change "color-clear-night" and other divs bgcolor

Hi All,
I would like to change --color-clear-night default color within the card style. I can't achieve this, can someone help how to do this?
I assuming this should work but not:
card_mod:   style: |     .clear-night {       background-color: #f00 !important       }
I can hardcore into in JS, but its not so elegant solution.
Many thanks,
Zoltan

Hi Zoltan, you should be able to use the colors option in yaml config to achieve this. See the docs here: https://github.com/decompil3d/lovelace-hourly-weather#color-options

Thanks, sorry, I overthinked it!


Transparency effects do not work in 1.8 Beta

Hello, after some quick tests with 1.8 beta, I've discovered that none of the effects under background work correctly, aside from auto. Setting it to 1 through 5 makes all context menus look like this:

Then, when I also tune opacity alongside, it looks like this:

The menu does go transparent, ish.
When I use opacity with the effect set to auto, there is no transparency at all, and the menu is fully opaque.

Increasing the opacity will cause the transparency to fade
theme
{
    background
    {
        opacity = 0 // transparent background
        effect = ["acrylic", auto, 50]
    }

    item
    {
        back
        {
            normal = 0	// transparent
            normal-disabled = 0
        }
    }
}

mica and tabbed not supported yet. only transparent, blur, and acrylic

https://nilesoft.org/blog/shell-version-1-8-beta


Updating swagger spec with changes due to PR#5407

PR generated by running hack/update-swagger-spec.sh

LGTM


Support n-dim input in fc layer

For now, fc layer support 2-dim input(batch, 1, 1, width).
NNTrainer needs to support n-dim input in fc layer.
This might be helpful. (https://numpy.org/doc/stable/reference/generated/numpy.matmul.html)
According to the description

If either argument is N-D, N > 2, it is treated as a stack of matrices residing in the last two indexes and broadcast accordingly.

:octocat: cibot: Thank you for posting issue #1924. The person in charge will reply soon.

This is done with https://github.com/nnstreamer/nntrainer/pull/1927.


buildpack dependency fix

There is an apparent dependency issue with yarn buildpack
On a simple repo with yarn.lock, it fails and yarn.lock is ignored. This leads to another buildpack group (with npm) to take over the build.
Result is that whether or not yarn.lock is present, application is always built using npm.
Some pack output demonstrating the issue:
✦ ❯❯❯ pack build -v small-yarn -b heroku/nodejs-engine -b heroku/nodejs-yarn
Builder cr.nrtn.dev/heroku/buildpacks:b8c5d04e is trusted
Pulling image cr.nrtn.dev/heroku/buildpacks:b8c5d04e
b8c5d04e: Pulling from heroku/buildpacks
Digest: sha256:79b3131b2f67bce8030fe1824574e4d37d24a7da365233681b65fbc904f2baf4
Status: Image is up to date for cr.nrtn.dev/heroku/buildpacks:b8c5d04e
Selected run image cr.nrtn.dev/infra/pack:20
Pulling image cr.nrtn.dev/infra/pack:20
20: Pulling from infra/pack
Digest: sha256:f774b9e6c779c6e7e168ae5b01eb8f78f393dcc8d02ba88eb22e2e5697f31a5e
Status: Image is up to date for cr.nrtn.dev/infra/pack:20
Setting custom order
Creating builder with the following buildpacks:
-><EMAIL_ADDRESS>-><EMAIL_ADDRESS>-><EMAIL_ADDRESS>-><EMAIL_ADDRESS>-><EMAIL_ADDRESS>-><EMAIL_ADDRESS>-><EMAIL_ADDRESS>-><EMAIL_ADDRESS>-><EMAIL_ADDRESS>-><EMAIL_ADDRESS>-><EMAIL_ADDRESS>-><EMAIL_ADDRESS>-><EMAIL_ADDRESS>-><EMAIL_ADDRESS>Using build cache volume pack-cache-library_small-yarn_latest-7623b5239096.build
Running the creator on OS linux with:
Container Settings:
  Args: /cnb/lifecycle/creator -daemon -launch-cache /launch-cache -log-level debug -cache-dir /cache -run-image cr.nrtn.dev/infra/pack:20 -process-type web small-yarn
  System Envs: CNB_PLATFORM_API=0.4
  Image: pack.local/builder/6e617364706f77646c74:latest
  User: root
  Labels: map[author:pack]
Host Settings:
  Binds: pack-cache-library_small-yarn_latest-7623b5239096.build:/cache /var/run/docker.sock:/var/run/docker.sock pack-cache-library_small-yarn_latest-7623b5239096.launch:/launch-cache pack-layers-fmxwuijyaj:/layers pack-app-qbkxereudo:/workspace
  Network Mode:
===> DETECTING
======== Results ========
pass<EMAIL_ADDRESS>pass<EMAIL_ADDRESS>Resolving plan... (try #1)
fail<EMAIL_ADDRESS>provides unused node
ERROR: No buildpack groups passed detection.
ERROR: Please check that you are running against the correct path.
ERROR: failed to detect: no buildpacks participating
ERROR: failed to build: executing lifecycle: failed with status code: 100

Without specific buildpacks and using full set, the group with npm takes over after this issue.
This pull request adds plan dependency on node similar to npm buildpack, that allows yarn to succeed in detection

Have you found a workaround for the issue until this gets merged? We are experiencing the same problem, even while just using the heroku/nodejs buildpack: Its using npm instead of yarn.

Hi @sawmurai
I use heroku stacks on my premises, so it was a bit easier to just fix it.
Without modification of buildpacks i didn't find any sensible way to trigger heroku stacks use yarn builder i'm afraid
But I can imagine you can call yarn workflows from npm scripts explicitly, and that way just bypass heroku logic

It looks like shell format checking is failing for the PR due to the newline:
$ brew install shfmt
$ shfmt -f . | grep -v ^test/ | grep -v '_shpec.sh$' | xargs shfmt -w
$ git diff
diff --git a/buildpacks/yarn/lib/detect.sh b/buildpacks/yarn/lib/detect.sh
index 8e40dd1..2522bc3 100644
--- a/buildpacks/yarn/lib/detect.sh
+++ b/buildpacks/yarn/lib/detect.sh
@@ -17,4 +17,4 @@ write_to_build_plan() {
        [[requires]]
        name = "node"
 EOF
-}
\ No newline at end of file
+}

The output took me a second to realize what was going on:
--- buildpacks/yarn/lib/detect.sh.orig
+++ buildpacks/yarn/lib/detect.sh

Isn't super helpful, maybe we could have it write and generate a diff on failure in the future?

I figured out that lined ending, thank you, but i don't get what's wrong with changelog now. Diff on my end shows it's in the list 🤔

Oh I see, checkout action is not pulling main branch ref, but there is a diff against it. Seems like related to recent action update here https://github.com/heroku/buildpacks-nodejs/blob/main/.github/workflows/check_changelog.yml#L16
Looks like in v2 they do not checkout main head ref :(

I've rebased against latest main :)

Thanks @noroutine -- I've been pushing each of your commits so they trigger CI. I've got my fingers crossed for this commit =P.

@joshwlewis @noroutine Hi! The Yarn cutlass test can now be updated to remove the manually specified yarn buildpack, and rely just on the main nodejs meta-buildpack:
https://github.com/heroku/buildpacks-nodejs/blob/d727ef98c3c4b43d3d862541dc43e4490e8a460c/test/specs/node/cutlass/basic_spec.rb#L26-L28

Hey @edmorley
Updated :) Catch another PR for that https://github.com/heroku/buildpacks-nodejs/pull/109

@noroutine Thank you! I'll leave to Josh to review (new Node.js owner).


Hook up WGD run attribute overrides

Sets attribute overrides for the WGD workflow.

LGTM, thanks for fixing this!


Why not try to be an all-platform music downloader?

Why not try to be an all-platform music downloader?
I think this project has a big future.
Come on! Waiter!🎉

No, that's a violation of the project purpose. This will not be work on.

O !  No! Developer Abandoned me!😥

You can fork this and DIY though. He's got the main part done and all you need to do is to write a simple GUI and get it ready for download. Looking forward to your project.
-------- Original message --------
From: 雾削木 @.>
Date: Sat, Mar 13, 2021, 16:47
To: M4TEC/PenguinPlayer @.>
Cc: Subscribed @.***>
Subject: Re: [M4TEC/PenguinPlayer] Why not try to be an all-platform music downloader? (#14)
O ! No! Developer Abandoned me!😥
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHubhttps://github.com/M4TEC/PenguinPlayer/issues/14#issuecomment-797965018, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AIOHJT2NE27UMIMRPUXLVOTTDMRAHANCNFSM4ZDRHJCA.

您可以对此进行分叉和DIY。他已经完成了主要部分，您所需要做的就是编写一个简单 GUI并准备好进行下载。期待您的项目。
…
-------- Original message -------- From: 雾削木 @.> Date: Sat, Mar 13, 2021, 16:47 To: M4TEC/PenguinPlayer @.> Cc: Subscribed @.***> Subject: Re: [M4TEC/PenguinPlayer] Why not try to be an all-platform music downloader? (#14) O ! No! Developer Abandoned me!😥 — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub<#14 (comment)>, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AIOHJT2NE27UMIMRPUXLVOTTDMRAHANCNFSM4ZDRHJCA.

That's not a good idea.
The Lord thinks you are more suitable.
Looking forward to your food.🎮

这波机翻是我没想到的🤣
发送自 Windows 10 版邮件https://go.microsoft.com/fwlink/?LinkId=550986应用
发件人: @.>
发送时间: 2021年3月13日 18:57
收件人: @.>
抄送: Leo Lingfeng @.>; @.>
主题: Re: [M4TEC/PenguinPlayer] Why not try to be an all-platform music downloader? (#14)
您可以对此进行分叉和DIY。他已经完成了主要部分，您所需要做的就是编写一个简单 GUI并准备好进行下载。期待您的项目。
…
-------- Original message -------- From: 雾削木 @.> Date: Sat, Mar 13, 2021, 16:47 To: M4TEC/PenguinPlayer @.> Cc: Subscribed @.***> Subject: Re: [M4TEC/PenguinPlayer] Why not try to be an all-platform music downloader? (#14https://github.com/M4TEC/PenguinPlayer/issues/14) O ! No! Developer Abandoned me!😥 — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub<#14 (comment)https://github.com/M4TEC/PenguinPlayer/issues/14#issuecomment-797965018>, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AIOHJT2NE27UMIMRPUXLVOTTDMRAHANCNFSM4ZDRHJCA.
That's not a good idea.
The Lord thinks you are more suitable.
Looking forward to your food.🎮
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHubhttps://github.com/M4TEC/PenguinPlayer/issues/14#issuecomment-798152593, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AIOHJTZ43KAKSE777FBQ3BTTDNAKTANCNFSM4ZDRHJCA.

