text:
Plugin start error

Hey there,
whenever I try to start my Lavalink server with this plugin in it, it fails and crashes with some errors.
org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'restHandler': Lookup method resolution failed
        at org.springframework.beans.factory.annotation.AutowiredAnnotationBeanPostProcessor.checkLookupMethods(AutowiredAnnotationBeanPostProcessor.java:471) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.annotation.AutowiredAnnotationBeanPostProcessor.determineCandidateConstructors(AutowiredAnnotationBeanPostProcessor.java:341) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.determineConstructorsFromBeanPostProcessors(AbstractAutowireCapableBeanFactory.java:1291) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.createBeanInstance(AbstractAutowireCapableBeanFactory.java:1186) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:560) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.createBean(AbstractAutowireCapableBeanFactory.java:520) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.AbstractBeanFactory.lambda$doGetBean$0(AbstractBeanFactory.java:326) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.DefaultSingletonBeanRegistry.getSingleton(DefaultSingletonBeanRegistry.java:234) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.AbstractBeanFactory.doGetBean(AbstractBeanFactory.java:324) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.AbstractBeanFactory.getBean(AbstractBeanFactory.java:200) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.DefaultListableBeanFactory.preInstantiateSingletons(DefaultListableBeanFactory.java:973) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.context.support.AbstractApplicationContext.finishBeanFactoryInitialization(AbstractApplicationContext.java:941) ~[spring-context-6.0.9.jar!/:6.0.9]
        at org.springframework.context.support.AbstractApplicationContext.refresh(AbstractApplicationContext.java:608) ~[spring-context-6.0.9.jar!/:6.0.9]
        at org.springframework.boot.web.servlet.context.ServletWebServerApplicationContext.refresh(ServletWebServerApplicationContext.java:146) ~[spring-boot-3.1.0.jar!/:3.1.0]
        at org.springframework.boot.SpringApplication.refresh(SpringApplication.java:733) ~[spring-boot-3.1.0.jar!/:3.1.0]
        at org.springframework.boot.SpringApplication.refreshContext(SpringApplication.java:435) ~[spring-boot-3.1.0.jar!/:3.1.0]
        at org.springframework.boot.SpringApplication.run(SpringApplication.java:311) ~[spring-boot-3.1.0.jar!/:3.1.0]
        at org.springframework.boot.builder.SpringApplicationBuilder.run(SpringApplicationBuilder.java:150) ~[spring-boot-3.1.0.jar!/:3.1.0]
        at lavalink.server.Launcher.launchMain(Launcher.kt:164) ~[classes!/:4.0.4]
        at lavalink.server.Launcher.main(Launcher.kt:126) ~[classes!/:4.0.4]
        at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method) ~[na:na]
        at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77) ~[na:na]
        at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) ~[na:na]
        at java.base/java.lang.reflect.Method.invoke(Method.java:568) ~[na:na]
        at org.springframework.boot.loader.MainMethodRunner.run(MainMethodRunner.java:49) ~[Lavalink.jar:4.0.4]
        at org.springframework.boot.loader.Launcher.launch(Launcher.java:95) ~[Lavalink.jar:4.0.4]
        at org.springframework.boot.loader.Launcher.launch(Launcher.java:58) ~[Lavalink.jar:4.0.4]
        at org.springframework.boot.loader.JarLauncher.main(JarLauncher.java:65) ~[Lavalink.jar:4.0.4]
Caused by: java.lang.IllegalStateException: Failed to introspect Class [dev.schlaubi.lyrics.lavalink.RestHandler] from ClassLoader [java.net.FactoryURLClassLoader@34f22f9d]
        at org.springframework.util.ReflectionUtils.getDeclaredMethods(ReflectionUtils.java:483) ~[spring-core-6.0.9.jar!/:6.0.9]
        at org.springframework.util.ReflectionUtils.doWithLocalMethods(ReflectionUtils.java:320) ~[spring-core-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.annotation.AutowiredAnnotationBeanPostProcessor.checkLookupMethods(AutowiredAnnotationBeanPostProcessor.java:449) ~[spring-beans-6.0.9.jar!/:6.0.9]
        ... 27 common frames omitted
Caused by: java.lang.NoClassDefFoundError: dev/schlaubi/lyrics/protocol/Lyrics
        at java.base/java.lang.Class.getDeclaredMethods0(Native Method) ~[na:na]
        at java.base/java.lang.Class.privateGetDeclaredMethods(Class.java:3402) ~[na:na]
        at java.base/java.lang.Class.getDeclaredMethods(Class.java:2504) ~[na:na]
        at org.springframework.util.ReflectionUtils.getDeclaredMethods(ReflectionUtils.java:465) ~[spring-core-6.0.9.jar!/:6.0.9]
        ... 29 common frames omitted
Caused by: java.lang.ClassNotFoundException: dev.schlaubi.lyrics.protocol.Lyrics
        at java.base/java.net.URLClassLoader.findClass(URLClassLoader.java:440) ~[na:na]
        at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:587) ~[na:na]
        at java.base/java.net.FactoryURLClassLoader.loadClass(URLClassLoader.java:867) ~[na:na]
        at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:520) ~[na:na]
        ... 33 common frames omitted

2024-04-06T15:57:03.729-07:00  INFO 5708 --- [           main] .s.b.a.l.ConditionEvaluationReportLogger :

Error starting ApplicationContext. To display the condition evaluation report re-run your application with 'debug' enabled.
2024-04-06T15:57:03.791-07:00 ERROR 5708 --- [           main] o.s.boot.SpringApplication               : Application run failed

org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'restHandler': Lookup method resolution failed
        at org.springframework.beans.factory.annotation.AutowiredAnnotationBeanPostProcessor.checkLookupMethods(AutowiredAnnotationBeanPostProcessor.java:471) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.annotation.AutowiredAnnotationBeanPostProcessor.determineCandidateConstructors(AutowiredAnnotationBeanPostProcessor.java:341) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.determineConstructorsFromBeanPostProcessors(AbstractAutowireCapableBeanFactory.java:1291) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.createBeanInstance(AbstractAutowireCapableBeanFactory.java:1186) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.doCreateBean(AbstractAutowireCapableBeanFactory.java:560) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.createBean(AbstractAutowireCapableBeanFactory.java:520) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.AbstractBeanFactory.lambda$doGetBean$0(AbstractBeanFactory.java:326) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.DefaultSingletonBeanRegistry.getSingleton(DefaultSingletonBeanRegistry.java:234) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.AbstractBeanFactory.doGetBean(AbstractBeanFactory.java:324) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.AbstractBeanFactory.getBean(AbstractBeanFactory.java:200) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.support.DefaultListableBeanFactory.preInstantiateSingletons(DefaultListableBeanFactory.java:973) ~[spring-beans-6.0.9.jar!/:6.0.9]
        at org.springframework.context.support.AbstractApplicationContext.finishBeanFactoryInitialization(AbstractApplicationContext.java:941) ~[spring-context-6.0.9.jar!/:6.0.9]
        at org.springframework.context.support.AbstractApplicationContext.refresh(AbstractApplicationContext.java:608) ~[spring-context-6.0.9.jar!/:6.0.9]
        at org.springframework.boot.web.servlet.context.ServletWebServerApplicationContext.refresh(ServletWebServerApplicationContext.java:146) ~[spring-boot-3.1.0.jar!/:3.1.0]
        at org.springframework.boot.SpringApplication.refresh(SpringApplication.java:733) ~[spring-boot-3.1.0.jar!/:3.1.0]
        at org.springframework.boot.SpringApplication.refreshContext(SpringApplication.java:435) ~[spring-boot-3.1.0.jar!/:3.1.0]
        at org.springframework.boot.SpringApplication.run(SpringApplication.java:311) ~[spring-boot-3.1.0.jar!/:3.1.0]
        at org.springframework.boot.builder.SpringApplicationBuilder.run(SpringApplicationBuilder.java:150) ~[spring-boot-3.1.0.jar!/:3.1.0]
        at lavalink.server.Launcher.launchMain(Launcher.kt:164) ~[classes!/:4.0.4]
        at lavalink.server.Launcher.main(Launcher.kt:126) ~[classes!/:4.0.4]
        at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method) ~[na:na]
        at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77) ~[na:na]
        at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) ~[na:na]
        at java.base/java.lang.reflect.Method.invoke(Method.java:568) ~[na:na]
        at org.springframework.boot.loader.MainMethodRunner.run(MainMethodRunner.java:49) ~[Lavalink.jar:4.0.4]
        at org.springframework.boot.loader.Launcher.launch(Launcher.java:95) ~[Lavalink.jar:4.0.4]
        at org.springframework.boot.loader.Launcher.launch(Launcher.java:58) ~[Lavalink.jar:4.0.4]
        at org.springframework.boot.loader.JarLauncher.main(JarLauncher.java:65) ~[Lavalink.jar:4.0.4]
Caused by: java.lang.IllegalStateException: Failed to introspect Class [dev.schlaubi.lyrics.lavalink.RestHandler] from ClassLoader [java.net.FactoryURLClassLoader@34f22f9d]
        at org.springframework.util.ReflectionUtils.getDeclaredMethods(ReflectionUtils.java:483) ~[spring-core-6.0.9.jar!/:6.0.9]
        at org.springframework.util.ReflectionUtils.doWithLocalMethods(ReflectionUtils.java:320) ~[spring-core-6.0.9.jar!/:6.0.9]
        at org.springframework.beans.factory.annotation.AutowiredAnnotationBeanPostProcessor.checkLookupMethods(AutowiredAnnotationBeanPostProcessor.java:449) ~[spring-beans-6.0.9.jar!/:6.0.9]
        ... 27 common frames omitted
Caused by: java.lang.NoClassDefFoundError: dev/schlaubi/lyrics/protocol/Lyrics
        at java.base/java.lang.Class.getDeclaredMethods0(Native Method) ~[na:na]
        at java.base/java.lang.Class.privateGetDeclaredMethods(Class.java:3402) ~[na:na]
        at java.base/java.lang.Class.getDeclaredMethods(Class.java:2504) ~[na:na]
        at org.springframework.util.ReflectionUtils.getDeclaredMethods(ReflectionUtils.java:465) ~[spring-core-6.0.9.jar!/:6.0.9]
        ... 29 common frames omitted
Caused by: java.lang.ClassNotFoundException: dev.schlaubi.lyrics.protocol.Lyrics
        at java.base/java.net.URLClassLoader.findClass(URLClassLoader.java:440) ~[na:na]
        at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:587) ~[na:na]
        at java.base/java.net.FactoryURLClassLoader.loadClass(URLClassLoader.java:867) ~[na:na]
        at java.base/java.lang.ClassLoader.loadClass(ClassLoader.java:520) ~[na:na]
        ... 33 common frames omitted

it is possibly related to https://github.com/DRSchlaubi/lyrics.kt/issues/3 but I don't know how that got fixed

Which version is this?

Which version is this?

