Godot 4.0 Crash if i use the dedicated gpu on a laptop

Godot version
v4.0.dev.20211210.official.21b81998b
System information
Winwos 10, Ryzen 9 5900hx, 32gb ram, 1tb m2 3.0, 3080 max-q 115w
Issue description
If i connect an external monitor or if i use the 3080 on my laptop, godot doesn't start and crash with this error: "vkEnumeratePhysicalDevices reported zero accessible devices.".
The only way to use godot 4.0 on my laptop is when i use it only with the internal monitor and with the integrated gpu (vega).
Steps to reproduce
Simply start godot 4.0 on a notebook without using the integrated gpu.
Minimal reproduction project
No response

Related to https://github.com/godotengine/godot/issues/54962. This may be fixed by https://github.com/godotengine/godot/pull/55020 – could you build https://github.com/bruvzg/godot/tree/vlk_device_surface_check from source to test it? See compiling instructions here: https://docs.godotengine.org/en/latest/development/compiling/index.html

Related to #54962. This may be fixed by #55020 – could you build https://github.com/bruvzg/godot/tree/vlk_device_surface_check from source to test it? See compiling instructions here: https://docs.godotengine.org/en/latest/development/compiling/index.html

sry now i have only the office pc and i can't install too many things on it ):

Related to #54962. This may be fixed by #55020 – could you build https://github.com/bruvzg/godot/tree/vlk_device_surface_check from source to test it? See compiling instructions here: https://docs.godotengine.org/en/latest/development/compiling/index.html

In any

Related to #54962. This may be fixed by #55020 – could you build https://github.com/bruvzg/godot/tree/vlk_device_surface_check from source to test it? See compiling instructions here: https://docs.godotengine.org/en/latest/development/compiling/index.html

sry at this moment, i have only the office pc and i can't install too many things on it ):

in any case i will try every new godot 4.0 version i will found on this link: https://downloads.tuxfamily.org/godotengine/testing/4.0/ and if sometime the bug will fix i will close and update this issue

I'm having the same issue, but it doesn't work on the laptop's internal monitor. I don't know how to set what GPU it should use, but I can try to tinker with that if it helps.
It worked yesterday fine. Looks like there were some automatic updates today, probably has something to do with it?

Godot version v4.0.dev.20220105.official.8f6cba3a4
Windows 10, AMD Ryzen 7 4800H with Radeon Graphics, 16,0 GB (15,4 GB usable)

Update: Building from source, or the latest build, Godot_v4.0-dev.20220118_win64, I get this:

I can't find any GPU setting that makes it work. I don't know what I'm doing with this, but these are the options I've tinkered with, I've tried everything...

Also, if it's relevant, when I go back to earlier 4.0 versions (e.g. from December) I get the same result.

...and another update:
This workaround worked for me: https://github.com/godotengine/godot/issues/45104#issuecomment-857516908

Are integrated GPU drivers up to date? It might be related to this driver bug: https://github.com/GPUOpen-Drivers/AMDVLK/issues/195, https://github.com/KhronosGroup/Vulkan-Loader/issues/552

I have try to update all driver, i always set the dedicated gpu to be the use for godot, and i always have the same error. i try all the alpha version. i will continue to try all new versions and if the problem will be solved i will instantly update this tread.

@Mikadini Try switching the graphics adapter in the Windows control panel, not the NVIDIA Control Panel. Apparently, the NVIDIA Control Panel's graphics adapter switch is ignored on recent Windows 10 versions and Windows 11.

This looks very similar to issue #57708.

Looking at OP's hardware configuration, this is surely a duplicate of https://github.com/godotengine/godot/issues/57708.


Created rails react

Set up a "Hello world" project as one app with Webpack
in this project, I implemented a connection between a Ruby on Rails back-end and React front-end.
Highlight :recycle:

Created a new Rails app called 'hello-rails-react'.
Used the commend rails new -j webpack my_new_rails_app as described in the previous lesson's tutorial.
Verify that the jsbundling-rails gem is added to your Gemfile.
Initialize your project with Git.
Install needed node dependencies as described in the previous lesson's tutorial.
Create a babel.config.js in the root folder of your project as described in the previous lesson's tutorial.
Update webpack.config.js to include the babel loader as described in the previous lesson's tutorial.
Make sure that your project has a Postgres database set up.
Create a table for storing your messages and create 5 different greetings.
Create an API endpoint that selects a random greeting from your table (you will need a controller with an action and Rails route).
Create a static view that will be the root of your app.
Create the App component with react-router and render it in your static view.
Create the Greeting component that will display a greeting. Set it up as a route in your App component.
Create a store, an action, and a reducer that will connect to your API endpoint to get the random greeting.
Display the random greeting in your Greeting component.

Thank you for approving my project :pray:


fix: add missing style-to-object in tools/challenge-md-parser/package…

Fix error when I run FreeCodeCamp locally
module.js:549
    throw err;
    ^
Error: Cannot find module 'style-to-object'
    at Function.Module._resolveFilename (module.js:547:15)
    at Function.Module._load (module.js:474:25)
    at Module.require (module.js:596:17)
    at require (internal/module.js:11:18)
    at Object.<anonymous> (/home/gossard/Dev/freeCodeCamp/tools/challenge-md-parser/node_modules/hast-to-hyperscript/index.js:8:13)
    at Module._compile (module.js:652:30)
    at Object.Module._extensions..js (module.js:663:10)
    at Module.load (module.js:565:32)
    at tryModuleLoad (module.js:505:12)
    at Function.Module._load (module.js:497:3)

[X] I have read freeCodeCamp's contribution guidelines.
[X] My pull request has a descriptive title (not a vague title like Update index.md)
[X] My pull request targets the master branch of freeCodeCamp.
[ ] None of my changes are plagiarized from another source without proper attribution.
[ ] My article does not contain shortened URLs or affiliate links.

Hi @CodingSolo, can you please give me steps to reproduce?

Hi @Bouncey ,
I run it under ubuntu
$npm install
$npm run bootstrap

I get the error after
><EMAIL_ADDRESS>prepare /home/gossard/Dev/freeCodeCamp/curriculum
> npm run build

><EMAIL_ADDRESS>build /home/gossard/Dev/freeCodeCamp/curriculum
> gulp build

module.js:549
    throw err;

Error: Cannot find module 'style-to-object'
at Object. (/home/gossard/Dev/freeCodeCamp/tools/challenge-md-parser/node_modules/hast-to-hyperscript/index.js:8:13)
Is the problem that npm install is not installing the dependencies of other modules, in this case it isn't installing the dependencies for hast-to-hyperscript
https://github.com/freeCodeCamp/freeCodeCamp/blob/master/docs/how-to-setup-freecodecamp-locally.md#troubleshooting
I am not sure what causes this problem, but shouldn't removing the node_modules folder and attempting npm install again may fix the issue?
Or is their another approach that should occur?

@nathanhannig you are right delete node_module and rerun npm install solve the problem.
@Bouncey  we can close it. it is useless.

Thanks for taking the time to report the issue and raising the PR. Closing as requested.


NGINX or Apache Installation Instructions?

Can anyone shed some light on the steps it takes to get this working with NGINX or Apache on Ubuntu 18.04?
After spending 4-days beating my head against a wall trying to get this to work in CentOS 8, CentOS 7, Debian, and now Ubuntu 18.04 - I was finally able to take bits and pieces of instructions from a handful of different documents I was to get everything working with the Flask server on port 9191.
At this point I have PowerDNS installed and working and have the server PowerDNS-Admin.service working too - but for the life of me can't get it to work through NGINX or Apache.
If someone can help - I would gladly share/document the steps I have taken so far to get things working so others can use it.
Thanks in advance...
-Adam
(to clarify - following the instructions listed on this site and the Wiki don't work...)

I've managed to get it working with nginx.  There's a few steps.

In the wiki is a good nginx config file you can use as a starting place
If you have selinux you'll need to disable it or allow connecting to external sockets
Create a user and group to own the process (I used pdnsa:pdnsa)
Start powerdns-admin using systemd and gunicorn, so that it binds to a unix socket.  This is the proxy socket mentioned in the nginx config.
Make sure to run systemctl daemon-reload and systemd-tmpfiles --create after setting up the config

This setup appears to work for us.  Note that I've installed under /opt/powerdns-admin , and that this config is for release 0.2.1 with  the config in powerdnsadmin/config.py
/etc/nginx/conf.d/powerdns-admin.conf
server {
  listen *:80;
  server_name         _;

  index                     index.html index.htm index.php;
  root                      /opt/powerdns-admin;
  access_log                /var/log/nginx/powerdns-admin.local.access.log combined;
  error_log                 /var/log/nginx/powerdns-admin.local.error.log;

  client_max_body_size              10m;
  client_body_buffer_size           128k;
  proxy_redirect                    off;
  proxy_connect_timeout             90;
  proxy_send_timeout                90;
  proxy_read_timeout                90;
  proxy_buffers                     32 4k;
  proxy_buffer_size                 8k;
  proxy_set_header                  Host $host;
  proxy_set_header                  X-Real-IP $remote_addr;
  proxy_set_header                  X-Forwarded-For $proxy_add_x_forwarded_for;
  proxy_headers_hash_bucket_size    64;

  location ~ ^/static/  {
    include  /etc/nginx/mime.types;
    root /opt/powerdns-admin/powerdnsadmin;

    location ~*  \.(jpg|jpeg|png|gif)$ {
      expires 365d;
    }

    location ~* ^.+.(css|js)$ {
      expires 7d;
    }
  }

  location / {
    proxy_pass            http://unix:/run/powerdns-admin/socket;
    proxy_read_timeout    120;
    proxy_connect_timeout 120;
    proxy_redirect        off;
  }

}

/etc/systemd/system/powerdns-admin.service
[Unit]
Description=PowerDNS web administration service
Requires=powerdns-admin.socket
Wants=network.target
After=network.target mysqld.service postgresql.service slapd.service mariadb.service

[Service]
PIDFile=/run/powerdns-admin/pid
User=pdnsa
Group=pdnsa
WorkingDirectory=/opt/powerdns-admin
ExecStart=/usr/bin/gunicorn-3.6 --workers 4 --log-level info --pid /run/powerdns-admin/pid --bind unix:/run/powerdns-admin/socket "powerdnsadmin:create_app(config='config.py')"
ExecReload=/bin/kill -s HUP $MAINPID
ExecStop=/bin/kill -s TERM $MAINPID
PrivateTmp=true
Restart=on-failure
RestartSec=10
StartLimitInterval=0

[Install]
WantedBy=multi-user.target

powerdns-admin.socket
[Unit]
Description=PowerDNS-Admin socket

[Socket]
ListenStream=/run/powerdns-admin/socket

[Install]
WantedBy=sockets.target

/etc/tmpfiles.d/powerdns-admin.conf
d /run/powerdns-admin 0755 pdnsa pdnsa -

The TLDR for above is - you're possibly running your server on port localhost:9191 but you want it to be on unix:/run/powerdns-admin/socket instead so that nginx or apache can proxy to it.  Else, change the proxy_pass definition in the nginx config.


open-all-notifications and open-all-conversations broken on iOS

This is because the background page isn’t being loaded at all.
It works on Safari desktop.
You can see here that no tabs are open after clicking the button
https://user-images.githubusercontent.com/1402241/177936256-a351fdf3-8278-464a-9e11-9920a8536eb1.MOV
Example URLs

https://github.com/notifications
https://github.com/refined-github/refined-github/issues

