Thermostat need a struct value for current humidity.

[ ] Provide an option to set current humidity. (same as current room temperature)
[ ] Provide a function to update humidity on remote update from the device.

Please let me know if this feature to be supported.
I can try contribute as well, with your guidance.

If you need specific characteristics for an accessory, you can add them yourself. For example if you need the current humidity for a thermostat, you can create your custom thermostat service and add the humidity as a new property.
type CustomThermostat struct {
	*service.Thermostat

	CurrentHumidity *characteristic.CurrentRelativeHumidity
}

func NewCustomThermostat() *CustomThermostat {
	return &CustomThermostat{
		Thermostat:      service.NewThermostat(),
		CurrentHumidity: characteristic.NewCurrentRelativeHumidity(),
	}
}

func main() {
	info := accessory.Info{ Name: "Thermostat" }
	a := accessory.New(info, accessory.TypeThermostat)

	// Add your custom thermostat service
	thermostat := NewCustomThermostat()
	a.AddS(thermostat.S)

	// Update the relative humidity
	thermostat.CurrentHumidity.SetValue(60)
	...
}

@brutella - Thanks for the sample. It worked and you are awesome 👍🏼 😍


ci: fix doc workflow on schedule

Build phase was skipped, we were checking for file changes which will
not have any results on a scheduled event.
Signed-off-by: Anas Nashif<EMAIL_ADDRESS>

Thanks for the quick fix, @nashif! I would suggest taking this in as a hotfix since until this is merged, docs.zephyrproject.org is not properly being updated.

@kartben @nashif feel free to add hotfix if you want and press the button. Otherwise, we just wait 3 hours , in which @stephanosio can look at it

Actually, something does not seem right in this PR. What problem is this fixing?

Making sure that the job that runs every 3 hours always actually builds the docs no matter what (i.e. even if there is seemingly no change as per the changed-files filter), so that the "publish" job always has a fresh site/PDF to deploy.

builds the docs no matter what (i.e. even if there is seemingly no change as per the changed-files filter)

Why do we want to re-build and re-publish docs when there is no change?
As far as I understand, tj-actions/changed-files supports schedule event and compares the content of the current schedule event against the last triggered schedule event. Was there a problem with this?

Why do we want to re-build and re-publish docs when there is no change?

because this is the original behaviour. We never did scheduled CI based on the files being changed. I prefer thas instead of trusting the files we list there which might become out of date for whatever reason. Let's just continue as before, aside from that, this actually has some real fixes to the workflow and dependencies.

because this is the original behaviour. We never did scheduled CI based on the files being changed. I prefer thas instead of trusting the files we list there which might become out of date for whatever reason. Let's just continue as before, aside from that, this actually has some real fixes to the workflow and dependencies.

Fair enough. While change-based triggering is nice way to optimise CI usage and reduce cost, HTML doc build only takes around 15 minutes and the associated cost is rather insignificant.


Taking Too Much CPU and Memory (RAM) on CPU

@NathanUA Thank you very much for such a good contribution.I am using the u2netp model which is 4.7 mb size
for inferences on the webcam video feed. I am running it on my CPU device but it is taking too much memory and processing power of CPU Device .My Device get slower while doing testing , Can you help me how I can make it memory efficient so I can use in CPU machine.Thank you

when you inference on images, how much ram does it use

when you inference on images, how much ram does it use

I am facing same issue.
Any suggestions ?


Add a shortcut to paste nodes as sibling of the selected node

This makes quick pasting jobs easier when you don't want a heavily nested structure, by pressing Ctrl + Shift + V (Cmd + Shift + V on macOS) instead of Ctrl + V (Cmd + V on macOS).
If you select the root node and use Paste as Sibling, it'll behave like Paste.

This closes https://github.com/godotengine/godot-proposals/discussions/6976.

Preview
https://github.com/godotengine/godot/assets/180032/efd07701-1d82-4d65-b27e-7450397b9508

Thanks!

On Debian this works the same as ordinary paste "Ctrl+V" from context menu.


Init catkin workspace only if it doesn't already exist

Previously, "hot-starting" the docker devcontainer failed due to an error in entrypoint.sh, which stopped the container early. This resulted in vscode being unable to load the workspace.
This PR should fix the bug that caused entrypoint.sh to fail, by checking if a CMakeLists.txt exists and only calling catkin_init_workspace if it doesn't. Thus IDE start-up time will be greatly reduced.
@sunny-5555 @Braafisch To apply this change on your local system please rebuild the container once (Ctrl + P > >Remote-Containers: Rebuild Container).

@sunny-5555, in the future you can use >Remote-Containers: Reopen in Container, which will be much faster than ... Rebuild and Reopen ....


Update license to match other Plotly projects

Updates the license to match other OSS Plotly projects.
@igiagkiozis let me know if you have any comments on this!

@igiagkiozis sending a quick poke -- let me know if you have any comments or concerns! Want to merge this in for the next release.

Going ahead with merging this PR to unblock you @andrei-ng -- @igiagkiozis if you do have any concerns don't hesitate to shoot me an email.


0.0.3 doesn't work with latest tornado (6.0.0)

'Tornado' released '6.0.0' on 01/03/2019, making 'jupyter_http_over_ws' raising an ImportError when invoking:
jupyter serverextension enable --py jupyter_http_over_ws
https://github.com/tornadoweb/tornado/issues/2383
 File "<site-packages\jupyter_http_over_ws\handlers.py", line 28, in <module>
    from tornado import stack_context
ImportError: cannot import name 'stack_context'

Using tornado==5.1 makes it work.

Thanks for the report! We'll work on tweaking setup.py accordingly.
Internal tracking: b/127337807

For now, we've restricted our setup.py to only install Tornado versions <6. You should be able to update your extension by running the following command:
pip install --upgrade jupyter_http_over_ws
Note that running the command will also downgrade your installed version of Tornado. Marking this as fixed, but please do reopen if you still encounter problems.


Upd dependecies

Issue #, if available: N/A
Description of changes:
Update all deps according to dependabot.
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.

AWS CodeBuild CI Report

CodeBuild project: GitHubCodeBuild8756EF16-pDO66x4b9gEu
Commit ID: 1acb0229f51f1c85aeaf466f0528a06e20c08b9f
Result: SUCCEEDED
Build Logs (available for 30 days)

Powered by github-codebuild-logs, available on the AWS Serverless Application Repository


Android Remote Control Options

Describe the bug
When the app using react-native-track-player runs on Android, the notification center (Notification Center and Control Center in Xiaomi devices on MIUI 12) becomes laggy. It appears to me that the player tries to open something in the notification center but fails and retries over and over.
I checked my app info in the setting and I saw the following:

I believe there's a problem in managing the remote control options in Android. I have no idea what is happening on the project's Android side since I'm a react-native developer but it seems that it's trying to send the meta info and control options of the music as a notification, which causes serious performance issues.
To Reproduce
Init an application using react-native-track-player as the player and set remote control options according to the documentation. Try to open the notification center while the app is running.
Environment
Run react-native info in your project and share the content:

What react-native-track-player version are you using?
v2
Are you testing on a real device or in the simulator? Which OS version are you running?
I faced this issue while testing on various android devices:

Xiaomi a2 lite running Android 10
Xiaomi redmi note8 pro running Android 10
Sumsung A31 running Android 10

Code
This is how I have initialized my player:
function NewPlayer() {
 const events = [
   Event.PlaybackTrackChanged,
   Event.PlaybackQueueEnded,
   Event.PlaybackError,
   Event.RemotePause,
   Event.RemoteNext,
   Event.RemotePrevious,
   Event.RemotePlay,
   Event.RemotePause,
   Event.RemoteStop,
   Event.RemoteSeek,
   Event.RemoteDuck,
 ];
 useTrackPlayerEvents(events, event => {
   switch (event.type) {
     case Event.RemoteDuck:
       pauseSong();
       break;
     case Event.PlaybackError:
       console.warn(
         'An error occured while playing the current track.',
         event,
       );
       break;
     case Event.RemoteNext:
       playNextSong();
       break;
     case Event.RemotePrevious:
       playPrevSong();
       break;
     case Event.RemotePlay:
       playSong();
       break;
     case Event.RemotePause:
       pauseSong();
       break;
     case Event.RemoteStop:
       pauseSong();
       break;
     case Event.RemoteSeek:
       TrackPlayer.seekTo(event.position);
       break;
     default:
   }
 });

 useEffect(() => {
   // Initialize
   TrackPlayer.setupPlayer({
     iosCategory: IOSCategory.Playback,
     // iosCategoryOptions:
     iosCategoryMode: IOSCategoryMode.Default,
   });
   TrackPlayer.updateOptions({
     stopWithApp: true,
     capabilities: [
       Capability.Play,
       Capability.Pause,
       Capability.SkipToNext,
       Capability.SkipToPrevious,
       Capability.Stop,
       Capability.SeekTo,
     ],
     compactCapabilities: [Capability.Play, Capability.Pause],
   });
 }, []);
 return null;
}

I'm using react-navigation v5 and my player is instantiated in the root of the project:
<Provider store={store}>
     <PersistGate persistor={persistor}>
       <SafeAreaProvider>
         <StatusBar barStyle="light-content" />
         <RootStack authContext={authContext} />
         <NewPlayer />
       </SafeAreaProvider>
     </PersistGate>
</Provider>

Dear @ZahraKhanjani, I have faced the same issue, if you find the solution please mention me. thanks 🌹 .

Could you run adb logcat and see if there is anything in the logs?


How to train the model in the ucf-101 dataset

Code version (Git Hash) and PyTorch version
Dataset used
Expected behavior
Actual behavior
Steps to reproduce the behavior
Other comment
@yjxiong  hello ,I'll say sorry if I disturb you,
I want to know how to extract the original dataset into the skeleton data set suitable for network training and train my own model, such as ucf101 dataset.

@anjingxing
Firstly, do you have skeleton data for your ucf1010 dataset? If you have not and if you have image sequence or videos for your original dataset, you can extract skeleton data using demo.py in their folder. Because you need to use OpenPose to extract skeleton data like kinetics-skeleton form.

Hi I am a student from ucf we can cooperate if you want!

@anjingxing
Firstly, do you have skeleton data for your ucf1010 dataset? If you have not and if you have image sequence or videos for your original dataset, you can extract skeleton data using demo.py in their folder. Because you need to use OpenPose to extract skeleton data like kinetics-skeleton form.

Hi! I want to know how to extract skeleton data like kinetics-skeleton form. I didn't find the file demo.py. Now I have installed openpose, st-gcn and mmskeleton. I am trying to train my own model and run a demo.


check H2O_WAVE_APP_ADDRESS env var before scanning free port

fixes https://github.com/h2oai/wave/issues/936

Dear Wave Team .. this one will also get your documentation in line with the implementation. In your documentation https://wave.h2o.ai/docs/configuration you mention that one can use "H2O_WAVE_APP_ADDRESS" to overwrite the address .. but your code at https://github.com/h2oai/wave/blob/master/py/h2o_wave/cli.py#L64 doesn't even look at that variable and just overwrites it with localhost and open port found ..  dos.environ['H2O_WAVE_APP_ADDRESS'] = addr


PYPI readme fix and publish coverage to Codecov

TL;DR
This PR fixes 2 problems

Ensure that the PYPI page is correctly formatted
Ensures that a code coverage report is published for Flytekit

Type

[x] Bug Fix
[x] Feature
[ ] Plugin

Are all requirements met?

