Inline footnote cannot be displayed

Please check that this issue hasn't been reported before.

[X] I searched previous Bug Reports didn't find any similar reports.

Expected Behavior
I hope to support inline footnotes like Obsidian, so that the plugin "better footnote" can preview footnotes，thank you very much indeed
Current behaviour
Inline footnotes cannot be displayed in current testing, however, official documentation supports inline footnotes

Steps to reproduce
Here is the minimum vault I have created
test.zip
Which Operating Systems are you using?

[ ] Android
[ ] iPhone/iPad
[ ] Linux
[ ] macOS
[X] Windows

Obsidian Version
V1.5.3
Tasks Plugin Version
5.6.0
Checks

[X] I have tried it with all other plugins disabled and the error still occurs

Possible solution
No response

Thank you for the report.
For future reference, the sample vault is a help to show the problem, but please, we still need information about how to reproduce the problem in a developer vault.
From my experiments, I've written them up below.
Inline footnotes work (by luck) when the query is in the same file as the task
- [ ] This is a task ^[with a working inline footnote]

---

```tasks
path includes {{query.file.path}}
```

Tasks Query results do not show inline footnotes on tasks that are in different markdown files than the query
Steps to reproduce:

Create a file Task.md
Paste in this content

This file contains the task.

- [ ] This is a task ^[with a working inline footnote]

View Task.md in both Live Preview and Reading modes. The inline footnote is shown.

Create a file Query.md
Paste in this content

This file contains the query which searches for the task in file  `Task`.

```tasks
path includes Task.md
```

View Query.md in both Live Preview and Reading modes. The inline footnote is missing.

I've renamed the ticket to describe the problem more precisely.

I hope to support inline footnotes like Obsidian, so that the plugin "better footnote" can preview footnotes，thank you very much indeed

I don't exactly understand that. Are you proposing to create a Pull Request on better footnotes?

I don't plan to work on this personally in the foreseeable future - I've a long list of other things I want to work on.
So I've added the 'help wanted` tag. The following info may help anyone who wishes to try working on this.
I've written a Contributing to Tasks guide, with much info about how to build, modify and tests the Tasks plugin.
It's worth searching for footnote in this vault to find all the references to that word in Code, Issues etc

That search for Footnote showed in the repo that Tasks is behaving as documented:
https://publish.obsidian.md/tasks/Queries/About+Queries#Limitations+of+Queries

I've update the documentation to make this more discoverable:
5b25936903908418d5c360085c747ff173ac25d9


Explain that custom nested fields are allowed within Optimade fields.

In the discussion on the new fields for Biomolecular data #389, it was not clear whether it was allowed to add database specific fields within OPTIMADE properties. With this PR I hope to clarify that this indeed allowed.

@JPBergsma you may also specify that this PR closes #397.

@JPBergsma you may also specify that this PR closes #397.

Sorry, I had not thought about your issue. I will update the description.

Glad to see this PR in! I was late to approve it, but I would still like to express even post factum support.


Unable to create app package

After following the 'Package the app' section of the tutorial here: https://docs.microsoft.com/en-us/windows/apps/desktop/modernize/host-standard-control-with-xaml-islands, I am unable to create an app package for the app due to the following errors:
• Validation error. error 80080204: App manifest validation error: Line 217, Column 27, Reason: The field "[local-name()='Extensions']/[local-name()='Extension']/[local-name()='InProcessServer']/[local-name()='ActivatableClass']" with value "Microsoft.Toolkit.Win32.UI.XamlHost.XamlApplication" must only be declared once. A duplicate exists on Line 42, Column 27.
• PRI175: 0x80073b0f - Processing Resources failed with error: Duplicate Entry.
• PRI222: 0x80073b0f - Unspecified error occurred.
I have added a reference to both the WPF app and the UWP app to the app package as per the tutorial as I would like to upload the app to the Microsoft Store. I am following this tutorial as I would like to use WinUI 2 with XAMLHost, which works fine when the WPF app is built outside of the package or if built inside the package without referencing the UWP app in the package.
App I am using is a new .NET Core 3.1 app and I have followed all of the requirements in the tutorial. There are no other packages or files that have been added.
It seems like this may have been broken in an update to Visual Studio as it used to work I believe.
I am using Visual Studio 2022 17.0.2.
I also tried using Visual Studio 2019 16.11.5.
Same issues with both.

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 6ba9095f-57b4-267d-8896-5375c68b01ee
Version Independent ID: 514d7e51-6f16-8199-aabf-26ee901a6ed3
Content: Host a standard WinRT XAML control in a WPF app using XAML Islands - Windows apps
Content Source: hub/apps/desktop/modernize/host-standard-control-with-xaml-islands.md
Product: uwp
Technology: apps
GitHub Login: @Karl-Bridge-Microsoft
Microsoft Alias: kbridge

I've reported this issue to Visual Studio Feedback: https://developercommunity.visualstudio.com/t/Unable-to-create-Store-app-package/1668742?port=1025&fsid=39faaef5-a58b-4a54-a337-8a160f88b801&entry=myfeedback&ref=native&refTime=1645291507519&refUserId=8bce036a-185d-4c7f-837f-f5f8df35f6a2

Thanks, @aquinn39. I'm getting the same build error with VS 2022 17.1. I've reached out to the product team for info about this particular issue.
Meanwhile, I took a pass through the topic, because previously it was talking about VS 2019. Since the steps work (apart from the issue you're seeing) for VS 2022, I updated the topic and just generally tidied it up and simplified it a little.
I'll get back to you when I get more info.
Thanks!
-Steve

Hi @stevewhims,
Do you have any updates on this?
I'd really like to use Visual Studio 2022 for many projects that have this issue but am still stuck using 2019 as 2022 can't build them (I've checked on the latest version at the time of writing this, 17.1.5).

Thanks, @aquinn39. I've reached out again for info. I'll keep you posted; sorry about the delay.
-Steve

Thanks for the reminder. I've reached out again for info.
-Steve

I've just made a small change to this topic (and 6 others like it). I added a note to draw attention to the support notice in the GitHub repo for the Windows Community Toolkit. All the relevant details are in that notice.
At the moment, it's not clear whether the problem is with the Windows Community Toolkit or with Visual Studio. At the same time, it's not clear that there are any changes that need to be made to the documentation in this topic. In light of all of that, and the age of this issue, I'm going to go ahead and close it. I'll be more than happy to reactivate it, and fix the topic, if anything concrete comes up that needs fixing.
Thanks!
-Steve


Sidekiq enterprise encryption failed to decrypt with this plugin

I run into an issue the secret bag is not decrypting properly and fallback to [encrypted data] using sidekiq-status middleware
Related issues:
https://github.com/mperham/sidekiq/issues/3706
https://github.com/utgarda/sidekiq-status/issues/153
Configuration for sidekiq initializer
Sidekiq.configure_client do |config|
  Sidekiq::Status.configure_client_middleware config
end

Sidekiq.configure_server do |config|
  Sidekiq::Status.configure_server_middleware config
  Sidekiq::Status.configure_client_middleware config
end

Would there be an elegant workaround for this besides just not using this plugin?

@kimyu92 just wanted to reach out and see if this was still an issue for you when using sidekiq 6.2.2 and sidekiq-status 2.1.0, or if you were able to find a solution. I don't have access to Sidekiq Enterprise, so unfortunately I can't weigh in on the encryption feature or how the middlewares interact.

@kimyu92 would you be able to paste your full sidekiq configuration, including the encryption stuff (minus any sensitive keys)?
My first theory is that it has to do with how the middlewares are ordered. It doesn't sound like this is a bug with either lib just yet.

Here is the snippet
https://github.com/mperham/sidekiq/issues/3706#issuecomment-878530814

@kimyu92 as a user of Sidekiq Enterprise, you may be in the best place to debug this. Please feel free to open a PR if there's anything that needs to be updated in sidekiq-status itself.

Closing as it has been over a year since the last update.


Set the seed when randMacAddr

If the seed was not seted, all machines get the same MAC address.
Then technique like Open vSwitch won't work due to the same MAC address
of all machines.

Can you please sign your commits following these rules:
https://github.com/docker/docker/blob/master/CONTRIBUTING.md#sign-your-work
The easiest way to do this is to amend the last commit:
$ git clone -b "fix-rand-mac" git@github.com:sayuan/libcontainer.git somewhere
$ cd somewhere
$ git commit --amend -s --no-edit
$ git push -f

This will update the existing PR, so you do not need to open a new one.

Thank you for the advice. Now I've updated it.

@estesp Is this ok or do you think we should do a package level var from rand.New() instead of using rand.Seed?

@crosbymichael I think a package level var is preferred as this is setting the seed for all users of rand in the process space.  It is possible some other package/init() has set the seed already or, alternatively, is using a different seed and gets init'ed after this package.
@sayuan an example of rand.New() is here: https://github.com/docker/docker/blob/master/pkg/namesgenerator/names-generator.go#L312

Please review it again. :)

LGTM


introduce Access consoles and Serial Console

The user can select from diferent console types to access.
Serial console is added to the existing VNC.
TODO:

[x] resolve recently broken pf-react dist (PR 894)
[x] have related pf-react patches merged (PRs 906, 909)
[x] move code from web-ui to web-ui-components
[x] increase web-ui-components dependency version once https://github.com/kubevirt/web-ui-components/pull/115 is merged
[x] remove redundant commits from here once #122 is merged

Based on: https://github.com/kubevirt/web-ui-components/pull/115

Last 2 commits moved to #122

@rawagner , this is ready once CI is green.