Extension version
22.7.1

😍  Fixed by

https://github.com/fregante/webext-domain-permission-toggle/pull/26
https://github.com/refined-github/refined-github/pull/6592


Incompatibility with sodium for version 3.0.2

i was using 3.0.1 and it was working fine, saw the 3.0.2 update and my game was stuck in a loading screen loop so i individually tested all the mods and saw sodium was causing the issue.
List of mods i use:
FerriteCore
Sodium
Indium
Hydrogen
Lithium
Enhanced block entities
Starlight
Mod Menu
Smooth Boot
Fabric API

Duplicate of #25 (despite the misleading title), the problem is the same on 1.16.5 and on 1.17.1


Imperfect read alignment, changing parameters does not help

Mapping a read
>A00297:159:HV2LVDSXX:3:1439:25572:32503
AGGCGGCCCCTGCAGTGGTCGCTGATGCAGGCGTTGAAGAATGGGCCCGGGGGCACAAGGTTGTGGCACTCAGCAAAGACCCTGTGGGGCAAAGCGATCAGGACGGAGGGCCCCCAGCGTGCATGCGGGCGGGCGGGGGCGCCCCAGGGC

to the reference
>ref
CCCATGCCCACCACAGCCGCTCTGTGATCTGATGCTGAGCCAGTGAGTCCTCCCCTCGGG
GGTTGCAGGCCCTGGGGCGCCCCCGCCCGCCCGCATGCACGCTGGGGGCCCTCCGTCCTG
ATCGCTTTGCCCCACAGGGTCTTTGCTGAGTGCCACAACCTTGTGCCCCCGGGCCCATTC
TTCAACGCCTGCATCAGCGACCACTGCAGGGCCGCCTTGAGGTGCCCTGCCAGAGCCTGA
GGCTTACGCAGAGCTCTGCCGCGCCCGGGGAGTGTGCAGTGACTGGCGAGGTGCAACCGG
TGGCCTGTGCGGTGAGTGGGGGCGGCCCCGGGCCCCCCAGACCCCTCGGCCTCTCTGAGT
GTCCTGTGCGGTGAGTGGGGGCGGCCCCGGGCCCCCCAGAC

using Strobealign v0.11.0 produces alignment 143=7S with score 296.
Mapping the same read using BWA MEM finds a better alignment 140=1I9= with score 143 (x2 = 286).
Setting high penalty for soft clipping -L 1000 produces a bad alignment 143=1X1=2X1=1X1= with score 2260, for some reason. Decreasing gap opening (-O) penalty and increasing match bonus/mismatch penalty (-A/B) did not help.
I tried changing seeding arguments -m/k/c/u/l, but with no luck for now.
Maybe part of the strobemer aligns in place of the 1 bp insert and this breaks the rest of the alignment, but it is strange that alignment cannot be fixed by modifying seeding arguments.
Also, extremely high score with high soft clipping penalty without the actual soft clipping seems like a bug.

Excellent bug report, I can reproduce your results.
I will discuss with @marcelm. Thanks for letting us know!

Also, extremely high score with high soft clipping penalty without the actual soft clipping seems like a bug.

The soft clipping penalty is not actually a penalty, but an "end bonus". It is added to the score for each end that reaches the end. This is also why you get the score 2260 when you set -L 1000.
(I know this is not documented correctly, and we need to fix this. – And maybe the better fix would be to make it actually be a soft-clipping penalty.)
I believe the issue may be that the alignment library we are using (SSW) does not directly support soft clipping penalties. We just let it find an alignment that is allowed to start and end anywhere within the read, and then afterwards try to extend it towards the end of the reads and adjust the score accordingly.
When we run SSW, we get 143=7S with a score of 286 (143 times match score). The end bonus for the 5' end is then added afterwards and gives a total score of 296.
SSW does not find 140=1I9= because it would result in a score of 280 - 12 - 1 + 18 = 285 (140 matches, 1 gap open, 1 gap extend, 9 matches). So although the total score would be 305 because we can add the end bonus twice, that variant is never considered.

SSW does not find 140=1I9= because it would result in a score of 280 - 12 - 1 + 18 = 285 (140 matches, 1 gap open, 1 gap extend, 9 matches).

Shouldn’t lowering -O adress the issue then, given your explanation? (I tried lowering -O and it still produces 143=7S).
(mentioned in anther discussion: I haven’t thought it through properly yet, but is it sound that the end bonus/penalty is part in determining the best location for PE-reads?)

Reflecting some direct emails, there seem to be some examples where the alignments have slightly odd indel behaviour, where bwa is happy to soft clip.
I made a recipe for reproducing some cases at https://gist.github.com/drtconway/962697804acd1d89c753b1d9a0378fc6

Perfect that you could pin this down. Easy to fix, but requires a bit of though how to do this without introducing too much runtime.
Perhaps hamming only over the span of the NAMs, but it may lead to a lot of extra ksw calls.  We can discuss this offline unless you already have something in mind.

(I wrote the above yesterday, I notice only now I haven’t actually posted it.)
It’s clear that just disabling the optimization is undesirable. On a test dataset (drosophila-50), runtime increases by more than 50%.
I think it makes sense to first ensure that the initial ungapped alignment is also done with soft clipping. The only reason for the current, inconsistent behavior is that I forgot this when I added soft clipping.
With that in place, we would get 143=7S as the first ungapped alignment in the example. If we count the soft-clipped bases as mismatches, that would give us 7/150 = 4.7%. That is still below the currently allowed threshold of 5%, so we would still skip SSW, but it’s a bit closer. Lowering the threshold to 4% (for example) is IMO not the way to go as it doesn’t help for longer reads.
I wonder whether we should then just run ksw on the ends that the ungapped alignment soft-clips. ksw can do extension alignment (unlike SSW) and because the soft-clipped ends are typically short, it should be quite fast.

I wonder whether we should then just run ksw on the ends that the ungapped alignment soft-clips. ksw can do extension alignment (unlike SSW) and because the soft-clipped ends are typically short, it should be quite fast.

Sounds good. So we need to start around _k_nt in w.r.t. the softclipp. So for the above example we would do extension alignment with the k+7 rightmost nt in the read to detect the indel.

Btw, what does strobealign currently do when the region with the NAM has the same length on the query and the reference and Hamming distance of the NAM region is high?
Do we fully realign such cases with SSW? If so, an optimization would be to run ksw on the ends only. I remember we have discussed similar scenarios when we tried out partitioning the alignments and use WFA2 but I don't remember the conclusions.


V7 logout is not idempotent

[x] I reviewed open and closed github issues that may be related to my problem.
[x] I tried updating to the latest version of the CF CLI to see if it fixed my problem.
[x] I attempted to run the command with CF_TRACE=1 to help debug the issue.
[x] I am reporting a bug that others will be able to reproduce.
[x] If this is an issue for the v7 beta release, I've read through the official docs and the release notes.

Describe the bug and the command you saw an issue with
cf logout command fails if you aren't targeted to an api.
This is irritating when you want to write scripts that ensure that any pre-existing logins are cleaned up first.
The cf cli version 6 is idempotent and does not have this issue.
What happened
cf logout exits 1
Expected behavior
cf logout exits 0
To Reproduce
Steps to reproduce the behavior; include the exact CLI commands and verbose output:

Run rm -rf ~/.cfto make sure there is no api targeted.
Run cf logout
See error

➜  relint-workstation git:(master) ✗ ~/Downloads/cf7-cli_7.0.2_osx/cf7 logout -v
No API endpoint set. Use 'cf7 login' or 'cf7 api' to target an endpoint.
FAILED

Provide more context
Mac OS X
CLI v7.0.2

Thanks for pointing out this regression @lisamburns !
We've prioritized fixing this in our backlog and will apply the fix to both the v6 and v7 lines.

this issue has been fixed in the v6 CLI v6.53.0

@heyjcollins , it looks like the fix is not yet in v7. The latest version is v7.1.0. Is there v7.2.0 forthcoming?


can geoip2 lookup be configured using a remotely stored mmdb file?

Usage question
Rather than an issue, I have a question I cannot determine the answer to.
I am using the geocoder and maxminddb gems successfully in development to geocode IPs for my site's analytics. I've written a rake task to download the GeoLite2-City.mmdb database from MaxMind to refresh the information twice weekly. The task stores the downloaded file in the application's tmp/ directory, and the geocoder configuration file (see below) successfully loads that file in development.
Geocoder.configure(
  ip_lookup: :geoip2,
  geoip2: {
    file: "tmp/GeoLite2-City.mmdb"
  }
)

I am aware that local address lookups like geoip2 are new and not yet production ready. However, I have been trying to get it to work in production on my personal site to see if it could work. Deploying to Heroku I realized that this strategy will fail because of Heroku's ephemeral data store. Running the application across multiple dynos means that a file stored in tmp/ might or might not be present when the application loads. In order to persist a file that I download through a rake task, I will need to upload it S3 or some other external datastore. That's easy enough, but I'm not sure how I would actually configure the geocoder gem to ingest a remotely stored file.
Is there a way to configure geoip2 lookup to load a file from S3 (rather than local storage)? Any tips on implementing this approach on Heroku would be appreciated!
Environment info

Geocoder version: 1.8.3
Rails version: <IP_ADDRESS>
Database (if applicable):
Lookup (if applicable): geoip2 (GeoLite2)

For anyone looking to do something similar, I seem to have found a solution. I modified my rake task for refreshing the MaxMind GeoLite2 database to store the ~50Mb .mmdb file in an AWS S3 bucket using v3 of the aws-sdk-ruby gem.
object = Aws::S3::Resource.new.bucket(ENV['GEO_BUCKET']).object('GeoLite2-City.mmdb')
object.upload_file(open(mmdb_file_location))

Then I updated the configuration for the geocoder to download the database file from the S3 bucket into the tmp/ folder when the application loads.
Geocoder.configure(
  ip_lookup: :geoip2,
  geoip2: {
    file: Aws::S3::Resource.new.bucket(ENV['GEO_BUCKET']).object('GeoLite2-City.mmdb').download_file('tmp/GeoLite2-City.mmdb') ? "tmp/GeoLite2-City.mmdb" : ''
  }
)

Doing it this way forces the download happens when the application launches, which seems to ensure the file is present in Heroku's ephemeral storage at the necessary moment to load it into memory.
It is currently working in production for me, but I am not sure how stable it is. If anyone has any critiques or better practice to offer, please share!

@deadroxy interesting solution! Thanks for sharing!

Thanks @alexreisner - I'll close this issue out, since I'm not sure if there is a more robust solution yet!


Fixed some comments

Codecov Report

Merging #142 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master     #142   +/-   ##
=======================================
  Coverage   87.51%   87.51%
=======================================
  Files          17       17
  Lines        2274     2274
=======================================
  Hits         1990     1990
  Misses        284      284

Impacted Files
Coverage Δ

biorbd_optim/dynamics.py
100.00% <ø> (ø)

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 7cbfbcb...e523392. Read the comment docs.


Cannot use this with a group chat

Hi,
I used this with my bot and a personal chat with him.
But I cannot make it work when using a private group chat with multiple people inside (and my bot).
Am I right to assume that if I don't use the optional SHHH_ALLOWED_CHAT_IDS everyone talking to this bot, or in a group where this bot is, should trigger an action ?
Thanks a lot

After some more tests, getting logs in a chat group works.
What does not work is sending a vocal_message to a group_chat where the bot is.
It does not pick the message and translate.
Would it be possible to have this feature ?

