distrobuilder: 3.0 -> 3.1

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://github.com/lxc/distrobuilder/releases.
meta.description for distrobuilder is: System container image builder for LXC and LXD
meta.homepage for distrobuilder is: https://github.com/lxc/distrobuilder
Updates performed

Golang update

To inspect upstream changes
Impact
Checks done

built on NixOS

[!CAUTION]
A test defined in passthru.tests did not pass.

found 3.1 with grep in /nix/store/c3knwk5j6nva89bwqdjrq7p07jxhhqch-distrobuilder-3.1
found 3.1 in filename of file in /nix/store/c3knwk5j6nva89bwqdjrq7p07jxhhqch-distrobuilder-3.1

Rebuild report (if merged into master) (click to expand)

2 total rebuild path(s)

2 package rebuild(s)

First fifty rebuilds by attrpath

distrobuilder

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/c3knwk5j6nva89bwqdjrq7p07jxhhqch-distrobuilder-3.1 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A distrobuilder https://github.com/r-ryantm/nixpkgs/archive/0bc5503c1dcaf1a0c2e214ee74e5b846d746647c.tar.gz

Or:
nix build github:r-ryantm/nixpkgs/0bc5503c1dcaf1a0c2e214ee74e5b846d746647c#distrobuilder

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/c3knwk5j6nva89bwqdjrq7p07jxhhqch-distrobuilder-3.1
ls -la /nix/store/c3knwk5j6nva89bwqdjrq7p07jxhhqch-distrobuilder-3.1/bin

Pre-merge build results
We have automatically built all packages that will get rebuilt due to
this change.
This gives evidence on whether the upgrade will break dependent packages.
Note sometimes packages show up as failed to build independent of the
change, simply because they are already broken on the target branch.
nixpkgs-review result
Generated using nixpkgs-review.
Command: nixpkgs-review

x86_64-linux

:white_check_mark: 1 package built:

distrobuilder

Maintainer pings
cc @aanderse @adamcstephens @jnsgruk @megheaiulian @mkg20001 for testing.

[!TIP]
As a maintainer, if your package is located under pkgs/by-name/*, you can comment @NixOS/nixpkgs-merge-bot merge to automatically merge this update using the nixpkgs-merge-bot.

Add a :+1: reaction to pull requests you find important.

@jnsgruk The failure in building the test is in fact important and should not have been ignored. In this case the lxc systemd generator, which is a patch set to customize it for nixos, failed to imply. This likely means lxc images are now broken.

error: builder for '/nix/store/9ibj8l4ii6vhpcj9hrwgiv76isa4dmcr-distrobuilder-nixos-generator.drv' failed with exit code 1;
       last 10 log lines:
       > Running phase: patchPhase
       > applying patch /nix/store/j6spyrs8c0988j8n0aiscpih04c6r5jn-nixos-generator.patch
       > patching file distrobuilder/lxc.generator
       > Hunk #1 succeeded at 21 (offset -4 lines).
       > Hunk #2 FAILED at 35.
       > Hunk #3 succeeded at 103 (offset 1 line).
       > Hunk #4 FAILED at 113.
       > Hunk #5 succeeded at 177 (offset 4 lines).
       > Hunk #6 succeeded at 206 with fuzz 1 (offset 4 lines).
       > 2 out of 6 hunks FAILED -- saving rejects to file distrobuilder/lxc.generator.rej
       For full logs, run 'nix log /nix/store/9ibj8l4ii6vhpcj9hrwgiv76isa4dmcr-distrobuilder-nixos-generator.drv'.

error: builder for '/nix/store/9ibj8l4ii6vhpcj9hrwgiv76isa4dmcr-distrobuilder-nixos-generator.drv' failed with exit code 1;
       last 10 log lines:
       > Running phase: patchPhase
       > applying patch /nix/store/j6spyrs8c0988j8n0aiscpih04c6r5jn-nixos-generator.patch
       > patching file distrobuilder/lxc.generator
       > Hunk #1 succeeded at 21 (offset -4 lines).
       > Hunk #2 FAILED at 35.
       > Hunk #3 succeeded at 103 (offset 1 line).
       > Hunk #4 FAILED at 113.
       > Hunk #5 succeeded at 177 (offset 4 lines).
       > Hunk #6 succeeded at 206 with fuzz 1 (offset 4 lines).
       > 2 out of 6 hunks FAILED -- saving rejects to file distrobuilder/lxc.generator.rej
       For full logs, run 'nix log /nix/store/9ibj8l4ii6vhpcj9hrwgiv76isa4dmcr-distrobuilder-nixos-generator.drv'.

Oops. That's totally my fault. I've added a new PR with an update to the patch which should address the issue.


Rename route

Today, we cannot rename routes. This is a problem.
We have a rename feature in the file browser that handles invocation (double click / ctx menu),  commitment, abdandon/blur validation etc. We can and should use the same approach here - the user should get the same experience as that in the file browser by default. Unfortunately we do not have an abstracted RenamableExpandableReorderableSelectableTreeView :(
The text inside the rename field should be the full path in the Remix style (ie not the page label, nor the resulting URL for a specific route with a parameter. Submission should parse and rewrite as needed. This is the same behaviour as that of a tool whose label starts with Frame.

@balazsbajorics can you edit this (and remove assignment if you want to open it up)?


DB error when running job "Prepared statement needs to be re-prepared"

There errors are being logged occasionally with some of my queued jobs. Any ideas? What do the question marks mean in the query?

SS 3.2.0
QueuedJobs 2.8.4

The ? ? ? is just the prepared statement syntax - the actual values are bound in when the sql statement is 'prepared' by the DB before inserting the values.
I've never seen the exception though (that the query needs to be re-prepared). Do you have a lot of things in your job queue before running the process task?

Hey thanks for the response, this turned out to be a server issue at the host, sorry! Closing..

@sheadawson mind sharing what the host had changed at the server? We also run into these errors now and then (unrelated to QueuedJobs btw).

@baukezwaan actually it's not the host so much. The heart of the issue is this mysql bug https://bugs.mysql.com/bug.php?id=42041. Being on a shared host, our prepared statements were often breaking because other customers on the server were running regular mysql-dump processes

I think when running queuedjobs as a service, given the expected long-life expectancy of some queries, it may make sense to periodically flush all prepared statements.
It may be necessary to build in some kind of max-lifetime into the query API.


cannot open atom from command line

This command was working for me, then I set some permissions or something. How do I fix this?
$ atom .
usage: dirname path
Cannot locate Atom.app, it is usually located in /Applications.
Set the ATOM_PATH environment variable to the directory containing Atom.app.

Running OSX

Gonna close this out - please feel free to reopen / comment if you can reproduce this with the latest version of Atom (0.210.0)

The error message, Cannot locate Atom.app, it is usually located in /Applications. Set the ATOM_PATH environment variable to the directory containing Atom.app. is being produced intermittently with Atom version 1.6.2 while running on OSX. At times the issue disappears completely and then it returns. Not entirely sure how to fix this.


CNI spec version clarify

You mentioned usage of CNI spec version 0.3.1 in Calico v3.9.1 - https://docs.projectcalico.org/v3.9/release-notes/
Use CNI spec version 0.3.1 calico #2882 (@caseydavenport)
I just downloaded fresh release archive and all Kubernetes manifests uses "cniVersion": "0.3.0".
grep -ri "cniVersion" k8s-manifests
k8s-manifests/flannel-migration/calico.yaml:      "cniVersion": "0.3.0",
k8s-manifests/canal.yaml:      "cniVersion": "0.3.0",
k8s-manifests/calico-policy-only.yaml:      "cniVersion": "0.3.0",
k8s-manifests/calico.yaml:      "cniVersion": "0.3.0",
k8s-manifests/calico-typha.yaml:      "cniVersion": "0.3.0",
k8s-manifests/canal-etcd.yaml:        "cniVersion": "0.3.0",
k8s-manifests/calico-etcd.yaml:      "cniVersion": "0.3.0",

Mentioned commit looks like fix for Helm chart, but shouldn't it be consistent with other deployment methods?

Interesting.
The manifests hosted in the docs website have the correct version: https://docs.projectcalico.org/v3.9/manifests/calico.yaml
Looks like perhaps the wrong manifests ended up in the release archive.

Looks like v3.9.1 was accidentally tagged from commit 8c0fba3d198f4eed7b31f4d4513120c3de68ca95 which doesn't include the cniVersion updates, so the release tarball didn't include the changes from 108e47678be6b6063e39fbcede1272012aca369a.

Closing this - we'll be cutting a new release in the near future. We shouldn't replace the existing tar archive despite the error.


rerunning rsconnect_deploy deploys new API

Describe the bug
using rsconnect_deploy to redeploy an existing API on Connect, it deploys a new API. I did not specify the new argument either
To Reproduce
Use can use the jupyter notebook published here.
Expected behavior
Redeploying an existing API should overwrite the existing content.

Ah, the new argument has a default of "True," so you can choose to turn that off by setting it equal to False. If you think it is strongly expected to be False, I can either update it or remove the default altogether. 👍

Is this the argument default?
https://github.com/rstudio/vetiver-python/blob/91c9856fef02ba99bf83bccf39db2dedc4c88aa1/vetiver/rsconnect.py#L16
Or am I missing something?

You are correct! I originally had thought there was something else going wrong. Upon further review, it looks like rsconnect.deploy_python_fastapi will think that every deployment is "new." When a model is sent to connect with deploy_rsconnect, it is deployed from a temporary directory where an app.py file is created from a pinned model. This temporary directory holds the manifest JSON file that would normally be used to determine if the deployment was "new" or not. An escape hatch out of this not-actually-new behavior that currently exists is to supply an app_id, which will force-overwrite the existing content.
I'll have to peek into rsconnect to see what validating newness looks like 👀


Remove legacy dependency

Description
Remove a legacy dependency not needed by plugins anymore. The consequence is it removes a huge amount of transitive dependencies in yarn.lock, many of which are dated and frequently cause CVE-related issues.
Testing done

yarn build works
yarn osd bootstrap works
sanity test on a local domain

Still understanding other potential impacts and original reasoning for having this dependency, will update here when more is learned from @opensearch-project/opensearch-core team. UPDATE: this has been confirmed by @kavilla , no other concerns.
Check List

[x] New functionality includes testing.

[x] All tests pass

[x] New functionality has been documented.
[x] Commits are signed per the DCO using --signoff

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

@opensearch-project/opensearch-core could I get assistance in understanding why this dependency is not needed anymore? My understanding is it was needed somewhere in the build or bootstrap logic for combining dependencies from core + plugin to build/run the plugin successfully. Is there any reference PR in core that I could reference here?

Nice.
Can we just completely delete yarn.lock and add it to .gitignore since it's always re-generated at run time anyway? Or would that prevent the CVE scanners from figuring out what needs updating?

We still want the lockfile, and with this fix it should not be re-generated often; only when we make direct changes in our package.json. The reason it was much more fluid before is the fact it was pulling in updated dependencies from the tip of main of core OSD.

@kavilla any further insight on this?

UT:
Test Suites: 1 skipped, 76 passed, 76 of 77 total
Tests:       2 skipped, 364 passed, 366 total
Snapshots:   70 passed, 70 total
Time:        98.704 s
Ran all test suites.
✨  Done in 100.18s.