[x] Code completed
[x] Smoke tested
[x] Unit tests added
[x] Code documentation added
[x] Any pending items have an associated Issue

Complete description
How did you fix the bug, make the feature etc. Link to any design docs etc
Tracking Issue
https://github.com/lyft/flyte/issues/258
Follow-up issue
NA

Codecov Report

:exclamation: No coverage uploaded for pull request base (master@bf3bd0a). Click here to learn what that means.
The diff coverage is n/a.

@@            Coverage Diff            @@
##             master     #102   +/-   ##
=========================================
  Coverage          ?   82.40%
=========================================
  Files             ?      206
  Lines             ?    13194
  Branches          ?     1095
=========================================
  Hits              ?    10872
  Misses            ?     2060
  Partials          ?      262

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 bf3bd0a...775a255. Read the comment docs.


Strategy: PNG-AVAX

Vault: 0xEDAF873002c512C47d6688985C7DC4D64A629697
Strategy: 0xa7531bFE23796ba6cE5192Ecd3889A337B44dE21
Want: 0xd7538cABBf8605BdE1f4901B47B8D42c61DE0367

Why did you change harvest(address callFeeReciepient)? Let's keep it consistent with the other contracts.

@MirthFutures I didn't, I just forked the existing Common MiniChef contract for all of these vaults with the exception of the single stake PNG vault (which needs redeploying as it is missing a harvest with a different call fee address function).
As far as I can see, the harvest callFeeRecipient stuff was added in the following PR to all the Common Strat contracts almost 4 months ago (https://github.com/beefyfinance/beefy-contracts/pull/107) and from doing a quick search in the beefy-contracts repo is now in fairly widespread use across 26 different strategy files. Given this is it still necessary to redeploy all of the Pangolin contracts again?

Closing this merge request to merge it in with the wider PangolinV2 work.


Adding instructions to help users visualise Open WebUI

Pull Request Checklist

[ x] **Description:Adding instructions to help users who are not familiar with Docker, and would struggle to visualise the interface of Open WebUI. Briefly describe the changes in this pull request.
[x ] Changelog: Ensure a changelog entry following the format of Keep a Changelog is added at the bottom of the PR description.
[ x] Documentation: Have you updated relevant documentation?
[x ] Dependencies: Are there any new dependencies? Have you updated the dependency versions in the documentation?

Description
[Insert a brief description of the changes made in this pull request]

Changelog Entry
Added

[List any new features or additions]

Fixed

[List any fixes or corrections]

Changed

[List any changes or updates]

Removed

[List any removed features or files]

Feel free to make a PR here: https://github.com/open-webui/docs Thanks!

Feel free to make a PR here: https://github.com/open-webui/docs Thanks!

Thanks for getting back @tjbck sure, I have opened a new PR on the docs : https://github.com/open-webui/docs/pull/35 please let me know if any issues and happy to collaborate further :)


Menu icon should be changed to move icon

Menu icons in the following GIF, refers to confusion that makes it hard to understand its purpose. To solve this issue, it needs to be changed to move icon.

Originally posted by @seahindeniz in https://github.com/seahindeniz/BrainlyTools_Extension/issues/127#issuecomment-626220757

After replacement


Please state why time recording is disabled for some service orders.

I came to this page to find out why Time recording is disabled (greyed out) for most of the service orders in my USMF demo system. However, the help page does not state what conditions must be true for the system to allow Time recording.

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

ID: e989513f-414e-c8f4-b8d1-67fd30cf7ea9
Version Independent ID: 1b130592-bb2d-7368-0d32-07d5cdeb2a00
Content: Start and stop time recording on a service order - Supply Chain Management | Dynamics 365
Content Source: articles/supply-chain/service-management/start-and-stop-time-recording-on-a-service-order.md
Service: dynamics-365-supply-chain
Product: ****
Technology: ****
GitHub Login: @sorenva
Microsoft Alias: sorenand

From my investigation, it seems that Time recording was disabled because the service orders had no Service level agreement.


pycromanager on wsl2 with micromanager 2.0 on windows 10

Just wondering if its possible to use pycromanager running on linux kernel with wsl2 while micromanger runs on windows 10?
I would like to use tensorflow 2.15 (so that I can use keras_cv package which requires tf 2.11 or higher) with gpu support and this is only possible on windows 10 with WLS2 because native windows has gpu support on tf 2.10 or lower.

After thinking about it for a moment, I would make the point that since Micro-Manager exposes a server one could connect to it - and with WSL2 you can still inspect Windows paths so it should be doable.
I'll give it a try.

I think this actually should work. You'd need to as you say run MM on the windows machine, then only run pycromanager on WSL. The key is that you'll need to forward ports from the windows machine to the linux machine (at least port 4827 for basic control of the core, additional ones depending on what features you're using).
I don't know exactly how to do this port forwarding, but it seems like its possible


Modified version from Kairos

Your Python wrapper for Kairos is very well done.  In response to one of our customers, I simplified some of the methods, and added remove_gallery, detect, and verify.  The README file has been updated, but the tests have not.

Sorry for taking so long to review this, I didn't notice my email notifications for PRs were not activated.
The changes look fine to me. I'll take some time eventually to update the test suite.


deprecation findDOMNode in React.StrictMode prevents edit

Ref: #3801
When React is run in strict mode the diagrams are not editable.
Reproduce:
Change harness/src/index.js to
  <React.StrictMode>
    <HashRouter>
      <IntlProvider locale='en'>
        <div>
          <Route exact path='/' component={App} />
          <Route exact path='/app-small' component={AppSmall} />
          <Route exact path='/app-tiny' component={AppTiny} />
          <Route path='/properties' component={CommonPropertiesComponents} />
          <Route path='/conditions' component={CommonPropertiesConditions} />
        </div>
      </IntlProvider>
    </HashRouter>
  </React.StrictMode>

Note none of the diagrams are editable and the console output
Warning: findDOMNode is deprecated in StrictMode. findDOMNode was passed an instance of ResizeDetector which is inside StrictMode. Instead, add a ref directly to the element you want to reference. Learn more about using refs safely here: https://reactjs.org/link/strict-mode-find-node
    at div
    at ResizeDetector (http://localhost:3001/js/canvasharness.js:166142:28)
    at Toolbar (http://localhost:3001/js/canvasharness.js:380154:86)
    at div
    at CommonCanvasToolbar (http://localhost:3001/js/canvasharness.js:305503:86)
    at injectIntl(CommonCanvasToolbar)
    at ConnectFunction (http://localhost:3001/js/canvasharness.js:493784:68)
    at div
    at div
    at div
    at CommonCanvasCentralItems (http://localhost:3001/js/canvasharness.js:303454:86)
    at ConnectFunction (http://localhost:3001/js/canvasharness.js:493784:68)
    at Provider (http://localhost:3001/js/canvasharness.js:493495:20)
    at CommonCanvas (http://localhost:3001/js/canvasharness.js:307885:86)
    at injectIntl(CommonCanvas)
    at IntlProvider (http://localhost:3001/js/canvasharness.js:492926:47)
    at div
    at App (http://localhost:3001/js/canvasharness.js:385109:86)
    at Route (http://localhost:3001/js/canvasharness.js:496974:29)
    at div
    at IntlProvider (http://localhost:3001/js/canvasharness.js:492926:47)
    at Router (http://localhost:3001/js/canvasharness.js:496603:30)
    at HashRouter (http://localhost:3001/js/canvasharness.js:496256:35)

Warnings have been fixed. Other issues recorded in issue 3801 so closing this one


Increase Length of Meta Title Tags

The current Meta Titles for the pages are around 22 characters.
However, the range is 20-70.
It is suggested that we make it longer and put in key words where possible.
https://www.woorank.com/en/www/chasemanning.co.nz

Title Tag Update to Freelance Developer | Chase Manning | Websites & Mobile


Keep track of protein structure coordinates

It would be nice to reuse the same protein view coordinates so that you can download protein image positioned the same way for different mAbs.

In the most recent version of the tool, the protein's position, scale, and orientation will not change unless an different PDB file is loaded in. So, if you're using a file with multiple antibodies and the same structure, the coordinates will be preserved for each antibody.


Getting only the n latest posts

Provide us a use case of the feature
There's no way to get only the latest, or the n latest posts from a profile. The way to go seems to be calling profile.get_posts() and getting the first value but that's really inefficient when you only want a few.

Whoops didn't realize it was iterable and I can exit in the first loop. Sorry for bothering!


FEAT: Added rancher ha command

This PR contains:

New rancher rke command that integrate rke in cli

# rancher rke -h
Rancher Kubernetes Engine, Running k8s cluster everywhere

Usage:
   rancher rke command [command options] [arguments...]

Commands:
     up       Bring the cluster up
     remove   Teardown the cluster and clean cluster nodes
     version  Show cluster Kubernetes version
     config   Setup cluster configuration
     etcd     etcd snapshot save/restore operations in k8s cluster

Options:
   --help, -h  show help

New rancher ha command

# rancher ha -h
Create Rancher HA minimal template and deployment files to rke and k8s
Create Rancher HA template and deployment manifest for rke and k8s.
Usage:
   rancher ha command [command options] [arguments...]

Commands:
     template  Create Rancher HA minimal template
     up        Up new RKE cluster from Rancher HA template

Options:
   --help, -h  show help

New rancher ha template subcommand to generate minimal cattle HA template.

# rancher ha template -h
Create Rancher HA minimal template
Create Rancher HA minimal template to be used by rancher ha up command or get k8s deployment manifest.

Output modes:
- rke: Generate Rancher HA minimal template. Add rke nodes info and use it with rancher ha up command to deploy your rke cluster.
- k8s: Generate Rancher HA template and k8s deployment manifest. Use manifest with kubectl to deploy it in your k8s cluster.

TLS modes:
- ingress: Ingress as SSL termination. Configure Rancher HA deployment to use user provided TLS certs.
  tls-key and tls-cert are required. tls-ca is required if selfsigned certs are used. Certs must be valid for hostname param.
- rancher: Rancher as SSL termination. Configure Rancher HA deployment to auto generate TLS certs. Just for rke output-mode.
- external: External LB as SSL termination. Configure Rancher HA deployment don't use TLS certs.

TLS issuer for TLS mode ingress:
- acme: Configure Rancher HA deployment to use letsencrypt TLS certs.
- ca: Configure Rancher HA deployment to use CA issuer to manage TLS certs.

Usage:
  rancher ha template [OPTIONS] -f <rancher_HA_template> --hostname <FQDN> --tls-key <KEY_FILE> --tls-cert <CERT_FILE> --tls-ca <CA_FILE> ...

