If I ReplaceComponent many times in one frame, Reactive System only call once. How to fix this?

Some "ReplaceComponent"s lose, does't call Reactive System.

"If I ReplaceComponent many times in one frame, Reactive System only call once. How to fix this" - this is desired behaviour

Reactive Systems are designed to aggregate changes until Execute is called.
If you replace a component multiple time, that actually only triggers the system once and the latest data will be read once you call execute

e.ReplacePosition3(new Vector3(0, 0, 0));
e.ReplacePosition3(new Vector3(1, 0, 0));
e.ReplacePosition3(new Vector3(2, 0, 0));

a reactive system with a trigger on Matcher.Position3 will collect the entity and when you call execute it and read the entity's position, you will read new Vector3(2, 0, 0)

e.ReplacePosition3(new Vector3(0, 0, 0));
e.ReplacePosition3(new Vector3(1, 0, 0));
e.ReplacePosition3(new Vector3(2, 0, 0));

a reactive system with a trigger on Matcher.Position3 will collect the entity and when you call execute it and read the entity's position, you will read new Vector3(2, 0, 0)

So that if I have some codes, need to react everytime I call replacePosition, even in one frame.
The codes should move out of the PositionReactiveSystem?

Reactive Systems are designed to aggregate changes until Execute is called.
If you replace a component multiple times, that actually only triggers the system once and the latest data will be read once you call execute

I do some experiments to take it in.

The ReactiveSystem.GetTrigger() collect what HAVE I triggered (Add(), Replace(), Remove()). (every frame once)
The ReactiveSystem.Filter() check what is it NOW.
If A_ReactiveSystem then B_ReactiveSystem, and B_ReactiveSystem.Execute() triggers A_ReactiveSystem.GetTrigger(), then A_ReactiveSystem will react next frame.

Anything I miss?
I had read the wiki.
https://github.com/sschmid/Entitas-CSharp/wiki/Systems

My original usage is AttackerEntity throw a DamageComponent to BehiterEntity.
Then ReactiveSystem deals with the Trigger“damage.add()”.
I should find another way to write this.

This is not how you should do this. There are a problem that in one frame you can receive several damage entries, and you need to count all of them. Because, for example, your entity have 2 health, and it attacked by three different player entities - each deal 1 damage, you need to know who is deal latest damage before entity dies.
Right thing is doing this - make and component that have List of damages that dealed, and make a reactive system that react to changes of that list. And system will determine how much damage is dealed.
// Component
[Umpire]
public sealed class DamageComponent : IComponent {
	public List<ADamage> List;
	public static implicit operator List<ADamage>(DamageComponent component) => component.List;
	public override string ToString() => "Damage";
}

// AbstractDamage
public abstract class ADamage {
	public readonly EDamageType Type;

	public WeaponId AttackUid;
	public InstanceId Applicator;

	public float Power;
	public float Lifesteal;
	public bool IsCritical;

	protected ADamage(EDamageType type) { Type = type; }
	public abstract float Evaluate(Character target);
}

// Processing damage
public class DamageSystem : ReactiveSystem<UmpireEntity>, ICleanupSystem {
	private readonly IClock _clock;
	private readonly List<UmpireEntity> _clean = new List<UmpireEntity>();

	public DamageSystem(UmpireContext umpire, IClock clock) : base(umpire) {
		_clock = clock;
	}

	protected override ICollector<UmpireEntity> GetTrigger(IContext<UmpireEntity> context)
		=> context.CreateCollector(
			UmpireMatcher.AllOf(
				UmpireMatcher.Character,
				UmpireMatcher.Damage,
				UmpireMatcher.AppliedDamage
			)
		);

	protected override bool Filter(UmpireEntity entity)
		=> entity.hasDamage && entity.hasAppliedDamage && entity.hasCharacter && entity.damage.List.Count > 0;

	protected override void Execute(List<UmpireEntity> entities) {
		foreach (var entity in entities) {
			if (!entity.isDead)
				ProcessDamageList(entity);
			_clean.Add(entity);
		}
	}

	private void ProcessDamageList(UmpireEntity entity) {
		var character = entity.character.Reference;
		var shield = 0f;
		var health = entity.health.Value;
		var bubble = false;
		foreach (var damage in entity.damage.List) {
			var trueDamage = damage.Evaluate(character);

			if (ProcessShieldAndAfterItHaveAnyLeft(entity, ref shield, ref trueDamage))
				continue;

			bubble = true;

			ProcessDamageEntry(entity, damage, ref trueDamage, ref health);
			ProcessLifesteal(damage, trueDamage);

			// system that determine that entity is dead - next down execution order
			if (health.IsZero())
				break;
		}

		if (bubble)
			entity.ReplaceAppliedDamage(entity.appliedDamage.List);
	}

	private static bool ProcessShieldAndAfterItHaveAnyLeft(UmpireEntity entity, ref float shield, ref float trueDamage) {	}

	private void ProcessDamageEntry(UmpireEntity entity, ADamage damage, ref float trueDamage, ref float health) {
		trueDamage = trueDamage.Min(health);
		entity.ApplyHealth(-trueDamage);
		entity.appliedDamage.List.Add(
			new DamageApplied {
				Applicator = damage.Applicator.id.Value
				AppliedAt = _clock.Time,
				Damage = trueDamage,
				Type = damage.Type,
				IsCritical = damage.IsCritical
			}
		);
	}

	private static void ProcessLifesteal(ADamage damage, float trueDamage) {
		if (damage.Lifesteal > 0f)
			damage.Applicator.ApplyLifesteal(trueDamage * damage.Lifesteal);
	}

	public void Cleanup() {
		foreach (var entity in _clean)
			entity.damage.List.Clear();
		_clean.Clear();
	}
}

My original usage is AttackerEntity throw a DamageComponent to BehiterEntity.
Then ReactiveSystem deals with the Trigger“damage.add()”.
I should find another way to write this.

This is not how you should do this. There are a problem that in one frame you can receive several damage entries, and you need to count all of them. Because, for example, your entity have 2 health, and it attacked by three different player entities - each deal 1 damage, you need to know who is deal latest damage before entity dies.
Right thing is doing this - make and component that have List of damages that dealed, and make a reactive system that react to changes of that list. And system will determine how much damage is dealed.
// Component
[Umpire]
public sealed class DamageComponent : IComponent {
	public List<ADamage> List;
	public static implicit operator List<ADamage>(DamageComponent component) => component.List;
	public override string ToString() => "Damage";
}

// AbstractDamage
public abstract class ADamage {
	public readonly EDamageType Type;

	public WeaponId AttackUid;
	public InstanceId Applicator;

	public float Power;
	public float Lifesteal;
	public bool IsCritical;

	protected ADamage(EDamageType type) { Type = type; }
	public abstract float Evaluate(Character target);
}

// Processing damage
public class DamageSystem : ReactiveSystem<UmpireEntity>, ICleanupSystem {
	private readonly IClock _clock;
	private readonly List<UmpireEntity> _clean = new List<UmpireEntity>();

	public DamageSystem(UmpireContext umpire, IClock clock) : base(umpire) {
		_clock = clock;
	}

	protected override ICollector<UmpireEntity> GetTrigger(IContext<UmpireEntity> context)
		=> context.CreateCollector(
			UmpireMatcher.AllOf(
				UmpireMatcher.Character,
				UmpireMatcher.Damage,
				UmpireMatcher.AppliedDamage
			)
		);

	protected override bool Filter(UmpireEntity entity)
		=> entity.hasDamage && entity.hasAppliedDamage && entity.hasCharacter && entity.damage.List.Count > 0;

	protected override void Execute(List<UmpireEntity> entities) {
		foreach (var entity in entities) {
			if (!entity.isDead)
				ProcessDamageList(entity);
			_clean.Add(entity);
		}
	}

	private void ProcessDamageList(UmpireEntity entity) {
		var character = entity.character.Reference;
		var shield = 0f;
		var health = entity.health.Value;
		var bubble = false;
		foreach (var damage in entity.damage.List) {
			var trueDamage = damage.Evaluate(character);

			if (ProcessShieldAndAfterItHaveAnyLeft(entity, ref shield, ref trueDamage))
				continue;

			bubble = true;

			ProcessDamageEntry(entity, damage, ref trueDamage, ref health);
			ProcessLifesteal(damage, trueDamage);

			// system that determine that entity is dead - next down execution order
			if (health.IsZero())
				break;
		}

		if (bubble)
			entity.ReplaceAppliedDamage(entity.appliedDamage.List);
	}

	private static bool ProcessShieldAndAfterItHaveAnyLeft(UmpireEntity entity, ref float shield, ref float trueDamage) {
		// to much code for example xD
	}

	private void ProcessDamageEntry(UmpireEntity entity, ADamage damage, ref float trueDamage, ref float health) {
		trueDamage = trueDamage.Min(health);
		entity.ApplyHealth(-trueDamage); // Shortcut extension - like entity.appliedHealth.List.Add(-trueDamage); entity.ReplaceAppliedHelath(entity.appliedHealth.List);
		// This lis holds all damages that received, and you can determine who kills who and who assists
		entity.appliedDamage.List.Add(
			new DamageApplied {
				Applicator = damage.Applicator.id.Value
				AppliedAt = _clock.Time,
				Damage = trueDamage,
				Type = damage.Type,
				IsCritical = damage.IsCritical
			}
		);
	}

	private static void ProcessLifesteal(ADamage damage, float trueDamage) {
		if (damage.Lifesteal > 0f)
			damage.Applicator.ApplyLifesteal(trueDamage * damage.Lifesteal);
	}

	public void Cleanup() {
		foreach (var entity in _clean)
			entity.damage.List.Clear();
		_clean.Clear();
	}
}

Thank you so much for sharing your codes to me :D
To memory a damage list instead of one damage component, clean it up at every end of the frame.
It solved my problem.
The “abstract” part also open up my eyes.


bug: Hang calling statusBedrock with unreachable server

Describe the bug:
Calling statusBedrock against a host that does not respond appears to cause a hang waiting for a promise to resolve.
Using the code below as the only code in a node script works successfully when targeting an online host/port combination. I see all the expected output and then the node process exits.
Changing to an IP address where there is no server and running the same code results in:
statusBedrock returned
Promise rejected
Failed to retrieve the status of the server within time

but then node never exits.
Code:
mcsutil.statusBedrock(server, {port:19132, timeout: 2000})
    .then((response) => {
        console.log("Promise resolved");
        console.log(response);
    })
    .catch((error) => {
        console.log("Promise rejected");
        console.log(error);
    });
console.log("statusBedrock returned");

Expected behavior:
When a bedrock server is unavailable the code above should exit cleanly on completion.
Additional context
The issue may be similar to https://github.com/PassTheMayo/minecraft-server-util/issues/27
I have tried to repro a simple case by simulating readPacket never resolving (as that was my suspicion) but cannot get into the same situation.

I was able to reproduce this issue on the most recent commit. I've determined that the source of the issue is that the UDP socket that is created never gets destroyed when there is an error located elsewhere. This was simply fixed by socket.unref() in the UDP socket class. I've published 3.4.3 just now which has fixed this issue. Let me know if you have any more problems.

