Traffic handover: Vehicle destination changed and is managed by multiple traffic providers

Steps to reproduce the bug
Steps to reproduce.
$ git checkout traffic-handover
# Retrieve the following scenario and place it here
# <path>/SMARTS/driving-smarts-2.competition-scenarios/t3/training/merge_exit_sumo_t_agents_1
$ cd <path>/SMARTS
$ python3.8 -m venv ./.venv
$ source ./.venv/bin/activate
$ pip install --upgrade pip
$ pip install -e .[camera_obs,argoverse]
$ scl zoo install examples/rl/platoon/inference
$ scl benchmark run driving_smarts_2023_3 examples.rl.platoon.inference:contrib-agent-v0 --auto-install

Press any key to step through the simulation. At each step, the traffic providers managing the lead vehicle "Leader-007" is printed. Additionally the destination road of the lead vehicle from the traffic provider is also printed.
High Level Description
After stepping the environment for a number of steps, TraCI error occurs resulting in the lead vehicle being handed over from SumoTrafficSimulation to LocalTraffic provider.
Issue-1: In all remaining steps within that episode, both SumoTrafficSimulation and LocalTrafficProvider appear to be managing "Leader-007".
Issue-2: The destination road of "Leader-007" appears to have changed from E4 under SumoTrafficSimulation control to E2.224.85 when controlled by LocalTrafficProvider.
Error logs and screenshots
Below is a sample terminal output when running the above example.
Leader-007 found in the following traffic providers: ['SumoTrafficSimulation']
Leader-007 in SumoTrafficSimulation has destination E4.
Press any key to proceed to next step .........

Leader-007 found in the following traffic providers: ['SumoTrafficSimulation']
Leader-007 in SumoTrafficSimulation has destination E4.
Press any key to proceed to next step .........

ERROR:SumoTrafficSimulation:TraCI has disconnected with: `connection closed by SUMO`. Please check the logging file `/home/kyber/.smarts/_sumo_run_logs/sumo-87a05c6a`.
WARNING:SumoTrafficSimulation:attempting to transfer SUMO vehicles to other providers...
Leader-007 found in the following traffic providers: ['SumoTrafficSimulation', 'LocalTrafficProvider']
Leader-007 in LocalTrafficProvider has destination E2.224.85.
Press any key to proceed to next step .........

Leader-007 found in the following traffic providers: ['SumoTrafficSimulation', 'LocalTrafficProvider']
Leader-007 in LocalTrafficProvider has destination E2.224.85.
Press any key to proceed to next step .........

Impact (If known)
Vehicle destination is changed upon traffic handover. Hence, the vehicle's total route distance which was computed beforehand at the start of the episode becomes inaccurate.
Version
version: 1.1.0
branch: traffic-handover
System info
No response

From what I can note from the handover,
Issue 1) is an easy fix which just needs a check if the provider is still connected.
Issue 2) is the result of not handing over the route information.


questions about swd

Sorry to bother, I saw you used SWD (sliced wasserstein distance) in the paper, and I also want to use this score as a metric for some tests. Could you offer your code to calculate it? thanks!

please refer to Utils/SWD/cal_sliced_wasserstein.py.

thanks!

well, i tested the code, and it seemed that the code somehow needs a  "sliced_wasserstein.API", and could you tell me where to get it?

please refer to Utils/SWD/sliced_wasserstein.py

I tested the code and it worked perfectly well. The last question I want to ask is that there are six scores
"SWDx1e3_256  SWDx1e3_128  SWDx1e3_64   SWDx1e3_32   SWDx1e3_16   SWDx1e3_avg" there,
and it seemed to use the last one, right?
also the two image folders I should use is the fake_B(generated_zebra, for example) and real_B(real_zebra, for example), right?

yes, as you described.


Make the carbon search box being locked by default

The problem
Since the release of today, the Carbon Search box is expanded by default, which is great. But it is not locked by default. Meaning that if we click anywhere on the page, the search box collapses. And so it makes using it difficult. If the users clicks somewhere else by accident, they lose the search box and have to click on the magnifying glass to expand it again.
It's counter intuitive
The solution
Make sure the search box is locked when expanded

@jeffchew Please disregard this ticket.


Remove deprecated Guzzle function call

The GuzzleHttp\Psr7\uri_for function is deprecated and removed in Guzzle 7.2.  Where available GuzzleHttp\Psr7\Utils::uriFor is used instead.
Given we support Guzzle 6 and 7, both the method and function call are required to be supported.
Fixes #134.

Hi, I have this issue yesterday and tested this PR. Seems to be a good solution.

Have the same issue, tested this PR and it solves the problem as well

@masakik and @hawkinbj thank you both for testing! Incoming release.

function is deprecated and removed in Guzzle 7.2

This is not true.

See https://github.com/thephpleague/oauth1-client/pull/136. :)

@GrahamCampbell if you would like, feel welcome to submit a PR


Do not send DELETE after QueryRow

When calling db.QueryRowContext() and scanning the result, the Scan() method calls Close() on the driver's result struct. The driver is not aware that there are no more results to read and issues an additional DELETE HTTP request. Because the query no longer exists on the server, it returns a 404 response, which is then returned to the calling code.
The driver should correctly set the internal err to io.EOF if there's no data and nextUri in the last received response.


Error when using pre-computed blast result

Hi @chenym1
I want to skip the blast process as it takes much time. So I used diamond to align protein fa file first using the following command for all four possible specie combination:

diamond makedb --in Obrac.fa -d Obrac &> Obrac_db.log
diamond makedb --in Omh63.fa -d Omh63 &> Omh63_db.log
diamond blastp -e 1e-5 -p 2 -q ${querie}.fa -d ${target}.dmnd -o ${target}_${querie}.blast -f 6 -k 5

The -f para specific the output format in blast tab. I checked this file and it's same with the file jcvi needs. The using the following command, I run genetribe:

genetribe core -l Obrac -f Omh63 -d ./ -r -s + -n 1

The -s is specificed to '+' as I already selected the longest transcript for each gene so I want to use this rare symbo to skip the selection process in your pipeline.
However, I got the following problems:

[11:51:31] DEBUG    Assuming --qbed=Obrac.bed --sbed=Omh63.bed                                                                      synteny.py:500
DEBUG    Load file Obrac.bed base.py:37
[11:51:32] DEBUG    Load file Omh63.bed base.py:37
DEBUG    Load BLAST file Obrac.Omh63.last (total 86573 lines)                                                       blastfilter.py:48
DEBUG    Load file Obrac.Omh63.last base.py:37
[11:51:33] WARNING  OsMH_10T0277800-mRNA-2 not in Obrac.bed                                                                      blastfilter.py:67
WARNING  OsMH_09T0060300.1 not in Obrac.bed                                                                           blastfilter.py:67
WARNING  OsMH_04T0543900-mRNA-2 not in Obrac.bed                                                                      blastfilter.py:67
WARNING  OsMH_02T0267100-mRNA-2 not in Obrac.bed                                                                      blastfilter.py:67
WARNING  OsMH_10T0367800-mRNA-1 not in Obrac.bed                                                                      blastfilter.py:67

It's so strange that jcvi would look for a MH63 gene in the bed of Obrac.
Is there anything I have overlooked?  I think this should make sense.

Hi, xitong,
In 'diamond blastp -e 1e-5 -p 2 -q ${querie}.fa -d ${target}.dmnd -o ${target}${querie}.blast -f 6 -k 5', you should replace '${target}${querie}.blast' with '${querie}_${target}.blast'

Thanks I should realize this problem. I will try it!
发自我的iPhone
------------------ Original ------------------
From: Yongming Chen @.>
Date: Fri,Jun 18,2021 0:32 PM
To: chenym1/genetribe @.>
Cc: Zhu xitong @.>, Author @.>
Subject: Re: [chenym1/genetribe] Error when using pre-computed blast result (#2)
Hi, xitong,
In 'diamond blastp -e 1e-5 -p 2 -q ${querie}.fa -d ${target}.dmnd -o ${target}${querie}.blast -f 6 -k 5', you should replace '${target}${querie}.blast' with '${querie}_${target}.blast'
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub, or unsubscribe.

Hi @chenym1
Yes indeed I set wrong output prefix in diamond and your suggestion is right.
I have some other questions and maybe those should be in a new ISSUE but I shall just ask here.

For the .chrlist file, I guess only the last character e.g. A in chrNA or nothing after N e.g. the one in Oryza_sativa_Japonica.chrlist is important for penalty. So is this mean that every abbr. in chrlist (like chrNA chrNB and chrND in another file) is a chromosome group ? For example if a pair of genes are in A and B, respectively, they would be penalized even A and B are in same chrlist file?

cat Oryza_sativa_Japonica.chrlist
N

At last, we could get 5 files for a comparison (1 RBH, 2 SBH, 2 Singleton, 2 1toMany). Will you have any suggestions on how to integrate many comparison like I think if we have three species, we can use the files of A->B, and B->C.
Moreover, I really like the this picture in you paper. Could you please kindly provide me ideas to draw such pictures.

Any little help is very appreciated.

Hi, @Zhuxitong
Sorry to reply you now,

A pair of genes would be penalized even A and B are in same chrlist file, for example, gene1 in chr1A, while gene2 in chr2B.
The effect of using RBH will be better.
The figure is plotted using R graphics package. The homologous relationships are generated using GeneTribe.
hope this helps.

@chenym1  Many thanks. I will close this issues.


Remove the horizontal separator bars from each page to reduce clutter and update color for remaining separators

@kawilkin Can you identify which ones just so it's clear?

@JakeRadMSFT  does this help?

Validated!


getSecondsUntilNextCycle does not use perpare phase

What version of Stacks.js are you using?
6.5.4
Describe the bug
getSecondsUntilNextCycle returns the seconds until the start of the reward phase, not of the prepare phase.
The prepare phase is important for stackers because stx locked after the prepare phase do not earn rewards during the upcoming reward phase.
How to reproduce
Check getSecondsUntilNextCycle() and compare to blocks_until_prepare_phase of e.g. https://api.hiro.so/v2/pox
Expected behavior
Return estimated seconds until start of next prepare phase
Additional context
Used in lockstacks.com/pool-admin

I'd say the current implementation on the stacking client is useless while technically correct.

Consensus: deprecate and switch to Get Seconds Until Next Stacking Deadline method for usability

GetSecondsUntilNextCycle is useful to show when the user's stx unlock.


TST: Add missing skip for pyarrow

[n/a] Closes #xxxx
[x] Tests added / passed
[x] Passes pre-commit run --all-files

thx @QuLogic


Fix build failure with Carthage

Not to use “Parallelize Build” and “Find Implicit Dependencies”.
Fixes https://github.com/ReactiveKit/ReactiveKit/issues/18.

