/usr/local/lib/libopencv_core.so：对‘cudaEventRecord’未定义的引用

when run make,the error like this:
/usr/local/lib/libopencv_core.so：对‘cudaEventRecord’未定义的引用
/usr/local/lib/libopencv_core.so：对‘cudaEventRecord’未定义的引用
....
collect2: error: ld returned 1 exit status

This is a problem with your OpenCV build, not FaceTracker.


Add File Download testing to Daily Data smoke test user flow

Problem statement
Checking for File Download capability was removed from the previous ticket #15211. So we need to add that capability back in.
What you need to know
We need to select a Covid pipeline receiver in order to ensure that the Report details lists facility data.
As an admin, select the ignore org and navigate to the Daily Data page.

UP receiver: ignore.FULL_ELR
CP receiver: ignore.CSV
ELIMS receiver: ignore.ELR_ELIMS

Acceptance criteria
For a Universal pipeline receiver:

[ ] First record downloads when filename clicked
[ ] Downloaded filename matches filename shown in Filename column

Still not working. Reopening.

@etanb for awareness

@etanb Can you double check the acceptance criteria and check off the completed ones?


Windows: ImportError: No module named termios

I am getting following exception while using capturer at https://github.com/binit92/OpenWARP
running build_ext
Traceback (most recent call last):
File "main.py", line 44, in
from openwarp.web import WebController
File "C:\Users\binit92\Downloads\OpenWARP-master\OpenWARP-master\source\openwarpgui\openwarp\web.py", line 27, in
from openwarp import services
File "C:\Users\binit92\Downloads\OpenWARP-master\OpenWARP-master\source\openwarpgui\openwarp\services.py", line 44, in
from capturer import CaptureOutput
File "C:\Anaconda\lib\site-packages\capturer__init__.py", line 10, in <module

import pty

File "C:\Anaconda\lib\pty.py", line 11, in
import tty
File "C:\Anaconda\lib\tty.py", line 5, in
from termios import *
ImportError: No module named termios

@binit92 , it looks like the dependency does not yet support windows [1]. Maybe if you know of a fix you could send PR to either there or here. Alternatively, maybe Microsoft has added a feature that would help and/or if you upgrade to Win10.1 it would work?
On OSX 10.11.6 it is working great for me. It is a terrific helper.
Anne
1.[] ; ; ; X.36.9. pty — Pseudo-terminal utilities — Python 2.7.12 documentation ; ; https://docs.python.org/2/library/pty.html
Because pseudo-terminal handling is highly platform dependent, there is code to do it only for Linux. (The Linux code is supposed to work on other platforms, but hasn’t been tested yet.)

Hi Binit and thanks for the feedback. I created the capturer package for use on UNIX systems with the specific goal of emulating a real terminal and to accomplish this I used the pty module. Even though this module is included in Python's standard library it is UNIX specific and so doesn't support Windows. This is mentioned in the readme:

The use of pty.openpty() means you need to be running in a UNIX like environment for capturer to work (Windows definitely isn't supported).

I don't know of any meaningful way to add Windows support to capturer, however I have made the supported operating systems more explicit by mentioning them in the introduction of the readme:

The capturer package makes it easy to capture the stdout and stderr streams of the current process and subprocesses. Output can be relayed to the terminal in real time but is also available to the Python program for additional processing. It's currently tested on cPython 2.6, 2.7, 3.4, 3.5 and PyPy (2.7). It's tested on Linux and Mac OS X and may work on other unixes but definitely won't work on Windows (due to the use of the platform dependent pty module).

I'm going to close this issue now given that the lack of Windows support is "by design".


Run tanka inside the cluster and use service account token

Hi team,
I tried to use tanka in my github runner which runs in my cluster. Different to kubectl which can pick up /run/secrets/kubernetes.io/serviceaccount/token and connect to kubernetes cluster API tanka relies on kubectl context(which doesn't exist in a container). Is there a way to tell tanka to use the service account token?
Currently I use a workaround:
tk show environments/default/ --dangerous-allow-redirect  |kubectl apply -f -

Please advise.
Thanks.
Ray

I often hear Tanka users implementing a CD solution like Flux or ArgoCD that reads the plain manifests generated by tk export. These CD solution are arguably more suited to run inside a cluster. Tanka was not build with that in mind and we currently don't have plans to turn this into a CD solution.
In case you still want to go through with it, you could devise a KUBECONFIG that uses the service account, have a look here for inspiration: https://stackoverflow.com/questions/55629894/kubernetes-kubeconfig-with-service-account-token

@Duologic thanks for the explanation, I'll have a look at ArgoCD.


Update Dockerfile URL

Thank you for submitting this pull request, however I do not see a valid CLA on file for you. Before we can merge this request please visit https://yahoocla.herokuapp.com/ and agree to the terms. Thanks! :smile:

hi
It doesn't work on my machine.
It fails at step 7/12
log here -->
https://gist.github.com/julienbalas/eef469ef827bdf21d58a46d333543a49
Best regards


LDAP username issue in v0.9.46

I'm a big fan of Gogs - I've been using it to host my department's Git repositories for the past 4 months. Gogs 0.9.13 works flawlessly with my company's LDAP server (using the BindDN authentication type).
Using the same settings, LDAP doesn't seem to work for me in Gogs 0.9.46. I tried each of the new "Security Protocol" settings, and also went through all of the TLS checkbox settings for each protocol mode.
In the logfile, I found the following message:
2016/07/20 17:39:27 [W] Failed to login 'nicholas.clark' via 'Boulder_Bind': Invalid pattern
for attribute 'username' [Nicholas.Clark]: must be valid alpha or numeric or dash(-_) or dot
characters

Is this some kind of a regex bug somewhere? The username "nicholas.clark" is only letters and dots, so I would have expected it to work. It also worked fine in Gogs 0.9.13.
Here's my setup:
Git: 2.7.4
Operating System: Ubuntu 16.04
Database: SQLite

Thanks your feedback!
Patch has pushed to fix this issue, please test on master branch or https://try.gogs.io.

This works now. Thanks!

Just hit this when updating the cloudron app. For those wondering, the fix is at https://github.com/gogits/gogs/commit/57af7432fc07f630e435228a306a9deeb3fefa1e


[BEAM-2852] Add support for Kafka as source/sink on Nexmark

Allows to use Kafka as as source/sink for Nexmark benchmark.
Based on original implementation of #3937 by @vectorijk
Follow this checklist to help us incorporate your contribution quickly and easily:

[x] Make sure there is a JIRA issue filed for the change (usually before you start working on it).  Trivial changes like typos do not require a JIRA issue.  Your pull request should address just this issue, without pulling in other changes.
[x] Format the pull request title like [BEAM-XXX] Fixes bug in ApproximateQuantiles, where you replace BEAM-XXX with the appropriate JIRA issue.
[x] Write a pull request description that is detailed enough to understand:

[ ] What the pull request does
[ ] Why it does it
[ ] How it does it
[ ] Why this approach

[ ] Each commit in the pull request should have a meaningful subject line and body.
[x] Run mvn clean verify to make sure basic checks pass. A more thorough check will be performed on your pull request automatically.
[ ] If this contribution is large, please file an Apache Individual Contributor License Agreement.

Run Java PreCommit

@aromanenko-dev please update gradle build to reflect maven one, squash this commit with code style one and run "Run Java PreCommit" to launch gradle build. LGTM at green lights of gradle build

Run Java PreCommit

Merging this PR, we will takle COMBINED mode (refactoring this mode in pub/sub and apply it to kafka) in another PR

Thanks! @aromanenko-dev

@vectorijk Thank you for your initial work!


[Peek] Add video previewer

Description of the new feature / enhancement
Add Video previewer for peek. Supports all video types
ex.  ".mp4", ".3g2", ".3gp", ".3gp2", ".3gpp", ".asf", ".avi", ".m2t", ".m2ts", ".m4v", ".mkv", ".mov", ".mp4", ".mp4v", ".mts", ".wm", ".wmv",
Scenario when this would be used?
When opening a video type.
Supporting information
No response

This is part of the main feature in #80


avoid TypeError when exiting

I'm developing a binding based on FFI, and frequently the C library asserts. That's okay. But then, instead of just reporting that failure, rspec crashes with a TypeError while exiting:
[...]
  #configure
    with support for UDP broadcasts
      sends correct message to actor
    no support for UDP broadcasts
      raises
  #publish
    with data
      sends correct message to actor
    with data too long
      raises
  #silence
Assertion failed: (self->handle), function zsock_new_checked, file src/zsock.c, line 69.
/Users/paddor/.rubies/ruby-2.3.0/bin/ruby -I/Users/paddor/.gem/ruby/2.3.0/gems/rspec-support-3.4.1/lib:/Users/paddor/.gem/ruby/2.3.0/gems/rspec-core-3.4.1/lib /Users/paddor/.gem/ruby/2.3.0/gems/rspec-core-3.4.1/exe/rspec --pattern spec/\*\*\{,/\*/\*\*\}/\*_spec.rb failed
rake aborted!
TypeError: no implicit conversion from nil to integer
/Users/paddor/.gem/ruby/2.3.0/gems/rspec-core-3.4.1/lib/rspec/core/rake_task.rb:84:in `exit'
/Users/paddor/.gem/ruby/2.3.0/gems/rspec-core-3.4.1/lib/rspec/core/rake_task.rb:84:in `run_task'
/Users/paddor/.gem/ruby/2.3.0/gems/rspec-core-3.4.1/lib/rspec/core/rake_task.rb:96:in `block (2 levels) in define'
/Users/paddor/.gem/ruby/2.3.0/gems/rspec-core-3.4.1/lib/rspec/core/rake_task.rb:94:in `block in define'
Tasks: TOP => default => spec
(See full trace by running task with --trace)

This leads to confusion when not used to seeing this failure. This PR solves this annoyance.

