Use current GCC from conda-forge on Linux

Hi! This is the friendly automated conda-forge-webservice.
I've started rerendering the recipe as instructed in #19.
If I find any needed changes to the recipe, I'll push them to this PR shortly. Thank you for waiting!
Here's a checklist to do before merging.

[x] Bump the build number if needed.

Fixes https://github.com/conda-forge/cudadecon-feedstock/issues/19

Re-rendering fails due to the conda_build_config.yaml file. As the plan is to try dropping that anyways, have done that above. Hopefully re-rendering should now work

@conda-forge-admin, please re-render

@tlambert03 , looks like it is passing! 🎉
So maybe we can just go ahead with this PR?

Awesome, sure!

Thanks Talley! 🙏

Thank you!


Update to stable quickcheck

It took some manual changes/updates so dependabot's PR didn't swing it

Codecov Report

Merging #77 (aaf1bcc) into main (0d037ce) will increase coverage by 0.36%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##             main      #77      +/-   ##
==========================================
+ Coverage   90.66%   91.03%   +0.36%
==========================================
  Files          10       10
  Lines         793      792       -1
==========================================
+ Hits          719      721       +2
+ Misses         74       71       -3

Impacted Files
Coverage Δ

src/expression.rs
94.54% <100.00%> (ø)

src/grammar.rs
87.98% <100.00%> (-0.49%)
:arrow_down:

src/production.rs
87.87% <100.00%> (+0.75%)
:arrow_up:

src/term.rs
93.15% <100.00%> (+4.10%)
:arrow_up:

tests/grammar.rs
81.25% <100.00%> (-1.11%)
:arrow_down:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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Codecov Report

Merging #77 (aaf1bcc) into main (0d037ce) will increase coverage by 0.36%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##             main      #77      +/-   ##
==========================================
+ Coverage   90.66%   91.03%   +0.36%
==========================================
  Files          10       10
  Lines         793      792       -1
==========================================
+ Hits          719      721       +2
+ Misses         74       71       -3

Impacted Files
Coverage Δ

src/expression.rs
94.54% <100.00%> (ø)

src/grammar.rs
87.98% <100.00%> (-0.49%)
:arrow_down:

src/production.rs
87.87% <100.00%> (+0.75%)
:arrow_up:

src/term.rs
93.15% <100.00%> (+4.10%)
:arrow_up:

tests/grammar.rs
81.25% <100.00%> (-1.11%)
:arrow_down:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 0d037ce...aaf1bcc. Read the comment docs.


luci-app-ddns failed to execute cbi dispatcher

I can't access the luci page for ddns on my custom build C7 image since a couple of months ago. Yesterday I created a custom build for R7800 and the exact same problem happens. removing ddns file from config dir does not solve the issue. this is the error:
Failed to execute cbi dispatcher target for entry '/admin/services/ddns'.
The called action terminated with an exception:
/usr/lib/lua/luci/controller/ddns.lua:84: attempt to index field '?' (a nil value)
stack traceback:
	/usr/lib/lua/luci/controller/ddns.lua:84: in function 'service_version'
	/usr/lib/lua/luci/controller/ddns.lua:91: in function 'service_ok'
	/usr/lib/lua/luci/model/cbi/ddns/overview.lua:16: in function 'e'
	/usr/lib/lua/luci/cbi.lua:48: in function 'load'
	/usr/lib/lua/luci/dispatcher.lua:672: in function </usr/lib/lua/luci/dispatcher.lua:667>

Which ddns version did you use? Did you try to install/reproduce this issue with official/buildbot generated packages?
What's the output of:
/usr/lib/ddns/dynamic_dns_lucihelper.sh -V
Maintainer: @Ansuel

ummm ddns doesn't use the lucihelper script anymore to obtain the version if LuCI IPKG utility is found... Can you post the content of the file? ( /usr/lib/lua/luci/controller/ddns.lua )

Removal of opkg might be the reason, if I combine Ansuel's comments and you explanation:

**remove opkg**
**Remove ipkg/opkg status data files in final images is not enabled ( it is as default )**

vs.

ddns doesn't use the lucihelper script anymore to obtain the version if LuCI IPKG utility is found.

You have rather non-standard options (gcc, binutils, minify, opkg removal) ...
So no wonder that something happens. opkg and opkg data are used in LuCI (and Openwrt) by various package scripts. Removing them will mean that some things will not work ok, and as opkg is pretty much assumed to be present in the build, not all scripts have fallback for that case. I haven't checked ddns sources closely, so this is pure hunch.

indeed, installing opkg resolves the issue.
thanks for narrowing down this for me.
I'm closing the issue.


Unable to copy RGBColor objects

I'm trying to copy/deepcopy an object that contains RGBColor objects. However RGBColor raises an exception when trying to copy since the class can't be pickled/unpickled
from copy import deepcopy
from pptx.dml.color import RGBColor
color = RGBColor(255, 255, 255)
deepcopy(color)

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/saleh/Git/app2/env/lib/python3.6/copy.py", line 180, in deepcopy
    y = _reconstruct(x, memo, *rv)
  File "/Users/saleh/Git/app2/env/lib/python3.6/copy.py", line 274, in _reconstruct
    y = func(*args)
  File "/Users/saleh/Git/app2/env/lib/python3.6/copyreg.py", line 88, in __newobj__
    return cls.__new__(cls, *args)
TypeError: __new__() missing 2 required positional arguments: 'g' and 'b'

__new__() missing 2 required positional arguments: 'g' and 'b'

I solved it by defining a __getnewargs__ function for the RGB class. If yall think this is a good addition to python-pptx, I can make a pr for it.
class RGBColor(RGBColor):
	# enables copy
	def __getnewargs__(self):
		return (*self, )

I can't say that "copyability" has been one of the target requirements so far. What do you find that useful for?

I needed to deepcopy a dictionary that contained RGBColor objects. My program gives the user the ability to set up general settings that can be applied to all slides. And then gives them another ability to further customize settings on slide by slide basis. Thus I deepcopy the general settings (which include RGBColor objects) so that if a slide has specific customization, it won't affect the general settings.

Maybe storing the colors in your settings object as strings like "1bf276" is a better idea, then you can convert those to RGBColor objects at application time with something like RGBColor.from_string(). That way your configuration object stays pure Python primitives and is guaranteed serializable, pickleable, copiable, etc.

Yeah I thought about, but wanted thought about abstracting out the color objects so the function that do the coloring don't have to convert from string. But I see your point. I'll close the issue :)


[REQUEST] Document how Theme Builder can be used to improve the accessibility of the FINOS TraderX as the simple use case of BYOD

Suggestion/Concern
The FINOS Tech Sprint is an opportunity to work with others in the FINOS community to expand awareness and capability of FINOS projects.
We would like to use this opportunity to use Theme Builder to improve the accessibility of the FINOS TraderX app, which has a very simple 'front end' that is a good 'hello world' level use case for accessible design best practices.
Proposed Solution
Notes are in the TraderX Discussion related to this use case:
https://github.com/finos/traderX/discussions/193
Steps could include:

Initial assessment of the existing app and CSS
Create wireframes using PenPot as a best practice and store them in the TraderX App
Use Theme Builder to design a palette and components
Generate CSS that can be dropped in to TraderX to enable some level of WCAG compliance, light/dark mode etc

@PaulaPaul I would like to help you with this issue. Let's collaborate.


[WFLY-18237]: Adding a connector shouldn't require to reload.

Adding a connector dynamically to the broker to avoid the reload requirement.

Jira: https://issues.redhat.com/browse/WFLY-18237

Thanks @ehsavoie


chore: update manifests to 0.13.1

Cherry pick of https://github.com/GoogleCloudPlatform/prometheus-engine/pull/1117/files#diff-812b265e1da8d8a3c64370d7d4b87bd6d109bda0d44b066ee86b8329d4004f43 and distroless bump.

suggestion: git cherry-pick https://github.com/GoogleCloudPlatform/prometheus-engine/commit/3d89ecba2a3841620b4a8021b688b2ed9788d531

Nice I like your flow started in https://github.com/GoogleCloudPlatform/prometheus-engine/pull/1117/files#diff-812b265e1da8d8a3c64370d7d4b87bd6d109bda0d44b066ee86b8329d4004f43
Cherry-pick + update of distroless here. PTAL @pintohutch @damemi

I am going to merge this. I think we have to simply claim that manifests from main will be not always buildable due to tag lag https://github.com/GoogleCloudPlatform/prometheus-engine/issues/1013#issuecomment-2363252303
0.13.1 is good to have here, but due to perms main manifests won't work anyway, proceeding cutting 0.14 release branch to get 0.14 prod images we can cherry pick later to main.


feat(config-server): add MongoDB environment repository support

This commit introduces MongoDB as a new backend option for the Spring Cloud Config Server,
enabling users to store and manage their configuration properties in a MongoDB database.

