
IMEMode: null
Id: "516b6de7-5ee4-4c71-af4b-020a4a679228"
InternalName: "DateStarted"
IsAutoHyperLink: false
LanguageId: "1033"
LocaleId: "2057"
MaxJDay: 2666269
MinJDay: 109207
Name: "DateStarted"
ReadOnlyField: false
Required: false
ShowWeekNumber: false
StaticName: "DateStarted"
TimeSeparator: ":"
TimeZoneDifference: "-00:00:00.0003475"
Title: "DateStarted"
Type: "DateTime"
WorkWeek: "0111110"

So I get a TimeSeparator property but that's about it in terms of what format the aforementioned APIs will accept. I also get a LocaleId which could be used in toLocaleString() on a Date object but MDN advises against relying on the output of that method.
Furthermore, SharePoint doesn't like the comma this method might place in between the date and time.
The error I get with my SPWeb locale configuration is as follows

Enter a date and time like this: 23/02/2012 14:25

And if I change the locale information on my SPWeb object

Enter a date and time like this: 2/23/2012 2:25 PM

I know that the Modern UI uses these APIs for creating/updating items so how are the default forms able to work out what date format to put in FieldValue for a date time field type?

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

ID: e5a8f160-c2fd-8692-1c3f-2c5c44c7a286
Version Independent ID: 2d7064f8-409c-4465-3fbb-bd6a4c2806f5
Content: Working with lists and list items with REST
Content Source: docs/sp-add-ins/working-with-lists-and-list-items-with-rest.md
Product: sharepoint
GitHub Login: @spdevdocs
Microsoft Alias: spdevdocs

It will be very helpful if ISO formatted date times were supported.

"yyyy-MM-dd hh:mm:ss"

It will be very helpful if ISO formatted date times were supported.

If you want to easily get the supported value from a Date:
let dateStringValue = new Date().toISOString().substr(0, 19).replace('T', ' ');

Thanks @EagleWizard28, that worked for me irrespective of Regional settings.

Thanks @EagleWizard28, that worked for me irrespective of Regional settings.

According to the SharePoint Online OData CSDL, the actions AddValidateUpdateItem and AddValidateUpdateItemUsingPath both accept a datesInUTC parameter where, judging from the name, you can force dates to be applied in UTC format irrespective of Regional settings

datesInUTC parameter seems to be available in ValidateUpdateListItem. It also seems like that allows submitting dates in ISO format.


Breaking most of our tests when upgrading to opentelemetry-instrumentation-base 0.22.1 from  0.22.0

When upgrading any of our open telemetry dependencies most of our tests break
Can reproduce locally and fail on our CI (GitHub Actions)

Operating system details: Linux, Ubuntu (ubuntu-latest in GitHub Actions). And Darwin computer.dorianmarie.fr 22.5.0 Darwin Kernel Version 22.5.0: Mon Apr 24 20:52:24 PDT 2023; root:xnu-8796.121.2~5/RELEASE_ARM64_T6000 arm64
RUBY_ENGINE: ruby
RUBY_VERSION: 3.2.2
RUBY_DESCRIPTION: CI ubuntu-latest ruby 3.2.2. And ruby 3.2.2 (2023-03-30 revision e51014f9c0) +YJIT [arm64-darwin22]

I think it was an issue with GitHub Actions, it's solved on our side


Add two new methods

Add methods getAttendeePollAnswers and getSessionPolls

wow you are fast 👍 :)

haha, we need that functionality! :) Thanks for maintaining!

Could you do me a favor and add a new release 1.0.1 so I can update the code in my projects? Sorry if I jumped the gun.

Nope just needed a few more minutes, updated the way I build paths in the Webinar class to how you did it in the PR... I like it more. Thanks for that! The release should be available by now.

ps. I brought back the way that I use the entity classes to enforce the data-structures and the required/default/optional fields on Webinar and Registrant back again. It just feels somehow robuster. Have a look at the code and the entity classes. If you have recommendations throw them may way :)

And at some point, I probably need to write a couple of tests for this thing... yaawwwnnn :)

Yeah, I've been running a lot of tests lately. Borrrring! I will have a peak at the code and make any recommendations that I see.

Would be nice to be able to do something like this:
GotoWebinar::webinar($webinarKey)->delete();
GotoWebinar::registrant($registrantKey)->update([]);
This is just a quick idea.

One other thing I was thinking about, it would be nice to also return all responses from GTW were already in a Laravel Collection. Thoughts?

On this point:
GotoWebinar::webinar($webinarKey)->delete();
GotoWebinar::registrant($registrantKey)->update([]);
my first thought is that I like it also a lot but I think that it would require me to re-structure the code differently if I'm not mistaken e.g. fluent style in separate classes..? Will check back at this at a later stage or if you maybe have some examples to get me going quickly it would be nice. Time is bit tricky on my side just at the moment as I have to also finish work on the actual project that is consuming this package :)
I like the idea of the collections a lot. It would work on most of the responses but might be an issue on the account response which is a collated response of data and a pagination object. But I like the idea! Here the same I'll have to check back on it at a later stage or if you have some time somewhere throw a pull request my way.
Can I please ask you once you feel that the package is stable enough that you give me also a heads-up then I can start the abandoned process on the old package and start moving other users over. Would be interesting to hear what type of project you are using it with.
Thanks for your ideas, I enjoy that someone is using this and helping to make it better and feel free to throw some PR's over I learned quite a bit already from you ;)

I agree that it is some work to refactor the code. At this point it works and I am grateful for this package. I would recommend keep going with this package as is until stable and you are good with the working code. Then you can consider refactoring and even make a major branch 2.0.0 or similar. I will be using this package in a live environment soon.

We have not used the code in production as of yet, but working well in our local environment. Will keep you posted should we run into issues. Thanks!


HSM Scenario Tests Failing on MacOS

From the main branch, clean install, docker desktop 4.3.1, MacOS 10.15.7, make scenario-test-go fails.
--- Failed steps:

  Scenario: Submit to org1 # /Users/jonathan/code/oss/fabric-gateway/scenario/features/endorsement_hsm.feature:18
    And I register and enroll an HSM user HSMUser1 in MSP Org1MSP # /Users/jonathan/code/oss/fabric-gateway/scenario/features/endorsement_hsm.feature:12
      Error: exit status 1

  Scenario: Submit to org2 # /Users/jonathan/code/oss/fabric-gateway/scenario/features/endorsement_hsm.feature:24
    And I register and enroll an HSM user HSMUser1 in MSP Org1MSP # /Users/jonathan/code/oss/fabric-gateway/scenario/features/endorsement_hsm.feature:12
      Error: exit status 1

  Scenario: Submit to org3 # /Users/jonathan/code/oss/fabric-gateway/scenario/features/endorsement_hsm.feature:30
    And I register and enroll an HSM user HSMUser1 in MSP Org1MSP # /Users/jonathan/code/oss/fabric-gateway/scenario/features/endorsement_hsm.feature:12
      Error: exit status 1

  Scenario: Submit to org1 and org3 # /Users/jonathan/code/oss/fabric-gateway/scenario/features/endorsement_hsm.feature:36
    And I register and enroll an HSM user HSMUser1 in MSP Org1MSP # /Users/jonathan/code/oss/fabric-gateway/scenario/features/endorsement_hsm.feature:12
      Error: exit status 1

  Scenario: Evaluate on org1 # /Users/jonathan/code/oss/fabric-gateway/scenario/features/endorsement_hsm.feature:45
    And I register and enroll an HSM user HSMUser1 in MSP Org1MSP # /Users/jonathan/code/oss/fabric-gateway/scenario/features/endorsement_hsm.feature:12
      Error: exit status 1

  Scenario: Evaluate on org2 # /Users/jonathan/code/oss/fabric-gateway/scenario/features/endorsement_hsm.feature:51
    And I register and enroll an HSM user HSMUser1 in MSP Org1MSP # /Users/jonathan/code/oss/fabric-gateway/scenario/features/endorsement_hsm.feature:12
      Error: exit status 1

  Scenario: Submit non-deterministic transaction # /Users/jonathan/code/oss/fabric-gateway/scenario/features/errors.feature:87
    And the error message should contain "failed to assemble transaction: ProposalResponsePayloads do not match" # /Users/jonathan/code/oss/fabric-gateway/scenario/features/errors.feature:91
      Error: transaction error message "rpc error: code = Aborted desc = failed to collect enough transaction endorsements, see attached details for more info" does not contain expected value "failed to assemble transaction: ProposalResponsePayloads do not match"

I posted on your previous issue but it's relevant here:

The HSM tests require a whole bunch of SoftHSM set up, which I'm not convinced works well (if at all) outside of Linux, so I wouldn't worry about them.

We can leave this open in case somebody has time to try to get the HSM scenario tests working on MacOS and the steps for doing it documented. Or perhaps at least to make it easier to not run them on MacOS. They always run in PR builds (on Linux).