Hmm, but this would default the rake task exit status to 1, which is not what we want. If RSpec is exiting with a 0 exit status for this the problem should be handled in the runner, not the rake task...

@JonRowe I'm not exactly sure what you mean. Keep in mind that 0 is a truthy value for Ruby. Running the test suite will nicely exit with exit status 0, in case the library doesn't assert.
Not sure in which cases $?.exitstatus returns nil, but if it does, something definitely went wrong. And if it can't tell what went wrong (by returning an Integer), it's IMHO okay to default it to 1.

Ah I see $? is nil? That wasn't clear from your initial report, hmm, technically this should return the RSpec failure code (which is configurable) or perhaps raise an error itself when this occurs...

Honestly I'm not sure. All I know is that, in case the test suite process exits abruptly, a TypeError is raised on line 84 in rake_task.rb. Here's the trailing output of rake --verbose --trace:
  #publish
    with data
      sends correct message to actor
    with data too long
      raises
  #silence
Assertion failed: (self->handle), function zsock_new_checked, file src/zsock.c, line 69.
/Users/paddor/.rubies/ruby-2.3.0/bin/ruby -I/Users/paddor/.gem/ruby/2.3.0/gems/rspec-support-3.4.1/lib:/Users/paddor/.gem/ruby/2.3.0/gems/rspec-core-3.4.2/lib /Users/paddor/.gem/ruby/2.3.0/gems/rspec-core-3.4.2/exe/rspec --pattern spec/\*\*\{,/\*/\*\*\}/\*_spec.rb failed
rake aborted!
TypeError: no implicit conversion from nil to integer
/Users/paddor/.gem/ruby/2.3.0/gems/rspec-core-3.4.2/lib/rspec/core/rake_task.rb:84:in `exit'
/Users/paddor/.gem/ruby/2.3.0/gems/rspec-core-3.4.2/lib/rspec/core/rake_task.rb:84:in `run_task'
/Users/paddor/.gem/ruby/2.3.0/gems/rspec-core-3.4.2/lib/rspec/core/rake_task.rb:96:in `block (2 levels) in define'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/file_utils_ext.rb:58:in `verbose'
/Users/paddor/.gem/ruby/2.3.0/gems/rspec-core-3.4.2/lib/rspec/core/rake_task.rb:94:in `block in define'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/task.rb:240:in `block in execute'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/task.rb:235:in `each'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/task.rb:235:in `execute'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/task.rb:179:in `block in invoke_with_call_chain'
/Users/paddor/.rubies/ruby-2.3.0/lib/ruby/2.3.0/monitor.rb:214:in `mon_synchronize'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/task.rb:172:in `invoke_with_call_chain'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/task.rb:201:in `block in invoke_prerequisites'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/task.rb:199:in `each'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/task.rb:199:in `invoke_prerequisites'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/task.rb:178:in `block in invoke_with_call_chain'
/Users/paddor/.rubies/ruby-2.3.0/lib/ruby/2.3.0/monitor.rb:214:in `mon_synchronize'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/task.rb:172:in `invoke_with_call_chain'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/task.rb:165:in `invoke'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/application.rb:150:in `invoke_task'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/application.rb:106:in `block (2 levels) in top_level'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/application.rb:106:in `each'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/application.rb:106:in `block in top_level'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/application.rb:115:in `run_with_threads'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/application.rb:100:in `top_level'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/application.rb:78:in `block in run'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/application.rb:176:in `standard_exception_handling'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/lib/rake/application.rb:75:in `run'
/Users/paddor/.gem/ruby/2.3.0/gems/rake-10.5.0/bin/rake:33:in `<top (required)>'
/Users/paddor/.gem/ruby/2.3.0/bin/rake:23:in `load'
/Users/paddor/.gem/ruby/2.3.0/bin/rake:23:in `<main>'
Tasks: TOP => default => spec

Line 84 of that file is this:
        exit $?.exitstatus

Where could that TypeError come from? It says that it expects an Integer but got nil and won't implicitly convert it. With my patch,
        exit $?.exitstatus || 1

RSpec is able to report the failure as expected, instead of crashing itself (or Rake) as well.
Here the same command's output, with the patch:
  #silence
    sends correct message to actor
  #subscribe
    sends correct message to actor
  #listen
    sends correct message to actor
  #unsubscribe
Assertion failed: (self->handle), function zsock_new_checked, file src/zsock.c, line 69.
/Users/paddor/.rubies/ruby-2.3.0/bin/ruby -I/Users/paddor/.gem/ruby/2.3.0/gems/rspec-support-3.4.1/lib:/Users/paddor/.gem/ruby/2.3.0/gems/rspec-core-3.4.2/lib /Users/paddor/.gem/ruby/2.3.0/gems/rspec-core-3.4.2/exe/rspec --pattern spec/\*\*\{,/\*/\*\*\}/\*_spec.rb failed

As you can see, Rake didn't crash. The rake command nicely exits with the given default status (1 in this case).
If the test suite completes without crashing, the output of rake --verbose --trace looks like this (with the patch):

Finished in 1.04 seconds (files took 0.86113 seconds to load)
623 examples, 0 failures, 2 pending

[Coveralls] Outside the CI environment, not sending data.
** Execute default
rake --verbose --trace  1.85s user 0.38s system 86% cpu 2.587 total

which is what one would expect. And the rake command nicely exits with status 0.
This is all the information I can provide at this moment.

Where could that TypeError come from? It says that it expects an Integer but got nil and won't implicitly convert it

It comes from nil being passed to exit

Ah true. I only tested it in pry, there it doesn't raise. In a Ruby script, it actually raises when nil is passed to exit. So the code contains an edge-case bug. This PR fixed that bug.

I'd rather figure out why we're not getting an exit status...

I'm also running into this issue:
Api::ClientConfigurationsController
  #show
/usr/local/rvm/rubies/ruby-2.2.3/bin/ruby -I/usr/local/rvm/gems/ruby-2.2.3/gems/rspec-core-3.3.1/lib:/usr/local/rvm/gems/ruby-2.2.3/gems/rspec-support-3.3.0/lib /usr/local/rvm/gems/ruby-2.2.3/gems/rspec-core-3.3.1/exe/rspec --pattern spec/\*\*\{,/\*/\*\*\}/\*_spec.rb -fd --no-color --tag ~exclude_from_ci failed
rake aborted!
TypeError: no implicit conversion from nil to integer
/usr/local/rvm/gems/ruby-2.2.3/gems/rspec-core-3.3.1/lib/rspec/core/rake_task.rb:75:in `exit'
/usr/local/rvm/gems/ruby-2.2.3/gems/rspec-core-3.3.1/lib/rspec/core/rake_task.rb:75:in `run_task'
/usr/local/rvm/gems/ruby-2.2.3/gems/rspec-core-3.3.1/lib/rspec/core/rake_task.rb:87:in `block (2 levels) in define'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/file_utils_ext.rb:58:in `verbose'
/usr/local/rvm/gems/ruby-2.2.3/gems/rspec-core-3.3.1/lib/rspec/core/rake_task.rb:85:in `block in define'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/task.rb:240:in `call'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/task.rb:240:in `block in execute'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/task.rb:235:in `each'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/task.rb:235:in `execute'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/task.rb:179:in `block in invoke_with_call_chain'
/usr/local/rvm/rubies/ruby-2.2.3/lib/ruby/2.2.0/monitor.rb:211:in `mon_synchronize'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/task.rb:172:in `invoke_with_call_chain'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/task.rb:201:in `block in invoke_prerequisites'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/task.rb:199:in `each'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/task.rb:199:in `invoke_prerequisites'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/task.rb:178:in `block in invoke_with_call_chain'
/usr/local/rvm/rubies/ruby-2.2.3/lib/ruby/2.2.0/monitor.rb:211:in `mon_synchronize'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/task.rb:172:in `invoke_with_call_chain'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/task.rb:165:in `invoke'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/application.rb:150:in `invoke_task'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/application.rb:106:in `block (2 levels) in top_level'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/application.rb:106:in `each'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/application.rb:106:in `block in top_level'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/application.rb:115:in `run_with_threads'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/application.rb:100:in `top_level'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/application.rb:78:in `block in run'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/application.rb:176:in `standard_exception_handling'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/lib/rake/application.rb:75:in `run'
/usr/local/rvm/gems/ruby-2.2.3/gems/rake-10.5.0/bin/rake:33:in `<top (required)>'
/usr/local/rvm/gems/ruby-2.2.3/bin/rake:23:in `load'
/usr/local/rvm/gems/ruby-2.2.3/bin/rake:23:in `<main>'
/usr/local/rvm/gems/ruby-2.2.3/bin/ruby_executable_hooks:15:in `eval'
/usr/local/rvm/gems/ruby-2.2.3/bin/ruby_executable_hooks:15:in `<main>'
Tasks: TOP => ci => ci_spec

Any tips as to how I can identify the underlying issue (I assume there's some genuine problem with the code that's contributing to the exitstatus being nil) while awaiting a patch to rspec-core?

Can either of you provide a git repo that demonstrates the issue?

Unfortunately I cannot. This is from a private repo/project and I'd have no idea how to reproduce in a public one. Hopefully @paddor can come thru.

Just tried to reproduce it with a small C program that exposes a function that asserts. Can't reproduce it, though. It only happens, on my side, when libczmq asserts.
I'm in favor of solving problems one by one. This PR solves the problem at hand right now. If there's a problem with it, it'll show soon enough and can be fixed by a more "right" solution later. Simple red/green/refactor cycle, right?
 No need to waste any more on non-existing problems.


Optimize about gradient of Text

Cache gradient
check whether canvas's size changed
If canvas's size or style.fill changed , re-create gradient, or use the cached one.

