[FEAT] Compile all content into one language json file from three separate files

⚠ IMPORTANT: Please fill out this template to give us as much information as possible to consider/implement the feature.
Prerequisites

[ ] check this box if you have completed the following:

Reviewed the contributing guidelines and support files
Reviewed the README file for the repository you are working in
Searched for relevant instructions on our Discord server
Searched the issues of the repository you are working in to make sure one was not already filed

Summary

Currently the education, health, and display text content for each language are three separate json files. For the front end end team to work with a particular language they need to have each language be one json file that's referenced in the locale chosen.
Motivation

This is to promote reference by the app to the proper, central language json file
Possible Alternatives

Keeping as is, which is a fragmented approach
Additional Context

This is part of the content continuous integration workflow being developed

Hi @ngiangre JSON file is updated here: https://github.com/COVID-19-electronic-health-system/Corona-tracker/blob/master/Translations/appText.json
cc: @salvolpe @tesla809 @SomeMoosery

Extremely detailed @BrianHHough! We can definitely make use of this.

Seriously!! Awesome work @BrianHHough

Undid this change - there's a PR process these things need to go through and we can't commit right to master. Don't want to be dictatorial but this can seriously break things. Will need a PR relating to this issue just like everything else.

Yeah agreed thanks @SomeMoosery. But @salvolpe and I can work with this file if @BrianHHough sends it through discord.

Yeah no prob! The file looks great, I agree - just need to make sure we're going through the git flow so things don't start to fall off track.
I'm also not sure what you mean - what are you trying to update? If you're trying to update components when some value changes that should be done with hooks in the React code.

Yeah don't want to obstruct the process at all.
We need to make sure the text is adequately translated dependent on the locale. We want to try to help you make your hooks with the proper content:

I should've first made an issue pertaining to this. @BrianHHough prematurely did a PR but it's ok you live and learn.
I need to make a more formal issue and description, but I guess this will do.
The idea is to allow hooks to be made dependent on the locale chosen (a file with the adequate translation will be pointed to for the correct translation). Sorry I'm not sure how much I can explain here. @SomeMoosery what would be the best way to proceed from here?

Yeah, so it seems like what can be done from this end is that once we get a master doc for each language merged in, we can create a new issue for which we change the locations specified in i18next to point to these new JSON files, and we should be set 👍

Ok great. I made a PR that was approved which put language json files in docs/content but now I'm working on another that puts everything in that language from 3 to one json file with the structure needed by front end - I'm working with @pavel-ilin and @AdhamAH on that. But @SomeMoosery if you have any suggestion on a better structure for the json files in docs/content let me know!

Closing other issues to have this be the issue with all the information.
https://github.com/COVID-19-electronic-health-system/Corona-tracker/issues/623#issue-605061240
https://github.com/COVID-19-electronic-health-system/Corona-tracker/issues/359#issue-592764712
https://github.com/COVID-19-electronic-health-system/Corona-tracker/issues/530#issue-601336342

Can we make sure that the privacy policies and terms and conditions are also included as all content? If so, this can be within this issue.

Yes @tesla809

@BrianHHough
I loved the file! It is clear and will be easy to use i18next
@ngiangre will you use this? or the examples you sent me?
As @SomeMoosery said as soon as the JSON ready we can start working on point the app to use i18next when needed

I'm working on it.
The issue is that we need to have the structure in our data model so However we make the keys is consistent, makes sense, and the values can be adapted in the future.
The data model is here:
https://docs.google.com/spreadsheets/d/1gifZGnj-ntIOXbZrRY4S5KEULoV64DCbi0pZSVWKsns/edit?usp=sharing
Right now only the health sheet follows the data model and has a field name to be included in the tag:
https://docs.google.com/spreadsheets/d/1tjeTH99QZSmyfG-TvX5seSYKa03yAHdMWrZt1z9521I/edit#gid=0
We need to fill in the parent/child keys and add a field name for education:
https://docs.google.com/spreadsheets/d/1OdasOk5y8w9JLv3VWmziV8XkznaYiW-OQzbQq5ZK26M/edit?usp=sharing
And Display Text is incomplete
https://docs.google.com/spreadsheets/d/1wn02oIks4avznMoJfxVHCo5221D9wwfu6yaWpi6QleA/edit?usp=sharing
I need help with the data model - I can handle this but @salvolpe can help and anyone else willing to help please reach out. And once the data model is done I can get the content from translations to populate the value via the python script src/python/pull_gsheets_data.py.
I work a lot with common data models so this is really important.

@BrianHHough I love your appText.json.
I would suggest modification of the survey section. I would like to store all questions in the array and add question type attribute to every question. This will help us not only with translation but also render all questions dynamically. We can iterate over the array and base on type of the question render components we need. This way we can move away from hardcoding every question.
Example:

I thin we can do the same with quizzes.
@ngiangre @AdhamAH @salvolpe @tesla809 @SomeMoosery What do you think?

Great! The structure is do-able. Can you make a sample @pavel-ilin for the education content and display text as well?

@pavel-ilin @AdhamAH or anyone on front end - to finish converting Sal and I need to understand what exactly is hard coded and how values are set to defaults so we can accommodate in our data model. Can someone ping me, @NickG, on discord or comment here?

I really still don't fully understand what are you trying to do and why it looks so complicated @ngiangre
Anyway I hope this would help you
https://docs.google.com/document/d/1f8RQFBNfLKEPPp2v1eYf693zU9hK8oEKq8Lb0S2VbFI/edit?usp=sharing

This is great @AdhamAH! Let’s chat on discord so we can be on the same page.

I think just to keep things clear in terms of this issue. The end result here is that we just end up with "master" JSON files for each language, which will be stored in /public/locales. We use i18next's useTranlsation hook, which pulls the currently-selected language from this directory and populates it by using the t(...) function.
There is no hard and fast rule on what's hard-coded and what's not, as every component is different just by nature of building out a responsive web app. This simply requires someone going through each component and looking for where there is hardcoded text, and making sure that text is captured in the master JSON file for translations.
I saw Brian was breaking his WIP master JSON file appText.json in terms of components, which I think is a good idea. For example, onboardSection: { ... } would correspond to Onboarding.jsx, disclaimerSection: { ... } would correspond to Disclaimer.jsx - so on and so forth.
This will be tedious but having someone go through and report back where things are hardcoded and need translating wouldn't save any time, as someone then still has to go through and add those hardcoded portions into the master JSON file, and use the useTranslation hook's t(...) function to translate.
This will likely be an iterative process - we can always create more issues to reformat the master JSON files and subsequently update the translated values in the corresponding components.

Correct @SomeMoosery - one master json for each language that will be within public/locales/
My goal is to get a "MVP" available - we will have every field needed in the gsheets that can then be transformed into the correct json file via python scripting with the google api.
In order to get the right structure, we needed to know how you would call the tags which wasn't clear. Now it is so thanks! You're right we might not be able to get everything, but we want to get most atleast. The over-engineered part might be from detailing everything, so we'll not do that. But we did need to understand the right structure so it's usable. The data model is important so it's consistent - if not in a data model, then iterative processing/modification/adding languages will get really convoluted and 'makeshift' real fast.
So I'm glad we are having this discussion!

That's a very good point!
Sounds good, since I've been somewhat away for a day or two I was just hoping to add some clarity as somewhat of an "outside" perspective to this translations bit. Seems like it's on the right track though thanks to yours and everyone's work on it, and this is one of the best discussion on an issue I think we've had 😄

teamwork makes the dream work!

Done. Finishing work in #665


Update Model.php to allow dynamic appending of attributes to query

We then could use it like this:
return $resource->findOrFail($id)
                      ->append(['custom_attribute'])
                      ->toArray();

:+1:

Thank you for the help @GrahamCampbell and @lukasgeiter.
Thank you for the merge @taylorotwell.


Add option & ".norminetteignore" file to ignore files

Thinking about this again, the .norminetteignore file could be abused if the reviewer fails to see the the file and does not realize some files are being ignored. I will add an option to enable the usage of the file.

I think you should not add the -g alias because it is not explicit. This one could be abused by some people saying -g is for global searching. 😅

You're right.

Hello and sorry, but I can't merge this as the basic usage of the norminette should not require any ignored files. Besides, it becomes easy to "hide" files during an evaluation so all in all, it's probably safer without it.


fix error

Acknowledgement of preliminary instructions

[X] I have read the preliminary instructions, and I am certain that my problem has not already been addressed.
[X] I have thoroughly looked through the available Wiki articles and could not find a solution to my problem.
[X] I am using the latest version of Bloxstrap.
[X] I did not answer truthfully to all the above checkboxes.

What problem did you encounter?
không chạy được và bị dính lỗi ngoài lề bloxtrap
Bloxstrap Log
N/A
Bloxstrap_20241009T034655Z.log

Roblox was down at the time.
Not a Bloxstrap issue.

https://github.com/bloxstraplabs/bloxstrap/wiki/"Deserialised-application-settings-is-null!"-when-launching-Roblox


How did you create the libsync.glb file?

Please describe the process you used. Esp. for generating the AnimationClips from the desired visemes.

Pinging...no answer yet?


[Added] Analyst search method

--BACKEND
-added Upload software engineering api.
--FRONTEND
-fixed api reference from analyst form api.
--INTERGRATION
-added software engineering api method to frontend and backend.

Well done.
I have personally checked that it is working, however need to add unit testing.

okay o-o

Unit test has been passed.


Update ModelProcessor to generate 2 services (one for each port - htt…

Update ModelProcessor to generate 2 services (one for each port - http and ssh)

Refer to this link for build results (access rights to CI server needed):
https://fabric8-ci.fusesource.com/job/fabric8-quickstarts-master-pullreq/462/
Test PASSed.

merged


Upgrade ex_doc and earmark to the latest versions

Coverage remained the same at 98.99% when pulling 616d04b07c346b6be305fe7f988e2982ffb54a4b on ex_doc into 601110d96c1f99881a715dfc84362b2a086a3a1c on master.


cats not working with 2.80

i tried everything to get the cats plugin to work and it just wont work or install i need help

i
I also encountered the same problem.

I think you would need an older version of blender. Try that and see if it works

Make sure that you are using the following version of blender
Requirement
Blender 2.79 or 2.80 (run as administrator is recommended)
mmd_tools is no longer required! Cats comes pre-installed with it!

Do you get any errors? If yes, please post a screenshot. Also make sure that you are using the latest version of cats

When I try to check cats, I get this

How do I fix it?