Create contributing document

What I currently have on the README is very quickly going to get out of hand. I would like to have an in-depth contributing document to help contributors get started with quality submissions.

I would like to work on it .

If this has not been completed, I would like to work on this issue.
Please let me know if I can take this up.

Sure...go ahead.
On Oct 19, 2019 10:33 PM, "Preeti Lolla"<EMAIL_ADDRESS>wrote:

If this has not been completed, I would like to work on this issue.
Please let me know if I can take this up.
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub
https://github.com/scrabill/how-many-days-until-halloween/issues/360?email_source=notifications&email_token=ANN24VD4IO3GOHH5SLL6E63QPM4WDA5CNFSM4JCN5IO2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEBXWYRA#issuecomment-544173124,
or unsubscribe
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.

@scrabill  I have created a pull request see if you like it or not !

A contributing doc has been added, but I am leaving this issue open if there are changes that should be made that would help to clarify for other users.

Nvm, closing this issue since #361 already exists for updates.


SEPG Automated Release - v2.9.3

SEPG Details
Release Build Link: http://sou-jenkins2.swinfra.net:8080/job/Auto-Release/393/
Build Token: github.com/CAFapi/opensuse-python3-image/master/597476f0fb7b1e5fe4f6083ef2c70aaa5790d958
Versioning Behaviour: Roll on to next minor
Artifacts For Release
Docker

cafapi/opensuse-python3:2.9.3 (Static Tag)
cafapi/opensuse-python3:2.9 (Dynamic Tag)
cafapi/opensuse-python3:2 (Dynamic Tag)

 Build Stage
Action
Status

Release Checks
completed
:heavy_check_mark:

Gather Release Data

:white_small_square:

QA Documentation Site Deployment

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QA Deployment Branch Promotion

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Docker Image Promotion

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Maven Artifact Promotion (Closed Source)

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Artifactory Release Artifact Tagging

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Generic Artifact Promotion

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Maven Staging Repository Removal (Open Source)

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Git Tagging

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Git Release

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Git Release Asset Deployment

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Pull Request Merge

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Release Branch Deletion

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view the build log here


Does Heartbeat use KeepAlive-Notifications of the OPC-Server?

Hi,
i'd like to use the heartbeat feature of the publisher. Does the publisher set a time for heartbeat itself, or does it use some opc feature to get notified by the server, that nothing has changed for a while?
Background:
We need to make sure that the values that are transmitted in heartbeat style actually come from the opc-server.
Best regards
Matthias

The publisher is sending the last value with an updated timestamp as heartbeat (from cache, not by reading it again). It's not using any OPC UA server feature.
Thanks!
Markus


You can select all available grant controls for the Other clients condition; however, the end-user experience is always the same - blocked access.

I don't quite understand what this means, "You can select all available grant controls for the Other clients condition; however, the end-user experience is always the same - blocked access."
Why is this even included in this article if we want to block legacy authentication?
If we grant controls for the "Other clients" why would it still be blocked?
Thanks so much, Regards, NavZ

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: ad5f26dc-2f8f-ef76-3d20-a0a42d2bbada
Version Independent ID: a0e971d1-05f2-2c21-06d4-60c087d45c0a
Content: Block legacy authentication - Azure Active Directory
Content Source: articles/active-directory/conditional-access/block-legacy-authentication.md
Service: active-directory
Sub-service: conditional-access
GitHub Login: @MicrosoftGuyJFlo
Microsoft Alias: joflore

@NavishkarSadheo, Thanks for the question! We are investigating and will update you shortly.

@NavishkarSadheo  The section means that you can use Grant the "block access" control in one policy and grant the "grant access"  control in other policy for other clients , block always wins . You can always have multiple conditional access policies but if you do not have any policies with "block access" control defined for "Other clients" in any policy then they will continue to work and legacy auth in older office apps and third party apps employing older methods of login will continue to work. But if you define the block access grant in any one policy which has other clients specified , the end user experience will always be blocked.
Hope this helps. we will now close this issue. In case you have any queries, feel free to tag me or the author of this article @MicrosoftGuyJFlo to your reply and we will be happy to help further.
Thank you.


NBU: Design to handle very small viewports

Add section to Responsive web design patterns.
(One of several issues raised to cover NBU requirements, as discussed via email — more detail here.)

I believe you did this, if not, please re-open and assign to yourself.


Fix Cognitive Services links on README

Fix broken links
Add some missing Bing properties (Auto Suggest, Visual Search)
Add missing Custom Vision

Can one of the admins verify this patch?

bump

@cthrash Picking up this Pr now... can you kindly merge Master into your branch and once CI passes after that i'll merge this change in.

GTG?


User should be able to choose if website is not needed.

User should be able to choose if website is not needed.
Sometimes user would want to use the dashboard only.

Deferring.


Test to illustrate problem with children instantiation

refs: #777

If you run npm run prettier and add it.skip I can merge this instead of copy-pasting

@koskimas Done!

Thank you!

Prettier was needed so that tests pass. Travis runs eslint that checks for prettier formatting.

Coverage remained the same at 95.015% when pulling cf0d56511a0798866fad17dcca55c7f8d8e65ac8 on igor-savin-ht:master into eaab72472586a11747fd66f001dd14f00fb59097 on Vincit:master.

Prettier is amazing, actually, switching between formatting styles of different projects is nightmare without it :)


Sync dmlc/tvm 20190513

Thanks for contributing to TVM!   Please refer to guideline https://docs.tvm.ai/contribute/ for useful information and tips. After the pull request is submitted, please request code reviews from Reviewers.

The tests passed. Please take a look @zhiics @yongwww @mnuyens


Create a vite plugin

Do you plan a Vite Plugin?
Originally posted by @blanklob in https://github.com/unshopable/liquidx/issues/1#issuecomment-1597785393

@blanklob do you have a specific project in mind? This would give me a head start so I don't have to create a boilerplate liquid vite project from scratch.


[Spatial.9] Suffix all CRTP method implementation by _impl ...

I think it is a good strategy to avoid infinite loop and decrease debugging time.
I would also suggest to set all those methods protected to force the user to use standard C++ operators and to let the compiler solve the computation tree.

I agree that this is necessary. We should have a single commit to propagate this change systematically in all the code (mostly spatial and joint modules). Anybody would volunteer to do it?

If nobody has started it, i can do it

I just realised that it is not possible to set methods with *_impl suffix protected. Or, one should use some back door to do that which leads to unreadable code.
In Eigen, they used some tricks to compile an API which fits pretty well for doxygen but which does not correspond to the real API, in terms of implementation. But I think the code will become very hard to read and maintain to.
Maybe the best thing for a clean API is to resort on gdb during the debug process ...


Rework unknown handling

This addresses Issues #127, #128, and #129:

It fixes the handling of unrecognized enum values in packed repeated enum fields

It simplifies the overall handling of unknown fields:  The generated decoders are now entirely ignorant of unknown field handling issues.  The only generated code that deals with unknown fields is the unknown property itself and the traversal logic which iterates that property.  In particular, the boolean handled values are entirely gone.

It migrates unknown handling to use Data instead of [UInt8] for consistency with the rest of the system.

It now tags generated messages as Proto2 or Proto3.

@allevato, @thomasvl: Any objections?
Refactoring the protocols is next on my list; I need to actually try a couple of the approaches and see where they lead.  I could tinker with the decodeIntoSelf factoring now (and the related proto2/proto3 distinctions), but I suspect it would be ripped up again in that work.

I'll defer to @allevato, aside from the quick scan the other night, I haven't gotten to go back and read through this.  Sorry. 🙁

LGTM.
I've been thinking about how to extend this to give us an actual unknown field storage type that lets users parse out the individual fields into more usable types (like varints, data blobs, fixed ints, etc.) while trying to preserve the performance of not parsing them if they're never requested. Such a class could also be used as a "raw message" like the one we used to have. Is that something you had planned to do? If not, I'm happy to poke at it once this is in.

@allevato that is captured in issue #130

Right—I guess my question was, are you already thinking about the implementation because I don't want to duplicate any work you might be doing. :)

I was planning to look next at the protocol refactoring (which may involve a first stab at splitting out the JSON/Text support metadata) and maybe help @BradLarson with the text format support.  In particular, the protocol refactoring is among the few areas that are likely to change the generated code.
I agree that it makes sense to tie ProtobufUnknown with the raw message support, and I really like the idea of making the actual parsing as lazy as possible, primarily to save memory for common cases where people never look at the unknown fields.  I'm not sure whether ProtobufUnknown is the raw message class or not; that will depend on how the implementation looks as it comes together.  It may be that ProtobufUnknown remains just a simple container and the raw message handling is a parser class that can be attached to any byte source; that would also give the stream parsing I know you've been interested in.  I can't wait to see what you come up with!