After some more tests, getting logs in a chat group works.
What does not work is sending a vocal_message to a group_chat where the bot is. It does not pick the message and translate.
Would it be possible to have this feature ?

I believe you need to make the bot an admin of the group so it can recieve messages via the API which aren't directly sent to it.

Oh ok thanks.
I will check how to make him admin and report back.

It works. You can close the issue, thank you.

I'm glad you got it working, happy speech to texting!


launch.json args should be array

If one follows https://github.com/BowlerHatLLC/vscode-as3mxml/wiki/launch.json-fields-for-SWF-debugging#args

VSCode will say:

Incorrect type. Expected "array".

This works:
"args": ["myFirsArgument", "222", "third"]

Fixed! Thanks.


Correct 0.12.1 CHANGELOG heading

Just looking at the CHANGELOG this morning and noticed this typo.

Thanks!


Enhancement Request: Allow forwarding custom attributes

Problem
Currently, type utility macros doesn't forward custom attributes like #[dummy(...)] to the generated structs. This limitation prevents users from utilizing important custom attributes in derived structures.
Current Behavior
#[derive(Omit)]
#[omit(arg(ident = EntityAttributes, fields(id), derive(Debug, Dummy)))]
pub struct Entity {
    id: i32,
    pub name: String,
    #[dummy(faker = "ExampleUrl()")]
    pub thumbnail_url: Url,
}

The #[dummy(...)] attribute is lost in the generated EntityAttributes struct.
Proposal
Add a forward_attrs option to the type utility macros:
#[derive(Omit)]
#[omit(arg(
    ident = EntityAttributes,
    fields(id),
    derive(Debug, Dummy),
    forward_attrs(dummy)
))]
pub struct Entity {
    id: i32,
    pub name: String,
    #[dummy(faker = "ExampleUrl()")]
    pub thumbnail_url: Url,
}

This seems like a bug since I want to pass the attributes by default. I will try to find out why ASAP.

Oh, I set forward_attrs(allow, doc, cfg) as the example of darling's documents. This prevents custom attributes from being forwarded.

I remember why I set it that way: This prevents forward pick to omit.
I'm trying to support this enhancement.

An implementation is in the PR#10. I think it mostly fixes this issue. Could you please check the changes of README.md, lib.rs, and tests, then point out whether there is something I haven't considered?

The pull request you submitted looks good, but since I am still relatively new to Rust and don't feel confident enough to conduct a thorough review, I would like to recommend my former colleague @siketyan, who is more experienced with Rust, as the reviewer.

A new version (v0.0.4) is released and includes this enhancement.


@as_bool meta key

It could be useful at some point to allow customization of the behaviour when a value is encountered in conditional expressions.
make_foo = |x|
  data: x
  @as_bool: |self| self.data > 0

my_foo = make_foo 42
if my_foo
  do_something()
else
  do_something_else()

#154 introduces new boolean coercion rules that mean that only false and null should be treated as false in boolean contexts, and all other values are treated as true. I'm uncertain about the benefit of allowing these rules to be customized with meta logic.
I'd be open to revisiting this with a concrete use case in mind, but for now I'll close this and hope that we can stick to the simple coercion rules.


Error in parsing SVG: Non-whitespace before first tag

ic_vendor_360.svg:1 Uncaught Error: Module build failed (from ../node_modules/svgo-loader/index.js):
Error: Error in parsing SVG: Non-whitespace before first tag.
Line: 0
Column: 1
Char: i
at Object.loader (Users/zhj/Documents/fe-dev/test/node_modules/svgo-loader/index.js:14)
at eval (ic_vendor_360.svg:1)
at Object../modules/holographic-archive/src/icons/svg/brand/ic_vendor_360.svg (index.js:2507)
at webpack_require (index.js:833)
at fn (index.js:130)
at webpackContext (eval at ./modules/test/src/icons/svg sync recursive .svg$ (index.js:2496), :31:9)
at Array.map ()
at requireAll (index.js?fb20:3)
at eval (index.js?fb20:4)
at Module../modules/test/src/icons/index.js (index.js:2485)
at webpack_require (index.js:833)
webpack config

Hi @jawn-ha . Could you provide svg file which produces this error?

Hi @jawn-ha . Could you provide svg file which produces this error?

this is the svg icons
svg_icon.zip

Cannot reproduce. Could you create repository with reproduction including webpack setup?

Cannot reproduce. Could you create repository with reproduction including webpack setup?

I create an repo to reproduce the question https://github.com/jawn-ha/svgo-test.
You can clone and run npm install andnpm run serveto reproduce

I see. It's not svgo-loader issue. Put svg-sprite-loader before svgo-loader.

I see. It's not svgo-loader issue. Put svg-sprite-loader before svgo-loader.
I had tried this，if you put  svg-sprite-loader before svgo-loader, svgo-loader will not working

I had tried this，if you put svg-sprite-loader before svgo-loader, svgo-loader will not working

I see. It's not svgo-loader issue. Put svg-sprite-loader before svgo-loader.

I don't see any issue with svgo. It produces correct svg, it removes fill from path. Maybe something wrong with svg-sprite-loader. I'm not experienced with it.

I have solved it, you are right! The cause of the problem is my SVGO config is wrong. Thanks for your patience

I don't see any issue with svgo. It produces correct svg, it removes fill from path. Maybe something wrong with svg-sprite-loader. I'm not experienced with it.


Fix crash in MongoCollection.findOneDocument(filter:) that occurred when no results were found for a given filter.

Fixes #7380.

We should also check if this is a problem for other findOne* methods that take options. What happens if the query for findOneAndDeleteWhere doesn't match a document?
I guess this wouldn't be an issue for findOneAndReplaceWhere or findOneAndUpdateWhere.


Question on NERSC Best Practices

In looking over https://e3sm-project.github.io/zstash/docs/html/best_practices.html , it seemed to me that a better approach on NERSC is to submit a job using zstash to the transfer queue:
https://docs.nersc.gov/filesystems/archive/#use-the-xfer-queue
Has that approach been tested?

Hi @matthewhoffman. This approach has not been tested. In fact, I think most users of zstash just run it on a login node, without submitting a batch job.
I'd guess one reason that this is recommended is to limit the number of HPSS instances to 15[1]. The part I'm hesitant about is:
"By default, xfer jobs get 2GB of memory allocated. The memory footprint scales
somewhat with the size of the file, so if you're archiving larger files,
you'll need to request more memory."

Most of the tar archives are in 64GB or 128GB sizes. I'm not sure if a user who just wants to download some model output would know how much memory is needed. I don't even know myself. The same question holds for archiving/uploading the data as well.

@zshaheen , I've used the transfer queue in the past for 500GB+ transfers without a problem.  I added
#SBATCH --mem=10GB

to my submit script, based on the documentation:

You can do this by adding #SBATCH --mem=XGB to the above script (where X in the range of 5 - 10 GB is a good starting point for large files).

Might be worth exploring at some point in the future.

@matthewhoffman,
I have used the xfer queue in the past. It works and that is definitely an option that could be added to the best practices documentation page (you are welcome to do so if you'd like).
The main reason I have not been using for most archiving tasks is the wall clock limit of 48 hours. For moderately-sized archiving jobs, 48 hours should be sufficient. But for really large archiving tasks, it won't be.
Also, we do not recommend running zstash on edison or cori login nodes, but rather on the data transfer nodes (DTN) which offer better performance.

Closing now. The currently recommended E3SM best practices is to archive from NERSC data transfer nodes using zstash from the E3SM unified environment. A 'screen' session is recommended for long archival tasks.


cls and Dn loss nan

Thanks for your excellent work. I closed the depth estimation branch but encountered cls loss nan and dn loss nan in 38000+ iters.

optimizer = dict(     type="AdamW",     lr=2e-4,     weight_decay=0.001,     paramwise_cfg=dict(         custom_keys={             "img_backbone": dict(lr_mult=0.5),         }     ), )

Reducing the batch size or disabling the depth auxiliary task both require reducing the learning rate. You need to further decrease the learning rate.

Reducing the batch size or disabling the depth auxiliary task both require reducing the learning rate. You need to further decrease the learning rate.

My batchsize is 64, the learningrate is set to 4e-4 at first, it is reduced to 2e-4, and the NAN still appears, do I need to adjust it to 1e-4

Is the dataset you are using the nuScenes dataset?

Is the dataset you are using the nuScenes dataset?
It's not nuscenes, it's custom dataset.

I can't determine the cause of the problem, because there are too many influencing factors.

I'll try to reduce the learning rate. Thanks.
------------------ Original ------------------
From: linxuewu @.>
Date: Fri,May 24,2024 8:02 PM
To: HorizonRobotics/Sparse4D @.>
Cc: jiandong.gao @.>, Author @.>
Subject: Re: [HorizonRobotics/Sparse4D] cls and Dn loss nan (Issue #50)

I'll try to reduce the learning rate. Thanks.
…
------------------ Original ------------------ From: linxuewu @.> Date: Fri,May 24,2024 8:02 PM To: HorizonRobotics/Sparse4D @.> Cc: jiandong.gao @.>, Author @.> Subject: Re: [HorizonRobotics/Sparse4D] cls and Dn loss nan (Issue #50)
Hello, how did you solve this problem.

Hello, how did you solve this problem.

learningrate 减低到1e-4看起来能收敛，如果还有问题，可以尝试再减小。

Hello, how did you solve this problem.

learningrate 减低到1e-4看起来能收敛，如果还有问题，可以尝试再减小。

谢谢回复！6e-5是一个不错的选择，模型已经收敛了。


Issue with No detection?

Hello,
If there are no objects on the image, what happens?
I'm having an error where the box result is negative:
prediction --> [[0. 0. 0. 0. 0. 0.]]
after the call to fit_pred_bboxes_to_original: [[ 0.    -1.156  0.     0.     0.     0.   ]]
time: 3171.96 ms
If I need to then use the box; the negative result will bring an error.
I'm using the following script
def run_obstacle_detection(img):
    start_time=time.time()
    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    resized_image = yolo.resize_image(img)
    # 0 ~ 255 to 0.0 ~ 1.0
    resized_image = resized_image / 255.
    #input_data == Dim(1, input_size, input_size, channels)
    input_data = resized_image[np.newaxis, ...].astype(np.float32)

    candidates = yolo.model.predict(input_data)

    _candidates = []
    result = img.copy()
    for candidate in candidates:
        batch_size = candidate.shape[0]
        grid_size = candidate.shape[1]
        _candidates.append(tf.reshape(candidate, shape=(1, grid_size * grid_size * 3, -1)))
        #candidates == Dim(batch, candidates, (bbox))
        candidates = np.concatenate(_candidates, axis=1)
        #pred_bboxes == Dim(candidates, (x, y, w, h, class_id, prob))
        pred_bboxes = yolo.candidates_to_pred_bboxes(candidates[0], iou_threshold=0.35, score_threshold=0.40)
        print(pred_bboxes)
        pred_bboxes = yolo.fit_pred_bboxes_to_original(pred_bboxes, img.shape)
        print(pred_bboxes)
        exec_time = time.time() - start_time
        print("time: {:.2f} ms".format(exec_time * 1000))
        result = yolo.draw_bboxes(img, pred_bboxes)
    return result, pred_bboxes

result, pred_bboxes = run_obstacle_detection(img_left)
plt.imshow(result)
plt.show()

Thanks for helping!

is the script above your full script?

is the script above your full script?


