Cannot run C# tasks on Linux - "Path to shell executable "dotnet" is not a file of a symlink" error.

VSCode Version: 1.49.0
OS Version: Debian GNU/Linux 10 (x64 5.7.0-0.bpo.2-amd64)

Steps to Reproduce:

Install VSCode and C# Omnisharp extension.
Install dotnet SDK.
Create a console app project in any folder ("dotnet new console" command).
Open this folder in VSCode.
Wait for editor to download required components.
Select "Run - Start Debugging" or press F5. Agree to add required assets.
Select "Run - Start Debugging" or press F5 again.

Does this issue occur when all extensions are disabled?: Yes

I've started to get this error some time ago. When I'm trying to run any task I get a message:
"The terminal process failed to launch: Path to shell executable "dotnet" is not a file of a symlink."
I tried uninstalling the editor and .Net SDK and installing it again. Also tried to replace the symlink "/usr/bin/dotnet" manually, but problem remains.
This problem only appears when trying to run some tasks from menu/button/key. If I type the command manually it works Ok.
This is also mentioned here:
https://stackoverflow.com/questions/63088161/visual-studio-code-c-sharp-debugging-problem-the-terminal-process-failed-to-lau
The OP's workaround is to replace the command "dotnet" with "/usr/bin/dotnet" in "tasks.json" file (worked for me too).

Today the problem disappeared after another clean install and removing all vscode and omnisharp config folders from user directory.

If you run that same command in the integrated terminal (not using tasks) does it work?

If you run that same command in the integrated terminal (not using tasks) does it work?

Yes, it worked when typing command directly. Problem was only with commands / hotkeys

How are you launching VS Code?
How did you install VS Code?
If you open the developer tools (command Developer: Toggle developer tools) and in the console run process.env.Path is the path to dotnet in there?

Launching from gnome application menu.
Installed first with deb package from Microsoft website, following installations were updates via package manager (Synaptic).
process.env.PATH has the directory with dotnet symlink

Ok, next time you see the problem, if you could check process.env.Path from the VS Code developer tools again that might provide a clue.

Ok, next time you see the problem, if you could check process.env.Path from the VS Code developer tools again that might provide a clue.

Actually last time problem was present, I forgot that I changed the command name as workaround suggests.

I've made a virualbox image with a snapshot of bug, if needed. It's ~2,5 Gb compressed.
https://drive.google.com/file/d/1Y0wFdgPwGqH_-WfbVAkRKzYg2uCSTS5o/

I was getting this error as well and found this thread while researching issue... i realized that i opened VS Code (~/some/dir code .") in bash terminal from different directory than the project i was working in, as "dotnet new" had yet to create the project's directory; once i created to the dir/project, wrote a little code, and tried to build, i got the reported error... fast forward, i closed out of VS Code and reopened properly in the project's directory and everything built fine

opened VS Code (~/some/dir code .") in bash terminal from different directory than the project i was working in

Indeed, this worked for me too. Yet if you launch VSC from application list, problem remains.

Count me in ! Do not close this bug ! The problem exists in my linux distro too :) I just faced it today.
dotnet command is fine, which dotnet executable file location is fine (which is in my path)
The problem can be solve only editing task.json write the whole path of dotnet in my case /usr/bin/dotnet
tasks.json file should look like this :

{
    "version": "2.0.0",
    "tasks": [
        {
            "label": "build",
            "command": "/usr/bin/dotnet",
            "type": "process",
            "args": [
                "build",
                "${workspaceFolder}/amazon_interview.csproj",
                "/property:GenerateFullPaths=true",
                "/consoleloggerparameters:NoSummary"
            ],
            "problemMatcher": "$msCompile"
        },
        {
            "label": "publish",
            "command": "/usr/bin/dotnet",
            "type": "process",
            "args": [
                "publish",
                "${workspaceFolder}/amazon_interview.csproj",
                "/property:GenerateFullPaths=true",
                "/consoleloggerparameters:NoSummary"
            ],
            "problemMatcher": "$msCompile"
        },
        {
            "label": "watch",
            "command": "/usr/bin/dotnet",
            "type": "process",
            "args": [
                "watch",
                "run",
                "${workspaceFolder}/amazon_interview.csproj",
                "/property:GenerateFullPaths=true",
                "/consoleloggerparameters:NoSummary"
            ],
            "problemMatcher": "$msCompile"
        }
    ]
}

Next time you see the problem, if you could check process.env.Path from the VS Code developer tools again that might provide a clue.

In tasks.json replace command:"dotnet",type:"process" by command:"dotnet",type:"shell"

In tasks.json replace command:"dotnet",type:"process" by command:"dotnet",type:"shell"

That did the trick. Thank you!

@alexr00 If you are talking about the developer console, it's undefined wrt. you wrote the last part Path
It sould be process.env.PATH and looks fine
"/home/caglar/.cargo/bin:/home/caglar/.cargo/bin:/home/caglar/.local/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/home/caglar/.dotnet/tools:/opt/bashtop:/opt/netcoredbg:/home/caglar/.local/bin:/home/caglar/.local/bin:/opt/qt/5.15.1/gcc_64/bin:/opt/anaconda3/bin:/home/caglar/.fzf/bin"
Here is the full env data
{
BASE16_THEME: "onedark"
CHROME_DESKTOP: "code-url-handler.desktop"
COLORTERM: "truecolor"
COMPlus_PerfMapEnabled: "1"
DBUS_SESSION_BUS_ADDRESS: "unix:path=/run/user/1000/bus"
DEFAULTS_PATH: "/usr/share/gconf/ubuntu.default.path"
DESKTOP_SESSION: "custom"
DISPLAY: ":1"
EDITOR: "mvim"
GDMSESSION: "custom"
GIO_LAUNCHED_DESKTOP_FILE: "/usr/share/applications/code.desktop"
GIO_LAUNCHED_DESKTOP_FILE_PID: "15309"
GJS_DEBUG_OUTPUT: "stderr"
GJS_DEBUG_TOPICS: "JS ERROR;JS LOG"
GNOME_DESKTOP_SESSION_ID: "this-is-deprecated"
GNOME_SHELL_SESSION_MODE: "ubuntu"
GPG_AGENT_INFO: "/run/user/1000/gnupg/S.gpg-agent:0:1"
GTK_MODULES: "gail:atk-bridge"
HOME: "/home/caglar"
IM_CONFIG_PHASE: "1"
INVOCATION_ID: "31e483b298c94e7e95b46325625ddaf6"
JOURNAL_STREAM: "8:48792"
LANG: "en_US.UTF-8"
LC_ADDRESS: "tr_TR.UTF-8"
LC_IDENTIFICATION: "tr_TR.UTF-8"
LC_MEASUREMENT: "tr_TR.UTF-8"
LC_MONETARY: "tr_TR.UTF-8"
LC_NAME: "tr_TR.UTF-8"
LC_NUMERIC: "tr_TR.UTF-8"
LC_PAPER: "tr_TR.UTF-8"
LC_TELEPHONE: "tr_TR.UTF-8"
LC_TIME: "tr_TR.UTF-8"
LESS: "-R"
LESS_TERMCAP_mb: ""
LESS_TERMCAP_md: ""
LESS_TERMCAP_me: ""
LESS_TERMCAP_se: ""
LESS_TERMCAP_so: ""
LESS_TERMCAP_ue: ""
LESS_TERMCAP_us: ""
LOGNAME: "caglar"
LSCOLORS: "Gxfxcxdxbxegedabagacad"
LS_COLORS: ""
MANAGERPID: "1763"
MANDATORY_PATH: "/usr/share/gconf/ubuntu.mandatory.path"
OLDPWD: "/home/caglar"
ORIGINAL_XDG_CURRENT_DESKTOP: "ubuntu:GNOME"
P9K_SSH: "0"
PAGER: "less"
PATH: "/home/caglar/.cargo/bin:/home/caglar/.cargo/bin:/home/caglar/.local/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/home/caglar/.dotnet/tools:/opt/bashtop:/opt/netcoredbg:/home/caglar/.local/bin:/home/caglar/.local/bin:/opt/qt/5.15.1/gcc_64/bin:/opt/anaconda3/bin:/home/caglar/.fzf/bin"
PWD: "/home/caglar"
QT_ACCESSIBILITY: "1"
QT_IM_MODULE: "ibus"
SESSION_MANAGER: "local/g5-5587:@/tmp/.ICE-unix/2051,unix/g5-5587:/tmp/.ICE-unix/2051"
SHELL: "/bin/zsh"
SHLVL: "0"
SSH_AGENT_PID: "2009"
SSH_AUTH_SOCK: "/run/user/1000/keyring/ssh"
USER: "caglar"
USERNAME: "caglar"
VSCODE_IPC_HOOK: "/run/user/1000/vscode-12d119d3-1.53.2-main.sock"
VSCODE_NLS_CONFIG: "{"locale":"en-us","availableLanguages":{},"_languagePackSupport":true}"
VSCODE_NODE_CACHED_DATA_DIR: "/home/caglar/.config/Code/CachedData/622cb03f7e070a9670c94bae1a45d78d7181fbd4"
VSCODE_PID: "15309"
WINDOWPATH: "2"
XAUTHORITY: "/run/user/1000/gdm/Xauthority"
XDG_CONFIG_DIRS: "/etc/xdg/xdg-ubuntu:/etc/xdg"
XDG_CURRENT_DESKTOP: "Unity"
XDG_DATA_DIRS: "/usr/share/ubuntu:/usr/local/share/:/usr/share/:/var/lib/snapd/desktop"
XDG_MENU_PREFIX: "gnome-"
XDG_RUNTIME_DIR: "/run/user/1000"
XDG_SESSION_CLASS: "user"
XDG_SESSION_DESKTOP: "ubuntu"
XDG_SESSION_TYPE: "x11"
XMODIFIERS: "@im=ibus"
ZSH: "/home/caglar/.oh-my-zsh"
ZSH_TMUX_CONFIG: "/home/caglar/.tmux.conf"
ZSH_TMUX_TERM: "screen"
_: "/usr/share/code/code"
_ZSH_TMUX_FIXED_CONFIG: "/home/caglar/.oh-my-zsh/plugins/tmux/tmux.extra.conf"
}

I agree, looks like your PATH is good.
What is the setting terminal.integrated.inheritEnv set to? If it's false, then your VS Code terminals won't get inherit that path.

What is the setting terminal.integrated.inheritEnv set to?
Set to true. Changing does not affect the error.

@shakir-timur can you check process.env.PATH from the VS Code developer tools console and share the output from that?

@shakir-timur can you check process.env.PATH from the VS Code developer tools console

"/usr/local/bin:/usr/bin:/bin:/usr/local/games:/usr/games:/home/timur/.dotnet/tools"
It's identical for both cases when it is working or not.