Thanks for the PR!  We are going to wait to merge this until we branch for our 2024 release train later this year.  Once we branch we will get this merged.


[e2e]: go push branch1 config-ldflags slsa3

Repo: https://github.com/slsa-framework/example-package/tree/branch1
Run: https://github.com/slsa-framework/example-package/actions/runs/3248001312
Workflow file: https://github.com/slsa-framework/example-package/tree/main/.github/workflows/e2e.go.push.branch1.config-ldflags.slsa3.yml
Workflow runs: https://github.com/slsa-framework/example-package/actions/workflows/e2e.go.push.branch1.config-ldflags.slsa3.yml
Trigger: push
Branch: branch1
Date: Fri Oct 14 06:57:02 UTC 2022

Repo: https://github.com/slsa-framework/example-package/tree/branch1
Run: https://github.com/slsa-framework/example-package/actions/runs/3252013209
Workflow file: https://github.com/slsa-framework/example-package/tree/main/.github/workflows/e2e.go.push.branch1.config-ldflags.slsa3.yml
Workflow runs: https://github.com/slsa-framework/example-package/actions/workflows/e2e.go.push.branch1.config-ldflags.slsa3.yml
Trigger: push
Branch: branch1
Date: Fri Oct 14 18:29:50 UTC 2022

Repo: https://github.com/slsa-framework/example-package/tree/branch1
Run: https://github.com/slsa-framework/example-package/actions/runs/3252288077
Workflow file: https://github.com/slsa-framework/example-package/tree/main/.github/workflows/e2e.go.push.branch1.config-ldflags.slsa3.yml
Workflow runs: https://github.com/slsa-framework/example-package/actions/workflows/e2e.go.push.branch1.config-ldflags.slsa3.yml
Trigger: push
Branch: branch1
Date: Fri Oct 14 19:07:43 UTC 2022
Tests are passing now. Closing this issue.


Type on DatabaseManager connection() is only respected on first call to method

When the connection() method on DatabaseManager is called for a connection that already exists, the type argument is ignored entirely. For example, if you were to call DB::connection('mysql::write')->... on a connection that already had been opened normally, you wouldn't get a write connection back.
It should either be clarified in the code that you cannot change the type of an already existing connection, or it should be changed so that you can change the type of an already existing connection (see #15064).

DB::connection simply gives temporary instantiation of a connection. I don't see any reason for it to be persisted.

As far as I can tell, it already is persisted (by being saved in $this->connections). This is why subsequent calls to connection() with the same name disregards the type (it returns the persisted connection).

The current code looks correct. This is just a subtlety.


No lts tag for 2.303.1 version on docker hub

Hello!
I see, that use lts tag on Dockerhub for
jenkins/jenkins:2.289.2-lts
jenkins/jenkins:2.289.3-lts

versions and it very useful.
Please, create lts tag for 2.303.1 version.
Thank you!

Duplicate of https://github.com/jenkinsci/docker/issues/1196


refactor: make TypeSet.inputText a positional argument to match Text semantics

Status
READY/IN DEVELOPMENT/HOLD
Description

Type of Change

[ ] ✨ New feature (non-breaking change which adds functionality)
[ ] 🛠 Bug fix (non-breaking change which fixes an issue)
[x] ❌ Breaking change (fix or feature that would cause existing functionality to change)
[ ] 🧹 Code refactor
[ ] ✅ Build configuration change
[ ] 📝 Documentation
[ ] 🗑 Chore

LGTM


[ci] Revert the change to codecov version

Codecov Report

Merging #2006 (9033d70) into master (41d5492) will decrease coverage by 0.15%.
The diff coverage is 89.24%.

@@            Coverage Diff             @@
##           master    #2006      +/-   ##
==========================================
- Coverage   87.61%   87.46%   -0.16%
==========================================
  Files          50       50
  Lines        8788     8850      +62
==========================================
+ Hits         7700     7741      +41
- Misses       1088     1109      +21

Impacted Files
Coverage Δ

reframe/core/decorators.py
64.70% <25.00%> (-18.49%)
:arrow_down:

reframe/core/hooks.py
92.78% <92.00%> (-1.82%)
:arrow_down:

reframe/core/meta.py
98.80% <96.66%> (-1.20%)
:arrow_down:

Continue to review full report at Codecov.

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linker error "duplicate symbols for architecture x86_64"

Hi,
I am getting a linker error "duplicate symbols for architecture x86_64" when calling audiofile.load()
Any suggestions? Are there any dependencies I am missing or duplicate libraries ofxAudioFile is including that might cause the error.

i'm pretty sure it was my fault, i missed the define guards, i just made a commit to fix it.
git pull and try again now, let me know if it's fixed

Hm. I tried with the new verison but no change. I can build the example project, but I cannot call audioFile.load() in my own project, though, the rest works.

please state your opeartive system, oF version, IDE and copy the full error output

Hey, I fixed it. The issue was a duplicate inclusion of stb_vorbis because the addon ofxMaxim that I am using also has a dependency to stb_vorbis
However I can set a flag #define STB_VORBIS_HEADER_ONLY true; in the stb_vorbis.c file or in the config.make to avoid the duplicate exclusions.

perfect!


Update MAX32xxx UART Driver

As per of irq_tx_ready and rx_ready function description these function content need to be updated. Expected workflow
tx_ready: if tx interrupt enabled AND tx fifo is not full
rx_ready: if rx interrupt enalbed AND rx fifo not empty
Test output with IPO/IBRO clock.

P.S: IBRO clock configuration

@MaureenHelm  FYI.

https://github.com/zephyrproject-rtos/hal_adi/pull/3 being merged,
SHA point in west.yml updated.


CIS friendly permissions

Cookbook version
5.0.1
Chef-client version
13.6.4
Platform Details
RHEL 7.4.1708
Scenario:
Use cron cookbook in CIS hardened systems
Steps to Reproduce:
Use any cookbook with CRON as a dependency or directly on a CIS system
Expected Result:
Allow permissions of various cron elements to be set (not reset) CIS requirements
Actual Result:
Enforces prescribed permissions

Per CIS guidelines, the following rules are violated in this cookbook:

5.1.2     Ensure permissions on /etc/crontab are configured (Scored)     recommended    chown root:root /etc/crontab; chmod og-rwx /etc/crontab
5.1.3     Ensure permissions on /etc/cron.hourly are configured (Scored)     recommended    chown root:root /etc/cron.hourly ; chmod og-rwx /etc/cron.hourly
5.1.4     Ensure permissions on /etc/cron.daily are configured (Scored)     recommended    chown root:root /etc/cron.daily ; chmod og-rwx /etc/cron.daily
5.1.5    Ensure permissions on /etc/cron.weekly are configured (Scored)     recommended    chown root:root /etc/cron.weekly ; chmod og-rwx /etc/cron.weekly
5.1.6     Ensure permissions on /etc/cron.monthly are configured (Scored)     recommended    chown root:root /etc/cron.monthly ; chmod og-rwx /etc/cron.monthly
5.1.7    Ensure permissions on /etc/cron.d are configured (Scored)     recommended    chown root:root /etc/cron.d ; chmod og-rwx /etc/cron.d

Allowing a permissions set for the above resources would allow the system to be compliant and allow cookbook usage in CIS scenarios

I've updated the cron files to all default to 0600. Thanks for the heads up


connection to mongodb not working

Currently on known issue is that the connection to the mongodb does not work when it is runningn in a web-app.
Before that I tried to use CosmosDB with the Mongodb interface but Cosmosdb is not really compatible with mongodb.

duplicate


Images on dark theme

The transparent images make it impossible to read on dark background. Would be great if we could get that fixed to something visible on all the offered themes :)

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

ID: 5e28d301-492c-3db3-72dd-699f6786985b
Version Independent ID: 653625e5-d919-9953-249d-7f33ee319265
Content: Azure AD UserPrincipalName population
Content Source: articles/active-directory/hybrid/plan-connect-userprincipalname.md
Service: active-directory
GitHub Login: @billmath
Microsoft Alias: billmath

@dcbrown16
Thanks for your feedback! We will investigate and update as appropriate.

Unfortunately that is not something I can do.  It would be our publishing folks.
#please-close

@MicahMcKittrick-MSFT shouldn't this be reassigned to "publishing folks" instead of just closed? Nothing was fixed.

@billmath who can I assign this to that can look into it further?


Please add topic for NSPanel

Can you please add the topic /tele/DeviceNAME/RESULT for de display of the new NSPanel?