Build:
yarn build
yarn run v1.22.19
$ yarn plugin-helpers build && echo Renaming artifact to $npm_package_config_plugin_zip_name-$npm_package_config_plugin_version.zip && mv ./build/$npm_package_config_plugin_name*.zip ./build/$npm_package_config_plugin_zip_name-$npm_package_config_plugin_version.zip
$ node ../../scripts/plugin_helpers build
 info Loaded config file from [/Users/ohltyler/workspace/opensearch/ad/3.0/OpenSearch-Dashboards/plugins/anomaly-detection-dashboards-plugin-1/.opensearch_dashboards-plugin-helpers.json]
 info deleting the build and target directories
 info running @osd/optimizer
 │ info initialized, 0 bundles cached
 │ info starting worker [1 bundle]
 │ succ 1 bundles compiled successfully after 41 sec
 info copying assets from `public/assets` to build
 info copying server source into the build and converting with babel
 info running yarn to install dependencies
 info compressing plugin into [anomalyDetectionDashboards-3.0.0.zip]
 info cleaning up compression temporary artifacts
Renaming artifact to

Sanity tested functionality and checked all pages on local cluster, no problems.

I see some failures in plugin bootstrap in CI, should we address these?

I see some failures in plugin bootstrap in CI, should we address these?

CI passes for linux. The failure is some timeout issue specific to windows, I believe this is an overall infra issue across the project, needs further investigation.
Prefer to keep the scope the same for this PR.


General tidy/refactor

remove dead code
no inline styles
separate components to own files
etc

Resolved: https://github.com/app-sapiens/ios-date-picker-js/pull/22


[live] <= [master] Moving to docfx v3

Docs Build status updates of commit 3d83ebf:
:white_check_mark: Validation status: passed

File
Status
Preview URL
Details

.openpublishing.publish.config.json
:white_check_mark:Succeeded

advocates/cecil-phillip.yml
:white_check_mark:Succeeded
View

For more details, please refer to the build report.
Note: Broken links written as relative paths are included in the above build report. For broken links written as absolute paths or external URLs, see the broken link report.
For any questions, please:Try searching in the Docs contributor and Admin GuideSee the frequently asked questionsPost your question in the Docs support channel


Update kubespray.md for link to ansible doc

update link to playbook variables in ansible

/check-cla

Ah, oops. You do need a  signed CLA before we can formally review this.

Ah, oops. You do need a signed CLA before we can formally review this.

/check-cla

Page preview:
https://deploy-preview-27366--kubernetes-io-master-staging.netlify.app/docs/setup/production-environment/tools/kubespray/

/kind cleanup

Thanks @tocado .
/approve


Remove metadata from images

Describe the bug
When a user does upload images and logos the metadata exif metadata are not stripped.
To Reproduce
Steps to reproduce the behavior:

Upload a testing image with EXIF tags filled.
Downloading the image or copying the URL for the same.
Using an online tool to view the EXIF data.

Expected behavior
Strip exif when uploading.

This issue was reported by an external user.
FYI @livio-a @fgerschwiler

estimate: <0.5d


Tips for better training

Dear @juntang-zhuang,
First of all, thank you for this repo.
I am trying to use it to train shelfnet on the Mapillary Vistas Dataset (here you can find my fork).
I have succeeded training she Real-Time version of Shelfnet, however the results are pretty bad even after 270000 epochs.
The reached mIOU is 34,06%, however in this paper they say that they were able to achieve 49.2% on your model.
I have already tried to contact the authors, but I got no response.
Therefore I wanted to ask you if you could give me some tips to improve the training to achieve better results.
Thank you in advance.
Best,
Micaela

Hi, sorry I have not experimented on Mapillary, too large for me. My suggestion would be first to check your dataloader and class definition, perhaps some tiny errors there. Second is you can try a smaller learning rate or a different optimizer such as Adam (it usually converges to a slightly worse result but not significantly worse). By "270000 epochs", are you referring to epochs or steps?

Ok thank you for your answer.
Yeah, I meant 270000 step. I think the loading is correct, but I will try with changing optimizer and lr.
I will let you know, Thanks!


Filter within a API

I am trying to write a API using Laravel and this MongoDB, I have been following along with this guide:  https://www.youtube.com/watch?v=YGqCZjdgJJk and I am up to the part of Filtering data:  https://youtu.be/YGqCZjdgJJk?t=2150 This is where I get stuck, as I assume the syntax is not correct for this laravel-mongodb connection into MongoDB.
Here is my code
Within my ProductController
class ProductController extends Controller
{
    /**
     * Display a listing of the resource.
     */
    public function index(Request $request)
    {
        //return Product::all();

        $filter = new ProductsFilter();
        $queryItems = $filter->transform($request);

        if(count($queryItems)== 0){
            return new ProductCollection(Product::paginate());
        }else {
            return new ProductCollection(Product::where($queryItems)->paginate());
        }
        //return new ProductCollection(Product::paginate());
    }

My ProductsFilter.php
<?php
namespace App\Filters\v1;

use Illuminate\Http\Request;
use App\Filters\ApiFilter;

class ProductsFilter extends ApiFilter {
    protected $safeParms = [
        'ProductId' => ['eq'],
        'name' => ['eq'],
        'category' => ['eq', 'ne']
    ];

    protected $columnMap = [
        'ProductId' => 'Product_id'

    ];

    protected $operatorMap = [
        'eq' => '=',
        'nq' => '!=',
        'lt' => '<',
        'lte' => '<=',
        'gt' => '>',
        'gte' => '>=',
    ];

}

My ApiFilter.php
<?php

namespace App\Filters;

use Illuminate\Http\Request;

class ApiFilter {
    protected $safeParams = [];

    protected $columnMap = [];

    protected $operatorMap = [];

    public function transform(Request $request){
        $eloQuery = [];

        foreach ($this->safeParams as $parm => $operators){
            $query = $request->query($parm);

            if(!isset($query)){
                continue;
            }

            $column = $this->columnMap[$parm] ?? $parm;

            foreach ($operators as $operator){
                if(isset($query[$operator])){
                    $eolQuery[] = [$column, $this->operator[$operator], $query[$operator]];
                }
            }
        }
        return $eloQuery;
    }
}

Does anyone have any suggestions please on how I could make this work?  At the moment, no matter what I try to filter with, I get the paginated result set back, but it is not applying the filter at all.
I have seen this method, https://www.youtube.com/watch?v=wlx5TZOV8_Q but I was hoping for something a little more generic and easily transferable between API endpoints.

Ignore this. there were a few typos in there


Add Infer plugin

https://github.com/pushtorefresh/storio/issues/381
I've added this Gradle plugin, which plays with Infer nicely.
It runs ok on my local machine. But we still need to install Infer to the CI server (not sure how) and then add two Gradle tasks to the CI script: inferDebug and eradicateDebug (for Eradicate feature).
Right now Infer doesn't see any issues (for testing purposes I've added dummy method with a silly null error and it has found it - so it actually works). Eradicate is finding one issue in storio-common module and fails right after that, so I can't say anything about other modules (can just run eradicate on separate modules, but haven't done it yet). If you are interested in applying these checks I could fix them before the merge.

[Current coverage][cc-pull] is 95.21%

Merging [#666][cc-pull] into [master][cc-base-branch] will not change coverage

@@             master       #666   diff @@
==========================================
  Files            84         84
  Lines          2548       2548
  Methods           0          0
  Messages          0          0
  Branches        325        325
==========================================
  Hits           2426       2426
  Misses           90         90
  Partials         32         32

Powered by Codecov. Last updated by [29a3b13...499610e][cc-compare]
[cc-base-branch]: https://codecov.io/gh/pushtorefresh/storio/branch/master?src=pr
[cc-compare]: https://codecov.io/gh/pushtorefresh/storio/compare/29a3b1348fd8e0b8d8b49227dd4288454e509099...499610e9fa5c6a89c90d162bc789825f63a9528c
[cc-pull]: https://codecov.io/gh/pushtorefresh/storio/pull/666?src=pr

But you don't run it during CI build. See https://github.com/artem-zinnatullin/qualitymatters/issues/21 :(

That sucks =(
I've found only this solution, but it looks really bad.
Maybe it is an option to you it just manually? Better than nothing at least and could be helpful sometimes.

Okay, I'm fine with running it locally
On Thu, Jun 30, 2016 at 1:34 PM, Ilya Zorin<EMAIL_ADDRESS>wrote:

That sucks =(
I've found only this https://github.com/facebook/infer/issues/153
solution, but it looks really bad.
Maybe it is an option to you it just manually? Better than nothing at
least and could be helpful sometimes.
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub
https://github.com/pushtorefresh/storio/pull/666#issuecomment-229622516,
or mute the thread
https://github.com/notifications/unsubscribe/AA7B3ObOviUB3O7LTrFCUxvlT633sH_fks5qQ5ubgaJpZM4JBb0I
.

All eradicate warnings are fixed now

Nice!
👍 but covarage

Yeah, but there is not much that I can do since I've added only annotation and couple of null checks

Hm, I think false branches of that checks weren't covered =) https://codecov.io/gh/pushtorefresh/storio/compare/29a3b1348fd8e0b8d8b49227dd4288454e509099...7529dfe424c59a30bb21de67886bc05f9e484d92

But most of these ifs are redundant actually and mostly about making infer stop complaining about them. So there is not much sense for covering them.

@artem-zinnatullin the thing is that it is impossible to suppress warnings on infer side, so without these redundant checks build is failing. Looks like infer is not smart enough for some cases.

@geralt-encore I definitely don't like that it changes logic in some places and instead of failing with NPE we're changing behavior.
What if you add plain old java assert value != null? It won't be executed on Android but will be executed in our JVM tests and probably will prevent Infer from complaining

Yeah, I completely agree with you. I'll try assert solution and if it won't work we will probably have to abandon this idea =(

Looks like assert stuff worked. I'll rework it then in a short time.

ok, great!

I have no idea what is the problem with PutResultsTest checkToStringImplementation. Something relate to assertions I guess.

lol wtf

Got it, your pr is #666

Damn knew it would be a problem 😬

Still fails :(

I have no idea how can I possibly fix it

@artem-zinnatullin probably we can close it since no one has an idea what's wrong with failing test and it's not really important one.

Yeah, ok :(


Response too slow.

Hi,
First of all thanks for this wonderful work.
I have tried it with sqlitedb but it was too slow that's why I shifted to mongodb. Initially it is good but Now I am having only 14500 statements and it is giving response after 4-5 seconds. How can I make response more faster. is there any way ?
bot = ChatBot(
'mychatbot',
read_only=True,
trainer='chatterbot.trainers.ListTrainer',
logic_adapters=[
{
'import_path': 'chatterbot.logic.BestMatch',
'threshold': 0.85,
'default_response': 'I am sorry, but I do not understand.'
},
{
'import_path': 'chatterbot.logic.LowConfidenceAdapter',
'threshold': 0.85,
'default_response': 'I am sorry, but I do not understand.'
}
],
filters=[
'chatterbot.filters.RepetitiveResponseFilter'
],
preprocessors=[
'chatterbot.preprocessors.clean_whitespace', 'chatterbot.preprocessors.unescape_html', 'chatterbot.preprocessors.convert_to_ascii'
],
storage_adapter='chatterbot.storage.MongoDatabaseAdapter',
database='mychatterbot'
}
If I am not wrong it is matching each input statement with all existing statements in loop that's why now responding slow with increase of number of statements.
Can we try elastic search as a db (as text based search is much faster in it). We can tokenize input statement and removing stop words than find out some top result from ES than apply LevenshteinDistance algo.
Please suggest.

use       "statement_comparison_function": "chatterbot.comparisons.levenshtein_distance"

but do pip install python-levenshtein

Thanks @bobland1 : But still response is taking 4-5 seconds in reply. Is there any other way to speed it up?