Image for pre-upgrade Job can't be overwritten

Image for pre-upgrade Job can't be overwritten using --set Helm flag (or any other way)
To Reproduce
Steps to reproduce the behavior:

Run helm install on environment where Docker registry is not available
mongodb-upgrade job can't be done due to ImagePullBackOff error

Expected behavior
I can overwrite that value using helm --set flag
Version / Cluster

1.9.92
Local kubernetes

Additional context
https://github.com/kubeshop/helm-charts/blob/main/charts/testkube/templates/pre-upgrade.yaml#L26

hi @michal-jagiello-tmpl,
we have added an option to override image for mongo job. Please upgrade Testkube to the latest version and let us know about the results.


openthread: off-by-one error when calculating ot_flash_offset for settings

Describe the bug
OpenThread uses a CONFIG_OT_PLAT_FLASH_PAGES_COUNT to calculate the # of pages at the end of flash to use for storing OpenThread settings.  This calculation is done here:
https://github.com/zephyrproject-rtos/zephyr/blob/master/subsys/net/lib/openthread/platform/flash.c#L33
There is an off by 1 error in this line:
	if (flash_get_page_info_by_idx(flash_dev,
		pages_count - CONFIG_OT_PLAT_FLASH_PAGES_COUNT - 1, &info)) {

The ending offset is actually 1 page earlier than it should be.
For example, on nRF52840:

default setting for CONFIG_OT_PLAT_FLASH_PAGES_COUNT is 4
flash size is 1MB (0x100000)
flash page size is 4096 (0x1000)
so expected offset here is 0xfc000

When adding print debug to this function the result is:
ot_flash_offset: 0xfb000
To Reproduce
Steps to reproduce the behavior:

apply the following patch to Zephyr:

diff --git a/subsys/net/lib/openthread/platform/flash.c b/subsys/net/lib/openthread/platform/flash.c
index b2776f31dd..947491e9c2 100644
--- a/subsys/net/lib/openthread/platform/flash.c
+++ b/subsys/net/lib/openthread/platform/flash.c
@@ -50,6 +50,8 @@ otError utilsFlashInit(void)
                ot_flash_size += info.size;
        }

+       printk(">>> %s: ot_flash_offset: 0x%x\n", __func__, ot_flash_offset);
+       printk(">>> %s: ot_flash_size  : 0x%x\n", __func__, ot_flash_size);
        return OT_ERROR_NONE;
 }

connect serial console to reel_board (or any OpenThread capable HW)
cd zephyr/samples/net/lwm2m_client/
mkdir build; cd build
cmake -DBOARD=reel_board
make
make flash
Note: console output:

>>> utilsFlashInit: ot_flash_offset: 0xfb000
>>> utilsFlashInit: ot_flash_size  : 0x4000

Expected behavior
Offset for OpenThread settings should be correctly calculated instead of off by one.
Impact
Noticed when the flash page under the expected OpenThread storage area was being overwritten with data.
Environment (please complete the following information):

OS: Arch Linux
Toolchain: Zephyr SDK
Commit SHA: fd49cf7d02914669df8d86b67a1c7f1a0de76a52 (today's master)

@rlubos I know you want to solve the OpenThread storage in better ways, but this should probably be fixed first.


Added --localtime to command line options

This fixes issue #128

I rebased it, see #185.

@andrasq may I suggest closing this PR since it's now obsolete?

obsolete how?

Sorry, I completely missed the rebase update.  I'll take a look and see what the current status is here.

@andrasq I mean that the functionality in this PR from you has merge conflicts and is available in your #185, so there is no reason to leave this PR open?

@edpbx oh, right you are.  #185 is the same, yes; this can be closed

Great! I'm not an admin of this: could you click the "close"? :-)

oh!  I think you meant to ask @killsto, the author of #130.  I, @andrasq, rebased (duplicated really) the feature in #185, but 130 isn't mine to close.

I forgot I did this! I will go ahead and close it.

:+1:

@andrasq
I run svn2git --localtime --rebase, based on => https://github.com/andrasq/svn2git
But the timestamp still is Date:   Thu Jun 8 04:50:40 2017 +0000
How can i fix it
Thanks

what is your local computer timezone?  The --localtime option is just passed
to git svn fetch --localtime, which I think prevents the svn commit timestamps
from getting converted to GMT.  I don't know what happens if the svn timestamps
themselves are GMT; our repos had localtime svn commit times.

@andrasq
Thanks for your reply.
Both local computer timezone and svn commit timestamp are 'China Standard Time UT+8:00'.
It can correctly convert timestamp when I use svn2git svn_url --localtime  to create a git repo.
But I use svn2git --rebase --localtime to pull in the latest changes from SVN into my git repo created from above, it doesn't work. the timestamp of commit still is GMT+0000.


Add Many-to-many support

Need to add many-to-many support for related fields (essential for managing grouping that is optional).

And one-to-many too.

Relationship types in Django, from here

Field.many_to_many -> Need to add support
Field.many_to_one -> Supported by current related field feature
Field.one_to_many -> Opposite of many_to_one, so I guess it is supported?
Field.one_to_one -> Supported by current related field feature


Add example for bind_var with Aql::builder()

Hello,
We got an issue https://github.com/fMeow/arangors/issues/29
So I add an example

Wait, something is wrong. I got it from the wrong banch


Fix exception on null json / jsonb value in postgres

Backport of  https://github.com/zio/zio-quill/pull/3023
Checklist

[x] Unit test all changes
[x] Update README.md if applicable
[x] Add [WIP] to the pull request title if it's work in progress
[x] Squash commits that aren't meaningful changes

@getquill/maintainers

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.Клюшников Владимир Анатольевич seems not to be a GitHub user. You need a GitHub account to be able to sign the CLA. If you have already a GitHub account, please add the email address used for this commit to your account.You have signed the CLA already but the status is still pending? Let us recheck it.


NICE TO HAVE: persistence of load chart and flex options options after editing

Now you have to re-do everything (zooming, choosing which flex options to use etc) after an edit.

Maybe we could save these options to localStorage whenever the user makes a change? That way it's easy to restore the settings when they come back to the page.

@grdw can we close this?

I think the relevant pull request is #457 which is unmerged. I'll look into it today.


QDMI info in license

https://github.com/Munich-Quantum-Software-Stack/QDMI/blob/d30ebfa0e045de028df064bb1ed377bb8c9bdb19/LICENSE#L189
Don't we need to update this?

Yes, we probably should. Although the original LLVM license also leaves this blank.
Should we just use "The QMDI contributors" with a link to https://github.com/Munich-Quantum-Software-Stack/QDMI/graphs/contributors?
Can someone quickly scout best-practices on GitHub for that?
I'd like to avoid listing explicit names as this information gets out of date so quickly.

This exact line is not supposed to be replaced. Instead, the entire boilerplate is meant to be copied to source files while substituting the placeholders.
See #97.


Naming conventions: _total vs. _count

The Metric and label naming documentation page states that "an accumulating count has a total as a suffix".
The Histograms and summaries best practice page however uses _count as the suffix for a counter.
Are these two recommendations not contradictory? Is the count+sum pair an exception to the general counter case, and thus warrants its own suffix? (If that's the case, it would probably make sense to mention that in the "Metric and label naming" page).

You should generally avoid naming a metric with a _count suffix. This suffix is a "magic" one that summaries and (classic) histograms auto-generate when ingested (or when represented in the text format). It's IMHO a bad practice, and native histograms avoid that.
Not sure if it is more confusing than useful to explain that on the "Metric and label naming" page.
Maybe we should just list suffixes to avoid (_count, _sum, _bucket, and also _total for non-counters). I'll change the title accordingly.

Thank you for the clarification!
Good to know that _count is to be avoided outside of the histogram context. So regular gauges that tell you the current count of something (e.g. the number of busy workers, number of open tasks etc.) should just not have any suffix at all (e.g. busy_workers, open_tasks), right?
What would you use if you currently only want sum + count (because a metric for the average is enough for the moment), but might want to introduce a histogram in the future? If you start with "_sum" and "_count", you could keep using them if you switch to a histogram later. Or are there subtle differences about a "naive"/manual count metric implemented as a counter and the "_count" metric published as part of a histogram?

If you just have sum + count, I would use a summary without quantiles. That's the most canonical way of representing it.
If you want a histogram later, so be it. You have to change the metric type then. (In principle, you could also create a bucket-less classic histogram, but in the future, you want native histograms anyway. Another reason to use a summary for as long as you just want sum + count.)


oss-fuzz-integration-is-split-across-(at-least)-3-repositories-and-is-fragile

https://github.com/containerd/containerd/issues/10226

Is there more explanation about how the builder will be called differently? How is instrumentation getting there today and what determines the version?

Can you link the corresponding PR to oss-fuzz as well?

@vishalRGurrala Can you fix the errors identified by the CI run?


Add llama.cpp for model flexible choices

It should be added due to the question from a reviewer

Now work with v1.0.1


Added gx package.json to chat-rendezvous

chat-rendezvous was not compiling due to the recent deletion of github.com/libp2p/go-msgio/mpool.

I just saw that the use of gx was questioned in #2, why is that?
@upperwal , what do you mean by saying that people should go get libp2p directly?

Hey @rob-deutsch gx is avoided in this repo for the sake of simplicity. github.com/libp2p/go-msgio/mpool isn't a direct dependency of this example so maybe you can try updating go-libp2p and compiling this example again.


Setting eukulele_db (sometimes) leads to a Cannot invoke method map() on null object error

Description of the bug
See title.
Command used and terminal output
Cannot invoke method map() on null object

Relevant files
No response
System information
No response

Fixed in #277


MSID: 87197 Version: 2 DOI: 2<IP_ADDRESS>8252

[PLACE MANUSCRIPT AND EDITOR DETAILS HERE WHEN AVAILABLE] See step 3
[PLACE PDF URL HERE WHEN AVAILABLE] See step 7
Step 1. Inform bioRxiv
Who can help: @QueenKraken, @nlisgo, @scottaubrey

[x] Manuscript is in data hub index (https://data-hub-api.elifesciences.org/enhanced-preprints/docmaps/v2/by-publisher/elife/get-by-manuscript-id?manuscript_id=87197)

Step 2. Create preview of manuscript
Who can help: @fred-atherden, @nlisgo, @scottaubrey

[ ] Manuscript is available for preview (https://prod--epp.elifesciences.org/preview/87197/v2)

[ ] Trigger import for staging: https://prod--epp.elifesciences.org/import
[ ] Sync data folder with s3://prod-elife-epp-data/data
[ ] Trigger import for staging: https://staging--epp.elifesciences.org/import
[ ] Sync data folder with s3://staging-elife-epp-data/data
[ ] Pull request created to enhanced-preprint-data
[ ] Post link to pull request below

Pull request: [PLACE LINK TO PULL REQUEST HERE]
Detailed instructions: https://github.com/elifesciences/enhanced-preprints-data#add-a-manuscript
Step 3: Awaiting public reviews and QC
Who can help: Production team

[ ] QC passed or QC not needed

Who can help: Editorial team

[x] Public reviews available on sciety (https://sciety.org/articles/activity/10.1101/2<IP_ADDRESS>8252)
[ ] Manuscript and editor details at the top of this issue (Supplied by Editorial team)
[ ] Reviews returned by EPP - https://prod--epp.elifesciences.org/api/reviewed-preprints/87197/v2/reviews

Example
"msas": "Genetics and Genomics", "Neuroscience"
"msid": "84628"
"version": "1"
"preprintDoi": "10.1101/2<IP_ADDRESS>4241"
"articleType": "Reviewed Preprint"
"status": "Published from the original preprint after peer review and assessment by eLife."