2.3.2

Can't reproduce this on 2.3.2

Can't reproduce this on 2.3.2

what versions are you using ?
I'm on jdk 17 and lavalink 4.0.4

Interestingly enough, version 2.2.3 work for me and does not crash

Having the same issue. on v2.3.2
No matter if i use the latest lavalink version or the version with the yt fix: https://repo.lavalink.dev/artifacts/lavalink/fe62703c/Lavalink.jar

└❯ java --version
openjdk 20 2023-03-21
OpenJDK Runtime Environment (build 20+36-2344)
OpenJDK 64-Bit Server VM (build 20+36-2344, mixed mode, sharing)

Operating System: Ubuntu 20.04.6 LTS
Kernel: Linux 5.19.5-051905-generic
Architecture: x86-64

maybe it's due to the combination of some other plugins?
└❯ ls plugins/
lavadspx-plugin-0.0.5.jar  lavalink-2.3.2.jar  lavasearch-plugin-1.0.0.jar  lavasrc-plugin-4.0.1.jar  skybot-lavalink-plugin-1.6.3.jar

  plugins:
    - dependency: "com.github.topi314.lavasrc:lavasrc-plugin:4.0.1" # LavaSrc - extra sources like deezer, spotify, etc.
      repository: "https://maven.lavalink.dev/releases"
    - dependency: "com.github.topi314.lavasearch:lavasearch-plugin:1.0.0"
      repository: "https://maven.lavalink.dev/releases"
    - dependency: "com.dunctebot:skybot-lavalink-plugin:1.6.3"
      repository: "https://maven.lavalink.dev/releases"
    - dependency: "dev.schlaubi.lyrics:lavalink:2.3.2"
      repository: "https://maven.lavalink.dev/releases"
    - dependency: "com.github.devoxin:lavadspx-plugin:0.0.5"
      repository: "https://jitpack.io"

authors: DRSchlaubi SCARTAL Tomato6966


text:
Added CSGO_2033_players.csv file and scraping.ipynb notebook

I have completed with my web scraping Task

Before I merge the Pull Request could you briefly mention the changes and link the issue number to the PR

@sbk2k1 I have created a scraping.ipynb notebook that will scrap data from this website
https://www.playerauctions.com/csgo-stats/ranking/
This is data of 2023 players with all rating, kills, country and many more fields
There are 37 column in Total
I have also added CSV file

Since the issue is not viable anymore, I'll be closing this PR.

source: gharchive/pull-request

repo: DSCKGEC/CS-GO-Professionals

license: MIT

license_type: permissive

license_source: github-api


text:
Add KNN classifier

The k-nearest neighbors algorithm, also known as KNN or k-NN, is a non-parametric, supervised learning classifier, which uses proximity to make classifications or predictions about the grouping of an individual data point.
###Requested Feature
Build a KNN classifier and in the output, f1-score, accuracy and confusion matrix must be printed, there is a function named metrics for printing the accuracy and confusion matrix.
Hyperparameter tuning can be done to improve the accuracy. As the dataset is imbalanced, do prefer f1 score as metric while training.

may I work on this issue?

@RohanHBTU issue is assigned. Go ahead!!

Issue is resolved in commit 3d1b41cecd769cce5bde462bb67dac02abfb8f84

source: gharchive/issue

repo: DSCKGEC/learn-machine-learn


text:
feat: Make resources configurable per tool

Instead of the hard-coded resource configuration, it can now be set per tool.
In addition, this commit adds job labels to cronjobs.
Resolves #1136.

Edited to say: ok wow this is a long one, still looking through it 😆

There were some outdated changes in the PR, which were removed during the last rebase.  You only have to review the commit "feat: Make resources configurable per tool".
Unfortunately I also merged https://github.com/DSD-DBS/capella-collab-manager/pull/1356 already, which you can ignore.

repo: DSD-DBS/capella-collab-manager


text:
🛑 Apps is down

In a739842, Apps (https://apps.unhas.ac.id) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Apps is back up in 9c454b4 after 7 minutes.


text:
🛑 Fakultas Ekonomi is down

In 4f424d0, Fakultas Ekonomi (https://feb.unhas.ac.id) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Fakultas Ekonomi is back up in 3a0d586.


text:
🛑 Unhas Main is down

In 6c80e55, Unhas Main (https://unhas.ac.id) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Unhas Main is back up in 9b862bd after 6 minutes.


text:
🛑 Fakultas Kehutanan is down

In 5c88b4b, Fakultas Kehutanan (https://forestry.unhas.ac.id) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Fakultas Kehutanan is back up in 004eb06 after 43 minutes.


text:
🛑 Fakultas Keperawatan is down

In b3dcbbe, Fakultas Keperawatan (https://nursing.unhas.ac.id) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Fakultas Keperawatan is back up in 72568ae after 28 minutes.


text:
🛑 SSO Unhas is down

In ee9288a, SSO Unhas (https://sso.unhas.ac.id) was down:

HTTP code: 0
Response time: 0 ms

Resolved: SSO Unhas is back up in 5a9636e after 5 minutes.


text:
🛑 Apps is down

In d1b137f, Apps (https://apps.unhas.ac.id) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Apps is back up in 2ed102c after 5 minutes.


text:
Request: time since last update

It would be great to be able to display the number of minutes since last update. Then there is a very simple mathematical operation that can be made in the head to estimate actual number of minutes to departure.
Time to departure at last update = 5
Time since last update = 2
Actual time to departure (estimated) = 3

With the latest update, we have calculation every minute independent of last update time. :)
Add adjust_times: true and (if wanted) hide_departured: true to the card. The card will adjust the time every minute.

That's perfect!!!

I am trying but no luck. The time is not adjusted. This is how my card is configured:
  - departures: true     deviations: true     timeleft: true     adjust_time: true     hide_departed: true     updated: true     entities:       - sensor.storamossen_3     name: Avgångar från Stora Mossen     type: 'custom:sl-card' t
In addition I have set scan_interval to 5 but it only updates every 10 minutes.

I do not know if I should make this a separate issue, but every time I restart hassio the sensor gets a new name:
sensor.storamossen
sensor.storamossen_2
sensor.storamossen_3

Make sure that you have the latest card and sensor.py. Reload page with Ctrl+F5.
departures: true
deviations: true
entities:
  - sensor.kullaberg_3
header: true
timeleft: true
type: 'custom:sl-card'
updated: true
adjust_times: true
hide_departured: true

I have emptied the cache and pressed F5.
The version of the card and the sensor i 1.0.3.

I just copied the sensor.py and the card from scratch to avoid any problem with the custom updater. I also restarted. No new name for the sensor this time. Otherwise we have configured the card the same way. Interestingly, there are several differences:

I also see that you have hide_departured and not hide_departed.

I'm not seeing this calculation either, and I don't have the time in parenthesis after the minutes left.

Can't remember if I used the release zip or "Clone or download"-button.
Uploaded my files here. Delete the "pycache" folder in sl-folder too.
configuration.yaml:
  - platform: sl
    ri4key: !secret sl_ri4key
    si2key: !secret sl_si2key
    siteid: !secret sl_siteid
    friendly_name: Kullaberg
    timewindow: 60
    scan_interval: 7
    # lines: 474, 480C
    # direction: 0
    # sensor: binary_sensor.test

Card:
departures: true
deviations: true
entities:
  - sensor.kullaberg_3
header: true
timeleft: true
type: 'custom:sl-card'
updated: true
adjust_times: true
hide_departured: true

files.zip

Should it be version 1.0.3 or something else?

That's what I have! Very strange. I have emptied caches and reloaded several times. Also restarted. But it doesn't seem to be the card but the sensor that gives us problems. The interval_scan options does not work.

Tried my files from the zip?

I will do that now

No change. Restarted with the new files. Emptied caches twice. Reloaded several times.

Maybe a bug related to the type of transit. Subway vs bus.

Interesting

First issue resolved:
The instruction say adjust_time but it should be adjust_times. using adjust_times: true renders the result I want.

As a consequence hide_departed also works.

I do not in any way know how to code in py and my general coding skills are old and limited. When I checked sensor.py I found that the default interval is 10 minutes (not five as stated in readme). Also I could not find that there was ay code in sensor.py that used the scan_interval instead of the default_interval.

Loggade mot SL:s app - fungerar perfekt!

Wow everyone! =) I have been offline for a day and so many things to do! =) I think I have read and understood everything in the thread:
adjust_times
I have have corrected adjust_time to adjust_times in readme, but the hide_departed seems to be right already as I can see. The hide_departured was from original code of the stuff that I copied over; did I miss it somewhere else than readme?
scan_interval
Yes, this is a bug, I am not a python developer but focusing on stuff like C#, C++, and JavaScript instead and I was under the impression that the Throttling would achive this for me. I will be looking into this further as a quick check shows that I need to instead do this another way. =) Will be opening a separate bug about this.
unique_id
Seems like a bug. Will try and get a grip of this soon. Will create a separate issue for this.
Therefore I will consider this thread to be about the adjust_times issue and I consider that resolved; if I have missed something then please open a new issue for those specific things so I can track them! Thanks!
I will be of celebrating easter with the family a couple of days so expect it to be a few days before something significant happens. But if you find fixes or whatever, please do not hesitate to initiate a PR!!
Thanks all for your assistant in making this stuff awesome!

authors: DSorlov NiklasOlofsson folrewef isabellaalstrom

repo: DSorlov/ha-sensor-sl


text:
Used isValidLength in the EmbedBuilder#build method

Pull Request Etiquette

[x] I have checked the PRs for upcoming features/bug fixes.
[x] I have read the contributing guidelines.

Changes

[x] Internal code
[ ] Library interface (affecting end-user code)
[ ] Documentation
[ ] Other: _____

Description
When looking at #1680, I stumbled upon this and another issue targeted in another PR.
This PR used the isValidLength method in EmbedBuilder#build.
Also removed the length variable in the isValidLength method and unified throwing the exception using the Helpers class.

I can't really tell what this changes? The checks seem identical to me.

Yes, it isn't a big change at all. Now the pre-existing isValidLength method is used to get rid of that minor code duplicate. And I unified that exception message so it's identical with the one above. So it's just minor things.

authors: DManstrator MinnDevelopment

license_source: bigquery


text:
Collapse hidden views – Last/First in group unaffected

If I use the "Collapse hidden views" feature in a group it will only work with surrounded layers.
For example a group with 3 layers: Headline, Copy, Link.
Whenever I hide the Link or Headline layer the group doesn't resize, only the Copy layer affects the group.
This feature would be great for whenever you have a long stacked maingroup-subgroup list with a lot of subgroup variaties. (e.g. Link isn't part of every element)

In other words, the first and last layers in a group, when hidden, do not affect the size of the group.

Great find @HendrikVdB!
This one turned out to be quite tricky to do surprisingly — but I think I cracked it. Will be included in v0.4 which will be out in the next day or 2.

Fixed for me.

Awesome. I'll close it for now

authors: DWilliames HendrikVdB aparajita


text:
Added years and new contests

Added years and new contests. Please check everything looks ok :)

Please ignore this PR. Made a mistake with bot names

repo: DadeKuma/bot-racer


text:
Mouse capture issue on Mac

Steps to reproduce:

Launch Unvanquished in a window with a map, like ./daemon -set r_fullscreen 0 -set r_mode 9 +devmap plat23
Click on Unvanquished's icon in the task bar before it finishes loading the map.
Leave the cursor outside the window until loading finishes.