It definitely can be made to work on MacOS, as demonstrated by this sample, which does work (for me) on MacOS:
https://github.com/hyperledger/fabric-samples/tree/main/hardware-security-module
I think the key is that the PKCS#11 shared library installed as part of SoftHSM by Homebrew is not in one of the "standard" (Linux) locations searched for by the script that generates the HSM user, or by the scenario test application code. Having it use a PKCS11_LIB environment variable (if set) as the sample does may get things going.


Update modules to handle skipped/unplaced points

Add a check for defined position status before using a landmark. If missing landmarks are not allowed, generate an error message with the name of the landmark point.
Could include an option to ignore that landmark for all subjects to correct missing landmark error. Alternatively the subject could be excluded, but this may be best handled manually.
Impacted modules:

GPA
PlaceSemiLMPatches
ProjectSemiLM

check that MergeMarkups is propagating all fields

We need to add this to the next update of the GPA module for sure (i.e., before the next stable is cut). Others are not that critical


fix: revert to mdx loader v1 to fix markdown rendering

Fixes https://github.com/asyncapi/website/issues/1018
caused by https://github.com/asyncapi/website/pull/1017

/rtm


Install script fails on pg_tle extension

Bug report

[x] I confirm this is a bug with Supabase, not with my own application.
[x] I confirm I have searched the Docs, GitHub Discussions, and Discord.

Describe the bug
Running the install script for dbdev locally via npx supabase db reset results in an error.
Resetting database...
Initialising schema...
Applying migration<PHONE_NUMBER>0000_setup_test_environment.sql...
Error: ERROR: extension "pg_tle" is not available (SQLSTATE 0A000)
At statement 2: create extension if not exists pg_tle
Try rerunning the command with --debug to troubleshoot the error.
 ELIFECYCLE  Command failed with exit code 1.

To Reproduce
Create a migration using the install script and run the db reset to initialise the DB.
Expected behavior
It appears to work fine in the hosted version when doing npx supabase db push, but running it locally doesn't work for some reason.
System information

OS: macOS Ventura Version 13.3.1 (a)
Version of supabase-js: 1.38.6
Version of Node.js: 18.15.0

Looks like the pg_tle extension was not available in the db. Which docker image version are you one? It works for me on public.ecr.aws/supabase/postgres:<IP_ADDRESS>.

Looks like updating supabase to the latest version has resolved this. Thanks for your help!


node build/index.js - Dynamic require of "fs" is not supported

To Reproduce
I start today building the project again , and the build didnt work anymore
Stacktraces
If you have a stack trace to include, we recommend putting inside a <details> block for the sake of the thread's readability:

Stack trace
file:///home/app/public_html/aaaaaaaaaaaa/releases/20210611102438Z/build/index.js:11
throw new Error('Dynamic require of "' + x + '" is not supported');
^
Error: Dynamic require of "fs" is not supported
at __require (file:///home/app/public_html/aaaaaaaaaaaa/releases/20210611102438Z/build/index.js:11:9)
at node_modules/better-sqlite3/lib/database.js (file:///home/app/public_html/aaaaaaaaaaaa/releases/20210611102438Z/build/index.js:742:15)
at __require2 (file:///home/app/public_html/aaaaaaaaaaaa/releases/20210611102438Z/build/index.js:14:44)
at node_modules/better-sqlite3/lib/index.js (file:///home/app/public_html/aaaaaaaaaaaa/releases/20210611102438Z/build/index.js:816:22)
at __require2 (file:///home/app/public_html/aaaaaaaaaaaa/releases/20210611102438Z/build/index.js:14:44)
at file:///home/app/public_html/aaaaaaaaaaaa/releases/20210611102438Z/build/index.js:2687:40
at ModuleJob.run (internal/modules/esm/module_job.js:152:23)
at async Loader.import (internal/modules/esm/loader.js:177:24)
at async Object.loadESM (internal/process/esm_loader.js:68:5)

Information about your SvelteKit Installation:

Diagnostics
System:
OS: Linux 4.19 Debian GNU/Linux 10 (buster) 10 (buster)
CPU: (1) x64 Intel Core Processor (Haswell, no TSX)
Memory: 315.97 MB / 1.90 GB
Container: Yes
Shell: 5.0.3 - /bin/bash
Binaries:
Node: 14.17.0 - /usr/bin/node
npm: 6.14.13 - /usr/bin/npm
npmPackages:
@sveltejs/adapter-node: ^1.0.0-next.22 => 1.0.0-next.25
@sveltejs/kit: ^1.0.0-next.109 => 1.0.0-next.114
svelte: ^3.38.1 => 3.38.2

Please provide a reproduction.

I resolve the issue
The better-sqlite was in the devDependencies
With the old version of sveltekit builder , it was working fine , but
After the updates it not working anymore
its make the build index.js look like a client compiled script and not like a node script

I resolve the issue

I will close this then. Thanks


options

[ ] -b (doubleclick instead of a single click)
[x] -s (don't click, just scan for matches)
[x] -o (stop scanning and exit after one match)
[x] -h (hold cursor without returning it back to its original position)
[x] -r (random click point & random mousedown time)

[ ] -l 5 --limit=5 (idea)

[ ] -w 5 (window id)

[ ] -d (enable drag cursor animation)

[ ] -q (quiet)

[ ] -a (animate cursor movement)

[ ] -c  (doubleclick (2) instead of a single click or any other amount of clicks)

-p should be for printing coordinates of matching spots;
-v should be for version (verbosity should perhaps be set as #define);
-o should be replaced with -l


Support for multiple

I have a project with the need for copyDependencies to different target folders.
So I then have 2 copyDependencies, but the plugin seems to execute only the last one.
It should be easy to have any numer for copy dependencies.

Ah, seems like the solution is dependencyGroup....

Yes, dependencyGroup is the solution. If you have any other questions on usage, please ask.

This plugin is really getting to be awesome.
Still some wishes, though. Not shure how maven limitations is related.
After beeing able to pull all dependencies, I can fire up quite complex application for local debugging with just one command : mvn -Pliberty
That means I would need better version management. I have already a BOM file and letting that manage versions in dependencies would be awesome, but don't know how to achieve that. Now all versions is hardcoded, easy to miss some updates then.

@bwa I'm glad copyDependencies is working well for you. I wanted to follow up on the version management point to make sure you are aware that the versions do not need to be specified in the copyDependencies configuration. If the dependency is defined in the Maven dependencies or dependencyManagement section, the version does not need to be repeated in copyDependencies. Can you elaborate on your current configuration and what you would like to achieve?


Securyty croup acces restrictons

Hi
First of all thanks for writing this amazing app :)
I have a question i use as authentication method to log in LDAP.
An even vith LDAP_GROUPS_ENABLED and groups external name specified all users from my AD are able to login regardless of their Group member ship is there any way how to disable login to users without SG ?
And other question whit is missing from docs. Is there any way how to delete Guest User and Public group ?
Thanks for any answer :)

Hi @GamerClassN7,
Sorry for my late response.
LDAP Groups
LDAP group sync does not control access itself. There are a couple of options to do what you're trying to achieve:

Update your LDAP_USER_FILTER value to be specific to only the users you allow to log into BookStack. BookStack searches for users using this so, if it does not match during a login attempt, the user should not be allowed in.
Allow login of these users but change the "Default Registration Role" in the settings area to be a role without any permissions.

Guest User & Public Role
No way to delete these since they power the public view system. Unless you've used these elsewhere, They are effectively not used if the "Public Access" setting is disabled. If you want to be safe, You can also remove all permission from the "Public" role to prevent any content being seen if the public setting is ever accidentally enabled.

Yes, i figure out all this think :)
But my superiors aren't happy that anyone in OU can login even that he see nothing  now i setup 3 AD groups which are mapped to Viewer, Admin, Editor groups in wiki. But would be nice to have some solid like stone switch how to completely disable public group or at least give admin a permission to delete it. :) your project is analysing and with this (corporate like feature) would more and more companys. :)

Sorry for only coming back to this now.

But my superiors aren't happy that anyone in OU can login even that he see nothing now i setup 3 AD groups which are mapped to Viewer, Admin, Editor groups in wiki.

I'm not overly familiar with AD, But I'm pretty sure you could update your LDAP_USER_FILTER to check the same groups, so something along the lines of:
(&(<current_criteria>)(|(memberof=<group_1>)(memberof=<group_2>)(memberof=<group_3>)))

But would be nice to have some solid like stone switch how to completely disable public group or at least give admin a permission to delete it.

I guess it would provide some re-assurance but allow actual full deletion while still providing a route to re-enable in the future would get tricky.

Since the original questions here has been answered I'll close this off.


Refactoring: Landscape.vue

The CSS part should be moved into style/ folder

I'm going to try to fix this one

@murdos I can do this ticket if you don't have time 🙂

@murdos I can do this ticket if you don't have time 🙂

Thanks, but I would like to do it since it's not my area of expertise and I would like to try and learn.
I'll tell you if I give up so you can take over 🙂

@murdos ok 🤝

@qmonmert : I didn't create other tickets but the goal is to extract the css to tikui, so it's easy to find other part to work on this

@pascalgrimaud ok 👍

@murdos always motivated to do this? it's the last file to refactor and after that we we'll be able to refactor some global CSS

@qmonmert : feel free to pick it

@murdos sure?