Since you manually installed it manually instead of installing it through Blender, you need to start Blender as admin.


bug: Cortex exited with code null immediately after loading a model

[X] I have searched the existing issues

Current behavior
Trying to load even the TinyLLaMa Chat 1.1B model doesn't work, Cortex seems to crash immediately after loading the model. This occurs on a fresh AppImage under Fedora 40.
Minimum reproduction step

Open Jan
Download TinyLLaMa when the app prompts you to do so
Write something as the input
Press enter

Expected behavior
The model should load and run without a problem.
Screenshots / Logs
2024-06-22T20:03:36.375Z [CORTEX]::CPU information - 2
2024-06-22T20:03:36.377Z [CORTEX]::Debug: Request to kill cortex
2024-06-22T20:03:36.429Z [CORTEX]::Debug: cortex process is terminated
2024-06-22T20:03:36.430Z [CORTEX]::Debug: Spawning cortex subprocess...
2024-06-22T20:03:36.431Z [CORTEX]::Debug: Spawn cortex at path: /home/user/jan/extensions/@janhq/inference-cortex-extension/dist/bin/linux-cpu/cortex-cpp, and args: 1,<IP_ADDRESS>,3928
2024-06-22T20:03:36.432Z [APP]::/home/user/jan/extensions/@janhq/inference-cortex-extension/dist/bin/linux-cpu
2024-06-22T20:03:36.550Z [CORTEX]::Debug: cortex is ready
2024-06-22T20:03:36.551Z [CORTEX]::Debug: Loading model with params {"cpu_threads":2,"ctx_len":2048,"prompt_template":"<|system|>\n{system_message}<|user|>\n{prompt}<|assistant|>","llama_model_path":"/home/user/jan/models/tinyllama-1.1b/tinyllama-1.1b-chat-v1.0.Q4_K_M.gguf","ngl":23,"system_prompt":"<|system|>\n","user_prompt":"<|user|>\n","ai_prompt":"<|assistant|>","model":"tinyllama-1.1b"}
2024-06-22T20:03:36.746Z [CORTEX]::Debug: cortex exited with code: null
2024-06-22T20:03:37.661Z [CORTEX]::Error: Load model failed with error TypeError: fetch failed
2024-06-22T20:03:37.661Z [CORTEX]::Error: TypeError: fetch failed
Jan version
0.5.1
In which operating systems have you tested?

[ ] macOS
[ ] Windows
[X] Linux

Environment details
Operating System: Fedora 40
Processor: Intel Core i5-3320M, 2C/4T
RAM: 16Gb

@mshpp I am closing this issue, as we are moving towards a cortex.cpp which is in full C++. The JS version had too many stability issues (like this).
I will be adding this to our Test Checklist for the C++ v0.1. We'll reach out again for you to test v0.1 when we release it (ETA 2 weeks)

Tracked in https://github.com/janhq/cortex.cpp/issues/1147


Improvement/configure cTDP

#26

additionally we should maybe check 0xCE bit 29 and bits 34:33.
(bit 30 for temperature target)

are you fine with it?

Sorry, I was busy with the DEF CON 26 CTF lately. I just reviewed your commits and they seems quite ok. I'm having a look at your questions now, although I think the register is right because I spent a few days looking at the (several) Intel datasheets.

As you can see in the 8th gen datatasheet vol 2 there is both 0x65c and 0x610 MSRs. The first is the platform one, I guess is an additional limit that the manufacturer/integrator can set, while the latter is the package power limit. We can override both just to be safe but in my T480s they are both set to 90W.

I was reading this vol 4 datasheet all the time


Validation loops always recompile inside supervised training loops

Hi 👋
first of all, thank you for all the great work your a putting into Nx* libraries. I'm slowly learning ML by playing with Nx and Axon, and that's a real pleasure 💜

I was playing with a simple model and i noticed that when the EXLA compiler is set globally with this command: Nx.Defn.global_default_options(compiler: EXLA) the training is slower compared when It is not set.
This surprises me a bit, but I might have overlooked something.
I shared the Livebook I used in a gist that you can use to reproduce the behaviour I described above.
https://gist.github.com/nickgnd/0d8c986b5887f4ccb7442b7145001d7f
A couple of screenshots as reference:

With Nx.Defn.global_default_options(compiler: EXLA) it takes 9.1 seconds to train the model (100 epochs)

With Nx.Defn.global_default_options([]) it takes 2.7 seconds to train the model (100 epochs)

Moving the call Nx.Defn.global_default_options(compiler: EXLA) from the top of the livebook right before the training does not change the behaviour.
To conclude, It can possibly be that I didn't understand how/when to use Nx.Defn.global_default_options and/or that I'm doing something wrong, sorry in advance for that 🙈
Let me know if there is anything else that I can do to support you,
Thanks.
Keep rocking 🎸

My current setup:

macOS Monterey 12.6

erlang 25.1.2

elixir 1.14.2-otp-25

livebook 0.8.0

processor: 2.3 GHz Quad-Core Intel Core i7

memory: 32 GB

graphic card: Intel Iris Plus Graphics 1536 MB

Hi @nickgnd! Can you try passing compiler: EXLA, debug: true in both cases and paste the log outputs. I am suspecting we are compiling things more frequently than we should. :)

Hi @nickgnd. I cannot reproduce this.
But generally speaking, you want to set Nx.global_default_backend(EXLA.Backend) (or on config) and pass the compiler on demand (instead of globally), I will improve the docs.

Btw, I could confirm we are getting cache hits for EXLA. :)

@josevalim thanks for trying it out and for the clarification!

Hi @nickgnd. I cannot reproduce this.

Interesting, it happens deterministically in my machine. I'm wondering what I'm doing wrong or what's wrong with my setup 🤔
Let me know if there is anything else that I check.
Feel free to close the issue :)

Yup, already tried and indeed now is faster

it should be the fastest. :)

Do you mean that it should be the fastest overall? Or only when creating the tensors?
The livebook should probably not considered a reliable benchmark, but here the numbers:

without setting backend via Nx.global_default_backend(EXLA.Backend) the trainer takes 2.9s
with setting the backend via  Nx.global_default_backend(EXLA.Backend) the trainer takes 3.1s

Maybe the dataset/model is too simple/small? Idk 🤔
☝ Needless to say, in both the cases I removed the function call Nx.Defn.global_default_options(compiler: EXLA) which was misused.

Side note, I found a bit confusing that Nx.global_default_backend/1 returns the current backed and not the one that have just been set.
Nx.global_default_backend(EXLA.Backend)
{Nx.BinaryBackend, []}

Without looking at the implementation underneath, it seems that it was not properly updated.
I can happily open a PR to update the implementation (i can give it a try) or the docs at least.

Cheers ✌

It is common for stateful operations to return their current state on update. So a PR to document that is welcome. :)

Make sure to restart the runtime on those changes, because application/pdict state can persist across evaluations.
But in general i would expect that:

No backend or compiler configuration to be the slowest
Backend only config to be faster than 1
Compiler only config to be faster than 1

It is unclear though why you are seeing much higher times for global compiler. My guess is that we are compiling functions that we should not (for example, zeros_like).

Hey @josevalim, thanks again for getting back to me.
I created a quick benchmark to try out your suggestions.
Apparently, what slows down the training when setting the compiler globally is the validation step in the training, i mean this line of code |> Axon.Loop.validate(model, validation_data).
Mix.install([
  {:exla, "~> 0.4.1"},
  {:nx, "~> 0.4.1"},
  {:axon, path: "../axon"},
  {:benchee, "~> 1.1.0"},
])

#######################################

# Benchmark: Nx compiler vs Nx backend
#
# run with `elixir axon_bench.ex`
#
# There are 4 scenarios, run them separately:
#
# 1.
# Set the backend globally
# Nx.global_default_backend(EXLA.Backend)

## 1.1 Without validation data

# Name               ips        average  deviation         median         99th %
# training         11.45       87.37 ms     ±3.50%       86.74 ms       96.43 ms
#
# Memory usage statistics:
#
# Name        Memory usage
# training        11.91 MB

## 1.2 With validation data

# Name               ips        average  deviation         median         99th %
# training          5.15      194.00 ms     ±6.35%      197.50 ms      205.55 ms
#
# Memory usage statistics:
#
# Name             average  deviation         median         99th %
# training        15.89 MB     ±0.00%       15.89 MB       15.89 MB

# 2.
# Set the compilation option globally
# Nx.Defn.global_default_options(compiler: EXLA)

## 2.1 Without validation data

# Name               ips        average  deviation         median         99th %
# training         14.71       67.98 ms     ±3.83%       67.64 ms       76.03 ms
#
# Memory usage statistics:
#
# Name        Memory usage
# training        10.47 MB

## 2.2 With validation data 💥

# Name               ips        average  deviation         median         99th %
# training          0.72         1.38 s     ±4.70%         1.37 s         1.45 s
#
# Memory usage statistics:
#
# Name             average  deviation         median         99th %
# training        12.99 MB     ±0.02%       12.99 MB       12.99 MB

#######################################

# Generate the data

key = Nx.Random.key(42)

{inputs, _new_key} = Nx.Random.normal(key, 0, 1, shape: {1000, 2}, type: :f16)

labels =
  Enum.map(0..999, fn _ -> Enum.random([0, 1]) end)
  |> Nx.tensor()
  |> Nx.reshape({:auto, 1})
  |> Nx.equal(Nx.tensor([0, 1]))

## Equally split the tensors in 2 parts: train and validation datasets

[x_train, x_validation] = Nx.to_batched(inputs, 500) |> Enum.to_list()
[y_train, y_validation] = Nx.to_batched(labels, 500) |> Enum.to_list()

## Divide the train dataset in batches

batch_size = 25

train_inputs = Nx.to_batched(x_train, batch_size)
train_labels = Nx.to_batched(y_train, batch_size)
train_batches = Stream.zip(train_inputs, train_labels)

validation_data = [{x_validation, y_validation}]

# Create and train the model

model =
  Axon.input("data")
  |> Axon.dense(100, activation: :sigmoid)
  |> Axon.dense(2, activation: :softmax)

loop =
  model
  |> Axon.Loop.trainer(:categorical_cross_entropy, Axon.Optimizers.rmsprop(0.001))
  |> Axon.Loop.metric(:accuracy)
  # |> Axon.Loop.validate(model, validation_data) # <----- uncomment this to add the validation step

Benchee.run(
  %{
    "training" => fn -> Axon.Loop.run(loop, train_batches, %{}, epochs: 10, compiler: EXLA) end
  },
  time: 4,
  memory_time: 2
)

Said that, I'm not asking you (or anyone else) to follow up on this, I just wanted to share my last findings.
Again, feel free to close the issue, and thanks for the great work you are doing here 🙇
Cheers ✌

@nickgnd Thanks for sharing this, it actually makes a lot of sense. In some of my recent work I noticed validation loops ALWAYS recompile, and I haven't been able to get to the source of the issue. I will leave this open until we can force cache hits in validation loops!

@nickgnd I believe this also was solved in #427 :)


AEGIS-6406 fix scripts

Removed the scripts and made them modules.
Tidied the code and added a bunch of #TODO items throughout.

I like how you have planned out stuff for others to do via todos. My only comment that doesn't block merging, it might be worth keeping that old README somewhere so you can understand those scripts / class usage until it's ready to be fully updated. I guess it's here in history and in old fork but just a thought.

I've removed the scripts so I also removed from the README as it no longer correlates.
The scripts and old README are in history and the original code too


Fix physics_sync only allowing one transform change per physics frame

Fixes #76685, fixes #98970
If the transform was set multiple times per frame, every attempt prior to the last would be overwritten by the final call from AnimatableBody's NOTIFICATION_LOCAL_TRANSFORM_CHANGED. This adds a member variable that accumulates those changes instead.
A bit worried about slowness though. I don't have a good sense for performance, but it seems expensive. It runs inverse, orthonormalize and matrix mults as many times as the transform is set on each AnimatableBody, which could be quite a lot of times per frame.

Nevermind, this would introduce a new problem. It works for separate elements (e.g. changing rotation and position, or position.x and position.y) and += type assignment, but if you have, for instance, this:
func _physics_process(delta):
	position.x = 1
	position.x = 1

it'll misbehave and oscillate wildly. I can't think of a practical way to tell apart what should be accumulated and what shouldn't. At this point in the code you can't distinguish between them.
Will think about it more


fix(ui): pin ssi agent validate button to bottom of page

Description
Pin validate button to bottom of Create SSI agent page
Checklist before requesting a review
Issue ticket number and link

[x] This PR has a valid ticket number or issue: DTIS-971

Testing & Validation

[x] This PR has been tested/validated in IOS, Android and browser.
[x] The code has been tested locally with test coverage match expectations.
[] Added new Unit/Component testing (if relevant).