这波机翻是我没想到的🤣 发送自 Windows 10 版邮件<https://go.microsoft.com/fwlink/?LinkId=550986>应用 发件人: @.> 发送时间: 2021年3月13日 18:57 收件人: @.> 抄送: Leo Lingfeng @.>; @.> 主题: Re: [M4TEC/PenguinPlayer] Why not try to be an all-platform music downloader? (#14) 您可以对此进行分叉和DIY。他已经完成了主要部分，您所需要做的就是编写一个简单 GUI并准备好进行下载。期待您的项目。 … -------- Original message -------- From: 雾削木 @.> Date: Sat, Mar 13, 2021, 16:47 To: M4TEC/PenguinPlayer @.> Cc: Subscribed @.***> Subject: Re: [M4TEC/PenguinPlayer] Why not try to be an all-platform music downloader? (#14<#14>) O ! No! Developer Abandoned me!😥 — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub<#14 (comment)<#14 (comment)>>, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AIOHJT2NE27UMIMRPUXLVOTTDMRAHANCNFSM4ZDRHJCA. That's not a good idea. The Lord thinks you are more suitable. Looking forward to your food.🎮 — You are receiving this because you commented. Reply to this email directly, view it on GitHub<#14 (comment)>, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AIOHJTZ43KAKSE777FBQ3BTTDNAKTANCNFSM4ZDRHJCA.

Oh! Are you Chinese too?

这波机翻是我没想到的🤣 发送自 Windows 10 版邮件<https://go.microsoft.com/fwlink/?LinkId=550986>应用 发件人: @.> 发送时间: 2021年3月13日 18:57 收件人<EMAIL_ADDRESS>抄送: Leo Lingfeng<EMAIL_ADDRESS>@._> 主题: Re: [M4TEC/PenguinPlayer] Why not try to be an all-platform music downloader? (#14) 您可以对此进行分叉和DIY。他已经完成了主要部分，您所需要做的就是编写一个简单 GUI并准备好进行下载。期待您的项目。 … -------- Original message -------- From: 雾削木 @.> Date: Sat, Mar 13, 2021, 16:47 To: M4TEC/PenguinPlayer @.> Cc: Subscribed @.*> Subject: Re: [M4TEC/PenguinPlayer] Why not try to be an all-platform music downloader? (#14<#14>) O ! No! Developer Abandoned me!😥 — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub<#14 (comment)<#14 (comment)>>, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AIOHJT2NE27UMIMRPUXLVOTTDMRAHANCNFSM4ZDRHJCA. That's not a good idea. The Lord thinks you are more suitable. Looking forward to your food.🎮 — You are receiving this because you commented. Reply to this email directly, view it on GitHub<#14 (comment)>, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AIOHJTZ43KAKSE777FBQ3BTTDNAKTANCNFSM4ZDRHJCA.

Oh! Are you Chinese too?

He's alien.


I²C for u8g2 with ssd1306

Adding i²C to the u8g2_esp32_hal and include a sample task

still don't know why the i²C have to be set (0x3C)
still don't know why the I²C commandcode have to be added (0x00 or 0x40)

There are reports coming in that this commit broke the SPI usage ...
From the IRC #ESP32 chatroom ...
<bleader> kolban: apparently pcbreflux commit in u8g2_esp32_hal breaks spi
<bleader> there is a chunk of code removed, that leaves the spi handle unitiliazed
<bleader> went back to a version before his commit and managed to get the hello world working
<bleader> (crazy how having a screen displaying text can make a man happy...)


Typer as only CLI option

Typer: https://typer.tiangolo.com/
Example: https://github.com/audreyfeldroy/cookiecutter-pypackage/blob/47f3d4df4973d92cd4ff5ae4fbb38bd9b061c2ca/{{cookiecutter.project_slug}}/src/{{cookiecutter.project_slug}}/cli.py

Duplicated #51


Doc Improvements

Answering these questions will probably just need doc improvements rather than other fixes, but I'm not sure so here goes:

Using cargo profiler callgrindwhich executable is run?
How does this work with cargo bench? Can I run cargo profiler --bench callgrind (or something like that) to get profile stats for the different benchmarks? For now I've been creating a main.rs building that (with debug symbols) and then using cargo profiler callgrind -n 20 --bin ./target/release/executable_name. I swap out the contents of main with my benchmarks to get results. This seems suboptimal. I'm probably missing something.
It's probably worth calling out specifically that -n <count> limits the shown instructions. That wasn't immediately clear.

Thanks.

The profiled binary comes from the build command.
Normally, rust benchmarks are separate binaries running with or without the --bench flag. This means, you can profile benchmars using the --bin flag (optionally with command line arguments via --)


Error in "Generate Installer" Step on Windows when Plugin Formats do not Include Standalone

Description:
When attempting to generate the installer on Windows, if the plugin formats do not include the Standalone format, I encounter an error. The error message is as follows:
Source file "D:\a\ ... \Release\Standalone\myplugin.exe" does not exist.

BTW, is AAX supported on Windows?

Where is the error encountered?
If you modify the formats you are building, you'll have to modify the packaging setup too. For windows, that means removing the standalone line from packaging/installer.iss

I see, Thank you!


Shadows

Added shadows.py

I adjusted the camera position, ball scale, and added a lot more materials.


"Assign name to window" doesnt do anithing

Describe the bug
It doesnt do anithing actually
MUST DO SOMETHING!!!
Screenshots

WAIT A SECOND..... IT ACTUALY WORKS.....!!!!! NEVERMIND


[FLINK-8230] [ORC] Improved mapping of Orc records to Flink Table rows.

What is the purpose of the change
Improved mapping of Orc records to Flink table rows and ensured nested structs are correctly mapped.
Brief change log

Introduced OrcRowReader to be used on a single input split
OrcRowReader was adapted from org.apache.orc.mapred.OrcMapredRecordReader
Added a bunch of test datasets, mostly from orc distribution

Verifying this change
This change added tests and can be verified as follows:

OrcRowReaderTest maps test datasets to rows comparing count
OrcRowReader is also covered by existing flink-orc unit tests.
Manually verified the change by running a 4 node cluster on YARN, reading an existing full dataset

Does this pull request potentially affect one of the following parts:

Dependencies (does it add or upgrade a dependency): no
The public API, i.e., is any changed class annotated with @Public(Evolving): no
The serializers: don't know
The runtime per-record code paths (performance sensitive): yes
Anything that affects deployment or recovery: JobManager (and its components), Checkpointing, Yarn/Mesos, ZooKeeper: don't know
The S3 file system connector: no

Documentation

Does this pull request introduce a new feature? no
If yes, how is the feature documented? not applicable

@twalthr Sure. And thanks to @fhueske for fixing the existing IF.


Fix: Button - Defaulting to small broke some props

!large ... conditional placement was ignoring fontSize and buttonStyles props

thanks @mcnamee !


Hide class  from document symbols

This prevents <static-init> for classes from showing in the document symbols outline. <static-init> is a Sorbet construction that we don't want to confuse the user with.
It also adds a comment in a place that confused me.
Motivation
To fix bugs.
Test plan
Updated the exp files.
(When updating the exp files, some tests of the flavor //gems/sorbet/test/snapshot:update_ruby_* failed.)

@DarkDimius Looking into it.


Track Covers

Add option to download cover to the album directory and to tracks metadata.

I thought of just commenting on the open issue instead, for the lacking metadata. if possible, please have look into the tags like Recorded date and URL to be included. this help in keep track of the download url and id personally.
the following is just an example for the metadata.
I downloaded the following track using this tool: QobuzDownloaderX-MOD
Sofia Carson - Come Back Home (From Purple Hearts Soundtrack Version).zip


[kafka_confluent] should propagate partitionkey on an event level

Issue
Currently you have to interact with https://github.com/cloudevents/sdk-go/blob/7fef294789916760157377cb07dc5bd55d31e562/protocol/kafka_confluent/v2/option.go#L137-L151 to set the partition key on an outgoing event. If you have multiple events are you sending on a single context you have to keep swapping values.
Proposal
I propose that the paradigm from kafka_sarama is copied over where it checks to see if the partition key is set on an a cloud event extension, if it is, set that on the outgoing record. https://github.com/cloudevents/sdk-go/blob/f1c0d0aac5ac90027b6e5504a44a14fa8f1985d9/protocol/kafka_sarama/v2/write_producer_message.go#L38-L48

tagging @yanmxa for thoughts since i seen you wrote the implementation of https://github.com/cloudevents/sdk-go/pull/988

Thanks @bread-amammay!
I see that both implementations use the same way to inject the partitionKey for the Sender. The difference is that the sarma implementation also adds partitionKey by event extension. But what if the key exists in both context and extension?
I agree with the idea of supporting the partitionKey at the event level.  But we need to document their priorities.


Support For Elasticsearch 7.0.1

Summary:

Added Support For Elasticsearch 7.0.1

Testing:

All Unit Tests Pass

+1


Support for default values in Request

Hi, first of all, thanks for writing such a nice macros.
There was one thing that I found disappointing.
The Swift syntax does not allow you to set default values for parameters in protocol functions.
If it's a normal protocol function, you can set the default value of the function parameter through an extension, but since it's a macro, it doesn't seem possible.
I don't know much about macros, but here's what I can think of.

@API
protocol Users {
  @GET("/users")
  func getList(size: Int = 20, cursor: String?) async throws -> [User]

  @POST("/user")
  func createUser(email: String, password: String, nickname: String? = nil) async throws
}

If it is possible to have an implementation that violates Swift syntax like the one above with just a macros, then the above seems to be the most convenient and reasonable.

@API
protocol Users {
  @GET("/users")
  func getList(@Default(20) size: Int, cursor: String?) async throws -> [User]

  @POST("/user")
  func createUser(email: String, password: String, @Default(nil) nickname: String?) async throws
}

Looking at the comments in the code and the post at, it seems that this is probably not possible at the moment, as there is no macros specification. If a spec is added in the future, this would be fine.
In addition to this, if there is a way to do this in the current implementation without a new one, I'd to hear about it!

Thanks for suggestion @PangMo5 - I'd definitely love if we could support this!
At one point I actually had the @Default functionality as you suggested but unfortunately we lost the ability to do that in the Xcode 15 Beta update that post you linked is about.
Also unfortunately, Swift doesn't support either default arguments (your first example) or property wrappers in protocol definitions yet. I don't believe there is another way to do it, otherwise I'd be very open to it. If you have any ideas of how this could be accomplished let me know!
For now, however, you can achieve the desired effect using (albeit verbose) extensions.
@API
protocol Users {
  @GET("/users")
  func getList(size: Int, cursor: String?) async throws -> [User]

  @POST("/user")
  func createUser(email: String, password: String, nickname: String?) async throws
}

extension Users {
    func getList(size: Int = 20, cursor: String?) async throws -> [User] {
        try await getList(size: size, cursor: cursor)
    }

    func createUser(email: String, password: String, nickname: String? = nil) async throws {
        try await createUser(email: email, password: password, nickname: nickname)
    }
}

Again - this is pretty verbose and I think your first example is the ideal solution, but default arguments aren't currently allowed in protocols.

@joshuawright11 ,
Is it possible to generate such Users extension by something like that?
@API
protocol Users {
  @GET("/users", defaults: ["size": 20])
  func getList(size: Int, cursor: String?) async throws -> [User]

  @POST("/user", defaults: ["nickname": nil])
  func createUser(email: String, password: String, nickname: String?) async throws
}

Looks not very type safe but probably we can match keys from defaults with endpoint's ages and verify values with appropriate types as well (and throw error if needed).


Temperature converter

Website to convert temperatures in any form within Celsius, Fahrenheit and Kelvin

Assign this to me for hacktoberfest please

@Im-postor Assign to you

i'll love to work on this issue...
Please do assign it to me :)


Add CI builds

I've added configuration for travis builds covering linux and OSX.
If accepted, the maintainers have to press a button at https://travis-ci.org to activate.
This change is motivated because in #560 I apparently created a build issue that I can't reproduce.
Incidentally, I find that OSX builds currently fail on io.aeron.MemoryOrderingTest. I've marked OSX as allowed to fail in the submission for now.