Enable setInvalidatedByBiometricEnrollment

Hello, I have a question,  it is possible to enable setInvalidatedByBiometricEnrollment?
I need to use setInvalidatedByBiometricEnrollment(true) while generating key and the key gets invalidated on any new biometric enrollment. An exception is thrown when you try to use the same key. In this situation, you can reset the biometric app settings inside your app and start the process of enabling biometrics again.

Hi,
I'm not quite sure what you are referring to. By default setInvalidatedByBiometricEnrollment is enabled, and as far as I can see we don't disable it anywhere.

How to disable the keyvalue if the user add new fingerprint to Android settings after he/she authenticate finger inside my application ?

@EdinsonNM as I said, imho this is the default behavior. Are you sure that this is not already the case?

I was reviewing your code apparently the way you perform the encryption is not taking into account when changes occur in the biometric.
I'm writing my own library and this one is working.  I am not an Android expert but I managed to encrypt in a different way than you do and it worked.
I'm sorry, my English is really bad :(

you can try writing a value, then try adding a fingerprint and then try reading that value.  this value must be permanently invalidated

I think I now found the problem. the API documentation https://developer.android.com/reference/android/security/keystore/KeyGenParameterSpec.Builder#setInvalidatedByBiometricEnrollment(boolean) reads:

Sets whether this key should be invalidated on biometric enrollment. This applies only to keys which require user authentication (see setUserAuthenticationRequired(boolean)) and if no positive validity duration has been set (see setUserAuthenticationValidityDurationSeconds(int), meaning the key is valid for biometric authentication only.
By default, invalidateKey is true

Now, what i thought this meant is, that invalidateKey is true, and it can be turned off when setUserAuthenticationRequired = true and setUserAuthenticationValidityDurationSeconds <= 0 -- but now I guess that it actually means this option all does not apply at all when either setUserAuthenticationRequired is not true, or setUserAuthenticationValidityDurationSeconds is > 0, because then the key is never invalidated? at least that seems to be the behavior.
And it is not possible to use setUserAuthenticationValidityDurationSeconds to 0 because androidx.security won't let you: https://android.googlesource.com/platform/frameworks/support/+/refs/heads/androidx-master-dev/security/crypto/src/main/java/androidx/security/crypto/MasterKeys.java?source=post_page---------------------------%2F&autodive=0%2F%2F%2F%2F%2F#126

Not sure how this can be workarounded from my end..

Are there any security concerns to use SecretKey instead of MasterKey to encrypt the data? It is also mentioned in this article on biometric authentication from android documentation

@loposkin the SecretKey in that article has nothing to do with the MasterKey used by this plugin.. these are just classes of different libraries for different abstractions, and are have nothing to do with the actual encryption being used.. also i'm not sure what these has to do with invalidatedByBiometricEnrollment...
fwiw, i'll close this issue, has detailed in my last comment i don't think setInvalidatedByBiometricEnrollment is applicable when using EncryptedFile from androidx.security.


Add a page for result encoding

When teachers click on a work, show them a page to encode the result

The result format is reversed:

TDV : A-D
RAN : xxx/100


Different global area for different languages.

I have a multilanguage site. I have some global areas inside that. I want to have different content for those global areas for different language. How can I achieve that.
Thanks in Advance.

github is not the right place to ask questions: you should use Slack

Thanks @mlocati . I have asked the question on slack.


Is there a way to make it generate unlimited codes?

Is there a way to make it generate unlimited codes? like so i don't need to enter a specific amount i wanna generate the codes until i manually stop the script.

Currently not, it will automatically stop if you didnt input a webhook, just set it as a really high amount, you can make a pr if you want to introduce the change yourself


docleaf is not available on arm64

Describe the bug
docleaf is not available on arm64
To Reproduce
Steps to reproduce the behavior:

pip3 install --user -r zephyr/scripts/requirements.txt

Expected behavior
Python packages installed
Impact
Break CI/CD on the ARM64 architecture to build native application
Logs and console output
$ west update
=== updating zephyr (zephyr):
--- zephyr: initializing
Initialized empty Git repository in /builds/xyz/workspace/zephyr/.git/
--- zephyr: fetching, need revision 630555d9f6ead7530b3d1e5a5fba96104607550c
....
OK

$ pip3 install --user -r zephyr/scripts/requirements.txt
Ignoring windows-curses: markers 'sys_platform == "win32"' don't match your environment
Ignoring python-magic-bin: markers 'sys_platform == "win32"' don't match your environment
Collecting pyelftools>=0.27
  Downloading pyelftools-0.29-py2.py3-none-any.whl (174 kB)
Requirement already satisfied: PyYAML>=5.1 in /usr/local/lib/python3.9/dist-packages (from -r zephyr/scripts/requirements-base.txt (line 11)) (6.0)
Requirement already satisfied: pykwalify in /usr/local/lib/python3.9/dist-packages (from -r zephyr/scripts/requirements-base.txt (line 14)) (1.8.0)
Collecting canopen
  Downloading canopen-2.1.0-py3-none-any.whl (60 kB)
Requirement already satisfied: packaging in /usr/local/lib/python3.9/dist-packages (from -r zephyr/scripts/requirements-base.txt (line 18)) (23.1)
Collecting progress
  Downloading progress-1.6.tar.gz (7.8 kB)
Collecting psutil
  Downloading psutil-5.9.5.tar.gz (493 kB)
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
    Preparing wheel metadata: started
    Preparing wheel metadata: finished with status 'done'
Collecting pylink-square
  Downloading pylink_square-1.2.0-py2.py3-none-any.whl (82 kB)
Collecting pyserial
  Downloading pyserial-3.5-py2.py3-none-any.whl (90 kB)
Collecting requests
  Downloading requests-2.31.0-py3-none-any.whl (62 kB)
Collecting anytree
  Downloading anytree-2.9.0-py3-none-any.whl (38 kB)
Collecting intelhex
  Downloading intelhex-2.3.0-py2.py3-none-any.whl (50 kB)
Requirement already satisfied: west>=0.14.0 in /usr/local/lib/python3.9/dist-packages (from -r zephyr/scripts/requirements-base.txt (line 33)) (1.1.0)
Requirement already satisfied: colorama in /usr/local/lib/python3.9/dist-packages (from -r zephyr/scripts/requirements-build-test.txt (line 7)) (0.4.6)
Collecting ply>=3.10
  Downloading ply-3.11-py2.py3-none-any.whl (49 kB)
Collecting gcovr>=4.2
  Downloading gcovr-6.0-py2.py3-none-any.whl (94 kB)
Collecting coverage
  Downloading coverage-7.3.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (229 kB)
Collecting pytest
  Downloading pytest-7.4.0-py3-none-any.whl (323 kB)
Collecting mypy
  Downloading mypy-1.5.1-py3-none-any.whl (2.5 MB)
Collecting mock>=4.0.1
  Downloading mock-5.1.0-py3-none-any.whl (30 kB)
ERROR: Could not find a version that satisfies the requirement docleaf==0.8.0
ERROR: No matching distribution found for docleaf==0.8.0

Environment (please complete the following information):

Use a raspberry PI with arm64 OS

doclead is being removed


ddim makes the generation worse

Hi, I met an issue that when I use ddim for the decoder sampling, the pics don't look good.

When I change the sample step to 1000, it comes to the following result.

Could I ask how to fix it?
The following is the ddim part of my code.
`    def p_sample_loop(self, unet, shape, image_embed, predict_x_start = False, learned_variance = False, clip_denoised = True, lowres_cond_img = None, text_encodings = None, text_mask = None, cond_scale = 1, is_latent_diffusion = False):
device = self.betas.device
    b = shape[0]
    img = torch.randn(shape, device = device)
    timesteps = 250
    times = torch.linspace(0., 1000, steps = timesteps + 2)[:-1]

    times = list(reversed(times.int().tolist()))
    time_pairs = list(zip(times[:-1], times[1:]))
    print(time_pairs)
    alphas = self.alphas_cumprod_prev
    if not is_latent_diffusion:
        lowres_cond_img = maybe(self.normalize_img)(lowres_cond_img)

    for time, time_next in tqdm(time_pairs, desc = 'sampling loop time step'):
        alpha = alphas[time]
        alpha_next = alphas[time_next]

        # print("alpha_next",alpha_next)
        # print("alpha_next1",alpha_next1)

        time_cond = torch.full((b,), time, device = device, dtype = torch.long)

        pred = unet.forward_with_cond_scale(img, time_cond, image_embed = image_embed, text_encodings = text_encodings, cond_scale = cond_scale, lowres_cond_img = lowres_cond_img)

        if learned_variance:
            pred, _ = pred.chunk(2, dim = 1)

        if predict_x_start:
            x_start = pred
            pred_noise = self.predict_noise_from_start(img, t = time_cond, x0 = pred)
        else:
            x_start = self.predict_start_from_noise(img, t = time_cond, noise = pred)
            pred_noise = pred

        if clip_denoised:
            s = 1.
            # clip by threshold, depending on whether static or dynamic
            x_start = x_start.clamp(-s, s) / s

        c1 = 1 * ((1 - alpha / alpha_next) * (1 - alpha_next) / (1 - alpha)).sqrt()
        c2 = ((1 - alpha_next) - torch.square(c1)).sqrt()
        noise = torch.randn_like(img) if time_next > 0 else 0.

        img = x_start * alpha_next.sqrt() + \
              c1 * noise + \
              c2 * pred_noise

    img = self.unnormalize_img(img)
    return img`

can you tell me the dataset you used thanks

can you tell me the dataset you used thanks

pics from Internet

can you tell me the dataset you used thanks

can you tell me the dataset you used thanks

pics from Internet

Can I see the code you trained


Corrected the twitter share  button README_EN.md.Solves the issue #293

Corrected twitter share button in readme_en.md by comparing it with readme.md.Closes the issue #293

@kazzyfrog idk how this got closed.Can i rasie a pr again?