Hmm your branch fails to build in my workspace... Any ideas ?
carthage build --no-skip-current --platform tvos works fine.
carthage build --no-skip-current fails .
$ carthage build --no-skip-current
*** xcodebuild output can be found in /var/folders/tr/3lftss053tqdh731cgt0w1p00000gn/T/carthage-xcodebuild.CTv6h4.log
*** Building scheme "ReactiveFoundation-tvOS" in ReactiveFoundation.xcworkspace
2015-12-24 10:37:11.745 xcodebuild[99866:1893704] ### Failed to load Addressbook class CNContactNameFormatter
** BUILD FAILED **

The following build commands failed:
	CompileSwift normal arm64 /Users/toshi0383/github/ikesyoReactiveFoundation/ReactiveFoundation/ReactiveNSObject.swift
	CompileSwift normal arm64 /Users/toshi0383/github/ikesyoReactiveFoundation/ReactiveFoundation/RKKeyValueObservable.swift
	CompileSwift normal arm64 /Users/toshi0383/github/ikesyoReactiveFoundation/ReactiveFoundation/ReactiveNSNotificationCenter.swift
	CompileSwiftSources normal arm64 com.apple.xcode.tools.swift.compiler
(4 failures)
/Users/toshi0383/github/ikesyoReactiveFoundation/ReactiveFoundation/ReactiveNSObject.swift:25:8: error: module file's minimum deployment target is tvos9.1 v9.1: /Users/toshi0383/Library/Developer/Xcode/DerivedData/ReactiveFoundation-btkzlyphhsrpncbtydkkjxvzllqt/Build/Products/Release-appletvos/ReactiveKit.framework/Modules/ReactiveKit.swiftmodule/arm64.swiftmodule
/Users/toshi0383/github/ikesyoReactiveFoundation/ReactiveFoundation/ReactiveNSObject.swift:25:8: error: module file's minimum deployment target is tvos9.1 v9.1: /Users/toshi0383/Library/Developer/Xcode/DerivedData/ReactiveFoundation-btkzlyphhsrpncbtydkkjxvzllqt/Build/Products/Release-appletvos/ReactiveKit.framework/Modules/ReactiveKit.swiftmodule/arm64.swiftmodule
/Users/toshi0383/github/ikesyoReactiveFoundation/ReactiveFoundation/ReactiveNSObject.swift:25:8: error: module file's minimum deployment target is tvos9.1 v9.1: /Users/toshi0383/Library/Developer/Xcode/DerivedData/ReactiveFoundation-btkzlyphhsrpncbtydkkjxvzllqt/Build/Products/Release-appletvos/ReactiveKit.framework/Modules/ReactiveKit.swiftmodule/arm64.swiftmodule
A shell task failed with exit code 65:
2015-12-24 10:37:11.745 xcodebuild[99866:1893704] ### Failed to load Addressbook class CNContactNameFormatter
** BUILD FAILED **

The following build commands failed:
	CompileSwift normal arm64 /Users/toshi0383/github/ikesyoReactiveFoundation/ReactiveFoundation/ReactiveNSObject.swift
	CompileSwift normal arm64 /Users/toshi0383/github/ikesyoReactiveFoundation/ReactiveFoundation/RKKeyValueObservable.swift
	CompileSwift normal arm64 /Users/toshi0383/github/ikesyoReactiveFoundation/ReactiveFoundation/ReactiveNSNotificationCenter.swift
	CompileSwiftSources normal arm64 com.apple.xcode.tools.swift.compiler
(4 failures)

$ carthage version
0.11.0
$ xcodebuild -version
Xcode 7.2
Build version 7C68
$  swift --version
Apple Swift version 2.1.1 (swiftlang-7<IP_ADDRESS> clang-700.1.81)
Target: x86_64-apple-darwin15.0.0

I succeeded to build with carthage build --no-skip-current. How about if you remove ReactiveKit-* and ReactiveFoundation-* from your derived data dir?

Removing derived data did not work for me.
Never mind, maybe I should reinstall Xcode or even OSX ...

My bad. I was on wrong branch.
Switched to the branch fix-carthage-build , removed all derived data, and still got this error.
target 'ReactiveKit-watchOS' has bitcode disabled (ENABLE_BITCODE = NO), but it is required for the 'watchos' platform

That seems the same as https://github.com/Carthage/Carthage/issues/685 and https://github.com/Carthage/Carthage/issues/716. Do you have valid watchOS simulators?

@ikesyo, thank you for fixing this, it's much appreciated!

@ikesyo  Resetting simulators solved my issue. thanks a lot !!!

:smile:


 components throws "Failed to execute 'removeChild' on 'Node'" when using next-intl with Nextjs' app router, parallel routes and route interception

Description
The <Link /> component throws an error when used with Nextjs' parallel routes and routes interception. A full refresh is necessary to clear the error.
The full error:
Unhandled Runtime Error
NotFoundError: Failed to execute 'removeChild' on 'Node': The node to be removed is not a child of this node.

Call stack
removeChildFromContainer
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (34039:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20984:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21132:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21094:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21079:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21079:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21079:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21094:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21079:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21079:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21132:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21132:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21079:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21132:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21094:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21079:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21094:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21079:0)
recursivelyTraverseDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20904:0)
commitDeletionEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21079:0)
commitDeletionEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (20891:0)
recursivelyTraverseMutationEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21291:0)
commitMutationEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21366:0)
recursivelyTraverseMutationEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21305:0)
commitMutationEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21327:0)
recursivelyTraverseMutationEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21305:0)
commitMutationEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21758:0)
recursivelyTraverseMutationEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21305:0)
commitMutationEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21758:0)
recursivelyTraverseMutationEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21305:0)
commitMutationEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21758:0)
recursivelyTraverseMutationEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21305:0)
commitMutationEffectsOnFiber
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21758:0)
recursivelyTraverseMutationEffects
node_modules/next/dist/compiled/react-dom/cjs/react-dom.development.js (21305:0)

Mandatory reproduction URL (CodeSandbox or GitHub repository)
~~https://codesandbox.io/p/github/DriesCruyskens/next-intl-mre/main~~
https://github.com/DriesCruyskens/next-intl-mre
Reproduction description

Open page (this opens the modal)

Changes locales
and/or:

Open page (this opens modal)

refresh page

Change locales

Expected behaviour
I expect  component to direct me to the new locale instead of throwing an error.

I think your CodeSandbox is private, can you make it public?

Is this a duplicate of https://github.com/amannn/next-intl/issues/255? So far my latest information is that Next.js currently has internal bugs that lead to issues when using parallel or intercepted routes with next-intl. Reproductions where next-intl is not used (but the behavior simulated) show the same errors, therefore this is unfortunately not actionable on the next-intl side and we have to wait for upstream fixes.
If your reproduction is able to demonstrate an error that is caused by next-intl and is not related to an internal Next.js bug, I'd be happy to look into it.

I think it is public but I can't access it either in private window.

Here is the GitHub project instead: https://github.com/DriesCruyskens/next-intl-mre
I never experienced this specific error in #255 so I thought I'd put it here in case others experience the same problem. I do understand that this seems like a waste of time since Nextjs is buggy still and the error message is cryptic. Parallel routes work fine without next-intl's  component though so I thought there must be something linked to next-intl specifically.

Thanks, that helps!
When I switch the language on the modal page, I also see this warning on the console:
Warning: validateDOMNesting(...): <div> cannot appear as a child of <#document>.

My understanding is that the request for the modal route returns invalid markup that causes your app to break.
Can you try to remove all next-intl APIs from the components in a branch and see if you can still reproduce the error?

Can you try to remove all next-intl APIs from the components in a branch and see if you can still reproduce the error?

I can't reproduce since parallel routes + route interception works fine without i18n. However, if I use next/link or useRouter() (from next-intl) somehow the const pathname = usePathname(); (from next-intl) fails to strip the language from the pathname causing 404 errors to /fr-be/en-eu/events for example.
Here's a reproduction: https://github.com/DriesCruyskens/next-intl-mre/commit/7e1ef9e756f6ce1a5d7e3dce3bff5b0fc30b8ba9

I actually found the cause of the validateDOMNesting warning. It's thrown because the root layout does not contain html and body tags when trying to display a 404 page. After moving these tags to the root layout, navigating to a different locale (from a subroute) throws a 404 page. This works fine when navigating without locale change or hard navigating to subpages.
https://github.com/DriesCruyskens/next-intl-mre/commit/43ac111311d86351e7f420821d033db95fa50fe3

I actually found the cause of the validateDOMNesting warning. It's thrown because the root layout does not contain html and body tags when trying to display a 404 page.

I found that you can render these from a root not-found page as well: https://github.com/amannn/next-intl/blob/main/examples/example-next-13/src/app/not-found.tsx
I also think that the bug is somehow related to the root layout not having an html tag, but we need to render this in ./[locale]/layout to be able to add the lang attribute (see also the reference implementation from Next.js).
Can the bug be summarized as parallel and intercepted routes not working properly when the root layout doesn't contain an html tag? In that case, I think it should be reported to Next.js, in reference to their i18n example in the docs.

Can the bug be summarized as parallel and intercepted routes not working properly when the root layout doesn't contain an html tag? In that case, I think it should be reported to Next.js, in reference to their i18n example in the docs.

Sadly I can't manage to create a minimal reproducible example with Nextjs alone (without next-intl). Parallel routes and intercepted routes on their own work fine when the root does not contain an html tag so I don't think they'll spent time on it either.

Hmm, I see. Can you point me to a commit where you have a working app with Next.js before and then in the commit it's visible which functionality from next-intl breaks the app? Ideally as minimal as possible, e.g. if we know that the app breaks once we add the middleware, but before any messages are used in the app, this would be really helpful.

Commit where all works fine: https://github.com/DriesCruyskens/next-intl-mre/commit/cc76436ada7f84c430eff7e73bef1beb45281e62
The commit right after that redirects to 404 inside parallel route: https://github.com/DriesCruyskens/next-intl-mre/commit/c0d10e97c3c9fb0cc14539f39827238f69a16b0c

I'm sorry, but that doesn't seem to indicate what's going wrong here. You only encounter the issue when you click on a link, but in https://github.com/DriesCruyskens/next-intl-mre/commit/cc76436ada7f84c430eff7e73bef1beb45281e62 there's no link to be clicked on, so naturally nothing can break, right?
I tried replacing your links that are created with next-intl/link with this:
import Link from 'next/link'

<Link className="underline" href="/en-eu/events/1">en-eu</Link>
<Link className="false" href="/fr-be/events/1">fr-be</Link>
<Link className="false" href="/nl-be/events/1">nl-be</Link>

There's no runtime error when clicking on a link, but the language isn't changed either.
That's what I tried to discuss above, that it would be necessary that we have a version of this that works without next-intl, so that we can isolate if the issue is related to Next.js or next-intl.


Add StatusCode() and GetPayload() methods to response

We need an easy way to get the response status code and payload.

discussed offline


What is the reason for installing a digital person but no voice output and input

What is the reason for installing a digital person but no voice output and input?

有看到提示：soul is death

如果提示：soul is death 表示后端没有连接上，看一下readme中常见问题关于该问题的说明


Deprecated code and update dependencies

Removed dependencies of swagger-validation-common and azure-js-dev-tools
Deprecated code for supporting track1 SDK generation
Deleted invalid tests
Updated dependencies

@raych1 are we at a point where we can have a buildable pipeline? If so lets try to get it added.

@raych1 are we at a point where we can have a buildable pipeline? If so lets try to get it added.

That's the next PR I am planning to add.