Thanks @lukepalmer. I've been considering adding a CI build for Aeron. I have some concerns about sufficient CPUs being available for the system tests for example.
If we add the support for C/C++ then the C driver should also be built and with a matrix of compilers. The build for SBE could serve as a template. https://github.com/real-logic/simple-binary-encoding/blob/master/.travis.yml

Compiler matrix sounds reasonable, I can take a shot at that.
Note that the submitted change does do both the java and C/C++ builds. So far, the system test does appear to work reliably on the 2 cores travis gives us.
Is the OS X failure known? Here's an example build. It's consistent.
https://travis-ci.org/lukepalmer/aeron/builds/446126370

The build failure is a timeout. Likely due to insufficient CPU resource. I also note it is building with Java 10.0.1 rather than 8.

Ok there we are. All linux builds for now, but we have Oracle JDK 8 and 11 and a full range of C/C++ builds.
I did see a single timeout failures on JDK11 but worked all other times.

Thanks. I've swapped Oracle JDK 11 for OpenJDK 11 and all seems to be passing now.


llama3.2-1b-base gives 'RuntimeError: no tokenizer was found'

🐛 Describe the bug
I'm following the basic 5+1 line instructions to get torchchat going with llama3.2-1b-base and it fails with RuntimeError: no tokenizer was found at /home/tonyr/.torchchat/model-cache/meta-llama/Meta-Llama-3.2-1B/tokenizer.model.  The 6 lines I'm using are from the README.md:
git clone https://github.com/pytorch/torchchat.git
cd torchchat
python3 -m venv .venv
source .venv/bin/activate
./install/install_requirements.sh
python3 torchchat.py generate llama3.2-1b-base --prompt "write me a story about a boy and his bear"

I also have llama3.2-3b-base which exhibits the same behaviour.  Full logs are below, note I already have llama3.2-1b-base downloaded:
(.venv) think1 tonyr: ls -lta /home/tonyr/.torchchat/model-cache/meta-llama/Meta-Llama-3.2-1B/
total 2424908
drwxrwxr-x 4 tonyr tonyr       4096 Dec  8 20:45 ..
drwxrwxr-x 4 tonyr tonyr       4096 Dec  8 20:40 .
drwxrwxr-x 2 tonyr tonyr       4096 Dec  8 20:40 original
-rw-rw-r-- 1 tonyr tonyr<PHONE_NUMBER> Dec  8 20:40 model.pth
-rw-rw-r-- 1 tonyr tonyr    9085657 Dec  8 20:38 tokenizer.json
-rw-rw-r-- 1 tonyr tonyr    2183982 Dec  8 20:38 tokenizer.model
-rw-rw-r-- 1 tonyr tonyr       1519 Dec  8 20:38 .gitattributes
-rw-rw-r-- 1 tonyr tonyr      50500 Dec  8 20:38 tokenizer_config.json
-rw-rw-r-- 1 tonyr tonyr        301 Dec  8 20:38 special_tokens_map.json
-rw-rw-r-- 1 tonyr tonyr        185 Dec  8 20:38 generation_config.json
-rw-rw-r-- 1 tonyr tonyr       7712 Dec  8 20:38 LICENSE.txt
-rw-rw-r-- 1 tonyr tonyr        843 Dec  8 20:38 config.json
-rw-rw-r-- 1 tonyr tonyr      41239 Dec  8 20:38 README.md
-rw-rw-r-- 1 tonyr tonyr       6021 Dec  8 20:38 USE_POLICY.md
drwxrwxr-x 3 tonyr tonyr       4096 Dec  8 20:38 .cache

Also note, there is a warning in the logs:
+ python3 torchchat/utils/scripts/patch_triton.py
/home/tonyr/torchchat/torchchat/utils/scripts/patch_triton.py:20: SyntaxWarning: invalid escape sequence '\s'
  new_match = 'self.src = self.src[re.search(r"^def\s+\w+\s*\(", self.src, re.MULTILINE).start():]'

and here is the full log, the interesting bit is at the end.
think1 tonyr: git clone https://github.com/pytorch/torchchat.git
Cloning into 'torchchat'...
remote: Enumerating objects: 14722, done.
remote: Counting objects: 100% (2820/2820), done.
remote: Compressing objects: 100% (598/598), done.
remote: Total 14722 (delta 2458), reused 2358 (delta 2211), pack-reused 11902 (from 1)
Receiving objects: 100% (14722/14722), 8.87 MiB | 24.88 MiB/s, done.
Resolving deltas: 100% (8755/8755), done.
think1 tonyr: cd torchchat
think1 tonyr: python3 -m venv .venv
think1 tonyr: source .venv/bin/activate
(.venv) think1 tonyr: ./install/install_requirements.sh
Using python executable: python3
Using pip executable: pip3
+ pip3 install -r install/requirements.txt --extra-index-url https://download.pytorch.org/whl/nightly/cu121
Looking in indexes: https://pypi.org/simple, https://download.pytorch.org/whl/nightly/cu121
Ignoring tomli: markers 'python_version < "3.11"' don't match your environment
Collecting huggingface_hub (from -r install/requirements.txt (line 4))
  Using cached huggingface_hub-0.26.5-py3-none-any.whl.metadata (13 kB)
Collecting gguf (from -r install/requirements.txt (line 7))
  Using cached gguf-0.10.0-py3-none-any.whl.metadata (3.5 kB)
Collecting tiktoken (from -r install/requirements.txt (line 10))
  Using cached https://download.pytorch.org/whl/nightly/tiktoken-0.8.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.2 MB)
[ deleted loads more Collecting .. Using cached ]]
Using cached chardet-5.2.0-py3-none-any.whl.metadata (3.4 kB)
Using cached lm_eval-0.4.2-py3-none-any.whl (1.4 MB)
Using cached huggingface_hub-0.26.5-py3-none-any.whl (447 kB)

