ModuleNotFoundError: No module named 'scipy.sparse.csgraph._tools'

The error "ModuleNotFoundError: No module named 'scipy.sparse.csgraph._tools'" suddenly appeared when runing code under python 3.6 enviroment with pycharm and I have scipy 1.5.0
In fact, the project processed successfully but only 5mins later (after I added just single one print statement), the error occured. I changed nothing and triple checked the settings!  Could someone help me out? I have no idea whether the module scipy was updated or the pycharm got some bugs.
Thanks!

No idea what is going on here. Probably an installation issue, hard to say without a traceback.
We dropped Python 3.6 already, so I don't think there's anything actionable here - hence I'll close this issue.


Core: ChainableAction does not catch exceptions in dispatched execution

I believe 4f2be2cb9c6759820a66af8c7292039986e50b98 reverted the fix for #4008.
Let me know if you want me to add a test for it.
A clear "will not fix" is also fine.

Hi @phiSgr ,
For now, I'm inclined for "won't fix". The example you provide in #4008 is actually incorrect: your Action has a next to propagate in case of an error, so it should be a ChainableAction and implement execute instead of !.
Do you have another example that would apply?

The custom wrongDispatcher action does not fail. It does propagate to the next action.
What dropped the user is SessionHook.

Edited the original issue to and used ChainableAction. It fails with the same behaviour.

You're right. Reverting.

Thanks!


High number of sequential requests result in large memory use in ArangoDB

The way this was observed initially was making many sequential requests (on the order of 100) to the api endpoint for retrieving the nodes/links for each node/edge table. The reason there was so many requests being made was that the number of rows in the response was limited to 100, thus resulting in many requests being made. When this limit was bumped to 1000, less requests were made, and this memory limit was not reached.
So it seems that for whatever reason, lots of small requests result in large memory use for Arango. I'm not sure what the exact reason for this is, and I don't think we have any immediate action items in this regard, just something to be aware of.

ArangoDB docs regarding reducing memory use: https://www.arangodb.com/2019/03/small-steps-reduce-arangodb-resource-footprint/

That docs page is very interesting and strikes me as exactly what was going wrong on @gotdairyya's local setup.
I have a feeling we might want to pull in some of our DBMS experts to help us fully understand the stuff in that docs page.


import of ResizeSensor in angular

Importing of ResizeSensor in angular causes the following error:

ERROR TypeError: ResizeSensor is not a constructor

https://stackblitz.com/edit/css-element-queries-d
It somehow magically works only in this project:
https://stackblitz.com/edit/css-element-queries-d-resize-sensor
Replicating the same in local machine and elsewhere returns the error that I mentioned earlier.

I unnecessarily complication the import. Here is the corrected version.
https://stackblitz.com/edit/css-element-queries-d-corrected
import should be:
import { ElementQueries, ResizeSensor } from 'css-element-queries' ;
instead of
import * as ElementQueries from 'css-element-queries/src/ElementQueries';
import * as ResizeSensor from 'css-element-queries/src/ResizeSensor';


buffer for chunked streaming breaks queries thru chproxy

0.8.0 introduced a buffer for HTTP streaming/chunked queries. This feature breaks integration with some types of ClickHouse proxies. For example a popular chproxy is affected.
The reason is simple. chproxy returns non-chunked response with a valid content-length and no transfer-encoding header.
urllib3.exceptions.ResponseNotChunked: Response is not chunked. Header 'transfer-encoding: chunked' is missing.

There's no way to walk around this buffer.
 "
                "Header 'transfer-encoding: chunked' is missing."
            )
E           urllib3.exceptions.ResponseNotChunked: Response is not chunked. Header 'transfer-encoding: chunked' is missing.

Thanks for the detailed report.  I suspect that chproxy "unchunks" the responses as part of its caching approach and the library should definitely support that.  My apologies for missing that use case.  We should have a fix in the next day or two.


Handle

Currently the value of a select component with the multiple is not reflected correctly in the form.
REPL for reproduction

Inspecting the objects, I can see that the _value in the FormControl is incorrect as well. And looking at the code, it seems that a string is always expected.
Expected:
The $form.values.foo to be an array of values.
Actual:
The first value of the array is taken as the value.

I was able to overcome this by cloning the repo and adding an extra value type string[];. You must change the types everywhere to suppress type mismatches. And in the validators you will have to check the value type before processing the validation.