That path should include your path to dotnet assuming it's installed in the usual location. Can you run which dotnet and share the output so I can make sure that you have dotnet in /usr/bin/dotnet?
Next, we should check if that process.env.PATH is making it to your task.
Add this task to your tasks.json file:
		{
			"label": "Echo path",
			"command": "echo $PATH",
			"type": "shell"
		}

Run that task and share the output and we'll see if you have the right path for tasks.

Can you run which dotnet and share the output

/usr/bin/dotnet
Running echo task produced following:
Executing task: echo $PATH <
/usr/local/bin:/usr/bin:/bin:/usr/local/games:/usr/games:/home/timur/.dotnet/tools

I did some digging, and it looks like this is intentional right now. For process tasks on Windows, we find the full path of the executable. We don't do the same on linux.  Seems like we probably could find the executable though.

I get this error if I launch code from the terminal as code . (in my project root folder), but I don't get the error if I launch from Ubuntu Dock (20.04).
process.env.PATH when launched from dock:
"/home/jibbers42/bin:/home/jibbers42/.nvm/versions/node/v14.16.0/bin:/home/jibbers42/code/go/bin:/usr/local/go/bin:/home/jibbers42/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/home/jibbers42/.dotnet/tools:/home/jibbers42/.dotnet/tools"

process.env.PATH when launched from terminal:
"/home/jibbers42/.nvm/versions/node/v14.16.0/bin:/home/jibbers42/code/go/bin:/usr/local/go/bin:/home/jibbers42/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/home/jibbers42/.dotnet/tools"

The paths are different, but both have /usr/bin
==> which dotnet
/usr/bin/dotnet

This feature request is now a candidate for our backlog. The community has 60 days to upvote the issue. If it receives 20 upvotes we will move it to our backlog. If not, we will close it. To learn more about how we handle feature requests, please see our documentation.
Happy Coding!

I realize you have to be an influencer to have smaller quality of life issues considered these days (https://github.com/microsoft/vscode/issues/117847), but is this auto-close policy intended to apply to bugs as well?

I confirm the issue and a workaround. On MacOS, if you open Vscode from the "last open" menu, commands work in the terminal but not from plugins.
If however, you cd into the folder and open vscode from there, everything works fine.

In tasks.json replace command:"dotnet",type:"process" by command:"dotnet",type:"shell"

That did the trick. Thank you!

Thank you so much.


To dos

[x] Switch default view depending on mobile or desktop
[x] Updated course logo
[x] Tooltip color
[ ] Fix forward/backward button for mobile
[ ] Padding between name columns

forward/backward button could still use further tweaking, but it's a bit better now

forward/backward button fixed in a87ae21b616d0adabb2f392a90a0444b4fc4c6e7

couldn't figure out how to do the padding so instead made number of columns responsive to display width 52b113b

and that's it


chore: do not batch telemetry events

Description
Segment does not respect the processing order of events in a batch, which causes out-of-order processing by the analytics platform.
This PR disables batching, as per Segment support recommendation. The hope is to reduce the number of (none) values.
A disadvantage is that central will communicate more often, making calls per event. A possible advantage is that central events will be better correlated in time with related UI events.
Checklist

[x] Investigated and inspected CI test results
[x] Unit test and regression tests added
[ ] ~Evaluated and added CHANGELOG entry if required~
[ ] ~Determined and documented upgrade steps~
[ ] ~Documented user facing changes (create PR based on openshift/openshift-docs and merge into rhacs-docs)~

If any of these don't apply, please comment below.
Testing Performed
Run the central in local, enable telemetry, check that the events appear immediately, with no batching.
roxctl central whoami command issued two events with the following timestamp:
  "properties": {
    "Code": 0,
    "Method": "/v1.AuthService/GetAuthStatus",
    "Path": "/v1.AuthService/GetAuthStatus",
    "User-Agent": "roxctl/4.4.x-426-g0732d30c78 (linux; amd64) grpc-go/1.61.1"
  },
  "receivedAt": "2024-04-18T16:57:01.018Z",
  "sentAt": "2024-04-18T16:57:01.001Z",
  "timestamp": "2024-04-18T16:57:01.017Z",

  "properties": {
    "Code": 0,
    "Method": "/v1.RoleService/GetMyPermissions",
    "Path": "/v1.RoleService/GetMyPermissions",
    "User-Agent": "roxctl/4.4.x-426-g0732d30c78 (linux; amd64) grpc-go/1.61.1"
  },
  "receivedAt": "2024-04-18T16:57:01.157Z",
  "sentAt": "2024-04-18T16:57:01.141Z",
  "timestamp": "2024-04-18T16:57:01.157Z",

Reminder for reviewers
In addition to reviewing code here, reviewers must also review testing and request further testing in case the
performed one does not seem sufficient. As a reviewer, you must not approve the change until you understand the
performed testing and you are satisfied with it.

Segment does not respect the processing order of events in a batch, which causes out-of-order processing by the analytics platform.

I don't get it? Why it's a case? Does not batching guarantee order? I think we should not rely on order of events in telemetry.

Do you have an estimation for the performance implications of reducing the batch size to 0? This means we now do at least one telemetry request for each API call, right? I think we should do some back of the envelope calculation on how noticeable this will be for larger clusters.

I don't get it? Why it's a case? Does not batching guarantee order? I think we should not rely on order of events in telemetry.

It's not up to us sadly. IIRC the issue is basically as follows. Take the following events:

Create group A
Emit event for group A
Create group B
Emit event for group B

If all these requests arrive in the correct order on Amplitude, both events will be attached correctly to the group. What can now happen due to the batching is that Segment actually sends the requests out of order:

Emit event for group A
Create group A
Emit event for group B
Create group B

Now when Amplitude ingests the event requests, the corresponding groups don't exist yet and are set to none.

ROX-22592


Easier installation

Please consider making an easy installation using curl or wget on Linux and an EXE for windows
https://ytdl-org.github.io/youtube-dl/download.html

the script is no more usable as it doesn't download the protected videos.


Enable arm64 big endian for AOSP LLVM

https://github.com/ClangBuiltLinux/continuous-integration2/runs/2655483207?check_suite_focus=true

Looks like this will be resolved with clang-r428724 . Once that has been enabled in Tux{Make,Suite}, we can enable it.

I have pushed https://gitlab.com/Linaro/tuxmake/-/merge_requests/224. Once that is merged and the image is updated, we can enable this and close the issue.


fix: add logs in traps server for situations when incoming traps have wrong credentials

Description
This PR adds logging for snmp traps errors
Fixes # (issue)
Type of change
Please delete options that are not relevant.

[x] Refactor/improvement

How Has This Been Tested?
Manual testing
Checklist

[x] My commit message is conventional
[x] I have run pre-commit on all files before creating the PR
[x] I have commented my code, particularly in hard-to-understand areas
[x] I have made corresponding changes to the documentation
[x] I have added tests that prove my fix is effective or that my feature works
[x] New and existing unit tests pass locally with my changes
[x] I have checked my code and corrected any misspellings

Codecov Report
Attention: 5 lines in your changes are missing coverage. Please review.

Comparison is base (8d9399f) 84.32% compared to head (9c5d43c) 84.11%.

:exclamation: Current head 9c5d43c differs from pull request most recent head 2203de7. Consider uploading reports for the commit 2203de7 to get more accurate results

Files
Patch %
Lines

splunk_connect_for_snmp/traps.py
0.00%
5 Missing :warning:

:exclamation: Your organization needs to install the Codecov GitHub app to enable full functionality.
Additional details and impacted files
@@             Coverage Diff             @@
##           develop     #953      +/-   ##
===========================================
- Coverage    84.32%   84.11%   -0.21%
===========================================
  Files           28       28
  Lines         2022     2027       +5
===========================================
  Hits          1705     1705
- Misses         317      322       +5

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

:tada: This PR is included in version 1.10.0-beta.4 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


Error in cross validation estimator in Mleap pipeline

Random forest + cross validation code
val rf = new RandomForestClassifier().setLabelCol("labels").setFeaturesCol("features").setMaxBins(200).setSeed(100)
// cross validation step
val paramGrid = new ParamGridBuilder()
.addGrid(rf.numTrees, Array(50, 100))
.addGrid(rf.maxDepth, Array(20,30))
.build()
val cv = (new CrossValidator()
.setEstimator(rf)
.setEvaluator(new BinaryClassificationEvaluator().setLabelCol("labels"))
.setNumFolds(3)
.setEstimatorParamMaps(paramGrid))
val sparkPipelineEstimatorRf = new Pipeline().setStages(Array(sparkFeaturePipelineModel, cv))
Error
key not found: org.apache.spark.ml.tuning.CrossValidatorModel
java.util.NoSuchElementException: key not found: org.apache.spark.ml.tuning.CrossValidatorModel

I think the error is expected because the CrossValidator transformer is not supported ( see #192 )
The purpose of crossValidator is not model building, but model checking to make sure you are not (over/under)fitting.

@yashaswini87 We don't support cross validation models or other models that are used in just training. In order to export your model, select the best model trained by the cross validator and include that in your output pipeline.
Closing this issue


Allow specifying bind address

Currently there is only a --port option

This is now fixed by #49.


proper casing for all packages

New toLowerCase map across website, service, and crawler. Addresses issue #237

Issue open #123

@dabutvin you might be interested in merging these changes into the work you are doing on case sensitivity in the service and crawler

this is now obsoleted by a different set of changes.


Is this a bug? im2rec using opecv  resize () function to reduce image

im2rec.py about reduce image :
def image_encode(item, q_out):
        try:
            img = cv2.imread(os.path.join(args.root, item[1]), color_modes[args.color])
        except:
            print 'imread error:', item[1]
            return
        if img == None:
            print 'read none error:', item[1]
            return
        if args.center_crop:
            if img.shape[0] > img.shape[1]:
                margin = (img.shape[0] - img.shape[1])/2;
                img = img[margin:margin+img.shape[1], :]
            else:
                margin = (img.shape[1] - img.shape[0])/2;
                img = img[:, margin:margin+img.shape[0]]
        if args.resize:
            if img.shape[0] > img.shape[1]:
                newsize = (img.shape[0]*args.resize/img.shape[1], args.resize)
            else:
                newsize = (args.resize, img.shape[1]*args.resize/img.shape[0])
            img = cv2.resize(img, newsize)
        header = mx.recordio.IRHeader(0, item[2], item[0], 0)

        try:
            s = mx.recordio.pack_img(header, img, quality=args.quality, img_fmt=args.encoding)
            q_out.put(('data', s, item))
        except:
            print 'pack_img error:',item[1]
            return

Python: cv.Resize(src, dst, interpolation=CV_INTER_LINEAR) → None
Parameters:
dsize –
output image size; if it equals zero, it is computed as:
\texttt{dsize = Size(round(fxsrc._cols_), round(fysrc.rows))}
Either dsize or both fx and fy must be non-zero.

cv2.imread function return about image shape  first  is cols (height ),so……
For example ，Im2rec will be the resolution of the 900x1200 image, in the input parameters of resize 90, the picture is reduced to 120X90, but the actual should be 90x120
This is a bug? Or did I use the wrong method?