Slim count [Breaking Change]

https://github.com/ppetzold/nestjs-paginate/issues/393
Limit = 0 (a single count query is generated)
Limit = -1 (act like old 0 unlimited result)

:tada: This PR is included in version 9.0.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


Create the Draft Components

Create Film Box react app components to include;
Header
Carousel
Tiles/Cards
Modal
Filter methods*
Unique Material UI components

#8 Trying to push to repo need to get approval from Ameya and Marcus to complete push to repo

Completed by full team.


bugfix Fix time zone issues and accuracy issues

Proposed changes
Issue Number: close #38174

run buildall

run buildall

@xinyiZzz PTAL

is it possible to add some test?

is it possible to add some test?


Reusing viewpool for imgur sometimes doesn't clear state

Reported by @hzsweers
Description
A wild dribbble shot (or two) appeared

App
Version: 0.0.1-18-g1412a44-dev
Version code: 813

Device details
Make: Google
Model: Pixel
Resolution: 1794x1080
Density: 420dpi (420)
Release: 8.0.0
API: 26

Logs
No logs provided

I have a feeling this is related to #67, going to merge this into that


Dask with AOI

Thank you for submitting your PR and helping us with GDL.
Please read the template below, fill it out as appropriate, and make additional changes to your code as needed.
Please feel free to submit your PR even if it doesn't satisfy all of the requirements below.
If you need assistance or review from a maintainer, add the label Status: Help Needed or Status: Review Needed respectively.
After review, a maintainer will add the label Status: Revision Needed if further work is required for the PR to be merged.
Description
Please include a summary of the change and which issue is resolved (if applicable).
Please also include relevant motivation and context.
List any dependencies that are required for this change.
If it fixes an open issue, please link to the issue here.
Fixes # (issue)
Type of change
What types of changes does your code introduce? Put an x in all the boxes that apply:

[ ] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Other

How Has This Been Tested?
If the added changes are already cover by tests, skip that section.
Otherwise, please describe tests that you added to the pytest codebase (if applicable).
Screenshots (if applicable):
Checklist:
If you're unsure about any of these, don't hesitate to ask. We're here to help!

[ ] My code follows the code style of this project
[ ] I have performed a self-review of my own code
[ ] My PR has a descriptive title
[ ] My code follows PEP8 (most of it)
[ ] My code have the proper documentation in the code
[ ] I have made corresponding changes to the documentation (if applicable)
[ ] My changes generate no new errors
[ ] My code is covered by the existing tests (if applicable)
[ ] My code includes tests that show that my feature works
[ ] My PR passes Travis CI tests

If your PR does not fulfill all of the requirements in the checklist above, that's OK! If you need help, @-mention a maintainer and/or add the Status: Help Needed label.

Hello @MarjanAsgari just a quick comment until I can look further into your MR. First of all, thank you for these changes that, I heard, will greatly improve the speed of inference and help with memory management, among other things.
Can you please fill in MR description above? Also, it seems your MR includes many log files and test data. Were they added on purpose? If not, could you remove them please?


⚠ Bofrost.at has degraded performance

In b2af13a, Bofrost.at (https://www.bofrost.at) experienced degraded performance:

HTTP code: 200
Response time: 2029 ms

Resolved: Bofrost.at performance has improved in aafcdaf after 13 minutes.


[预研] 图像识别

https://github.com/NetEaseGame/aircv
https://github.com/tesseract-ocr/tesseract

https://github.com/PaddlePaddle/PaddleOCR


Could not find variable in saved models

Here are references for the issue https://github.com/tensorflow/tensorflow/issues/73158       and      https://github.com/tensorflow/tensorflow/issues/72963

also getting issue from cifar10_model and iris_model:      logs:                                                                                2024-08-08 08:16:11.407139: I external/org_tensorflow/tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable TF_ENABLE_ONEDNN_OPTS=0.
2024-08-08 08:16:11.500499: I tensorflow_serving/model_servers/server.cc:77] Building single TensorFlow model file config:  model_name: cifar10_model model_base_path: /models/cifar10_model
2024-08-08 08:16:11.503247: I tensorflow_serving/model_servers/server_core.cc:474] Adding/updating models.
2024-08-08 08:16:11.503278: I tensorflow_serving/model_servers/server_core.cc:603]  (Re-)adding model: cifar10_model
2024-08-08 08:16:11.709794: I tensorflow_serving/core/basic_manager.cc:740] Successfully reserved resources to load servable {name: cifar10_model version: 1}
2024-08-08 08:16:11.709855: I tensorflow_serving/core/loader_harness.cc:68] Approving load for servable version {name: cifar10_model version: 1}
2024-08-08 08:16:11.709884: I tensorflow_serving/core/loader_harness.cc:76] Loading servable version {name: cifar10_model version: 1}
2024-08-08 08:16:11.716917: I external/org_tensorflow/tensorflow/cc/saved_model/reader.cc:83] Reading SavedModel from: /models/cifar10_model/1
2024-08-08 08:16:11.729105: I external/org_tensorflow/tensorflow/cc/saved_model/reader.cc:52] Reading meta graph with tags { serve }
2024-08-08 08:16:11.729159: I external/org_tensorflow/tensorflow/cc/saved_model/reader.cc:147] Reading SavedModel debug info (if present) from: /models/cifar10_model/1
2024-08-08 08:16:11.730837: I external/org_tensorflow/tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-08-08 08:16:11.775236: I external/org_tensorflow/tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:388] MLIR V1 optimization pass is not enabled
2024-08-08 08:16:11.782870: I external/org_tensorflow/tensorflow/cc/saved_model/loader.cc:236] Restoring SavedModel bundle.
2024-08-08 08:16:11.948435: I external/org_tensorflow/tensorflow/cc/saved_model/loader.cc:220] Running initialization op on SavedModel bundle at path: /models/cifar10_model/1
2024-08-08 08:16:11.961415: I external/org_tensorflow/tensorflow/cc/saved_model/loader.cc:462] SavedModel load for tags { serve }; Status: success: OK. Took 244832 microseconds.
2024-08-08 08:16:11.963256: I tensorflow_serving/servables/tensorflow/saved_model_warmup_util.cc:82] No warmup data file found at /models/cifar10_model/1/assets.extra/tf_serving_warmup_requests
2024-08-08 08:16:12.070870: I tensorflow_serving/core/loader_harness.cc:97] Successfully loaded servable version {name: cifar10_model version: 1}
2024-08-08 08:16:12.073985: I tensorflow_serving/model_servers/server_core.cc:495] Finished adding/updating models
2024-08-08 08:16:12.074074: I tensorflow_serving/model_servers/server.cc:121] Using InsecureServerCredentials
2024-08-08 08:16:12.074608: I tensorflow_serving/model_servers/server.cc:388] Profiler service is enabled
2024-08-08 08:16:12.079460: I tensorflow_serving/model_servers/server.cc:423] Running gRPC ModelServer at <IP_ADDRESS>:8500 ...
[warn] getaddrinfo: address family for nodename not supported
2024-08-08 08:16:12.083437: I tensorflow_serving/model_servers/server.cc:444] Exporting HTTP/REST API at:localhost:8501 ...
[evhttp_server.cc : 250] NET_LOG: Entering the event loop ...
2024-08-08 08:17:38.815509: I external/org_tensorflow/tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: FAILED_PRECONDITION: Could not find variable sequential/conv2d/kernel. This could mean that the variable has been deleted. In TF1, it can also mean the variable is uninitialized. Debug info: container=localhost, status error message=Resource localhost/sequential/conv2d/kernel/N10tensorflow3VarE does not exist.
[[{{function_node __inference_serving_default_45404}}{{node sequential_1/conv2d_1/convolution/ReadVariableOp}}]]
2024-08-08 08:17:38.815626: I external/org_tensorflow/tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: ABORTED: Stopping remaining executors.
2024-08-08 08:17:45.111537: I external/org_tensorflow/tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: ABORTED: Stopping remaining executors.

HI @yashprakashsharma, this appears to be a duplicate of https://github.com/keras-team/keras/issues/20095 given the issue you referenced above. Closing the issue for now to avoid duplication, thanks!


Tweaks to scripts and docs to support prod Atlas host and containers

What
Changes to more easily support prod Atlas host and containers.
Add section in README about adding our ssh keys to the Atlas host so we can get into our containers the first time.

Forgot to sign this one. Abandoned and made changes on a different PR.


question about haplotype bam files

Hi, I am currently trying to phase a diploid genome assembled with nanopore data
and Ive been playing around with longshot. Everything looks good until now, I was just wondering what is the actual output of the phased bam files. Are this containing only the phased block or the actual reads associated to the complete haplotype, including common regions between both haplotypes? I ask this cause I have the intention of extracting those reads and reassembling every haplotype indepdendently.
Thanks for your time.

The haplotype-assigned bams are obtained by taking each read and calculating the probability that it came from either haplotype, based on the phased alleles found in the output VCF.
Reads that can be confidently assigned go in .hap1.bam or .hap2.bam, while the reads that fall below the --hap_assignment_qual go in .unassigned.bam.
Currently, the phase block that a read belongs to is not annotated. I.e, if there is a large unphaseable gap with two independent phase blocks on either side, the reads assigned to Hap1 for each block will be written to the same file and similarly for Hap2. Even though in real life, those reads are not confidently phased to one another. But, you could infer what block a read belongs to based on the PS annotations in the corresponding VCF (I.e. figure out the boundaries of SNVs with a specific PS annotation, and then extract that region from the phased BAM file)

Thanks for your quick response Peter.
Ok, so if I understand you well, in theory to try and re-assemble each haplotype independently , lets say H1, the reads to use should be the H1.bam reads combined with the unassigned reads?
Thanks.

no -- the unassigned reads contain a mixture of H1 and H2, they just didn't have enough evidence to confidently assign one way or the other.

Thanks for clarifying.
Thanks again.

To re-assemble independent haplotype for H1 just use the H1.bam. Just keep in mind that close range information is good (i.e. reads in the bam that are near each other on the chromosome are probably from the same haplotype), but the long-range information is probably not good (reads that are far away from one another on the chromosome may or may not be really from the same haplotype).

anytime -- good luck!

Hi, I have some errors following this ,how to solve it ?
2019-10-30 22:24:30 Min read coverage set to 6.
2019-10-30 22:24:30 Max read coverage set to 8000.
2019-10-30 22:24:30 Estimating alignment parameters...
[E::bgzf_read] Read block operation failed with error 2 after 0 of 4 bytes
error: Error estimating alignment parameters.
caused by: Error reading BAM record.
caused by: truncated record

@baishengjun Your issue does not seem to be related to the haplotype bam separation feature. Nonetheless, I'll try to answer. Can you verify that the bam is not corrupted? I've had errors similar to the one you describe and it is often a result of corruption. And would it be possible for you to create a shareable minimal example file that reproduces the issue?


Default to 'main' container in Sensor logs

Signed-off-by: jsvk<EMAIL_ADDRESS>Fixes #TODO

sorry still working on the write-up (in the form of Github Issue, hope that's ok), but the short summary is we're injecting a sidecar container to the Sensor pod (fluent-bit in our case, for forwarding logs to Splunk).
Without specifying the container, the UI fails to load the logs and instead returns with a 504 - Gateway Timeout.
Error logs in the Server pod say it encountered this error -
time="2022-08-25T14:30:21.960Z" level=error msg="a container name must be specified for pod adobe-platform--[snip], choose one of: [main fluent-bit]" namespace=ns-team-adobe-platform--[snip] podName=adobe-platform--[snip]

I saw the API does support parsing podLogOptions.container, and so by appending ?podLogOptions.container=main to the API call, I confirmed the call returns instantly with the logs we expect, so this is a matter of updating this at the UI level.
Is there a better approach I'm not thinking of?