Options:
   --hostname FQDN          FQDN to access rancher. Required
   --replicas NUMBER        Rancher deployment replicas NUMBER (default: 1)
   --image IMAGE            Rancher docker image to deploy IMAGE (default: "rancher/rancher:latest")
   --file FILE, -f FILE     Save Rancher HA template to a yaml FILE (default: "rancher_HA.yml")
   --namespace NAMESPACE    Namespace to deploy Rancher HA NAMESPACE (default: "cattle-system")
   --output-mode MODE       Output MODE, [ rke | k8s ]. k8s mode generate deployment manifest. (default: "rke")
   --output FILE, -o FILE   Save Rancher HA deployment FILE, just for k8s output-mode. Default value 'k8s_ingress_file'
   --tls-mode MODE          TLS MODE, [ ingress | rancher | external ] (default: "ingress")
   --tls-cert FILE          TLS cert FILE to use with rancher. Required for TLS mode ingressif TLS issuer none
   --tls-key FILE           TLS key FILE to use with rancher. Required for TLS mode ingressif TLS issuer none
   --tls-ca-cert FILE       TLS ca certs FILE to use with rancher. Required for TLS mode ingressif TLS issuer ca
   --tls-ca-key FILE        TLS ca key FILE to use with tls-issuer ca. Required for TLS issuer ca
   --tls-provider PROVIDER  TLS cert PROVIDER, [ cert-manager ]. Valid on TLS mode ingress (default: "cert-manager")
   --tls-issuer ISSUER      TLS cert ISSUER, [ ca | acme ] managed by tls-manager. Valid on TLS mode ingress
   --tls-issuer-default     Set tls-issuer as default cert issuer. Change ingress default cert on output-mode rke. Valid on TLS mode ingress
   --tls-acme-email EMAIL   Email address EMAIL to use with tls-issuer acme. Required for TLS issuer acme
   --tls-acme-prod          tls-issuer acme production enviroment. Staging if false. Used for TLS issuer acme

New rancher ha up subcommand to up rke cluster with cattle HA as addon.

# rancher ha up -h
Up new RKE cluster from Rancher HA template

Usage:
  rancher ha up [OPTIONS] -f <cattle_HA_template> ...

Options:
   --file FILE, -f FILE    Read Rancher HA minimal template from FILE (default: "rancher_HA.yml")
   --output FILE, -o FILE  Save Rancher HA deployment FILE. Default value 'output-mode_tls-mode_file'
   --preview, -p           Preview mode. Just generate Rancher HA template don't up cluster

3 TLS modes:

ingress: Ingress as SSL termination. Configure Rancher HA deployment to use user provided TLS certs.

Integrated with cert-manager CA issuer. Autogenerated certs and default ingress cert.
Integrated with cert-manager acme issuer.

rancher: Rancher as SSL termination. Configure Rancher HA deployment to auto generate TLS certs. Just for rke output-mode.
external: External LB as SSL termination.

Updated vendor.conf

How to deploy rancher in HA with this command:

Requirements:

rke v0.1.6 in OS path.
nodes to deploy cluster.
FQDN for rancher ui pointing to rke cluster nodes.
If SSL mode self: key, cert and cacert pem files.

Generate a minimal RKE cattle HA template.
rancher ha template -f rancher_HA.yml
Edit minimal RKE cattle HA template rancher_HA.yml

Setup nodes configuration for RKE cluster.
For RKE HA minimal of 3 nodes are required. rancher ha up command will let you deploy with just one node, but a WARNING is showed.
Optionally, any other RKE config object could be added.
Setup cattle HA configuration.

FQDN for rancher ui.
image if needed.
SSL mode, that could be passthrough | self.

# Minimal RKE Cattle HA template
# rke v0.1.6 is required to be set in your path
# Download from https://github.com/rancher/rke/releases
# Setup nodes configuration. 3 nodes required for RKE HA.
nodes:
- address: <IP>
  role:
  - controlplane
  - etcd
  - worker
  user: <USER>
  ssh_key_path: <PEM_FILE>  # Optionally ssh_key: <PEM_KEY> could be used
#
# Optionally, any other RKE config object could be added here.
#
# Setup cattle configuration.
# SSL mode could be 'passthrough' or 'self' to configure ingress controller.
# SSL 'passthrough' mode:
#   could remove rest of fields.
# SSL 'self' mode:
#   key_path, cert_path and ca_path are mandatory.
#   ingress_key_path and ingress_cert_path are optional. If empty, key_path and cert_path values are used.
cattle:
  fqdn: '<FQDN> # FQDN used for cattle'
  image: rancher/rancher:v2.0.0
  ssl:
    mode: < passthrough | self >
    key_path: '<CATTLE_KEY_PEM_FILE> # SSL key path to cattle.'
    cert_path: '<CATTLE_CERT_PEM_FILE> # SSL cert path to cattle..'
    ca_path: '<CA_PEM_FILE> # SSL cacert path to cattle.'
    ingress_key_path: '<INGRESS_KEY_PEM_FILE> # SSL key path to ingress.'
    ingress_cert_path: '<INGRESS_CERT_PEM_FILE> # SSL cert path to ingress.'

Once template is edited, up rke cluster
rancher ha up -f rancher_HA.yml -o RKE_rancher_HA.yml

Based on rancher_HA.yml, RKE template RKE_rancher_HA.yml with rancher configured as addon, will be generated.
Using RKE_rancher_HA.yml RKE cluster will up.

If execution goes fine, kube_config_RKE_rancher_HA.yml will be generated for kubectl connection to the RKE cluster.
By default cattle deployment is configured with 1 replica. To get real HA, scale it up to desired instances number N would be needed.
kubectl -n cattle-system scale —replicas=<N> deployment/cattle
RKE cluster will publish rancher UI by ingress-controller on all running nodes and host FQDN. Rancher UI should be available at https://FQDN

Added --no-cacerts param to rancher server on tls-mode external with public CA. Solve https://github.com/rancher/rancher/issues/11388
Commented out until https://github.com/rancher/rancher/pull/13423 is merged

Big PR! I assume we don't want to move forward with this.


fix: handle undefined namedType for introspection

Description
This PR handles instances where the namedType is undefined and prevents it from being passed to the isIntrospectionType function which would result in a crash as outlined in  #8389
Type of change
Please delete options that are not relevant.

[x] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] This change requires a documentation update

How Has This Been Tested?
I've ran and ensured that the existing tests pass
Test Environment:

Operating System: Linux
Node Version:     v14.19.1
Package Manager<EMAIL_ADDRESS>
Checklist:

[x] I have followed the CONTRIBUTING doc and the style guidelines of this project
[x] I have performed a self-review of my own code
[ ] I have commented my code, particularly in hard-to-understand areas
[ ] I have made corresponding changes to the documentation
[x] My changes generate no new warnings
[ ] I have added tests that prove my fix is effective or that my feature works
[x] New and existing unit tests pass locally with my changes
[ ] Any dependent changes have been merged and published in downstream modules

This PR handles instances where the namedType is undefined and prevents it from being passed to the isIntrospectionType function which would result in a crash as outlined in #8389

Hi @Diizzayy,
Could you provide an example of reproduction for this bug?

Could you provide an example of reproduction for this bug?

@charlypoly Thank you for getting back to me on this, the linked issue #8389 provides a reproduction at that demonstrates this bug https://github.com/Diizzayy/cgenbug


Error when running evaluation step

Hi,
I'm following the NMT tutorial (medium) with my data. The model trains fine but crashes when reaches the eval step. Error:

InvalidArgumentError (see above for traceback): logits and labels must have the same first dimension, got logits shape [1120,69999] and labels shape [1568]
         [[Node: model/att_seq2seq/cross_entropy_sequence_loss/SparseSoftmaxCrossEntropyWithLogits/SparseSoftmaxCrossEntropyWithLogits = SparseSoftmaxCrossEntropyWithLogits[T=DT_FLOAT, Tlabels=DT_INT64, _device="/job:localhost/replica:0/task:0/gpu:0"](model/att_seq2seq/cross_entropy_sequence_loss/SparseSoftmaxCrossEntropyWithLogits/Reshape, model/att_seq2seq/cross_entropy_sequence_loss/SparseSoftmaxCrossEntropyWithLogits/Reshape_1)]]
         [[Node: mean/broadcast_weights/assert_broadcastable/AssertGuard/switch_f/_282 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_1273_mean/broadcast_weights/assert_broadcastable/AssertGuard/switch_f", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

69999 is my vocab size (-1)

Duplicate #103


Update container-registry-faq.md

Add FAQ for pushing non-distributable/foreign layers to ACR

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

#sign-off


Removing SDL from Lengine executable

Remove sdl dependencies from Lengine executable. Have Lengine be more general, being able to load any plugin without prior linkage to any libraries (any unorthodox libraries at least). This is trivial for simple libraries that can simply be linked against the plugin itself, but with more complex libraries, such as sdl, it's tricky as they may hold internal states about various things.
One approach I came up with would be to have another plugin (call it config) that would hold all the linking information related to this tricky libraries, the user could then pass the path to this plugin as well and it would get loaded together with all the symbols. The difference of this config plugin is that it would only be closed when the executable is to be closed, avoiding losing any internal states. There could be a cool idea for letting the plugins manage this config plugin internally too, but that's for the future.

fixed this issue by adding the possibility of passing a "configuration object" path to Lengine, which then loads it into the shared channel. This way the plugins can use the handle of this configuration object instance to get special symbols, as the configuration object does not get unloaded until all programs shutdown, or is closed internally by one of the plugins, the problem seems fixed. Performance and memory may not be optimal though... Oh well


unable to select item from sap.ui.commons.DropdownBox

OpenUI5 version: 1.32.x, 1.34.x
Browser/version (+device/version): Only on Chrome mostly from version 50+
Any other tested browsers/devices(OK/FAIL): IE 11, Edge, Firefox
URL (minimal example if possible):
User/password (if required and possible - do not post any confidential information here):
Steps to reproduce the problem:

Create an instance of sap.ui.commons.DropdownBox with 20 entries with a default value of *
Click the down arrow button and scroll down to select a list item

What is the expected result?
The item should be selected and popup closed
What happens instead?
Popup stays and does not select the item
Any other information? (attach screenshot if possible)

Any update on this ?

Hi @prospectatech ,
The versions 1.32.x, 1.34.x are out of maintenance. The sap.commons library is also deprecated. I'm recommending to upgrade to 1.44. You should use sap.m library and in this case use sap.m.ComboBox instead of sap.ui.commons.DropdownBox. See the reference .
Kind regards,
Diana

Hi @Shtilianova ,
Thanks for the update. At this point we cannot upgrade to 1.44 due to the amount of testing required in our application. Is there a way to debug this issue and provide a solution which we can implement in our project ?
Regards,
Prospecta Tech

Hi @prospectatech ,
I understand but this version and library are out of maintenance, sorry that I can't help you more. I can only recommend you to upgrade when it's possible. I'm sure that you will see the benefits of using our new sap.m. liblary.
Regards,
Diana


fix(detect-secrets): pin detect secrets version

Changes

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#786  👈
#781
main

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ansible: Set empty array by default in kubernetes master role if tasks skipped

Fix for https://github.com/kubernetes/contrib/issues/2026

This change is

@ingvagabund pushed updated commit. ptal

@mkumatag LGTM, thanks.


Usage of breakpoints and loop together leads to hydration mismatch in SSR (Vite/Vue3/Swiper)

Check that this is really a bug

[X] I confirm

Reproduction link
https://stackblitz.com/edit/vite-vue3-ssr-swiper-mismatch?file=src/App.vue
Bug description
The combined use of breakpoints & loop in SSR project leads to hydration mismatch between Server and Client:

When using only breakpoints without loop it works fine.
When using only loop without breakpoints it works fine.
Using both together ends in hydration mismatch.
See reproduction link: https://stackblitz.com/edit/vite-vue3-ssr-swiper-mismatch?file=src/App.vue (check dev tools console)
Setup: vite, vue3, swiper
Expected Behavior
No hydration mismatches
Actual Behavior
Getting hydration mismatches
Swiper version
^8.1.4
Platform/Target and Browser Versions
MacOs, Google Chrome Version 100.0.4896.127 (Offizieller Build) (arm64)
Validations

[X] Follow our Code of Conduct
[X] Read the docs.
[X] Check that there isn't already an issue that request the same feature to avoid creating a duplicate.
[X] Make sure this is a Swiper issue and not a framework-specific issue

Would you like to open a PR for this bug?