I talked about it here
#1963

Sorry to bother you.I don't have to search for it .
Thank you.

Sorry to bother you. I don't have to search for it .
Thank you

@piiswrong

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


The triplet loss converges to the margin

Hi, I have tried to replace infoNCE loss by triplet loss (using hardest negative sample), but the triplet loss simply converges to the margin, resulting in collapsed model where all examples have the same embedding. Any suggestion?
BTW, would you please share the loss function you used in your paper? Thanks.

Thanks so much for your interest in our work! As our paper suggests, the hardest negative sample has several problems, and using smoothed-rank-k triplet loss is our main contribution. Please use the smoothed-rank-k triplet loss.
Our full code will be here soon.

Thanks for your reply. Another question is: what is median_triplet_head.py? Does it correspond to any number in the paper?

@viyjy median_triplet_head.py is 73.6 in the paper. As is mentioned by the paper, median triplet loss is not as good as smoothed-rank-k triplet loss, especially when training longer.

Thanks very much.


Update restic to v0.12.0

Damnit, just saw #73 also includes a restic update. Please merge either of them soon, thx !

Will do. But I'd rather take the other one since it updates rclone as well.


Adds QCAlgorithm methods for TEMA and TRIMA indicators

Well at least you're paying attention! Looks like I missed the fact that these were missing in the review. Did we miss any others?

@mchandschuh Not in the latest additions :)
I'll do a full check and report back.

Sounds good, will merge this PR -- if there's any others we can bring them in separately.


use crio client and add fs handler

wire in crio client and add fs handler @derekwaynecarr  @mrunalp PTAL (you need crio master + https://github.com/kubernetes-incubator/cri-o/pull/821 + https://github.com/kubernetes-incubator/cri-o/pull/824 to work with this)

second commit add ImageFsInfo impl, I'm working on net mode now (then?)


create new file for testing

want to git over with just review and accept it please

sounds good to me


Issue with node shebang

Current Behavior
I could be doing something wrong here but creating a new "basic" project and adding the node shebang to index.ts and running yarn build --target node results in this error:
23:34:20 in tsdx-issue on  master is 📦  v0.1.0 via ⬢ v8.15.0 took 7s
➜ yarn build --target node
yarn run v1.15.2
warning package.json: No license field
$ tsdx build --target node
✓ Creating entry file 3.5 secs
Error when using sourcemap for reporting an error: Can't resolve original location of error.
Error when using sourcemap for reporting an error: Can't resolve original location of error.
Error when using sourcemap for reporting an error: Can't resolve original location of error.
Error when using sourcemap for reporting an error: Can't resolve original location of error.
(node:60781) UnhandledPromiseRejectionWarning: Error: Unexpected character '#' (Note that you need plugins to import files that are not JavaScript)
    at error (/Users/malves/Development/tmp/tsdx-issue/node_modules/rollup/dist/rollup.js:9236:30)
    at Module.error (/Users/malves/Development/tmp/tsdx-issue/node_modules/rollup/dist/rollup.js:12909:9)
    at tryParse (/Users/malves/Development/tmp/tsdx-issue/node_modules/rollup/dist/rollup.js:12825:16)
    at Module.setSource (/Users/malves/Development/tmp/tsdx-issue/node_modules/rollup/dist/rollup.js:13102:33)
    at Promise.resolve.catch.then.then.then (/Users/malves/Development/tmp/tsdx-issue/node_modules/rollup/dist/rollup.js:15924:20)
    at <anonymous>
(node:60781) UnhandledPromiseRejectionWarning: Unhandled promise rejection. This error originated either by throwing inside of an async function without a catch block, or by rejecting a promise which was not handled with .catch(). (rejection id: 1)
(node:60781) [DEP0018] DeprecationWarning: Unhandled promise rejections are deprecated. In the future, promise rejections that are not handled will terminate the Node.js process with a non-zero exit code.
Error when using sourcemap for reporting an error: Can't resolve original location of error.
✨  Done in 5.38s.

Expected behavior
Should build without an error as far as I know.
Suggested solution(s)
Not quite sure where the issue lies here. Spent a bit of time digging around to see if maybe I could figure it out but wasn't very successful.
Additional context
Sample Repo
Your environment

Software
Version(s)

TSDX
0.5.11

TypeScript
3.4.5

Browser
Chrome 74

npm/Yarn
1.15.2

Operating System
macOS 10.14.4

rollup seems to not handle this on purpose: https://github.com/rollup/rollup/issues/235
we use @jaredpalmer's own shebang plugin: https://github.com/palmerhq/tsdx/blob/71817a33628983ee8a3adb4d10e852b5895d7a00/src/createRollupConfig.ts#L12 so it should work... will just leave it to you two to figure it out

👋 @sw-yx thanks for chiming in here
I hadn't seen that issue in my searching! I'm thinking my project it might be a better route to build with tsc and stick to using tsdx when it comes to web-based packages.
I don't have enough experience with rollup to really dig in here. I did see this plugin which adds the shebang afterwards so that users don't have to add it themselves. I replaced the current one in createRollupConfig.ts and it seemed to work okay. But it looks like the preserve one should work too
Thanks again!

Took a look into this.  What's the desired output?  A shebang in each bundle, or one in dist/index.js?  If the former, one way I got it to work is by changing the preserve shebang plugin's processEntry function to remove the shebang from the files before being processed and rewrite them to disk:
function processEntry(entry) {
		if (entry) {
			let contents = fs.readFileSync(entry, 'utf8');
			let matches = contents.match(/^\s*(#!.*)/);
			shebang = matches && matches[1] || false;

                        // new code:
                        if (!shebang) return;
                        contents = contents.replace(shebang, '')
       	                fs.writeFileSync(entry, contents)
		}
	}

not sure if there's a better way to do that, but it worked.  on the flip side, it seems pretty easy to also automate it so they don't have to add their own.
lemme know what'd be preferred and i can implement it

You just want it in the entry file that has it. Not in every one.


Update comment about ResolveVersion default version

What does this PR try to resolve?
Point out that the current ResolveVersion defaults to V3
How should we test and review this PR?

Introduced in 1.47.0 https://github.com/rust-lang/cargo/blob/rust-1.47.0/src/cargo/core/resolver/resolve.rs#L60-L73
As default in 1.53.0 https://github.com/rust-lang/cargo/blob/rust-1.53.0/src/cargo/core/resolver/resolve.rs#L412

r? @epage
(rust-highfive has picked a reviewer for you, use r? to override)

@bors r+

:pushpin: Commit d94ce9fc9083742542e6504ead2ccc7f6e9056a2 has been approved by epage
It is now in the queue for this repository.

:hourglass: Testing commit d94ce9fc9083742542e6504ead2ccc7f6e9056a2 with merge ef7ab8bb62d42ee6009caa4f490b8ff980c059d1...

:sunny: Test successful - checks-actions
Approved by: epage
Pushing ef7ab8bb62d42ee6009caa4f490b8ff980c059d1 to master...


proposal: Add support for retrieving function parameter names with reflect

Currently there is no way to retrieve function/method parameter names with the reflect package. The only introspection available is for the types of the input and output parameters of a function. The seems to be an exception with the reflect package, since it does offer naming information in most other cases.
When building RPC/API libraries it is useful to be able to retrieve these method parameters names for purposes of runtime schema output, input validation on unstructured data, and possibly some API semantics. There are some alternatives right now:

Parse the source and use code generation to compile this metadata into the running program.
Use structs for all input/output and then use the field names in the structs, along with their tags, for introspection.

Some other considerations:

I understand that this might lead to binary and/or memory size increase due to the additional metadata that might have to be stored. This change might not be ideal this far into the 1.X cycle, but I think it should at least be considered for 2.0.
A fairly straightforward way to do this, that would not break backwards compatibility, would be to add two methods to reflect.Type that would retrieve the In/Out parameter names by Index.

Apologies if this is a duplicate issues. I searched the forums (nuts/dev) and this issue tracker and could not find any previous issues filed on this topic.

It's a fairly significant change to allow code that depends on parameter names. Today, a library writer is free to change any parameter names in their API; with this change, the names would have to be considered part of the exported API and therefore the library author would be under some obligation never to change them.

Reflect provides information about types. Function parameter names are not part of the func type. In contrast, struct field names are. That is:
var f func(x int)
var g func(y int)
f = g // perfectly fine, same type
var s struct { x int }
var t struct { y int }
s = t // compiler error, not same type
Reflect provides access to struct field names because they are part of the type. Func parameter names are not.
I think it would likely be a mistake to expand the scope of package reflect beyond the clearly defined line of "types". It's not obvious to me where else to draw a line between func parameter names and the entire source files.
Also, because parameter names are not part of type checking and have a history of having literally no semantic meaning outside the function body and documentation, I'd be wary of enabling reflection-based programs that break when you rename a function parameter. People understand that renaming a struct field can break things, because struct fields can be referred to in other places in the source. No one expects that renaming a function parameter (and updating references in the function body) would break anything else.

As mentioned in the recent named parameter proposal, I think
one solution to your RPC/API library problem is to define inline
(anonymous) parameter structs as function parameter. e.g.
func (r *State) MethodA(args struct { Arg1 int; Arg2 string }) error {
// use args.Arg1, args.Arg2, etc.
}
And then reflect should be able to pick up the names easily.
Because these RPC methods are only intended to be called indirectly
using reflect, having anonymous struct as sole argument won't
complicate anything.

Caleb, I can see your point. It would definitely be something that people would have to watch out for in the future. If this feature is added to the reflect package then I don’t see how that additional “cognitive” burden of having to watch out for parameter changes and freeze API functions could be avoided. I don’t necessarily think that it would impact most people, but I can see how it could lead to some tricky issues between dependencies.
Russ, thank for your insight. I also read through the named parameters discussion that Minux referenced and it seems that both proposals present similar issues. I have a better appreciation of the problems involved here.
Obviously changing the definition of the function Type to include parameter names this late in the 1.x release is out of the question, and I don't even think that's necessarily a good idea. And I can see why you would be reluctant to expand the scope of the reflect package beyond Type information, especially without a clear boundary.
Minux thank you for the suggestion, I took a similar path here.
Taking all of your points into consideration, I think that this proposal would cause more complications than solutions. I'm going to close it for now, please re-open if you feel like additional discussion is warranted.