Hello
I have the same part for "/tele/DeviceNAME/RESULT". But I have an other defice.
I got a SerialReceived value:
15:21:31.419 MQT: tele/SINO_ENERGIE02/STATE = {"Time":"2022-01-04T15:21:31","Uptime":"0T01:10:09","UptimeSec":4209,"Heap":27,"SleepMode":"Dynamic","Sleep":50,"LoadAvg":19,"MqttCount":12,"POWER":"OFF","Wifi":{"AP":1,"SSId":"ichsmarthome","BSSId":"B2:BE:76:59:BF:92","Channel":3,"Mode":"11n","RSSI":88,"Signal":-56,"LinkCount":1,"Downtime":"0T00:00:03"}} 15:21:37.408 RUL: RULES#TIMER=1 performs "backlog SerialSend5 fe010f080000001c; RuleTimer1 10" 15:21:37.450 MQT: stat/SINO_ENERGIE02/RESULT = {"SerialSend":"Done"} 15:21:37.660 MQT: stat/SINO_ENERGIE02/RESULT = {"T1":10,"T2":0,"T3":0,"T4":0,"T5":0,"T6":0,"T7":0,"T8":0} 15:21:37.677 MQT: tele/SINO_ENERGIE02/RESULT = {"SerialReceived":"FE0108020000002323000000000000005000000000000000000000000000000010000083"} 15:21:48.382 RUL: RULES#TIMER=1 performs "backlog SerialSend5 fe010f080000001c; RuleTimer1 10" 15:21:48.422 MQT: stat/SINO_ENERGIE02/RESULT = {"SerialSend":"Done"} 15:21:48.631 MQT: stat/SINO_ENERGIE02/RESULT = {"T1":10,"T2":0,"T3":0,"T4":0,"T5":0,"T6":0,"T7":0,"T8":0} 15:21:48.648 MQT: **tele/SINO_ENERGIE02/RESULT** = {"SerialReceived":"FE0108020000002123000000000000005000000000000000000000000000000010000085"} 15:21:59.413 RUL: RULES#TIMER=1 performs "backlog SerialSend5 fe010f080000001c; RuleTimer1 10" 15:21:59.456 MQT: stat/SINO_ENERGIE02/RESULT = {"SerialSend":"Done"}
Many thanks for your greate work!
Best regards
ichda

Hello, please add NSPanel.
THANK YOU.

Ich habe auch 2 hier liegen. Die Relais funktionieren ja wundervoll.


Header disappears when clicking the down-caret next to name if scroll position is not at the top

Using release 2.6.1.
If you scroll down, then click the down-caret next to your name, the log out button appears, but the header disappears.
This behavior does not occur if you are scrolled to the top.
Example:

I can recreate this on the docs page (http://uw-madison-doit.github.io/uw-frame/latest/)

Created https://jira.doit.wisc.edu/jira/browse/MUMUP-2703 to track in the Jira

PR ready: https://github.com/UW-Madison-DoIT/uw-frame/pull/295


Evaluate http://gitbook.com|gitbook.com :octocat: !

Evaluate http://gitbook.com|gitbook.com :octocat: !
--
by restuta

It's already done. Here it is – RCN wiki, so I think, we can close this issue.

great


Double nested Classes are not compatible with Java

With the current Implementation, the plugin is not compatible with Java even though Gatling provides multiple compatibilities with Scala/Java/Kotlin. Therefore to make it Java compatible it is needed to apply a minor refactor at KafkaRequestBuilderBase.scala to remove the double nested class definition for
def replyTopic(outputTopic: Expression[String], headerIdentifier:Option[String] = None)
and
def requestTopic(rt: Expression[String]): RRInTopicStep = RRInTopicStep(rt)
I will propose a solution to this issue in a feature/branch

we are planning to add java/kotlin compatibility in this quarter

We have added Java and Kotlin support in #125

https://github.com/Tinkoff/gatling-kafka-plugin/releases/tag/v0.11.0


Library design

This is more of a discussion than an issue.
I love the idea of a common interface for the libraries but after implementing Lucide, I realized that with each new set added we'll also get bloat. I almost think the libraries should be extracted into their own gems with the icon set and config with the main gem being the interface.
That way if i want to only use heroicons, I'd add rails_icons-heroicons to my gemfile but if i wanted to have a mix i could also add rails_icons-lucide, or any additional combination.
With that design change the end user doesn't have to deal with a bunch of extra file size from items they never intend to use.
Thoughts?

I agree with the file bloat sentiment. I worry that splitting into multiple gems may be cumbersome for the author(s). Honestly, it would be awesome if the installation script could pull from source and vendor the icons in the parent application. This would have the added benefit of making it easier to manage changes when the icon libraries inevitably release new icons

How about using rake tasks to install icon libraries?  That gets rid of bloat in the gem itself, and lets each user decide which library or libraries they want to make use of.  The rake tasks could pull the icons and install them into local assets.  Unless you expressly want to keep the icons out of peoples git repos?


Policy definition for Front door diagnostic logs only works against Front Door classic

Describe the bug
The policy definition "Deploy Diagnostic Settings for Front Door to Log Analytics workspace don't work against new Front Door.
The definition only enable logging for Front Door classic.
Screenshots

Thanks @tlfzhylj, we will triage and address.
Looping in @Springstone & @paulgrimley

Closing this as we've deprecated all our diagnostic settings policies and shifted to the PG owned initiative to do the same. Please review https://aka.ms/alz/whatsnew for details.


Fix missing paragraph in testing-operators.md

Fix missing paragraph in testing-operators.md, which would result in bad formatting. See screenshot.

cc @camilamacedo86


New performance improvements

I've done a reasonable chunk of work on performance, including documenting some of the improvements in transfer speed. You might want to take these improvements on board in your copy.

@chemistorge I've got the UART-based transfer performance about 10 times faster in this new work. I also have the basic radio building blocks working behind the scenes, but want to get some of the remaining performance issues nailed before adding radio to the mix. Now, with 4-times over-sending (for resilience) we can send a typical 35K jpeg image in about a minute. It's obviously a lot faster with no over-sending, but then the chance of a lost packet stopping the transfer is much higher.

@chemistorge I have added a myboard.py, which maps the GPIO pins used on the specific board in one file. This will allow you to re-map these pins easily if moving between the Pimoroni Pico Explorer board and your custom board.
I have also improved the platform switching (platdeps) between the host and pico builds. There is scaffolding in place when running on host for the @micropython.viper and ptr8 definitions. This will allow the easy introduction of the viper compiler to other functions in order to get improved performance on the pico, without breaking the host builds.
The host build is useful for testing changes before deploying to the pico,

I've written a ton of stuff about performance optimisation, that you might find useful.


Move change log to github and automate

It is currently at https://docs.google.com/spreadsheets/d/1G5ri-vUERgy3zfzj_MQsZEff0K8mT1LT/edit#gid=1075103823
We can copy this file to the repo for now, but we need to automate the change log going forward to make sure it captures all changes.
Todo:

[x] move file to github
[ ] devise plan for automation
[ ] implement plan

change log added with commit 025e5ce

Our current plan is to use github issues, branches, PRs, and releases to autogenerate change logs. Documentation in progress at https://github.com/GenomicsStandardsConsortium/mixs/blob/606-mixs-editing-workflow-and-policy/src/docs/edit_workflow.md.
Should close this issue when #606 is closed.

Should be documented in PR


let kgx freely update to get infores/knowledge source fixes in 1.7.2

my tests in both KGX and locally with this repo, show aggregator_knowledge_source being added to edge files even when knowledge_source is provided in the files to transform.  Keeping the changelog small, I think if we let KGX freely float, it will pick up the updates to the infores/knowledge source fixes in KGX.

@caufieldjh

Thank you!


[Event Request] Report 11703 "Accounting Sheets CZL" - trigger OnInitReport()

Describe the request
Hello,
I would like to ask for a new publisher in the report 11703 "Accounting Sheets CZL", trigger OnInitReport(). We need to change a value of the GroupGLAccounts. Thank you.
trigger OnInitReport()
begin
    GroupGLAccounts := true;
    OnAfterOnInitReport(GroupGLAccounts);
end;

// NEW EVENT
[IntegrationEvent(true, false)]
local procedure OnAfterOnInitReport(var GroupGLAccounts: Boolean)
begin
end;

Additional context
We need to change a value of the GroupGLAccounts.
Internal work item: AB#496821

@jlorenc01Hello. Is it really necessary to add this event when request 25702 asks for change the access scope of the variable GroupGLAccounts to protected?

@jlorenc01 The solution for you would be to add the InitializeRequest function (see below).
procedure InitializeRequest(NewGroupGLAccounts: Boolean)
begin
    GroupGLAccounts := NewGroupGLAccounts;
end;

Is it ok for you?

@DavidHolusa No, it is not a solution. We are talking about the action "Post and Print" on the page 51 "Purchase Invoice", it means the CU 92 "Purch.-Post + Print". After the document is posted, reports are printed via the procedure PrintRecords(ShowRequestPage: Boolean) defined in the table 122 "Purch. Inv. Header".

It finds all reports with the defined report usage (in our case "P.Invoice") and print reports via Report.RunModal(ReportId, ...). So we do not have the report as the variable to be able to call some procedure within the report.

