fix: Load file labels with appropriate byteorder

Motivation
BinaryFileWrapper::int_from_bytes previously used hard-coded preprocessor definitions for determining the endianness. We now want to use the byteorder specified in the filesystem_wrapper_config.
fyi. @XianzheMa

@MaxiBoether could you please add me as a codebase collaborator, I cannot trigger CI workflows. Thank you! :)

Sorry about that, you should have received an invite!


GetResourceAllocationInfo corruption

Using this function produces D3D12 CORRUPTION error. Suggested fix by @msiglreith :
fn GetResourceAllocationInfo(
        &mut self, __ret_val: *mut ::D3D12_RESOURCE_ALLOCATION_INFO, visibleMask: ::UINT, numResourceDescs: ::UINT,
        pResourceDescs: *const ::D3D12_RESOURCE_DESC
    ) -> *mut ::D3D12_RESOURCE_ALLOCATION_INFO,

This is only applicable to 0.2 and should be fixed in 0.3. Closing.

It wasn't actually fixed at the time you closed this issue, but it is fixed now. It's a good thing I switched to a #[fixme] attribute marking those functions, so it was trivial to swap the order of parameters to fix the issue.

@retep998 How [fixme] works? Or it is just a part of patterns in RIDL macro?

@pravic It's just an arbitrary string that the RIDL! macro matches on and results in a simple transformation to account for an ABI difference.


Engagement widget tweaks

A few changes to the widget:
Add the "current phase" icon with text "Current Phase and Comment Period" in 13px italic next to it. All past phases will be greyed-out in #7B8283 with a 1px border in #565656.
https://xd.adobe.com/view/4f8d7697-971c-4010-9d8d-db80bf63a841-1ade/screen/52c90a20-4a75-4fa9-b95a-15dc7aa474e1/
"Learn more" link should be underlined in white (not blue), Hover in bold
Background colors for the boxes:
EE: #A8D5DD
RD: #EFBDB9
PP:#89A4C4
AD&R: #9AC0E0
EA&R: #EDC970
D: #AAA2BF
PC: #D5DE9E
Change the icon for this one:
<svg id="Group_495" data-name="Group 495" xmlns="http://www.w3.org/2000/svg" width="72.696" height="69.501" viewBox="0 0 72.696 69.501">
<g id="Rectangle_167" data-name="Rectangle 167" fill="#458686" stroke="#fff" stroke-width="2">
<rect width="65" height="35" rx="10" stroke="none"/>
<rect x="1" y="1" width="63" height="33" rx="9" fill="none"/>
</g>
<g id="Group_488" data-name="Group 488" transform="translate(72.696 69.501) rotate(180)">
<g id="Group_487" data-name="Group 487" transform="translate(0 0)">
<g id="Rectangle_167-2" data-name="Rectangle 167" fill="#9be2df" stroke="#fff" stroke-width="1">
<rect width="65" height="35" rx="10" stroke="none"/>
<rect x="0.5" y="0.5" width="64" height="34" rx="9.5" fill="none"/>
</g>
<path id="Path_166" data-name="Path 166" d="M18.449,0s-7.276,32.853-7.82,20.193S0,.278,0,.278" transform="translate(37.175 33.042)" fill="#9be2df"/>
</g>
</g>
<path id="Path_166-2" data-name="Path 166" d="M-22838.951-17532s-8.5,36.906-9.141,22.686-12.42-22.373-12.42-22.373" transform="translate(22893.012 17560.459)" fill="#458686"/>
</svg>

Vineet observed:
on the phases widget we have a text like "
Effect Assessment & Review"
the wireframe says "
Effect Assessment & Recommendation"

@jadmsaadaot
Attaching the document we have to use for correct wording.
The page says "Recommendation" but it should be "Effects Assessment & Recommendation".
I also noticed the "recommendation" gets cut.

No Engagement icon for Readiness Decision.
We have to tweak the colour background for the boxes. (My bad, they are still too dark.)
Please change for the following:
EE: #cce5e9
RD: #ead0ce
PP: #bed1e7
AD&R: #bbd3e7
EA&R: #f2e1b6
D: #dbd7e5
PC: #e9eecc
For the "greyed-out" phases, let's do a #f2f2f2 background with #494949 text.


updated all sections of Setting Up Environment section...

… to reflect the most recent libraries  and api

Typings library is deprecated. Must use @types npm package, and must specify d3 version, and need not be installed globally - updated link and instructions.
Current pbiviz api is 1.10.0
Current TypeScript is 2.3.3
Current supported d3 is v3.5
Capabilities.json no longer accepts an integer as Kind for Categories and Values
small grammatical fixes

Thank you @luisamiranda for submitting those fixes and updates!

thanks for the contribution!


Not able to Enable Remote Desktop on DragonBoard 410c

I installed the Windows 10 IOT (v17134) on DragonBoard 410c and connected to WiFi and next i logged in to Windows Device Portal, and Tried to enable Remote Desktop, but it fails, The Checkbox goes ON but it says: Failed to enable Windows IOT Remote Server.
Not sure if i am missing a step or something is not right?

cant replicate  that issue on 17134 and later

Yes it fails to enable it every time, here is the screen shot, the Windows 10 IOT version number i have is v.10.0.17134.1

It always show message: Failed to enable Windows IoT Remote Server

can you check if you can control it from command line ?
ssh into your DragonBoard and

To query if it is running:
schtasks.exe /query /tn \Microsoft\Windows\NanoRDP\Start /fo csv /nh
To schedule it for startup:
schtasks.exe /Create /SC ONSTART /TN \Microsoft\Windows\NanoRDP\Start /TR %SystemRoot%\\System32\\NanoRDPServer.exe /RU DefaultAccount /F
To Run it:
schtasks.exe /Run /TN \Microsoft\Windows\NanoRDP\Start

if this works for you ?

Ok these commands worked and Remote Desktop Enabled, thanks, Next i am trying to install latest Insider Build Image to make sure the Serial Port issue is resolved

schtasks.exe /Create /SC ONSTART /TN \Microsoft\Windows\NanoRDP\Start /TR %SystemRoot%\System32\NanoRDPServer.exe /RU DefaultAccount /F
Worked on older release of Windows 10 IOT by running that command directly on the Application Command App in side Windows 10 iot, but what i am trying to Run same on later Insider Build it says Access Denied , Windows 10 IOT Version is:  10.0.17692.1000


Always stack at converting one song from a playlist when running inside script

System Operating System (OS)
MacOS
Python Version
3.9 (CPython)
Install Source
pip / PyPi
Install version / commit hash
3.9.6
Expected Behavior vs Actual Behavior
I am downloading couple of playlists so I have made a script and always there is one song stuck at "Converting".
It works fine if I directly call spotdl in the terminal with one playlist.
The  script:
#!/bin/bash

while IFS=';' read -r name addr; do
	echo $name
	mkdir $name
	cd $name
	spotdl "$addr" --dt 8 --st 8
	cd ..
done < dl

And for example a dl file is:
organic_chill;https://open.spotify.com/playlist/2x6ejoBhjrHRIeWevEBUmK?si=f0f7071423964803

Steps to reproduce
Run spotdl inside zsh script
Traceback
No error, its stuck.

The other time, other song:

Other details
There is also this strange file .spotdlTrackingFile present in the output folder with some random song.
Like it failed to convert or something?
It really bugs me, why this only happens when running from a script

Seems to be working inside a python script though:
import csv
import os

file = open('dl')
csvreader = csv.reader(file, delimiter=';')

for row in csvreader:
	name = row[0]
	addr = row[1]

	print(name)

	os.mkdir(name)
	os.chdir(name)
	os.system("spotdl '" + addr + "' --dt 8 --st 8")

	os.chdir("..")

file.close()

no idea what is going on

Check if the song actually finishes converting (check the size/metadata).
Try using v4 if the song actually gets stuck
pip install -U https://codeload.github.com/spotDL/spotdl-v4/zip/master --force (beta)
run it with --log-level DEBUG

with v4 works in both python and zsh.
v3 works with python only.
v3 does not have log level :-)

yeah but I was talking about v4s log level

with v4 it works so there is no need for logs :-)

ok same thing happened to me on v3 without script. so it is rare, but sometimes items are stuck on "Converting".
not sure how I can provide more details

I think I encountered a similar issue. The file starts converting then after a few seconds, it stops, like its stuck. Some trial and errors later, I noticed the task was actually backgrounded.
Found YouTube URL for "Blue - Best In Me" : https://www.youtube.com/watch?v=OfMyEMpy7w8

Blue - Best In Me                        Converting         ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╺━━━━  90% 0:00:01

[1]+  Stopped                 spotdl https://open.spotify.com/playlist/...

So I tried fg and it started working again.
/tmp/mp3$ fg
spotdl https://open.spotify.com/playlist/...
Blue - Best In Me                        Done               ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00

This doesn't happen if I run 'python3 spotdl/main.py' directly, only happens if I run spotdl.

Fixed in v4 i suppose


Version 3.0

version 0.3.0

By the way Anton - I know you're going to be upset, but we're adding setDebug back in on Android: https://github.com/BranchMetrics/android-branch-deep-linking/pull/290

Don't worry :), I will fix that in an hour

Just ping me when you will finish adding, right now I can't see setDebug in source code


[RIP-35] Use rocketmq instead of mysql as state store

https://github.com/apache/rocketmq-streams/issues/131

Codecov Report

Merging #132 (e5fd612) into main (8ba8e00) will not change coverage.
The diff coverage is 0.00%.

@@           Coverage Diff           @@
##            main    #132     +/-   ##
=======================================
  Coverage   0.00%   0.00%
=======================================
  Files        713     650     -63
  Lines      35571   31951   -3620
  Branches    5924    5403    -521
=======================================
+ Misses     35571   31951   -3620

Impacted Files
Coverage Δ

...org/apache/rocketmq/streams/sink/RocketMQSink.java
0.00% <0.00%> (ø)

...ketmq/streams/source/MessageListenerDelegator.java
0.00% <0.00%> (ø)

...apache/rocketmq/streams/source/RocketMQSource.java
0.00% <0.00%> (ø)

...cketmq/streams/client/source/DataStreamSource.java
0.00% <0.00%> (ø)

.../rocketmq/streams/client/transform/DataStream.java
0.00% <0.00%> (ø)

.../rocketmq/streams/client/transform/JoinStream.java
0.00% <0.00%> (ø)

...cketmq/streams/common/channel/AbstractChannel.java
0.00% <0.00%> (ø)

.../streams/common/channel/source/AbstractSource.java
0.00% <0.00%> (ø)

...rocketmq/streams/common/utils/CreateTopicUtil.java
0.00% <0.00%> (ø)

.../apache/rocketmq/streams/common/utils/SQLUtil.java
0.00% <0.00%> (ø)

... and 51 more

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config: Gemfile(barebones), _config

/opt/hostedtoolcache/Ruby/3.3.4/x64/bin/bundle config --local path /home/runner/work/blog/blog/vendor/bundle
/opt/hostedtoolcache/Ruby/3.3.4/x64/bin/bundle lock
[!] There was an error parsing Gemfile: There are no gemspecs at /home/runner/work/blog/blog. Bundler cannot continue.
from /home/runner/work/blog/blog/Gemfile:2
-------------------------------------------
source "https://rubygems.org"

gemspec

-------------------------------------------
Error: The process '/opt/hostedtoolcache/Ruby/3.3.4/x64/bin/bundle' failed with exit code 15


opCode '||' not work

The following program output a wrong result:
var a error = nil
if a == nil || a.Error() == "nil" {
	println("a is nil")
}

Expected result:
print 'a is nil'

Got:
print nothing

reopened by https://github.com/containous/yaegi/issues/474#issue-540844498


CPH 2.0!