Run IS testgrid build job for each build in WSO2 Jenkins CI

Description:
We need to periodically run product-is build for each build that has happened in WSO2 Jenkins instance. [1]. The latest stable distribution ZIP can be downloaded from [1].
When this is in place, whenever a build has failed, we need to generate the report and send it as a mail. Since mailing functionality is not available for testgrid yet, we need to provide an alternative notification mechanism instead.
Approach:
We can use the periodic build trigger support available in the testgrid jenkins instance for this purpose.
[1] https://wso2.org/jenkins/job/products/job/product-is/lastStableBuild/org.wso2.is$org.wso2.is.product/
Affected Product Version:
0.9.0-m13
Steps to reproduce:
N/A
Related Issues:
https://github.com/wso2/testgrid/issues/508

We need to push this a bit further as we have not yet finalized the AMI creation process for products.

Hi Harshan,
I think this is a critical piece of information that we need to figure out how to solve. We can do this as part of cloudformation-apim since it is the reference impl. May be I'll create a new issue for that.
Thanks,
KasunG


Add support for LXD storage pools

This adds basic support for storage pools as well
as tests to verify their function, taken from the
LXD REST API.

Codecov Report

Merging #240 into master will increase coverage by 0.16%.
The diff coverage is 100%.

@@            Coverage Diff            @@
##           master    #240      +/-   ##
=========================================
+ Coverage   95.93%   96.1%   +0.16%
=========================================
  Files          14      15       +1
  Lines         689     718      +29
  Branches       78      79       +1
=========================================
+ Hits          661     690      +29
  Misses         14      14
  Partials       14      14

Impacted Files
Coverage Δ

pylxd/client.py
98.44% <100%> (+0.01%)
:arrow_up:

pylxd/models/storage_pool.py
100% <100%> (ø)

pylxd/managers.py
100% <100%> (ø)
:arrow_up:

pylxd/tests/models/__init__.py
100% <0%> (ø)
:arrow_up:

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Documentation on how to trigger ConfigDiffScript programmatically

How can I (if it isn't a hard limitation of netbox) invoke a configdiff script run from another custom script or from nb-shell?
I have a few custom scripts that import data into netbox (device interface configurations). Some imports are done through ansbile, some through a custom script.
Usually when I import data to a device in netbox or update the switch-config oxidized based netbox datasource, I have to manually run another ConfigDiffScript run or wait for the next scheduled run.
I wonder if I could trigger the generation of a new ConfigCompliance object programmatically, when I know I data has changed.

Hi @chris240189, you can run script like this
from django.utils.datastructures import MultiValueDict
from extras.models import Script
from utilities.request import NetBoxFakeRequest

script = Script.objects.get(name=self.script_name)
request = NetBoxFakeRequest(
    {
        "COOKIES": {},
        "FILES": MultiValueDict(),
        "GET": QueryDict(),
        "META": {
            "HTTP_HOST": "netbox",
            "REQUEST_METHOD": "POST",
        },
        "POST": QueryDict(),
        "path": <path to script like "/extras/scripts/{id}">,
        "user": job.user,
        "id": uuid.uuid4(),
    }
)

data = {
    "_commit": True,
    # here you add data for script
}
ScriptJob = import_string("extras.jobs.ScriptJob")
new_job = ScriptJob.enqueue(
    instance=script,
    user=request.user,
    schedule_at=data.pop("_schedule_at", None),
    interval=data.pop("_interval", None),
    data=data,
    request=request,
    job_timeout=script.python_class.job_timeout,
    commit=data.pop("_commit", None),
)

thank you for supplying some code so quickly.
Right now I have two scripts that update data in netbox.

I get new device configs from oxidized and put them into a netbox local datasource that I use a source to diff to though a scheduled netbox custom script.
The second is a ansible playbook that fetches device interface configuration data from an external source.

I'll have a look how to integrate your snippet into my code.

I think the best way is in the end to run ConfigDiffScript  script from API, it takes less code and is easy to support

okay, I am trying to invoke it through the REST-API using ansible:
- name: '{{ netbox_url }}/api/extras/scripts/1/'   uri:     url: '{{ netbox_url }}/api/extras/scripts/1/'     method: POST     body:       data:         data_source: 1         devices: 934       commit: true     body_format: json     headers:       Authorization: 'Token {{ netbox_token }}'       Content-Type: application/json       Accept: 'application/json; indent=4'   register: result
the integer values are the netbox-ids of the data_source and device in question, however the script fails with
"message": "An exception occurred: KeyError: 'site'\n\nTraceback (most recent call last):\n  File \"/opt/netbox/netbox/extras/jobs.py\", line 45, in run_script\n    script.output = script.run(data, commit)\n  File \"/opt/netbox/netbox/scripts/config_diff.py\", line 12, in run\n    self.run_script(data)\n  File \"/opt/netbox/venv/lib/python3.10/site-packages/netbox_config_diff/compliance/base.py\", line 68, in run_script\n    devices = self.validate_data(data)\n  File \"/opt/netbox/venv/lib/python3.10/site-packages/netbox_config_diff/compliance/base.py\", line 75, in validate_data\n    if not data[\"site\"] and not data[\"role\"] and not data[\"devices\"]:\nKeyError: 'site'\n\n",

in data define keys site and role with any number
in next release I will fix mandatory of this fields in validation

that still doesn't work.
I believe netbox handles passed IDs weirdly and is interpreting them not automatically as object id (and doesn't convert them to an object).
See also:
https://github.com/netbox-community/netbox/discussions/16255

yeah, I also can't run the script from the API, so try to run like in the code I provided,
feel free to ask any questions about this approach


Add topologySpreadConstraints to support scaling of coredns

Proposed Changes
The coredns service is not highly available by default. It is possible to set the replication count to 2, but even then, pods might be scheduled on the same nodes. Adding a topologySpreadConstraint distributes the containers on different nodes.
Types of Changes
Add topologySpreadConstraints declaration to coredns deployment spec.
Verification
Scale the coredns deployment and check whether the pods are distributed on different nodes.
Linked Issues
https://github.com/k3s-io/k3s/issues/1606
User-Facing Change
NONE

Sorry, I'm not sure why the build is failing. Tried to run mkdir -p build/data && ./scripts/download && go generate, but now there's another error.

it looks like you're missing the tools to properly generate the bindata via ./scripts/download && go generate. Ensure that you have yq installed, and are running the script on a Ubuntu based system so that the gzip content matches that output by CI.

Ok, now it succeded on ubuntu.
There were some diffs of traefik and some build args comments I didn't include in the commit:

That's. It something I've seen before. What version of go are you using?

go version go1.17.1 linux/amd64
started using docker run -v $PWD:$PWD -w=$PWD -it --rm golang:1.17.1-bullseye bash

Ah, that might be it - Kubernetes is still using 1.16.8; can you try with that?

Now I got the correct output without those new annotations 👍
Still some tar diffs of traefik. But they might be related to something else. This PR would be ready.

Codecov Report

Merging #4133 (014dca4) into master (12e675e) will decrease coverage by 0.37%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master    #4133      +/-   ##
==========================================
- Coverage   11.66%   11.28%   -0.38%
==========================================
  Files         134      134
  Lines        9055     9055
==========================================
- Hits         1056     1022      -34
- Misses       7773     7816      +43
+ Partials      226      217       -9

Flag
Coverage Δ

inttests
?

unittests
11.28% <ø> (-0.03%)
:arrow_down:

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files
Coverage Δ

pkg/deploy/zz_generated_bindata.go
0.00% <ø> (ø)

tests/util/cmd.go
0.00% <0.00%> (-42.03%)
:arrow_down:

pkg/flock/flock_unix.go
0.00% <0.00%> (-20.00%)
:arrow_down:

pkg/agent/netpol/utils/iptables.go
16.21% <0.00%> (-5.41%)
:arrow_down:

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Thanks for the contribution!


[DEV] Minor UI Refinements

Feedback regarding UI:

The hireflow logo on the sidebar is too big.
The filter module does not span across the width of the page until the side margins. I think it’s gonna look better if it’s wider, as per the design.
(See Image Attached) I think I did a mistake regarding the color of the container. I think it looks way cleaner if we just use pure white (#FFFFFF) as the background instead of the current washed out white.

Hey @LeonardoKamino I'll add a bit more info to the requirements:

Can you change the sidebar logo to 75% width and make it align left instead of center

In wider resolutions, the filter container is not all the way across
For the container color @filbertmang , we actually take the whole element from Figma and don't change the color in the code. If you can change the color, Leo can upload the new image

UPDATE:Just changed the container colour on Figma. @LeonardoKamino you can now upload the new image :)


PHOENIX-6583 Inserting explicit Null into a (fixed length) binary field is stored as an array of zeroes

PHOENIX-6583 Inserting explicit Null into a (fixed length) binary field is stored as an array of zeroes
In the test BinaryTypeIT:

it  create the table
it make a simple upsert without using the binary field and test if it is null.
3)it makes an upsert to the binary field but with a null value. Without the change, it stores a 0x00 array of bytes instead of a null.
it makes an upsert to the binary field but now with a value.
5)it makes an upsert to the binary field again with a null. Without the change, it does not remove the data and it is not a null value.

IMPORTANT: while I was doing the tests, I tried to pass all the test, but failed in the test "org.apache.phoenix.end2end.DefaultColumnValueIT.testDefaultAllDataTypesKeyValueCol" , but in my opinion the fail is regarding what I have explained it in JIRA PHOENIX-6585 report. This is the stack trace of the test:
[ERROR] Tests run: 24, Failures: 1, Errors: 0, Skipped: 0, Time elapsed: 230.567 s <<< FAILURE! - in org.apache.phoenix.end2end.DefaultColumnValueIT
[ERROR] org.apache.phoenix.end2end.DefaultColumnValueIT.testDefaultAllDataTypesKeyValueCol  Time elapsed: 4.806 s  <<< FAILURE!
arrays first differed at element [4]; expected:<0> but was:<2>
at org.junit.internal.ComparisonCriteria.arrayEquals(ComparisonCriteria.java:78)
at org.junit.internal.ComparisonCriteria.arrayEquals(ComparisonCriteria.java:28)
at org.junit.Assert.internalArrayEquals(Assert.java:534)
at org.junit.Assert.assertArrayEquals(Assert.java:343)
at org.junit.Assert.assertArrayEquals(Assert.java:354)
at org.apache.phoenix.end2end.DefaultColumnValueIT.testDefaultAllDataTypes(DefaultColumnValueIT.java:581)
at org.apache.phoenix.end2end.DefaultColumnValueIT.testDefaultAllDataTypesKeyValueCol(DefaultColumnValueIT.java:506)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:566)
at org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:59)
at org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12)
at org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:56)
at org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17)
at org.junit.internal.runners.statements.RunBefores.evaluate(RunBefores.java:26)
at org.junit.runners.ParentRunner$3.evaluate(ParentRunner.java:306)
at org.junit.runners.BlockJUnit4ClassRunner$1.evaluate(BlockJUnit4ClassRunner.java:100)
at org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:366)
at org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:103)
at org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunne

