With the Airportitlwm.kext on macOS from original configuration Wi-Fi is not working/broken on Windows

So, after pretty successful Big Sur 11.1 installation based on the original config.plist having Airportitlwm.kext enabled the Wi-Fi under macOS was running quite fine.
However:
When booting into Windows the Wi-Fi device seems to be completely broken

Nothing helps: driver update, reinstall, disabling/enabling.
This is reported here: https://github.com/OpenIntelWireless/itlwm/issues/329
Any suggestions as always much appreciated.

I don't have Windows installed on my laptop so i don't know how to fix this. The post you linked seems to know what's wrong

I don't have Windows installed on my laptop so i don't know how to fix this. The post you linked seems to know what's wrong

Indeed it's related to OpenCore boot.
Solution: do not boot Windows from OpenCore. Boot it by selecting Windows Boot Manager from UEFI boot menu. F12 on T450s

Indeed it's related to OpenCore boot.
Solution: do not boot Windows from OpenCore. Boot it by selecting Windows Boot Manager from UEFI boot menu. F12 on T450s


How to use mx.simple.bind() in R package

The help information of mx.simple.bind() is too simple. I just can't figure out how to really use it from its help message.  Also, I can't find any sample code that used this function. I wonder if any of you can help me understand its usage a little better.
Many thanks for your help.

Can anyone help me with this? The limited help documentation appears to be the biggest obstacle for mxnet to have wider acceptance.

@junshui We are working to improve documents and provide more examples. I will really appreciated your understanding of the situation that we are all students and have limited time.
For usage of mx.simple.bind(), you can find a good example from
https://github.com/dmlc/mxnet/blob/master/R-package/R/model.R#L472
For the documentation, my advice is to use python doc as a reference, like
https://github.com/dmlc/mxnet/blob/master/python/mxnet/symbol.py#L495-L499

Many thanks for your help. After some research, I saw a lot of potential in mxnet. I have decided to switch to it. Hopefully, you guys can keep it up, and make it one of the dominate DL packages.

Thank you for your support. We want to make mxnet one of the first choices when people want to use deep learning in R.
Right now I am closing this. Feel free to open it if necessary.


How to get real-time logs?

It would be better if the run_command_with_progress() method could return real-time logs.

The progress method returns the progress in percent, but you can get the stderr from the main class if you need it:
from tqdm import tqdm
from ffmpeg_progress_yield import FfmpegProgress

cmd = [
    "ffmpeg", "-i", "test/test.mp4", "-c:v", "libx264", "-vf", "scale=1920x1080", "-preset", "fast", "-f", "null", "/dev/null",
]

ff = FfmpegProgress(cmd)
with tqdm(total=100, position=1, desc="Test") as pbar:
    for progress in ff.run_command_with_progress():
        pbar.update(progress - pbar.n)
        print(ff.stderr) # this should be the cumulative output


Error with node 13.0.1

I have a project that packages with bytenode before deployment. Unfortunately with node 13.0.1, I'm seeing a new error:
$ bytenode app.jsc
terminate called after throwing an instance of 'std::out_of_range'
what():  vector::_M_range_check: __n (which is 0) >= this->size() (which is 0)
This is happening when creating the vm.Script object: https://github.com/OsamaAbbas/bytenode/blob/master/index.js#L91-L93

When node 13 was released I tested it out with a simple hello world example. Appareantly this is not enough.
I will look into this issue. I guess I know its cause, but if you have a minimal example that reproduce the error it'd help.

I can reproduce the error, using the express-hello-world example but only if the whole server is bundled using browserify (see this README for details).
However, the same error occurs in Node 12 too. So either this is another issue that happens in both node 12 and 13, or it is the same issue as yours. I need you to try out the same setup with node 12, so that we see if node 12 will reproduce it or not.
And still investigating to find a fix.

Please update to bytenode 1.1.2.
$ sudo npm install --global bytenode

Let me know if this version fixes your issue.

That fixed it. Thanks for the quick response!


Some problems about Time Synchronization

Hi PEIYU, WaiPang
@KwanWaiPang @cpymaple
Firstly, I would like to express my gratitude for your exceptional work on the ECMD dataset. I am interested in utilizing your dataset for my research and have some questions regarding sensor time synchronization:

In the ECMD paper, it is mentioned that the Precision Time Protocol (PTP) was employed for multi-sensor time synchronization, with the clock source being the satellite time provided by the u-blox M8T GNSS receiver. Could you please specify which sensors were involved in the PTP time synchronization process? Did the Infrared Camera, Event Camera, Industrial Camera, and Xsens also participate in this synchronization?

I noticed that the primary clock source in your setup was the u-blox M8T GNSS receiver, even though you also have the NovAtel SPAN-CPT. May I ask why the NovAtel SPAN-CPT was not used directly for satellite time synchronization?

Thank you for your time and effort in advancing this field. I look forward to your response and am eager to explore your dataset further.
Best regards,
Kaho

Hi Kaho, regarding your time sync questions,

The ROS system on the industrial PCs is synchronized using the PTP protocol. The event cameras are synced based on the master event camera. Other sensors share the same ROS timestamp with GNSS but are not involved in PTP synchronization.
NovAtel SPAN-CPT is a good choice for synchronization, as it provides PPS (Pulse Per Second) and NMEA signals. However, we are currently not using it. According to the information from u-blox, the time accuracy of the u-blox M8T can also reach nanosecond accuracy. You can find more details here

Dear Darren,
@DarrenWong
Thank you for your insightful response regarding the time synchronization process used in the ECMD dataset. I have a few follow-up questions to further understand the details:

Regarding your mention of "The ROS system on the industrial PCs is synchronized using the PTP protocol",  does this mean that the satellite time provided by the u-blox (offering PPS and NMEA signals) is aligned with the PC system time, thereby correct the ROS system Timestamp? As I understand, the ROS system time typically relies on ros::time::now(), which corresponds to the current system time of the PC. I apologize if my understanding is incorrect and would appreciate any clarification.

In your ECMD paper, it is noted that "the event cameras are synced based on the master event camera". In the dataset, does the master event camera acquire data directly using the ROS driver? Is the time of the event camera synchronized with the time of the PC or other sensors? I am aware that connecting the PC and event camera via USB might introduce some latency.

3.I find the use of the u-blox M8T for the master clock to be a very impressive solution.
I look forward to hearing from you and delving deeper into using your dataset.
Best regards,
Kaho

Dear Kaho

Yes, we sync GNSS time with the PCs.

Yes, we use the ROS driver to acquire data. The wire latencies between sensors and ROS computers are not considered in this dataset. We will consider implementing it in the future.

Cool! Hope it helps!

Best Regards,
HUANG Feng

Dear Darren,
Thank you for your great help!!!
Best Regards,
Kaho


[SCRC-407] Doxygen generation on gh-pages branch from GitHub Actions

Default GitHub pages site for this repository is now set to run from the gh-pages branch, added to the GitHub actions is now the automated process of generating new documentation whenever changes occur to master or dev. These changes should appear here.

For workflow yml, is that possible to organize doxygen , coverage, cpp-check into blocks, currently runs are interweaven. because I will use your yml as my future template :).

With your permission I am going to take these changes as non-compulsory. If I have time I will definitely look into tidying up, but right now this does not prevent the merge. Always a good idea to tidy though! :+1:

The following features have now been added:

sim_c++ which gives a report on code similarity, probably not mandatory and I think in a lot of cases not relevant to use but still.
flawfinder again not mandatory for us, but this helps with security etc.
clang-format: When pushing to dev the code will now automatically be formatted so it will not matter how people indent etc. This will lead to automated commits which have the title: Applied Code Formatting <date> being present. Initially I thought I would have to force push in the automation but it seems it will work without so there is no risk of overwriting someones work.

IMPORTANT: This branch must be rebased before merging! At the time of writing this branch was up to date with dev, if any other merge requests are added after 09:28 12 June 2020 this branch must be again rebased.


(maint) Add jruby to puppetserver bootstrap.cfg

It's been needed for a long time, but for some reason just started making builds
fail.

Test FAILed

CLA signed by all contributors.


Permissions Issue

Hello,
All of a sudden tonight I am getting the below error.  Any thoughts?
Traceback (most recent call last):
File "C:\Program Files\SABnzbd\scripts\SABPostProcess.py", line 11, in
fileConfig(os.path.join(os.path.dirname(sys.argv[0]), 'logging.ini'), defaults={'logfilename': os.path.join(os.path.dirname(sys.argv[0]), 'info.log').replace("\", "/")})
File "c:\python27\lib\logging\config.py", line 85, in fileConfig
handlers = _install_handlers(cp, formatters)
File "c:\python27\lib\logging\config.py", line 163, in install_handlers
h = klass(*args)
File "c:\python27\lib\logging\handlers.py", line 117, in init
BaseRotatingHandler.init(self, filename, mode, encoding, delay)
File "c:\python27\lib\logging\handlers.py", line 64, in init
logging.FileHandler.init(self, filename, mode, encoding, delay)
File "c:\python27\lib\logging_init.py", line 911, in init
StreamHandler.init(self, self.open())
File "c:\python27\lib\logging_init.py", line 941, in _open
stream = open(self.baseFilename, self.mode)
IOError: [Errno 13] Permission denied: 'C:\Program Files\SABnzbd\scripts\info.log'

just make info.log writeable by whichever user or group sabnzbd is running as

I've changed the permissions and it works now, but I was just curious if there was a reason it all of a sudden stopped working after working fine for quite a while with no permissions errors.

did you pull any updates? or do any thing that caused it to be overwritten? or change the permissions over the entire directory?

No, the only thing that happened is that the pc crashed about an hour before this, but no updates were made to any of those directories.

I haven't changed anything regarding permissions. I suspect this is on your end and the permissions were changed somehow
Sent from my iPhone

On May 4, 2017, at 19:19, wraith1385<EMAIL_ADDRESS>wrote:
No, the only thing that happened is that the pc crashed about an hour before this, but no updates were made to any of those directories.
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub, or mute the thread.


Replace msgpack as the main network encoding format

Closes #2881
This changes the underlying network protocol to use msgpack only for the initial handshake for backwards compatibility. Actual network messages are instead encoded using fixed-settings bincode for now.
The tests have been improved, now using the actual encoder instead of a "replication". Furthermore a potential, rare race condition in the handshake has been removed by making the sending of the handshake a background task.
Benchmarks
I've benchmarked this quickly using casper-test: https://github.com/casper-network/casper-test/blob/06db5ed0127b9e915201b683196515df55abb96a/src/bin/benchmark_network_traffic_gossiping.rs
release-1.5.0 results (run twice):
Total bytes gossiped across the network: 79420
Total bytes gossiped across the network: 81964

With the changes in this PR:
Total bytes gossiped across the network: 42838

That's roughly a 45% reduction in traffic.
Important
Note: If this merges, the resulting node will be entirely incompatible with all previous versions of 1.5.0 currently used in testnets. The underlying network protocol has changed in a manner invisible to the nodes, they will just report encoding errors when talking to older nodes.

bors r+


Wox crashes at launch "Stopped working" (Windows 10)

Since I updated to Windows 10, Wox crashes at every start :

Report.wer
WER3E05.tmp.WERInternalMetadata.xml

I never developped under Windows so tell me if I can provide aditionnal information.
I miss wox :) Thanks

Did you see any errors in the log file, which should be located under logs folder that besides Wox.exe

Here it is : http://pastebin.com/2kq9HUdX
Seems to be a UserSettingsStorage error.