Security

[x] No secrets are being committed (i.e. credentials, PII)
[x] This PR does not have any significant security implications

Code Review

[x] There is no unused functionality or blocks of commented out code (otherwise, please explain below)
[x] In addition to this PR, all relevant documentation (e.g. Confluence) and architecture diagrams (e.g. Miro) were updated

Design Review

[x] If this PR contains changes to the UI, it has gone through a design review with UX Designer or Product owner.
[x] In case PR contains changes to the UI, add some screenshots to notice the differences

IOS

Android

Browser

Could you please also fix “Create your password” page, I added a screenshot to the ticket on Jira to show it has the same issue.

I updated create password screen. Please help me check.
IOS

Android

Browser


get_redirect_location return error hostname

when I visited site http://bitsnoop.com/chano-dominguez-hecho-a-mano-200-q18406062.html like this:
In [3]: r = get('http://bitsnoop.com/chano-dominguez-hecho-a-mano-200-q18406062.html', allow_redirects=False)
In [4]: r.status_code
Out[4]: 302
In [5]: r.raw.get_redirect_location()
Out[5]: 'http://<IP_ADDRESS>/'

I got the error redirect address. So I test the website with curl:
$ curl -v http://bitsnoop.com/chano-dominguez-hecho-a-mano-200-q18406062.html
* Hostname was NOT found in DNS cache
*   Trying <IP_ADDRESS>...
*   Trying 2a02:29b8:1925::2...
* Immediate connect fail for 2a02:29b8:1925::2: Network is unreachable
* Connected to bitsnoop.com (<IP_ADDRESS>) port 80 (#0)
> GET /chano-dominguez-hecho-a-mano-200-q18406062.html HTTP/1.1
> User-Agent: curl/7.35.0
> Host: bitsnoop.com
> Accept: */*
>
< HTTP/1.1 301 Moved Permanently
< Content-Type: text/html; charset=utf-8
< Keep-Alive: timeout=300
< Location: http://bitsnoop.com/chano-dominguez-hecho-a-mano-2002-q18406062.html
< Transfer-Encoding: chunked
< Date: Sat, 13 Feb 2016 01:29:09 GMT
< Connection: keep-alive
* Server Hampsterbox/2.0 is not blacklisted
< Server: Hampsterbox/2.0
<
* Connection #0 to host bitsnoop.com left intact

Obviously the right redirect address is http://bitsnoop.com/chano-dominguez-hecho-a-mano-2002-q18406062.html. It's really confusing;)

r.raw.get_redirect_location() is not actually part of the Requests API, and is not a supported way to procure that information.
The proper way (as it stands) is to simply look at the value of the Location header:
>>> r.headers['Location']
'http://<IP_ADDRESS>/'

It looks like this server is sending a phony redirect based on the User-Agent header the request used.
This works for me:
url = 'http://bitsnoop.com/chano-dominguez-hecho-a-mano-200-q18406062.html'
headers = {'User-Agent': 'curl/7.43.0'}
r = requests.get(url, allow_redirects=False, headers=headers)

   >>> r.headers['location']
'http://bitsnoop.com/chano-dominguez-hecho-a-mano-2002-q18406062.html'

This is why you were seeing differing results with cURL.

Thx.
It helps me a lot;)

@jaron92 sure thing! :cake:


Omit the test files from the coverage report

Currently the test files are included in the coverage report, this tells pytest-cov to omit them via .coveragerc. It should drop coverage by around 3%.

Coverage decreased (-3.4%) to 90.031% when pulling 44c9e2828fadeeac8d2589e8de5166f7adfb4fec on benlongo:ignore_test_files_for_coverage into bc8542466fb38929831bbd80067f299c6fa477e5 on kensho-technologies:master.

Coverage decreased (-3.4%) to 90.031% when pulling 56badfd34268ddd77230fbc951d90a7c3a7432dd on benlongo:ignore_test_files_for_coverage into bc8542466fb38929831bbd80067f299c6fa477e5 on kensho-technologies:master.

Great -- thank you for the help!
As an aside, there's another coverage-related thing I've been meaning to do but haven't gotten around to it. If you look at the coverage report, there are many uncovered lines to the effect of raise AssertionError("this should never happen"). In fact, that's all AssertionError is used for.
If you're interested, I could use some help making the coverage ignore those lines, since they are not reachable anyway so they are pointless coverage misses.


*: drop obsolete gentoo repo reference

Instead of patching portage to support the disabled flag now we just
patch it to leave the [gentoo] section out of the default repos.conf.
Follow up to https://github.com/coreos/coreos-overlay/commit/585275b268da9f549d93c7c37744dcda3411cca2

lgtm


L2SS spatial subsetting fails when ordering from Earthdata Seach

After some debugging, it seems like there is an issue with the L2SS service when ordering from Earthdata Search with a shapefile for subsetting. We have confirmed we are successfully passing a valid shapefile. When the request is made to Harmony we receive the following error:
WorkItem [16079488] failed with error: podaac/l2ss-py:2.4.0: Service request failed with an unknown error
Jira: PCESA-2733

@jamesfwood
Do you recall what cloud collection(s) had this issue?

@sliu008 Can you answer David's question?  What collections did you create this for and fix?

L2SS-Py - v2.6.0rc14
HiTIDE UI (UAT)- v4.16.0-RC.6
HiTIDE Profile - v4.9.8-rc.1
Since I didn't hear back from DEV regarding the affected collections, I went ahead and validated CYGNSS_L2_V3.1 for this testing.
Confirmed the user no longer receives the respective podaac/l2ss-py error as before
Test Complete
https://harmony.uat.earthdata.nasa.gov/jobs/cf0e48c2-159e-4cf1-92a4-bca71ac28d04


test: fix -Wstrict-prototypes warnings

These have been around for some time apparently (commit 391f0098de from
May 2011) but went unnoticed so far.  No longer.

CI: https://ci.nodejs.org/view/libuv/job/libuv-test-commit/513/


Translations update from Hosted Weblate

Translations update from Hosted Weblate for Flashy/Flashy.
Current translation status:

Thank you so much for your support, @kuragehimekurara1! 😘


Add configurable async route

Adding AsyncFunctionInvocation variable in the
ControllerConfig in order to enable/disable
asynchronous invokation of functions along
with augmenting on how we build the gateway
URL
Vendored change can be tested in kafka-connector by augmenting the image with mine:
martindekov/kafka-connector:0.3.5
and adding environmental variable asynchronous_invocation to true/false or 1/0 for true in the connector-dep.yml file
Closes #1
Tested by vendoring the change in the kafka-connector and invoking function
through the asynchronous path, the output in the kafka-connector looks like this:
2019/06/10 13:24:11 Syncing topic map
[#1] Received on [faas-request,0]: 'asdf'
2019/06/10 13:24:12 Invoke function: figlet
2019/06/10 13:24:12 connector-sdk got result: [202] faas-request => figlet (0) bytes
[202] faas-request => figlet

Signed-off-by: Martin Dekov<EMAIL_ADDRESS>

@martindekov what's the helm install/upgrade step that someone can type in such as myself or @zeerorg?

For vendoring into kafka-connector, etc: https://github.com/openfaas-incubator/connector-sdk/releases/tag/0.4.1

I will vendor it as soon as I can

Also will add it to the helm chart in the faas metes repo


Add flag for dry-run

With the dry-run capability, cargo-autoinherit can be run in CI and used
to enforce strict inheritance except for excluded workspace members.
The dry run will not touch any files in the workspace. However if any
file would be touched or there are any dependencies which could not be
autoinherited, it returns with a non-zero exit code.

Just saw this may be covered by #17


[chore] Run go tests on Windows GitHub runners CI

Resolves #450

Looks like multimod diff isn't working on Windows, always thought it was an issue with my local git
multimod diff -m tools -p 1.2.3
error running diff: VerifyWorkingTreeClean failed: working tree not clean

Related issue with go-git https://www.github.com/go-git/go-git/issues/691 :eyes:

I suggest adding something like
if runtime.GOOS == "windows" {
  t.Skip("diff does not work on Windows. See: https://github.com/open-telemetry/opentelemetry-go-build-tools/issues/467.")
}

to `TestHasChanged` unless you find a quick way to solve https://github.com/open-telemetry/opentelemetry-go-build-tools/issues/467


plot.TrajectoriesFile

Is there anyway to plot the trajectory with a tracerfield greater than a 2D array? Or can we read the velocity fields with only latitude and longitude? My data has dimensions: lat, lon, depth and time.
Thanks.

This has been fixed in #401


clock animation

Wall clock animation

Close #3793

Checklist:

[x] I have mentioned the issue number in my Pull Request.
[x] I have commented my code, particularly in hard-to-understand areas
[x] I have created a helpful and easy to understand README.md

@MohitGupta121 @TusharKesarwani Kindly review this PR.


Typings wrong, also not marked in package.json

Hi, I tried to use you library from typescript, but the typings seem to be wrong. createOSMStream returns void, but from the example you provide it should return an Iterator. Additionally, the availability of types is not marked in the package.json in the typings field.

Your's works, but produces some warning by the TypeScript Compiler. This should be the right version:
declare module 'osm-pbf-parser-node' {
    import { Transform, TransformOptions } from 'node:stream';

    type WithTags = boolean | string[];

    export interface OSMOptions {
        withTags?: boolean | { node?: WithTags, way?: WithTags, relation?: WithTags },
        withInfo?: boolean,
        writeRaw?: boolean
    }

    export class OSMTransform extends Transform {
        constructor(osmopts?: OSMOptions, opts?: TransformOptions);
    }

    export function createOSMStream(file: string, opts?: OSMOptions): AsyncGenerator<object, void, unknown>;
    export function parse(osmdata: Buffer, transform: OSMTransform | OSMOptions): Array<object>;
}

And, as you are using the Buffer Type, you will have to add "@types/node", which defines it, to the dev dependencies.

Works for me using my simple test,js:
$ node test.js 2 nordrhein-westfalen-latest.osm.pbf
reading from nordrhein-westfalen-latest.osm.pbf
withInfo: false, withTags: {"node":["name","amenity","shop"],"way":[],"relation":["boundary"
]}
header: seqno: 3897, timestamp: 07 Dec 2023 21:21:32 GMT, url: http://download.geofabrik.de/
europe/germany/nordrhein-westfalen-updates
counted: 80157377 nodes, 13337831 ways, 140286 relations
         1348515 items/sec.
elapsed: 1:09.437 (m:ss.mmm)

Can you create a small test to help me to reproduce the problem?

Sorry, I gave you the wrong url. I tried it using this one: https://download.bbbike.org/osm/bbbike/Bochum/Bochum.osm.pbf , thought they were from the same source, but aren't.

Tried it again with the file I sent yesterday, works fine.

The problem reproduced, hope to fix soon.

Fixed in 1.1.2, please try again.

Fixed in 1.1.2, please try again.

The errors mentioned in https://github.com/borisgontar/osm-pbf-parser-node/issues/1#issuecomment-1847095381 are still present (and should definitely by fixed), but the call stack size error is gone. Type-Definition reference in package.json looks good as well.