I was able to overcome this by cloning the repo and adding an extra value type string[];. You must change the types everywhere to suppress type mismatches. And in the validators you will have to check the value type before processing the validation. Otherwise string != string[] which will return an invalid value state.

Hmm i like this multiple feature but it raises the problem of having non string form controls. I mean it would be possible to expand values to be of type string | string[] but as moalamri already said, this would result in the user having to type check the input every time.
I'm currently not sure if this is a trade off that is worth it.
Although making the value any would allow us  to also return the value of a datetime-local input as a Date… 🤔

I was able to overcome this by cloning the repo and adding an extra value type string[];. You must change the types everywhere to suppress type mismatches. And in the validators you will have to check the value type before processing the validation. Otherwise string != string[] which will return an invalid value state.

Hmm i like this multiple feature but it raises the problem of having non string form controls. I mean it would be possible to expand values to be of type string | string[] but as moalamri already said, this would result in the user having to type check the input every time.
I'm currently not sure if this is a trade off that is worth it. Although making the value any would allow us to also return the value of a datetime-local input as a Date… 🤔

I really faced a huge kill with dynamic data where I might need to use an object or a list of strings/numbers/objects as a value. I didn't want to make a mess to the core code so I eventually used objects as string using stringify and joined array values to be strings, then later I convert those values in the validators back to their original type and do the validation. So perhaps this could be easier way for @c00 to make the value as a joined string?
It's for sure an overkill because I needed to sterilize values again before submitting the form data as well 😓

In general all inputs always return a single string. As for selects wiith multiple it seems that when binding to the value in svelte, it does not take the value of the select but rather a newly added property called selectedOptions which is an array of what was selected.

Furthermore for inputs with type="date" value is still just a string "yyyy-mm-dd" but the HTML spec exposed a valueAsDate property which probably just does new Date(inputElement.value).

#17 is kind off similar to this issue.

Would also be great if svelte-use-form can handle multiple checkboxes with the same name. I really think you should add string[] support, sure it sucks having 2 types, but there are just so many use cases for it.


[BUG] Reveal file does not work

See below:
https://user-images.githubusercontent.com/31262046/151678010-26a1cb1a-166d-471f-bf04-9268fdefabb6.mp4
where the steps to reproduce would be:

Open a file
Use :NeoTreeReveal
Observe that the correct file is not revealed, and instead the tree is simply shrunk

This was introduced via 4787b637895fccfedb813c9bf8926453f187c2e8, as the same action works (meaning the tree properly focuses the current file) on 751ee6b4e840d36915ab5ac7234e848aa45db1ac.

I'm not seeing the same issue. Are you currently on the latest release, which is 517cf66523139071df05c45c221b8e186343aeb2?
Can you paste your config here?

I am using 59d22bbc767a16ebce4d706e9b5e4be350be9278, and it happens for me when using a minimal configuration like:
vim.opt.runtimepath = { vim.env.VIMRUNTIME }

vim.cmd([[
  packadd plenary.nvim
  packadd neo-tree.nvim
]])

require("neo-tree").setup({})

and then running nvim --noplugin -u /tmp/neo-tree.lua (assuming the file above is at the path mentioned here). Open a path in the same directory as where you ran nvim, and run :NeoTreeReveal.

Thanks, I see it now. I am pretty sure the first invocation works but the second invocation is messing it up by not having the correct folders open.

@levouh Can you try the latest in main and let me know if it works correctly?

I think this problem still exists.
https://user-images.githubusercontent.com/24765272/153723388-c573129f-8922-4e80-9ddc-5d33fa68506d.mov

Usually happen after all packages get updated via packer.nvim (while don't restart the session)

That was the missing detail I needed! I found the bug and am fixing it now.

@nyngwang I think this is fixed now in mian.

That was the missing detail I needed! [...]

@cseickel Lol, I thought this info was not important days ago so I didn't provide it. Let me check it now!


Fix CSR Array adapter batch columns.

The function isn't used in current codebase.
Part of https://github.com/dmlc/xgboost/pull/7070 .

Will merge it into another PR.