Using cached smmap-5.0.1-py3-none-any.whl (24 kB)
Using cached yarl-1.18.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (336 kB)
Installing collected packages: zstd, word2number, sqlitedict, sentencepiece, pytz, mpmath, zstandard, xxhash, wheel, watchdog, urllib3, tzdata, typing-extensions, tqdm, tornado, toml, threadpoolctl, tenacity, tcolorpy, tabulate, sympy, sniffio, smmap, six, setuptools, safetensors, rpds-py, regex, pyyaml, pygments, pycryptodomex, pybind11, pyarrow, psutil, protobuf, propcache, portalocker, pillow, pathvalidate, packaging, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, numpy, ninja, networkx, narwhals, multidict, more-itertools, mdurl, MarkupSafe, lxml, joblib, jiter, itsdangerous, idna, h11, fsspec, frozenlist, filelock, distro, dill, colorama, cmake, click, charset-normalizer, chardet, certifi, cachetools, blinker, attrs, annotated-types, aiohappyeyeballs, absl-py, yarl, Werkzeug, triton, tqdm-multiprocess, snakeviz, scipy, sacrebleu, requests, referencing, python-dateutil, pydantic-core, nvidia-cusparse-cu12, nvidia-cudnn-cu12, numexpr, nltk, multiprocess, mbstrdecoder, markdown-it-py, jsonlines, Jinja2, httpcore, gitdb, gguf, blobfile, anyio, aiosignal, typepy, tiktoken, scikit-learn, rouge-score, rich, pydeck, pydantic, pandas, nvidia-cusolver-cu12, jsonschema-specifications, huggingface_hub, httpx, gitpython, flask, aiohttp, torch, tokenizers, openai, jsonschema, transformers, datasets, DataProperty, altair, accelerate, tabledata, streamlit, peft, evaluate, pytablewriter, lm_eval
Successfully installed DataProperty-1.0.1 Jinja2-3.1.4 MarkupSafe-3.0.2 Werkzeug-3.1.3 absl-py-2.1.0 accelerate-1.2.0 aiohappyeyeballs-2.4.4 aiohttp-3.11.10 aiosignal-1.3.1 altair-5.5.0 annotated-types-0.7.0 anyio-4.7.0 attrs-24.2.0 blinker-1.9.0 blobfile-3.0.0 cachetools-5.5.0 certifi-2024.8.30 chardet-5.2.0 charset-normalizer-3.4.0 click-8.1.7 cmake-3.31.1 colorama-0.4.6 datasets-3.1.0 dill-0.3.8 distro-1.9.0 evaluate-0.4.3 filelock-3.16.1 flask-3.1.0 frozenlist-1.5.0 fsspec-2024.9.0 gguf-0.10.0 gitdb-4.0.11 gitpython-3.1.43 h11-0.14.0 httpcore-1.0.7 httpx-0.28.1 huggingface_hub-0.26.5 idna-3.10 itsdangerous-2.2.0 jiter-0.8.2 joblib-1.4.2 jsonlines-4.0.0 jsonschema-4.23.0 jsonschema-specifications-2024.10.1 lm_eval-0.4.2 lxml-5.3.0 markdown-it-py-3.0.0 mbstrdecoder-1.1.3 mdurl-0.1.2 more-itertools-10.5.0 mpmath-1.3.0 multidict-6.1.0 multiprocess-0.70.16 narwhals-1.16.0 networkx-3.4.2 ninja-<IP_ADDRESS> nltk-3.9.1 numexpr-2.10.2 numpy-1.26.4 nvidia-cublas-cu12-<IP_ADDRESS> nvidia-cuda-cupti-cu12-12.4.127 nvidia-cuda-nvrtc-cu12-12.4.127 nvidia-cuda-runtime-cu12-12.4.127 nvidia-cudnn-cu12-<IP_ADDRESS> nvidia-cufft-cu12-<IP_ADDRESS> nvidia-curand-cu12-<IP_ADDRESS> nvidia-cusolver-cu12-<IP_ADDRESS> nvidia-cusparse-cu12-<IP_ADDRESS> nvidia-nccl-cu12-2.21.5 nvidia-nvjitlink-cu12-12.4.127 nvidia-nvtx-cu12-12.4.127 openai-1.57.1 packaging-24.2 pandas-2.2.3 pathvalidate-3.2.1 peft-0.14.0 pillow-11.0.0 portalocker-3.0.0 propcache-0.2.1 protobuf-5.29.1 psutil-6.1.0 pyarrow-18.1.0 pybind11-2.13.6 pycryptodomex-3.21.0 pydantic-2.10.3 pydantic-core-2.27.1 pydeck-0.9.1 pygments-2.18.0 pytablewriter-1.2.0 python-dateutil-2.9.0.post0 pytz-2024.2 pyyaml-6.0.2 referencing-0.35.1 regex-2024.11.6 requests-2.32.3 rich-13.9.4 rouge-score-0.1.2 rpds-py-0.22.3 sacrebleu-2.4.3 safetensors-0.4.5 scikit-learn-1.6.0 scipy-1.14.1 sentencepiece-0.2.0 setuptools-75.6.0 six-1.17.0 smmap-5.0.1 snakeviz-2.2.2 sniffio-1.3.1 sqlitedict-2.1.0 streamlit-1.40.2 sympy-1.13.1 tabledata-1.3.3 tabulate-0.9.0 tcolorpy-0.1.6 tenacity-9.0.0 threadpoolctl-3.5.0 tiktoken-0.8.0 tokenizers-0.21.0 toml-0.10.2 torch-2.5.1 tornado-6.4.2 tqdm-4.67.1 tqdm-multiprocess-0.0.11 transformers-4.47.0 triton-3.1.0 typepy-1.3.2 typing-extensions-4.12.2 tzdata-2024.2 urllib3-2.2.3 watchdog-6.0.0 wheel-0.45.1 word2number-1.1 xxhash-3.5.0 yarl-1.18.3 zstandard-0.23.0 zstd-<IP_ADDRESS>
+ pip3 uninstall -y triton
Found existing installation: triton 3.1.0
Uninstalling triton-3.1.0:
  Successfully uninstalled triton-3.1.0
+ pip3 install --extra-index-url https://download.pytorch.org/whl/nightly/cu121 torch==2.6.0.dev20241013 torchvision==0.20.0.dev20241013 torchtune==0.4.0.dev20241013
Looking in indexes: https://pypi.org/simple, https://download.pytorch.org/whl/nightly/cu121
Collecting torch==2.6.0.dev20241013
  Downloading https://download.pytorch.org/whl/nightly/cu121/torch-2.6.0.dev20241013%2Bcu121-cp312-cp312-linux_x86_64.whl (783.6 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 783.6/783.6 MB 1.3 MB/s eta 0:00:00
Collecting torchvision==0.20.0.dev20241013
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchvision-0.20.0.dev20241013%2Bcu121-cp312-cp312-linux_x86_64.whl (7.4 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 7.4/7.4 MB 10.2 MB/s eta 0:00:00
Collecting torchtune==0.4.0.dev20241013
  Downloading https://download.pytorch.org/whl/nightly/cu121/torchtune-0.4.0.dev20241013%2Bcu121-py3-none-any.whl (577 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 577.4/577.4 kB 1.8 MB/s eta 0:00:00
Requirement already satisfied: filelock in ./.venv/lib/python3.12/site-packages (from torch==2.6.0.dev20241013) (3.16.1)
Requirement already satisfied: typing-extensions>=4.8.0 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0.dev20241013) (4.12.2)
Requirement already satisfied: networkx in ./.venv/lib/python3.12/site-packages (from torch==2.6.0.dev20241013) (3.4.2)
Requirement already satisfied: jinja2 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0.dev20241013) (3.1.4)
Requirement already satisfied: fsspec in ./.venv/lib/python3.12/site-packages (from torch==2.6.0.dev20241013) (2024.9.0)
Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch==2.6.0.dev20241013)
  Using cached https://download.pytorch.org/whl/nightly/cu121/nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)
Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch==2.6.0.dev20241013)
  Using cached https://download.pytorch.org/whl/nightly/cu121/nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)
Collecting nvidia-cuda-cupti-cu12==12.1.105 (from torch==2.6.0.dev20241013)
  Using cached https://download.pytorch.org/whl/nightly/cu121/nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB)
Requirement already satisfied: nvidia-cudnn-cu12==<IP_ADDRESS> in ./.venv/lib/python3.12/site-packages (from torch==2.6.0.dev20241013) (<IP_ADDRESS>)
Collecting nvidia-cublas-cu12==<IP_ADDRESS> (from torch==2.6.0.dev20241013)
  Using cached https://download.pytorch.org/whl/nightly/cu121/nvidia_cublas_cu12-<IP_ADDRESS>-py3-none-manylinux1_x86_64.whl (410.6 MB)
Collecting nvidia-cufft-cu12==<IP_ADDRESS> (from torch==2.6.0.dev20241013)
  Using cached https://download.pytorch.org/whl/nightly/cu121/nvidia_cufft_cu12-<IP_ADDRESS>-py3-none-manylinux1_x86_64.whl (121.6 MB)
Collecting nvidia-curand-cu12==<IP_ADDRESS> (from torch==2.6.0.dev20241013)
  Using cached https://download.pytorch.org/whl/nightly/cu121/nvidia_curand_cu12-<IP_ADDRESS>-py3-none-manylinux1_x86_64.whl (56.5 MB)
Collecting nvidia-cusolver-cu12==<IP_ADDRESS> (from torch==2.6.0.dev20241013)
  Using cached https://download.pytorch.org/whl/nightly/cu121/nvidia_cusolver_cu12-<IP_ADDRESS>-py3-none-manylinux1_x86_64.whl (124.2 MB)
Collecting nvidia-cusparse-cu12==<IP_ADDRESS> (from torch==2.6.0.dev20241013)
  Using cached https://download.pytorch.org/whl/nightly/cu121/nvidia_cusparse_cu12-<IP_ADDRESS>-py3-none-manylinux1_x86_64.whl (196.0 MB)
Requirement already satisfied: nvidia-nccl-cu12==2.21.5 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0.dev20241013) (2.21.5)
Collecting nvidia-nvtx-cu12==12.1.105 (from torch==2.6.0.dev20241013)
  Using cached https://download.pytorch.org/whl/nightly/cu121/nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)
Collecting pytorch-triton==3.1.0+cf34004b8a (from torch==2.6.0.dev20241013)
  Using cached https://download.pytorch.org/whl/nightly/pytorch_triton-3.1.0%2Bcf34004b8a-cp312-cp312-linux_x86_64.whl (239.6 MB)
Requirement already satisfied: setuptools in ./.venv/lib/python3.12/site-packages (from torch==2.6.0.dev20241013) (75.6.0)
Requirement already satisfied: sympy==1.13.1 in ./.venv/lib/python3.12/site-packages (from torch==2.6.0.dev20241013) (1.13.1)
Requirement already satisfied: numpy in ./.venv/lib/python3.12/site-packages (from torchvision==0.20.0.dev20241013) (1.26.4)
Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in ./.venv/lib/python3.12/site-packages (from torchvision==0.20.0.dev20241013) (11.0.0)
Requirement already satisfied: datasets in ./.venv/lib/python3.12/site-packages (from torchtune==0.4.0.dev20241013) (3.1.0)
Requirement already satisfied: huggingface-hub in ./.venv/lib/python3.12/site-packages (from torchtune==0.4.0.dev20241013) (0.26.5)
Requirement already satisfied: safetensors in ./.venv/lib/python3.12/site-packages (from torchtune==0.4.0.dev20241013) (0.4.5)
Requirement already satisfied: sentencepiece in ./.venv/lib/python3.12/site-packages (from torchtune==0.4.0.dev20241013) (0.2.0)
Requirement already satisfied: tiktoken in ./.venv/lib/python3.12/site-packages (from torchtune==0.4.0.dev20241013) (0.8.0)
Requirement already satisfied: blobfile>=2 in ./.venv/lib/python3.12/site-packages (from torchtune==0.4.0.dev20241013) (3.0.0)
Requirement already satisfied: tqdm in ./.venv/lib/python3.12/site-packages (from torchtune==0.4.0.dev20241013) (4.67.1)
Collecting omegaconf (from torchtune==0.4.0.dev20241013)
  Using cached https://download.pytorch.org/whl/nightly/omegaconf-2.3.0-py3-none-any.whl (79 kB)
Requirement already satisfied: psutil in ./.venv/lib/python3.12/site-packages (from torchtune==0.4.0.dev20241013) (6.1.0)
Requirement already satisfied: nvidia-nvjitlink-cu12 in ./.venv/lib/python3.12/site-packages (from nvidia-cusolver-cu12==<IP_ADDRESS>->torch==2.6.0.dev20241013) (12.4.127)
Requirement already satisfied: mpmath<1.4,>=1.1.0 in ./.venv/lib/python3.12/site-packages (from sympy==1.13.1->torch==2.6.0.dev20241013) (1.3.0)
Requirement already satisfied: pycryptodomex>=3.8 in ./.venv/lib/python3.12/site-packages (from blobfile>=2->torchtune==0.4.0.dev20241013) (3.21.0)
Requirement already satisfied: urllib3<3,>=1.25.3 in ./.venv/lib/python3.12/site-packages (from blobfile>=2->torchtune==0.4.0.dev20241013) (2.2.3)
Requirement already satisfied: lxml>=4.9 in ./.venv/lib/python3.12/site-packages (from blobfile>=2->torchtune==0.4.0.dev20241013) (5.3.0)
Requirement already satisfied: pyarrow>=15.0.0 in ./.venv/lib/python3.12/site-packages (from datasets->torchtune==0.4.0.dev20241013) (18.1.0)
Requirement already satisfied: dill<0.3.9,>=0.3.0 in ./.venv/lib/python3.12/site-packages (from datasets->torchtune==0.4.0.dev20241013) (0.3.8)
Requirement already satisfied: pandas in ./.venv/lib/python3.12/site-packages (from datasets->torchtune==0.4.0.dev20241013) (2.2.3)
Requirement already satisfied: requests>=2.32.2 in ./.venv/lib/python3.12/site-packages (from datasets->torchtune==0.4.0.dev20241013) (2.32.3)
Requirement already satisfied: xxhash in ./.venv/lib/python3.12/site-packages (from datasets->torchtune==0.4.0.dev20241013) (3.5.0)
Requirement already satisfied: multiprocess<0.70.17 in ./.venv/lib/python3.12/site-packages (from datasets->torchtune==0.4.0.dev20241013) (0.70.16)
Requirement already satisfied: aiohttp in ./.venv/lib/python3.12/site-packages (from datasets->torchtune==0.4.0.dev20241013) (3.11.10)
Requirement already satisfied: packaging in ./.venv/lib/python3.12/site-packages (from datasets->torchtune==0.4.0.dev20241013) (24.2)
Requirement already satisfied: pyyaml>=5.1 in ./.venv/lib/python3.12/site-packages (from datasets->torchtune==0.4.0.dev20241013) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.venv/lib/python3.12/site-packages (from jinja2->torch==2.6.0.dev20241013) (3.0.2)
Collecting antlr4-python3-runtime==4.9.* (from omegaconf->torchtune==0.4.0.dev20241013)
  Using cached antlr4_python3_runtime-4.9.3-py3-none-any.whl
Requirement already satisfied: regex>=2022.1.18 in ./.venv/lib/python3.12/site-packages (from tiktoken->torchtune==0.4.0.dev20241013) (2024.11.6)
Requirement already satisfied: aiohappyeyeballs>=2.3.0 in ./.venv/lib/python3.12/site-packages (from aiohttp->datasets->torchtune==0.4.0.dev20241013) (2.4.4)
Requirement already satisfied: aiosignal>=1.1.2 in ./.venv/lib/python3.12/site-packages (from aiohttp->datasets->torchtune==0.4.0.dev20241013) (1.3.1)
Requirement already satisfied: attrs>=17.3.0 in ./.venv/lib/python3.12/site-packages (from aiohttp->datasets->torchtune==0.4.0.dev20241013) (24.2.0)
Requirement already satisfied: frozenlist>=1.1.1 in ./.venv/lib/python3.12/site-packages (from aiohttp->datasets->torchtune==0.4.0.dev20241013) (1.5.0)
Requirement already satisfied: multidict<7.0,>=4.5 in ./.venv/lib/python3.12/site-packages (from aiohttp->datasets->torchtune==0.4.0.dev20241013) (6.1.0)
Requirement already satisfied: propcache>=0.2.0 in ./.venv/lib/python3.12/site-packages (from aiohttp->datasets->torchtune==0.4.0.dev20241013) (0.2.1)
Requirement already satisfied: yarl<2.0,>=1.17.0 in ./.venv/lib/python3.12/site-packages (from aiohttp->datasets->torchtune==0.4.0.dev20241013) (1.18.3)
Requirement already satisfied: charset-normalizer<4,>=2 in ./.venv/lib/python3.12/site-packages (from requests>=2.32.2->datasets->torchtune==0.4.0.dev20241013) (3.4.0)
Requirement already satisfied: idna<4,>=2.5 in ./.venv/lib/python3.12/site-packages (from requests>=2.32.2->datasets->torchtune==0.4.0.dev20241013) (3.10)
Requirement already satisfied: certifi>=2017.4.17 in ./.venv/lib/python3.12/site-packages (from requests>=2.32.2->datasets->torchtune==0.4.0.dev20241013) (2024.8.30)
Requirement already satisfied: python-dateutil>=2.8.2 in ./.venv/lib/python3.12/site-packages (from pandas->datasets->torchtune==0.4.0.dev20241013) (2.9.0.post0)
Requirement already satisfied: pytz>=2020.1 in ./.venv/lib/python3.12/site-packages (from pandas->datasets->torchtune==0.4.0.dev20241013) (2024.2)
Requirement already satisfied: tzdata>=2022.7 in ./.venv/lib/python3.12/site-packages (from pandas->datasets->torchtune==0.4.0.dev20241013) (2024.2)
Requirement already satisfied: six>=1.5 in ./.venv/lib/python3.12/site-packages (from python-dateutil>=2.8.2->pandas->datasets->torchtune==0.4.0.dev20241013) (1.17.0)
Installing collected packages: antlr4-python3-runtime, pytorch-triton, omegaconf, nvidia-nvtx-cu12, nvidia-cusparse-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusolver-cu12, torch, torchvision, torchtune
  Attempting uninstall: nvidia-nvtx-cu12
    Found existing installation: nvidia-nvtx-cu12 12.4.127
    Uninstalling nvidia-nvtx-cu12-12.4.127:
      Successfully uninstalled nvidia-nvtx-cu12-12.4.127
  Attempting uninstall: nvidia-cusparse-cu12
    Found existing installation: nvidia-cusparse-cu12 <IP_ADDRESS>
    Uninstalling nvidia-cusparse-cu12-<IP_ADDRESS>:
      Successfully uninstalled nvidia-cusparse-cu12-<IP_ADDRESS>
  Attempting uninstall: nvidia-curand-cu12
    Found existing installation: nvidia-curand-cu12 <IP_ADDRESS>
    Uninstalling nvidia-curand-cu12-<IP_ADDRESS>:
      Successfully uninstalled nvidia-curand-cu12-<IP_ADDRESS>
  Attempting uninstall: nvidia-cufft-cu12
    Found existing installation: nvidia-cufft-cu12 <IP_ADDRESS>
    Uninstalling nvidia-cufft-cu12-<IP_ADDRESS>:
      Successfully uninstalled nvidia-cufft-cu12-<IP_ADDRESS>
  Attempting uninstall: nvidia-cuda-runtime-cu12
    Found existing installation: nvidia-cuda-runtime-cu12 12.4.127
    Uninstalling nvidia-cuda-runtime-cu12-12.4.127:
      Successfully uninstalled nvidia-cuda-runtime-cu12-12.4.127
  Attempting uninstall: nvidia-cuda-nvrtc-cu12
    Found existing installation: nvidia-cuda-nvrtc-cu12 12.4.127
    Uninstalling nvidia-cuda-nvrtc-cu12-12.4.127:
      Successfully uninstalled nvidia-cuda-nvrtc-cu12-12.4.127
  Attempting uninstall: nvidia-cuda-cupti-cu12
    Found existing installation: nvidia-cuda-cupti-cu12 12.4.127
    Uninstalling nvidia-cuda-cupti-cu12-12.4.127:
      Successfully uninstalled nvidia-cuda-cupti-cu12-12.4.127
  Attempting uninstall: nvidia-cublas-cu12
    Found existing installation: nvidia-cublas-cu12 <IP_ADDRESS>
    Uninstalling nvidia-cublas-cu12-<IP_ADDRESS>:
      Successfully uninstalled nvidia-cublas-cu12-<IP_ADDRESS>
  Attempting uninstall: nvidia-cusolver-cu12
    Found existing installation: nvidia-cusolver-cu12 <IP_ADDRESS>
    Uninstalling nvidia-cusolver-cu12-<IP_ADDRESS>:
      Successfully uninstalled nvidia-cusolver-cu12-<IP_ADDRESS>
  Attempting uninstall: torch
    Found existing installation: torch 2.5.1
    Uninstalling torch-2.5.1:
      Successfully uninstalled torch-2.5.1
Successfully installed antlr4-python3-runtime-4.9.3 nvidia-cublas-cu12-<IP_ADDRESS> nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cufft-cu12-<IP_ADDRESS> nvidia-curand-cu12-<IP_ADDRESS> nvidia-cusolver-cu12-<IP_ADDRESS> nvidia-cusparse-cu12-<IP_ADDRESS> nvidia-nvtx-cu12-12.1.105 omegaconf-2.3.0 pytorch-triton-3.1.0+cf34004b8a torch-2.6.0.dev20241013+cu121 torchtune-0.4.0.dev20241013+cu121 torchvision-0.20.0.dev20241013+cu121
+ pip3 install torchao==0.5.0
Collecting torchao==0.5.0
  Using cached torchao-0.5.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (12 kB)
Using cached torchao-0.5.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB)
Installing collected packages: torchao
Successfully installed torchao-0.5.0
+ python3 torchchat/utils/scripts/patch_triton.py
/home/tonyr/torchchat/torchchat/utils/scripts/patch_triton.py:20: SyntaxWarning: invalid escape sequence '\s'
  new_match = 'self.src = self.src[re.search(r"^def\s+\w+\s*\(", self.src, re.MULTILINE).start():]'
+ pip3 install evaluate==0.4.3 lm-eval==0.4.2 psutil==6.0.0
Requirement already satisfied: evaluate==0.4.3 in ./.venv/lib/python3.12/site-packages (0.4.3)
Requirement already satisfied: lm-eval==0.4.2 in ./.venv/lib/python3.12/site-packages (0.4.2)
Collecting psutil==6.0.0
  Using cached psutil-6.0.0-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (21 kB)
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Using cached psutil-6.0.0-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (290 kB)
Installing collected packages: psutil
  Attempting uninstall: psutil
    Found existing installation: psutil 6.1.0
    Uninstalling psutil-6.1.0:
      Successfully uninstalled psutil-6.1.0
Successfully installed psutil-6.0.0
(failed reverse-i-search)`download': llama model ^Cwnload --source meta --model-id Llama3.2-3B
(.venv) think1 tonyr: python3 torchchat.py list