/azp run

/azp run tools - spec-gen-sdk

/azp run "tools - spec-gen-sdk"

@weshaggard
could you review the pipeline changes?

@mikeharder do you have any further feedback on this PR?


Usage of init_score results in no boosting

It seems if lightgbm.train is used with an initial score (init_score) it cannot boost this score. Here is a simple example:
params = {"learning_rate": 0.1,"metric": "binary_logloss","objective": "binary",
          "boosting_type": "gbdt","num_iterations": 5, "num_leaves": 2 ** 2,
          "max_depth": 2, "num_threads": 1, "verbose": 0, "min_data_in_leaf": 1}

x = pd.DataFrame([[1, 0.1, 0.3], [1, 0.1, 0.3], [1, 0.1, 0.3],
                  [0, 0.9, 0.3], [0, 0.9, 0.3], [0, 0.9, 0.3]], columns=["a", "b", "prob"])
y = pd.Series([0, 1, 0, 0, 1, 0])

d_train = lgb.Dataset(x, label=y)
model = lgb.train(params, d_train)
y_pred_default = model.predict(x, raw_score=False)

In the case above, no init_score is used. The predictions are correct: y_pred_default = [0.33333333, ... ,0.33333333]
d_train = lgb.Dataset(x, label=y, init_score=scipy.special.logit(x["prob"]))
model = lgb.train(params, d_train)
y_pred_raw = model.predict(x, raw_score=True)

In this part, we assume colum "prob" from x to be our initial guess (maybe by some other model). We apply logit and use it as initial score. However, the model cannot improve and the boosting will always return 0: y_pred_raw = [0, 0, 0, 0, 0, 0]
y_pred_raw_with_init = scipy.special.logit(x["prob"]) + y_pred_raw

y_pred = scipy.special.expit(y_pred_raw_with_init)

This part above shows the way I suppose is correct to translate the initial scores together with the boosting back to probabilities. Since the boosting is zero y_pred yields [0.3, ..., 0.3] which is our initial probability.
I am doing it wrong or assuming init_score to do something else here?

I believe the problem is with your example. You give the model the same samples (x) labeled both as positive (y = 1) and negative (y = 0), so the model can't learn anything from it, which is printed out as a warning:
[LightGBM] [Warning] No further splits with positive gain, best gain: -inf.
If you inspect the model (for example using model.trees_to_dataframe()) you'll see that it didn't make any splits, so with both datasets it's using the init_score as the predictions. In the first case, since you don't explicitly specify init_score it uses the logit of the mean of the target (logit(0.333)). In the second case it uses the one you specified (logit(0.3)).

Thanks for your reply. I agree that the example is a bit strange. And you are correct, the first model simply returns the mean of the target and did not create a tree since it doesn't improve the prediction.
However, I assumed that the second model should at least create a tree. It could simply select the first feature "a=0.5" as a split. Then it would also predict a raw score of logit(0.333) (depending on the learning rate of course), which results in lower log loss than a logit of 0.3. Don't you agreee?
So for me it seems as if the model is not trying to improve the provided init_score. From my understanding init_score can be treated as the result of some other initial prediction output and gradient boosting will try to boost this prediction by further reducing the loss. But this is not what I see here.
Or is this some wrong assumption of me?

However, I assumed that the second model should at least create a tree. It could simply select the first feature "a=0.5" as a split. Then it would also predict a raw score of logit(0.333) (depending on the learning rate of course), which results in lower log loss than a logit of 0.3. Don't you agreee?

This is a vs y:

So as you can see a split at a=0.5 doesn't produce any gain, since you'd still have the same points at y=0 and y=1, therefore lightgbm doesn't use that feature for splitting, same for b.

From my understanding init_score can be treated as the result of some other initial prediction output and gradient boosting will try to boost this prediction by further reducing the loss. But this is not what I see here.

This is correct.
Here's an example:
import lightgbm as lgb
import matplotlib.pyplot as plt
import numpy as np

X = np.arange(4).reshape(-1, 1)
y = np.array([0, 1, 1, 1])

This is the data

LightGBM will use the mean of the target as init_score, so here it'd be 0.75, let's try setting that manually:
ds = lgb.Dataset(X, y, init_score=np.array([0.75] * 4))
model = lgb.train({'num_round': 1, 'num_leaves': 2, 'min_data_in_leaf': 1, 'objective': 'l2', 'learning_rate': 1}, ds)
model.predict(X, raw_score=True)
# array([-0.75,  0.25,  0.25,  0.25])

So here the boosting subtracts 0.75 for the first sample and adds 0.25 for the others, the final predictions here are 0, 1, 1, 1.
If we try a different init_score:
ds = lgb.Dataset(X, y, init_score=np.array([0.5] * 4))
model = lgb.train({'num_round': 1, 'num_leaves': 2, 'min_data_in_leaf': 1, 'objective': 'l2', 'learning_rate': 1}, ds)
model.predict(X, raw_score=True)
# array([-0.5,  0.5,  0.5,  0.5])

As you can see here the boosting is starting from 0.5 in this case, and the tree is either subtracting or adding 0.5 to get to the same final predictions (0, 1, 1, 1).

Thanks the examples. I think I finally figured what my problem is. It might be my misunderstanding or a wrong expectation:
I use gradient boosting for probability prediction. Hence my goal is to achieve best likelihood estimates. This is also why I came up with this strange input matrix with duplicates.
So it terms of classification, simply deciding whether an input example belongs to class 1 or 0, the classifier does actually the correct thing. I, however, assumed that it would continue splitting the data until the probability estimates are best and hence, also the log loss would be minimal. So I think it does not have anything to do with the init_score but simply my understanding of the optimization itself.
Here again an example to show what I mean:
        import lightgbm as lgb
        import numpy as np

        X = np.array([1, 3, 2, 2]).reshape(-1, 1)
        y = np.array([0, 1, 0, 1])

        ds = lgb.Dataset(X, y)
        model = lgb.train({'num_round': 3 'num_leaves': 2, 'min_data_in_leaf': 1, 'objective': 'l1', 'learning_rate': 1}, ds)
        model.predict(X, raw_score=True)
        # array([0.5, 1.0, 0.5, 0.5])

So basically the algorithm stops after one iteration, predicting f(the feature)=3 to be positive, all other three examples to be negative. The L1 loss would be 0.5+0.5 + 0.5 = 1.5 Creating another tree/leaf that would put example with f=1 in it, would result in the prediction vector [0.0, 1.0, 0.5, 0.5] and hence would reduce the loss to 0.5 + 0.5 = 1.0, which would be ideal in my application.
However, it terms of binary prediction, it wouldn't matter since still all three example with f <=2 would end up in the negative class.
Is this assumption correct? Because in my very first example where I said a=0.5 would be a good split, it would also not change the class assignment (I assume that is what you wanted to show me with your plot). However, creating the split would improve the loss (predictions would change from 0.3 to 0.333).
And if this is correct, and tree splitting would stop before the metric is minimal, is there way to force such a behaviour?

Creating another tree/leaf that would put example with f=1 in it, would result in the prediction vector [0.0, 1.0, 0.5, 0.5] and hence would reduce the loss to 0.5 + 0.5 = 1.0, which would be ideal in my application.

In this new example this is actually possible, I believe you're not getting it because of the bins. As you may know, in order to reduce the number of possible splits that LightGBM can perform, the features are first binned and then the possible splits are the bin boundaries. The default min_data_in_bin is 3, so it's possible that the split you're referring to (feature <=1) wasn't actually computed here. You can get the result you described in the example reducing that parameter (notice that I set num_leaves=3 to get that extra split. I also set objective='l2' because I'm not sure how the predictions are computed with l1):
import lightgbm as lgb
import numpy as np

X = np.array([1, 3, 2, 2]).reshape(-1, 1)
y = np.array([0, 1, 0, 1])

ds = lgb.Dataset(X, y, params={'min_data_in_bin': 1})
model = lgb.train({'num_round': 3, 'num_leaves': 3, 'min_data_in_leaf': 1, 'objective': 'l2', 'learning_rate': 1}, ds)
np.round(model.predict(X), 2)
# array([0. , 1. , 0.5, 0.5])

If you change objective='binary' you can get roughly the same for classification:
ds = lgb.Dataset(X, y, params={'min_data_in_bin': 1})
model = lgb.train({'num_round': 3, 'num_leaves': 3, 'min_data_in_leaf': 1, 'objective': 'binary', 'learning_rate': 1}, ds)
np.round(model.predict(X), 2)
# array([0.02, 0.96, 0.52, 0.52])

And if this is correct, and tree splitting would stop before the metric is minimal, is there way to force such a behaviour?

Boosting will run for as many iterations as you specify and it can reach a very small loss. However, it requires that the features you provide allow it to get there. In this example for the last two samples there's nothing a tree can do to improve, because for f=2, y = 1 and y = 0, so there's no way to use this feature and improve the loss. If you had an extra feature that actually split these samples, then LightGBM would find it and split it to get to a perfect score.

You are correct. Your changes lead to a perfect fit. Thanks for this!
However, if the algorithm is finding the loss minimum, I don't understand why in my initial example a split at e.g. a = 0.5 would not do anything. The first three examples will be in one leaf and the other in the second leaf. Of course the mean of y will not change. Is this what you referring at as gain? The logit does not change. Is this the reason the split is not made?
This split would of course only make sense if the initial score is off, then the log loss would improve:
        import lightgbm as lgb
        import numpy as np
        import sklearn

        X = pd.DataFrame([[1, 0.1, 0.3], [1, 0.1, 0.3], [1, 0.1, 0.3],
                                         [0, 0.9, 0.3], [0, 0.9, 0.3], [0, 0.9, 0.3]], columns=["a", "b", "prob"])
        y = pd.Series([0, 0, 1, 0, 1, 0])

        ds = lgb.Dataset(X, y, init_score=X["prob"])
        model = lgb.train({'num_round': 3, 'num_leaves': 4, "metric": "logloss", 'min_data_in_bin': 1, 'min_data_in_leaf': 1,
                                        'objective': 'binary', 'learning_rate': 1}, ds)

        raw_y = scipy.special.logit(X["prob"]) + model.predict(X, raw_score=True)
        loss = sklearn.metrics.log_loss(y, scipy.special.expit(raw_y))
        # 0.6391075640678002

        loss = sklearn.metrics.log_loss(y,  np.array([0.333] * 6))
        # 0.6365141707948961

Basically the model learns nothing more than the correct offset / intercept in this case. 0.3 is already close but splitting the examples and predicting even a tiny bit more than 0.3 will improve the log loss.
Anyways I think this an extreme case and you proofed that the init_score is used in the correct way, so I assume its not buggy.

I don't understand why in my initial example a split at e.g. a = 0.5 would not do anything. The first three examples will be in one leaf and the other in the second leaf. Of course the mean of y will not change. Is this what you referring at as gain? The logit does not change. Is this the reason the split is not made?