Safeguard: No default passwords for databases in ConfigMap or Secret

As per the Product Management meeting on 2021-06-14, we should have easy-to-understand examples online that shows the utility of policy as code. These should be showcased on the https://compliantkubernetes.io/ciso-guide/policy-as-code/ page, with some minor text accompanying them.
This issue requests a policy that prevents the use of default passwords in ConfigMap or Secret objects in any namespace. You can make a list up, such as password123 and pass1, and prevent those.
This is literally a requirement in SOC2, so please mention that in the text as well.

@Xartos Thanks for bringing this up. "Re-evaluate" sounds perfect until we made up our mind in PM on how we want to systematically deal with OPA-based safeguards. This is likely something for Q2.


Installation troubles

Hi guys. Here is not about really issues, but mostly lack of documentation and my middleware loading process misunderstanding.
What I expect:
I did installation of middleware using setup.py
Also I add a configuration settings to /etc/swift/proxy-server.conf
[pipeline:main]
pipeline = swift_undelete
[filter:swift_undelete]
paste.filter_factory = swift_undelete:filter_factory
Swift proxy booting properly, but when I tried delete a object nothing happened. I expect new .trash- container.
What exactly I did wrong?

download source from github and install it "python setup.py install"
follow configuration write your proxy-server.conf  and insert swift_undelete in pipeline
swift-init proxy object-expirer start.
Delete any object. it move to  trash container. will be removed by object-expirer.

[filter:swift_undelete]
use = egg:swift_undelete#undelete
trash_prefix = .trash-
trash_lifetime = 120
block_trash_deletes = no
enable_by_default = yes

Hi guys! Here is my configuration of proxy-server.conf
[pipeline:main]
pipeline = swift_undelete

[filter:swift_undelete]
use = egg:swift_undelete#undelete
trash_prefix = .trash-
trash_lifetime = 120
block_trash_deletes = no
enable_by_default = yes

When I restart proxy, I got the following error:
LookupError: No section 'swift_undelete' (prefixed by 'app' or 'application' or 'composite' or 'composit' or 'pipeline' or 'filter-app') found in config /etc/swift/proxy-server.conf

When I change the [filter:swift_undelete] to [filter-app:swift_undelete], I got another error:
LookupError: The [filter-app:swift_undelete] section in /etc/swift/proxy-server.conf is missing a 'next' setting

And how to fix it? Thanks!

Swift uses PasteDeploy to construct WSGI applications. While PasteDeploy's homepage seems to be down currently, other places include some docs, and the whole site is still available via the Wayback Machine if you want to learn more about pipelines, filters, and apps.
The TL;DR though is that the filter needs to be added to the proxy pipeline, rather than replacing it. I pushed up 764c8b8 which should help explain that.

@tipabu Many thanks! it worked!


Just inference your trained model to another dataset

Thank you for your hard work.
I am now considering using your inference code directly on a new dataset. How should I proceed?

Hi, you can simply prepare your dataset to follow the directory mentioned here.
Then, you can simply follow the readme


The MSVC BS patch

Fixed with an upstream patch, adding /EHsc: https://github.com/LunarWatcher/SConsStandard/commit/c90d8e5e05cab1edba9cc94dc910c9c99bea16ec
Might not work, but it works in the tests. None of the tests that usually broke it. If this fails, this might be the only option: https://stackoverflow.com/a/747001/6296561


vessel bin runs indefinitely

The command
vessel bin

does not exit already for a few minutes.
vessel.dhall:
{
  dependencies = [ "base", "btree", "stable-rbtree", "stable-buffer" ],
  compiler = Some "0.9.1"
}

$ vessel --version
vessel 0.6.5

Behind the scenes, one of the files from this GitHub release (depending on your operating system) is downloaded when running the vessel bin command:
https://github.com/dfinity/motoko/releases/tag/0.9.1
If necessary, you could manually add these compiler files to the .vessel/.bin/ directory.
The most likely explanation for the delay is a very slow Internet connection, although it's also possible that this could be an OS-specific bug. Which operating system are you using?
In case it helps with debugging, here is the relevant source code.

The most likely explanation for the delay is a very slow Internet connection

GitHub downloading is extremely slow for me. You need to replace GitHub by another files hosting.


Add clarketm@ to our CI team so he can help us move our prow instance.