Model                                        Aliases                                                    Downloaded
-------------------------------------------- ---------------------------------------------------------- -----------
meta-llama/llama-2-7b-hf                     llama2-base, llama2-7b
meta-llama/llama-2-7b-chat-hf                llama2, llama2-chat, llama2-7b-chat
meta-llama/llama-2-13b-chat-hf               llama2-13b-chat
meta-llama/llama-2-70b-chat-hf               llama2-70b-chat
meta-llama/meta-llama-3-8b                   llama3-base
meta-llama/meta-llama-3-8b-instruct          llama3, llama3-chat, llama3-instruct
meta-llama/meta-llama-3-70b-instruct         llama3-70b
meta-llama/meta-llama-3.1-8b                 llama3.1-base
meta-llama/meta-llama-3.1-8b-instruct        llama3.1, llama3.1-chat, llama3.1-instruct
meta-llama/meta-llama-3.1-70b-instruct       llama3.1-70b
meta-llama/meta-llama-3.1-8b-instruct-tune   llama3.1-tune, llama3.1-chat-tune, llama3.1-instruct-tune
meta-llama/meta-llama-3.1-70b-instruct-tune  llama3.1-70b-tune
meta-llama/meta-llama-3.2-1b                 llama3.2-1b-base                                           Yes
meta-llama/meta-llama-3.2-1b-instruct        llama3.2-1b, llama3.2-1b-chat, llama3.2-1b-instruct
meta-llama/llama-guard-3-1b                  llama3-1b-guard, llama3.2-1b-guard
meta-llama/meta-llama-3.2-3b                 llama3.2-3b-base                                           Yes
meta-llama/meta-llama-3.2-3b-instruct        llama3.2-3b, llama3.2-3b-chat, llama3.2-3b-instruct
meta-llama/llama-3.2-11b-vision              llama3.2-11B-base, Llama-3.2-11B-Vision-base
meta-llama/llama-3.2-11b-vision-instruct     llama3.2-11B, Llama-3.2-11B-Vision, Llama-3.2-mm
meta-llama/codellama-7b-python-hf            codellama, codellama-7b
meta-llama/codellama-34b-python-hf           codellama-34b
mistralai/mistral-7b-v0.1                    mistral-7b-v01-base
mistralai/mistral-7b-instruct-v0.1           mistral-7b-v01-instruct
mistralai/mistral-7b-instruct-v0.2           mistral, mistral-7b, mistral-7b-instruct
openlm-research/open_llama_7b                open-llama, open-llama-7b
stories15m
stories42m
stories110m

(.venv) think1 tonyr: python3 torchchat.py generate llama3.2-1b-base --prompt "write me a story about a boy and his bear"
NumExpr defaulting to 12 threads.
PyTorch version 2.6.0.dev20241013+cu121 available.
Using device=cuda NVIDIA GeForce RTX 4070 Ti
Loading model...
Time to load model: 0.90 seconds
-----------------------------------------------------------
Traceback (most recent call last):
  File "/home/tonyr/torchchat/torchchat.py", line 96, in <module>
    generate_main(args)
  File "/home/tonyr/torchchat/torchchat/generate.py", line 1235, in main
    gen = Generator(
          ^^^^^^^^^^
  File "/home/tonyr/torchchat/torchchat/generate.py", line 311, in __init__
    self.tokenizer_args.validate_model(self.model)
  File "/home/tonyr/torchchat/torchchat/cli/builder.py", line 264, in validate_model
    raise RuntimeError(f"no tokenizer was found at {self.tokenizer_path}")
RuntimeError: no tokenizer was found at /home/tonyr/.torchchat/model-cache/meta-llama/Meta-Llama-3.2-1B/tokenizer.model

Versions
(.venv) think1 tonyr: python3 ~/collect_env.py
Collecting environment information...
PyTorch version: 2.6.0.dev20241013+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 24.04.1 LTS (x86_64)
GCC version: (Ubuntu 13.2.0-23ubuntu4) 13.2.0
Clang version: Could not collect
CMake version: version 3.31.1
Libc version: glibc-2.39

