runtime: kernel crash on darwin (Sierra)?

What version of Go are you using (go version)?
go version go1.9 linux/amd64 (cross-compiled to darwin)
Does this issue reproduce with the latest release?
yes
What operating system and processor architecture are you using (go env)?
GOARCH="amd64"
GOBIN=""
GOEXE=""
GOHOSTARCH="amd64"
GOHOSTOS="linux"
GOOS="linux"
GOPATH="/home/fd0/shared/work/go"
GORACE=""
GOROOT="/usr/lib/go"
GOTOOLDIR="/usr/lib/go/pkg/tool/linux_amd64"
GCCGO="gccgo"
CC="gcc"
GOGCCFLAGS="-fPIC -m64 -pthread -fmessage-length=0 -fdebug-prefix-map=/tmp/go-build170408252=/tmp/go-build -gno-record-gcc-switches"
CXX="g++"
CGO_ENABLED="1"
CGO_CFLAGS="-g -O2"
CGO_CPPFLAGS=""
CGO_CXXFLAGS="-g -O2"
CGO_FFLAGS="-g -O2"
CGO_LDFLAGS="-g -O2"
PKG_CONFIG="pkg-config"

What did you do?
I've built the official released binaries for restic on Linux for darwin. A user reported a kernel crash on a Mac with Sierra. According to the user, the machine is otherwise rock solid. The stack trace is:
Anonymous UUID:       72A2DB74-5BE6-0759-EAAF-962BC14E3A29

Sat Sep 23 20:43:12 2017

*** Panic Report ***
panic(cpu 3 caller 0xffffff8021ffe39d): Kernel trap at 0xffffff8021fa4431, type 14=page fault, registers:
CR0: 0x000000008001003b, CR2: 0xffffff7f868ce884, CR3: 0x00000003c9b1e033, CR4: 0x00000000001626e0
RAX: 0xffffff802ba4d438, RBX: 0xffffff7f80000000, RCX: 0xffffff7f868ce880, RDX: 0x000000008013e781
RSP: 0xffffff9220e33ab0, RBP: 0xffffff9220e33af0, RSI: 0x00000000008b5487, RDI: 0x0000000080000000
R8:  0xffffff8038fc6880, R9:  0x0000000000000000, R10: 0x00000000ffffff9f, R11: 0x00000000001f1ac4
R12: 0xffffff80509fe900, R13: 0xffffff802ced8738, R14: 0x0000003fffffffc0, R15: 0x0000000000000000
RFL: 0x0000000000010246, RIP: 0xffffff8021fa4431, CS:  0x0000000000000008, SS:  0x0000000000000010
Fault CR2: 0xffffff7f868ce884, Error code: 0x0000000000000002, Fault CPU: 0x3, PL: 1, VF: 5

Backtrace (CPU 3), Frame : Return Address
0xffffff9220e33740 : 0xffffff8021ee953c
0xffffff9220e337c0 : 0xffffff8021ffe39d
0xffffff9220e339a0 : 0xffffff8021e9a593
0xffffff9220e339c0 : 0xffffff8021fa4431
0xffffff9220e33af0 : 0xffffff8021faa4e5
0xffffff9220e33b40 : 0xffffff8021f89d31
0xffffff9220e33e40 : 0xffffff8021f80d2c
0xffffff9220e33f30 : 0xffffff8022374685
0xffffff9220e33f50 : 0xffffff80224240f5
0xffffff9220e33fb0 : 0xffffff8021e9ad96

BSD process name corresponding to current thread: restic_0.7.3_dar

Mac OS version:
16G29

Kernel version:
Darwin Kernel Version 16.7.0: Thu Jun 15 17:36:27 PDT 2017; root:xnu-3789.70.16~2/RELEASE_X86_64
Kernel UUID: D3314D98-5D40-3CD8-98A4-F1DD46C20E03
Kernel slide:     0x0000000021c00000
Kernel text base: 0xffffff8021e00000
__HIB  text base: 0xffffff8021d00000
System model name: Macmini6,1 (Mac-031AEE4D24BFF0B1)

Please let me know if there's anything we can do on our end to help debugging this issue. Thank you!
What did you expect to see?
No kernel crash.
What did you see instead?
A kernel crash.

Is this reproducible?  How easily?
Unfortunately I don't see any useful information in that panic report.  I don't even see which system call was executing or anything.  Perhaps others can pull out something useful.
If we can reproduce the problem, then ideally we could get the Darwin equivalent of an strace showing the system call sequence that led to the crash.

I'll try to find that out, thanks!

It looks like it's faulty memory, the user managed to crash the kernel with the Apple Hardware Test and memtest86. I'm therefore closing this issue. Thanks!

Thanks for following up.


Webpack imported Module is not a function

i installed d3.tip() with
npm install d3-tip
i get this error:
Uncaught TypeError: WEBPACK_IMPORTED_MODULE_2_d3.tip is not a function
My Versions:
"d3": "^4.13.0",
"d3-tip": "^0.7.1",

somebody has an idea?

This should be fixed in 0.9.1.


QANet executed with an error

Hi,
I tried to execute QANet.
It raiseed with an error:

Reason looks somthing index is out of range.
idx2word cotains lesser elements while code tries to access idx2word[105844]
Something in tensor needs attention.
Your help is appreciated. Thanks again.

This issue was occurring due to wrong file names while loading pickle files for word2idx and char2idx. It was initially loading the pickle files saved from the BIDAF notebook. It has been fixed now. Thank you for bringing this to my notice.


Inside Figma missing the visual layers

Describe the bug
There is no representation of the actual layer, colors, or text.
Where does this fantastic capability disappear?
I can see in live that the colors change.
To Reproduce
Steps to reproduce the behavior:

open the plugin
Click on Create team
no visual representation

Expected behavior
View the color scheme as in the Figma file inside "material design 3 kit."
Screenshots
If applicable, add screenshots to help explain your problem.

This picture is from your kit, and this part needs to be included for me.
Desktop (please complete the following information):

OS: MacOS
Figma desktop version.

We had to remove it for performance issues, but it is in the playground file and design kit file.
Both can be swapped to to your theme.

Hi Ivy,
Where is the playground file?
Inside the Figma file "material design kit (community)" there is no option
to edit and swap colors.
Can you please elaborate more on how I can edit and swap the color?
Thanks,
Ronen
On Thu, May 2, 2024 at 6:52 PM Ivy Knight @.***> wrote:

We had to remove it for performance issues, but it is in the playground
file and design kit file.
Both can be swapped to to your theme.
—
Reply to this email directly, view it on GitHub
https://github.com/material-foundation/material-theme-builder/issues/302#issuecomment-2090867149,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/A3YYXLWZ3CIFTWKUVADBVYDZAJONDAVCNFSM6AAAAABHDPNAKSVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDAOJQHA3DOMJUHE
.
You are receiving this because you authored the thread.Message ID:
@.***
com>

From the community page: https://www.figma.com/community/plugin/1034969338659738588/material-theme-builder
Click Open with… and then +Playground File


When exporting as PDF, shadows are not exported

Try it:
1.Draw some shapes, say some rectangles. Then select the rectangle and from Styles, check shadows (Styles->Shadows)
2.Now, from File menu click on Export as->pdf.
3.After downloading, I do not see shadows included!
Observing the same with both global and local shadows.

Hi, I've just noticed the same issue. A few months ago I found that in order to see the shadows when exporting as PDF I needed to apply the shadow to every shape one buy one rather than ticking "shadow" in the general "Diagram" panel on the right when nothing is selected. It seems like a recent update has led to a failure in the rendering of the PDF even if you apply the shadow to each shape. If I save the plot using a JPEG or png format the shadows are displayed.
Can you check it out?

We had to remove shadows in PDF for technical reasons. The shadow wasn't vector, it was raster.


Q: Long delays before websocket is open

Hi, I don't think this is a bug per say related to this project but curious if anyone is observing very long delays before the LG TV websocket is available for connection?
I have done many tests without using this framework to characterize timing and this is roughly what I found out, issuing *nix commands from my old rpi (which will run homebridge). Ive also done the equivalent using the core LGTV2 project that this homebridge extension uses, and it connects roughly after that long delay.