A split will only be made if it makes a positive gain (the predictions are better than before). In that example you have 6 samples (2 positive and 4 negative, therefore that leaf has 2/6 = 33% positives), if you make a split at a <= 0.5 you'll have 3 samples in each leaf (1 positive and 2 negatives or 1/3 = 33% positives), so each leaf is pretty much the same as its parent (which means that performing that split results in no gain and therefore it won't be made). The same applies for b.
If you had a feature that could actually split the classes, something like: X['c'] = [0.2, 0.3, 0.7, 0.4, 0.8, 0.1]. Then when X['c'] <= 0.5 y = 0 and otherwise y = 1. This split would separate the classes effectively (have a positive gain) so it would be performed and you could achieve a very small loss.

Yes, you are correct and I think we might start going in circles :-)
Let's settle with the fact that a split will result in the same mean of y, so the same positive ratio in each leaf. By looking at this metric alone, there is no gain in splitting. This is exactly as you mentioned before. I got this and totally agree.
But suppose your init_score is off by far, say we predicted y to be only 0.01. When splitting, we should not compare the positive rate of 1/3 in the leafs with the positive rate in the original data of 1/3 but with the "predicted" initial positive rate of 0.01.  So a split would do nothing more than to trigger the model to correct this initial score.
We can simulate this by using a bagging since then the model would, by chance, see a subset of the data that needs correction.  Again an example (note I also switched to l2 norm, since you mentioned this is more familiar to you):
        import lightgbm as lgb
        import numpy as np
        import sklearn

        X = pd.DataFrame([[1, 0.1, 0.01], [1, 0.1, 0.01], [1, 0.1, 0.01],
                                         [0, 0.9, 0.01], [0, 0.9, 0.01], [0, 0.9, 0.01]], columns=["a", "b", "prob"])
        y = pd.Series([0, 0, 1, 0, 1, 0])

        ds = lgb.Dataset(X, y, init_score=X["prob"])
        model = lgb.train({'num_round': 10, 'num_leaves': 4, "metric": "logloss", 'min_data_in_bin': 1, 'min_data_in_leaf': 1,
                                       'objective': 'mse', 'learning_rate': 1, 'bagging_freq': 1, 'bagging_fraction': 0.7}, ds)
        loss = sklearn.metrics.log_loss(y, X["prob"] + model.predict(X, raw_score=True))
        # bagging_fraction=1.0 => 1.541756952565031
        # bagging_fraction=0.7 => 0.6365141682948128

        optimal_loss = sklearn.metrics.log_loss(y, np.array([1/3] * 6))
        # 0.6365141682948127

I understood that this is not how the algorithm works. But maybe you see my point that there is something to gain from a split, but the algorithms 'gain' is still zero.


Replace create react app with vite

This PR builds upon https://github.com/cogentapps/chat-with-gpt/pull/163 and thus includes the changes from that PR as well. If #163 gets merged, the diff in this PR will be smaller.
For reviewing purposes, you could check out the "Commits" tab and review the commits separately.

create-react-app seems to struggle a bit https://github.com/reactjs/react.dev/pull/5487#issuecomment-1409720741 and many folks are
recommending vite as an alternative, as that project is more active.
For me the reason to switch to vite is to reduce dependencies and speed
up the build process.
Replacing create-react-app with vite reduce the number of dependencies
from 1762 to 444.
I was also quite surprised, by how small the actual diff in this commit
is. From that perspective there is almost no discernible difference
between the two tools.

Not sure, if you are up for any major changes, I just forked this repository and started tinkering a bit - feel free to close it if it doesn't fit in your vision.
:warning: Please note that I didn't test this extensively, so further testing to verify that all features still work as expected is required. :warning:

Thanks for working on this!
I’ll need some time to review and test it out, but from a quick skim it looks good, and I agree with the reasoning for switching away from CRA.

Looks good, merging. Thanks again, this is great work!


Workflow fails when a new issue already belongs to a project

If the workflow runs on an issue that already exists in a project, it'll fail.
This can happen when convverting a note on the board into an issue, i.e.:

On the project board automated with this action, create a new note (with the ➕ button on the column)
In the drop-down menu on the note, choose "Convert to issue"
Note that the workflow fails.

Here's the error:
Run docker://takanabe/github-actions-automate-projects:v0.0.1
  env:
    GITHUB_TOKEN: ***
    GITHUB_PROJECT_URL: [REDACTED]
    GITHUB_PROJECT_COLUMN_NAME: [REDACTED]
/usr/bin/docker run --name takanabegithubactionsautomateprojectsv001_3c592a --label e87b52 --workdir /github/workspace --rm -e GITHUB_TOKEN -e GITHUB_PROJECT_URL -e GITHUB_PROJECT_COLUMN_NAME -e HOME -e GITHUB_REF -e GITHUB_SHA -e GITHUB_REPOSITORY -e GITHUB_RUN_ID -e GITHUB_RUN_NUMBER -e GITHUB_ACTOR -e GITHUB_WORKFLOW -e GITHUB_HEAD_REF -e GITHUB_BASE_REF -e GITHUB_EVENT_NAME -e GITHUB_WORKSPACE -e GITHUB_ACTION -e GITHUB_EVENT_PATH -e RUNNER_OS -e RUNNER_TOOL_CACHE -e RUNNER_TEMP -e RUNNER_WORKSPACE -e ACTIONS_RUNTIME_URL -e ACTIONS_RUNTIME_TOKEN -e GITHUB_ACTIONS=true -v "/var/run/docker.sock":"/var/run/docker.sock" -v "/home/runner/work/_temp/_github_home":"/github/home" -v "/home/runner/work/_temp/_github_workflow":"/github/workflow" -v "/home/runner/work/outcome-origination-platform/outcome-origination-platform":"/github/workspace" takanabe/github-actions-automate-projects:v0.0.1
2020/02/21 17:00:39 [INFO] Event name: issues
2020/02/21 17:00:39 [INFO] Payload for issues extract correctly
2020/02/21 17:00:39 [INFO] project url: [REDACTED]
2020/02/21 17:00:39 [INFO] Project Name: [REDACTED]
2020/02/21 17:00:39 [INFO] Project type:repository
2020/02/21 17:00:39 [INFO] Column Name: [REDACTED]
2020/02/21 17:00:39 [INFO] Project card is being added to column [REDACTED]
2020/02/21 17:00:40 [ERROR] POST https://api.github.com/projects/columns/[REDACTED]/cards: 422 Validation Failed [{Resource:ProjectCard Field:data Code:unprocessable Message:Project already has the associated issue}]
Failed to get results from GitHub
main.validateGitHubResponse
	/app/main.go:264
main.addToProject
	/app/main.go:239
main.main
	/app/main.go:86
runtime.main
=```

One workaround for this issue is to add continue-on-error: true to the github-actions-automate-projects step(s) of the job in your workflow .yml file.  This allows the job/workflow to succeed even if the project assignment step fails (i.e. because it was already assigned), eliminating the annoying failure emails.  More info:
https://help.github.com/en/actions/reference/workflow-syntax-for-github-actions#jobsjob_idstepscontinue-on-error

this will be solved with the latest docker image or v0.0.3 which I'm preparing
Related PR: https://github.com/takanabe/github-actions-automate-projects/pull/26


Always include data-layout attribute.

We're missing various styling like min-height when we don't include data-layout

Reassigning back to myself since the padding changes can mess with our printing stylings.

Discussed offline that we're okay with the vertical padding changes since we don't preserve the vertical padding from converted docs.

Still going to revert this because of the interactions with printing, as I raised previously (I unassigned reviewers because I didn't want this to merge yet).

Opened https://github.com/chanzuckerberg/czi-prosemirror/pull/31 instead


[RFC] Un-fused softmax for short-query(decode) attention

Motivation
FlashAttention saves memory access to softmax scores, which is critical for training or prefilling stage in inference, but not necessarily for decoding.
Proposal
Consider the case we don't fuse the two matrix multiplication, but use two kernels instead:

The first kernel computes the first GEMM $Q\cdot K$ and the first stage (compute $M, D$) of online softmax (check this note).
The second kernel computes the second stage of online softmax (divide $P$ by $D$) and computes the second GEMM $P\cdot V$.

Analysis
The I/O of each matrix in unfused kernel are:
$$ size(QO) = 2L_q\cdot H_{qo}\cdot D $$
$$ size(KV) = 2L_{kv}\cdot H_{kv}\cdot D $$
$$ size(softmax) = L_q\cdot L_{kv} \cdot H_{qo} $$
The ratio of $softmax$ (we double the I/O of softmax because we have to write it in the first kernel and read it in the second kernel) in the entire I/O is:
$$ \frac{1}{1 + \frac{H_{kv}}{H_{qo}}\frac{D}{L_{qo}} + \frac{D}{L_{kv}}} $$
For the decoding case, $L_q$ is $1$ so that ratio of softmax I/O can't exceed $1/(1+\frac{H_{kv}}{H_{qo}}D)$ and $D$ is usually a large value such as $128$, $\frac{H_{kv}}{H_{qo}}$ is the reciprocal of GQA group ratio (usually 4/8), so flashattention-style fusion is actually not very useful here, saving 1/16 I/O at most.
Benefits
But what are the benefits of un-fused kernels?

Less register pressure and we can use larger tiles for both stages.
We can use hardware instructions for in-place reduction. More explicitly, there are PTX instructions such as red.global (for early GPUs such as ampere) and cp.reduce.async (for Hopper) for inplace reduction: dst @ global = RedOp(dst @ global, src @ smem), the cp.reduce.async can leverage TMA and thus further reduce the epilogue time.

NOTE: we can also leverage cp.reduce.async for FlashAttention-style attention aggregation, but we need to know a prior rowmax $M$ beforehead (such as Flash-Decoding++) so that we don't need to multiply dst data on global memory with a renormalization term (there is no NVGPU instruction that supports dst @ global = RedOp(alpha * (dst @ global), src @ smem)).

Required Changes
What do we need to support in FlashInfer:

Implement gather-GEMM for both kernels.
Use RaggedTensor for softmax storage with proper padding so that we can easily read/write them in both kernels.

Concerns

Maintenance overhead in the future
If future models keep increasing GQA group ratio, the softmax I/O ratio will gradually dominate and it doesn't make sense not to fuse them.

I’m not convinced it’s worth implementing unfused softmax attention kernels, so I opened this issue to spark a discussion. Any feedback is appreciated!
cc @tqchen @JamesLim-sy @merrymercy @spectrometerhbh

Having $L_q$ to be 8~32 seems more common in serving settings.
Regardless, in the $L_q=1$ case,

the QK kernel is mem bound anyway.

The PV kernel probably can benefit from larger tile size and less register pressure.
In a fused kernel, you need to cache QKV (O can overlap), and have additional registers allocated for QK gemv.
In the second PV kernel, you need to cache PV (O can overlap).
But $L_q << L_{kv}$, so I feel Q plays marginal effect here.


False Positive: AI022700 (Microsoft WCF)

Found a false positive on one of the rules:
        "pattern": "ServiceContract|using System\\.ServiceModel|WSHttpBinding|[HttpGet]|[HttpPut]",

The [HttpGet] and [HttpPut] strings need to have the brackets escaped, otherwise they're interpreted as regexs (any H, t, p, P, u, or t character, etc.).

Thanks!