Thanks for reporting this. We agree, and we’ll publish a fix asap, either in an update for the current version or in the next major release. Please do not reply to this, as we do not monitor closed issues. If you have follow-up questions or requests, please create a new issue where you reference this one.
Build ID: 15718.


gltfio: [extended] Fix generated color default

Fixes #7905

Doesn't seem to fix the issue.  Model (attached in the original issue) still appears all black,

@poweifeng @pixelflinger

Doesn't seem to fix the issue. Model (attached in the original issue) still appears all black,  @poweifeng @pixelflinger

Can you attach the model again?  It seems corrupted in the previous comment.

It was attached as .zip cz of github attachment restriction.  Removing the .zip extension should work, i just tried from previous comment.
Here is the same model,
walls.glb.zip

Let's continue the conversation in #7905.

Clean build worked.  Model appears as expected.  Thanks.


stale jobs are getting scheduled even after invoking scheduler.cancel() for all the jobs

When ever jobs are scheduled using the rq-scheduler, the job always remain scheduled.   I am unable to delete the stale jobs (scheduler.cancel() dosen't seem to work at all.). Every time i restart the rq-scheduler, the stale jobs start running. I tried deleting all the KEYS in the redis. Even after that i couldn't solve this. Somehow all the KEYS are restored.  Can somebody help me solve this and also brief me how the KEYS are restored ?

facing this same issue in 2023 :((


Modifying the original tensor can change the value of copied tensor

Click to expand!
Issue Type
Bug
Have you reproduced the bug with TF nightly?
Yes
Source
source
Tensorflow Version
2.13.0.dev20230204
Custom Code
Yes
OS Platform and Distribution
No response
Mobile device
No response
Python version
No response
Bazel version
No response
GCC/Compiler version
No response
CUDA/cuDNN version
No response
GPU model and memory
No response
Current Behaviour?
Modifying the original tensor can change the value of the copied tensor. This buggy behavior is unstable so we run it 100 times to reproduce. The bug only happens on the CPU.

Standalone code to reproduce the issue
import tensorflow as tf
import numpy as np

for _ in range(100):
    with tf.device("cpu"):
        x = np.arange(10)
        x_copy = tf.experimental.numpy.copy(x)

        x[3] = 42
        assert tf.experimental.numpy.all((x_copy == tf.range(10, dtype=tf.int64))), x_copy

Relevant log output
AssertionError: tf.Tensor([ 0  1  2 42  4  5  6  7  8  9], shape=(10,), dtype=int64)

Hey @trickiwoo try this x_copy = tf.identity(x) instead of  x_copy = tf.experimental.numpy.copy(x).

FYI follow this link :- https://www.tensorflow.org/api_docs/python/tf/identity

@trickiwoo,
tf-nightly v2.13.0.dev20230204 which is not the stable version. I tried to execute the code multiple tiimes with the stable version tf 2.11 and haven't faced any issue. Kindly find the text of the same and also the image below for the reference.

(tf) tilakrayal@tilak-cpu-instance:~$ python3 59729numpy.py
2023-02-20 10:49:30.254453: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-20 10:49:30.466013: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2023-02-20 10:49:30.466232: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2023-02-20 10:49:31.412451: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:49:31.412593: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:49:31.412617: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2.11.0
2023-02-20 10:49:32.198426: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2023-02-20 10:49:32.198468: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2023-02-20 10:49:32.198505: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (tilak-cpu-instance): /proc/driver/nvidia/version does not exist
2023-02-20 10:49:32.198901: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
(tf) tilakrayal@tilak-cpu-instance:~$ python3 59729numpy.py
2023-02-20 10:49:38.750996: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-20 10:49:38.937838: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2023-02-20 10:49:38.937881: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2023-02-20 10:49:39.835979: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:49:39.836100: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:49:39.836122: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2.11.0
2023-02-20 10:49:40.626076: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2023-02-20 10:49:40.626116: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2023-02-20 10:49:40.626150: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (tilak-cpu-instance): /proc/driver/nvidia/version does not exist
2023-02-20 10:49:40.626547: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
(tf) tilakrayal@tilak-cpu-instance:~$ python3 59729numpy.py
2023-02-20 10:49:46.471764: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-20 10:49:46.641868: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2023-02-20 10:49:46.641908: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2023-02-20 10:49:47.534333: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:49:47.534448: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:49:47.534470: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2.11.0
2023-02-20 10:49:48.324850: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2023-02-20 10:49:48.324888: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2023-02-20 10:49:48.324921: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (tilak-cpu-instance): /proc/driver/nvidia/version does not exist
2023-02-20 10:49:48.325328: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
(tf) tilakrayal@tilak-cpu-instance:~$ python3 59729numpy.py
2023-02-20 10:49:51.697105: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-20 10:49:51.902325: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2023-02-20 10:49:51.902389: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2023-02-20 10:49:52.835385: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:49:52.835510: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:49:52.835535: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2.11.0
2023-02-20 10:49:53.621156: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2023-02-20 10:49:53.621197: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2023-02-20 10:49:53.621230: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (tilak-cpu-instance): /proc/driver/nvidia/version does not exist
2023-02-20 10:49:53.621683: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
(tf) tilakrayal@tilak-cpu-instance:~$ python3 59729numpy.py
2023-02-20 10:49:57.771047: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-20 10:49:58.005568: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2023-02-20 10:49:58.005674: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2023-02-20 10:49:59.020246: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:49:59.020377: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:49:59.020400: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2.11.0
2023-02-20 10:49:59.836802: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2023-02-20 10:49:59.836924: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2023-02-20 10:49:59.837011: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (tilak-cpu-instance): /proc/driver/nvidia/version does not exist
2023-02-20 10:49:59.837558: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
(tf) tilakrayal@tilak-cpu-instance:~$ python3 59729numpy.py
2023-02-20 10:50:04.571082: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-20 10:50:04.760537: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2023-02-20 10:50:04.760590: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2023-02-20 10:50:05.698994: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:50:05.699141: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:50:05.699170: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2.11.0
2023-02-20 10:50:06.499657: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2023-02-20 10:50:06.499711: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2023-02-20 10:50:06.499751: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (tilak-cpu-instance): /proc/driver/nvidia/version does not exist
2023-02-20 10:50:06.500157: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
(tf) tilakrayal@tilak-cpu-instance:~$ python3 59729numpy.py
2023-02-20 10:50:11.225399: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-20 10:50:11.448887: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2023-02-20 10:50:11.448949: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2023-02-20 10:50:12.396209: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:50:12.396372: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:50:12.396396: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2.11.0
2023-02-20 10:50:13.185562: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2023-02-20 10:50:13.185610: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2023-02-20 10:50:13.185667: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (tilak-cpu-instance): /proc/driver/nvidia/version does not exist
2023-02-20 10:50:13.186108: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
(tf) tilakrayal@tilak-cpu-instance:~$ python3 59729numpy.py
2023-02-20 10:50:18.252309: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-20 10:50:18.461471: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2023-02-20 10:50:18.461534: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2023-02-20 10:50:19.411662: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:50:19.411806: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:50:19.411828: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2.11.0
2023-02-20 10:50:20.215193: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2023-02-20 10:50:20.215244: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2023-02-20 10:50:20.215279: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (tilak-cpu-instance): /proc/driver/nvidia/version does not exist
2023-02-20 10:50:20.215699: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
(tf) tilakrayal@tilak-cpu-instance:~$ python3 59729numpy.py
2023-02-20 10:50:23.607334: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-20 10:50:23.804093: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2023-02-20 10:50:23.804141: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2023-02-20 10:50:24.719589: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:50:24.719712: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:50:24.719734: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2.11.0
2023-02-20 10:50:25.514461: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2023-02-20 10:50:25.514590: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2023-02-20 10:50:25.514671: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (tilak-cpu-instance): /proc/driver/nvidia/version does not exist
2023-02-20 10:50:25.515096: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
(tf) tilakrayal@tilak-cpu-instance:~$ python3 59729numpy.py
2023-02-20 10:50:29.199966: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-20 10:50:29.372612: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2023-02-20 10:50:29.372657: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2023-02-20 10:50:30.303912: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:50:30.304036: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:50:30.304060: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2.11.0
2023-02-20 10:50:31.100249: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2023-02-20 10:50:31.100288: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2023-02-20 10:50:31.100324: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (tilak-cpu-instance): /proc/driver/nvidia/version does not exist
2023-02-20 10:50:31.100720: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
(tf) tilakrayal@tilak-cpu-instance:~$ python3 59729numpy.py
2023-02-20 10:50:37.436578: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-20 10:50:37.606332: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2023-02-20 10:50:37.606511: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2023-02-20 10:50:38.509385: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:50:38.509661: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:50:38.509691: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2.11.0
2023-02-20 10:50:39.302680: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2023-02-20 10:50:39.302792: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2023-02-20 10:50:39.302877: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (tilak-cpu-instance): /proc/driver/nvidia/version does not exist
2023-02-20 10:50:39.303293: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
(tf) tilakrayal@tilak-cpu-instance:~$ python3 59729numpy.py
2023-02-20 10:50:44.109269: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-20 10:50:44.275432: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2023-02-20 10:50:44.275480: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2023-02-20 10:50:45.183550: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:50:45.183669: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2023-02-20 10:50:45.183691: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2.11.0
2023-02-20 10:50:45.979766: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2023-02-20 10:50:45.979816: W tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:265] failed call to cuInit: UNKNOWN ERROR (303)
2023-02-20 10:50:45.979866: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (tilak-cpu-instance): /proc/driver/nvidia/version does not exist
2023-02-20 10:50:45.980332: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

@tilakrayal Shouldn't we investigate the issue on the nightly build, to ensure that we don't have a regression waiting for us later?
The issue is reproducible using the nightly build -- although it does not happen on all runs. You may have to run the code many times to observe it.
It seems to reproduce on a much higher percentage of runs on my laptop compared to on Colab.
Here's a gist reproducing the issue on nightly.
Here's a gist reproducing the issue on 2.11.