Issue wakeonlan command, T=0, issue a periodic netcat cmd to TV_IP:3000
TV powers T=2-3 s after wake command (you hear the relay switch click)
TV displays picture (livetv) at T=5-6s
Netcat connects to [TV_IP:3000] at T=14-15s

LG TV: OLED65E7/801.11ac connection, rpi/Enet
Thanks for an insight/info !

Hi,
LG has pretty slow channel changing times, somehow they never improved that over the years, for this reason i think there is a big delay between turning on the tv till the picture is there. Even on my 2018 OLED TV this is still slow.
As of the powering on, my TV powers on (click sound from TV) instantly after i press the Homekit power on button. There is no noticeable delay, so maybe this delay is related somehow to your network?

I think it’s the combination of the old rpi I am using and maybe the network, but my observation was regarding how soon can the LG accept a web socket connection and a request after it’s ON or pic is displayed. (If I use wakeonlan from my iMac, the TV powers on very quickly)
If you don’t mind, can you try with your plugin the following:

power on the LG, then
switch to another input, and check the delay!

What I am trying to do, is to create a plugin that will mimic the Harmony One activity concept (turn on TV, choose input, turn on AVR, turn on player,...). Thank you.

This all depends on the environment (network, hardware and also some randomness is involved).  So you cannot say that for each TV it takes 10 seconds. It will vary from user to user.

I never said that for each TV it takes long, I was asking for additional input so I can better understand the variables.
I will close this request for info and maybe follow up in the base lgtv2 project that your plugin uses.


make it clear its a dummy

people keep asking, is this real?
lets stop that conversation

r+

Is there somewhere I can click 'like?'


docs: update readmes

Description

Add a known issue about access tags and the UI. Addresses https://github.com/terraform-ibm-modules/terraform-ibm-cos/issues/202
Update the FS Cloud profile and example readmes for style and terminology and to be consistent among the modules. (See terraform-ibm-icd-postgresql PR 185.)

Types of changes in this PR
Changes that affect the core Terraform module or submodules

[ ] Bug fix
[ ] New feature
[ ] Dependency update

Changes that don't affect the core Terraform module or submodules

[ ] Examples or tests (addition or updates of examples or tests)
[x] Documentation update
[ ] CI-related update (pipeline, etc.)
[ ] Other

Release required?
Identify the type of release. For information about the changes in a semantic versioning release, see Release versioning.

[ ] No release
[ ] Patch release (x.x.X)
[ ] Minor release (x.X.x)
[ ] Major release (X.x.x)

Release notes content
If a release is required, replace this text with information that users need to know about the release. Write the release notes to help users understand the changes, and include information about how to update from the previous version.
Your notes helps the merger write the commit message for the PR that is published in the release notes for the module.

Checklist for reviewers

[ ] If relevant, a test for the change is included or updated with this PR.
[ ] If relevant, documentation for the change is included or updated with this PR.

Merge actions for mergers

Use a relevant conventional commit message that is based on the PR contents and any release notes provided by the PR author. The commit message determines whether a new version of the module is needed, and if so, which semver increment to use (major, minor, or patch).
Merge by using "Squash and merge".

:tada: This PR is included in version 6.6.1 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


Updated K2 extension to Manifest V3

Fixes https://github.com/Expensify/Expensify/issues/422655
Loading the plugin in Chrome after building produces no errors in console, which should be visible if there are any Manifest V3 incompatibilities.
Tested as much as I could, but will appreciate another pair of eyes looking into this. Afterwards, we need to submit the beta to Google for review to see if it really passes Manifest V3 restrictions.
Migration steps checked out:

[x] Update the manifest.json file appropriately - URL permissions needed to be moved to host_permissions and manifest version incremented
[x] Replace callbacks with promises - no API callbacks were made
[x] Double check we don't block any sites or web requests - no requests are blocked
[x] Double check we aren't loading code (libraries, etc.) from elsewhere - no remote code being loaded
[x] Migrate everything necessary out of the existing events.js and into a service worker - declared events.js as the service worker, I hope this is enough

Yeah I think the biggest change is that the service worker can be the only that is running in the background and it's governed by new rules (i.e. no global variables or any form of constant state keeping), but since we don't have any global variables there and only a bunch of listeners, events.js should work fine as a quasi service worker in principle.

Seems to work well for me to. All in favor to merge? ✋

I'll work on getting this deployed today. @mjasikowski after I merged this, I realized you missed adding an entry to https://github.com/Expensify/k2-extension/blob/main/CHANGELOG.md
Could you please submit a new PR with that change? Thanks!

@tgolen sure, will do that tomorrow


Use of Deprecated Constants part 3

DEVICE_CLASS_HUMIDIFIER was used from xiaomi_miot, this is a deprecated constant which will be removed in HA Core 2025.1. Use HumidifierDeviceClass.HUMIDIFIER instead, please create a bug report at https://github.com/al-one/hass-xiaomi-miot/issues
DEVICE_CLASS_DEHUMIDIFIER was used from xiaomi_miot, this is a deprecated constant which will be removed in HA Core 2025.1. Use HumidifierDeviceClass.DEHUMIDIFIER instead, please create a bug report at https://github.com/al-one/hass-xiaomi-miot/issues
SUPPORT_MODES was used from xiaomi_miot, this is a deprecated constant which will be removed in HA Core 2025.1. Use HumidifierEntityFeature.MODES instead, please create a bug report at https://github.com/al-one/hass-xiaomi-miot/issues

Logger: homeassistant.components.humidifier.const
Source: helpers/deprecation.py:205
Integration: Humidifier (documentation, issues)
First occurred: 20:04:53 (3 occurrences)
Last logged: 20:04:53
DEVICE_CLASS_HUMIDIFIER was used from xiaomi_miot, this is a deprecated constant which will be removed in HA Core 2025.1. Use HumidifierDeviceClass.HUMIDIFIER instead, please create a bug report at https://github.com/al-one/hass-xiaomi-miot/issues
DEVICE_CLASS_DEHUMIDIFIER was used from xiaomi_miot, this is a deprecated constant which will be removed in HA Core 2025.1. Use HumidifierDeviceClass.DEHUMIDIFIER instead, please create a bug report at https://github.com/al-one/hass-xiaomi-miot/issues
SUPPORT_MODES was used from xiaomi_miot, this is a deprecated constant which will be removed in HA Core 2025.1. Use HumidifierEntityFeature.MODES instead, please create a bug report at https://github.com/al-one/hass-xiaomi-miot/issues


archive sees no drives available

I'm trying to use the archival feature to copy to my main machine (which happens to be windows until some additional hardware arrives).
I'm running rsync inside ubuntu on wsl2.  The host drives are all auto mounted under /mnt/[windows drive letter]
I obviously don't want to sync to every drive on my windows machine, so I tried creating a diretory  /chiaplots and adding symlinks to the mounted drives inside it
cd /chiaplots
ln -s /mnt/p/PlotsFinal ./drive_p
ln -s /mnt/q/PlotsFinal ./drive_q

Running rsync manually from the plotting machine is able to successfully copy files, but  plotman says "No free archive dirs found."
rsyncd.conf
port = 12000
use chroot = false
read only = false

[chia]
  path = /chiaplots
  read only = no
  list = yes
  hosts allow = [plotter ip]

plotman.yaml
        archive:
                rsyncd_module: chia
                rsyncd_path: /chiaplots
                rsyncd_bwlimit: 80000  # Bandwidth limit in KB/s
                rsyncd_host: [windows ip]
                rsyncd_user: [username]

Do I have something misconfigured?

For now, I've been able to work around this by mapping the windows drive a 2nd time
mount -t drvfs P: /chiaplots/plots1

I think my solution is sufficient, so I'm going to close this


Question/Issue: adbc_driver_manager.AdbcDatabase could not be found when testing python snowflake driver

Hi,
Feel like I'm running in circles a little bit here when trying to test out connections, consistently running into the below error.
Hoping it's quite a simple oversight from my side, any help would be greatly appreciated
    return adbc_driver_manager.AdbcDatabase(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "adbc_driver_manager\_lib.pyx", line 555, in adbc_driver_manager._lib.AdbcDatabase.__init__
  File "adbc_driver_manager\_lib.pyx", line 385, in adbc_driver_manager._lib.check_error
adbc_driver_manager._lib.InternalError: ADBC_STATUS_INTERNAL (9): GetProcAddress(AdbcDriverInit) failed: (127) The specified procedure could not be found.