Is there a way to disable editor caching on arrays?

This is not documented behaviour, so I'm not entirely sure if it's a feature or a bug. If it's a feature, I'm not sure why - it really only complicates and confuses the experience for the user.
If I remove an item from an array and then add a new one, I would expect the behaviour to be that a new, empty/default editor appears. Instead, the deleted editor simply reappears just as it was. In the very simplest cases, this is probably not really a problem, but if the object editor is extremely complex, with multiple objects/arrays of its own, it can be incredibly frustrating and annoying.
Is there an easy way to disable/remove/fix this behaviour?

+1

+1

+1

+1

Does anyone have a workaround?

+1

+1 from me as well. This behaviour is basically extremely broken for arrays of objects. The only workaround for the user is to create new items before deleting old ones.


update stu.txt

our school add a sub domain to use student mailbox

this is the login page.

@qzztf I am sorry, the domain stu.zuel.edu.cn is removed from our trusted domains list because the school allows to register an email address there even if you are not a student of the school. If you are the student of this school, please apply with official document (OFFICIAL DOCUMENT tab at https://www.jetbrains.com/shop/eform/students).


RKE - Cluster state keeps toggling between "active" and "unavailable" when adding a node with a name that is already name of existing node in cluster.

Rancher server: v2.0 built on jan 23.
Steps to reproduce the problem:
Create RKE cluster with 3 nodes say node1(ip1),node2(ip2) and node3 (ip3).
Added another node to the cluster with node name that is already existing in the cluster , say "node3"(ip4).
Node gets added to the cluster.
Cluster state keeps toggling between "active" and "unavailable" when adding a node with a name that is already name of existing node in cluster.
Following is the error state when node is in   "unavailable"  state:
"Not received heartbeat from cluster-agent"
In the Nodes page , I see the ip address of the newly added node , node3's ip address switching between ip3 and ip4 constantly.
Should RKE prevent a node with duplicate name to be added to the cluster?

@sangeethah this issue has been resolved from rke's side by validating duplicate nodes, also it has been resolved from the UI side, where you can't create two nodes with the same name

Tested with master from March 2nd. UI does not allow duplicate names for nodes. Although we can have duplicate pool names, the node names are always unique


Add cupy.format_float_scientific API

Hello!
This PR adds a version of format_float_scientific as requested in #6078 . This is my first contribution here, I hope it's the expected format and documented.

Thanks for your contribution! It's almost fine except for one I commented above.

/test mini

@kmaehashi, would you merge this if Jenkins looks okay?


Quantile Huber Loss to predict Specific Quantile Value

We know that we have huber loss function added in keras tf-2 already which can perform both kind of behaviour MSE and MAE depending on the scale of data. In most of the prediction and analysis models, we often do not need just median or mean predicted value, but we also need the specific quantile value of prediction. This is the loss function I am adding which is derived from huber_loss here
https://arxiv.org/pdf/1402.4624.pdf. I name it quantile_huber_loss and the class which calls it is QuantileHuber. I have given great attention to the detail in implementing the function. function takes two extra arguements delta and quantile, where delta is common as the huber_loss and quantile is the float number between 0 and 1. Equation looks as below.

@abhinavsagar @fchollet Please Review this PR. I have added QuantileHuber loss. As per my observation, this is first Quantile loss function added in keras. This branch has no conflict with the tf-2 branch. Although, Some default integration failures are there. Please review this PR.

Could you fix the build errors.

There are default build errors even before I added my code. Although, I have fixed the issues related to BinaryCrossEntropy and its tests. There are no additional failures other than default ones. @abhinavsagar

LGTM
Cc @fchollet

Thank you for preparing this PR.
We are no longer adding new features to multi-backend Keras, as we are refocusing development efforts on tf.keras. If you are still interested in submitting this PR, please direct it to tf.keras in the TensorFlow repository instead.

Thank you for preparing this PR.
We are no longer adding new features to multi-backend Keras, as we are refocusing development efforts on tf.keras. If you are still interested in submitting this PR, please direct it to tf.keras in the TensorFlow repository instead.

Thank you @fchollet , I will directly add it into tf.keras.


Webview scrollbars are seemingly unstyleable in Insiders

Here is what my webview scrollbars look like in 1.89.1:

Here is what they look like in 1.90-insiders:

Looks styled still based on the colors, just different rendering

They really don't look that similar (other than the colors are close) -- in the first the scrollbar has no corners (arrows) is much thinner, and what you can't tell in the screenshot is that it behaves just like other VS Code scrollbars in that it hides and fades based on hover/focus.
While in Insiders none of those style are taking affect -- it seems ::-webkit-scrollbar* properties don't seem to apply anymore.
So we seem to be stuck with almost standard platform scrollbars.

Version: 1.90.0-insider (Universal)
Commit: 81c89c4d00663e1718871bab2f9bf2064a060b63
Date: 2024-05-22T09:32:21.946Z
Electron: 29.3.1
ElectronBuildId: 9464424
Chromium: 122.0.6261.156
Node.js: 20.9.0
V8: 12.2.281.27-electron.0
OS: Darwin arm64 22.6.0
I see a similar issue.

Executing Webview View API Sample: https://github.com/microsoft/vscode-extension-samples/tree/main/webview-view-sample
The background color of the scrollbar is white.

A workaround is adding the following to main.css:
html {
	scrollbar-color: var(--vscode-scrollbarSlider-background) var(--vscode-sideBar-background);
}

Adding ::-webkit-scrollbar* doesn't work.

This is now broken in Stable -- @isidorn can we get a fix or resolution on this, since this is a regression from existing webview behavior.

If this is a confirmed regression, it would help to know which change caused it. We maintain a node.js based CLI tool  vscode-bisect that automatically downloads and runs previous VS Code insiders and asks for each build if the issue reproduces. It takes up to 8 steps to find exactly the build that caused the regression.
Steps:

install node.js (if not yet done)
npx --yes @vscode/vscode-bisect@latest
follow the instructions until you found the offending build (its fine to leave the commit empty)
report back the commit range in this issue

Thanks!

same issue

same issue.
Made it thinner with this:
body {
  scrollbar-width: thin;
  scrollbar-color: var(--vscode-scrollbarSlider-background) transparent;
 }

But still not like before !

So this is a behavior change in Chrome 121 -- if scrollbar-color or scrollbar-width are used then the ::-webkit-scrollbar* props are ignored.
And the webview's index.html sets scrollbar-color.
I've opened #220121 to address this, but in the meantime, extensions can work around this by adding html { scrollbar-color: unset; } in their webview css to workaround this.

JFYI - I see the same problem in stable now.
Version: 1.92.2 (user setup)
Commit: fee1edb8d6d72a0ddff41e5f71a671c23ed924b9
Date: 2024-08-14T17:29:30.058Z
Electron: 30.1.2
ElectronBuildId: 9870757
Chromium: 124.0.6367.243
Node.js: 20.14.0
V8: <IP_ADDRESS>-electron.0
OS: Windows_NT x64 10.0.22631


Create uprm-civic.nrel-op.json

Created UPRM CIVIC config based on their MOU

I added the mode_studied field and set it to e-bike for now.

did you compare against a few other programs? or just pick from stage-program?

@sebastianbarry I have squash-merged, please pull from upstream before submitting any other changes.

did you compare against a few other programs? or just pick from stage-program?

I actually copied it from wyoming but removed mode_studied since I didn't see that specified in the MOU


auto-commit does not auto-install

m1:auto-commit nv$ curl -fsSL https://raw.githubusercontent.com/m1guelpf/auto-commit/main/install.sh | sh -
https://github.com/m1guelpf/auto-commit/releases/latest/download/auto-commit-darwin-aarch64
downloading latest binary
  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0
  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0
100 5023k  100 5023k    0     0  1009k      0  0:00:04  0:00:04 --:--:-- 1147k
installed - Auto Commit 0.1.5
m1:auto-commit nv$ auto-commit --help
-bash: auto-commit: command not found
m1:auto-commit nv$

I realize the issue is because I am using ~/.profile instead of ~/.bashrc
I would recommend at least putting a note in the README, or at most automatically detecting which file is being loaded in.

We're trying to do both! See the note about restarting your terminal in the README, and the install script. Any ideas to improve are welcome :D

It's not about restarting the terminal. From what I understand, if ~/.profile exists on macOS, then it will not load ~/.bashrc unless you explicitly tell it to e.g. source ~/.bashrc
The current installation process will only append the necessary config in ~/.bashrc
Because macOS loads several configs in a certain order, it could be useful to detect that to smooth the installation process!

Hi @pavlovcik, what is the workaround for someone using ~/.bashrc ?

source ~/.bashrc in ~/.profile
To clarify, I moved everything into ~/.bashrc and now my ~/.profile in its entirety appears as follows:

#!/bin/bash/env bash
source ~/.bashrc


Generalize for other distributions

…starting with Debian derivatives such as Ubuntu.
For now, this issue tracks things which are specific to Debian, so that we can come up with a good way to make the relevant parts pluggable.

file
specifically
Debian only
Debian & derivatives only

rendermanpage.go
bySuite
-
yes

renderaux.go
bySuiteStr
-
yes

archive.go
-
-
yes

getcontents.go
-
yes
-

getpackages.go
-
yes
-

download.go
-
yes
-

i documented this in the FAQ section: https://anonscm.debian.org/git/srv-manpages/debian-assets.git/tree/faq.tmpl?h=faq


Subtask #1: Related to #69 Configure Statistics - Adding average speed to the strings.xml

Description
To access the Strings.xml file, it is necessary to create entries for average speed strings. These entries will allow the application to display average speed in both kilometers per hour and miles per hour.

Added the string for average speed in km/h in string.xml.
The necessary changes were made to the code and pushed from branch Group-13 to main after the review was done.
commit id: [d3077f3]


datetime substitution is broken

@rultor release, tag is 0.0.23

@rultor release, tag is 0.0.23

@yegor256 OK, I will release it now. Please check the progress here.

@rultor release, tag is 0.0.23

@yegor256 Done! FYI, the full log is here (took me 5min).


VB-1157-Defect---correct-R__VB-819_add_hewell_code_HEI_prison_data.sql

What does this pull request do?
corrects a case issue with the main room name from visits main room to Visits Main Room
What is the intent behind these changes?
to match VSiP with other services

@AledWEvans I wonder if this is correct now since there is no main visits room, we just have Open, Closed and Unknown on the visits page now.

It's a funny one really! is still used in migration and we were getting different cases, so all this PR does is make the case consistent, see https://dsdmoj.atlassian.net/browse/SDI-224. We should perhaps remove it later...