"Reviewed Preprint posted": "2023-01-02"
"Sent for peer review": "2022-10-28"
"Posted to bioRxiv": "2022-11-21" (link: "Go to bioRxiv": "https://www.biorxiv.org/content/10.1101/2<IP_ADDRESS>4241v1")

Editors:
Reviewing Editor
Michael B Eisen
University of California, Berkeley, United States
Senior Editor
Michael B Eisen
University of California, Berkeley, United States

Step 4: Modify manuscripts.json (no PDF)

[ ] Reviewed preprint is published to EPP (https://elifesciences.org/reviewed-preprints/87197)

[ ] Pull request created to enhanced-preprint-client
[ ] Pull request switched to "Ready for review"
[ ] Post link to pull request below

[ ] Request that a doi be registered

[ ] Post link to #enhanced-preprint comment below

Pull request: [PLACE LINK TO PULL REQUEST HERE]
#enhanced-preprint comment thread: [PLACE LINK TO COMMENT HERE]

Instructions to modify manuscripts.json

Visit: https://github.com/elifesciences/enhanced-preprints-client/actions/workflows/publish-manuscript.yaml
Click: Run workflow
Complete the form and click "Run workflow"
A successful run should result in a new pull request at https://github.com/elifesciences/enhanced-preprints-client/pulls
Open the pull request and click the "Ready for review" button to trigger tests
Once the tests pass and you are happy with the changes the PR can be merged

Example pull request: https://github.com/elifesciences/enhanced-preprints-client/pull/334/files
Once the pull request is merged in it should be available a few minutes later.

Request that a doi
Post the following in #enhanced-preprint:
@Fred can you register a doi for https://elifesciences.org/reviewed-preprints/87197

Step 5: Awaiting search reindex

[ ] Reviewed preprint is avaliable on journal homepage (https://elifesciences.org)

The search reindex is triggered once an hour. We need the reviewed preprint to be indexed as the search application serves the journal homepage.

Additional info
If needed, the jenkins pipeline to reindex search can be triggered sooner.
https://alfred.elifesciences.org/job/process/job/process-reindex-reviewed-preprints/

Step 6: Published! Request PDF generation

[ ] Post the link to the PDF url at the top of the issue

[ ] Post link to #enhanced-preprint comment below

#enhanced-preprint comment thread: [PLACE LINK TO COMMENT HERE]
Post the following to the #enhanced-preprint on slack:
@Ryan Dix-Peek please can you generate a PDF for https://elifesciences.org/reviewed-preprints/87197

Step 7: Introduce PDF to data folder and git repo

[ ] PDF is avaliable at https://github.com/elifesciences/enhanced-preprints-data/raw/master/data/87197/v2/87197-v2.pdf

Detailed instructions: https://github.com/elifesciences/enhanced-preprints-data#add-a-pdf
Step 8: Add PDF url to manuscripts.json

[ ] Reviewed preprint PDF is available for download (https://prod--epp.elifesciences.org/reviewed-preprints/87197)

[ ] Pull request created to enhanced-preprint-client
[ ] Pull request switched to "Ready for review"
[ ] Post link to pull request below

[PLACE LINK TO PULL REQUEST HERE]

Instructions to add PDF url to manuscripts.json

Visit: https://github.com/elifesciences/enhanced-preprints-client/actions/workflows/add-pdf-url-to-manuscript.yaml
Click: Run workflow
Complete the form and click "Run workflow"
A successful run should result in a new pull request at https://github.com/elifesciences/enhanced-preprints-client/pulls
Open the pull request and click the "Ready for review" button to trigger tests
Once the tests pass and you are happy with the changes the PR can be merged

Example pull request: https://github.com/elifesciences/enhanced-preprints-client/pull/397/files
Once the pull request is merged in it should be available a few minutes later.

Step 9: Done!

[ ] Kettle is on!

Reference 70 has not been imported correctly.

elocations missing from references.

Nicely spotted @JGilbert-eLife. The reference was mistagged. I've changed the tagging to be semantically correct. Unfortunately , the publisher name is still lost, but I think this is the best we can expect right now.


Update tests

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=========================================
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  Complexity        ?      240
=========================================
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=========================================
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Improve page reorder

Changes:

The pages in store are now reloaded after a page is reordered

When a new page is created, it is placed on the bottom of the page tree

LGTM

@Fajfa, status? :)


Dimension exponent doesn't support arithmetic

I can't declare types whose dimension is the result of some arithmetic expression:
x: ℝ^(dn + 3)
d: ℤ
n: ℤ

FWIW,
>>> from sympy import *
>>> m,n = symbols('m n', integer=True)
>>> n+n+m == m+n+n
True

etc. etc.

Even better:
sympify('m+n+n == n+n+m')


BUG-Renaming a node resets its position

Description
Renaming a node resets it to its spawn position. This is probably linked to #58 and #59

How to reproduce
Open VSCode
Open the View of a Config in Taipy Studio
Rename a Node
It should move back to its spawn position
Expected behavior
Renaming a node should not change its position
Runtime environment
Please specify relevant indications.

OS: Windows 11
Visual Studio Code version: 1.78.2
Taipy Studio Config version: 1.0.4
and any other relevant information.

is this the same as #68

Ah yeah my bad, I closed the other issue


Dockerize JEval

@QAInsights Instead of dockerize why not publish this as a python pip package ?
Supporting both ubuntu and alpine linux - so that it can be used inside a docker image in CI or in local easily.

Thanks @leelaprasadv . Let me explore into it.


CI: For some jobs, use ubuntu-18.04 instead of ubuntu-latest

This could potentially help us support slightly older glibc versions.
See also: #321

either vendoring openssl or switching to rustls

We should be using rustls on Linux already in any case.

We should be using rustls on Linux already in any case.

Then do we need binaries dynamically linked to glibc?

Probably not, I like your suggestion here very much. The more self-contained we can make juliaup and julialauncher the better.

Great, I'll test static musl binaries first thing in the morning tomorrow.

Great, I'll test static musl binaries first thing in the morning tomorrow.

Awesome!

I'll use the rustls PR for the test.

Oh, you can ignore that PR, rustls is used on main right now for Linux.

Oh, you can ignore that PR, rustls is used on main right now for Linux.

Why don't I see it in Cargo.toml as a dependency then?

@davidanthoff, the musl binaries work! Completely statically linked. No dynamic libraries, not even libc.

Amazing!
The size for juliaup is perfectly fine, the thing we do need to worry about (a bit) is the size of julialauncher. I've tried to keep the size of that really as small as possible, given that that sits in the "load path" for every Julia invocation and we want it to start as quickly as possible. At some point I had julialauncher at around 400 KB on Windows, but I'm not actually sure whether that is still the case. Could you check how big that one is with the static musl build? And maybe we could also try and see whether the ideas in https://github.com/JuliaLang/juliaup/issues/320 would make the julialauncher smaller with the static musl?
I should say, though, that the benefits of having everything self-contained probably even trump any size considerations we might have :) Really fantastic to see your results here!

the thing we do need to worry about (a bit) is the size of julialauncher

Then you won't be happy to hear that size has ballooned to 4 MB
❯ du target/x86_64-unknown-linux-musl/release/julialauncher
4092	target/x86_64-unknown-linux-musl/release/julialauncher

Even with stripping the symbols, it's still 2 MB:
❯ du target/x86_64-unknown-linux-musl/release/julialauncher
2016	target/x86_64-unknown-linux-musl/release/julialauncher

How should I measure the performance impact?

@davidanthoff, I can safely say at this point that using musl will have no adverse effects.

That's not true anymore

Yep, it is what I feared :) Probably actually due to me just using additional crates since I originally tested this.
@DilumAluthge does this all make sense to you as well?
@SaadiSave do you want to open a PR where this is added? Or would it be easier if I add this to the (admittedly very) cumbersome and convoluted workflow. I think with the info you provided me I could do this really quickly.

@SaadiSave do you want to open a PR where this is added? Or would it be easier if I add this to the (admittedly very) cumbersome and convoluted workflow. I think with the info you provided me I could do this really quickly.

Okay, do it.

@DilumAluthge I think https://github.com/JuliaLang/juliaup/pull/370 takes care of this, so OK to close this? Do protest if you disagree :)


Make sure checkboxes load as checked for PAT test snapshot

Ticket: [N/A]
Feature flag: n/a

Purpose

Fix unchecked checkbox in Personal Access Token test's Percy snapshot
Make sure the parameters used in checkbox are the types we expect them to be

Summary of Changes

handle cases when the relation array is a promise and force it into an array

Side Effects
n/a
QA Notes

Please keep an eye on checkbox behavior (I doubt this should adversely effect existing things, but just in case 👀 )

Oh, it's merged now. NVM then.


Fixing HOCON comment annotations

@rwalpole Those changes are already in https://github.com/nationalarchives/ctd-omega-services/pull/69 see https://github.com/nationalarchives/ctd-omega-services/pull/69/commits/2fb24296123236db629ad0b05d9ef228ac3ec1cf


Fix post-commit failure after pr/30205.

The PR #30205 introduced a bug of early termination when there is any exception in batch copy/delete. As a result, the error code is not propagated correctly and one of our post-commit tests failed.
AssertionError: BeamIOError not raised
self = <apache_beam.io.gcp.gcsfilesystem_integration_test.GcsFileSystemIntegrationTest testMethod=test_rename_error>

    @pytest.mark.it_postcommit
    def test_rename_error(self):
      num_copies = 10
      srcs = [self.INPUT_FILE] * num_copies
      dests = [
          self.gcs_tempdir + '/%s_%d' % (self.INPUT_FILE, i)
          for i in range(num_copies)
      ]
      self.fs.copy(srcs, dests)
      new_names = [
          self.gcs_tempdir + '/%s_%d' % ("renamed", i) for i in range(num_copies)
      ]
      # corrupt one of the destination names
      bad_name = self.gcs_tempdir + '/errorbadwrong'
      dests[int(num_copies / 2)] = bad_name
>     with self.assertRaises(BeamIOError):
E     AssertionError: BeamIOError not raised

apache_beam/io/gcp/gcsfilesystem_integration_test.py:127: AssertionError

addresses #28398

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cc'ed @Abacn


Update Go (to 1.12) and some libraries

Update to Go 1.12

No compilation errors
No test failures
It seems that go vet has been used in a very simple way like this, so I did not change it
Go 1.12.5 is supported in Travis CI!