Many thanks @PassTheMayo for your amazing response! Just tried it now and all looks good. Really appreciate having one package that happily queries both java and bedrock editions.

No problem! Glad my package suits your needs.


Fixing NodeGatewayStartedShards bwc (de)serialization issues

Signed-off-by: Andriy Redko<EMAIL_ADDRESS>Description
The bwc (de)serialization issue has been introduced by [1], breaking the main builds (fe [2])
[1] https://github.com/opensearch-project/OpenSearch/pull/4252
[2] https://build.ci.opensearch.org/job/gradle-check/1896/testReport/junit/org.opensearch.backwards/MixedClusterClientYamlTestSuiteIT/test__p0_indices_open_20_multiple_indices_Only_wildcard_/
Issues Resolved
N/A
Check List

[ ] New functionality includes testing.

[ ] All tests pass

[ ] New functionality has been documented.

[ ] New functionality has javadoc added

[X] Commits are signed per the DCO using --signoff

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
For more information on following Developer Certificate of Origin and signing off your commits, please check here.

@dreamer-89 fyi


[Bug]: Issues with CORS configuration, Duplicate Routes, and Environment Variables in Backend

Is there an existing issue for this?

[X] I have searched the existing issues

Describe the bug
There are multiple issues in the backend of the application:

CORS Configuration Issue: The origin field in the CORS middleware is set twice, leading to conflicts and overwriting of the allowed origin.
Duplicate Routes: The /admin route is defined twice, which could cause unexpected behavior.
Environment Variable Issue: The environment variables PORT and MONGO_URL are incorrectly accessed as process.env.sample.PORT and process.env.sample.MONGO_URL, causing errors during the application startup.

Tell Us What You See!

CORS Issue: The application fails to properly handle requests from the frontend due to conflicting CORS settings.
Duplicate Routes: One of the /admin routes behaves unexpectedly or is ignored due to the second route definition.
Environment Variables Issue: The application throws an error stating that MONGO_URL is undefined, which prevents the app from connecting to the database.

Expected behavior

The CORS configuration should allow requests from the correct origin without conflicts.
The duplicate route issue should be resolved, ensuring that only one /admin route exists.
The environment variables (PORT and MONGO_URL) should be correctly accessed from the .env file, and the application should start without errors.

Add ScreenShots
No response
On which device are you experiencing this bug?
Chrome, Windows
Record

[X] I have read the Contributing Guidelines
[X] I'm a GSSOC'24 contributor
[X] I have starred the repository

Is there an existing issue for this?

[x]  I have searched the existing issues

Describe the bug
There are multiple issues in the backend of the application:

CORS Configuration Issue: The origin field in the CORS middleware is set twice, leading to conflicts and overwriting of the allowed origin.
Duplicate Routes: The /admin route is defined twice, which could cause unexpected behavior.
Environment Variable Issue: The environment variables PORT and MONGO_URL are incorrectly accessed as process.env.sample.PORT and process.env.sample.MONGO_URL, causing errors during the application startup.

Tell Us What You See!

CORS Issue: The application fails to properly handle requests from the frontend due to conflicting CORS settings.
Duplicate Routes: One of the /admin routes behaves unexpectedly or is ignored due to the second route definition.
Environment Variables Issue: The application throws an error stating that MONGO_URL is undefined, which prevents the app from connecting to the database.

Expected behavior

The CORS configuration should allow requests from the correct origin without conflicts.
The duplicate route issue should be resolved, ensuring that only one /admin route exists.
The environment variables (PORT and MONGO_URL) should be correctly accessed from the .env file, and the application should start without errors.

Add ScreenShots
No response
On which device are you experiencing this bug?
Chrome, Windows
Record

[x]  I have read the Contributing Guidelines
[x]  I'm a GSSOC'24 contributor
[x]  I have starred the repository

Hello @chikatlarakesh, Go for it
All the Best


Reader module: Angularize

The outbreak_time_series_reader module should be vanilla ES5 for maximal reusability in old browsers and even in context which where there is no browsers.
Separately there should be an Angular data service which uses the outbreak_time_series_reader module to parse and model the data but which provides the data to SPAs a la Angular style (Promises, Service, etc.).

Early prototyping of code used [angular-dsv](https://www.npmjs.com/package/angular-dsv]. Clearly this violated the above implied architecture. Next rev should have CSV parsing happening in the outbreak_time_series_reader module. The Angularization happens outside that module. Angular's $http or $resource loads the data and uses the outbreak_time_series_reader module to model the data.

Maybe this thing should just be called OutbreakReader.


Update OTEL to v0.71.0

Description of change
This updates OpenTelemetry Collector, FN fork of it and contrib packages to latest released version, which is v0.71.0
Checklist

[x] Tested in playground or other setup
[x] Screenshot (Grafana) from playground added to PR for 15+ minute run

This change is

@kwapik Looked at the profile. key takes about 2% – just as before. The Get() in the loop, that's possible quadratic takes 0.27%, so it's not a problem now, but it's "on the edge". Eg. if we have 10× more labels, we'd have 100× slowdown and Get() would be at ~27%. Worth addressing in the future.


add warning about long npm install command

What did you experience? Which part of the install was slow for you?

I'm pretty sure it was the install of esy. It's not actually much slower than I would expect, but npm gives no visual feedback when installing from git, it just spins and looks like its frozen or failed or something.
It's been a visual feedback issue for a few people I've helped install, not so much a length of install time issue.

@bassjacob Were they binary installs? Binary installs don't install esy at all. They merely install the result of a build. Only dev builds install esy.

Ah, was still looking at master, not the binary tag. Perfect, if we're moving away from installing esy then we can just ignore this 😄

esy is just a tool that helps us package up opam packages on npm, and by the time you even get an npm package, esy has deleted itself. (The exception is dev packages which go through the whole process - most people don't install those)


perf(base): sent low memory notification when worker switches to retired state

What kind of change does this PR introduce?
Enhancement
Description
When the worker is retired early by the supervisor, provide timing to run GC forcibly.

prefix as a fix so it'd make a version bump


JAVA-882 - skipping index rows that belong to another table

Thanks @bdeggleston.
Your fix works, but I prefer filtering index rows upstream, as is already done for columns. I've pushed changes to #430 directly, I cherry-picked your unit test there.


Perfected A LOT the register/login system. Now accounts are verified …

…via an email and users can retrieve passwords when the forget them

Hello! I added all new functionality for the register and login systems. What is missing is the merging with DiscourseConnect in order to be able to have the future connected with the same login system. Working on that the next days.


White shadows issue in JPEG image sequence in iOS AR app having linear color space

I am seeing the shadows coming white in the JPEG image sequences on iOS in our AR app having Linear color space built with Unity 2022.3.16f1. On Android, the shadows look fine but on iOS all shadows appear white in the JPEG image sequences. I am using VideoKit version 0.0.18alpha2 and Function version 0.0.4.
Also, just for your reference, the shadows are coming fine in the MP4 video recorded with the same asset on the same device with the same app.
I have attached the shader I am using for casting shadows on detected planes along with a demo image of the JPEG sequence.

Here is the shader that I am using for generating shadows in AR:
Shader "InvisibleShadowCaster"
{
	Properties
	{
		_ShadowIntensity("Shadow Intensity", Range(0, 1)) = 0.6
	}
	SubShader
	{
		Tags{ "Queue" = "AlphaTest" }
		Pass
		{
			Tags{ "LightMode" = "ForwardBase" }
			Cull Back
			ZWrite Off
			Blend SrcAlpha OneMinusSrcAlpha
			CGPROGRAM
			#pragma vertex vert
			#pragma fragment frag
			#pragma multi_compile_fwdbase
			#include "UnityCG.cginc"
			#include "AutoLight.cginc"
			uniform float _ShadowIntensity;
			struct v2f
			{
				float4 pos : SV_POSITION;
				LIGHTING_COORDS(0,1)
			};
			v2f vert(appdata_base v)
			{
				v2f o;
				o.pos = UnityObjectToClipPos(v.vertex);
				TRANSFER_VERTEX_TO_FRAGMENT(o);

				return o;
			}
			fixed4 frag(v2f i) : COLOR
			{
				float attenuation = LIGHT_ATTENUATION(i);
				return fixed4(0,0,0,(1 - attenuation)*_ShadowIntensity);
			}
			ENDCG
		}
	}
	Fallback "VertexLit"
}

P.S. - I don't remember exactly when but I think I had raised a similar issue back in the day with white shadows coming in the mp4 videos recorded using NatCorder on iOS and you had solved it with some color correction for linear color space. Maybe you need to apply the fix to JPEG image sequences as well.

@thesanketkale this bug should be fixed in VideoKit 0.0.18, because we've made a number of changes and fixes that would affect this issue. You can test out the latest alpha to confirm that it works. If it doesn't, please open a new issue.


Add setting to lock the minimap width

Oftentimes, I find myself accidentally dragging the the minimap and changing the width. It'd be nice if there was a setting to lock the width to prevent accidental resizing.

:+1: Yes please!

should be fixed in 1.5.2

You're the best!


stats: make it compatible with Windows

This is a simple fix to make cio_stats.c compilable on Windows.
In short, it needs chunkio_compat.h to load a chain of Windows-
specific headers.
Signed-off-by: Fujimoto Seiji<EMAIL_ADDRESS>

thanks


Enable CI for pull requests

Right now this is not the case:
https://github.com/maplibre/maplibre-plugins-android/blob/main/.github/workflows/ci.yml#L4

This can be closed :+1:


[DO NOT MERGE] [PROTOTYPE]

prototype for #1027 define a crd

@sbawaska Please sign the Contributor License Agreement!
Click here to manually synchronize the status of this Pull Request.
See the FAQ for frequently asked questions.

@sbawaska Thank you for signing the Contributor License Agreement!


Autocorrect fixed the Rspec HooksBeforeExamples checks

What are you trying to accomplish?
The Rspec rubocop tests for HooksBeforeExamples were skipped.  This pull request re-enables them
Anything you want to highlight for special attention from reviewers?
Please pay attention to the fixes in the rspec files.
How will you know you've accomplished your goal?
The rubocop rules will fire as needed.
Checklist

[x] I have run the complete test suite to ensure all tests and linters pass.
[x] I have thoroughly tested my code changes to ensure they work as expected, including adding additional tests for new functionality.
[x] I have written clear and descriptive commit messages.
[x] I have provided a detailed description of the changes in the pull request, including the problem it addresses, how it fixes the problem, and any relevant details about the implementation.
[x] I have ensured that the code is well-documented and easy to understand.

Merge conflicts too severe.  redoing this PR.


HDDS-4742. Make trash work with FS Optimised Buckets.

What changes were proposed in this pull request?
Integrate trash with HDDS-2939.
What is the link to the Apache JIRA
https://issues.apache.org/jira/browse/HDDS-4742
How was this patch tested?
testTrash() run through TestOzoneFileSystemV1 configs.

@sadanand48
Can you rebase this PR?

Thanks @rakeshadr for the review. Addressed comments.