Hi,
I think that I solved. I forget to check ptr. Before I was checking only for the Object. In my test, now is not having failures.
But now, I found something that for me is streange. I tested it not only with fixed binaries, but algo with integers. At the begining I thought that it was bacause my fixed; so I proved without my changes. But I had the same result, so I thing that it is not because of my changes and it comes before.
The question is that it seems that there is a conflict between "field is null" and "filed=null". It is supoused that the result should be the same; but it is not. Followin is what I mean (you can try in master branch without my changes):
0: jdbc:phoenix:> create table  DUMMY (id integer not null, int2 INTEGER, text varchar(255), testbin binary(16), CONSTRAINT pk primary key (id));
No rows affected (2.478 seconds)
0: jdbc:phoenix:> upsert into dummy values (1);
1 row affected (0.055 seconds)
0: jdbc:phoenix:> select * from dummy;
+----+------+------+---------+
| ID | INT2 | TEXT | TESTBIN |
+----+------+------+---------+
| 1  | null |      |         |
+----+------+------+---------+
1 row selected (0.039 seconds)
0: jdbc:phoenix:> select * from dummy where int2 is null;
+----+------+------+---------+
| ID | INT2 | TEXT | TESTBIN |
+----+------+------+---------+
| 1  | null |      |         |
+----+------+------+---------+
1 row selected (0.03 seconds)
0: jdbc:phoenix:> select * from dummy where int2=null;
+----+------+------+---------+
| ID | INT2 | TEXT | TESTBIN |
+----+------+------+---------+
+----+------+------+---------+
No rows selected (0.033 seconds)
"select * from dummy where int2 is null;" should returns the same as "select * from dummy where int2=null;". should't ?

The null behaviour you describe is correct, as defined by SQL spec. Look it up.
Please fix the formatting problems reported by Yetus.

Done.
About SQL spec, I do not know why it was speced like that , but I do not agree (for me it has no sense, but I tested it postgres and the  behaviour is the same)... but  it's like fighting giants.
NOTE: I am always getting the same error report in test, both before and after the changes I made in PhoenixMetricsIT.testGlobalPhoenixMetricsForQueries. This is the stack trace:
[INFO] Running org.apache.phoenix.monitoring.PhoenixTableLevelMetricsIT
[ERROR] Tests run: 24, Failures: 1, Errors: 0, Skipped: 0, Time elapsed: 289.222 s <<< FAILURE! - in org.apache.phoenix.monitoring.PhoenixMetricsIT
[ERROR] org.apache.phoenix.monitoring.PhoenixMetricsIT.testGlobalPhoenixMetricsForQueries  Time elapsed: 7.059 s  <<< FAILURE!
java.lang.AssertionError
at org.junit.Assert.fail(Assert.java:87)
at org.junit.Assert.assertTrue(Assert.java:42)
at org.junit.Assert.assertTrue(Assert.java:53)
at org.apache.phoenix.monitoring.PhoenixMetricsIT.testGlobalPhoenixMetricsForQueries(PhoenixMetricsIT.java:199)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:566)
at org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:59)
at org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12)
at org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:56)
at org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17)
at org.junit.runners.ParentRunner$3.evaluate(ParentRunner.java:306)
at org.junit.runners.BlockJUnit4ClassRunner$1.evaluate(BlockJUnit4ClassRunner.java:100)
at org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:366)
at org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:103)
at org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:63)
at org.junit.runners.ParentRunner$4.run(ParentRunner.java:331)
at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:79)
at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:329)
at org.junit.runners.ParentRunner.access$100(ParentRunner.java:66)
at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:293)
at org.junit.internal.runners.statements.RunBefores.evaluate(RunBefores.java:26)
at org.apache.phoenix.SystemExitRule$1.evaluate(SystemExitRule.java:40)
at org.junit.rules.ExternalResource$1.evaluate(ExternalResource.java:54)
at org.junit.rules.RunRules.evaluate(RunRules.java:20)
at org.junit.runners.ParentRunner$3.evaluate(ParentRunner.java:306)
at org.junit.runners.ParentRunner.run(ParentRunner.java:413)
at org.junit.runners.Suite.runChild(Suite.java:128)
at org.junit.runners.Suite.runChild(Suite.java:27)
at org.junit.runners.ParentRunner$4.run(ParentRunner.java:331)
at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:79)
at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:329)
at org.junit.runners.ParentRunner.access$100(ParentRunner.java:66)
at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:293)
at org.junit.runners.ParentRunner$3.evaluate(ParentRunner.java:306)
at org.junit.runners.ParentRunner.run(ParentRunner.java:413)
at org.apache.maven.surefire.junitcore.JUnitCore.run(JUnitCore.java:55)
at org.apache.maven.surefire.junitcore.JUnitCoreWrapper.createRequestAndRun(JUnitCoreWrapper.java:137)
at org.apache.maven.surefire.junitcore.JUnitCoreWrapper.executeEager(JUnitCoreWrapper.java:107)
at org.apache.maven.surefire.junitcore.JUnitCoreWrapper.execute(JUnitCoreWrapper.java:83)
at org.apache.maven.surefire.junitcore.JUnitCoreWrapper.execute(JUnitCoreWrapper.java:75)
at org.apache.maven.surefire.junitcore.JUnitCoreProvider.invoke(JUnitCoreProvider.java:157)
at org.apache.maven.surefire.booter.ForkedBooter.runSuitesInProcess(ForkedBooter.java:428)
at org.apache.maven.surefire.booter.ForkedBooter.execute(ForkedBooter.java:162)
at org.apache.maven.surefire.booter.ForkedBooter.run(ForkedBooter.java:562)
at org.apache.maven.surefire.booter.ForkedBooter.main(ForkedBooter.java:548)

(I apologies if this is not the correct place to say following, but I think that if somebody read this conversation may get the the same doubt that I had about regarding SQL spec)
I read the following article I clarified my ideas:
https://www.xaprb.com/blog/2006/05/18/why-null-never-compares-false-to-anything-in-sql/
It remenber me a puzzle that I read in this book (http://www.javapuzzlers.com/) where you can have a instance like this:
if (a!=a)
System.out.println('Hello!! I am here");
And the mesage will be shown. How? well... initializating a like:
double a = Math.log(-1);
In this case, a is 'NaN'; and java spec saiys that 'NaN' is not equal to anything... neither NaN, so ' NaN  != NaN' is true.

sorry for hightlighting the parragraph about the book. It was not my intent. I don't know why it did it... I only write simple text... next time I will "preview" the mesage. This is my first time using github

Hi,
I do not understand the error that Yetus(jenkins) is reporting because the file phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java was deleted from the branck and it does not exists. You can check it in the PHOENIX-6583 branch on alejandro-anadon/phoenix.
Here is when I deletted it:
https://github.com/apache/phoenix/pull/1342/commits/eae4b115e18f932debb6aca9ce1b6d8a7ff5c2df
Just as you suggested, that test was moved to phoenix-core/src/it/java/org/apache/phoenix/end2end/NullIT.java.
In my enviroment, the only failed test is PhoenixMetricsIT.testGlobalPhoenixMetricsForQueries; but I passed also all the test before my changes, and I have the same failed test; so I guess it has nothing to do with my changes that I have made.
I am going to post ascreen log file in case it may help. It is absolutly from begining. I mean, from firt 'git clone' of my repositorie.
(I also have an error after all the test has been done. It is  another error when it is supoused to begin to generate the report when it try to execute' org.jacoco:jacoco-maven-plugin:0.8.7:report' and I do not know why. But It has nothing of relation with , and I do not care too much because if I try to build the binaries without test, it works until the end.
(I am trying to build with hbase profile 2.1.9 and using -Dmaven.compiler.executable=/usr/lib/jvm/jdk1.8.0_202/bin/javac  because I have by default an openjdk version "11.0.12" 2021-07-20).

Here is the file log
PHOENIX-6583-SCREEN-LOG-IN-BUILDING.txt

You are right. With 'ptr.getLength() > 0' is enough.
At the begining I thought that only 'o' should be checked.
Later I added ptr.lenght (it was necesary for default values) without cheking if 'o != null' could be removed.
Finally, as you sugest, I tested  with only  'ptr.getLength() > 0'.
And, of course, if there is not something that I do not see, It can be removed.
About the test, in my enviroment, I tested the changes sereval times. the results are:
default-test -> never fails
ParallelStatsEnabledTest ->  never fails
ParallelStatsDisabledTest -> never fails
NeedTheirOwnClusterTests -> randon failures
Those random test are not allways the same failures.
for example, in my last test, the failure is in: 'PermissionNSEnabledWithCustomAccessControllerIT>BasePermissionsIT.testSystemTablePermissions:1027->BasePermissionsIT.verifyAllowed:894->BasePermissionsIT.verifyAllowed:901 » UndeclaredThrowable'.
But other time, I have 'PhoenixMetricsIT.testGlobalPhoenixMetricsForQueries:199' (now I don't know if that error was with jdk8 or jdk11)
Another time I had:
'MaxConcurrentConnectionsIT.testDeleteRuntimeFailureClosesConnections:124 Found 1 connections still open. expected:<0> but was:<1>'
and 'LogicalTableNameIT.testUpdatePhysicalIndexTableName_runScrutiny:215->LogicalTableNameBaseIT.test_IndexTableChange:187 » SnapshotCreation'.
Summing up, in 'NeedTheirOwnClusterTests', I can't give a fault pattern, but I think the faults I have have nothing to do with the change I am proposing.
Finally, when maven is going to build the report with jacoco, it allways fails (in my enviroment).
[ERROR] Failed to execute goal org.jacoco:jacoco-maven-plugin:0.8.7:report (report) on project phoenix-core: Execution report of goal org.jacoco:jacoco-maven-plugin:0.8.7:report failed: Incompatible execution data for class org/apache/hadoop/hbase/regionserver/MetricsRegionAggregateSourceImpl with id 2687434e0753a2bc. -> [Help 1]
(I drop the screen log of my last execution).
PHOENIX-6583-SCREEN-LOG-IN-BUILDING.txt
I wanted to point out that, regarding test, I had lots of problems and fails when using 'openjdk version "11.0.12" 2021-07-20' with semi-random test failures. So I decided to change all to 'java version "1.8.0_202"'.
Since them, I only have random failures in NeedTheirOwnClusterTests . I followed the instruction in https://github.com/apache/phoenix/blob/master/BUILDING.md . so I sugest, if it is necesary a specific jvm to compile and test, it is advisable to indicate it that file.
Besides, when you ask to 'Please also fix the remaining spaces at the end of lines.', I thing that there is some king of cache with file 'phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java' beacuse it was removed from the branch in the commit eae4b11. I saw several times to "remove spaces' in that file. But the file is removed. You can check it int the PHOENIX-6583 branch on alejandro-anadon/phoenix.
(https://github.com/alejandro-anadon/phoenix).
In the checkstile chekers I see follow (but not allways apears... sometimes appers, another not):
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:40:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:42:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:44:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:46:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:49:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:51:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:52:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:59:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:66:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:73:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:80:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:81:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:84:
But that file does not exist anymore. The test that I propose was moved to phoenix-core/src/it/java/org/apache/phoenix/end2end/NullIT.java as you sugested.