On 0.52 with SDL 2.0.12, the bug manifests as following: the cursor is outside the window, but the game responds to mouse movements (changing view direction). The program returns to a normal state upon moving the cursor into the window.
With SDL 2.0.22, the bug is worse. The game does not respond to mouse movements and does not capture the mouse, even if you move the mouse into the window and click on it. To get out of the buggy state you must click on another program and then click on Unvanquished again.

It's worse than I thought with 2.0.22. The bug occurs after every cgame restart, even if you keep the mouse in the window. I think I'll hold back SDL to 2.0.12 for the release.

Good to know… and another argument in favor of recommending our own builds !

The SDL 2.0.22 part would hopefully be solved by #600.

The symptoms of these bugs don't look similar to me :\

On 0.52 with SDL 2.0.12, the bug manifests as following: the cursor is outside the window, but the game responds to mouse movements (changing view direction). The program returns to a normal state upon moving the cursor into the window.

For information this bug is also present on Linux.

Another way to produce the bug is to start the game like ./daemon -resetconfig -set r_mode 7 -set r_fullscreen 0 +map parpax with the mouse outside the window when it starts, and then not touch anything until the map loads. I guess the important thing is that when the game loads the app has focus but the mouse is outside of it.
I think the problem is that IN_CenterMouse doesn't work when the cursor is outside the window.

Actually IN_CenterMouse just wasn't called when switching to deltas mode (I misread the code). With some difficulty I was able to get it to center the mouse in that case, but it still didn't help anything. The real problem is that the mouse does not get trapped in the window. When enabling deltas mode we do SDL_SetWindowGrab(SDL_ENABLE) and SDL_SetRelativeMouseMode(SDL_ENABLE), both of which are supposed to confine the cursor to the window, but they don't work. The cursor is not grabbed and it is still possible to move the cursor outside the window. The mouse is only grabbed after you click inside the window.
Some more ways to produce the bug:

Open the console, move the cursor outside the window, then close the console
Click on Unvanquished in the taskbar while it is unfocused

On Windows there is the correct behavior in all cases: whenever Deltas mode is activated, the cursor gets confined to the window (regardless of where it was located before). On Mac the APIs are not working as advertised in the case that the cursor starts outside the window.

In the simple test program below, SDL_SetWindowGrab works as expected. When enabled it relocates the cursor to the inside of the window and prevents it from escaping. (SDL_SetRelativeMouseMode, on the other hand, does not keep the cursor confined on its own.) So something within the greater complexity of Daemon makes it not work.
#include <SDL.h>
#include <iostream>

const int SCREEN_WIDTH = 800;
const int SCREEN_HEIGHT = 600;

int main(int arc, char ** argv) {

    if (SDL_Init( SDL_INIT_VIDEO ) < 0) {
        std::cout << "SDL could not initialize! SDL_Error: " << SDL_GetError() << std::endl;
    }

        auto* window = SDL_CreateWindow(
            "SDL2 Demo",
            SDL_WINDOWPOS_CENTERED, SDL_WINDOWPOS_CENTERED,
            SCREEN_WIDTH, SCREEN_HEIGHT,
            SDL_WINDOW_SHOWN
        );

    bool grabby = false;
    while (true) {
        SDL_Event e;
        SDL_WaitEvent(&e);
        switch (e.type) {
            case SDL_QUIT:
                return 0;
            case SDL_KEYDOWN:
                if (e.key.keysym.sym == SDLK_SPACE ) {
                    grabby = !grabby;
                    std::cout << "grabby set to " << grabby << std::endl;
                    SDL_SetWindowGrab(window, (SDL_bool)grabby);
                    //SDL_SetRelativeMouseMode((SDL_bool)grabby);
                }
        }
    }
}

Oh, it's precisely SDL_SetRelativeMouseMode that makes it not work! If I uncomment the call to SDL_SetRelativeMouseMode in the demo above, then grabbing no longer works if the cursor is outside the window.

The demo with both SDL_SetWindowGrab and SDL_SetRelativeMouseMode is broken on SDL 2.0.12, but works on SDL 2.0.22. And I have found that this bug is fixed by the combination of updating to newer SDL and adding a call to SDL_PumpEvents (#871).

The demo with both SDL_SetWindowGrab and SDL_SetRelativeMouseMode is broken on SDL 2.0.12, but works on SDL 2.0.22. And I have found that this bug (#628) is fixed by the combination of updating to newer SDL and adding a call to SDL_PumpEvents (#871).

Does updating to SDL2 2.26.5 still works?

https://github.com/DaemonEngine/Daemon/pull/857

Let's avoid testing things with SDL 2.0.22, because there is a related
regression https://github.com/libsdl-org/SDL/issues/5569.
On Mon, May 15 2023 at 05:31:30 -07:00:00, Thomas Debesse
@.***> wrote:

The demo with both SDL_SetWindowGrab and SDL_SetRelativeMouseMode is
broken on SDL 2.0.12, but works on SDL 2.0.22. And I have found that
this bug (#628) is fixed by the combination of updating to newer SDL
and adding a call to SDL_PumpEvents (#871).

Does updating to SDL2 2.26.5 still works?
#857
—
Reply to this email directly, view it on GitHub, or unsubscribe.
You are receiving this because you commented.Message ID:
@.***>

Yes this bug can still be fixed with SDL 2.26.5

This was fixed by #857 and https://github.com/Unvanquished/Unvanquished/pull/2695.

authors: illwieckz necessarily-equal slipher

repo: DaemonEngine/Daemon


text:
mowe emoji (ꈍᴗꈍ)

i added some mowe e-emoji, 😳 these ones a-awe cat themed and awso incwude s-some unicode stuff i hope you w-wike them,,, OwO
i kept the wut tabwe t-to a powew of 2 because i know computews wike t-that (ꈍᴗꈍ)

yay now whoever wants to add more emojis will have to come up with 32 more :)


text:
& lifting above function call when it's part of the function

`a${&}b` c
// vvv
($) => `a${$}b`(c);

The fundamental question here is whether & should lift above a function call when it's part of the function. Currently it does:
& x -> $ => $(x)

I think this is the correct behavior. Another example to illustrate:
items.forEach .add 1
// items.forEach(($) => $.add(1));

repo: DanielXMoore/Civet


text:
Postfix if doesn't add destructure declaration to block

x if { x } := y

Expected
let ref;
if ((ref = y)) {
  const { x } = y;
  x;
}

Actual
let ref;
if ((ref = y)) {
  x;
}

Wow, I learned from this that JavaScript chose the value of the destructuring assignment ({x} = y) to be y, not {x}. Seems like a very strange choice because it means that ({x} = {y} = z) does not mean the same thing as ({y}=z); ({x}={y}); which seems very counterintuitive. But oh well, I guess the TC39 knows best ;-).


text:
torch2trt on jetson nano

Hi, I want to speed up this model so I tried to use torch2trt to convert this model into Tensorrt and run it on jetson nano.
so basically I used torch2trt(net, data, fp16_mode=True) to convert the model. And in demo.py, I used
model_trt.load_state_dict(torch.load('trt.pth')) to load the model. i set the input with (1,3,192,192)
It works but did not get higher FPS. I think because of fp16. Since I tried both True and also fp16_mode = False. The result of both models is the same. Do you know what should I fix it?
best regards
chenwei

Hi! We have similar issue in the neighborhood repository. I suggest to profile which part of pipeline takes the most of time. This probably may be due to Python-based post-processing. If so, C++ version from that repository can be reused.

Hi! We have similar issue in the neighborhood repository. I suggest to profile which part of pipeline takes the most of time. This probably may be due to Python-based post-processing. If so, C++ version from that repository can be reused.

Hi! We have similar issue in the neighborhood repository. I suggest to profile which part of pipeline takes the most of time. This probably may be due to Python-based post-processing. If so, C++ version from that repository can be reused.

thanks for your advice, I think its because of pose processing.  will try

Hi! We have similar issue in the neighborhood repository. I suggest to profile which part of pipeline takes the most of time. This probably may be due to Python-based post-processing. If so, C++ version from that repository can be reused.

thanks for your advice, I think its because of pose processing.  will try

It works but did not get higher FPS. I think because of fp16. Since I tried both True and also fp16_mode = False. The result of both models is the same. Do you know what should I fix it?

If your device doesn't support float 16 inference type, fp16 mode on or off is same


text:
Question regarding overlapping

First of all, Thank you for sharing your excellent work!
I have a question about overlapping (pingpong design). From my understanding:

With FP8 precision and a head dimension of 128, the exponential function seems to take the same amount of time as GEMM0 + GEMM1. This is because matmul is 512 times faster than the exponential function, and there are 512 times more FLOPs in matmul than the exponential operation.

The softmax function involves two MUFU: one for the exponential function and another for floating-point division. This indicates that softmax should be about twice as slow as GEMM0+GEMM1.

However, the figure provided shows that softmax takes only half as much time as GEMM0 + GEMM1.
If softmax takes twice more time than GEMMs (GEMM0 + GEMM1), GEMM operations might be idle for half of the time.

So my questions are:

Is my understanding of the time consumption for GEMM and softmax correct?
Specifically, is the time consumption really bound by MUFU for FP8 precision and a head dimension of 128?
If my understanding is correct, does this mean that GEMM operations are only executing for half the time while the other half of the time, they remain idle?
Thank you!

The figure is not drawn to scale, it's just an illustration.
The way we do it, softmax only has 1 MUFU (exponential). There's no floating point division. Division is done at the very end.

authors: tridao wookjeHan

repo: Dao-AILab/flash-attention


text:
BalancerWhitePaperAna

BalancerWhitePaperAna
basically the math calculation part for the balancer. please help to check

add the balancer recent hack. for the SNX token, it can lead to DOS attack to balancer flashloan

repo: Dapp-Learning-DAO/Dapp-Learning


text:
App not asking for storage perms and not downloading anything as well as the downloads button/folder not oppening within app

Your issue may already be reported!
Please search on the issue tracker before creating one.
Expected Behavior

Current Behavior

Possible Solution

Steps to Reproduce (for bugs)

Context

Your Environment

Version used:
Operating System version:

NHentai link (if relevant):

The same thing happened to me. Here's how I fixed it:

Back up all downloaded comics then uninstall the current version.
Install version 2.8 and grant storage permission.
Overwrite the installation to the latest version(for me is 3.0.0).

If normal, the granted permissions are retained.

Thanks so much bro ... at last I can keep the hentai that I want!


text:
Calibrate OM10 magnitudes to PhoSim Catalog magnitudes

Need to figure out what bands the magnitudes that come out of OM10 are in and convert to LSST magnitudes for catalogs.

Added to task list under #37

Hi @drphilmarshall,
Do you have any sort of legend for the OM10 catalog variables? I'm just wondering what values I should give for magnitudes of the images. I originally thought that the 'MAG' column was a magnification in magnitudes but when @SimonKrughoff was trying to make phosim images he was getting problems and I went to the OM10 catalog and realized some of those 'MAG' values are in the order +/- 100 so that can't be the case.

I found this code from the OM10 repo here, so I will go with what's there for RA, DEC, MAG adjustments for images for now until I hear otherwise.