Going to close this because we need to focus on larger performance issue with Text for v5. This is a minor performance improvement. If users are hitting this as a performance issue on low end devices, there's 2 workarounds: use BitmapText or disable the use of gradients on these devices.


Resource Loading Bug Found in Frontend (http status 502 bug)

The frontend nginx server returns a 502 for a different asset every time we refresh the page.
Context
There is a problem at the frontend component nginx server or with the frontend helm charts.
Since we joined both frontend and backend helm charts this bug was observed, however it was not happening always. Now after the version  v0.7.0 it stopped working.
Affects (v0.7.0 &  v0.8.0)
What is the problem?
The browser always gives a 502 to one file when loading the application.
The file that receives a 502 is random and can vary from .css to .js. The compiled resources are not fully loaded from the NGINX server and here is a use case where we refresh the frontend page application 5 times and receive different files with 502.
Example:
Lets reload the page 5 times and see how the resources get not load:
1º Try gets no response for index.js

2º After Reloading gives 502 for vuetify

3º reload it works but gives a 502 for the icons

4º reload it gives to index.css

Another interesting thing is that we get no error logs, it just not appear at the logs...:

And sometimes it works to retrieve all the webpage:

How to solve it?
I am investigating about it. Maybe the problem can be related with the following things:

The one helm chart configuration was not correctly made
The nginx has not enough resources to retrieve all the assets
There were some merge conflict or something was missing between the versions v0.6.0 and v0.7.0...

If you know what is possibly the problem it would help a lot to solve this issue.

Fixed in release v0.8.1: https://github.com/eclipse-tractusx/digital-product-pass/releases/tag/v0.8.1


Does not update when changing themes

I am changing my application to use a DayNight theme so it will follow the user's device preferences. However, the FloatingSearchView is the only View not changing themes and is locked to whatever theme the app started in. I've tried invaliding FloatingSearchView and setting a dark/light theme as one of its XML attributes.
Here's the XML declaration.
        <com.arlib.floatingsearchview.FloatingSearchView
            android:id="@+id/floating_search_view"
            android:theme="@style/AppTheme"
            android:layout_width="match_parent"
            android:layout_height="match_parent"
            android:visibility="gone"
            android:translationZ="5dp"
            app:layout_constraintTop_toTopOf="@id/toolbar_container"
            app:floatingSearch_dismissFocusOnItemSelection="true"
            app:floatingSearch_leftActionMode="showSearch"
            app:floatingSearch_searchBarMarginLeft="8dp"
            app:floatingSearch_searchBarMarginRight="8dp"
            app:floatingSearch_searchSuggestionTextSize="14sp"
            app:floatingSearch_showSearchKey="true"
            app:floatingSearch_suggestionsListAnimDuration="250" />

I figured out a hack to prevent the previous theme's colors from leaking into. the current theme. There will be adverse changes in regards to persistence of all the other attributes.
class FloatingSearchViewDayNight @JvmOverloads constructor(
        context: Context,
        attrs: AttributeSet? = null)
    : FloatingSearchView(context, attrs) {

    // hack to remove color attributes which should not be reused
    override fun onSaveInstanceState(): Parcelable? {
        super.onSaveInstanceState()
        return null
    }
}


[18/10/2022]Task3.2: Added event cards

Summary: https://github.com/Open-Science-Community-Saudi-Arabia/OSCSA_Website/issues/186
Tasks 3
We need to add an events subpage where we can link our events in Zenodo.
3.1 Add this to the nav bar PR.
3.2 Add three cards with each event, title, name of the speaker, and language.
Fixes

Added event cards on the homepage*
Users can see listed events when they click the Event link on the navbar
The Arabic version of the page is updated
Result

What should a reviewer concentrate their feedback on?

[ ] Everything looks ok?

@alswajiab @BatoolMM  please review

This looks fantastic 🌷
Can you make the link for (More OSCSA events) open a new page on the website with all previous events?

This looks fantastic 🌷
Can you make the link for (More OSCSA events) open a new page on the website with all previous events?

Noted @BatoolMM

It looks fantastic, can you move this section to just before the UNESCO recommendation and resolve the conflict, please?

@sandygudie can you rebase this PR, please?

@sandygudie can you rebase this PR, please?

done @BatoolMM

@BatoolMM
TypoError , "Materials"

@BatoolMM TypoError , "Materials"  and the divider should be below the title text

Thank you for catching this!

@BatoolMM TypoError , "Materials"  and the divider should be below the title text

Thank you for catching this!

i have fixed this

I made changes to the Arabic translation - The Materials in the nav bar should direct to the cards you created, can you fix that @sandygudie.

I made changes to the Arabic translation - The Materials in the nav bar should direct to the cards you created, can you fix that @sandygudie.

Alright, I will fix that right away

Thank you @sandygudie 🌷 , for the speedy fix, I noticed that the Arabic page has no padding in all directions - the card reaches the end of the screen.

In terms of the English page, needs padding on the top and bottom only.

Can you fix this issue, I'd love to merge this today but no rush!

Thank you @sandygudie 🌷 , for the speedy fix, I noticed that the Arabic page has no padding in all directions - the card reaches the end of the screen.

In terms of the English page, needs padding on the top and bottom only.

Can you fix this issue, I'd love to merge this today but no rush!

I will fix that now

Fantastic!
Isn't the card supposed to direct you to its page in Zenodo once it's clicked but that's not the case?

Fantastic @sandygudie !
Isn't the card supposed to direct you to its page in Zenodo once it's clicked but that's not the case?

Based on the Task description(Task 3) clicking on a card should open a more detailed subpage  with description ,  to view slides or download etc
https://github.com/Open-Science-Community-Saudi-Arabia/OSCSA_Website/issues/186

@sandygudie It would be nice for each card would direct you to a subpage - but this can be made in a separate PR - otherwise, this will be heavy PR. To merge this PR, it should at least direct you to the slides from Zenodo (their page in Zenodo), if that makes sense! Let me know if that's not clear!

@sandygudie if you need assistance with the subpages, i'm open to assist

Yes, that’s right @BatoolMM,
The subpage is been worked on here https://github.com/Open-Science-Community-Saudi-Arabia/OSCSA_Website/pull/191

Looks fantastic, thank you again @sandygudie!

@sandygudie, the CSS for the Arabic page is completely distorted - can you open a PR to fix it, please?

Oh No, i had  just pushed a fixed  before you merged, I will fix it quick
thanks

@BatoolMM the fix : https://github.com/Open-Science-Community-Saudi-Arabia/OSCSA_Website/pull/214


ERROR - Fatal Python error: Py_Initialize: can't initialize sys standard streams

When I try to install OOO Development Tools 0.17.13 in LO <IP_ADDRESS> (RHEL8) I get following errors:
PYTHONPATH is unset
2023-12-30 17:50:09,020 - uno_component - INFO - Pip is not installed. Attempting to install
2023-12-30 17:50:09,021 - ooodev_tools_pip.install.install_pip - INFO - Installing PIP via default installer
2023-12-30 17:52:54,994 - uno_component - INFO - Pip is not installed. Attempting to install
2023-12-30 17:52:54,994 - ooodev_tools_pip.install.install_pip - INFO - Installing PIP via default installer
2023-12-30 17:53:52,023 - uno_component - INFO - Pip is not installed. Attempting to install
2023-12-30 17:53:52,024 - ooodev_tools_pip.install.install_pip - INFO - Installing PIP via default installer
2023-12-30 17:53:52,561 - ooodev_tools_pip.install.pip_installers.default_installer - INFO - PIP installation file has been saved
2023-12-30 17:53:52,562 - ooodev_tools_pip.install.pip_installers.default_installer - INFO - Starting PIP installation…
2023-12-30 17:53:52,647 - ooodev_tools_pip.install.pip_installers.default_installer - ERROR - PIP installation has failed
2023-12-30 17:53:52,647 - ooodev_tools_pip.install.pip_installers.default_installer - ERROR - Fatal Python error: Py_Initialize: can't initialize sys standard streams
Traceback (most recent call last):
  File "/opt/libreoffice7.6/program/python-core-3.8.17/lib/abc.py", line 64, in <module>
ModuleNotFoundError: No module named '_abc'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/opt/libreoffice7.6/program/python-core-3.8.17/lib/io.py", line 52, in <module>
  File "/opt/libreoffice7.6/program/python-core-3.8.17/lib/abc.py", line 68, in <module>
  File "/opt/libreoffice7.6/program/python-core-3.8.17/lib/_py_abc.py", line 35
    def __new__(mcls, name, bases, namespace, /, **kwargs):
                                              ^
SyntaxError: invalid syntax

2023-12-30 17:53:52,648 - ooodev_tools_pip.install.pip_installers.default_installer - ERROR - PIP installation has failed
2023-12-30 17:53:52,709 - uno_component - INFO - Pip was not successfully installed
2023-12-30 17:53:52,709 - uno_component - INFO - OooDevRunner execution time: 1.549 seconds

... is there something missing in LO 7.6 Python packages !?

I am not certain what is causing this error.
It seems like the abc module may be not available which does not make a lot of sense.
Do you have APSO installed LibreOffice?
If so open the Console and try import abc and import _abc. Should not get any errors.
APSO python console [LibreOffice]
3.8.18 (default, Nov 30 2023, 14:52:54) [MSC v.1929 64 bit (AMD64)]
Type "help", "copyright", "credits" or "license" for more information.
>>> import abc
>>> import _abc
>>>

Also I just noticed:
    def __new__(mcls, name, bases, namespace, /, **kwargs):
                                              ^

This appears to indicate that the / in the _py_abc.py file is an issue.
The / in methods is a recent addition to pythhon that indicates only key word arguments from this point on.
Could there be a bug in version 3.8.17 of pyhon? This will take a little more investigation.