Update libraries

No compilation errors
No test failures
github.com/go-sql-driver/mysql

version: origin/master was specified, so I simply executed glide update

benchmark results

master (HEAD) https://github.com/fireworq/fireworq/commit/478e5a58be25b9da7c550f90dbc10dcf6377d776

JobConcurrency: 10, Score: 100.398
JobConcurrency: 20, Score: 21.182
JobConcurrency: 30, Score: 73.990
JobConcurrency: 40, Score: 69.861
--------------------------------
[Queue]
Took        69.108 sec.
Throughput: 144.700 /s
Score:      144.700
[Worker]
Took        136.216 sec.
Throughput: 73.002 /s
Score:      -38.998
[Overall]
Score:      -38.998
{"scenario":{"queue_name":"benchmark1","total_jobs":1000,"job_concurrency":10,"max_workers":50,"polling_interval":100,"error_rate":0,"max_payload_size":10,"max_retries":0,"max_run_after":0,"max_cycle_time":0},"result":{"queue_total_jobs":10000,"queue_errors":0,"queue_time":69108373427,"worker_total_jobs":10000,"worker_errors":56,"worker_time":136216141929}}

this branch (1st try)

JobConcurrency: 10, Score: 28.956
JobConcurrency: 20, Score: -19.282
JobConcurrency: 30, Score: -12.674
JobConcurrency: 40, Score: 47.616
JobConcurrency: 50, Score: -14.739
JobConcurrency: 60, Score: 66.592
JobConcurrency: 70, Score: 65.476
JobConcurrency: 80, Score: 68.473
JobConcurrency: 90, Score: -71.288
JobConcurrency: 100, Score: -586.132
JobConcurrency: 110, Score: -971.559
--------------------------------
[Queue]
Took        70.124 sec.
Throughput: 142.463 /s
Score:      122.463
[Worker]
Took        156.060 sec.
Throughput: 57.388 /s
Score:      -2010.612
[Overall]
Score:      -2030.612
{"scenario":{"queue_name":"benchmark1","total_jobs":1000,"job_concurrency":80,"max_workers":50,"polling_interval":100,"error_rate":0,"max_payload_size":10,"max_retries":0,"max_run_after":0,"max_cycle_time":0},"result":{"queue_total_jobs":10000,"queue_errors":10,"queue_time":70123661453,"worker_total_jobs":9990,"worker_errors":1034,"worker_time":156060401184}}

this branch (2nd try)

JobConcurrency: 10, Score: 104.924
JobConcurrency: 20, Score: -167.096
JobConcurrency: 30, Score: 71.153
JobConcurrency: 40, Score: 71.112
--------------------------------
[Queue]
Took        68.711 sec.
Throughput: 145.537 /s
Score:      145.537
[Worker]
Took        137.526 sec.
Throughput: 72.713 /s
Score:      72.713
[Overall]
Score:      72.713
{"scenario":{"queue_name":"benchmark1","total_jobs":1000,"job_concurrency":10,"max_workers":50,"polling_interval":100,"error_rate":0,"max_payload_size":10,"max_retries":0,"max_run_after":0,"max_cycle_time":0},"result":{"queue_total_jobs":10000,"queue_errors":0,"queue_time":68711232992,"worker_total_jobs":10000,"worker_errors":0,"worker_time":137526264606}}

Analysis
I do not know how we can trust these results because scores vary so widely. I guess the bad result of 1st try in updated  environment is caused by too high JobConcurrency. At least, 2nd try in updated environment finished with no queue_errors and no worker_errors. Probably, we could say there are no critical errors.

Benchmark
I used https://github.com/fireworq/benchworker.
In macOS Mojave, following settings will be required to process a huge number of requests per second.
> sudo sysctl -w kern.ipc.somaxconn=4096
> sudo sysctl -w net.inet.tcp.msl=1000

Results

master branch https://github.com/fireworq/fireworq/commit/478e5a58be25b9da7c550f90dbc10dcf6377d776

JobConcurrency: 10, Score: 161.487
JobConcurrency: 20, Score: 143.547
JobConcurrency: 30, Score: 138.451
JobConcurrency: 40, Score: 154.648
--------------------------------
[Queue]
Took        30.166 sec.
Throughput: 331.501 /s
Score:      331.501
[Worker]
Took        64.400 sec.
Throughput: 155.280 /s
Score:      155.280
[Overall]
Score:      155.280
{"scenario":{"queue_name":"benchmark1","total_jobs":1000,"job_concurrency":10,"max_workers":50,"polling_interval":100,"error_rate":0,"max_payload_size":10,"max_retries":0,"max_run_after":0,"max_cycle_time":0},"result":{"queue_total_jobs":10000,"queue_errors":0,"queue_time":30165839413,"worker_total_jobs":10000,"worker_errors":0,"worker_time":64399841654}}

this branch

JobConcurrency: 10, Score: 175.573
JobConcurrency: 20, Score: 137.607
JobConcurrency: 30, Score: 123.212
JobConcurrency: 40, Score: 131.853
--------------------------------
[Queue]
Took        34.474 sec.
Throughput: 290.070 /s
Score:      290.070
[Worker]
Took        80.370 sec.
Throughput: 124.424 /s
Score:      124.424
[Overall]
Score:      124.424
{"scenario":{"queue_name":"benchmark1","total_jobs":1000,"job_concurrency":10,"max_workers":50,"polling_interval":100,"error_rate":0,"max_payload_size":10,"max_retries":0,"max_run_after":0,"max_cycle_time":0},"result":{"queue_total_jobs":10000,"queue_errors":0,"queue_time":34474446588,"worker_total_jobs":10000,"worker_errors":0,"worker_time":80370477318}}


Extracting CSS Components From Tailwind

Issue
Right now, applying Tailwind CSS classes is horrendous, and it'll likely worsen as the project continues. Here's an example of what how the classes are applied from Title.vue:
<router-link :to='{ name: "login" }'
      class='btn bg-purple-500 hover:bg-purple-600 mt-8 px-3 py-1
      text-base sm:text-xl md:text-2xl lg:text-3xl xl:text-4xl rounded-lg'
      >
        Get Started | 开始
      </router-link>

Clearly, the classes are not very readable, and it would be a nightmare to switch later on. The goal is to fix this so we can have three or four classes max applied to each HTML element.
Ideas
This section of the Tailwind CSS Docs describes how to extract components. It looks like PostCSS is needed to use the @apply directive, but that could be false.
Try using the v-bind:class = ' ' attribute and take in an array of classes as a prop from the data function in App.vue (this can just be static binding).

I will look into this!


Add explicit BR: epel-rpm-macros

Another little thing  ;)

I was just doing this, but you beat me to it 😄

Hehe  :P


Add support for AWS DocumentDB

As per thread in #273, there are some changes required to add support for DocumentDB. These were written by @AlimovSV originally, I've just re-factored them to get a mergeable PR.
Note that I'm not properly across what is going on in this code, so it warrants careful attention and testing.

@jethro-solve I may make a PR if I manage to track down what's happening (I literally just discovered this and am happy it had an explanation!) but this PR will break the work cursor.ex is doing because in line 77 of that file when it runs Mongo.get_more the new returned value appears to match what should be returned by the first batch but not what should be returned from the "next" batches.
I'm going to get more specific shortly but just wanted to shout about it because I'm excited.

To be clear, Mongo.Cursor.next_fun/2 has a pattern match that goes as such:
case Mongo.get_more(conn, coll, cursor, opts) do
            {:ok, %{"cursor" => %{"id" => cursor, "nextBatch" => []}}} ->
              {:halt, state(state, cursor: cursor)}

            {:ok, %{"cursor" => %{"id" => cursor, "nextBatch" => docs}}} ->
              {docs, state(state, cursor: cursor, limit: new_limit(limit, batch_size))}

            {:error, error} ->
              raise error
          end

But the proposed changes make it so that Mongo.get_more returns something looking like:
{:ok, %{from: 0, num: Enum.count(docs), cursor_id: id, docs: docs}}

So you get a no case clause matching error on anything that needs more than reduces more than the first response from the cursor.


TVPlayer.com broken

It seems that TVPlayer.com has broken something a few days ago.
I had a Windows bat script that recorded them just fine and now I get "404 Not Found" for the m3u8 files any more. Same with the TVPlayer Kodi/XBMC addon.
I noticed that livestreamer is experiencing the exact same error.
[cli][info] Found matching plugin tvplayer for URL http://tvplayer.com/watch/trutv
error: Unable to open URL: http://live.cdn.tvplayer.com/8C16FNV3Z9J3DAWSFY6T/playlist.m3u8?e=1431699854&h=fbdf8409006f0cd7d632cba860b79b89 (404 Client Error: Not Found)
I ran Wireshark on each method and while it works playing in the browser, the only thing I can see differently that the browser is doing is it's using the SWF file in the "Referrer" in the HTTP headers.
Also it could be the cookie also but this just seems less likely.

hi
need user agent
livestreamer --http-header "User-Agent=Mozilla/5.0 (Windows NT 5.1; rv:37.0) Gecko/20100101 Firefox/37.0"  "http://tvplayer.com/watch/trutv" best
[cli][info] Found matching plugin tvplayer for URL http://tvplayer.com/watch/trutv
[cli][info] Available streams: 1416k, 2029k, 2745k (best), 395k, 64k (worst), 803k
[cli][info] Opening stream: 2745k (hls)
[cli][info] Starting player: /usr/bin/vlc

Oh ok that worked. Thank you!
I could have swore I tried User-Agent before in my script, but I may have
accidentally coded it wrong.
Either way, using livestreamer is so much easier and cross platform :)
On Fri, May 15, 2015 at 12:34 PM, biezom<EMAIL_ADDRESS>wrote:

hi
need user agent
livestreamer --http-header "User-Agent=Mozilla/5.0 (Windows NT 5.1;
rv:37.0) Gecko/20100101 Firefox/37.0" "http://tvplayer.com/watch/trutv"
best
[cli][info] Found matching plugin tvplayer for URL
http://tvplayer.com/watch/trutv
[cli][info] Available streams: 1416k, 2029k, 2745k (best), 395k, 64k
(worst), 803k
[cli][info] Opening stream: 2745k (hls)
[cli][info] Starting player: /usr/bin/vlc
--
Reply to this email directly or view it on GitHub
https://github.com/chrippa/livestreamer/issues/909#issuecomment-102454373
.

Fixed by #929.


Hello, are there any other modules that can be added to improve the effect?

Hello, thank you for sharing. I would like to ask if you have made any improvements based on the original thesis project, or just modified some parameters. The results according to your code are beyond the results written in the paper.

Hello, thank you for sharing. I would like to ask if you have made any improvements based on the original thesis project, or just modified some parameters. The results according to your code are beyond the results written in the paper.

Our methodology is applicable to any model. The paper is currently being reviewed, and code showing improved performance will also be released soon.


docs: DOC-209: Remove LSE params from the community helm chart page

There is a section in the helm chart page that lists Enterprise-only parameters. This doesn't need to be visible in the Community version of the page.
Affects:

[X] Community docs
[ ] Enterprise docs

This PR is stale because it has been open 45 days with no activity. Remove stale label or comment or this will be closed in 10 days.