@PAVAN507-STAR
Did you delete the forked repository by any chance?
If you deleted the forked repository before the changes were merged, the PR will be closed.
PR will incorporate changes in the fork repository, so if it is deleted, it will no longer work properly.

Yes please!
Thank you for your contribution!
If you have any other needs, we can support you👍

@kazzyfrog if u don't mind can u share what changes need to be done once again ,the readme seems to be changed

Sure!
Please replace the half-width spaces in line 393,
specifically in the text Start your OSS activity with a tutorial🚀, with %20.
This will allow the text to be treated as a single URL string.
This allows the user to be redirected to X site once the X-share button is pressed!


Assignees' name are not displaying when viewing task details

If you haven’t already, check out our contributing guidelines for onboarding and email<EMAIL_ADDRESS>to request to join our Slack channel!

Action Performed:

Create new task
Share somewhere and SELECT A GROUP
Create task
Click to view the details of created task at step 3

Expected Result:
Information about the assignee should be displayed
Actual Result:
No information about the person being shared the field TO now display only 1 avatar
Sometimes, the avatar under TO field changed randomly - (see above video at 1:25)
Workaround:
Can the user still use Expensify without this being fixed? Have you informed them of the workaround?
Platforms:

Which of our officially supported platforms is this issue occurring on?

[ ] Android / native
[ ] Android / Chrome
[ ] iOS / native
[ ] iOS / Safari
[x] MacOS / Chrome / Safari
[ ] MacOS / Desktop

Version Number: 1.3.32-5
Reproducible in staging?: y
Reproducible in production?: y
If this was caught during regression testing, add the test name, ID and link from TestRail:
Email or phone of affected tester (no customers):
Logs: https://stackoverflow.com/c/expensify/questions/4856
Notes/Photos/Videos: Any additional supporting documentation
https://github.com/Expensify/App/assets/43996225/03b049be-b79f-461c-9410-5522400ce729
https://github.com/Expensify/App/assets/43996225/0bd08013-c89d-4124-96b3-f1ee58e04090
Expensify/Expensify Issue URL:
Issue reported by: @tranvantoan-qn
Slack conversation: https://expensify.slack.com/archives/C049HHMV9SM/p1686883770678979
View all open jobs on GitHub

@sophiepintoraetz there is another way to make the avatar change randomly to:

Click on a task to view task details
Pin and Unpin it (repeatedly)

Avatar changed randomly
Avatar changed.mov

Clarifying the repro steps in slack

Properly discussing the expected behaviour for:

To field
Able to reproduce the changing avatar icon


WIP: Catapult plugin fixes

INFRA-1578: output the error from catapult more clearly
INFRA-1747: fail the entire build if catapult publish fails

Test catapult publish (on drone-staging using marathon-stats test branch):

[x] Successful publish with valid catapult URL (no regression)

[x] Correct behavior/result (check Dockerhub and /applications and /applications/marathon-stats/builds)
[x] No regression in output

[x] Failed publish with missing or no-proto catapult URL (it's checked explicitly)

[x] Correct behavior/result
[x] Clear error message in last lines of build output

[x] Failed publish with "valid-format" catapult URL (no parse error but POST fails when catapult server isn't actually running/reachable)

[x] Correct behavior/result
[x] Clear error message in last lines of build output

[x] Failed publish (valid catapult URL, use invalid launch yaml - see INFRA-1747)

[x] Correct behavior/result
[x] Clear error message in last lines of build output

Notes
Better. Now exits with nonzero code upon error, so (1) the entire Drone build fails if the publish step fails (2) the last line is generally the most relevant error message.
Still not amazing when the actual POST to catapult returns a non-200.
curl -w "%{http_code}" --output /dev/null means we only get back the HTTP code and don't log anything else (security concern or just reduce verbosity?). catapult should be idempotent, so copy-pasting the commands into your terminal without -o /dev/null is useful, but shouldn't be required.
Tried curl -w "\n%{http_code}" (manpage says \nshould work for newline), so in theorytail -n 1` would get the status code and the output is preserved, but it just adds a single space rather than newline.
Example output from bad launch yaml below. Using a raw curl, the second POST outputs: {"message":"Failed to fetch launch config for Application: yaml: did not find expected key"}
$
SC=$(curl -X POST -sL -w "%{http_code}" --output /dev/null -H "Content-Type: application/json" -d '{"id":"ecs-service-metrics","source":"github:clever/ecs-service-metrics","artifacts":"dockerhub:clever/ecs-service-metrics"}' https://peggy--catapult.int.clever.com/applications/)
if [ $SC -eq 500 ]; then
  SC=$(curl -X POST -sL -w "%{http_code}" --output /dev/null -H "Content-Type: application/json" -d '{"id":"ecs-service-metrics","source":"github:clever/ecs-service-metrics@03ff106d173b6eff01c2af70884a2a39a793150c","artifacts":"dockerhub:clever/ecs-service-metrics"}' https://peggy--catapult.int.clever.com/applications/)
fi
if [ $SC -eq 400 ]; then
  SC=$(curl -X PUT -sL -w "%{http_code}" --output /dev/null -H "Content-Type: application/json" -d '{"id":"ecs-service-metrics","source":"github:clever/ecs-service-metrics","artifacts":"dockerhub:clever/ecs-service-metrics"}' https://peggy--catapult.int.clever.com/applications/ecs-service-metrics)
fi

if [ $SC -ne 200 ]; then
  echo -e "Failed to publish catapult application"
	exit 1
fi

Failed to publish catapult application

@mohit - belated assign to you from yesterday.
I went through the cases (in the top comment) again to double-check the behavior. The only questionable case is an invalid hostname, where curl exits with a non-zero code. The buildfile writes set -e by default, so the build exits/fails before we can check the HTTP code (000) and do any additional logging.
Since we're trying to automate params and very rarely encounter bad catapult_urls, I think it makes sense to optimize for cases where the catapult server rejects an application/build for some reason.

@peggyl is there an example build where I can see this in action?

@mohit I'm going to change the WriteCmd to WriteCmdSilent, then redeploy the new build and check the resulting output to see if we can keep that change.

Examples:
http://drone-staging.ops.clever.com/github.com/Clever/marathon-stats/ci-test/db1c495676606c70fdda99a55dbd494e6f7b934f

Invalid catapult URL (https://fakeenv--catapult.int.clever.com)

TODO

Good catapult URL
Good build, should publish

TODO

Good catapult URL
Bad build, should not publish

Hm, #3 should have failed. This should not be valid yaml syntax as far as I know... https://github.com/Clever/marathon-stats/commit/899abe22383b956bdb8b3f9ddc46fe496e94d9e1

@nathanleiby @mohit Updated the output - it's a little more verbose since I added both human-friendly updates as well as all the curl commands and responses (for non-200), but I think it's pretty debugging-friendly now (and people generally do not check logs upon a success unless they expected a test to fail). Let me know what you think.

lgtm -- my priorities are that (1) it's correct (2) it errors/fails appropriately (3) it has more logging. looks like it meets all those.
hopefully we can move to a non-bash solution not toooo far in the future!

@mohit does example build output on https://github.com/Clever/drone/pull/45#issuecomment-224450720 look okay to you?

LGTM


2023-2024 Playoff Data

Adjust all statistical functions to include the option of selecting 2023-2024 Regular Season stats or 2023-2024 Playoff Stats

This addition will be added by midnight on March 27th, 2024.

The RawStats function has been updated locally to reflect the addition of the 2024 Playoff data. All remaining fuctions need to be adjusted before launch.

More functions have been adjusted locally. Still on track for March 27th, 2024 release.

The package will be released this evening.

Completed - Version 2.0.0


#3883 remove non-existent host

The domain rakudo.party no longer exists. Since Undercover bot only differs from SourceBaby because it points to wtf.rakudo.party,
this link is pointless. Zoffix, perhaps could point to a different domain???
The problem
Solution provided

Zoffix is, unfortunately, out of the picture, and that site has not been updated. Closest thing is Blin, I guess.


Monaco toolbox colors don't match Blockly colors

This is a regression, perhaps due to the recent language service updates.

Fixed


Include HF transformer model tests for gaudi devices

What does this PR do?