That's right: 'MAG' is the magnification of each quasar image, so you need
to subtract -2.5log10 of MAG from the source magnitude. The magnification
is the same in each filter, since lensing (and geometric optics in general)
is achromatic.
On Wed, Feb 10, 2016 at 11:39 AM, Bryce Kalmbach notifications@github.com
wrote:

I found this code from the OM10 repo here
https://github.com/drphilmarshall/OM10/blob/master/om10/db.py#L215, so
I will go with what's there for RA, DEC, MAG adjustments for images for now
until I hear otherwise.
—
Reply to this email directly or view it on GitHub
https://github.com/DarkEnergyScienceCollaboration/Twinkles/issues/46#issuecomment-182544209
.

With #119 we have the correct magnification definition in the sprinkler now. Also, the 'i' band magnitudes for lens galaxies has been translated into the "imsimband" for the correct magNorm values.

Boom!
On Thu, Feb 11, 2016 at 3:56 PM, Bryce Kalmbach notifications@github.com
wrote:

Closed #46
https://github.com/DarkEnergyScienceCollaboration/Twinkles/issues/46.
—
Reply to this email directly or view it on GitHub
https://github.com/DarkEnergyScienceCollaboration/Twinkles/issues/46#event-547932475
.

authors: drphilmarshall jbkalmbach

repo: DarkEnergyScienceCollaboration/Twinkles

license: mit


text:
Mem spd displayed v2

Replaces: https://github.com/Dasharo/open-source-firmware-validation/pull/204
Results:

QEMU:

==============================================================================
Setup-Menu-Information
==============================================================================
SET001.001 CPU clock speed displayed in setup menu :: This test ca... | PASS |
------------------------------------------------------------------------------
SET002.001 RAM speed displayed in setup menu :: This test case ver... | FAIL |
RAM speed not found
------------------------------------------------------------------------------
SET003.001 RAM size displayed in setup menu :: This test case veri... | PASS |
------------------------------------------------------------------------------
SET004.001 Expected CPU clock speed displayed in setup menu :: Thi... | SKIP |
SET004.001 not supported: Variable: ${PLATFORM_CPU_SPEED} is not defined
------------------------------------------------------------------------------
SET005.001 Expected RAM speed displayed in setup menu :: This test... | SKIP |
SET005.001 not supported: Variable: ${PLATFORM_RAM_SPEED} is not defined
------------------------------------------------------------------------------
SET006.001 Expected RAM size displayed in setup menu :: This test ... | SKIP |
SET006.001 not supported: Variable: ${PLATFORM_RAM_SIZE} is not defined
------------------------------------------------------------------------------
Setup-Menu-Information                                                | FAIL |
6 tests, 2 passed, 1 failed, 3 skipped
==============================================================================

The RAM speed failure is expected, as QEMU firmware does not report this value in fact.

Pass on Protectli VP4630/VP4670

==============================================================================
Setup-Menu-Information
==============================================================================
SET001.001 CPU clock speed displayed in setup menu :: This test ca... | PASS |
------------------------------------------------------------------------------
SET002.001 RAM speed displayed in setup menu :: This test case ver... | PASS |
------------------------------------------------------------------------------
SET003.001 RAM size displayed in setup menu :: This test case veri... | PASS |
------------------------------------------------------------------------------
SET004.001 Expected CPU clock speed displayed in setup menu :: Thi... | PASS |
------------------------------------------------------------------------------
SET005.001 Expected RAM speed displayed in setup menu :: This test... | PASS |
------------------------------------------------------------------------------
SET006.001 Expected RAM size displayed in setup menu :: This test ... | PASS |
------------------------------------------------------------------------------
Setup-Menu-Information                                                | PASS |
6 tests, 6 passed, 0 failed
==============================================================================

@mkopec can you please try one one of the APUs as well?

Log from apu4 - 3 first tests pass, rest are SKIP due to missing variables in platform configs. LGTM overall
log2.zip

authors: macpijan mkopec

repo: Dasharo/open-source-firmware-validation


text:
[DUOS-1740][risk=no] Update react select 5.7.7 -> 5.8.0

Addresses
https://broadworkbench.atlassian.net/browse/DUOS-1740
Summary
Update react select to latest

Have you read Terra's Contributing Guide lately? If not, do that first.

Label PR with a Jira ticket number and include a link to the ticket
Label PR with a security risk modifier [no, low, medium, high]
PR describes scope of changes
Get a minimum of one thumbs worth of review, preferably two if enough team members are available
Get PO sign-off for all non-trivial UI or workflow changes
Verify all tests go green
Test this change deployed correctly and works on dev environment after deployment

Dependabot will update this

repo: DataBiosphere/duos-ui


text:
Tweak behavior of data tab refreshing

On the Data tab, when I click the tab header, the page refreshes its data. If I happen to be on page 3 of samples, for example, I remain on page 3 of samples.
If I click the sample data type, the data refreshes but I am placed back on page 1.
I wonder if this is a history state problem. Should we be storing to history only on component-will-unmount so the behavior better matches our expectations?

What are our users' expectations of this behavior?

Good question, and I don't know. @bradtaylor might weigh in, but I think for our first pass we should just have consistent behavior between the two.

authors: dmohs panentheos

repo: DataBiosphere/saturn-ui


text:
Add Delete & Create for Galaxy [Saturn-1803] [SATURN-1805]

This is the first Galaxy PR. Adding the button in the Notebooks tab which will be used for the 'Create' and 'Delete' flows. There is a new 'newGalaxyModal' file which closely follows the feel/look/style of the 'newClusterModal' for these flows. With this PR a user should be able to create a Galaxy App and Delete a Galaxy App when the feature flag is enabled.
Need to test! Don't merge yet
Also before merging ensure all feature flags are set to 'false'

@breilly2 will update the delete call to specify deleting the PD as well. Do you think the labels/filtering needs to be done in this PR or can that be a followup ?

repo: DataBiosphere/terra-ui


text:
Remove useLabelAssert

In theory, useLabelAssert checks if an interactive element has an accessible name.
However, it doesn't do that very well. It may check if the element has an id or aria-labelledby attribute, but it doesn't check if there's actually a label element that references the ID or an element with the ID referenced by aria-labelledby. Also, its logic related to tooltips is dependent on how component uses the tooltip prop.
Now that we have better tools (axe DevTools and @axe-core/react) to check for this sort of accessibility issue, I think we can get rid of useLabelAssert.

Excellent judgment.

I second that.  Great call Nick.

authors: msilva-broad nawatts


text:
Add ability to start the agent without waiting for it to be ready

Currently it takes over 50 seconds for this action to be ready. Most of this time is spent waiting for the datadog agent to be ready.
It will be very useful if we can start the agent without waiting, then do some other work (like restoring cache for instance) and then check and wait for it to be ready.
This can be exposed by adding two additional inputs to the action:

skip_wait - skip the wait for the agent to be ready
skip_start - don't start the agent - this will be useful to run the action with just wait for an agent that was started before already.

+1 to the solution proposed. Right now the start of the agent is blocking and adds 60s to all builds, which isn't ideal for something meant to help make CI pipelines faster.

Like @pcothenet said, it's far from ideal to increase ~60s our pipelines and also increase the related GH actions costs just to monitor them.
Are you planning to improve this? Do you have any setup proposals to make this faster?

Hi! Thanks for the proposal: I think it makes sense and should be something we do. In the meantime, it's possible to report tests to CI Visibility via what we call "agentless mode", that is, not using an agent: https://docs.datadoghq.com/continuous_integration/tests/javascript/?tab=cloudciprovideragentless
Let me know if you're able to test this mode and if it works for you 😄

@juan-fernandez Is the agentless mode available for Ruby? I see it mentioned only in the JS docs.

@juan-fernandez Is the agentless mode available for Ruby? I see it mentioned only in the JS docs.

sadly not yet. It's only available in .NET, Java, Swift and Javascript.

hey @dsantosmerino, agentless mode is now supported in Ruby: https://docs.datadoghq.com/tests/setup/ruby/?tab=cloudciprovideragentless. This is the way we're recommending github actions users to use.
We're deprecating this action

authors: dpp23 dsantosmerino juan-fernandez pcothenet

repo: DataDog/agent-github-action


text:
[Ochestrator] add retry strategy to syncinformer

What does this PR do?
Implement exponential backoff to syncinformer. The Deadline is 60 seconds and each n times try it will augment timeout value to kube_cache_sync_timeout_seconds+2^n .
For example , when kube_cache_sync_timeout_seconds = 5s :
First try : 5s
Second retry : 6s
Third retry : 7s
Forth retry : 9s
....
until 60s
Tested locally:
2021-12-02 15:05:51 UTC | CLUSTER | WARN | (pkg/util/kubernetes/apiserver/util.go:48 in func1) | couldn't sync informer RoleBinding in 3.246µs
2021-12-02 15:05:51 UTC | CLUSTER | WARN | (pkg/util/kubernetes/apiserver/util.go:51 in func1) | increase kube_cache_sync_timeout_seconds to 1s
2021-12-02 15:05:51 UTC | CLUSTER | WARN | (pkg/util/kubernetes/apiserver/util.go:48 in func1) | couldn't sync informer ClusterRole in 1.91µs
2021-12-02 15:05:51 UTC | CLUSTER | WARN | (pkg/util/kubernetes/apiserver/util.go:51 in func1) | increase kube_cache_sync_timeout_seconds to 1s
2021-12-02 15:05:51 UTC | CLUSTER | DEBUG | (pkg/util/kubernetes/apiserver/util.go:60 in func1) | Sync done for informer Service in 100.87932ms, last resource version: 60711
2021-12-02 15:05:51 UTC | CLUSTER | DEBUG | (pkg/util/kubernetes/apiserver/util.go:60 in func1) | Sync done for informer StatefulSet in 100.394564ms, last resource version: 60711
2021-12-02 15:05:51 UTC | CLUSTER | DEBUG | (pkg/util/kubernetes/apiserver/util.go:60 in func1) | Sync done for informer ClusterRoleBinding in 100.160187ms, last resource version: 60711
2021-12-02 15:05:51 UTC | CLUSTER | DEBUG | (pkg/util/kubernetes/apiserver/util.go:60 in func1) | Sync done for informer ReplicaSet in 100.564022ms, last resource version: 60711
2021-12-02 15:05:51 UTC | CLUSTER | DEBUG | (pkg/util/kubernetes/apiserver/util.go:60 in func1) | Sync done for informer CronJob in 101.657379ms, last resource versi

Motivation

Additional Notes

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

Reviewer's Checklist

[ ] If known, an appropriate milestone has been selected; otherwise the Triage milestone is set.
[ ] The appropriate team/.. label has been applied, if known.
[ ] A release note has been added or the changelog/no-changelog label has been applied.
[ ] Changed code has automated tests for its functionality.
[ ] Adequate QA/testing plan information is provided if the qa/skip-qa label is not applied.
[ ] If applicable, docs team has been notified or an issue has been opened on the documentation repo.
[ ] If applicable, the need-change/operator and need-change/helm labels have been applied.
[ ] If applicable, the config template has been updated.

what would be the total retry time to reach the last 60s retry?

what would be the total retry time to reach the last 60s retry?

