Cleaning hyphenation at line breaks in XML files leads to formatting issues (and eventually unrecognized speaker entities)

Describe the bug
My first observation is the cleaned by the OD scripts in part look less clean than the original XML protocols. As an example, a short paragraph of text from both the original XML file and the processed 18 / 148 in the raw data folder.
First, the original text in the XML.

Je besser und je rascher Integration gelingt, desto eher
ist die Möglichkeit gegeben, dass sich solche Ausschrei-
tungen nicht wiederholen . Wir stehen nicht nur vor einer
Herausforderung, –
Präsident Dr. Norbert Lammert:
Lieber Kollege Bosbach .

Here is the very same paragraph in the session_content.txt:

Je besser und je rascher Integration gelingt, desto eher
ist die Möglichkeit gegeben, dass sich solche Ausschreitungen nicht wiederholen . Wir stehen nicht nur vor einer
Herausforderung, Präsident Dr. Norbert Lammert:
Lieber Kollege Bosbach .

As wen can see the word "Herausforderung" is merged with a line is wasn't part of before (and is thus later misrepresented as its own speaker label)
Before the punctuation and extra whitespace is added
Another related problem, but not core of the issue: Leftovers from the removal of meta data still remain :"Eva Högel" in this script.

To Reproduce
Steps to reproduce the behavior:

Run the OD scripts to download and clean the data

Why does the error occur?
My guess it, this is a combination of two lines of code in https://github.com/pmayd/open-discourse/blob/main/python/src/open_discourse/helper_functions/clean_text.py, a processing script that runs after the XML files are downloaded.
filetext = filetext.replace("–", "-")
The code explicitly converts various types of dashes (em dash "—", en dash "–") into regular hyphens "-" before the rest of the processing. In our case, "Herausforderung, –" would be converted to "Herausforderung, -".
This eventually becomes a problem when the code wants to remove all hyphenation at line breaks:
# Remove delimeter
filetext = regex.sub(r"-\n+(?![^(]*\))", "", filetext)

This line is designed to handle hyphenation at line breaks (common in PDF text extraction) by removing hyphens followed by newlines. The regex pattern -\n+(?![^(]*\)) matches:
- - a hyphen
\n+ - one or more newlines
(?![^(]*\)) - negative lookahead to ensure we're not inside parentheses
The issue might be the reason for https://github.com/open-discourse/open-discourse/issues/104

Current questions I have:
Dashes usually have a white space before them, at least in German, so we could exclude substituting dashes for hyphens when they are "freestanding"? I am not sure if we had a couple of English speeches in the Bundestag, that could create new problems.
Thus, in

tungen nicht wiederholen . Wir stehen nicht nur vor einer
Herausforderung, –

not substitution would take place. But in in

tungen nicht wiederholen . Wir stehen nicht nur vor einer
Herausforderung–

it would.


Test hangs when takeScreenshot is called in headless Chrome on Windows

Are you requesting a feature or reporting a bug?
bug
What is the current behavior?
test hangs on Windows (works properly on MacOS)
Provide the test code and the tested page URL (if applicable)
fixture('example')
    .page('http://example.com');

test('take screenshot', async (t) => {
  await t.takeScreenshot();
});

Specify your

operating system: Windows 10
testcafe version: 0.17.0
browser: Version 62.0.3181.0 (Official Build) canary (64-bit)

Looks like it is a Chrome bug: https://bugs.chromium.org/p/chromium/issues/detail?id=754708
Workaround is on the way.
BTW, headless is available in the latest Chrome stable on Windows, we should change the docs to get rid of Canary notes.

@AndreyBelym Create please a separate issue with the Documentation label and assign it to @VasilyStrelyaev since it's a separate task


feat: Add context offchain profile to wallet connection

Thank you for your contribution to the Koda - Generative Art Marketplace.
👇 __ Let's make a quick check before the contribution.
PR Type

[x] Feature

Needs Design check

@exezbcz please review

Needs QA check

@kodadot/qa-guild please review

Context

[x] Closes #10652

Did your issue had any of the "$" label on it?

[x] My DOT address: Payout

Screenshot 📸

[x] My fix has changed something on UI; a screenshot is best to understand changes for others.

can we add skeleton loader?

Yes, updated

reviewdog is failing

reviewdog is failing

It's not related to this PR : )

I'd rather have the skeleton match the shape of the actual content,

I changed the shape of the skeleton a bit.

@Jarsen136 the test is still failing

@Jarsen136 the test is still failing

It got fixed here https://github.com/kodadot/nft-gallery/pull/10618#issuecomment-2242151709

works for me, thank you!


Adding Settings Screen

This PR is purely for layout purposes; proper icons, interactions and preferences implementation will be added in the next PR

UI Light
UI Dark

@cedricbahirwe I ll get back to you in an hour


[Don't merge] Disable header link on homepage

Did you include those things @pixeltrix was suggesting?
On 14 Jul 2015 18:02, "Henry Hadlow"<EMAIL_ADDRESS>wrote:

You can view, comment on, or merge this pull request online at:
https://github.com/alphagov/e-petitions/pull/319
Commit Summary

Disable header link on homepage
Add js to handle link edge-case

File Changes

A app/assets/javascripts/homepage.js
https://github.com/alphagov/e-petitions/pull/319/files#diff-0 (13)
M app/assets/stylesheets/petitions/_header.scss
https://github.com/alphagov/e-petitions/pull/319/files#diff-1 (6)
M app/views/application/_header.html.erb
https://github.com/alphagov/e-petitions/pull/319/files#diff-2 (10)
M app/views/layouts/application.html.erb
https://github.com/alphagov/e-petitions/pull/319/files#diff-3 (3)
M config/initializers/assets.rb
https://github.com/alphagov/e-petitions/pull/319/files#diff-4 (1)

Patch Links:

https://github.com/alphagov/e-petitions/pull/319.patch
https://github.com/alphagov/e-petitions/pull/319.diff

—
Reply to this email directly or view it on GitHub
https://github.com/alphagov/e-petitions/pull/319.

Nope I thought he was going to do that. Outside my expertise.
On 14 July 2015 at 18:11, Pete Herlihy<EMAIL_ADDRESS>wrote:

Did you include those things @pixeltrix was suggesting?
On 14 Jul 2015 18:02, "Henry Hadlow"<EMAIL_ADDRESS>wrote:

You can view, comment on, or merge this pull request online at:
https://github.com/alphagov/e-petitions/pull/319
Commit Summary

Disable header link on homepage
Add js to handle link edge-case

File Changes

A app/assets/javascripts/homepage.js
https://github.com/alphagov/e-petitions/pull/319/files#diff-0 (13)
M app/assets/stylesheets/petitions/_header.scss
https://github.com/alphagov/e-petitions/pull/319/files#diff-1 (6)
M app/views/application/_header.html.erb
https://github.com/alphagov/e-petitions/pull/319/files#diff-2 (10)
M app/views/layouts/application.html.erb
https://github.com/alphagov/e-petitions/pull/319/files#diff-3 (3)
M config/initializers/assets.rb
https://github.com/alphagov/e-petitions/pull/319/files#diff-4 (1)

Patch Links:

https://github.com/alphagov/e-petitions/pull/319.patch
https://github.com/alphagov/e-petitions/pull/319.diff

—
Reply to this email directly or view it on GitHub
https://github.com/alphagov/e-petitions/pull/319.

—
Reply to this email directly or view it on GitHub
https://github.com/alphagov/e-petitions/pull/319#issuecomment-121311292.

--
Henry Hadlow
Designer
Government Digital Service https://gds.blog.gov.uk/

Yup OK waiting on @pixeltrix to optimise the js etc

@henryhadlow @yahoopete updated for caching

LGTM


[Situ is out until May] [HOLD for payment 2024-03-22] [HOLD for payment 2024-03-20] Chat - Emoji is not showing in chat

If you haven’t already, check out our contributing guidelines for onboarding and email<EMAIL_ADDRESS>to request to join our Slack channel!

Version Number:  1.4.51-0
Reproducible in staging?: Y
Reproducible in production?: N
If this was caught during regression testing, add the test name, ID and link from TestRail: N/A
Issue reported by: Applause - Internal Team
Action Performed:

Go to staging.new.expensify.com
Go to any chat
Send an emoji

Expected Result:
The emoji shows up in chat
Actual Result:
The emoji is not showing up in chat
Workaround:
Unknown
Platforms:

Which of our officially supported platforms is this issue occurring on?

[x] Android: Native
[x] Android: mWeb Chrome
[x] iOS: Native
[x] iOS: mWeb Safari
[x] MacOS: Chrome / Safari
[x] MacOS: Desktop

Screenshots/Videos
Add any screenshot/video evidence

https://github.com/Expensify/App/assets/78819774/4d2a21c3-df00-4d30-8fb8-6ab074b91032
View all open jobs on GitHub

@yuwenmemon  FYI I haven't added the External label as I wasn't 100% sure about this issue. Please take a look and add the label if you agree it's a bug and can be handled by external contributors

We think that this bug might be related to #vip-vsp
CC @quinthar

Looks like https://github.com/Expensify/App/pull/37559 caused regression. expensify-common version bump in that PR includes changes from https://github.com/Expensify/expensify-common/pull/649 which should be only merged with #37814.

Looks like that well pre-dates it - so if you're correct I think we should revert Expensify/expensify-common#649 and then update expensify-common in this repo and CP that.

Agree

@yuwenmemon
Emojis not displayed in task and IOU description also, I believe this might stem from the same underlying issue, but I'll double-check.
Let me know if we need a separate issue. Thanks
https://github.com/Expensify/App/assets/93399543/db2c10d5-4088-4ad9-91c6-4e5dd899449e

Agree with the revert of https://github.com/Expensify/expensify-common/pull/649

This is fixed in staging

Adding bug label to process payment

This is resolved

Can someone confirm who we're paying and for what here? The PR linked here looks like a revert.