@murdos sure?

Sure 😉. I'm busy with the yaml spring configuration right now and real life 😀

@pascalgrimaud https://opencollective.com/generator-jhipster/expenses/167698 🙂

@qmonmert : approved


Mention listener node in AudioStreamPlayer3D description

Mentions that by default audio is heard from the camera position, and that this can be changed with a Listener node. Closes https://github.com/godotengine/godot-docs/issues/3851

Fixed.

Thanks!

Cherry-picked for 3.2.3.


Branch Transformers Gen 1 Table Commit

I added the 1.7 to the readme. I tried to add it so as not to confuse anyone when they download the files. The table name at the top now includes the 1.7 so should be good now.


adding postcode generator for en_GB

seems that running 3 local tests is not enough :)
will provide a large array with valid codes


typecheck before launch

The Observatory must validate the model before running it.

solved by https://github.com/ReMobidyc/ReMobidyc/pull/149


Cannot change banner color

Cannot change the banner color. An index out of range error pops up for
let attributeDescription = NSMutableAttributedString(string: String("\(tempContainer[0])\n\(tempContainer[1])"))

Sorry looks like the issue was with me adding text with the displayContent.

@rlee1990  No problem, If you found any other issues feel free to open a Issue.


Switch to Number.isSafeInteger

Can't  believe I didn't know about this function.

Codecov Report

Merging #17 (abe60aa) into main (c9a6c09) will not change coverage.
The diff coverage is 100.00%.

@@            Coverage Diff            @@
##              main       #17   +/-   ##
=========================================
  Coverage   100.00%   100.00%
=========================================
  Files           14        14
  Lines         2202      2198    -4
  Branches       358       354    -4
=========================================
- Hits          2202      2198    -4

Files Changed
Coverage Δ

src/encoder.ts
100.00% <100.00%> (ø)

:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more


Refactor entity replacement code generation

Split out loading of entity definitions from an external file
into separate functions in a new HtmlEntities.Utils module.
This simultaneously fixes some Elixir 1.2 warnings regarding
piping into function calls without parentheses, and makes the
core part of entity definition loading testable.

Eh.. I just meant to fix the warnings, and then got carried away.. sorry :)

Thanks! I like the refactor. :heart: :green_heart: :blue_heart: :yellow_heart: :purple_heart:

Awesome! :bowtie:


updating input data size to match texture issue

I'm getting a debug log every frame that corresponds to the error "LoadRawTextureData: not enough data provided (will result in overread)"
This only occurs when UseAsyncGPUReadback is true

No bounding box is rendered and detected objects stays constant at 1

Hi @djsoapyknuckles,
I'm guessing there is something about Barracuda that causes strange behavior at odd resolutions.
Some resolutions in "Free Aspect" mode cause the behavior you describe, while the issue does not occur with the "16:9" aspect ratio.
Free Aspect:
https://github.com/cj-mills/barracuda-inference-yolox-demo-brp/assets/9126128/7faa27bc-a893-47aa-8730-db6b3faa0c5b
16:9 Aspect
https://github.com/cj-mills/barracuda-inference-yolox-demo-brp/assets/9126128/507887fd-bc22-4888-8e33-b89dc372059d

Ahh, I was wondering that - i have a widescreen so i sometimes pull windows out to non typical rarios to make use of the screen... I'll test it out on my end.
Thank you!

Issue resolved - that was definitely the problem. I have a widescreen, so occasionally I pull windows out to odd ratios and forget to lock aspect ratio. Thank you for the assistance!


Doesn't work with global context

I'm using global context in my app, when i pass global context to .show(context) it doesn't pop-ups

@Usamakabir07 can you describe more how it's used in your app, and provide a code snippet

with go router and global navigation key context not working


Allow customization of grid headers

Closing as focus is now switched towards basic content accessibility instead of building rich widgets.


Color picker crash (Fedora 37/flatpak/Wayland)

Preflight Checklist

[x] I agree to follow the Code of Conduct that this project adheres to.
[x] I have searched the issue tracker for a feature request that matches the one I want to file, without success.

Describe the bug
Each time I click on color picker, Drawio crash.
To Reproduce
Steps to reproduce the behavior:

Open a new diagram
Click to change color
Click on color picker
Drawio crash with the following first line :
com.jgraph.drawio.desktop.desktop[83811]: [2:0213/185139.183093:ERROR:shared_x_display.cc(39)] Unable to open display

Expected behavior
Get the color picker
draw.io version (In the Help->About menu of the draw.io editor):

diagrams.net 20.7.4
coredump.txt

Desktop (please complete the following information):

OS: Fedora 37
Drawio from flatpak com.jgraph.drawio.desktop 20.7.4

Additional context
Wayland without X11
I can attach multiple coredump if it's usefull.

We're not the author of that app, the repo is at https://github.com/flathub/com.jgraph.drawio.desktop


HoP Cloak description had a spelling error

About the PR
The examine description for the HoP Cloak said "shoudlers" instead of shoulders. The most minor thing to fix but this is the limit of my abilities.
Changelog

:cl:

fix: HoP's cloak description now correctly drapes over your shoulders instead of your "shoudlers"

you removed soul


HAWQ-255: change CHECKPOINT_START_LOCK to a fine grained scope so that checkpoint not blocked.

In some scenarios the request order of this lock and CheckpointStartLock may cause deadlock, MirroredLock and LockRelationForResynchronize()  are useless in hawq now, and it may cause deadlock in AbortTransaction()/CommitTransaction()/smgrDoDeleteActions(), so we remove them.
MirroredLock was removed at previous checkin. LockRelationForResynchronize() need to be removed here.

looks good


Define Dimensions of Belly Screen

Since the screen instructions only take an a single line of input, the <input> needs to be changed to a <textarea> to render multiple lines of text (and style needs to be updated appropriately.


⚠ Bofrost.lu has degraded performance

In fb1ad95, Bofrost.lu (https://www.bofrost.lu) experienced degraded performance:

HTTP code: 200
Response time: 1107 ms

Resolved: Bofrost.lu performance has improved in 214a219.


ci: hook fps on travis

Summary
This PR hooks Fullstack Prod Suite build on Travis.
Test plan
Issues

"THING-1234" or "Fixes #123"

Pull Request Test Coverage Report for Build 1435

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 89.472%

Totals

Change from base Build 1426:
0.0%

Covered Lines:
3952

Relevant Lines:
4417

💛  - Coveralls


There is a Helloworld.xcworkspace file in the ios folder every time I use the typescript template.

Description
Recently, I created a new project using react-native 0.70 with this command: npx react-native init ExpenseTracker ---template react-native-template-typescript. After creating it, I checked the ios folder and found the Helloworld.xcworkspace file. And when I try to run the app, it shows this error:`
error Failed to build iOS project. We ran "xcodebuild" command but it exited with error code 65. To debug build logs further, consider building your app with Xcode.app, by opening Helloworld.xcworkspace.
Command line invocation:
/Applications/Xcode.app/Contents/Developer/usr/bin/xcodebuild -workspace Helloworld.xcworkspace -configuration Debug -scheme Helloworld -destination id=1D32553F-4ADB-43DE-BD09-630294126564
User defaults from command line:
IDEPackageSupportUseBuiltinSCM = YES
`
Version
0.70
Output of npx react-native info
info Fetching system and libraries information...
System:
    OS: macOS 12.6
    CPU: (8) x64 Apple M1
    Memory: 39.34 MB / 8.00 GB
    Shell: 5.8.1 - /bin/zsh
  Binaries:
    Node: 16.17.0 - /usr/local/bin/node
    Yarn: 1.22.19 - /usr/local/bin/yarn
    npm: 8.15.0 - /usr/local/bin/npm
    Watchman: 2<IP_ADDRESS> - /opt/homebrew/bin/watchman
  Managers:
    CocoaPods: 1.11.3 - /usr/local/bin/pod
  SDKs:
    iOS SDK:
      Platforms: DriverKit 21.4, iOS 16.0, macOS 12.3, tvOS 16.0, watchOS 9.0
    Android SDK: Not Found
  IDEs:
    Android Studio: 2021.2 AI-212.5712.43.2112.8815526
    Xcode: 14.0/14A309 - /usr/bin/xcodebuild
  Languages:
    Java: <IP_ADDRESS> - /usr/bin/javac
  npmPackages:
    @react-native-community/cli: Not Found
    react: 18.1.0 => 18.1.0
    react-native: 0.70.1 => 0.70.1
    react-native-macos: Not Found
  npmGlobalPackages:
    *react-native*: Not Found

Steps to reproduce
Run this command on terminal npx react-native init ExpenseTracker --template react-native-template-typescript
And check ios folder
Snack, code example, screenshot, or link to a repository
https://github.com/younisrahman/react-native-70-issue

You should open this same issue inside https://github.com/react-native-community/react-native-template-typescript
The typescript template is not part of this repo.
I have the suspect they're including the file:
https://github.com/react-native-community/react-native-template-typescript/blob/main/template/ios/Helloworld.xcworkspace/contents.xcworkspacedata
while they should not.