Thanks @sadanand48 for the contribution. +1 for the changes.


video tutorials or experience articles for beginners?

Where can I find lark video tutorials or experience articles for beginners?
I want to check the configuration of the project based on lark.

I'm not a ware of video tutorials for Lark.
Have you read the JSON tutorial and the "How to write a DSL" articles?
If you have, what sort of information is missing from them?

Thank you for your reply.
For example, I want to check the configuration shown in the figure.

After the coding is implemented, it is expected that multiple configuration files can be reused through the corresponding inspection rules configuration.

Are you sure you need Lark? It looks like you can solve this with a simple regexp..

Yes

Hope to lower the threshold for users.
There is also a logical (+-* /) relationship check between cells in different excel profiles.

I'm not entirely sure what you're trying to do, or what's the difficulty you're encountering.
I'll try to give a short outline based on what I've seen, so we can build on that.
You have different sorts of constraints that you need to apply to some text. Some are syntactic (and context free), while some are value-based.
You can use Lark to parse and verify the syntactic constraints, and then use a transformer to validate the values.
You should do each one in a different rule, so that you can tell which path was taken at the end of the parse. You can also use the start parameter to pick which one to start from (in case you know what type that expression should be).
Is that enough to get you started?

Thank you very much!
I will first try to use the regular expression you mentioned above, and then try to implement it based on lark.


Some kind of grid to resize entire window

Find some kind of solution to enable resizing the window and automatically resize/reposition its components.

Could be solved via #29
To simply have helper functions to resize/reposition all widgets relative to the window size


Upgrade ZAP version for Matter SDK master branch

As the Matter SDK branch has been switched to master, the ZAP version is now outdated, leading to build failures in the edge channel. The ZAP version needs to be updated according to the MIN_ZAP_VERSION.

Since https://github.com/project-chip/connectedhomeip/pull/26636, the SDK automatically downloads a compatible ZAP version for arm64.
Moreover, it is recommended to programmatically download the compatible ZAP version by looking into one of zap.version or zap.json, rather than hard cording a version.


Implement column title alignment for Tree

Closes godotengine/godot-proposals#982
Implement methods Tree::set_column_title_alignment and Tree::get_column_title_alignment.
Results using the attached project:

test_project.zip

Squashed.

Could you amend the commit message to state that this is for the Tree node? The title of the PR is a good option to use.

Hopefully this is good to go now.

Thanks! And congrats for your first merged Godot contribution :tada:

Thanks @akien-mga.

I cannot find this in 4.1 even if it has been merged, is there something I'm missing? @Barugon @akien-mga

I cannot find this in 4.1 even if it has been merged, is there something I'm missing? @Barugon @akien-mga

https://github.com/godotengine/godot/blob/2d3b2abcf6edcc9b02a9b1894ba43f79845ad2f4/scene/gui/tree.cpp#L4929C12-L4929C38
Documentation: https://docs.godotengine.org/en/4.1/classes/class_tree.html#class-tree-method-set-column-title-alignment

My bad, was using TreeItem instead of Tree. Thanks, this is great! 🚀


Ensure google_root_disk_size_gb is an integer

Otherwise, the comparison on existing_size_gb in create_disk will be comparing a string versus an integer, which will never match.

LGTM


Do some adjustments for epoll

Summary
1.Fix epoll cannot work under 64-bit operating system by switching to the real file handle.
2.Fix one bug of EPOLL_CTL_DEL.
Impact
The return value from epoll_create is a real file handle not the raw pointer anymore.
Testing

@buyuer - Please fill in the details here

@davids5 is the description enough?

@xiaoxiang781216 yes


FXT edge filer support ticket flow appears to be broken

This flow appears to no longer work, the only options I get are 'billing' and 'subscription' when I click 'new support request'.  The described 'technical' option is not there.

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

ID: af9931c2-d339-d765-a59d-e19e9355afe7
Version Independent ID: 72daeda3-53db-5459-18cb-0a0aa56644be
Content: Open a support ticket for Microsoft Azure FXT Edge Filer
Content Source: articles/fxt-edge-filer/support-ticket.md
Service: fxt-edge-filer
GitHub Login: @femila
Microsoft Alias: femila

@altmiket
Thank you for bringing this to our attention.
I've delegated this to content author @femila, who will review it and offer their insightful opinions.

@femila
Please review it.


Adding heat source forcing term

Added a heat source term. It can input via the ini file as specified in the example src/runfileExample.ini
Support for both the GPU and CPU versions has been added.

@marc-85, I ended up tweaking a tiny bit more to add an enable/disable flag for each heat source. Not sure we would want multiple sources but if we did, I like being able to enable/disable quickly while leaving the majority of the input file as is.
Assuming CI passes, you ok with this mod?

Yes, that is a good idea.


AMD loading?

Would really like to try this out in my project, but AMD loading (define([deps], factory)) is a requirement of my environment.  Any advice for getting this to load in an AMD environment with little effort?

Could really use some input here.  bump

@agraboso to get this working with AMD, a UMD build version is required -- add webpack, add build steps to package.json to create dist versions, etc.  Would you be open to a PR that implements this?

What exactly would a UMD build version entail?
But yes i would look at your PR, if its just an extra file or two.
However i cant test AMD modules, i'm no expert.


[Bug]: Fails to accurately capture value with missing opening quote if a comma comes before closing quote

Version of the library
0.23.1
Describe the bug
When parsing broken json that looks like this:
[
  {
    "Snippet Summary Id": 1,
    "Overview": "Syncing with Company",
    "Description": The conversation focused on how this company's release management system integrates with ours, providing a streamlined workflow for documentation approval, unlike Jim.",
    "What the Prospect said": "John was interested in understanding how the release flow works and how it can be used to approve documentation and drawings directly in the product.",
    "Seller Response": "Gene explained that the configuration allows the release flow to start from the other product and push information to ours, enabling a wider team to approve documentation without needing direct access to our product.",
    "Quote": "Okay. So configuration is done right now."
  },
  {
    "Snippet Summary Id": 2,
    "Overview": "Assigning Part Numbers",
    "Description": "The discussion covered the capability of this product to assign part numbers to CAD data, a feature that might differentiate Our product from theirs.",
    "What the Prospect said": "Eve was looking at the part table and seemed curious about how part numbers could be assigned and mapped to categories in our product.",
    "Seller Response": "Gene demonstrated how part numbers could be assigned to CAD data through our product and mapped to various categories, showcasing the product's flexibility.",
    "Quote": "One of the options is that you can ask the product to assign per numbers to your CAD data."
  }
]

The missing quote after "Description": is repaired but instead of closing the quote at the existing closing quote, the package inserts a new quote at the first comma it finds, resulting in this:
[
  {
    "Snippet Summary Id": 1,
    "Overview": "Syncing with Company",
    "Description": "The conversation focused on how this company's release management system integrates with ours",
    "Jim.": "What the Prospect said\": \"John was interested in understanding how the release flow works and how it can be used to approve documentation and drawings directly in the product.",
    "Seller Response": "Gene explained that the configuration allows the release flow to start from the other product and push information to ours, enabling a wider team to approve documentation without needing direct access to our product.",
    "Quote": "Okay. So configuration is done right now."
  },
  {
    "Snippet Summary Id": 2,
    "Overview": "Assigning Part Numbers",
    "Description": "The discussion covered the capability of this product to assign part numbers to CAD data, a feature that might differentiate Our product from theirs.",
    "What the Prospect said": "Eve was looking at the part table and seemed curious about how part numbers could be assigned and mapped to categories in our product.",
    "Seller Response": "Gene demonstrated how part numbers could be assigned to CAD data through our product and mapped to various categories, showcasing the product's flexibility.",
    "Quote": "One of the options is that you can ask the product to assign per numbers to your CAD data."
  }
]

How to reproduce
string = """
[
  {
    "Snippet Summary Id": 1,
    "Overview": "Syncing with Company",
    "Description": The conversation focused on how this company's release management system integrates with ours, providing a streamlined workflow for documentation approval, unlike Jim.",
    "What the Prospect said": "John was interested in understanding how the release flow works and how it can be used to approve documentation and drawings directly in the product.",
    "Seller Response": "Gene explained that the configuration allows the release flow to start from the other product and push information to ours, enabling a wider team to approve documentation without needing direct access to our product.",
    "Quote": "Okay. So configuration is done right now."
  },
  {
    "Snippet Summary Id": 2,
    "Overview": "Assigning Part Numbers",
    "Description": "The discussion covered the capability of this product to assign part numbers to CAD data, a feature that might differentiate Our product from theirs.",
    "What the Prospect said": "Eve was looking at the part table and seemed curious about how part numbers could be assigned and mapped to categories in our product.",
    "Seller Response": "Gene demonstrated how part numbers could be assigned to CAD data through our product and mapped to various categories, showcasing the product's flexibility.",
    "Quote": "One of the options is that you can ask the product to assign per numbers to your CAD data."
  }
]
"""
repair_json(string, return_objects=True)

Expected behavior
I'd expect this:
[
  {
    "Snippet Summary Id": 1,
    "Overview": "Syncing with Company",
    "Description": "The conversation focused on how this company's release management system integrates with ours, providing a streamlined workflow for documentation approval, unlike Jim.",
    "What the Prospect said": "John was interested in understanding how the release flow works and how it can be used to approve documentation and drawings directly in the product.",
    "Seller Response": "Gene explained that the configuration allows the release flow to start from the other product and push information to ours, enabling a wider team to approve documentation without needing direct access to our product.",
    "Quote": "Okay. So configuration is done right now."
  },
  {
    "Snippet Summary Id": 2,
    "Overview": "Assigning Part Numbers",
    "Description": "The discussion covered the capability of this product to assign part numbers to CAD data, a feature that might differentiate Our product from theirs.",
    "What the Prospect said": "Eve was looking at the part table and seemed curious about how part numbers could be assigned and mapped to categories in our product.",
    "Seller Response": "Gene demonstrated how part numbers could be assigned to CAD data through our product and mapped to various categories, showcasing the product's flexibility.",
    "Quote": "One of the options is that you can ask the product to assign per numbers to your CAD data."
  }
]

Overall this is an awesome tool!! It's handled everything else I've thrown at it perfectly.