Me as reviewed that PR (along with finding the root cause) and was not involved in offending PR.

Ah okay, cool. So payment summary as follows:

$500 to @situchan for the C+ review

Sent you an offer!

@situchan is out until May. I'm dropping this to weekly.

I am back. Can you please send new offer? Old one was expired.

New offer sent.

Situ paid, closing!


Config's file exclude key not working

Hi,
For some reason I have a read-only file in my project.
When I specify this file's exclusion within config file as described in the documentation :
sources:
    include:
      - .
    exclude:
      - ./excludedFolder

I have error file.extension isn't writeable even if file.extension is in the excludedFolder
So I have moved all my included files into a specific folder that I only include in my config file :
sources:
    include:
      - ./includedFiles

But the same error is raised even if file.extension is not in the includedFiles.
It seems that files are accessed in writeable mode even if they are excluded or  not included ?

Relates to #880
@jeremierichard If I understand this correctly, passing a single file to output instead of a folder (or the default current folder) should solve this issue.

sounds like a bug, will take a look


Can't diffentiate identical posts

Hello!
I ran into a problem: Facebook repeats the sending of the same message, when the server doesn't responds fast enough. Example:
» 24 Jun 2016 13:04:29.310 1077 <190>1 2016-06-24T11:04:28.883542+00:00 app web.1 - - Parameters: {"object"=>"page", "entry"=>[{"id"=>"278485275816386", "time"=>1466766268677, "messaging"=>[{"sender"=>{"id"=>"11489850 ...
» 24 Jun 2016 13:04:39.697 1077 <190>1 2016-06-24T11:04:39.335768+00:00 app web.1 - - Parameters: {"object"=>"page", "entry"=>[{"id"=>"278485275816386", "time"=>1466766279130, "messaging"=>[{"sender"=>{"id"=>"11489850 ...
Identical messages could be identified with entry["id"], which is not available in the called methods.
Any idea how to solve this problem?

Hello!
Do you check seq value?

https://developers.facebook.com/docs/messenger-platform/webhook-reference

Hello! The seq value counts up. In the first request it was 14040 an in the second it was 14043.
The only value which stays identical is entry["id"].
PS: The requests have images attached and even those urls are different even it's the same photo.
https://scontent.xx.fbcdn.net/v/t35.0-12/XXXXXXX_10153877314488585_200648850_o.jpg?_nc_ad=z-m&oh=f0cc0020e4e7bb428b270351ce7bd76b&oe=576F4E85
https://scontent.xx.fbcdn.net/v/t35.0-12/XXXXXXX_10153877314488585_200648850_o.jpg?_nc_ad=z-m&oh=f0cc0020e4e7bb428b270351ce7bd76b&oe=576F4E85
'X' used for privacy.

@Bernhard
Hello! I think seq value check(save each user's seq) is the best way currently.
If you have better idea please share with me.
recipient id is same with entry["id"].
Parameters: {"object"=>"page", "entry"=>[{"id"=>"130266200653463", ...........
"recipient" => {"id" => "130266200653463"}.........

PS -> because images upload from facebook server. so it return different URL..


Including ignition-gazebo6 package adds HOME directory to search path in Clion

Environment

OS Version: Ubuntu 20.04
Binary build version: ignition-fortress
- [x] running on a dual GPU machine (integrated GPU + discrete GPU)
- [ ] running on a multi-GPU machine (it has multiple discrete GPUs)
- [x] running on real hardware
- [ ] running in virtual machine
- [ ] running in Docker/Singularity
- [ ] running remotely (e.g. via SSH)
- [ ] running in a cloud
- [ ] using VirtualGL, XVFB, Xdummy, XVNC or other indirect rendering utilities
- [ ] GPU is concurrently used for other tasks
- [ ] desktop acceleration
- [ ] video decoding (i.e. a playing Youtube video)
- [ ] video encoding
- [ ] CUDA/ROCm computations (Tensorflow, Torch, Caffe running)
- [ ] multiple simulators running at the same time

Description
When adding ignition-gazebo6 package to a project, the HOME directory gets included in the search path, so a CMake-aware IDEs (e.g. CLion) may get stuck indexing too many files.
Steps to reproduce

install ignition-fortress from binary
open empty c++ library project in Clion and paste code below to CMakeLists.txt

cmake_minimum_required(VERSION 3.23)
project(test_project)

set(CMAKE_CXX_STANDARD 20)

find_package(ignition-gazebo6 REQUIRED)

add_library(GazeboPlugin SHARED main.cpp)
target_link_libraries(GazeboPlugin
        ignition-gazebo6::ignition-gazebo6
        )

reload cmake in Clion
added home directory should be visible in the External Libraries tab on the left

Output

My suspicion is that it is this line: https://github.com/gazebosim/sdformat/blame/sdf12/src/CMakeLists.txt#L126

@Jakub-Krakowiak can you take a look at https://github.com/gazebosim/sdformat/pull/1170 and see if it fixes this for you.

the issue is resolved, thank you <3


✨ - Team Create

Team create

Player types $team create
Bot says who are your team members
Player then reply's by pinging the members @DJam98#1565
Bot says players added (into a newly created role)
Bot says who is the captain? (you could think of a way to do this)
Bot says What is your team name?
Player replies with team name
Bot says Team created, you can now enter teamed tournaments

This would add another thing for the bot to check in like special series
When entering a team event (assuming team is already done)

Bot says choose the team playing
selection bar of all the teams that the player is a part of

No longer relevant

No longer relevant


Hamdpac.gissaettnummer version 1.0.0

[x] Have you signed the Contributor License Agreement?
[x] Have you checked that there aren't other open pull requests for the same manifest update/change?
[x] This PR only modifies one (1) manifest
[x] Have you validated your manifest locally with winget validate --manifest <path>?

[x] Does your manifest conform to the 1.4 schema?

Note: <path> is the name of the directory containing the manifest you're submitting.

Microsoft Reviewers: Open in CodeFlow

kompany=

@microsoft-github-policy-service agree@microsoft-github-policy-service agree

@microsoft-github-policy-service agree


I dont get this line, is this correct?

This line checks all the checkboxes, is this correct?
https://github.com/sf9v/multi-select-facet/blob/4b8965cd3ee63ce513dea5d3a3ae1502374eea94/webapp/src/components/Filters.vue#L8

I just saw that you use BEufy and :native-value has a value, so this is fine.


V2.0.11 is mislabeled[BUG]

Module Version: 2.0.11
Describe the bug
On the Forge the version number for 2.0.11 is labeled as 2.011. This is causing the Forge to see all new versions as older because 2.011 is greater than 2.0.x

@p4535992 That was because the tag was mislabeled when you did the release :
https://github.com/p4535992/foundryvtt-arms-reach/releases/tag/v2.011
Even if the module.json had the correct 2.0.11 in it, the github action overrides that value with the version as defined by the tag name.
See https://github.com/p4535992/foundryvtt-arms-reach/blob/v2.011/.github/workflows/release.yml#L40
I've manually renamed 2.011 into 2.0.11 in our database. Thanks for letting us know about it.

@p4535992 That was because the tag was mislabeled when you did the release : https://github.com/p4535992/foundryvtt-arms-reach/releases/tag/v2.011 Even if the module.json had the correct 2.0.11 in it, the github action overrides that value with the version as defined by the tag name. See https://github.com/p4535992/foundryvtt-arms-reach/blob/v2.011/.github/workflows/release.yml#L40 I've manually renamed 2.011 into 2.0.11 in our database. Thanks for letting us know about it.

Ty for the fast fix.


Missing publishDiagnostics.relatedInformation capability

Bug:
Missing textDocument.publishDiagnostics.relatedInformation capability
	/**
	 * Capabilities specific to `textDocument/publishDiagnostics`.
	 */
	publishDiagnostics?: {
		/**
		 * Whether the clients accepts diagnostics with related information.
		 */
		relatedInformation?: boolean;
	};

Add in plugin/core/main.py
                "publishDiagnostics": {
                    "relatedInformation": True
                },

Thanks for pointing out this new API!
Are you using it with LSP? I'd like to avoid turning the capability on until it is in use (so language servers can save the effort of calculating the field contents)

I use only internal LSP, the VSCode example use it: https://github.com/Microsoft/vscode-extension-samples/blob/4581ade9c7ef054751c672cc2e6fdf43bcd328a8/lsp-sample/server/src/server.ts#L33

Ok, good to know for the future.
I'm not sure what the "bug" or current improvement to LSP is?
The protocol allows omitting the field and that sounds like a reasonable thing to do until we have a use for it the data. I'll close this issue for now!


sgemm with 15548cf is 30X slower than with libclBLAS.so.2.3

Using workload size M=N=K=8192, clblasSgemm is about 3X slower with libclBLAS.so.2.11 than with libclBLAS.so.2.3
To recreate, apply my patch to src/samples/example_sgemm.c from https://gist.github.com/matejaputic/6fcf4cf0ee872c8c57e8
The only modification is that the workload size is 8192x8192x8129 instead of 3x4x5, and memory for the buffers is allocated on the heap.
I profiled the GPU counters with AMD's CodeXL sprofile command on an AMD FirePro W9100 card, the outputs are here for both libclBLAS.so.2.3 and libclBLAS.so.2.11 https://gist.github.com/matejaputic/6437e74ac7064e12aa77
The 2.11 version dispatches four runs of the same kernel, one of which runs for about 15 seconds, the others which run for between 3 and 20 ms. The 2.3 version uses only a single kernel run, which runs in about 535 ms.
Please let me know if I can provide additional info. I realize this is only a single datapoint, but I thought it significant enough to bring it to the attention of the dev team.
Am I doing anything wrong here?