During and after testing, I created these files which contain useful tab configurations for use with tinyweb as well as Burp rules and macros for the advanced stuff:
https://www.dropbox.com/s/gu5obyf4zcbywwd/CPH_Test_json_files.zip?dl=0

If all is well, this will close issues:
#3, #11, #12, #13, #14, #15


post-processing labelled graph into structured table

Hi ,
thanks for the code from which i was able to train and reproduce results.
In your paper, you mention "we employ a simple post-processing to
convert a labeled graph to structure data".  Could you bring more details on the post-processing used?
Thanks and Regards
Youcef

@ykacer I tried a quick run to compare the results, and that seems to be pretty bad,
Did you manage to train the model with the complete data? How many epochs did you take it through? What was the final loss?

Hi ,
thanks for the code from which i was able to train and reproduce results.
In your paper, you mention "we employ a simple post-processing to
convert a labeled graph to structure data". Could you bring more details on the post-processing used?
Thanks and Regards
Youcef

Any breakthrough with the post processing?


implement RPC nonce query that takes delayed transactions

https://github.com/mangata-finance/substrate/pull/12 needs to be merged first


Prerequisites

[X] I have searched all issues/PRs to ensure it has not already been reported or fixed.

Criteria

[X] Reasonably well-known and widely used (e.g. if it's a GitHub project, it should have at least 100 stars and/or 50 forks)
[X] English interface (or at least English documentation)
[X] Latest stable version
[X] Full version (i.e. not a trial version)
[X] Fairly standard install (e.g. uses a version-specific download URL, no elaborate pre/post install scripts)

Name
PortableBuildTools
Description
Portable VS Build Tools installer
Homepage
https://github.com/Data-Oriented-House/PortableBuildTools
Download Link(s)
https://github.com/Data-Oriented-House/PortableBuildTools/releases/download/v1.6/PortableBuildTools.exe
Some Indication of Popularity/Repute
It has more than 100 stars on Github and also there is a good Youtube video for it:
https://www.youtube.com/watch?v=SRkD9TOIlCM

I have a manifest for this in my bucket.

I have a manifest for this in my bucket.

It reports page not found.

https://github.com/milnak/scoop-bucket/blob/main/bucket/portable-build-tools.json


CFE-3812: cfbs init now prompts user whether to use default masterfiles

The cfbs init command now prompts users whether or not they want to use
the default masterfiles policy framework. If the user says no, they're
prompted with which masterfiles they want to add, allowing them to skip
if empty.
Ticket: CFE-3812
Changelog: Title
Signed-off-by: Lars Erik Wik<EMAIL_ADDRESS>

So cfbs --non-interactive init now adds MPF? Is that what we want?

The option --non-interactive should probably perform the default behaviour?  In this case the question would be; should cfbs init add MPF by default? 🤔  What do you think @vpodzime @olehermanse?

So cfbs --non-interactive init now adds MPF? Is that what we want?

Yes

So cfbs --non-interactive init now adds MPF? Is that what we want?

The option --non-interactive should probably perform the default behaviour?  In this case the question would be; should cfbs init add MPF by default? 🤔

Yes and yes


We need List view (Scroll view ) in Phaser 3 for Leaderboard Scene

Please support ListView in Phaser 3 so we can make Leaderboard and high score easier!
Thank so much!

Grid/list table is a huge UI componment,
Here is a demo my grid table ui componment.

Closing this issue off, as it won't be added natively to Phaser 3 and there are great open-source alternatives available like those from rex.

Please support ListView in Phaser 3 so we can make Leaderboard and high score easier! Thank so much!

Hey @takaaptech you can use this Scroll list view from rex for now if you need.


Hardcoded font-size on .container

Describe the bug
There is hardcoded value for font-size on .container which prevents font variables to work properly.
To Reproduce
Go to line 394 of https://github.com/majalinet/Agile-CSS/blob/master/css/style.css
@media (min-width: 992px) {
  .container {
    max-width: 960px;
    font-size: 16px; /* should be removed */
  }
}

Expected behavior
Font-size should be removed from this rule.

Thanks, Vladimir Mincev,
You are right, It's already controlled here --font-size-desktop
I fixed it

Glad I could help. Have a great holidays!

Thanks again Vladimir for your help! Have a great hlidays too!


Onboard Microsoft.Chaos RP to dotnet SDK Release.

All SDK Contribution checklist:
This PR is to onboard Microsoft.Chaos, a soon-to-be public preview Azure RP, to the dotnet release.
Swagger for Microsoft.Chaos PR: https://github.com/Azure/azure-rest-api-specs/commit/1e00e8d52c5da01410e898db01c4954c7bd29ba5
link to swagger used to generate this sdk: https://github.com/Azure/azure-rest-api-specs/tree/main/specification/chaos/resource-manager/Microsoft.Chaos/preview/2021-09-15-preview
This checklist is used to make sure that common guidelines for a pull request are followed.

[ ] Please open PR in Draft mode if it is:

Work in progress or not intended to be merged.
Encountering multiple pipeline failures and working on fixes.

[x] If an SDK is being regenerated based on a new swagger spec, a link to the pull request containing these swagger spec changes has been included above.
[x] I have read the contribution guidelines.
[x] The pull request does not introduce breaking changes.

General Guidelines and Best Practices

[x] Title of the pull request is clear and informative.
[x] There are a small number of commits, each of which have an informative message. This means that previously merged commits do not appear in the history of the PR. For more information on cleaning up the commits in your PR, see this page.

Testing Guidelines

[x] Pull request includes test coverage for the included changes.

SDK Generation Guidelines

[x] The generate.cmd file for the SDK has been updated with the version of AutoRest, as well as the commitid of your swagger spec or link to the swagger spec, used to generate the code. (Track 2 only)
[x] The *.csproj and AssemblyInfo.cs files have been updated with the new version of the SDK. Please double check nuget.org current release version.

Additional management plane SDK specific contribution checklist:
Note: Only applies to Microsoft.Azure.Management.[RP] or Azure.ResourceManager.[RP]

[x] Include updated management metadata.
[x] Update AzureRP.props to add/remove version info to maintain up to date API versions.

Management plane SDK Troubleshooting

If this is very first SDK for a services and you are adding new service folders directly under /SDK, please add new service label and/or contact assigned reviewer.

If the check fails at the Verify Code Generation step, please ensure:

Do not modify any code in generated folders.
Do not selectively include/remove generated files in the PR.
Do use generate.ps1/cmd to generate this PR instead of calling autorest directly.
Please pay attention to the @microsoft.csharp version output after running generate.ps1. If it is lower than current released version (2.3.82), please run it again as it should pull down the latest version.

Note: We have recently updated the PSH module called by generate.ps1 to emit additional data. This would help reduce/eliminate the Code Verification check error. Please run following command:
  `dotnet msbuild eng/mgmt.proj /t:Util /p:UtilityName=InstallPsModules`

Old outstanding PR cleanup
Please note:
If PRs (including draft) has been out for more than 60 days and there are no responses from our query or followups, they will be closed to maintain a concise list for our reviewers.

/azp run

/azp run net - mgmt - ci


Refactor Hamming weight phasing to use QVR

fixes #1218

@tanujkhattar original author of these bloqs: are you good with the merger?

@tanujkhattar @anurudhp what's the status of this?

This has deviated too much from main, closing it for now. We can make a new refactor PR if needed


Get Rid of jQuery

@sushil-truemark , @mausam this is currently not in priority as we are working only on api and headless ecom..
We might want to revisit this should we require to work on frontend repo in future


Send Sentry reports on uncaught throws/exits

Fix #446
Previously PlugCapture would only catch exceptions. If there was an uncaught exit or throw, this would be ignored and Plug/Phoenix would end up send a 500 Internal Server Error to the clients with no notification to Sentry.

Thank you so much, this is perfect! 💖

Can this be released?  I just noticed this issue and I see that the latest sentry package is 8.0.4 from Nov 16th

@cheerfulstoic yep, thank you for the reminder and sorry for the delay. I've just pushed version 8.0.5 to hex.

🎉  ❤  Thanks!


(PDB-4449) travis: test against lein 2.9.1

While pdb doesn't require it yet, let's make sure it works, since
we'll need it for trapperkeeper 3+.

CLA signed by all contributors.


[QUESTION]:  It appears that scaffold splits always return the same splits

When I use the code below, I get the same splits regardless of random_state

i = 0
res = train_test_split_molecules(molecules=df.SMILES.values, return_indices=True, sampler='scaffold',random_state=i)

It might be useful to adopt the convention used by ChemProp, which enables different scaffold splits based on random_state
https://github.com/chemprop/chemprop/blob/master/chemprop/data/scaffold.py

A related followup.  I've been doing some experiments, and it appears that random, kmeans, and optsim respect the random_state variable, but scaffold, dbscan, and sphere_exclusion do not.  As such, it seems like the first three would be useful for examining multiple cross validation folds, but the second three would not.
Also, it seems like the behavior of train_test_split is different from the scikit_learn_implementation.  In sklearn, if random_state is not specified, it is assigned at random.  In your implementation, if random_state is unspecified, it's set to a default value, correct?

Hi @PatWalters! Thanks so much for trying out our package! We appreciate your questions and will try to get to the bottom of this.
Regarding your first question, we agree with you and also like Chemprop's implementation so our code only slightly modifies theirs (Chemprop fills the training set first while we fill the testing set first). We use the random seed to shuffle the clusters for all extrapolative sampling methods so the random state should make a difference. This happens during the call to get_sorted_cluster_counter
https://github.com/JacksonBurns/astartes/blob/main/astartes/main.py#L185
which ultimately runs this line
https://github.com/JacksonBurns/astartes/blob/main/astartes/samplers/abstract_sampler.py#L101
However, if the dataset is comprised of only a few clusters/scaffolds rather than many small sets of clusters/scaffolds, I can see how this could cause the behavior you're observing. As a simple conceptual example, if a dataset had only 3 clusters that comprised 50%, 30%, and 20% of the molecules, no amount of shuffling would change that 50% would go to train, 30% would go to val, and 20% would go to test (or however the user requested the split). In this case, the random state would appear to do nothing. One hypothesis is that the default hyperparameters for dbscan and sphere_exclusion are not creating enough small clusters for shuffling to have an impact.
Could you please share the dataset you were testing this with? I'd be happy to investigate this further to make sure our package is giving the expected behavior.