[ ] I'm willing to open a PR

expected as it is impossible to detect browser window on SSR resulting in different amount of duplicated slides, use loopedSlides parameter or init it only on client side

I don't understand how to use loopedSlides, can you please explain?

works, thanks!

@nolimits4web how exactly should the logic of loopedSlides work? because when i use it, swipe back to left really is endless loop, but swipe to right is not. After some images the right button seems to be disabled, as there would be no more images on the right, even if set to loop. you can see what i mean on this stackblitz: https://stackblitz.com/edit/vite-vue3-ssr-swiper-playground?file=src/App.vue
slide to the right, until it stops. no endless loop to the right.
so to be honest i don't understand loopedSlides. Can you please explain me how it works and which behaviour i should expect?


Compile Typescript with babel

Typescript support came to Babel 7. Do you consider a possibility to choose typescript compiler? Using Babel only solves quite a lot of issues.

I think it'll be useless.
Babel isn't very fast compared to the TypeScript transpiler.

What if I do not care about the speed of the compilation, rather the robustness of the babel infrastructure?

@tomitrescak FuseBox care.
But, you can make a plugin :wink:

@tomitrescak transform() is only executed once.
You should try overloading the compiler.

@tomitrescak You need to take a look at File.ts all transpilation happens there!

I can see that u also bundle js with typescript. Rewriting this to Babel would be a gargantuan effort with meek benefits. I’ll check how much performance suffers using the Babel plugin, but knowing your caching system it will be marginal.


Fix potential bugs caused by delegation calculations

Fix potential bugs caused by delegation calculations

Is this fixed now, via the changes you'd make in https://github.com/oceanprotocol/df-py/pull/574 , @trizin ?

Closed because no issues found over many months. If issues pop up then we will create a new github issue.


Refactor Partitioner::Maven

Move the code that is sharable to Go Partitioner to DependencyAnalysis

This refactoring will help https://github.com/square/kochiku/pull/255.
cc: @robolson


What's MAX_DECIMAL_EXCEEDED_ERROR means?

Try searching the docs and API reference but can't find anything about this error response
I can guess from the message, but this one error caught us off-guard because there's nothing about it in the docs
And I'm a little bit worried if there's another edge cases that's not on the docs yet

Hi @vasilenka
Thank you for reaching us. We would like to inform you that MAX_DECIMAL_EXCEEDED_ERROR returned because we don't support decimal in IDR. We put a note on your suggestion to keep updated our api reference.
Thank you for the feedback and sorry for the inconvenience.
Regards,
Cindy Harum


Create partialuser.js

Using this argument will allow users to specify part of a username, along with all other types of identifying a user, including full username, full tag, user ID, and mention.
Works the same as Akairo's method of resolving users.

Just one random though, what does this have that the username argument doesn't?

You don't have to type the whole username; just part of it will do fine.

Not really, that one matches partial usernames too, it was part of an old version of a username search from my main bot, and served its purpose well.

Hey! What's your status, did the username argument work?

Closing due to lack of response. Feel free to re-open!


Quick Guide Install: Cannot Add host

ISSUE TYPE

Bug Report
Documentation Report

COMPONENT NAME

KVM Agent/Host

CLOUDSTACK VERSION

4.13 / Latest

CONFIGURATION

OS / ENVIRONMENT

CentOS Linux release 7.8.2003 (Core)
SUMMARY

STEPS TO REPRODUCE

Follow the quick install guide, add a kvm host as explained:

Quick install guide

EXPECTED RESULTS

Host should be added to the UI

ACTUAL RESULTS

The host addition process is failing. Looks like the Agent and Libvirtd cannot talk as per exception:

2020-04-29 12:25:32,753 ERROR [kvm.resource.LibvirtConnection] (AgentShutdownThread:null) (logid:) Connection with libvirtd is broken: invalid connection pointer in virConnectGetVersion

It also looks like my changes to /etc/libvirt/libvirt.conf are been wiped out each time I try to add the host.

I wonder if the quick install guide is up-to-date or the Agent is now trying to do the libvirt configuration itself.

Ok, I just noticed issue #3509
This seems to be the same thing I am experimenting. And there is a bunch of other users there.
I still have not worked out my problem but the consensus there seems to be that the error message "invalid connection pointer in virConnectGetVersion"... can be discarded

I can see that the agent is not capable to connect to libvirt
I can also see that the Agent confiruration has modified my network setup in ways that I did not expect or anticipate, has created a bridge on eth0 despite me having a dedicated interface for the cloud... that does not seem to be in use.
I guess my setup is not just like in the quick install guide, and also cloudstack is fairly intrusive in the network configuraiton. I need to better understand how it owrks. I leave this log in case anybody else finds the same situation.

Have you solve this problem

Have you solve this problem

Yes it is now working.
I think my problem was related to firewall. My firewall policy was to close all, and only add the rules specified in the documentation, but it was not enough, or there was conflict between my firewall rules and rules managed by the agent.
are you having this problem too?

Yes it is now working.
I think my problem was related to firewall. My firewall policy was to close all, and only add the rules specified in the documentation, but it was not enough, or there was conflict between my firewall rules and rules managed by the agent.
are you having this problem too?


Dedicate documentation info for observers

Overview
Add dedicated section in SA getting started to directly point people to more detailed setup and information
Changes

Fixes: #6881

Verification

As a reviewer, it is possible to check out this change locally by using the following
commands (substituting {PR_ID} with the ID of this pull request):
git fetch origin pull/{PR_ID}/head:name_of_local_branch
git checkout name_of_local_branch

/azp run mrtk_docs


NSF Funding Announcement

Adding announcement for NSF travel funding for the summer school, updated summer school page along with some rearranging (putting the most important/time sensitive information further up the page), and added necessary logos to img dir.

Woohoo thanks NSF! This is exciting. Merging to get the word out pronto! 🙂


Auth not working

Thanks for your work on this - I'm hoping to do some things that godaddy tech support can't help me with.
Following your sample code with my apikey/secret raised an exception:
In [1]: from godaddypy import Client, Account

In [2]: my_acct = Account(api_key='...', api_secret='...')

In [3]: client = Client(my_acct)

In [4]: client.get_domains()
---------------------------------------------------------------------------
HTTPError                                 Traceback (most recent call last)
~/anaconda/lib/python3.8/site-packages/godaddypy/client.py in _validate_response_success(response)
    104         try:
--> 105             response.raise_for_status()
    106         except Exception:

~/anaconda/lib/python3.8/site-packages/requests/models.py in raise_for_status(self)
    942         if http_error_msg:
--> 943             raise HTTPError(http_error_msg, response=self)
    944

HTTPError: 401 Client Error: Unauthorized for url: https://api.godaddy.com/v1/domains

During handling of the above exception, another exception occurred:

BadResponse                               Traceback (most recent call last)
<ipython-input-4-fe3d6858cad8> in <module>
----> 1 client.get_domains()

~/anaconda/lib/python3.8/site-packages/godaddypy/client.py in get_domains(self, **params)
    147         """
    148         url = self.API_TEMPLATE + self.DOMAINS
--> 149         data = self._get_json_from_response(url, params=params)
    150         domains = list()
    151         for item in data:

~/anaconda/lib/python3.8/site-packages/godaddypy/client.py in _get_json_from_response(self, url, json, **kwargs)
     73
     74     def _get_json_from_response(self, url, json=None, **kwargs):
---> 75         return self._request_submit(requests.get, url=url, json=json, **kwargs).json()
     76
     77     def _log_response_from_method(self, req_type, resp):

~/anaconda/lib/python3.8/site-packages/godaddypy/client.py in _request_submit(self, func, **kwargs)
     95         resp = func(headers=self._get_headers(), **kwargs)
     96         self._log_response_from_method(func.__name__, resp)
---> 97         self._validate_response_success(resp)
     98         return resp
     99

~/anaconda/lib/python3.8/site-packages/godaddypy/client.py in _validate_response_success(response)
    105             response.raise_for_status()
    106         except Exception:
--> 107             raise BadResponse(response.json())
    108
    109     def add_record(self, domain, record):

BadResponse: Response Data: {'code': 'UNABLE_TO_AUTHENTICATE', 'message': 'Unauthorized : Could not authenticate API key/secret'}

I'm sorry for not getting back to you sooner. This looks like an issue authenticating with your API key and secret. Unfortunately, these are issued via GoDaddy, and the library has no control over the validity of the credentials.
Hopefully, you were able to have resolved this before now.


Various Issues With Lichdom

https://github.com/Polarice3/Goety-2/blob/e39ea7d1fef5b987ab3aabce6b8103e5c74d321f/src/main/java/com/Polarice3/Goety/common/events/LichEvents.java#L93
getActiveEffects returns a collection that is still backed by the map, and removeEffectNoUpdate operates on the map, so this will CME as I just found out.
	at java.util.HashMap$HashIterator.nextNode(HashMap.java:1605) ~[?:?] {}
	at java.util.HashMap$ValueIterator.next(HashMap.java:1633) ~[?:?] {}
	at com.Polarice3.Goety.common.events.LichEvents.onPlayerLichdom(LichEvents.java:93) ~[Goety-2.3.3.jar%23494!/:2.3.3] {re:classloading}

Also it might not be a good idea to use removeEffectNoUpdate since it doesn't run cleanup on attribute modifiers or fire events, so a hypothetical zombie-immune effect that reduces an attribute will permanently lower it upon lichdom. This also includes soul hunger itself, so the player would be permanently stuck with reduced move/attack speed and damage.
As coded, iron golems will ignore invisibility and other mods that add stealth mechanics (like my own) to attack the lich, as well as ignore any potential follow range upgrades from other mods. getVisibilityPercent can be used to check whether the golem can see the player.
Lastly, this is a bit more of a selfish request, but my mod tags a few items (claws, gauntlets, gloves, and the like) from other mods as wardance:unarmed, which allows them to be used with unarmed techniques from my mod. It would be kind of neat if they could apply to lich's withering touch as well. Feel free to ignore this one though.
And just a small question, do arcas work across dimensions for revival and the like?

Thank you for informing me! I'll fix these issues right away! And that you for giving me tips on how to fix the issues, it's really appreciated. :) 👍

Oh yeah, forgot to answer your question. Yes, the Arca works across dimensions!

in retrospect it may be weird for one mod to depend on another's tags, so perhaps a tag like goety:lich_kiss_items that default to just minecraft:air would be more fitting.

Yeah, I just discovered a long time mistake when it comes to the Wither Touch. It's supposed to work if the player isn't holding anything and attack empty-handed, but currently it works if the player attacks even with items. Will use the tag as you suggested! Sounds like a good way to fix this bug!

Should all be fixed in 2.3.4 for 1.19.2 and 1.32.0 for 1.16.5!


update docker hub release notes

Updated Docker Hub Release Notes to add new images to untagged filters.  Also added corresponding API reference.

Thank you both! Looks good!