It works, but the compiler isn't happy about it. It's basically about which syntax is allowed in the type definitions of libraries (e.g. marking a function as async as redundant, because all that matters to the consuming code is that the function returns a promise). This checking can be disabled in the tsconfig (using skipLibCheck), but only on project level, not library level. I can send you the exact warnings later.

Your's works, but produces some warning by the TypeScript Compiler. This should be the right version:

declare module 'osm-pbf-parser-node' {

    import { Transform, TransformOptions } from 'node:stream';

    type WithTags = boolean | string[];

    export interface OSMOptions {

        withTags?: boolean | { node?: WithTags, way?: WithTags, relation?: WithTags },

        withInfo?: boolean,

        writeRaw?: boolean

    }

    export class OSMTransform extends Transform {

        constructor(osmopts?: OSMOptions, opts?: TransformOptions);

    }

    export function createOSMStream(file: string, opts?: OSMOptions): AsyncGenerator<object, void, unknown>;

    export function parse(osmdata: Buffer, transform: OSMTransform | OSMOptions): Array<object>;

}

These changes mitigate the warnings.

Please use 1.1.3, an ugly misprint was fixed. The index.d.ts is now your code.


update llvm-backend submodule

This updates to the version of K that I can use to execute the C semantics on the llvm backend! (at least one program)

Subsumed by #576


Add unique position test

Checklist

[X] I ran npm test locally and it passed without errors.
[ ] I only edited the _data/pixels.json file.
[ ] I entered the username in the pixels.json that I'm also using to create this pull request.
[X] I acknowledge that all my contributions will be made under the project's license.

Description
I added 2 tests.
One to check that the positions of pixels was unique, and one to check that the pixels file was in order.
Related issues
List any related issues here
#206

@dkundel I've reverted the commit to only include the unique position test. I'll create a new pull request later with the test to ensure the correct order.

I'm sure how I would remove them, without working on a clean branch. Is there a better way?


Package optimizer binary when releasing new version

As titled.

A test for this PR:
https://github.com/sctb512/nydus-snapshotter/releases/tag/v0.8.0

What's the difference between static and non-static versions?

Here is the difference:
Static version:
❯ ldd nydus-snapshotter-static/*
nydus-snapshotter-static/02-optimizer-nri-plugin:
	not a dynamic executable
nydus-snapshotter-static/containerd-nydus-grpc:
	not a dynamic executable
nydus-snapshotter-static/optimizer-server:
	statically linked

Non-static version:
❯ ldd nydus-snapshotter/*
nydus-snapshotter/02-optimizer-nri-plugin:
	linux-vdso.so.1 (0x00007ffd38990000)
	libpthread.so.0 => /lib/x86_64-linux-gnu/libpthread.so.0 (0x00007f8077769000)
	libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007f80775a9000)
	/lib64/ld-linux-x86-64.so.2 (0x00007f8077796000)
nydus-snapshotter/containerd-nydus-grpc:
	linux-vdso.so.1 (0x00007ffffbd11000)
	libpthread.so.0 => /lib/x86_64-linux-gnu/libpthread.so.0 (0x00007fa2bd053000)
	libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007fa2bce93000)
	/lib64/ld-linux-x86-64.so.2 (0x00007fa2bd080000)
nydus-snapshotter/optimizer-server:
nydus-snapshotter/optimizer-server: /lib/x86_64-linux-gnu/libc.so.6: version `GLIBC_2.33' not found (required by nydus-snapshotter/optimizer-server)
nydus-snapshotter/optimizer-server: /lib/x86_64-linux-gnu/libc.so.6: version `GLIBC_2.32' not found (required by nydus-snapshotter/optimizer-server)
nydus-snapshotter/optimizer-server: /lib/x86_64-linux-gnu/libc.so.6: version `GLIBC_2.34' not found (required by nydus-snapshotter/optimizer-server)
	linux-vdso.so.1 (0x00007ffc69dd5000)
	libgcc_s.so.1 => /lib/x86_64-linux-gnu/libgcc_s.so.1 (0x00007f5e193bc000)
	libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007f5e191fc000)
	/lib64/ld-linux-x86-64.so.2 (0x00007f5e19451000)

Codecov Report
Patch coverage has no change and project coverage change: -0.06 :warning:

Comparison is base (d0d9f04) 29.80% compared to head (4334e2b) 29.75%.

Additional details and impacted files
@@            Coverage Diff             @@
##             main     #418      +/-   ##
==========================================
- Coverage   29.80%   29.75%   -0.06%
==========================================
  Files          40       39       -1
  Lines        4181     4084      -97
==========================================
- Hits         1246     1215      -31
+ Misses       2774     2711      -63
+ Partials      161      158       -3

see 2 files with indirect coverage changes
Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Do you have feedback about the report comment? Let us know in this issue.

Now, optimizer-server is always a static version.
❯ ldd nydus-snapshotter/*
nydus-snapshotter/02-optimizer-nri-plugin:
	linux-vdso.so.1 (0x00007ffc4f3ed000)
	libpthread.so.0 => /lib/x86_64-linux-gnu/libpthread.so.0 (0x00007f030f045000)
	libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007f030ee85000)
	/lib64/ld-linux-x86-64.so.2 (0x00007f030f072000)
nydus-snapshotter/containerd-nydus-grpc:
	linux-vdso.so.1 (0x00007ffc973e7000)
	libpthread.so.0 => /lib/x86_64-linux-gnu/libpthread.so.0 (0x00007f4c17120000)
	libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007f4c16f60000)
	/lib64/ld-linux-x86-64.so.2 (0x00007f4c1714d000)
nydus-snapshotter/optimizer-server:
	statically linked
❯ ldd nydus-snapshotter-static/*
nydus-snapshotter-static/02-optimizer-nri-plugin:
	not a dynamic executable
nydus-snapshotter-static/containerd-nydus-grpc:
	not a dynamic executable
nydus-snapshotter-static/optimizer-server:
	statically linked

@sctb512 okay, why do we need a non-static version in the release?

@sctb512 okay, why do we need a non-static version in the release?

We have static version binaries. Non-static version binaries, which have a smaller file size, are also required. Libraries used by non-static binaries can be upgraded dynamically.

@sctb512 okay, why do we need a non-static version in the release?

We have static version binaries. Non-static version binaries, which have a smaller file size, are also required. Libraries used by non-static binaries can be upgraded dynamically.

Is it necessary to support the library upgrade? Most releases don't seem to have this requirement cc @changweige

Most releases don't seem to have this requirement

Got it. I 'll take it off if this is not necessary.
I find that containerd have released static and non-static versions.
By the way, our release packages do not specify architecture. Are they compatible with all platforms?

I think only releasing static binaries including containerd-nydus-grpc and other tools should meet our requirements now. We can also release other platform like arm64, however, it is low-priority now.

Updated.
https://github.com/sctb512/nydus-snapshotter/releases/tag/v0.8.1
❯ ldd nydus-snapshotter/*
nydus-snapshotter/containerd-nydus-grpc:
	not a dynamic executable
nydus-snapshotter/optimizer-nri-plugin:
	not a dynamic executable
nydus-snapshotter/optimizer-server:
	statically linked

PTAL @changweige @imeoer

Thanks, indeed containerd provided non-static versions, if snapshotter also does that, nydusd should do the same.

By the way, our release packages do not specify architecture. Are they compatible with all platforms?

Nydusd supports more platforms, we can do it later.


groups/roles support

Hi,
I'm using the LdapExtension with the AD flavour.
Are groups/roles supported yet?
I can't get it working. The authentication process is working well.
Is there anything I've to configure in advanced?

Okay, I found it myself.
Just add
services.AddScoped<IProfileService, LdapUserProfileService<ActiveDirectoryAppUser>>();
in ConfigureServices method in Startup.cs

Hi, I try with services.AddScoped<IProfileService, LdapUserProfileService<ActiveDirectoryAppUser>>(); but not work.
I need a role for each group the user belongs to.
Thanks for help.


Baichuan model can not be run

Hello, the PR one merged into main are actually can not run.....
The output can not be given just thrown some value error which I don't know where caused it.
However, I have tested another Baichuan PR, it works as expected. Please fix it, otherwise would cause many users confused.

@zhuohan123 that's weird, on my side, when a request come, the output is just a bounch of Tensor print (which I thought it was caused by a exception throw)
I can not see the orignal error since it was tooo long.

its that could possible for multi gpu com problem? Since i found this pr implement using Parellral Linear

Here was the previous error:
baichuan.py", line 138, in forward
    attn_output = self.attn(
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/m/vllm/vllm/model_executor/layers/attention.py", line 328, in forward
    return super().forward(
  File "/m/vllm/vllm/model_executor/layers/attention.py", line 223, in forward
    self.single_query_cached_kv_attention(
  File "/mn/deploy/vllm/vllm/model_executor/layers/attention.py", line 135, in single_query_cached_kv_attention
    attention_ops.single_query_cached_kv_attention(
TypeError: single_query_cached_kv_attention(): incompatible function arguments. The following argument types are supported:
    1. (arg0: torch.Tensor, arg1: torch.Tensor, arg2: torch.Tensor, arg3: torch.Tensor, arg4: float, arg5: torch.Tensor, arg6: torch.Tensor, arg7: int, arg8: int, arg9: Optional[torch.Tensor]) -> None

Invoked with: tensor([[[-1.4512, -0.1887,  0.8198,  ..., -0.5977,  0.0824, -1.0752],
         [ 0.6411,  0.7500,  0.6460,  ...,  1.6650, -0.6650,  1.1973],
         [-0.6343,  1.5195,  0.9277,  ..., -1.3799, -0.4526,  0.1371],
         ...,
         [ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000],
         [ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000],
         [ 0.0000,  0.0000,  0.0000,  ...,  0.0000,  0.0000,  0.0000]]],

Do u know why? I didn't change anything in attention behavior

I think I know why!

@zhuohan123  turns out I have to rebuild cpp files after upgraded.
BTW, may I consult how to get input seq_len in vllm, since I wanna get the seq_len and recache rope sincos values.
For detail：
def forward(
        self,
        positions: torch.Tensor,
        hidden_states: torch.Tensor,
        kv_cache: KVCache,
        input_metadata: InputMetadata,
        cache_event: Optional[torch.cuda.Event],
    ) -> torch.Tensor:
        qkv, _ = self.W_pack(hidden_states)
        q, k, v = qkv.chunk(chunks=3, dim=-1)
        k_cache, v_cache = kv_cache
# How to get seq_len here?
        attn_output = self.attn(
            positions, q, k, v, k_cache, v_cache, input_metadata, cache_event, seq_len=512
        )
        output, _ = self.o_proj(attn_output)
        return output

How to get seq_len at Atten layer. (I printed shapes of each tensor but can really know how to according them to torch side), Can u help?

How to support the Bai Chuan 13B-Chat model?

@lucasjinreal I'm facing the same TypeError issue. What did you do to fix it? You mentioned rebuilding. I completely nuked the source, pulled from github and rebuilt and got the same error.
Thanks

How to support the Bai Chuan 13B-Chat model?

I think baichuan-13b and baichuan-7b are only different in PE, 13b use ALiBi PE and 7b use RoPE, all supported by vLLM, you can replace the PagedAttentionWithRoPE to PagedAttentionWithALiBi and it should work fine.

Did you do a throughput of baichun-7b? I found it much slower than other 7b models.