Hello,
many thanks for looking at this.
Yes, APSO was installed.
... anything else I can help with ?
Christian

Also I just noticed:
    def __new__(mcls, name, bases, namespace, /, **kwargs):
                                              ^

This appears to indicate that the / in the _py_abc.py file is an issue. The / in methods is a recent addition to python that indicates only key word arguments from this point on. Could there be a bug in version 3.8.17 of pyhon? This will take a little more investigation.

My mistake. / is a positional only indicator implement in Python 3.8. It should work, but seems is an issue here.

Hello, many thanks for looking at this. Yes, APSO was installed.
... anything else I can help with ? Christian

Did you try the import manually?
APSO python console [LibreOffice]
3.8.18 (default, Nov 30 2023, 14:52:54) [MSC v.1929 64 bit (AMD64)]
Type "help", "copyright", "credits" or "license" for more information.
>>> import abc
>>> import _abc
>>>

Hello,
abc imports w/o problems on the APSO Python console :
APSO python console [LibreOffice]
3.8.18 (default, Dec  1 2023, 09:10:43)
[GCC 7.3.1 20180303 (Red Hat 7.3.1-5)]
Type "help", "copyright", "credits" or "license" for more information.
>>> import abc
>>> import _abc
>>>

Note: Python version slightly changed from the original description because I upgraded LO to the latest version meanwhile.

Note: Python version slightly changed from the original description because I upgraded LO to the latest version meanwhile.

Is the issue still there since you upgraded?

Yes, it was there before and after the LO Upgrade.

Would you mind putting the extension log level to debug and trying again.
The higher level debug log may reveal more details.
Also download the latest oxt file directly from the project source directory.

If the issue presist you could always pip install ooo-dev-tools.
Also note there is an extension just for pip installing in LibeOffice as well, zaz-pip.


add ECR gate and approximation_degree option

Adds a new 2-qubit gate, the echo cross-resonance (ECR), which is two CR(π/4) pulses with an X gate between them for the echo. This gate is locally equivalent to a CNOT (can convert to a CNOT with local pre- or post-rotation). It is the native gate on current IBM hardware and compiling to it allows the pre-/post-rotations to be merged into the rest of the circuit.
Additionally a new option is added to the transpiler for approximate synthesis of unitaries. The synthesis fidelity can be given to the transpiler. This capability was already there in the synthesizer, it is just now exposed to the transpiler.

"Synthesis fidelity" is not a good description of the parameter. "Basis fidelity" is better. The actual meaning of the parameter is that it assumes each use of the 2-qubit basis gate has the given gate fidelity, and trades that off with the approximation fidelity. For example if the target gate is the small fractional SWAP exp(0.0647 i (xx+yy+zz)) with basis_fidelity=0.9966 the decomposer will prefer the 0.99 gate fidelity 0-CNOT product decomposition in preference to the perfect 3-CNOT decomposition, whereas in this case I would say the "synthesis fidelity" is 0.9900

"Synthesis fidelity" is not a good description of the parameter. "Basis fidelity" is better. The actual meaning of the parameter is that it assumes each use of the 2-qubit basis gate has the given gate fidelity, and trades that off with the approximation fidelity. For example if the target gate is the small fractional SWAP exp(0.0647 i (xx+yy+zz)) then with basis_fidelity=0.9966 the decomposer will prefer the 0.99 gate fidelity 0-CNOT product decomposition in preference to the perfect 3-CNOT decomposition, whereas in this case I would say the "synthesis fidelity" is 0.9900

Yes but I wanted to somehow avoid making this too specific to this pass. I'm trying to add a knob to the high-level "transpile" command that allows users to control approximation degree. You can imagine this knob can be useful in things like compiling to a discrete gate set, or using approximate QFT, or whatnot. I know this particular pass makes its approximation decision based on finding a sweet spot in the tradeoff between applying more gates and fidelity of synthesis. So I'd be open to suggestions for a general name. Would "approximation_degree" be good?

I know this particular pass makes its approximation decision based on finding a sweet spot in the tradeoff between applying more gates and fidelity of synthesis. So I'd be open to suggestions for a general name. Would "approximation_degree" be good?

Wouldn't finding a sweet spot between gates fidelity and synthesis fidelity be fairly generic also to things like Solovay-Kitaev or whatever? I would argue that some interpretation basis_fidelity could/should be used in many/most circumstances.

If the range of approximation_degree is supposed to be 0 (full approximation) to 1 (no approximation) then that could be scaled for TwoQubitBasisDecomposer, so  that basis_fidelity=approximation_degree*0.6+0.4 since it stops doing any additional approximation beyond basis_fidelity=0.4 (below 0.4, given a basis gate of iSWAP and target gate of iSWAP it anyway prefers a 0-uses-of-basis approximation). Or maybe you don't care about such scaling

If the range of approximation_degree is supposed to be 0 (full approximation) to 1 (no approximation) then that could be scaled for TwoQubitBasisDecomposer, so that basis_fidelity=approximation_degree*0.6+0.4 since it stops doing any additional approximation beyond basis_fidelity=0.4 (below 0.4, given a basis gate of iSWAP and target gate of iSWAP it anyway prefers a 0-uses-of-basis approximation). Or maybe you don't care about such scaling

Where is 0.4 coming from?

Where is 0.4 coming from?

F(iSWAP, Id) == (4+abs(Tr(iSWAP))^2)/16 == (4 + abs(4cos(π/4)cos(π/4)cos(0) + 4jsin(π/4)sin(π/4)sin(0))**2)/20 == 0.4

Ok I think I understand what you mean. You're saying the minimum basis fidelity that would make a difference to your approximation is basis_gate of 0.4 fidelity.
That's even though the approximation itself can go lower than 0.4 in the Weyl chamber:
average_gate_fidelity(SwapGate(), CXGate()) = 0.25

I'm happy to do whatever you prefer here. I do want to make a follow up PR where I make the basis_fidelity reference those from backend.properties() if available, so that each gate can be approximated according to its own basis fidelity. It should only fall back on this generic approximation_degree in the absence of cal information.

After optimizing over single-qubit pre/post rotation max_{pre/post} F_avg(SWAP, CX) == 0.4

perhaps the right thing is to require that approximation-aware synthesis methods expose an approximation_degree kwarg as well as whatever their domain-specific kwarg such as basis_fidelity, or rtol, or search_depth or whatever. Each synthesis method can check that it only receives at most one such kwarg and can do its own domain-specific mapping from the 0<=approximation_degree<=1 range to their native parameter?

Yes I think something like that makes sense, a pass-specific parameter and a generic parameter that can be mapped to that for each pass. I can do this for the 2-qubit synthesizer in the follow-up PR.


[SPARK-41849][CONNECT] Implement DataFrameReader.text

What changes were proposed in this pull request?
This PR implements DataFrameReader.text alias in Spark Connect.
Why are the changes needed?
For API feature parity.
Does this PR introduce any user-facing change?
This PR adds a user-facing API but Spark Connect has not been released yet.
How was this patch tested?
Unittest was added.

Merged to master.


Improve GitLab dependency scanning parser

Improve GitLab dependency scanning parser, adding component name and version for the findings.
Removed SAST components, since they are not present in this kind of report.

Current findings from GitLab dependency scanning have this structure:

Now they will appear as:

Thanks for the quick feedback @valentijnscholten .
That's an interesting point that I was thinking about. According to GitLab's Dependency Scanning documentation, those fields must be present, otherwise the finding would not make much sense.
Do you still find prudent to add the checks anyway?

also as you are adding more data to findings, could you add more checks in the unit tests?

Thanks for the quick feedback @valentijnscholten .
That's an interesting point that I was thinking about. According to GitLab's Dependency Scanning documentation, those fields must be present, otherwise the finding would not make much sense.
Do you still find prudent to add the checks anyway?

Yes. Everytime I agree not to add any checks, the parser has failed 3 weeks later and the PR author was gone and we had to deal with the slack support, github issues, bugfix PRs etc. The parsers should really be made fool proof otherwise we can't keep up.

@valentijnscholten Can you please reopen the PR?
I was about to add the checks and test data. Just didn't had enough time to update before you closed it.

I didn't mean to close it, sorry. Must have misclicked or something. Sorry!

No worries @valentijnscholten and thanks for reopening the PR.
I've added the checks and also a unit test. Please let me know if everything is as expected or not.
Additionally, could you also review the PRs https://github.com/DefectDojo/Documentation/pull/173 and https://github.com/DefectDojo/sample-scan-files/pull/69 to update the documentation regarding the new integration and to add the sample scan files, respectively, please?

thanks for the PR, just one more approval needed....


how to use insulation score to identify TAD domains

Hi,
Recently, I am interested to your developed method "insulation score". And I tried to use matrix2insulation.pl to identify TAD domains. I am curious about the result of this perl script. Because, the final result from matrix2insulation.pl is a summary about the boundary location. So, if I want to call TAD domains, is that simply divide the genome into several parts according to this boundaries? For example, if the boundary is chr1:4000000-4500000. Then the TAD domains are two parts？(chr1:0-4000000,chr1:4500000-...)
Could you give me some advise?
Thank you so much!
Best,
Garen

Hi,
I am having the same question, so do you solve this question? thank you.
Best

Hi,
My problem has been solved. The reason is happened the label of my input matrix. I changed my middle lane of label as my reference genome.

Sorry for the delay - for the original question, yes it is as simple as that.  Simply divide the genome into segments defined by the boundary locations.
One caveat - you may  wish to also consider the strength of the boundaries.  e.g.
boundaries:
chr1:2500000:  strong
chr1:5000000: weak
chr1:5500000: strong
The above reflects 2 distinct tads, however, one may also wish to capture the fact that the major tad (chr1:2500000-5500000) also contains within it a smaller 'sub/nested' tad as evidenced by the much weaker boundary strength.
Hope that is clear.