Python version: 3.12.3 (main, Nov  6 2024, 18:32:19) [GCC 13.2.0] (64-bit runtime)
Python platform: Linux-6.8.0-49-generic-x86_64-with-glibc2.39
Is CUDA available: True
CUDA runtime version: 12.4.131
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 4070 Ti
Nvidia driver version: 550.127.05
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        46 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               12
On-line CPU(s) list:                  0-11
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Core(TM) i7-3930K CPU @ 3.20GHz
CPU family:                           6
Model:                                45
Thread(s) per core:                   2
Core(s) per socket:                   6
Socket(s):                            1
Stepping:                             7
CPU(s) scaling MHz:                   78%
CPU max MHz:                          3800.0000
CPU min MHz:                          1200.0000
BogoMIPS:                             6403.76
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx est tm2 ssse3 cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic popcnt tsc_deadline_timer aes xsave avx lahf_lm epb pti ssbd ibrs ibpb stibp tpr_shadow flexpriority ept vpid xsaveopt dtherm ida arat pln pts vnmi md_clear flush_l1d
Virtualization:                       VT-x
L1d cache:                            192 KiB (6 instances)
L1i cache:                            192 KiB (6 instances)
L2 cache:                             1.5 MiB (6 instances)
L3 cache:                             12 MiB (1 instance)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-11
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          KVM: Mitigation: VMX disabled
Vulnerability L1tf:                   Mitigation; PTE Inversion; VMX conditional cache flushes, SMT vulnerable
Vulnerability Mds:                    Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Meltdown:               Mitigation; PTI
Vulnerability Mmio stale data:        Unknown: No mitigations
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Retpolines; IBPB conditional; IBRS_FW; STIBP conditional; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] nvidia-cublas-cu12==<IP_ADDRESS>
[pip3] nvidia-cuda-cupti-cu12==12.1.105
[pip3] nvidia-cuda-nvrtc-cu12==12.1.105
[pip3] nvidia-cuda-runtime-cu12==12.1.105
[pip3] nvidia-cudnn-cu12==<IP_ADDRESS>
[pip3] nvidia-cufft-cu12==<IP_ADDRESS>
[pip3] nvidia-curand-cu12==<IP_ADDRESS>
[pip3] nvidia-cusolver-cu12==<IP_ADDRESS>
[pip3] nvidia-cusparse-cu12==<IP_ADDRESS>
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.1.105
[pip3] pytorch-triton==3.1.0+cf34004b8a
[pip3] torch==2.6.0.dev20241013+cu121
[pip3] torchao==0.5.0
[pip3] torchtune==0.4.0.dev20241013+cu121
[pip3] torchvision==0.20.0.dev20241013+cu121
[conda] Could not collect
(.venv) think1 tonyr:

Hmm looks like the migration https://github.com/pytorch/torchchat/commit/fff956c5c3a68025025c5d906af80eb44e960ce4 messed something up
Taking a look

https://github.com/pytorch/torchchat/pull/1414

Should work now, feel free to reopen and let us know if it doesn't

Fantastic, it now works for me - thanks so much for the quick fix.


[BUG] Remote installation failing on macos without interactive user logged in

Trying to manage a remote installation on MacOS BigSur (running commands through ssh) in case there user has no active interactive session crc setup ends up failing as it is not able to add crc-tray to launchd
Logs for crc setup
redhat@blr-crc-macserver 1.33.1 % crc setup --log-level debug
DEBU CodeReady Containers version: 1.33.1+3cfaa10f
DEBU OpenShift version: 4.8.12 (bundle installed at /Applications/CodeReady Containers.app/Contents/Resources/crc_hyperkit_4.8.12.crcbundle)
DEBU Running 'crc setup'
INFO Checking if running as non-root
INFO Checking if crc-admin-helper executable is cached
INFO Checking for obsolete admin-helper executable
DEBU Checking if an older admin-helper executable is installed
DEBU No older admin-helper executable found
INFO Checking if running on a supported CPU architecture
INFO Checking minimum RAM requirements
DEBU Total memory of system is<PHONE_NUMBER>6 bytes
INFO Checking if running emulated on a M1 CPU
INFO Checking if HyperKit is installed
INFO Checking if qcow-tool is installed
INFO Checking if crc-driver-hyperkit is installed
INFO Checking if CodeReady Containers daemon is running
DEBU Running 'bash -c launchctl list | grep crc.daemon | awk '{print $1}''
INFO Checking if launchd configuration for tray exists
INFO Check if CodeReady Containers tray is running
DEBU Running 'bash -c launchctl list | grep crc.tray | awk '{print $1}''
DEBU Tray is not running
INFO Starting CodeReady Containers tray
DEBU Starting tray agent
DEBU Running 'launchctl load /Users/redhat/Library/LaunchAgents/crc.tray.plist'
DEBU Command failed: exit status 112
DEBU stdout:
DEBU stderr: Could not find domain for port (Aqua)
DEBU Running 'launchctl error 112'
112: Could not find specified domain

Did they change the default behaviour in Big Sur? Until now, sshd was not running until I logged in with my user. Maybe this could be changed in the preferences, but I never tried to change it. Do you know if this is the defautl behaviour in Big Sur?

I did not change nothing on Big Sur, so not sure if this is default or someone else customize it. But definitely there is the option to running sshd without an active x session. And as per error message related to aqua currently there should be an active x session on the server to setup crc.


Add config flag to make Canvas not draggable

Hi @MrBlenny ! First off, this library is great and I appreciate the way it was design for extensibility and simplicity.
One thing is that, for my use case, I want to be able to prevent the canvas from being dragged with the mouse. Instead, users will scroll around in the canvas in my app. However, in the Canvas.wrapper.tsx file, the Draggable item is disabled only in the following case (Canvas.wrapper.tsx:91):
disabled={config.readonly}

However, I don't want to disable the entire application and make it readonly. I only want to make that specific draggable component disabled.
Would it be possible to add a flag to the config, such as canvasDragDisabled, defaulted to false, which can be set to true so that the above line could be changed to:
disabled={config.readonly || config.canvasDragDisabled}

Let me know what you think! It would be great to get this config option rather than needing to fork the repo and maintain a fork of this.
Thanks!
Rohan

@rnvarma I think I may have found a solution to what you were looking for since I had the same problem.
Check out the properties for zoom:
export interface IZoomConfig {
    transformEnabled?: boolean;
    minScale?: number;
    maxScale?: number;
    pan?: {
        disabled?: boolean;
        touchPadEnabled?: boolean;
    };
    wheel?: {
        disabled?: boolean;
        step?: number;
        wheelEnabled?: boolean;
        touchPadEnabled?: boolean;
    };
    zoomIn?: {
        disabled?: boolean;
        step?: number;
    };
    zoomOut?: {
        disabled?: boolean;
        step?: number;
    };
}

Disabling the panning seems to stop canvas transform
<FlowChartWithState
  initialValue={chartSimple}
  config={{
    zoom: {
      pan: {disabled: true}
    }
  }}
/>

First time posting so I hope I'm doing this right!

Yep, hopefully the above works. Closing for now.


How to observe the results?

hello,
i've got somewhat dumb straightforward question:
i have completed the distillation process for SR model (took 5 days on 1080ti). the result was ~550mb model, reported as having 0.75M params (two orders of magnitude less than original teacher model), performing with 356 GFLOPS (rather close to the original). your recently provided models have about the same characteristics (550mb, 0.54M and 316G respectively). the speed of processing also stayed the same as the original (teacher) SR model.
how can i observe speedup and size decrease, mentioned in the repo readme?

The GFLOPs is determined by the input image size. If the input size is 256*256, the computation of original ESRGAN will be 1176.61 GFLOPs, while the one of AGD will be 108.06 GFLOPs (10x smaller). Did you control the same input size? BTW, how did you calculate the GFLOPs of original ESRGAN (two orders of magnitude less params with similar FLOPs does not make sense)?

i meant log messages printed out during training procedure - that's the only metrics i noticed. so i compared values at the beginning of the first stage and at the end of the last one. of course, i didn't change resolution or anything during training process.

These logs are not the FLOPs of the original ESRGAN, instead they are the FLOPs of the searched networks at each searching epoch, which are calculated with the average input size of training dataset DIV2K (510*350). The flops of the final model on the evaluation dataset (Set5, Set14, Urban100, BSD100) can be found in the Readme or the paper. BTW, if you are interested in reproducing the FLOPs of the original ESRGAN, your can use thop package to measure the provided model in their official github https://github.com/xinntao/ESRGAN.


Jitpack build: Remove unnecessary --insecure curl flag

The certificate issues are fixed on our mvn server and curl works without the --insecure flag:
curl https://mvn.breez.technology/releases/breez_sdk/bindings-android/0.4.0-rc5/bindings-android-0.4.0-rc5.aar --output bindings-android-0.4.0-rc5.aar

I ran the build after merging, looks good:
https://github.com/breez/breez-sdk/actions/workflows/build-bindings-android.yml


Errors when applying example three_node_cluster_appstack_new_vpc_new_subnet

When applying the three_node_cluster_appstack_new_vpc_new_subnet example, I receive the following errors, preventing the successful completion of the terraform apply.
Error: collecting instance settings: empty result
│
│   with module.f5xc_aws_cloud_ce_three_node_appstack_single_nic_new_vpc_new_subnet.module.node_master["master0"].aws_instance.instance,
│   on ../../modules/f5xc/ce/appstack/aws/nodes/master/main.tf line 1, in resource "aws_instance" "instance":
│    1: resource "aws_instance" "instance" {
│
╵
╷
│ Error: collecting instance settings: empty result
│
│   with module.f5xc_aws_cloud_ce_three_node_appstack_single_nic_new_vpc_new_subnet.module.node_master["master1"].aws_instance.instance,
│   on ../../modules/f5xc/ce/appstack/aws/nodes/master/main.tf line 1, in resource "aws_instance" "instance":
│    1: resource "aws_instance" "instance" {
│
╵
╷
│ Error: collecting instance settings: empty result
│
│   with module.f5xc_aws_cloud_ce_three_node_appstack_single_nic_new_vpc_new_subnet.module.node_master["master2"].aws_instance.instance,
│   on ../../modules/f5xc/ce/appstack/aws/nodes/master/main.tf line 1, in resource "aws_instance" "instance":
│    1: resource "aws_instance" "instance" {

input values with some fields redacted
owner =<EMAIL_ADDRESS>project_prefix = "tenantname"
project_suffix = "78"
ssh_public_key_file = "/somepathto/.ssh/id_rsa.pub"
f5xc_tenant = "tenantname-abcdefghi"
f5xc_api_url = "https://tenantname.console.ves.volterra.io/api"
f5xc_cluster_name = "aws-ce-test"
f5xc_api_p12_file = "/somepathto/tenantname.console.ves.volterra.io.api-creds.p12"
f5xc_api_p12_cert_password = "abcdefghi"
f5xc_api_token = "abcdefghijklmno=="
aws_region = "us-west-2"
aws_vpc_cidr_block = ""<IP_ADDRESS>/22""
aws_vpc_slo_subnet_node0 = ""<IP_ADDRESS>/26""
aws_vpc_slo_subnet_node1 = ""<IP_ADDRESS>/26""
aws_vpc_slo_subnet_node2 = ""<IP_ADDRESS>/26""
aws_vpc_slo_subnet_worker0 = ""<IP_ADDRESS>/26""
aws_vpc_slo_subnet_worker1 = ""<IP_ADDRESS>/26""
aws_vpc_slo_subnet_worker2 = ""<IP_ADDRESS>/26""
aws_availability_zone_node0 = ""a""
aws_availability_zone_node1 = ""b""
aws_availability_zone_node2 = ""c""
aws_availability_zone_worker0 = ""a""
aws_availability_zone_worker1 = ""b""
aws_availability_zone_worker2 = ""c""

environment variables set with some values redacted
VOLT_API_URL=https://tenantname.console.ves.volterra.io/api
VOLT_API_TIMEOUT=60s
VOLT_API_P12_FILE=/somepathto/tenantname.console.ves.volterra.io.api-creds.p12
VES_P12_PASSWORD=abcdefghi
VOLTERRA_TOKEN=abcdefghijklmno==
AWS_PROFILE=abcdefghi
AWS_ACCESS_KEY_ID=abcdefght
AWS_SECRET_ACCESS_KEY=abcdefghi
AWS_SESSION_TOKEN=abcdef...xyz

@mjmenger fix has been pushed. Running TF apply and waiting for test results

@mjmenger TF apply was successful. Please pull latest.