For context

issues on both python 3.10 & 3.11
windows machine
0.5.1 on both adbc-driver-manager and adbc-snowflake-driver

Some sample connection code below which works fine for sqlalchemy.
conn_str = f"{user}:{password}@{account}/{database}/{schema}?warehouse={warehouse}&role={role}"
import adbc_driver_snowflake.dbapi
import sqlalchemy

with sqlalchemy.create_engine(f"snowflake://{conn_str}").connect() as conn:
    print("connected sqlalchemy")

with adbc_driver_snowflake.dbapi.connect(conn_str) as conn:
    print("connected adbc")

How were the packages installed?

(We admittedly don't test Windows very deeply due to lack of experience and lack of machines)

Just the

Just the classic
pip install adbc-driver-manager
pip install adbc-driver-snowflake
Would be happy to do some testing on windows if pointed in right direction

You installed these both for Py10/11? Pretty old SO answer but I wonder if this applies:
https://stackoverflow.com/questions/14627047/windowserror-error-127-the-specified-procedure-could-not-be-found

Yep installed on both 10 & 11.
Hmm that doesn't seem to have been the issue as did try uninstalling the packages on 3.10 and testing with 3.11 and vice versa.
Even uninstalling 3.10 didn't seem to remedy

Sorry for the delay. It's likely we've packaged something wrong (the release verification process doesn't test wheels on Windows - any help would be appreciated). If I can find some time I'll deal with the Windows VM and see if I can reproduce.

No rush at all! Massively
appreciate the responses. As far as I can tell, the issues seem to come from trying to import the .__lib in the init, maybe some quirk with cython & windows?

It looks to be because none of the Adbc* symbols are exported. I think we'd just need to figure out how to configure CGO/Go/CMake

OK! Turns out that was the only issue. Easy enough, thankfully. I'll have a PR up later today...


Feat/rate limiter

[x]  Adding rate limiter to project
[x] Adding openapi-comment-parser to project
[x] Applying decoupling to the logger

Codecov Report

Merging #26 (2b34dec) into develop (806bd9b) will not change coverage.
The diff coverage is 100.00%.

@@            Coverage Diff            @@
##           develop       #26   +/-   ##
=========================================
  Coverage   100.00%   100.00%
=========================================
  Files           24        26    +2
  Lines          274       300   +26
  Branches        26        25    -1
=========================================
+ Hits           274       300   +26

Impacted Files
Coverage Δ

src/controllers/builds.ts
100.00% <ø> (ø)

src/controllers/testCases.ts
100.00% <ø> (ø)

src/controllers/testPlans.ts
100.00% <ø> (ø)

src/controllers/testProjects.ts
100.00% <ø> (ø)

src/controllers/testSuites.ts
100.00% <ø> (ø)

src/logger.ts
100.00% <100.00%> (ø)

src/middlewares/rateLimiterMiddleware.ts
100.00% <100.00%> (ø)

src/openapirc.ts
100.00% <100.00%> (ø)

src/server.ts
100.00% <100.00%> (ø)

... and 1 more

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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Aggregate - From selector reseting when editing

Steps:

Go to aggregates.
Add simple transaction and select in "From" multisig account. Save.
Open again transaction.

Result: From is reset and it's presenting cosigner instead multisig account.
Video: https://www.loom.com/share/c62eeb16640f44e78c782fcb107fda46

This should as well be fixed by https://github.com/nemgrouplimited/symbol-desktop-wallet/pull/1032

@rg911 no. Still able to reproduce but now I have open twice:
https://share.getcloudapp.com/NQuJvejL

Fixed.


[cherry-pick][BACKLOG-16179] Fix String to Numeric conversion behaviour that was…

…causing it to throw a KettleException
@pentaho/millenniumfalcon cherry-pick from master. please review

Build Completed
:white_check_mark: This pull request has passed all validations.
Build Commands
ant -Dtestreports.dir=bin/reports/unit-test -f core/build.xml clean-all resolve jacoco && ant -f core/build.xml checkstyle publish-local

Cleanup Commands
rm -r ~/.ivy2/local || echo no publish local to remove

Changed files
  assembly/package-res/samples/transformations/JavaScript - String to Number to String conversion.ktr
  core/src/org/pentaho/di/core/row/value/ValueMetaBase.java

Unit test coverage change
These statistics help you identify how your changes have affected the coverage of the following files. If a file is not in this list, then its coverage was not affected by your changes. To get some help interpreting these metrics, please refer to Jacoco's documentation.
org.pentaho.di.core.row.value.ValueMetaBase

Branch Change: -.23%:small_red_triangle_down:
Complexity Change: -.26%:small_red_triangle_down:
Instruction Change: -.12%:small_red_triangle_down:
Line Change: -.08%:small_red_triangle_down:
Method Change: -.11%:small_red_triangle_down:


Improper bracket pair highlighting in .ts file

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

VS Code Version: 1.78.2
OS Version: Windows

Steps to Reproduce:

Thanks for creating this issue! It looks like you may be using an old version of VS Code, the latest stable release is 1.78.2. Please try upgrading to the latest version and checking whether this issue remains.
Happy Coding!

Can you share the full typescript snippet? Thanks!

This is the full snippet


how to config InternVL2-Llama3-76B-AWQ

System Info / 系統信息
{
"version": 1,
"context_length": 32000,
"model_name": "InternVL2-Llama3-76B-AWQ",
"model_lang": [
"en",
"zh"
],
"model_ability": [
"generate",
"vision",
"chat"
],
"model_description": "",
"model_family": "other",
"model_specs": [
{
"model_format": "awq",
"model_size_in_billions": 76,
"quantizations": [
"4-bit"
],
"model_id": null,
"model_hub": "huggingface",
"model_uri": "/root/.xinference/InternVL2-Llama3-76B-AWQ",
"model_revision": null
}
],
"prompt_style": null,
"is_builtin": false
}
Running Xinference with Docker? / 是否使用 Docker 运行 Xinfernece？

[X] docker / docker
[ ] pip install / 通过 pip install 安装
[ ] installation from source / 从源码安装

Version info / 版本信息
lastest
The command used to start Xinference / 用以启动 xinference 的命令
docker run -dit -v /data/ez/llms:/root/.xinference -e XINFERENCE_HOME=/root/.xinference -p 9999:9997 --gpus all --shm-size 20g --ipc=host aicenter/xinference:latest xinference-local -H <IP_ADDRESS>  --log-level debug
Reproduction / 复现过程
File "/usr/local/lib/python3.10/dist-packages/xinference/model/llm/pytorch/core.py", line 771, in _get_full_prompt
assert self.model_family.prompt_style is not None
Expected behavior / 期待表现
how to config InternVL2-Llama3-76B-AWQ

@amumu96 Could you look at this issue.

engine Transformers does not support AWQ format, and AWQ format should not launch by engine Transformers. Could you tell me how do you launch it? If you want to launch AWQ format internvl2, please use engine LMDEPLOY

engine Transformers does not support AWQ format, and AWQ format should not launch by engine Transformers. Could you tell me how do you launch it? If you want to launch AWQ format internvl2, please use engine LMDEPLOY

Just tried this with no success, returns error RuntimeError: Failed to launch model, detail: [address=<IP_ADDRESS>:58248, pid=3691355] Model internvl2 cannot be run on engine LMDEPLOY.
I used this command to launch: xinference launch --model-engine LMDEPLOY --model-name internvl2 --size-in-billions 76 --model-format awq --quantization Int4

Did you install lmdeploy?

Did you install lmdeploy?

Confirmed it's running after installing lmdeploy, thanks!

OK, close this issue then.

@danialcheung @qinxuye
How do I install lmdeploy in xinference? I used Docker to run 'pip install lmdeploy' but it still doesn't work.

try python -c "import lmdeploy" to see if it's installed correctly.