we did observed the SGEMM declined sharply at particular size 2048, 4096,
8192, before.
The four kernel was introduced to "mitigate" the decline.  Timmy can tell
more, but you can test other size,like 8000 to see if it is still slow.
On Fri, Mar 11, 2016 at 7:31 PM, Mateja Putic<EMAIL_ADDRESS>wrote:

Using workload size M=N=K=8192, clblasSgemm is about 3X slower with
libclBLAS.so.2.11 than with libclBLAS.so.2.3
To recreate, apply my patch to src/samples/example_sgemm.c from
https://gist.github.com/matejaputic/6fcf4cf0ee872c8c57e8
The only modification is that the workload size is 8192x8192x8129 instead
of 3x4x5, and memory for the buffers is allocated on the heap.
I profiled the GPU counters with AMD's CodeXL sprofile command on an AMD
FirePro W9100 card, the outputs are here for both libclBLAS.so.2.3 and
libclBLAS.so.2.11 https://gist.github.com/matejaputic/6437e74ac7064e12aa77
The 2.11 version dispatches four runs of the same kernel, one of which
runs for about 15 seconds, the others which run for between 3 and 20 ms.
The 2.3 version uses only a single kernel run, which runs in about 535 ms.
Please let me know if I can provide additional info. I realize this is
only a single datapoint, but I thought it significant enough to bring it to
the attention of the dev team.
Am I doing anything wrong here?
—
Reply to this email directly or view it on GitHub
https://github.com/clMathLibraries/clBLAS/issues/239.

--
Tingxing dong

Another to check is make sure you have selected OpenCL 2.0 compiler from CMAKE here:
https://github.com/clMathLibraries/clBLAS/wiki/Build#offline-kernel-compilation
By default 1.2 compiler is selected and does use a lot more registers.

Thanks, Timmy. I am going to have to look into this further.
With OpenCL 2.0, the same benchmark segfaults in clBuildProgram when called from makeGemmKernel. I will follow up with this. In the mean time, here is the stack trace.
https://gist.github.com/matejaputic/5b7509ce564befd70454

No more complaints in over a week. I'll close it out assuming it was that compiler issue.


[crash] InferAnalyze Failed when analyzing my ios project

Today, I use infer to analyze our IOS project:
Capture part is OK, but analyze part is failed:
log here:
[INFO] Capture phrase was successful
[INFO] Starting analysis
[ERROR] Failure during run_makefile, original command was
[u'infer', u'-g', u'infer', u'--', u'javac']
Crash strace:
make: *** [cl2558] Error 137
make: Target `default' not remade because of errors.
Traceback (most recent call last):
File "/Users/bensonqin/Documents/infer-osx-v0.9.3/infer/bin/../lib/python/infer.py", line 230, in
main()
File "/Users/bensonqin/Documents/infer-osx-v0.9.3/infer/bin/../lib/python/infer.py", line 214, in main
analysis.analyze_and_report()
File "/Users/bensonqin/Documents/infer-osx-v0.9.3/infer/lib/python/inferlib/analyze.py", line 537, in analyze_and_report
elif self.analyze() == os.EX_OK:
File "/Users/bensonqin/Documents/infer-osx-v0.9.3/infer/lib/python/inferlib/analyze.py", line 428, in analyze
self.args.analyzer
File "/Users/bensonqin/Documents/infer-osx-v0.9.3/infer/lib/python/inferlib/analyze.py", line 240, in run_command
raise e
subprocess.CalledProcessError: Command '[u'make', u'-k', u'-j', '8', u'-s']' returned non-zero exit status 2
A..ha...I build my IOS project... Why the log tells me that "infer --javac"?

Can you share the command that you are using to run Infer on your project?

infer  -- xcodebuild -target dailybuildipa -configuration DailyBuild -sdk iphonesimulator CODE_SIGN_IDENTITY="" CODE_SIGNING_REQUIRED=NO
But run twice.. the problem is missing...

Could you try with the current <IP_ADDRESS> release, which includes much more robust integration with xcodebuild using xcpretty?  Optimistically closing, but please reopen if the problem remains.


[BUG] Cluster Flow Ouptut Selection UI Tag Gets Overfilled

Describe the bug
When building a Cluster Flow, selecting an output that has the length of 42 characters, cross-reference:
Python 3.8.13 (default, Mar 28 2022, 17:40:36)
[GCC 11.2.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> x = "sample-had-to-use-embbeded-to-build-secret"
>>> len(x)
42

The tag created overfills the "tag"'s allowed "space" and overwhelms the selection area.
 id: vs212__combobox
 class: vs__selected-options
 class: vs__selected
To Reproduce
Steps to reproduce the behavior:

Create a cluster output that's name contains 42 characters
Create a cluster flow -> select "Outputs" -> select previously created cluster output

Expected behavior
The tag not to be overfilled.
Environment

Harvester ISO version: v1.1.2-rc1
Underlying Infrastructure: qemu/kvm

Additional context

This looks good in v1.1.2-rc3, I'll go ahead and close this out :smile:  - thanks for the fix @DaiYuzeng


Fix standard method codec alignment

This PR fixes the byte alignment in the standard method codec. Support for writing Value::F64 has been added as well.

Merged.


Unexpected stalls during repeated, rapid publishing calls on v2.0.0-alpha.4

When publishing a large (~5000+) number of messages in a tight loop it seems that Lapin can end up sleeping despite having pending message backlog.
The trace usually stops with a message like:
Sep 15 00:23:41.318 TRACE lapin::io_loop: io_loop run
Sep 15 00:23:41.318 TRACE lapin::io_loop: io_loop do_run can_read=false can_write=true has_data=false
Sep 15 00:23:41.318 TRACE pinky_swear: Called from future, registering waker. promise=[Frames]
Sep 15 00:23:41.318 TRACE async_io::driver: block_on: sleep until notification

Sending resumes when some event interrupts this "sleep", usually a heartbeat, at which point more messages are quickly fired through, though the potential for another stall exists if the backlog processing takes a sufficiently long amount of time.
I've reproduced this issue reliably with RabbitMQ 3.9.5 on both Linux (AMD 5950X, Xeon E5-2697v2) and macOS (M1 ARM). It usually takes in excess of 5,000 messages to trip it, but 50,000 will do it nearly every time.
The example project I've created does not exhibit this problem using the current release version of Lapin, but does with both the published beta and the GitHub main branch used directly.

Is it possible that a new basic_publish call can squeak in at a time where the decision to sleep has already been made? It looks like the mechanism to wake from that isn't completely aligned with the inner IoLoop::run system meaning the promise returned to the basic_publish caller isn't acted on until after the sleep interval.


Inserting a Base64 image

Thank you for sharing these updates.

Regarding Image Insert -
What I am trying to do is use your version of richeditor in an email app.

From a server I am receiving an image in Base64 via a json return, and then want to insert that directly into the richeditor. However looking at the code it seems it needs to pull the image from a link ?  Is that correct ?
Can it insert the image as I receive it as mentioned ?
More specifically, I want that inline image to be seen in Outlook (Hotmail) and GMail.
I have been able to dummy up data into richedit to show an image in Hotmail however it does not appear in GMail. It seems the image insert does not present an image in a format that can be recognised across the board ?
So my question is, which I am hoping you can guide me on, is ;
a) using your version of richeditor, how do I insert a image (data:image/png;base64) directly into the editor area.
b) do you happen to know how then that data needs to be formatted to appear in GMail as well as Hotmail as well as being generally displayed ?
I have used  "data:image/png;base64,iVBORw0KG .......
which as I say works fine in Hotmail but does not work for GMail
Cheers
Mark

Hi Mark,
a)
There is a function:
public void insertImageAsBase64(Uri imageURI, String alt, String width, String height, Boolean relative, Integer inSampleSize) {
Please have look at how to implement it.
NoteDetailActivity.java
Start with line 231:
also see this function in this file:
private void processShareIntent(Intent intent) {
}
An Image is shared to the app. and a dialog is shown, where the user can set the size and scaling of the image...
b) Why it doesn't work properly on gmail, I don't know, but I can check this...but it takes some time...
Greetings, Peter

What you are looking for is inserHTML:
mEditor.insertHTML("");

for gmail (and others):
I guess embedded images are just blocked:
https://mailtrap.io/blog/embedding-images-in-html-email-have-the-rules-changed/
you need some thing like this:


How does same class different instances distinguished?

I logged out sizes of output:
INFO 12.22 11:31:34 demo.py:65: boxes: (15, 4)
INFO 12.22 11:31:34 demo.py:66: masks: torch.Size([15, 720, 1280])
INFO 12.22 11:31:34 demo.py:67: scores: (15,)

Seems every mask contains more than one instance.
This got a situation that, some mask didn't have mask related with it:

how to remove those separate masks that does instance or does have box related with it?

@jinfagang  hi did u run these inference in the cpu or in the gpu ?? since i also used to face this issue when i run the eval.py in the cpu settings

I think nothing to do with cpu or GPU.
predictions on mask is not instance level since there were a lot of spots that not have a box bounding it.

Hello, how do you output only the mask. Can it be output directly？

@Naturalvolume  aas you can see the mask shape:
masks: torch.Size([15, 720, 1280])

I am only visualized channel by channel

@jinfagang did you solve the issue with the overlapping masks? I'm facing the same issue :( don't understand what's wrong, because I get almost perfect bboxes..

@jinfagang can you please share me specifically that you can create a binary mask?
I would like to crop white/ segmented object save into database.