This change is

/assign @zhenghuiwang

/lgtm

/approve


Create a pattern for quick iterations of terraform/nomad code

Right now the only way to run your terraform code is through a make up that runs your ansible_local provisioner with vagrant. Running the provisioning process again without removing the box first will result in a fail because of the bootstrap process. This means each iteration of terraform (or nomad) code you need to run make clean then make up which takes a lot of time
To get around this one could simply ssh into the box and run the vagrant/dev/ansible/playbook.yml directly with ansible-playbook <playbook-name>, but it is not described anywhere.
Options:

add section to docs explaining the functionality described above (might as well add a note about nomad job run <hcl-file> as well to quickly iterate over the hcl-code)
create a new workflow (within Makefile or something else) that allows quick testing of iterations

option 3 - I installed terraform on localhost, and run directly against the vagrant box.

option 3 - I installed terraform on localhost, and run directly against the vagrant box.

Ah yeah that too, and I actually like this a lot. Not confined to the environment inside the box.

You could also do make ssh and cd /vagrant/example; terraform apply -auto-approve

In sum there are many ways to do it. We should document the ways we think are the most useful.

You could also do make ssh and cd /vagrant/example; terraform apply -auto-approve

template/example dir is not mounted to /vagrant/example. Am I missing some steps?
vagrant@vagrant:~$ pwd
/home/vagrant
vagrant@vagrant:~$ ll
total 52
drwxr-xr-x 7 vagrant vagrant 4096 Aug 21 06:06 ./
drwxr-xr-x 3 root    root    4096 Aug 15  2019 ../
drwx------ 3 vagrant vagrant 4096 Aug 19 07:03 .ansible/
-rw-r--r-- 1 vagrant vagrant  220 Aug 15  2019 .bash_logout
-rw-r--r-- 1 vagrant vagrant 3771 Aug 15  2019 .bashrc
drwx------ 2 vagrant vagrant 4096 Aug 15  2019 .cache/
-rw-r--r-- 1 root    root     270 Aug 19 07:09 .env_default
drwx------ 3 vagrant vagrant 4096 Aug 15  2019 .gnupg/
drwx------ 3 vagrant vagrant 4096 Aug 21 06:06 .minio/
-rw-r--r-- 1 vagrant vagrant  807 Aug 15  2019 .profile
drwx------ 2 vagrant root    4096 Aug 21 06:06 .ssh/
-rw-r--r-- 1 vagrant vagrant    0 Aug 15  2019 .sudo_as_admin_successful
-rw-r--r-- 1 vagrant vagrant    6 Aug 15  2019 .vbox_version
-rw-r--r-- 1 root    root     180 Aug 15  2019 .wget-hsts


Circle Tool: can't specify a decimal point in Radius/Diameter parameter (ArcGIS Pro)

I can specify a decimal point in the ArcMap addin.

@elinz sending this one back to verify.

this sounds the same as #328  which i verified was fixed this morning. also looked at it again when i came across this issue and from the small amount of detail in the original issue write up, this looks to be fixed


[KED-1581] Add on_pipeline_error and on_node_error methods to hooks

Description
I have tried the hooks implementation described which is part of #219. It works very smoothly, but I feel that it would be nice to have a method to deal with errors which may occurs during the execution between two hooks call.
Context
By now, hooks work by calling two methods (```before_WHATEVERandafter_WHATEVER) which frame the code line they should wrap. In case this code line fails, the user does not have a proper to end a behaviour that was triggered by the begin_WHATEVER`` function.
A typical example is in #113 : if a mlflow run is started before a pipeline call, you want to be able to close it whatever even if the pipeline fails to avoid unintended side effects  (further code execution will be logged in the current mlflow runs without any user warning)
Possible Implementation
Add a hook_spec where it fits (before the following line?)
https://github.com/quantumblacklabs/kedro/blob/e377bd5114b68caf236fa9f4c924bf58291efa9c/kedro/hooks/specs.py#L157-L158
@hook_spec
    def on_pipeline_error(
        self, err, other?)
    )

and adjust the following call from this :
https://github.com/quantumblacklabs/kedro/blob/8bfa0a8ce0e3bef194ba8d4ca682becf8accdc24/kedro/context/context.py#L637-L646
to this:
self._hook_manager.hook.before_pipeline_run(  # pylint: disable=no-member
    run_params=record_data, pipeline=filtered_pipeline, catalog=catalog
 )
try:
    run_result = runner.run(filtered_pipeline, catalog, run_id)
except Exception as err:
    self._hook_manager.hook.on_pipeline_error(err)
    raise err
self._hook_manager.hook.after_pipeline_run(  # pylint: disable=no-member
        run_params=record_data,
        run_result=run_result,
        pipeline=filtered_pipeline,
        catalog=catalog,
    )