Liquibase with Simba JDBC, INVALID_ARGUMENT: Type not found: INT

hi,
trying to work with Liquibase + Liquibase Bigquery extension + Simba JDBC + emulator.
JDBC version 1.3.0 (https://storage.googleapis.com/simba-bq-release/jdbc/SimbaJDBCDriverforGoogleBigQuery42_<IP_ADDRESS>1.zip)
connection URL set as follow:
jdbc:bigquery://localhost:49946;ProjectId=project;DefaultDataset=dataset;Location=us-central1;RootURL=http://localhost:49946;OAuthType=2;OAuthAccessToken=a25c7cfd36214f94a79d;OAuthRefreshToken=1jt9Pcyq8pr3lvu143pfl4r86;OAuthClientId=11b5516f132211e6;LogLevel=6
liquibase tries to create it's metadata table with no success :
{"query": "CREATE TABLE dataset.DATABASECHANGELOGLOCK (ID INT, LOCKED BOOLEAN, LOCKGRANTED datetime, LOCKEDBY STRING(255))", "values": []}
{"error": "jobInternalError: failed to analyze: INVALID_ARGUMENT: Type not found: INT [at 1:48]"}
same code works fine with real BQ.

INT is not recognized in the Google ZetaSQL library. One workaround is to use a more explicit integer type i.e. INT64 in your queries.


Execute long running commands via a remote agent.

This makes LongRunningRemoteCommand a little more robust via two scripts run on the guest VM:

remote_command.py: executed via nohup, runs a command, holding a lock on a status file until the command exits.
wait_for_command.py: waits for the long running command to finish by waiting on the lock held by remote_command.py, then returns the long-running command's stdout and stderr, exiting with the command's exit status.  This can be safely retried on SSH failure.

We gain a bit of resilience on SSH flakiness, will catch non-zero exits from the long running command, and avoid parsing the command name to find the PID.
Ran HPCC against CentOS 6 and Ubuntu 14.04 to test.

I've done the first pass, mostly LGTM, just some questions need clarifications but almost ready to go.
Thanks for making this happen Connor!

Addressed comments. PTAL.

@stfeng: PTAL.

LGTM. Ship it!


fix: support for 32-bit ASN

The variable customer_gateway_bgp_asn now automatically sets bgp_asn or bgp_asn_extended whether the value cannot be represented as a 32-bit number
what
This PR adds support for ASN numbers greater than<PHONE_NUMBER>
why
Customer Gateways created by the module only use variable bgp_asn, which does not support 32-bit integers
Instead the aws_customer_gateway resource provides a different variable, bgp_asn_extended which is not currently used by the module
references
https://github.com/hashicorp/terraform-provider-aws/issues/38738

@Gowiem thank you for the comment, I've applied the changes you requested and aligned the PR with the latest commits.

/terratest

Hi @Gowiem, I've updated the versions.tf with the correct pin.

Merged latest changes from main and updated documentation due to AWS provider version update

Hi @Gowiem @nitrocode can you review the code? Thanks!

Bumping to minor because we're bumping the AWS Provider version.


Check playground manifests against baselines.

The purpose of this PR is to inject some steps into the build that will help us detect if the playground projects have not had their manifests and/or Bicep outputs regenerated. If someone adjusts the playground project we want to make sure we are seeing what the impacts are to the manifests across the spectrum of playground projects we have ... this will break the they get updated.

-      "path": "../../../../../Users/midenn/AppData/Local/Temp/tmp0cmpqc.tmp.bicep"
+      "path": "../../../../../../../../tmp/tmpMUnPth.tmp.bicep"

Are these paths correct?

-      "path": "../../../../../Users/midenn/AppData/Local/Temp/tmp0cmpqc.tmp.bicep"
+      "path": "../../../../../../../../tmp/tmpMUnPth.tmp.bicep"

Are these paths correct?

Nope. I need to figure out why that is happening.


API: limit arc move heights based on pipette max achievable height

P300 multi Gen2s are very tall on the top, with a homing position of 151. When you use a tall labware setup, like a Nest deep well plate on top of a magnetic module or an aluminum tube rack with screwcap tubes on top of a temperature module, the end of the tips of a P300 Multi Gen2 are less than 10mm - the default labware margin - from the top of the labware.
That means that arc moves that use deck.highest_z will try and drive the pipette up above its maximum achievable height, and you'll get a hard limit error.
Instead, we should

Have hardware controller expose the maximum height achievable by each pipette in deck coordinates (by taking the home position, subtracting the retract, passing it through deck calibration, and adding the critical point offset)
Have geometry.plan_moves take a maximum height input that will be based on that
If the planned move is above the max height, take it out of the extra margin
If the planned move is above the max height even after removing the margin, raise an exception

Based on this:
Total height of labware sitting on top of mag module: 128.25 mm
Bracket height: 4.052 mm
Safety margin: 10 mm
Safe height without tip = 142.27 (sum of above)
Safe height with tip = 142.27 + 39.997 (tip length) = 182.299 (absolute value from deck)
Highest point to be reached by the pipette: 181.5 (absolute homed position) - 2 mm (backoff distance) = 179.5 mm (smoothie value)
With our current margin, a P300 Gen2 Multi could exceed the max limit by ~2.80 mm.


PDF doesn't render in Android - No matter the source uri

Issue Description
PDF doesn't get rendered in Android but only in iOS. I tried both local file directory and an online pdf file. It only shows on iOS and not on Android.
Steps to Reproduce / Code Snippets
<PDFReader
           style={{
               width: Dimensions.get("window").width,
                height: Dimensions.get("window").height,
            }}
           source={{
               uri: "http://gahp.net/wp-content/uploads/2017/09/sample.pdf",
           }}
       />

Additional Information

React Native version: "https://github.com/expo/react-native/archive/sdk-37.0.1.tar.gz"
rn-pdf-reader-js version: "^3.1.0"
Platform(s) (iOS, Android, or both?): "both"
TypeScript version: "3.7.5"

I made the same comment here

+1

@xcarpentier, could you help, please?

This helped me.


[OLINGO-1435] New getter for HasStream

New getter as described in https://issues.apache.org/jira/browse/OLINGO-1435

Done


[SPARK-3325][Streaming] Add a parameter to the method print in class DStream

This PR is a fixed version of the original PR #3237 by @watermen and @scwf.
This adds the ability to specify how many elements to print in DStream.print.

Jenkins, test this.

Jenkins, test this.

Test build #24981 has started for   PR 3865 at commit 7c09f16.

This patch merges cleanly.

Test build #24981 has started for   PR 3865 at commit 7c09f16.

This patch merges cleanly.

Test build #24981 has finished for   PR 3865 at commit 7c09f16.

This patch fails Scala style tests.
This patch merges cleanly.
This patch adds no public classes.

Test build #24981 has finished for   PR 3865 at commit 7c09f16.

This patch fails Scala style tests.
This patch merges cleanly.
This patch adds no public classes.

Test FAILed.
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Test FAILed.

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Test build #24982 has started for   PR 3865 at commit cd34e9e.

This patch merges cleanly.

Test build #24982 has started for   PR 3865 at commit cd34e9e.

This patch merges cleanly.

Test build #24982 has finished for   PR 3865 at commit cd34e9e.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

Test build #24982 has finished for   PR 3865 at commit cd34e9e.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

Test PASSed.
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lgtm

lgtm

I have merged this. Thanks all!


Create clean/ca/hayward_pd.py

Additional details
Getting Hayward PD will require GovQA platform code #128 , with Hayward as (one of) the inaugural examples.
Related pull request(s)

#128

Hayward draft code and sample metadata output is available.

This was a one-off, we ran it and uploaded the files to our case files repo.


multiple credentialIds for ssh-agent

The ssh-agent plugin can provide multiple SSH keys to a build. This pull request surfaces this functionality like this:
ssh-agent('acme', 'bracme')

The test run fails on codenarc. How can I see the report?

You can run the build locally with ./gradlew build.
I tested this PR and it does not work for me. The job's config page shows only one credential. Make sure to test your changes in Jenkins before open a PR.


Determine the language of a comment and bail if it's not in English

Input: tolerance
Output: bool (True/False)
Methods:

using pyenchant to check if word in spellchecker's language

may be issue installing on Windows, otherwise, bottleneck performance on large amounts of words

set(nltk.corpus.words.words()) --> may be a good place to start

Task completed with commit: https://github.com/recommeddit/labs/commit/c6ca9ca9f4c9936d10cd3e7ae5302f123518578c


sending nil body of type *bytes.Buffer in http.NewRequest() function is causing panic

Please answer these questions before submitting your issue. Thanks!
What version of Go are you using (go version)?
go version go1.10.3 linux/amd64
Does this issue reproduce with the latest release?
yes
What operating system and processor architecture are you using (go env)?
GOARCH="amd64"
GOBIN=""
GOCACHE="/home/okumar/.cache/go-build"
GOEXE=""
GOHOSTARCH="amd64"
GOHOSTOS="linux"
GOOS="linux"
GOPATH="/home/okumar/GO_Workspace"
GORACE=""
GOROOT="/usr/local/go"
GOTMPDIR=""
GOTOOLDIR="/usr/local/go/pkg/tool/linux_amd64"
GCCGO="gccgo"
CC="gcc"
CXX="g++"
CGO_ENABLED="1"
CGO_CFLAGS="-g -O2"
CGO_CPPFLAGS=""
CGO_CXXFLAGS="-g -O2"
CGO_FFLAGS="-g -O2"
CGO_LDFLAGS="-g -O2"
PKG_CONFIG="pkg-config"
GOGCCFLAGS="-fPIC -m64 -pthread -fno-caret-diagnostics -Qunused-arguments -fmessage-length=0 -fdebug-prefix-map=/tmp/go-build577645390=/tmp/go-build -gno-record-gcc-switches"
What did you do?
If possible, provide a recipe for reproducing the error.
A complete runnable program is good.
A link on play.golang.org is best.
https://play.golang.org/p/fQfn9BincB-
What did you expect to see?
Sending a nil body of type *bytes.Buffer should not cause panic
What did you see instead?
panic: runtime error: invalid memory address or nil pointer dereference
[signal SIGSEGV: segmentation violation code=0xffffffff addr=0x0 pc=0x22e622]
goroutine 1 [running]:
bytes.(*Buffer).Len(...)
/usr/local/go/src/bytes/buffer.go:74
net/http.NewRequest(0x2b335f, 0x3, 0x2b70da, 0x15, 0x2fa500, 0x0, 0x3ae01, 0x6d4, 0x1073a040, 0x0)
/usr/local/go/src/net/http/request.go:802 +0x662
main.main()
/tmp/sandbox012127239/main.go:11 +0x60

When a function takes in an io.Reader, you should generally only send an untyped nil or an actual variable that can be read from. For example, passing it nil directly, or a zero io.Reader variable: https://play.golang.org/p/2eYCsyygdZ9
Passing it a nil *bytes.Buffer breaks because the bytes.Buffer.Read method ends up being called, and a *bytes.Buffer cannot be used if it is nil.
In the future, for questions about Go, see https://golang.org/wiki/Questions.


Changes in file structure and makefile

Added apt-update to prevent installations to fail on debian with old apt caches.
Added folder for Interpolation as per decided Issue.
Renamed 3_playing_with_colors to 3_playing_with_images as per decided file structure.
Removed folder for 2_color_spaces_conversion as per decided content.