For your second question, yes that's correct. In the current state of our package, if the random seed is not explicitly specified by the user, we assign it to the same default value. There's pros and cons to this approach. The pro is that this approach prioritizes reproducibility by default. So even if someone is just quickly testing an idea and doesn't think to specify a random seed, they should get the same splits (and thus same ML model results), which should hopefully enable easier comparison and benchmarking. The con is that users would have to explicitly specify n different random states to obtain n different splits, such as for cross validation.
Thanks again for your questions! Please feel encouraged to share additional thoughts and feedback if we can make the package more intuitive.

Here's an example.
https://gist.github.com/PatWalters/c64d59c262ba1993d20af815cd5e0b5a
There are more than 30 Murcko scaffolds in the set.

Thanks @PatWalters for the thorough report and @kspieks for jumping in on this.
Kevin has thoroughly covered everything in the original question, the one thing I will add is to reiterate that we do set the random_state by default on every run (42, for the curious) to (1) force reproducibility and (2) encourage users to be very deliberate with their random seeding!
I'm going to review the linked PR and set it to automatically close this issue when merged, since I think should fix this issue by better defining the behavior. @PatWalters if the original question hasn't been answered or another one arises, please feel free to re-open this issue or start a new one!

Hi @PatWalters,
Thanks again for trying our package and identifying this bug that was affecting the train_test_split() function. train_val_test_split() was working fine but we accidentally didn't write a unit test for train_test_split(). Our apologies for that. After merging PR #164, both the train_test_split() and train_val_test_split() functions should work as intended and our unit test coverage is 97%. The new version has been automatically pushed to pypi and Zenodo so users should no longer encounter the issue raised here.
I re-ran your notebook with the latest main branch and it seems to give the expected behavior. I double checked that the generated train and test indices are unique. The notebook is attached below.
Let us know if you have additional feedback! Our goal is to provide an easy interface to several useful data splitting techniques so ML researchers can evaluate their models in both interpolative and extrapolative settings.
astartes_test_v2-Copy1.ipynb.zip

Thanks for the quick response and the fix.  I really like the package.  From a selfish perspective, I'd love to see more molecule-related splitting strategies.
Hierarchical splits
SIMD splits
MOOD splits
Neighbor splits (moving the compounds with the least number of neighbors to the test set)

We've found that sometimes the molecule-oriented splitters can have interesting effects on non-molecule data, so it's hardly selfish! Thanks for these suggestions!


drivers: i2c: i2c_nrfx_twi: Add return -EBUSY when I2C bus is in busy state

Return -EBUSY instead of -EIO when trying to access the I2C bus while it is currently used
Signed-off-by: Aurelien Vouaillat<EMAIL_ADDRESS>

Codecov Report

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The diff coverage is n/a.

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=========================================
  Coverage          ?   53.25%
=========================================
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  Lines             ?    26693
  Branches          ?     5924
=========================================
  Hits              ?    14216
  Misses            ?    10059
  Partials          ?     2418

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please fix the commit message:
1: UC5 Title exceeds max length (75>72): "drivers: i2c: i2c_nrfx_twi: Add return -EBUSY when I2C bus is in busy state"
3: UC4 Line exceeds max length (90>72): "Return -EBUSY instead of -EIO when trying to access the I2C bus while it is currently used"

Added the modification to i2c_nrfx_twim as well and reduced the length of commits messages


Create branches with different README for each project

@jeffmendoza

or, is it ok with having multiple README template with postfix?
For example
readme.md.appengine
readme.md.snippets
readme.md.compute
?

I think it's preferable to have it in branches as then we don't have to do extra work after cloning.

ah, good point

Do your project need documentation? I am ready to do it in my summers.

@elibixby, does this still need to be done?

I'm not sure this is relevant since we've moved to megarepos.

-Hello thank you so much for writing me can you Help me please
warm regards.
Raul.
2016-07-06 14:03 GMT-05:00 elibixby<EMAIL_ADDRESS>
I'm not sure this is relevant since we've moved to megarepos.
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You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/GoogleCloudPlatform/Template/issues/18#issuecomment-230872124,
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Some more rust rayon perf updates

cuts a few MS on my machine, give it a try.

They are pretty much equal on my machine.


Error when running npm install

npm ERR! Darwin 14.1.0
npm ERR! argv "node" "/usr/local/bin/npm" "install"
npm ERR! node v0.12.1
npm ERR! npm  v2.7.3
npm ERR! code EPEERINVALID

npm ERR! peerinvalid The package jest-cli does not satisfy its siblings' peerDependencies requirements!
npm ERR! peerinvalid Peer<EMAIL_ADDRESS>wants<EMAIL_ADDRESS>
npm ERR! Please include the following file with any support request:
npm ERR!     /Users/martijn/Development/react-datepicker/npm-debug.log

Can you run rm -r node_modules and try again? I can't reproduce.

Thanks, fixed!


Add extras for filetype workflow

Automate tests
Add extras for filetype workflow

This PR includes the other one in order to add the tests.
The indented usage is to import group_from_ft and then:
      vim.keymap.set("n", "<C-A>", dm.inc_normal(group_from_ft), { noremap = true })

It's a bit hacky but does not require internal changes, actually, it's the same I'm already doing locally.

I had to remove the <Plug> maps we can try to bring them back (do we actually nee them?) and probably some cleanup needs to be done, but I don't wanna proceed without your opinion.

I had to remove the <Plug> maps we can try to bring them back (do we actually nee them?)

<Plug> mapping is provided for those who want to easily configure dial.nvim with Vim script. Limiting it to a Lua-based interface is a reasonable choice, as dial.nvim is a Neovim-only plugin.
Note that removing the <Plug> mapping is a breaking change. We would like to have a certain period of time to publish a deprecation warning before merging.

Please clarify why the code around lua/dial/map.lua needs to be modified.

I will prefer not to have to change the map function, but the issue is that there you are composing a string to be used in the mapping but within a string you can't encode a lua closure. So I'm trying to replicate the behavior in pure lua.

The nvim_feedkeys function is difficult to predict the behavior, making debugging and maintenance hard.

Yes, but the . register is read-only, so I can't do  setreg('.', "g@"), I think the issue with the . in visual mode is the fact that I'm passing a feeding a motion. I will try doing it only in normal mode :thinking:  and see if that fixes it.
I'm sorry I forgot to test that use case.

The issue is not the motion, but anyway should not the  dial#operator#* family of operators use the position as passed by g@ ?

Now that I understand a little more what you want to achieve, I have created another PR, #56.
It is implemented using the :normal command as shown above. As far as I have tried at hand, dot repeat works well, but the count feature does not work.
The implementation is still in progress, but I think this approach is easier to achieve the function-based I/F.


Float Support

This adds float support (fixes #75).
Thanks, @SimonIT, for major help.
To do that, we decided on making FixedValue, RustType & ConceptualRustType only derive PartialEq.
This was done, because floats don't give all equivalence relations, as per the rust docs :tm: .
Still a draft because:

[ ] Panic on --preserve-encodings=true for floats.
[x] Ranges seam broken for floats.
Are as broken as everywhere else.
[x] I would like to test it some more.

But we would accept suggestions for the code and/or generated code.

Can this be marked as ready for review, or is there still a blocker?

Can this be marked as ready for review, or is there still a blocker?

We just decided to mark it as ready for review like 5 hours ago, but I had other things to attend to and forgot…


Version 10.2.0 Released

Hi Jocelyn,
Looks like version 10.2.0 has been released.
https://support.code42.com/Release_Notes/CrashPlan_for_Small_Business_release_notes#July_2022

I tried to download the latest build from today (twice), but it still says Version <IP_ADDRESS>3

Just 5 minutes ago. I tried both "Lates" and 2.17.1

Third attempt seems to have done the trick. I deleted the Crashplan cache directory for good measure in between.
Now it is up and running (synchronising) with version <IP_ADDRESS>

Great!


Fix command

Fix just do-it command in tutorial document

Summary by CodeRabbit

Documentation

Updated the command usage instructions in the Quickstart guide for consistency and clarity.

Thanks! Also fixed in #47


Fix ScoreboardPlayerUpdate packet

Description
Fix the contents of the ScoreboardPlayerUpdateS2c packet resolving #284.
Test Plan
Run the included playground code.

Playground
use valence::client::despawn_disconnected_clients;
use valence::client::event::default_event_handler;
use valence::prelude::*;
use valence::protocol::packet::s2c::play::scoreboard_objective_update::{Mode, RenderType};
use valence::protocol::packet::s2c::play::scoreboard_player_update::Action;
use valence::protocol::packet::s2c::play::{
    ScoreboardObjectiveUpdateS2c, ScoreboardPlayerUpdateS2c,
};
use valence::protocol::var_int::VarInt;

pub fn build_app(app: &mut App) {
    app.add_plugin(ServerPlugin::new(()))
        .add_system(default_event_handler.in_schedule(EventLoopSchedule))
        .add_startup_system(setup)
        .add_system(init_clients)
        .add_system(scoreboard)
        .add_system(despawn_disconnected_clients);
}

fn setup(world: &mut World) {
    let mut instance = world
        .resource::<Server>()
        .new_instance(DimensionId::default());

    for z in -5..5 {
        for x in -5..5 {
            instance.insert_chunk([x, z], Chunk::default());
        }
    }

    world.spawn(instance);
}

fn init_clients(
    mut clients: Query<&mut Client, Added<Client>>,
    instances: Query<Entity, With<Instance>>,
) {
    let instance = instances.get_single().unwrap();

    for mut client in &mut clients {
        client.set_instance(instance);
    }
}

// Add new systems here!
fn scoreboard(mut clients: Query<&mut Client, Added<Client>>) {
    for mut client in &mut clients {
        client.write_packet(&ScoreboardObjectiveUpdateS2c {
            objective_name: "test",
            mode: Mode::Create {
                objective_display_name: "test display".into_text(),
                render_type: RenderType::Integer,
            },
        });
        client.write_packet(&ScoreboardPlayerUpdateS2c {
            action: Action::Update {
                objective_score: VarInt(0),
                objective_name: "test",
            },
            entity_name: "name",
        });
        client.write_packet(&ScoreboardPlayerUpdateS2c {
            action: Action::Remove {
                objective_name: "test",
            },
            entity_name: "name",
        });
    }
}

Just ran this, doesn't crash my client.


Just a thought...

Nice project!
When i saw it i thought immediately about using RGB-Leds with an integrated controller.
Like this one: https://jlcpcb.com/partdetail/Xinglight-XL_1010RGBCWS2812B/C5349953
It is a tiny bit wider (0,5mm) and costs a bit more then the LED you used but you would save the MAX7219 and a lot of pins for connecting it to an MCU.

Hey, any chance u could share an arduino sketch sample how to address them ?

Search for ws2812b + arduino and you'll find a lot of examples...


[Edit Docs] Update incorrect import statements

Description
Updated incorrect import statement found in the hello-stacks tutorial. "AuthDetails" was to be imported from @stacks/connect and based on this console message in my browser:

it does not exist. Further down in the tutorial "openContractCall" is correctly shown to be imported instead. (Line 513)
Removed 2 semicolons that resulted in the build to fail.
Updated a semi-unclear instruction seemingly telling the user to add the Mocknet network twice in the file.