@basit26374 See #286

@dbolya
How to label a single category with labelme? After looking at the user-defined data set, there is no annotation naming method. For example, there is only one category in a graph: cat, cat, cat or CAT1, cat2, Cat3 or cat-0, cat-1, cat


Change Download Method used for EMIT granules

There was a memory issue for large files/long lists of files for the methods used in our notebooks. Switched from using an fsspec https session to a requests https session and improved the code to write to disk in smaller chunks.

diff is so large because I removed cell outputs


Header styling updates #1

Jira: https://issues.redhat.com/browse/RHCLOUD-31189
Old

New

Old

New

@epwinchell FYI I'm noticing some issues merging this with my draft:

It seems in FF 115.7.0esr (64-bit) the header background doesn't continue across the page (like the blue background in the widget drawer)
It also seems like the widgets in the drawer to not wrap down (I've added 2 widgets that you can see)
With the correct 4 column config the widgets still bleed past the hard edge


daemon: Add hidden --cflags debug command

Support compiling with dedicated compile options to assist development.

@borkmann there are a few other flags we could maybe make better use of like -Wundef, but in general just having this capability at all is useful to play around with newer clang flags in the container we deploy rather than locally based on my own environment setup.

Given that the flag is hidden, I don't think there's a big deal to wait for the remaining @cilium/cli codeowner review (especially given  there's already four reviews). Good to merge.


Typo in the description

There is a typo in the description of exponential growth: "where cases_n stands for the number of cases registered on day n", because "number of cases" can be easily interpreted as "on the specific day, only".
With this misinterpretation at hand, it would look like that the absolute number of positive cases is still getting larger and larger, which is not always the case.
I assume that the sentence should be replaced with something along the line: "where cases_n stands for the number of cases registered UP TO day n", or - less preferable - "where cases_n stands for the TOTAL number of cases registered on day n"(implying "total number of cases" means "since the beginning").

Thank you for your comment, I agree that the description could be misleading! I will tweak it with the next feature release :)


Finished Rewards processing loop before rewards-end-block

@KyleMoser  do you mind taking a long at this.  I think it's one of the last issues around rewards indexing.
when using
    rewards-start-block = 1
    rewards-end-block = 2612736

I get this, see attached
rewards.txt
Points of note:

it doesn't look like it searches block 1 - 13363 for rewards, not sure if this matters, but i think there should be a way to tell the code to index sequentially, if needed.
It hit the Finished Rewards processing loop, before it got to block 2612736.
It didn't find any rewards in the 36 minutes it successfully ran for

I fixed the start height so it will be honored if set explicitly in the config.
I fixed the for loop condition so it will stop at the correct block height (I think...I tested with 1-200). The new condition in question is startHeight+delta <= endHeight.

I don't think point 3 "It didn't find any rewards in the 36 minutes it successfully ran for" really matters:

To find Osmosis rewards epochs (which only happen once daily at predictable intervals), the indexer does a smart search. Based on the last known delta (number of blocks between two previous epochs) it will "jump" that many blocks to find the next epoch.
It does this by searching backwards/forwards simultaneously, and giving up if an epoch isn't found within 1000 blocks in either direction. Since you're starting at block one it doesn't know of any previous epochs, and therefore will do a block by block sequential search to find the next epoch. So I don't think the 36 minute "no rewards found" result is indicative of any issue.

thanks, ill try running it again


Bugs in physics Quiz

In the physics quiz section,while giving the quiz, if a person checks an option more than once the score gets added more than once which shouldn't occur. Also if I click a wrong option  and then I immediately check the correct option the score gets incremented which is also a bug.

I want to work on this issue under JWOC

@VATSAL-IIT go ahead


Rest inside tuples

type restStartTuple = [...number, string];

(["2"]: restStartTuple);
([1, "2"]: restStartTuple);
([1, 2, "3"]: restStartTuple);

([1, 2, 3]: restStartTuple); // FlowError
([1, "2", 3]: restStartTuple); // FlowError

type restMiddleTuple = [string, ...number, string];

(["1", "2"]: restMiddleTuple);
(["1", 2, "3"]: restMiddleTuple);
(["1", 2, 3, "4"]: restMiddleTuple);

(["1"]: restMiddleTuple); // FlowError
(["1", 2]: restMiddleTuple); // FlowError
([1, 2, 3]: restMiddleTuple); // FlowError
(["1", "2", "3"]: restMiddleTuple); // FlowError

The primary use case is to support rest arguments in functions in other positions (i.e. func(...a, b))
This syntax would be most natural to people:
function restStart(...a: Array<number>, b: string) {...}
function restMiddle(a: string, ...b: Array<number>, c: string) {...}

However, since JavaScript does not support that kind of syntax we need a workaround. I would suggest this:
function restStart(...args: [...Array<number>, string]) {...}
function restStart(...args: [string, ...Array<number>, string]) {...}

So really there's two feature requests here: Support for rest inside tuples and for them to work with function arguments.
The current work around is to create libdefs with a bunch of possible combinations like here: https://github.com/flowtype/flow-typed/pull/260

But how can this type be used?
For example, we have var x of type [...number, string]. What's the type of x[1], x[2], x[3]? It's number | string, at best. So for reading it is essentially the same as Array<number|string>.

Yeah that seems expected. Correct types enter, unknown types leave. If you were writing a function that accepted a variable number of args in a starting or middle position you'd have to check them anyways.
function method(...args: [...number, string]) {
  for (let arg of arg) {
    if (typeof arg === 'number') {...} else {...}
  }
}

method(1, 2, 3, "hi");

What about restEndTuple?
For example:
type restEndTuple = [void, ...string];

In my case this is useful because I'm representing a heap using an array and while every element has a certain type, heap[0] is undefined.

1

For me the primary need is to be able to define rest arguments as tuples. Rest inside tuples seems a lot more complex of a feature to add and also less used (i.e. less overall value). But we desparately need to be able to do the former, eg:
type Action
 = {
    type: string,
    payload?: P,
    error?: bool,
    meta?: any,
  }

type ActionCreator<T, P> = (...args: T) => Action
 // this won't typecheck since args must be any or Array<something>

type Payload = { index: number, foo: string }

const performAction: ActionCreator<[number, string] , Payload> = createAction('PERFORM_ACTION', (index: number, foo: string): Payload => ({ index, foo }))

I mean how are you supposed to have an abstract type declaration for complex libraries that do things like return functions (e.g. redux-actions, react-redux, etc) if you can't create the library definition abstract enough to allow you, in client code, to specify a tuple of argument types. If you just did the following, typechecking stops:
type ActionCreator<T, P> = (...args: any) => Action

and of course the following won't work because you will rarely ever have all your arguments be the same type:
type ActionCreator<T, P> = (...args: Array<T>) => Action

I'd like to be able to type s-expression grammars encoded as tuples, e.g.:
type Expression =
    | number
    | ['+', ...Expression]
    | ['*', ...Expression]
    | ['-', Expression, Expression]
    | ['/', Expression, Expression];

function evaluate(e: Expression) {
    if (typeof e === 'number') {
        return e;
    }

    const [op, ...args] = e;
    switch (op) {
    case '+': return args.map(evaluate).reduce((a, b) => a + b, 0);
    case '*': return args.map(evaluate).reduce((a, b) => a * b, 1);
    case '-': return args[0] - args[1];
    case '/': return args[0] / args[1];
    }
}

@jfirebaugh if rest is the last bit, then it should work. Probably not that hard to implement, even. The problem is that disjoint union refinement doesn't work with tuples at the moment.

I would like to be able to do something like:
type AtLeastTwo<T> = [T, T, ...T];

This is for modelling an AST for a math expression parser that I'm building.  It treats addition and multiplication as n-ary operations, but addition and multiplication need at least two operands to make sense.

One case here:
type $AddEntryFn =
    & (<T1>([], T1) => [T1])
    & (<T1, T2>([T1], T2) => [T1, T2])
    & (<T1, T2, T3>([T1, T2], T3) => [T1, T2, T3])
    & (<T1, T2, T3, T4>([T1, T2, T3], T4) => [T1, T2, T3, T4])
    & (<T1, T2, T3, T4, T5>([T1, T2, T3, T4], T5) => [T1, T2, T3, T4, T5])
    & (<T1, T2, T3, T4, T5, T6>([T1, T2, T3, T4, T5], T6) => [T1, T2, T3, T4, T5, T6])
    & (<T1, T2, T3, T4, T5, T6, T7>([T1, T2, T3, T4, T5, T6], T7) => [T1, T2, T3, T4, T5, T6, T7])
    // and again, and again, ....
;

replaced by :
type $AddEntryFn = (TuppleTyped,Added) => [...TuppleTyped, Added];
leading to many fun :
type $AddEntry = $Call<$AddEntryFn, B, N>;

export type SelectBuilder<S, O> = {|
    innerJoin<E: Entity>(
        alias: string,
        source: Source<E>,
        on: (sources: $AddEntry<S, E>) => SqlExpression<boolean>,
    ): SelectBuilder<$AddEntry<S, E>, O>,

    select<E: Entity>((sources: S) => E): SelectBuilder<S, E>,
|}


docs.factorcode.org "Glossary" link returns 404

"Glossary" links to http://docs.factorcode.org/content/article-conventions.html

help.html generates the sha1 hashes for each topic, but the Glossary link is hard-coded in the help-navbar word.

This will be fixed when docs upload later tonight.

Fixed by 1f9dccb2233a5956f223b3d167379bf8527b408a

When you type in a search term the Glossary link continues to point to "article-conventions.html".
The Glossary link is fixed only from the homepage (docs.factorcode.org).
I still saw this behaviour even though cookies/cache/local data was flushed from the browser.

Fixed. Thanks erg.