Add ability to count Flow Nodes in BPMN diagram - Full Diagram and Selection

Would be helpful if there was a Statistics tab or some sort of inspector that would allow us to easily count the number of Flow Nodes (Activities-Tasks and Sub-Processes, Gateways, and Events) in a BPMN diagram.
Would be looking for both a diagram wide count and then just being able to count based on the current selection.

Why would that be helpful? I personally think this is out of scope for the Camunda Modeler.

@nikku, I thought this would be a good item to add to the modeler because the flow node count is a number that is often used to determine level of complexity and the aggregate is often used by support contracts (N number of flow node instances per year will be supported under the contract).
As teams work on their BPMN, it would be helpful for them to understand the number of flow nodes they are creating to allow faster calculations of the total flow node instances being generated in a year (their estimates).  If there is not a auto-count, then people have to manually count.
The count is not a perfect representation because of sub-processes, multi-instance, and branching with percentage variation, but it is a good base.

I'd rather have that information as part of the run-time rather than the design time environment. Or are you talking about a design time only use-case here?

@nikku I think it is valuable in both locations.  Run-time is good for understanding actual usage.
But at the design time I think it is valuable because someone builds XYZ process and a common question can be "whats the predicted node flow instance impact?" Which would be at the highest level of detail: Node Flow Count * estimated instances.
Either the designer has to manually count and keep recounting during adjustments, or the modeler provides a general count (of course won't be able to account for everything, but it is much better than a manual count).

whats the predicted node flow instance impact?

The only way this makes sense to me if we rephrase the question to "What is the process complexity" (flow node instances is one of the metrics there).
We may provide ways to extend the Modeler beyond element templates some time into the future. This functionality would be a good candidate for such an extension.

The only way this makes sense to me if we rephrase the question to "What is the process complexity" (flow node instances is one of the metrics there).

Sure, that makes sense for my use case.
Thanks

We'll not support this any time soon. Modeler plug-ins may be the way to implement such feature.
We're happy to feature such plug-in, if you implement it.


Hypergraphs

Is there any intention to support hypergraphs? The main deadlock to integrate hypergraphs in Graphs is the assumption that edges point to 2 vertices. Currently is weird to implement a "undirected" HyperEdge type: dst and src have no point there (even in an undirected graph dst and src look weird) because there will be more than 2 vertices.
My proposal is the following:

See simple edges as a special case of hyperedges whose cardinality is 2.
Stop using dst and src for undirected edges $\rightarrow$ Use vertices(edge) where possible instead.
For graph algorithms that need a non-hyper graph view, a hyperedge can be seen as the powerset of cardinality 2 of the connecting vertices (i.e. all vertices in an hyperedge are at distance 1).

If we relax this assumption, open edges could also be supported and implemented as cardinality 1 hyperedges.

A directed hyperedge $H_D$ contains two sets of vertices: the set of source vertices $S$ and the set of target vertices $T$. $H_D$ can be seen as the collection of all directed edges from $S$ to $T$.
$$ H_D = S \times T $$
A undirected hyperedge $H_U$ contains only the set of connecting vertices $C$. As above, $H_U$ can be seen as a the collection of all undirected edges in $R$, which is equivalent to the powerset $\mathcal{P}$ of $R$ of cardinality 2.
$$ H_U = R \times R = \mathcal{P}_2(R) $$
Remark A undirected hyperedge can be seen as a directed hyperset where $R = S = T$.[^1]
[^1]: The Wikipedia definition for undirected graph says something similar, but its definition is wrong because it leaves some edges out.
A possible implementation would be:
struct HyperEdge{T}
    vertices::Set{T}
end

struct HyperDiEdge{T}
    src::Set{T}
    dst::Set{T}
end

# Base.issubset, Base.in definitions

Only question I have is what behavior should we define if src and dst are not disjoint in HyperDiEdge. In my head, the directed hyperedge would also contain all the directed edges from and to the repeated elements... but should we allow self-loops too?

Oh god don't get me started about self-loops. No one really knows how far they are supported in the current code base

Oh god don't get me started about self-loops. No one really knows how far they are supported in the current code base

:joy: Then let's forget about self-loops for now and just check that $S$ and $T$ are disjoint when creating a $HyperDiEdge$.


Dupli objects support

Add support for duplis
Motion blur related fixes
Code cleanups

I'm going to go ahead and merge this as is.  We can fix the interactive update later.


Python › Auto Complete: Add Brackets

Issue Type: Feature Request
Auto Complete for brackets not working with pylance
Extension version: 2020.8.1
VS Code version: Code 1.48.0 (db40434f562994116e5b21c24015a2e40b2504e6, 2020-08-13T07:40:55.768Z)
OS version: Linux x64 5.4.0-42-generic

Can you provide more details about what you mean by "add brackets"? Are you referring to automatically adding parentheses when completing a symbol that is callable? If so, I think this is a duplicate of #37.

Yeah
python.autoComplete.addBrackets": true
automatic complete by adding brackets to python function and methods not working

OK, thanks. Marking this as duplicate since we're already tracking this in #37.


Fix fire button ripple

Task/Issue URL: https://app.asana.com/0/488551667048375/1208089433074776/f
Description
Steps to test this PR
Feature 1

[ ]
[ ]

UI changes

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After

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(Upload after screenshot)

#4922  👈
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Camera preview for front camera is flipped post Impeller updates

What package does this bug report belong to?
camera
What target platforms are you seeing this bug on?
Android
Have you already upgraded your packages?
Yes
Dependency versions
Latest version of camera_android_camerax: 0.6.10, however, the bug was first observed in 0.6.8+2
Steps to reproduce

Run example on an Android device (in my case, Samsung Galaxy A25 5G)
Use the front camera
See camera preview being incorrect

Expected results
The camera preview should be mirrored like it is with default cameras apps.
Actual results
The camera preview is shown like it is recorded (from the perspective of the user, it is mirrored).
Code sample
Code sample
import 'package:camera/camera.dart';
import 'package:flutter/foundation.dart';
import 'package:flutter/material.dart';

void main() async {
  runApp(const MainApp());
}

class MainApp extends StatefulWidget {
  const MainApp({super.key});

  @override
  State<MainApp> createState() => _MainAppState();
}

class _MainAppState extends State<MainApp> {
  final _runner = _Runner();

  @override
  Widget build(BuildContext context) {
    return MaterialApp(
      home: Scaffold(
        body: ValueListenableBuilder(
          valueListenable: _runner,
          builder: _build,
        ),
      ),
    );
  }

  Widget _build(BuildContext context, _State value, Widget? child) {
    switch (value) {
      case _Loaded():
        return Center(
          child: CameraPreview(value.controller),
        );

      case _Simple.initializing:
        return const Center(
          child: CircularProgressIndicator(),
        );

      case _Simple.error:
        return const Center(
          child: Icon(Icons.error),
        );
    }
  }
}

class _Runner with ChangeNotifier implements ValueListenable<_State> {
  _Runner() {
    _init();
  }

  void _init() async {
    final available = await availableCameras();
    if (available.isEmpty) {
      _emit(_Simple.error);
    } else {
      final controller = CameraController(
          available.firstWhere((candidate) {
            return candidate.lensDirection == CameraLensDirection.front;
          }, orElse: () {
            return available.first;
          }),
          ResolutionPreset.veryHigh);
      try {
        await controller.initialize();
        _emit(_Loaded(
          controller: controller,
          available: available,
        ));
      } catch (e) {
        _emit(_Simple.error);
      }
    }
  }

  _State _value = _Simple.initializing;
  @override
  _State get value => _value;
  void _emit(_State state) {
    _value = state;
    notifyListeners();
  }
}

sealed class _State {}

enum _Simple implements _State {
  initializing,
  error,
}

class _Loaded implements _State {
  final CameraController controller;
  final List<CameraDescription> available;

  const _Loaded({
    required this.controller,
    required this.available,
  });
}

Screenshots or Videos
No response
Logs
No response
Flutter Doctor output
Doctor output
[✓] Flutter (Channel stable, 3.24.3, on macOS 15.0.1 24A348 darwin-arm64, locale en)
    • Flutter version 3.24.3 on channel stable at /Users/User/Development/flutter
    • Upstream repository https://github.com/flutter/flutter.git
    • Framework revision 2663184aa7 (5 weeks ago), 2024-09-11 16:27:48 -0500
    • Engine revision 36335019a8
    • Dart version 3.5.3
    • DevTools version 2.37.3

[✓] Android toolchain - develop for Android devices (Android SDK version 34.0.0)
    • Android SDK at /Users/User/Library/Android/sdk
    • Platform android-35, build-tools 34.0.0
    • Java binary at: /Applications/Android Studio.app/Contents/jbr/Contents/Home/bin/java
    • Java version OpenJDK Runtime Environment (build 17.0.10+0-17.0.10b1087.21-11609105)
    • All Android licenses accepted.