@ozwin

try the solution of this issue
it is probably a permission issue, try put it on your user folder or D:


[Documentation] Push jaxtyping over torchtyping for type-checking PyTorch tensors

Hi. I was trying to use beartype as a drop-in replacement for typeguard with torchtyping.
from torch import rand
from torchtyping import TensorType, patch_typeguard
from typeguard import typechecked

patch_typeguard()

@typechecked
def func(x: TensorType["batch"],
         y: TensorType["batch"]) -> TensorType["batch"]:
    return x + y

func(rand(3), rand(1))

This raises the expected error.
TypeError: Dimension 'batch' of inconsistent size. Got both 1 and 3.

but it doesn't work. Should we manually write patch_beartype like patch_typeguard?
from torch import rand
from torchtyping import TensorType
from beartype import beartype

@beartype
def func(x: TensorType["batch"],
         y: TensorType["batch"]) -> TensorType["batch"]:
    return x + y

func(rand(3), rand(1))

@patrick-kidger: By the power invested in me from [insert macguffin], @beartype summons thee to dispense keyboard justice, infernal wisdom, and Christmas cheer! A torchtyping issue rears up like Godzilla giving birth in Tokyo Harbour. Curse you, Godzilla.
As I'm now squinting at its commit history, torchtyping kinda looks like it's quietly gone into moribund maintenance mode. This absolutely makes sense. Since JAX now predominates the hallowed halls where only Googlers tread, PyTorch is on the burned-out back burner.
Is there anything @beartype can do here? Is @beartype doing anything wrong here? I can't quite tell from the Canadian wilderness, where even the Internet pathetically crawls like a glacial snow turtle. I can tell that the torchtyping.patch_typeguard() monkey-patch frightens me. Clearly, typeguard needs a plugin API. Clearly, so does @beartype. Clearly, everyone's just gonna offload all the work onto torchtyping instead.
I see a distinct lack of __instancecheck__() shenanigans in torchtyping but an abundance of those shenanigans in jaxtyping. Is torchtyping mostly fait accompli at this point or would lightly (okay, heavily) refactoring torchtyping towards __instancecheck__() and away from patch_typeguard() be pragmatically feasible? Pragmatically is a keyword here. I'm guessing... not so much, which totally makes sense. But it is a conundrum, indeed.
I still pine for a unified tensor typing API. I pine amidst the pines. :evergreen_tree: :christmas_tree: :evergreen_tree:

Oh, boy! F_aaaaaaaaa_scinating. This is great fodder for our FAQ. Let's rename this issue.
To my future self: make better decisions than older self. Also, revise the currently bad recommendations in our PyTorch FAQ entry to use torchtyping  into actually good recommendations to just use jaxtyping for everything.
To @patrick-kidger: now that the courageous truth has finally come out, I'd :heart_eyes: to see a breakdown of the comparative trade-offs between jaxtyping and possibly similar alternatives in the same typing space not authored by you. Of course, no should use those. Against all wisdom, someone will. Are there any practical reasons (besides existing vendor lock-in) to using nptyping over jaxtyping in 2023 or does the latter mostly subsume the former now?

...loosen its dependency on JAX so that it doesn't needlessly install JAX for PyTorch users.

Maybe optional install-time extras? Like, say:
all = ['jax', 'numpy', 'tensorflow', 'torch']
jax = ['jax']
...

...I foresee this becoming annoying rapidly. :grin:

Thanks for the insights @patrick-kidger. jaxtyping works like a charm! 🙂 (with beartype, of course 👍 @leycec) It's nice that we can annotate tensors from multiple backends in the same way. Just like we do in the einops world! It would be really great if jaxtyping became a bit more backend-agnostic.

Update: as a quick hack to make things easier, the latest version (0.2.9) of jaxtyping should now no longer have JAX as a mandatory dependency.
If JAX is installed then the jaxtyping.{Array, PyTree} types will exist. If it isn't, then they won't. Either way the Float, Int etc. types will exist and should work with PyTorch tensors.
Choice of name aside, this should mean that jaxtyping is now backend-independent.

Phenomenal! Thanks so much for your dedication to good stuff, @patrick-kidger – and on a Friday night that could otherwise have been filled with back-breaking martial arts, ice skating on thin Bay Area ice, scuba diving methane sea vents off the coast of Hawaii, or playing ruthlessly competitive board games about those things.
Your productivity has shamed me into action. beartype 0.12.0: it's time to work on you.

I've just checked and it works flawlessly. Now I'm ready to confidently write 7-dim torch functions with the blessing of it. 🫢 Thanks @patrick-kidger @leycec!

Resolved by b856ffd3a. Thanks entirely to @patrick-kidger for doing the good hard work we should have done but were too shamefully lazy honestly exhausted by the @beartype 0.15.0 release cycle to do. So many bear hugs! :hugs: :bear: :hugs:


Some fixes on Bluetooth (IDFGH-8050)

A set of small fixes on bluetooth.
This is a new version of (IDFGH-7972) #9485 pull request, which was closed by mistake.

Thanks for your contribution.

Thanks for your contribution, and I see the pre-commit check failed.
Please install pre-commit as install-pre-commit saying.
Thank

Installed pre-commit and run pre-commit install --allow-missing-config.
Reverted commit that was failing and made new commit. Checks are failing again on a new commit.
There seems to be difference in line endings if I run pre-commit install --allow-missing-config from mingw environment and cmd. After running from mingw, I cannot make commit in Github desktop:
Mixed line ending................................................................................................................Failed
- hook id: mixed-line-ending
- exit code: 1

components/bt/host/bluedroid/bta/dm/bta_dm_pm.c: fixed mixed line endings

Also I ran pre-commit run --all-files on a fresh master branch and got massive amount of fixes.
BTW, what is wrong with this commit?

My colleagues reviewed the code and suggested that:
I think these 12 commits need to be "squashed" into fewer commits, for example

1. Several commits all make changes to tBTA_DM_SEARCH_PARAM or related logics can be combined.
2. The commits to check status against HCI_SUCCESS can be squashed
3. Some small commits in changing the typos are better to be combined

However, in order to keep the commits count as "valid" contribution on authors profile, I can not make any change to original PR,  can you please rebase and squash your PR into a single commit? thanks.

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you all sign our Contributor License Agreement before we can accept your contribution.3 out of 20 committers have signed the CLA.:white_check_mark: suda-morris:white_check_mark: dobairoland:white_check_mark: tgotic:x: songruo:x: esp-wzh:x: nachiketkukade:x: RoshanESP:x: hmalpani:x: ESP-Marius:x: Harshal5:x: mahavirj:x: mythbuster5:x: pacucha42:x: KonstantinKondrashov:x: o-marshmallow:x: Lindazhxy:x: rahult-github:x: murphymomo:x: sudeep-mohanty:x: 0xjakobYou have signed the CLA already but the status is still pending? Let us recheck it.

Mistake, sorry


fix wrong link

use hugo relref tag fix wrong link

LGTM

LGTM

Looks like it have not been tested, the link results in https://docs.gitea.io/zh-cn/hacking-on-gitea/zh-cn/installation/from-source

The local server results in correct link, but the docs page link results in

@tboerger that seems like a config-error for our træfik/caddy/hugo-setup (whatever we use) though 😉

Traefik and caddy don't really change something like that. Feels more like some Hugo inconsistency

Hello, is this pr need to backport v1.0 or not? as seems there is a hugo issue would cause 404 error.

@tboerger Why remove the backport/v1.0?

Please tell me if need backport to v1.0 or not? thanks.

@tboerger here is OKay. @luffyke please send a PR to v1.0. Thanks.


Added Support to hide exception attachments to be configurable from AppSettings

Hi @mgibas
I just noticed that it's not possible to disable attaching exception details from the AppSettings config file, so I added support for this. Would love to see this release sometime soon so I can optimize our error reporting :)
Cheers
Michael

LGTM :+1:


feat(offline-packages): add 'offline-packages' config option

Adds the offline-packages config option. It should be set to a path where package tarballs will be stored, and used as sources in offline mode.
Motivation
I want to able to keep all project dependencies colocated with the source code, and be able to 're-hydrate' the whole project fully offline and without any external dependencies whatsoever (like an external package cache). This approach is similar to yarn's offline mirror, which works, but still has some drawbacks:

can generate churn on yarn.lock and the mirror folder depending on how it's used
there is still an intermediate global cache involved
requires explicit --offline and --check-files flags to achieve a clean install from cache

Pointing the npm cache to a local folder is a possibility, but committing the cache contents makes for very polluted diffs, not much better than committing node_modules itself. Storing .tgz is ideal as the contents don't show up in diffs, and it also significantly reduces total archive size.
Other options
I also tried to make this work with vanilla npm, but ended up having to use npm pack which is extremely slow, and would end up overwriting either package.json or package-lock.json with file:... resolutions. It also can't seamlessly switch between online and offline mode, I could not achieve a sane setup.
pnpm is very fast, but stores both a packed.tgz and the extracted source code in it's cache folder, using more space than necessary and clogging up diffs.
The alternatives are also much more complex than cipm and more prone to breaking with future npm updates - I really like how cipm reaches out directly to npm's guts and manages to implement consistent behaviour with very little code.

This PR is more of a request for comments and feedback, not expecting it to be merged as-is. It appears to work for the largest repo I have, node_modules structure matches npm install, but needs more extensive testing (and tests!). Performance seems to be on par with yarn --offline which is great.
Thank you for this project!

Hi!
So, I've played around with this idea before, and I think it's a bigger feature that needs a bit more design work. It's worth noting that there's already a project working on this, and they have some specific npm5-related issues before they can ship support for it.
My strong preference would be to start by implementing something like this over at shrinkpack, so we have a working tool that we can poke around UX issues with without having to do that in cipm or the npm CLI, which are supposed to be much more stable about potentially breaking changes (as changing our minds about specific things would, about the design for this).
I think what you're doing is a great place to start! I'm just not sure cipm is the right place to implement this right now. I'd love it if you joined us over at https://package.community, specially the Discord, and we can probably start the process of getting together an RFC and starting to play with prototypes for this idea. I want to make sure we're solving the right problems with this, and that this is the best way to do so!
For what it's worth, enabling this was one of the things I was hoping cacache would eventually help enable!

I'm going to close this -- this feature is being worked on separately, over at the my-precious repo, and even has a nice prototype implementation. It'll be a while before it's ready for release though. npm will be able to install packages with file:-based resolved fields with the next npm release, though, so feel free to play with your own thing all you want (or help with libprecious!)


[BEAM-554] Set Gcs upload buffer size to 1M in DataflowRunner streaming mode

This PR solves OOMs when DataflowRunner streaming mode writes hundreds files in parallel.

R: @lukecwik @dpmills

I don't think this is a good idea since it impacts all hadoop GCS client users including the pipeline author.

When pipeline authors write gcs files in a ParDo, they will have the same OOM issue.
I think in most cases, streaming DataflowRunner pipeline will write small files in parallel, rather than huge files in sequential.
If pipeline authors have to write big files, they can always create their own gcs GoogleCloudStorageWriteChannel.