Invoke CPU as accelerator instead of CUDA

Hi there.  an unrelated FYI, I was also able to get imaginiary running on my Intel Mac without conda using python 3.10.
I am attempting to get the concept-trainer to work, and getting the error below.  It looks like pytorch will support CPU instead of GPU, however, I cannot determine where to make the code change to call the CPU as the trainer.  Any ideas?  Thanks in advance, I know this is just experimental, but WAY simpler to use than anything else I have seen!
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.10/bin/aimg", line 8, in
sys.exit(aimg())
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/click/core.py", line 1130, in call
return self.main(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/click/core.py", line 1055, in main
rv = self.invoke(ctx)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/click_shell/core.py", line 164, in invoke
ret = super(Shell, self).invoke(ctx)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/click/core.py", line 1657, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/click/core.py", line 1404, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/click/core.py", line 760, in invoke
return __callback(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/imaginairy/cmds.py", line 504, in train_concept
train_diffusion_model(
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/imaginairy/train.py", line 499, in train_diffusion_model
trainer = Trainer(
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/utilities/argparse.py", line 340, in insert_env_defaults
return fn(self, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 414, in init
self._accelerator_connector = AcceleratorConnector(
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/accelerator_connector.py", line 208, in init
self._set_parallel_devices_and_init_accelerator()
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/accelerator_connector.py", line 528, in _set_parallel_devices_and_init_accelerator
raise MisconfigurationException(
lightning_lite.utilities.exceptions.MisconfigurationException: CUDAAccelerator can not run on your system since the accelerator is not available. The following accelerator(s) is available and can be passed into accelerator argument of Trainer: ['cpu'].

I managed to fix this by updating the trainer.py, and got much further, until this (below).  Still researching this, as this is outside of my depth.....
Training the full unet
Setting up LambdaLR scheduler...
Epoch 0:   0%|                                                                           | 0/578 [00:00<?, ?it/s]Summoning checkpoint.
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.10/bin/aimg", line 8, in
sys.exit(aimg())
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/click/core.py", line 1130, in call
return self.main(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/click/core.py", line 1055, in main
rv = self.invoke(ctx)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/click_shell/core.py", line 164, in invoke
ret = super(Shell, self).invoke(ctx)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/click/core.py", line 1657, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/click/core.py", line 1404, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/click/core.py", line 760, in invoke
return __callback(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/imaginairy/cmds.py", line 504, in train_concept
train_diffusion_model(
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/imaginairy/train.py", line 529, in train_diffusion_model
trainer.fit(model, data)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 604, in fit
call._call_and_handle_interrupt(
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/trainer/call.py", line 36, in _call_and_handle_interrupt
return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/strategies/launchers/subprocess_script.py", line 90, in launch
return function(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 646, in _fit_impl
self._run(model, ckpt_path=self.ckpt_path)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 1099, in _run
results = self._run_stage()
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 1178, in _run_stage
self._run_train()
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 1201, in _run_train
self.fit_loop.run()
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/loops/loop.py", line 199, in run
self.advance(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/loops/fit_loop.py", line 267, in advance
self._outputs = self.epoch_loop.run(self._data_fetcher)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/loops/loop.py", line 199, in run
self.advance(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 214, in advance
batch_output = self.batch_loop.run(kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/loops/loop.py", line 199, in run
self.advance(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 88, in advance
outputs = self.optimizer_loop.run(optimizers, kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/loops/loop.py", line 199, in run
self.advance(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/loops/optimization/optimizer_loop.py", line 200, in advance
result = self._run_optimization(kwargs, self._optimizers[self.optim_progress.optimizer_position])
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/loops/optimization/optimizer_loop.py", line 239, in _run_optimization
closure()
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/loops/optimization/optimizer_loop.py", line 147, in call
self._result = self.closure(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/loops/optimization/optimizer_loop.py", line 133, in closure
step_output = self._step_fn()
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/loops/optimization/optimizer_loop.py", line 406, in _training_step
training_step_output = self.trainer._call_strategy_hook("training_step", *kwargs.values())
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 1481, in _call_strategy_hook
output = fn(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/strategies/ddp.py", line 352, in training_step
return self.model(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/parallel/distributed.py", line 1040, in forward
output = self._run_ddp_forward(*inputs, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/parallel/distributed.py", line 1003, in _run_ddp_forward
return module_to_run(*inputs, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pytorch_lightning/overrides/base.py", line 98, in forward
output = self._forward_module.training_step(*inputs, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/imaginairy/modules/diffusion/ddpm.py", line 592, in training_step
loss, loss_dict = self.shared_step(batch)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/imaginairy/modules/diffusion/ddpm.py", line 1141, in shared_step
x, c = self.get_input(batch, self.first_stage_key)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/imaginairy/modules/diffusion/ddpm.py", line 1056, in get_input
c = self.get_learned_conditioning(xc)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/imaginairy/modules/diffusion/ddpm.py", line 876, in get_learned_conditioning
c = self.cond_stage_model.encode(c)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/imaginairy/modules/clip_embedders.py", line 49, in encode
return self(text)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/imaginairy/modules/clip_embedders.py", line 43, in forward
outputs = self.transformer(input_ids=tokens)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/transformers/models/clip/modeling_clip.py", line 811, in forward
return self.text_model(
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/transformers/models/clip/modeling_clip.py", line 708, in forward
hidden_states = self.embeddings(input_ids=input_ids, position_ids=position_ids)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/transformers/models/clip/modeling_clip.py", line 223, in forward
inputs_embeds = self.token_embedding(input_ids)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/modules/sparse.py", line 160, in forward
return F.embedding(
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/functional.py", line 2210, in embedding
return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
RuntimeError: Placeholder storage has not been allocated on MPS device!

Glad to hear it's working more places than expected. Super slow though right?
I should update docs to state training requires a (nice) graphics card and even then takes hours.  No idea whether it could technically be made to work on the CPU but practically speaking it wouldn't work.  Would have to run for months... That's not accounting for trial-and-error nature of it either. I've run probably ~6 trainings on images of myself and am still not happy with the results.
I'd consider just paying for a service online to do it instead.


Cuda 11.0 with cuDNN v8.0.1 problem when using GPU : libcudnn.so.7: cannot open shared object file

System information

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Debian GNU/Linux 10 (buster)
TensorFlow installed from (source or binary): binary
TensorFlow version: 2.2.0
Python version: 3.7.0
Installed using virtualenv: from pyenv using pip
CUDA/cuDNN version: 11.0 / v8.0.1
GPU model and memory: NVIDIA Corporation TU102 [GeForce RTX 2080 Ti Rev. A]

Problem encountered:
I first installed cuda 11.0 using runfile:
wget http://developer.download.nvidia.com/compute/cuda/11.0.1/local_installers/cuda_11.0.1_450.36.06_linux.run
sudo sh cuda_11.0.1_450.36.06_linux.run

Then installed cuDNN v8.0.1 (cuDNN Library for Linux (x86)) following Nvidia website : https://developer.nvidia.com/rdp/cudnn-download
tar -xzvf cudnn-x.x-linux-x64-v8.x.x.x.tgz

sudo cp cuda/include/cudnn*.h /usr/local/cuda/include
sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64
sudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*

I configured some PATH variables into my ~/.bashrc and reload it using source:
export PATH=/usr/local/cuda-11.0/bin:${PATH}
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:${LD_LIBRARY_PATH}
export LD_LIBRARY_PATH=/usr/local/cuda-11.0/lib64:${LD_LIBRARY_PATH}
export CUDA_HOME=/usr/local/cuda

Encountered problem with libcudnn.so.7 which is not found:
2020-07-02 21:06:53.502117: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcudnn.so.7'; dlerror: libcudnn.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.0/lib64:/usr/local/cuda/lib64:
2020-07-02 21:06:53.502124: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1598] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...

The problem was as I installed cuDNN v8.0.1, hence the expected share object file is now (and cannot be found by TensorFlow):
/usr/local/cuda/lib64/libcudnn.so.8

I do not know if I have to reconfigure TensorFlow to tell him the cuDNN version. I fixed the problem (worst fix ever) doing:
sudo mv /usr/local/cuda/lib64/libcudnn.so.8 /usr/local/cuda/lib64/libcudnn.so.7

Now, TensorFlow can recognized the share object file... When lauching a neural network training script, now my GPU is used and seems to work well:
I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
...
Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 10211 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2080 Ti, pci bus id: 0000:2d:00.0, compute capability: 7.5)

Can you please tell me how I can fix this problem following a better way always using my virtualenv ?

Tensorflow is compiled for a specific CUDA + cuDNN version. Either build from source or down grade these CUDA libraries.
By the way people constantly post these kind of questions. Maybe one should train a tensorflow bot to detect questions + auto close and reply to questions like these.

Hello,
Thank you for your comment.
I agree with you and I've never said otherwise before. The problem here is that I want to go through a python virtual environment and unless I'm wrong, it doesn't seem to me that it's possible to retrieve a binary version via the python manager package with the latest version of cuda (or at least target a cuda version). I just wanted to know if it was possible and if so, how.

@jbuisine
Please refer to this comment and let us know if it helps.
#40423 link

I tried to install Tensorflow 2.3.0 as well but the cuDNN 8.0.1 library is always not found.

As shown in the documentation for tensorflow 2.2.0 use CUDA 10.1 and CuDNN 7.6 and let me know if the problem still persists. Thanks!

It seems I need last cuda version for my GPU and hence cuDNN 8.0.1, that's why I opened this issue

@jbuisine As mentioned here, please try using cuDNN 7.6 and let me know if you are running into the same error. Thanks!

@gowthamkpr Sorry for the delay in answering. My GPU card seems to really need cuda v11.0, hence cuDNN v8.0.1. Compiling tensorflow from scratch works but the issue was using the available binary from pip (it seems to not have v11.0 cuda support as indicated in your link). You can close the issue if you want.

@jbuisine Glad that its working. I am gonna go ahead and close this issue. Thanks!