[Wait for #2489,#2495,#2497,#2498][Tensor] Refactorize Tensor Class to TensorV2 @open sesame 03/08 16:34

This pull request introduces a major refactorization of the Tensor class in our codebase by introducing the new TensorV2 class.
The previous Tensor class is removed, and all instances where it was used have been updated accordingly.
With this change, the overall functionality and stability of our system are expected to be increased.
Self-evaluation:

Build test: [X]Passed [ ]Failed [ ]Skipped
Run test:   [X]Passed [ ]Failed [ ]Skipped

:memo: TAOS-CI Version: 1.5.20200925. Thank you for submitting PR #2500. Please a submit 1commit/1PR (one commit per one PR) policy to get comments quickly from reviewers. Your PR must pass all verificiation processes of cibot before starting a review process from reviewers. If you are new member to join this project, please read manuals in documentation folder and wiki page. In order to monitor a progress status of your PR in more detail, visit http://ci.nnstreamer.ai/.

:octocat: cibot: @djeong20, A builder checker could not be completed because one of the checkers is not completed. In order to find out a reason, please go to http://ci.nnstreamer.ai/nntrainer/ci/repo-workers/pr-checker/2500-202403081422460.15307211875916-b86dc2ac092b931ae8f75ce2bb55d4d3439f18ad/.

:octocat: cibot: @djeong20, A builder checker could not be completed because one of the checkers is not completed. In order to find out a reason, please go to http://ci.nnstreamer.ai/nntrainer/ci/repo-workers/pr-checker/2500-202403081634500.4846498966217-b86dc2ac092b931ae8f75ce2bb55d4d3439f18ad/.

I could find trivial typos or missed descriptions, but think it is not the major target of this PR. Overall, LGTM! Thanks for your hard work! :)

please comment on the parts where it has typos or missed descriptions so I can fix it!

:octocat: cibot: @djeong20, A builder checker could not be completed because one of the checkers is not completed. In order to find out a reason, please go to http://ci.nnstreamer.ai/nntrainer/ci/repo-workers/pr-checker/2500-202403251656290.69447207450867-ad6b0199cba783153747fa51028a3ff05f9c7597/.


Where is symbols folder in Inkscape 0.92? (Mac OSX)

Hi Guys. Happy new year!
I'm following instructions of this project to install new symbols in my brand new Inkscape 0.92 on a Mac. However this folder does not seem to exist. (~/.config/inkscape/symbols)
Any advices? Thanks in advance.

Great! :tada:


Rendering Performance

Hi,
I have a view where I have to display 480 sliders (120 rows with 4 sliders each).
Once the view is rendered it looks nice and every slider can be used without any delay.
But the rendering process takes als 5-7 seconds, which is not really acceptable.
In the console log I see again some violation issues:
[Violation] 'message' handler took 5208ms
[Violation] Forced reflow while executing JavaScript took 4087ms
---
[Violation] 'click' handler took 11076ms
[Violation] Forced reflow while executing JavaScript took 6416ms
[Violation] 'resize' handler took 15084ms
[Violation] Forced reflow while executing JavaScript took 2992ms

As I need only a simple layout, I already tried to disable all possible options.

  defaultOptions: Options = {
    floor: 0,
    ceil: 255,
    step: 1,
    noSwitching: true,
    hideLimitLabels: true,
    hidePointerLabels: true,
    showOuterSelectionBars: false,
    showSelectionBarEnd: false,
    showSelectionBar: false,
    showTicksValues: false
  };

Is there more I can tweak?

The problem in this case is that initial render of the slider is always going to be slow, as a result of the design.
The slider can't set the positions and styles of its sub-elements until it knows the dimensions of its container in the DOM. So the slider waits until it is rendered for the first time, and then initialises itself, adjusting the styles of its sub-elements as necessary. This is also complicated somewhat by Angular, because once the view has changed (again), Angular change detection kicks in, re-checking all the bindings.
I would also say that 480 dynamic elements on a page, be it sliders or something else, is already quite a lot to handle for the browser. I think you are going to see performance issues no matter what component you use.

I expected something like this and can understand the background.
The thing is, if I switch to the standard input type=range elements, it's loading/rendering the page within 400-600ms, which is absolutely acceptable.

With this I only need the ng5 slider for the 'real' range mode, which is ok if I just need the basic style.
As you can see I just need the basic elements. Is there maybe an option (with some triggers) to reduce the layout/DOM elements to decide between functionality and performance?

No, I'm afraid it's all or nothing at the moment. The time it takes for each slider to initialise itself and apply all the styles just adds up.
Now, there might be a way to improve it, by cutting out some of Angular's overhead, and possibly skipping some initialisation steps when they are not needed. But to do that, I'll need to profile the code and I'll see what I can do.


After connecting to outline, the connection via SSH is interrupted

Subj

This is to be expected. If you try to connect to a VPN mid-session, it will result in asymmetric routing, which may (and usually does) cause some network devices along the way to simply discard the packets. This is just how things are, so I don't think there's something to be done here.
However, you can easily configure the routing on your machine to your liking! If you don't require a VPN to connect to your server, you may as well inform your system about that:
sudo ip rule add from all to <ip-of-the-target-machine> table main priority 23331

Hope this helps! :)

"sudo ip rule add from all to  table main priority 23331"
Unfortunately it didn't work.
There are no such problems with the official client  Outline-Client.AppImage.  But it cannot be controlled via SSH and cli.

Apologies for the late response!

Unfortunately it didn't work.

That's strange - it consistently works on my machine. The only thing is that this solution isn't persistent. Did you happen to reboot between attempts? Also, which distro are you using?

The same problem is here. After enabling vpn all inbound connections to the server are unavailable.

Could you please describe your issue in more detail and explain how it can be reproduced?

Could you please describe your issue in more detail and explain how it can be reproduced?

You have
1 Remote server
2 Your Workstation
You need to run outline-cli on Remote server so applications on the server can make outgoing connection through ‘vpn’.
So you do on your workstation (suppose outline-cli is already installed on the remote server):
<local>$ ssh <remote server>
<remote>$ vpn connect 1

After vpn is up you can’t connect your remote server from your workstation until you somehow make vpn disconnected. That is the big problem.
PS: And another problem I found is when restarting server Network Manager make the connection up that make is much harder to make the remote server connectable - nice trap :)

Oh, yikes. I sincerely hope the remote server here is a test machine and that this didn't happen to your production server or anything critical! If it did, you'll need to detach the storage disk from your server (hopefully, your cloud provider allows this), attach it to a temporary droplet, chroot into it, and rm /var/lib/outline/session to bring the machine back to life.
Okay, back to the issue at hand. outline-cli redirects all of your traffic to the VPN server. Based on the limited feedback I have, the Outline Client works a bit differently in this regard and uses split tunneling somewhere along the way (I couldn't test it myself since the Outline Client only seems to work on Ubuntu, and maybe Debian). I'm not sure if it uses allowlists or denylists, but in our case, it's more natural to go with the latter. I already have rules in place to block requests to the LAN from being forwarded (fun fact: for better or worse, I forgot to make them persistent, so they only work until the first reboot). However, it's not as simple with "SSH requests", as they aren't as easily identifiable.
The simplest solution I suggested to the author of this issue was to hardcode the IP of the target machine to prevent redirection and avoid asymmetric routing. Unfortunately, that didn't work for them for some reason. Maybe I misread their problem, and they were also trying to connect their server to a VPN instead of their desktop.
However, hardcoding IPs clearly isn't a viable long-term solution for a server that could theoretically accept requests from any machine in the world. In this scenario, we could try identifying SSH traffic by the port it uses, which is typically port 22 (though some people tend to change it, thinking this makes their machine more "secure"). To do this, we can first mangle all the traffic traveling through that port and attach a special mark to it so we can identify it later:
# SSH doesn't use UDP for anything, at least anymore, so TCP rules should suffice
iptables -t mangle -A PREROUTING -p tcp --dport 22 -j MARK --set-mark 22
iptables -t mangle -A OUTPUT -p tcp --sport 22 -j MARK --set-mark 22

Then, we can exclude this marked traffic from being rerouted by running:
ip rule add fwmark 22 table main priority 23331

You can check if this works for you (please, don't try this on a production server in case something doesn't work right the first time! :))
However, note that these rules ARE NOT PERSISTENT! They'll be lost as soon as the machine reboots. So, you'll need to run these commands every time the server starts to ensure you can connect to it afterward.
Since I need to fix the LAN rerouting issue anyway, I could create a better config for outline-cli that would allow you to specify which traffic should be exempt from rerouting. By default, it might include the following rules:
# LAN
<IP_ADDRESS>/16
<IP_ADDRESS>/12
<IP_ADDRESS>/8

# TUN
!<IP_ADDRESS>
!<IP_ADDRESS>

# SSH
:22

If someone needs to add their own rules, for example, if they've changed their SSH port, they'll be able to do so easily. How does that sound?

@Kir-Antipov I'm not an expert in all that network staff :) As I understand we will have the config where we can exclude traffic by networks or by protocols(like ssh) from rerouting them to 'vpn'. If this is correct then it sounds good.
ps: In spite of all this obstacles, thank you for your attempt to make outline-cli more friendly.


ansible-lint 2.3.5 introduces octal file permissions errors

ansible-lint 2.3.5 starting failing the gate checks with the following
  play #1 (Verify MaaS setup):	TAGS: []
    Verify Checks & Alarms are registered	TAGS: []
    Allow MAAS time to run checks before verifying their status	TAGS: []
    Verify Check & Alarm Status	TAGS: []

ansible-lint 2.3.5
Running ansible-lint

[ANSIBLE0008] Octal file permissions must contain leading zero
/home/travis/build/rcbops/rpc-openstack/rpcd/playbooks/roles/logstash/tasks/logstash_post_install.yml:22
    mode: 644

[ANSIBLE0008] Octal file permissions must contain leading zero
/home/travis/build/rcbops/rpc-openstack/rpcd/playbooks/roles/beaver/tasks/beaver_install.yml:47
    mode: 755

[ANSIBLE0008] Octal file permissions must contain leading zero
/home/travis/build/rcbops/rpc-openstack/rpcd/playbooks/roles/beaver/tasks/beaver_install.yml:59
    mode: 644

This happens locally, and downgrading to 2.3.0 works.
Branches:

[x] master
[x] kilo

Needs backport

Backport is #818

Assigned @prometheanfire since he's done the kilo backport.

fixed, closing


Temporarily run integration tests just on linux

This commit changes the workflow which test executed when building
integration tests of PRs coming from forks (Run Integration Tests
for Forks). It temporarily disables builds to run on MacOS and Windows.

nitpick: Could you add the reason "why" running on different OSs in parallel is disabled to your commit message?
relates to issue #30

nitpick: Could you add the reason "why" running on different OSs in parallel is disabled to your commit message?
relates to issue #30

Changed the commit message and PR description.


building-easygenivigo-in-jenkins: Do not runme.sh

Replace it with docker-compose up
until https://github.com/gmacario/easy-genivigo/issues/2 is resolved
Signed-off-by: Gianpaolo Macario<EMAIL_ADDRESS>

LGTM, merging


Update docker agent to work in domain mode

Also updates start-with-hawkular.sh to expect server url instead of hostname.
This allows to specify https (if needed) or a different port.

LGTM


maya-apiserver fails to create replicas when the "size" attribute in volumeClaimTemplates is given in a format "Gi" and "Mi".