 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.You have signed the CLA already but the status is still pending? Let us recheck it.


Dry run option not doing anything with register-component-version command

Problem
mach-composer cloud register-component-version test-component --organization <org> --project <project> 1234 --dry-run actually performs the command and applies it in MACH cloud, and doesn't do a dry run.
Versions tested
v2.19.0
v2.17.1

Double-checked the code, and looks like dry-run is only used when we run it in auto-mode (--auto). Auto adds the commits to the version.  When it is not in auto-mode it will only create a new component version with version and branch. I will update that to log the same line we do in --auto (but without the commits it found)


MINOR: Remove unused StreamsGraphNode#repartitionRequired

I found this defect while inspecting KAFKA-7293: Merge followed by groupByKey/join might violate co-partitioning; This flag is never used now. Instead, KStreamImpl#repartitionRequired is now covering its functionality.
cc/ @mjsax
Committer Checklist (excluded from commit message)

[ ] Verify design and implementation
[ ] Verify test coverage and CI build status
[ ] Verify documentation (including upgrade notes)

Ping @bbejeck for second review.

retest this please

Java 8 failure kafka.api.AdminClientIntegrationTest.testMinimumRequestTimeouts
Java 11 failure kafka.api.SaslSslAdminClientIntegrationTest.testMinimumRequestTimeouts
retest this please

Java 8 passed, Java 11 failed
kafka.api.ClientIdQuotaTest.testThrottledProducerConsumer
kafka.api.PlaintextConsumerTest.testMaxPollRecords

retest this please

Rebased against the latest trunk.

Java 8 failed kafka.api.AdminClientIntegrationTest.testMinimumRequestTimeouts , Java 11 passed this time.
retest this please

Java 8 passed, Java 11 failed (results already gone)
retest this please

Java 8 passed, Java 11 failed kafka.cluster.PartitionTest.testDelayedFetchAfterAppendRecords
retest this please

retest this please

merged #6227 to trunk

Thanks @dongjinleekr for the contribution!


Select leaderboard submission rule from competition.yaml

The leaderboard submissions rule is a crucial feature of Codabench:

It seems that it can only be selected from the editor. Indeed, no fields are mentionned in the Wiki (YAML Structure) and it seems to be left for later in the code:
LEADERBOARD_FIELDS = [
    'title',
    'key',
    'hidden',

    # For later
    # 'force_submission_to_leaderboard',
    # 'force_best_submission_to_leaderboard',
    # 'disallow_leaderboard_modifying',
]

In https://github.com/codalab/codabench/blob/develop/src/apps/competitions/tasks.py

By the way, the current default rule is "ADD":
https://github.com/codalab/codabench/blob/46f68ee91511a79d10fab817ca1164e35cd32d58/src/apps/leaderboards/models.py#L28
Is that what we want?

EDIT: I found have to use it actually:
# Leaderboard
leaderboards:
- index: 0
  title: Results
  key: Results
  submission_rule: "Force_Last"

I will update the documentation accordingly.


md-radio labelPosition doesn't do anything

BUG
[labelPosition] inputs of radio buttons or groups should have some effect...?
https://plnkr.co/edit/kc9Eyzlgdc5QeLyHgKTC?p=preview

Remove the square brackets. With the brackets there, you are attempting to bind to variables called 'before' and 'after'. see here

ah right sorry


promenu: fix removal of final menu item

A small bug that crept in as part of #3416

Tested for a day or two, no issues


Keras: near-future directions

Here are a few things I think would be valuable to add to Keras in the near future.
These are mere suggestions. You are welcome to discuss them, contest them, add your own ideas... I would like the development of Keras to be increasingly driven by the community. I don't want to be a bottleneck of development.
I won't be writing code myself, but I will happily give feedback and advice to any contributor who wants to tackle some of these features. I will also keep reviewing and merging PRs.
Here's a list of features. Their focus is on simplicity and user experience.

Automatic tensor shape inference. We should be able to add layers to a Sequential mode or a Graph model without having to worry about input shapes.
Introduction of Input layers as part of the above, to define expected input data dimensions.
Ability to re-initialize layer weights without re-compiling a model.
New API for the Graph container. Some thoughts here. As part of this change I believe we should get rid of the add_input and add_output methods, which are cumbersome. A single add method should suffice.
Thorough checking of assumptions made about user-provided constructor arguments throughout the codebase, and raising helpful and clear error messages when some assumptions aren't respected. Ideally no error will ever be raised by Theano, because we will be catching everything on the Keras side. This will make debugging of Keras models much faster and easier.
Abstracting all references to Theano functionality to a Keras backend. This will allow us to implement non-Theano backends in the near future (for instance, based on Nervana's Neon library), that could be readily plugged into Keras in a seamless way. This will allow Keras to keep up with new advances in symbolic tensor libraries (Neon, CGT, etc...)

@fchollet How would You like to deal with the add_input method?
All unused names in the namespace are considered inputs?

@elanmart that would be way too implicit. No, it's actually really simple: after we introduce an Input layer (which is necessary for automatic tensor shape inference), you don't need to mark certain layers as inputs via something like add_input.

Ability to re-initialize layer weights without re-compiling a model.

Don't forget this also means re-initialize the optimizer (for adam, rmsprop and other moving averages).

Abstracting all references to Theano functionality to a Keras backend.

How would you train models with different backends though? You pick and choose one at a time right?
I would also suggest a better way of dealing with desired output shapes. Right now, Keras implicitly assumes the desired is either a matrix (samples x dim) or a tensor3 (samples x time x dim). I had an image as desired and it took me days (partially my bad though) to realize what was wrong, my (samples x rows x cols) was being reshaped as (samples-rows x cols) without warning. This is really dangerous since the method just compiled and ran like nothing was wrong.

@EderSantana right, I also think a simplified and more intuitive way of applying loss functions, masks and weights would be welcome.

Also I think we should be able to implement any neural network easily using Keras backend API only without complicated theano codes (for instance, implementing GRU with keras api only like #620 )

Yes, the recurrent Container would be great to have. It could really speed up experimenting with different RNN architectures.

First, I'll apologize for not completing the caffe PR yet. I'll try to do it over the weekend.
Maybe some of the things done in Caffe PR could be used in shape inference and inferring input and output nodes?
The very first and bad implementation of non sequential models that I wrote did something like that - fallback to recently added layer if previous node is not explicitly mentioned.

Automatic tensor shape inference

I have started doing this in my fork because current way of using convolutional layers is too difficult. I can do the same with all layers and make a PR.

@matsuyamax in your solution can the user still define the shapes himself and continue compatible with the current API?

@EderSantana I don't think compatibility can be achieved if we make input dimensions optional, because they are not keyword arguments. Constructor of convolutional layers looks like this:
def __init__(self, input_dim, nb_filter, filter_length, init='uniform', activation='linear', ...)

Currently we use it like this:
layer = Convolution1D(input_dim, nb_filter, filter_length, init='uniform', activation='linear', ...)

We want to make input_dim optional, to use it like this:
layer = Convolution1D(nb_filter, filter_length, init='uniform', activation='linear', ...)

That's not possible with compatibility.

@matsuyamax that would be bad I think. Sometimes we just need a quick layer and skip the lazy-initialization that inferred shapes would impose. What if input_dim is optional and the inferred value has the last word? Like, for example, lets assume the Dense layer
class Dense(Layer)
    def __init__(output_dim, input_dim=None, *args, **kwargs):
        self.input_dim = input_dim
        self.output_dim = output_dim
        self. ...
        ...

        self.initialize()

    def initialize(self):
        if self.input_dim is None:
             raise ValueError("Using lazy initialization, either define `input_dim` or set a `previous_layer`)
        else:
             self.W = self.init((self.input_dim, self.output_dim))
             self.b = shared_zeros((self.output_dim))

    def set_previous(self, layer)
            self.previous = layer
            if self.input_dim is None:
                self.input_dim = layer.output_dim
            elif self.input_dim != layet.output_dim:
                warn("Overwriting `input_dim` of layer {}. The user defined parameter differs from what we inferred".format(self.name))

This way, I would not be forced to define two layers (input and output) in the cases where I need only one of them.

This way, I would not be forced to define two layers (input and output) in the cases where I need only one of them. What do you think?

I agree, but your solution breaks compatibility too. You see what I mean?
We could do your solution, but then we would have to implement input shape management in every layer __init__. maybe it would be simpler to do like:
layer = Dense(output_dim)
layer.set_input_shape(input_shape)

or
layer = Dense(output_dim)
layer.input_shape = input_shape

Then we would have a single method common with all layer.

The major problem with shape inference is that the layer objects are created first and then added to the model. So, at initialization, the object has no idea whether it will receive an input dimension or should it raise an error.
The way I did this was to basically split up the current initialization method into two parts and calling the second part (the one where parameters are initialized) after the layer has been added to the model.
Backwards compatibility is possible, the code just gets ugly. input_dim will be the first argument with defaults. We would then have to swap the arguments cleverly. If  input_dim is None , shape has to be inferred. If it's not None ,  it has been provided and the user view would have it as first argument. So you'd have to essentially rotate the first few arguments and input_dim right.

I also think a simplified and more intuitive way of applying loss functions, masks and weights would be welcome.

Loss functions could be reduced to layers.

TL;DR Maybe we should expose less OOP and makes things even easier to use.

Loss functions could be reduced to layers.

The more layers we introduce, the longer it will take to write a model and start training it. One of the things I like the most about Keras is that you can actually memorize all the steps to write a model, compile and run the experiment. If we introduce too much boilerplate, like a layer for input, a layer for the cost, lazy only initialization, etc. we are going to be just another Blocks and we will always have to go back to copy paste from the documentation to do anything. I'm not saying Blocks is bad, I used to contribute to it as well. I'm just saying that we don't need another Blocks.
What do you think? I honestly believe that this simple API is a huge PLUS about Keras. That is why it is more popular than Blocks or Lasagne which were started almost at the same time. I'm not saying we should just appeal to the masses, I'm saying that simple is the ultimate sophistication and I believe Keras did it and we shouldn't go back. Maybe the solution is in the direction of less OOP not even more OOP. I also think that progress means making things even easier to use, like an optional lazy initialization or easier to develop RNNs.
For the case of losses, the reshaping and masking should go inside the objective. This would give the user more control when necessary, without making to hidden. For example, the mse cost would just be
def mse(y_true, y_pred):
    return T.sqr(y_true.flatten(ndim=2) - y_pred.flatten(ndim=2)).mean(axis=-1)

In other words the reshaping goes inside the objective, and we never collapse data dimensions with the first samples dimensions. For masking we could have an extra optional parameter
def mse(y_true, y_pred, mask=None):
    if mask is None:
        return T.sqr(y_true.flatten(ndim=2) - y_pred.flatten(ndim=2)).mean(axis=-1)
    else
        cost = T.sqr(y_true.flatten(ndim=2) - y_pred.flatten(ndim=2)) * mask
        return cost.sum(axis=-1) / mask.sum(axis=-1)

where mask would have the same shape as the desired. Sorry for the long comment.