UserViewController crashes for some users

Fatal Exception: RCTFatalException: Unhandled JS Exception: Network request failed

Resolved in release 1.0.5 here and here


Shouldn't upgrading an glib::WeakRef be thread safe?

GWeakRef  says it's thread safe but in the binding we panic when trying to upgrade() a glib::SendWeakRef from a thread different from the thread in which we created it. Shouldn't it also be thread safe in the rust world?

No, why would it? SendWeakRef allows to send non-Send objects to other threads as long as you only ever upgrade it from the correct thread.
WeakRef also allows sending Send objects to other threads, but not non-Send objects.

According to the docs is g_weak_ref_get() thread safe, which is the C function used in upgrade()

ok nevermind. For some reason I though  WeakRef wasn't Send nor Sync.

The problem is not GWeakRef but the object you're storing. It must be impossible to get a strong reference to a non-Send object from a different thread.


Publishing of posts not working

Is there an existing issue for this?

[X] I have searched the existing issues

Current Behavior
I just installed the package and wrote a dummy post.
I clicked published and also clicked published now instead of scheduling.
But when I go to the posts page I can't find any published posts, but it appears in drafts.
I tried publishing it again but it doesn't work.
Expected Behavior
No response
Steps To Reproduce
No response
Environment
No response
Anything else?
No response

@PaulChase Can you verify that the timestamp in the database is sometime in the past?

@PaulChase Can you verify that the timestamp in the database is sometime in the past?

The published_at column has a timestamp but yet the posts are showing as published posts

Okay I don't understand what is going on here, the posts I published last night are now showing as published after about 24hrs.
I then wrote another dummny post to test it out.
After I pubished it, it is still showing as draft in the 'canvas/posts' page.
Is there some kind of delay before a post shows as published?

It seems I've figured it out, It was difference in timezone that was the issue since canvas uses the laravel default timezone.
I just changed it to match my timezone (west african time).

It seems I've figured it out, It was difference in timezone that was the issue since canvas uses the laravel default timezone.
I just changed it to match my timezone (west african time).


Consider making use of CLI library such as urfave/cli

In current implementation there is custom abstractions in place to implement sub-commands. From one side it is reasonable since it does not require additional 3rd party dependencies, on the other hand it is a case of NIH perhaps.
At some point it may make sense to consider some lite-weight CLI "framework" like urfave/cli.
But in any case adoption should be carefully weighed.

I'd also take a look at https://github.com/spf13/cobra , it has very solid docs and adoption (e.g. it's used by most Go-based CLI tools like kubectl), and has an optional command/subcommand generator, which greatly speeds up work.

@DaniruKun Thank you for suggestions. Out of the context of this specific project I evaluated cobra. I agree to all points you highlight, the main reason for my subjective opinion against adopting it - it's relatively heavy-weight dependency. I prefer lightweight.


Add examples

Adds a set of example fab tasks for:

Configuring NTP (timesyncd) via jinja2 template
Enabling / disable Container Linux updates, and optionally running update checks

These examples have only been tested on Container Linux hosts.

Casual bystander comment: I kind of dislike this PR because those examples go against what we are pushing for at OS level (immutable infra configured upon provisioning) and against the stated goals of this repo (gather statistics, debug issues, or repair configuration issues). I'd suggest to drop the timesyncd and update_engine configuration from here and only leave the "trigger" and "status" actions.

I agree with @lucab . The update engine status stuff is OK but I would like to avoid poking update engine, etc and rely on stuff like the CLUO.

Closing this unless you have time/energy to clean this up @justaugustus


Single source for docs on external storage URLs

Compare:

https://www.cockroachlabs.com/docs/stable/import.html#import-file-temp-directory-urls
https://www.cockroachlabs.com/docs/stable/backup.html#backup-file-urls
https://www.cockroachlabs.com/docs/stable/restore.html#backup-file-urls

All document the same things in slightly different ways. We need either:

A common file we include into these docs that we change in only one place.
A separate page that these link to.

This is done.


FCM Crash:Bad notification posted from package

Android device: Samsung(SM-G610F,SM-G950F,Galaxy A5(2016),Galaxy A3(2016),SM-G955F....)
Android OS version: 7.0
Google Play Services version: 11.0.4
Firebase/Play Services SDK version: 11.0.4

crash log:
Fatal Exception: android.app.RemoteServiceException: Bad notification posted from package com.xxx.xxx: Couldn't expand RemoteViews for: StatusBarNotification(pkg=com.xxx.xxx user=UserHandle{0} id=0 tag=FCM-Notification:126882220 key=0|com.xxx.xxx|0|FCM-Notification:126882220|10173: Notification(pri=0 contentView=null vibrate=null sound=content://settings/system/notification_sound defaults=0x0 flags=0x10 color=0x00000000 vis=PRIVATE semFlags=0x0 semPriority=0))
at android.app.ActivityThread$H.handleMessage(ActivityThread.java:1813)
at android.os.Handler.dispatchMessage(Handler.java:102)
at android.os.Looper.loop(Looper.java:154)
at android.app.ActivityThread.main(ActivityThread.java:6776)
at java.lang.reflect.Method.invoke(Method.java)
at com.android.internal.os.ZygoteInit$MethodAndArgsCaller.run(ZygoteInit.java:1496)
at com.android.internal.os.ZygoteInit.main(ZygoteInit.java:1386)
Steps to reproduce:

push an message to old version app
upgrade new app from google play store
click the message push to device before
app crash

updates?

I've opened an issue with this crash here: https://issuetracker.google.com/issues/119839527

@sillysachin could you provide your code for handling the incoming notification?

I solved it by use of standard images instead of vector drawables. It was issue of Notification not being able to handle vector images.

I'm not using vector images and still got this crashes.

I'm not using vector images and still got this crashes.

me too

I'm not using vector images and still got this crashes.

me too

Same. And I am getting this only on Samsung note 9 Android 8.0


pass USER and XARGO_HOME to the Docker containers

@homunkulus r+

:hourglass: Testing commit 2a1f90f with merge 2a1f90f...

:sunny: Test successful - status-travis
Approved by: japaric
Pushing 2a1f90f8d484e75cf189ccaadda74e382cc1f5f0 to master...


remove extra replaces

Closes: #XXX
Description
no need for these anymore

For contributor use:

[ ] Targeted PR against correct branch (see CONTRIBUTING.md)
[ ] Updated relevant documentation (docs/) or specification (x/<module>/spec/)
[ ] Added a relevant changelog entry to the Unreleased section in CHANGELOG.md
[ ] Re-reviewed Files changed in the Github PR explorer

Not sure how useful dependabot is going to be, e.g. I'll often want to hold back on patch versions, e.g. IAVL.
But worth a try, and removing it if its problematic!

Not sure how useful dependabot is going to be, e.g. I'll often want to hold back on patch versions, e.g. IAVL.
But worth a try, and removing it if its problematic!

you can mark dependencies as don't update. This way you can update on your own

ah cool!


test(MigrateColumn): mock alter column to improve field compare

[x] Do only one thing
[x] Non breaking API changes
[x] Tested

What did this pull request do?

A way for improve compare field in different drivers.
We can find the following problems
postgres:
smallint -> int2
integer -> int4
bigint -> int8
decimal ->  numeric

mysql:
bool -> tinyint

sqlserver:
value, ok = columnType.DefaultValue()
// ok alway true, means default value not null

User Case Description

@jinzhu Yes, this PR should not be merged unless the issues that occurred in all drivers are fixed. Now its purpose is to find the problem in driver MigrateColum.


Upgrade quinn-proto version to fix security vulnerability

What was changed

Added a quinn-proto version requirement of 0.11.7. This ends up adding v0.11.8 to Cargo.lock.
Why?

This security issue was flagged from the python SDK, https://github.com/temporalio/sdk-python/issues/642,

We don't need to do this here -Core doesn't depend directly on this and don't need to. All that needs to happen is to run cargo update in the Python SDK so that the lock there gets the new version.


Why bias is not considered in count_linear()?

This is how nn.Linear FLOPs are counted in the current version:
def count_linear(m, x, y):
    # per output element
    total_mul = m.in_features
    # total_add = m.in_features - 1
    # total_add += 1 if m.bias is not None else 0
    num_elements = y.numel()
    total_ops = total_mul * num_elements
    m.total_ops += torch.DoubleTensor([int(total_ops)])

Link: https://github.com/Lyken17/pytorch-OpCounter/blob/master/thop/vision/basic_hooks.py#L131-L140
I noticed that it's not considering whether the Linear layer has bias, although adding the bias probably won't change the overall FLOPs a lot but still we should check for #the bias in the function right?