Is this a BUG REPORT or FEATURE REQUEST?
BUG REPORT

What happened:
Most of the examples that Kubernetes has in its repo, uses the "Gi" or "Mi" notation to specify the volume size. If the same is provided for openebs, it fails to create the persistent storage as the replicas fail to launch.
What you expected to happen:
maya-apiserver must be able to also accept formats that are followed in the Kubernetes examples and not fail to provide persistent storage.
How to reproduce it (as minimally and precisely as possible):

Use and YAML having volumeClaimTemplates
Provide openebs-basic (or any openebs storage class) as the storage class for persistent storage.
For the size attribute, provide the size as 5Gi
When the YAML is applied the replicas fail to create and end up in CrashloopBackof.
Anything else we need to know?:

Environment:

kubectl get nodes
kubectl get pods --all-namespaces
kubectl get services
kubectl get sc
kubectl get pv
kubectl get pvc
OS (e.g. from /etc/os-release):
Kernel (e.g. uname -a):
Install tools:
Others:

An iterm fix has been merged with https://github.com/openebs/jiva/pull/32
Keeping this open for the next release to resolve this with a cleaner solution.


Footer jsx

Closes #2284
Render the footer in JSX

I feel the lift and shift of these components has left us with quite a lot of stuff to tidy in the common folder.


how to drag a model in vertical plane?

i add a model in vertical plane,but can't drag it in vertical orientation .

Can you provide a code snippet on how you are implementing the drag?

Were you able to get the drag working? Closing this issue due to inactivity but please re-open if you are still having issues.


cmd/link: need to add buildids to wasm modules

dist is failing for js/wasm right now (when run via make.bash, etc) due to missing buildids:
https://build.golang.org/log/4dfe5bd474996d98e85d77bfa4f63b9713b2ccbe
Repro:
$ GOOS=js GOARCH=wasm ./make.bash

@rsc says:

the reason things look stale is that cmd/go recomputes what the expected build id is and then looks in the binary to see if that's the recorded buildid. if so, not stale. if not, then it's stale
go tool buildid $GOROOT/pkg/tool/js_wasm/dist
prints an empty string
looks like the build id is not in the binary
...
what we do on systems with inflexible object formats (like darwin and windows) is arrange for the build id to appear early in the binary (in teh first few kilobytes) as string data
and we search for a magic indicator to find it.
src/cmd/link/internal/ld/data.go textbuildid
so wasm should do something like that too
we almost certainly want build ids generally. it's not just about dist
...
it's going to just keep rebuilding because it looks out of date
i mean, i don't think we'll run any of the binaries in pkg/js_wasm/tool
but still

/cc @neelance @ianlancetaylor

The linker's Link.textbuildid code is running and prepending to ctx.Textp, and then cmd/link/internal/wasm/asm.go has code that looks for it:
        for i, fn := range ctxt.Textp {
                wfn := new(bytes.Buffer)
                if fn.Name == "go.buildid" {
                        writeUleb128(wfn, 0) // number of sets of locals
                        writeI32Const(wfn, 0)
                        wfn.WriteByte(0x0b) // end

                } else {

I think we need to note the string value there and add a wasm data section early in the module. Not sure it's valid to have multiple data sections, though. (I'd considered a name, but names must be UTF-8, and the buildid is intentionally invalid UTF-8)

Ah, we can use a custom section. Perfect.
CL forthcoming.


Tensorflow Addons connected components not working properly

Please make sure that this is a bug. As per our
GitHub Policy,
we only address code/doc bugs, performance issues, feature requests and
build/installation issues on GitHub. tag:bug_template
System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): yes
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Windows 10
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
TensorFlow installed from (source or binary): binary
TensorFlow version (use command below): 2.4.0
Python version: 3.8.5
Bazel version (if compiling from source):
GCC/Compiler version (if compiling from source):
CUDA/cuDNN version: Cuda compilation tools, release 10.1, V10.1.243
GPU model and memory: GEForce GTX 1080 Ti, 11264 MB Dedicated Video Memory (I'm using CPU)

You can collect some of this information using our environment capture
script
You can also obtain the TensorFlow version with:

TF 1.0: python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"
TF 2.0: python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"

Describe the current behavior
TFA connected components should produce 2 components with the attached script. It is not.
Describe the expected behavior
TFA result should show same number of components as Scipy.ndimage.measurements.label, as claimed in the documentation
Standalone code to reproduce the issue
Provide a reproducible test case that is the bare minimum necessary to generate
the problem. If possible, please share a link to Colab/Jupyter/any notebook.
"""
TFA Addons Connected Components check
Using:
TensorFlow 2.4.0
Python 3.8.5
TFA 0.12.1
Scipy 1.6.1

"""
import tensorflow
import numpy as np
import tensorflow_addons as tfa
import matplotlib.pyplot as plt
import scipy.ndimage.measurements as meas
with tensorflow.device('/CPU:0'):
M = 500
img = np.zeros((M, M))

# One square
top = 50
bottom = 270
left = 300
right = 450
img[np.ix_(np.arange(top, bottom + 1), np.arange(left, right + 1))] = 1

# Second one
top = 100
bottom = 150
left = 200
right = 250
img[np.ix_(np.arange(top, bottom + 1), np.arange(left, right + 1))] = 1

# Convert image to tensor
img = tensorflow.convert_to_tensor(img)
imgtf = tensorflow.expand_dims(img, -1)

# Connected components with TFA
d_img_tfa = tfa.image.connected_components(imgtf).numpy()

# Plot it
plt.figure()
plt.title('TFA Connected Components Image')
_ = plt.imshow(d_img_tfa)
plt.show(block=False)

# Connected components with scipy
d_img_scipy, _ = meas.label(imgtf)

# Count number of non-background components (subtract 1 for background)
num_comp_tfa = np.unique(d_img_tfa.flatten()).size - 1
num_comp_scipy = np.unique(d_img_scipy.flatten()).size - 1

# These images should be the same
print("\nTFA connected components has %d components." % num_comp_tfa)
print("Scipy connected components has %d components.\n" % num_comp_scipy)

# Plot
plt.figure()
plt.title('Scipy Connected Components Image')
_ = plt.imshow(d_img_scipy)
plt.show(block=True)

Other info / logs Include any logs or source code that would be helpful to
diagnose the problem. If including tracebacks, please include the full
traceback. Large logs and files should be attached.

@jeball
I ran the code shared and face a different error, please refer to this gist here.

Remove the plot commands – the print statements will show different numbers. Alternately just squeeze the last dimension out.
John Ball, Ph.D.
Associate Professor and Robert Guyton Endowed Chair for Teaching Excellence | Electrical and Computer Engineering
<EMAIL_ADDRESS>Associate Editor | IEEE Signal Processing Letters
Associate Editor | Journal of Applied Remote Sensing
Editorial Board Member | MDPI Electronics
Faculty Advisory Council | Transactions on Stem Education
Lab Director | Simrall Radar Laboratory
Lab Co-Director | Center for Advanced Vehicular Systems (CAVS) Sensor Lab
Research Fellow | Geosystems Research Institute (GRI)
Simrall 233, 406 Hardy Rd., Mississippi State, MS 39762
p:662.325.4169  e:jeball<EMAIL_ADDRESS>From: Saduf2019<EMAIL_ADDRESS>Sent: Monday, March 1, 2021 3:28 AM
To: tensorflow/tensorflow<EMAIL_ADDRESS>Cc: Ball, John<EMAIL_ADDRESS>Mention<EMAIL_ADDRESS>Subject: Re: [tensorflow/tensorflow] Tensorflow Addons connected components not working properly (#47451)
@jeballhttps://secure-web.cisco.com/1vUn2dmy25OnfaqG2wLu54VMP7WdGqLYRUOy2zg4ZhpoAKjb0vS5GtAVO45oQeztm97ds6K1W75j0trRQU5EfdwtRbSN_AHyKKJphuR79fwHToQ4eIOFHB8AQ3NYJZ4bFf6u_5siUoy9sUWrPhUKTkGnS7DYcH53oogiphYX7mpY8dc6MB2MYMHnekokv5Yd9JZuliOMFa2LqYj_u7uzqobnvrKSGSyG90MLS7RD4zYMc1TQ0vgwG1pnn7RD3FZViAM4TJLbmlytvVqW6UPVDChg0kNyJ0B--bx98EUnvzB36zj_e9X9EX2kJ0eZq-c5h/https%3A%2F%2Fgithub.com%2Fjeball
I ran the code shared and face a different error, please refer to this gist herehttps://secure-web.cisco.com/1WIBilSUPM0uE_IQSF69SXlOgInrP054t_ngzJmOVNZQs956TtyBNDKAut26CoSSZIlLhWOixerkjHns14Klp1sCppCHLADR971lIR8tw-7gtDjbdqyGEMk3qOQdbjZ3eQRdg4VkvtfDKYWi8srpFC6gZaKsYf4COUu23rvxrXcPVB35nWOQqV-vpU9Fe0G_5b9C1MU4X6Gt_ZcnqONJQ4v5EdwnNe_CSruqoFLFq1C03AO2kv0sMQ5ljLP6KOoqWvAiuPwByV4b34ZSIoePhuWaACeYz_QJUgQJEdpOezOW5nBAVXyIPq7494Ps9JgI7/https%3A%2F%2Fcolab.sandbox.google.com%2Fgist%2FSaduf2019%2Fd5326e86b8bd3905ab35163d41e20189%2Funtitled554.ipynb.
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I have made the changes in the notebook. Code runs now.
John Ball, Ph.D.
Associate Professor and Robert Guyton Endowed Chair for Teaching Excellence | Electrical and Computer Engineering
<EMAIL_ADDRESS>Associate Editor | IEEE Signal Processing Letters
Associate Editor | Journal of Applied Remote Sensing
Editorial Board Member | MDPI Electronics
Faculty Advisory Council | Transactions on Stem Education
Lab Director | Simrall Radar Laboratory
Lab Co-Director | Center for Advanced Vehicular Systems (CAVS) Sensor Lab
Research Fellow | Geosystems Research Institute (GRI)
Simrall 233, 406 Hardy Rd., Mississippi State, MS 39762
p:662.325.4169  e:jeball<EMAIL_ADDRESS>From: Saduf2019<EMAIL_ADDRESS>Sent: Monday, March 1, 2021 3:28 AM
To: tensorflow/tensorflow<EMAIL_ADDRESS>Cc: Ball, John<EMAIL_ADDRESS>Mention<EMAIL_ADDRESS>Subject: Re: [tensorflow/tensorflow] Tensorflow Addons connected components not working properly (#47451)
@jeballhttps://secure-web.cisco.com/1vUn2dmy25OnfaqG2wLu54VMP7WdGqLYRUOy2zg4ZhpoAKjb0vS5GtAVO45oQeztm97ds6K1W75j0trRQU5EfdwtRbSN_AHyKKJphuR79fwHToQ4eIOFHB8AQ3NYJZ4bFf6u_5siUoy9sUWrPhUKTkGnS7DYcH53oogiphYX7mpY8dc6MB2MYMHnekokv5Yd9JZuliOMFa2LqYj_u7uzqobnvrKSGSyG90MLS7RD4zYMc1TQ0vgwG1pnn7RD3FZViAM4TJLbmlytvVqW6UPVDChg0kNyJ0B--bx98EUnvzB36zj_e9X9EX2kJ0eZq-c5h/https%3A%2F%2Fgithub.com%2Fjeball
I ran the code shared and face a different error, please refer to this gist herehttps://secure-web.cisco.com/1WIBilSUPM0uE_IQSF69SXlOgInrP054t_ngzJmOVNZQs956TtyBNDKAut26CoSSZIlLhWOixerkjHns14Klp1sCppCHLADR971lIR8tw-7gtDjbdqyGEMk3qOQdbjZ3eQRdg4VkvtfDKYWi8srpFC6gZaKsYf4COUu23rvxrXcPVB35nWOQqV-vpU9Fe0G_5b9C1MU4X6Gt_ZcnqONJQ4v5EdwnNe_CSruqoFLFq1C03AO2kv0sMQ5ljLP6KOoqWvAiuPwByV4b34ZSIoePhuWaACeYz_QJUgQJEdpOezOW5nBAVXyIPq7494Ps9JgI7/https%3A%2F%2Fcolab.sandbox.google.com%2Fgist%2FSaduf2019%2Fd5326e86b8bd3905ab35163d41e20189%2Funtitled554.ipynb.
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Not sure changes get saved?
Add these lines in
d_img_tfa = np.squeeze(d_img_tfa)
and
d_img_scipy = np.squeeze(d_img_scipy)
just before the plots.
John Ball, Ph.D.
Associate Professor and Robert Guyton Endowed Chair for Teaching Excellence | Electrical and Computer Engineering
<EMAIL_ADDRESS>Associate Editor | IEEE Signal Processing Letters
Associate Editor | Journal of Applied Remote Sensing
Editorial Board Member | MDPI Electronics
Faculty Advisory Council | Transactions on Stem Education
Lab Director | Simrall Radar Laboratory
Lab Co-Director | Center for Advanced Vehicular Systems (CAVS) Sensor Lab
Research Fellow | Geosystems Research Institute (GRI)
Simrall 233, 406 Hardy Rd., Mississippi State, MS 39762
p:662.325.4169  e:jeball<EMAIL_ADDRESS>From: Saduf2019<EMAIL_ADDRESS>Sent: Monday, March 1, 2021 3:28 AM
To: tensorflow/tensorflow<EMAIL_ADDRESS>Cc: Ball, John<EMAIL_ADDRESS>Mention<EMAIL_ADDRESS>Subject: Re: [tensorflow/tensorflow] Tensorflow Addons connected components not working properly (#47451)
@jeballhttps://secure-web.cisco.com/1vUn2dmy25OnfaqG2wLu54VMP7WdGqLYRUOy2zg4ZhpoAKjb0vS5GtAVO45oQeztm97ds6K1W75j0trRQU5EfdwtRbSN_AHyKKJphuR79fwHToQ4eIOFHB8AQ3NYJZ4bFf6u_5siUoy9sUWrPhUKTkGnS7DYcH53oogiphYX7mpY8dc6MB2MYMHnekokv5Yd9JZuliOMFa2LqYj_u7uzqobnvrKSGSyG90MLS7RD4zYMc1TQ0vgwG1pnn7RD3FZViAM4TJLbmlytvVqW6UPVDChg0kNyJ0B--bx98EUnvzB36zj_e9X9EX2kJ0eZq-c5h/https%3A%2F%2Fgithub.com%2Fjeball
I ran the code shared and face a different error, please refer to this gist herehttps://secure-web.cisco.com/1WIBilSUPM0uE_IQSF69SXlOgInrP054t_ngzJmOVNZQs956TtyBNDKAut26CoSSZIlLhWOixerkjHns14Klp1sCppCHLADR971lIR8tw-7gtDjbdqyGEMk3qOQdbjZ3eQRdg4VkvtfDKYWi8srpFC6gZaKsYf4COUu23rvxrXcPVB35nWOQqV-vpU9Fe0G_5b9C1MU4X6Gt_ZcnqONJQ4v5EdwnNe_CSruqoFLFq1C03AO2kv0sMQ5ljLP6KOoqWvAiuPwByV4b34ZSIoePhuWaACeYz_QJUgQJEdpOezOW5nBAVXyIPq7494Ps9JgI7/https%3A%2F%2Fcolab.sandbox.google.com%2Fgist%2FSaduf2019%2Fd5326e86b8bd3905ab35163d41e20189%2Funtitled554.ipynb.
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@jeball
I have added the two lines as suggested but face the same error, please share a colab gist with the error reported.