I think loss layers are a great idea that would add flexibility add make it easier to implement things like hierarchal softmax or NCE cost. I believe they would also simplify masking.

One of the things I like the most about Keras is that you can actually memorize all the steps to write a model, compile and run the experiment.

I agree. Being able to build networks by heart after using Keras a few times is proof that it does a good job at reducing cognitive load, and we want to keep that. Deep learning should be like playing with Duplo blocks and coloring with crayons.
We can back off the idea of having Input layers, I agree they seemed quite a bit boilerplatey. But then what would we use?
I guess we could have an input argument input_shape and it could be handled by the super __init__ of the base layer class so we don't have to reimplement logic in every layer like @matsuyamax points out. I would be fine with that. Other ideas?

I think loss layers are a great idea that would add flexibility add make it easier to implement things like hierarchal softmax or NCE cost. I believe they would also simplify masking.

It don't think it's necessary to have object losses, because losses don't have a state, unlike optimizers and layers. Everything you could do with a loss layer, you should be able to do it with a loss function.
Also, if it's a loss layer then it's not a layer. Layers only access the previous layer's input.

For example, the mse cost would just be

Sure, but what of masking and weighting?

Maybe the solution is in the direction of less OOP not even more OOP.

OOP is a big part of what made Keras successful and it is the most appropriate paradigm for deep learning, where modules are stateful (e.g. layers).

@fchollet

But then what would we use?

We just have to enforce an input_dim in the first layer. Then everything else follows smoothly. Even when the other input_dim are being inferred. See my discussion with @matsuyamax above.

Sure, but what of masking and weighting?

I showed an example of how to do masking above.
This does not need to be repeated on every layer necessarily. We could write a generic decorator that does the masking
def mask_decorator(func):
    @wraps(func)
     def wrapper(y_pred, y_true, mask, sample_weight):
         cost = func(y_pred, y_true)
         cost = cost[sample_weight]
         if mask is None:
             return cost.mean(axis=-1)
         else:
             mask = mask[sample_weight]
             return cost.sum(axis=-) / (mask.sum(axis=-1) + 1e-7)

OOP is a big part of what made Keras successful and it is the most appropriate paradigm for deep learning, where modules are stateful (e.g. layers).

I agree, we just don't have to force the user to always define classes to be able to use Keras. Sequential and Graph allow us to do that. We can create new cost functions and new inputs without having to define whole new class for it.

decorators are not super intuitive tho... Thoughts?

Adding output shape inference to all layers has given me to occasion to dive deeper into the repo. Here are some thoughts about the code in general. I think the code has potential, but several issues need addressing.

All layers should have a set_name method, not just Dense.
core.RepeatVector should use broadcasting, currently it is copying input data and that is inefficient.
Same for convolutional.UpSample2D.
Every layer should specify input/output shape in docstring (like what keras.io does).
All layers need proper docstrings with descriptions of what the layer does, what the arguments are.
Online documentation should mirror docstrings. Otherwise the online documentation risks getting outdated and the docstrings risk not being informative enough (which they currently are).
Reshape should take a tuple as argument.
layers.core is too long. Should be broken down in a few files.
All layers should be importable from a single module, keras.layers.
Why is there a ZeroPadding2D layer but not ZeroPadding1D?
Small inconsistency in MaxPooling1D/2D: poolsize vs. pool_length. Should probably be pool_size.
Convolution1D and Convolution2D should use a stride argument instead of subsample (which is not standard).
Inconsistency in handling of get_output for Convolution1D and Convolution2D: Convolution2D uses a hack for cuDNN bot not Convolution1D.
Tests take too long to run. Most of them are not real unit tests and more like holistic tests. It's good to have both but the time impact of the latter should be minimized.

We could write a generic decorator that does the masking. If I didn't get my syntax wrong, it should be something like

It would be a rather elegant solution. I'm all for it.

Small inconsistency in MaxPooling1D/2D: poolsize vs. pool_length. Should probably be pool_size.

I would be fine with such a change.

Reshape should take a tuple as argument.

Again, this is fine.

Why is there a ZeroPadding2D layer but not ZeroPadding1D

Feel free to add it.

A few comments:

Why is there a ZeroPadding2D layer but not ZeroPadding1D

Feel free to add it.

What about adding support for Convolution3D and ZeroPadding3D as well. I think I have this working in my fork.
In the same fork, I have added support to freeze layers. This now works for Graph as well and the trainable can be serialized. Maybe this is something to include in the main Keras?

I would also suggest a better way of dealing with desired output shapes. Right now, Keras implicitly assumes the desired is either a matrix (samples x dim) or a tensor3 (samples x time x dim). I had an image as desired and it took me days (partially my bad though) to realize what was wrong, my (samples x rows x cols) was being reshaped as (samples-rows x cols) without warning. This is really dangerous since the method just compiled and ran like nothing was wrong.

I lost quite some time time on that one too. Reshaping should definitely be inside the objective function.

Convolution1D and Convolution2D should use a stride argument instead of subsample (which is not standard).

Another nice addition would be an upsample mode (or "deconvolution"). This is particularly useful for image segmentation (see here and here).

Another nice addition would be an upsample mode (or "deconvolution").

We have UpSampling1D and 2D layers, I think this is what you are looking for.

In the same fork, I have added support to freeze layers. This now works for Graph as well and the trainable state can be serialized. Maybe this is something to include in the main Keras?

Possibly. You can submit a PR and I will review it.

What about adding support for Convolution3D and ZeroPadding3D as well? I think I have this working in my fork.

Certainly. We already have a PR with Convolution3D undergoing review, you might want to review it to make sure you're on the same page.

Ability to re-initialize layer weights without re-compiling a model.

I would love to see that. I would like to use Keras in for "online" predictions while training is done "offline". Right now I use the save / load procedure as described in the FAQ but it takes rather long (approx 1 min) to load everything until a prediction on new data can be made.

@holderm : you can already do so. Let's say you have a compiled model in production and you would like to update it (to sync it with an identical model that you've just finished training somewhere else). You can just dump the weights of your newly trained model to HDF5, and load them in your production without recompiling, just via save_weights and load_weights. This takes a few hundred milliseconds for a large model.

Yes, that's true but assume training and prediction take place in different sessions, so one needs to compile the (previously trained) model before predictions can be made.

Another nice addition would be an upsample mode (or "deconvolution").

We have UpSampling1D and 2D layers, I think this is what you are looking for.

I was more thinking of a straight "reverse" of the convolution in a single layer like the one in Caffe or MatConvNet. This is more efficient than a upsampling + convolution.

Yes, that's true but assume training and prediction take place in different sessions.

As long as you have a compiled model with the same architecture living in each session, you will be fine. But if you don't, the model re-initialization feature we will add is not going to help you anyway.

Here is what I think we should go for the Graph API:

No more inputs and input arguments, instead, a single inputs argument that could be a string or a list of strings.
A single .add(name, layer, inputs, **kwargs) method. When no inputs argument is provided, the layer is assumed to be an input layer. If is_output is set to True, an output node is created.

Also untrainable outputs would be nice. Such as returning the output of intermediate layers in the predict() function but without having to actually define a 0 loss function for them and slow down the training procedure.

Here is what I think we should go for the Graph API:

I am not so sure anymore about this. This will require more design work. We'll post-pone it for now.

If i recall, There was some issues about polymorphism right? With having input being a variety of data types

If i recall, There was some issues about polymorphism right? With having input being a variety of data types

I think having input support a variety of input modes (name, list of names, dict {output_name: input_name}) would be a much better UX than having separate keyword args for all these.
The thing I am less sure of is the removal of add_input and add_output.

@fchollet any new thoughts on the Graph API? Maybe input argument shouldn't have a default value, and input would be created only if None is passed?
Also, are there any plans to implement a base class for multi-io layers?
I assume that if they were to be implemented in Keras, they would have an outputs property (being a list of Layers) just as Graph does?


Improved loading

Fixes Issue #1104
Changes proposed

Go through each and every folder
Changed the path to webp
Improved loading

Screenshot (loading time difference)
Original

Updated

Check List (Check all the applicable boxes)

[ x] My code follows the code style of this project.
[ ] My change requires changes to the documentation.
[ ] I have updated the documentation accordingly.
[x ] All new and existing tests passed.

Hey @MonalikaPatnaik Please review it once


Unfortunately IAMRole.RoleName doesn't exist, so output ARN instead

This is a follow on from https://github.com/buildkite/elastic-ci-stack-for-aws/pull/428.
@dblandin unfortunately IAMRole.RoleName doesn't exist, so we'll have to settle for the ARN.

I'm going to merge this as the master build is broken currently.

If you want the role name, just !Ref it.

If you want the role name, just !Ref it.

How did I not think of this. 😓Thanks @holmesjr


Document: Component-Definition Generation

Research and documentation for how Lula will generate and operate on component-definition's.
Objective
Establish a document for component-definition that evolves as research develops around:

The purpose of a component-definition generically
Derivation of controls to a component from a catalog
How Lula performs this mapping during generation
Expectations for hybrid (automation/manual) authorship of the artifact

Consider this a research spike that also educates/informs others about opinionation of Lula workflows. Human readable format means a lower barrier to entry for external expertise to evaluate and challenge assumptions.

Completed in #401


Enhancement: Segmentation of namespace mx.sym

With ongoing development, having a flat list of operators in mx.sym becomes cumbersome. There will be more and more closely related groups of operators for support of certain special types of computations and I think we should reflect that in terms of different namespaces for operators for

easier navigation and usage
keeping development of operators more consistent (by forcing them to belong to a certain namespace and therfore  to comply in interfaces/functionality with the other operators in that namespace).

Some examples of such namespaces:
mx.sym.random (for all random sampling methods)
mx.sym.la  (for all advanced single/double precision linear algebra as matrix decompositions etc)
I think that can improve the outside perception of MXNet by the user community.

This issue is closed due to lack of activity in the last 90 days. Feel free to reopen if this is still an active issue. Thanks!


CM-2687 - Introduce go modules

see related: ChannelMeter/cm-go-api#465

Closing as don't seem to impact builds


test PR

don't merge

Current coverage is 56.80%

Merging #1 into master will not affect coverage as of cd5ea2c

@@            master     #1   diff @@
=====================================
  Files           31     31
  Stmts         1961   1961
  Branches         0      0
  Methods          0      0
=====================================
  Hit           1114   1114
  Partial          0      0
  Missed         847    847

Review entire Coverage Diff as of cd5ea2c

Powered by Codecov. Updated on successful CI builds.

I need to come back to this before I forget what I was doing...


Fixed cart rule condition input fields ui

Issue Reference
Fixed cart rule condition input fields ui

@shivendra-webkul
Please check there are some conflicts in the PR. Resolve them.