Added tests

Minor comments and then LGTM

PTAL

LGTM, will merge after checks run

Checkstyle failures
[ERROR] /home/jenkins/jenkins-slave/workspace/beam_PreCommit_MavenVerify/runners/google-cloud-dataflow-java/src/main/java/org/apache/beam/runners/dataflow/DataflowRunner.java:128:8: Unused import: com.google.cloud.hadoop.util.AbstractGoogleAsyncWriteChannel. [UnusedImports]
[ERROR] /home/jenkins/jenkins-slave/workspace/beam_PreCommit_MavenVerify/runners/google-cloud-dataflow-java/src/test/java/org/apache/beam/runners/dataflow/DataflowRunnerTest.java:92:8: Unused import: com.google.cloud.hadoop.util.AbstractGoogleAsyncWriteChannel. [UnusedImports]

fixed unused imports

LGTM
Once DoFn setup/teardown go out, we could migrate to using a single persistent connection across bundles.


Problems setting server

I am learning node.
i made this simple js file:
(function (port, rootPath, callback) {
express = require('express');
var server;
if (process.argv[2]) port = process.argv[2]; else port = 3333;
if (process.argv[3]) rootpath = process.argv[3]; else rootPath = '.';
if (callback == null) callback = (function () { });
server = express.createServer();
server.configure(function () {
    server.use(express.static(rootPath));
    server.set('views', rootPath);
    return server.set('view options', {
        layout: false
    });
});
server.get('/', function (req, res) {
    return res.render('index.html');
});
server.listen(parseInt(port, 10));
server.on('listening', callback);

}).call(this);

i excecute it like this:

node -p ./expressServer.js 4000 D:\Proyectos\MobileNet\build\WWW

and i am getting this error:
node.js:201
throw e; // process.nextTick error, or 'error' event on first tick
^
Error: static() root path required
at Object.static (D:\Proyectos\MobileNet\TestMobileBuilder\bin\Debug\node_modules\express\node_modules\connect\lib\m
iddleware\static.js:54:20)
at HTTPServer. (D:\Proyectos\MobileNet\TestMobileBuilder\bin\Debug\expressServer.js:24:28)
at HTTPServer.configure (D:\Proyectos\MobileNet\TestMobileBuilder\bin\Debug\node_modules\express\lib\http.js:542:61)
at Object.<anonymous> (D:\Proyectos\MobileNet\TestMobileBuilder\bin\Debug\expressServer.js:23:12)
at Object.<anonymous> (D:\Proyectos\MobileNet\TestMobileBuilder\bin\Debug\expressServer.js:38:4)
at Module._compile (module.js:441:26)
at Object..js (module.js:459:10)
at Module.load (module.js:348:31)
at Function._load (module.js:308:12)
at Array.0 (module.js:479:10)

Any ideas? I copied the server creation from Brunch.io proyect and it was running ok on Windows.

if i try this:

cd build
cd WWW
node -p ../../expressServer.js 4000

Server runs ok, but i need the first one option.

Another thing i am getting is:
GET http://localhost:4000/assets/app.js 403 (Forbidden)
in chrome, i need to add some perms to files?
Thanks.

i logged the rootpath variable and has a value. I dont know why express.static() is throwing and exception. I tried googling it but i havent got an answer.
Some parts were generated by coffee (the ones i borrowed from brunch.io). The 2 lines like: "if (process.argv[2]) port = process.argv[2]; else port = 3333;" were writen by to test the script. The are working ok, both get values from command line.

what's the value? that's the exception it will give you if you dont pass a truthy (string) https://github.com/senchalabs/connect/blob/master/lib/middleware/static.js#L53

you might want to step through with the debugger to get a better idea, but 99% sure this is a user-error, if you have new info re-open


Build error of core-image-minimal for Jetson TX2

Hi,
I am trying to build core-image-minimal for Jetson TX2. My build configuration is
Build Configuration:
BB_VERSION	=	"1.46.0"
BUILD_SYS	=	"x86_64-linux"
NATIVELSBSTRING	=	"ubuntu-18.04"
TARGET_SYS	=	"aarch64-oe4t-linux"
MACHINE	=	"jetson-tx2"
DISTRO	=	"tegrademo"
DISTRO_VERSION	=	"3.1+snapshot-20210208"
TUNE_FEATURES	=	"aarch64 armv8a crc"
TARGET_FPU	=	""
meta	=	"HEAD:6e89d668246fb37b2217aae7ae57390e793696d8"
meta-tegra
contrib	=	"HEAD:3b4df1ac05e9f96e0363630c036f5445800af435"
meta-tegra-support	=	"dunfell-l4t-r32.4.3:63f3bf90e9c40428ec6ba4b30b57a8596faf5a56"
meta-oe
meta-python
meta-networking
meta-filesystems	=	"HEAD:de37512b25c1f8c6bb6ab2b3782ac0fe01443483"
meta-tegrademo	=	"dunfell-l4t-r32.4.3:63f3bf90e9c40428ec6ba4b30b57a8596faf5a56"
meta-virtualization	=	"HEAD:92cd3467502bd27b98a76862ca6525ce425a8479"
meta-rust	=	"common-rust-native:3b783652cc9e0e0ff95fdf151eab3e178b5f1667"
meta-iotedge	=	"dunfell:6840cf2afb51b4f2c535a05d5635736652f664f7"
But I got this below error related to tegra-minimal-initramfs recipe.
The problem is that I have built the same image before with the same packages and I didn't get this error.
[2021-02-08T13:00:28.598Z] ERROR: tegra-minimal-initramfs-1.0-r0 do_image_complete: Error executing a python function in exec_python_func() autogenerated:
[2021-02-08T13:00:28.598Z]
[2021-02-08T13:00:28.598Z] The stack trace of python calls that resulted in this exception/failure was:
[2021-02-08T13:00:28.598Z] File: 'exec_python_func() autogenerated', lineno: 2, function:
[2021-02-08T13:00:28.598Z]      0001:
[2021-02-08T13:00:28.598Z]  *** 0002:sstate_report_unihash(d)
[2021-02-08T13:00:28.598Z]      0003:
[2021-02-08T13:00:28.598Z] File: '/home/jenkins/workspace/dges_yoctoazureiot_jetson_master/tegra-demo-distro/layers/meta/classes/sstate.bbclass', lineno: 844, function: sstate_report_unihash
[2021-02-08T13:00:28.598Z]      0840:    report_unihash = getattr(bb.parse.siggen, 'report_unihash', None)
[2021-02-08T13:00:28.598Z]      0841:
[2021-02-08T13:00:28.598Z]      0842:    if report_unihash:
[2021-02-08T13:00:28.598Z]      0843:        ss = sstate_state_fromvars(d)
[2021-02-08T13:00:28.598Z]  *** 0844:        report_unihash(os.getcwd(), ss['task'], d)
[2021-02-08T13:00:28.598Z]      0845:}
[2021-02-08T13:00:28.598Z]      0846:
[2021-02-08T13:00:28.598Z]      0847:#
[2021-02-08T13:00:28.598Z]      0848:# Shell function to decompress and prepare a package for installation
[2021-02-08T13:00:28.598Z] File: '/home/jenkins/workspace/dges_yoctoazureiot_jetson_master/tegra-demo-distro/repos/poky/bitbake/lib/bb/siggen.py', lineno: 555, function: report_unihash
[2021-02-08T13:00:28.598Z]      0551:
[2021-02-08T13:00:28.598Z]      0552:            if "." in self.method:
[2021-02-08T13:00:28.598Z]      0553:                (module, method) = self.method.rsplit('.', 1)
[2021-02-08T13:00:28.598Z]      0554:                locs['method'] = getattr(importlib.import_module(module), method)
[2021-02-08T13:00:28.598Z]  *** 0555:                outhash = bb.utils.better_eval('method(path, sigfile, task, d)', locs)
[2021-02-08T13:00:28.598Z]      0556:            else:
[2021-02-08T13:00:28.598Z]      0557:                outhash = bb.utils.better_eval(self.method + '(path, sigfile, task, d)', locs)
[2021-02-08T13:00:28.598Z]      0558:
[2021-02-08T13:00:28.598Z]      0559:            try:
[2021-02-08T13:00:28.598Z] File: '/home/jenkins/workspace/dges_yoctoazureiot_jetson_master/tegra-demo-distro/repos/poky/bitbake/lib/bb/utils.py', lineno: 420, function: better_eval
[2021-02-08T13:00:28.598Z]      0416:    if extraglobals:
[2021-02-08T13:00:28.598Z]      0417:        ctx = copy.copy(ctx)
[2021-02-08T13:00:28.598Z]      0418:        for g in extraglobals:
[2021-02-08T13:00:28.598Z]      0419:            ctx[g] = extraglobals[g]
[2021-02-08T13:00:28.598Z]  *** 0420:    return eval(source, ctx, locals)
[2021-02-08T13:00:28.598Z]      0421:
[2021-02-08T13:00:28.598Z]      0422:@contextmanager
[2021-02-08T13:00:28.598Z]      0423:def fileslocked(files):
[2021-02-08T13:00:28.598Z]      0424:    """Context manager for locking and unlocking file locks."""
[2021-02-08T13:00:28.598Z] File: '', lineno: 1, function:
[2021-02-08T13:00:28.598Z]   File "", line 1, in
[2021-02-08T13:00:28.598Z]
[2021-02-08T13:00:28.598Z] File: '/home/jenkins/workspace/dges_yoctoazureiot_jetson_master/tegra-demo-distro/layers/meta/lib/oe/sstatesig.py', lineno: 593, function: OEOuthashBasic
[2021-02-08T13:00:28.598Z]      0589:
[2021-02-08T13:00:28.598Z]      0590:                update_hash("\n")
[2021-02-08T13:00:28.598Z]      0591:
[2021-02-08T13:00:28.598Z]      0592:            # Process this directory and all its child files
[2021-02-08T13:00:28.598Z]  *** 0593:            process(root)
[2021-02-08T13:00:28.598Z]      0594:            for f in files:
[2021-02-08T13:00:28.598Z]      0595:                if f == 'fixmepath':
[2021-02-08T13:00:28.598Z]      0596:                    continue
[2021-02-08T13:00:28.598Z]      0597:                process(os.path.join(root, f))
[2021-02-08T13:00:28.598Z] File: '/home/jenkins/workspace/dges_yoctoazureiot_jetson_master/tegra-demo-distro/layers/meta/lib/oe/sstatesig.py', lineno: 553, function: process
[2021-02-08T13:00:28.598Z]      0549:                    add_perm(stat.S_IXOTH, 'x')
[2021-02-08T13:00:28.598Z]      0550:
[2021-02-08T13:00:28.598Z]      0551:                if include_owners:
[2021-02-08T13:00:28.598Z]      0552:                    try:
[2021-02-08T13:00:28.598Z]  *** 0553:                        update_hash(" %10s" % pwd.getpwuid(s.st_uid).pw_name)
[2021-02-08T13:00:28.598Z]      0554:                        update_hash(" %10s" % grp.getgrgid(s.st_gid).gr_name)
[2021-02-08T13:00:28.598Z]      0555:                    except KeyError:
[2021-02-08T13:00:28.598Z]      0556:                        bb.warn("KeyError in %s" % path)
[2021-02-08T13:00:28.598Z]      0557:                        raise
[2021-02-08T13:00:28.598Z] Exception: KeyError: 'getpwuid(): uid not found: 1000'
Please let me know how do we fix it