See https://github.com/Lyken17/pytorch-OpCounter/tree/master/benchmark for the discussion
Basically, for the simplicity, thop only considers multiplication


Update aarch64 install insturctions

Starting in CuPy v12, aarch64 wheels are now on PyPI.

/test mini


Add Ruby to Gemfile

Heroku build previews were breaking because it wasn't using .ruby-version. This does mean we have two places to update the Ruby version though. :/

Is there a better way to approach this?

It's unfortunate the this duplicates the info, but I'm a heroku n00b so I'm not sure if there's a better way. If it unblocks you, maybe it's worth holding your nose and doing.

@plaindocs @yob There's a little trick folks add to their Gemfile to work around this:
ruby File.read(".ruby-version").strip
Happy to add a fresh PR for it.

Done: https://github.com/buildkite/docs/pull/1401


Nan loss after several training iteration

❓ Questions and Help
Hi. I am training maskrcnn model with e2e_faster_rcnn_R_50_FPN_1x.yaml on coco dataset. However, after a few iterations (460), all the losses in this model become nan. I have checked the default number of class in config file, but the result (81) seems correct for coco dataset. Can anyone give me some suggestion about how to solve that? Many thanks!

Hi,
Did you change the hyper parameters for training, like number of iterations or batch size?
The loss becoming nan usually happens when you have a learning rate that is too high.
If you change the batch size, you need to adapt the learning rate / number of iterations accordingly.
For example, if you set the number of GPUs to be 1, then you need to modify the IMS_PER_BATCH to be 2, and the learning rate / etc should follow the rules in here.

Hi, all the losses keep updating after I set a smaller learning rate for the model. It seems that your suggestion works. Many thanks!

Great, thanks!
I'll update the README with more details.

Hi,
Did you change the hyper parameters for training, like number of iterations or batch size?
The loss becoming nan usually happens when you have a learning rate that is too high.
If you change the batch size, you need to adapt the learning rate / number of iterations accordingly.
For example, if you set the number of GPUs to be 1, then you need to modify the IMS_PER_BATCH to be 2, and the learning rate / etc should follow the rules in here.

Hi, because the objects in my own dataset is small, so i made two change:
_C.MODEL.RPN.ANCHOR_SIZES = (32, 64, 128, 256, 512)  ---> (16, 32, 64, 128, 256)
ANCHOR_STRIDE: (4, 8, 16, 32, 64)  ---> (2, 4, 8, 16, 32)
training after a few iterations , all the losses in this model become nan.
My lr is 0.01 and i have 4 gpu.
Why?

@guanbin1994 actually ANCHOR_STRIDE is not a free parameter of the model, but instead depends on the backbone. In your case, your feature maps should define the ANCHOR_STRIDE.
Ideally we would like to remove ANCHOR_STRIDE altogether, and this is being tracked in #87.

I just use Res101 and FPN, so what should i do?

You should keep the same ANCHOR_STRIDE, and increase the INPUT.MIN_SIZE_* and INPUT.MAX_SIZE_*.
But it will require more memory.

I also had this problem and I solved it.
As everyone mentioned in different issues raised in this repo, the problem is with the learning rate.
In my case the original setting in config file is:
BASE_LR: 0.02  |  STEPS: (60000, 80000)  | MAX_ITER: 90000
which caused nan for loss after the 3rd iteration! Then I changed it to:
BASE_LR: 0.0025  |  STEPS: (480000, 640000)  | MAX_ITER: 720000
which comes from dividing the first by 8, and multiplying the other two by 8, as suggested in the readme here.
The default setting is set for 8 GPUs. I have only 2. So, some changes were expected.


sections aren't being garbage collected

Running
dend2 = n.Section("dend2");
dend2 = n.Section("dend2");

leaves TWO sections, both called "dend2"

By MATLAB classes are value classes. To get the behavior you desire, I think it simply needs to be defined as a handle class.
See comparison of the two types at: https://www.mathworks.com/help/matlab/matlab_oop/comparing-handle-and-value-classes.html

I don't think making the Matlab class a handle class will fix this issue; the issue (as far as I understand) has to do with the C++ object not being garbage collected properly. In other words, we probably have to fix the reference count decrease for the Section by calling the correct NEURON functions in the correct order.

I think handle class specification would impact calls to underlying C++ object constructors.
If there's a need to explicitly call the C++ object destructors, then that likely requires to implement explicitly the handle class destructor to make sure the underlying C++ destructor is called.

@vijayiyer05 Making Section a handle subclass now makes matlab call delete() as expected.
@ramcdougal However, the C++ object still is not deleted properly. I have tried a few ways to delete the Section but I run into some problems. When I follow the example in https://github.com/mcdougallab/neuron-c-api-demos/blob/delete-section/delete-section-demo/delete-section-demo.cpp#L64, by using:
        function delete(self)
            self.push();
            clib.neuron.hoc_oc("delete_section()");
            clib.neuron.nrn_sec_pop();
        end

The first run (of example_allsec) goes well, but upon subsequent runs I get warnings:
nrn_test: Accessing a deleted section
 near line 0
 delete_section()
                 ^
Warning: The following error was caught while executing 'neuron.Section' class destructor:
Error using clib.neuron.nrn_sec_pop
User Library threw std::exception with message:'hoc_execerror: Accessing a deleted section'.

Error in neuron.Section/delete (line 61)
            clib.neuron.nrn_sec_pop();

Error in clearvars (line 107)
evalin('caller', clearExpr);

Error in example_allsec (line 2)
clearvars -except testCase;  % Make sure testing params are not cleared.
> In clearvars (line 107)
In example_allsec (line 2)
nrn_test: Accessing a deleted section
 near line 1
 delete_section()
                 ^
        delete_section()
nrn_test: Section access unspecified
 near line 0
 ^
Warning: The following error was caught while executing 'neuron.Section' class destructor:
Error using clib.neuron.nrn_sec_pop
User Library threw std::exception with message:'hoc_execerror: Section access unspecified'.

Error in neuron.Section/delete (line 61)
            clib.neuron.nrn_sec_pop();

Error in clearvars (line 107)
evalin('caller', clearExpr);

Error in example_allsec (line 2)
clearvars -except testCase;  % Make sure testing params are not cleared.
> In clearvars (line 107)
In example_allsec (line 2)
nrn_test: Accessing a deleted section
 near line 1
 delete_section()
                 ^
        delete_section()
nrn_test: Section access unspecified
 near line 0
 ^
Warning: The following error was caught while executing 'neuron.Section' class destructor:
Error using clib.neuron.nrn_sec_pop
User Library threw std::exception with message:'hoc_execerror: Section access unspecified'.

Error in neuron.Section/delete (line 61)
            clib.neuron.nrn_sec_pop();

Error in clearvars (line 107)
evalin('caller', clearExpr);

Error in example_allsec (line 2)
clearvars -except testCase;  % Make sure testing params are not cleared.
> In clearvars (line 107)
In example_allsec (line 2)
nrn_test: Accessing a deleted section
 near line 1
 delete_section()
                 ^
        delete_section()
nrn_test: Section access unspecified
 near line 0
 ^
Warning: The following error was caught while executing 'neuron.Section' class destructor:
Error using clib.neuron.nrn_sec_pop
User Library threw std::exception with message:'hoc_execerror: Section access unspecified'.

Error in neuron.Section/delete (line 61)
            clib.neuron.nrn_sec_pop();

Error in clearvars (line 107)
evalin('caller', clearExpr);

Error in example_allsec (line 2)
clearvars -except testCase;  % Make sure testing params are not cleared.
> In clearvars (line 107)
In example_allsec (line 2)

I am now wondering if I need to be using clib.neuron.section_unref(self.sec) in the destructor.

Update: I think it's fixed now!


g_hwnd !=0 error

rebuilt lib and injected throws this error if i click ignore hit f12 it will just crash any d3d12 game its injected to!
line throwing the error.
 static void ImGui_ImplWin32_UpdateMousePos() {     ImGuiIO& io = ImGui::GetIO();     IM_ASSERT(g_hWnd != 0);

attached with vs
A breakpoint instruction (__debugbreak() statement or a similar call) was executed in UE4Game.exe.