Test failure: ClosesAfterDataSent

This test fails occasionally with the following error:
Assert.Contains() Failure
Not found: Server: Microsoft-IIS/10.0
In value:  List<String> ["Transfer-Encoding: chunked", "Server: Microsoft-IIS/8.5", "Date: Wed, 19 Sep 2018 05:57:23 GMT", ""]
   at Microsoft.AspNetCore.Server.IntegrationTesting.TestConnection.ReceiveHeaders(String[] lines) in /_/test/Common.Tests/Utilities/TestConnections.cs:line 204
   at Microsoft.AspNetCore.Server.IISIntegration.FunctionalTests.ResponseAbortTests.ClosesAfterDataSent() in /_/test/IIS.Tests/ResponseAbortTests.cs:line 57
--- End of stack trace from previous location where exception was thrown ---
------- Stdout: -------
| [0.001s] TestLifetime Information: Starting test ClosesAfterDataSent at 2018-09-19T05:57:21
| [2.046s] Microsoft.AspNetCore.Server.IISIntegration.FunctionalTests.TestServer Debug: Method: GET, RequestUri: 'http://localhost:58636/start', Version: 2.0, Content: <null>, Headers:
|                                                                                {
|                                                                                }
| [2.051s] Microsoft.AspNetCore.Hosting.Internal.WebHost Debug: Hosting starting
| [2.052s] Microsoft.AspNetCore.Hosting.Internal.WebHost Debug: Hosting started
| [2.052s] Microsoft.AspNetCore.Hosting.Internal.WebHost Debug: Loaded hosting startup assembly IIS.Tests, Version=<IP_ADDRESS>, Culture=neutral, PublicKeyToken=adb9793829ddae60
| [2.053s] Microsoft.AspNetCore.Hosting.Internal.WebHost Information: Request starting HTTP/1.1 GET http://localhost:58636/start
| [2.053s] Microsoft.AspNetCore.Hosting.Internal.WebHost Information: Request finished in 0.4561ms 200
| [2.054s] Microsoft.AspNetCore.Server.IISIntegration.FunctionalTests.TestServer Debug: StatusCode: 200, ReasonPhrase: 'OK', Version: 1.1, Content: System.Net.Http.HttpConnection+HttpConnectionResponseContent, Headers:
|                                                                                {
|                                                                                Transfer-Encoding: chunked
|                                                                                Server: Microsoft-IIS/8.5
|                                                                                Date: Wed, 19 Sep 2018 05:57:23 GMT
|                                                                                }
| [2.054s] Microsoft.AspNetCore.Server.IISIntegration.FunctionalTests.TestServer Debug: Done
| [2.056s] Microsoft.AspNetCore.Hosting.Internal.WebHost Information: Request starting HTTP/1.1 POST http://localhost/  1
| [2.072s] Microsoft.AspNetCore.Hosting.Internal.WebHost Debug: Hosting shutdown
| [302.073s] Microsoft.AspNetCore.Hosting.Internal.WebHost Information: Request finished in<PHONE_NUMBER>ms 200
| [303.446s] TestLifetime Information: Finished test ClosesAfterDataSent in 303.442544s

Other tests within that build may have failed with a similar message, but they are not listed here. Check the link above for more info.
This test failed on 2.2.
CC @muratg
This issue was made automatically. If there is a problem contact ryanbrandenburg.

Please use this workflow to address this flaky test issue, including checking applicable checkboxes and filling in the applicable "TODO" entries:

Is this actually a flaky test?

No, this is a regular test failure, fix the test/product (TODO: Link to commit/PR)
Yes, proceed below...

Is this test failure caused by product code flakiness? (Either this product, or another product this test depends on.)

[ ] File a bug against the product (TODO: Link to other bug)
Is it possible to change the test to avoid the flakiness?

Yes? Go to the "Change the test!" section.
No?

[ ] Disable the test (TODO: Link to PR/commit)
[ ] Wait for other bug to be resolved
[ ] Wait for us to get build that has the fix
[ ] Re-enable our test (TODO: Link to PR/commit)
[ ] Close this bug

Is it that the test itself is flaky? This includes external transient problems (e.g. remote server problems, file system race condition, etc.)

Is there is a way to change our test to avoid this flakiness?

Yes? Change the test!

[ ] Change the test to avoid the flakiness, for example by using a different test strategy, or by adding retries w/ timeouts (TODO: Link to PR/commit)
[ ] Run the test 100 times locally as a sanity check.
[ ] Close this bug

No?

Is there any logging or extra information that we could add to make this more diagnosable when it happens again?

Yes?

[ ] Add the logging (TODO: Link to PR/commit)

No?

[ ] Delete the test because flaky tests are not useful (TODO: Link to PR/commit)

This comment was made automatically. If there is a problem contact ryanbrandenburg.

ClosesAfterDataSent failed with about the same error on 2.2.
This comment was made automatically. If there is a problem contact ryanbrandenburg.


[WIP] Fixed #24726 -- Fix SQL Generation for ArrayField(RangeField)

@mjtamlyn asked that I open this PR. I feel that I'm in a bit over my head with this one. Work from others is welcome!
Discussion here: https://code.djangoproject.com/ticket/24726

I guess we'll close this for now given the lack of activity.

@timgraham I agree that closing this for now makes sense. I hope whoever is deep in the Django/PostgreSQL side of things can eventually take a look. @mjtamlyn or maybe someone else?
Thanks!


Icons disappeared

Describe the bug
Icons are not loading/showing
Steps to Reproduce
I have 2 places that I use these icons and they are not populating
Expected behavior
I expect them to show up
Screenshots

The blank spaces are where the icons usually populate as links.
Context (please complete the following information):

Additional notes

I also have the same issue where the icons are not showing

I was informed that switching out from

to

Seems to have fixed the issue

@msfoxett this is a result of a different version of the icon font being loaded in your page – either icon names or the unicode codepoints they are represented by have changed between versions. In general you should always pin phosphor to a specific version number to keep this from happening, and to take advantage of a single version being cached in the user's browser and therefore loading much faster.
Since v2.1.0 we have stabilized the codepoints so they won't change, meaning future versions will be backwards-compatible with the current version. But I still recommend choosing a version explicitly, and checking the icons whenever you make an upgrade. I'll update the README here to reflect this.


[feature] Add support for different or custom address icons.

What problem does this new feature solve?
We are currently restricted to a metallic ball looking icon.

Describe the solution you'd like
It would be nice if we had other options, or even better, allow us to set a custom component alltogether.

Useful library: https://github.com/bpierre/blo


service.sp.authn_requests_signed=True causes bytes/str-related TypeError on Python 3

This is because binding automatically gets set to HTTP-POST in this case (views.py:143), which leads to this line of code in views.py:207:
'SAMLRequest': base64.b64encode(request_xml),

which fails with TypeError because request_xml is a str, not bytes.
Additionally, if I fix this line to 'SAMLRequest': base64.b64encode(request_xml.encode('utf-8')), I get this error:
TemplateDoesNotExist at /saml2/login/
djangosaml2/post_binding_form.html

There is an example_post_binding_form.html in the folder, but the template path is not configurable. If I copy it over to post_binding_form.html, things start working and requests are signed.

Why is POST binding preferred over REDIRECT in this case? URL length considerations? Can this be configurable?
Let's fix the TypeError
Can the template path be configurable (and working by default, even if as plain as the example template is) ?

Thanks a lot!

Fixed in 0.16.0.


Hide overload from intellisense

https://github.com/Azure/azure-sdk-for-net/issues/30105

API change check
APIView has identified API level changes in this PR and created following API reviews.
Microsoft.Extensions.Azure


Split JS and HTML apart

This is a tracking issue for splitting the HTML and JS in the bundle apart.
Currently, JS is inlined into the HTML using a very simple line-based preprocessor.
The JS bundle size is 22.7kb, of which 18.4kb is the list of Wordle solution words.
The Html file size is about 3.6kb - 2.6kb in the template, 1kb of server side rendered DOM nodes.
The total bundle size is 26.3 kb.
We could split the JS into a separate bundle, I tested it out today by adding this to the head:
<script async defer src="./index.js"></script>
And of course removing the script at the bottom of the file.
Results were not encouraging. The page load time (DCL) didn't move, still around 130ms. All this does is turn Parse HTML time into Compile Script time.
Still, separating into a JS bundle has advantages, like being able to provide source maps. Will have to add some code to detect script load errors as inline JS into the html.
At any rate, this is on the backlog for now.

Some thoughts: Since we SSR the nodes, the user can load the page without loading JS. So in theory what I'd like is for the whole Paint / Render Tree / Layout cycle to finish, before we start compiling and evaluating the JS.
The compiling is what takes the most time (~5ms), the evaluation finishes really quickly since V8 is amazing.
Unfortunately defer on scripts defers the evaluation, not the compilation.


Install FFMpeg

$ heroku buildpacks:add https://github.com/shunjikonishi/heroku-buildpack-ffmpeg
!    You do not have permission to manage articles2podcast. Only the app owner, nick, can do that.

$ heroku buildpacks:add https://github.com/shunjikonishi/heroku-buildpack-ffmpeg
Buildpack added. Next release on articles2podcast will use:
  1. https://github.com/heroku/heroku-buildpack-php
  2. https://github.com/shunjikonishi/heroku-buildpack-ffmpeg
Run `git push heroku master` to create a new release using these buildpacks.


Google Chrome: Go to Address Bar and press enter to go to that Address

Extension – google-chrome

Author: @rgomezcasas

Describe the feature and the current behavior/state.
Similar to pressing CMD + L in Chrome it moves to the search/address bar and can enter a URL and go to that URL

cc: @rgomezcasas

+1, would be great to have this.

+1, would be great to have this.


Building on M1 Mac OS does not work

Disclaimer: I do not understand cython builds well.
When I try to install crick from source on my M1 Mac, I get error messages that seem to indicate that the M1 architecture is confusing the build system into thinking it's Windows and then Windows build tools clearly aren't available. My reason for thinking this is related to M1 Macs is that the CI is currently successfully running pip install --no-deps --global-option build --global-option --debug -e . on Linux, Mac OS, and Windows.