It keeps saying: "Apache Yetus(jenkins) error: blanks — The patch has 13 line(s) that end in blanks. " over the file that does not exits any more in  PHOENIX-6583 branch on alejandro-anadon/phoenix:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:40:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:42:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:44:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:46:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:49:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:51:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:52:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:59:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:66:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:73:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:80:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:81:
phoenix-core/src/it/java/org/apache/phoenix/end2end/BinaryTypeIT.java:84:
That file was deleted in the commit https://github.com/apache/phoenix/commit/eae4b115e18f932debb6aca9ce1b6d8a7ff5c2df

Thank you @alejandro-anadon.

The Jacoco instability is also known, but we do no have a solution for it.
There are also some flaky tests, so that's OK.

BTW the solution you found to is te same the code that is used in PChar.

@alejandro-anadon
The patch is good commit, but I have noticed that your email address has an IP address in it.
Do you want to use that as your committer email ?
If not, then please push another commit with the email that you want to use.
If yes, please confirm it.

Hi,
now I am lost. I saw that you closed the PR with unmerged commits. Now I don't know how to proceed.
Should I  delete alejandro-anadon:PHOENIX-6583 branch, open a new one (same name?) and do a new PR ? (Belive or not... I am a new user of git. I had been using subversion until this colavolarion)

I've merged this patch manually, not via the GitHub interface. It's already in the master repo (check it).
You can delete this PR, or leave it as it is, it doesn't matter.


Is there a way to pull

Requires a lot of superfluous wrapping  just for styling purposes.
I'm sure there's rationale behind it and it's not a deal-breaker, but can we start a discussion if it seems possible?

It is not clear to me what you mean by "pull

@giuseppeg  I think he mean something like this:
const styles = (

)

export default () => (

Hello

    {styles}

)

I'm looking for solution for this problem too.
Can we do this?

Sorry, I meant, does anyone have any ideas on how to inject styles?
As an example, if I have a stateless component that is just an
 tag, I have to wrap it in a superfluous
 just to be able to use


Avoid a crash in grpc_security_connector_shutdown.

Can one of the admins verify this patch?

Can one of the admins verify this patch?


Please release latest version

Problem
I want to gem install fluent-plugin-aws-elasticsearch-service and get the latest version because it supports fluent-plugin-elasticsearch>=4, but this version is not yet available on Ruby gems.
Steps to replicate
$ gem install fluent-plugin-aws-elasticsearch-service:2.3.0
$ gem list | grep -i elastic
...
fluent-plugin-aws-elasticsearch-service (2.3.0)
fluent-plugin-elasticsearch (3.8.0)

Expected Behavior or What you need to ask
Please release the latest version on Ruby gems :-)
Using Fluentd and ES plugin versions
I am using Docker image fluent/fluentd:v1.11.0-1.0 and running gem install fluent-plugin-aws-elasticsearch-service.
OS version:
$ uname -a
Linux 3dacadfd4385 4.19.76-linuxkit #1 SMP Tue May 26 11:42:35 UTC 2020 x86_64 Linux

FluentD version:
$ fluentd --version
fluentd 1.11.0

@atomita Could you kindly take a look? Thanks in advance.

@AndreLouisCaron
I released v2.4.0
Thank you.
@cosmo0920
Thank you for your support.

Thanks a lot for releasing, it now works like a charm :-)


GoogleDataTransport not compile in Xcode 12

[REQUIRED] Step 1: Describe your environment

Xcode version: 12
Firebase SDK version: 6.32.2
Firebase Component: GoogleDataTransport
Component version: 7.3.0
Installation method: CocoaPods

[REQUIRED] Step 2: Describe the problem
Parse issue
Could not build module 'nanopb'

Lexical or Preprocessor Issue

Duplicate of #6484. tldr Update to CocoaPods 1.10


Error loading Tensorflow model

I'm experiencing an error when loading a TF model and deploying the Vespa app:
Uploading application '/app/target/application.zip' using http://localhost:19071/application/v2/tenant/default/session
Session 2 for tenant 'default' created.
Preparing session 2 using http://localhost:19071/application/v2/tenant/default/session/2/prepared
Request failed. HTTP status code: 400
Invalid application package: default.default: Error loading model: Could not import TensorFlow model from directory '/opt/vespa/var/db/vespa/config_server/serverdb/tenants/default/sessions/2/.preprocessed/models/factorization_machine/saved': Output of 'dense_out/Sigmoid' has no type.

This also occurs if attempt to use a different layer as the output.
The model is trained in Keras, which I would assume to not be a problem as it's just an API to the underlying TF implementation.
My code for exporting the model is as used in: https://github.com/vespa-engine/vespa/blob/b3f6782b32990164ea703c7bcb44085cdb8c4fdb/model-integration/src/test/models/tensorflow/mnist/simple_mnist.py except for the I/O layer dicts.
The saved model and weights can be found on GDrive: https://drive.google.com/drive/folders/1kyvW88Y2_6RzQBQUVd8EYycFTvRx_vt4?usp=sharing
Thanks in advance

Thanks @lukealexmiller. I see a few import warnings here where the low level operations VarHandleOp, ReadVariableOp, Pack, StridedSlice and ResourceGather are not implemented in Vespa yet:
embedding_product_slug/embeddings: operation 'VarHandleOp' is currently not implemented
embedding_product_slug/embedding_lookup: operation 'ResourceGather' is currently not implemented
flatten/strided_slice: operation 'StridedSlice' is currently not implemented
flatten/Reshape/shape: operation 'Pack' is currently not implemented
embedding_user_guid/embeddings: operation 'VarHandleOp' is currently not implemented
embedding_user_guid/embedding_lookup: operation 'ResourceGather' is currently not implemented
flatten_1/strided_slice: operation 'StridedSlice' is currently not implemented
flatten_1/Reshape/shape: operation 'Pack' is currently not implemented
batch_normalization_v1/moving_variance: operation 'VarHandleOp' is currently not implemented
batch_normalization_v1/cond_1/ReadVariableOp: operation 'ReadVariableOp' is currently not implemented
batch_normalization_v1/gamma: operation 'VarHandleOp' is currently not implemented
batch_normalization_v1/batchnorm/mul/ReadVariableOp: operation 'ReadVariableOp' is currently not implemented
batch_normalization_v1/beta: operation 'VarHandleOp' is currently not implemented
batch_normalization_v1/batchnorm/ReadVariableOp: operation 'ReadVariableOp' is currently not implemented
batch_normalization_v1/moving_mean: operation 'VarHandleOp' is currently not implemented
batch_normalization_v1/cond/ReadVariableOp: operation 'ReadVariableOp' is currently not implemented
dense_out/kernel: operation 'VarHandleOp' is currently not implemented
dense_out/MatMul/ReadVariableOp: operation 'ReadVariableOp' is currently not implemented
dense_out/bias: operation 'VarHandleOp' is currently not implemented
dense_out/BiasAdd/ReadVariableOp: operation 'ReadVariableOp' is currently not implemented

With the exception of StridedSlice I can't find the other operations in the TF doc: https://www.tensorflow.org/api_docs/cc . Do you know if these are from some contrib packages?
Cheers,

Lester

Is the above information logged out somewhere? I can't find the low-level info in vespa-logfmt. Would be good to be able to see this while debugging.
Testing a new model where I freeze and optimize the original model, and then remove embedding layers (my mistake including them in original model) I have the following file: https://drive.google.com/file/d/1fKQQwMmMl1RJu6W7gmXqtw2Yx1RxqRyh/view?usp=sharing
However this gives the same error as before, even though all ops are supported in https://github.com/vespa-engine/vespa/blob/master/model-integration/src/main/java/ai/vespa/rankingexpression/importer/tensorflow/GraphImporter.java#L22 .
I then upgraded to latest Vespa (7.34.16 -> 7.62.30) and I now have a new error message:
Uploading application '/app/target/application.zip' using http://localhost:19071/application/v2/tenant/default/session
Session 2 for tenant 'default' created.
Preparing session 2 using http://localhost:19071/application/v2/tenant/default/session/2/prepared
Request failed. HTTP status code: 400
Invalid application package: default.default: Error loading model: Index 1 out of bounds for length 1
Tips on accessing the low-level information and any other insight would be greatly appreciated. Thanks!

I reproduced this. The immediate cause is that MatMul is invoked with a rank 1 tensor, while it assumes 2 (i.e matrixes). I added an explicit check for that so the error message makes sense.
Now, why does this happen? That's where it gets tricky. You're right that we're missing a way to debug the intermediate graph created during conversion. I'm adding that now, not released yet but here's what it prints in this case:
dense_out/MatMul:
MatMul(
Join(
Join(
ExpandDims(
Sum(
Join(
Join(
Argument(tensor(d0[],d1[32])),
Map(
Join(
Sum(
Map(Argument(tensor(d0[],d1[32])), f(a)(a * a)),
Const(tensor()),
[input_embedding_user_guid_1]),
Const(tensor()),
f(a,b)(max(a, b))),
f(a)(1.0 / sqrt(a))),
f(a,b)(a * b)),
Join(
Argument(tensor(d0[],d1[32])),
Map(
Join(
Sum(
Map(
Argument(tensor(d0[],d1[32])),
f(a)(a * a)),
Const(tensor()),
[input_embedding_user_guid_1]),
Const(tensor()), f(a,b)(max(a, b))),
f(a)(1.0 / sqrt(a))), f(a,b)(a * b)),
f(a,b)(a * b)),
Const(tensor()),
[input_embedding_user_guid_1]),
Const(tensor()),
[]),
Join(
Map(
Join(
Const(tensor(test_batch_normalization_v1_moving_variance_0[1])),
Const(tensor()),
f(a,b)(a + b)),
f(a)(1.0 / sqrt(a))),
Const(tensor(test_batch_normalization_v1_moving_variance_0[1])),
f(a,b)(a * b)),
f(a,b)(a * b)),
Join(
Const(tensor(test_batch_normalization_v1_moving_mean_0[1])),
Join(
Const(tensor(test_batch_normalization_v1_moving_mean_0[1])),
Join(
Map(
Join(
Const(tensor(test_batch_normalization_v1_moving_variance_0[1])),
Const(tensor()),
f(a,b)(a + b)),
f(a)(1.0 / sqrt(a))),
Const(tensor(test_batch_normalization_v1_moving_variance_0[1])),
f(a,b)(a * b)), f(a,b)(a * b)),
f(a,b)(a - b)), f(a,b)(a + b)),
Const(tensor(test_dense_out_kernel_0[1],test_dense_out_kernel_1[1])))
Can't say I immediately see the cause - do you have a clue? Otherwise I think I'll need to add some deeper consistency checking at this level similar to what we have for our tensor language.
Btw, regarding the Keras/TF2.0 thing - we're aware and will add support for that.