Hi,
I also have this problem when I would like to try to build Xavier-NX platform and error message like yours.
I have no idea how to solve this issue, if you could give some tips will be appreciated, thanks in advance.
============== build error message ===============
Build Configuration:
BB_VERSION           = "1.46.0"
BUILD_SYS            = "x86_64-linux"
NATIVELSBSTRING      = "universal"
TARGET_SYS           = "aarch64-poky-linux"
MACHINE              = "jetson-xavier-nx-devkit"
DISTRO               = "poky"
DISTRO_VERSION       = "3.1.5"
TUNE_FEATURES        = "aarch64 armv8a crc"
TARGET_FPU           = ""
meta-tegra           = "wip-dunfell-l4t-r32.5.0:3a410d4229bcd13ecf726ac63efa8d76d230ad27"
meta
meta-poky
meta-yocto-bsp       = "dunfell:977b7268bf4fd425cb86d4a57500350c9b829162"
Initialising tasks: 100% |####################################################################################################| Time: 0:00:01
Sstate summary: Wanted 61 Found 3 Missed 58 Current 1090 (4% match, 94% complete)
NOTE: Executing Tasks
WARNING: tegra-minimal-initramfs-1.0-r0 do_image_complete: KeyError in .
ERROR: tegra-minimal-initramfs-1.0-r0 do_image_complete: Error executing a python function in exec_python_func() autogenerated:
The stack trace of python calls that resulted in this exception/failure was:
File: 'exec_python_func() autogenerated', lineno: 2, function:
0001:
*** 0002:sstate_report_unihash(d)
0003:
File: '/mnt/uSSD/tegra-yocto/poky-dunfell/meta/classes/sstate.bbclass', lineno: 844, function: sstate_report_unihash
0840:    report_unihash = getattr(bb.parse.siggen, 'report_unihash', None)
0841:
0842:    if report_unihash:
0843:        ss = sstate_state_fromvars(d)
*** 0844:        report_unihash(os.getcwd(), ss['task'], d)
0845:}
0846:
0847:#
0848:# Shell function to decompress and prepare a package for installation
File: '/mnt/uSSD/tegra-yocto/poky-dunfell/bitbake/lib/bb/siggen.py', lineno: 555, function: report_unihash
0551:
0552:            if "." in self.method:
0553:                (module, method) = self.method.rsplit('.', 1)
0554:                locs['method'] = getattr(importlib.import_module(module), method)
*** 0555:                outhash = bb.utils.better_eval('method(path, sigfile, task, d)', locs)
0556:            else:
0557:                outhash = bb.utils.better_eval(self.method + '(path, sigfile, task, d)', locs)
0558:
0559:            try:
File: '/mnt/uSSD/tegra-yocto/poky-dunfell/bitbake/lib/bb/utils.py', lineno: 420, function: better_eval
0416:    if extraglobals:
0417:        ctx = copy.copy(ctx)
0418:        for g in extraglobals:
0419:            ctx[g] = extraglobals[g]
*** 0420:    return eval(source, ctx, locals)
0421:
0422:@contextmanager
0423:def fileslocked(files):
0424:    """Context manager for locking and unlocking file locks."""
File: '', lineno: 1, function:
File "", line 1, in
File: '/mnt/uSSD/tegra-yocto/poky-dunfell/meta/lib/oe/sstatesig.py', lineno: 593, function: OEOuthashBasic
0589:
0590:                update_hash("\n")
0591:
0592:            # Process this directory and all its child files
*** 0593:            process(root)
0594:            for f in files:
0595:                if f == 'fixmepath':
0596:                    continue
0597:                process(os.path.join(root, f))
File: '/mnt/uSSD/tegra-yocto/poky-dunfell/meta/lib/oe/sstatesig.py', lineno: 553, function: process
0549:                    add_perm(stat.S_IXOTH, 'x')
0550:
0551:                if include_owners:
0552:                    try:
*** 0553:                        update_hash(" %10s" % pwd.getpwuid(s.st_uid).pw_name)
0554:                        update_hash(" %10s" % grp.getgrgid(s.st_gid).gr_name)
0555:                    except KeyError:
0556:                        bb.warn("KeyError in %s" % path)
0557:                        raise
Exception: KeyError: 'getpwuid(): uid not found: 1000'
ERROR: Logfile of failure stored in: /mnt/uSSD/tegra-yocto/build/tmp/work/jetson_xavier_nx_devkit-poky-linux/tegra-minimal-initramfs/1.0-r0/temp/log.do_image_complete.335097
ERROR: Task (/mnt/uSSD/tegra-yocto/meta-tegra/recipes-core/images/tegra-minimal-initramfs.bb:do_image_complete) failed with exit code '1'
NOTE: Tasks Summary: Attempted 3024 tasks of which 2885 didn't need to be rerun and 1 failed.
Summary: 1 task failed:
/mnt/uSSD/tegra-yocto/meta-tegra/recipes-core/images/tegra-minimal-initramfs.bb:do_image_complete
Summary: There was 1 WARNING message shown.
Summary: There was 1 ERROR message shown, returning a non-zero exit code.
================== message end ====================

I'm not sure what's going on there, but it looks like there's some confusion over file ownership that's causing a problem.  I've seen reports of similar issues happening when trying builds in containers.  Is that what you are doing?
Was this a build from a clean workspace, or were you rebuilding in an existing workspace?  In some of the reports I've seen, cleaning the workspace (or at least doing a bitbake -c cleanall for the recipe that triggered the problem) has helped.

I'm not sure what's going on there, but it looks like there's some confusion over file ownership that's causing a problem. I've seen reports of similar issues happening when trying builds in containers. Is that what you are doing?
Was this a build from a clean workspace, or were you rebuilding in an existing workspace? In some of the reports I've seen, cleaning the workspace (or at least doing a bitbake -c cleanall for the recipe that triggered the problem) has helped.

Yes, right tried building in docker container.
We tired both with new workspace and existing workspace, getting same error. However did not try with bitbake -c cleanall.
After adding this setting TEGRA_INITRAMFS_INITRD = "0" to local.conf file, it is working fine. I am not sure with the implications of this on build.

After adding this setting TEGRA_INITRAMFS_INITRD = "0" to local.conf file, it is working fine.
OK, interesting.  That leaves the initial ramdisk unbundled from the kernel.  There must be something in the minimal-initramfs recipe that, when it's bundled into the kernel, is triggering the problem.

We tired both with new workspace and existing workspace, getting same error. However did not try with bitbake -c cleanall.
OK.  Were you reusing the sstate-cache between those builds, or using a prior build's shared state as an SSTATE_MIRROR?

When I get a chance, I'll see if I can put together a container-based build environment to run some experiments in, to see if I can reproduce.

I have the same error. I am not in a container though, I am using a native Ubuntu 18.04.
I am not a Yocto expert but my guess is that the pwd function is looking for a /etc/passwd file in one of the sysroots that doesn't have a uid 1000 instead of the hosts /etc/passwd.

Attached is the log from running
bitbake -DDD tegra-minimal-initramfs &> initramfs_error.log
initramfs_error.log

How do you create the users for the container? Did you use volume mapping?
On our host PCs, we have a buildsystem group created with gid 1500, a jenkins user created with uid and gid 150. We create matching user and group in the containers
...

That way we can access the files from both host and container, to keep the sstate and download directories between builds without too much overhead, and have an nginx instance on the host serve those directories as local mirrors.
I think for Ubuntu based distro the first uid assigned is 1000 so it's probably this type of configuration issue.

Attached is the log from running
bitbake -DDD tegra-minimal-initramfs &> initramfs_error.log
initramfs_error.log

Maybe try to print the files to see which one gives you trouble and could have non-existent group/owner
for f in files:
    print(f)

@pnewman-cti Thanks, it helps to know that it's not just container-based builds.
I'm guessing that there is some interaction between the unusual setup we have here of enabling shared state for the initramfs image (image recipes typically don't) and the new hashserv feature in OE-Core.  I disable hashserv in my builds, since it doesn't really work well for my CI environment, which would explain why I haven't seen this.

initramfs_error_after_clean.log
here is the log after running cleanall then building. Probably more useful to you.
How do you disable hashserv?

How do you disable hashserv?

Set
BB_SIGNATURE_HANDLER = "OEBasicHash"

in your build configuration (e.g. in local.conf).  For poky-derived distros, the default is to use OEEquivHash, which enables the generation of output hashes for the hash equivalence server.

How do you disable hashserv?

Set
BB_SIGNATURE_HANDLER = "OEBasicHash"

in your build configuration (e.g. in local.conf). For poky-derived distros, the default is to use OEEquivHash, which enables the generation of output hashes for the hash equivalence server.

Adding that did allow for it to build.

Turns out I already had a workaround  (7a8cf92) in place for this issue in master and gatesgarth.  I've gone ahead and back-ported it to the dunfell-based branches, and have updated the corresponding branches in tegra-demo-distro to pick up the change.
If you've been seeing this issue, try updating to latest.  It should work better.


Add toggle grayscale option

We should squash all of these commits together into one before we merge (after we're done reviewing)


Document required Transport nuget packages

Recently I found myself installing the wrong nuget package for the Azure Service Bus transport.
Would do you guys think of a link to the required nuget for that transport on every transport page? If you agree, I'll create a small PR for this soon.

They are all listed on the packages page: https://masstransit-project.com/architecture/packages.html
And in the vnext branch, many of the rewritten example code fragments I've added package links at the top, but it isn't consistent yet.
I've essentially stopped accepting PR's against develop until I merge vnext for the v7 release next week.

Then I won't make a PR at this moment, if the vnext documentation also visable somewhere? Maybe I can help improve those.

The vnext branch has the latest: https://github.com/MassTransit/MassTransit/tree/vnext/docs
It isn't published yet though, until I merge vnext into develop which may be over the weekend.

Going to call this one good: https://masstransit-project.com/usage/transports/azure-sb.html

Looks very nice!
May I also suggest a sample where you load the connection string from the config, by loading the IConfiguration from the service provider?

You mean similar to how it is done in the platform?
https://github.com/MassTransit/MassTransit-Platform/blob/master/src/MassTransit.Platform/Transports/ServiceBus/ServiceBusStartupBusFactory.cs


Responsive Navbar

Would like semantic UI to create a responsive navbar similar to bootstrap.
It is currently impossible to have the semantic UI dropdowns function correctly when collapsed in a mobile view.
Tried to use the "accordion" functionality when on mobile, but that solution does not convert well for desktop.
https://getbootstrap.com/examples/navbar-static-top/

svansoeren, Semantic UI has an outstanding "all-in-a-box" Sidebar menu (http://semantic-ui.com/modules/sidebar.html#/definition), which works great on tablets and mobiles. All you have to do is to hide navbar menu items on small screens and show a button that will trigger the sidebar menu.
However, bad thing is that you have to duplicate menu items for navbar and sidebar.

Thank you for the alternative page functionality and layout suggestion.
As well as the HTML / CSS re-structure suggestion.
However, not really interested in duplicating the HTML and design elements (makes the content more difficult to maintain).
Still interested in seeing a responsive navbar developed. (if this does get completed it would not be difficult translate the responsiveness to the "sidebar").