Project license

The project is now being released under the MIT license, as announced and seen in the LICENSE file, but all code files still have the previous commercial license the code were distributed before.
Doesn't the header of those files have to be changed to the MIT notice instead?

Good catch, yes I’ll update the headers.

This has been resolved in #4


Custom drawable as button

Hi, how can I use my own image instead of the circle?
If that's not possible, is there an option to set the spacing only between the floating menu and the first fab (not all the fabs)?
Thanks.

Sorry, there are no such options in this library.


Read cluster domain from resolv.conf or env

Why are these changes needed?

In k8s,  cluster domains are configuration.  But now kuberay hard coded it to cluster.local. So fix this to either read cluster domain from /etc/resolv.conf or environmental variable

Related issue number

Checks

[ ] I've made sure the tests are passing.
Testing Strategy

[x] Unit tests
[x] Manual tests

Thanks @harryge00 for pointing this out! If possible, please provide a detailed reproduction script for either Kind or Minikube so that I can also test it manually. Your assistance in this matter would be greatly appreciated.

Thanks @harryge00 for pointing this out! If possible, please provide a detailed reproduction script for either Kind or Minikube so that I can also test it manually. Your assistance in this matter would be greatly appreciated.↳

@kevin85421
kind: Cluster
apiVersion: kind.x-k8s.io/v1alpha4
nodes:
- role: control-plane
  kubeadmConfigPatches:
  - |
    kind: ClusterConfiguration
    metadata:
      name: config
    networking:
      dnsDomain: "foo.bar.com"
  - |
    kind: InitConfiguration
    nodeRegistration:
      kubeletExtraArgs:
        cluster-domain: "foo.bar.com"

kind create cluster --config=config.yaml then a k8s cluster will be created with foo.bar.com domain name.
Deploy kuberay:
https://github.com/ray-project/kuberay#use-yaml
Deploy rayjob:
kubectl apply -f ray-operator/config/samples/ray_v1alpha1_rayjob.yaml

Get rayjob status:
kubectl get rayjob -oyaml

Check the dashboardURL.

@kevin85421 I have updated the code, to use env only. Where should I add the document to? I think there should be a document recording all the parameters/env vars for the operator?

@kevin85421 I have updated the code, to use env only. Where should I add the document to? I think there should be a document recording all the parameters/env vars for the operator?

Thank you for the update! You can create a document in this directory. We have an issue to track the progress of the document for environment variables (https://github.com/ray-project/kuberay/issues/957), and we will finish it before release v0.5.0.

I test this PR manually.

Step 1: Create a Kind cluster by following this https://github.com/ray-project/kuberay/pull/951#issuecomment-1465098772

Step 2: Add a environment variable CLUSTER_DOMAIN in KubeRay operator
env:
- name: CLUSTER_DOMAIN
  value: foo.bar.com

Step 3: Deploy a RayJob

Note that: we need to update the init container. Currently. the init container hardcoded the CLUSTER_DOMAIN with cluster.local.initContainers:
  # the env var $FQ_RAY_IP is set by the operator if missing, with the value of the head service name
  - name: init
    image: busybox:1.28
    command: [ 'sh', '-c', "until nslookup $RAY_IP.$(cat /var/run/secrets/kubernetes.io/serviceaccount/namespace).svc.cluster.local; do echo waiting for K8s Service $RAY_IP; sleep 2; done" ]
# Replace: "until nslookup $RAY_IP.$(cat /var/run/secrets/kubernetes.io/serviceaccount/namespace).svc.cluster.local;"
# With: "until nslookup $FQ_RAY_IP"

kubectl apply -f ray_v1alpha1_rayjob.yaml

I also tested this PR with a RayCluster, and FQ_RAY_IP is as expected.

The CI failure has no relationship with this PR. Merged.


Cut initial release

This is the placeholder issue for cutting the first release. I think we should wait for https://github.com/kubernetes/test-infra/pull/18667 and everything in milestone v1.
Cutting the release would imply a PR changing the version in the operator.yaml manifest. This commit could be tagged afterwards as the actual version. The built image (after finishing the postsubmit job) could be promoted to the actual tag.
I see that we infer the version from the git tag as an issue, because it breaks the above described workflow. We probably have to stick to hard coded versions.

/assign

Some release notes draft:
# Release notes for v0.1.0

Welcome to the first release of the seccomp-operator, we hope you enjoy this
release as much as we do!

The basic set of features as well as the installation guide can be found [in the
corresponding documentation][0].

Feel free to provide us any kind of feedback in the official [Kubernetes Slack
#seccomp-operator channel][1].

[0]: installation-usage.md
[1]: https://app.slack.com/client/T09NY5SBT/C013FQNB0A2

## Changes by Kind

### Feature

- Added `version,v` subcommand and CLI parser (`--version` works too now) ([#20](https://github.com/kubernetes-sigs/seccomp-operator/pull/20), [@saschagrunert](https://github.com/saschagrunert))
- Added ability to restrict seccomp-operator to watch config maps in a single namespace ([#94](https://github.com/kubernetes-sigs/seccomp-operator/pull/94), [@hasheddan](https://github.com/hasheddan))
- Added basic seccomp profile validation before syncing them on disk ([#72](https://github.com/kubernetes-sigs/seccomp-operator/pull/72), [@saschagrunert](https://github.com/saschagrunert))
- Added default operator profiles to the deployment. For now we added an nginx:1.19.1 profile ([#54](https://github.com/kubernetes-sigs/seccomp-operator/pull/54), [@saschagrunert](https://github.com/saschagrunert))
- Added manifest for deploying operator to watch for profile ConfigMaps in a single namespace. ([#100](https://github.com/kubernetes-sigs/seccomp-operator/pull/100), [@hasheddan](https://github.com/hasheddan))
- Added new `seccompProfile` field to `examples/pod.yaml`, which can be used for Kubernetes releases > v1.19.0 ([#90](https://github.com/kubernetes-sigs/seccomp-operator/pull/90), [@saschagrunert](https://github.com/saschagrunert))
- Added support for seccomp operator in master nodes ([#95](https://github.com/kubernetes-sigs/seccomp-operator/pull/95), [@pjbgf](https://github.com/pjbgf))
- Do not requeue after successfully writing profile to disk and do not immediately requeue on errors. ([#101](https://github.com/kubernetes-sigs/seccomp-operator/pull/101), [@hasheddan](https://github.com/hasheddan))
- Link seccomp-operator statically for easier distribution ([#16](https://github.com/kubernetes-sigs/seccomp-operator/pull/16), [@saschagrunert](https://github.com/saschagrunert))
- Make rootless operator deployment the default ([#38](https://github.com/kubernetes-sigs/seccomp-operator/pull/38), [@saschagrunert](https://github.com/saschagrunert))
- Nodes not supporting seccomp will not reconcile profiles to disk. Additionally a warning event will be thrown for the config map. ([#85](https://github.com/kubernetes-sigs/seccomp-operator/pull/85), [@saschagrunert](https://github.com/saschagrunert))
- Operator now runs under a specific seccomp profile. ([#52](https://github.com/kubernetes-sigs/seccomp-operator/pull/52), [@pjbgf](https://github.com/pjbgf))
- Profile controller will emit warning events on failure to get profile path or save profile to disk ([#56](https://github.com/kubernetes-sigs/seccomp-operator/pull/56), [@hasheddan](https://github.com/hasheddan))
- Seccomp profiles can be created in any namespace now. Profiles end up in different subdirectories per namespace. ([#49](https://github.com/kubernetes-sigs/seccomp-operator/pull/49), [@rhafer](https://github.com/rhafer))

Done https://github.com/kubernetes-sigs/seccomp-operator/releases/tag/v0.1.0


Nested/Sub Flow : Flow reuse/encapsulation

Is there a concept/mechanism to support flow reuse through nested/sub flow whereby a flow definition can be wrap up in a way that e.g. exposes salient inputs/outputs, when view from the outside, user only see those salient inputs/outputs like a function.

Sure, what you're after is a component like this: https://github.com/cross-platform/dspatchables/tree/master/Components/InOut
For example, connect one of these (let's call it inComp) to the input of a complex circuit, and one (let's call it outComp) to the circuit's output. Inject input(s) via inComp.PushOutput(), Tick() the circuit, and retrieve output(s) via outComp.PopInput()


Subtracting a CFTimeIndex from a CFTimeIndex should return a TimedeltaIndex

In [1]: import xarray as xr

In [2]: start_dates = xr.cftime_range('1999-12', periods=12, freq='M')

In [3]: end_dates = start_dates.shift(1, 'M')

In [4]: end_dates - start_dates
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-4-43c24409020b> in <module>()
----> 1 end_dates - start_dates

/Users/spencerclark/xarray-dev/xarray/xarray/coding/cftimeindex.pyc in __sub__(self, other)
    365
    366     def __sub__(self, other):
--> 367         return CFTimeIndex(np.array(self) - other)
    368
    369

TypeError: unsupported operand type(s) for -: 'numpy.ndarray' and 'CFTimeIndex'

Problem description
Subtracting one DatetimeIndex from another produces a TimedeltaIndex:
In [5]: import pandas as pd

In [6]: start_dates = pd.date_range('1999-12', periods=12, freq='M')

In [7]: end_dates = start_dates.shift(1, 'M')

In [8]: end_dates - start_dates
Out[8]:
TimedeltaIndex(['31 days', '29 days', '31 days', '30 days', '31 days',
                '30 days', '31 days', '31 days', '30 days', '31 days',
                '30 days', '31 days'],
               dtype='timedelta64[ns]', freq=None)

This should also be straightforward to enable for CFTimeIndexes and would be useful, for example, in the problem described in https://github.com/pydata/xarray/issues/2481#issue-369639339.
Expected Output
In [1]: import xarray as xr

In [2]: start_dates = xr.cftime_range('1999-12', periods=12, freq='M')

In [3]: end_dates = start_dates.shift(1, 'M')

In [4]: end_dates - start_dates
Out[4]:
TimedeltaIndex(['31 days', '29 days', '31 days', '30 days', '31 days',
                '30 days', '31 days', '31 days', '30 days', '31 days',
                '30 days', '31 days'],
               dtype='timedelta64[ns]', freq=None)

Adding a TimedeltaIndex to a CFTimeIndex would also make sense:
In [1]: import xarray as xr; import pandas as pd

In [2]: a = xr.cftime_range('2000', periods=5)

In [3]: deltas = pd.TimedeltaIndex([pd.Timedelta(days=1) for _ in range(5)])

In [4]: a + deltas
Out[4]:
CFTimeIndex([2000-01-02 00:00:00, 2000-01-03 00:00:00, 2000-01-04 00:00:00,
             2000-01-05 00:00:00, 2000-01-06 00:00:00],
            dtype='object')

In [5]: deltas + a
Out[5]:
CFTimeIndex([2000-01-02 00:00:00, 2000-01-03 00:00:00, 2000-01-04 00:00:00,
             2000-01-05 00:00:00, 2000-01-06 00:00:00],
            dtype='object')


Split method definitions to avoid docstring overwriting

Solves #40.
This should also get rid of the possible method call errors.
The change also had the benefit of allowing the default simulate/log density definitions to be combined with the interface definitions.