Thanks for getting back to me! I can still reproduce this issue. Please run it multiple times. Thanks!

Hi, @trickiwoo
Apologize for the delayed response and I was able to replicate the issue and I have executed the same code more than 100 times with tf-nightly, tensorflow==2.11,tensorflow==2.12.0rc0, tensorflow==2.12.0rc1  and in my case I got error with tf-nightly, for your reference I have added gist-file so we'll have to dig more into this issue and we'll update you soon, Thank you for noticing this issue.
@sachinprasadhs, Could you please look into this issue? Thank you!

@trickiwoo,
I tried to execute the above code in multiple iterations in the same colab notebook and observed it was executed without any fail/error. Kindly find the gist of it here. Thank you!


🐛 Bug Report: Uploading 0 byte files causes a hang

👟 Reproduction steps
https://user-images.githubusercontent.com/54511555/224586912-f92ed4eb-0dad-4de9-b186-37315691920e.mp4
👍 Expected behavior
Upload like normal files?
👎 Actual Behavior
Spinning wheel of death. Even though these files are obviously empty garbage, it should still allow an upload? The only use case here is imagine if the filename is what had the relevant information, not what's actually inside the file. We do not see Pingvin popup the share link modal, nor are any files copied into the shared directory that gets made. The folder is made, however, and possibly that means it's also in the database. It also does NOT show up in the shares if I refresh. So this might possibly cause ghost shares in the database. (preventing you from making a share with the same name due to a database conflict)
If there's a mix of normal files (aka >0 bytes) and one that isn't, it'll cause this break as well.
🌐 Browser
Chrome

Thanks for your report. This was fixed in f82099f36eb4699385fc16dfb0e0c02e5d55b1e3.

Fixed in the newest release.

[Nest] 260  - 03/14/2023, 5:04:30 PM   ERROR [ExceptionsHandler] The first argument must be of type string or an instance of Buffer, ArrayBuffer, or Array or an Array-like Object. Received undefined
03/14/2023 10:04:30 AM
TypeError [ERR_INVALID_ARG_TYPE]: The first argument must be of type string or an instance of Buffer, ArrayBuffer, or Array or an Array-like Object. Received undefined
03/14/2023 10:04:30 AM
    at new NodeError (node:internal/errors:399:5)
03/14/2023 10:04:30 AM
    at Function.from (node:buffer:326:9)
03/14/2023 10:04:30 AM
    at FileService.create (/opt/app/backend/dist/src/file/file.service.js:51:31)
03/14/2023 10:04:30 AM
    at async FileController.create (/opt/app/backend/dist/src/file/file.controller.js:31:16)

Windows. Right-Click -> New -> Text Document or Bitmap image
Here are my test files: https://we.tl/t-lmrRZcvS50

Oh, I see it's again an issue only in chrome :/ I'll look into it

https://www.w3schools.com/browsers/
Not a fan of Google either, but at 80% market share yeah, Chrome should be supported. :/
Btw the new modals previews are 🔥🔥🔥!!

Yeah sure, every modern browser must be supported. It's just that I forget sometimes to test everything in chrome too.
On my roadmap are Cypress tests, with them I would be able to test the app easily in all browsers but currently I don't have the time for it.
Thanks :) It was a really good suggestion to add modals because a user can now preview files much faster.

Btw. I've just released the fix but it can take up to an hour to finish the build of the image.

Works great. Thanks for the fix!


Update exporting-and-building-a-unity-visual-studio-solution.md

Updated exporting doc - Redundant information from Unity development overview, I noticed was updated in #379 but this was not.

:white_check_mark: Validation status: passed

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Status
Preview URL
Details

mixed-reality-docs/exporting-and-building-a-unity-visual-studio-solution.md
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For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.

Thanks @TobiahZ!


I Have Requests Installed...

...Python doesn't think so though:
Traceback (most recent call last):
File "B:\Facebook Savior\Project Outsmart\Project Outsmart\Project_Outsmart.py", line
14, in <module>
import requests
ModuleNotFoundError: No module named 'requests'

The script is programmed to exit immediately once opened and is completely useless.

Yeah, this script is s***, it does run at all when I specify options.

Oh man, the amount of times I tried to run this.......

8 times.......... and this is all it spits out:
Usage: python ./faceboom.py [OPTIONS...]
-------------
OPTIONS:
 |
|--------
| -t <target email> [OR] <FACEBOOK ID>    ::> Specify target Email [OR] Target Profile ID
|--------
| -w <wordlist Path>                      ::> Specify Wordlist File Path
|--------
| -s <single password>                     ::> Specify Single Password To Check
|--------
| -p <Proxy IP:PORT>                      ::> Specify HTTP/S Proxy (Optional)
 |--------
  | -g <TARGET Facebook Profile URL>        ::> Specify Target Facebook Profile URL For Get HIS ID
-------------
Examples:
 |
|--------
| python faceboom.py -t<EMAIL_ADDRESS>-w wlist.txt
|--------
| python Faceboom.py -t<PHONE_NUMBER>3246323 -w wlist.txt
|--------
| python faceboom.py -t<EMAIL_ADDRESS>-w wlist.txt -p <IP_ADDRESS> default(port=8080,80)
|--------      | python faceboom.py -t<EMAIL_ADDRESS>-s 1234567 |-------- | python faceboom.py -g https://www.facebook.com/victim-username |--------``

And the programmer has not arrived to rectify this.

You are getting banned for using inappropriate language and exploiting code of conduct of Faceboom.

Your projects getting reported for being useless.
On Tue, 23 Aug 2022, 11:03 pm Hassan Tahir, @.***>
wrote:

You are getting banned for using inappropriate language and exploiting
code of conduct of Faceboom.
—
Reply to this email directly, view it on GitHub
https://github.com/thehassantahir/Faceboom/issues/20#issuecomment-1224084749,
or unsubscribe
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You are receiving this because you authored the thread.Message ID:
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Added helm ignore file

This git patch/diff format is a standard format that shows the changes made to a repository. It includes the author, date, subject, and a list of files that were modified, added, or deleted.
In this specific patch, the author added a .helmignore file to the charts/applicationset directory and updated the version number in the Chart.yaml file from 0.8.23 to 0.8.24. The author also updated the artifacthub.io/changes annotation in the Chart.yaml file to reflect the addition of the .helmignore file.
Regarding optimization, it is difficult to suggest any optimization without more context on the project and its goals. However, it is always good practice to keep the changes as minimal as possible and to ensure that they are well-documented and easy to understand. In this case, the changes seem reasonable and well-documented.

This git patch/diff format is adding a .helmignore file to the charts/applicationset directory and updating the version number in the Chart.yaml file from "0.8.23" to "0.8.24". It also updates the annotations in the Chart.yaml file to reflect the addition of the .helmignore file.
In terms of optimization, it is difficult to suggest any specific changes based on the modified lines in the patch/diff. However, it is generally good practice to keep the changes as small and focused as possible, and to provide clear and concise commit messages that explain the purpose of the changes. In this case, the commit message "Added helm ignore file" is clear and concise, and the changes are focused on adding the .helmignore file and updating the version number and annotations in the Chart.yaml file.


Make IUIA() not a singleton back to resolve potential threading issues

This might be a root cause of the threading issue mentioned on StackOverflow.

Hey I have got the same threading issue. I don't think I can work around it using a single thread. Is there any chance to have a fix for this soon or at least get a hack in the meantime?
Thanks.

Hmm... I'm pretty busy this month. But will try to take some time for that. I think only this issue + NULL COM pointer crash #296 will be included into next bug fix release. Because both issues can't be workarounded. Thanks for follow up.