Add trace domian

Add trace domian

@andreasgerstmayr regarding this:

I'm curious, as the monitoring stack is moving towards COO and allowing users to deploy multiple monitoring stacks in the cluster, how are they discovered and utilized in korrel8r?
korrel8r can already be configured with multiple stores per domain, although currently it will use them all as one combined store. We'll need some work to give it a notion of different stores having different roles  (e.g. for multi-cluster)
The intent is that the COO will be responsible for knowing where everything is, and generating the correct korrel8r configuration. Korrel8r has limited ability to discover store locations at runtime - e.g. it can query the API server for a known route and extract the IP info to connect via that route. That's mostly useful for deveopment (e.g. allows dev to run korrel8r outside the cluster with a standard config) and probably it makes more sense to make the COO responsible for discovery than to try to elaborate what korrel8r can do.


Fix for #17168 issue

Now lastErr saves the errors returned from subsequent attempts from puller.Pull(), when trying to look for a image in same endpoint with different version (v2,v1,v0). The returned error value is appended to the lastErr, which is returned to the caller and in turn to the client. This would ensure the client gets the correct error messages and not only the most recent (v0) message during the pull request.
fixes https://github.com/docker/docker/issues/17168

I think this could be easier to understand if you used an slice to append error strings. That way you wouldn't need to check whether it's the first error or not every time. Something like this:
var errors []string // Initialize the errors
...
errors = append(errors, err.Error()) // When there is an error
...
if len(errors) > 0 { // At the end of the function
  return fmt.Error(strings.Join(errors, "\n"))
}
return nil

@calavera, thank you for input. I have incorporated suggested changes to use a slice, now the fix should reflect the changes.

Hi @RichardScothern: Now the fix is updated with a check to prevent fall back to V1,V0 on disk full error.

LGTM. @RichardScothern what do you think about this change?

Thanks @askb!
I edited the top comment to include fixes #17168

Is it possible to add a test?

@RichardScothern: imu not sure if there is a way add to the existing cli integration test for this fix presently as no quota support is available for the containers, therefore mostly requires running manual tests. The test itself this requires limiting the disk space either on the container or vm hosting the container, except for keeping around 100 blocks system reserved space free, which needs to configured tune2fs -r. Please let me any others ways to add a test case ? I would be happy to give it a go. Thanks

@askb we could add a test that is skipped if there is no quota suport on the test machine and thus be easy to test if there is support.. (using testRequire and co)

Hi @vdemeester testRequire is a good, wondering if there are some gaps in my understanding on how this can be implemented. Could we query a configuration file to determine if disk quotas for containers is available, something similar to what is done for IPv6 testRequirement ex: cmd := exec.Command("test", "-f", "/proc/net/if_inet6"). What flags or commands do we use to start or setup a container with disk quota, limiting the container to maybe 512MiB, this would be required in the caller or test function (in integration-cli/docker_cli_{*}_test.go). Thanks.

I'm not sure how feasible it is to add a test for running out of space...
Maybe we can create a small mount and point the daemon graph dir there?

@cpuguy83 I tried mounting a container into a loopback-fs, and faced some issues. I think this sounds good idea to point only the graph dir root into mount point, wihch avoids the need for doing a sync of the files from the container to the mount point. Will try it out and update here. Thanks

Looks like we would not be able to merge this PR because of merge conflicts. Please rebase, fix conflicts, and force push to your branch.

@cpuguy83, Now adding test for the fix #17168. The test creates a mount point, starts the daemon with the graph dir pointing to the mount and initiates a pull request. We should be able to check for the error message when the mount point gets filled during pull request. Thanks

LGTM

Thanks for your contribution!

:+1: Thanks for doing this. Sorry we've been silent during DockerCon!
Really good work on the test!


Explicitely disable access to /run/shm/lttng* for vms

vm is trying to access /run/shm/lttng* file which is denied by apparmor, and
thus apparmor was throwing the denied logs in high volume. Explicitely denying
this should stop logging the incident.
Also this patch add apparmor package and service management code

please test this

@sorenh Could you please review this?


Make Bioplastic meltable in smeltery?

From kane_thornwyrd (Stranded Strained modpack dev) here:

I even sometimes add new ways to get some stuffs, and in that context the possibility to smelt bio-plastic and cast it into other things.

Seems like it wouldn't hurt. Could even add potato starch -> melted bioplastic smelting recipe.

:smiley: I just hope it won't be too much of an hassle to implement it, for the time being, people interested in that kind of possibilities can use MineTweaker and ModTweaker to make Vegan Option, Tinker's Construct and MFR work together:
https://gist.github.com/kane-thornwyrd/a9e691a3857d73697269
Except that there is a weird bug with ModTweaker and TConstruct, the table recipes are well registered, but they just don't work, so, you may add something like this to be able to use the liquid plastic :
mods.tconstruct.Casting.addBasinRecipe(<MineFactoryReloaded:plastic>, <liquid:plastic> * 576, null, false, 20);

N.B. Plastic parts can still be made using the plastic made by smelting the starch in a furnace.
Note, that for now I've set the required temperature high to nerf the recipe a bit, ideally I would like a liquid starch registered, and use MineChem's Sodium Hydroxide and Hydrogen Chloride to register a new "alloy recipe" for liquid plastic and lower the required heat and materials for the whole process.
So basically, plastic made out of salt water, starch and energy :smile: .
At least an alternative to the rubber tree way.


Add mirror mode toggle during capture

Add a button to the capture page that let's you toggle between mirrored and non-mirrored. If we know that this is a front-facing camera, default to mirrored.

Done


Fix host with anonymous connection

I was actually making an attempt to use XMPP anonymous connection. And when trying to connect it seems to not sending a domain (host) to the XMPP server. So I fixed that.

Use a switch statement rather than a if-else chain

Thank you


Hotstart Video isnt downloading!

Checklist

[X] I'm reporting a broken site
[X] I've verified that I'm running yt-dlp version 2022.02.04. (update instructions)
[X] I've checked that all provided URLs are alive and playable in a browser
[X] I've checked that all URLs and arguments with special characters are properly quoted or escaped
[X] I've searched the bugtracker for similar issues including closed ones. DO NOT post duplicates
[X] I've read the guidelines for opening an issue
[X] I've read about sharing account credentials and I'm willing to share it if required

Region
India
Description
i am running it on my pc, Indian ip still facing issue.
Verbose log
[debug] Command-line config: ['https://www.hotstar.com/in/movies/dhruva/1000192697/watch?utm_source=gwa', '-vU']
[debug] Encodings: locale cp1252, fs utf-8, out utf-8, err utf-8, pref cp1252
[debug] yt-dlp version 2022.02.04 [c1653e9] (win_exe)
[debug] Python version 3.8.10 (CPython 64bit) - Windows-10-10.0.22000-SP0
[debug] exe versions: ffmpeg 2022-02-03-git-e1a14479a8-full_build-www.gyan.dev (setts), ffprobe 2022-02-03-git-e1a14479a8-full_build-www.gyan.dev, phantomjs 2.1.1
[debug] Optional libraries: Cryptodome, mutagen, sqlite, websockets
[debug] Proxy map: {}
Latest version: 2022.02.04, Current version: 2022.02.04
yt-dlp is up to date (2022.02.04)
[debug] [hotstar] Extracting URL: https://www.hotstar.com/in/movies/dhruva/1000192697/watch?utm_source=gwa
[hotstar]<PHONE_NUMBER>: Downloading JSON metadata
ERROR: [hotstar]<PHONE_NUMBER>: Unable to download JSON metadata: HTTP Error 475: Unknown (caused by <HTTPError 475: 'Unknown'>); please report this issue on  https://github.com/yt-dlp/yt-dlp , filling out the "Broken site" issue template properly. Confirm you are on the latest version using -U (caused by <HTTPError 475: 'Unknown'>); please report this issue on  https://github.com/yt-dlp/yt-dlp , filling out the "Broken site" issue template properly. Confirm you are on the latest version using -U
  File "yt_dlp\extractor\common.py", line 730, in _request_webpage
  File "yt_dlp\YoutubeDL.py", line 3558, in urlopen
  File "urllib\request.py", line 531, in open
  File "urllib\request.py", line 640, in http_response
  File "urllib\request.py", line 569, in error
  File "urllib\request.py", line 502, in _call_chain
  File "urllib\request.py", line 649, in http_error_default

[debug] Command-line config: ['-F', '--list-subs', '-v', 'https://www.hotstar.com/in/movies/dhruva/1000192697/watch?utm_source=gwa']
[debug] Encodings: locale cp1252, fs utf-8, out utf-8, err utf-8, pref cp1252
[debug] yt-dlp version 2022.02.04 [c1653e9ef]
[debug] Python version 3.8.8 (CPython 64bit) - Windows-10-10.0.19041-SP0
[debug] exe versions: ffmpeg N-105029-gf3a949dc4c-20211225 (setts), ffprobe N-105029-gf3a949dc4c-20211225
[debug] Optional libraries: Cryptodome, mutagen, sqlite, websockets
[debug] Proxy map: {}
[debug] [hotstar] Extracting URL: https://www.hotstar.com/in/movies/dhruva/1000192697/watch?utm_source=gwa
[hotstar]<PHONE_NUMBER>: Downloading JSON metadata
[hotstar]<PHONE_NUMBER>: Downloading webpage
[hotstar]<PHONE_NUMBER>: Downloading token
[hotstar]<PHONE_NUMBER>: Downloading JSON metadata
[hotstar]<PHONE_NUMBER>: Downloading m3u8 information
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), acodec, filesize, fs_approx, tbr, vbr, abr, asr, proto, vext, aext, hasaud, source, id
1000192697 has no subtitles
[info] Available formats for<PHONE_NUMBER>:
ID           EXT RESOLUTION FPS │   FILESIZE   TBR PROTO  │ VCODEC        VBR ACODEC    ABR
────────────────────────────────────────────────────────────────────────────────────────────
sdr-hls-97   mp4 250x140     25 │ ~110.53MiB   97k m3u8_n │ avc1.42c015   97k mp4a.40.5  0k
sdr-hls-148  mp4 320x180     25 │ ~168.43MiB  148k m3u8_n │ avc1.42c015  148k mp4a.40.5  0k
sdr-hls-260  mp4 320x180     25 │ ~294.60MiB  260k m3u8_n │ avc1.42c015  260k mp4a.40.2  0k
sdr-hls-401  mp4 416x234     25 │ ~454.79MiB  401k m3u8_n │ avc1.42c01e  401k mp4a.40.2  0k
sdr-hls-409  mp4 640x360     25 │ ~463.17MiB  409k m3u8_n │ avc1.42c01e  409k mp4a.40.2  0k
sdr-hls-499  mp4 720x404     25 │ ~565.27MiB  499k m3u8_n │ avc1.42c01e  499k mp4a.40.2  0k
sdr-hls-909  mp4 1280x720    25 │ ~  1.01GiB  909k m3u8_n │ avc1.4d401f  909k mp4a.40.2  0k
sdr-hls-1320 mp4 1600x900    25 │ ~  1.46GiB 1320k m3u8_n │ avc1.4d4028 1320k mp4a.40.2  0k
sdr-hls-1861 mp4 1920x1080   25 │ ~  2.06GiB 1861k m3u8_n │ avc1.4d4028 1861k mp4a.40.2  0k

Confirm whether you are able to access the video in browser using the same IP


Adding scale parameter to ResizeMediaUrl function

https://github.com/OrchardCMS/Orchard/blob/274b4416ec2a9dd6794207ffd7868cf7f706f866/src/Orchard.Web/Modules/Orchard.MediaProcessing/Shapes/MediaShapes.cs#L31
In certain cases we got messed images from ResizeMediaUrl call: images were grainy when resized
We need to add scaling as an optional parameters to ResizeMediaUrl  function.

fixed via #8713


Update precommit check isort version.