@zhuohan123 I execute python examples/llm_engine_example.py --model baichuan-inc/Baichuan-7B --trust-remote-code and it works fine.
But when I execute CUDA_VISIBLE_DEVICES=4 python /workdir/vllm/vllm/entrypoints/openai/api_server.py --model baichuan-inc/Baichuan-7B --served-model-name baichuan --trust-remote-code,
(vllm) root@k8s-node-master-38:/workdir# CUDA_VISIBLE_DEVICES=4 python /workdir/vllm/vllm/entrypoints/openai/api_server.py --model baichuan-inc/Baichuan-7B --port 8012 --host <IP_ADDRESS> --served-model-name baichuan --trust-remote-code
INFO 07-19 02:29:17 llm_engine.py:60] Initializing an LLM engine with config: model='baichuan-inc/Baichuan-7B', tokenizer='baichuan-inc/Baichuan-7B', tokenizer_mode=auto, trust_remote_code=True, dtype=torch.float16, use_dummy_weights=False, download_dir=None, use_np_weights=False, tensor_parallel_size=1, seed=0)
WARNING 07-19 02:29:18 tokenizer.py:64] Using a slow tokenizer. This might cause a significant slowdown. Consider using a fast tokenizer instead.
INFO 07-19 02:29:31 llm_engine.py:134] # GPU blocks: 915, # CPU blocks: 512
<class 'bool'> False
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ /workdir/vllm/vllm/transformers_utils/tokenizer.py:36 in get_tokenizer                           │
│                                                                                │
│    33 │   │   │   "tokenizer.")                                                                  │
│    34 │   try:                                                                                │
│    35 │   │   print(type(trust_remote_code), trust_remote_code)                                  │
│ ❱  36 │   │   tokenizer = AutoTokenizer.from_pretrained(                                         │
│    37 │   │   │   tokenizer_name,                                                                │
│    38 │   │   │   *args,                                                                         │
│    39 │   │   │   trust_remote_code=trust_remote_code,                                           │
│                                                                                │
│ /root/anaconda3/envs/vllm/lib/python3.10/site-packages/transformers/models/auto/tokenization_aut │
│ o.py:669 in from_pretrained                                                                      │
│                                                                                │
│   666 │   │   │   tokenizer_class = None                                                         │
│   667 │   │   │   if tokenizer_auto_map is not None:                                             │
│   668 │   │   │   │   if not trust_remote_code:                                                  │
│ ❱ 669 │   │   │   │   │   raise ValueError(                                                      │
│   670 │   │   │   │   │   │   f"Loading {pretrained_model_name_or_path} requires you to execut   │
│   671 │   │   │   │   │   │   " repo on your local machine. Make sure you have read the code t   │
│   672 │   │   │   │   │   │   " then set the option `trust_remote_code=True` to remove this er   │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
ValueError: Loading baichuan-inc/Baichuan-7B requires you to execute the tokenizer file in that repo on your local machine. Make sure you have read
the code there to avoid malicious use, then set the option `trust_remote_code=True` to remove this error.

The above exception was the direct cause of the following exception:

╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ /workdir/vllm/vllm/entrypoints/openai/api_server.py:587 in <module>                              │
│                                                                                │
│   584 │   engine_model_config = asyncio.run(engine.get_model_config())                           │
│   585 │                                                                                │
│   586 │   # A separate tokenizer to map token IDs to strings.                                    │
│ ❱ 587 │   tokenizer = get_tokenizer(engine_args.tokenizer,                                       │
│   588 │   │   │   │   │   │   │     tokenizer_mode=engine_args.tokenizer_mode)                   │
│   589 │                                                                                │
│   590 │   uvicorn.run(app,                                                                       │
│                                                                                │
│ /workdir/vllm/vllm/transformers_utils/tokenizer.py:59 in get_tokenizer                           │
│                                                                                │
│    56 │   │   │   │   "tokenizer not yet available in the HuggingFace transformers "             │
│    57 │   │   │   │   "library, consider setting `trust_remote_code=True` in LLM "               │
│    58 │   │   │   │   "or using the `--trust-remote-code` flag in the CLI.")                     │
│ ❱  59 │   │   │   raise RuntimeError(err_msg) from e                                             │
│    60 │   │   else:                                                                              │
│    61 │   │   │   raise e                                                                        │
│    62                                                                                │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
RuntimeError: Failed to load the tokenizer. If the tokenizer is a custom tokenizer not yet available in the HuggingFace transformers library,
consider setting `trust_remote_code=True` in LLM or using the `--trust-remote-code` flag in the CLI.

Log shows that  --trust-remote-code did set to True, but AutoTokenizer.from_pretrained didn't work well, and if I set the truse_remote-code parameter to True manually, it works fine. It's weird.

How to support the Bai Chuan 13B-Chat model?

I think baichuan-13b and baichuan-7b are only different in PE, 13b use ALiBi PE and 7b use RoPE, both supported by vLLM already. You can replace the PagedAttentionWithRoPE to PagedAttentionWithALiBi and it should work fine.

Thank you for the hint, but how should I specify the slopes argument if I replace PagedAttentionWithRoPE to PagedAttentionWithALiBi?

@o0fatigue Hope this help you.(#512).

Closing this issue as stale as there has been no discussion in the past 3 months.
If you are still experiencing the issue you describe, feel free to re-open this issue.


TCP Support

Would it be possible if you could add an option allowing TCP or UDP? Would be really appreciated.

No, sorry. I understand it has some use cases, but TCP over TCP is generally not a good idea and I don't want users misunderstanding this choice.
For anyone who needs it, switching to TCP is easy enough :)

@aabosh
You can look at
https://github.com/pl48415/openvpn-install-advanced
or my fork
https://github.com/zabullet/openvpn-install-advanced


Move map specific reader code to map module

Description
Refactor subject scheme code for preprocess2 to support all features of subject scheme that preprocess supports. This changes how preprocess2 does filtering. Before preprocess2 map filtering was lazy, meaning it happened at the end of preprocess2 map step. This changes the map filtering to be early, after initial map parsing and mapref merge. It's not as early as in preprocess2 topic processing, because filtering requires reading subject schemes and those are part of the map.
Motivation and Context
Support all subject scheme features in preprocess2 that are supported by preprocess.
How Has This Been Tested?
Existing and new tests.
Type of Changes

New feature (non-breaking change which adds functionality)

Documentation and Compatibility
https://www.dita-ot.org/dev/reference/map-first-preprocessing could mention that since DITA-OT 4.2 preprocess2 supports more subject scheme features.

https://www.dita-ot.org/dev/reference/map-first-preprocessing could mention that since DITA-OT 4.2 preprocess2 supports more subject scheme features.

@jelovirt While it's fresh in your mind: could you provide details on which features?


Fix issues with Lumen

Fix errors when using with Lumen:

namespace of Application class
access to the configuration when defined in config/mangopay.php file

Happy to merge in the Lumen fixes.  But you should revert the change to composer.json

It's done

Thanks!


feat: allow for adding single dimensions in whitelist

right now whitelist only supports compound dimensions, this will help create single dimensions also when using onlyCreatewhiteList

#173 and #174


Pinned snapshot pre release binaries use -SNAPSHOT operator image version

The pre release binaries coming from nightly build must not use -SNAPSHOT operator image versions when doing a yaks install
This leads to image pull errors as -SNAPSHOT image versions are obviously not released to dockerhub or quay.io
The pinned snapshot binaries must use docker.io/yaks/yaks:<pinned-version> as operator image when doing a yaks install

I'd suggest adding this workaround to the README.md for the time being.


Update FRETBursts to 0.8.1

Checklist

[x] Used a fork of the feedstock to propose changes
[x] Bumped the build number (if the version is unchanged)
[x] Reset the build number to 0 (if the version changed)
[ ] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
[ ] Ensured the license file is being packaged.

Moving on to 0.8.2


support injecting single static files into nitro public folder

By default, we could add favicon.ico (1x1 transparent gif) and empty robots.txt if there's no explicit public/ folder. Modules might also want to inject other files (like sw.js).
In order to do this we need support within nitro for injecting single static files into the output.
addAsset('favicon.ico', ...)
addBuildAsset('icon.hash123.png')

See https://github.com/nuxt/framework/discussions/2294#discussioncomment-1756029.

result what for that is needed to alter nitro config some how if I want to add some static files from module or plugin for example?

I added
nitro: {
    serverAssets: [{
      baseName: 'swagger-ui-dist',
      dir: './node_modules/swagger-ui-dist',
    },

and no result for http://localhost:3000/swagger-ui-dist/swagger-ui-bundle.js or http://localhost:3000/api/swagger-ui-dist/swagger-ui-bundle.js

oh, its /assets/bla-bla-bla


Not able to start a smaller network than default

Try to startup a minimal Fabric network instead of the default one. For this, use the modified spec.yaml file to look like -
fabric:
  cas:
  - "ca1.org0.example.com"
  peers:
  - "peer1.org0.example.com"
  - "peer2.org0.example.com"
  orderers:
  - "orderer1.example.com"
  - "orderer2.example.com"
  - "orderer3.example.com"
  settings:
    ca:
      FABRIC_LOGGING_SPEC: DEBUG
    peer:
      FABRIC_LOGGING_SPEC: DEBUG
    orderer:
      FABRIC_LOGGING_SPEC: DEBUG

The Fabric network fails to spawn. Is there something else that needs to be done as well?

Orderer and peer orgs must be different. There is no penalties to have two different orgs for a network. Try to make either your peer or orderer org different, you should be fine. Please close this one since this is not a supported use case.

The below network does spin up -
fabric:
  cas:
  - "ca1.org0.example.com"
  peers:
  - "peer1.org0.example.com"
  - "peer2.org0.example.com"
  orderers:
  - "orderer1.org1.example.com"
  settings:
    ca:
      FABRIC_LOGGING_SPEC: DEBUG
    peer:
      FABRIC_LOGGING_SPEC: DEBUG
    orderer:
      FABRIC_LOGGING_SPEC: DEBUG

Thanks @litong01 for the direction. Closing as the issue stated above is not valid.


Migrate to GitHub Actions

Lints are already failing on travis, but --fatal-infos isn't passed there.

Lints are already failing on travis, but --fatal-infos isn't passed there.

Talked to @sigmundch, and removed the --fatal-infos.

Lints are already failing on travis, but --fatal-infos isn't passed there.

Talked to @sigmundch, and removed the --fatal-infos.


Add game_event and game_event_player fixtures to conftest

###Desired Outcome
one fixture of game_event and game_event_player, reducing the creation of those entities in test files.
Will make the code more readable.
###Implemented Changes
game_event and game_event_player fixtures added to conftest.
Adjustments were made in the relevant test files for change to work: remove game_event and game_event_player from the test files, changed the name from saved_ game_event => game_event, saved_game_event_player => game_event_player.
###Connected Issue/Story
Resolves #82 #81
###Dependencies
This PR does not depend on other PR's
Definition of Done
one game_event and one game_event_player fixture, all the other test files will use those fixtures if needed.
Test coverage
The changes in this PR do not require tests
Documentation
Most of the test files required adjustments.

I like this convention to move all the fixtures to the conftest.
Nicely done.