Fixes # (issue)
Before submitting

[ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
[ ] Did you make sure to update the documentation with your changes?
[ ] Did you write any new necessary tests?

This PR includes the model test cases found in : https://github.com/huggingface/transformers/tree/main/tests/models
and adapts them to run on Gaudi devices. Following models are included as part of this PR, the other supported models will be added in subsequent runs. This TCs runs the basic model functionality on a scaled down model which enables faster execution.
The eventual goal is to include these as part of our internal promote jobs so that regressions can be avoided.
Models Included in this PR :

T5
GPT2
GPTJ
GPTNEOX
Bridgetower

Here is the current status of the run ( Ran on Gaudi coral simulator):
Optimum Habana Transformers :

T5 :
================================================================================== short test summary info ==================================================================================
FAILED test_modeling_t5.py::T5ModelTest::test_beam_sample_generate - NotImplementedError: Beam search sampling is not supported by optimum-habana yet.
FAILED test_modeling_t5.py::T5ModelTest::test_beam_sample_generate_dict_output - NotImplementedError: Beam search sampling is not supported by optimum-habana yet.
FAILED test_modeling_t5.py::T5ModelTest::test_beam_search_generate - KeyError: 'limit_hpu_graphs'
FAILED test_modeling_t5.py::T5ModelTest::test_beam_search_generate_dict_output - KeyError: 'limit_hpu_graphs'
FAILED test_modeling_t5.py::T5ModelTest::test_beam_search_generate_dict_outputs_use_cache - KeyError: 'limit_hpu_graphs'
FAILED test_modeling_t5.py::T5ModelTest::test_constrained_beam_search_generate - KeyError: 'limit_hpu_graphs'
FAILED test_modeling_t5.py::T5ModelTest::test_constrained_beam_search_generate_dict_output - KeyError: 'limit_hpu_graphs'
FAILED test_modeling_t5.py::T5ModelTest::test_generate_with_head_masking - RuntimeError: [Rank:0] FATAL ERROR :: MODULE:PT_BRIDGE Exception in acc thread pool task has been thrown: Got a non-HPU tensor, expecting an HPU tensor
FAILED test_modeling_t5.py::T5ModelTest::test_generate_with_past_key_values - NotImplementedError: Beam search sampling is not supported by optimum-habana yet.
FAILED test_modeling_t5.py::T5ModelTest::test_greedy_generate - KeyError: 'limit_hpu_graphs'
FAILED test_modeling_t5.py::T5ModelTest::test_greedy_generate_dict_outputs - KeyError: 'limit_hpu_graphs'
FAILED test_modeling_t5.py::T5ModelTest::test_greedy_generate_dict_outputs_use_cache - KeyError: 'limit_hpu_graphs'
FAILED test_modeling_t5.py::T5ModelTest::test_group_beam_search_generate - NotImplementedError: Group beam search is not supported by optimum-habana yet.
FAILED test_modeling_t5.py::T5ModelTest::test_group_beam_search_generate_dict_output - NotImplementedError: Group beam search is not supported by optimum-habana yet.
FAILED test_modeling_t5.py::T5ModelTest::test_model_fp16_forward - RuntimeError: float16/half is not supported on Gaudi.
FAILED test_modeling_t5.py::T5ModelTest::test_resize_tokens_embeddings - AssertionError: ValueError not raised
FAILED test_modeling_t5.py::T5ModelTest::test_sample_generate - KeyError: 'limit_hpu_graphs'
FAILED test_modeling_t5.py::T5ModelTest::test_sample_generate_dict_output - KeyError: 'limit_hpu_graphs'
FAILED test_modeling_t5.py::T5EncoderOnlyModelTest::test_model_fp16_forward - RuntimeError: float16/half is not supported on Gaudi.
============================================================ 19 failed, 109 passed, 60 skipped, 31 warnings in 102.49s (0:01:42) ============================================================

GPT2

=================================================================================== short test summary info ====================================================================================
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_assisted_decoding_sample - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_beam_sample_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_beam_sample_generate_dict_output - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_beam_search_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_beam_search_generate_dict_output - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_beam_search_generate_dict_outputs_use_cache - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_constrained_beam_search_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_constrained_beam_search_generate_dict_output - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_contrastive_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_contrastive_generate_dict_outputs_use_cache - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_contrastive_generate_low_memory - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_generate_from_inputs_embeds_decoder_only - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_generate_without_input_ids - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_gpt2_token_classification_model - NameError: name 'GPT2ForTokenClassification' is not defined
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_greedy_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_greedy_generate_dict_outputs - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_greedy_generate_dict_outputs_use_cache - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_group_beam_search_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_group_beam_search_generate_dict_output - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_pipeline_text_generation - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_resize_tokens_embeddings - AssertionError: ValueError not raised
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_sample_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_sample_generate_dict_output - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_torch_fx - AssertionError: Couldn't trace module: Proxy object cannot be iterated. This can be attempted when the Proxy is used in a loop or as a *args or **kwargs function argument. See the torch.f...
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_torch_fx_output_loss - AssertionError: Couldn't trace module: Proxy object cannot be iterated. This can be attempted when the Proxy is used in a loop or as a *args or **kwargs function argument. See the torch.f...
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_training - RuntimeError: Function torch::autograd::CppNode returned an invalid gradient at index 1 - expected device cpu but got hpu:0
FAILED test_modeling_gpt2.py::GPT2ModelTest::test_training_gradient_checkpointing - RuntimeError: Function torch::autograd::CppNode returned an invalid gradient at index 1 - expected device cpu but got hpu:0
============================================================== 27 failed, 49 passed, 51 skipped, 8 warnings in 113.34s (0:01:53) ==============================================================

GPTJ

=================================================================================== short test summary info ====================================================================================
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_assisted_decoding_sample - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_beam_sample_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_beam_sample_generate_dict_output - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_beam_search_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_beam_search_generate_dict_output - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_beam_search_generate_dict_outputs_use_cache - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_constrained_beam_search_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_constrained_beam_search_generate_dict_output - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_contrastive_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_contrastive_generate_dict_outputs_use_cache - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_contrastive_generate_low_memory - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_generate_from_inputs_embeds_decoder_only - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_generate_without_input_ids - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_greedy_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_greedy_generate_dict_outputs - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_greedy_generate_dict_outputs_use_cache - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_group_beam_search_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_group_beam_search_generate_dict_output - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_resize_tokens_embeddings - AssertionError: ValueError not raised
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_sample_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_sample_generate_dict_output - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_torch_fx - AssertionError: Couldn't trace module: 'len' is not supported in symbolic tracing by default. If you want this call to be recorded, please call torch.fx.wrap('len') at module scope
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_torch_fx_output_loss - AssertionError: Couldn't trace module: 'len' is not supported in symbolic tracing by default. If you want this call to be recorded, please call torch.fx.wrap('len') at module scope
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_training - AttributeError: 'NoneType' object has no attribute 'backward'
FAILED gptj/test_modeling_gptj.py::GPTJModelTest::test_training_gradient_checkpointing - AttributeError: 'NoneType' object has no attribute 'backward'
=================================================================== 25 failed, 49 passed, 42 skipped, 14 warnings in 44.87s ====================================================================

GPTNEOX:

=================================================================================== short test summary info ====================================================================================
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_assisted_decoding_sample - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_beam_sample_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_beam_sample_generate_dict_output - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_beam_search_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_beam_search_generate_dict_output - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_beam_search_generate_dict_outputs_use_cache - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_constrained_beam_search_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_constrained_beam_search_generate_dict_output - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_contrastive_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_contrastive_generate_dict_outputs_use_cache - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_contrastive_generate_low_memory - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_decoder_model_past_large_inputs - RuntimeError: synNodeCreateWithId failed for node: rotary_pos_embedding_fwd_f32 with synStatus 26 [Generice failure]. .
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_generate_from_inputs_embeds_decoder_only - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_generate_without_input_ids - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_greedy_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_greedy_generate_dict_outputs - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_greedy_generate_dict_outputs_use_cache - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_group_beam_search_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_group_beam_search_generate_dict_output - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_model_rope_scaling_0_linear - RuntimeError: synNodeCreateWithId failed for node: rotary_pos_embedding_fwd_f32 with synStatus 26 [Generice failure]. .
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_model_rope_scaling_1_dynamic - RuntimeError: synNodeCreateWithId failed for node: rotary_pos_embedding_fwd_f32 with synStatus 26 [Generice failure]. .
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_resize_tokens_embeddings - AssertionError: ValueError not raised
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_sample_generate - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_sample_generate_dict_output - TypeError: pad(): argument 'pad' must be tuple of ints, but found element of type NoneType at pos 2
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_training - AttributeError: 'NoneType' object has no attribute 'backward'
FAILED gpt_neox/test_modeling_gpt_neox.py::GPTNeoXModelTest::test_training_gradient_checkpointing - AttributeError: 'NoneType' object has no attribute 'backward'
=================================================================== 26 failed, 52 passed, 37 skipped, 12 warnings in 32.90s ====================================================================