I have found a way to put it on the main thread but that's not ideal. That will do for now.
Thanks.

Hmm I talked too fast. Well it works on the main application but then I can't run my unit tests which needs to be on a separate thread :(

I tried to look into it today. Here several my findings so far.
Comtypes package we use, automatically calls to CoInitializeEx() and CoUnitialize() on the main thread. It means that by default our IUIA singleton runs in STA (Single Threaded Appartments). Since the inability to interact with the COM client from other threads - the main thread has to run a special loop with PeekMessage() and DispatchMessages() to process messages from other threads sent by UIA. The comtypes initialization can be changed to MTA through  sys.coinit_flags even without modifying pywinauto sources:
import sys
sys.coinit_flags = 0  # COINIT_MULTITHREADED = 0x0
import pywinauto

This will enable access to the COM from different threads. However it comes with the price, the caller has to take care of the thread safety. It works for simple examples like in #416, but more hiccups will quickly pop up with more complicated scenarios.
Another problem with MTA, I bumped into, is RPC_E_CHANGED_MODE error. For example, an attempt to run pywinauto unit tests rises WindowsError exception in comtypes init with RPC_E_CHANGED_MODE. Most probably, it's due to another DLL that already set up the main thread mode to STA during its loading. A possible solution would be moving IAUA singleton in a separate thread initialised as MTA, thus allowing access to the COM from different threads (but taking the risks of data access synchronisation)
These are also Microsoft recommendations for UI automation threading:

If your client application is intended to interact with all elements on the desktop, including its own UI, you should make all UI Automation calls from a separate thread. This includes locating elements, for example, by using IUIAutomationTreeWalker or the IUIAutomationElement::FindAll method and using control patterns. This thread should not own any windows, and should be a Component Object Model (COM) Multithreaded Apartment (MTA) model thread (one that initializes COM by calling CoInitializeEx with the COINIT_MULTITHREADED flag.)

pywinauto satisfies the requirement do not own any windows so, probably, UI Automation calls can be done from any thread. However, from my search in the Internet it's not clear how stable is UI Automation under multi threading.

@vasily-v-ryabov, seems that I figured out the RPC_E_CHANGED_MODE problem in our unit tests: I suspect that pythoncom has been imported implicitly before our code and set up STA mode. Now if I change the imports order in our unit tests we can run them under MTA. Should I create PR to switch on MTA by default or we can stick to STA but users will be required to specify sys.coinit_flags = 0 explicitly before importing pywinauto ?
@maxime-viargues-serato, could you please try running your multi-threading program  with the sys.coinit_flags as I described in my previous comment ?

@airelil maybe explicit switching to MTA makes sense by default. But I'd suggest to warn user if STA mode was enabled before importing pywinauto. Or maybe some function/property like threading_mode makes sense. Calling sys.coinit_flags = 0 explicitly looks like a hack. Calling pywinauto.multi_threading_mode = True is more clear I think.

I made some work in my mta branch. These changes switching MTA on by default. So far, looks good, but as usual, got stuck with a couple of failing unit tests (not sure yet, if it's related to the change). I also considering to add threading.Lock to all IUAI calls.

@airelil Yes indeed that fixes the problem to use sys.coinit_flags = 0


Run prettier on PR

We need to figure out how to not let people push in non-prettified code

Do the pre-commit hooks not resolve this already? And ik what happened yesterday but still, don't ppl just need to run 'npm install' to get that set up?

yes and no - I think lintstaged doesn't auto install the git precommit hooks
doesn't hurt to just redo what we did over at the hkn-server repo and run prettier --check :)

Oh oops, I was thinking this was on hkn-server when I wrote that comment. I'll make the changes


Part of face even no real face can be recognize as humanbeings.

Issue Description
Part of face even no real face can be recognize as humanbeings.
Steps to Reproduce
1.Open  face detector only.
2.Fist to the camera.
3.Function of human.detect returns value which has face and the face.length>0.
Expected Behavior
The fucntion reutrns value no face if there is no face in the detection area.
**Environment

Browser or NodeJS and version (e.g. NodeJS 14.15 or Chrome 86)
OS and Hardware platform (e.g. Windows 10, Ubuntu Linux on x64, Android 10)
Packager (if any) (e.g, webpack, rollup, parcel, esbuild, etc.)

Additional
    "@vladmandic/human": "0.9.26",

{
    backend: 'webgl', // select tfjs backend to use
    wasmPath: `/human/assets/`, // path for wasm binaries
    // only used for backend: wasm
    console: debug, // enable debugging output to console
    async: true, // execute enabled models in parallel
    // this disables per-model performance data but
    // slightly increases performance
    // cannot be used if profiling is enabled
    profile: false, // enable tfjs profiling
    // this has significant performance impact
    // only enable for debugging purposes
    // currently only implemented for age,gender,emotion models
    deallocate: false, // aggresively deallocate gpu memory after each usage
    // only valid for webgl backend and only during first call
    // cannot be changed unless library is reloaded
    // this has significant performance impact
    // only enable on low-memory devices
    scoped: false, // enable scoped runs
    // some models *may* have memory leaks,
    // this wrapps everything in a local scope at a cost of performance
    // typically not needed
    videoOptimized: true, // perform additional optimizations when input is video,
    // must be disabled for images
    // basically this skips object box boundary detection for every n frames
    // while maintaining in-box detection since objects cannot move that fast
    warmup: 'face', // what to use for human.warmup(), can be 'none', 'face', 'full'
    // warmup pre-initializes all models for faster inference but can take
    // significant time on startup
    filter: {
      enabled: false, // enable image pre-processing filters
      width: 0, // resize input width
      height: 0, // resize input height
      // if both width and height are set to 0, there is no resizing
      // if just one is set, second one is scaled automatically
      // if both are set, values are used as-is
      return: true, // return processed canvas imagedata in result
      brightness: 0, // range: -1 (darken) to 1 (lighten)
      contrast: 0, // range: -1 (reduce contrast) to 1 (increase contrast)
      sharpness: 0, // range: 0 (no sharpening) to 1 (maximum sharpening)
      blur: 0, // range: 0 (no blur) to N (blur radius in pixels)
      saturation: 0, // range: -1 (reduce saturation) to 1 (increase saturation)
      hue: 0, // range: 0 (no change) to 360 (hue rotation in degrees)
      negative: false, // image negative
      sepia: false, // image sepia colors
      vintage: false, // image vintage colors
      kodachrome: false, // image kodachrome colors
      technicolor: false, // image technicolor colors
      polaroid: false, // image polaroid camera effect
      pixelate: 0 // range: 0 (no pixelate) to N (number of pixels to pixelate)
    },

    gesture: {
      enabled: true // enable simple gesture recognition
    },

    face: {
      enabled: true, // controls if specified modul is enabled
      // face.enabled is required for all face models:
      // detector, mesh, iris, age, gender, emotion
      // (note: module is not loaded until it is required)
      detector: {
        modelPath: `/human/models/blazeface-back.json`, // can be 'front' or 'back'.
        // 'front' is optimized for large faces
        // such as front-facing camera and
        // 'back' is optimized for distanct faces.
        inputSize: 256, // fixed value: 128 for front and 256 for 'back'
        rotation: false, // use best-guess rotated face image or just box with rotation as-is
        maxFaces: 5, // maximum number of faces detected in the input
        // should be set to the minimum number for performance
        skipFrames: 11, // how many frames to go without re-running the face bounding box detector
        // only used for video inputs
        // e.g., if model is running st 25 FPS, we can re-use existing bounding
        // box for updated face analysis as the head probably hasn't moved much
        // in short time (10 * 1/25 = 0.25 sec)
        minConfidence: 0.5, // threshold for discarding a prediction
        iouThreshold: 0.2, // threshold for deciding whether boxes overlap too much in
        // non-maximum suppression (0.1 means drop if overlap 10%)
        scoreThreshold: 0.5 // threshold for deciding when to remove boxes based on score
        // in non-maximum suppression,
        // this is applied on detection objects only and before minConfidence
      },

      mesh: {
        enabled: false,
        modelPath: `/human/models/facemesh.json`,
        inputSize: 192, // fixed value,
        returnRawData: false // in addition to standard mesh and box values, return raw normalized values as well
      },

      iris: {
        enabled: false,
        modelPath: `/human/models/iris.json`,
        inputSize: 64 // fixed value
      },

      age: {
        enabled: false,
        modelPath: `${resourcesUrl}human/models/age-ssrnet-imdb.json`, // can be 'age-ssrnet-imdb' or 'age-ssrnet-wik'
        // which determines training set for model
        inputSize: 64, // fixed value
        skipFrames: 31 // how many frames to go without re-running the detector
        // only used for video inputs
      },