Well, menu element duplication is wrong IMHO. May @jlukic consider this improvement.

Check issue #157

Agreed. Let's close this and keep it on #157.

See #157.

Hi,
Since #157 comments are blocked I post here, shall others have similar issues.
For me using https://react.semantic-ui.com/collections/menu#menu-example-stackable was enough on mobile.

I made this "plugin" - Semantic UI Hamburger Menu https://github.com/natzar/SemanticUiHamburgerMenu


Bug: intellisense does not see new files.

VSCode Version: 1.18.0
OS Version: Ubuntu 16.04

Steps to Reproduce:

add new tmp.ts file to TypeScript-project;
import this new file: import { } from './' and VS Code does not see tmp.ts.

Reproduces without extensions: Yes

I can't repo this in an empty project:

Can you please provide additional repo steps or a small example project that demonstrates this problem

@mjbvz, yes, sorry. I rewrite my previous "Steps to Reproduce".

@KostyaTretyak I still can't reproduce this. What if you manually tigger suggestions by using ctrl+space after the /. Also you've disabled all extensions, right?

@mjbvz, yes, right. This bug reproduce only first open VS Code and follow "Steps to Reproduce".

In addition, after deleting files, import suggestions use deleted filenames.

This issue was moved to Microsoft/TypeScript#20023


chore: cache dropgz:v0.0.15

What type of PR is this?
cache dropgz/v0.0.15 for cilium dualstack support

What this PR does / why we need it:
Which issue(s) this PR fixes:

Fixes #
Requirements:

[ ] uses conventional commit messages

[ ] includes documentation
[ ] adds unit tests
[ ] tested upgrade from previous version

Special notes for your reviewer:
dropgz v<IP_ADDRESS> and v0.0.11 are still needed, so will leave those unchanged
Release note:
none

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 79.007%

Totals

Change from base Build<PHONE_NUMBER>:
0.0%

Covered Lines:
2243

Relevant Lines:
2839

💛  - Coveralls


[openwrt/luci] ifaces.lua - HTML template to create DynamicList custom fields

In LUCI Interfaces-LAN > DHCP Server > Advanced Settings > DHCP-Options, you have to type for example '3,<IP_ADDRESS>', then click on [+], then type '6,<IP_ADDRESS>'.
I want to do simplest GUI settings like
Alternative DNS :
Alternative Gateway :
I written the following codes
In luci/model/cbi/admin_network/ifaces.lua
dhcpopt3 = s:taboption("advanced", DynamicList, "dhcp_option", translate("Alternative Gateway"), translate(""))
dhcpopt3.template = "cbi_defrouter"
function dhcpopt3.validate(self, value)
local defrouter = self.map:formvalue(self:cbid(section) .. ".defrouter")
return "3," .. defrouter
end
In luci/view/cbi_defrouter.htm
<%+cbi/valueheader%>
<input type="text" class="cbi-input-text" onchange="cbi_d_update(this.id)"<%=attr("name", cbid .. ".defrouter") .. attr("id", cbid ..".defrouter") .. attr("value",
(self:cfgvalue(section) or ""):match("%d,(%d+.%d+.%d+.%d+)")) %> />
<%+cbi/valuefooter%>
It could not work. Unless I change the DynamicList to Value in luci/model/cbi/admin_network/ifaces.lua, then it can work and successfully save the IP into DHCP config file with DHCP option enum at the beginning, as shown below.
In /etc/config/dhcp
config dhcp 'lan'
...
option dhcp_option '3,<IP_ADDRESS>'
It's not flexible, because "option dhcp_option" limits me to setup multiple DHCP option at one interface (the correct config is
list dhcp_option '3,<IP_ADDRESS>'
list dhcp_option '6,<IP_ADDRESS>'
). What can I modify so that we can write template to create custom dynamic list field in LUCI view?
Thank you.

You cannot express such a logic in CBI / HTML templates. You need to override the .write, .remove and .cfgvalue functions to decompose and join the values as needed.
When you have multiple fields presenting (parts of) the value of a single uci option then the usual approach is to let the .write() and .remove() function of the first field handle all the logic while the functions of the other fields are no-ops that do not actually write into uci.
To see a real worl example, refer to https://github.com/openwrt/luci/blob/master/protocols/luci-proto-ppp/luasrc/model/cbi/admin_network/proto_pppoe.lua#L73 and see how keepalive_failure and keepalive_interval write into the same option keepalive which takes two space separated numbers as value.

When considering the example I linked, you need to keep in mind that you need to pass an array to the uci set() function in order to store the value as list dhcp_option instead of option dhcp_option.
Also keep in mind that the get() function can return either an array if the user already has list dhcp_option ... in his config or a string if the config contains option dhcp_option ... so within the .cfgvalue() callback you need to silently convert a string value to a one-element array if needed.

Thanks Jow for your tips, it helps me a lot. This is what I did.
-- create seperate field for user input DHCP option 3 (Router) and 6 (DNS)
	local dhcpopt6 = s:taboption("advanced", DynamicList, "dhcp_option", translate("Alternative Default DNS"), translate(""))
	dhcpopt6.datatype = "ip4addr"

	-- ip4addr datatype does not seems work in dhcpopt3
	local dhcpopt3 = s:taboption("advanced", DynamicList, "dhcp_option", translate("Alternative Default Gateway"), translate(""))
	dhcpopt3.datatype = "ip4addr"
	dhcpopt3.default = "<IP_ADDRESS>"

	--check dhcp option enum for dhcpopt3 and dhcpopt6 cfgvalue
	function dhcpopt6.cfgvalue(self, section)
		local v = m2.uci:get("dhcp", section, "dhcp_option")
		-- convert the string value to a one-element array
		local a = {}
		local op = 0
		local j = 1
		if v and #v > 0 then

			for i=1,#v,1 do
				-- discard one or more characters after the the comma
				op = v[i]:match("[^,]+")
				if op == "6" then
					-- print one or more characters after the the comma
					a[j] = v[i]:match("[,](.*)")
					j = j + 1

				end
			end

			return a
		end
	end

	function dhcpopt3.cfgvalue(self, section)
		local v = m2.uci:get("dhcp", section, "dhcp_option")
		local a = {}
		local op = 0
		if v and #v > 0 then

			for i=1,#v,1 do
				op = v[i]:match("[^,]+")
				if op == "3" then
					a[1] = v[i]:match("[,](.*)")
				end
			end

			return a
		end
	end

I wrote .cfgvalue() function to read IP from dhcp_option, and sort them out to respectively fields based on their dhcp option enum.

However I'm lost in writing .write() function because either
m2.uci:get("dhcp", section, "dhcp_option") or 0 OR
dhcp_option:formvalue(section) or 0
return only IP address, without the dhcp option enum at the beginning, so I cannot differentiate whether the IP address is belong to dhcpopt3 or dhcpopt6.
I tried writing separate dhcpopt6.write() and dhcpopt3.write() but it don't work as well.
How can I retrieve value from uci files in lua? Thank you.


PPO gets stuck in custom environment

Hello and thank you for the implementation it really helps.  I have an environment that is sparse and only receives a reward on task completion.  I followed your code and implemented a PPO algorithm that uses a simple actor-critic network.  I am attaching my code for the network and PPO here.
ActorCritic
class ActorCritic(nn.Module):

    def __init__(self):
        super(ActorCritic, self).__init__()

        self.fc1 = nn.Linear(33, 128)
        self.fc2 = nn.Linear(128, 128)

        self.critic = nn.Linear(128, 1)
        self.actor = nn.Linear(128, 3)
        self.apply(init_weights)

    def forward(self, x):
        x = torch.tanh(self.fc1(x))
        x = torch.tanh(self.fc2(x))

        return self.critic(x), F.softmax(self.actor(x), dim=-1)

PPO
class PPO():

    def __init__(
        self,
        env,
        policy,
        lr,
        gamma,
        betas,
        gae_lambda,
        eps_clip,
        entropy_coef,
        value_coef,
        max_grad_norm,
        timesteps_per_batch,
        n_updates_per_itr,
        summary_writer,
        norm_obs = True):

        self.policy = policy
        self.env = env
        self.lr = lr
        self.gamma = gamma
        self.betas = betas
        self.gae_lambda = gae_lambda
        self.eps_clip = eps_clip
        self.entropy_coef = entropy_coef
        self.value_coef = value_coef
        self.max_grad_norm = max_grad_norm
        self.timesteps_per_batch = timesteps_per_batch
        self.n_updates_per_itr = n_updates_per_itr
        self.summary_writer = summary_writer
        self.norm_obs = norm_obs
        self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
        self.total_updates = 0

        self.optimizer = torch.optim.Adam(self.policy.parameters(), lr=self.lr, betas=self.betas)

    def learn(self, total_timesteps=1000000, callback=None):

        timesteps = 0
        while timesteps < total_timesteps:
            batch_obs, batch_actions, batch_log_probs, batch_rtgs, batch_advantages, batch_lens = self.rollout()

            timesteps += np.sum(batch_lens)

            advantage_k = (batch_advantages - batch_advantages.mean()) / (batch_advantages.std() + 1e-10)

            for i in range(self.n_updates_per_itr):
                state_values, action_probs = self.policy(batch_obs)
                state_values = state_values.squeeze()

                dist = Categorical(action_probs)
                curr_log_probs = dist.log_prob(batch_actions)

                ratios = torch.exp(curr_log_probs - batch_log_probs)

                surr1 = ratios * advantage_k
                surr2 = torch.clamp(ratios, 1 - self.eps_clip, 1 + self.eps_clip) * advantage_k

                policy_loss = (-torch.min(surr1, surr2)).mean()
                value_loss = F.mse_loss(state_values, batch_rtgs)
                total_loss = policy_loss + self.value_coef * value_loss
                self.optimizer.zero_grad()
                total_loss.backward()
                self.optimizer.step()

                self.total_updates += 1
                self.summary_writer.add_scalar("policy_loss", policy_loss, self.total_updates)
                self.summary_writer.add_scalar("value_loss", value_loss, self.total_updates)
                self.summary_writer.add_scalar("total_loss", total_loss, self.total_updates)

            if callback:
                callback.eval_policy(self.policy, self.summary_writer, self.norm_obs)

    def rollout(self):
        batch_obs = []
        batch_acts = []
        batch_state_values = []
        batch_log_probs = []
        batch_rewards = []
        batch_rtgs = []
        batch_lens = []
        batch_advantages = []
        batch_terminals = []

        timesteps_collected = 0
        while timesteps_collected < self.timesteps_per_batch:
            eps_rewards = []
            eps_state_values = []
            eps_terminals = []
            obs = self.env.reset()

            done = False
            eps_timesteps = 0
            for _ in range(50):
                timesteps_collected += 1
                if self.norm_obs:
                    obs = (obs - obs.mean()) / (obs.std() - 1e-10)
                batch_obs.append(obs)

                state_value, action_probs = self.policy(torch.from_numpy(obs).type(torch.float).to(self.device))

                dist = Categorical(action_probs)
                action = dist.sample()
                act_log_prob = dist.log_prob(action)

                obs, reward, done, _ = self.env.step(action.cpu().detach().item())

                eps_rewards.append(reward)
                eps_state_values.append(state_value.squeeze().cpu().detach().item())
                eps_terminals.append(0 if done else 1)

                batch_acts.append(action.cpu().detach().item())
                batch_log_probs.append(act_log_prob.cpu().detach().item())

                eps_timesteps += 1
                if done:
                    break
            batch_lens.append(eps_timesteps)
            batch_rewards.append(eps_rewards)
            batch_state_values.append(eps_state_values)
            batch_terminals.append(eps_terminals)

        batch_obs = torch.tensor(batch_obs, dtype=torch.float).to(self.device)
        batch_acts = torch.tensor(batch_acts, dtype=torch.float).to(self.device)
        batch_log_probs = torch.tensor(batch_log_probs, dtype=torch.float).flatten().to(self.device)

        for eps_rewards, eps_state_values, eps_terminals in zip(reversed(batch_rewards), reversed(batch_state_values), reversed(batch_terminals)):
            discounted_reward = 0
            gae = 0
            next_state_value = 0
            next_terminal = 0
            for reward, state_value, terminal in zip(reversed(eps_rewards), reversed(eps_state_values), reversed(eps_terminals)):
                discounted_reward = reward + self.gamma * discounted_reward
                delta = reward + self.gamma * next_state_value * next_terminal - state_value
                gae = delta + self.gamma * self.gae_lambda * next_terminal * gae
                batch_rtgs.insert(0, discounted_reward)
                batch_advantages.insert(0, gae)
                next_state_value = state_value
                next_terminal = terminal

        batch_rtgs = torch.tensor(batch_rtgs, dtype=torch.float).to(self.device)
        batch_advantages = torch.tensor(batch_advantages, dtype=torch.float).to(self.device)
        return batch_obs, batch_acts, batch_log_probs, batch_rtgs, batch_advantages, batch_lens