Update _torchscript_model_adapter.py

converting the input to the model to float to avoid numpy array errors from torch
@oeway

I agree it should not be directly converted to float32, however, it should not leave it as is either since pytorch does not support all numpy types, it seems all the unsigned types cause error, so we can either do float32 right now, or explicitly write a mapping for unsupported types.

But data.type is a required field. So there is always a known, fixed data type at this point in the code.
(field data_type for v0_4 models).
Could you please point me to the example where you encountered the issue?


Fix async worker return type

Fixes #7248.
#7088 enabled support for asynchronous implementations of individual worker operations, to prevent long-running operations from blocking subsequent requests. But, the types did not accurately capture these semantics, so you couldn't return { result: T, transfer: Transferable[] } from async implementations without the compiler complaining. It would expect you to return { result: Promise<T>, transfer: Transferable[] } instead.
Adjusted the types to fix this.

@aruniverse I would like to get it backported to 4.9.x

@mergifyio backport release/4.9.x


[Feature Suggestion]Add param "Delay"

In some cases, the title of the page is dynamic added by javascript, in this case utterances will get the wrong title(i.e. the old title in html file). To add a param "Delay" would let utterances's client.js run after the javacript which changes the title.

you can insert the utterances script dynamically once you've determined the page title
https://github.com/utterance/utterances/issues/299#issuecomment-626125665


Add authorisation to support and assessor interface

This uses the Pundit library to add authorisation to staff users. Specifically, we require that a staff user has the support_console_permission to access the support console, and that a staff user has the award_decline_permission to perform any actions in the assessor interface.
Trello Card

Looks good and all seems to be working. I wonder if we should follow up with hiding some of the things, links etc that people can't do. Not sure that's a priority though at the minute. I didn't test with a no-permission staff user but it looks like it should be good on that front.

Yeah, agree that we should follow up with hiding links, etc.


[Help] Relationship

Report
I have a parent - child relationship where I am able to successfully pull data and display it on the LIST as well SHOW operations.  However I would like to display two fields from the dependent table where I have defined relationship.  Please refer the code below:
 CRUD::column('material')->label('Material')->type('relationship')->attribute('shortname'); CRUD::column('material')->label('Category')->type('relationship')->attribute('category');
The above code overwrites the 'shortname' attribute and displays only 'category' - as FORM can not have duplicate field names.
I have read somewhere using 'field id' kind of a mechanism to overcome this problem wherein we can display multiple fields from the dependent table without modifying the model.
Workaround
I have defined method in my Model class getCategoryAttribute() which returns the category.  However I am looking for a cleaner solution, if available.
Disadvantage in the workaround
Because it is a method defined in model, the default search option doesn't work and the developer has to write 'search' logic part of the filed definition.
Thanks in advance for your help here.

@srigurubyo I'm not sure I understand your use case, but yes, your second CRUD::column() call will refer to the same column and edit it, if it has the same name.
Can you try material.shortname and material.category as the names of your columns? You can then lose the type and attribute, Backpack will deduct them from the dot notation.
CRUD::column('material.shortname')->label('Material');
CRUD::column('material.category')->label('Category');

I'm going to close this as it's not a bug. Feel free to answer here if the above doesn't solve your problem though.
Cheers!

This is super cool @tabacitu.  I was not aware of such feature and thanks a lot for providing that piece of information.

I am wondering can the below statement be simplified using fluent syntax?

        CRUD::column('material.category')->label('Category')
        ->wrapper(['element' => 'span',
                   'class'   => function ($crud, $column, $entry, $related_key) {
                                    return CommonHelper::getMEStatusColor($column);
                                }
                  ]);

I figured this out. Thanks!

@srigurubyo I'm not sure I understand your use case, but yes, your second CRUD::column() call will refer to the same column and edit it, if it has the same name.
Can you try material.shortname and material.category as the names of your columns? You can then lose the type and attribute, Backpack will deduct them from the dot notation.
CRUD::column('material.shortname')->label('Material');
CRUD::column('material.category')->label('Category');

I'm going to close this as it's not a bug. Feel free to answer here if the above doesn't solve your problem though.
Cheers!

Is there any such shortcuts available for 'field' as well or is this applicable only to 'column'?

Same thing. CRUD::field() will create a new field, or modify an existing field. Otherwise if you want only one you can use CRUD::addField() or CRUD::modifyField(). More info about this in the docs:

https://backpackforlaravel.com/docs/4.1/crud-cheat-sheet
https://backpackforlaravel.com/docs/4.1/crud-api
https://backpackforlaravel.com/docs/4.1/crud-fluent-syntax


Fix RN 0.25 deprecation

This should remove the warning in 0.25

LOL didn't notice there were already 4 PRs to fix this ;)


unittest

added folders for my module: unittest ,helpers, html report, allure report.

@TatsianaLentz you could merge your PR to the Main branch if you want to 👍


The generated ONNX model needs run with the custom op supports.

Hello, I am trying to convert my Keras model to ONNX format, but I am getting lots of warnings and an error:
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/TensorArrayStack/TensorArrayGatherV3 of type TensorArrayGatherV3
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/TensorArray_1 of type TensorArrayV3
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/Exit_2 of type Exit
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/TensorArrayStack/TensorArraySizeV3 of type TensorArraySizeV3
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/Switch_2 of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/Merge_2 of type Merge
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/LoopCond of type LoopCond
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/Enter_2 of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/NextIteration_2 of type NextIteration
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/cond/Merge of type Merge
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/cond/Merge_1 of type Merge
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/cond/Merge_2 of type Merge
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/cond/Merge_3 of type Merge
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/TensorArrayWrite/TensorArrayWriteV3 of type TensorArrayWriteV3
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/TensorArrayWrite/TensorArrayWriteV3/Enter of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/cond/Merge of type Merge
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/Merge of type Merge
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/Less/Enter of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/Merge_1 of type Merge
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/cond/ExpandDims_4/Switch of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/cond/ExpandDims_5/Switch of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/cond/ExpandDims_6/Switch of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/cond/ExpandDims_7/Switch of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/Switch_1 of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/Enter of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/NextIteration of type NextIteration
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/Enter_1 of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/NextIteration_1 of type NextIteration
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/cond/mul/Switch of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/cond/mul/Switch_1 of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/cond/mul_1/Switch of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/cond/mul_1/Switch_1 of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/cond/mul_2/Switch of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/cond/mul_3/Switch of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/cond/strided_slice/Switch of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/cond/Shape/Switch of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/cond/sub/Switch of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/cond/TopKV2/Switch of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/GreaterEqual/Enter of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/TensorArrayStack/TensorArrayGatherV3 of type TensorArrayGatherV3
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/Switch of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/TensorArray_1 of type TensorArrayV3
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/Exit_2 of type Exit
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/TensorArrayStack/TensorArraySizeV3 of type TensorArraySizeV3
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/Switch_2 of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/Merge_2 of type Merge
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/LoopCond of type LoopCond
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/Enter_2 of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/NextIteration_2 of type NextIteration
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/TensorArrayWrite/TensorArrayWriteV3 of type TensorArrayWriteV3
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/TensorArrayWrite/TensorArrayWriteV3/Enter of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/Merge of type Merge
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/Less/Enter of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/Merge_1 of type Merge
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/Switch_1 of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/cond/Merge of type Merge
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/Enter of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/NextIteration of type NextIteration
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/Enter_1 of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/NextIteration_1 of type NextIteration
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/cond/strided_slice/Switch of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/cond/non_maximum_suppresion/NonMaxSuppressionV3/Switch of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/cond/non_maximum_suppresion/NonMaxSuppressionV3/Enter_1 of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/Switch of type Switch
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/cond/non_maximum_suppresion/NonMaxSuppressionV3/Enter of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/strided_slice/Enter of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/TensorArrayReadV3 of type TensorArrayReadV3
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/TensorArrayReadV3 of type TensorArrayReadV3
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/Greater/Enter_1 of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/TensorArrayReadV3/Enter of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/TensorArrayReadV3/Enter_1 of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/TensorArrayReadV3/Enter of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/TensorArrayReadV3/Enter_1 of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/while/Greater/Enter of type Enter
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/TensorArray of type TensorArrayV3
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/while/loop_over_classes/TensorArrayUnstack/TensorArrayScatter/TensorArrayScatterV3 of type TensorArrayScatterV3
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/TensorArray of type TensorArrayV3
      The generated ONNX model needs run with the custom op supports.
WARN: No corresponding ONNX op matches the tf.op node decoded_predictions/loop_over_batch/TensorArrayUnstack/TensorArrayScatter/TensorArrayScatterV3 of type TensorArrayScatterV3
      The generated ONNX model needs run with the custom op supports.
Traceback (most recent call last):
  File "onnx_test.py", line 11, in <module>
    onnx_model = onnxmltools.convert_keras(keras_model)
  File "/home/pislb/packages/onnxmltools/onnxmltools/convert/main.py", line 33, in convert_keras
    return convert(model, name, doc_string, target_opset, channel_first_inputs)
  File "/home/pislb/.local/lib/python3.6/site-packages/keras2onnx/main.py", line 80, in convert_keras
    parse_graph(topology, tf_graph, target_opset, output_names, output_dict)
  File "/home/pislb/.local/lib/python3.6/site-packages/keras2onnx/parser.py", line 842, in parse_graph
    graph, keras_node_dict, topo, top_level, output_names)
  File "/home/pislb/.local/lib/python3.6/site-packages/keras2onnx/parser.py", line 606, in _parse_graph_core
    _on_parsing_tf_nodes(graph, nodes, varset, topology.debug_mode)
  File "/home/pislb/.local/lib/python3.6/site-packages/keras2onnx/parser.py", line 323, in _on_parsing_tf_nodes
    var_type = infer_variable_type(i_, varset.target_opset)
  File "/home/pislb/.local/lib/python3.6/site-packages/keras2onnx/_parser_tf.py", line 48, in infer_variable_type
    "Unable to find out a correct type for tensor type = {} of {}".format(tensor_type, tensor.name))
ValueError: Unable to find out a correct type for tensor type = 0 of decoded_predictions/loop_over_batch/while/TensorArrayWrite/TensorArrayWriteV3/Enter:0

Does this mean I have to reimplement all the ops mentioned in the warnings in ONNX? And how do I fix the error? Thanks for help
(I also posted this to onnxmltools (https://github.com/onnx/onnxmltools/issues/411).