Having this exact same issue here. Any known fixes?

globals::mainWindow = (HWND)FindWindow(0, "Renderer: [DirectX12], Input: [Raw input], 64 bits");
you definitely need to change that


Prevent duplicates when adding data

Use Case
In our use case we are adding a dataset of articles to Weaviate. These articles have properties which are unique to each article, like title and abstract, and they have some properties which are shared over multiple articles, like author or publisher. These shared properties are modeled in our schema as individual classes.
Let me give an example to illustrate the issue we run into:

ID
Title
Author

1
Bugs are cool
John D.

2
Preferred method of squashing
Jane Doe

3
Small animals and computers
John D.

4
Using machines to evict bugs
Marie C.

Id column exists only for easy referral to the table in the following text.
Issue
During import we add an author with name "John D." and use the UUID returned when we add the article with ID 1 to link to this author. We do the same for the next article and so on.
This results in 4 separate things of class author in Weaviate of which 2 share the exact same values for all their properties (name = "John D.").
Off course we want to point the author of article 1 and 3 both to the same thing.
Possible current solutions
This is quite a challenge with the current Weaviate API. We've looked at the following:

Create a hashing function which creates a predictable UUID based on the objects field contents and use that to also create the UUID of author objects, so article 1 and 3 will both point to the same UUID. Still the object has to be created once, so some state has to be kept by the importer,
Create a key value table during import which consists of (a hash of the properties of) the author and UUID generated by Weaviate. Before creating a new thing, consult the key value table to check if the thing is already created and get the UUID form there or create the thing.
Before creating a new thing in Weaviate always first query for the existence of a thing with the same properties.

All options have there own drawbacks, but most of all, it creates a hurdle to get data into Weaviate.
Improvement proposal
A change which would really help in this case is the following:
A POST to /v1/{semanticKind} should not create a new thing if a thing with the exact same properties already exists. It should return the beacon to the existing thing instead.
I do see that this behaviour is not always the expected or intended behaviour. Switching between the current and proposed behaviour could be done based on:

query parameter. i.e. /v1/{semanticKind}?checkDuplicate=true forces the proposed behaviour
http header. A defined http header i.e. X-WEAVIATE-checkDuplicate: true is sent with the POST request to indicate the expected behaviour
specific endpoint. i.e. /v1/{semanticKind}/no-duplicates to force the proposed behaviour
a new field in the posted data object

Hi @technimad
Thanks for the very thorough issue description.
Regarding

This results in 4 separate things of class author in Weaviate of which 2 share the exact same values for all their properties (name = "John D.").
Off course we want to point the author of article 1 and 3 both to the same thing.

When about to import a potential duplicate, can't you do a simple check for a duplicate:

Give me all the authors whose name is exactly "John D."
If there is a result, take the UUID of that result
If there is no result, proceed with importing as planned and take the UUID of the new item

This way you can reuse existing APIs and you are 100% in control of what makes something a duplicate (e.g. you could compare some fields, but not all, etc.)

Yes, we could do that. Yet this would make the import code more complex and less performant. Worst case it doubles the calls made to Weaviate. The use case described above is a simplification of reality. In reality we have more than 10 related things for one article.
It's not that Weaviate is lacking functionality.
Adding functionality which detects duplicates will remove friction during the on-boarding of new data.
In our use case we will deterministically generate the uuid's based on the content of the author thing. And always POST to Weaviate. Which works, but feels like a work around which should not be needed.

@technimad do you set UUID's yourself or do you use the dynamically assigned one?

We set the uuids. If we add it and it’s a duplicate, the python lib throws a nice exception.

Aha, but that solves your problem, right? Or am I missing something

Yes.


Explicit specify jdk11 for codeql

Motivation:
The master branch requires jdk11
Modifications:
Specifiy jdk11 to use
Result:
no more failure during executing the action

@netty-bot test this please


On a desktop wallet it isn't intuitive how to get back to the login screen once logged in.

If I'm in my Dashboard after I've logged in, and then realize I'm in the wrong profile and want to go back to login screen, there isn't an intuitive way to do so. In some apps, this would be done by clicking the "Symbol from NEM" logo in the top left hand corner.

The log out button has been removed. It can go inside settings or in the right of settings in the main menu

Since the logout button is added to the settings page, this issue is fixed.


How can I run the fine-tuning on a GPU with <= 16GB of VRAM?

I've been trying to run the fine-tuning code on an NVIDIA T4 by following the configuration instructions in the README for GPUs with <= 16GB of VRAM, but I have been encountering OOM errors.
I'm using pytorch 2.01 and my configuration is as follows.
Any help will be much appreciated.
# Pretrained diffusers model path.
pretrained_model_path: cerspense/zeroscope_v2_576w

# The folder where your training outputs will be placed.
output_dir: "./outputs"

# You can train multiple datasets at once. They will be joined together for training.
# Simply remove the line you don't need, or keep them all for mixed training.

# 'image': A folder of images and captions (.txt)
# 'folder': A folder a videos and captions (.txt)
# 'json': The JSON file created with automatic BLIP2 captions using https://github.com/ExponentialML/Video-BLIP2-Preprocessor
# 'single_video': A single video file.mp4 and text prompt
dataset_types:
#   - 'image'
  - 'folder'
#   - 'json'
#   - 'single_video'

# Adds offset noise to training. See https://www.crosslabs.org/blog/diffusion-with-offset-noise
offset_noise_strength: 0.1
use_offset_noise: True

# When True, this extends all items in all enabled datasets to the highest length.
# For example, if you have 200 videos and 10 images, 10 images will be duplicated to the length of 200.
extend_dataset: False

# Caches the latents (Frames-Image -> VAE -> Latent) to a HDD or SDD.
# The latents will be saved under your training folder, and loaded automatically for training.
# This both saves memory and speeds up training and takes very little disk space.
cache_latents: False

# If you have cached latents set to `True` and have a directory of cached latents,
# you can skip the caching process and load previously saved ones.
cached_latent_dir: null #/path/to/cached_latents

# Train the text encoder. Leave at false to use LoRA only (Recommended).
train_text_encoder: False

# https://github.com/cloneofsimo/lora
# Use LoRA to train extra layers whilst saving memory. It trains both a LoRA & the model itself.
# This works slightly different than vanilla LoRA and DOES NOT save a separate file.
# It is simply used as a mechanism for saving memory by keeping layers frozen and training the residual.

# Use LoRA for the UNET model.
use_unet_lora: True

# Use LoRA for the Text Encoder.
use_text_lora: True

# The modules to use for LoRA. Different from 'trainable_modules'.
unet_lora_modules:
  - "ResnetBlock2D"

# The modules to use for LoRA. Different from `trainable_text_modules`.
text_encoder_lora_modules:
  - "CLIPEncoderLayer"

# The rank for LoRA training. With ModelScope, the maximum should be 1024.
# VRAM increases with higher rank, lower when decreased.
lora_rank: 6

# Training data parameters
train_data:

  # The width and height in which you want your training data to be resized to.
  width: 256
  height: 256

  # This will find the closest aspect ratio to your input width and height.
  # For example, 512x512 width and height with a video of resolution 1280x720 will be resized to 512x256
  use_bucketing: False

  # The start frame index where your videos should start (Leave this at one for json and folder based training).
  sample_start_idx: 1

  # Used for 'folder'. The rate at which your frames are sampled. Does nothing for 'json' and 'single_video' dataset.
  fps: 1

  # # For 'single_video' and 'json'. The number of frames to "step" (1,2,3,4) (frame_step=2) -> (1,3,5,7, ...).
  frame_step: 5

  # # The number of frames to sample. The higher this number, the higher the VRAM (acts similar to batch size).
  n_sample_frames: 2

  # 'single_video'
  single_video_path: "path/to/single/video.mp4"

  # The prompt when using a a single video file
  single_video_prompt: ""

  # Fallback prompt if caption cannot be read. Enabled for 'image' and 'folder'.
  fallback_prompt: ""

  # 'folder'
  path: "data/videos"

  # 'json'
  json_path: 'path/to/train/json/'

  # 'image'
  image_dir: 'path/to/image/directory'

  # The prompt for all image files. Leave blank to use caption files (.txt)
  single_img_prompt: ""

# Validation data parameters.
validation_data:

  # A custom prompt that is different from your training dataset.
  prompt: "A beautiful girl smiling"

  # Whether or not to sample preview during training (Requires more VRAM).
  sample_preview: False

  # The number of frames to sample during validation.
  num_frames: 2

  # Height and width of validation sample.
  width: 256
  height: 256

  # Number of inference steps when generating the video.
  num_inference_steps: 20

  # CFG scale
  guidance_scale: 13

# Learning rate for AdamW
learning_rate: 5e-6

# Weight decay. Higher = more regularization. Lower = closer to dataset.
adam_weight_decay: 1e-3

# Optimizer parameters for the UNET. Overrides base learning rate parameters.
extra_unet_params: null
  #learning_rate: 1e-5
  #adam_weight_decay: 1e-4

# Optimizer parameters for the Text Encoder. Overrides base learning rate parameters.
extra_text_encoder_params: null
  #learning_rate: 5e-6
  #adam_weight_decay: 0.2

# How many batches to train. Not to be confused with video frames.
train_batch_size: 1
gradient_accumulation_steps: 1

# Maximum number of train steps. Model is saved after training.
max_train_steps: 5000

# Saves a model every nth step.
checkpointing_steps: 1000

# How many steps to do for validation if sample_preview is enabled.
validation_steps: 0

# Which modules we want to unfreeze for the UNET. Advanced usage.
trainable_modules:
  - "all"
  # If you want to ignore temporal attention entirely, remove "attn1-2" and replace with ".attentions"
  # This is for self attetion. Activates for spatial and temporal dimensions if n_sample_frames > 1
#   - "attn1"