If the kube_cache_sync_timeout_seconds is 5s, the total retry time will be 5+2^0 + 5+2^1 + 5+2^2 + 5+2^3 + 5+2^4 + 5+2^5 + 65(in last retry, normally it should be 5+2^6=69, but 69> 60+5 so we take 65) = 6+7+9+13+21+37+65=158s

I left some comments inline, but I have a bigger question:
I may be missing something completely, and definitely not an expert in k8s APIs, but this code doesn't seem to implement backoff: WaitForCacheSync is retried immediately after it has failed, without any delay, but with progressively larger timeouts. Actual sync seems to be happening elsewhere (only impl of HasSynced I found doesn't do any work), so we're not backing off from the API even if a delay was inserted. From reading the changelog entry I expected we would backoff from the kubelet API, but it isn't what is happening here.
And given that WaitForCacheSync is just waiting for a boolean to become true, what is the reason to increase timeouts slowly? If we're going to wait 60 seconds anyway, we might just pass that as a timeout to begin with. (WaitForCacheSync can also wait on multiple informers, so the code where we launch sync one by one in separate goroutines could possibly be simplified too).

Hi @vickenty  I think you are perfectly right. This is not an API backoff, what we do is progressively increase the timeout value. But it solves the issue of the default timeout and it avoids waiting too much time on the sync in case the sync fails if we only set a higer timeout value .  I will rename it to exponentialWait to make it make clearer.

But it solves the issue of the default timeout and it avoids waiting too much time on the sync in case the sync fails if we only set a higer timeout value.

Sorry, I'm not sure I follow. In what situation the code would wait too much? WaitForCacheSync returns true as soon as the sync is complete (HasSynced returned true). Calling it once with a large timeout, or several times with smaller timeouts would have the same effect: either sync is done and we get out early, or we wait the full time (combined) timeout.

But it solves the issue of the default timeout and it avoids waiting too much time on the sync in case the sync fails if we only set a higer timeout value.

Sorry, I'm not sure I follow. In what situation the code would wait too much? WaitForCacheSync returns true as soon as the sync is complete (HasSynced returned true). Calling it once with a large timeout, or several times with smaller timeouts would have the same effect: either sync is done and we get out early, or we wait the full time (combined) timeout.

Indeed, my initial idea is wrong. If the sync fails, we have wait the full time timeout in both cases.

closing this in favor of a simpler and safer solution #10470

authors: kangyili mfpierre vickenty

repo: DataDog/datadog-agent


text:
Fix cgo type file relative path processing

What does this PR do?
Fixes the post-processing of cgo type files to handle additional parameters in the cgo command.
Motivation
Maintain relative paths, rather than absolute which usually includes personal workspace folders.
Additional Notes

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

Reviewer's Checklist

[ ] If known, an appropriate milestone has been selected; otherwise the Triage milestone is set.
[ ] Use the major_change label if your change either has a major impact on the code base, is impacting multiple teams or is changing important well-established internals of the Agent. This label will be use during QA to make sure each team pay extra attention to the changed behavior. For any customer facing change use a releasenote.
[ ] A release note has been added or the changelog/no-changelog label has been applied.
[ ] Changed code has automated tests for its functionality.
[ ] Adequate QA/testing plan information is provided if the qa/skip-qa label is not applied.
[ ] At least one team/.. label has been applied, indicating the team(s) that should QA this change.
[ ] If applicable, docs team has been notified or an issue has been opened on the documentation repo.
[ ] If applicable, the need-change/operator and need-change/helm labels have been applied.
[ ] If applicable, the k8s/<min-version> label, indicating the lowest Kubernetes version compatible with this feature.
[ ] If applicable, the config template has been updated.

Thanks for doing this !

authors: brycekahle paulcacheux


text:
[NPM] test E2E containerized agent tests

What does this PR do?
Run NPM basic test when an agent is deploy in a container (docker)
Motivation
Additional Notes
Depend on test infra PR581
Docker Images are from public ECR aws rate limited at 10 pull per seconds
https://docs.aws.amazon.com/AmazonECR/latest/public/public-service-quotas.html
Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

Reviewer's Checklist

[ ] If known, an appropriate milestone has been selected; otherwise the Triage milestone is set.
[ ] Use the major_change label if your change either has a major impact on the code base, is impacting multiple teams or is changing important well-established internals of the Agent. This label will be use during QA to make sure each team pay extra attention to the changed behavior. For any customer facing change use a releasenote.
[ ] A release note has been added or the changelog/no-changelog label has been applied.
[ ] Changed code has automated tests for its functionality.
[ ] Adequate QA/testing plan information is provided. Except if the qa/skip-qa label, with required either qa/done or qa/no-code-change labels, are applied.
[ ] At least one team/.. label has been applied, indicating the team(s) that should QA this change.
[ ] If applicable, docs team has been notified or an issue has been opened on the documentation repo.
[ ] If applicable, the need-change/operator and need-change/helm labels have been applied.
[ ] If applicable, the k8s/<min-version> label, indicating the lowest Kubernetes version compatible with this feature.
[ ] If applicable, the config template has been updated.

/merge


text:
usm: kafka: Parse fetch responses

What does this PR do?
Adds parsing of fetch responses in order to get the counts of records fetched.

Motivation
https://datadoghq.atlassian.net/browse/USMON-818

Additional Notes
See this page for more details about the implementation and test results:
https://datadoghq.atlassian.net/wiki/spaces/UT/pages/3575776080/Kafka+Fetch+Response+handling

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

Please attach the load test results to the PR

Please add to the PR description the cost of the 2 new maps (assuming 65K entries)

Added load test results and map sizes information to the PR description.

Can merge

/merge

authors: DanielLavie guyarb vitkyrka


text:
[ASCII-2415] Add merged CPU profiles for each agent process and use PGO

What does this PR do?
Same as https://github.com/DataDog/datadog-agent/pull/30313 but using merged profiles from prod.
Motivation
Describe how to test/QA your changes
Possible Drawbacks / Trade-offs
Additional Notes

Regression Detector Results
Run ID: f9ba7d3a-26ae-469b-845e-effef8ec6509 Metrics dashboard Target profiles
Baseline: 7.58.0
Comparison: 7-58-1-beta-pgo-prod-profiles-merged-py3
Performance changes are noted in the perf column of each table:

✅ = significantly better comparison variant performance
❌ = significantly worse comparison variant performance
➖ = no significant change in performance

Significant changes in experiment optimization goals
Confidence level: 90.00%
Effect size tolerance: |Δ mean %| ≥ 5.00%

perf
experiment
goal
Δ mean %
Δ mean % CI
trials
links

❌
tcp_syslog_to_blackhole
ingress throughput
-9.08
[-9.10, -9.06]
1
Logs

Fine details of change detection per experiment

perf
experiment
goal
Δ mean %
Δ mean % CI
trials
links

➖
idle_all_features
memory utilization
+0.60
[+0.56, +0.64]
1
Logs bounds checks dashboard

➖
quality_gate_idle_all_features
memory utilization
+0.45
[+0.41, +0.49]
1
Logs bounds checks dashboard

➖
idle
memory utilization
+0.22
[+0.20, +0.25]
1
Logs bounds checks dashboard

➖
basic_py_check
% cpu utilization
+0.13
[-1.06, +1.33]
1
Logs

➖
file_to_blackhole_1000ms_latency
egress throughput
+0.09
[-0.13, +0.30]
1
Logs

➖
file_to_blackhole_0ms_latency
egress throughput
+0.02
[-0.13, +0.17]
1
Logs

➖
file_to_blackhole_500ms_latency
egress throughput
+0.02
[-0.09, +0.13]
1
Logs

➖
uds_dogstatsd_to_api
ingress throughput
+0.00
[-0.04, +0.05]
1
Logs

➖
tcp_dd_logs_filter_exclude
ingress throughput
+0.00
[-0.00, +0.00]
1
Logs

➖
quality_gate_idle
memory utilization
-0.01
[-0.04, +0.01]
1
Logs bounds checks dashboard

➖
file_to_blackhole_300ms_latency
egress throughput
-0.04
[-0.13, +0.04]
1
Logs

➖
file_to_blackhole_100ms_latency
egress throughput
-0.11
[-0.21, -0.00]
1
Logs

➖
otel_to_otel_logs
ingress throughput
-0.63
[-0.99, -0.27]
1
Logs

➖
file_tree
memory utilization
-0.64
[-0.69, -0.59]
1
Logs

➖
pycheck_lots_of_tags
% cpu utilization
-1.39
[-2.48, -0.30]
1
Logs

➖
uds_dogstatsd_to_api_cpu
% cpu utilization
-4.06
[-4.39, -3.74]
1
Logs

❌
tcp_syslog_to_blackhole
ingress throughput
-9.08
[-9.10, -9.06]
1
Logs

Bounds Checks

perf
experiment
bounds_check_name
replicates_passed

❌
idle
memory_usage
20/50

❌
quality_gate_idle
memory_usage
27/50

✅
file_to_blackhole_0ms_latency
memory_usage
50/50

✅
file_to_blackhole_1000ms_latency
memory_usage
50/50

✅
file_to_blackhole_100ms_latency
memory_usage
50/50

✅
file_to_blackhole_300ms_latency
memory_usage
50/50

✅
file_to_blackhole_500ms_latency
memory_usage
50/50

✅
idle_all_features
memory_usage
50/50

✅
quality_gate_idle_all_features
memory_usage
50/50

Explanation

A regression test is an A/B test of target performance in a repeatable rig, where "performance" is measured as "comparison variant minus baseline variant" for an optimization goal (e.g., ingress throughput). Due to intrinsic variability in measuring that goal, we can only estimate its mean value for each experiment; we report uncertainty in that value as a 90.00% confidence interval denoted "Δ mean % CI".
For each experiment, we decide whether a change in performance is a "regression" -- a change worth investigating further -- if all of the following criteria are true:

Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.

Its 90.00% confidence interval "Δ mean % CI" does not contain zero, indicating that if our statistical model is accurate, there is at least a 90.00% chance there is a difference in performance between baseline and comparison variants.

Its configuration does not mark it "erratic".


text:
Where to put this on multi module project?

Hi Guys,
This is not really a bug, just a question.. I have a multi module project and I tried putting this on main app module and also on every module but I always get the
"The dd-android-gradle-plugin has been applied on a non android application project" warning.
Is this ok?

Hi @mpaduchh,
Thanks for contacting us. Plugin is supposed to work with application module only, so it should be added only once in your setup. Let us know if you have more questions or experience other issues with plugin installation.

Please update the samples, they contain commented code and it's not clear where to add things exactly

Hi, @pvegh, as mentionned in our documentation, you need to add the plugin to your application's build.gradle or build.gradle.kts file:
// In your app's build.gradle script
plugins {
    id("com.datadoghq.dd-sdk-android-gradle-plugin") version "x.y.z"
}

We have a project to indeed make our samples project more understandable, which should be done in the next few months.

authors: 0xnm mpaduchh pvegh xgouchet

repo: DataDog/dd-sdk-android-gradle-plugin


text:
[manager] verify program type for tail_call map

What does this PR do?
Tail call map must have an unique program type per program array (post check)
Motivation
Inserting multiple program (fd) type in a prog array is possible, but will not work

How would this fail without this code? Would the verifier reject the program? or would the map put fail?

@nplanel mind answering my earlier question? What happens if two different program types share the same prog array map? Is that even allowed?