Tensorflow is compiled for a specific CUDA + cuDNN version. Either build from source or down grade these CUDA libraries.
By the way people constantly post these kind of questions. Maybe one should train a tensorflow bot to detect questions + auto close and reply to questions like these.

Instead of creating a bot to reply with that answer to people asking this, it would probably be useful if any other place on the internet would mention this. Your comment is the only place where I can find this claim. For example, https://www.reddit.com/r/nvidia/comments/hg45ux/is_cuda_11_compatible_with_tensorflow/ claims that because of backwards compatibility it should work just fine...
Creating a bot to respond to people is not solving the problem of bad documentation of this fact. It's just solving the symptom of people getting confused by this.

@jbuisine
Run this command
source /home/{user_name}/.bashrc
You must have these two environment variables there "PATH" & "LD_LIBRARY_PATH" and also cuda variable
export PATH="/usr/local/cuda-11.4/bin:$PATH"
export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/cuda-11.4/lib6
If you don't have these variables there you must add them. Otherwise, you will face this issue.


broken install in current bolt version

In a fresh bolt install today (June 6th, 2021), installing this theme fails:
$  composer require bobdenotter/bolt-tufte-theme
Using version ^1.1 for bobdenotter/bolt-tufte-theme
./composer.json has been updated
Running composer update bobdenotter/bolt-tufte-theme
Loading composer repositories with package information
Updating dependencies
Your requirements could not be resolved to an installable set of packages.

  Problem 1
    - Root composer.json requires bobdenotter/bolt-tufte-theme ^1.1 -> satisfiable by bobdenotter/bolt-tufte-theme[1.1.0].
    - bobdenotter/bolt-tufte-theme 1.1.0 requires twig/twig ^2.0 -> found twig/twig[v2.0.0, ..., v2.14.6] but the package is fixed to v3.3.2 (lock file version) by a partial update and that version does not match. Make sure you list it as an argument for the update command.

Use the option --with-all-dependencies (-W) to allow upgrades, downgrades and removals for packages currently locked to specific versions.

Installation failed, reverting ./composer.json and ./composer.lock to their original content.

actually, in addition to the fresh install, I also added the composer require bolt/article


radix job status codes has changed

Need to update radix_job_handler to reflext this change

Seems to work now...


feat: New options to install packages via micromamba

Close #7
Implement two options to install packages via micromamba:

packages option to install by the micromamba install command.
envFile option to install by the micromamba create command.

The errors that are occurring when non-root users try to run micromamba install may need to be fixed on the micromamba side.
Changing the directory permission by the chown command just before executing these commands did not resolve the errors.
critical libmamba filesystem error: cannot set file time: Operation not permitted [/opt/conda/conda-meta/history]

critical libmamba filesystem error: status: Permission denied [~/conda-bld]

critical libmamba filesystem error: cannot set file time: Operation not permitted [/opt/conda/conda-meta/history]

critical libmamba filesystem error: status: Permission denied [~/conda-bld]

micromamba 1.3 seems to have fixed the first error. The second error continues to occur.

Hey, thanks for the update! I took a very quick look at this. The activation test seems to be failing due to it running as root (where the shell has not been initialized) instead of the vscode user. I didn't see anywhere where the vscode user was specified. Do we need to add USER vscode to the end of thetest-specific Dockerfile?
Regarding Permission denied [~/conda-bld] this looks to me like a micromamba bug. For instance it worked after I ran mkdir ~/conda-bld, so it's not true that permissions are lacking. I think we can submit a bug report as soon as we come up with a minimal reproducing example.

Thank you for taking a look at this.

The activation test seems to be failing due to it running as root (where the shell has not been initialized) instead of the vscode user. I didn't see anywhere where the vscode user was specified. Do we need to add USER vscode to the end of the test-specific Dockerfile?

Testing with the Dev Container CLI reads remoteUser name from the metadata recorded as a label (devcontainer.metadata) and executes the script by the remote user, so there should be no need to change the user on the Dockerfile.
I am probably missing something because I am pretty clueless about conda activation.......

Regarding Permission denied [~/conda-bld] this looks to me like a micromamba bug. For instance it worked after I ran mkdir ~/conda-bld, so it's not true that permissions are lacking. I think we can submit a bug report as soon as we come up with a minimal reproducing example.

I too think this is a micromamba bug, but I can't explain the situation well and sorry I haven't created an issue yet.
It would be very helpful for you to dig into this.

Hi @eitsupi, I've been trying to understand what's going on here.
I am no longer seeing Permission denied [~/conda-bld], so perhaps it's fixed in v1.3.1?
I am however seeing a "Shell not initialized" error in test-specfile-option-non-root.sh. This seems to be due to the test scripts running in a non-interactive Bash shell. Thus the ~/.bashrc is not being run. One possible ugly workaround is to run
eval "$(micromamba shell hook --shell=bash)"

in the test script if you ever need to run micromamba activate.
To explain what's going on, the micromamba activate command is supposed to modify the current shell's environment, which it cannot do when executed as a subprocess of the shell. Therefore, the trick is to define a "Bash function" called micromamba which overrides the micromamba executable. This function passes arguments through to the micromamba executable unless the command is micromamba activate [...]. (You can look at the output of micromamba shell hook --shell=bash, the relevant part being micromamba() { ... }.)

@maresb Thanks for making sure the bug is fixed and your advice!
After some more struggle, I think it now works as it's supposed to!

Thanks for taking this over!
I think all of these are very good, but I am concerned about the effort it will take to maintain the special base image.
Could we use mcr.microsoft.com/devcontainers/base:debian here?
This image has a non-root user, but for scenario testing, we should be able to test the root user as well by specifying like "remoteUser": "root".

I think I should add a comment by each reference to ghcr.io/maresb/docker-debian-curl to clarify that my image can be safely replaced by debian:stable-slim.

Since the test is run on CI with the default options, debian:stable-slim is not necessary to use it for scenario testing.
https://github.com/mamba-org/devcontainer-features/blob/1a36e997d10589b1a95d732737866c7d504b0ccd/.github/workflows/test.yaml#L36-L41

[Oops, I see now that this is a .json file, so I probably can't add comments. 😞]

I believe these are actually jsonc files so perhaps comments can be added.

I couldn't be sure because I didn't have time to look into it at the time I made my comment the other day, but I believe that buildpack-deps:curl (Docker Official Image) is exactly a minimal image that bzip2 and curl are installed.
How about using this?
https://hub.docker.com/_/buildpack-deps
https://github.com/docker-library/buildpack-deps

Since the test is run on CI with the default options, debian:stable-slim is not necessary to use it for scenario testing.

To clarify, I was using the Dev Container CLI devcontainer features test command to run the tests locally, and they were running slowly. That's why I'm trying to speed up the testing. (Especially since Bash often has such strange behavior!)

I believe that buildpack-deps:curl (Docker Official Image) is exactly a minimal image that bzip2 and curl are installed.

Ah, that looks really promising, but I just checked, and unfortunately bzip2 is missing.
But anyways, I'm really excited that we will now support specifiers and lockfiles. This will be very powerful! :rocket:
If you manage to find the time, please feel free to finish this up. Regarding the test infrastructure, I think the details are not so important as long as we're doing the right tests. Feel free to revert my stuff if it makes things easier.

Ah, that looks really promising, but I just checked, and unfortunately bzip2 is missing.

Oh, sorry. It seems bzip2 is only installed in buildpack-deps:scm...
I am in no hurry to merge this, but I see no problem with merging it as it is now and making improvements later.
If you want to make updates at this time, feel free to do so at your own pace.

I agree that it's currently mergeable.
I'll merge and create two issues for the todos in https://github.com/mamba-org/devcontainer-features/pull/11#issuecomment-1465313667.
Would you like to make a new release?

New version is released! https://github.com/mamba-org/devcontainer-features/releases/tag/feature_micromamba_1.1.0


MarioInWonderland-game

Project title
Mario In WonderLand
Project Description
Save Mario from Zombies!!
A simple game in HTML,CSS and JavaScript. Jump over the zombies to score points and save mario.
Stack:

[x] Html
[x] CSS
[x] JavaScript

/assign


Error on environment reset with MetaCurriculum in TrainerController

I created a MetaCurriculm and added it to the TrainerController. I got an error on the environment reset.
I modified the trainMLAgents.py:
# ...

maybe_meta_curriculum = MetaCurriculum('configs/curricula/')

# ...

tc = TrainerController(model_path, summaries_dir, run_id + '-' + str(sub_id),
                       save_freq, maybe_meta_curriculum,
                       load_model, train_model,
                       keep_checkpoints, lesson, external_brains, run_seed, arena_config_in)
tc.start_learning(env, trainer_config)

And this is the error:
Traceback (most recent call last):
  File "trainMLAgents.py", line 87, in <module>
    tc.start_learning(env, trainer_config)
  File "/Applications/anaconda3/envs/animalai/lib/python3.6/site-packages/animalai_train/trainers/trainer_controller.py", line 205, in start_learning
    curr_info = self._reset_env(env)
  File "/Applications/anaconda3/envs/animalai/lib/python3.6/site-packages/animalai_train/trainers/trainer_controller.py", line 183, in _reset_env
    return env.reset(config=self.meta_curriculum.get_config())
TypeError: reset() got an unexpected keyword argument 'config'

I need to adapt the ML-Agents curriculum to work with yaml configuration files, this won't work at the moment. Let me have a look and get back to you with an ETA for this.

Could you describe what you were trying to use as a curriculum?
Did you want to be able to reset arenas with new configurations each time an agent reaches some threshold on a given metric?

Yes exactly. The documentation says that this is easy to implement, but I just know the ML-Agents way.

Some update for you: I've adapted the MetaCurriculum and Curriculum to work with the yaml configuration files, I'm running some tests and writing documentation. I plan on releasing this in v1.1 on Monday.