Bridgetower :
=================================================================================== short test summary info ====================================================================================
FAILED bridgetower/test_modeling_bridgetower.py::BridgeTowerModelTest::test_for_image_and_text_retrieval - RuntimeError: Input type (torch.FloatTensor) and weight type (HPUFloatType) should be the same or input should be a MKLDNN tensor and weight is a dense tensor
FAILED bridgetower/test_modeling_bridgetower.py::BridgeTowerModelTest::test_for_masked_language_modeling - RuntimeError: Input type (torch.FloatTensor) and weight type (HPUFloatType) should be the same or input should be a MKLDNN tensor and weight is a dense tensor
FAILED bridgetower/test_modeling_bridgetower.py::BridgeTowerModelTest::test_hidden_states_output - RuntimeError: Input type (torch.FloatTensor) and weight type (HPUFloatType) should be the same or input should be a MKLDNN tensor and weight is a dense tensor
FAILED bridgetower/test_modeling_bridgetower.py::BridgeTowerModelTest::test_model - RuntimeError: Input type (torch.FloatTensor) and weight type (HPUFloatType) should be the same or input should be a MKLDNN tensor and weight is a dense tensor
FAILED bridgetower/test_modeling_bridgetower.py::BridgeTowerModelTest::test_retain_grad_hidden_states_attentions - RuntimeError: Input type (torch.FloatTensor) and weight type (HPUFloatType) should be the same or input should be a MKLDNN tensor and weight is a dense tensor
FAILED bridgetower/test_modeling_bridgetower.py::BridgeTowerModelTest::test_save_load - RuntimeError: Input type (torch.FloatTensor) and weight type (HPUFloatType) should be the same or input should be a MKLDNN tensor and weight is a dense tensor
==================================================================== 6 failed, 33 passed, 48 skipped, 8 warnings in 26.39s =====================================================================

@regisss  , @ZhaiFeiyue  : please check and help with merging these, Thank you.

@ankurneog @ZhaiFeiyue Sure, it would be great to be able to run all the tests from Transformers. That being said, it will require a lot of time to adapt them to Optimum Habana as we cannot copy-paste them and expect them to pass as it is done in this PR (otherwise I would have done it a long time ago).
A few remarks after taking a quick look at the PR:

Most errors reported here are not related to Optimum Habana. We cannot use Transformers on Gaudi as it is otherwise Optimum Habana would be pointless.
I don't understand why TF and Flax tests were copy-pasted here, Optimum Habana doesn't support these frameworks.
Pipelines are not officially supported. While they should work, they should not be part of the CI as it is not a priority to support them at the moment.
Tests should not be implemented in optimum/habana/ as they are not part of the source code.

So, while having all these tests here would be nice, I don't think that's a priority at the moment. Besides, I don't have an ETA for when we can enable them. As I said before, making sure tests are correctly implemented for Gaudi will take some time, and even more time to maintain for each Transformers release.
The best would be to have a PR open here (not from a fork) where we could be several to push so that we can advance faster. Let me discuss that with Sree and I'll give you an update.

The intention was to take the content as is from the HF transformer repo , so that we can check the coverage in Gaudi, so instead of changing the TCs , we can mark them as skipped with a comment.

Okay, that sounds good. But I would still remove the test files with names that include fp16 (not supported on Gaudi and never will be I guess) or tf and flax (not supported in Optimum Habana and it's not planned). Otherwise, users may think that we will add support for that later.

Pipelines was copied as the test files uses it and it would need unnecessary refactoring.

At least the files in tests/pipelines should be removed, this should not require any refactoring.

The directory structure was made similar to the HF transformer repo, so there is one to one match between the directory in the HF transformers/tests and optimum-habana transformers. Again the intention is to keep a single reference point ( HF transformers)

I understand that, but we cannot have these tests in the source code of the lib. Otherwise, users will be able to import from optimum.habana.transformers.tests and we don't want that.
To explain more:

transformers/src/transformers corresponds to optimum-habana/optimum/habana/transformers
transformers/tests (note that these tests are not in src and thus are not part of the source code of the package) should correspond to optimum-habana/tests/transformers (there is currently no repo called transformers in tests but let's create it).

We believe that this will greatly add value , since the runs are fast on the strip down model and we get to evaluate regressions in the ops. For eg: recent regression of segv in the GPTNeox model.

I'm sure it will, but I'm mainly saying that adding all those tests is not that straightforward and requires some time to maintain.

Thanks @regisss on the details.
Let me see if I can move the Content to optimum-habana/tests
As
optimum-habana/tests/transformers/tests/models
I will also check how I can address your other comments.


Support builtin types other than string

The capabilities.json allows us to specify custom functions with a specific return type.  I would like to return a boolean, but OpaPolicy.RegisterBuiltin(string, Func<string, bool> func) is not a possible overload.  I do see that the _registeredBuiltins is a Dictionary<string, object> so it should be able to support what I'm after.
In this proposed solution, the RegisterBuiltin overloads are generics that wrap the callback parameter with another func to handle converting the object pointers to their correct types.

https://github.com/christophwille/dotnet-opa-wasm/pull/22#issuecomment-958685402
We had that discussion before - why do we need a level of indirection at this layer?

And one other thing comes to mind when deserializing this way (typed instead of string) - thread culture.

And one other thing comes to mind when deserializing this way (typed instead of string) - thread culture.

I don't follow what you mean by "deserializing this way."  The library currently does JsonSerializer.Deserializer<string>(dumpedJsonValue).  The only thing I changed there was using generics to parameterize which type it gets deserialized as.

#22 (comment)
We had that discussion before - why do we need a level of indirection at this layer?
Edit: https://github.com/christophwille/dotnet-opa-wasm/blob/master/src/Opa.Wasm.UnitTests/BuiltinTests.cs#L30 I mean doing it in the lambda (and then calling a typed method of yours)

Using a single lambda of known types (the arg addresses) in a closure, I can avoid using costly reflection to figure out which type the argument is to deserialize it correctly for a user. I do mean deserialize correctly, too. There are 2 problems with the way the library is currently written, and this solution solves both problems:

I cannot return anything to a rego from my custom function but strings.  This forces a rego to do an extra deserialization step that should have been the responsibility of the called function.
I can only pass strings to my custom function, and I do mean only strings.  If, in my rego I call custom.func(3), the library will break because this will not properly deserialize.  Likewise for enumerables, or objects.

json = DumpJson(addr); // value of json is "3" here, not "\"3\""
JsonSerializer.Deserialize<string>(json); // breaks
----
json = "[\"value\", \"object\"]";
JsonSerializer.Deserialize<string>(json); // breaks

If the goal is to have the library only return strings and let the caller do serialization concerns, then DumpJson(addr) needs to be returned directly - and this is immediately less convenient because even simple string parameters have to be deserialized by calling code. It would then also then be the user's responsibility to serialize a return type so the library only directly calls LoadJson() when returning a value.  Otherwise, you run the risk of different serializer settings being used between reads/writes.

The (potential) issue re:culture - when you serialize a float say 3.14159 with US culture, you get exactly that. If you do it in a German culture, you get 3,14159. I haven't ever tried that with the new STJ serialization (but it happened with a different serializer way back in the day in SharpDevelop - we shipped settings that were serialized US, and the target system happened to be German, and obviously it didn't deserialize properly). We need to verify that.

Ah, that's what you meant. I didn't think about that. I'll check it out later. I'm more curious to know about what the wasm will support. It might be in our interest to explicitly set SerializerSettings to force what opa expects.
I have another branch where I was starting to flesh out some abstractions to make Microsoft dependency injection simple. As part of that, there would be a serializer interface that users could configure to have the library use their settings instead of default. That's a much broader set of breaking changes, though, and probably worth a major version bump instead of a simple PR.
Thanks,
Will H.

From: Christoph Wille @.>
Sent: Sunday, January 30, 2022 2:51:41 AM
To: christophwille/dotnet-opa-wasm @.>
Cc: Will Hausman @.>; Author @.>
Subject: Re: [christophwille/dotnet-opa-wasm] Support builtin types other than string (PR #30)
The (potential) issue re:culture - when you serialize a float say 3.14159 with US culture, you get exactly that. If you do it in a German culture, you get 3,14159. I haven't ever tried that with the new STJ serialization (but it happened with a different serializer way back in the day in SharpDevelop - we shipped settings that were serialized US, and the target system happened to be German, and obviously it didn't deserialize properly). We need to verify that.
—
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Added a test that shows serialization working in de-DE culture.
This is noteworthy.  https://play.openpolicyagent.org/p/jbCZm4XTTd We really want to avoid putting the wrong serialization in place.  Suggests to me that maybe the library should concern itself with more serialization and just expose the ability to interact with raw json for the undaunted.

I have another branch where I was starting to flesh out some abstractions to make Microsoft dependency injection simple. As part of that, there would be a serializer interface that users could configure to have the library use their settings instead of default. That's a much broader set of breaking changes, though, and probably worth a major version bump instead of a simple PR.

can you please open an issue with your ideas (before doing a PR)?

Thanks for your contribution!


Feature Request: Hide module when nothing ist playing

Title says it all: Hide the module when nothing is playing, both for minibar and normal mode (and free the space the module needs when visible!)