      gender: {
        enabled: false,
        minConfidence: 0.1, // threshold for discarding a prediction
        modelPath: `/human/models/gender-ssrnet-imdb.json`, // can be 'gender', 'gender-ssrnet-imdb' or 'gender-ssrnet-wik'
        inputSize: 64, // fixed value
        skipFrames: 41 // how many frames to go without re-running the detector
        // only used for video inputs
      },

      emotion: {
        enabled: false,
        inputSize: 64, // fixed value
        minConfidence: 0.2, // threshold for discarding a prediction
        skipFrames: 21, // how many frames to go without re-running the detector
        modelPath: `/human/models/emotion-large.json` // can be 'mini', 'larg'
      },

      embedding: {
        enabled: false,
        inputSize: 112, // fixed value
        modelPath: `/human/models/mobilefacenet.json`
      }
    },

    body: {
      enabled: false,
      modelPath: `/human/models/posenet.json`,
      inputSize: 257, // fixed value
      maxDetections: 10, // maximum number of people detected in the input
      // should be set to the minimum number for performance
      scoreThreshold: 0.5, // threshold for deciding when to remove boxes based on score
      // in non-maximum suppression
      nmsRadius: 20, // radius for deciding points are too close in non-maximum suppression
      outputStride: 16, // size of block in which to run point detectopn, smaller value means higher resolution
      // defined by model itself, can be 8, 16, or 32
      modelType: 'MobileNet' // Human includes MobileNet version, but you can switch to ResNet
    },

    hand: {
      enabled: false,
      inputSize: 256, // fixed value
      skipFrames: 15, // how many frames to go without re-running the hand bounding box detector
      // only used for video inputs
      // e.g., if model is running st 25 FPS, we can re-use existing bounding
      // box for updated hand skeleton analysis as the hand probably
      // hasn't moved much in short time (10 * 1/25 = 0.25 sec)
      minConfidence: 0.5, // threshold for discarding a prediction
      iouThreshold: 0.1, // threshold for deciding whether boxes overlap too much
      // in non-maximum suppression
      scoreThreshold: 0.8, // threshold for deciding when to remove boxes based on
      // score in non-maximum suppression
      maxHands: 1, // maximum number of hands detected in the input
      // should be set to the minimum number for performance
      landmarks: true, // detect hand landmarks or just hand boundary box
      detector: {
        modelPath: `/human/models/handdetect.json`
      },
      skeleton: {
        modelPath: `/human/models/handskeleton.json`
      }
    }
  };

Looking forward to ur reply.
Tks.

how it works is that detector prepares list of candidates for face boxes and then mesh actually discards invalid entries and also stabilizes facial bounding boxes
if mesh is disabled, output of detector only is not reliable
can you retry with mesh enabled,
but instead of just looking at face.length > 0, check the values for
for (const f in face) console.log(`Face #{f} ${face[f].faceConfidence} ${face[f].boxConfidence}`);

i'll update docs to reflect this

if you only need face detection and nothing else, you can try alternative model
default model is BlazeFace, but that only works when combined with FaceMesh
but there is also FaceBoxes which is a standalone detector - exactly for the reason that BlazeFace is not that good when running as standalone model
const myConfig = {
  videoOptimized: false,
  face: {
    enabled: true,
    detector: { modelPath: '/human/models/faceboxes.json', enabled: true, minConfidence: 0.5 },
    mesh: { enabled: false },
    iris: { enabled: false },
    age: { enabled: false },
    gender: { enabled: false },
    emotion: { enabled: false },
  },
  body: { enabled: false },
  hand: { enabled: false },
};

I'm still looking for a single good algorithm for face detection that can replace both.

Where can I find this faceboxes model?

I wrote a month ago:

You can skip testing faceboxes, I've decided to remove it and focus on improving primary model - blazeface

If you really want to check it out, you can clone the repository and go back to version 0.9.x (faceboxes model was removed with 1.0 release). alternative, old versions are archived on npmjs, so you can just install a 0.9.x version of human using npm.


Added colors and put [Expose] ontop of props

Colors == happy eyes while reading a cool library
Also I put the [Expose] Attribute ontop of the class properties like the other properties had

Neat. I didn't know that was possible.


Storing koji build id as label.

[ Issue #439 ]
Modified KojiPromotePlugin to return the ID of the started Koji build.
Added to DockerBuildWorkflow exit_result attribute to store results from exit plugins.
Modified StoreMetadataInOSv3Plugin to set a label on the OS Build with the previously stored Koji build ID.
Also, fixed PrePublishPluginsRunner to use the correct results dict.

Coverage increased (+0.07%) to 86.919% when pulling c66d700577345d4fe072d54e259cc7bbf61270e4 on lcarva:storing-koji-build-id into 3a19d4cc2548eb27f4d2925a329efa37e417c701 on projectatomic:master.

Coverage increased (+0.07%) to 86.919% when pulling 50964c9fbfa892d56ee891c965f294ad7da12249 on lcarva:storing-koji-build-id into 3a19d4cc2548eb27f4d2925a329efa37e417c701 on projectatomic:master.

LGTM

Having tested this in an environment where CGImport() returns the build information, I now see that we'll have to change to order that the plugins run. Currently the store_metadata plugin runs before koji_promote, so it doesn't see the build ID result.
I've filed a pull request to fix this: https://github.com/projectatomic/osbs-client/pull/406


Refactoring: Auth page

I extracted some logic from view layer to re-frame handler

thanks looks good

@yogthos tnx for review, pls check out #42 last commit fix that issue


Ensure generate-helper-types works with single-file mode

This resolves https://github.com/dotnet/ClangSharp/issues/339

Hi, it seems generate-helper-types does not work in multi-file mode? I tried with 15.0.2 and received error like "cannot open stream to write".


Provide uninstall parameter and logic in the role

Summary
I would like to see a way for this role to be modified so that a user can uninstall an agent. The official documentation references a parameter that doesn't exist in this role.
Desired Behavior
We should be able to set a variable, like agent_state to absent to remove the installation.
Additional context
This features matters to me because my team has a case where we need to reduce data getting sent to New Relic and we have over 100 servers that we have to login manually and uninstall.

As well as change parameters... If I disable logging in vars, it should be disabled on the servers.


Not all boosts, stars, replies, followers, etc of a post are taken into account for scoring

Since the user's home instance is not aware of all followers of the author and all boosts, stars, etc, related to the post, the Scorer works with incomplete information when calculating the score for the post based on the information retrieved from the timeline request to the home instance.
It would be more accurate to query the information about the post and the user from their respective home instance.

I think my main concern here is that it would result in the script potentially making up to 10,000 HTTP requests to generate, since it would GET each post to build out the data. I agree that the incomplete data is not ideal, but I'm trying to balance "good enough" with precision. Right now, I suspect the "good enough" is actually working well enough, but I'm open to your thoughts here.

The "good enough" strongly depends on your instance (and also on the followed person). If you instance knows a lot of the fediverse, resp. parts relevant to the post, which should be stored, you are fine with the approximate result, probably.
What are the concerns with the GET-requests?
I thought, it might not be too bad, since they are directed to many different hosts, usually, plus there is a timeout, after which further requests are aborted.

I truly appreciate the interest in iterating on this tool. I hope folks can find home in their unique forks. Please see the update in the readme:

⚠ Update, 2023-05-21: Mastodon Digest is currently in maintenance-only mode. I do not have the capacity to continue fielding feature requests or PRs that fundamentally alter the way the tool works. If you have an idea for a new feature, forks are encouraged. I will continue to push updates for bug or security fixes. If you're looking for options that are more actively maintained, I suggest: Fediview or this fork. I'm heartened by how much positive attention this got among many Mastodon communities. For me this was always a toy. I'm glad I could push some open source code that gave people room to experiment.


Added the code to extract the YouTube Trending Page Data

Added the code to extract the YouTube Trending Page Data
I added the code, which will output a CSV file containing the data of currently Trending videos on YouTube.
Dependencies:
Following libraries & modules:

selenium
pandas
json

In order to run Selenium on the local system, the user might have to install the relevant browser drivers for Selenium.
Fixes #124
Type of change
Please delete options that are not relevant.

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

Checklist:

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

@aditsawant Supper happy with the implementation! Thanks for contributing

@aditsawant Supper happy with the implementation! Thanks for contributing

Thank you for the idea! Learned a lot along the way :)


Swiper Slider RTL - Ending Puncutation and Special Characters go to the left instead of the right

I was implementing Swiper Slider's RTL feature and I notice that the punctuation and special characters on the text seems to shift to the left instead of the right when towards the end of a sentence. This is rather irritating. I've looked over the documentation and the settings seem to be the same. Just wanted to bring this up to your attention in case you know of a fix to it.
This is a (multiple allowed):

[x] bug

[ ] enhancement

[ ] feature-discussion (RFC)

Swiper Version: EXACT RELEASE VERSION OR COMMIT HASH, HERE.