[✓] Xcode - develop for iOS and macOS (Xcode 16.0)
    • Xcode at /Applications/Xcode.app/Contents/Developer
    • Build 16A242d
    • CocoaPods version 1.15.2

[✓] Chrome - develop for the web
    • Chrome at /Applications/Google Chrome.app/Contents/MacOS/Google Chrome

[✓] Android Studio (version 2024.1)
    • Android Studio at /Applications/Android Studio.app/Contents
    • Flutter plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/9212-flutter
    • Dart plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/6351-dart
    • Java version OpenJDK Runtime Environment (build 17.0.10+0-17.0.10b1087.21-11609105)

[✓] VS Code (version 1.95.0-insider)
    • VS Code at /Applications/Visual Studio Code - Insiders.app/Contents
    • Flutter extension version 3.98.0

[✓] Connected device (5 available)
    • Pixel (mobile)                  • FA76R0301797          • android-arm64  • Android 10 (API 29)
    • SM A256B (mobile)               • R5CX806EZNE           • android-arm64  • Android 14 (API 34)
    • macOS (desktop)                 • macos                 • darwin-arm64   • macOS 15.0.1 24A348 darwin-arm64
    • Mac Designed for iPad (desktop) • mac-designed-for-ipad • darwin         • macOS 15.0.1 24A348 darwin-arm64
    • Chrome (web)                    • chrome                • web-javascript • Google Chrome 129.0.6668.101

[✓] Network resources
    • All expected network resources are available.

• No issues found!

I can reproduce this issue as well with camera_android_camerax's example on Pixel 7, Android 15. Confirmed this on Flutter Channel master, 3.27.0-1.0.pre.87.
I'm unsure if this has the same root cause as https://github.com/flutter/flutter/issues/154241, so I will keep this as an variant to have the team's thoughts.

Demo screenshots (comparing with device's camera)

Flutter camera
Device camera

If you want to fix the camera perspective (just the UI), you can implement the following code:

import 'dart:math' as math;

Transform(
  alignment: Alignment.center,
  transform: Matrix4.rotationY(math.pi),
  child: CameraPreview(cameraController),
)

This will flip the camera preview horizontally, adjusting the perspective as needed.

Same issue,
I overridden to a lower version
camera_android_camerax: 0.6.5+2


Scope results over custom space domains example AttributeError, no 'elemental_volume'

hey,
i was trying to use the Scope results over custom space domains example (https://dpfdocs.pyansys.com/examples/00-basic/09-results_over_space_subset.html?highlight=named) but when it gets to line 66 it will give the error :
AttributeError: 'CommonResults' object has no attribute 'elemental_volume'
Something in this block is not working:
# Choose specific elements
# ~~~~~~~~~~~~~~~~~~~~~~~~
# If some elements are specifically of interest, an elemental ``mesh_scoping``
# can be connected.

elements_scoping = dpf.mesh_scoping_factory.elemental_scoping(range(500, 5000))
print(elements_scoping)

# or
elements_scoping = dpf.Scoping(ids=range(500, 5000), location=dpf.locations.elemental)
print(elements_scoping)

volume = model.results.elemental_volume.on_mesh_scoping(elements_scoping).eval() # it has an error from this line.

model.metadata.meshed_region.plot(volume)`

updated core, now it works. ignore.


use the common default page size

Current coverage is 65.30% (diff: 0.00%)

Merging #457 into master will decrease coverage by 0.11%

@@             master       #457   diff @@
==========================================
  Files            46         46
  Lines          2195       2199     +4
  Methods           0          0
  Messages          0          0
  Branches          0          0
==========================================
  Hits           1436       1436
- Misses          609        611     +2
- Partials        150        152     +2

Powered by Codecov. Last update 22be2a3...0f96d98

@aslakknutsen please review

I think it would make sense to extract the parameter handling code an use it everywhere we do paging.

@tsmaeder Agree. The pagination stuff is pretty general purpose.

I have created a separate issue to track moving the pagination related things to a common function (#494). Closing this PR.


sciond: Go sciond is not informed about first hop revocations

In the python sciond we had a flush flag which meant that the local path segment cache would be cleared and new segments are fetched from the PS.
In the Go sciond we no longer do flushing, we instead just have a refresh flag which means fetch new segments from the PS and then reply.
This leads to Go sciond possibly never be informed about a revocation, which is on the first hop.
The client will time out when waiting on the response but does not know that the interface has been revoked.
The PS will not return segments with revoked on-segment interfaces.
That means sciond will assume that the segment is still valid and return it again to the client.
Possible solutions:

The client informs sciond that it assumes a certain interface is broken. Sciond will then query the PS for this explicit interface. This could be done using an IFStateRequest.
PS returns "interesting"/"recent" revocations in the reply if the refresh flag is set. (Note that for this the segverifier probably has to be adapted to consider all revocations)
The refresh flag could again be used to flush the DB.

Related: https://github.com/scionproto/scion/issues/2871

To deal with link issues, the current plan is to go with #3743. This means SCIOND will never see a revocation, so we don't need to implement this any more.


Please add DaemonSettings documentation

I'm a little mystified about what the properties do.
LeadingEdgeBuffer seems to need to be set to 0 if I want awaiting a Rebuild(or RebuildAll) to be deterministic and actually complete the rebuild before returning. No idea what it actually means or why I'd set it to something else, though. :)
ExceptionHandling seems to do nothing regardless of what I set it to. I'm sure I just don't understand how it works, though.
Many thanks for the help!

@tetious I'll take that on me. Valid request 👍

@tetious I started to add samples for AsyncDaemon in my repository. I hope to present also other settings there https://github.com/oskardudycz/EventSourcing.NetCore/pull/24

This should be made a blocker for 4.0 right? No excuse for traversing into GH issues or unit tests to understand or discover the behavior?

I planned to add it now, but as the Async Daemon will change significantly in v4 then after consultation we decided to add it in the v4. If I have enough time I'll try to squeeze it earlier.

Async Daemon docs are added in v4, closing this.


Update readme

Signed-off-by: Shriti<EMAIL_ADDRESS>Description
This PR fixes https://github.com/layer5io/layer5/issues/771
Notes for Reviewers
Signed commits

[x] Yes, I signed my commits.

Added zoom links


tfrecords giving parsing error when saved examples are too big

When I try to save a example to a tfrecord that is too large a parsing error occurs.
What related GitHub issues or StackOverflow threads have you found by searching the web for your problem?
I think that this might be the same error and problem that other people are getting when saving long sequences to tfrecords like seen here https://github.com/tensorflow/tensorflow/issues/5234 and https://github.com/OliviaMG/xiaomeng/issues/1. While both of these threads found solutions the underlining problem does not seem to be found.
Environment info
Operating System:
Ubuntu 16.04
CUDA 8.0
CUDNN 5.1
TensorFlow 0.12.1
If possible, provide a minimal reproducible example
Running this minimal script will cause the error. Lowering the SIZE_RECORD value will cause the script to run with out error.
from tqdm import tqdm
import numpy as np
import tensorflow as tf

# this will kill it
SIZE_RECORD=20000000
# this will run just fine
# SIZE_RECORD=2000000

writer = tf.python_io.TFRecordWriter("test.tfrecords")
# iterate over 10 times
# wrap with tqdm for a progress bar
for example_idx in tqdm(xrange(2)):
    features = np.zeros((SIZE_RECORD))