I am using the Generalised Advantage Estimate in my case but even when using the simpler advantage function,R-V(s) my implementation still gets stuck and will always choose the same action when I am evaluating.  This is how I evaluate the policy in a deterministic way. I am not sampling from a categorical distribution.
_, action_probs = policy(torch.from_numpy(obs).type(torch.float).to(device))
action = torch.argmax(action_probs).item()

Can you provide any pointers as to where the problem might be?  I have used stablebaselines3 with the same environment implementation however because I want to have more control over the model I am using I opted for a custom implementation.  I can't seem to figure out where the problem might be however.

Let me add that in stablebaselines3 I am able to complete the task.  Success is increasing and episode length is decreasing which are both an indication of the model learning.

Let me add that in stablebaselines3 I am able to complete the task.  Success is increasing and episode length is decreasing which are both an indication of the model learning.

Hi Nikolas, thanks for using my implementation! I want to test your code locally (also because it's hard to tell what's wrong from just looking at it), but want to ask a few questions:

What are your imports for each file?
Where is init_weights in self.apply(init_weights) defined?
What values do you input to PPO constructor?

Will probably ask more along the way, but just want these clarifications for now.

Hi Nikolas, thanks for using my implementation! I want to test your code locally (also because it's hard to tell what's wrong from just looking at it), but want to ask a few questions:

What are your imports for each file?
Where is init_weights in self.apply(init_weights) defined?
What values do you input to PPO constructor?

Will probably ask more along the way, but just want these clarifications for now.

Thank you for your answer Eric! To give you more information I have a custom gym environment in using pybullet for a pick and place task.  The action space is discrete that denotes approach and grasp an object and finally move it to a target location so 0, 1, 2 respectively.  The actual robot movements are hardcoded.

The import for each file are the regular imports torch, numpy etc. I am not sure why you are asking this so until you get back this is my answer!
It is defined in a file where the models used for the policy are defined and that initialises the weights of the policy.

def init_weights(m):
    class_name = m.__class__.__name__
    if class_name.find("Linear") != -1:
        torch.nn.init.xavier_normal_(m.weight)

The values are the environment on which to train the policy, the policy network, the learning rate (3e-4), betas passed to Adam optimizer (0.9, 0.999), the GAE lambda (0.95), clip range for the loss (0.2), the entropy coefficient (0.01) if I am correct you don't use this and it is easy to remove it for my case, the value loss coefficient (0.5), the max grad norm (0.5), the number of timsteps per update (2000) and the number of updates of the policy (5).  Finally I pass in the tensorboard summary writer from Pytorch.

Is my implementation of PPO with GAE correct? I struggle to get a handle of how to manipulate all the data structures.  I can try to run the code without GAE and simply use the advantage to see the effect if any.

Thank you for your answer Eric! To give you more information I have a custom gym environment in using pybullet for a pick and place task.  The action space is discrete that denotes approach and grasp an object and finally move it to a target location so 0, 1, 2 respectively.  The actual robot movements are hardcoded.

The import for each file are the regular imports torch, numpy etc. I am not sure why you are asking this so until you get back this is my answer!
It is defined in a file where the models used for the policy are defined and that initialises the weights of the policy.

def init_weights(m):
    class_name = m.__class__.__name__
    if class_name.find("Linear") != -1:
        torch.nn.init.xavier_normal_(m.weight)

The values are the environment on which to train the policy, the policy network, the learning rate (3e-4), betas passed to Adam optimizer (0.9, 0.999), the GAE lambda (0.95), clip range for the loss (0.2), the entropy coefficient (0.01) if I am correct you don't use this and it is easy to remove it for my case, the value loss coefficient (0.5), the max grad norm (0.5), the number of timsteps per update (2000) and the number of updates of the policy (5).  Finally I pass in the tensorboard summary writer from Pytorch.

Is my implementation of PPO with GAE correct? I struggle to get a handle of how to manipulate all the data structures.  I can try to run the code without GAE and simply use the advantage to see the effect if any.

@ericyangyu I remove the GAE implementation from the loss function and the implementation works. So it seems my GAE implementation had errors, at least that is my assumption.  It seems to work well like this anyway!

@ericyangyu I remove the GAE implementation from the loss function and the implementation works. So it seems my GAE implementation had errors, at least that is my assumption.  It seems to work well like this anyway!

This is great news Nikolas! Glad you were able to figure out your issue :) Apologies for the previous post, I meant to remove question 1 since question 2 was supposed to be the replacement. I'm going to go ahead and close this issue soon if there are no further issues.

This is great news Nikolas! Glad you were able to figure out your issue :) Apologies for the previous post, I meant to remove question 1 since question 2 was supposed to be the replacement. I'm going to go ahead and close this issue soon if there are no further issues.

Thank you for your help!  Yes close the issue there are no further issues!

Thank you for your help!  Yes close the issue there are no further issues!


remove support of smoke test on python 2.7

reference: smoke tests failed on python 2.7 due to unicode support error,   since python 2.7 will not be supported in next release, it's safe to remove. cc: @vincentqb

Since current python 2.7 smoke tests are failing, merge this now will give us better signal. Discussed with @vincentqb , will merge it now


[FEA]: Move to the CUDA Base container + Morpheus conda install

Is this a new feature, an improvement, or a change to existing functionality?
New Feature
How would you describe the priority of this feature request
Significant improvement
Please provide a clear description of problem this feature solves
Right now, nv-ingest is built atop the Morpheus container. Not all functionality and features found within that container are necessary, and we can reduce container size and dependency maintenance by using the minimal cuda container and installing only what we need.
Describe the feature, and optionally a solution or implementation and any alternatives
We will need to update the dockerfile and identify what dependencies we do need; and then manage installation through conda/pip as necessary.
Additional context
No response

It looks like Morpheus uses the 12.1 base container, but since we recommend driver 535 which aligns with 12.2, let's use the 12.2.2 base container as a starting point.


Reorganize C

This splits the Cython code from the C code, and breaks up _pywt.
I'd still like to make some changes, but if this builds and passes the tests it may as well go in.
Also can somebody familiar with numpy distutils chime in whether I've done the right thing with pywt/setup.py - adding _extensions as a subpackage to get the __init__.py included?

There is now an API change in the exception raised by converting invalid values to a Mode. _try_mode was originally added to avoid this, but there was no other reason than matching exactly the old API.

@rgommers I've added a setup.py, does this look right now?

@rgommers I've added a setup.py, does this look right now?

Looks good to me now.

Great. I'll rebase once v0.4.0 is out, but otherwise this is good to go I think.

Re-basing onto 0.4 is quite difficult because a lot of code has moved. I'm re-applying this manually, will be a new PR.


Unable to catch bad requests

Version
2.0.1
What happened
We would like to be able to catch and log exceptions such as bad requests. It looks like the bad request 400 status code is returned by the runtime. Can expressly throw an error that we can catch for these requests? We are using custom error middleware and they are not catching 400s.
A bad request to an expressly service can be recreated with:
curl -svo /dev/null  "http://<IP_ADDRESS>:PORT/<"

Hi @aivong3,
This looks like a runtime issue, rather than an expressly issue.
Taking the following Compute application, which should return OK (HTTP 200) on any route, and running curl -svo /dev/null  "http://<IP_ADDRESS>:7676/<", produces the same 400 Bad Request response:
/// <reference types="@fastly/js-compute" />

addEventListener("fetch", (event) => event.respondWith(handleRequest(event)));

async function handleRequest(event) {
  console.log(`Request received in Compute: ${event.request.method} ${event.request.url}`)
  return new Response("OK", { status: 200 });
}

I am therefore redirecting this issue to the runtime team – CC @JakeChampion
I suspect it's something to do with the < in particular.
Running the following:
curl -svo /dev/null  "http://<IP_ADDRESS>:7676/not-a-route"
curl -svo /dev/null  "http://quickly-sure-caribou.edgecompute.app/not-a-route"

In expressly:
import { Router } from "@fastly/expressly";

const router = new Router();

router.use((req, res) => {
  console.log(`Request received: ${req.method} ${req.url}`);
});

router.get("/", async (req, res) => {
  return res.send("Hello world!");
});

router.use((err, req, res) => {
  console.error(err);
  res.withStatus(500).send(`Uh-oh! Something went wrong: ${err.message}`);
});

router.listen();```

Results in the appropriate logs and 500 error, as expected.

Hi @doramatadora,
Thanks for taking a look! It would be nice to have the flexibility to handle these bad requests in a custom way like we can for the other errors. Will see if this is possible with the runtime team

Hi @aivong3, I'll close this issue now, with some additional context:

the behaviour is limited to non-RFC3986 compliant paths
the underlying issue stems from the httparse library upstream (via hyper, in our Compute host): https://github.com/seanmonstar/httparse/issues/146
because of the potential security implications, we'd first need to carefully define what additional syntax we'd like to accept; preferably there would be a basis in a spec, at the very least a modification to the ABNF of a spec that limits the scope of the change.


included 7.7.0

The lint-markdown check is failing due to trying to fetch a circleCI link that is down due to their resources being down. I would prefer to remove this markdown check altogether as our deployment shouldn't rely on outside links working. This can be ignored for now.


Add new interfaces to API docs

Could we also keep this alphabetical within section? Is there a way to automate this so we don't have to remember to add them to the docs every time?

Alphabetized the ophys section
automodule alphabetized contents automatically, but then we can't control the section titles as nicely (which is why we apply it to each format as a sub-module)


Update display UI and add syntax highlighting

Updated the display UI within the id folder: Describes the UI changes made in the specific folder.
Integrated svelte-highlight library to enable automatic syntax highlighting: Highlights the addition of the new library for syntax highlighting.