  # This is for cross attention (image & text data). Activates for spatial and temporal dimensions if n_sample_frames > 1
#   - "attn2"

  #  Convolution networks that hold temporal information. Activates for spatial and temporal dimensions if n_sample_frames > 1
#   - 'temp_conv'

# Which modules we want to unfreeze for the Text Encoder. Advanced usage.
trainable_text_modules:
  - "all"

# Seed for validation.
seed: 64

# Whether or not we want to use mixed precision with accelerate
mixed_precision: "fp16"

# This seems to be incompatible at the moment.
use_8bit_adam: False

# Trades VRAM usage for speed. You lose roughly 20% of training speed, but save a lot of VRAM.
# If you need to save more VRAM, it can also be enabled for the text encoder, but reduces speed x2.
gradient_checkpointing: True
text_encoder_gradient_checkpointing: True

# Xformers must be installed for best memory savings and performance (< Pytorch 2.0)
enable_xformers_memory_efficient_attention: False

# Use scaled dot product attention (Only available with >= Torch 2.0)
enable_torch_2_attn: True

Hi. Try this config, I've marked the changed lines with "New". I haven't tested it on my rig, but it should be able to sustain under 16GB VRAM. These settings effectively enable LoRA only training. I've also added save_pretrained_model, which is always true, but you can disable it here by setting it to false if you like.
If you can't get memory savings using Pytorch 2.0, try enabling Xformers if you can, and you can try enabling validation previews as well to see if it works.
# Pretrained diffusers model path.
pretrained_model_path: cerspense/zeroscope_v2_576w

# The folder where your training outputs will be placed.
output_dir: "./outputs"

# You can train multiple datasets at once. They will be joined together for training.
# Simply remove the line you don't need, or keep them all for mixed training.

# 'image': A folder of images and captions (.txt)
# 'folder': A folder a videos and captions (.txt)
# 'json': The JSON file created with automatic BLIP2 captions using https://github.com/ExponentialML/Video-BLIP2-Preprocessor
# 'single_video': A single video file.mp4 and text prompt
dataset_types:
#   - 'image'
  - 'folder'
#   - 'json'
#   - 'single_video'

# Adds offset noise to training. See https://www.crosslabs.org/blog/diffusion-with-offset-noise
offset_noise_strength: 0.1
use_offset_noise: True

# When True, this extends all items in all enabled datasets to the highest length.
# For example, if you have 200 videos and 10 images, 10 images will be duplicated to the length of 200.
extend_dataset: False

# Caches the latents (Frames-Image -> VAE -> Latent) to a HDD or SDD.
# The latents will be saved under your training folder, and loaded automatically for training.
# This both saves memory and speeds up training and takes very little disk space.
cache_latents: True # New

# If you have cached latents set to `True` and have a directory of cached latents,
# you can skip the caching process and load previously saved ones.
cached_latent_dir: "./outputs" # New

# New / Assuming you want to use with webui
# https://github.com/cloneofsimo/lora
# Use LoRA to train extra layers whilst saving memory. It trains both a LoRA & the model itself.
# This works slightly different than vanilla LoRA and DOES NOT save a separate file.
# It is simply used as a mechanism for saving memory by keeping layers frozen and training the residual.
# The LoRA rank for each is hard coded at `16`. Go higher and we're back where we started :-).

lora_version: "stable_lora"

# This saves a LoRA that is compatible with the text2video webui extension.
# It only works when the lora version is 'stable_lora'.
# This is also a DIFFERENT implementation than Kohya's, so it will not work the same as that implementation.
save_lora_for_webui: True

# The LoRA file will be converted to a different format to be compatible with the webui extension.
# The difference between this and 'save_lora_for_webui' is that you can continue training a Diffusers pipeline model
# when this version is set to False
only_lora_for_webui: False

# Train the text encoder. Leave at false to use LoRA only (Recommended).
train_text_encoder: False

# https://github.com/cloneofsimo/lora
# Use LoRA to train extra layers whilst saving memory. It trains both a LoRA & the model itself.
# This works slightly different than vanilla LoRA and DOES NOT save a separate file.
# It is simply used as a mechanism for saving memory by keeping layers frozen and training the residual.

# Use LoRA for the UNET model.
use_unet_lora: True

# Use LoRA for the Text Encoder.
use_text_lora: True

# The modules to use for LoRA. Different from 'trainable_modules'.
unet_lora_modules: # New
  - "ResnetBlock2D"
  - "TransformerTemporalModel" # New / Remove this line if you get OOM
  - "Transformer2DModel"
  - "CrossAttention"
  - "Attention"
  - "GEGLU"

# The modules to use for LoRA. Different from `trainable_text_modules`.
text_encoder_lora_modules:
  - "CLIPAttention" # New

# The rank for LoRA training. With ModelScope, the maximum should be 1024.
# VRAM increases with higher rank, lower when decreased.
lora_rank: 4 # New

# Training data parameters
train_data:

  # The width and height in which you want your training data to be resized to.
  width: 256
  height: 256

  # This will find the closest aspect ratio to your input width and height.
  # For example, 512x512 width and height with a video of resolution 1280x720 will be resized to 512x256
  use_bucketing: False

  # The start frame index where your videos should start (Leave this at one for json and folder based training).
  sample_start_idx: 1

  # Used for 'folder'. The rate at which your frames are sampled. Does nothing for 'json' and 'single_video' dataset.
  fps: 1

  # # For 'single_video' and 'json'. The number of frames to "step" (1,2,3,4) (frame_step=2) -> (1,3,5,7, ...).
  frame_step: 1 # New

  # # The number of frames to sample. The higher this number, the higher the VRAM (acts similar to batch size).
  n_sample_frames: 8 # New

  # 'single_video'
  single_video_path: "path/to/single/video.mp4"

  # The prompt when using a a single video file
  single_video_prompt: ""

  # Fallback prompt if caption cannot be read. Enabled for 'image' and 'folder'.
  fallback_prompt: ""

  # 'folder'
  path: "data/videos"

  # 'json'
  json_path: 'path/to/train/json/'

  # 'image'
  image_dir: 'path/to/image/directory'

  # The prompt for all image files. Leave blank to use caption files (.txt)
  single_img_prompt: ""

# Validation data parameters.
validation_data:

  # A custom prompt that is different from your training dataset.
  prompt: "A beautiful girl smiling"

  # Whether or not to sample preview during training (Requires more VRAM).
  sample_preview: False

  # The number of frames to sample during validation.
  num_frames: 8 # New

  # Height and width of validation sample.
  width: 256
  height: 256

  # Number of inference steps when generating the video.
  num_inference_steps: 20

  # CFG scale
  guidance_scale: 13

# Learning rate for AdamW
learning_rate: 5e-6

# Weight decay. Higher = more regularization. Lower = closer to dataset.
adam_weight_decay: 1e-3

# Optimizer parameters for the UNET. Overrides base learning rate parameters.
extra_unet_params: null
  #learning_rate: 1e-5
  #adam_weight_decay: 1e-4

# Optimizer parameters for the Text Encoder. Overrides base learning rate parameters.
extra_text_encoder_params: null
  #learning_rate: 5e-6
  #adam_weight_decay: 0.2

# How many batches to train. Not to be confused with video frames.
train_batch_size: 1
gradient_accumulation_steps: 1

# Maximum number of train steps. Model is saved after training.
max_train_steps: 5000

# Saves a model every nth step.
checkpointing_steps: 1000

# Save full pretrained model.
save_pretrained_model = True # New

# How many steps to do for validation if sample_preview is enabled.
validation_steps: 200 # New

# Which modules we want to unfreeze for the UNET. Advanced usage.
trainable_modules: null # New
  #- "all"
  # If you want to ignore temporal attention entirely, remove "attn1-2" and replace with ".attentions"
  # This is for self attetion. Activates for spatial and temporal dimensions if n_sample_frames > 1
#   - "attn1"

  # This is for cross attention (image & text data). Activates for spatial and temporal dimensions if n_sample_frames > 1
#   - "attn2"

  #  Convolution networks that hold temporal information. Activates for spatial and temporal dimensions if n_sample_frames > 1
#   - 'temp_conv'

# Which modules we want to unfreeze for the Text Encoder. Advanced usage.
trainable_text_modules: null # New

# Seed for validation.
seed: 64

# Whether or not we want to use mixed precision with accelerate
mixed_precision: "fp16"

# This seems to be incompatible at the moment.
use_8bit_adam: False

# Trades VRAM usage for speed. You lose roughly 20% of training speed, but save a lot of VRAM.
# If you need to save more VRAM, it can also be enabled for the text encoder, but reduces speed x2.
gradient_checkpointing: True
text_encoder_gradient_checkpointing: True

# Xformers must be installed for best memory savings and performance (< Pytorch 2.0)
enable_xformers_memory_efficient_attention: False

# Use scaled dot product attention (Only available with >= Torch 2.0)
enable_torch_2_attn: True

Thank you for the reply!
When fine-tuning with the configuration above, I get an ZeroDivisionError: division by zero error in the line num_train_epochs = math.ceil(max_train_steps / num_update_steps_per_epoch).
If I change the configuration line cached_latent_dir: "./outputs" to cached_latent_dir: null, it works.