Thanks for reporting the issue, give a spin to 0.24.0 and let me know if it works

Oh wow!  First of all you are an absolute legend for this! It works perfectly for that case. Now that this issue is fixed I found one more 😅 , I can put it here but lmk if you want me to open a new issue and I can also do that:
I also get errors when there's no opening OR closing quote but there are commas in the value:
[
  {
    "Snippet Summary Id": 1,
    "Overview": "Transition from company 1 to company 2",
    "Description": The conversation touches on a customer who moved from company 1 to company 2 and encountered some challenges with the employment of record services. This highlights a particular area of scrutiny from the prospect's perspective.
    "What the Prospect said": Marie mentions a customer who transitioned from company 1 to company 2. This customer praised company 2 but raised an issue concerning the employment of record services, specifically related to contractual obligations and compensation adjustments.
    "Seller Response": Alex acknowledges the comment and prepares to proceed with the meeting by introducing more participants into the room.
    "Quote": "They came over from company 1... she dropped a flag on me."
  }
]

parses into:
[
  {
    "Snippet Summary Id": 1,
    "Overview": "Transition from company 1 to company 2",
    "Description": "The conversation touches on a customer who moved from company 1 to company 2 and encountered some challenges with the employment of record services. This highlights a particular area of scrutiny from the prospect's perspective.\n    \"What the Prospect said",
    "Seller Response": "Alex acknowledges the comment and prepares to proceed with the meeting by introducing more participants into the room.\n    \"Quote\": \"They came over from company 1... she dropped a flag on me."
  }
]

but I want:
[
  {
    "Snippet Summary Id": 1,
    "Overview": "Transition from company 1 to company 2",
    "Description": "The conversation touches on a customer who moved from company 1 to company 2 and encountered some challenges with the employment of record services. This highlights a particular area of scrutiny from the prospect's perspective.",
    "What the Prospect said": "Marie mentions a customer who transitioned from company 1 to company 2. This customer praised company 2 but raised an issue concerning the employment of record services, specifically related to contractual obligations and compensation adjustments.",
    "Seller Response": "Alex acknowledges the comment and prepares to proceed with the meeting by introducing more participants into the room.",
    "Quote": "They came over from company 1... she dropped a flag on me."
  }
]

There are also no commas here between the k-v pairs so this whole thing is kind of a mess.
Thanks again for the 0.24.0 fix, you're incredible!!

No worries about opening a new issue, I have released 0.25.0 that should fix this case more generally

Works perfectly 🏆 thank you so much!!


Handle the case when split subsets is empty

From 1.6.2 testing, found these errors:
=================================== FAILURES =====================
FAILED test_split.py::test_splits - assert 0.31782106782106784 <= 0.313725490...
FAILED test_split.py::test_pipeline_split_only - ValueError: Distribution can...
FAILED test_split.py::test_pipeline_split_and_train - ValueError: Distributio...
================== 3 failed, 12 warnings in 962.65s (0:16:02) ==================
Kevin said the failure is in the code that computes the Wasserstein distance between response value distributions in the split subsets where it is empty. A workaround will be provided.

Fixed in https://github.com/ATOMScience-org/AMPL/commit/a001100decbfb50cf09de49aacb514d06a4471ce


May I request ModType ID for Lowrider?

May I request ModType ID for Lowrider?

Which one

All, the speakers, hydraulics, steering wheels, etc, etc

It's the indexes 25-48, try them out.

ok, i'll try, but is there any native to install them on the vehicle? or i just use this VEHICLE::SET_VEHICLE_MOD?

Just like any other mod

Thanks it works, but just the dashboard color not working :+1:

@Guad the dashboard color not working

It's a separate native, look on gtaforums.

@Guad how to call $F40DD601A65F7F19?

@Guad can you explain which native get the dashboard color, which native set the dashboard color and dial color, lights color, etc tqvm

Note that if they don't have the lowrider update (pirated version) the game will crash.
    private int GetInteriorTrimColor(Vehicle veh)
    {
        OutputArgument arg = new OutputArgument();
        if (HasLowriderUpdate)
            Function.Call((Hash) 0x7D1464D472D32136, veh.Handle, arg);
        else
            return 0;
        return arg.GetResult<int>();
    }

    private int GetInteriorDashboardColor(Vehicle veh)
    {
        OutputArgument arg = new OutputArgument();
        if (HasLowriderUpdate)
            Function.Call((Hash) 0xB7635E80A5C31BFF, veh.Handle, arg);
        else
            return 0;
        return arg.GetResult<int>();
    }

Great! I try it once i get home

@Guad
Type parameter 'T' for 'Public Shared Overloads Function [Call](Of T)(hash As Hash, ParamArray arguments As InputArgument()) As T' cannot be inferred.
Value of type 'Long' cannot be converted to 'Hash'.
my code like this
    Public Shared Function GetVehicleInteriorTrimColor(Vehicle As Vehicle) As Integer
        Dim arg As New OutputArgument()
        If My.Settings.HasLowriderUpdate = True Then
            Native.Function.Call(DirectCast(&H7D1464D472D32136L, Hash), Vehicle.Handle, arg)
        Else
            Return 0
        End If
        Return arg.GetResult(Of Integer)()
    End Function

Sorry, I don't know visual basic.

Alright, thanks a lot!

@Guad after some Trial and Error, i figure it out! Thank you very much!!!
    Public Shared Function GetVehicleInteriorTrimColor(Vehicle As Vehicle) As Integer
        Dim arg As New OutputArgument()
        If My.Settings.HasLowriderUpdate = True Then
            Native.Function.Call(&H7D1464D472D32136L, Vehicle.Handle, arg)
        Else
            Return 0
        End If
        Return arg.GetResult(Of Integer)()
    End Function

    Public Shared Function GetVehicleInteriorDashboardColor(Vehicle As Vehicle) As Integer
        Dim arg As New OutputArgument()
        If My.Settings.HasLowriderUpdate = True Then
            Native.Function.Call(&HB7635E80A5C31BFFUL, Vehicle.Handle, arg)
        Else
            Return 0
        End If
        Return arg.GetResult(Of Integer)()
    End Function

        Native.Function.Call(&H6089CDF6A57F326C, _Vehicle.Handle, CInt(ReadCfgValue("DashboardColor", VehicleCfgFile)))
        Native.Function.Call(&HF40DD601A65F7F19UL, _Vehicle.Handle, CInt(ReadCfgValue("TrimColor", VehicleCfgFile)))


Add a changelog to keep track of version differences

I thought this might be useful to keep track of changes over time.
I am happy to maintain it, but ideally we could encourage PR authors
to add their changes as they go.
This might also be useful to get an idea of the appropriate version
change, depending on the significance of the included changes.

There was a changelog.md in the original repository. I deleted it since it duplicates the contents of the release notes here: https://github.com/jertel/elastalert2/releases. I try to avoid having to maintain duplicate content. But if enough feel strongly about having this inside the repository then we could stop putting the release notes in the GitHub releases area and instead place a single sentence instructing the reader to find the changes in the changelog.md.
Anyone else have an opinion on this?

Fair enough, that's a good point. I was hoping for something a bit more curated, that separated out breaking changes from new features etc., so it would be easy to understand what things to worry about before upgrading...but that is potentially overengineering things at such an early stage.

I think that it is difficult to immediately judge whether it is a function addition, a document fix, or a bug fix if it is described in the current release notes.
If you make a ChangeLog, you can add alerts or fix bugs, but the description of library updates and document fixes is not included in ChangeLog.
If you don't create a ChangeLog, it may be better to at least list the release notes for each category.
For example, in the categories of feature additions, bug fixes, document fixes, and more. If that is the case, I think that ChangeLog will not be needed.

@jertel do you have complete control of the content of the release notes? Or is it auto-generated by Github when tagging a release?

@jertel do you have complete control of the content of the release notes? Or is it auto-generated by Github when tagging a release?

It's a free-form text field so I can enter anything. But I'm starting to be swayed towards the changelog.md. I like that you all can help construct that content. It's been a 20+ minute process for the past 2 releases to assemble all the PRs and get them formatted correctly to make that bulleted list, and then review for incomplete PR descriptions, etc. So I could use the help on that.


Fixed #9649 - Spanish Translations corrected

Issue Reference
#9649
Description
The Spanish translations for the Bagisto Installer, the Shop and the Admin dashboard has been corrected.
Branch Selection

[x] Target Branch: master

@ashishkumar-webkul, @amit-webkul, @shivendra-webkul, @jitendra-webkul, can you please review this?


TypeError: LlamaRotaryEmbedding.forward() got an unexpected keyword argument 'seq_len'

Please check that this issue hasn't been reported before.

[X] I searched previous Bug Reports didn't find any similar reports.

Expected Behavior
Model training should run when the command accelerate launch -m axolotl.cli.train test.yaml is used.
Current behaviour
Throwing the error as below
return forward_call(*args, **kwargs)
File "/opt/conda/envs/axolotl/lib/python3.10/site-packages/accelerate/hooks.py", line 165, in new_forward
output = module._old_forward(*args, **kwargs)
File "/home/aion/axolotl/src/axolotl/monkeypatch/llama_attn_hijack_flash.py", line 442, in flashattn_forward
cos, sin = self.rotary_emb(
File "/opt/conda/envs/axolotl/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/opt/conda/envs/axolotl/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/opt/conda/envs/axolotl/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
TypeError: LlamaRotaryEmbedding.forward() got an unexpected keyword argument 'seq_len'
0%|                                                                                | 0/9 [00:01<?, ?it/s]
Traceback (most recent call last):
File "/opt/conda/envs/axolotl/bin/accelerate", line 8, in
sys.exit(main())
File "/opt/conda/envs/axolotl/lib/python3.10/site-packages/accelerate/commands/accelerate_cli.py", line 47, in main
args.func(args)
File "/opt/conda/envs/axolotl/lib/python3.10/site-packages/accelerate/commands/launch.py", line 1023, in launch_command
simple_launcher(args)
File "/opt/conda/envs/axolotl/lib/python3.10/site-packages/accelerate/commands/launch.py", line 643, in simple_launcher
raise subprocess.CalledProcessError(returncode=process.returncode, cmd=cmd)
subprocess.CalledProcessError: Command '['/opt/conda/envs/axolotl/bin/python3.10', '-m', 'axolotl.cli.train', 'test.yaml']' returned non-zero exit status 1.
Steps to reproduce
Run the train command with the yaml file provided
Config yaml
base_model: codellama/CodeLlama-7b-hf
model_type: LlamaForCausalLM
tokenizer_type: CodeLlamaTokenizer
is_llama_derived_model: true

load_in_8bit: true
load_in_4bit: false
strict: false

datasets:
  - path: summies.jsonl
    ds_type: json
    type: alpaca
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./lora-out/summies

sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true
eval_sample_packing: false

adapter: lora
lora_model_dir:
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:

wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 3
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
s2_attention:

warmup_steps: 10
evals_per_epoch: 4
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  bos_token: "<s>"
  eos_token: "</s>"
  unk_token: "<unk>"

Possible solution
No response
Which Operating Systems are you using?

[X] Linux
[ ] macOS
[ ] Windows

Python Version
3.10
axolotl branch-commit
OpenAccess-AI-Collective / axolotl
Acknowledgements

[X] My issue title is concise, descriptive, and in title casing.
[X] I have searched the existing issues to make sure this bug has not been reported yet.
[X] I am using the latest version of axolotl.
[X] I have provided enough information for the maintainers to reproduce and diagnose the issue.

I had same issue here. Set flash_attention: false  and got working

Setting flash attention false fixed it for me too, thanks @imchkkim

well. we cant use flash attn?

Going back to 40a88e8c4a2f32b63df0fe2079f7acfe73329273 on main commit should work

I had same issue here. Set flash_attention: false  and got working

Yes this is the only solution. Thanks

Reverting to commit 40a88e8c4a2f32b63df0fe2079f7acfe73329273 and re-running pip3 install -e '.[flash-attn,deepspeed]' to downgrade Transformers/Accelerate resolved the issue for me.
Annoying, but better then disabling flash attention.