M1 build errors (`pip install -e .`)

14:18:39 in crick on  fix-skew-kurt-edge-cases [+?] via 🅒 crick-dev
➜ pip install -e .
Processing /Users/paul/work/sources/crick
  Preparing metadata (setup.py) ... done
Building wheels for collected packages: crick
  Building wheel for crick (setup.py) ... error
  error: subprocess-exited-with-error

  × python setup.py bdist_wheel did not run successfully.
  │ exit code: 1
  ╰─> [31 lines of output]
      /Users/paul/work/sources/crick/setup.py:4: DeprecationWarning:

        `numpy.distutils` is deprecated since NumPy 1.23.0, as a result
        of the deprecation of `distutils` itself. It will be removed for
        Python >= 3.12. For older Python versions it will remain present.
        It is recommended to use `setuptools < 60.0` for those Python versions.
        For more details, see:
          https://numpy.org/devdocs/reference/distutils_status_migration.html

        import numpy.distutils.misc_util as np_misc
      running bdist_wheel
      running build
      running build_py
      copying crick/_version.py -> build/lib.macosx-11.0-arm64-cpython-39/crick
      copying crick/__init__.py -> build/lib.macosx-11.0-arm64-cpython-39/crick
      copying crick/tests/test_stats.py -> build/lib.macosx-11.0-arm64-cpython-39/crick/tests
      copying crick/tests/test_space_saving.py -> build/lib.macosx-11.0-arm64-cpython-39/crick/tests
      copying crick/tests/test_tdigest.py -> build/lib.macosx-11.0-arm64-cpython-39/crick/tests
      UPDATING build/lib.macosx-11.0-arm64-cpython-39/crick/_version.py
      set build/lib.macosx-11.0-arm64-cpython-39/crick/_version.py to '0.0.3+6.g2e827d2.dirty'
      running build_ext
      building 'crick.tdigest' extension
      Warning: Can't read registry to find the necessary compiler setting
      Make sure that Python modules winreg, win32api or win32con are installed.
      INFO: C compiler: clang -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -fwrapv -O2 -Wall -fPIC -O2 -isystem /Users/paul/mambaforge/envs/crick-dev/include -arch arm64 -fPIC -O2 -isystem /Users/paul/mambaforge/envs/crick-dev/include -arch arm64

      INFO: compile options: '-Icrick -I/Users/paul/mambaforge/envs/crick-dev/lib/python3.9/site-packages/numpy/core/include -Icrick/klib -I/Users/paul/mambaforge/envs/crick-dev/include/python3.9 -c'
      INFO: clang: crick/tdigest.c
      xcrun: error: invalid active developer path (/Library/Developer/CommandLineTools), missing xcrun at: /Library/Developer/CommandLineTools/usr/bin/xcrun
      error: Command "clang -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -fwrapv -O2 -Wall -fPIC -O2 -isystem /Users/paul/mambaforge/envs/crick-dev/include -arch arm64 -fPIC -O2 -isystem /Users/paul/mambaforge/envs/crick-dev/include -arch arm64 -Icrick -I/Users/paul/mambaforge/envs/crick-dev/lib/python3.9/site-packages/numpy/core/include -Icrick/klib -I/Users/paul/mambaforge/envs/crick-dev/include/python3.9 -c crick/tdigest.c -o build/temp.macosx-11.0-arm64-cpython-39/crick/tdigest.o" failed with exit status 1
      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
  ERROR: Failed building wheel for crick
  Running setup.py clean for crick
Failed to build crick
Installing collected packages: crick
  Running setup.py install for crick ... error
  error: subprocess-exited-with-error

  × Running setup.py install for crick did not run successfully.
  │ exit code: 1
  ╰─> [40 lines of output]
      /Users/paul/work/sources/crick/setup.py:4: DeprecationWarning:

        `numpy.distutils` is deprecated since NumPy 1.23.0, as a result
        of the deprecation of `distutils` itself. It will be removed for
        Python >= 3.12. For older Python versions it will remain present.
        It is recommended to use `setuptools < 60.0` for those Python versions.
        For more details, see:
          https://numpy.org/devdocs/reference/distutils_status_migration.html

        import numpy.distutils.misc_util as np_misc
      running install
      /Users/paul/mambaforge/envs/crick-dev/lib/python3.9/site-packages/setuptools/command/install.py:34: SetuptoolsDeprecationWarning: setup.py install is deprecated. Use build and pip and other standards-based tools.
        warnings.warn(
      running build
      running build_py
      creating build
      creating build/lib.macosx-11.0-arm64-cpython-39
      creating build/lib.macosx-11.0-arm64-cpython-39/crick
      copying crick/_version.py -> build/lib.macosx-11.0-arm64-cpython-39/crick
      copying crick/__init__.py -> build/lib.macosx-11.0-arm64-cpython-39/crick
      creating build/lib.macosx-11.0-arm64-cpython-39/crick/tests
      copying crick/tests/test_stats.py -> build/lib.macosx-11.0-arm64-cpython-39/crick/tests
      copying crick/tests/test_space_saving.py -> build/lib.macosx-11.0-arm64-cpython-39/crick/tests
      copying crick/tests/__init__.py -> build/lib.macosx-11.0-arm64-cpython-39/crick/tests
      copying crick/tests/test_tdigest.py -> build/lib.macosx-11.0-arm64-cpython-39/crick/tests
      UPDATING build/lib.macosx-11.0-arm64-cpython-39/crick/_version.py
      set build/lib.macosx-11.0-arm64-cpython-39/crick/_version.py to '0.0.3+6.g2e827d2.dirty'
      running build_ext
      building 'crick.tdigest' extension
      Warning: Can't read registry to find the necessary compiler setting
      Make sure that Python modules winreg, win32api or win32con are installed.
      INFO: C compiler: clang -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -fwrapv -O2 -Wall -fPIC -O2 -isystem /Users/paul/mambaforge/envs/crick-dev/include -arch arm64 -fPIC -O2 -isystem /Users/paul/mambaforge/envs/crick-dev/include -arch arm64

      creating build/temp.macosx-11.0-arm64-cpython-39
      creating build/temp.macosx-11.0-arm64-cpython-39/crick
      INFO: compile options: '-Icrick -I/Users/paul/mambaforge/envs/crick-dev/lib/python3.9/site-packages/numpy/core/include -Icrick/klib -I/Users/paul/mambaforge/envs/crick-dev/include/python3.9 -c'
      INFO: clang: crick/tdigest.c
      xcrun: error: invalid active developer path (/Library/Developer/CommandLineTools), missing xcrun at: /Library/Developer/CommandLineTools/usr/bin/xcrun
      error: Command "clang -Wno-unused-result -Wsign-compare -Wunreachable-code -DNDEBUG -fwrapv -O2 -Wall -fPIC -O2 -isystem /Users/paul/mambaforge/envs/crick-dev/include -arch arm64 -fPIC -O2 -isystem /Users/paul/mambaforge/envs/crick-dev/include -arch arm64 -Icrick -I/Users/paul/mambaforge/envs/crick-dev/lib/python3.9/site-packages/numpy/core/include -Icrick/klib -I/Users/paul/mambaforge/envs/crick-dev/include/python3.9 -c crick/tdigest.c -o build/temp.macosx-11.0-arm64-cpython-39/crick/tdigest.o" failed with exit status 1
      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
error: legacy-install-failure

× Encountered error while trying to install package.
╰─> crick

note: This is an issue with the package mentioned above, not pip.
hint: See above for output from the failure.

tangentially related: https://github.com/coiled/platform/issues/130#event-7785886843


Do not build other branches unless they are part of a PR.

@dsjen

Coverage remained the same at 100.0% when pulling 7b078d0191b633b920b244ad10a8584dbe075313 on benp/only-master into b1a40a908f718e1bbd9403942b836739724bac75 on master.

also @clytwynec (I needed to add the edx group as a collaborator first)


Document a new plugin for shorter thematic breaks

Context
I am using mdformat but having troubles with the current thematic break rendering composed of 70 underscore characters, which I am rather used to typing as three dashes ---.
My (very personal and opinionated) reasons being:

The default vim highlighting for Markdown syntax breaks when multiple underscores are put together, because it conflicts with the italics format. Notice that this can probably be solved with Vim plugins or configuration tweaks, but the origin of the problem is about raw vim with no plugins.
Typing --- while writing a document is quick and easy, while typing a line of exactly 70 underscores is comparatively much harder and needs some sort of copy/paste action. My usual coding workflow involves code style checkers like mdformat and black as pre-commit hooks, but in general I try to type in code and documentation that is already valid to minimize the number of times that these tools have to modify what I have typed, which forces me to redo the review, git add and pre-commit loop.

I admit that these are very personal reasons, so I do not wish to engange in any discussions about the current rendering  style and the rationale behind it.
Instead, I thought best to take the route of coding a new plugin which overrides the rendering style for thematic breaks with three dashes, so anyone who wants can take advantage of it without having to do any change in the main mdformat project: https://github.com/csala/mdformat-simple-breaks
Proposal
The proposal is just to add the plugin to the corresponding list in the documentation
I'm happy to make a PR for it.
Tasks and updates

[ ] Discuss and decide if a PR is wanted
[ ] Do the corresponding PR

A PR is very welcome! :smile_cat:

Closing (https://github.com/executablebooks/mdformat/pull/418)


add hotfix and make python3.6 friendly

Example:
githubflow_release --release-type hotfix  --github-repo canaltp/toto --remote-name origin --base-branch master --hotfix-pr-id=41 --hotfix-pr-id=42 --hotfix-pr-id=43

haven't tested, but seems nice +1 !
do you plan to release it to pypi? I don't know if I can still find my credentials roll_eyes

It would be great that this can be published on pypi. It won't bother me it won't be case either.

ok ping me after the merge, I'll check if I can remember how to publish it 😜

hop released @xlqian : https://pypi.org/project/githubflow-release/


Add decimal annotations

Change Summary
Create some decimal.Decimal annotated types to replace deprecated condecimal methods.
Related issue number
Closes #8246

Checklist

[x] The pull request title is a good summary of the changes - it will be used in the changelog
[x] Unit tests for the changes exist
[x] Tests pass on CI
[x] Documentation reflects the changes where applicable
[x] My PR is ready to review, please add a comment including the phrase "please review" to assign reviewers

This PR might require a new PR in pydantic-core to support ConfigDict.ser_json_inf_nan='null'
In this PR ConfigDict.ser_json_inf_nan='null', will not result in a null value for Deciml('Infinity') after dumping the model_dump_json

You got a point aswell tbh, i find it a useful feature to be consistent with existing annotations for float. I also noticed many devs don't know about python builtin annotated_types,  they mostly use Pydantic ready types.
Regarding the docs, can you elaborate on the md/rst fix needed? thank you

I also noticed many devs don't know about python builtin annotated_types

annotated_types is a library on its own, but I agree I don't think people know much about it :thinking:

I also noticed many devs don't know about python builtin annotated_types

annotated_types is a library on its own, but I agree I don't think people know much about it 🤔

Oh I didn't notice it was a library

Sorry closed by mistake :)

Closing now.
@ahmedabdou14, thanks for your work. Looks like you understand parts of the codebase quite well. I've marked lots of issues with good first issue and help wanted if you're interested in diving into other projects :).


[WIP] Docker Support

I drafted a basic version of docker support. I managed to install all packages described in https://github.com/Park-Hyung-Joo/laygo2_sky130_docs and walk through the demo.
To use this, first install Docker and docker-py, then run
./docker/main.py run

This should spawn a docker container that you can access in the browser through http://localhost:6080/
And using
./docker/main.py shell

gives you a bash shell that's connected to the spawned container.
Let me know if it's working for you.

Thanks for your contribution! We'll review and merge the request early in december, as we are undergoing an evaluation phase for an award application.