Thank you for the reply! When fine-tuning with the configuration above, I get an ZeroDivisionError: division by zero error in the line num_train_epochs = math.ceil(max_train_steps / num_update_steps_per_epoch). If I change the configuration line cached_latent_dir: "./outputs" to cached_latent_dir: null, it works.

Glad it's working for you! Yes, this was my bad. For cached latents to work, it should be cache_latents: True.


Wireless 4 scenes switch: 'NLDP' is not a valid DeviceType

It seems that my Wireless 4 scenes switch (bought as Legrand 756368) is reported as "NLDP" which seems to break the Netatmo Home Assistant integration. I've opened a relevant bug here: https://github.com/home-assistant/core/issues/91755
The issue actually comes from this library, which doesn't include NLDP as a DeviceType.
Traceback (most recent call last):
  File "/usr/local/lib/python3.11/site-packages/pyatmo/home.py", line 72, in get_module
    return getattr(modules, module["type"])(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
AttributeError: module 'pyatmo.modules' has no attribute 'NLDP'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/src/homeassistant/homeassistant/config_entries.py", line 387, in async_setup
    result = await component.async_setup_entry(hass, self)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/src/homeassistant/homeassistant/components/netatmo/__init__.py", line 185, in async_setup_entry
    await data_handler.async_setup()
  File "/usr/src/homeassistant/homeassistant/components/netatmo/data_handler.py", line 153, in async_setup
    await self.subscribe(ACCOUNT, ACCOUNT, None)
  File "/usr/src/homeassistant/homeassistant/components/netatmo/data_handler.py", line 244, in subscribe
    await self.async_fetch_data(signal_name)
  File "/usr/src/homeassistant/homeassistant/components/netatmo/data_handler.py", line 200, in async_fetch_data
    await getattr(self.account, self.publisher[signal_name].method)(
  File "/usr/local/lib/python3.11/site-packages/pyatmo/account.py", line 69, in async_update_topology
    self.process_topology()
  File "/usr/local/lib/python3.11/site-packages/pyatmo/account.py", line 58, in process_topology
    self.homes[home_id] = Home(self.auth, raw_data=home)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/pyatmo/home.py", line 49, in __init__
    self.modules = {
                   ^
  File "/usr/local/lib/python3.11/site-packages/pyatmo/home.py", line 50, in <dictcomp>
    module["id"]: self.get_module(module)
                  ^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/pyatmo/home.py", line 78, in get_module
    return getattr(modules, "NLunknown")(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/pyatmo/modules/module.py", line 520, in __init__
    self.device_type = DeviceType(module["type"])
                       ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/enum.py", line 712, in __call__
    return cls.__new__(cls, value)
           ^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/enum.py", line 1128, in __new__
    raise ve_exc
ValueError: 'NLDP' is not a valid DeviceType

Please add a  missing function  in DeviceType to redirect to NLunknow or fake pyatmo device to not fail each time legrand create a new device type

@jabesq I've updated my original issue and title. Hope that helps. Thanks


Missing overload for document.createElementNS() function

The createElementNS function has an optional third parameter, options, that can be either a string(for backwards compatibility) or an object. The document.createElement() function already has an equivalent function overload being generated, createElement(tagName: string, options?: ElementCreationOptions): HTMLElement;.
There should be an overload signature like this:
createElementNS(namespaceURI: string, qualifiedName: string, options?: ElementCreationOptions): Element;
There are existing overloads for createElementNS located in the AddedTypes JSON file, but the overloads for createElement are in the emitter.ts file, this inconsistency raises the question, in my mind, where should the additional overload for createElementNS be located?

where should the additional overload for createElementNS be located?

addedTypes.json


Review, please -- "simple" example for command-line program

For issue #1540
This PR is more for review & guidance than for merging (though it is mergeable best I can tell).
I'm looking to see if I'm heading in the right direction before I go too far along.
Things I'd like to understand/address include:

How should I test this code?
Is it OK to create an executable uberjar?  (I'm using this for manual command-line testing)
Is there a better way to detect "isatty"?
Did I pick the right directory and/or package for this work?

The initial commits are all code.
Before I write up separate documentation, I'd like working code to back up those docs.

Hi, sorry for the late response. I have been traveling with family. It may take me some time to get to this.


Proper error definition on BulkOps features

Add proper error definition to the audit log on the below feature

Single delete/create user
Bulk create user
Bulk add/remove users from groups.

Update on better error handling #452


baseic active admin setup closes #22

Coverage remained the same at 100.0% when pulling 392a34bc18b001d1120b55d3bdc2a652d803161d on activeadmin-#22 into fa64e82924331ba639a923bd9cde8454f5bca8fa on develop.


Loading chunk failed

This plugin is causing my JS chunks to not load.
I'm getting errors like,

Loading chunk 25 failed

Simply removing the plugin makes the problem go away.
Under this plugin, the CSS and JS should have different filenames as I understand it, but that's not what webpack is trying to load:

I'm using a runtime chunk:
            optimization: {
                minimize: false,
                removeAvailableModules: false,
                runtimeChunk: 'single',
            }

I suspect that doesn't play well with this plugin?
Versions, for your reference:
❯ yarn list | grep webpack
├─<EMAIL_ADDRESS>│  └─<EMAIL_ADDRESS>│  └─<EMAIL_ADDRESS>├─<EMAIL_ADDRESS>│  ├─<EMAIL_ADDRESS>├─<EMAIL_ADDRESS>├─<EMAIL_ADDRESS>│  ├─<EMAIL_ADDRESS>├─<EMAIL_ADDRESS>│  └─<EMAIL_ADDRESS>├─<EMAIL_ADDRESS>│  ├─<EMAIL_ADDRESS>│  ├─<EMAIL_ADDRESS>├─<EMAIL_ADDRESS>├─<EMAIL_ADDRESS>├─<EMAIL_ADDRESS>├─<EMAIL_ADDRESS>│  ├─<EMAIL_ADDRESS>│  └─<EMAIL_ADDRESS>└─<EMAIL_ADDRESS>   └─<EMAIL_ADDRESS>
Let me know if there's anything else you need. I'm going to disable this for now.

I can't reproduce this problem.
runtimeChunk is supported and tested (https://github.com/scinos/webpack-plugin-hash-output/tree/master/test/runtime-chunk), so it should work. I tried with the other two options (minimize and removeAvailableModules) just to be sure and it still works for me.
I suspect this is caused by extract-text-webpack-plugin. Note that this plugin is not compatible with Webpack 4 (see first warning in https://github.com/webpack-contrib/extract-text-webpack-plugin), so I'd suggest to update your config to use https://github.com/webpack-contrib/mini-css-extract-plugin instead.

I figured out the "CSS ordering issue" -- wasn't an ordering issue at all, it was cssnano changing my z-indexes. Speaking of, I'll try disabling postcss altogether and see if that changes anything...
Nope. Same result. it's not in the entry chunk, but one that's included later at runtime.
The CSS chunk that does load appears to be a combined chunk -- the contents appear to be from two different CSS files. I'm not sure what was supposed to be in that JS chunk that's 404ing, but it was something critical to a particular page in my app.
Not sure if that's at all helpful.


Update app-lifecycle.md

Fix the link of "GetDeferral" to go to the specific page. The current link goes to documentation that is too broad and not specific about GetDeferral.

@thalesx : Thanks for your contribution! The author(s) have been notified to review your proposed change.

Looks good! Thanks for your contribution. I'll complete this and then it should show up on the docs page within a day or two.


[Enhancement] The Images of Books and Audiobooks are not of the same size

Description
The Images in Cards are not taking equal height because of different aspect-ratio, this can be fixed by making all images same height using object-fit or aligning all of them center.
Screenshots

Checklist

[X] I have checked the existing issues
[X] I have read the [Contributing Guidelines]
[X] I have read the discussion tab thoroughly and got the project idea
[X] I am willing to work on this issue (optional)
[X] I am a GSSoC'23 contributor

Please Assign me this issue under GSSoC 23

@rohansx Please review PR #363 merging that PR closes this issue

@ManasMadan You don't need to do anything as I'm adding these labels, this will assist the organizers in reviewing the PRs and assigning points accordingly.

@rohansx Ok Thanks for the reply, one of the few repo where mentors are active. Appreciated !!!


Blocking for candidate generation

Implementation:

Computes blocks
Computes similarities within each block
Merges the similarities in a sorted way
Removes duplicates that may exist since a record may be in multiple blocks
Enforces any k value on the whole merged set

I've clarified in the docstring that this is an experimental feature. I'd like to run some more benchmarks on it.