OpenCV overview is the second last topic before blob detection, and arrange the interpolation according the sequence of the timetable

Please check, I've made changes as suggested


More changes to the docs!

Proposed changes:

Added new information to docs

I'm in the middle of learning about redux which I found out the project uses, so ill be learning that before I continue making the docs on reducers or anything :smile:

I umm dont know what to do since it errored, but I assume you have to do something to get it working? If you need me to do something then just tell me please.

Changes Unknown when pulling e9cb97c085f5b6a3fe4b0a187d99938bc9d96178 on GambitAnimating:patch-3 into ** on jacob-grahn:master**.

Looks good, thanks! Jiber doesn't use Redux, but it was very heavily inspired by Redux.

Anytime! Working on this project is really fun, but ohhh I see, so would learning about redux help?


Potential PSNR calculation issue due to in-place resize operation of non-contiguous tensors

Hello,
Thank you for your excellent open-source work!
I’ve encountered a potential issue with the calculation of PSNR in newer versions of PyTorch, which I believe is caused by  the in-place resize operations of non-contiguous tensors.
Specifically, notice that slice operations are performed before calling criterion_psnr, creating non-contiguous tensors:
loss_psnr = criterion_psnr(output[:, :, 128:-128, 128:-128], target[:, :, 128:-128, 128:-128])

Later, in the Loss_PSNR class, we use in-place operations with resize_:
Itrue = im_true.clamp(0., 1.).mul_(data_range).resize_(N, C * H * W)
Ifake = im_fake.clamp(0., 1.).mul_(data_range).resize_(N, C * H * W)

However, the torch.Tensor.resize_ method assumes the input tensor is contiguous, which may lead to unintended data access. Please see PyTorch 1.7.0 resize_:

Warning
This is a low-level method. The storage is reinterpreted as C-contiguous, ignoring the current strides (unless the target size equals the current size, in which case the tensor is left unchanged). For most purposes, you will instead want to use view(), which checks for contiguity, or reshape(), which copies data if needed. To change the size in-place with custom strides, see set_().

Therefore, the current implementation relies on  the clamp operation to produce a contiguous output, which seems not to be guaranteed by PyTorch conventions.
A quick evaluation can be made like this:
assert (im_true.reshape(N, C * H * W) != im_true.clone().resize_(N, C * H * W)).any()

Maybe we can change the resize_ to reshape for robustness purpose?
Possibly related issues: #4, #8, #29, #45.
Thanks!

Hi, thanks for reminding us! I pin this issue with the label.
If you find our repo useful, please help us star it :)


Skip SCHEDULED/IN_PROGRESS task

Hi
I was wondering if we can skip IN_PROGRESS task. We would like to skip a task that was already IN_PROGRESS, and continue the workflow.
I modified the following code to achieve this, could anyone please let us know if it is okay or has any side effect?
In common/metadata/tasks/TaskResult.java
@@ -30,7 +30,7 @@ public class TaskResult {
    public enum Status {

          IN_PROGRESS, FAILED, COMPLETED, SCHEDULED;              //SCHEDULED is added for the backward compatibility and should NOT be used when updating the task result

          IN_PROGRESS, FAILED, COMPLETED, SCHEDULED, SKIPPED; //SCHEDULED is added for the backward compatibility and should NOT be used when updating the task result
  };

In core/execution/DeciderService.java, function decide(..)
@@ -183,7 +183,7 @@ public class DeciderService {
return;
}

          List<Task> pendingTasks = workflow.getTasks().stream().filter(t -> (!t.isRetried() && !t.getStatus().equals(Status.SKIPPED)) || SystemTaskType.isBuiltIn(t.getTaskType())).collect(Collectors.toList());

          List<Task> pendingTasks = workflow.getTasks().stream().filter(t -> (!t.isRetried()) || SystemTaskType.isBuiltIn(t.getTaskType())).collect(Collectors.toList());
          boolean reeval = false;

Thanks!

Hi, We thought about it, we do not want to mess up your SKIPPED concept, so can we add "no-op" field in the task result? A task can be set to "no-op" when it was scheduled/in_progress, which means it did not perform any action after it started.

@lilwan how is no-op different from just marking the task as completed with no output?

@v1r3n Thanks for the reply, because we would like to show user that the task was not actually performed. If we mark it completed with no output, user may confused with other task which we have that is actually performed and completed but no output.

@lilwan maybe an additional attribute can be added to task output indicating no work was performed?


Fork

This pull request has all the DNN Database tables created as classes (in the Data folder) with foreign key constraints implemented. It also includes the EF migration script to dynamically build the DNN Database at runtime.

Awesome @CBPSC - that is a lot of great and monotonous work there sir!


Support async/await

Is it possible to use this validator with async/await?

async/await is a feature of the language, not of a library. Your code with async/await constructions will work till you have proper browser support or do a transpiling.


Add example and document undocumented behavior for Get-AzureADGroupMember

Add example and document undocumented behavior for Get-AzureADGroupMember

If -All is not specified (or false), and -top is not specified, only the first 100 members are returned in a query.
Add example of -All

Docs Build status updates of commit 60d0cf2:
:white_check_mark: Validation status: passed

File
Status
Preview URL
Details

azureadps-2.0/AzureAD/Get-AzureADGroupMember.md
:white_check_mark:Succeeded
View (azureadps-2.0)

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

Thanks @anstein-msft for your contribution.
@CelesteDG, this is good to go.


Changed the Bulgarian module to avoid using \d and \D

The Bulgarian module did not work in LibreOffice. When I investigated, it turned out that \d and \D are apparently not supported by the regex engine used in LO under Windows, so I expanded them to [0-9] and [^0-9] respectively. The module now appears to work correctly (tested both in Calc and in Writer).

Thanks for your bug report and patch. Likely the solution will be replacing \d, \D with their portable equivalent [0-9], [^0-9]...


Working with Swift 2 and Xcode 7

These updates bring UIImageColors.swift and the playground up to speed with Swift 2 and Xcode 7. They aren't backwards compatible without Xcode 6 though so if you want to accept the PR I'd recommend doing it on a swift-2.0 branch for now.

Thanks, but @devxoul already made a PR for Swift 2 migration.


Chicken and goose infestation

Upppon starting a new game I have found too many of chicken and goose are be being generated by villages and towns which appreas to be upsetting the economy of other items.

All animal productions have been fixed as of <IP_ADDRESS>. Thanks.


Not working for me!

Running StardewXnbHack 1.1.1.
Found game folder: C:\Steam\steamapps\common\Stardew Valley.
Loading game instance...
Unhandled exception: System.Reflection.ReflectionTypeLoadException: Unable to load one or more of the requested types.
Could not load type 'StardewModdingAPI.IManifestPrivateAssembly' from assembly 'SMAPI.Toolkit.CoreInterfaces, Version=<IP_ADDRESS>, Culture=neutral, PublicKeyToken=null'.
at System.Reflection.RuntimeModule.GetTypes(RuntimeModule module)
at System.Reflection.Assembly.GetTypes()
at StardewValley.LocalMultiplayer.GetStaticFieldsAndDefaults() in D:\GitlabRunner\builds\Gq5qA5P4\0\ConcernedApe\stardewvalley\Farmer\Farmer\LocalMultiplayer.cs:line 121
at StardewValley.LocalMultiplayer.Initialize() in D:\GitlabRunner\builds\Gq5qA5P4\0\ConcernedApe\stardewvalley\Farmer\Farmer\LocalMultiplayer.cs:line 92
at StardewValley.GameRunner..ctor() in D:\GitlabRunner\builds\Gq5qA5P4\0\ConcernedApe\stardewvalley\Farmer\Farmer\LocalMultiplayer.cs:line 440
at StardewXnbHack.Program.CreateTemporaryGameInstance(PlatformContext platform, String contentPath) in /home/pathoschild/git/StardewXnbHack/StardewXnbHack/Program.cs:line 327
at StardewXnbHack.Program.Run(String[] args, GameRunner game, String gamePath, Func`3 getLogger, Boolean showPressAnyKeyToExit) in /home/pathoschild/git/StardewXnbHack/StardewXnbHack/Program.cs:line 149
System.TypeLoadException: Could not load type 'StardewModdingAPI.IManifestPrivateAssembly' from assembly 'SMAPI.Toolkit.CoreInterfaces, Version=<IP_ADDRESS>, Culture=neutral, PublicKeyToken=null'.

Written with the help of a translator.
I reinstalled Stardew Valley and tried unsuccessfully.

Download
https://www.mediafire.com/file/nyekc4ehyxg2ijy/fix.zip/file
In the installer menu, select "gcc."

Download
https://www.mediafire.com/file/nyekc4ehyxg2ijy/fix.zip/file
In the installer menu, select "gcc."

Mediafire blocked the download of the file. :(
Dangerous File Blocked
The file you attempted to download was determined to be dangerous. For your protection, MediaFire does not enable distribution of dangerous files.

@dswpg1 Hi! The StardewXnbHack 1.1.1 prerelease version is for Stardew Valley 1.6.9-beta only. You probably have Stardew Valley 1.6.8, so you should use StardewXnbHack 1.1.0 instead.


[New Team]: no(low)-code tools for DAO,NFT,AI (ERC4337)

Introduction

a full-stack dev in tokyo (prefer frontend dev and UX).
been involved in web3 for about 4 years, mainly DeFi project.
have attended ethglobal hackathons several times and got some prizes.
I would like to try a passkey idea, but I would like to join any other team that has a good idea.

Idea description

set up app web3 functionality (dify.ai like UI) and publish app link
create accounts with passkey (smartwallet.dev or safe or other AA)
add web3 functionality to existing apps and groups via app link

Skillset

interested in this area and would like to discuss ideas.

[ ] Core Blockchain Development (Go, Rust, C++)

[x] Smart Contracts (Solidity, Vyper)

[x] dApps (JavaScript, webdev)

[ ] Blockchain Operations, Infrastructure

[ ] Game theory, Crypto-Economics

[ ] Design, User Experience

[ ] Project Management

[ ] Other: ...

Communication

telegram: yujiym
twitter: @yujiym

@yujiym messaged you on Telegram


Add Typescript support

is there typescript definition file available  for croppie to make it work for typescript angulr2 projects

See https://github.com/Foliotek/Croppie/issues/180#issuecomment-237901436

type definitions for this library already exist at https://www.npmjs.com/package/@types/croppie
npm i --save-dev @types/croppie croppie
should give you all you need to use this in Typescript, a problem with the type definitions should probably be reported to the maintainer there? If you want to add the type definitions to the package.json I'm happy to put a pull request together but I don't think it's necessary?

Can this be updated to the newest version (2.5)?