This PR was closed because it has been stalled for 10 days with no activity.


nanosam: can not run example 1 , error for corrupted size vs. prev_size

Hi,
I directly pulled down the image using the jetson containers run Dustynv/nanosam: r36.2.0 command, and when I ran it directly, the following problem occurred. I haven't made any changes.  Has anyone encountered this problem? Thanks
/opt/nanosam# python3 examples/basic_usage.py     --image_encoder="data/resnet18_image_encoder.engine"     --mask_decoder="data/mobile_sam_mask_decoder.engine"
/usr/local/lib/python3.10/dist-packages/transformers/utils/hub.py:123: FutureWarning: Using TRANSFORMERS_CACHE is deprecated and will be removed in v5 of Transformers. Use HF_HOME instead.
warnings.warn(
[12/17/2024-20:20:29] [TRT] [W] Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors.
[12/17/2024-20:20:29] [TRT] [W] Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors.
/opt/nanosam/nanosam/utils/predictor.py:84: UserWarning: The given NumPy array is not writable, and PyTorch does not support non-writable tensors. This means writing to this tensor will result in undefined behavior. You may want to copy the array to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at /tmp/pytorch/torch/csrc/utils/tensor_numpy.cpp:206.)
image_torch_resized = torch.from_numpy(image_np_resized).permute(2, 0, 1)
/opt/nanosam/nanosam/utils/predictor.py:103: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at /tmp/pytorch/torch/csrc/utils/tensor_new.cpp:261.)
image_point_coords = torch.tensor([points]).float().cuda()
corrupted size vs. prev_size
Aborted (core dumped)

Hi @usernameXYS , it looks like maybe it is built against a different version of TensorRT - which version of JetPack-L4T are you running?   Can you try running a container of the same tag, or rebuilding the container / re-generating those TRT engines for nanosam?

Hi @dusty-nv ,
Thank you for your reply，Below is my environment.
Host environment:
L4T_VERSION=36.4.0
JETPACK_VERSION=6.1
CUDA_VERSION=12.6
PYTHON_VERSION=3.10
LSB_RELEASE=22.04 (jammy)
Dustynv/nanosam: r36.2.0， Docker container environment:
TensorRT: <IP_ADDRESS>-1+cuda12.2
In addition, I tried Dustynv/nanosam: r35.2.1 version, which had some issues with the GLIBC version when running. I updated it to run Example 1, but there were also some other problems. I couldn't install nvarguscamerasrc, and there were conflicts with some libraries that prevented me from obtaining camera data. Cannot run example 4.
and now i try to build nanosam: r36.4.0. Still in testing......

Hi @dusty-nv ,
I can use locally built nanosam, jetson build nanosam， The version is 36.4.0, and the issue mentioned above does not occur anymore. thank!
The 36.4 version environment is as follows, and the above issue may be due to differences between the local machine and Docker environment.
nanosam36.4
TensorRT：10.4
CUDA: 12.6.77

Ok great, glad you got it working!  I think it was because 35.2 image was from JetPack 5, and 36.4 is JetPack 6.

From: yisen.xu @.>
Sent: Thursday, December 19, 2024 1:13:41 AM
To: dusty-nv/jetson-containers @.>
Cc: Dustin Franklin @.>; Mention @.>
Subject: Re: [dusty-nv/jetson-containers] nanosam: can not run example 1 , error for corrupted size vs. prev_size (Issue #749)
Hi @dusty-nvhttps://github.com/dusty-nv ,
I can use locally built nanosam, jetson build nanosam， The version is 36.4.0, and the issue mentioned above does not occur anymore. thank!
The 36.4 version environment is as follows, and the above issue may be due to differences between the local machine and Docker environment.
nanosam36.4
TensorRT：10.4
CUDA: 12.6.77
—
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Fix: raven traffic ignore nat

Fixes #124

@njucjc PTAL

LGTM

@BSWANG This pr still needs some modifications based on our last discussion.

@YTGhost It seems that unit tests is not enough, please fix it.


Minor follow-up to #1695

Issue and/or context:
Minor follow-up to https://github.com/single-cell-data/TileDB-SOMA/pull/1695
Changes:

logger->set_pattern call should run unconditionally (currently runs on "!windows")

Also:

remove EXCLUDE_FROM_ALL cmake annotation on unit_soma so that the target updates reliably
add a note about a failure mode of readGitVersion when working from an unsynchronized fork

Notes for Reviewer:

Codecov Report
Patch has no changes to coverable lines.

:exclamation: Current head 7637e71 differs from pull request most recent head a433e3b. Consider uploading reports for the commit a433e3b to get more accurate results

:exclamation: Your organization needs to install the Codecov GitHub app to enable full functionality.
:loudspeaker: Thoughts on this report? Let us know!.


Revert "assignment 1 done"

Reverts joseDePaiva/scaling_to_production#3

Hello, why the revert?

Did it wrong!
Sent from my iPhone
On Jul 9, 2024, at 12:45 AM, Vishnou Vinayagame @.***> wrote:

Hello, why the revert?
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@joseDePaiva  please un-revert it because I can't see any content in A1 right now

@joseDePaiva please un-revert it because I can't see any content in A1 right now

IT IS DONE PLEASE CHECK IT!

Hi back, I’ve graded A1 but your A2 and quizzes are missing...
On Jul 16, 2024, at 6:09 PM, Jose Mario DePaiva @.***> wrote:
@joseDePaivahttps://github.com/joseDePaiva please un-revert it because I can't see any content in A1 right now
IT IS DONE PLEASE CHECK IT!
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Will work on A2 today. But the quizes I don’t have access anymore.
The provided links are expired .
Can you please send once again?
I have been travelling a lot for work for different times zone which make a bit of delay on have the things done.
Thank you
Sent from my iPhone
On Jul 16, 2024, at 7:22 PM, Vishnou Vinayagame @.***> wrote:

Hi back, I’ve graded A1 but your A2 and quizzes are missing...
On Jul 16, 2024, at 6:09 PM, Jose Mario DePaiva @.***> wrote:
@joseDePaivahttps://github.com/joseDePaiva please un-revert it because I can't see any content in A1 right now
IT IS DONE PLEASE CHECK IT!
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Unsuported URL error on Twitter.com / X.com: x.com does not work for yt-dlp

DO NOT REMOVE OR SKIP THE ISSUE TEMPLATE

[X] I understand that I will be blocked if I intentionally remove or skip any mandatory* field

Checklist

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Region
Sweden/Europe
Provide a description that is worded well enough to be understood
YT-DLP now gives an error on twitter.com url's (that are now x.com).
I noticed that twitters name-change and domain-change from twitter.com to x.com has progressed a bit more.
Before I could right-click a video and choose "Copy Video Address" and use that in a yt-dlp dowload request in terminal.
That url used to have twitter.com as domain, and now it's x.com. So yt-dlp now tries and fails and gives the error message "Unsupported URL".
If I change the url manually from x.com to twitter.com in the same yt-dlp download it works and the clip is downloaded.
I'm guessing x.com needs to be added as an correct url?
Provide verbose output that clearly demonstrates the problem

[X] Run your yt-dlp command with -vU flag added (yt-dlp -vU <your command line>)
[X] If using API, add 'verbose': True to YoutubeDL params instead
[X] Copy the WHOLE output (starting with [debug] Command-line config) and insert it below

Complete Verbose Output
[debug] Command-line config: ['-vU', 'https://x.com/i/status/1792744751076417813', '--list-formats']
[debug] User config "/Users/ola/.config/yt-dlp/config": ['--no-mtime', '-o', '~/Movies/%(title)s.%(ext)s', '--format', 'mp4', '-f', 'bestvideo+bestaudio']
[debug] Encodings: locale UTF-8, fs utf-8, pref UTF-8, out utf-8, error utf-8, screen utf-8
[debug] yt-dlp version<EMAIL_ADDRESS>from yt-dlp/yt-dlp [ff0779267] (pip)
[debug] Python 3.12.3 (CPython x86_64 64bit) - macOS-12.7.4-x86_64-i386-64bit (OpenSSL 3.3.0 9 Apr 2024)
[debug] exe versions: ffmpeg 7.0 (setts), ffprobe 7.0
[debug] Optional libraries: Cryptodome-3.20.0, brotli-1.1.0, certifi-2024.02.02, mutagen-1.47.0, requests-2.31.0, sqlite3-3.45.3, urllib3-2.2.1, websockets-12.0
[debug] Proxy map: {}
[debug] Request Handlers: urllib, requests, websockets
[debug] Loaded 1810 extractors
[debug] Fetching release info: https://api.github.com/repos/yt-dlp/yt-dlp/releases/latest
Latest version<EMAIL_ADDRESS>from yt-dlp/yt-dlp
yt-dlp is up to date<EMAIL_ADDRESS>from yt-dlp/yt-dlp)
[generic] Extracting URL: https://x.com/i/status/1792744751076417813
[generic]<PHONE_NUMBER>076417813: Downloading webpage
WARNING: [generic] Falling back on generic information extractor
[generic]<PHONE_NUMBER>076417813: Extracting information
[debug] Looking for embeds
ERROR: Unsupported URL: https://x.com/i/status/1792744751076417813
Traceback (most recent call last):
  File "/usr/local/Cellar/yt-dlp/2024.4.9_1/libexec/lib/python3.12/site-packages/yt_dlp/YoutubeDL.py", line 1606, in wrapper
    return func(self, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/Cellar/yt-dlp/2024.4.9_1/libexec/lib/python3.12/site-packages/yt_dlp/YoutubeDL.py", line 1741, in __extract_info
    ie_result = ie.extract(url)
                ^^^^^^^^^^^^^^^
  File "/usr/local/Cellar/yt-dlp/2024.4.9_1/libexec/lib/python3.12/site-packages/yt_dlp/extractor/common.py", line 734, in extract
    ie_result = self._real_extract(url)
                ^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/Cellar/yt-dlp/2024.4.9_1/libexec/lib/python3.12/site-packages/yt_dlp/extractor/generic.py", line 2514, in _real_extract
    raise UnsupportedError(url)
yt_dlp.utils.UnsupportedError: Unsupported URL: https://x.com/i/status/1792744751076417813

There were recent fixes for this on master:
https://github.com/yt-dlp/yt-dlp/commit/4813173e4544f125d6f2afc31e600727d761b8dd
https://github.com/yt-dlp/yt-dlp/commit/3e35aa32c74bc108375be8c8b6b3bfc90dfff1b4
Please try the latest version from git or a nightly build.

if you installed with homebrew, this is how to update to master:
brew uninstall yt-dlp
brew update
brew install --HEAD yt-dlp


Encode feature

Currently sorta works.
Seems to work on other people PCs but not mine. Works if I don't do full paths.
Ex: java -jar duckencode.jar -i helloworld.txt
Works
java -jar "C:\duckencode.jar" -i "C:\Users\Hayden Meloche\Desktop\Ducky\helloworld.txt"
Does not.
Also currently. Encode does not support custom file names (only helloworld.txt)  and does not support custom outputs so those need to be added to the cmd processing area.
This code is located in Encoder.cs in the encode button method near the bottom.

I ended up cloning the repo to one of my laptops. When clicking the encode button, I got an error message, but it also appears to have created an inject.bin file at the same time (it was not there before clicking the button)

I pushed a possible solution that at least fixes my error but changing around the variables a bit, let me know if it fixes it on your end.