Thank you for creating this issue. I will close it, as it is a duplicate of #176


D.shaped.exit.hole.count must be filled "0" if there are none

@briannakcalkins , I'm reviewing the errors that persisted after your fixes yesterday. Most of them seem to because of NA's in D.shaped.exit.hole.count:

This issue is just FYI. You can close this once you've read it.

These are legitimately NA if DE is not included in the EABF field. @ValentineHerr , we'll want to modify the tests accordingly. I'll fix the list of tests when I have a moment.

@ValentineHerr , this is a common unnecessary error. Could you please fix it as soon as you get a chance?
Specificially, "missing_EAB_info" should not be triggered if D.shaped.exit.hole.count = NA unless DE is selected in the EABF field.

should be done now.

Thanks! This should clean up a  lot of errors. Looks like the tests failed to run though.

ha... sorry, I didn't have the time to wait for it and I am back at it only now. Will fix it once I understand what is going on.

Thanks!


fix(treasury): fix distribute condition

Changed the distribute() function's running condition.

Now, it depends on block.timestamp instead of the distributable amount to prevent overpaying interest to past depositors.

Also, I added two unit tests.

Call distribute() in the same block.
When the distribution amount is zero.

Codecov Report

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Travis CI build fail due to OpenCL 1.2 header requirement

Travis CI seems to provide OpenCL 1.2 headers only. The recently pushed in code requires OpenCL 1.2 and later header files.

fixed with pull request #85


test: Give initial VM more memory for running tests

The introduction of ControllerSuite.TestBackup has caused the following types of errors in CI:
    t.Assert(run(t, exec.Command("cp", "-r", filepath.Join("apps", nameOrURL), dir)), Succeeds)
... result *main.CmdResult = &main.CmdResult{Cmd:[]string{"cp", "-r", "apps/empty", "/tmp/check-6334824724549167320/0/repo"}, Output:"", Err:(*os.PathError)(0xc23fc6f3b0)}
... command failed with error: fork/exec /bin/cp: cannot allocate memory

Giving the initial VM more memory should prevent this from being an issue.

LGTM


Support code snippets as parameters in Discord.Net.Commands

Currently, if a parameter such as
`hello, i am some code`

is used, it will not yield "hello, i am some code", likewise, the following examples have the same issue
```C
int x = 0;```

```
hello, i am more code```

ParameterType.Unparsed in 0.9, or [Remainder] in 1.0.

In 1.0, you can make your own type reader. I would strongly recommend making one for this.
It would also allow you to take advantage of the language indicator for hints to pass to your evaluator.
But anyways, the functionality of you being able to create your own Type Readers was for this very purpose, so we didn't have to cover every situation, especially when there would be difference of opinion on implementation.


ClarifyBreakable in ModelicaReference

Remove "breakable branch" from connect (since it is confusing).
As decided in https://trac.modelica.org/Modelica/ticket/2201
Also try to explain Connections.branch in a clearer way: both that it is required to be part of spanning-tree, whereas connect is optional for the spanning-tree; and also that Connections.branch does not generate equation - but assumes that equations are present; whereas connect generates equations.

Thanks!


optimize CNI logs and codes

Signed-off-by: Icarus9913<EMAIL_ADDRESS>What type of PR is this?
/kind cleanup
What this PR does / why we need it:
improve the CNI logs and optimize the codes

/lgtm
/approve


cfn-lint doesn't support GovCloud targeted templates.

Is this feature request related to a new rule or cfn-lint capabilities?
New capability
Describe the feature you'd like to request
cfn-lint doesn't recognize the ARNs for govcloud items as valid.
[cfn-lint] W1031: {'Fn::Sub': 'arn:aws-us-gov:iam::${AWS::AccountId}/managed-by-org/test-policy'} does not match 'arn:(aws[a-zA-Z-]*)?:iam::(\d{12}|aws):policy/[a-zA-Z_0-9+=,.@\-_/]+' when 'Fn::Sub' is resolved
Describe the solution you'd like
Allow cfn-lint to be aware of GovCloud ARNS.
Additional context
No response
Is this something that you'd be interested in working on?

[ ] 👋 I may be able to implement this feature request

Would this feature include a breaking change?

[ ] ⚠ This feature might incur a breaking change

arn:aws-us-gov:iam::${AWS::AccountId}/managed-by-org/test-policy this doesn't look quit right to me.
From the docs I have a policy arn as arn:aws:iam::123456789012:policy/ManageCredentialsPermissions. I don't see :policy in your Sub string.


HRTF panning

#44
I used hrtf crate and an ircam HRTF file. Convert azimuth/elevation to required sample_vec for the HrtfContext
It took me a lot of time to get the coordinate system right and feed it into the hrtf crate properly.
The result is subtle, but audible for me. I created a spectogram of the result and it shows more lower frequencies when the panner object is behind the listener.
HRTF file downloaded from http://recherche.ircam.fr/equipes/salles/listen/download.html
after examining http://recherche.ircam.fr/equipes/salles/listen/sounds.html I found this one works best for me.
TODO:

[x] tail time
[x] update panning model type while running
[ ] choose the best HRTF file - check license
[x] embed HRTF file in library

It's not entirely clear to me if there are license or attribution requirements for the Ircam files, or we can just ship them inside our lib

Hey, didn't have the time to test or look at the code yet but looks promising, congrats!
Just a few notes on the HRTF file itself (I just asked to a colleague from the spat team):

the database you use is outdated, there is a more recent one called Bili that has been released since (can't find the link right now)
integrating the file directly into the library may also be touchy because the files are copyrighted. I will need to ask to the head of the team for more information and know if we can do that (considering it's an open-source project etc.)

Cool, thanks for digging in. I won't merge before we get the final answer on this

(didn't receive any answer yet about the HRTF file... I will retry next week)

Hey, finally some (quite good) news on that point. I managed to have a talk with the head of the spat team who is ok that we use one of their file. Few points:

He confirmed the file you used is quite old and pointed me to a more recent database, (unfortunately I don't have my notebook right now, so I'll give you the link tomorrow...). The database works with the SoFa protocol so we might have to do some work to just retrieve what we need (I could probably help here using this https://github.com/Ircam-RnD/serveSofaHrir), also there are each time 2 versions of the HRTF: one for implementation based on convolution and one based on some kind of (probably much more efficient) bank of IIR filters (but it doesn't seem the lib you used implements that strategy and while I can vaguely figure out the principles, I wouldn't try implementing that myself...)
We should also add some Acknowledgement in the README saying where the impulses comes from, and also that any problems comes from our implementation and not from the HRTF files

actually this could be interesting to check: https://github.com/Ircam-RnD/binauralModeled

@b-ma shall I merge this version? Or do you have the more recent databases at hand?

Or do you have the more recent databases at hand?

Arg no, I can send you the link tomorrow

shall I merge this version?

Let me just check w/ the spat team that they are ok with the acknowledgements

Alright!


Capturing EventSource with perfcollect

@brianrob in https://github.com/tmds/Tmds.LinuxAsync/issues/53#issuecomment-596023594 you commented:

perfcollect is harder to use with EventSource because LTTng doesn't allow for dynamic registration of tracepoints. Instead, all EventSources emit via a single tracepoint called EventSource. Then you can control exactly which events are emitted via an environment variable. It's really not ideal.

What should we do to include events from a specific source when using perfcollect?
cc @antonfirsov @adamsitnik

It turns out that there wasn't a great way to get EventSource events into a trace file, so I just pushed #1163 to fix this.
You can run ./perfcollect collect <traceName> -events EventSource
This will enable all EventSources.  You can then filter them by telling the runtime which ones you want.  There are two COMPlus variables for this.
See https://github.com/dotnet/runtime/blob/70bfd2ac9b844701c361b90b90ef399ae6fec483/src/libraries/System.Private.CoreLib/src/System/Diagnostics/Tracing/TraceLogging/XplatEventLogger.cs#L20

@brianrob this is great!
@sebastienros could you please update the perfcollect used by aspnet machines?

@brianrob thanks!