Update display UI and add auto syntax highlighting

i pushed in the wrong repo


Add support for invoice recognition API's

Add implementation efforts for supporting invoice recognition api's formrecognizer
Invoice swagger 2.1-preview.3 : https://github.com/Azure/azure-rest-api-specs/pull/10805/files

https://github.com/Azure/azure-sdk-for-java/pull/17167


Structure tool to work as a node module

Ultimate goal is to install this tool as Node/bower module. Restructure where certain tasks point so that the "config.json" file is in the directory above the Dragoman tool.  In order to avoid conflicts, the file should be renamed to dragoman.json. In order to test the restructure, you may want to clone the tool within an empty folder, or a blank seed app (two levels deep to simulate "node_modules/Dragoman" structure) and place dragoman.json (config) file at the root directory. Please be sure to submit pull request to 'development'  branch

This is a show stopper for me. I'd like to work dragoman into an existing project without doing major refactoring of the existing code.


Add photo album download support

DO NOT REMOVE OR SKIP THE ISSUE TEMPLATE

[X] I understand that I will be blocked if I intentionally remove or skip any mandatory* field

Checklist

[X] I'm requesting a feature unrelated to a specific site
[X] I've looked through the README
[X] I've verified that I'm running yt-dlp version 2023.10.13 (update instructions) or later (specify commit)
[X] I've searched known issues and the bugtracker for similar issues including closed ones. DO NOT post duplicates
[X] I've read the guidelines for opening an issue

Provide a description that is worded well enough to be understood
With the addition of shorts and photo album to major social networking sites, most sites now supports posting both shorts (e.g. instagram reels) and album (e.g. tiktok album) however the support to download photo album seems to be spotty at best. For example, downloading tiktok album doesn't seem to work or it only downloads the first image and the music attached.
Please add full support to fully download photo album from major social network sites (eg. tiktok & instagram)
Thank you.
Provide verbose output that clearly demonstrates the problem

[ ] Run your yt-dlp command with -vU flag added (yt-dlp -vU <your command line>)
[ ] If using API, add 'verbose': True to YoutubeDL params instead
[ ] Copy the WHOLE output (starting with [debug] Command-line config) and insert it below

Complete Verbose Output
No response

Downloading photos is out-of-scope
Duplicate of #6168, #6217
Look into gallery-dl


♻ Check manual credentials in path.fs, actually reuse anon

subj

@falexwolf is hosted init broken again?

Something seems off, yes. I haven't debugged it yet.

It started to appear all of a sudden, I need to check this.

It seems to be on the side of hub. Also the same test on build / prod-staging (staging) passes.

Yes, so, this is the reason for why hosted storage was broken: https://laminlabs.slack.com/archives/C04TMJPNCBS/p1707171896355059


xlab not being rendered

I love this and I'm working on wrapping it as an htmlwidget for R called explodingboxplotR.  As I was testing, I noticed that xlab does not get drawn in line.  I assume this is an oversight, but didn't know if it was intentional.  Happy to submit a pull if you would like.
Thanks again for this!

Hi!
xlab was missing indeed. It's fixed now.
Thanks for the htmlwidget it's cool.

works great!  thanks.


LibK causing a nil value

So I don't know how this is coming up, but apparently I keep getting this error. Sorry for not giving enough details, just curious if I need glib or if it is a config issue.
addons/libk/lua/libk/3rdparty/glib/loader/loader.lua:321: attempt to index a nil value
The line that it is showing that is nil would be:
if not GetConVar ("sv_allowcslua"):GetBool () then return true end

Can't reproduce this, I have updated GLib in the repo which might have fixed the issue.


generics: a type declarations inside generic functions in some cases is not reported in the error report

What version of Go are you using (go version)?

$ go version
go version devel go1.18-59122f85bd Thu Jan 20 16:31:11 2022 +0000 linux/amd64

Does this issue reproduce with the latest release?
What operating system and processor architecture are you using (go env)?
go env Output
$ go env
GO111MODULE="on"
GOARCH="amd64"
GOBIN="/home/manlio/.local/bin"
GOCACHE="/home/manlio/.cache/go-build"
GOENV="/home/manlio/.config/go/env"
GOEXE=""
GOEXPERIMENT=""
GOFLAGS=""
GOHOSTARCH="amd64"
GOHOSTOS="linux"
GOINSECURE="*.local"
GOMODCACHE="/home/manlio/.local/lib/go/pkg/mod"
GONOPROXY=""
GONOSUMDB="*.local"
GOOS="linux"
GOPATH="/home/manlio/.local/lib/go:/home/manlio/src/go"
GOPRIVATE=""
GOPROXY="https://proxy.golang.org,direct"
GOROOT="/home/manlio/sdk/gotip"
GOSUMDB="sum.golang.org"
GOTMPDIR="/tmp/gotmp"
GOTOOLDIR="/home/manlio/sdk/gotip/pkg/tool/linux_amd64"
GOVCS=""
GOVERSION="devel go1.18-59122f85bd Thu Jan 20 16:31:11 2022 +0000"
GCCGO="gccgo"
GOAMD64="v1"
AR="ar"
CC="gcc"
CXX="g++"
CGO_ENABLED="1"
GOMOD="/home/manlio/src/go/src/test.localhost/type-params/proposal/go.mod"
GOWORK=""
CGO_CFLAGS="-g -O2"
CGO_CPPFLAGS=""
CGO_CXXFLAGS="-g -O2"
CGO_FFLAGS="-g -O2"
CGO_LDFLAGS="-g -O2"
PKG_CONFIG="pkg-config"
GOGCCFLAGS="-fPIC -m64 -pthread -fmessage-length=0 -fdebug-prefix-map=/tmp/gotmp/go-build1471284302=/tmp/go-build -gno-record-gcc-switches"
GOROOT/bin/go version: go version devel go1.18-59122f85bd Thu Jan 20 16:31:11 2022 +0000 linux/amd64
GOROOT/bin/go tool compile -V: compile version devel go1.18-59122f85bd Thu Jan 20 16:31:11 2022 +0000
uname -sr: Linux 5.15.13-arch1-1
/usr/lib/libc.so.6: GNU C Library (GNU libc) release release version 2.33.
gdb --version: GNU gdb (GDB) 11.1

What did you do?
I have a source file with code that should compile according to the Type Parameter Proposal but is invalid in go1.18:
https://gotipplay.golang.org/p/A4_vnuyiy_H
It contains several errors.
What did you expect to see?
The compiler to report the error
type declarations inside generic functions are not currently supported.
What did you see instead?
./prog.go:23:9: p.x undefined (type T has no field or method x)
./prog.go:25:4: p.x undefined (type T has no field or method x)
./prog.go:36:23: cannot use generic type Iterable[T any] without instantiation
./prog.go:74:35: cannot use a type parameter as RHS in type declaration

The compiler reports the error in the S.Build() method only when removing all the unrelated invalid code.

The error "type declarations inside generic functions are not currently supported" is produced at a later phase in the compiler than those other errors. The compiler exits before that later phase when those other errors happen.
It would be nice to produce them all at one go, but I don't think it is necessary. Lots of non-generic errors have that property currently. For instance, this program:
package main

func f() {
	var x int
}

produces a declared but not used error. The following program also has that error, but the compiler exits much earlier and never gets to the phase that produces it.
package main

zzz

func f() {
	var x int
}

Closing because the current behavior is OK and there is a lot of other stuff to do first.  We can take this up again at some later date if it really seems worthwhile.


tests/kernel/mem_protect/syscall crashes on freedom_k64f, sam_e70_xplained and nrf52_pca10040

Execution log:
***** Booting Zephyr OS zephyr-v1.13.0-1017-gc0a6801 (delayed boot 1000ms) *****
Running test suite syscalls
===================================================================
starting test - test_string_nlen
***** BUS FAULT *****
  Precise data bus error
  BFAR Address: 0xfffffff0
PASS - test_string_nlen
===================================================================
starting test - test_string_nlen
***** BUS FAULT *****
  Stacking error
  NXP MPU error, port 3
    Mode: Supervisor, Data Address: 0x20001a10
    Type: Write, Master: 0, Regions: 0x8200
***** Hardware exception *****
Current thread ID = 0x20001bc4
Faulting instruction address = 0xaac0460
Fatal fault in thread 0x20001bc4! Aborting.

Reverting this
commit 3fb6ea210a0742f1c223c96d6c7cfb937bd873aa
Author: Ioannis Glaropoulos<EMAIL_ADDRESS>Date:   Tue Oct 9 23:05:13 2018 +0200

    arch: arm: re-program MPU stack guard upon userspace enter

    Before entering userspace, the MPU stack guard is
    configured to guard the default (i.e. afterwards, the "user")
    thread stack, as the privileged stack has not yet been set. Upon
    entering userspace the MPU stack guard needs to be re-programmed
    to the privileged stack, otherwise, there is a risk that the
    first system call might be serviced without privileged stack
    protection, if it occurs before any context-switch. This commit
    fixes this issue, by calling configure_mpu_stack_guard(..) upon
    userspace entering.

    Signed-off-by: Ioannis Glaropoulos<EMAIL_ADDRESS>
and the test passed on frdm_k64f and nrf52_pca10040.

The test passed on nrf52_pca10040 after increasing PRIVILEGED_STACK_SIZE to 512.

I think this was a problem of not sufficient size for supervisor threads.
Anyways, we can close this after we merge #12817; the tests are passing on both frdm_k64f, and nrf52_pca10040. (may be already passing now, but we can wait a bit)


DBZ-581 Improve error handling for replicators

https://issues.jboss.org/browse/DBZ-581

@gunnarmorling Fixed and rebased to master

Rebased and applied. Thanks, @jpechane!


chore: update base image version to 6OOB

What type of PR is this?
/kind feature

What this PR does / why we need it:
Update base image version to 6OOB.
Which issue(s) this PR fixes:

Fixes #
Requirements:

[x] uses conventional commit messages

[ ] includes documentation
[ ] adds unit tests
[ ] tested upgrade from previous version

Special notes for your reviewer:
Release note:
none

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall First build on junjiezhang/test-release-with-2023-6oob at 61.537%

Totals

Change from base Build<PHONE_NUMBER>:
61.5%

Covered Lines:
2563

Relevant Lines:
4165

💛  - Coveralls


[Usage]: speculative model

How would you like to use vllm
I am curious about the speculative model support in VLLM. I could not find much about speculation in docs, except the following flags:
--speculative-model
The name of the draft model to be used in speculative decoding.
--num-speculative-tokens
The number of speculative tokens to sample from the draft model in speculative decoding.
I am curious if this is supported now. And possibly how to use. (If possible, prompt based decoding like in tranformers)
thanks

Thanks for the interest! We are merging the last speculative decoding correctness PR. After that, those two flags can be used and should be correct. That PR also contains tests that check speculative decoding correctness, feel free to check it out. But we will update the doc soon as well, stay tuned.

+1, but note that performance isn't good yet, we're still optimizing it

@cadedaniel First of all, thank you for your work. I'm curious about one thing. I've tested speculative decoding(SD) to compare latency using only target model VS SD. All variable are same except one thing that number of request per second. The more number of request per second , the worse latency when using SD than using only target model. When I set test data with long input or max output token is worse on SD. I guess too many queue make the SD worse.. of course many queue make latency worse. But the ratio of deterioration is bigger on SD. Could you guess what is the key point of this?