Hi @Galileo-Galilei, thank you for raising this and thank you for the initial work on the plugin. It looks very promising. So happy to see traction on this.
Regarding your feature request, I agree that all the existing hooks only take into account the happy paths. I'm inclined to agree that a hook for on_pipeline_error would be nice for your use case. Could you give me your use cases for on_node_error? The reason I'm asking is that our design principle for hooks is only to to add the absolutely necessary hooks if possible. It's very easy to add new hooks, but very hard to remove them once users start using them.
Once we confirm the use cases, we will discuss internally to see whether to make this hook available or whether there is a better way to solve your use case that we haven't thought of yet.

Hello @limdauto,
I actually do not have real use cases for _on_node_error, but here are some uses cases that we could imagine :

implement a custom "retry" strategy when the node fails (for instance, if mflow fails logging the dataset but the node was correctly executed, I may want skip mlflow logging and continue the pipeline with a warning)
force saving the inputs of the nodes which are MemoryDataset on the disk (for instance, as pickle or other generic format) to be able to run the pipeline from this nodes (which is currently possible only if the datasets are persisted)

I am not sure these use cases should be supported, they seem rather hacky. My original idea to introduce _on_node_error was rather for consistency between pipeline hooks and node hooks.

@Galileo-Galilei Hi, just a quick update on this one: we are implementing both of these hooks and will release it in 0.16.

@Galileo-Galilei We have just merged these two hooks into develop. Thank you very much for the suggestion. It should go out with 0.16.


updates the Jenkins plugin script + adds support for Jenkins agent container on controller VM

Fixes the install-plugins.sh script issue
Adds Jenkins agent docker container on the same VM
Updates all outdated versions

Will switch the work to the new repo:
https://github.com/oracle-devrel/terraform-jenkins-ci-cd-oci


standardize Makefile entries

sync Makefile with skeleton generated by operator-sdk init

/retest

/lgtm

/approve

/retest

/retest

/test telemetry-operator-build-deploy-kuttl


46274ef4dd8d846bf5a1cbe804e4767a91ce726e

46274ef4dd8d846bf5a1cbe804e4767a91ce726e
Originally posted by @Ebimk2 in https://github.com/tronprotocol/java-tron/pull/3877#issuecomment-878521187

Yes

I’m closing this issue since it’s unrelated to the open grants program as far as I can see. If this isn’t the case feel free to add additional explanation here.


Help needed with logo design

Need a good designer to help contribute to this repository by creating a logo for this project and
we would like the logo to incorporate elements of Artificial Intelligence, collection, and tools.
We are open to creative ideas that reflect the spirit of our project and the logo will be used on our website and social media pages. It is important that the logo be scalable to different sizes and formats.
Please submit your logo designs in vector format (.svg,.ai, or .eps).
I would love to see the open-source community come together and contribute in this month of #Hacktoberfest!

Hey, I would like to create a logo...working on it

can i work on this?

I want to work on it

will be sharing figma link so that we can clearly know the thought process

Thank you for your valuable contributions 🎉. We will carefully review all the submitted assets and select the one that best aligns with our project. It's worth noting that your design assets will remain a part of this project, even if they aren't chosen as the final logo. Please format your assets as follows: /assets/logo_version/logo_version.extension, for example, /assets/logo_v1/logo_v1.webp, and please consider raising a PR to include this.
This is an open-source project, and we encourage original contributions. Please avoid copyrighted materials and refrain from blindly copying designs from the internet. Your unique creativity is highly valued in this collaboration.
We value your ongoing contributions and encourage you to stick around and keep contributing to the project. We'll be launching a GitHub discussion tab soon for further collaboration.💫


feat: [IDP]: Added the docs on gitlab integration in IDP stage

Thanks for contributing to the Harness Developer Hub! Our code owners will review your submission.
Description

Please describe your changes: __________________________________
Jira/GitHub Issue numbers (if any): ______________________________
Preview links/images (Internal contributors only): __________________

PR lifecycle
We aim to merge PRs within one week or less, but delays happen sometimes.
If your PR is open longer than two weeks without any human activity, please tag a code owner in a comment.
PRs must meet these requirements to be merged:

[ ] Successful preview build.
[ ] Code owner review.
[ ] No merge conflicts.
[ ] Release notes/new features docs: Feature/version released to at least one prod environment.