Update isort to 5.11.5 to address issue that occurs in relation of a isort's dependencies.
Error output example:
https://github.com/home-assistant/core/issues/86892
Release tag:
https://github.com/PyCQA/isort/releases/tag/5.11.5

Sorry reviewing this 😅

It's gold

Thanks Keith!


Post notification on currency change and fix memory leaks

📲 What
@ifbarrera and I paired on bringing back the .ksr_userLocalePreferencesChanged and fixing the memory leaks that we suspected were being created by retaining view controllers in Signals in RootViewModel.
🤔 Why
In order for currency selection changes to have immediate effect in the app, we need to recreate the underlying view controllers on the tab bar when a currency preference change is made. For this reason we post the .ksr_userLocalePreferencesChanged notification and respond to that in RootViewModel by emitting a new array of root UIViewControllers.
Previously this was causing these view controllers to leak due to the way the Signals were set up, they were retaining their last emission in some cases.
🛠 How
Updated the Signals that previously emitted actual UIViewControllerarrays to instead emit an enum which we've called RootViewControllerData so that the instantiation of those view controllers could be handled outside of the view model and thereby not be retained and leaked.
NB: This is a change to our app's navigation so it should be tested fairly thoroughly for regressions.
✅ Acceptance criteria

[ ] Tests pass
[ ] Navigation works as before
[ ] Scroll to top works as before

 Re-add "userLocaleChanged" notification after user changes currency

 Fix root view controller memory leak

@dusi this is now ready for review at your convenience :)


Tchat

Implement tchat feature

Done!
https://github.com/hercemer42/baby-foot-manager/commit/6b61cbf9dacf98dde68833e152ccebb4c6c37d06


Question: Is there any way to change the delay between comments/replies?

When a comment is read, it takes way too long for the next one imo.

I agree, I remember noticing this as well and couldn't find a way to make it faster.
I'll keep this issue open until I have a solution for this.

Alright

Instead of a faster transition there could be a way to configure it and choose a delay in ms

What is the cause of the delay?


Support linux/arm64/v8

Component(s)
router, controlplane, studio
Is your feature request related to a problem? Please describe.
Hi Team,
Could you add multi-arch (arm64) support to the Docker images soon? This will help Cosmo reaches more users on ARM64 systems. Thoughts?
Thanks,
Harry
Describe the solution you'd like
multi-arch support
Describe alternatives you've considered
No response
Additional context
No response

Hi @harrytang,
As mentioned in your PR, we will work on multi-architecture images soon.
Thank you!


feat(archive): Add is_archived to /projects/{project_pk}/features/

Let's add an optional query parameter to include / exclude archive flags.


Allow specifying role names instead of hardcoded dms-access-for-endpoint / dms-cloudwatch-logs-role / dms-vpc-role

Is your request related to a problem? Please describe.

I applied this module twice, and ended up with
│ Error: creating IAM Role (dms-access-for-endpoint): operation error IAM: CreateRole, https response error StatusCode: 409, RequestID: 1d3032eb-ed29-4e97-95e9-4f584a63e9fa, EntityAlreadyExists: Role with name dms-access-for-endpoint already exists.
│
│   with module.database_migration_service.aws_iam_role.dms_access_for_endpoint[0],
│   on .terraform/modules/database_migration_service/main.tf line 80, in resource "aws_iam_role" "dms_access_for_endpoint":
│   80: resource "aws_iam_role" "dms_access_for_endpoint" {
│
╵
╷
│ Error: creating IAM Role (dms-cloudwatch-logs-role): operation error IAM: CreateRole, https response error StatusCode: 409, RequestID: 0cf957a0-9ea2-408d-91b3-5f6e7f811364, EntityAlreadyExists: Role with name dms-cloudwatch-logs-role already exists.
│
│   with module.database_migration_service.aws_iam_role.dms_cloudwatch_logs_role[0],
│   on .terraform/modules/database_migration_service/main.tf line 94, in resource "aws_iam_role" "dms_cloudwatch_logs_role":
│   94: resource "aws_iam_role" "dms_cloudwatch_logs_role" {
│
╵
╷
│ Error: creating IAM Role (dms-vpc-role): operation error IAM: CreateRole, https response error StatusCode: 409, RequestID: 74d6de97-a5af-4118-8160-5689ca49da7d, EntityAlreadyExists: Role with name dms-vpc-role already exists.
│
│   with module.database_migration_service.aws_iam_role.dms_vpc_role[0],
│   on .terraform/modules/database_migration_service/main.tf line 108, in resource "aws_iam_role" "dms_vpc_role":
│  108: resource "aws_iam_role" "dms_vpc_role" {

Describe the solution you'd like.

Being able to specify the role names, like access_iam_role_name. Or maybe an unique prefix for the whole module... as long as I can make it unique.
Describe alternatives you've considered.

I guess I can try out switching create_iam_roles to false on the 2nd DMS, but obviously if I ever delete the first one, boom.

Please read the DMS docs and search past issues on this


Feat/apply incremental schema changes

Summary
implementation of schema changes for incremental models are currently missing. detecting schema changes during materialization would fallback to the legacy incremental strategy. this is not user-friendly and not feasible for very large models. schema changes for distributed_incremental materialization were not supported at all.
this pr contains

support for applying schema changes for incremental and distributed_incremental materializations
implementation of the on_schema_change='sync_all_column' strategy as per official dbt specs
fix of an issue in distributed_incremental materialzation and on_schema_change='ignore', where new columns in the target relation would break the dbt run during creation of the __dbt_new_data_ tables
fix of an issue in distributed_incremental materialzation, where column order changes would break the dbt run (or insert data to the wrong columns)

Checklist
Delete items not relevant to your PR:

[ x ] Unit and integration tests covering the common scenarios were added
[ x ] A human-readable description of the changes was provided to include in CHANGELOG
[ ] For significant changes, documentation in https://github.com/ClickHouse/clickhouse-docs was updated with further explanations or tutorials

 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.Can Bekleyici 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.

Github changed its docker-compose command so all the tests failed. I adjusted it in #334 and merged it to main.
@canbekley Could you please merge main to your branch?


PHP notice Gamification

I get the following notice when uploading a dataset. (happens 4 times in one call)
In order to remove the notice message, I have build a check around the if statement that causes this problem. However, it seems like the problem is more deep (e.g., how can a like or download not have a knowledge type?).

A PHP Error was encountered

Severity: Notice

Message:  Undefined property: stdClass::$kt

Filename: libraries/ElasticSearch.php

Line Number: 744

Backtrace:

            File: /var/www/openml.org/public_html/openml_OS/libraries/ElasticSearch.php

            Line: 744

            Function: _error_handler

            File: /var/www/openml.org/public_html/openml_OS/libraries/ElasticSearch.php

            Line: 587

            Function: build_user

            File: /var/www/openml.org/public_html/openml_OS/libraries/ElasticSearch.php

            Line: 394

            Function: index_user

            File: /var/www/openml.org/public_html/openml_OS/models/api/v1/Api_data.php

            Line: 355

            Function: index

            File: /var/www/openml.org/public_html/openml_OS/models/api/v1/Api_data.php

            Line: 44

            Function: data_upload

            File: /var/www/openml.org/public_html/openml_OS/controllers/Api_new.php

            Line: 118

            Function: bootstrap

            File: /var/www/openml.org/public_html/openml_OS/controllers/Api_new.php

            Line: 82

            Function: bootstrap

            File: /var/www/openml.org/public_html/index.php

            Line: 329

            Function: require_once

Turns out to be an error in the SQL query. Fixed in the server upgrade branch (for ES 5). Won't fix for the old server since we're switching soon.


ERROR: Unable to connect to service.

I just installed localtunnel v2 on OS X, and I'm getting this error. Not sure why this is happening...as far as I know, there's nothing wrong with my internet connection. The older localtunnel was working fine just a few minutes ago.

That version has reached EOL. Ngrok is much more stable now. However there is also a minimal Go implementation in master for those that find that interesting.


Upgradability of Polygon Hermez is potentially inaccurate

A question was raised on Polygon's Discord server, to which one of the responses from the team was:
https://discord.com/channels/635865020172861441/910852199905624124/914840921814732851

According to the response that I've received for my initial question, the delay variable for the following smart contract is responsible for the upgradability delay:
https://etherscan.io/address/0xf7b20368Fe3Da5CD40EA43d61F52B23145544Ec3#readContract
604800 / 86400 = 7
If this is the case, the Upgradeability of Polygon Hermez needs to be changed from 'Yes' to '7 days delay'.

Fixed in #341


Alarm state on startup instead of on first refresh

Fixes #1289 by forcing all entity state to be gathered during network discovery discovery.
Previously, each platform forced a refresh on the coordinator. This was slow and error prone. Now, when the network is discovered full entity state is discovered as well.

Can you confirmed you ran black on this? I did a recent commit and noticed it was not formatted with black.

Running black manually found a change to make. PR updated.  I have been running pre-commit run --all-files before sending PRs. I assumed that would do black for me, but apparently not? I'll make sure to start doing black manually.

Those failed checks look like a github problem?

Running black manually found a change to make. PR updated.  I have been running pre-commit run --all-files before sending PRs. I assumed that would do black for me, but apparently not? I'll make sure to start doing black manually.

Yah I probably need to fix the precommit. My editor does it for me so never noticed.


Unable to use Service Bus Explorer to access a Topic

I have a connection string that provides access to a Topic, but not to the Namespace.  I need to be able to connect to that Topic and create/update Subscriptions, but when I try to use the connection string it fails with message:
"Exception: The remote server returned an error: (401) Unauthorized. claim is empty..".
The purpose for this is to allow our external teams to have manage rights over a single Topic while not letting them Manage the whole namespace.  Is there any way around this?

Hi @nkeeslin the tool currently does not support entity-level connection string and the ability to connect to a single topic or queue, sorry about that. If you like, you can extend the tool with a PR. At the moment, I'm quite busy with some work, and I can't do it personally.


email  template not found

email template module not found in version laravel 5.8
how i can copy it form the old version?

We have removed the email template. you can download the Email Template module from the older release.


wav2vec unsupervised GAN training poor results

❓ Questions and Help
Before asking:

search the issues.
search the docs.

What is your question?
I am trying to use wav2vec unsupervised to train a Lithuanian speech recognition model. I have successfully converted audio and text data (see below), but am struggling with getting an acceptable UER. Currently, after training for 150k steps, the UER improved from 180% (measured after 30k steps) to ~120%, which is still ridiculously bad. I describe my process below, I would like to know what I'm doing wrong.
Code
All code snippets are in the what have you tried section.
What have you tried?
Audio prep:
I started by removing silences, preparing transcription and split files for the conversion. The results were audio files without silences stored in /home/usr/w2v/audio/clips_no_silence/clips and transcription/split files {train, test, valid}.{tsv, phn, wrd, ltr} + dict.{train, test, valid} files stored in /home/usr/w2v/audio/clips_no_silence/manifests. I used the splits provided by commonvoice.