Hello @Gryphe , thank you for pointing out that commit. Can anyone confirm this helped them too?
this should have only affected the tokenizing process for sharegpt.

Downgrading transformers to version 4.38 or lower will solve the issue.
pip install transformers==4.38

This error occurs because in transformers version 4.39, the seq_len argument in the LlamaRotaryEmbedding.forward() function was deprecated. You can see the change at https://github.com/huggingface/transformers/commit/ffe60fdcd60c17c3f216694160c2521da90f984c#diff-06392bad3b9e97be9ade60d4ac46f73b6809388f4d507c2ba1384ab872711c51.
In the file axolotl/src/axolotl/monkeypatch/llama_attn_hijack_flash.py, line 290 calls LlamaRotaryEmbedding.forward() with the argument seq_len=kv_seq_len, which is no longer supported in the updated version of transformers.

Will close this thanks to @BMPixel 's PR #1443

Downgrading transformers to version 4.38 or lower will solve the issue.
pip install transformers==4.38

This error occurs because in transformers version 4.39, the seq_len argument in the LlamaRotaryEmbedding.forward() function was deprecated. You can see the change at huggingface/transformers@ffe60fd#diff-06392bad3b9e97be9ade60d4ac46f73b6809388f4d507c2ba1384ab872711c51.
In the file axolotl/src/axolotl/monkeypatch/llama_attn_hijack_flash.py, line 290 calls LlamaRotaryEmbedding.forward() with the argument seq_len=kv_seq_len, which is no longer supported in the updated version of transformers.

thanks, remove param "seq_len", it work


proxychains-ng: init at 4.14

Motivation for this change
Add proxychains-ng which is more maintained than proxychains.
Things done

[ ] Tested using sandboxing (nix.useSandbox on NixOS, or option sandbox in nix.conf on non-NixOS)
Built on platform(s)

[x] NixOS
[ ] macOS
[ ] other Linux distributions

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[x] Tested compilation of all pkgs that depend on this change using nix-shell -p nix-review --run "nix-review wip"
[x] Tested execution of all binary files (usually in ./result/bin/)
[ ] Determined the impact on package closure size (by running nix path-info -S before and after)
[ ] Ensured that relevant documentation is up to date
[ ] Fits CONTRIBUTING.md.

Version 4.15 already in Nixpkgs.


add inner mac address to the session for encapsulated protocols like: GRE, Geneve, VxLAN

Is your feature request related to a problem? Please describe.
While capturing ERSPAN encapsulated traffic from a virtual environment we needed to filter on encapsulated mac-address to label traffic, this was not possible with the latest version.
Describe the solution you'd like
We would like to discuss our solution before doing a pull-request.
My working solution can be found in https://github.com/scilicet64/arkime/tree/multimac.
All tests pass and lint gives no error. Expected tests results for GRE, Geneve and VxLAN where modified because it now outputs the multiple mac addresses.
For showing and debugging purpose it's currently using a debug with LOG function "moloch_field_macoui_add_debug" that needs to be removed when this solution is checked and discussed for performance.
My code is storing the offset to the first found mac address in the ethernet callback (moloch_packet_ether).
I picked a maximum of 10 encapsulated mac's to be stored (MOLOCH_ETHER_MAX_STORE 10), when it would arrive at encapsulated mac 11, it would overwrite the latest most inner mac. Three encapsulated addresses is what I have seen in practice, I would suggest ten is safe.
Describe alternatives you've considered
First we just added the mac and ouifields for only the most inner mac, however we encoutered multilayer GRE/VxLAN and also needed to track those mac-addresses. Also we experimented with a new field name "encapsulated_mac", but the usability of this was not so great. We found adding it to the existing "mac" field feels more natural, just like in Wireshark for example.
related issue
issue: https://github.com/arkime/arkime/issues/1676 can possibly be solved with the same method for multiple encapsulated ip's. The issue how it's described is already implemented, it already shows the most inner encapsulated GRE-ip. However it can be improved for multiple ip's

Can you do a PR maybe in just your own repo so its easy to see the diff if you don't want to do one here.

My initial reaction is adding 60 bytes to an important 88 byte data structure isn't the right approach. I would think about using offsets instead to the mac addresses and/or double parsing if this feature is turned on.

Can you do a PR maybe in just your own repo so its easy to see the diff if you don't want to do one here.

here you are: https://github.com/arkime/arkime/pull/1888

My initial reaction is adding 60 bytes to an important 88 byte data structure isn't the right approach. I would think about using offsets instead to the mac addresses and/or double parsing if this feature is turned on.

I did use offsets in the molochpacket_t datastructure inspired by the style of the used ipOffset. Or do you mean something else?

sorry for the extra PR, i meant to do the first on my personal repo and needed a new one for the correct information template


Syntax error on numbers with underscores, such as 1_000_000

As with other modern languages, JavaScript numbers may contain _.
Examples:
let population = 8_501_000_000;
let cents = 1_000_000_00;

jshint doesn't seem to be able to parse numbers that use underscores. It fails on the first digit whenever underscores are used:
[jshint] Unexpected '1'. [E]

Thanks for taking the time to file an issue! The language feature you are looking for is called "numeric separators", and if you search this project's issue tracker for that term, you'll find a corresponding feature request. In order to keep things organized, I'm going to close this issue as a duplicate.


Fix typo in physical device Features struct

As suggested in PR 2539, this fixes the Features struct to have the correct names. Going by https://www.khronos.org/registry/vulkan/specs/1.1-khr-extensions/html/vkspec.html#features-features the SHADER_RESIDENCY_IMAGE_2D and SHADER_RECIDENSY_IMAGE_3D should be changed to     SPARSE_RESIDENCY_IMAGE_2D and SPARSE_RESIDENCY_IMAGE_3D.
PR checklist:

[ ] make succeeds (on *nix)
[ ] make reftests succeeds
[ ] tested examples with the following backends:
[ ] rustfmt run on changed code

Thank you!
bors r+


Add html-rendered declaration to export db.

Instead of exporting the internal type and argument strings (the U+E000 were never meant to leave doc-gen), export an HTML-rendered version of the declaration statement.

This is how it looks like:

Hmm. This failed to deploy, with
2020-08-14T13:38:16.2614749Z remote: error: GH001: Large files detected. You may want to try Git Large File Storage - https://git-lfs.github.com.
2020-08-14T13:38:16.2615078Z remote: error: Trace: bc56aa92c063cdc424b1a9e6d63ddee3
2020-08-14T13:38:16.2615322Z remote: error: See http://git.io/iEPt8g for more information.
2020-08-14T13:38:16.2615946Z remote: error: File docs/export_db.json is 122.02 MB; this exceeds GitHub's file size limit of 100.00 MB

The website build only uses the gzipped version, maybe we should just delete the other?

Yes, we should remove the non-gzipped version.


Error: Cannot find module './normalized-options'

I just installed this command line tool:
yarn global add create-react-native-module

Everything seems fine.
However, trying to execute any command fails:
$ create-react-native-module -V
internal/modules/cjs/loader.js:657
    throw err;
    ^

Error: Cannot find module './normalized-options'
    at Function.Module._resolveFilename (internal/modules/cjs/loader.js:655:15)
    at Function.Module._load (internal/modules/cjs/loader.js:580:25)
    at Module.require (internal/modules/cjs/loader.js:711:19)
    at require (internal/modules/cjs/helpers.js:14:16)
    at Object.<anonymous> (~/.config/yarn/global/node_modules/create-react-native-module/command.js:3:27)
    at Module._compile (internal/modules/cjs/loader.js:805:30)
    at Object.Module._extensions..js (internal/modules/cjs/loader.js:816:10)
    at Module.load (internal/modules/cjs/loader.js:672:32)
    at tryModuleLoad (internal/modules/cjs/loader.js:612:12)
    at Function.Module._load (internal/modules/cjs/loader.js:604:3)

I guess it's because normalized-options.js seems to be missing from https://github.com/brodybits/create-react-native-module/blob/dev/package.json#L28 ?

Thanks guys, should be fixed on npm now. I just raised #14 to avoid this kind of an issue in the future.


Timeout on deye inverter

Is this a known issue? My main goal is to change the voltage in time of use. Mabey someone can assist me in how to make this?
Traceback (most recent call last):
File "/root/Python-3.8.2/tte/test1.py", line 31, in
main()
File "/root/Python-3.8.2/tte/test1.py", line 14, in main
val = modbus.read_input_registers(register_addr=x, quantity=1)[0]
File "/usr/local/lib/python3.9/dist-packages/pysolarmanv5/pysolarmanv5.py", line 347, in read_input_registers
modbus_values = self._get_modbus_response(mb_request_frame)
File "/usr/local/lib/python3.9/dist-packages/pysolarmanv5/pysolarmanv5.py", line 261, in _get_modbus_response
mb_response_frame = self._send_receive_modbus_frame(mb_request_frame)
File "/usr/local/lib/python3.9/dist-packages/pysolarmanv5/pysolarmanv5.py", line 248, in _send_receive_modbus_frame
v5_response_frame = self._send_receive_v5_frame(v5_request_frame)
File "/usr/local/lib/python3.9/dist-packages/pysolarmanv5/pysolarmanv5.py", line 233, in _send_receive_v5_frame
v5_response = self.sock.recv(1024)
socket.timeout: timed out

update:
was able to exacly what i wanted todo with this library. thanks:
""" A basic client demonstrating how to use pysolarmanv5."""
from pysolarmanv5 import PySolarmanV5
def main():
modbus = PySolarmanV5(
"xxxx",xxxx, port=8899, mb_slave_id=1, verbose=False
)
print(modbus.read_holding_registers(register_addr=262, quantity=1))
print(modbus.write_multiple_holding_registers(register_addr=262, values=[5700]))

if name == "main":
main()


Value not valid and remote_params

I'd like to use the select2 tags option to add a non existing entity (e.g: a new Country entity) but I have a "This value is not valid" error, presumably from the ChoicesTransformer and the fact that the entity does not exist yet.
How to avoid that ?
Also, I have linked two Entities: Country and PostalCode (Zip Code). When choosing a Country I want to load all the PostalCode associated but don't know how to pass the param in my ajax call.

I have the same issue, coming from a doctrine exception:
TransformationFailedException {#614 ▼
  #message: "Unable to reverse value for property path "name": The choice "__eau" does not exist or is not unique"
 ...
}
TransformationFailedException {#679 ▼
  #message: "The choice "__eau" does not exist or is not unique"
  #file: "D:\dev\WWMenu\vendor\tetranz\select2entity-bundle\Tetranz\Select2EntityBundle\Form\DataTransformer\EntityToPropertyTransformer.php"
  #line: 97
...
}

Created the PR #67 that should fix this issue.
Let me know if it helps for you as well.


ios video'sounds in iframe is too small

my Page web.html has a iframe like this :
`

 `
and my ts is:
`import { Component } from '@angular/core';
import { NavController, NavParams } from 'ionic-angular';
import { DomSanitizer } from '@angular/platform-browser';
@Component({
selector: 'page-web',
templateUrl: 'web.html'
})
export class WebPage {
title: string;
srcUrl: any;
constructor(public navCtrl: NavController,public navParams: NavParams, private sanitizer: DomSanitizer) {
}
ionViewDidLoad(){
this.title = this.navParams.get('title');
this.srcUrl = this.sanitizer.bypassSecurityTrustResourceUrl(this.navParams.get('url'));
console.log('url=' + this.srcUrl);
console.log('title=' + this.title);
}
}`
srcUrl is passed from previous page like:
this.srcUrl = ' http://m.v.6.cn/live/u1?src=ummeda5263&forceback=1';
And then ,the video like this  is no sounds or too small sounds on iphone.
However,Android is fine.
Please help me ,Thanks.