Try this one: import Croppie from 'croppie';

That doesn't add Typings


Flaky test: test_operator.test_op_roi_align

======================================================================

FAIL: test_operator.test_op_roi_align

----------------------------------------------------------------------

Traceback (most recent call last):

  File "/usr/local/lib/python3.5/dist-packages/nose/case.py", line 198, in runTest

    self.test(*self.arg)

  File "/work/mxnet/tests/python/unittest/common.py", line 157, in test_new

    orig_test(*args, **kwargs)

  File "/work/mxnet/tests/python/unittest/test_operator.py", line 6170, in test_op_roi_align

    test_roi_align_value()

  File "/work/mxnet/tests/python/unittest/test_operator.py", line 6149, in test_roi_align_value

    assert np.allclose(data.grad.asnumpy(), dx, atol = 1e-6), np.abs(data.grad.asnumpy() - dx).max()

AssertionError: 1.3150275e-06

-------------------- >> begin captured logging << --------------------

common: INFO: Setting test np/mx/python random seeds, use MXNET_TEST_SEED=1619190489 to reproduce.

--------------------- >> end captured logging << ---------------------

http://jenkins.mxnet-ci.amazon-ml.com/blue/organizations/jenkins/incubator-mxnet/detail/PR-11058/1/pipeline

Relax with rtol should be fine, the diff is acceptable

@zhreshold increased the rtol to 1e-4 and passed 500 consecutive test runs, the change is included in #11058

This failure persists - http://jenkins.mxnet-ci.amazon-ml.com/blue/rest/organizations/jenkins/pipelines/incubator-mxnet/branches/PR-11229/runs/9/nodes/752/log/?start=0

Hi @anirudhacharya, please note that the problem is not this test but many tests are failing if you scroll up. This is documented in https://github.com/apache/incubator-mxnet/issues/11395

Seems to still happen:
======================================================================
FAIL: test_operator_gpu.test_op_roi_align
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/local/lib/python2.7/dist-packages/nose/case.py", line 197, in runTest
    self.test(*self.arg)
  File "/usr/local/lib/python2.7/dist-packages/nose/util.py", line 620, in newfunc
    return func(*arg, **kw)
  File "/work/mxnet/tests/python/gpu/../unittest/common.py", line 173, in test_new
    orig_test(*args, **kwargs)
  File "/work/mxnet/tests/python/gpu/../unittest/test_operator.py", line 6994, in test_op_roi_align
    test_roi_align_value()
  File "/work/mxnet/tests/python/gpu/../unittest/test_operator.py", line 6970, in test_roi_align_value
    assert np.allclose(output.asnumpy(), real_output)
    AssertionError:
-------------------- >> begin captured logging << --------------------
common: INFO: Setting test np/mx/python random seeds, use MXNET_TEST_SEED=35650200 to reproduce.
--------------------- >> end captured logging << ---------------------

http://jenkins.mxnet-ci.amazon-ml.com/blue/organizations/jenkins/mxnet-validation%2Funix-gpu/detail/master/45/pipeline

Maybe we should take another look, however, the log won't show the detailed error anymore?

Maybe there is some difference between C++ implementation and Python implementation. I will test and fix it.

When MXNET_TEST_SEED=35650200, the error shows that:
AssertionError:
Items are not equal:
Error 3.147267 exceeds tolerance rtol=0.000010, atol=0.000000.  Location of maximum error:(6, 0, 0, 1), a=0.005887, b=0.005887
 a: array([[[[<PHONE_NUMBER>9,<PHONE_NUMBER> ,<PHONE_NUMBER>5,<PHONE_NUMBER>2],
         [<PHONE_NUMBER>9,<PHONE_NUMBER>4,<PHONE_NUMBER>9,<PHONE_NUMBER> ],
         [<PHONE_NUMBER>7,<PHONE_NUMBER>8,<PHONE_NUMBER>4,<PHONE_NUMBER>1]],...
 b: array([[[[<PHONE_NUMBER>7,<PHONE_NUMBER>1,<PHONE_NUMBER>5,<PHONE_NUMBER>9],
         [<PHONE_NUMBER> ,<PHONE_NUMBER>4,<PHONE_NUMBER>8,<PHONE_NUMBER>2],
         [<PHONE_NUMBER>3,<PHONE_NUMBER>7,<PHONE_NUMBER>1,<PHONE_NUMBER>5]],...

It's strange.


Children not exiting with overviewer

Children are not killed when overviewer quits. This is problematic with long running scripts such as servers etc.

A simple process.on('exit', () => child.kill()) can do the trick. However I notice that you use webpack to compile your published files and it will shim process and it's not a good thing. You should probably compile your lib using babel alone. Is there a reason for you to use webpack here?

Hi @Yomguithereal
I added your solution in e68764205bdb37e0eccb87e8af0e87c955f43396 and published a new minor version – I am pretty sure what webpack does not shim process because I configured to build a bundle for Node (and not the browser) so it should work.

@renke I am still having an issue with child processes not exiting. Any advice?
I tried a variety of similar packages and this issue happened with all of the following:

http-server
lr-http-server
webpack-dev-server

The first time, everything runs fine. If I quit overviewer and start it again, I get "port is already in use" type warnings. I then have to manually kill the process before restarting overviewer.


kerberos / ldap / imap inside docker images ?

Hi,
Why there is kerberos / ldap package installed inside the docker image of php8 ?
https://github.com/artifakt-io/artifakt-docker-images/blob/9907b05b071a6b441cbb71a91f4ba9719097f2fd/magento/2.4-php8/Dockerfile#L57-L60
According to devdocs it's not needed but maybe used by artifakt ?
https://experienceleague.adobe.com/docs/commerce-operations/installation-guide/prerequisites/php-settings.html?lang=en
cc @an0rak-dev

In case we have to keep ldap, we have to change this line :
ldap --with-libdir=lib/x86_64-linux-gnu
by:
ldap --with-libdir=lib/$(uname -m)-linux-gnu
In order to make it works with arm64
Thanks


Add table expiry

Description & motivation
Add hours_to_expiration as an option to external tables in bigquery
resolves: #225
version: 2

sources:
  - name: test
    loader: gcloud storage
    dataset: "{{ target.dataset }}"
    tables:
      - name: test
        description: Sheet
        external:
          hours_to_expiration: 24
          location: 'https://docs.google.com/spreadsheets/d/id'
          options:
            format: google_sheets
            skip_leading_rows: 1
            sheet_range: 'sheetrange'
        columns:
          - name: column_name
            data_type: STRING
            description: "Column Name"

Checklist

[x] I have verified that these changes work locally
[x] I have updated the README.md (if applicable)
[x] I have added an integration test for my fix/feature (if applicable)

any progress on this @thomas-vl?


Update Weekly External Release manifest

Update weekly manifest

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Fix handling of enclitics in word tokenizer

Handles: -que, -ne, -ue/-ve, -cum
Includes expanded and better organized list of exceptions
Prepends '-' (hyphen) to separated enclitics to better mark them in returned list, e.g. 'arma virumque' > ['arma','virum','-que']

Fantastic. Only qualm is that one of my tests is broken. Would you mind, Patrick, fixing the test at cltk/tests/test_tokenize.py?
Error output below from https://travis-ci.org/kylepjohnson/cltk/builds/73632567.

======================================================================
FAIL: Test Latin-specific word tokenizer.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/travis/build/kylepjohnson/cltk/cltk/tests/test_tokenize.py", line 60, in test_latin_word_tokenizer
    self.assertEqual(tokens, target)
nose.proxy.AssertionError: Lists differ: ['atque', 'haec', 'abuter', '-que', 'nihil'] != ['atque', 'haec', 'abuter', 'que', 'nihil']
First differing element 3:
-que
que
- ['atque', 'haec', 'abuter', '-que', 'nihil']
?                              -
+ ['atque', 'haec', 'abuter', 'que', 'nihil']

Don't have a lot of experience with testing, but it seems to pass for me.
Output:
(diss)diyair:cltk diyclassics$ python ./tests/test_tokenize.py
..
Ran 2 tests in 0.746s
OK


Customizable OpenAI API  / proxy

Could you consider adding support for customizing OpenAI API or proxy address? This would make it easier to integrate some custom LLMs.
Thanks a lot.

Hi there,
would you like to integrate it? Can you share examples, maybe someone would like to implement it.
I am busy with some other tasks and not located in my homebase atm.

Close issue.

Close issue


Check spelling and correctness of import statements

Case 1
Input line: import math
Assume the keyword "import" is correctly typed
Extract the word immediately following "import"
Perform a search of this word against a list of Python standard libraries
If it exists, pass
If it does not exist, syntax error identified, offer suggestions (to be designed)
Case 2
Input line: from random import randint
Search for the keyword "from"
If it is not the first word (i.e. index 0), syntax error identified
If it is, continue:
Extract the word immediately following "from"
Perform a search of this word against a list of Python standard libraries
If it exists, pass
If it does not exist, syntax error identified, offer suggestions (to be designed)
At this point, no measures are taken to verify if randint belongs to the random module


Bug fix: Dapars parsing output with wrong cast to string

Fixes #207
Checklist

[x] I have performed a self-review of my own code
[x] I have commented my code, particularly in hard-to-understand areas
[x] I have updated corresponding READMEs (if applicable)
[x] My code follows the templates/style guidelines of the repository
[x] In- and output formats comply with APAeval specifications
[x] No parameters or file names are hardcoded
[x] Results, logs or other output is not commited to the repository
[x] I have tested my code

Thanks! The fix seems to work :) Tested differential usage on this branch and the output file now carries two genes, which based on dapars_output_All_Prediction_Results.txt have both the lowest observed p-value.
Possibly easier to merge this one before the big refactoring.

Thanks for reviewing and approving this PR @dominikburri ! :D Sounds good, I'll aim to merge this fist before the refactoring PR


tsp, update cadl ranch

Add 1 multipart test.
I cannot test @flattenProperty because I disabled the feature for DPG :-(
(and I don't want to open it just for a test)
@haolingdong-msft after this merged, you can add patch test, or ask Hong to add.

sure, for json-merge-patch, I will update myself.


updated to DotnetCore 1.0.1

Hi,
I've updated the DotnetCore to the latest version.
C+++

Hi @khelben, I'm your friendly neighborhood .NET Foundation Pull Request Bot (You can call me DNFBOT). Thanks for your contribution!

In order for us to evaluate and accept your PR, we ask that you sign a contribution license agreement. It's all electronic and will take just minutes. I promise there's no faxing. https://cla2.dotnetfoundation.org.

TTYL, DNFBOT;

@khelben, Thanks for signing the contribution license agreement so quickly! Actual humans will now validate the agreement and then evaluate the PR.
Thanks, DNFBOT;

we've done that manually. thanks!


Console width off by one on some terminals / ssh

On some consoles the output width seems to be calculated one character too wide. See the following example:
>>> from rich.console import Console
>>> from rich.table import Table
>>> c = Console()
>>> t = Table("Yo!", "Tables!")
>>> t.add_row("a", "row")
>>> t.add_row("another", "row")
>>> c.print(t)
┏━━━━━━━━━┳━━━━━━━━━┓

┃ Yo!     ┃ Tables! ┃

┡━━━━━━━━━╇━━━━━━━━━┩

│ a       │ row     │

│ another │ row     │

└─────────┴─────────┘

>>> c = Console(width=c.width-1)
>>> c.print(t)
┏━━━━━━━━━┳━━━━━━━━━┓
┃ Yo!     ┃ Tables! ┃
┡━━━━━━━━━╇━━━━━━━━━┩
│ a       │ row     │
│ another │ row     │
└─────────┴─────────┘

I played around a bit and tested some combinations, some seem fine, others not:

ssh terminal in vscode: OK
ssh terminal in ConEmu: one too wide
ssh terminal in Windows command interpreter (Win+R, cmd): one too wide

Source System is Win10, the system the console runs on was either Ubuntu 18 or Oracle Linux
A possible workaround is as shown above: get a Console, and then get another one which is one narrower than the first one.
Looking ath the code, i understand that you are retrieving the terminal size via shutil.get_terminal_size(), so maybe that issue is beyond the reach of the lib.