Can't resolve '../../StyledIconBase'

I tried to upgrade from 6.4.0 to 7.1.0 today and hit the following error:
> Failed to build
{ Error: (client) ../node_modules/styled-icons/boxicons-regular/LoaderAlt/LoaderAlt.esm.js
Module not found: Error: Can't resolve '../../StyledIconBase' in '/home/circleci/project/node_modules/styled-icons/boxicons-regular/LoaderAlt'
 @ ../node_modules/styled-icons/boxicons-regular/LoaderAlt/LoaderAlt.esm.js 3:0-54 8:32-46
 @ ./components/StyledSpinner.js
 @ ./components/StepsProgress.js
 @ ./pages/createOrderNewFlow.js
 @ multi ./pages/createOrderNewFlow.js
    at /home/circleci/project/node_modules/next/dist/build/index.js:144:31
    at finalCallback (/home/circleci/project/node_modules/webpack/lib/MultiCompiler.js:247:12)
    at runWithDependencies.err (/home/circleci/project/node_modules/webpack/lib/MultiCompiler.js:270:6)
    at done (/home/circleci/project/node_modules/neo-async/async.js:2920:13)
    at runCompilers (/home/circleci/project/node_modules/webpack/lib/MultiCompiler.js:174:48)
    at err (/home/circleci/project/node_modules/webpack/lib/MultiCompiler.js:181:7)
    at compiler.run (/home/circleci/project/node_modules/webpack/lib/MultiCompiler.js:263:7)
    at finalCallback (/home/circleci/project/node_modules/webpack/lib/Compiler.js:204:39)
    at hooks.done.callAsync.err (/home/circleci/project/node_modules/webpack/lib/Compiler.js:220:13)
    at AsyncSeriesHook.eval [as callAsync] (eval at create (/home/circleci/project/node_modules/tapable/lib/HookCodeFactory.js:32:10), <anonymous>:33:1)
    at AsyncSeriesHook.lazyCompileHook (/home/circleci/project/node_modules/tapable/lib/Hook.js:154:20)
    at onCompiled (/home/circleci/project/node_modules/webpack/lib/Compiler.js:218:21)
    at hooks.afterCompile.callAsync.err (/home/circleci/project/node_modules/webpack/lib/Compiler.js:547:14)
    at AsyncSeriesHook.eval [as callAsync] (eval at create (/home/circleci/project/node_modules/tapable/lib/HookCodeFactory.js:32:10), <anonymous>:15:1)
    at AsyncSeriesHook.lazyCompileHook (/home/circleci/project/node_modules/tapable/lib/Hook.js:154:20)
    at compilation.seal.err (/home/circleci/project/node_modules/webpack/lib/Compiler.js:544:30)

I guess it comes from https://github.com/jacobwgillespie/styled-icons/pull/612, probably because we don't use Typescript? I've downgraded to 7.0.0 and it works correctly.
Otherwise thanks for the automatic support of CommonJS and ES Modules code, that's a great change for us!

Thanks for catching this - not TypeScript, just a misconfiguration on my part that omitted that file from the NPM package. 😞 I really need to get integration tests running that use the .tgz from npm pack to catch stuff like this.
It's building now and should be fixed in v7.1.1.  It does speed up TypeScript type-checking quite a bit, but you may also see some frontend performance improvements (reduced memory probably) when rendering multiple icons, since they share most of the heavy logic inside a common component now.

This has been fixed in v7.1.1 - sorry for the disruption!


No more updates?

It's been a few months since the last update, and I was wondering if someone is still working on this repo. If not, I'll have to switch to something else.

Sounds great!


Can you feed many images when training an embedding?

I saw this text while training an embedding for the shuimo embedding.
I named the embedding test1 and give it access to images folder with only one image inside it (shuimo.jpg).

So I speculated that you can feed more than one image to train an embedding.
Is it true that I can feed more images to training process and would that theoretically improve performance?

I tried with 3 images of 3 different characters drawn by same artist, but did not achieve any success. After running over 12000 steps, the model would just keep cycling between trying to represent each image in dataset in a very blurry way.

Multiple images depicting the same object or style is possible to improve the performance. If you think the result is not good enough, you can try the newly released and improved version of DreamArtist++. https://github.com/7eu7d7/HCP-Diffusion/issues


Change EnqueueAsync to TryEnqueue

Just change in the code snippet, that's all!
DispatcherQueue dispatcherQueue = DispatcherQueue.GetForCurrentThread();
dispatcherQueue.TryEnqueue(...

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 6c7574e6-1b97-b6f7-f554-252ff896cf64
Version Independent ID: fedc454f-3887-6645-afdb-8468be6658b4
Content: DispatcherQueueExtensions - Windows Community Toolkit
Content Source: docs/extensions/DispatcherQueueExtensions.md
Product: community-toolkit
GitHub Login: @Sergio0694
Microsoft Alias: mhawker

@ArchieCoder Which section are you referring to?  The top code snippet, or the bottom code snippet (for "Migrating from DispatcherHelper")?

@XAML-Knight Everywhere, the method EnqueueAsync does not exist anymore. It is TryEnqueue.

@XAML-Knight Everywhere, the method EnqueueAsync does not exist anymore. It is TryEnqueue.

@ArchieCoder just FYI the method EnqueueAsync  is in the DispatcherQueueExtensions in Microsoft.Toolkit.Uwp ;)

Yeah, that's what this article is referring to, the API helper in the Toolkit which makes this more natural to use.
Maybe if anything the example code needs the using statement at the top to make that more clear?


Update client.py

because the intention is good but instead receives an annoying print.

@zodman please, can you make the change in _async section and execute the make build_sync command?

@zodman thank you very much for your contribution


Document how recursion works compared to the VM

Focus on limitations related to the stack size and provide an example where Native throws a stack overflow error.

@gabrielbosio To prevent stack overflow errors due to deep recursion:
Increase Stack Size: In some environments, such as Node.js, you can increase the stack size via command-line options (node --stack-size=SIZE).
Switch to Iteration: Instead of using recursion, you can refactor the code to use an iterative approach (loops), which doesn't consume additional stack space.
Use Tail Recursion: If the language supports it, ensure your recursive functions are tail-recursive to enable optimization.


atsec/4 - Section <IP_ADDRESS>.3 - Type FCS_COP.1/SK

paragraph 313
Comment:
FCS_COP.1/SK should be replaced by "FCS_COP.1/SKC" in paragraph 313.
Proposal:
Replace "FCS_COP.1/SK" with "FCS_COP.1/SKC".
Priority: 1

Agreed to move to v1.1 at this time.

Combine into editorial SD TD rollup

https://github.com/DSC-iTC/DSC-iTC.github.io/pull/4


DefaultHttp2ConnectionDecoder notifies frame listener before connection of GOAWAYS

Motivation:
Users of the DefaultHttp2ConnectionDecodcer are notified of inbound GoAwayFrames
after the connection has already closed any ignored streams, potentially
losing the signal that some streams may have been ignored by the peer and
are thus retryable.
Modifications:
Reorder the notifications of the frame and connection listeners to
propagate the frame first, giving the frame listeners the opportunity to
clean up ignored streams in their own way.
Result:
Fixes #9986

See also https://github.com/netty/netty/pull/10002 for a version that fixes this for users of the Http2FrameCodec, but I don't think is as good.

@netty-bot test this please

@bryce-anderson thanks a lot!


Magisk Module Update.Json

Add support for the module updating mechanism now in the magisk manager.

It's ready and waiting for merge #22

That pull request has been merged


Custom ssl engine parameters

Deploying tomcat with a custom ssl engine could require to perform some extra configuration before its usage. As an example, tomcatjss project needs to provide the actual IPs of client and server for audit purpose.
To provide the IPs we are working on a patch which require to copy several tomcat methods from NIO endpoint and channel because the current implementation does not allow to access the ssl engine before it is used (the method to be replaced are in this PR).
Changes in this PR allow to extend tomcat NIO classes and modify the ssl engine without reimplementing the existing methods.

The only thing that caught my eye was that the signature of AbstractNetworkChannelEndpoint.createChannel has changed by widening the return value from NetworkChannel to Channel. This change is not backward compatible and we might want to introduce a new method instead of changing the signature of the current one.

Hi @ChristopherSchultz, the AbstractNetworkChannelEndpoint.createChannel is introduced by this PR so I am not sure this is widening the return value. Currently, the channel is created inside the method NioEndpoint.setSocketOptions and does not invokes other methods. I have introduced the createChannel so I can override  it in a subclass  and associate a different channel keeping the endpoint logic.
The only problem with back-porting I can think of it is that classes extending the AbstractNetworkChannelEndpoint will need to implement this method. To avoid this I can convert to a concrete method which throw an exception when invoked. In this way classes not using it will still work and the other have to override it.
Would this change make it  good for back-porting or should I look at different approaches. Thanks!

This proposed change looks good to me.

I merged this change to Tomcat main branch (11). Backporting is not straightforward however as this is an API change stacked on top of a previous API change for Tomcat 11, so the code that uses it would be tied to 11 anyway.

@rmaucher thanks for the merge. I have tested cherry-picking to tomcat 9 and it required a couple of minor fixes to work. Is there something I can do to facilitate the backport?

@rmaucher thanks for the merge. I have tested cherry-picking to tomcat 9 and it required a couple of minor fixes to work. Is there something I can do to facilitate the backport?

This seems difficult, AbstractJsseEndpoint would be the spot (same for 10.1), but it would be an incompatible API change (so probably not ok), and code written for 11 would not be compatible anyway.

but it would be an incompatible API change

Yes,  the API would be slightly different between version 9 and 11.


PlantUML and mermaid UML support

Using code chunks  to generate UML diagram:
    ```mermaid
     ```

     ```plantuml
     ```

It is a very useful feature if can support in al-folio .

@ihexon, thanks for the suggestion! Would you mind providing more details/examples of how mermaid and plantuml rendering would work? Are there any JS libraries that provide support? Thanks.

mermaid
plantuml
Project using mermaid and plantuml:

codime
jekyll-TeXt-theme

relate commit

it looks like jekyll-diagrams provides support for mermaid, platuml, vega-lite, etc. definitely worth integrating into al-folio.