    # construct the Example proto boject
    example = tf.train.Example(
        # Example contains a Features proto object
        features=tf.train.Features(
          # Features contains a map of string to Feature proto objects
          feature={
            # A Feature contains one of either a int64_list,
            # float_list, or bytes_list
            'image': tf.train.Feature(
                float_list=tf.train.FloatList(value=features.astype("float"))),
    }))
    # use the proto object to serialize the example to a string
    serialized = example.SerializeToString()
    # write the serialized object to disk
    writer.write(serialized)
writer.close()

def read_and_decode_single_example(filename):
    # first construct a queue containing a list of filenames.
    # this lets a user split up there dataset in multiple files to keep
    # size down
    filename_queue = tf.train.string_input_producer([filename],
                                                    num_epochs=None)
    # Unlike the TFRecordWriter, the TFRecordReader is symbolic
    reader = tf.TFRecordReader()
    # One can read a single serialized example from a filename
    # serialized_example is a Tensor of type string.
    _, serialized_example = reader.read(filename_queue)
    # The serialized example is converted back to actual values.
    # One needs to describe the format of the objects to be returned
    features = tf.parse_single_example(
        serialized_example,
        features={
            # We know the length of both fields. If not the
            # tf.VarLenFeature could be used
            'image': tf.FixedLenFeature([SIZE_RECORD], tf.float32)
        })
    # now return the converted data
    image = features['image']
    return image

# get single examples
image = read_and_decode_single_example("test.tfrecords")
# groups examples into batches randomly
images_batch = tf.train.shuffle_batch(
    [image], batch_size=1,
    capacity=3,
    min_after_dequeue=2)

# simple model
w = tf.get_variable("w1", [SIZE_RECORD, 1])
y_pred = tf.matmul(images_batch, w)
loss = tf.nn.l2_loss(y_pred - 1.0)

# for monitoring
loss_mean = tf.reduce_mean(loss)

train_op = tf.train.AdamOptimizer().minimize(loss)

sess = tf.Session()
init = tf.initialize_all_variables()
sess.run(init)
tf.train.start_queue_runners(sess=sess)

_, loss_val = sess.run([train_op, loss_mean])
print loss_val
print("worked!!!")

What other attempted solutions have you tried?
I have tried saving the example in a variety of different ways including converting it to a string and breaking up the vector into multiple features.
Logs or other output that would be helpful
This is the output when the tfrecord is too big
W tensorflow/core/framework/op_kernel.cc:975] Invalid argument: Could not parse example input, value: '
���&
���&
image���&���&
���&
ERROR:tensorflow:Exception in QueueRunner: 'utf8' codec can't decode byte 0x9b in position 40: invalid start byte
Exception in thread Thread-3:
Traceback (most recent call last):
File "/usr/lib/python2.7/threading.py", line 801, in __bootstrap_inner
self.run()
File "/usr/lib/python2.7/threading.py", line 754, in run
self.__target(*self.__args, **self.__kwargs)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/queue_runner_impl.py", line 234, in _run
sess.run(enqueue_op)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 766, in run
run_metadata_ptr)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 964, in _run
feed_dict_string, options, run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1014, in _do_run
target_list, options, run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1021, in _do_call
return fn(*args)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1003, in _run_fn
status, run_metadata)
File "/usr/lib/python2.7/contextlib.py", line 24, in exit
self.gen.next()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/errors_impl.py", line 468, in raise_exception_on_not_ok_status
compat.as_text(pywrap_tensorflow.TF_Message(status)),
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/util/compat.py", line 84, in as_text
return bytes_or_text.decode(encoding)
File "/usr/lib/python2.7/encodings/utf_8.py", line 16, in decode
return codecs.utf_8_decode(input, errors, True)
UnicodeDecodeError: 'utf8' codec can't decode byte 0x9b in position 40: invalid start byte
Thank!!!

@ebrevdo I'm suspicious that this is a TFRecord problem, since the sizes don't approach INT_MAX.  The next likely candidate is the example parsing code.  Thoughts?

I have the same issue when writing large float lists to the tfrecords file. 64 MB seems to be the limit.

@jonasrauber Ah, right.  Protobufs are limited to 64 MB outside of Google for some unfathomable reason.  @martinwicke Was there a hack to increase this?

Using the other protobuf library as mentioned here doesn't help: https://github.com/tensorflow/tensorflow/issues/5676

I am having a similar problem when trying to read my Example protocol bufffer in batches. I have also tried the other protobuf library, but that did not help.

Same issue for me. Increasing size of protobufs would be great :)

I had the same issue on Python 2.7/TF 1.0.1 and I solved it by installing the modified protobuf library (https://www.tensorflow.org/install/install_linux#protobuf_pip_package_31).
However, just upgrading the old protobuf version using pip din't work for me initially.
I suggest to first uninstall any older version of protobuf explicitly with
pip uninstall protobuf
(you may need to run this command multiple times)
and then installing the modified version with:
pip install --upgrade  https://storage.googleapis.com/tensorflow/linux/cpu/protobuf-3.1.0-cp27-none-linux_x86_64.whl
Hope this helps.

Facing the same issue working with high-resolution images. Anyone found a hack around this?

Looks like installing Tensorflow 1.1.0-rc0 solved the issue for me.

I can also confirm that using Tensorflow 1.1.0 solved the problem for us.

Same here :D
On Apr 24, 2017 4:33 PM, "Elmer Garduno"<EMAIL_ADDRESS>wrote:

I can also confirm that using Tensorflow 1.1.0 solved the problem for us.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/tensorflow/tensorflow/issues/7311#issuecomment-296828348,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AEv26DKUPuzl_kTfBrjuYtZKn7gvPlCwks5rzRU1gaJpZM4L4-up
.

Thank you for checking back. I will close this issue as resolved in 1.1.


##[error]Validation Failed  Why does this error happen?

This my workflow yaml. I think there is no error. But it always fails. Someone can help me ? Thanks.

# on:
#   watch:
#     types: [started]
on: push
name: Upload Release Asset

jobs:
  build:
    name: Upload Release Asset
    runs-on: ubuntu-latest
    steps:
      - uses<EMAIL_ADDRESS>        id: runcmd
        with:
          architecture: aarch64
          distribution: ubuntu18.04
          run: |
            echo ::set-env name=ARCH::$(uname -m)
            echo ::set-output name=ARCH::$(uname -m)
            echo ::set-env name=TIME::$(date)
            ARCH=$(uname -m)
            echo "arch:::",$ARCH
            echo "123" >> ${ARCH}.zip
            echo `ls`
            echo `pwd`
      - name: test
        run: |
          echo ${TIME}
          echo "456" > ${ARCH}a.zip
          echo `uname -a`
          echo `pwd`
          echo `ls`
          echo ${ARCH}
      - name: Create Release
        id: create_release
        uses<EMAIL_ADDRESS>        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
          ARCH: ${{ env.ARCH }}
        with:
          tag_name: ${{ github.sha }}
          release_name: Release ${{ github.sha }}
          draft: false
          prerelease: false
      - name: Upload Release Asset
        id: upload-release-asset
        uses<EMAIL_ADDRESS>        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
          ARCH: ${{ env.ARCH }}
        with:
          upload_url: ${{ steps.create_release.outputs.upload_url }}
          asset_path: ${ARCH}.zip
          asset_name: ${ARCH}.zip
          asset_content_type: application/zip

I get this too. Relevant yaml:
jobs:
  release:
    runs-on: ubuntu-latest
    name: Release
    steps:
      - name: checkout
        uses: actions/checkout@v2
        with:
          fetch-depth: 1
      - name: build
        <omitted>
      - name: create release
        id: create_release
        uses: actions/create-release@v1
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
        with:
          tag_name: ${{ github.ref }}
          release_name: Release ${{ github.ref }}
          draft: false
          prerelease: false
      - name: upload release asset
        id: upload_release_asset
        uses: actions/upload-release-asset@v1
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
        with:
          upload_url: ${{ steps.create_release.outputs.upload_url }}
          asset_path: ./grax
          asset_name: grax
          asset_content_type: application/octet-stream

Logs:
##[debug]..Evaluating String:
##[debug]..=> 'ref'
##[debug]=> 'refs/tags/v0.1.0'
##[debug]Result: 'refs/tags/v0.1.0'
##[debug]Evaluating: format('Release {0}', github.ref)
##[debug]Evaluating format:
##[debug]..Evaluating String:
##[debug]..=> 'Release {0}'
##[debug]..Evaluating Index:
##[debug]....Evaluating github:
##[debug]....=> Object
##[debug]....Evaluating String:
##[debug]....=> 'ref'
##[debug]..=> 'refs/tags/v0.1.0'
##[debug]=> 'Release refs/tags/v0.1.0'
##[debug]Result: 'Release refs/tags/v0.1.0'
##[debug]Loading env
Run actions/create-release@v1
  with:
    tag_name: refs/tags/v0.1.0
    release_name: Release refs/tags/v0.1.0
    draft: false
    prerelease: false
  env:
    GITHUB_TOKEN: ***
##[error]Validation Failed
##[debug]Node Action run completed with exit code 1
##[debug]Finishing: create release

Repro: create a release via github.com web-ui. The actions starts because of the tag beeing created behind the scenes. The action tries to create a release with the name the user actualy created just in the step beforehand

Duplicate of #2 and sort of #29, #12.