This is now live, you can find the documentation here
I'll leave this topic open for a bit in case there are any questions.


Add horizontal margin/padding on Certificate page

The text on the certificate page touches the border on smaller screen sizes. Here is a screenshot for iPhoneXR

We should probably add a margin or padding so there is some space between the edge of the screen and the text

Did #541 not fix this?  cc @Genne23v

Did #541 not fix this? cc @Genne23v

We have a proper margin in all the pages now, but


"show" button is not un-pressing when you press "show" in another script

It works fine within a script though. Probably the presenter is just over-relying on self.gui.flow_canvas when searching for a node widget to unpress a button on.

Ah, ok, it is getting un-pressed, we just aren't re-drawing the node after that.


Fix quick option buttons to have no default behavior (default is submit when inside a form)

old behavior https://drive.google.com/file/d/0B75i_S1A9mU2RF9PRFZVQmx4WkU/view
the current fix prevents that

Codecov Report

Merging #305 into master will not change coverage.
The diff coverage is 100%.

@@          Coverage Diff          @@
##           master   #305   +/-   ##
=====================================
  Coverage     100%   100%
=====================================
  Files         137    137
  Lines        3281   3281
  Branches      732    732
=====================================
  Hits         3281   3281

Impacted Files
Coverage Δ

src/components/optionPicker/Option.tsx
100% <100%> (ø)
:arrow_up:

src/components/datePicker/DatePickerDropdown.tsx
100% <100%> (ø)
:arrow_up:

Continue to review full report at Codecov.

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Alert rules not firing due to extra "juju_charm" key in labels

Bug Description
While testing the alerts for the hardware-observer charm, I'm not able to see any of them firing even when the metric being exported was giving the fail value.
Example
For the redfish_call_success metric, I've provided wrong credentials and the querying the exporter shows that the metric has value 0.
ubuntu@bomberto:~$ curl localhost:10000

(...)

# HELP redfish_service_available Indicates if redfish service is available or not on the system.
# TYPE redfish_service_available gauge
redfish_service_available 1.0
# HELP redfish_call_success Indicates if call to the redfish API succeeded or not.
# TYPE redfish_call_success gauge
redfish_call_success 0.0

This is reflected on COS Prometheus as well

But the alert rule attached to the failure of this metric is not being fired.

Upon troubleshooting this for a bit, I found that the alert rule is being injected with an extra juju_charm key which is not present in the metric itself. So all the alerts that are supposed to be fired are not being triggered due to this extra key.
To Reproduce
Setup of principal and subordinate charms
juju deploy ubuntu
juju deploy hardware-observer
juju deploy grafana-agent

juju relate ubuntu hardware-observer
juju relate ubuntu grafana-agent
juju relate hardware-observer grafana-agent

COS Setup on microk8s
juju deploy microk8s
juju config microk8s addons="dns ingress hostpath-storage metallb:<IP_ADDRESS>-<IP_ADDRESS>"

# add microk8s cloud to controller
juju add-k8s micro -c my-ctrl

# add new model to cloud
juju add-model cos micro
juju deploy cos-lite --channel edge --trust
juju offer prometheus:receive-remote-write

Setting up the CMR
juju relate grafana-agent micro:cos.prometheus

Environment
Running juju on a MAAS cloud backend. Deployed all applications from latest/stable
❯ juju --version
2.9.44-ubuntu-amd64

❯ juju status
Model  Controller    Cloud/Region     Version  SLA          Timestamp
hw     ct-maas-ctrl  ct-maas/default  2.9.43   unsupported  14:36:35+05:30

SAAS        Status  Store         URL
prometheus  active  ct-maas-ctrl  ashley/cos.prometheus

App                Version  Status  Scale  Charm              Channel        Rev  Exposed  Message
grafana-agent               active      6  grafana-agent                       4  no       logging-consumer: off, grafana-cloud-config: off
hardware-observer           error       6  hardware-observer                  26  no       hook failed: "upgrade-charm"
microk8s                    active      1  microk8s           legacy/stable  101  no
ubuntu                      active      6  ubuntu             latest/stable   24  no

Unit                     Workload  Agent  Machine  Public address  Ports                     Message
microk8s/0*              active    idle   13       <IP_ADDRESS>     80/tcp,443/tcp,16443/tcp
ubuntu/3*                active    idle   3        <IP_ADDRESS>
  grafana-agent/41*      active    idle            <IP_ADDRESS>                               grafana-cloud-config: off, logging-consumer: off
  hardware-observer/59   error     idle            <IP_ADDRESS>                               hook failed: "upgrade-charm"
ubuntu/4                 active    idle   4        <IP_ADDRESS>
  grafana-agent/42       active    idle            <IP_ADDRESS>                                logging-consumer: off, grafana-cloud-config: off
  hardware-observer/58*  active    idle            <IP_ADDRESS>                                Unit is ready
ubuntu/5                 active    idle   5        <IP_ADDRESS>
  grafana-agent/44       active    idle            <IP_ADDRESS>                              grafana-cloud-config: off, logging-consumer: off
  hardware-observer/60   blocked   idle            <IP_ADDRESS>                              Missing resources: ['sas2ircu-bin']
ubuntu/7                 active    idle   7        <IP_ADDRESS>
  grafana-agent/40       active    idle            <IP_ADDRESS>                                grafana-cloud-config: off, logging-consumer: off
  hardware-observer/56   active    idle            <IP_ADDRESS>                                Unit is ready
ubuntu/10                active    idle   10       <IP_ADDRESS>
  grafana-agent/43       active    idle            <IP_ADDRESS>                               logging-consumer: off, grafana-cloud-config: off
  hardware-observer/61   blocked   idle            <IP_ADDRESS>                               Missing resources: ['sas2ircu-bin']
ubuntu/12                active    idle   12       <IP_ADDRESS>
  grafana-agent/39       active    idle            <IP_ADDRESS>                                logging-consumer: off, grafana-cloud-config: off
  hardware-observer/57   blocked   idle            <IP_ADDRESS>                                Missing resources: ['storcli-deb']

Machine  State    Address       Inst id   Series  AZ        Message
3        started  <IP_ADDRESS>   coinfish  jammy   default   Deployed
4        started  <IP_ADDRESS>    bomberto  jammy   default   Deployed
5        started  <IP_ADDRESS>  gurley    jammy   Cert Lab  Deployed
7        started  <IP_ADDRESS>    rozary    jammy   default   Deployed
10       started  <IP_ADDRESS>   prunus    jammy   Cert Lab  Deployed
12       started  <IP_ADDRESS>    kongfu    jammy   Cert Lab  Deployed
13       started  <IP_ADDRESS>   birdo     jammy   default   Deployed

Relevant log output
Output of running `juju show-unit grafana-agent/x`: https://pastebin.ubuntu.com/p/nDTjPnBx6W/

Additional context
ubuntu@bomberto:~$ cat /etc/grafana-agent.yaml
integrations:
  agent:
    enabled: true
    relabel_configs:
    - regex: (.*)
      replacement: juju_hw_dfaf0254-3e9c-4684-8575-5b86266f1581_grafana-agent_self-monitoring
      target_label: job
    - regex: (.*)
      replacement: hw_dfaf0254-3e9c-4684-8575-5b86266f1581_hardware-observer_hardware-observer/58
      target_label: instance
    - replacement: grafana-agent
      source_labels:
      - __address__
      target_label: juju_charm
    - replacement: hw
      source_labels:
      - __address__
      target_label: juju_model
    - replacement: dfaf0254-3e9c-4684-8575-5b86266f1581
      source_labels:
      - __address__
      target_label: juju_model_uuid
    - replacement: grafana-agent
      source_labels:
      - __address__
      target_label: juju_application
    - replacement: grafana-agent/42
      source_labels:
      - __address__
      target_label: juju_unit
  node_exporter:
    enable_collectors:
    - logind
    - systemd
    - mountstats
    - processes
    - sysctl
    enabled: true
    relabel_configs:
    - regex: (.*)
      replacement: juju_hw_dfaf0254-3e9c-4684-8575-5b86266f1581_grafana-agent_node-exporter
      target_label: job
    - regex: (.*)
      replacement: hw_dfaf0254-3e9c-4684-8575-5b86266f1581_hardware-observer_hardware-observer/58
      target_label: instance
    - replacement: hw
      source_labels:
      - __address__
      target_label: juju_model
    - replacement: dfaf0254-3e9c-4684-8575-5b86266f1581
      source_labels:
      - __address__
      target_label: juju_model_uuid
    - replacement: hardware-observer
      source_labels:
      - __address__
      target_label: juju_application
    - replacement: hardware-observer/58
      source_labels:
      - __address__
      target_label: juju_unit
    sysctl_include:
    - net.ipv4.neigh.default.gc_thresh3
  prometheus_remote_write:
  - tls_config:
      insecure_skip_verify: false
    url: http://<IP_ADDRESS>/cos-prometheus-0/api/v1/write
logs:
  configs:
  - clients: []
    name: log_file_scraper
    scrape_configs:
    - job_name: varlog
      pipeline_stages:
      - drop:
          expression: .*file is a directory.*
      static_configs:
      - labels:
          __path__: /var/log/*log
          instance: hw_dfaf0254-3e9c-4684-8575-5b86266f1581_hardware-observer_hardware-observer/58
          juju_application: hardware-observer
          juju_model: hw
          juju_model_uuid: dfaf0254-3e9c-4684-8575-5b86266f1581
          juju_unit: hardware-observer/58
        targets:
        - localhost
    - job_name: syslog
      journal:
        labels:
          instance: hw_dfaf0254-3e9c-4684-8575-5b86266f1581_hardware-observer_hardware-observer/58
          juju_application: hardware-observer
          juju_model: hw
          juju_model_uuid: dfaf0254-3e9c-4684-8575-5b86266f1581
          juju_unit: hardware-observer/58
      pipeline_stages:
      - drop:
          expression: .*file is a directory.*
  positions_directory: ${SNAP_DATA}/grafana-agent-positions
metrics:
  configs:
  - name: agent_scraper
    remote_write:
    - tls_config:
        insecure_skip_verify: false
      url: http://<IP_ADDRESS>/cos-prometheus-0/api/v1/write
    scrape_configs:
    - job_name: hardware-observer_0
      metrics_path: /metrics
      static_configs:
      - labels:
          instance: hw_dfaf0254-3e9c-4684-8575-5b86266f1581_hardware-observer_hardware-observer/58
          juju_application: hardware-observer
          juju_model: hw
          juju_model_uuid: dfaf0254-3e9c-4684-8575-5b86266f1581
          juju_unit: hardware-observer/58
        targets:
        - localhost:10000
  wal_directory: /tmp/agent/data
server:
  log_level: info

Related to existing issue #190

Closing this as a duplicate of #190


Add method team get_by_id()

Fixes #46

@Gby56 , this is a pretty straightforward change, but could I ask for one change? In other methods in this area, we use object().get(guid) rather than the method name here (get_by_id). Can we change the method name so it's consistent with the other getters?