Crashes with index out of range error

Expected behavior
Invalid command line invocations should produce appropriate error messages and not stack traces.
Actual behavior
It's been a while between kpt cfg set calls and I ran the command wrong which produced the stack trace shown below.
> kpt cfg set account-id abc

panic: runtime error: index out of range [2] with length 2

goroutine 1 [running]:
sigs.k8s.io/kustomize/cmd/config/internal/commands.(*SetRunner).preRunE(0xc000970000, 0xc00096cb00, 0xc00093cd80, 0x2, 0x2, 0x0, 0x0)
	sigs.k8s.io/kustomize/cmd/config@v0.9.5/internal/commands/cmdset.go:78 +0x331
github.com/spf13/cobra.(*Command).execute(0xc00096cb00, 0xc00093cd40, 0x2, 0x2, 0xc00096cb00, 0xc00093cd40)
	github.com/spf13/cobra@v1.0.0/command.go:831 +0x523
github.com/spf13/cobra.(*Command).ExecuteC(0xc00094e000, 0x200000003, 0xc000000180, 0xc0007d7f78)
	github.com/spf13/cobra@v1.0.0/command.go:950 +0x375
github.com/spf13/cobra.(*Command).Execute(...)
	github.com/spf13/cobra@v1.0.0/command.go:887
main.main()
	github.com/GoogleContainerTools/kpt/main.go:37 +0x65

Information
Kpt version: 0.38.1

dupe of #1593
@phanimarupaka do we have a patch release of this?   I thought this was in .38.1
@runewake2 do you know if you grabbed the dependency update for this?

I believe we'd need a new cmd/config release to pick up the fix for this.

@runewake2 can you spin one up and create .38.2?

We could build v0.39.1 after cmd/config is released. I am not able to perform releases in Kustomize though.

The fix for this should be available in version v0.39.1 of kpt.


Cannot set both parallelism and namespaceParallelism

Pre-requisites

[X] I have double-checked my configuration
[X] I can confirm the issues exists when I tested with :latest
[ ] I'd like to contribute the fix myself (see contributing guide)

What happened/what you expected to happen?
In the workflow-controller-configmap, setting:
  parallelism: "10"
  namespaceParallelism: "5"

Expectation
The global number of running workflows to be limited at 10, and the running workflows per namespace limited to 5.
Actual
However, in testing, argo-workflows limits the global number of workflows to 5.
Having each setting individually works as expected, but not when they are together. This is a cluster installation.
Version
v3.4.5
Paste a small workflow that reproduces the issue. We must be able to run the workflow; don't enter a workflows that uses private images.
Simple workflow that sleeps 5 mins.
apiVersion: argoproj.io/v1alpha1
kind: Workflow
metadata:
  generateName: parallelism-test-
spec:
  entrypoint: test
  podGC:
    strategy: OnWorkflowCompletion
  ttlStrategy:
    secondsAfterCompletion: 60
  templates:
  - name: test
    steps:
    - - name: test-1
        template: sleep
  - name: sleep
    container:
      image: alpine:latest
      command: [sleep, "300"]

Script that submits the above workflow 10 times to a namespace
#!/bin/bash

for i in {1..10}
do
    argo submit workflow.yaml -n $1 &
done

Submit to default and devops namespace
./submit.sh default
./submit.sh devops

Screenshots from UI, notice the number of running workflows for each namespace, and stuck waiting.

Logs from the workflow controller
controller_logs.txt
Logs from in your workflow's wait container
I don't think this is relevant.

This issue is reproducible. I can provide logs if needed.
Yes please. That's why they are requested in the template.

This looks like a bug where one of the configurations is overridden by another. Would anyone like to submit a PR?

bump

it is possible to know which overrides which in the configuration? namespaceParallelism > parallelism ?

global parallelism overrides namespaceParallelism but uses the value from namespaceParallelism. Please read the original issue description to see the behavior. It's straight forward to reproduce all outlined.


Separate Simulator device models

It would be nice to be able to test different device configurations on the simulator rather than them being included as a separate device aka GBDeviceModelSimulatoriPhone or GBDeviceModelSimulatoriPad

I don't think it is possible to distinguish between different device models inside a simulator. One could do it by screen size, but then it's still ambiguous between iPhone 5 vs iPhone 5S vs iPhone 5C, etc.


[BUG] import fails with latest antlr4-python3-runtime

Minimal Code To Reproduce
import fugue_sql

Error message:

 Error Trace
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "miniconda3/envs/terr/lib/python3.8/site-packages/fugue_sql/__init__.py", line 4, in <module>
    from fugue_sql.workflow import FugueSQLWorkflow, fsql
  File "miniconda3/envs/terr/lib/python3.8/site-packages/fugue_sql/workflow.py", line 4, in <module>
    from fugue import (
  File "miniconda3/envs/terr/lib/python3.8/site-packages/fugue/__init__.py", line 17, in <module>
    from fugue.execution.execution_engine import ExecutionEngine, SQLEngine
  File "miniconda3/envs/terr/lib/python3.8/site-packages/fugue/execution/__init__.py", line 3, in <module>
    from fugue.execution.factory import (
  File "miniconda3/envs/terr/lib/python3.8/site-packages/fugue/execution/factory.py", line 4, in <module>
    from fugue.execution.native_execution_engine import NativeExecutionEngine
  File "miniconda3/envs/terr/lib/python3.8/site-packages/fugue/execution/native_execution_engine.py", line 34, in <module>
    from qpd_pandas import run_sql_on_pandas
  File "miniconda3/envs/terr/lib/python3.8/site-packages/qpd_pandas/__init__.py", line 3, in <module>
    from qpd_pandas.engine import QPDPandasEngine, run_sql_on_pandas
  File "miniconda3/envs/terr/lib/python3.8/site-packages/qpd_pandas/engine.py", line 6, in <module>
    from qpd import PandasLikeUtils, QPDEngine, run_sql
  File "miniconda3/envs/terr/lib/python3.8/site-packages/qpd/__init__.py", line 7, in <module>
    from qpd.run import run_sql
  File "miniconda3/envs/terr/lib/python3.8/site-packages/qpd/run.py", line 3, in <module>
    from qpd._parser.sql import QPDSql
  File "miniconda3/envs/terr/lib/python3.8/site-packages/qpd/_parser/sql.py", line 6, in <module>
    from _qpd_antlr import QPDLexer, QPDParser
  File "miniconda3/envs/terr/lib/python3.8/site-packages/_qpd_antlr/__init__.py", line 3, in <module>
    from _qpd_antlr.sqlLexer import sqlLexer as QPDLexer
  File "miniconda3/envs/terr/lib/python3.8/site-packages/_qpd_antlr/sqlLexer.py", line 1313, in <module>
    class sqlLexer(Lexer):
  File "miniconda3/envs/terr/lib/python3.8/site-packages/_qpd_antlr/sqlLexer.py", line 1315, in sqlLexer
    atn = ATNDeserializer().deserialize(serializedATN())
  File "miniconda3/envs/terr/lib/python3.8/site-packages/antlr4/atn/ATNDeserializer.py", line 28, in deserialize
    self.checkVersion()
  File "miniconda3/envs/terr/lib/python3.8/site-packages/antlr4/atn/ATNDeserializer.py", line 50, in checkVersion
    raise Exception("Could not deserialize ATN with version " + str(version) + " (expected " + str(SERIALIZED_VERSION) + ").")
Exception: Could not deserialize ATN with version  (expected 4).

Describe the bug
On creating a new environment either via pip pip install fugue[sql] or conda conda install -c conda-forge fugue, importing fugue_sql fails with errors pointing to antlr4. Caught by upstream CI in dask-sql: https://github.com/dask-contrib/dask-sql/issues/455.
There was a new 4.10 antlr4 (& antlr4-python-runtime) release recently which now gets picked up by the solvers that seems to be the cause of incompatibility, confirmed that things work with the older 4.9.3.
Expected behavior
Working import either via pinning to an older version of antlr or updating to be compatible with the latest version.
Environment (please complete the following information):

Backend: N/A
Backend version: N/A
Python version: 3.8
OS: linux (ubuntu 20.04)

@ayushdg thanks for reporting. The incompatibility between antlr 4.10 and 4.9 is unexpected. It will take some effort to make it work. So I just made a quick fix: adding the version cap for antlr4-python-runtime. And in the later versions I will remove the cap when we fix the root cause.

@ayushdg I have released Fugue 0.6.6, it should have solved this issue

Thanks @goodwanghan, appreciate the quick fix. Can confirm that the 0.6.6 release does fix this 😄 .
Just adding a quick note about conda though it's not directly related to fugue: People getting fugue from conda will still see issues in imports since the conda solver picks up the newer antlr version. The fugue package doesn't explicitly specify antlr in it's conda recipe but qpd one of the packages fugue depends on, has the antlr dependency and faces the same import issues.


SourceLink 3 Plan

SourceLink exists to fill a gap in the .NET tooling. For version 2, much of the functionality was replaced by new .NET tooling that was developed along with .NET Core such as the Portable PDB format and the System.Reflection.Metadata that provides an API to it. For version 3, functionality found in version 2 will also move upstream into the .NET tooling. There will be three layers:

Microsoft.Build.Tasks.RepositoryInfo
Shipped with MSBuild and available from Microsoft.Common.targets.
source control packages
Microsoft.Build.Tasks.Git
Microsoft.Build.Tasks.TFVC
They may be added via a PackageRefernce
source link packages
Provide necessary info for specific source control hosts
SourceLink.GitHub
SourceLink.VSO.Git
SourceLink.VSO.TFVC

https://github.com/dotnet/sourcelink is now available with libraries published on NuGet.

Will Microsoft be providing the functionality in SourceLink.Embed.AllSourceFiles

The plan for 3.0 has been broken up into issues and attached to a milestone:
https://github.com/ctaggart/SourceLink/milestone/30
Most functionality is to be replaced by https://github.com/dotnet/sourcelink Microsoft.SourceLink packages. Some utilities to fill in the gaps will remain here. Feedback welcome.


have you considered adding an RSS feed?:)

Hey, Jason.
Really loved reading a lot of your posts. I really would hate to miss anything new from you. Have you considered adding an RSS feed to your website?

I have one! It's just not linked anywhere. 😅  https://www.jason.af/feed.xml


Updated validations.py python script.

Updated validations.py python script.
Fixed the behavior of validate_user function in validations.py.
Closes: #1
Fixes #<issue_number_goes_here>

It's a good idea to open an issue first for discussion.

[ ] Tests pass
[ ] Appropriate changes to README are included in PR

chukwuemeka google it automation with python; course 3 quick lab exercise


nixos/kubernetes: use correct -o option with bash install when copying certs in cfssl prestart script

Description of changes
install does not have a -u option, it seems the intention was to use -o which sets file ownership
Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
24.05 Release Notes (or backporting 23.05 and 23.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

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

@JorisBolsens greetings, can you update commit message to match contribution guidelines.
https://github.com/NixOS/nixpkgs/blob/master/nixos/README.md#commit-conventions

@kirillrdy Sorry about that, updated

no need to apologise !
can you also change PR title to match commit message, this helps people to find in progress PRs related to same code

@kirillrdy done 🫡


Cpa 495 2

🗣 Description

💭 Motivation and Context

🧪 Testing

📷 Screenshots (if appropriate)
🚥 Types of Changes

[ ] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (causes existing functionality to change)

✅ Checklist

[ ] My code follows the code style of this project.
[ ] My change requires a change to the documentation.
[ ] I have updated the documentation accordingly.
[ ] I have read the CONTRIBUTING document.
[ ] I have added tests to cover my changes.
[ ] All new and existing tests passed.

Looks like this is a duplicate. Not sure how it got pushed up.