Repro: create a release via github.com web-ui. The actions starts because of the tag beeing created behind the scenes. The action tries to create a release with the name the user actualy created just in the step beforehand

Steps I followed
1, Pushed changes to the to develop branch
2. PR Develop to Master
3. Merged the PR
4. From CLI triggered the below commands (Note it : NOT from WEB Console)

git tag  release_tag
git push origin  release_tag

i.g.

git tag v1.0.15
git push origin v1.0.15

This will solve it.


Non existing Dao interface in new OASP4J archetype

Steps to reproduce

Create a new Maven project using OASP4J archetype version 3.0.0-alpha.
Create a simple entity with one attribute:

public class EmployeeEntity  {

  private Long employeeId;

}

Generate CRUD Dao increment, which generatesApplicationDao.

Class ApplicationDao extends from a io.oasp.module.jpa.dataaccess.api.Dao interface, whose new archetype version is not included on its dependencies. Therefore, there are multiple compilation errors related to this non existing interface.
Archetype version 3.0.0 files:

Archetype version 2.4.0 files:

Objective
We should review the use of this Dao interface and find a new way to implement the CRUD Dao increment using other libraries included on the new OASP4J archetype version.

Has been fixed with the release of the new templates-devon4j.


ZIO AWS 5 (ZIO 2) release

TODO:

[x] zio-reactivestreams-interop for ZIO 2 (https://github.com/zio/interop-reactive-streams/pull/282)
[x] zio-config for ZIO 2 (https://github.com/zio/zio-config/pull/648)
[x] upgrade to http4s backend to CE3
[ ] Fix http4s backend (probably fs2-reactive-interop) (https://github.com/vigoo/zio-aws/issues/467)
[x] https://github.com/vigoo/zio-aws/issues/558
[x] https://github.com/vigoo/zio-aws/issues/92
[x] https://github.com/vigoo/zio-aws/issues/411
[x] https://github.com/vigoo/zio-aws/issues/388
[x] https://github.com/vigoo/zio-aws/issues/150
[ ] https://github.com/vigoo/zio-aws/issues/412
[x] Merge model.primitives into model? - won't do (https://github.com/vigoo/zio-aws/pull/643)
[x] Rename packages
[x] Move to ZIO org
[ ] https://github.com/zio/zio-aws/issues/648
[ ] Update documentation (https://github.com/zio/zio-aws/issues/646) and migrate to zio documentation template (https://github.com/zio/zio-aws/issues/647)
[ ] https://github.com/zio/zio-aws/issues/649

After moving to the zio org, this branch is continued on master. Remaining tasks are added to Milestone 5.x.x.x


Process nodes asynchronously

This will process node interviews and subscriptions asynchronously and block from running the task again until all queued nodes have been processed.
fixes: https://github.com/home-assistant-libs/python-matter-server/issues/265

Also is there any reason we process nodes hourly? wouldn't that make it so anything that was offline during startup wait a whole hour before it can be used?

I actually did that on purpose because the ResolveNode was a bit fragile when called simultane so interview them one by one at startup (if needed) and run a task every hour to check if there are any nodes that need a (re)interview.
So... this needs real proper testing. It would be great if the SDK can now handle multiple resolve and interviews commands at the same time  but in my experience that is not the case.
Also for thread devices this causes A LOT of traffic so I am not a fan of doing this async unless we have some lock on the interview/read call

As discussed on discord:

semaphore for max 5 interviews/read requests at the same time
assume that we now can call resolvenode multiple times simultanuous

works like a charm!


expose Notify for CommonJS

I'm building with Grunt and not using ES6 includes with babel or webpack.
Would be handy for the lib to attach to window.Notify if possible
Cheers

The library uses UMD, so a global should not be a problem. This is how the example demonalready works.

Hmmm, I must be missing something.
I took a look at the demo code and it couldn't be more simple 😄

I'm really not sure what you're doing here, can you give some more info?

So, I have two files. base.js and app.js. base.js contains all my libs like notify.js and then app.js contains the angular app.
All I'm trying to do is call upon Notify - nothing outlandish ;) But yea, I must have a conflict somewhere.
Will dig deeper. Looking forward to getting this working! 👊

That looks better, apologies for not checking more before opening a ticket. Just needed to walk away for a minute

No worries, glad it's working for you 👍


"Open with Windows Terminal" context menu not display on desktop (or right click without selected folder)

Windows Terminal version
v1.11.2921.0
Windows build number
22000.384 and dev
Other Software
No response
Steps to reproduce
It is difficult to reproduce, until found the association with onedrive
clean install 22000.194 and delete onedrivesetup.exe before oobe
install Windows Terminal
Expected Behavior
"Open with Windows Terminal" context menu display
Actual Behavior

but after install onedrive , the menu working properly
test result is:
22000.194 without onedrive = ok
update to 384 without onedrive = not display
384 with onedrive installed= ok

I have OneDrive installed.

@EdiWang
my windows(dev) had this problem before, I uninstalled onedrive, installed the latest 64-bit version... and then fixed the problem

@ikas-mc Wait, so, is this still an issue? If it is, I reached out to someone on the explorer team, and they told me how to get some advanced diagnostics that might help.
You should be able to take an advanced trace on in the Feedback Hub, on the bottom page:

then, file feedback on the File Explorer path as usual, and make sure to include the zip file from the advanced diagnostics trace. Add the "Share my feedback" link here, and I can make sure it gets promoted to the right folks.
Of course, if this isn't an issue anymore, we can just close this out without the trace ☺

@ikas-mc
Thanks for the tip. But for me, uninstall and reinstall OneDrive didn't help. Sad...

@zadjii-msft
This is still an issue, we just happened to find that this problem can be reproduced with onedrive
If it is determined that it is a system problem(api), then it can be closed..

Okay great, this was promoted internally to MSFT:37214068. There's not much for us to do here - this seems like a bug firmly in the explorer team's codebase. So, I'm gonna close this one out for now. I'm following the internal bug, and I'll give you an update once there's something to share. Thanks!

I can confirm that this bug occurs after removing the OneDriveSetup automatic startup from SOFTWARE\Microsoft\Windows\CurrentVersion\Run.

Is there at least a workaround?

The File Explorer team hasn't provided one, unfortunately. @danieldaeschle do you also not have OneDrive installed? That might help narrow the problem space for the explorer team

I have Onedrive installed

But it also does not get displayed in context menu

@EdiWang my windows(dev) had this problem before, I uninstalled onedrive, installed the latest 64-bit version... and then fixed the problem

this helped for me

I can confirm. Installed OneDrive x64, restarted File Explorer, context menu entry returned, uninstalled OneDrive, menu entry still remained.
Win 22000.469, WT 1.13.10336.0

@eddiezato
I uninstalled OneDrive, and install 64 bit version from https://oneclient.sfx.ms/Win/Insiders/21.139.0711.0001/amd64/OneDriveSetup.exe, restart my computer. It didn't work. Windows Terminal is still missing from context menu. Sad :(

However, I do have Windows Terminal menu if I right click on a folder instead of in a folder

I am also curios how can Windows Terminal menu be related to OneDrive, they seems to be two completely different things.