Looks good, thanks!


Crash resolve, delay was 60 seconds terminating task.

Crash resolve, delay was 60 seconds terminating task. so after next immediate launch it gets crashed. so i change it to 0 to terminate it immediately.

Can you post log of an a crash?

i will i am a little busy right now. sorry.

the problem was occurring because if geolocation is not terminated because of the 60 seconds delay, and App tries to restart the service again, it crashes.


Template files created by forge init are licensed under The Unlicense

In the interest of having sane and safe defaults, the license specifier should probably be SPDX-License-Identifier: UNLICENSED, and not SPDX-License-Identifier: unlicense.
Wouldn't want to accidentally make someone release code in the public domain.

SGTM, PR welcome for it!


Make hooks funcallable.

This makes hooks funcall-able. Not much practical value, except allowing for more relaxed hook invocations, compared to the regular nhooks:run-hook.
This adds a closer-mop dependency, which might be problematic for other projects (potentially) relying on this library, but it's fine for Nyxt—it already depends on closer-mop :)
As an additional mind-boggling thing: SBCL allows extending sequence class to allow for any class to behave like sequences. Maybe implement this too, indexing handlers etc...
Does that look sane?

@Ambrevar, any feedback?

This adds a closer-mop dependency, which might be problematic for other projects (potentially) relying on this library

closer-mop could have been named trivial-mop: it's super lightweight, no dependencies.  So no hassle, we can include it!

OK, handlers are funcallable now. Which makes me wonder: do we actually need fn anymore?—it all can be simulated with funcall-able instance setting. Not sure how symbol-based handlers would work, but we can generate proxy lambdas for those in the worst case ( ͡° ͜ʖ ͡°)

I'm not sure we can get rid of fn because how would we check the types otherwise?

I'm not sure we can get rid of fn because how would we check the types otherwise?

We can do that the same way we do it now: by compiling and ftype-declaring it. For example, the following two snippets work as intended (on SBCL, CCL, and ECL):
;; Basic type check. Handlers are functions.
(typep (make-instance 'nhooks:handler :name 'hey :fn (lambda () (print "hey!"))) 'function)
;; A more complicated check from nhooks::probe-ftype. Handlers inherit the type of their funcallable instances.
(compile
 nil
 `(lambda ()
    (let ((fn ,(make-instance 'nhooks:handler :name 'hey :fn (lambda () (print "hey!")))))
      (declare (type (function ()) fn))
      fn)))

CL is so well-planned...

I wasn't sure it also works on values... Just checked: it does.
From what I recall it does not work on CCL because the compiler does less function type checking, plus it does not raise a condition.
Did you get it to work on CCL?
Also you are still using :fn.  Or do you mean to only use it as an initialize-instance :after parameter?

I wasn't sure it also works on values... Just checked: it does.
From what I recall it does not work on CCL because the compiler does less function type checking, plus it does not raise a condition.
Did you get it to work on CCL?

I did, but note that I've checked to arg-less function type, and it may stop working if we add args...

Also you are still using :fn. Or do you mean to only use it as an initialize-instance :after parameter?

I am using it, but we can safely turn it into an initialize-instance :after parameter and closer-mop:set-funcallable-instance-function on it there!

Exactly, CCL cannot go as sophisticated as SBCL.  Try the following on various compiler:
(compile
 nil
 `(lambda ()
    (let ((fn (lambda (s) (* 2 s))))
      (declare (type (function (number) string) fn))
      fn)))

(compile
 nil
 `(lambda ()
    (let ((fn (lambda (s) (declare (type number s)) (* 2 s))))
      (declare (type (function (string) number) fn))
      fn)))

But then, does it work right now? What would incorporating functions inside handlers change anyway?

Sorry, what works right now?

I mean, handler/hook ftype checking on CCL. Your snippet applies to functions, which makes me think that it doesn't work as a super-reliable ftype checker, at least on CCL. But then, you've used it as an argument against :fn slots being merged inside handlers, somewhy saying that situation with ftype checking would change in some way if we merge those.
But it won't -- CCL ftype checking would still be too permissive, no matter what we're checking -- functions or some funcallable-standard-object. It should be fine merging fn inside the handler, as it will change nothing except removing an unnecessary slot from the semantically funcallable and ftype-check-able object.

Misunderstanding: I was just being confused because nhooks used to be implemented differently, by type-checking functions.  But that does not make sense with the current implementation.
All good!

Okay, there's no more fn. However, all this funcallability business strips us off the most important feature of nhooks -- binding handlers to symbols, with the ability of symbol-bound function redefinition.
Given that, we'd have to revert the handler funcallability so that handlers use the old mechanism. But then, it wouldn't make much sense making hooks solely funcallable, I guess?
I can see the benefits of both approaches (making everything funcallable vs. allowing symbol hooks), but I guess allowing symbols is more pragmatic. @Ambrevar, @BlueFlo0d, @aadcg, any ideas on that? Can we have both?
Unless anyone is strongly against it, or unless we find some way to support symbols, I'll close this PR in a week :)

Oh yes, that makes sense.
Hanving funcallable hooks and handlers is still possible even if we keep the fn slot though, no?

OK, the old behavior is preseverd (in regards to symbol-bound handlers), while both hooks and handlers are properly funcallable. It's fully backward-compatible. I'll think some more on how to make it more elegant, and will merge today's evening.

Interesting work. Nothing much to add :)

Thanks!


OSD-19418: Add template for pull requests in backplane-api

Adding pull request template in backplane-api repository for getting information about the work done in the PR.

/lgtm
/approve


Feedback from David and API Review/ Tests

@Tratcher @BrennanConroy @davidfowl

Note, I will fix this be from my github account rather than my local computer.

:shipit:

:up: :date:

Will add RedirectPermanent in another PR

:up: :date:

@ZestyBread why is the build failing

Cause I'm bad at naming.

No one is good at naming. Don't feel bad about it.

@davidfowl @troydai Cool to ship? Next PR is going to address the rest of the comments (doing right now)


Allowing '(' and ')' in regex.

Allowing '(' and ')' in regex using '\(' and '\)'.
Changed regex syntax in README to match rust regex.
Added a test for regex.

as far as I see it closes  #53 ?

Should close #52

Yeah. My last comment had an intention to do what you did in your last one but I apparently made a typo.


docs: development: Add a section about required Ubuntu deps for running the app in dev mode

LGTM. Once we have a proper Debian package (see https://github.com/headlamp-k8s/headlamp/issues/1320 ), we should update these docs to just set up the PPA and run apt build-dep headlamp.

I added a task on #1320 for that.


Minor issues on Android

I am trying to study react-native directly on my phone. I am able to perform basic development on the phone, but I have to workaround a couple of annoying issues.
Environment
Environment:
OS: android
Node: 8.9.4
Yarn: 1.3.2
npm: 4.6.1
Watchman: Not Found
Xcode: N/A
Android Studio: Not Found
Packages: (wanted => installed)
react: 16.2.0 => 16.2.0
react-native: 0.52.0 => 0.52.0
Expected Behavior
create-react-native-app applicationname should work and the created application project should be usable.
Actual Behavior

the creation procedure fails with the following error:

ngrok - error unpacking binary { Error: ENOENT: no such file or directory, open<EMAIL_ADDRESS>  errno: -2,
  code: 'ENOENT',
  syscall: 'open',
  path<EMAIL_ADDRESS>}

I was able to skip this issue by just copying ngrok-stable-linux-arm.zip into<EMAIL_ADDRESS>in a continuous loop during the creation process;
2. Created project is not working because os.cpus() is undefined. I was able to workaround this by patching node_modules/metro/src/lib/getMaxWorkers.js and node_modules/metro/src/lib/getMaxWorkers.js.flow with a change like const cores = (os.cpus() || {length: 1}).length;.
Steps to Reproduce
On an Android system with Oreo, install Termux, then in Termux install npm, patch npm as described in github.com/termux/termux-packages/issues/1798, use npm to install npm version 4.6.1, use npm 4.6.1 to install react-native, try to create a new project.

I have not tried with a recent version, but the issue is present with the
most recent create-react-native-app, which is not installing 0.54.
Best,
Giulio
Il 05 mar 2018 18:21, "React Native Bot"<EMAIL_ADDRESS>ha
scritto:
Thanks for posting this! It looks like your issue may refer to an older
version of React Native. Can you reproduce the issue on the latest stable
release http://facebook.github.io/react-native/versions.html?
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