@brycekahle sorry I didn't see your last messages, I don't remember the full context but hit this issue and had a chat with @Gui774ume

@brycekahle it's when you mix socket filter type and trancepoint or uprobes ....
When the caller setup the tail calls via manager.TailCallRoute

closing for now. If we decide we need/want this, we can open a new PR.

authors: brycekahle nplanel

repo: DataDog/ebpf-manager


text:
Use WeakRef

What does this PR do?
Use WeakRef to remove some circular references
Motivation

Additional Notes

Review checklist (to be filled by reviewers)

[ ] Feature or bugfix MUST have appropriate tests (unit, integration, e2e)
[ ] PR title must be written as a CHANGELOG entry (see why)
[ ] Files changes must correspond to the primary purpose of the PR as described in the title (small unrelated changes should have their own PR)
[ ] PR must have changelog/ and integration/ labels attached

Motivation?

I think mostly these https://github.com/DataDog/integrations-core/pull/6933 https://github.com/DataDog/integrations-core/pull/7150.
Alex found an issue with circular dep when passing raw logger as arguments

This might not an actual issue since check instances are reused and they can still be garbage collected.

authors: AlexandreYang coignetp

repo: DataDog/integrations-core


text:
🛑 Angry is down

In 14e3a0e, Angry (https://angry.data-ensta.fr) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Angry is back up in 88ba35a after 3 hours, 23 minutes.

repo: DataEnsta/upptime


text:
The  _set_sysmeta method writes wrong CID into file

The  _set_sysmeta method writes the CID of the PID itself into the system metadata file. Actually, the CID of the data object  should be written into the file.
So we may modify the method to:
def _set_sysmeta(self, pid, sysmeta, obj_cid):

@doulikecookiedough Fixed this in sha 2e91dfb by adding a new argument for the systemmetadata cid.

Thank you for updating this issue Matt - closing issue as bug has been resolved.

authors: doulikecookiedough mbjones taojing2002

repo: DataONEorg/hashstore


text:
[HW]

Name: Pradeepa Seelam
Email: pradeepa.seelam@gmail.com
Linkedin Profile: https://www.linkedin.com/in/pradeepa-seelam-43947b150/
Attach the homework screenshots below for both step II and step III:

Hi Pradeepa, thank you for your submission. Please include a screenshot of the completed "CRUD" step, step 3 from the repo as well. :)

Sorry, here is the screenshot

Awesome Pradeepa, thank you so much.

Congrats! Here it is: https://api.badgr.io/public/assertions/RbRQIwXmRziC2ha8UANAuA?identity__email=pradeepa.seelam%40gmail.com

authors: HadesArchitect SonicDMG pradeepa45


text:
chore: release main

:robot: I have created a release beep boop
accesskit: 0.8.1
0.8.1 (2023-04-01)
⚠ BREAKING CHANGES

Move thread synchronization into platform adapters; drop parking_lot (#212)
Make Node opaque and optimize it for size (#205)

Features

Add C bindings (#230) (7f7f4c7)

Bug Fixes

Set appropriate representations on all public types that will be exposed via FFI (54e82f6)

Documentation

Fix outdated documentation for TreeUpdate (#182) (dd658c7)

Code Refactoring

Make Node opaque and optimize it for size (#205) (4811152)
Move thread synchronization into platform adapters; drop parking_lot (#212) (5df52e5)

accesskit_c: 0.2.0
0.2.0 (2023-04-01)
Features

Add C bindings (#230) (7f7f4c7)

Bug Fixes

Improve C bindings package directory structure (6942f55)

Dependencies

The following workspace dependencies were updated

dependencies

accesskit bumped from 0.11.0 to 0.8.1
accesskit_windows bumped from 0.14.0 to 0.15.0
accesskit_macos bumped from 0.7.0 to 0.8.0
accesskit_unix bumped from 0.4.0 to 0.5.0

accesskit_consumer: 0.16.0
0.16.0 (2023-04-01)
⚠ BREAKING CHANGES

Force a semver-breaking version bump in downstream crates (#234)
Move thread synchronization into platform adapters; drop parking_lot (#212)
Make Node opaque and optimize it for size (#205)

Features

Automatically get button and link labels from descendants (#184) (ec5c38e)
Basic Unix platform adapter (#198) (1cea32e)
Text support on macOS (#191) (3a35dbe)

Bug Fixes

Force a semver-breaking version bump in downstream crates (#234) (773389b)
Make Node::filtered_parent recursive as it was meant to be (#203) (d2faef5)
More reliable handling of the edge case for wrapped lines (#192) (c626d2c)

Code Refactoring

Make Node opaque and optimize it for size (#205) (4811152)
Move thread synchronization into platform adapters; drop parking_lot (#212) (5df52e5)

Dependencies

The following workspace dependencies were updated

dependencies

accesskit bumped from 0.11.0 to 0.8.1

accesskit_macos: 0.8.0
0.8.0 (2023-04-01)
⚠ BREAKING CHANGES

Force a semver-breaking version bump in downstream crates (#234)
Move thread synchronization into platform adapters; drop parking_lot (#212)
Make Node opaque and optimize it for size (#205)
Move lazy initialization from the core platform adapter to the caller (#179)

Features

Live regions on macOS (#196) (47d8d9f)
Text support on macOS (#191) (3a35dbe)

Bug Fixes

Correctly apply the DPI scale factor to coordinates (#185) (d263938)
Don't expose the window title in our root element on macOS (#187) (9739b74)
Expose static text as the value rather than the title on macOS (#186) (e3720c8)
Expose which accessibility selectors are actually allowed for a particular node (#181) (c4cbb23)
Fix macOS leaks (e8537fc)
Fix problems related to the root node (#231) (7228494)
Force a semver-breaking version bump in downstream crates (#234) (773389b)
Handle views with flipped coordinates (#174) (d14484c)
Make VoiceOver move through nodes in logical order (#176) (f060be4)
More reliable handling of the edge case for wrapped lines (#192) (c626d2c)
Pin objc2 dependency to 0.3.0-beta.3 (#201) (0adfed1)
Re-export types from objc2 (#172) (1ac67ad)

Code Refactoring

Make Node opaque and optimize it for size (#205) (4811152)
Move lazy initialization from the core platform adapter to the caller (#179) (f35c941)
Move thread synchronization into platform adapters; drop parking_lot (#212) (5df52e5)

Dependencies

The following workspace dependencies were updated

dependencies

accesskit bumped from 0.11.0 to 0.8.1
accesskit_consumer bumped from 0.15.0 to 0.16.0

accesskit_unix: 0.5.0
0.5.0 (2023-04-01)
⚠ BREAKING CHANGES

Force a semver-breaking version bump in downstream crates (#234)
Move thread synchronization into platform adapters; drop parking_lot (#212)
Make Node opaque and optimize it for size (#205)

Features

Basic Unix platform adapter (#198) (1cea32e)

Bug Fixes

Force a semver-breaking version bump in downstream crates (#234) (773389b)
Update atspi dependency (#217) (93f2dc9)

Code Refactoring

Make Node opaque and optimize it for size (#205) (4811152)
Move thread synchronization into platform adapters; drop parking_lot (#212) (5df52e5)

Dependencies

The following workspace dependencies were updated

dependencies

accesskit bumped from 0.11.0 to 0.8.1
accesskit_consumer bumped from 0.15.0 to 0.16.0

accesskit_windows: 0.15.0
0.15.0 (2023-04-01)
⚠ BREAKING CHANGES

Force a semver-breaking version bump in downstream crates (#234)
Move thread synchronization into platform adapters; drop parking_lot (#212)
Make Node opaque and optimize it for size (#205)
Update winit to 0.28 (#207)
Move lazy initialization from the core platform adapter to the caller (#179)

Bug Fixes

Correct broken UIA method implementation that was incompatible with Windows 11 ATs (#193) (3c527c7)
Fix Windows 32-bit build errors (#223) (41f28b6)
Force a semver-breaking version bump in downstream crates (#234) (773389b)
More reliable handling of the edge case for wrapped lines (#192) (c626d2c)
Provide fallback property implementations for the window root (#194) (f3d30b9)
Update windows-rs to 0.44 (#220) (a6b0a12)

Miscellaneous Chores

Update winit to 0.28 (#207) (3ff0cf5)

Code Refactoring

Make Node opaque and optimize it for size (#205) (4811152)
Move lazy initialization from the core platform adapter to the caller (#179) (f35c941)
Move thread synchronization into platform adapters; drop parking_lot (#212) (5df52e5)

Dependencies

The following workspace dependencies were updated

dependencies

accesskit bumped from 0.11.0 to 0.8.1
accesskit_consumer bumped from 0.15.0 to 0.16.0

accesskit_winit: 0.14.0
0.14.0 (2023-04-01)
⚠ BREAKING CHANGES

Force a semver-breaking version bump in downstream crates (#234)
Move thread synchronization into platform adapters; drop parking_lot (#212)
Make Node opaque and optimize it for size (#205)
Update winit to 0.28 (#207)
Move lazy initialization from the core platform adapter to the caller (#179)

Features

Basic Unix platform adapter (#198) (1cea32e)
Feature-gate the Unix adapter in accesskit_winit (#214) (be95807)

Bug Fixes

Don't force winit's X11 and Wayland features to be enabled (#209) (a3ed357)
Force a semver-breaking version bump in downstream crates (#234) (773389b)
Reduce the winit version requirement to match egui (#170) (1d27482)

Miscellaneous Chores

Update winit to 0.28 (#207) (3ff0cf5)

Code Refactoring

Make Node opaque and optimize it for size (#205) (4811152)
Move lazy initialization from the core platform adapter to the caller (#179) (f35c941)
Move thread synchronization into platform adapters; drop parking_lot (#212) (5df52e5)

Dependencies

The following workspace dependencies were updated

dependencies

accesskit bumped from 0.11.0 to 0.8.1
accesskit_windows bumped from 0.14.0 to 0.15.0
accesskit_macos bumped from 0.7.0 to 0.8.0
accesskit_unix bumped from 0.4.0 to 0.5.0

This PR was generated with Release Please. See documentation.

:robot: Release is at https://github.com/DataTriny/accesskit/releases/tag/accesskit-v0.8.1 :sunflower:

:robot: Release is at https://github.com/DataTriny/accesskit/releases/tag/accesskit_consumer-v0.16.0 :sunflower:

:robot: Release is at https://github.com/DataTriny/accesskit/releases/tag/accesskit_macos-v0.8.0 :sunflower:

:robot: Release is at https://github.com/DataTriny/accesskit/releases/tag/accesskit_unix-v0.5.0 :sunflower:

:robot: Release is at https://github.com/DataTriny/accesskit/releases/tag/accesskit_windows-v0.15.0 :sunflower:

:robot: Release is at https://github.com/DataTriny/accesskit/releases/tag/accesskit_winit-v0.14.0 :sunflower:

:robot: Release is at https://github.com/DataTriny/accesskit/releases/tag/accesskit_c-v0.2.0 :sunflower:

repo: DataTriny/accesskit


text:
streaming

Add suppport for Streaming
Fixes #22

Coverage increased (+0.09%) to 95.823% when pulling a5deef2e62eb8f11e12a7e28c5669708608d9a3b on streaming into 9adfa9ae008707d4473b3c2c306e9acfef3c89b4 on master.

authors: DatenMetzgerX coveralls


text:
[feature][client app]: email preview with email grouping

I would love to organize my emails based on folders then it render the tree on the left side bar.
Folder emails/ = "All Emails"
Folder emails/Company/newsletter.vue

All Emails

Company

newsletter

[...reset_of_emails]

This could be useful as it helps organize it and doesn't contain everything in on subfolder within the view.

hi, yeah good idea, we'll work on adding it ot he nuxt client, thanks


text:
🛑 (Server) World Evolved RU is down

In 5b4fe5e, (Server) World Evolved RU (http://92.63.111.195:8680/soapbox-race-core/Engine.svc/GetServerInformation) was down:

HTTP code: 0
Response time: 0 ms

Resolved: (Server) World Evolved RU is back up in 765de18.

repo: DavidCarbon-SBRW/Status


text:
Possible bug: failed to find or open the following file: (ffopen) toto.in.mos[1]

This is happening during emchain runs, and at another point in the stderr output there is 'sh: lcurve: command not found'
I suspect they might be connected.
lcurve is a part of xronos section of HEASoft, which I may not have selected for my laptop install of HEASoft. This could help me learn which parts of HEASoft are actually required for SAS to work in its entirety.
My ICER install of HEASoft is the whole thing, so I can test running emchain on there to see if the same problem pops up.