This issue seems to still exist as of today. It is observed that the "Open in Windows Terminal" menu appears on the Desktop Context Menu just by restarting the "Windows Explorer" from Task Manager. May be someone else can also confirm this behavior? This being the case, I am not sure if it is related to OneDrive. As mentioned earlier in this thread, it looks like a bug in the Windows Explorer code base. @zadjii-msft Did the Windows Explorer team acknowledge and any indication of what could be the potential fix?
It is still unclear why it happens only in some Windows machines and not all.

They haven't been able to find a repro unfortunately. More "advanced traces" might be helpful here, if it's happening consistently for you.

Yes, it is happening consistently. While all seems okay when I restart my PC, the item from the "Open in Windows Terminal" Context Menu disappears every time I log off from my ID and login to Windows (using same ID or another ID). I have also observed that the context menu issue gets fixed when I restart the Windows Explorer task in Task Manager. I have reported the bug with Steps Recorder screenshots and diagnostics log in the Feedback App. Refer: https://aka.ms/AAfyhpg. Hope this helps @zadjii-msft.

 And my "open in windows terminal" option was gone. I tried editing the regedit to add it but there was not blocked folder inside it also.

I believe this was fixed last Friday and should be flowing out to Insiders builds soonTM

In which build is this issue expected to be fixed?

Hey @iGattreX, it seems the issue was fixed in the 22598.200 build version

Finally its been months

I think I found the solution!!
So its an application called "terminal" created by Microsoft and can be found in the Microsoft Store. Re-downloaded the application and the right-click menu pops up with the "open in terminal" option. If anyone else could verify that this works that would be amazing.
Wish I took a screenshot before because it was 100% not there before I re-downloaded the application but see pics below for the after screenshots where the options menu is working again.

Hope this helps! Happy coding 😄

I'm found that the problem starts after installing the MS PowerToys. And it fixes after uninstalling the PowerToys and rebooting your PC but I'm reinstalled Windows 11 because I'm pollutws thw registry while tried fix problem. Is anyone who ran into a problem has been installed MS PowerToys on their PC's?

I'm found that the problem starts after installing the MS PowerToys. And it fixes after uninstalling the PowerToys and rebooting(or just log out) your PC but I'm reinstalled Windows 11 because I'm pollutws thw registry while tried fix problem. Is anyone who ran into a problem has been installed MS PowerToys on their PC's?

I had PowerToys installed, I tried to remove it and reboot but it didn’t show me the Open In Terminal, even after reinstalling Windows Terminal. Too bad, as I used this shortcut a lot on Windows 10.

There actually was a regression our side. The thread over at https://github.com/microsoft/terminal/issues/13523#issuecomment-1219393733 has the details. It was a combo of us changing a thing, and Windows 11 also changing a thing. There are more details in https://github.com/microsoft/terminal/issues/12578#issuecomment-1238859062 also.

Same Issue at Windows 10
Gif:

Terminal version

Windows 10 version

Same Issue at Windows 10
Gif:
Terminal version
Windows 10 version

I have the exact same issue.

Hi @omeilick ,
I think the workaround works. Unfortunately I couldn't get the screenshot of before but captured the workflow when it works.
https://github.com/microsoft/terminal/assets/99791294/23ecde69-bd2b-4e7b-8450-37ab201977e7

This issue seems to still exist as of today. It is observed that the "Open in Windows Terminal" menu appears on the Desktop Context Menu just by restarting the "Windows Explorer" from Task Manager. May be someone else can also confirm this behavior? This being the case, I am not sure if it is related to OneDrive. As mentioned earlier in this thread, it looks like a bug in the Windows Explorer code base. @zadjii-msft Did the Windows Explorer team acknowledge and any indication of what could be the potential fix?
It is still unclear why it happens only in some Windows machines and not all.

this worked for me


Detection and classification performance evaluation?

Are there any performance evaluation results for Apollo's detection and classification algorithms?

When we have evaluation data, we will let you know it.


Support Person payload

Welp that's the last time I trust the new Github merge resolution, sorry about your master branch, let me know if that caused any problems on your end.
Also thanks for the contribution, I'll take a closer look at it this weekend and probably merge it. From a first look it looks good.

A new test in 0.5.0 is failing, I'll probably pull this in and fix it on the staging branch though. 👍

Many thanks for looking into that. That's my first PR on GitHub so I've selected master by mistake.
I'll look into 0.5.0 and try to work with that version locally first.

Awesome, looks good to me. So I'll pull this in. 👍


Unable to debug SourceGenerator, no output and no log files created

Package versions:
    <PackageReference Include="NTypewriter.CodeModel">
      <Version><IP_ADDRESS></Version>
    </PackageReference>
    <PackageReference Include="NTypewriter.CodeModel.Functions">
      <Version><IP_ADDRESS></Version>
    </PackageReference>
    <PackageReference Include="NTypewriter.Editor.Config">
      <Version><IP_ADDRESS></Version>
    </PackageReference>
    <PackageReference Include="NTypewriter.SourceGenerator">
      <Version>0.2.5</Version>
    </PackageReference>

The error:
CSC: Warning CS8785 : Generator 'NTypewriterSourceGenerator' failed to generate source. It will not contribute to the output and compilation errors may occur as a result. Exception was of type 'ArgumentNullException' with message 'Value cannot be null.
How do I debug the SourceGenerator version or how do I enable full exception logging?

Does it not work on any project or only on a specific one?

what can I say, developing source generators is really painful.

what can I say, developing source generators is really painful.

Any way to get logs? I can't find any that are mentioned in the docs

Logs are generated only if everything went well on SG side:
https://github.com/NeVeSpl/NTypewriter/blob/deda6ab19f3e73b3b6b070103a8cc611d0287e65/NTypewriter.SourceGenerator/SourceGenerator.cs#L99C20-L99C20
if there is a problem with SG side, you should look for exceptions and what is in VS output window:
https://github.com/NeVeSpl/NTypewriter/blob/deda6ab19f3e73b3b6b070103a8cc611d0287e65/NTypewriter.SourceGenerator/SourceGenerator.cs#L103

It was probably the same bug as #103, related to missing build output path, fixed in version v0.3.4.


fix: deal with edage case in errorPropertyToPath

Reasons for making this change
When there is '.' in side a key of an object, the errorPropertyToPath function failed to parse the string into a path array.
Checklist

[x] I'm adding or updating code

[x] I've added and/or updated tests

Thanks for contributing :+1:

Released along v0.41.2.


fix(blog): link jumps (Closes #36)

The reason for jumps not working properly is because of the fixed header.
The links move exactly to the very top, but they get hidden behind the fixed header.
To solve this problem, we can make the header not fixed.

The linking issue is solved, but
there is some space before the page headings. This needs to be resolved. Otherwise, it just looks a bit odd.

[Actual]

[Expected]

The Hyperlinks / Table of Contents is more of a priority now that I am writing theory blogs/notes on Machine Learning. Hence, I will be merging this change. However, I will open another issue for the spacing problem.


Memory management

When I have a ListView of many paused Video components, the memory usage is out of control. I've resorted to unmounting the component when its paused and showing a screen shot instead. (Remounting & playing the video when the screenshot is tapped).
Does anyone have any ideas for a better solution here?

hi @elzii - unfortunately I stopped developing the project - but at the time I was really focused on just unmounting components :\


500 internal server error

I am trying this code and its giving me 500 internal server error,
I am not sure why, can anyone help me please. Am I doing anything wrong here?
\Auth::user()->hasRole('superadmin')
or
\Auth::user()->can('edit-user')
none of these work. I am not sure why?

I'm not sure too. More info is needed


Add cla-signed as prerequisite to mergify

Use the success status of the bot as a condition
for both the queue and the actual PR merging.
Use a different approach from the label used in: #16604 which didn't work, so PRs were not added to the queue by mergify.

retest this please

JFYI: Adding a 2nd label condition would work as well, see https://github.com/crate/crate/pull/16604/files#diff-6a30e47dd51449847422017b16878889b848f6602ac56d5a2e67ce8a19afade2L36-L37. But checking the verification bot result is probably even better.

Yes, I believe the issue is that I didn't add it to the queue conditions before, but I agree that the bot status is better, since the label can be added accidentally, manually.