Next, I used the prepare_audio.sh script to prepare audio for training. I used
zsh prepare_audio.sh /home/usr/w2v/audio/clips_no_silence/manifests /home/usr/w2v/preprocessed_audio /home/usr/w2v/models/xlsr_53_56k.pt

I realise that the results would be better if I used a pre-trained wav2vec model specifially for Lithuanian. I am currently working on making it work with this pretrained model. Even with this, the UER is still too high in my opinion.

Audio conversion logs
Note: this was done on google colab so path logs are different from the settings above.  This means you can write to the underlying (supposedly non-writeable) NumPy array using the tensor. You may want to copy the array to protect its data or make it writeable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at  /pytorch/torch/csrc/utils/tensor_numpy.cpp:180.)
  x = torch.from_numpy(features[start:end]).cuda()
tcmalloc: large alloc<PHONE_NUMBER> bytes == 0x5642ea9f0000 @  0x7f56730a3b6b 0x7f56730c3379 0x7f5609d0b26e 0x7f5609d0c9e2 0x7f564e427a73 0x7f564d95db7b 0x7f564e0b8bef 0x7f564e09d480 0x7f564dca6454 0x7f564d9511c8 0x7f564e22b310 0x7f564e3f6217 0x7f566036e9ae 0x7f56604ba9de 0x564252caf010 0x564252da0c0d 0x564252d230d8 0x564252cb065a 0x564252d1eb0e 0x564252d1dc35 0x564252d1d933 0x564252de7402 0x564252de777d 0x564252de7626 0x564252dbf313 0x564252dbefbc 0x7f5671eabbf7 0x564252dbee9a
100% 1/1 [01:35<00:00, 95.39s/it]
data path: /content/gdrive/MyDrive/legego/preprocessed_audio_new/precompute_pca512/train
100% 4743/4743 [00:29<00:00, 158.14it/s]
data path: /content/gdrive/MyDrive/legego/preprocessed_audio_new/precompute_pca512_cls128_mean/train
  0% 0/4743 [00:00<?, ?it/s]/content/libs/fairseq/examples/wav2vec/unsupervised/scripts/mean_pool.py:78: UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors. This means you can write to the underlying (supposedly non-writeable) NumPy array using the tensor. You may want to copy the array to protect its data or make it writeable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at  /pytorch/torch/csrc/utils/tensor_numpy.cpp:180.)
  x = torch.from_numpy(feats).cuda()
100% 4743/4743 [00:32<00:00, 147.96it/s]
data path: /content/gdrive/MyDrive/legego/preprocessed_audio_new/valid
  0% 0/1 [00:00<?, ?it/s]/content/libs/fairseq/examples/wav2vec/unsupervised/scripts/apply_pca.py:70: UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors. This means you can write to the underlying (supposedly non-writeable) NumPy array using the tensor. You may want to copy the array to protect its data or make it writeable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at  /pytorch/torch/csrc/utils/tensor_numpy.cpp:180.)
  x = torch.from_numpy(features[start:end]).cuda()
100% 1/1 [00:00<00:00, 11.55it/s]
data path: /content/gdrive/MyDrive/legego/preprocessed_audio_new/precompute_pca512/valid
100% 33/33 [00:00<00:00, 123.31it/s]
data path: /content/gdrive/MyDrive/legego/preprocessed_audio_new/precompute_pca512_cls128_mean/valid
  0% 0/33 [00:00<?, ?it/s]/content/libs/fairseq/examples/wav2vec/unsupervised/scripts/mean_pool.py:78: UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors. This means you can write to the underlying (supposedly non-writeable) NumPy array using the tensor. You may want to copy the array to protect its data or make it writeable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at  /pytorch/torch/csrc/utils/tensor_numpy.cpp:180.)
  x = torch.from_numpy(feats).cuda()
100% 33/33 [00:03<00:00,  8.56it/s]
data path: /content/gdrive/MyDrive/legego/preprocessed_audio_new/test
  0% 0/1 [00:00<?, ?it/s]/content/libs/fairseq/examples/wav2vec/unsupervised/scripts/apply_pca.py:70: UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors. This means you can write to the underlying (supposedly non-writeable) NumPy array using the tensor. You may want to copy the array to protect its data or make it writeable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at  /pytorch/torch/csrc/utils/tensor_numpy.cpp:180.)
  x = torch.from_numpy(features[start:end]).cuda()
tcmalloc: large alloc<PHONE_NUMBER> bytes == 0x5594bd186000 @  0x7fd41a461b6b 0x7fd41a481379 0x7fd3b10c926e 0x7fd3b10ca9e2 0x7fd3f57e5a73 0x7fd3f4d1bb7b 0x7fd3f5476bef 0x7fd3f545b480 0x7fd3f5064454 0x7fd3f4d0f1c8 0x7fd3f55e9310 0x7fd3f57b4217 0x7fd40772c9ae 0x7fd4078789de 0x559426803010 0x5594268f4c0d 0x5594268770d8 0x55942680465a 0x559426872b0e 0x559426871c35 0x559426871933 0x55942693b402 0x55942693b77d 0x55942693b626 0x559426913313 0x559426912fbc 0x7fd419269bf7 0x559426912e9a
100% 1/1 [01:19<00:00, 79.16s/it]
data path: /content/gdrive/MyDrive/legego/preprocessed_audio_new/precompute_pca512/test
100% 3398/3398 [00:23<00:00, 143.79it/s]
data path: /content/gdrive/MyDrive/legego/preprocessed_audio_new/precompute_pca512_cls128_mean/test
  0% 0/3398 [00:00<?, ?it/s]/content/libs/fairseq/examples/wav2vec/unsupervised/scripts/mean_pool.py:78: UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors. This means you can write to the underlying (supposedly non-writeable) NumPy array using the tensor. You may want to copy the array to protect its data or make it writeable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at  /pytorch/torch/csrc/utils/tensor_numpy.cpp:180.)
  x = torch.from_numpy(feats).cuda()
100% 3398/3398 [00:17<00:00, 196.32it/s]

Audio conversion output
The main directory contains all of the aforementioned transcription files and {test, valid, train}.{npy, lengths} files.
preprocessed_audio/pca  contains 512_pca_A.npy and 512_pca_b.npy
preprocessed_audio/CLUS128 contains centroids.npy, {test, train, valid}.{phn, src, tsv}
There are 3 preprocessed_audio/precompute_pca512* (cls128 mean and mean_pooled) directories, all containing {test, valid, train}.{lengths, npy, phn, tsv, wrd}

Text prep:
For text data, I am using the Leipzig university corpora, Wikipedia 2020, Web 2016 and 2020, News 2020 and Newscrawl 2014-2016. I filter all sentences with non Lithuanian letters and run the prepares_text.sh script. My output directory is /home/usr/w2v/preprocessed_text

Text conversion output
The preprocessed_text directory contains

dict.txt,
kenlm.wrd.o40003.{arpa, bin},
lexicon.lst,
lexicon_filtered.lst,
lm.upper.lid.txt,
phones.txt,
preprocess.log,
words.txt.

preprocessed_text/phones contains:

dict.phn.txt,
dict.txt,
lm.phones.filtered.{04, 06}.{arpa, bin},
lm.phones.filtered.txt,
preprocessed.log,
train.{bin, idx}.

preprocessed_text/fst contains three directories (phn_to_phn_sil, phn_to_words, phn_to_words_sil), which all contain:

G_lm.phones.filtered.06.fst,
H.phn.fst, H.phn.fst.isym,
H.phn.fstisym_disambig.int,
HLG.phn.lm.phones.filtered.06.fst,
HLGa.phn.lm.phones.filtered.06.fst,
kaldi_dict.h_out.phn.txt,
kaldi_dict.lm.phones.filtered.06.txt,
kaldi_dict.lm.phones.filtered.06.txt_disamig,
kaldi_dict.phn.txt,
kaldi_dict.phn_disambig.txt,
kaldi_dict.phn_disambig.txt.int,
kaldi_dict.phn_disambig.txt_disamig,
kaldi_lexicon.phn.lm.phones.filtered.06.txt,
kaldi_lexicon.phn.lm.phones.filtered.06_disambig.txt,
L.phn.lm.phones.filtered.06.fst,
LG.phn.lm.phones.filtered.06.fst.

GAN training:
For gan training, I use the following code:
PREFIX="w2v_unsup_gan_xp"

# Path to audio/precompute_pca512_cls128_mean_pooled
TASK_DATA="/home/usr/w2v/preprocessed_audio/precompute_pca512_cls128_mean_pooled"

# path to fairseq-preprocessed GAN data (phones dir)
TEXT_DATA="/home/usr/w2v/preprocessed_text/phones"

# KenLM 4-gram phoneme language model (LM data = GAN data here)
KENLM_PATH="$/home/usr/w2v/preprocessed_text/phones/lm.phones.filtered.04.bin"

OUT_PATH=/home/usr/w2v/gan_out
mkdir -p $OUT_PATH
# Path to the the config file of the unsupervised gan model
CONFIG_PATH="${FAIRSEQ_ROOT}/examples/wav2vec/unsupervised/config/gan"

PYTHONPATH=$FAIRSEQ_ROOT PREFIX=$PREFIX CUDA_LAUNCH_BLOCKING=1 fairseq-hydra-train \
	-m --config-dir ${CONFIG_PATH} \
	--config-name w2vu \
	task.data=${TASK_DATA} \
	task.text_data=${TEXT_DATA} \
	task.kenlm_path=${KENLM_PATH} \
	checkpoint.no_epoch_checkpoints=true \
	checkpoint.keep_last_epochs=20 \
	checkpoint.save_dir=${OUT_PATH} \
	common.user_dir=${FAIRSEQ_ROOT}/examples/wav2vec/unsupervised \
	model.code_penalty=2,4 model.gradient_penalty=1.5,2.0 \
	model.smoothness_weight=0.5,0.75,1.0 'common.seed=range(0,5)'

I didn't edit the config files at all.