Change remove-segment-by-id to remove segment

Rename remove-segment-by-id to remove segment
Remove binlog files entries as well
Add segment backup to file before removing it

/kind improvement
Signed-off-by: Congqi Xia<EMAIL_ADDRESS>

/lgtm


Hassio Integration problem

I have the pellet stove (Anselmo Cola) with the same WiFi module. I try to setup the hassio custom component but unfortunately without success.
I can configure the connection with this data:

This is the log:
2021-12-18 23:53:30 ERROR (MainThread) [aiohttp.server] Error handling request Traceback (most recent call last): File "/usr/local/lib/python3.9/site-packages/aiohttp/web_protocol.py", line 435, in _handle_request resp = await request_handler(request) File "/usr/local/lib/python3.9/site-packages/aiohttp/web_app.py", line 504, in _handle resp = await handler(request) File "/usr/local/lib/python3.9/site-packages/aiohttp/web_middlewares.py", line 117, in impl return await handler(request) File "/usr/src/homeassistant/homeassistant/components/http/security_filter.py", line 60, in security_filter_middleware return await handler(request) File "/usr/src/homeassistant/homeassistant/components/http/forwarded.py", line 98, in forwarded_middleware return await handler(request) File "/usr/src/homeassistant/homeassistant/components/http/request_context.py", line 28, in request_context_middleware return await handler(request) File "/usr/src/homeassistant/homeassistant/components/http/ban.py", line 78, in ban_middleware return await handler(request) File "/usr/src/homeassistant/homeassistant/components/http/auth.py", line 181, in auth_middleware return await handler(request) File "/usr/src/homeassistant/homeassistant/components/http/view.py", line 137, in handle result = await result File "/usr/src/homeassistant/homeassistant/components/config/config_entries.py", line 157, in post return await super().post(request, flow_id) File "/usr/src/homeassistant/homeassistant/components/http/data_validator.py", line 62, in wrapper result = await method(view, request, *args, **kwargs) File "/usr/src/homeassistant/homeassistant/helpers/data_entry_flow.py", line 110, in post result = await self._flow_mgr.async_configure(flow_id, data) File "/usr/src/homeassistant/homeassistant/data_entry_flow.py", line 252, in async_configure result = await self._async_handle_step(flow, cur_step["step_id"], user_input) File "/usr/src/homeassistant/homeassistant/data_entry_flow.py", line 325, in _async_handle_step result: FlowResult = await getattr(flow, method)(user_input) File "/config/custom_components/aguaiot/config_flow.py", line 67, in async_step_user await self.hass.async_add_executor_job(agua_iot, api_url, customer_code, email, password, gen_uuid, login_api_url, brand_id) File "/usr/local/lib/python3.9/concurrent/futures/thread.py", line 52, in run result = self.fn(*self.args, **self.kwargs) File "/usr/local/lib/python3.9/site-packages/py_agua_iot/__init__.py", line 92, in __init__ self._login() File "/usr/local/lib/python3.9/site-packages/py_agua_iot/__init__.py", line 96, in _login self.login() File "/usr/local/lib/python3.9/site-packages/py_agua_iot/__init__.py", line 186, in login claimset = jwt.decode(res['token'], verify=False) File "/usr/local/lib/python3.9/site-packages/jwt/api_jwt.py", line 119, in decode decoded = self.decode_complete(jwt, key, algorithms, options, **kwargs) File "/usr/local/lib/python3.9/site-packages/jwt/api_jwt.py", line 86, in decode_complete raise DecodeError( jwt.exceptions.DecodeError: It is required that you pass in a value for the "algorithms" argument when calling decode().
Can some help me to solve or correct this problem, please?

You just need to edit the manifest.json( found in \config\custom_components\aguaiot\manifest.json) by replace this two lines:
  "version": "0.0.7",   "requirements": ["py-agua-iot==0.0.7"],
with:
  "version": "0.0.8",   "requirements": ["py-agua-iot==0.0.8"],

After update HA to core-2022.3.0 the integration stop working with this error:
2022-03-03 02:44:23 ERROR (SyncWorker_4) [homeassistant.util.package] Unable to install package py-agua-iot==0.0.8: ERROR: Cannot install py-agua-iot==0.0.8 because these package versions have conflicting dependencies. ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/topics/dependency-resolution/#dealing-with-dependency-conflicts 2022-03-03 02:44:23 INFO (SyncWorker_0) [homeassistant.util.package] Attempting install of py-agua-iot==0.0.8 2022-03-03 02:44:28 ERROR (SyncWorker_0) [homeassistant.util.package] Unable to install package py-agua-iot==0.0.8: ERROR: Cannot install py-agua-iot==0.0.8 because these package versions have conflicting dependencies. ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/topics/dependency-resolution/#dealing-with-dependency-conflicts 2022-03-03 02:44:28 INFO (SyncWorker_2) [homeassistant.util.package] Attempting install of py-agua-iot==0.0.8 2022-03-03 02:44:33 ERROR (SyncWorker_2) [homeassistant.util.package] Unable to install package py-agua-iot==0.0.8: ERROR: Cannot install py-agua-iot==0.0.8 because these package versions have conflicting dependencies. ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/topics/dependency-resolution/#dealing-with-dependency-conflicts 2022-03-03 02:44:33 ERROR (MainThread) [homeassistant.setup] Setup failed for aguaiot: Requirements for aguaiot not found: ['py-agua-iot==0.0.8'].

same here. Error with the requirements.
Downgraded to previous HA core solved the problem.


Doesn't work on Ubuntu

Doen't pass generator tests. Exiting with message
--- FAIL: TestGenerateZip (0.34s)
    generator_test.go:81: Starting generation for 2 files, 45 pages total...
    generator_test.go:82:
    generator_test.go:87: Compression error: open /tmp/1443131279/2. Вторник.docx: no such file or directory
FAIL
exit status 1
FAIL    github.com/tymbaca/go-yadt      0.340s

It says that this is a compression error. But looks like generator simply didn't create an docx file.

OHH. I forgot about pagemerger tool ahaha. Gonna try to build it at first

Oh yeah. It works now. BUT. Before a came up with that, when i debugging i find out that any error returns of generateFile() and generatePageFile() functions are simply not working. They are GOROUTINES. They cannot return values. Gonna open new issue about that.


connect to AWS s3 bucket

How to connect to AWS s3 bucket, where to change the endpoint? Sorry I checked didn't found out

#90

if you inspect the page and go to local storage you should see something like:
loginUrl: s3.us.cloud-object-storage.appdomain.cloud

if you change that to an aws s3 endpoint you might be able to access the bucket, but also maybe not because Im not using HMAC, I'll hopefully have a feature to make it easier to use other cloud provider buckets in the next release

if you inspect the page and go to local storage you should see something like:
loginUrl: s3.us.cloud-object-storage.appdomain.cloud

if you change that to an aws s3 endpoint you might be able to access the bucket, but also maybe not because Im not using HMAC, I'll hopefully have a feature to make it easier to use other cloud provider buckets in the next release

thanks Nick!! Yes I will try this out and update you here later (for today I need to work for some Spark stuff, so will do it in the middle of this week)


Upload files throught POST.

Hi,
Is it possible to upload a file using the POST method of the resources?
Something like:
myapi.myresource.post(params={'foo': 1},
                      data=open('bar.raw', 'r').read())

Thank you.

Any luck on this issue?

@keithjjones , sorry I never make any progress in the issue and I never will, because we stopped using the library as a dependency in our project (nothing wrong with the library, but our requirements changed)


asserting type of non_empty_string triggers psalm error when asserting known string

Describe the bug
Psalm reports a string is always a string here, but we are checking for a non empty string.
How can I avoid this error?
To Reproduce
<?php

use Psl\SecureRandom;
use Psl\Type;

$prefix = SecureRandom\string(SecureRandom\int(0, 1));

Psl\Invariant(
    !Type\non_empty_string()->matches($prefix),
    'string is empty!',
);

ERROR: TypeDoesNotContainType - test.php:8:1 - Type string for $prefix is always string (see https://psalm.dev/056)
Psl\Invariant(

Expected behavior
No errors
Environment (please complete the following information):

PHP version 8.0
vimeo/psalm:4.10.0
azjezz/psl:1.8.0

Additional context

@azjezz any ideas here?

Hm, i'm taking a look at this, weird thing, when the return type is a TypeInterface, it fails, but when it's NonEmptyStringType, it doesn't 🤔
https://psalm.dev/r/68932ca73c
vs
https://psalm.dev/r/8ecfbcc96a

strange!

ref: https://github.com/vimeo/psalm/issues/6573

since this is a psalm issue, i'm closing it here.


KARAF-4814, Special character in stop script

The stop script contains an   for what should be a regular space.

R: @jbonofre

LGTM

I'm merging on master and 4.0.x.


Please merge revision 19bb19d7162cfae8e9fc1981fc12d8c75a2f83b0 into dev channel

@ricowind @whesse @kasperl
Fixes a heap corruption bug in the VM.
Revisions to be merged:
19bb19d7162cfae8e9fc1981fc12d8c75a2f83b0
This merged cleanly.

Cherry-picked to 1.11.0-dev.5.3, c0e90cb


Issue running tests.

I am having issues running the tests. I keep getting these errors running test.ps1:
ClientAttributeCertificate\KeycloakClientShould.cs(14,51): error CS8306: Tuple element name 'Id' is inferred. Please use language version 7.1 or greater to access an element by its inferred name. [D:\repos\Keycloak.Net\test\Keycloak.Net.Tests\Keycloak.Net.Tests.csproj]
ClientAttributeCertificate\KeycloakClientShould.cs(14,51): error CS8306: Tuple element name 'Key' is inferred. Please use language version 7.1 or greater to access an element by its inferred name. [D:\repos\Keycloak.Net\test\Keycloak.Net.Tests\Keycloak.Net.Tests.csproj]

I have dotnet core sdk 1.1.13 installed:
PS D:\repos\Keycloak.Net\test\Keycloak.Net.Tests> dotnet --info
.NET Command Line Tools (1.1.13)

Product Information:
 Version:            1.1.13
 Commit SHA-1 hash:  b5abece65c

Runtime Environment:
 OS Name:     Windows
 OS Version:  10.0.16299
 OS Platform: Windows
 RID:         win10-x64
 Base Path:   C:\Program Files\dotnet\sdk\1.1.13

Host (useful for support):
  Version: 3.0.0
  Commit:  7d57652f33

.NET Core SDKs installed:
  1.1.13 [C:\Program Files\dotnet\sdk]
  2.0.2 [C:\Program Files\dotnet\sdk]
...

Is there something up with my environment?

You should bump up your SDK version if you want to support C# 7.1 language features. I believe you'll have to go to .NET Core 2.1 or higher.