This error does not occur when running on ICER, which seems to confirm my suspicions

I'm going to close this now, as I added a simple check for l_curve and things will fail with a useful error now.


text:
PSF corrected images don't seem to be being read back in

Just was using Castor in a PointSource class to make a demo plot, and I have to re-run PSF correction for the ratemap to be available

It doesn't appear to be that the PSF corrected ratemaps just aren't being generated either, the images themselves don't seem to be loaded in

I think  was a mistake on my part actually, it was working fine


text:
Esquelete e estructuración do xogo

Estructura de clases
Crear e organizar as distintas clases que se utilizarán no proxecto.
Exemplo: GameManager, InxtrumentoX, InstrumentoY...

Me pongo con esto ahora, lo subiré en la rama feature/EstructuraBasica

Me llevo aprox 25-30 minutos el plantear y hacer la estructura.

authors: DavidVidaMi Gontrojon

repo: DavidVidaMi/Sadhana


text:
NativeChain optionally require MetaChain Execution Layer?

What would you like to be added:
While the current proposed specification (earmark for documentation in #8) requires MetaChain to run alongside NativeChain 100% of the time. This issue proposes the possibility of running NativeChain without connectivity to MetaChain for sustaining existing node operator operations.
While for miners, it is required (or preferably required) for them to have both chains up since they need introspection to the internal state of both chains for trustless bridging. A case can be made for a miner that doesn't care about mining on MetaChain (due to the cost of maintaining both chains and ignoring EVM chain since rewards come from Native chain only) and modify their node such that they always mine an empty block/template for EVM. (Due to trustless bridging, they can implement "mindless bridging" where the modified node doesn't process trustless bridging and take the amount as it is without during state verification.)
That being said, tokenomics could easily be adjusted for "forced" participation on MetaChain. Economically incentivizing miners to run EVM nodes when a percentage of their rewards can only be claimed on the EVM side.
While for the connectivity providers (e.g. think ocean or infura) that don't care about EVM DFI and only process UTXO DFI. They "technically" don't need to be aware of the EVM state or have no concern over the "internal state" of Meta Chain.
Why is this needed:

It won't force immediate deprecation/upgrade on node operators as there are increased complexity and changes to operation when running 2 nodes.
Allow non miners to run Native Chain without Meta Chain.

Related comment from https://github.com/DeFiCh/metachain/issues/106#issuecomment-1266390720

Part of it. With DMC embedded, the "server profile" and server maintenance's operational flow must be changed if we force defid to be prepackaged. Several operators such as exchanges, individuals, and node operators would have to reconfigure their setup to fit the runtime requirements running defid. It's not simply a plug-and-play since these must be pre-communicated, tested, and operationalized.

The fundamental way to think of this, is that EVM is just a part of defichain consensus (whether it's a separate chain or not is an internal detail of DeFiChain consensus). There is no reason for a operators to think of them as 2 separate chains. The data will be all inclusively managed by defid.
This requirement will unnecessarily complicates things further to allow things to be run separately, exposing implementation details into the user world, since now there needs to logic to ignore EVM consensus, which now creates a partial validation case, which defeats the purpose of validation in the first place. There shouldn't be any need or separation externally when everything is just a part of the defid.

In summary:

Operators shouldn't be thinking of these as 2 different chain. It's still just DeFiChain. That's it.
EVM layer in it's current form utilizing substrate libraries to implement it as isolated chain is an internal implementation detail. This could potentially change at any point (if substrate doesn't fit the needs or a different EVM impl is better suited at a later point).
Validation should be either all or nothing. Creating a partial validation condition is a rabbit hole that I'd wouldn't start.
Operators of masternodes will have to no additional difference - makes things easier to reason with, simplifies developer experience, testing, all of it. Running both together shouldn't matter from a computational perspective when it's all managed by the same process and crash boundaries. The only additional cost is data. That's unavoidable. I'd accept that as a technical requirement and work on larger optimizations for data overall, instead of splitting these into 2 just for the sake of data.

Adding more details:

It won't force immediate deprecation/upgrade on node operators as there are increased complexity and changes to operation when running 2 nodes.

There will be no increased complexity on any level with the current mechanism of integration worked on defid, and running 2 nodes is not a requirement that we'll pass on to users at all. It's a testing only case / advanced case to separate and run for those who choose to, who are expected to understand the complexity if they choose to. By default is, it's fully integrated and managed by defid.

Allow non miners to run Native Chain without Meta Chain.

This defeats the purpose of validation. As there is no way to validate the full block.

@prasannavl generally, I agree with your concerns. The insights are great.
The only doubt/question I have is the operational workflow of running the new "defid" and communicating that with our partners is quite a challenge. The end-goal north-star would be scraping this issue, but till we have a sound resolution to address the operational workflow. I don't have a good answer for it yet.
@wafflespeanut, what's your take?

Related comment from #106 (comment)

Part of it. With DMC embedded, the "server profile" and server maintenance's operational flow must be changed if we force defid to be prepackaged. Several operators such as exchanges, individuals, and node operators would have to reconfigure their setup to fit the runtime requirements running defid. It's not simply a plug-and-play since these must be pre-communicated, tested, and operationalized.

The only doubt/question I have is the operational workflow of running the new "defid" and communicating that with our partners is quite a challenge. The end-goal north-star would be scraping this issue, but till we have a sound resolution to address the operational workflow. I don't have a good answer for it yet.

As far as I can see, the only change from an external perspective will be a bigger size for defid executable. Unless we concretely know that running both of them in parallel is gonna hurt the performance of either, I'd say we can go ahead with our current plan of prepackaging. If it causes problems when we try it out, then we always have the RPC work to fallback.

The only doubt/question I have is the operational workflow of running the new "defid" and communicating that with our partners is quite a challenge. The end-goal north-star would be scraping this issue, but till we have a sound resolution to address the operational workflow. I don't have a good answer for it yet.

As far as I can see, the only change from an external perspective will be a bigger size for defid executable. Unless we concretely know that running both of them in parallel is gonna hurt the performance of either, I'd say we can go ahead with our current plan of prepackaging. If it causes problems when we try it out, then we always have the RPC work to fallback.

Yup, sounds good. I was doing back of the mind calculation the other day; it's insignificant and doesn't warrant a change of operations, with at most an increase of 1-2GB RAM and 1 CPU at most. Storage increase will growth will be slow and linear and won't result in drastic operational changes either.

Will keep this open for now since this thread wasn't triage/accepted to be worked on either, acting more as an RFC.

authors: fuxingloh prasannavl wafflespeanut

repo: DeFiCh/metachain


text:
[lib/panmaster] Add panmaster tests

This is a work in progress. @ncasaril Can you tell me is there any way to add more nodes? I can initiate only one node, and I don't know if im doing this correctly?

@ncasaril Ready for review.

@Guilhem23 Are we allowed to merge these tests to master yet?

Yes Niklas you can proceed.

authors: Guilhem23 ncasaril szymon-czapracki

repo: Decawave/uwb-core


text:
change spring/damping calculation, added centre of mass option

The spring/damper value will now be calculatet based on absolut values, means when you change the spring length, the spring/damp stiffnes will be the same.
when u work with normalized values, the spring/damp stiffness will change when you change the spring length
added a node "CentreOfMass".
it will change the com, based on the nodes position, so you can change the COM without changing the collider size/pos. could manipulate it to represent the fuel consume

I hope that's how you do it.

Hey! Thanks for the pull request. For the most part this seems fine, but ever since Godot 4 it has been possible to set center of gravity of a RigidBody from the inspector, so there is no need for a node to set it. One just needs to set the center_of_mass_mode to custom and you can then specify a Vector3 that will be used as center of mass.  I'll also leave few comments on naming conventions for variables.

ok, i did nor know that with the com option... lol.
as far as i know i can change my pull request by change the sugested inputs from you and pull again?
i never done this, where can i see the comments on the naming conventions?

as far as i know i can change my pull request by change the sugested inputs from you and pull again?
Yeah thats how i imagine it works, i am actually quite new to collaborating on github myself. I have some experience with gitlab and thats how it was done there.

The comments should be visible somewhere in this thread and / or in the files changed tab. You were so fast to reply i probably had not written them yet lol

The dot net property is fine, i can still open the project with non .Net version of Godot.
Weird that the comments are not showing up. Not even in this thread? I see a section saying "Dechode started a review" and that's where the comments are. I left some comments again in the newest change about typos in comments in code.
Other than that it looks good now, I will try out the changes soon and then merge this after those few typos are corrected.