I added type annotations to the prettyprinting, which makes it easy to see the problem:
java.lang.IllegalArgumentException: Expected 2 dimensions in the first argument to MatMul(tensor(input_embedding_user_guid_0[]), tensor(test_dense_out_kernel_0[1],test_dense_out_kernel_1[1])) but got just [input_embedding_user_guid_0[]] from tensor(input_embedding_user_guid_0[]):                                 Join( tensor(input_embedding_user_guid_0[]):                                   Join( tensor(input_embedding_user_guid_0[]):                                     ExpandDims( tensor(input_embedding_user_guid_0[]):                                       Sum[keep_dims=false]( tensor(input_embedding_user_guid_0[],input_embedding_user_guid_1[32]):         Join( tensor(input_embedding_user_guid_0[],input_embedding_user_guid_1[32]):           Join( tensor(input_embedding_user_guid_0[],input_embedding_user_guid_1[32]):             Argument(tensor(d0[],d1[32])), tensor(input_embedding_user_guid_0[],input_embedding_user_guid_1[1]):              Map( tensor(input_embedding_user_guid_0[],input_embedding_user_guid_1[1]):                Join( tensor(input_embedding_user_guid_0[],input_embedding_user_guid_1[1]):                  Sum[keep_dims=true]( tensor(input_embedding_user_guid_0[],input_embedding_user_guid_1[32]):                   Map( tensor(input_embedding_user_guid_0[],input_embedding_user_guid_1[32]):                     Argument(tensor(d0[],d1[32])),                                                                                f(a)(a * a)                                                                                )                                                                                , tensor():                                                                                Const(tensor()),                                                                                [input_embedding_user_guid_1]                                                                                )                                                                                , tensor():                                                                              Const(tensor()), f(a,b)(max(a, b))                                                                                )                                                                                , f(a)(1.0 / sqrt(a))                                                                                )                                                                                , f(a,b)(a * b)                                                                                )                                                                                , tensor(input_embedding_user_guid_0[],input_embedding_user_guid_1[32]):           Join( tensor(input_embedding_user_guid_0[],input_embedding_user_guid_1[32]):             Argument(tensor(d0[],d1[32])), tensor(input_embedding_user_guid_0[],input_embedding_user_guid_1[1]):              Map( tensor(input_embedding_user_guid_0[],input_embedding_user_guid_1[1]):                Join( tensor(input_embedding_user_guid_0[],input_embedding_user_guid_1[1]):                  Sum[keep_dims=true]( tensor(input_embedding_user_guid_0[],input_embedding_user_guid_1[32]):                   Map( tensor(input_embedding_user_guid_0[],input_embedding_user_guid_1[32]):                     Argument(tensor(d0[],d1[32])),                                                                                f(a)(a * a)                                                                                )                                                                                , tensor():                                                                                Const(tensor()),                                                                                [input_embedding_user_guid_1]                                                                                )                                                                                , tensor():                                                                              Const(tensor()), f(a,b)(max(a, b))                                                                                )                                                                                , f(a)(1.0 / sqrt(a))                                                                                )                                                                                , f(a,b)(a * b)                                                                                )                                                                                , f(a,b)(a * b)                                                                                )                                                                                , tensor():                                                                      Const(tensor()),                                                                                [input_embedding_user_guid_1]                                                                              )                                                                              , tensor():                                                                    Const(tensor()),                                                                              []                                                                            )                                                                            , tensor(test_batch_normalization_v1_moving_variance_0[1]):                  Join( tensor(test_batch_normalization_v1_moving_variance_0[1]):                    Map( tensor(test_batch_normalization_v1_moving_variance_0[1]):                      Join( tensor(test_batch_normalization_v1_moving_variance_0[1]):                        Const(                                                                                tensor(                                                                                test_batch_normalization_v1_moving_variance_0[1]                                                                                )                                                                                )                                                                                , tensor():                                                                        Const(tensor()), f(a,b)(a + b)                                                                                )                                                                                , f(a)(1.0 / sqrt(a))                                                                              )                                                                              , tensor(test_batch_normalization_v1_moving_variance_0[1]):                    Const(                                                                                tensor(                                                                                test_batch_normalization_v1_moving_variance_0[1]                                                                                )                                                                              )                                                                              , f(a,b)(a * b)                                                                            )                                                                            , f(a,b)(a * b)                                                                          )                                                                          , tensor(test_batch_normalization_v1_moving_mean_0[1]):                    Join( tensor(test_batch_normalization_v1_moving_mean_0[1]):                      Const(                                                                              tensor(                                                                                test_batch_normalization_v1_moving_mean_0[1]                                                                              )                                                                            )                                                                            , tensor(test_batch_normalization_v1_moving_mean_0[1]):                      Join( tensor(test_batch_normalization_v1_moving_mean_0[1]):                        Const(                                                                                tensor(                                                                                test_batch_normalization_v1_moving_mean_0[1]                                                                                )                                                                              )                                                                              , tensor(test_batch_normalization_v1_moving_variance_0[1]):                    Join( tensor(test_batch_normalization_v1_moving_variance_0[1]):                      Map( tensor(test_batch_normalization_v1_moving_variance_0[1]):                        Join( tensor(test_batch_normalization_v1_moving_variance_0[1]):                          Const(                                                                                tensor(                                                                                test_batch_normalization_v1_moving_variance_0[1]                                                                                )                                                                                )                                                                                , tensor():                                                                          Const(tensor()), f(a,b)(a + b)                                                                                )                                                                                , f(a)(1.0 / sqrt(a))                                                                                )                                                                                , tensor(test_batch_normalization_v1_moving_variance_0[1]):                      Const(                                                                                tensor(                                                                                test_batch_normalization_v1_moving_variance_0[1]                                                                                )                                                                                )                                                                                , f(a,b)(a * b)                                                                              )                                                                              , f(a,b)(a * b)                                                                            )                                                                            , f(a,b)(a - b)                                                                          )                                                                          , f(a,b)(a + b)                                                                        )

The root cause was ExpandDims being unwilling to add a new dimension to the end of the list of dimensions (because it incorrectly ensured that the index of the new dimension is not larger than the existing set of dimensions). I fixed that, but there is another problem with this model which I'm looking at now.

The other problem was that the intermediate data layout optimizer (how to lay out the data to cause the least jumping in memory to make the entire computation) could not find a solution for this model due to not being willing to work hard enough. All of this was fixed in https://github.com/vespa-engine/vespa/pull/9944 which is released 7.72.36.


Add 0xc030 as a supported TLS cipher

This gives us ~500 more decoys over Merit. We can probably add a couple more GCM cipher suites since they will work, but this is the popular one.

See #70


Cannot run manage.py runserver command after upgrade to latest version

I upgraded to the latest version from version 1.8.2 from version 1.7.2 r1. I used the method of cloning the git repository. Once I upgraded I tried to use the run manage.py runserver command that is saved in the command history on my VM and now I am getting an import error.
ImportError: No module named packaging.version

how do i fix this problem?
Thanks

./manage.py migrate Traceback (most recent call last):   File "./manage.py", line 10, in <module>     execute_from_command_line(sys.argv)   File "/usr/local/lib/python2.7/dist-packages/django/core/management/__init__.py", line 367, in execute_from_command_line     utility.execute()   File "/usr/local/lib/python2.7/dist-packages/django/core/management/__init__.py", line 341, in execute     django.setup()   File "/usr/local/lib/python2.7/dist-packages/django/__init__.py", line 27, in setup     apps.populate(settings.INSTALLED_APPS)   File "/usr/local/lib/python2.7/dist-packages/django/apps/registry.py", line 108, in populate     app_config.import_models(all_models)   File "/usr/local/lib/python2.7/dist-packages/django/apps/config.py", line 199, in import_models     self.models_module = import_module(models_module_name)   File "/usr/lib/python2.7/importlib/__init__.py", line 37, in import_module     __import__(name)   File "/opt/netbox/netbox/dcim/models.py", line 14, in <module>     from extras.rpc import RPC_CLIENTS   File "/opt/netbox/netbox/extras/rpc.py", line 1, in <module>     from ncclient import manager   File "/usr/local/lib/python2.7/dist-packages/ncclient/manager.py", line 22, in <module>     from ncclient import operations   File "/usr/local/lib/python2.7/dist-packages/ncclient/operations/__init__.py", line 16, in <module>     from ncclient.operations.rpc import RPC, RPCReply, RPCError, RaiseMode   File "/usr/local/lib/python2.7/dist-packages/ncclient/operations/rpc.py", line 20, in <module>     from ncclient.transport import SessionListener   File "/usr/local/lib/python2.7/dist-packages/ncclient/transport/__init__.py", line 18, in <module>     from ncclient.transport.ssh import SSHSession   File "/usr/local/lib/python2.7/dist-packages/ncclient/transport/ssh.py", line 26, in <module>     import paramiko   File "/usr/local/lib/python2.7/dist-packages/paramiko/__init__.py", line 30, in <module>     from paramiko.transport import SecurityOptions, Transport   File "/usr/local/lib/python2.7/dist-packages/paramiko/transport.py", line 33, in <module>     from cryptography.hazmat.backends import default_backend   File "/usr/local/lib/python2.7/dist-packages/cryptography/hazmat/backends/__init__.py", line 7, in <module>     import pkg_resources   File "/usr/local/lib/python2.7/dist-packages/pkg_resources/__init__.py", line 70, in <module>     import packaging.version ImportError: No module named packaging.version
Having the same issue here...

This does not appear to be a NetBox bug. If you'd like assistance with upgrading, please post to the mailing list.

This is for dietervanhoutte, since we were so quickly shut down without even a comment as to why it may not be working.
Uninstall pip:
sudo apt-get purge python pip
Re-install pip:
curl https://bootstrap.pypa.io/get-pip.py | sudo python
When you try to run your web server it will tell you to run this command:
python manage.py migrate
After this netbox will start working as intended.