Apply settings from ovsdb-config file (mounted configmap) via ovs-vsctl

Depends-On: https://github.com/openstack-k8s-operators/dataplane-operator/pull/356

Changes:

switch format of configmap file to yaml
load as facts
apply defaults to external_ids edpm variable
added molecule verify step

recheck etcdserver: request timed out

recheck RETRY_LIMIT

recheck

/lgtm

recheck

recheck

The failure is legit
2023-08-29T16:36:54.475110792+00:00 stdout F TASK [osp.edpm.edpm_ovn : Load ovsdb configuration from file] ******************
2023-08-29T16:36:54.476636615+00:00 stdout F Tuesday 29 August 2023  16:36:54 +0000 (0:00:00.466)       0:00:09.481 ********
2023-08-29T16:36:54.538751534+00:00 stdout F fatal: [edpm-compute-0 -> localhost]: FAILED! => {"ansible_facts": {"edpm_ovn_configmap_facts": {}}, "ansible_included_var_files": [], "changed": false, "message": "Could not find or access '/var/lib/openstack/configs/ovsdb-config' on the Ansible Controller.\nIf you are using a module and expect the file to exist on the remote, see the remote_src option"}

recheck

The failure seems legit, though I haven't seen it before, maybe something broke in tree in flight?
[pod/dataplane-deployment-ovn-edpm-compute-gtrpw/openstackansibleee] TASK [osp.edpm.edpm_ovn : Create persistent directories] ***********************
[pod/dataplane-deployment-ovn-edpm-compute-gtrpw/openstackansibleee] task path: /usr/share/ansible/collections/ansible_collections/osp/edpm/roles/edpm_ovn/tasks/install.yml:17
[pod/dataplane-deployment-ovn-edpm-compute-gtrpw/openstackansibleee] Tuesday 29 August 2023  23:41:39 +0000 (0:00:00.987)       0:00:03.639 ********
[pod/dataplane-deployment-ovn-edpm-compute-gtrpw/openstackansibleee] failed: [edpm-compute-0] (item={'path': '/var/log/containers/openvswitch', 'setype': 'container_file_t', 'mode': '0750'}) => {"ansible_loop_var": "item", "changed": false, "item": {"mode": "0750", "path": "/var/log/containers/openvswitch", "setype": "container_file_t"}, "msg": "There was an issue creating /var/log/containers/openvswitch as requested: [Errno 13] Permission denied: b'/var/log/containers/openvswitch'", "path": "/var/log/containers/openvswitch"}
[pod/dataplane-deployment-ovn-edpm-compute-gtrpw/openstackansibleee] failed: [edpm-compute-0] (item={'path': '/var/log/containers/neutron', 'setype': 'container_file_t', 'mode': '0750'}) => {"ansible_loop_var": "item", "changed": false, "item": {"mode": "0750", "path": "/var/log/containers/neutron", "setype": "container_file_t"}, "msg": "There was an issue creating /var/log/containers/neutron as requested: [Errno 13] Permission denied: b'/var/log/containers/neutron'", "path": "/var/log/containers/neutron"}
[pod/dataplane-deployment-ovn-edpm-compute-gtrpw/openstackansibleee] failed: [edpm-compute-0] (item={'path': '/var/lib/openvswitch/ovn', 'setype': 'container_file_t'}) => {"ansible_loop_var": "item", "changed": false, "item": {"path": "/var/lib/openvswitch/ovn", "setype": "container_file_t"}, "msg": "There was an issue creating /var/lib/openvswitch/ovn as requested: [Errno 13] Permission denied: b'/var/lib/openvswitch/ovn'", "path": "/var/lib/openvswitch/ovn"}

OK, looks like the environment used for molecules is not the same as used for actual ansibleee images, hence failures. How do we make molecule env identical to ansibleee?.. Until we sync the environments somehow, my attempts to fix the CI failures are blind because I can't effectively reproduce the issue.
I can of course build a full cluster and then override edpm-ansible through NFS or otherwise, but that's not very effective, comparing to molecule...

OK, looks like the environment used for molecules is not the same as used for actual ansibleee images, hence failures. How do we make molecule env identical to ansibleee?.. Until we sync the environments somehow, my attempts to fix the CI failures are blind because I can't effectively reproduce the issue.

This looks is happening as different image is used in molecule which have sudo installed https://github.com/openstack-k8s-operators/edpm-ansible/blob/main/molecule/common/Containerfile.j2#L10 vs ansiblee which don't have sudo(https://github.com/openstack-k8s-operators/edpm-ansible/blob/main/openstack_ansibleee/Dockerfile). And with global become: and delegate: localhost tasks it doesn't work

I can of course build a full cluster and then override edpm-ansible through NFS or otherwise, but that's not very effective, comparing to molecule...
Seems same issue could be reproduced by not installing sudo as part of Containerfile.j2? Below reproduces the current issue as seen in CI as sudo is missing in the image.
apiVersion: ansibleee.openstack.org/v1alpha1
kind: OpenStackAnsibleEE
metadata:
name: ansibleee-playbook-local
namespace: openstack
spec:
play: |
- name: Print hello world
hosts: all
become: true
tasks:
- name: Using debug statement
become: false
ansible.builtin.debug:
msg: "Hello, world! This is openstack-ansibleee-play.yaml"
inventory: |
all:
vars:
ansible_connection: local
hosts:
localhost
env:
- name: ANSIBLE_FORCE_COLOR
value: "True"
- name: ANSIBLE_SSH_ARGS
value: "-C -o ControlMaster=auto -o ControlPersist=80s"
- name: ANSIBLE_ENABLE_TASK_DEBUGGER
value: "True"

oc logs job/ansibleee-playbook-local -f

recheck

recheck

recheck

recheck

recheck

/lgtm


Update to RingCentral recipes

As per #23, updates to the RingCentral recipes to download the latest version of RingCentral.

Hello! I think this whole RingCentral issue is a bit more complex than it seemed at first glance.
This recipe, although titled RingCentral, was actually the recipe for the (still current) RingCentral product "RC Phone" (also called RingCentral for Mac.app), which is not in fact at all related to the soon-to-be retired "RingCentral Classic" app (originally called Glip.app) which is being replaced with a newer version simply called RingCentral.app.
The lightweight RC Phone app is a dedicated app to the calling, voicemail and texting features of RingCentral, and lacks all the extra (likely to many people unnecessary/unwanted) features present in the larger RingCentral Classic.app / RingCentral.app, which in addition to calling functionality, attempts to be a bit of a Slack alternative, with team IM, video conferencing, meetings, plugin-apps for third party connections, etc.
This recipe should probably have been renamed some time ago to RingCentral Phone, once the Glip app was renamed RingCentral.app (before being renamed again to RingCentral Classic).
Now that the Classic app is fully going offline, the Classic recipe at psaintmarie Repo should likely be the one to be replaced with a recipe that downloads the primary RingCentral.app.
If RingCentral.app were in fact just an update to the RC Phone/RingCentral for Mac.app, or if the RC Phone app were being retired as the Classic Glip app is, then I would say this recipe change would be fine, however as it stands currently, with this change we'll now have a completely separate application being downloaded than the one people who use this recipe would be expecting.
For reference, here's a full list of the current RC-developed apps:
https://support.ringcentral.com/download.html

Hello! I think this whole RingCentral issue is a bit more complex than it seemed at first glance.
This recipe, although titled RingCentral, was actually the recipe for the (still current) RingCentral product "RC Phone" (also called RingCentral for Mac.app), which is not in fact at all related to the soon-to-be retired "RingCentral Classic" app (originally called Glip.app) which is being replaced with a newer version simply called RingCentral.app.
The lightweight RC Phone app is a dedicated app to the calling, voicemail and texting features of RingCentral, and lacks all the extra (likely to many people unnecessary/unwanted) features present in the larger RingCentral Classic.app / RingCentral.app, which in addition to calling functionality, attempts to be a bit of a Slack alternative, with team IM, video conferencing, meetings, plugin-apps for third party connections, etc.
This recipe should probably have been renamed some time ago to RingCentral Phone, once the Glip app was renamed RingCentral.app (before being renamed again to RingCentral Classic).
Now that the Classic app is fully going offline, the Classic recipe at psaintmarie Repo should likely be the one to be replaced with a recipe that downloads the primary RingCentral.app.
If RingCentral.app were in fact just an update to the RC Phone/RingCentral for Mac.app, or if the RC Phone app were being retired as the Classic Glip app is, then I would say this recipe change would be fine, however as it stands currently, with this change we'll now have a completely separate application being downloaded than the one people who use this recipe would be expecting.
For reference, here's a full list of the current RC-developed apps:
https://support.ringcentral.com/download.html

@Balthamos thanks for this review! I've consequently created a new PR (https://github.com/autopkg/bradclare-recipes/pull/25) that brings back the original recipes and changes a few details to better denote the app that they're for. This way, we don't need to make any additional changes to the RingCentral classic recipes at psaintemarie-recipes. How does this sound? Would be good to get your review before @bradclare approves this PR.
Thanks!

@Balthamos thanks for this review! I've consequently created a new PR (https://github.com/autopkg/bradclare-recipes/pull/25) that brings back the original recipes and changes a few details to better denote the app that they're for. This way, we don't need to make any additional changes to the RingCentral classic recipes at psaintemarie-recipes. How does this sound? Would be good to get your review before @bradclare approves this PR.
Thanks!

Also, I don't use Munki, so it would be great to test these Munki recipes and make any necessary changes.

Also, I don't use Munki, so it would be great to test these Munki recipes and make any necessary changes.

Just wanted to step in and give @Balthamos some extra kudos. That was a very thorough and helpful breakdown! ⭐

Just wanted to step in and give @Balthamos some extra kudos. That was a very thorough and helpful breakdown! ⭐

This looks good, thank you!
I tested the Munki Recipe's and they're both working properly. The only thing I might potentially change is the %NAME% key in the Munki recipe from "RingCentral Phone" to "RingCentralPhone". Don't think it makes any real difference but it seems like the norm is to have spaces in the display_name but not in the NAME/name variables?
Also, for both recipes, although this and the name thing above are easily fixable with the Recipe Override, it wouldn't hurt to have defaults set for
<key>developer</key> <string>RingCentral</string> <key>category</key> <string>Communication</string>
Finally, I'm not entirely clear on why the following is now lacking but maybe one of you can enlighten me:
Previously, the override I was using to import the RingCentral.app into Munki would provide pkginfo keys for
<key>blocking_applications</key> <array> <string>RingCentral.app</string> </array>
and an Installs array for the installed app, and now there's just a package receipt, but no Installs item.
From the looks of it, I wonder if it's because this Munki references as its parent the download.ringcentral recipe, whereas what I was using previously references the pkg.ringcentral recipe with the following Process arguments:
<key>Process</key> 	<array> 		<dict> 			<key>Arguments</key> 			<dict> 				<key>faux_root</key> 				<string>%RECIPE_CACHE_DIR%/%NAME%</string> 				<key>installs_item_paths</key> 				<array> 					<string>/Applications/RingCentral.app</string> 				</array> 			</dict> 			<key>Processor</key> 			<string>MunkiInstallsItemsCreator</string> 		</dict> 		<dict> 			<key>Processor</key> 			<string>MunkiPkginfoMerger</string> 		</dict> 		<dict> 			<key>Arguments</key> 			<dict> 				<key>repo_subdirectory</key> 				<string>%MUNKI_REPO_SUBDIR%</string> 			</dict> 			<key>Processor</key> 			<string>MunkiImporter</string> 		</dict> 	</array>
Anyway, thanks again for so quickly jumped on this!