Live Link or JSFiddle/Codepen or website with isssue: PREFERABLY (IF YOU WANT YOUR ISSUE TO BE RESOLVED ASAP).

Expected Behavior
EXPLAIN WHAT IS TO BE EXPECTED, HERE.
Actual Behavior
EXPLAIN WHAT IS ACTUALLY HAPPENING, HERE.
P.S. Remember, an issue is not the place to ask questions. You can use Stack Overflow
for that.
Before you open an issue, please check if a similar issue already exists or has been closed before.

Sorry but it is not related to Swiper, closing the issue


Want to delete host but stay at REMOVING status

**Rancher Version: 1.14
**Docker Version:1.12.1
**Environment Type: Cattle
**Steps to Reproduce: At first, I found one of my host is dissconnected, there were some containers run in this host before,  then I want to delete it
**Results: but I find that the host is stay at REMOVING, and have no change any more
**Expected: so where I can fix this problems, by the way, it there any way I can re-connect my host if without delete it alreay dissconnect

Same for me, but rancher version 1.2.1

2016-12-19 13:50:43,752 ERROR [:] [] [] [] [ecutorService-7] [.e.s.i.ProcessInstanceDispatcherImpl] Unknown exception running process [host.remove:175522] on [26], canceled by [State [requested] is not valid for process [storagepoolhostmap.remove:null] on resource [39]]
2016-12-19 13:50:43,784 ERROR [:] [] [] [] [cutorService-14] [.e.s.i.ProcessInstanceDispatcherImpl] Unknown exception running process [host.remove:169961] on [14], canceled by [State [requested] is not valid for process [storagepoolhostmap.remove:null] on resource [25]]
2016-12-19 13:50:43,784 ERROR [:] [] [] [] [ecutorService-6] [.e.s.i.ProcessInstanceDispatcherImpl] Unknown exception running process [host.remove:176749] on [27], canceled by [State [requested] is not valid for process [storagepoolhostmap.remove:null] on resource [41]]

Downgraded back to 1.2.0 and the error disappeared, seems to have been introduced in 1.2.1

Ok I've setup a new instance today, completely fresh and can confirm, this bug seems to have been introduced in 1.2.1, and does only occur there and only for cloud environments like Azure.

Having this issue as well on:
Rancher: version 1.2.1
Kernel: 4.8.6
Docker: 1.12.3

Thanks, I'll see if I can address this in 1.2.2.  Some of the cleanup logic may have adversely impacted host delete.

I am seeing this as well on 1.2.1. Hosts running on EC2
The hosts are added and removed by spotinst, if it matters.
I hopped onto one of the hosts in this state and got the end of the network manager log:
time="2016-12-21T13:58:56Z" level=error msg="Failed to evaluate network state for 078b36b920a23f4a210ff32ae5362f5469d18dfceff848756bd3f6d739dc2a28: netplugin failed but error parsing its diagnostic message \"\": unexpected end of JSON input"
time="2016-12-21T13:58:56Z" level=error msg="Error processing event &docker.APIEvents{Action:\"die\", Type:\"container\", Actor:docker.APIActor{ID:\"078b36b920a23f4a210ff32ae5362f5469d18dfceff848756bd3f6d739dc2a28\", Attributes:map[string]string{\"io.rancher.project_service.name\":\"staging1-apps/proxy\", \"io.rancher.service.requested.host.id\":\"198\", \"com.redacted.desc\":\"Application request router\", \"io.rancher.loadbalancer.target.app-chat\":\"/cgi-bin/WebObjects/ChatServer.woa=56795\", \"io.rancher.loadbalancer.target.app-mobile\":\"/cgi-bin/WebObjects/MobileServer.woa=56793\", \"io.rancher.cni.wait\":\"true\", \"io.rancher.container.create_agent\":\"true\", \"io.rancher.service.hash\":\"ea398cec4b913bc3de1c54cc00f1a90ef056fc45\", \"io.rancher.loadbalancer.target.app-router\":\"/cgi-bin/WebObjects/Router.woa=56794\", \"io.rancher.service.deployment.unit\":\"45f0a39b-7238-4eb5-b86a-5cdbe08940cf\", \"io.rancher.cni.network\":\"ipsec\", \"io.rancher.container.hostname_override\":\"container_name\", \"io.rancher.loadbalancer.target.app-mmvxml\":\"/cgi-bin/WebObjects/MMVXML.woa=56790\", \"io.rancher.container.agent_id\":\"1486\", \"io.rancher.container.ip\":\"<IP_ADDRESS>/16\", \"io.rancher.container.uuid\":\"d15c0b09-a2d0-49e1-ac8b-97e19c3fb0a9\", \"io.rancher.loadbalancer.target.app-api\":\"/cgi-bin/WebObjects/MMAPI.woa=56792\", \"io.rancher.scheduler.global\":\"true\", \"image\":\"rancher/lb-service-haproxy:v0.4.6\", \"io.rancher.container.name\":\"staging1-apps-proxy-2\", \"io.rancher.loadbalancer.target.app-redacted\":\"/cgi-bin/WebObjects/redacted.woa=56789\", \"io.rancher.loadbalancer.target.app-redacted-rest\":\"/cgi-bin/WebObjects/redacted.woa/wa/Rest=56789\", \"io.rancher.project.name\":\"staging1-apps\", \"io.rancher.stack.name\":\"staging1-apps\", \"exitCode\":\"1\", \"io.rancher.container.agent.role\":\"environmentAdmin\", \"name\":\"r-staging1-apps-proxy-2-d15c0b09\", \"io.rancher.service.launch.config\":\"io.rancher.service.primary.launch.config\", \"io.rancher.stack_service.name\":\"staging1-apps/proxy\"}}, Status:\"die\", ID:\"078b36b920a23f4a210ff32ae5362f5469d18dfceff848756bd3f6d739dc2a28\", From:\"rancher/lb-service-haproxy:v0.4.6\", Time:1482328736, TimeNano:1482328736136302250}. Error: netplugin failed but error parsing its diagnostic message \"\": unexpected end of JSON input"
time="2016-12-21T13:58:57Z" level=info msg="CNI down" cid=29bdb8905309ee6544c810bcc37c023b4a4d2d80493e1675a53debc79c3eae7b networkMode=ipsec
nsenter: cannot open /proc/10545/ns/ipc: No such file or directory

I am seeing this issue on Rancher 1.2.1 with hosts (Ubuntu 16.04 LTS) deployed on AWS. In one environment, the issues occurred and in another one it did not.

Does anyone have any reproducible steps so I can try to reproduce it?

Hi @deniseschannon.
Steps are:

Register a host/agent (in my case a GCE Instance)
Wait for it to show in Rancher UI
Delete the Instance (before removing from the UI)
Wait for it to show as "Disconnected" in UI
Try and Deactivate+Delete it in Rancher

Rancher configuration:

"Fresh" Rancher 1.2.1 installation and its database
Default Rancher Environment (cattle)
Using rancher-nfs

@francoishill , Thank you. I am able to reproduce the issue with the steps you have provided.

@sangeethah In my case, the issue happened after I did the following:

Add a new host
Deactivate old host
Wait for services to be restarted on another host
Remove old host
At this point the old host is stuck in state "removing". Unfortunately, this happened in one of three environments. All environments are managed by the same Rancher server.

Tested with v1.2.2-rc2:
Cattle environment with few  hosts( from GCE) and rancher-nfs deployed.
Delete the host from GCE (before removing from the cattle UI)
Wait for it to show as "Disconnected" in UI
Try and Deactivate+Delete it in Rancher.
Host gets removed successfully.
@nicholasdille , there was a fix relating to failure in storagepoolhostmap.remove that was done.Fix should be available in v1.2.2 release.

@sangeethah Thanks! Is there a way to remove those hosts manually before the update to v1.2.2 or will v1.2.2 take care of this automagically?


Task 5

Task 5
User Story
AS AN employer
I WANT to view a potential employee's deployed portfolio of work samples
SO THAT I can review samples of their work and assess whether they're a good candidate for an open position
Acceptance Criteria
GIVEN I need to sample a potential employee's previous work
WHEN I click on the images of the applications
THEN I am taken to that deployed application

completed in previous commits


Doc links broken

http://social-stream.dit.upm.es/started#components
Just shows error, "Error establishing a database connection"

Works right over here.


feat(ch-unit): remove links

Both links give a 404

Fixed the first link, it'd simply moved, replaced the second link with this one.
But thanks for bringing this up!


Fix bug gt50 when jumping too low below 50%

Similar to https://github.com/teobais/percircle-vue/pull/3

@miller-kevin same approach here too if time allows, otherwise, it's listed as up for grabs anyway for others that might want to give this a try

@teobais I'll try to find time to address this. Picked up an extra side contract this week and will be busy until ~March 1st.  I think it should be simple enough to make it happen here too, and will try my best to handle it as time allows