I've noticed this on Windows terminal. I think the issue is that the Windows terminal treats a new line character has having width of 1. On Linux terminal emulators the new line has no width.
The master branch does width-1 for windows, but it doesn't feel like a good solution, so I'm investigating alternatives.

I just tried it with the code at the master branch with no luck. I think it is because the code does not run on Windows, i just connect to the terminal from a windows machine.
I'll stick with the workaround for the moment, i think i can spare that one character even if it is not necessary to cut it. Besides of this little issue, rich is a great lib!

Glad you like it.
With a bit of experimentation, it appears as though Windows inserts new lines for you when the text reaches the right of the terminal, MacOS and Linux doesn't. I think the only option is to always subtract 1, as you did. v0.3.3 has that fix.


fix(es/compat): Super method call in loose mode

Description:

Seems like to be caused by #5576 cc @magic-akari
BREAKING CHANGE:

Related issue (if exists):
closes #5936

Can you add a fixture test for this case?


How to add a custom class?

I have a condition on my layout
"other",
                        {
                            "key" : "other_explain",
                            "condition" : "model.other",
                            "type" : "textarea"
                        }

Now I want to add a custom class to other_explain key.

What exactly are you trying to achieve? Do you want the textarea widget to have a custom HTML class? Something like this? <textarea class="yourCustomClass">...</textarea> ?
I'm not an expert user of this plugin but afaik, that's not possible. You could try using the form array in the json-definition of your form, wrap a "parent" section element around your other_explain, assign yourCustomClass to that and do some CSS-magic. I'm thinking of something like this:
"form": [
  {
    "type": "section",
    "htmlClass": "yourCustomClass",    // parent-div with your custom class
    "items": [
      "other_explain"                  // your textarea "other_explain"
    ],
    ...

Hope this helps. But I suggest you describe what you want to achieve in a little bit more detail

@RichardMViGEM <textarea class="yourCustomClass">...</textarea> This is what I want to acheive.

@subratawebops
have you got the solution

@rmayuri try this
layout = [
    ... ,
    {
         key: 'MY_KEY',
         title: 'MY_TITLE',
         htmlClass: 'custom_css_class',
         fieldHtmlClass: 'custom_field_css_class',
         labelHtmlClass: 'custom_label_css_class',
         itemLabelHtmlClass: 'custom_itemlabel_css_class',
         activeClass: 'custom_active_css_class',
         labelHelpBlockClass: 'custom_help_css_class',
         etc..

    },
    ...
]

Have you tried this:
{
      "key" : "other_explain",
      "condition" : "model.other",
      "type" : "textarea",
       "htmlClass": 'yourCustomClass'
}

?

This doesn't work at all.

@subratawebops
it worked for me, place the css in style.css file

@rmayuri Could you tell me which css class getting applied among
htmlClass: 'custom_css_class',
         fieldHtmlClass: 'custom_field_css_class',
         labelHtmlClass: 'custom_label_css_class',
         itemLabelHtmlClass: 'custom_itemlabel_css_class',
         activeClass: 'custom_active_css_class',
         labelHelpBlockClass: 'custom_help_css_class'

I'm using angular2-json-schema-form as a dependency and I want to apply some custom classes to the fields and I didn't manage to do it. Any ideas please?

mylayout = [
{ key: 'msid',
labelHelpBlockClass: 'col-xs-10',
fieldHtmlClass:"form-control",
labelHtmlClass: "col-xs-2",
}
]
add style class in style.css file

I don't know why I need it and where to put it. The idea is that in the past I had a module named "angular-json-form-renderer" (which was a custom angular2-json-schema-form) and there I didn't had styles or something, the custom styles were applied without any "myLayout" . Now, I use directly "angular2-json-schema-form" as a dependency and the styles are not working. I hope you understand the issue.


[BUG] Scanner goes Not working every time. SPO environment is relatively small and doing Classic Workflow detection since they will be retired soon.

Problem Area
[ ] Page Transformation: Error during the use of page transformation from PnP PowerShell
[ ] Page Transformation: Error during the use of page transformation from .Net
[ ] Page Transformation: Page is not looking correct after transformation
[x ] Modernization Scanner: something went wrong...
Expected or Desired Behavior
Expecting the scan to kick off and run.
Observed Behavior
Scanning tool goes Not working. Does not produce an error code.
Steps to Reproduce
Running the Scanner produces this each time, on 2012 R2 and Win 10.

Please open a cmd prompt and launch the scanner executable from the prompt, this will show the error in in the cmd prompt. Also please provide the settings you've entered in the scanner

Closing this issue as there was no feedback for the last 2 weeks. If this still is a problem then please create a new issue and do what I've proposed in the previous comment. Thanks for your understanding.


Test diff generated

CI gfxreconstruct build queued with queue ID 45141.

CI gfxreconstruct build # 2258 passed.


fix: add refactor type to githooks

Signed-off-by: iyear<EMAIL_ADDRESS>Pre-Checklist
Note: please complete ALL items in the following checklist.

[x] I have read through the CONTRIBUTING.md documentation.
[x] My code has the necessary comments and documentation (if needed).
[x] I have added relevant tests

Description
Add refactor type to githooks
Related Issues
close #831

lgtm


API call failed in Console when using '+' or '-'

See screenshot:

Doing a Call Resourse against the mock server fails when using the '+' or '-' characters in the parameter fields.

@sgriffiths Could you try using GREATER%2BBRISBANE-QLD? That said, please note that is a repository for the API Blueprint spec. The above issue is an apiary documentation issue. Please send an email to apiary support from the next time. Thanks.
@Baggz Are we encoding the values given for URI parameters?

Hi,
That works when using "GREATER%2BBRISBANE-QLD". Will go through support next time.


[CWS] ensure GetEvents is actually streaming

What does this PR do?
CWS events are streamed from the system probe to the security agent through gRPC. The previous implementation of GetEvents was broken in a way that was closing the stream:

every 10 messages
every second
when the rate limiter was hit

This meant that instead of streaming events, we were actually:

opening a stream
streaming a small amount of events
closing it directly
every seconds at least, adding 2 potentially costly operations to the mix (open/close)

This PR fixes the GetEvents issue we were seeing, ensuring we are actually streaming events between the security agent and the system probe.

Motivation

Additional Notes

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes
This change should be a no-op from a functional point of view, but should mean that the security agent and the system probe should use way less CPU when the event count is higher than the rate limiter.
Reviewer's Checklist

[ ] If known, an appropriate milestone has been selected; otherwise the Triage milestone is set.
[ ] Use the major_change label if your change either has a major impact on the code base, is impacting multiple teams or is changing important well-established internals of the Agent. This label will be use during QA to make sure each team pay extra attention to the changed behavior. For any customer facing change use a releasenote.
[ ] A release note has been added or the changelog/no-changelog label has been applied.
[ ] Changed code has automated tests for its functionality.
[ ] Adequate QA/testing plan information is provided if the qa/skip-qa label is not applied.
[ ] At least one team/.. label has been applied, indicating the team(s) that should QA this change.
[ ] If applicable, docs team has been notified or an issue has been opened on the documentation repo.
[ ] If applicable, the need-change/operator and need-change/helm labels have been applied.
[ ] If applicable, the k8s/<min-version> label, indicating the lowest Kubernetes version compatible with this feature.
[ ] If applicable, the config template has been updated.

Can you add QA instructions :)))))

Yes after close we reopened the stream. I already added QA instructions, basically there is nothing more to do than ensuring the security agent is still receiving events


[Issue] Cluster Bomb Hardly Ever Being Used

In room 4 (41661), my Cluster Bomb has hardly (or never) been used in 7000 levels / 5 hours. Logic needs to be revisited to utilize this cooldown - it doesn't appear to be used on bosses due to there only being one target, and it's never used on creep/spawner waves because they die so quickly. Occasionally I'll see someone use theirs but I believe its a manual usage, almost never script used.

Fix in  #170

Yep, that would do it. Nice.

Should be fixed by 04436e14506881b58d6016b233dbe0743c1d7417

Yep. Closing.


Add transport data from maps.yandex.ru api

Breaking Change:

Description:
This feature allow to obtain bus departure time at transport stops in many russian cities
Related issue (if applicable): fixes #
Pull request with documentation for home-assistant.io (if applicable): home-assistant/home-assistant.io#<home-assistant.io PR number goes here>
Example entry for configuration.yaml (if applicable):
sensor:
     - platform: yandex_transport
       stop_id: 9639579

Checklist:

[x] The code change is tested and works locally.
[x] Local tests pass with tox. Your PR cannot be merged unless tests pass
[x] There is no commented out code in this PR.
[x] I have followed the development checklist

If user exposed functionality or configuration variables are added/changed:

[x] Documentation added/updated in home-assistant.io

If the code communicates with devices, web services, or third-party tools:

[x] The manifest file has all fields filled out correctly. Update and include derived files by running python3 -m script.hassfest.
[x] New or updated dependencies have been added to requirements_all.txt by running python3 -m script.gen_requirements_all.
[x] Untested files have been added to .coveragerc.

If the code does not interact with devices:

[x] Tests have been added to verify that the new code works.

Documentation pull request:
https://github.com/home-assistant/home-assistant.io/pull/10375

Hi all.
Feature was developed in the image dublin_bus_transport (https://www.home-assistant.io/components/dublin_bus_transport/)

File CODEOWNERS is not up to date. Please run python3 -m script.hassfest and commit the changes.

Also run script/gen_requirements_all.py and commit the changes.

Please also update .coveragerc to exclude this integration.

These instructions were in the PR template before you removed them.
https://github.com/home-assistant/home-assistant/blob/dev/.github/PULL_REQUEST_TEMPLATE.md

⚠ I was unable to find a documentation PR (matching this code change) in our documentation repository.
Please, update the documentation and open a PR for it (be sure to create a documentation PR against the next branch) and link 🔗 this PR and the new documentation PR by mentioning the link to the PR's in both openings posts/descriptions.
🏷 I am adding the docs-missing label until this has been resolved.

⚠ I was unable to find a documentation PR (matching this code change) in our documentation repository.
Please, update the documentation and open a PR for it (be sure to create a documentation PR against the next branch) and link 🔗 this PR and the new documentation PR by mentioning the link to the PR's in both openings posts/descriptions.
🏷 I am adding the docs-missing label until this has been resolved.
Hi! Docs pull request here:
https://github.com/home-assistant/home-assistant.io/pull/10375

Please solve the lint issues and run black to format the code.

Please solve the lint issues and run black to format the code.

Done 😊

Great!

Great thanks to you for the instructions! 😊

Can be merged when build passes.

Can be merged when build passes.

lets do it!)