Also worth noting that I noticed some inconsistency in whether state or step came first in the parameters for when transitioning/observing. Since the inclusion of step is the key thing that distinguishes initialisation from transitioning, I've put it first. Happy to flip them if people think state first is more sensible.


Can we potentially use x-ray on a thin-client while the x-ray core server could be installed remotely?

Firstly, I think this project looks really promising, kudos to the team!
Can we potentially use x-ray on a thin-client while the x-ray core server could be installed remotely?

of course you can


Week 0 - Sovereign Tuned

Due: Friday 26th, 2024
Assigned: @IsaccBarker

Sovereign / Roadrunner implementation tuned & tested
Mark down what needs to be debugged for Week 1 (Week of 1/29/23)

Roadrunner tuned close enough that we can test Sovereign.
Week one debug list:

Pathing
Execution

Component system already tested.

Please Close w/ PR :D


Some more specific info and setting sampler_param to 1 by default

Some more specific info which folks would find helpful and setting sampler_param to 1 by default.
People when referring to the yaml might end up setting sampler_param to 0 because of which no trace is captured.

[] CHANGELOG entry if change is relevant to the end user.

Changes

Verification
Checked on MD editor

@bwplotka Please review

Sounds good @bwplotka


feat: reduce size of setInitialMode to 357 bytes instead of 500 bytes

if I am not mistaken, this code is not minimized.
therefore this patch could make sense - some readability is sacrificed to reduce the amount of bytes transferred to the end user.
it's also possible to optimize this further:
function setInitialMode(){const e=document.documentElement,t=localStorage.getItem("mode")||"system",o="light"===t||"system"===t&&window.matchMedia("(prefers-color-scheme: light)").matches;e.classList[o?"remove":"add"]("dark"),e.style.colorScheme=o?"light":"dark",localStorage.setItem("mode",t)}

but that is really hard to read and only saves 63 bytes. you would also have to add some prettier ignores or something like that, or it would be formatted to be similar to the code used in this patch anyways

nevermind, it seems like this code IS minimized somehow so this is not needed I think


Docs and republish site.

Hi Mark, where are  the SBT instructions now and which repo is  it in? looked in https://ambiata-oss.s3.amazonaws.com/ couldnt find it.
Cheers
Karl

Will have. Look and make sure it is somewhere reliable tonight.

Cheers.

@karlroberts A bit bigger of a job than I thought to get this up, will have to wait til the weekend. If you have time, happy for you to publish it somewhere like bintray though, even if I have to give permissions or similar.

@markhibberd OK, I'll publish it somewhere if I can, and then hassle you when I can't :-)


Add network simulation delay

Castle Mock projects should be able to be configured to simulated network delay.

Added support for simulated network delay. It can be configured for each SOAP operation or each REST method.

Hi @karldahlgren:
Is there a way to make the network delay available for each mock, not the whole operation? I want to make request match on SOAP, but I want only specific mocks to show network delay. Right now, as long as I've seen, the network delay is applied to the whole operation.
Thank you in advance.
Regards,

Hi @spartancr8.
My apologies for the delay. Unfortunately, it can only be done on an operation level, but it has crossed my mind to move that functionality to the mocked response itself (Or at least have it as an alternativ). Is this something that would help you?
Thank you!
Best regards,
Karl Dahlgren


Create readme2

@reachmw I guess you've opened this PR by accident as it doesn't appear to be valid change that we would like to merge...

I am sorry.  That was a mistake.


docs: move to their own repository

The docs extend beyond just the workflow repo. It makes sense for them to be independent.

:+1:

I thought this initially.  I don't any longer.  Deis is clearly evolving beyond "just a PaaS."  We have a variety of workloads that are reusable in other contexts.  Documenting each independently is crucial, but I would suggest that the PaaS (and that's what workflow embodies) is the hub of all that we do, with every other component being a spoke.  I think it's unavoidable that a certain degree of documentation for the other component might land in workflow out of sheer necessity.  Of course, it's no excuse to not also document each component independently.  </$0.02>

@krancour I agree, and this issue is not for splitting the docs up into individual components. This issue simply represents moving the docs folder into its own dedicated repo. The docs therein would, IMO, still look the same as they do now.
However, right now they go well beyond the functionality that just the code in this repository provides. For example, they cover:

Installing Deis with helm
In depth instructions on configuring the router
The git push workflow
Using and configuring storage (including deis/minio)

Gotcha.  I misunderstood the title and OP.  I interpreted as docs currently residing in deis/workflow moving out to other existing repos.
I'm on board with what you are suggesting.  And for the most part, I'm not entirely opposed to abandoning the monorepo of yore (no need to rehash that again though, lol), but I will say that having docs and code in separate repos makes it quite tough to enforce a notion of completeness where a change isn't complete until it's been documented.

not going to be able to do this for v2-beta. punting this

Closing with the creation of https://github.com/deis/docs-v2


Registration link expired before user clicks it

SQLite query to show pending registrations:
select m.id, m.date_joined,
m.name_first, m.name_last, m.email,
p.activation_key, CASE WHEN datetime(m.date_joined, '+14 days')<datetime('now') THEN 'EXPIRED' ELSE 'available' END as expired
from registration_registrationprofile p
left join clubmembers_member m on p.user_id=m.id
where p.activation_key!="ALREADY_ACTIVATED" AND m.is_active=0
order by m.date_joined;

Looks like this bug has affected 7 people so far.

Assuming this isn't an actual bug (link expired before arriving in the user's inbox), increasing settings.ACCOUNT_ACTIVATION_DAYS.


[BUG]

Undo does not work anymore if the last action was in another tab (such as changing a crosssection in the Materials tab)
Expected behavior
Undo actions
What happens:
Goes to Materials tab and does not undo anything. (the steps before the action in another tab cannot be undone anymore).

Thank you. Issue replicated, sending to be fixed.


Incorrect compiler env variables if different compiler versions are installed

My wsl system had gcc-9 (only, no gfortran), and a full gcc-11* installed. The environmet created the following env variables:
CC=$'/usr/bin/gcc-9\n/usr/bin/gcc'
OMPI_CC=$'/usr/bin/gcc-9\n/usr/bin/gcc'
FC=$'None\n/usr/bin/gfortran'
OMPI_FC=$'None\n/usr/bin/gfortran'

Reason is the following output of spack compiler info:
RUN spack compiler info gcc
<EMAIL_ADDRESS>        paths:
                cc = /usr/bin/gcc-9
                cxx = None
                f77 = None
                fc = None
        modules  = []
        operating system  = ubuntu22.04
<EMAIL_ADDRESS>        paths:
                cc = /usr/bin/gcc
                cxx = /usr/bin/g++
                f77 = /usr/bin/gfortran
                fc = /usr/bin/gfortran
        modules  = []
        operating system  = ubuntu22.04

I have a branch that fixes it, once I have confirmed (by rebuilding I'd guess :( ) that it works, I'll do a PR.

This patch actually does not work (the script aborts), I assume the script is set to abort on error, and the grep statement fails with an error state.
Verify that it works if two consistent settings are provided (which I believe it does), e.g. I have seen:
<EMAIL_ADDRESS>        paths:
                cc = /usr/bin/gcc
                cxx = /usr/bin/g++
                f77 = /usr/bin/gfortran
                fc = /usr/bin/gfortran
        modules  = []
        operating system  = ubuntu24.04
<EMAIL_ADDRESS>        paths:
                cc = /usr/bin/x86_64-linux-gnu-gcc-13
                cxx = /usr/bin/x86_64-linux-gnu-g++-13
                f77 = /usr/bin/x86_64-linux-gnu-gfortran-13
                fc = /usr/bin/x86_64-linux-gnu-gfortran-13
        modules  = []
        operating system  = ubuntu24.04

Probably extracting the compiler info isn't sufficiently specific at https://github.com/MetOffice/ngmo-environments/blob/main/utils/install-compiler.sh#L40
If NGMOENVS_COMPILER is just "gcc" then you might get multiple matches, which then pass through to the other stages. Easy fix may be just to pull the first (or last, whichever spack will actually use when compiling with %gcc) matched line from the sed output.

While I have fixed the script (https://github.com/MetOffice/ngmo-environments/compare/main...handle_multiple_installed_compilers) to handle incomplete compilers, the second issue still exist (no surprise) - which makes the resulting environment not working:
OMPI_FC is set to e.g. /usr/bin/gcc\n/usr/bin/x86_64-linux-gnu-gfortran-13, so mpif90 does not work. Manually fixing the environment variables results in a working environment.


Detached child form also minimized when main form minimzed

I've added a dockable form to my main form, however when the child is detached outside the main form I wish to be able to minimize the main form leaving the child in its current position. My problem is that both forms minimize when the main form is minimized.
MP3PlayerWindow = New MP3Player()
MP3PlayerWindow.Show(DockPanel1, DockState.DockLeft)

Is there a solution to this please?

The FloatWindow is owned by the Form on which the DockPanel is located and there isn't currently a built-in configuration to change that (and in WinForms, owned windows will always minimize with their owner).  It might be as simple as creating your own FloatWindow factory that unsets the Owner (see wiki cookbook), but there are likely some other ramifications to that.


[!] Error: local variable 'numspec_items' referenced before assignment

Hello.
I just had a quick go with your program when this happened...
$ >python3.8 spraygen.py --mode plain --type iterative --iter full --max_length 12 --sort random -o AllASCIIpasswd.txt

     _
    (  \_
    (    \_
    (       \_
    (         \_            ___
    ( Password   \         |   |
    (   Spray     |คคคคคคคค|___|
    (           _ /          |
    (       _ /         /~~~~~~~~~\
    (   _ /            (  Spray    )
    (_/                 |  This   |
                        |         |
                        | Get     |
                        |  Creds  |
                        |_________|

    Original Art by Alex Chudnovsky (Unaffiliated)
    Spraygen tool by 3ndG4me
    Version 1.6

[*] Info: Year Start not provided, setting to current year...
[*] Info: Year End not provided, setting to current year...
[*] Info: Generating PLAIN list...
[*] Info: Generating ITERATIVE list...
[*] Info: List size will be: 4
[*] Info: List keyspace will be: full
[*] Info: This is generating literally every permutation in that keyspace, this will take some time...

[!] Error: local variable 'numspec_items' referenced before assignment

I think something needs double-checking ;)
AFAIK I installed the prerequisites as instructed:
$ >pip install -r requirements.txt
Collecting argparse
  Downloading argparse-1.4.0-py2.py3-none-any.whl (23 kB)
Requirement already satisfied: colorama in /usr/lib/python3/dist-packages (from -r requirements.txt (line 2)) (0.4.3)
Collecting progress
  Downloading progress-1.6.tar.gz (7.8 kB)
Building wheels for collected packages: progress
  Building wheel for progress (setup.py) ... done
  Created wheel for progress: filename=progress-1.6-py3-none-any.whl size=9615 sha256=07d849d4f4388f27a6341ff1eb624f62d28510f22f0aa4fd6bb1b83bd1badb10
  Stored in directory: /home/XXXX/.cache/pip/wheels/bb/01/5a/c916509df9b12c6465864251dbe826def8e31a16fa7da54f08
Successfully built progress
Installing collected packages: argparse, progress
Successfully installed argparse-1.4.0 progress-1.6

Hey sorry for the delayed response! I found the syntax error here it is related to a variable misuse on line 403. I'll be updating ASAP.