Awesome! Ya just variables need to be changed now to support custom files. Also support for "-o " is needed at some point too


Unable to pass variables to Azure Pipeline

Hi guys,
I'm trying to use 'azure-pipelines-variables' parameters to pass some values to Azure Pipeline. Azure Pipeline is getting triggered but variables are not gets passed.
There is a warning in the GitHub Actions log:
Warning: Unexpected input(s) 'azure-pipeline-variables', valid inputs are ['azure-devops-project-url', 'azure-pipeline-name', 'azure-devops-token']
Run Azure/pipelines@v1
  with:
    azure-devops-project-url: https://dev.azure.com/qxzone/ContactPoint%20IP%20phone
    azure-pipeline-name: Release
    azure-pipeline-variables: { "cp.CoreVersion": "1.13.1" }
    azure-devops-token: ***
  env:
    CoreVersion: 1.13.1

GitHub Workflow (part):
  release:
    runs-on: ubuntu-18.04

    steps:
    - name: Trigger Azure Release Pipeline
      uses: Azure/pipelines@v1
      with:
        azure-devops-project-url: 'https://dev.azure.com/qxzone/ContactPoint%20IP%20phone'
        azure-pipeline-name: 'Release'
        azure-pipeline-variables: '{ "cp.CoreVersion": "${{ env.CoreVersion }}" }'
        azure-devops-token: '${{ secrets.AZURE_DEVOPS_TOKEN }}'

Runner options: ubuntu-latest, ubuntu-18.04

I wonder if this feature has been released yet.

It is merged but not yet released. When can we expect it to be released?

@alexrster: I am also getting the same warning. When we can expect this feature to release? @azure, @MicrosoftGit

@alexrster: did you find another way?

@alexrster: did you find another way?

Yup, the actual implementation seems to work fine but it isn't yet included in master branch here for some reason. I've forked this repo and created the v2 release with this feature enabled from there (https://github.com/alexrster/pipelines).
My pipeline now looks like the following:
    steps:
    - name: Trigger Azure Release Pipeline
      uses: alexrster/pipelines@v2
      with:
        azure-devops-project-url: 'https://dev.azure.com/.......'
        azure-pipeline-name: '.......'
        azure-pipeline-variables: '{ "cp.CoreVersion": "${{ env.CoreVersion }}" }'
        azure-devops-token: '${{ secrets.AZURE_DEVOPS_TOKEN }}'

Would it be possible to tag a new release in the Azure/pipelines repo with support for azure-pipeline-variables? 👀

Any news on this?

Would it be possible to tag a new release in the Azure/pipelines repo with support for azure-pipeline-variables? 👀

Any news on this? Thanks!!

Please try this: https://github.com/ladvivek7/Az_Pipeline

Merged #35

Merged #35

Awesome! Could you also tag a new release?

Merged #35

Awesome! Could you also tag a new release?

Hi @tlrh314 ,
Tagged here 👍

+1
This is a bit crazy it's gone on for 8 months and it's already documented in the public docs :-(

Thank you @Josh-01 and team for v1.2. I updated my GitHub template to use<EMAIL_ADDRESS>and now variables are passed to my pipeline on the Azure side.


move deprecated functionality into an extra module

move all deprecated implemenations (e.g. backwards compatible stuff, or support for older specs2 suites) into a separate module
stop bundling this module with scalamock-core
check if we can then use a linter on core in the build process, e.g.
https://github.com/HairyFotr/linter
https://github.com/scalastyle/scalastyle
https://github.com/sksamuel/scapegoat

removed old specs2 MockFactory that was deprecated since 3.2

#192 made this unnessary. should exclude certain files in scapegoat instead


Does it support version 8?

Hi. Seems that only till version 7 is supported, do you have plans to support v8 of ES?
Thanks.

Have you tried to set the version to 7.x? Maybe it's already working as expected.

With https://github.com/rolehippie/elasticsearch/pull/23 you should be able to install v8.


Improve docs

I tried apollo-codegen today for the first time. My scenario is that I want to generate typescript types. When going through the readme I found it a bit difficult to understand what the purpose of the operations are. So I propose that a sentence for each operation is added to the readme like this:

introspect-schema

The purpose of this operation is to convert a graphql schema to a JSON file which can then be used by the "generate" operation.

generate

The purpose of this operation is to generate types for queries and mutations made against the schema (it will not generate types for the schema itself).

If the above is correct (which it might not be because I misunderstood something), then I would be happy to make a PR with the above changes.

Thanks for the feedback! I agree we need to improve the docs. We'd eventually like to revise some of these commands and integrate better with other tools, but your basic understanding is correct:

introspect-schema was originally only used to introspect a GraphQL server and download the introspection result (schema.json). We then added the ability to use it to convert a local schema.graphql into that same JSON representation. As has been mentioned in some issues, it may actually make more sense to allow schema.graphql to be used as input directly, so you wouldn't have to use introspect-schema for a local schema file.

generate is indeed used to generate types for query and mutation results, as well as types used by these operations, such as enums and input object types. A point of continued confusion is that people expect types to be generated from the schema alone, but that wouldn't give you the type safety you get form operation-specific types.

(apollo-codegen was originally written to support Apollo iOS, and I wrote a blog post about the benefits of operation-specific types that we may want to link to. But it would be even better to explain this in the context of TypeScript/Flow types.)
A PR to the docs is definitely welcome, and so is any other feedback you may have on how the tool works or should work!

I think part of the expectation that full schema types will be generated is that the example specifies the output file name as schema.ts. Here is the example command in the readme:
# TypeScript
apollo-codegen generate **/*.graphql --schema schema.json --target typescript --output schema.ts

I think it would clarify a bit if the output file name would be changed to operation-types.ts or something similar, instead like this:
# TypeScript
apollo-codegen generate **/*.graphql --schema schema.json --target typescript --output operation-types.ts

I hadn't noticed that, but that makes sense! Maybe operation-result-types.ts?

I made a PR in #265. Please check if it makes sense :-).

The PR is merged now so I'm closing this.


SvgIcon component does not work in IE11

I'm not sure what the browser support for VueDS is, but the SvgIcons do not work in ie11 because ie11 does not support innerHTML on svg elements.
I tried to use the innersvg-polyfill, but it does not seem to be working (even in plain HTML without Vue).
I'm able to get it working using img tags with the svg as the src, but that means that icons cannot be filled dynamically with the fill prop.

This approach works in IE11. It will also be helpful for codesplitting/treeshaking steps discussed in #111 since the icons become components that are "imported" rather than "loaded".

This has been fixed now in the latest 3.1.0 release.


Integrate WASI test suite

Add wasi-testsuite to set of tests executed from test_wamr.sh.
Additional description here: #1761

What's missing in the PR (I'll resume the work after I return from vacation, but I pushed the change to get some feedback):

is the return 0 here actually needed? I commented it out and ran the spec test in GitHub actions and they succeed without that part; I asked already in #1377
one test fails right now, I need to look into it

I don't think the PR has anything to do with wasi threads, could you change the destination branch to main?

LGTM


Gas energy consumption not recording in HA

See https://github.com/home-assistant/core/issues/63393

See https://github.com/home-assistant/core/issues/59015

Resolved after completely recreating the HA DB.


Support for permitted_attributes

Hey, thanks for the gem, I've been using it on a project and am really enjoying the design.
Wondering if you have any ideas about implementing pundit's permitted_attributes feature (https://github.com/elabs/pundit#strong-parameters) via a pundit-resources defined policy.

If I'm not mistaken, this would be as simple as something like this:
module PunditResource
  def self.updatable_fields(context)
    policy.permitted_attributes
  end

  def self.creatable_fields(context)
    policy.permitted_attributess
  end
end

JSONAPI::Resources already provides hooks for this exact purpose.  I'll send a PR in a couple weeks if I have a chance and nobody beats me to the punch


Increasing maximum number face count to 5000

Hi, thank you for providing the code to your MeshNet paper. I have been exploring the use of more detailed meshes and how well MeshNet performs when using meshes with maximum face count of 5000.
Currently, I am using MeshNet to distinguish between 2 categories of meshes that have been created using structure from motion photogrammetry: meshes that have carvings, and meshes that do not have carvings. Since the subject matter is of faint prehistoric carvings on stones, I believe I need to increase the face count to improve the amount of detail given to MeshNet.
Do you have any advice on what I should do, such as changing parameters or some of your code to improve the accuracy of training and testing of these 5k face meshes? Currently, the accuracy I am getting when applying MeshNet to my data is very low. I am rather new to neural networks.
I have attached an example of a carving and an example of areas without carvings (flat).
carving_meshes.zip
Thank you for your help!

Thanks for your interest on our work!
I have seen the provided examples and the difference between two categories seems to be quite small, making it a difficult task. MeshNet may not be suitable for this task, since it focus on the obvious structural features of models. In my opinion, you could try some methods from computer graphics, such as curvature calculation, or get the 2D depth map for classification, which may be better for capturing the slight changes of the surface.

The visulization of curvature:


🐛 Bug Report: query documents on bool false does not work

👟 Reproduction steps

Create Collection
Create Document with bool "isActive", default
Create sample data with "isActive" = false
Get list via apple sdk

func loadData( offset: Int?, filter: Filter, completion: @escaping(Data]) -> ()) {                 Database(client).listDocuments(                     collectionId: collectionId,                     queries: filter.getQuery(), // isActive.equal(false)                     limit: 25,                     offset: 0                 ) { result in                     switch result {                     case .failure(let error):                         print(error.message)                     case .success(let documentList):                         print(documentList)                    }         }     }
Note: if i set isActive=true in the query i get data
👍 Expected behavior
Return data
👎 Actual Behavior
returns no data
🎲 Appwrite version
Version 0.10.x
💻 Operating system
MacOS
🧱 Your Environment
local docker instance in my mac
👀 Have you spent some time to check if this issue has been raised before?

[X] I checked and didn't find similar issue

🏢 Have you read the Code of Conduct?

[X] I have read the Code of Conduct

Not a SDK Problem. Closed.
More here:
Bug Report: Default value for bool attribute is not set properly if added later to document #2768


Admin - Integrate API to Create Admin

UI was created here: https://github.com/mestafrica/mobile-wallet-fraud-database/issues/97
Reference Create Admin API: https://www.loom.com/share/8d81a259d8be45e3a52860772c349d60?sid=cfa58701-1e56-4010-b0d9-78a5c960fcdf

@muchinon Please I would like to work on this


Add mobile vitals screen to sample

What does this PR do?
Support US5 endpoints

Codecov Report

Merging #697 (8dc5627) into master (e64121f) will increase coverage by 0.04%.
The diff coverage is 100.00%.

@@             Coverage Diff              @@
##             master     #697      +/-   ##
============================================
+ Coverage     88.63%   88.67%   +0.04%
- Complexity     1709     1710       +1
============================================
  Files           189      189
  Lines          5645     5648       +3
  Branches        695      695
============================================
+ Hits           5003     5008       +5
+ Misses          407      402       -5
- Partials        235      238       +3

Impacted Files
Coverage Δ

...main/kotlin/com/datadog/android/DatadogEndpoint.kt
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...src/main/kotlin/com/datadog/android/DatadogSite.kt
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...m/internal/domain/scope/ExternalResourceTimings.kt
67.65% <0.00%> (-11.76%)
:arrow_down:

...g/internal/domain/event/DdSpanToSpanEventMapper.kt
91.84% <0.00%> (-8.16%)
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83.02% <0.00%> (-5.66%)
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.../android/error/internal/DatadogExceptionHandler.kt
93.10% <0.00%> (-3.45%)
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...droid/rum/internal/domain/scope/RumSessionScope.kt
97.78% <0.00%> (ø)

...l/net/info/BroadcastReceiverNetworkInfoProvider.kt
79.17% <0.00%> (ø)

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... and 4 more