I can see your comment about variable name maybe being too long. I try to request a review from myself again, maybe that has something to do with my comments not showing up.

i see the review request, but thats for you, i cannot open it

now i can see it all!
well, its weird, my project works just fine,
i think its because i first added a node (com) which mix up all the indexes of the scene.
i will make a complete new pull request, i think it will be better.
can you just reject the pull? i will then re synk the fork and redo the pull, since there are now a lot less changes.
or ho can i undo the pull?

authors: Dechode michurebmann

repo: Dechode/Godot-Advanced-Vehicle


text:
TypeError: expected string or bytes-like object

💡 Your Question
When I tried to train model on a custom dataset with pretained weights I came across an error:
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
[<ipython-input-36-63d1d2b55e46>](https://8n6lgpl7uz-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20240205-060127_RC00_604283622#) in <cell line: 1>()
----> 1 trainer.train(model = model_small,training_params = train_params,train_loader = train_data,valid_loader = val_data)

6 frames
[/usr/lib/python3.10/re.py](https://8n6lgpl7uz-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20240205-060127_RC00_604283622#) in sub(pattern, repl, string, count, flags)
    207     a callable, it's passed the Match object and must return
    208     a replacement string to be used."""
--> 209     return _compile(pattern, flags).sub(repl, string, count)
    210
    211 def subn(pattern, repl, string, count=0, flags=0):

TypeError: expected string or bytes-like object

In my previous runs with practically the same configuration of training parameters everything was ok. Couldn't find out where is the problem:(
Just in case I will provide a block of code from my Collab Notebook:
dataset_params = {
    'data_dir':ROOT_DIR,
    'train_images_dir':train_imgs_dir,
    'train_labels_dir':train_labels_dir,
    'val_images_dir':val_imgs_dir,
    'val_labels_dir':val_labels_dir,
    'test_images_dir':test_imgs_dir,
    'test_labels_dir':test_labels_dir,
    'classes':classes
}

train_data = coco_detection_yolo_format_train(
    dataset_params={
        'data_dir': dataset_params['data_dir'],
        'images_dir': dataset_params['train_images_dir'],
        'labels_dir': dataset_params['train_labels_dir'],
        'classes': dataset_params['classes']
    },
    dataloader_params={
        'batch_size':BATCH_SIZE,
        'num_workers':WORKERS
    }
)

val_data = coco_detection_yolo_format_val(
    dataset_params={
        'data_dir': dataset_params['data_dir'],
        'images_dir': dataset_params['val_images_dir'],
        'labels_dir': dataset_params['val_labels_dir'],
        'classes': dataset_params['classes']
    },
    dataloader_params={
        'batch_size':BATCH_SIZE,
        'num_workers':WORKERS
    }
)

test_data = coco_detection_yolo_format_val(
    dataset_params={
        'data_dir': dataset_params['data_dir'],
        'images_dir': dataset_params['test_images_dir'],
        'labels_dir': dataset_params['test_labels_dir'],
        'classes': dataset_params['classes']
    },
    dataloader_params={
        'batch_size': BATCH_SIZE,
        'num_workers': WORKERS
    }
)

train_params = {
    'silent_mode': False,
    "average_best_models":True,
    "warmup_mode": "linear_epoch_step",
    "warmup_initial_lr": 1e-6,
    "lr_warmup_epochs": 3,
    "initial_lr": 5e-4,
    "lr_mode": "cosine",
    "cosine_final_lr_ratio": 0.1,
    "optimizer": "SGD",
    "optimizer_params": {"weight_decay": 0.0005, "momentum": 0.937},
    "zero_weight_decay_on_bias_and_bn": True,
    "ema": False,
    "max_epochs": EPOCHS,
    "mixed_precision": True,
    "loss": PPYoloELoss(
        use_static_assigner=False,
        num_classes=len(dataset_params['classes']),
        reg_max=16,
    ),
    "seed": 42,
    "train_metrics_list": [
        DetectionMetrics_050(
            score_thres=0.1,
            top_k_predictions=300,
            num_cls=len(dataset_params['classes']),
            normalize_targets=True,
            post_prediction_callback=PPYoloEPostPredictionCallback(
                score_threshold=0.01,
                nms_top_k=1000,
                max_predictions=300,
                nms_threshold=0.7
            )
        ),
        DetectionMetrics_050_095(
            score_thres=0.1,
            top_k_predictions=300,
            num_cls=len(dataset_params['classes']),
            normalize_targets=True,
            post_prediction_callback=PPYoloEPostPredictionCallback(
                score_threshold=0.01,
                nms_top_k=1000,
                max_predictions=300,
                nms_threshold=0.7
            )
        )
    ],

    "valid_metrics_list": [
        DetectionMetrics_050(
            score_thres=0.1,
            top_k_predictions=300,
            num_cls=len(dataset_params['classes']),
            normalize_targets=True,
            post_prediction_callback=PPYoloEPostPredictionCallback(
                score_threshold=0.01,
                nms_top_k=1000,
                max_predictions=300,
                nms_threshold=0.7
            )
        ),
        DetectionMetrics_050_095(
            score_thres=0.1,
            top_k_predictions=300,
            num_cls=len(dataset_params['classes']),
            normalize_targets=True,
            post_prediction_callback=PPYoloEPostPredictionCallback(
                score_threshold=0.01,
                nms_top_k=1000,
                max_predictions=300,
                nms_threshold=0.7
            )
        )
    ],
    "metric_to_watch": ['mAP@0.50:0.95', 'mAP@0.50'],

    #define weights and biases logging
    "sg_logger": 'wandb_sg_logger',
    "sg_logger_params":
    {
        "project_name": "Yolo-NAS",
        "save_checkpoints_remote": True,
        "save_tensorboard_remote":True,
        'save_logs_remote':True,
        'entity':'ml_team_mskv'

    }
}

model_small = models.get('yolo_nas_s',
                   num_classes=len(dataset_params['classes']),
                   pretrained_weights="coco"
                   )

trainer.train(model = model_small,training_params = train_params,train_loader = train_data,valid_loader = val_data)

Versions
Collecting environment information...
PyTorch version: 2.1.0+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A
OS: Ubuntu 22.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: 14.0.0-1ubuntu1.1
CMake version: version 3.27.9
Libc version: glibc-2.35
Python version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-6.1.58+-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.2.140
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: Tesla T4
Nvidia driver version: 535.104.05
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.6
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
CPU:
Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Address sizes:                      46 bits physical, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             2
On-line CPU(s) list:                0,1
Vendor ID:                          GenuineIntel
Model name:                         Intel(R) Xeon(R) CPU @ 2.00GHz
CPU family:                         6
Model:                              85
Thread(s) per core:                 2
Core(s) per socket:                 1
Socket(s):                          1
Stepping:                           3
BogoMIPS:                           4000.37
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves arat md_clear arch_capabilities
Hypervisor vendor:                  KVM
Virtualization type:                full
L1d cache:                          32 KiB (1 instance)
L1i cache:                          32 KiB (1 instance)
L2 cache:                           1 MiB (1 instance)
L3 cache:                           38.5 MiB (1 instance)
NUMA node(s):                       1
NUMA node0 CPU(s):                  0,1
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit:        Not affected
Vulnerability L1tf:                 Mitigation; PTE Inversion
Vulnerability Mds:                  Vulnerable; SMT Host state unknown
Vulnerability Meltdown:             Vulnerable
Vulnerability Mmio stale data:      Vulnerable
Vulnerability Retbleed:             Vulnerable
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Vulnerable
Vulnerability Spectre v1:           Vulnerable: __user pointer sanitization and usercopy barriers only; no swapgs barriers
Vulnerability Spectre v2:           Vulnerable, IBPB: disabled, STIBP: disabled, PBRSB-eIBRS: Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Vulnerable
Versions of relevant libraries:
[pip3] numpy==1.23.0
[pip3] onnx==1.13.0
[pip3] onnx-simplifier==0.4.35
[pip3] onnxruntime==1.13.1
[pip3] torch==2.1.0+cu121
[pip3] torchaudio==2.1.0+cu121
[pip3] torchdata==0.7.0
[pip3] torchmetrics==0.8.0
[pip3] torchsummary==1.5.1
[pip3] torchtext==0.16.0
[pip3] torchvision==0.16.0+cu121
[pip3] triton==2.1.0

Please provide a full stacktrace, it's impossible to understand what part of the input arguments causing this crash

repo: Deci-AI/super-gradients


text:
How to apply transform?

Running a T1 image through fastsurfer with -- or without -- the --surfreg parameter doesn't seem to do anything - there are no spatially normalized images. I see transforms in the xfm directory, but am uncertain how to apply that. As well, the transforms are there even without the --surfreg parameter! I got no error messages on output.

What transform do I use? Presumably the talairach.xfm?
How do I apply this to an output image?

Thanks, James

Hi James, FreeSurfer and fastsurfer provide results in subject space. You get segmentations and statistics for all structures. Also you can do a cortical surface group analysis with spatial correspondence on the surfaces (eg point wise thickness analysis). All this is described on the FreeSurfer wiki and tutorials and mailing list.

Thank you. I don't really see a whole lot about analysis however, but I think my problem is elsewhere. I'm going to close this one, and open another.

repo: Deep-MI/FastSurfer


text:
deeplink开发不能调用我写的算子

我在开发deleplink的时候遇到了一个问题一直不能解决，
我在/home/deeplink/deeplink.framework/dipu/third_party/DIOPI/impl里面编译好了共享库libdiopi_impl.so，so里面只实现了这么一段代码
#include <diopi/functions.h>
#include <math.h>
#include
#include "../musa_pytorch.h"
// #include "../common/common.hpp"
namespace impl {
namespace musa {
static const char* name = "MUSADevice";
DIOPI_RT_API const char* diopiGetVendorName() { return name; }
DIOPI_API diopiError_t diopiAdd(diopiContextHandle_t ctx, diopiTensorHandle_t out, diopiConstTensorHandle_t input, diopiConstTensorHandle_t other,
const diopiScalar_t* alpha) {
std::cout << "==================diopiAdd===========================\n";
return diopiSuccess;
}
编译deeplink之后在打开python之后，不能调用我写的算子，说我回退到cpu端了，如下
import torch,torch_dipu,os
dipu device will show as cuda device. if it's not expected behavior, please set env DIPU_PYTHON_DEVICE_AS_CUDA=false
Wed Jul 17 16:01:46 2024 dipu | git hash:fdc1b4c1-dirty
::diopiFill 01 is not yet implemented, fill_.Scalar will be fallback to cpu
::diopiAddScalar 01 is not yet implemented, add.Scalar_out will be fallback to cpu
::diopiAddInpScalar 01 is not yet implemented, add_.Scalar will be fallback to cpu
::diopiAddInp 01 is not yet implemented, add_.Tensor will be fallback to cpu
::diopiAdd 01 is not yet implemented, add.out will be fallback to cpu
::diopiAdd 01 is not yet implemented, add.Tensor will be fallback to cpu
这怎么解决？

先看下 torch_dipu.so 是否 link了  diopi_impl.so 的动态库 (最新版 dipu 能保证一定 link, 老的版本有一段时间改坏了, 取决于模板编译选项). 然后看下 diopi_impl.so 里  diopiAdd 是否正确的导出了

另外 dipu 里是否已经实现了 MUSA 相关的 接口.

如果你的 diopi 和 dipu 是分别编译的, 编译dipu时 请确定使用  -DWITH_DIOPI_LIBRARY  指定 依赖的 diopi

你好，我在代码里加了extern "C" 就可以找到我写的算子了，如下，我是看有的厂商是这么做的，我也就这么写了，但是我不知道这是什么原因，哈哈，您能跟我说下是为什么吗？
namespace impl {
namespace musa {
extern "C" {
static const char* name = "MUSADevice";
DIOPI_RT_API const char* diopiGetVendorName() { return name; }
DIOPI_API diopiError_t diopiAdd(diopiContextHandle_t ctx, diopiTensorHandle_t out, diopiConstTensorHandle_t input, diopiConstTensorHandle_t other,
const diopiScalar_t* alpha) {
std::cout << "==================hello,diopiAdd===========================\n";
return diopiSuccess;
}
}   //extern C
}  // namespace musa
}  // namespace impl

我可能了解了，可能因为c++函数重载的问题，不加extern "C"，C++编译器会按照C++的方式进行名称修饰
，这样因为c++的函数重载的原因会出现问题，加了extern C 函数名在链接时保持原样，这样链接器在链接阶段就不会报出未解析的外部符号错误，哈哈是这样子吗？

diopi 对外导出的符号, 都是要加 extern C 的.     但是目前 diopi 项目里的 代码大多是 有一个 adapter  封装, adapter 才是真正用来导出的, 是 c api,     而实际的实现在内部, 是 c++的

authors: fandaoyi jianlonghaha