If there are too many tf.ops in the error message, probably there are some layers were not able to be converted.
can you share more details about this model?

Hello, the model is SSD network from https://github.com/pierluigiferrari, the problematic layer is this one: https://github.com/pierluigiferrari/ssd_keras/blob/master/keras_layers/keras_layer_DecodeDetections.py#L27

Hello, here is a simple example which demonstrates the problem:
import keras

import sys
sys.path.insert(0, "./ssd_keras")  #path to https://github.com/pierluigiferrari/ssd_keras

from keras_layers.keras_layer_DecodeDetections import DecodeDetections

import onnxmltools

output_onnx_model = 'model.onnx'

keras_model = keras.Sequential()
keras_model.add(DecodeDetections(img_height=512, img_width=512))
keras_model.build(input_shape=(None, 24564, 98))

onnx_model = onnxmltools.convert_keras(keras_model, target_opset=12)

onnxmltools.utils.save_model(onnx_model, output_onnx_model)

To run it you will have to clone https://github.com/pierluigiferrari/ssd_keras


bug: sstable files in L0 could not be compacted to base level

Describe the bug
The data in Level 0 becomes more and more but it could not compact to next level. It would cause read performance decrease and the throughput of our system would also decrease.
To Reproduce
No response
Expected behavior
No response
Additional context
No response

I did some tests locally and on ec2 (nexmark_q7 test), and found that the system's compaction trigger is not as expected.I found the following problems:
Describe

all data is piled up in l0

3000+ l0 files with 70+ sub-level

system no longer triggers base_level_compaction, It can be observed from metrics that all base-level-compactions from 0 to 6 are rejected (skip-by-overlapping)

Explore

The compaction of a sub-level layer is blocked, resulting in an increase in the number of layers, and the number of files in each layer is small, which does not meet the compact requirements. The overall write-amp is large and can only wait for the merger, so TierCompaction is blocked

BaseLevelCompaction is blocked by first overlapping sub-level.
Due to the implementation of TierPicker, compact-task needs to meet the limitations of file_count and write_amp, which may lead to skipping the middle layer under the existing implementation.
In turn, the restrictive condition of BaseLevelPicker is triggered, so that BaseLevelCompaction can no longer be generated, as shown in the figure


Settings "search.include"

There is a setting "search.exclude", but not "search.include".
I want to exclude ALL (**) BUT not /src. Only search in /src.
I expected that I can set the include which is evaluated after exclude to set:
{
  "search.exclude": {
    "**": true
  },
  "search.include": {
    "/src": true
  }
}

(include > exclude)
Is there already way to only search in the src-folder? Without setting it every time in the vs code editor earch input? Is there already a setting / config file to enable this?
I do not want to exclude every folder in my project. It's easier to just include the few folders.
Current VS Code Version: 1.25.1

https://github.com/Microsoft/vscode/issues/869


EJS views

Hi,
I'm adapting Jingo to my app, where views are written in EJS.
These views produces similar outputs compared to those written in jade.

Hi!
to be honest, if I will start jecho now I'd probably use EJS. Jade has some nice feature, but the ability to use HTML templates with just some additional markup (the ejs one) is – imho – a major reason to use it.
The "problem" is that there are users who have changed jingo templates for their own purpose and I don't think that changing the template system would be fair. The problem is maintenance: using both syntaxes together, means that I'd have to change two separate sets of files which is not a good idea.
Thank you very much for the PR, anyway: maybe I'll merge it for Jingo 3 :)

I am using something similar locally, except with Handlebars instead. It might be a good idea to think about how Jingo could support user-provided "themes" with whatever layout engine Express can handle, perhaps even installable via NPM. That way people could still customize, but you wouldn't have to support two (or more!) separate layouts.

@ryanvarick I'm adaptating Jingo to mount it as a subapp, and the ability to set an arbitrary layout I need (among others) looks like "user-provided themes".
More in next PR soon :-)


[Bug]: Error during startup

Add-on version
1.3.2
HomeAssistant version
2023.2.5
Operating System type
Docker
Operating system version
HAOS
Describe the bug
Error during startup (see log)
To reproduce
Start the add-on
Screenshots & Logfiles
Log file
s6-rc: info: service s6rc-oneshot-runner: starting s6-rc: info: service s6rc-oneshot-runner successfully started s6-rc: info: service fix-attrs: starting s6-rc: info: service fix-attrs successfully started s6-rc: info: service legacy-cont-init: starting s6-rc: info: service legacy-cont-init successfully started s6-rc: info: service legacy-services: starting s6-rc: info: service legacy-services successfully started /run.sh: line 118:   187 Segmentation fault      /usr/bin/node /usr/src/app/node_modules/eufy-security-ws/dist/bin/server.js --host <IP_ADDRESS> --config $CONFIG_PATH $DEBUG_OPTION $PORT_OPTION s6-rc: info: service legacy-services: stopping s6-rc: info: service legacy-services successfully stopped s6-rc: info: service legacy-cont-init: stopping s6-rc: info: service legacy-cont-init successfully stopped s6-rc: info: service fix-attrs: stopping s6-rc: info: service fix-attrs successfully stopped s6-rc: info: service s6rc-oneshot-runner: stopping s6-rc: info: service s6rc-oneshot-runner successfully stopped
Config file:
username: HA@********
password: *******
country: NL
port: 3200
polling_interval: 10
accept_invitations: false
debug: true
event_duration: 10
stations:
serial_number: T8010P*********
ip_address: 192.168..

I have exactly the same issue. Do you need anything for debugging?

https://en.m.wikipedia.org/wiki/Segmentation_fault

@RienduPre @JoostV
Which image do you use? armhf? aarch64? armv7? amd64? i386?

I have a odroid N2 this is an ARM  CPU

I have a odroid N2 this is an ARM CPU

Ok, I think the problem is in the AppArmor profile. Couldn't test it for this architecture yet.

Ok I can help test for you. Let me know what I can do?

Het a odriod n2+, so also arm

@RienduPre @JoostV
Action plan:

Download this repository
Unpack the zip file
Replace the file apparmor.txt in the directory eufy-security-ws with the following:
apparmor.txt
Copy the directory eufy-security-ws to your addons directory on your HomeAssistant installation
On the HomeAssistent cli launch the following command:
ha core restart
On HomeAssistant go to Settings → Add-ons → Add-on store. You should now see the following:

Install this add-on, configure it according to documentation and launch the add-on. Now you should not get any Segmentation fault anymore.
Test everything briefly.
Now you need to go to the HomeAssistant operating system and run the following:
journalctl _TRANSPORT="audit" -g 'apparmor="ALLOWED"'
Please send me the result of the command.

Thanks!

Hi,
Add-on is working without errors now :-)
But where do you want me to run step 9.  I only can go the the CLI, and there the command is not working

@RienduPre
Yes, because AppArmor now no longer intervenes and only audits. So you are without protection.
You must follow the documentation below to access the OS and issue the above command:
https://developers.home-assistant.io/docs/operating-system/debugging/

Hi @bropat
This is way over my head. And I'm afraid I will ruin my setup.
What exact risk do I have if I don't do this?

s6-rc: info: service s6rc-oneshot-runner: starting
s6-rc: info: service s6rc-oneshot-runner successfully started
s6-rc: info: service fix-attrs: starting
s6-rc: info: service fix-attrs successfully started
s6-rc: info: service legacy-cont-init: starting
s6-rc: info: service legacy-cont-init successfully started
s6-rc: info: service legacy-services: starting
s6-rc: info: service legacy-services successfully started
2023-02-24 21:10:33.894  DEBUG [undefined.constructor] Loaded API_BASE: https://security-app-eu.eufylife.com
2023-02-24 21:10:33.970  DEBUG [EufySecurity._initializeInternals] Load previous login_hash: 1c38ff04abb0f9235d14e2b3aadcfdd8
2023-02-24 21:10:33.973  DEBUG [EufySecurity._initializeInternals] Generated new openudid: 180ad1fe592d1eba
2023-02-24 21:10:33.976  DEBUG [EufySecurity._initializeInternals] Generated new serial_number: bf734e965e85
2023-02-24 21:10:34.033  DEBUG [EufySecurityServer.start] Starting server on host <IP_ADDRESS>, port 3000
node:events:491
throw er; // Unhandled 'error' event
^
Error: listen EADDRINUSE: address already in use <IP_ADDRESS>:3000
at Server.setupListenHandle [as _listen2] (node:net:1740:16)
at listenInCluster (node:net:1788:12)
at doListen (node:net:1937:7)
at process.processTicksAndRejections (node:internal/process/task_queues:83:21)
Emitted 'error' event on WebSocketServer instance at:
at Server.emit (node:events:525:35)
at emitErrorNT (node:net:1767:8)
at process.processTicksAndRejections (node:internal/process/task_queues:82:21) {
code: 'EADDRINUSE',
errno: -98,
syscall: 'listen',
address: '<IP_ADDRESS>',
port: 3000
}
Node.js v18.14.2
s6-rc: info: service legacy-services: stopping
s6-rc: info: service legacy-services successfully stopped
s6-rc: info: service legacy-cont-init: stopping
s6-rc: info: service legacy-cont-init successfully stopped
s6-rc: info: service fix-attrs: stopping
s6-rc: info: service fix-attrs successfully stopped
s6-rc: info: service s6rc-oneshot-runner: stopping
s6-rc: info: service s6rc-oneshot-runner successfully stopped

Didn't stop the other add-on...
Now it is starting

Also do not know how to run the command from step 9

Basically, this is just about temporarily enabling the SSH service, then logging in via SSH and running the journalctl command to get the audit logs I need to properly configure AppArmor for the aarch64 architecture. After that you can disable the SSH service as described in the documentation above. Here you basically can't break anything.