A snippet of the gan training logs
[2021-07-31 16:17:00,565][fairseq.trainer][INFO] - begin training epoch 612
[2021-07-31 16:17:00,566][fairseq_cli.train][INFO] - Start iterating over samples
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[2021-07-31 16:17:13,969][fairseq_cli.train][INFO] - end of epoch 612 (average epoch stats below)
[2021-07-31 16:17:13,972][train][INFO] - {"epoch": 612, "train_loss": "2.545", "train_ntokens": "153", "train_nsentences": "153", "train_temp": "0.775", "train_code_ppl": "10.728", "train_loss_code_pen": "0.312", "train_loss_smoothness": "1.724", "train_loss_dense_g": "2.912", "train_lm_score_sum": 0.0, "train_num_pred_chars": 0.0, "train_loss_grad_pen": "0.356", "train_loss_dense_d": "0.072", "train_loss_token_d": "0.067", "train_wps": "352.9", "train_ups": "2.31", "train_wpb": "153", "train_bsz": "153", "train_num_updates": "18972", "train_lr_discriminator": "0.0005", "train_lr_generator": "0.0004", "train_gnorm": "25.175", "train_clip": "90.3", "train_train_wall": "13", "train_gb_free": "4.8", "train_wall": "7566"}
[2021-07-31 16:17:14,009][fairseq.trainer][INFO] - begin training epoch 613
[2021-07-31 16:17:14,010][fairseq_cli.train][INFO] - Start iterating over samples
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[2021-07-31 16:17:26,101][train_inner][INFO] - {"epoch": 613, "update": 612.903, "loss": "2.73", "ntokens": "153.49", "nsentences": "153.49", "temp": "0.775", "code_ppl": "10.712", "loss_code_pen": "0.306", "loss_smoothness": "1.707", "loss_dense_g": "2.98", "lm_score_sum": 0.0, "num_pred_chars": 0.0, "loss_grad_pen": "0.35", "loss_dense_d": "0.068", "loss_token_d": "0.075", "wps": "358", "ups": "2.33", "wpb": "153.5", "bsz": "153.5", "num_updates": "19000", "lr_discriminator": "0.0005", "lr_generator": "0.0004", "gnorm": "26.02", "clip": "93", "train_wall": "42", "gb_free": "4.8", "wall": "7578"}
[2021-07-31 16:17:26,102][fairseq_cli.train][INFO] - begin validation on "valid" subset
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[2021-07-31 16:17:26,318][unsupervised.tasks.unpaired_audio_text][INFO] - REF: p a ɭ e i nʲ e rʲ iː b u v oː pʲ ɪ r k ɭʲ uː s a n dʲ ee ɭ e i
[2021-07-31 16:17:26,321][unsupervised.tasks.unpaired_audio_text][INFO] - HYP: dʲ e l̩ s d u a b oː t a p a dʲ ee j oː s tʲ i s a ʒ e rʲ ɪ ɡ a r d a
[2021-07-31 16:17:26,324][unsupervised.tasks.unpaired_audio_text][INFO] - LM [REF]: -44.36577224731445, 38.41420644057458
[2021-07-31 16:17:26,326][unsupervised.tasks.unpaired_audio_text][INFO] - LM [HYP]: -61.0944938659668, 81.13400851623487
[2021-07-31 16:17:26,331][valid][INFO] - {"epoch": 613, "valid_loss": "1.054", "valid_ntokens": "771", "valid_nsentences": "16.5", "valid_lm_score_sum": "-4181.57", "valid_num_pred_chars": "1885", "valid_vocab_seen_pct": "0.44", "valid_uer": "105.383", "valid_weighted_lm_ppl": "782.11", "valid_lm_ppl": "151.416", "valid_wps": "1431.4", "valid_wpb": "771", "valid_bsz": "16.5", "valid_num_updates": "19000", "valid_best_weighted_lm_ppl": "668.63"}
[2021-07-31 16:17:26,332][fairseq.checkpoint_utils][INFO] - Preparing to save checkpoint for epoch 613 @ 19000 updates
[2021-07-31 16:17:26,333][fairseq.trainer][INFO] - Saving checkpoint to /home/zygimantas/Downloads/gan_out_large_07_31/checkpoint_613_19000.pt
[2021-07-31 16:17:26,362][fairseq.trainer][INFO] - Finished saving checkpoint to /home/zygimantas/Downloads/gan_out_large_07_31/checkpoint_613_19000.pt
[2021-07-31 16:17:26,478][fairseq.checkpoint_utils][INFO] - Saved checkpoint /home/zygimantas/Downloads/gan_out_large_07_31/checkpoint_613_19000.pt (epoch 613 @ 19000 updates, score<PHONE_NUMBER>248666) (writing took 0.1455865339958109 seconds)
[2021-07-31 16:17:27,639][fairseq_cli.train][INFO] - end of epoch 613 (average epoch stats below)
[2021-07-31 16:17:27,642][train][INFO] - {"epoch": 613, "train_loss": "2.863", "train_ntokens": "153", "train_nsentences": "153", "train_temp": "0.774", "train_code_ppl": "10.737", "train_loss_code_pen": "0.3", "train_loss_smoothness": "1.679", "train_loss_dense_g": "2.936", "train_lm_score_sum": 0.0, "train_num_pred_chars": 0.0, "train_loss_grad_pen": "0.314", "train_loss_dense_d": "0.068", "train_loss_token_d": "0.074", "train_wps": "347", "train_ups": "2.27", "train_wpb": "153", "train_bsz": "153", "train_num_updates": "19003", "train_lr_discriminator": "0.0005", "train_lr_generator": "0.0004", "train_gnorm": "26.898", "train_clip": "96.8", "train_train_wall": "13", "train_gb_free": "5.2", "train_wall": "7580"}
[2021-07-31 16:17:27,673][fairseq.trainer][INFO] - begin training epoch 614
[2021-07-31 16:17:27,674][fairseq_cli.train][INFO] - Start iterating over samples
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[2021-07-31 16:17:40,624][fairseq_cli.train][INFO] - end of epoch 614 (average epoch stats below)
[2021-07-31 16:17:40,626][train][INFO] - {"epoch": 614, "train_loss": "2.676", "train_ntokens": "153", "train_nsentences": "153", "train_temp": "0.773", "train_code_ppl": "10.856", "train_loss_code_pen": "0.315", "train_loss_smoothness": "1.764", "train_loss_dense_g": "2.892", "train_lm_score_sum": 0.0, "train_num_pred_chars": 0.0, "train_loss_grad_pen": "0.473", "train_loss_dense_d": "0.071", "train_loss_token_d": "0.066", "train_wps": "365.4", "train_ups": "2.39", "train_wpb": "153", "train_bsz": "153", "train_num_updates": "19034", "train_lr_discriminator": "0.0005", "train_lr_generator": "0.0004", "train_gnorm": "27.159", "train_clip": "93.5", "train_train_wall": "13", "train_gb_free": "4.8", "train_wall": "7593"}
[2021-07-31 16:17:40,662][fairseq.trainer][INFO] - begin training epoch 615
[2021-07-31 16:17:40,663][fairseq_cli.train][INFO] - Start iterating over samples
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[W pthreadpool-cpp.cc:90] Warning: Leaking Caffe2 thread-pool after fork. (function pthreadpool)
[2021-07-31 16:17:53,370][fairseq_cli.train][INFO] - end of epoch 615 (average epoch stats below)
[2021-07-31 16:17:53,372][train][INFO] - {"epoch": 615, "train_loss": "2.854", "train_ntokens": "153", "train_nsentences": "153", "train_temp": "0.772", "train_code_ppl": "10.729", "train_loss_code_pen": "0.298", "train_loss_smoothness": "1.698", "train_loss_dense_g": "2.966", "train_lm_score_sum": 0.0, "train_num_pred_chars": 0.0, "train_loss_grad_pen": "0.242", "train_loss_dense_d": "0.067", "train_loss_token_d": "0.072", "train_wps": "372.2", "train_ups": "2.43", "train_wpb": "153", "train_bsz": "153", "train_num_updates": "19065", "train_lr_discriminator": "0.0005", "train_lr_generator": "0.0004", "train_gnorm": "24.491", "train_clip": "80.6", "train_train_wall": "12", "train_gb_free": "5.3", "train_wall": "7606"}

After the training I use the w2vu_generate.py with the 4 gram lm and evaluate the generated files with wer.py. I am currently stuck figuring out why the training results are so poor, please help!
What's your environment?

fairseq Version: master
PyTorch Version: 1.9
OS: Ubuntu LTS 20.04.2
How you installed fairseq: source
Build command you used (if compiling from source): pip install --editable ./
Python version: 3.7.10
CUDA/cuDNN version: 11.2
GPU models and configuration: RTX2060 Mobile, 16Gb Ram, Intel i7-9750H
Any other relevant information: Pykaldi installed using conda, Kaldi and kenlm from source

Hello, have you completed the realization of the wav2vec-u project? I have completed the entire process in this docker environment:wav2vec-u-exp but currently my WER is very high. I find it difficult to converge using this docker environment for training. Do you have any good suggestions?

I am having the same issue, please update if you found the solution

Hello, have you solved this problem now? I have the same problem. I think the hyperparameter setting during GAN training has a greater impact

I am having the same issue, please update if you found the solution

Hello, have you solved this problem now? I have the same problem. I think the hyperparameter setting during GAN training has a greater impact

I have tried verifying the results of the paper by applying my process to the Tatar language but failed to replicate the results, which must mean that there's something wrong with my process. After failing to progress I left the issue alone and haven't touched it for a while now.

I am having the same issue, please update if you found the solution

Hello, have you solved this problem now? I have the same problem. I think the hyperparameter setting during GAN training has a greater impact

True. The hyper-param setting seems to be very tricky 😒


Add CommandRecommendationEngine

Fixes #105
Open for feedback about the implementation.
Main Changes:

Add CommandRecommendationEngine
Update UI to show suggestions

Key design considerations:

Drop-down autocomplete vs inline text recommendation + tab autocompletion
Main magic happens in CommandRecommendationEngine::generateArgumentRecommendation

Key points:

Cannot add more than 2 instances of name/nric (only 1)
Can add multiple tags & dates ranges

https://user-images.githubusercontent.com/63457492/226355355-5b3ebab1-5c8e-409a-8f1d-810277273919.mp4
TODOS:

[ ] Update documentation
[ ] Add testcases

Codecov Report
Patch coverage: 38.92% and project coverage change: -4.76 ⚠

Comparison is base (89d64d3) 75.95% compared to head (63a3bd9) 71.19%.

Additional details and impacted files
☔ View full report in Codecov by Sentry. 📢 Do you have feedback about the report comment? Let us know in this issue.

What is testing, amiright 💀

Regarding the prefixes in cliSyntax, i'm thinking of using their long form instead. For example, a/ -> address/ since we have autocomplete now.

Regarding the prefixes in cliSyntax, i'm thinking of using their long form instead. For example, a/ -> address/ since we have autocomplete now. What do you guys think?

I think I'll still prefer the short form, since they are still easier to type out. It also prevents the commands from becoming too long.

Yup that has been fixed! @zhacatomn

Cool, resolve the conflicts, and go ahead and merge this in. Thanks for the amazing work!

Thanks, everyone @AY2223S2-CS2103T-W12-1/developers. I will go ahead and merge this in.


JS rules are not applied in Whale browser

Environment
AdGuard for Windows, versions: 7.5.0 - 7.5.2
Naver Whale version: <IP_ADDRESS>
Reproduction

Add the following rule to AdGuard user filter: ( adguard.com#%#document.cookie = "testasdasd=1"; )
[15-10-2020 14:18] Accessing the <adguard.com> site from the Chrome browser new incognito window
[15-10-2020 14:20] Accessing the <adguard.com> site from the Whale browser new incognito window
Confirmation with testasdasd in cookie
No testasdasd are generated in the Whale browser, but testasdasd are generated in the chromium

Customer ID & debug logs
2863997

Is this Whale browser added to the list of filtered apps (settings -> network -> filtered apps)?
It'd be better to test this on example.org

Yes - customer claims that other filtering rules are applied without any issues.
I'll ask him to test on example.org.

@AdguardTeam/qa-team guys, can we reproduce this?

Yes, I managed to reproduce the issue in the specified browser.
Also, it stays on Nightly (33).

screenshot

Is there any solution other than to stop using the Whale browser?

No solutions yet, we'll need to implement a fix on our side first.


STORM-1739 (1.x) update the mini JAVA version dependency in 0.10.0 and above.

Storm drops supporting JDK 1.6 in Apache Storm 0.10.0 and above.

+1