Hello support,
The lines were not there?
Please install TF 2.4, not a nightly build. TFA does not seem compatible to this version.
Please use the commands below.
pip install tensorflow==2.4
pip install tensorflow-addons[tensorflow]
The script is shown below.
""
TFA Addons Connected Components not working properly
Using:
TensorFlow 2.4.0
Python 3.8.5
TFA 0.12.1
Scipy 1.6.1

To install:
pip install tensorflow==2.4
pip install tensorflow-addons[tensorflow]

"""
import tensorflow as tf
import numpy as np
import tensorflow_addons as tfa
import matplotlib.pyplot as plt
import scipy.ndimage.measurements as meas
with tf.device('/CPU:0'):
M = 500
img = np.zeros((M, M))

# One square
top = 50
bottom = 270
left = 300
right = 450
img[np.ix_(np.arange(top, bottom + 1), np.arange(left, right + 1))] = 1

# Second one
top = 100
bottom = 150
left = 200
right = 250
img[np.ix_(np.arange(top, bottom + 1), np.arange(left, right + 1))] = 1

# Convert image to tensor
img = tf.convert_to_tensor(img)
imgtf = tf.expand_dims(img, -1)

# Connected components with TFA
d_img_tfa = tfa.image.connected_components(imgtf).numpy()

# Remove last dimension and convert to numpy matrix
d_img_tfa = tf.squeeze(d_img_tfa, axis=-1).numpy()

# Plot it
plt.figure()
plt.title('TFA Connected Components Image')
_ = plt.imshow(d_img_tfa)
plt.show(block=False)

# Connected components with scipy
d_img_scipy, _ = meas.label(imgtf)
d_img_scipy = tf.squeeze(d_img_scipy, axis=-1).numpy()

# Count number of non-background components (subtract 1 for background)
num_comp_tfa = np.unique(d_img_tfa.flatten()).size - 1
num_comp_scipy = np.unique(d_img_scipy.flatten()).size – 1

John Ball, Ph.D.
Associate Professor and Robert Guyton Endowed Chair for Teaching Excellence | Electrical and Computer Engineering
<EMAIL_ADDRESS>Associate Editor | IEEE Signal Processing Letters
Associate Editor | Journal of Applied Remote Sensing
Editorial Board Member | MDPI Electronics
Faculty Advisory Council | Transactions on Stem Education
Lab Director | Simrall Radar Laboratory
Lab Co-Director | Center for Advanced Vehicular Systems (CAVS) Sensor Lab
Research Fellow | Geosystems Research Institute (GRI)
Simrall 233, 406 Hardy Rd., Mississippi State, MS 39762
p:662.325.4169  e:jeball<EMAIL_ADDRESS>From: Saduf2019<EMAIL_ADDRESS>Sent: Tuesday, March 2, 2021 4:34 AM
To: tensorflow/tensorflow<EMAIL_ADDRESS>Cc: Ball, John<EMAIL_ADDRESS>Mention<EMAIL_ADDRESS>Subject: Re: [tensorflow/tensorflow] Tensorflow Addons connected components not working properly (#47451)
@jeballhttps://secure-web.cisco.com/1e-c4_AW70HcU3XZ1qPKrfcApKk5l3DY5GESvMf-MzmQmpJS8_cSwvtwRU59PHVLnb6uhq2MwvHauNM4ilvRyuFavs0q3tzfTmtWC-8Ou4vxz27a6KXzkTb_lDJroD4lc9B22bp2fKnMxNULDoiJ0fM25okfkrSCSGG9FV5JuxVV1md-S1A0dV4nUhUtbNu7q8YNVhR7Qr7hWSl6ql1yZz4cKJ20yq9i8YKyxOd7f4wSplzl6F7PV9fYUKE7SzV1ahBZrR33oRWCxpbYm8LmOob7p_5CWEu2xulMfWCgAzWWUx45PCU3SAEk2mL4p7AKg/https%3A%2F%2Fgithub.com%2Fjeball
I have added the two lines as suggested but face the same errorhttps://secure-web.cisco.com/1T1z2rXTkhSV-6Jayk_w2kV4RpzOzkw1swo_14BX4AacG5V47REIz0Etn3G3MYipCLFp7lvAb_LAQmyeDcF3meMcjp64NcURzgenY4mIYAzGYVWckHkYsTLkJ45mS4Jtr27DNcOLxWVb4Jhc6izZchBP87A2xQD0eJFibMidkeCBwDSMpgAkJBj_t4qbI3MvxY2ewmw3kcV36SwwPICLUR225DydIkUcnVWRaxOb0q2jLwAOe-XygwugVH-hBRI5-sKR6IJpCjr9KlmLwLCUb_YXuqAOquh9Vk_7V7fT0Wf_Mn3ziBpT-DoBRltsHpsTt/https%3A%2F%2Fcolab.research.google.com%2Fgist%2FSaduf2019%2Ff038f646736a2ddf5bba2d995f97e193%2Funtitled554.ipynb, please share a colab gist with the error reported.
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@jeball Looks like this is more related to tf-addons repo. Can you please open this issue in tf-addons repo and close the issue here. Thanks!

Will close this one. Thanks.
John Ball, Ph.D.
Associate Professor and Robert Guyton Endowed Chair for Teaching Excellence | Electrical and Computer Engineering
<EMAIL_ADDRESS>Associate Editor | IEEE Signal Processing Letters
Associate Editor | Journal of Applied Remote Sensing
Editorial Board Member | MDPI Electronics
Faculty Advisory Council | Transactions on Stem Education
Lab Director | Simrall Radar Laboratory
Lab Co-Director | Center for Advanced Vehicular Systems (CAVS) Sensor Lab
Research Fellow | Geosystems Research Institute (GRI)
Simrall 233, 406 Hardy Rd., Mississippi State, MS 39762
p:662.325.4169  e:jeball<EMAIL_ADDRESS>From: Vishnuvardhan Janapati<EMAIL_ADDRESS>Sent: Friday, March 5, 2021 2:49 PM
To: tensorflow/tensorflow<EMAIL_ADDRESS>Cc: Ball, John<EMAIL_ADDRESS>Mention<EMAIL_ADDRESS>Subject: Re: [tensorflow/tensorflow] Tensorflow Addons connected components not working properly (#47451)
@jeballhttps://secure-web.cisco.com/17jtGKQmwg5OWWys_tyMqckm6Lmgz-cn-EzYJXu3Oz7oOrj2d75Y-otk0hTA5GFT9QQ4J21W9BGIqAIyduLm2d2r3yzpOIdHOSBDbgX2wZaUf_jhmlOaU3jD9RgzK3bSalPrYOtdKRDLjLPNd-Qs5uc63utCH3wSJ4QM4H20w_4Mvt2JnKKhfrQgkPOHgGcbG3VZUg4NtcAvtcqRjcsEr9N6uMmAPEzVSsdIlQimPYIvtyjc53TLZMIKdm_J8mXPXibW13yfxnt3yO8sUZP9T7cmRmsXLSIP4jJT1vpi9ynt2l-OqboTT9HjiDGkyNjcC/https%3A%2F%2Fgithub.com%2Fjeball Looks like this is more related to tf-addons repo. Can you please open this issue in tf-addonshttps://secure-web.cisco.com/121AV0fV5OQB5e87ktszug_6cqrP5ZetWStAiSi9gnp9RyvS5r2Px7AMY4M72oIwggkyhTyT4UViWXV3yM1B6dfKw6pXW3DXtgDAfztIWRmKpw9d5WgGw2zvKVGOLOM4D9j30CfjKA06PIY5JGc6qisHKaZzx0B63wy5E8rkeENhUucclHf7QizhPJdLssNks_qU9G26aPujtsxUiUaUiTAn0DGyRSIOZePiBikzonnMEFF0nJMB5E5TOHRjqL2ZHwrXyym8s3ioQWGpUAjfzBVatfeFG8oh15zzs6aLHNPx7UK-UPerjZnIKyeS2A3lc/https%3A%2F%2Fgithub.com%2Ftensorflow%2Faddons repo and close the issue here. Thanks!
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Improve performance of MediaType::from_content_type to not do any allocations

We should remove the allocations that it does while maintaining the functionality (case insensitive comparison)

Removed a vector allocation for this in #7. Not sure how to remove the .to_lowercase() in a way that will be maintainable and actually faster.


empty null file created

Hello,
the nuget targets file contains a command which create a empty "null" file in the project folder:
<Exec Command='xcopy "$(SourcePath)" "$(ObjPath)" /e/s/y >>null' />

I don't know what this >>null command should do, but if it should redirect stderr to 'null' then "2>nul" should be used.