Hi @jbro209070,
At the end I've managed to fix it already by your actions mentioned yesterday evening.
Thanks to add it to this topic as it might help other people as well.
D


Use importlib and import GenericForeignKey from from django.contrib.contenttypes.fields

Importlib is included in Python 2.7, and will be dropped in Django 1.9 as it is no longer needed
django.contrib.contenttypes.generic will be removed in Django 1.9 and has been replaced by
fields, forms, and admin submodules instead of generic.
This should hopefully fix: #309
Kinda hard to test when all the Django 1.8 stuff ain't working yet. I'll fix it if there is a need to after the Django 1.8 pull-requests are merged :)

Coverage decreased (-0.05%) to 92.72% when pulling bc28e30c8e5c27273c215454c44fe45267500707 on frwickst:dj19depracation into 17fa48a24fc2188f17876891f94bc65869fba4c7 on lukaszb:devel.

Coverage decreased (-0.05%) to 92.72% when pulling bc28e30c8e5c27273c215454c44fe45267500707 on frwickst:dj19depracation into 17fa48a24fc2188f17876891f94bc65869fba4c7 on lukaszb:devel.

I just verified that the deprecation warnings I got with django-admin check are fixed with this PR.

Thanks @frwickst and @TauPan !

Would it be possible to get a release that includes this fix ?
Would be much appreciated to go forward with Django REST Framework against master.

Yup, just started vacations, hopefully I would release new version soon.

Looking forward to it and enjoy your vacations !


Device: (3:2294) null is not an object (evaluating 'f.getRandomBase64') on react-native

When I try to generate an UUID on react-native I get null is not an object error
the error only comes when I test on mobile but the app works fine in the browser. I have posted the question on stack overflow
Question Here

@afashaisakiye this is definitely unexpected.
Could you try https://github.com/ctavan/uuid-example-react-native to see if that works for you? And if so compare with your app to see where the difference is?

@afashaisakiye this is definitely unexpected.
Could you try https://github.com/ctavan/uuid-example-react-native to see if that works for you? And if so compare with your app to see where the difference is?

I checked this  code but it's a bit complicated but here is my code
import * as React from 'react';
import { View } from 'react-native';

import 'react-native-get-random-values';
import { v4 as uuidv4 } from 'uuid';

export default function App() {
  return (
    <View>
     {uuidv4()}
    </View>
  );
}

@afashaisakiye are you using Expo? The snack is running in Expo so it won't work there.
If you are using Expo, getRandomValues is currently not supported, please upvote this issue: https://github.com/expo/expo/issues/7209

Thank you I probably would have scratched my head for forever

@afashaisakiye are you still experiencing this issue? If it is expo-related, we are already tracking this in #375
If you think this is a different issue, then feel free to reopen and add more information.


WebXR/WebGL: Article about perspective [MVP]

We need an article talking about perspective: what it is, why it's used, and how to apply it, as well as the various types of perspective and how perspective is represented in transforms.
Topics

[ ] Intro: what is perspective?
[ ] Perspective concepts
[ ] Why perspective matters
[ ] Types of perspective
[ ] Fitting into reality in an AR scene

Resources

https://en.wikipedia.org/wiki/3D_projection
https://developer.mozilla.org/en-US/docs/Web/API/WebGL_API/WebGL_model_view_projection

Acceptance criteria

[ ] Content complete and accurate
[ ] Submitted for review as deemed necessary

It was decided to not move this into next sprint. Removing the milestone.

Aaaand this is now back into the India-Juliett sprint, since the security work I was going to be doing is pushed back due to the unavailability of the security team to help until July sometime.

https://wiki.developer.mozilla.org/en-US/docs/Web/API/WebXR_Device_API/Perspective
Some of the information included in the task list have been added to the previously-existing article on the topic of perspective:
https://wiki.developer.mozilla.org/en-US/docs/Web/API/WebGL_API/WebGL_model_view_projection


Can we use it with Classes?

Hi, I see that the project uses Hooks, that's neat!
Thoigh I was wondering if some version it's available with classes or such

Hi!
You mean the lib internally using classes? Why exactly do you need that? Retrocompatibility with some specific React version?
Or perhaps you only need examples with classes?


[1.7.10] Can't cancel Flame burn

I have a server and i have Mekanism and MyTown2 mods installed. I created a protection to check each tick for a EntityFlame:
    {
      "class": "mekanism.common.entity.EntityFlame",
      "type": "entity",
      "actions": "TRACKED",
      "flags": "PVP",
      "range": 20,
      "priority": "HIGH"
    }

The protection works fine, except because the target starts burning, even without the flame impact it. Maybe it is setting the target in burning, instead waiting for the flame strike the target.

Consider disabling aesthetic world damage in the config, accomplishes the same thing.

It's false and I still able to burn stuff with a Flamethrower, even cancelling right-click and the flame.


Update README.md

Added Voicy to the open-source list

Thanks, and sorry for the delay. I accidentally marked the notification of this PR as read.


Multiple clicks on comment

Multiple clicks on the comment button will result in opening the comments multiple times (multiple requests)
Steps to reproduce:

Go to a post
Click on the comment button multiple times and quickly

The same issue in notification, when you click on notification multiple times it'll open the screen multiple times


Ember.EnumerableUtils is deprecated

EnumerableUtils has been removed from ember 2.
Would it be possible to remove it's usage?
https://github.com/emberjs/ember.js/pull/11455

:+1:, ran into this when trying to use this addon with Ember 2.2.0


Change DataServlet file to include name

Complete step 1 of week 3 walkthrough by adding name to DataServlet.java

Please feel free to disregard until I merge changes from last PR!

I'm a little confused when I try to pull from master from this branch it says it's already up to date


Adds view transitions features for cross-document transitions and transition selection, and adds a new group

New Features:

Active view transition (selectors)
Cross-document view transitions
View transition class

Updated Features:

View transitions

Groups:

View Transitions

@ddbeck the rationales for the splits were

The at-rule, view-class, and pseudos are part of a different spec (level 2 vs 1) than the original and have a different and incompatible support story from the original (and each other). All things being equal this could also have been handled with compute_from
The at-rule and related keys are strictly cross-document which feels right as a separate feature even though it uses common mechanisms otherwise
The classes work in a way unusual and distinct enough (added CSS classes to a non-DOM entity) that a separate feature seemed warranted

I'm not strongly committed to this division. The first commit in this branch actually included everything new in the original feature if you want to see that in context: 4f59b14

OK, cool. I'm happy with this. Let's merge this.


Add env render module

Hi,
This PR addresses https://github.com/apple/pkl/issues/273.
I assumed the .env format defined by https://github.com/motdotla/dotenv.
Since .env can only represent single line value assignments (e.g., NAME="foo") the primary challenge was deciding how to simplify pkl structures. Here, I decided to minimize parsing for the .env consumer.
So, I chose the following conversions:

Hierarchical structures (Mappings) are flattened, using keys as the components.
Array structures (Listings) are flattened, using indexes as the components.

So,
// .pkl file
name="joe"
server {
  host = "localhost"
  port = 8080
}

becomes
// .env file
NAME="joe"
SERVER_HOST="localhost"
SERVER_PORT="8080"

And
// .pkl file
ports {
  8080
  8081
  8082
}

becomes
// .env file
PORTS_0="8080"
PORTS_1="8081"
PORTS_2="8082"

Alternatively, array structures could be inlined, so that the above example would instead become
PORTS="[8080, 8081, 8082]"

letting flattening be the responsibility of converters.
Thanks for reading!

Hey, thanks for the contribution!
This seems a little too opinionated for something like pkl-pantry--the handling of nested values seems a little too tied to the dotenv library, and doesn't seem generally usable as a format. For that reason, I don't think pkl-pantry is the best fit for this.
However, you don't need to submit this package here in order for it to be shareable. Feel free to publish it yourself as a GitHub release. When you do that, you can import the package via package://pkg.pkl-lang.org/github.com/<org>/<repo>/<release>@<version>.
For an example of another package that's published independently, take a look at @jamesward's https://github.com/jamesward/pklgha


add extension methods for SetAppTheme and SetAppThemeColor

Description of Change

Linked Issues

Fixes #
#117

PR Checklist

[ ] Has a linked Issue, and the Issue has been approved(bug) or Championed (feature/proposal)
[ ] Has tests (if omitted, state reason in description)
[ ] Has samples (if omitted, state reason in description)
[ ] Rebased on top of main at time of PR
[ ] Changes adhere to coding standard
[ ] Documentation created or updated: https://github.com/MicrosoftDocs/CommunityToolkit/pulls/XYZ

Additional information

Thanks @fredericoregateiro!
Your Proposal Champion is @bijington and he will help guide you through the New Feature Proposal Process.
The Proposal for this feature, #117, must first be approved by the core maintainer team before we can review, approve and merge this PR. Shaun will bring this feature to a vote at our upcoming Monthly Standup meeting this Thursday.
After it is approved, we'll also need you to write the Docs by opening a PR on our Docs repo: https://github.com/MicrosoftDocs/CommunityToolkit/
I did take a quick look at this PR and noticed a few things missing:

[ ] Add Unit Tests
[ ] Update the Sample App to display the use of the new feature.

Thanks again for your hard work!

Thanks @brminnick
I'll be updating those taks as soon as i can

Thanks @brminnick
I'll be updating those taks as soon as i can

Thanks @fredericoregateiro, do let me know if you need any assistance with the tasks as I am here to assist in any way 👍

Docs are ready to go afaic


Issues converting custom pggan models

It seems that for pggan, state dictionaries for the model trained by paper authors (file karras2018iclr-celebahq-1024x1024.pkl) and custom models that are trained by their released code are different. You can check the differences here: https://www.diffchecker.com/0hFYlK82.
Unfortunately I was unable to tweak your code so that it would convert my trained model correctly.
Did you try converting custom trained model using pggan code? If so, could you please provide a model you trained that worked for you other than the one provided by pggan authors?

Sorry, but we didn't test on custom models. However, according to the diff file, you can simply change all Conv0 to Conv0_up in file models/pggan_generator_model.py. And swap the last two channels of weight parameter of Conv0_up layer when converting models (if needed).

Yes, I tried those changes but they didn't help. Converted model generates some random stuff instead of a well-formed images.
If you have some time to play around with that stuff I can email you a custom model that I was trying to convert.

Sure, I would like to help. Please also provide the training and inference code if possible. I want to make sure I use your model correctly.

I have the same question!

@AndrewMakar Thanks for pointing out this issue. I have done some tests on your model and successfully converted it. Solutions are as follows:

The officially released model does not use fused_scale, which means to combine conv2d and upsample2d together as conv2d_transpose. However, the official implementation uses fused_scale as default. I have already update the repo which now well supports fused_scale.

Your model hasn't been finished. Or say, the progressive progress is supposed to train until 1024x1024 resolution yet stops at 256x256 resolution. Actually, the tensorflow model employs a variable lod to handle this case. Accordingly, I have also involved this variable to make this repo more robust.

Now, please do experiments with the latest version. Hopefully it helps.

Works like a charm. Thank you so much!