I have updated the action plan above.

journalctl _TRANSPORT="audit" -g 'apparmor="ALLOWED"'
-- Boot 674386a07dca48b1b9f18ace3ca719e4 --
-- Boot a738f8e1d4974b8ea3fe7ba13ac54c83 --
-- Boot 674386a07dca48b1b9f18ace3ca719e4 --
-- Boot a738f8e1d4974b8ea3fe7ba13ac54c83 --
-- Boot 674386a07dca48b1b9f18ace3ca719e4 --
-- Boot a738f8e1d4974b8ea3fe7ba13ac54c83 --
-- Boot 404bae153fc245a08370d6dcddb16409 --
-- Boot 6aacaa728cc447ef9766b53fae090f82 --
Feb 24 21:09:19 homeassistant audit[19632]: AVC apparmor="ALLOWED" operation="file_mmap" profile="local_eufy_security_ws//node" name="/usr/bin/node" pid=19632 comm="node" requested_mask="m" denied_mask="m" fsuid=0 ouid=0
Feb 24 21:10:31 homeassistant audit[19922]: AVC apparmor="ALLOWED" operation="file_mmap" profile="local_eufy_security_ws//node" name="/usr/bin/node" pid=19922 comm="node" requested_mask="m" denied_mask="m" fsuid=0 ouid=0
Feb 24 21:15:12 homeassistant audit[20670]: AVC apparmor="ALLOWED" operation="file_mmap" profile="local_eufy_security_ws//node" name="/usr/bin/node" pid=20670 comm="node" requested_mask="m" denied_mask="m" fsuid=0 ouid=0

Hope this gives the needed information

@JoostV
Yes, it does. Thank you very much!

Hi @bropat
So you dont my information?
and can you tell me how to get back to the formal addon implementation when the fixed version is available

Hi @RienduPre ,
no I don't need them anymore. Thanks anyway.

can you tell me how to get back to the formal addon implementation when the fixed version is available

Of course:

Uninstall the local add-on.
Delete the directory eufy-security-ws from the addon directory of HomeAssistant
On the HomeAssistent cli launch the following command:
ha core restart
Go back to the official add-on as soon as the new version is released (I will share here).

Fixed in version 1.3.4. Already published.

Thx for the fast support


Use "pgx" when opening a database

Codecov Report

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The diff coverage is n/a.

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========================================
  Coverage    52.98%   52.98%
========================================
  Files           24       24
  Lines         3605     3605
========================================
  Hits          1910     1910
  Misses        1406     1406
  Partials       289      289

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Unix socket support

Hey treeform, I just pushed OPT_UNIX_SOCK_PATH into libcurl.nim
https://github.com/Araq/libcurl/commit/7a420498f60a31d99fc8513886ce36c4e8c3a4ae
Is it possible to get unix socket support in libcurl.nim?
I'm using something like this which works.

type CurlWriteFnHandle* = proc (
                buffer: cstring,
                size: int,
                count: int,
                outstream: pointer): int {. gcsafe, locks: 0.}

proc defaultCurlWriteFn(
        buffer: cstring,
        size: int,
        count: int,
        outstream: pointer
    ): int =
    let outbuf = cast[ref string](outstream)
    outbuf[] &= buffer
    result = size * count

# can swap this to puppy if puppy supported sockets
proc request*(
            req: Request,
            path: string,
            httpMethod: HttpMethod,
            body: string,
            multipartData: MultipartData,
            useCurl: bool = false,
            headers: HttpHeaders = newHttpHeaders({"Accept": "application/json",
                "Content-Type": "application/json"}),
            curlWriteFn: CurlWriteFnHandle = defaultCurlWriteFn
        ): string =

        let useUnix = docker.baseUrl.startsWith("unix://")
        if useCurl or useUnix:
            let webData: ref string = new string
            let socketPath = ctx.baseUrl[7..ctx.baseUrl.high]
            let curl = easy_init()

            if useUnix:
                discard curl.easy_setopt(OPT_UNIX_SOCKET_PATH,
                        socketPath.cstring)
                discard curl.easy_setopt(OPT_URL, path.cstring)
            else:
                discard curl.easy_setopt(OPT_URL, (docker.baseUrl & "/" & path).cstring)

            discard curl.easy_setopt(OPT_CUSTOMREQUEST, ($httpMethod).cstring)
            discard curl.easy_setopt(OPT_POSTFIELDSIZE, body.len)
            discard curl.easy_setopt(OPT_POSTFIELDS, body)

            var headerChunk: Pslist
            headerChunk = headerChunk.slist_append("Accept: application/json")
            headerChunk = headerChunk.slist_append("Content-Type: application/json")
            discard curl.easy_setopt(OPT_HTTPHEADER, headerChunk);

            discard curl.easy_setopt(OPT_WRITEDATA, webData)
            discard curl.easy_setopt(OPT_WRITEFUNCTION, curlWriteFn)
            discard curl.easy_setopt(OPT_VERBOSE, 1)
            let ret = curl.easy_perform()

            if ret != E_OK:
                raise newException(Defect, $ret & $easy_strerror(ret))

            result = webData[]
            curl.easy_reset()

I have never used Unix sockets, therefore, I do not think it is a frequently used feature. Do Windows or macOS have Unix socket equivalents? I do not want to increase the size of the library when I do not see a clear benefit. I do not think I will be adding Unix sockets at this time. Sorry.

I have never used Unix sockets, therefore, I do not think it is a frequently used feature. Do Windows or macOS have Unix socket equivalents? I do not want to increase the size of the library when I do not see a clear benefit. I do not think I will be adding Unix sockets at this time. Sorry.

Macos does (example; docker macos uses simlink), windows supports it now. It's used quite heavily in unix programs, ( I think most daemons use it, sql, docker...)
Araq merged my change in libcurl.nim to support it but makes sense not to do it if I'm the only one asking.
ended up patching std/net.nim std/asyncnet.nim to make it work and a custom httpclient.nim
Thanks for considering it though :)

MacOS and Linux have supported Unix sockets forever, and as of Windows 10, Windows actually supports Unix sockets too.
It's a very common protocol for interprocess communication.

UNIX sockets are a thing of the past. No need to hold onto it. The only reason they are not uncommon is because of how certain low-level Linux things sadly work.
If Linux would be modern, there would be no UNIX sockets.

Look, I'm not here to argue philosophical discussions. I don't even have a problem if the maintainer doesn't want to include Unix socket support in this library. I commented to point out that a) there is cross-platform support and b) it's not an infrequently used functionality. And I wouldn't bother commenting if I wasn't planning on using them - either way I'll likely end up implementing support for myself.

UNIX sockets are a thing of the past. No need to hold onto it. The only reason they are not uncommon is because of how certain low-level Linux things sadly work.
If Linux would be modern, there would be no UNIX sockets.

I don't think this this is exactly true, I believe the following still use unix sockets

Docker
PhpFpm
Mysql
X11
Nginx
PulseAudio (?)
Systemd (?)

This was a while ago but if IRC I ended up finding that there isn't really anything that needed to be changed so that puppy supported sockets. The issue with the sockets ended up being a problem in the std/net library. It was just not dialling correctly.
https://github.com/nim-lang/Nim/issues/20062


Update alert-policies.md

Adding new policies

@dfantham PR merged. Updated topic should be live tomorrow (Aug. 5).


View Article action should be in a fixed position on the page cards (Lower right corner)

We weren't resolving articles that are redirected when this was reported. This should be resolved because most articles will have a full extract (description). Absolute positioning is not recommended.


Manifest field to select default build targets for project.

It would be nice to have a field in manifest for selecting default build targets.
Use case 1
I have a project with support for 3 targets. Just now I have to manually ask cargo to build one:
cargo build --target=<triplet>
For testing purpose and production it is reasonable to build for all platforms (as example). And now it would be 3 calls to Cargo. But when I debug one of them I do not need neither all of then, nor cargo current default.
Use case 2
For project with only one (cross-compiling) target (such as arm-linux-androideabi), we also have to specify target by hand every time we use cargo. But it's project specific, so it should be in Cargo.toml, I think.

Thanks for the issue! Dealing with targets, however, is quite a platform specific issue and doesn't quite seem like something that belongs in a manifest. For example all compilers we distribute today can only currently target one platform, and whether or not a project will compile for a various platform or not probably shouldn't be limited by the manifest.
For first case you have you can probably just provide a script in the repo which builds all the necessary targets, and for the second case it seems like a README mention with a TODO of porting to more platforms.

It isn't critical, I agree. But I don't understand enough: if Cargo is a package manager, then why (ideally) should I need additional script for build process? Also similar entities for other languages has that feature. Proofs: Ruby's RubyGems, Ruby's Bundler (see "PLATFORMS (:platforms)" section), Python's PIP, Haskell's Cabal (See "Conditions" in "Configuration" section).

Cargo allows you to have platform-specific configuration, but Cargo is not trying to be a complete build system. It sounded like this was a bug that wasn't asking for configuration though, but rather changing the behavior of cargo build?

Both of them: add configuration options and make cargo build use them (so the default behavior would change).

Cargo is not trying to be a complete build system

Why? Is there are plans for another tool for that sort of functionality, or GNU make is enough, and there are no need for special Rust build system?

Cargo does not want to be a complete build system because that's just not what it's chartered to do. Cargo builds Rust code well, but you need to rely on other external tools to do more advanced features.