Please submit a pull request with this fix.


FA3 No perf gain noticed.

I'm using flash attention in my code.
and I installed FA3 and I noticed to perf gain when I run the model again.
My CUDA is 12.4 and I'm using H100.
do we need to modify something or should we see the perf gain automatically?

Same here — using a head dim of 256 in fp16 fwd/bwd

FA3 is a beta release, you'd need to call a different interface to use it (for now).
https://github.com/Dao-AILab/flash-attention/blob/main/hopper/flash_attn_interface.py
As we roll it out (e.g. after v3.0.0 tag) eventually the old interface will automatically call the faster code.

FA3 is a beta release, you'd need to call a different interface to use it (for now). https://github.com/Dao-AILab/flash-attention/blob/main/hopper/flash_attn_interface.py
As we roll it out (e.g. after v3.0.0 tag) eventually the old interface will automatically call the faster code.

Thanks for the answer,
so to make it clear.
for example in this class:
https://github.com/Dao-AILab/flash-attention/blob/5018ac6ac531aabdb05c8af1ba3d98a2235bdbde/flash_attn/modules/mha.py#L53
do we replace these guys:
flash_attn_varlen_qkvpacked_func
flash_attn_qkvpacked_func
with these guys from the hopper folder
flash_attn_func
flash_attn_qkvpacked_func
Thanks

ya

I haven't confirmed this, but the lack of speedup may be in part due to the contiguous requirement (#1087) as when I am benchmarking, I am comparing to using FA2 QKVPacked without forcing the tensors to be contiguous.

FA3 now doesn't require tensors to be contiguous.

Hm, I was just compiling with the most recent commit (3f1b4d38) and despite the maybe_contiguous, I found that I got an Input tensors must be contiguous error (like this comment mentions).
I found I need to do something like:
q, k, v = qkv.unbind(dim=2)
flash_attn_func_v3(q.contiguous(), k.contiguous(), v.contiguous())

Please make sure you use the latest commit (e.g. uninstall previous versions). The newest code doesn't do any contiguous check anymore.

Sorry I mispoke, let me update to remove those checks.

done, thanks for checking

Thanks! Just pulled and was able to run it without the forced .contiguous(). I'll note [mainly for other users, if they run into it] that I found flash_attn_qkvpacked_func [FA2] to still be quite a bit faster (~10-15%, end to end training in my case) than the regular flash_attn_func [FA2 or FA3] which was unexpected. Looking at the code, I wouldn't expect such a large difference as qkvpacked appears to be a thin wrapper, but these are the results I'm getting. Might be an oddity with my specific configuration [BS=12, Seqlen=1024, Headdim=128, Heads=16 on a single H100] but thought I should note it.

qkvpacked avoids the concat in the backward pass (backward of unbind is concat).

Also just pulled and tried removing the manual .contiguous() calls. I'm hitting
  File "/workspace/flash-attention/hopper/flash_attn_interface.py", line 46, in _flash_attn_backward
    dq, dk, dv, softmax_d, *rest = flashattn_hopper_cuda.bwd(
RuntimeError: dq must have contiguous last dimension

Does backward still require contiguous grads?

As it says, contiguous last dimension. I.e. last stride should be 1.


[Suggestion] Mass select buttons in the UI and hybrid card

Having a button that enables all inventory slots, everything but the hotbar, and just the hotbar (at least in the insert card's UI).
In addition, a single card that had the functionality of both cards would be great (and if you ever add more, there could be a super-combo card).

https://legacy.curseforge.com/minecraft/mc-mods/ae2-import-export-card/files/5551385

I don't like the idea of a hybrid card, so it won't be added, sorry


Process finished with exit code 137 (interrupted by signal 9: SIGKILL)

I am doing experiment on large scale datasets with extensive memory and GPU. Actually, when i started an experiments on Ensemble-Face-Recognition my process has been killed. Is it possible to consume my GPU for these experiments.
(236167, 3)
Process finished with exit code 137 (interrupted by signal 9: SIGKILL)

I want to used GPU because process has been killed again and again

Then, you can set is as shown below.
import os
os.environ["CUDA_VISIBLE_DEVICES"]="0"

In my opinion pandas and numpy do not use GPU. Am i right? Because i tried you above but it did not work.

Yes, numpy and pandas don't use gpu. GPU is available for keras models in deepface.

What about ensemble-Face-Recognition.py?

It will build lightgbm model as well and it can run gpu as well. Could you share the detailed error message?

Actually, i just got this error. I takes 3 minutes and then this error occurred  .
(236167, 3)
Process finished with exit code 137 (interrupted by signal 9: SIGKILL)

Meanwhile, I just used one model and one distance metric

You got still error when you disable GPU? That's all?

Yes in both conditions, i got an error

Could you share the code you are running?

It seems that your python program got this error. Your dictionary is too large.

I am facing the same error for Mask-RCNN model. It is unable to run even single epoch


RoleDefinition deploy fails due to delayed creation

When attempting to create a Pulumi.Azure.Authorization.RoleDefinition with Pulumi.Azure v3.47.0, the resource gets created, but Pulumi throwns an error that it cannot find it:

azure:authorization:RoleDefinition (test-peering-role):
error: authorization.RoleDefinitionsClient#Get: Failure responding to request: StatusCode=404 -- Original Error: autorest/azure: Service returned an error. Status=404 Code="RoleDefinitionDoesNotExist" Message="The specified role definition with ID 'd840520b-e698-cf0d-4940-5825bce188ca' does not exist."

Running pulumi a second time results in an error that the resource already exists:

azure:authorization:RoleDefinition (test-peering-role):
error: authorization.RoleDefinitionsClient#CreateOrUpdate: Failure responding to request: StatusCode=409 -- Original Error: autorest/azure: Service returned an error. Status=409 Code="RoleDefinitionWithSameNameExists" Message="A role definition cannot be updated with a name that already exists."

It appears there's a multi-second delay in creating the RoleDefinition which Pulumi doesn't wait for, causing the failure the first time. I've been able to reproduce this delay by running az role definition list --name d840520b-e698-cf0d-4940-5825bce188ca, which returns an empty array the first couple of attempts after running pulumi up. I'm not sure this is an issue that should be solved on Azure's side or in pulumi-azure.
Example code (simplified to omit business details):
var subscriptionId = "...";
var scope = "...";

var roleDefinition = new RoleDefinition($"test-peering-role", new RoleDefinitionArgs
{
    Name = "test-peering-role",
    Description = "Test description",
    AssignableScopes = scope,
    Permissions = new RoleDefinitionPermissionArgs
    {
        Actions = new[]
        {
            "Microsoft.Network/virtualNetworks/virtualNetworkPeerings/read",
        }
    },
    Scope = $"/subscriptions/{subscriptionId}"
});

This sounds like an upstream issue tracked in https://github.com/terraform-providers/terraform-provider-azurerm/issues/10602 (and described in https://github.com/terraform-providers/terraform-provider-azurerm/issues/10442)

Ah, great that they're working on it. Do you mind if I keep this open for visibility for other devs running into this issue?


multiple runs on same machine, with ctrl+c, all runs are killed

i have two machine with 8 GPUs on each. I want to run ds with 4 GPUs on machine 1 and and machine 2 and then another 4 GPUs on machine 1 and 2 also. Then when both ds cmmand are called, if I ctrl + c any, it will kill both. idk why.
However, if I only run on single machine with two runs, it wont kill both.
Anyone met this issue before?

Did some further experimentation. it seems that if I reuse the same SSH port, this will happen. If I use different ssh port for the two run, it's ok. however I don't feel this makes sense tho. but wishing someone with more authority to verify this behavior.

Hi @ysyyork - is there a reason you are using the same ssh port for both of your DeepSpeed jobs in this instance?

Hi, i thought it's by default? I'm coming from horovod + MPI background and they reuse the same SSH port. Otherwise everytime when I run deepspeed command, I have to manually specify a different --ssh_port？Is this expected?

@ysyyork - what is your use case?  Lots of multiple runs on the same node?  Or from the same master node onto other nodes?

i'm creating a cluster that can support multiple researchers to run distributed training simultaneously. ideally on each server, I should just setup one environment with fixed ssh port. then anyone can run distributed training jobs. Otherwise, I have to open a ton of ssh port and different researchers has to align on who is using what port to run. this is very troublesome.


refactor(pattern-matcher): remove forked traversals

This PR changes how patterns with wildcards are handled internally in the pattern matcher.
There is a detailed comment in the implementation, but the general gist of it is as follows.
Let's say we have a pattern with wildcards x??y?z. We can think of this as "x", then 2 characters, then "y", then one character, then "z". This does not seem to be helpful at first (it's the literal definition of a wildcard, rephrased a bit), but if you think about it we could try matching "x", "y", "z", and seeing if there is some position where:

z matched;
one character before, y matched;
two characters before that, x matched.

In other words, we match the literal segments normally, and then try to connect them.
This should be considerably more performant than the previous approach with forked traversals.
I ran fuzz tests on this change with the number of runs set to 20,000. No issues were found, so I'm fairly sure that the implementation is sound here.

Codecov Report

Merging #4 (0356d2e) into main (6566b16) will not change coverage.
The diff coverage is 100.00%.

@@            Coverage Diff            @@
##              main        #4   +/-   ##
=========================================
  Coverage   100.00%   100.00%
=========================================
  Files           40        38    -2
  Lines          868       877    +9
  Branches       170       172    +2
=========================================
+ Hits           868       877    +9

Impacted Files
Coverage Δ

src/matcher/WhitelistedTermMatcher.ts
100.00% <ø> (ø)

src/matcher/PatternMatcher.ts
100.00% <100.00%> (ø)

src/matcher/trie/BlacklistTrieNode.ts
100.00% <100.00%> (ø)

src/pattern/Util.ts
100.00% <100.00%> (ø)

src/util/CircularBuffer.ts
100.00% <100.00%> (ø)

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scripts: set_maintainer: add log messages for skipped collabs

Refactor the skip collaborator logic to add log messages when a collaborator is skipped because they self removed of not part of the org.

$ ./scripts/set_assignees.py -v -y -P 70972
working on https://github.com/zephyrproject-rtos/zephyr/pull/70972 : Test only, please ignore
file: soc/ti/k3/hello
Area matches: {<Area TI K3 Platforms>: 1}
labels: {'Trivial', 'platform: TI K3'}
collab: ['vaishnavachath', 'gramsay0']
Submitted by: grantramsay
candidate maintainers: {'vaishnavachath': 1}
Picked assignee: vaishnavachath (100.00% ownership)
+++++++++++++++++++++++++
adding label Trivial...
adding label platform: TI K3...
Skip 'gramsay0': not in collaborators
not setting assignee