Hello! Thanks for opening an issue with us! As this seems like more of a support question i will urge that you ask this question on our forum or on our slack channel. Thanks for using Ionic!

@jgw96 Thanks!I have ask this question on forum.And anyone who will help me ?


Is there anyone success to train this model?

I tried to train this model few days. However, the reconstruction results always abnormal. If there is anyone success to train this model, can you tell me some tips for training?

The reconstruction images are like solid image.

start with this configuration. it works https://github.com/lucidrains/magvit2-pytorch/issues/16

Can you show the images after training?

It always looks like this image.

This configuration works  https://github.com/lucidrains/magvit2-pytorch/issues/16 and it is a good place to start. I find that the number of epochs need to be huge! you can also vary the size and architecture of the model like Pfiel did.

@bridenmj How much epochs do you use? Are you working on the ImageNet Pretrain?

Actually I reimplement the model structure to align with the magvit2 paper. But I find that the LFQ Loss is negative and the recon loss will get converage easily with or without GAN. The reconstructed images are vague but not the solid color. What about you? @Jihun999

Ok, I will reimplement the model first. Thank you for your comment.

Actually I reimplement the model structure to align with the magvit2 paper. But I find that the LFQ Loss is negative and the recon loss will get converage easily with or without GAN. The reconstructed images are vague but not the solid color. What about you? @Jihun999

Hey, is it possible to share the code modification for model architecture alignment? Thanks a lot!

someone i know has trained it successfully.

wow, could i know who did it.

@RobertLuo1 @Jihun999 @lucidrains If you successfully trained this model, would you like to share the pretrained weights and the modified model code?

Hello there,
Thanks @lucidrains  for your work! I have successful trainings on toy data (tried it on images and video) with code in this fork  https://github.com/vinyesm/magvit2-pytorch/blob/trainvideo/examples/train-on-video.py and with this video data https://huggingface.co/datasets/mavi88/phys101_frames/tree/main. What seemed to fix the issue is to stop using accelerate (I only train on one GPU).
I tried with only MSE and then also the other losses, and also with/without attend_space layers. All work but I did not try to tune hyperparameters..

thank you for sharing this Marina! I'll see if I can find the bug, and worse comes to worse, can always rewrite the training code in pytorch lightning

Hi, recently we have devoted a lot to training the tokenizer in Magvit2, and now we have open source the tokenizer trained with imagenet. Feel free to use that. The project page is https://github.com/TencentARC/Open-MAGVIT2.

Hey @lucidrains, I trained a MAGVIT2 tokenizer without modifying your implementation of the accelerate framework. As others have experienced, I initially saw just a solid block in the results/sampled.x.gif files. However, upon loading the model weights from my most recent checkpoint, I was able to get pretty good reconstructions in a sample script that I wrote that performs inference without using the accelerate framework. Additionally, the reconstruction MSE scores were consistent with the ones observed in your training script. This means that whatever bug others are experiencing is not the result of flawed model training, but rather something going wrong with the gif rendering.

*Note: the first image is the saved gif in the results folder. The ground truth image has a weird colour scheme because I normalized the frame pixels to be between [-1, 1]. The second image is the reconstructed image from my inference script. MSE was ~0.011 after training on a v100 for 5 hours.

Hello everyone, I also have been struggling training the model.
My goal is to first try to overfit magvit2 on a single video.
I haven't made any modifications to the code base at all. I am using accelerate and training on a single GPU.
Here is the result I get:

Here are the corresponding training curves:

The reconstruction loss does seem to decrease and then plateau.
Let me know if you have any idea why this is happening?
Some additional info:
I am loading the video using the video loader from magvit (ie frames are normalized between [0,1]).
I'm on Ubuntu 20.04, pytorch 2.4 with cuda 12.1, training on a single A40 GPU.
The VideoTokenizer I used is the one provided in the readme ie:
tokenizer = VideoTokenizer(
    image_size = 128,
    init_dim = 64,
    max_dim = 512,
    codebook_size = 1024,
    layers = (
        'residual',
        'compress_space',
        ('consecutive_residual', 2),
        'compress_space',
        ('consecutive_residual', 2),
        'linear_attend_space',
        'compress_space',
        ('consecutive_residual', 2),
        'attend_space',
        'compress_time',
        ('consecutive_residual', 2),
        'compress_time',
        ('consecutive_residual', 2),
        'attend_time',
    )
)

Hi @vincentcartillier,
Please check Tencent's https://github.com/TencentARC/Open-MAGVIT2, which is based on this implementation but modify some parts

Thanks for your reply. I did came across the Open-MAGVIT2 repo, but correct me if I'm wrong, I don't think they've implemented the video tokenizer yet?
I believe there is only an image tokenizer that has been evaluated on ImageNet

typically, if the recon loss is below 0.03, you will see an outline of the video. What you encountered may indicate the architecture is difficult to converge as I manually re-implement magvit2, it will quickly produce the reconstruction within a few hundred steps. In order to debug, you can first skip quantization and only use encoder's output as decoder's input to adjust the whole model's structure. When it's done, then you add quantization as it hard to train. BTW, the repo uses a 2d gan which takes samples frames as input, which is not aligned with the paper. You can use a 3d vqgan instead. But from my point of view, discriminator's training is not the most import part. The encoder and decoder's structures matters.

Got it. Thanks a lot for all the tips.  I'll try these out. In the meantime, do you think you could share your re-implementation of magvit2? I'm assuming this is based of this repo.

Sorry, I can't because it's an internal project and is still under development > <. The implementation is not based on this project. I followed the google's magvit-v1 jax repo and modified it. The adjustments between v1 and v2 are minimal.

But I use the vector-quantize-pytorch's LFQ as it used in here.

Got it. Totally understandable. Thanks a lot for all the tips I'll give it a try!

Got it thanks so much for the pointer. I think the reason why you're seeing such a low learning rate is because of the use of warmup.  You can set warmup_step=1 in the VideoTokenizerTrainer() setup parameters to bypass this.
If you haven't used LFQ, are you using FSQ instead? (finite scalar quantization) or another thing?
Could you try running the same thing (same learning rate) with LFQ and see if it works? -  it would be great to see if that's the source of the problem we're facing.
Also could you share your setup? (OS, cuda, pytorch version, linux kernel version, GPU type etc..)

@vincentcartillier I encountered the same difficult convergence problem as described by @Jason3900 , but before that, I found that the learning rate is not set correctly. When I checked lr in the optimizer, it was extremely low (~1e-10). And when I train with a higher learning rate (e.g., 1e-5), I get better results. 5k iters       40k iters       train with only 1 video and LFQ is not used.

Yep, but still it shouldn't take that many steps to get the reconstructed result only with 1 Video. It may indicate that the model is too hard to converge.

@vincentcartillier sure!

If you haven't used LFQ, are you using FSQ instead? (finite scalar quantization) or another thing?

to test the convergence of this enc / dec arch, I just drop the quantizer and use continuous representation with dim 512

Could you try running the same thing (same learning rate) with LFQ and see if it works? - it would be great to see if that's the source of the problem we're facing.

yes I run the same setting with LFQ, but can't get a converged result in 40k steps.
So I re-implemented the enc / dec arch (using code in this repo with little modification) according to the paper. a surprising result I got this time. Still follow @Jason3900 's suggestion, skip quantization
2k iters, 1 video, no quant with dim 18

Amazing! Would you be comfortable sharing the code modifications you've made? ( maybe via a PR or just sharing your fork).
It's really promising, then I guess the challenge is to include the LFQ part, which, based of Jason's comment should be working piece already.

I also got to something kinda working. This is the same code, ie no modifications, same settings as my initial post above. Except I've changed the learning rate, or rather I've turned of the warmup (as @JingwWu pointed out). Here is the overfitting results I have after ~5k steps.

This is with using the LFQ + original enc dec implementation.
It is much better than before, but I would have expected to have an even cleaner output given that this is an overfitting experiment.

Yes, this is the modified CausalConv3d module. The key is to allow stride in the spatial dim. This module can get correct results under kernel size and stride settings mentioned in the paper, and I've dropped other features for simplicity
class CausalConv3d(nn.Module):
    def __init__(
        self,
        chan_in,
        chan_out,
        kernel_size,
        pad_mode = 'constant',
        s_stride = 1,
        t_stride = 1,
        **kwargs
    ):
        super().__init__()
        kernel_size = cast_tuple(kernel_size, 3)

        time_kernel_size, height_kernel_size, width_kernel_size = kernel_size

        assert is_odd(height_kernel_size) and is_odd(width_kernel_size)

        self.pad_mode = pad_mode
        time_pad = time_kernel_size - 1
        height_pad = height_kernel_size // 2
        width_pad = width_kernel_size // 2

        self.time_pad = time_pad
        self.time_causal_padding = (width_pad, width_pad, height_pad, height_pad, time_pad, 0)

        stride = (t_stride, s_stride, s_stride)
        self.conv = nn.Conv3d(
            chan_in,
            chan_out,
            kernel_size,
            stride = stride,
            **kwargs
        )

    def forward(self, x):
        pad_mode = self.pad_mode if self.time_pad < x.shape[2] else 'constant'

        x = F.pad(x, self.time_causal_padding, mode = pad_mode)
        return self.conv(x)

Next is to implement ResBlock X, ResBlock X->Y, ResBlockDown X->Y as described in paper, using the CausalConv3d above and other common Pytorch nn module (eg, nn.Conv3d, nn.GroupNorm, etc) and Blur in this repo. They are then assembled into encoder and decoder

@Jason3900 This is a great open source work! I will check it out in detail.
I basically replicated the performance described in the paper two months ago (FVD ~ 6.9 and LPIPS ~ 0.06, reported on K700 val set), using K700 pre-training and 64 A800 GPUs. I observed two things:
First, the performance of video reconstruction is largely impacted by the frame rate of input video, and when the frame rate is too low (meaning there is less redundancy between adjacent frames), the reconstructed video will appear fuzzy.
Second, I tried a more aggressive compression in spatial domain, such as 16x (instead of 8x as reported in the paper), and I also tried to change the structure of the model for this purpose, but the results were not as expected.
Have you encountered the above two problems? Looking forward to your reply.


extract common pre-push and push uploading code

I have some issues with this code. But at least now pre-push and push both call shared functions to upload objects.
From https://github.com/github/git-lfs/pull/1040#discussion_r55821731:

Now that filteredPointers is used in multiple places, maybe promote it to the lfs package for re-use rather than keep it in the pre-push source file?