Speed up Kodi serving

This is a note for myself.
My latest commits that generate new art links on request need to access TVDb images repository, AniDB anime repository, and use get all series. These are slow. They literally double the processing time and then some. I need to move all of it into a list of image IDs in the contract cache, then serve a random one on request.

@maxpiva if there is anything I need to know about adding something to the cache, please let me know

Fixed

From ~20s to less than 2s. Good enough!


New Line Hover Button

Details
Technology used:
HTML
CSS
ScreenShort

Screenshots
Demo Vedio
https://github.com/Spyware007/Animating-Buttons/assets/98798977/71daaeca-f811-4b04-9145-01c9b5ac1dd1
Type of Contribution

[ ] Update to an existing Animated Button
[X] Adding a new Button
[ ] Resolving a bug
[ ] Proposal to the Repository
[ ] Changes related to documentation or README.md
[ ] Other Changes

Checklist

[X] I have checked the existing issues
[X] I have read the Contributing Guidelines
[X] I am willing to work on this issue
[X] I am a GSSoC'23 contributor

Sorry for the inconvinience, but we are closing all the issues! Please open a new issue if you want to contribute anything. Also now you can create a new button from the website itself! You will get points for those too! I will add the instructions on how to create a new button soon and create an empty pr for the same to get points!


Please reopen #109968

          ### Thanks for your contribution to our documentation

We sincerely apologize for the delayed response. Unfortunately, we have been unable to review this issue in a timely manner. However, we are making overall enhancements to our content. We are closing this issue for now as there has been no activity for a while. If you feel that the problem persists, please respond to this issue with additional information.
?
Please continue to provide feedback about the documentation. We appreciate your contributions to our community.
#please-close
Originally posted by @akashdubey-ms in https://github.com/MicrosoftDocs/azure-docs/issues/109968#issuecomment-1938812228

@aut0pil0t
Thanks for your feedback! We will investigate and update as appropriate.

@aut0pil0t
Thank you for bringing this to our attention.
I've delegated this to content author @mimckitt, who will review it and offer their insightful opinions.

Looks like the other issue was reopened so I will close this one.
#please-close


Naming restrictions?

The portal appears to indicate that a directory name should be 256 characters or less.
Are there any restrictions on the characters that can be included? And is it case-sensitive?

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

ID: 14ab965b-dc45-f450-1302-5ffe491ca129
Version Independent ID: 0d96d50d-a349-3408-3b93-d8b084e1cbd1
Content: Create an Azure Active Directory tenant
Content Source: articles/active-directory/develop/quickstart-create-new-tenant.md
Service: active-directory
GitHub Login: @CelesteDG
Microsoft Alias: celested

Updated info was published 10 days ago.
#please-close

Awesome, thanks!

@dcbrown16 - Forgot to hit comment earlier. Thank you very much for your feedback and for helping us improve our docs.


Is backbone-tastypie unnecessary when Resource.always_return_data is set?

See http://django-tastypie.readthedocs.org/en/latest/resources.html#always-return-data

Probably but built-in handling of custom URLs and parsing is convenient.


HTMLBars compatibility?

We've been using this project with success on Ember versions prior to 1.10, but the upgrade to Ember 1.10 is causing us problems.
Until now we've had success compiling templates that are passed into the typeahead component and passing that along to the typeahead library like this:
templates: {
    suggestion: Handlebars.compile(this.get('suggestionTemplate')),
    <other code>
  }

This does not work in Ember 1.10, however, as typeahead.js throws the below error when executing this line of code:
Code:
$el = $(html.suggestion).append(that.templates.suggestion(suggestion)).data(datasetKey, that.name).data(valueKey, that.displayFn(suggestion)).data(datumKey, suggestion);

Error:
Uncaught TypeError:  that.templates.suggestion is not a function

The reason for this seems to be that with HTMLBars that.templates.suggestion is no longer a function but rather is an HTMLBars object.
I know this library is not under active development lately, but I was curious if anyone else had solved a similar issue?

Ended up just keeping a plain handlebars dependency in the project, but it would be nice to be able to remove it


Fix slug read-only bug

The slug property is not being reassigned since it's read-only. Change to let.
Relates to #46

I already fixed this this morning https://github.com/eluv-io/elv-asset-manager/commit/c6c1be7e08d8269b928c66fdbb2e0a79b56c4082


Adapt paths and line breaks for Windows

Fix typos
Checklist

[X] I have filed an issue about this change and discussed potential changes with the maintainers.
[X] I have received the approval from the maintainers to make this change.
[X] This is not a stylistic, refactoring, or cleanup change.

Please note that the maintainers will not be reviewing this change until all checkboxes are ticked. See
the Contributions section in the README for more
details.
Discussion thread for this change
Issue number: 5470
Description of this change
Fix directory separators and line-breaks on Windows, and fix some typos.
Closes #5470

Hi @ahmedyarub, Could you please sign the CLA?

I would run both replacements conditionally, only for non-WSL WIndows. In unix systems you can have backslash in a filename (try mkdir a\\b).
Same story for \r, just because it's not required outside Windows

Good catch

This one is still tagged with Awaiting user response. Do I need to do anything?

Do I need to add anything here?

Thanks for adding the changes! Please note that CI doesn't run on Windows, so it might break in the future.

Just tag me anytime a bug is reported and I'll make sure to fix it ASAP. I appreciate this great project really!


Can't start Lama Cleaner getting an ImportError

Hello, I just bought Lama Cleaner, installed it without errors (I assume), I get to the Browser page where I can save the settings, I didn't change anything, I just chose save configurations, the file is created, I start win_start.bat and I get this error.
`ImportError: cannot import name 'cached_download' from 'huggingface_hub' (C:\Users[USER NAME]\AppData\Local\Programs\Python\Python310\lib\site-packages\huggingface_hub_init_.py)``
What to do?

Did you download the lama-cleaner.zip file? Please download the IOPaint.zip file, this error should have been fixed.

Well the other folder, IOPaint-v1 that I installed and it worked, been using it for a while, works very well. Thanks for making it by the way.


Apple Notes: Drawings not imported

Drawings in imported Apple Notes show the following error
**(error reading attachment)**
We should try to import/convert the drawing, or display a more useful error

@mirnovov what is the storage format for drawings?

Drawings are stored as a format containing their lines etc, similar to SVG. However, a fallback image is generated, which this importer uses. I believe I've found a bug where the path for this image is resolved incorrectly which will probably fix this issue.
btw @kepano what macOS and iOS versions are you on? and were your drawings and scans created on those versions, or earlier?

In my test I used iOS 17.0.3 to create the drawing, then synced it to my Mac running macOS 13.0.1 before importing.

Thanks. In that case, I think it will possibly be fixed by this PR, since the changes to the drawing location are made in macOS 14/iOS 17.

Hi guys, unfortunately this problem persists, iOS 16.7.5 and Ventura 13.4. the drawings fail to import.

I have also written some notes about this  here
I think the issue is to do with old notes like #137 . If I clean out notes and create new notes it works fine.
It seems to me to have something to do with the ZIDIDENTIFIER in the notes db, unformantly I no longer have any old notes to look at in the db.

Have been using apple notes on the iPad over the years with apple pencil/handwriting. I get these errors on every note with handwriting:
Failed: "" because Cannot read properties of undefined (reading 'ZIDENTIFIER')
Newer notes seem to get imported, but with " (error reading attachment)" instead of the chunk of handwriting.
Older notes are raised as a "failed" import note with the ZIDENTIFIER error above, and the entire note is empty, even if it was a mix of handwriting and plain text.
Anything I can do to help troubleshoot?

I am thinking if there are two separate issues here?
ZIDENTIFIER with old notes
and the other, I wonder it has something to do with the fact that there are currently two iCloud modes normal and advanced data protection?

I also have a similar issue: I tried to import my Apple notes, and I receive the following failure:
...
Failed: "DATASET NAME RULE" because Cannot read properties of undefined (reading 'ZIDENTIFIER')
...

In these notes, I have text alternated to text drawings made with the Apple pencil.


fix: Autoscaling/v2beta1 to autoscaling/v2

It should be possible to use autoscaling/v2 instead of the v2beta1.
At least it fails on my cluster, let me know if you need better guards or anything to improve the charts.

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


Fails to link existing remote app with local environment

I am attempting to link my remote app with a local environment by running
nhost init --remote -n my-nhost-app

Then I ran nhost dev (clean docker install). The local console app starts with an error:
GraphQL Engine metadata is inconsistent with database

From the error page, it looks like the issue is with computed_fields.
version: Nhost CLI v0.6.12 for darwin-arm64
Here is the screenshot of the full error page:

This seems to be an issue specifically with computed fields. Do you have an example table with computed fields we can use to reproduce this bug?

@elitan I have a couple of tables in my app with computed fields. I have added you as a member to my workspace https://app.nhost.io/viva. The specific project is vivamosolo-nhost-dev. And the tables are:
group and member.
Let me know if you need anything for better debugging

@seyaobey-dev I was able to reproduce your problem and found out that the functions used by all computed fields are not being included in the migration files generated by pg_dump. It should be safe for you to ignore those inconsistencies (but don't delete them) if you don't need to change those functions for now. In the meantime, we will work on a fix. Thank you for reporting!

@seyaobey-dev sorry for only now circling back, but this issue should be fixed in the latest release of the CLI. Do you confirm?

We've done significant updates to the CLI, so this issue should have been fixed now. If anyone has issues with linking an existing app and computed fields, please write a comment with a description, and we can re-open this issue.


Not danloud whiy

please complete the following information:

OS version: [e.g. Win 10, Mac Catalina]
Editor version:
Programming language: [e.g. js, ts, c++]
TabNine extension version:

If the issue is related to TabNine failure, please provide log files:
Type TabNine::config in your editor, the logs are located at the bottom of the page.
Issue Details:
gz#976

Can you provide more information? Did you succeed in installing Tabnine? If not, at what step did the installation failed?