@cadedaniel First of all, thank you for your work. I'm curious about one thing. I've tested speculative decoding(SD) to compare latency using only target model VS SD. All variable are same except one thing that number of request per second. The more number of request per second , the worse latency when using SD than using only target model. When I set test data with long input or max output token is worse on SD. I guess too many queue make the SD worse.. of course many queue make latency worse. But the ratio of deterioration is bigger on SD. Could you guess what is the key point of this?

Thanks for asking! Yes, this is expected. Intuitively, speculative decoding trades extra compute for reduced latency. When system has low load (low request rate), you can use spare FLOPs for speculative decoding. But when the system is already compute bound, it's hard to see any benefits of speculative decoding. Speculative decoding can even hurt the performance because it wastes some compute for wrong tokens.
After vanilla speculative decoding, we will also open source policies/algorithms to automatically adjust and turn off speculative decoding. This is based on a recent research from the team. Please stay tuned!

thanks for your nice work! looking forward to this.

But when the system is already compute bound, it's hard to see any benefits of speculative decoding. Speculative decoding can even hurt the performance because it wastes some compute for wrong tokens.

Thanks for your reply! I have one question based on your reply. Above sentence mean that when the system is compute bound with using speculative decoding, it make higher probability to emit wrong token in draft-model, and also cause more time to verify in target-model. right? Why compute-bound make draft-model emit wrong token? please correct me if i misunderstood. Thank you. @LiuXiaoxuanPKU

Sorry for the confusion here. The probability to emit wrong token will not change based on the system load. It only depends on the draft model, target model, and dataset. Once those factors are fixed, the token acceptance rate is the same. But the 'cost' to emit wrong tokens is different based on the system load. When the request rate is low, you have some free compute, so you can use those compute to do speculative decoding. If you make a mistake, it's fine because those compute is free anyways. However, when the request rate is high, the compute you use for speculative decoding is not free anymore, if you emit a wrong token, it's wasting some compute. The compute can otherwise be used to serve other requests. Does it make a bit more sense?

@LiuXiaoxuanPKU Thank you for your kind explanation! I obviously understand it. I hope to see your contribution on speculative decoding.

I have seen support has been added in V4.1 and am testing the code with:
I am starting the server with the following code:
python -m vllm.entrypoints.openai.api_server
--model meta-llama/Llama-2-7b-chat-hf
--speculative-model JackFram/llama-68m
--num-speculative-tokens 5
--use-v2-block-manager
--num-lookahead-slots 5
But when i request the endpoint, I am getting the following error on server side:
TypeError: SpecDecodeWorker.execute_model() missing 1 required positional argument: 'num_lookahead_slots'

Can anyone please help me with this?

By the way I am able to run using speculation model using LLM class. I was wondering if the openai.api_server also supports it:
from vllm import LLM, SamplingParams
prompts = [
"Hello, my name is",
"The president of the United States is",
"The capital of France is",
"The future of AI is",
]
sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
MODEL_NAME="facebook/opt-125m"
MODEL_NAME="meta-llama/Llama-2-7b-chat-hf"
llm = LLM(model=MODEL_NAME,
speculative_model="JackFram/llama-68m",
num_speculative_tokens=5,
use_v2_block_manager=True)
outputs = llm.generate(prompts, sampling_params)
Print the outputs.
for output in outputs:
prompt = output.prompt
generated_text = output.outputs[0].text
print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")


Can this fix the 'Leave guild' bug

https://www.reddit.com/r/Palworld/comments/19cgxol/important_multiplayer_bug_stuck_loading_screen/
Reports a bug, where someone leaving the guild while another player is offline, will cause that player to be stuck infinitely loading.
I'm about to do some investigation into what changes when this happens, but it's my gut feeling that the guild guid is probably changing out and being recreated, leaving offline players stranded.

This has been patched, at least to my knowledge, in the latest update. Tested on a dedicated server, people leaving guild with multiple people coming and going.

It doesn’t fix the guild issues. Guilds just don’t work properly and cause issues transferring.

I don't think this script fixes it, but you can find a workaround at https://www.reddit.com/r/Palworld/comments/19f71p7/guild_leave_bug_fix_for_dedicated_servers/


SSL Certificates in truststores

I am looking for guidance around SSL certificates for talking to Splunk for an app (data input) implemented using your Java SDK. Currently, the Script gets access to "server_host", "session_key" which are great because they allow the app to know how talk to Splunk and be authorized to do things, EXCEPT there's no truststore that could be used to make sure this communication can be done securely.
It might be that I'm misunderstanding something, so I would appreciate some context around this:

Is server_host ALWAYS guaranteed to be "localhost" or loopback address?
If not, how is my application supposed to figure out which certificate to trust? If I want to deploy to splunk marketplace, I cannot really ship a trust store, because wherever my app is installed is going to have a different certificate to trust.
As I understand it, the current sdk implementation would probably load the truststore using the standard "javax.net.ssl.trustStore" property; who is supposed to set that? Should I tell my users to extract the certificate from their splunk server and add it to my truststore somehow? This feels like an unnecessary extra step. Can I somehow find out the location of the certificate on disk and load it from there?

My gut feeling is that along with "server_host" etc. variables, the app should be given the certificate it should trust, but I'm not sure if that fits your deployment model.
Any help would be appreciated, I couldn't find any guidance in available documentation.

Hi @jkozlowski , we are looking at couple of approaches for SSL security through SDK using self signed or Splunk generated SSL certificates. We would like to hear from you as well, if you have any suggestions for the same.

Another question: the value of server_uri passed to a modular input from my observation (from deploying a splunk docker container locally) is always something like https://<IP_ADDRESS>:<port>; whereas server_host contains the actual hostname, that I presume the certificate presented by splunkd will be signed for. I think that means I should splice the hostname into the uri to make sure that certificate checking works?


FancyZones improved opacity controls

Description of the new feature / enhancement
Replace the zone opacity slider with a slider for each of the colours, and add a toggle to only render the selected state colour once per pixel
Scenario when this would be used?
This could be used to make the selected zone be even more obvious than inactive zones, and to improve visiblity to programs behind multiple zones
Supporting information
I use a layout with a lot of overlapping zones, and I'd like to be able to see the background windows more easily while simultaneously being able to obviously see which zone is selected. Some of my zones overlap more than they overlay other zones, and I would also like the opacity of all the zones of the same selected state to be the same.

Just curious, but may I ask for a screenshot of your layouts or for the reason you have many overlapping? :-)

believe this is a dup of https://github.com/microsoft/PowerToys/issues/4098#issuecomment-955576892
This will be in 0.53 release


WAR-1647: moving config.json to inside settings/.data directory

REST Regression is failing. Travis has passed otherwise


Indexing error when mask is only one gridcell in x and/or y direction

 File "/home/stoop/anaconda3/lib/python3.6/site-packages/salem/sio.py", line 280, in _lonlat_grid_from_dataset     dy = lat[1]-lat[0] [...] IndexError: index 1 is out of bounds for axis 0 with size 0
This error is caused by the fact that the mask is only one gridcell long in a certain direction.
Maybe a general dy or dx definition could be made?
I am trying to select narrow regions, based on the Eurostat NUTS levels, from my data for climatology analysis.

I see the error message results from salem - are you sure this is a regionmask problem? Can you add reproducible example?
The mask should have the same (lat/ lon) shape as the input dataset, so unless your original dataset has size 0 x n, this probably happens at a later stage. What can easily happen is that one of your regions has 0 selected gridcells - did you plot the resulting map?
Do you select data based on a mask (e.g. ds.flatten()[mask.flatten() == 1])?

Double checking made that if I chose the margin (a function of salem) to high that the code failed.
Sorry for the inconvenience, but I couldn't find a fault yesterday.


Adapted to Ubuntu 18.04

I made some adaptions because I tried the howto with my Serverbörse server with Ubuntu 18.04. I think the changes apply as well to Debian. The dropbear SSH key part was missing as well.

@nodomain awesome thank you! I take a look.

LGTM Thanks!


Typo correction

Some typo correction in change (adopt script to latest curl / webserver version, tarball was not read)

its not a "typo" as this was how it worked before wube decided to break things but this looks great

Thnx for the input, I've resorted to using a different approach with grep and some perl regexes instead.


Fix spelling of the example abbreviation (e.g.)

Most of the instances of this abbreviation already use the "e.g." form.
This commit changes the non-conforming ones to match.
Note that although this commit changes 29 files, almost all of these changes are in code comments. The only user-visible ones are in the README, and in localizable strings on the following six files:

src/vs/code/node/cliProcessMain.ts
src/vs/workbench/contrib/debug/common/debugSchemas.ts
src/vs/workbench/contrib/extensions/electron-browser/extensions.contribution.ts
src/vs/workbench/contrib/markers/browser/messages.ts
src/vs/workbench/contrib/snippets/browser/snippets.contribution.ts
src/vs/workbench/services/keybinding/electron-browser/keybindingService.ts

By the way, I'm not making this change spuriously; My original goal was to propose a change one of these messages (the one in src/vs/workbench/contrib/markers/browser/messages.ts), to make it clearer and more explicit, like this:
-"Filter. Eg: text, **/*.ts, !**/node_modules/**");
+"Filter files. E.g.: text, **/*.ts, !**/node_modules/**");

but didn't want to change the "Eg." to "E.g." in one place while leaving the others in an inconsistent state.

The files under src\typings are copied in, and shouldn't be changed since the changes will get overwritten.

Thanks for the careful review, @alexr00. I'll fix and update the PR shortly.

@alexr00 thanks for the quick merge :) for future reference, was the extended message in this specific commit not particularly useful, or is there some guideline to not add additional details to commit messages?

Concise details are always welcome!


Add QT Py ESP32-S3 with 2MB PSRAM

Related PR: https://github.com/adafruit/Wippersnapper_Boards/pull/112

Tested OK against production


update smart contract framework

The smart contract framework is outdated so that the build will be failed if  developers download the project and run it directly.
Therefore, we should updated all the smart contract framework to the latest version to avoid unnecessary problem.

@shargon @erikzhang @lock9 can you please help us to merge this PR if there is no issues ?Thank you


MM-31634 Remove stages and restore single checklist.

Summary
Removes stages and restores a single checklist. Prelude to incident status.
Screenshot

Ticket Link
https://mattermost.atlassian.net/browse/MM-31634
Testing Notes
Try and see if you can find places we still use the word Stage in the UI.

Note that the e2e tests are broken, so this will require some updates to the tests once I am able to do so.

Note that the e2e tests are broken, so this will require some updates to the tests once I am able to do so.

I found Stage in the UI:

I found Stage in the UI:

(Removing request for @prapti until merge conflicts resolved.)

(Removing request for @prapti until merge conflicts resolved.)

@prapti Merge conflicts resolved.

@prapti Merge conflicts resolved.


~/.gbp.conf affects dh-make-golang pristine-tar behaviour

dh-make-golang v0.3.3 would create pristine-tar branch regardless of command-line option when pristine-tar = True is defined in ~/.gbp.conf or /etc/git-buildpackage/gbp.conf.
See Tong Sun's report at https://lists.debian.org/debian-go/2020/03/msg00013.html

(removing from milestone since already released)