This PR is a start towards shared functions for pre-push and push commands. While it seems to work, there are a number of things I'd like to change:

I don't like using lfs.Configuration like this. I wanted something more than a StringSet to share between multiple ref uploads in the same command.
Filtering could probably be cleaned up.

EDIT: Fixed this in a later commit ^^^
Instead of promoting to the lfs package, what if we started on a high level client like we discussed in https://github.com/github/git-lfs/issues/779? I am a little concerned that my yak shave trying to get #969 merged is going on too long though :)
I don't think the commands should be assembling upload queue objects or anything. I think they should just be responsible for turning the CLI or STDIN arguments into code like this:
c := client.New("origin")
c.DryRun = false

for _, ref := range args[1:] {
  c.Upload(scanObjectsLeftToRight(ref, "", lfs.ScanRefsMode))
}

errs := c.Errors()
// error handling, os.Exit(2), etc

Feeling a lot better about this *clientContext struct. It's no longer coupled to the git scanner. Here's a simple example of usage:
cli := newClient()
cli.RemoteName = lfs.Config.CurrentRemote
cli.DryRun = prePushDryRun

scanOpt := lfs.NewScanRefsOptions()
scanOpt.ScanMode = lfs.ScanLeftToRemoteMode
scanOpt.RemoteName = cli.RemoteName

pointers, err := lfs.ScanRefs(left, right, scanOpt)
if err != nil {
  Panic(err, "Error scanning for Git LFS files")
}

cli.Upload(pointers)

Hopefully this wasn't a bad idea (if it is, I'll just merge b5356900f5354f681957d8b5e76fa64978da76b3 into #1040), but I merged #969 in here, fixing merge conflicts. It's obvious where we're not filling out the transfer meta data for lfs push. I guess I'll have to figure out how to get remote tracking branches given a list of local branches.

Here's a compare view if you just want to review the push/pre-push changes to #1040.
https://github.com/github/git-lfs/compare/skip-pre-push-dupes...b5356900f5354f681957d8b5e76fa64978da76b3

Are you intending to wrap downloading in clientContext too? Although there's somewhat less for it to do than in the upload case. If not, or even if 'not right away' then maybe rename clientContext to uploadContext for now.

#1040 now conflicts after your scanner fixes. Totally fine. I'm going to chalk this up as experimentation, merge this PR into #1040, and then redo the changes on master.


[NSE-403]Add Dataproc integration section to README

What changes were proposed in this pull request?
Add Dataproc integration section to README,  it will redirect to a detailed guide and related scripts on oap-tools.
How was this patch tested?

@weiting-chen Please take a review, thanks!


Building from source ubuntu 22

Encountered many issues, is anyone able to build this from source on ubuntu 22?

$ sudo wget https://github.com/codablock/bls-signatures/archive/v20181101.zip
$ sudo unzip v20181101.zip
$ cd bls-signatures-20181101
$ sudo cmake .
$ sudo make install
This does not work, make fails. There are several errors

error: size of array element is not a multiple of its alignment 101 | blake2s_state S[8][1];
https://github.com/Raptor3um/raptoreum/issues/48#issuecomment-969125200

If I fix that issue there are still other issues. And thats just to build the deps, not even building the qt

I think you are the first trying on ubuntu 22.

I think you are the first trying on ubuntu 22.

Yes sir I can only be grateful that there is someone who is willing to look at this at all. If you need anything from me let me know.
ubuntu 24 is coming soon, and there is no binaries for any linux - so it would be nice if we could get this working.

I think you are the first trying on ubuntu 22.

ser plz help
Is there a way I can build this in ubuntu 18 but it will run on ubuntu 22?

It will run in Ubuntu 22
On Wed, Jan 31, 2024 at 7:32 AM Setvin @.***> wrote:

I think you are the first trying on ubuntu 22.
ser plz help
Is there a way I can build this in ubuntu 18 but it will run on ubuntu 22?
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If you build for Ubuntu 18 it will run with Ubuntu 18, if you got the executables then upgrade to Ubuntu 22, they will run, but if you build from source, the depends have to be specific to your build environment. What are the errors you are getting? There are already compiled binaries available to download, but if you are building from source, what's the error?


⚠ Samsung has degraded performance

In 69e1edd, Samsung (https://samsung.com) experienced degraded performance:

HTTP code: 200
Response time: 2184 ms

Resolved: Samsung performance has improved in 4ead949.


Train model with NPU

Hi, how can I train my model on Ascend NPU? Could you provide me with some examples? Thanks!

Install dependent libraries like CANN, torch, torch_npu, and Deepspeed. Then just add import torch_npu at the beginning of the model, other operations are the same as other accelerators.
More information see: https://www.hiascend.com/zh/document

Can you provide more info about your environment?
First make sure you are abel to successfully run torch_npu like:
>>> import torch
>>> import torch_npu
>>> a = torch.tensor([1])
>>> a
tensor([1])
>>> a.to('npu:0')
tensor([1], device='npu:0')

Hi, I have installed the deepspeed==0.9.2 and torch_npu. But I run the BingBertSquad and meet the following error
EZ9999: Inner Error!
EZ9999  Kernel task happen error, retCode=0x26, [aicore exception].[FUNC:PreCheckTaskErr][FILE:task_info.cc][LINE:1518]
        TraceBack (most recent call last):
        The error from device(2), serial number is 37, there is an aicore error, core id is 0, error code = 0x10, dump info: pc start: 0x1000124080280000, current: 0x124080280250, vec error info: 0x159fdfdf, mte error info: 0xa5, ifu error info: 0x27b7f3f75a400, ccu error info: 0xffdbd1ff00609e8d, cube error info: 0x72, biu error info: 0, aic error mask: 0x65000200d000288, para base: 0x1240c0411800, errorStr: Illegal instruction, which is usually caused by unaligned UUB addresses.[FUNC:PrintCoreErrorInfo][FILE:device_error_proc.cc][LINE:523]
        The extend info from device(2), serial number is 37, there is aicore error, core id is 0, aicore int: 0x1, aicore error2: 0, axi clamp ctrl: 0, axi clamp state: 0x1717, biu status0: 0x101e44800000000, biu status1: 0x940002092a0000, clk gate mask: 0x1000, dbg addr: 0, ecc en: 0, mte ccu ecc 1bit error: 0, vector cube ecc 1bit error: 0, run stall: 0x1, dbg data0: 0, dbg data1: 0, dbg data2: 0, dbg data3: 0, dfx data: 0[FUNC:PrintCoreErrorInfo][FILE:device_error_proc.cc][LINE:554]
        The device(2), core list[0-0], error code is:[FUNC:PrintCoreInfoErrMsg][FILE:device_error_proc.cc][LINE:577]
        coreId( 0):            0x10    [FUNC:PrintCoreInfoErrMsg][FILE:device_error_proc.cc][LINE:591]
        Aicore kernel execute failed, device_id=0, stream_id=13, report_stream_id=13, task_id=2118, flip_num=0, fault kernel_name=53/69_-1_53_NLLLoss_tvmbin, program id=69, hash=690753179031245533.[FUNC:GetError][FILE:stream.cc][LINE:1418]
        [AIC_INFO] after execute:args print end[FUNC:GetError][FILE:stream.cc][LINE:1418]
        rtStreamSynchronizeWithTimeout execute failed, reason=[aicore exception][FUNC:FuncErrorReason][FILE:error_message_manage.cc][LINE:50]
        synchronize stream failed, runtime result = 507015[FUNC:ReportCallError][FILE:log_inner.cpp][LINE:161]

DEVICE[0] PID[33781]:
EXCEPTION STREAM:
  Exception info:TGID=33781, model id=65535, stream id=13, stream phase=3
  Message info[0]:RTS_HWTS: aicore exception, slot_id=36, stream_id=13
    Other info[0]:time=2024-01-04-03:57:13.963.085, function=int_process_hwts_task_exception, line=1704, error code=0x26
Iteration:   0%|                                                                                | 0/29324 [00:11<?, ?it/s]
Epoch:   0%|                                                                                | 0/2 [00:11<?, ?it/s]
Traceback (most recent call last):
  File "nvidia_run_squad_deepspeed.py", line 1169, in <module>
    main()
  File "nvidia_run_squad_deepspeed.py", line 1023, in main
    1 - args.loss_plot_alpha) * loss.item()
RuntimeError: ACL stream synchronize failed.

How can I solve this problem? My device information is
+------------------------------------------------------------------------------------------------+
| npu-smi 23.0.rc2                 Version: 23.0.rc2                                             |
+---------------------------+---------------+----------------------------------------------------+
| NPU   Name                | Health        | Power(W)    Temp(C)           Hugepages-Usage(page)|
| Chip                      | Bus-Id        | AICore(%)   Memory-Usage(MB)  HBM-Usage(MB)        |
+===========================+===============+====================================================+
| 2     910B                | OK            | 62.8        41                0    / 0             |
| 0                         | 0000:01:00.0  | 0           2363 / 15039      3    / 32768         |
+===========================+===============+====================================================+
+---------------------------+---------------+----------------------------------------------------+
| NPU     Chip              | Process id    | Process name             | Process memory(MB)      |
+===========================+===============+====================================================+
| No running processes found in NPU 2                                                            |
+===========================+===============+====================================================+

CANN version is 5.0RC2 and torch==1.11

Hi, I have installed the deepspeed==0.9.2 and torch_npu. But I run the BingBertSquad and meet the following error
EZ9999: Inner Error!
EZ9999  Kernel task happen error, retCode=0x26, [aicore exception].[FUNC:PreCheckTaskErr][FILE:task_info.cc][LINE:1518]
        TraceBack (most recent call last):
        The error from device(2), serial number is 37, there is an aicore error, core id is 0, error code = 0x10, dump info: pc start: 0x1000124080280000, current: 0x124080280250, vec error info: 0x159fdfdf, mte error info: 0xa5, ifu error info: 0x27b7f3f75a400, ccu error info: 0xffdbd1ff00609e8d, cube error info: 0x72, biu error info: 0, aic error mask: 0x65000200d000288, para base: 0x1240c0411800, errorStr: Illegal instruction, which is usually caused by unaligned UUB addresses.[FUNC:PrintCoreErrorInfo][FILE:device_error_proc.cc][LINE:523]
        The extend info from device(2), serial number is 37, there is aicore error, core id is 0, aicore int: 0x1, aicore error2: 0, axi clamp ctrl: 0, axi clamp state: 0x1717, biu status0: 0x101e44800000000, biu status1: 0x940002092a0000, clk gate mask: 0x1000, dbg addr: 0, ecc en: 0, mte ccu ecc 1bit error: 0, vector cube ecc 1bit error: 0, run stall: 0x1, dbg data0: 0, dbg data1: 0, dbg data2: 0, dbg data3: 0, dfx data: 0[FUNC:PrintCoreErrorInfo][FILE:device_error_proc.cc][LINE:554]
        The device(2), core list[0-0], error code is:[FUNC:PrintCoreInfoErrMsg][FILE:device_error_proc.cc][LINE:577]
        coreId( 0):            0x10    [FUNC:PrintCoreInfoErrMsg][FILE:device_error_proc.cc][LINE:591]
        Aicore kernel execute failed, device_id=0, stream_id=13, report_stream_id=13, task_id=2118, flip_num=0, fault kernel_name=53/69_-1_53_NLLLoss_tvmbin, program id=69, hash=690753179031245533.[FUNC:GetError][FILE:stream.cc][LINE:1418]
        [AIC_INFO] after execute:args print end[FUNC:GetError][FILE:stream.cc][LINE:1418]
        rtStreamSynchronizeWithTimeout execute failed, reason=[aicore exception][FUNC:FuncErrorReason][FILE:error_message_manage.cc][LINE:50]
        synchronize stream failed, runtime result = 507015[FUNC:ReportCallError][FILE:log_inner.cpp][LINE:161]