This looks good, thank you!
I tested the Munki Recipe's and they're both working properly. The only thing I might potentially change is the %NAME% key in the Munki recipe from "RingCentral Phone" to "RingCentralPhone". Don't think it makes any real difference but it seems like the norm is to have spaces in the display_name but not in the NAME/name variables?
Also, for both recipes, although this and the name thing above are easily fixable with the Recipe Override, it wouldn't hurt to have defaults set for
<key>developer</key> <string>RingCentral</string> <key>category</key> <string>Communication</string>
Finally, I'm not entirely clear on why the following is now lacking but maybe one of you can enlighten me:
Previously, the override I was using to import the RingCentral.app into Munki would provide pkginfo keys for
<key>blocking_applications</key> <array> <string>RingCentral.app</string> </array>
and an Installs array for the installed app, and now there's just a package receipt, but no Installs item.
From the looks of it, I wonder if it's because this Munki references as its parent the download.ringcentral recipe, whereas what I was using previously references the pkg.ringcentral recipe with the following Process arguments:
<key>Process</key> 	<array> 		<dict> 			<key>Arguments</key> 			<dict> 				<key>faux_root</key> 				<string>%RECIPE_CACHE_DIR%/%NAME%</string> 				<key>installs_item_paths</key> 				<array> 					<string>/Applications/RingCentral.app</string> 				</array> 			</dict> 			<key>Processor</key> 			<string>MunkiInstallsItemsCreator</string> 		</dict> 		<dict> 			<key>Processor</key> 			<string>MunkiPkginfoMerger</string> 		</dict> 		<dict> 			<key>Arguments</key> 			<dict> 				<key>repo_subdirectory</key> 				<string>%MUNKI_REPO_SUBDIR%</string> 			</dict> 			<key>Processor</key> 			<string>MunkiImporter</string> 		</dict> 	</array>
Anyway, thanks again for so quickly jumped on this!


Revert renaming method onMaster() and offMaster() in interface LocalNodeMasterListener

Description
Revert renaming method onMaster() and offMaster() in interface LocalNodeMasterListener
I didn't realize that the onMaster() and offMaster() is exposed to the public, then renamed it directly to make the method name inclusive. The classes that implement the interface need to implement the method in new name, so it breaks backwards compatibility.
The original file: https://github.com/opensearch-project/OpenSearch/blob/2.0.1/server/src/main/java/org/opensearch/cluster/LocalNodeMasterListener.java
Issues Resolved
https://github.com/opensearch-project/OpenSearch/issues/3688
Check List

[ ] New functionality includes testing.

[ ] All tests pass

[ ] New functionality has been documented.

[ ] New functionality has javadoc added

[ ] Commits are signed per the DCO using --signoff

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
For more information on following Developer Certificate of Origin and signing off your commits, please check here.

In log 6281:
> Task :plugins:repository-s3:yamlRestTest

REPRODUCE WITH: ./gradlew ':plugins:repository-s3:yamlRestTest' --tests "org.opensearch.repositories.s3.RepositoryS3ClientYamlTestSuiteIT.test {yaml=repository_s3/20_repository_permanent_credentials/Snapshot and Restore with repository-s3 using permanent credentials}" -Dtests.seed=7AAB1C43DFD5610D -Dtests.security.manager=true -Dtests.jvm.argline="-XX:TieredStopAtLevel=1 -XX:ReservedCodeCacheSize=64m" -Dtests.locale=el-GR -Dtests.timezone=Europe/Busingen -Druntime.java=17 -Dtests.rest.denylist=repository_s3/30_repository_temporary_credentials/*,repository_s3/40_repository_ec2_credentials/*,repository_s3/50_repository_ecs_credentials/*,repository_s3/60_repository_eks_credentials/*

org.opensearch.repositories.s3.RepositoryS3ClientYamlTestSuiteIT > test {yaml=repository_s3/20_repository_permanent_credentials/Snapshot and Restore with repository-s3 using permanent credentials} FAILED
    java.lang.AssertionError: Failure at [repository_s3/20_repository_permanent_credentials:257]: expected [2xx] status code but api [snapshot.delete] returned [500 Internal Server Error] [{"error":{"root_cause":[{"type":"repository_exception","reason":"[repository_permanent] concurrent modification of the index-N file, expected current generation [5761] but it was not found in the repository","stack_trace":"RepositoryException[[repository_permanent] concurrent modification of the index-N file, expected current generation [5761] but it was not found in the repository]\n\tat org.opensearch.repositories.blobstore.BlobStoreRepository.ensureSafeGenerationExists(BlobStoreRepository.java:2142)\n\tat org.opensearch.repositories.blobstore.BlobStoreRepository.lambda$writeIndexGen$55(BlobStoreRepository.java:2023)\n\tat org.opensearch.action.ActionListener$1.onResponse(ActionListener.java:80)\n\tat org.opensearch.common.util.concurrent.ListenableFuture$1.doRun(ListenableFuture.java:126)\n\tat
...

start gradle check

This PR has been backported to 2.1 branch in PR https://github.com/opensearch-project/OpenSearch/pull/3687 / commit https://github.com/opensearch-project/OpenSearch/commit/8aadcc056513a2edf21978d2c9a2f41756d8366c

@tlfeng do you want to revert this main?
I understand it makes sense for 2.x line.

@saratvemulapalli I want to merge in main as well to reduce the code difference between branches, and it will make me have a clear mind on the whole process 😄.
Besides, there is a chance that the non-inclusive public Java API will not be removed in version 3.0, so I think making this part of code the same on all branches is better.

@saratvemulapalli Thanks a lot for your review! 👍


Fix for caching on stim paths

Added test for caching as well.
Resolves #284

Coverage decreased (-0.1%) to 93.787% when pulling 42c49955ccb9bc8faa17c9f2aa0068d2e666b99c on path-caching into 64285d30b3fbcda0d46a726fd126e11f7ed0af4d on master.


Add Company Name

Description
This PR displays the company name.
EDIT: The company name of the demo@ in this example is the Enterprise—not the Developer. Will need to revisit.
Type of change

[ ] Bug fix / chore (non-breaking change that fixes an issue)
[ ] New feature (non-breaking change that adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)

Related PRs / Issues
Asana links
Testing plan

maybe just make it "SaaS Co"?


Using own training set

Can you train both the Vanilla and the DCN networks with your own data set or some data set like ImageNet for example. and If so how would you do it? for both Pytorch and Tensorflow.

any luck with this?

Use data loaders for pytorch, and costumize them accordingly (for example change image size according to your dataset)
Data loaders example:https://pytorch.org/tutorials/beginner/data_loading_tutorial.html

Hi, @i-am-mel-dev is correct. You can create a new loader to put the data in!


AWS S3 preventing pulling pictures?

I proved my Twitter, Facebook, and GitHub, and the MacOS Client and the web still aren't showing my picture, and the MacOS Client isn't showing my email as verified.
Is this all due to the AWS S3 issues today?

Looks like it fixed itself.  Now it's just a curiousity :)


Javascript

JavaScript
User Story
As a boot camp student
I want the prework notes to be structured on a webpage
So that I can easily find and read the information
Acceptance Criteria
GIVEN a Prework Study Guide website
WHEN I view the study guide
THEN I can see the four topics I learned listed along with a suggestion on what I should study first

Added the javascript file with variables and functions


[DF] Importing Context attempts to load server components

I've just built the datafusion-sql-planner branch from source in a fairly stripped down conda environment.
On trying to: from dask_sql import Context, I got errors about missing uvicorn:
>>> from dask_sql import Context
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/studio-lab-user/.conda/envs/dsql/lib/python3.9/site-packages/dask_sql/__init__.py", line 6, in <module>
    from .server.app import run_server
  File "/home/studio-lab-user/.conda/envs/dsql/lib/python3.9/site-packages/dask_sql/server/app.py", line 7, in <module>
    import uvicorn
ModuleNotFoundError: No module named 'uvicorn'
>>>

Surprisingly, this is from the server code. Does it seem like something's wrong with my build, or is it expected to load Dask-SQL server code when trying to create a Context?

Looks like something might be wrong in your build here - I'm seeing uvicorn listed as a dependency both in our setup file and conda recipes.
I will note that thinking about how to wrap imports like this conditionally is definitely part of the work that would go into separating the server out into an optional component of the packages, xref #435

For future reference to others, python setup.py install wont complain about missing dependencies.
conda install -c conda-forge uvicorn fastapi fixed this issue for me.


Add servo node config to disable advertising /get_planning_scene

Disables the servo node from advertising /get_planning_scene, which in the default launchfile, conflicts with move_group's /get_planning_scene. See https://github.com/moveit/moveit2/issues/2731 for discussion.
Tested on a Humble branch.

Thank you @mrjogo that change seems reasonable. I'll check it and come back to this.

I just tested this and it seems to be fine. If you don't mind, I would include this commit into #998 for jazzy/rolling. This PR here would then be targeting iron and humble only.

Sounds good. Let me know if you need me to do anything for that.

@Mergifyio backport humble


Template/Generic Compilation

I mentioned this over the phone, however, I found a temporary solution and would like some input on why it was necessary.
The problem stems from a generic LinkedList implementation I made:
template<typename T>
class LinkedListRoot {
   public:
   LinkedList<T>* root = NULL;
   LinkedListRoot();
   ~LinkedListRoot();
   void addNode(T val);

   private:
   LinkedList<T>* tail = NULL;
};

When this was implemented in pong-menu.h and pong-menu.cpp (where it was used), everything worked fine. However, when I was setting up a new class for rendering centered text I moved it to extra.h and extra.cpp so it could be used among multiple files. When I did this, I started getting the following linking errors:
wasm-ld: error: out/pong-menu.o: undefined symbol: LinkedListRoot<MenuButton>::LinkedListRoot()
wasm-ld: error: out/pong-menu.o: undefined symbol: LinkedListRoot<MenuButton>::addNode(MenuButton)
wasm-ld: error: out/pong-menu.o: undefined symbol: LinkedListRoot<MenuButton>::addNode(MenuButton)
wasm-ld: error: out/pong-menu.o: undefined symbol: LinkedListRoot<MenuButton>::addNode(MenuButton)
wasm-ld: error: out/entry-point.o: undefined symbol: LinkedListRoot<MenuButton>::~LinkedListRoot()

I found that moving the MenuButton struct into extra.h and adding:
template class LinkedListRoot<MenuButton>;

to extra.cpp fixed it.
I was wondering if you knew what might be causing the explicit declaration to be necessary and if there's any other way I could fix this?

I figured out that putting all of the function definitions in the header fixed the issue. I'm still not quite sure why it's necessary, but it's a better solution than needing to define every variant of the class in extra.cpp.

I had answered this in a different issue.  https://github.com/twiddlingbits/twr-wasm/issues/14. Here is what I found:

However, I keep getting linking issues with it. Do you know what might be causing these?

chatGPT says: https://chatgpt.com/share/66f9d97d-481c-800a-9372-c31f27465483
Here is what I wrote before I aske chatGPT, but I haven't really used templates in c++ (i do use them in typescript):
If you show me the code (commit it, or provide a link, or whatever), i can take a look.
But I will say that in the past whenever I have tried to put actual code in a .h file it has never ended well and I always end up putting it in a .cpp file (and the class detentions in a .h file, like canvas.cpp). When it's in the .h, then you end up with name collision (same name compiled into multiple .o). I think you can work around it with appropriate use of inline, but that seems to be very fragile and confusing. I gave up getting it to work the one time i tried recently. You could make the code static, which might avoid the collision. But then you still have multiple copies of the same code, which doesn't seem clean, and there are probably other issues.

i sent you an email with an intro to don, who can explain this in detail.

please close this if you think its fixed.


[sw] Cleanup boot_rom/crt0.S.

This change makes crt0.S conform to the uncontentious parts of the assembly style guide proposed in #1067.
I also changed the exact registers used in some places to be less rude about the calling convention (I think the old version uses callee-saved registers without saving them).

Does the tail synthetic inject a PC-relative load for the call that's pushing the rest of the calls down?

This seems likely. In this case, I think using j <symbol> should do the right thing, as these jumps have to be short jumps (because they must fit into a single instruction).

Oops. Should be fixed now!