DEVICE[0] PID[33781]:
EXCEPTION STREAM:
  Exception info:TGID=33781, model id=65535, stream id=13, stream phase=3
  Message info[0]:RTS_HWTS: aicore exception, slot_id=36, stream_id=13
    Other info[0]:time=2024-01-04-03:57:13.963.085, function=int_process_hwts_task_exception, line=1704, error code=0x26
Iteration:   0%|                                                                                | 0/29324 [00:11<?, ?it/s]
Epoch:   0%|                                                                                | 0/2 [00:11<?, ?it/s]
Traceback (most recent call last):
  File "nvidia_run_squad_deepspeed.py", line 1169, in <module>
    main()
  File "nvidia_run_squad_deepspeed.py", line 1023, in main
    1 - args.loss_plot_alpha) * loss.item()
RuntimeError: ACL stream synchronize failed.

How can I solve this problem? My device information is
+------------------------------------------------------------------------------------------------+
| npu-smi 23.0.rc2                 Version: 23.0.rc2                                             |
+---------------------------+---------------+----------------------------------------------------+
| NPU   Name                | Health        | Power(W)    Temp(C)           Hugepages-Usage(page)|
| Chip                      | Bus-Id        | AICore(%)   Memory-Usage(MB)  HBM-Usage(MB)        |
+===========================+===============+====================================================+
| 2     910B                | OK            | 62.8        41                0    / 0             |
| 0                         | 0000:01:00.0  | 0           2363 / 15039      3    / 32768         |
+===========================+===============+====================================================+
+---------------------------+---------------+----------------------------------------------------+
| NPU     Chip              | Process id    | Process name             | Process memory(MB)      |
+===========================+===============+====================================================+
| No running processes found in NPU 2                                                            |
+===========================+===============+====================================================+

CANN version is 5.0RC2 and torch==1.11

Looks like your CANN version is too old, 5.0 is two years old, try to update the CANN version.

@CurryRice233 Hi, I have updated the CANN to 6.3RC2 but the error still exists.

I follow the deepspeed_npu to install the deepspeed and deepspeed_npu

@CurryRice233 Could you help me solve this problem? I just added torch_npu at the beginning of the code.

@CurryRice233 Hi, I have updated the CANN to 6.3RC2 but the error still exists.

The newest version is 7.0, try to this https://www.hiascend.com/developer/download
If the same problem persists, contact Ascend Technical Support.


[HOTFIX] SAP Monitor: Remove replay backlog fields from SapHana / HSR

To ensure compatibility with older HANA versions (< 2.0 SPS02), replay backlog fields were removed from the underlying SQL queries (see PR 108 on payload side).
This PR removes the pertinent fields (which are not ingested anymore) from the workbook templates as well. Otherwise, customers would see the following error message:

PR Checklist

[x] Explain your changes, so people looking at the PR know what and why, the code changes are the how.
[ ] if updating templates, it is helpful to post a screenshot of what the changes look like.
[x] if updating templates, ensure that your parameters and steps have meaningful names.
[ ] if adding new templates, ensure that your parameters and columns have display names.
[ ] if adding new templates, or changing items in a gallery, it's helpful to post a screenshot of what the gallery looks like now

Sucks that JSON doesn't support multi-line.
Reviewing this massive line is difficult

Verified that line with:

REPLAY_BACKLOG_SIZE_d
replay_backlog_size = REPLAY_BACKLOG_SIZE_d,,
replay_backlog_size,

are removed


Update Typescript optional field with upsertGraph

Hi,
I have a model which looks like the typescript example:
export default class Movie extends Model {
  readonly id!: number;
  name?: string;

I'm wondering how to handle the case when you want to set the name to NULL using upsertGraph? From what I observed:

when inserting and by using useNullAsDefault you can omit the field which will be inserted as NULL
when updating, undefined value are ignored by knex
you can't update using null value as Typescript will complain about it:
Movie.query().upsertGraphAndFetch({...country, name: null}); produces Type null is not assignable to type string | undefined

To overcome this I could eventually change the type of name to:

name: string | null
name? string | null
But I'm not fond of this as it can lead to some kind of inconsistency (sometimes using ?, sometimes using | null)

I know the issue is not due to Objection (undefined value are ignored by knex), however I was wondering if there is something we could add in the library to overcome this (am I the only one having this issue ?).
Thanks for your feedback.

am I the only one having this issue ?

Hey, we're at least 2! Quite a big issue, from what I see basically it's not possible to set a nullable column to null using objection in typescript, unless you set the property as type | null in the model definition.

If you can set the value to null, then the type type | null is correct.

I am facing this problem, too!
Here's the error message when upsertGraph of a nullable type relation in model.
( I use the koa-ts Person model as example)
Type '{ firstname: string; }' is not assignable to type 'Expression<Person | null | undefined>'.
export default class Person extends Model {
  id!: number
  firstName!: string
  lastName!: string
  age!: number

  pets?: Animal[]
  movies?: Movie[]
  children?: Person[]
  parent?: Person | null // <--- make the parent nullable
}

// This one shows the error above.
const upsertGraph1 = await Person.query(trx)
        .upsertGraph({ id: 123, parent: { firstname: "hello" } })

// This one works using upsert to unrelate a relation model
const upsertGraph2 = await Person.query(trx)
        .upsertGraph({ id: 123, parent: null })

How should we define the relation type which is nullable when using objection?
It seems that parent?:Parent or parent?:Parent | null both had conditions that doesn't fit in typescript.


Remove BASH_BIN in favor of referencing bash via /usr/bin/env

Type of change
Bug fix.
While using rules_py in combination with rules_oci, I discovered an unexpected behaviour: rules_py generates #! shebang lines using the path to bin that the sh toolchain uses. This has the unexpected side effect of baking in the bash path from the machine that built the container, which may or may not be the same bash path that the container itself will have.
I discovered that macOS, Ubuntu, and the official python Docker image all have bash at /bin/bash, but surprisingly, GitHub Actions workers have it at /usr/bin/bash. As a result, containers built there end up with non-functional binaries. This can be worked around by providing entrypoints like ["bash", "<path to my py_binary>"] rather than ["<path to my py_binary>"], but it'd be ideal to not have to do this.
We can side step this problem entirely by using #!/usr/bin/env bash as our shebang line, which I believe to be sufficiently portable and robust to use for rules_py's scripts. See this Stack Overflow question for further discussion on the approach.
Test plan

Manual testing required. I can put together a sample project if that's useful, but verifying this change just requires running a py_binary and ensuring that it starts up correctly on various host platforms.

 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.

Thank you for the clarification around the exec toolchain; I appreciate it. I'm still getting up to speed in this universe.
Is the concern about hermecity a blocker, or would you like to proceed? If so, let me know what you'd like to see in this PR and I'd happily take a crack at it.

Hi @alexeagle! Just wanted to do a friendly nudge; is this patch something you think would be useful for the broader community or should I close it out? (I just don't want to clutter your open PRs. 😅 )

Yes, sorry I'm just behind getting to this repo. I'd like to understand this one a bit more deeply before merging.

Totally fine! I'm not in a rush (it's a very easy problem to work around on my end). I'm just sensitive to leaving open source folks with gigantic backlogs of PRs from strangers. 😂


Unable to connect to OpenConnect api issue

I have confirmed that my firewall is off and the PC is still showing Approach R10 for the Bluetooth connection. The GSP-R10 Connect says the launch monitor is connected, but unable to connect with OpenConnect api. Any help you can provide is greatly appreciated.

Based on the logs the only thing I can suggest is to double check that gspro open api program is actually running alongside gspro on the same computer you’re running the connector on. It should be a secondary window that pops up when you start gspro. If that is not running I think you need to enable it somewhere in the settings

Any tips on where to enable openapi connect to open with launch? It used to do it and has suddenly stopped for me

Has anyone figured out a fix to this? I am having the same issue


Missing feature as described in the Teams admin portal

This feature is not shown in the TAC>
See:  https://docs.microsoft.com/en-us/microsoftteams/meeting-policies-in-teams#meeting-policy-settings---meeting-attendance-report
++
Currently, you can only use PowerShell to configure this policy setting. You can edit an existing Teams meeting policy by using the Set-CsTeamsMeetingPolicy cmdlet. Or, create a new Teams meeting policy by using the New-CsTeamsMeetingPolicy cmdlet and assign it to users.
And we named the flag differently; so its not obvious to an admin in PS:
AllowEngagementReport

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

ID: 9a8b1087-ae40-6813-16bc-a69c90e50d19
Version Independent ID: b808e843-80d8-4a96-c6ed-e8175968eb73
Content: Microsoft Teams meeting attendance report - Microsoft Teams
Content Source: Teams/teams-analytics-and-reports/meeting-attendance-report.md
Service: msteams
GitHub Login: @SerdarSoysal
Microsoft Alias: serdars

@lynnroe Thank you for submitting feedback.
I think the best way forward is if you open a service ticket in your tenant so this can get resolved ASAP. Based on the outcome let me know if it is something that can be called out in the docs.
Please follow this link to contact support for business products:https://docs.microsoft.com/office365/admin/contact-support-for-business-products
Please keep us posted here on the resolution so we can feed whatever information you discover into the content.


Returning to body as a ghost resets Boo cooldown.

Do Boo
Return to body
Exit the body
Do Boo again

Realy spooky.

Example of bug being reproduced:
https://user-images.githubusercontent.com/31836813/170586549-2826bb3e-363c-423a-ad01-e670ee32af55.mp4

this was fixed a week ago, someone close

Fixed by https://github.com/space-wizards/space-station-14/pull/12936


Publish Blogs 14-05-2021

@ArnavNair Please review

Beginner's Guide to Microservices
Future of Power Generation


Create a '.gitignore' in the 'springdog-embedded-database' path that is generated

Prevent embedded databases from being included in git versions of projects that use that library

is good that includes derby.log too to this patch?

Will be resolved this issue including derby.log too!


Quick change display name for custom namespace

Add a custom.ts property to the example so that you can quickly change the display name for the specified namespace.
The user will always be in front of how to change the display name of the category.

@kimprice You can view? It seems to me that this option should initially be specified so that all users know how to change the name of the created namespace...