Please check the Execution Link of the Pipeline for the Website Draft URL. This is located in the Preview Step behind the Harness VPN and also is available in #hdh_alerts. E.g Website Draft URL: https://unique-id--harness-developer.netlify.app. Current Draft URL is: https://66e95f68ed55bbf871c1b4bd--harness-developer.netlify.app


Yamlfmt is too big as pre-commit hook

I'm using yaml format as a hook in pre-commit tool, but it's biggest in our docker container - 243Mb! And almost all 243Mb is folder golangenv-default
Its biggest pre-commit hook I've used with my Python code
Second largest hook only 80Mb

I don't know much about pre-commit, but my guess is that it's because language: golang ends up downloading the entire Go language to be able to build the program on your machine to then run as a hook. One thing I'm not sure about is whether this is circumvented if Go is already installed locally; it would make sense to me if having a local version of Go meant that pre-commit would just use that instead of downloading it as part of the hook.
The other option is to download a version of yamlfmt from the GitHub Releases and use that local binary. The yamlfmt binary is only 3.1 Mb itself, and if you go this route then I don't think pre-commit has to download anything. Here are the instructions to do that: https://github.com/google/yamlfmt/releases/download/v0.13.0/yamlfmt_0.13.0_Linux_x86_64.tar.gz
I don't know if there's anything I can substantially do on the yamlfmt side to assuage this, so I'll close this issue. Hopefully the info helps.

Ok, thanks. I would think about that


Revert "Abseil Flags"

Reverts grpc/grpc#24506
MSVC2017 has difficulties compiling with these changes.

Presuming this goes through, would you please reopen https://github.com/grpc/grpc/issues/24493?


github-runner: 2.284.0 -> 2.285.0

Motivation for this change
Update the GitHub Actions Runner to the v2.285.0 release.
Adds support for Node.js 16.
Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
22.05 Release Notes (or backporting 21.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module
[ ] (Release notes changes) Ran nixos/doc/manual/md-to-db.sh to update generated release notes

[ ] Fits CONTRIBUTING.md.

Result of nixpkgs-review pr 148342 run on x86_64-linux 1

1 package built:

github-runner

Didn't test an action yet which actually requires Node.js 16:
https://github.com/actions/runner/blob/a519f96a410a10c4be6e38e8249d33a9b25f716b/src/Test/TestData/node16action.yml#L18-L19

The ofborg build on aarch64-linux did not succeed due to a failing test:
  [xUnit.net 00:00:03.68]     GitHub.Runner.Common.Tests.Worker.StepHostL0.DetermineNodeRuntimeVersionInAlpineContainerAsync [FAIL]
    X GitHub.Runner.Common.Tests.Worker.StepHostL0.DetermineNodeRuntimeVersionInAlpineContainerAsync [9ms]
EXEC : error Message:  [/build/source/src/dir.proj]
     System.NotSupportedException : JavaScript Actions in Alpine containers are only supported on x64 Linux runners. Detected Linux Arm64
    Stack Trace:
       at GitHub.Runner.Worker.Handlers.ContainerStepHost.DetermineNodeRuntimeVersion(IExecutionContext executionContext, String preferredVersion) in /build/source/src/Runner.Worker/Handlers/StepHost.cs:line 149
     at GitHub.Runner.Common.Tests.Worker.StepHostL0.DetermineNodeRuntimeVersionInAlpineContainerAsync() in /build/source/src/Test/L0/Worker/StepHostL0.cs:line 75
  --- End of stack trace from previous location where exception was thrown ---

Ignored the respective test.

Meanwhile, v2.285.1 has been released: https://github.com/actions/runner/releases/tag/v2.285.1


NixOS application are unable to find OpenGL drivers

Describe the bug
Despite having specified the wanted graphic drivers in configuration.nix:
services.xserver.videoDrivers = [ "amdgpu" "radeon" "cirrus" "vesa" "nouveau" ];

...the applications just fall back to llvmpipe (meaning, no GPU used at all):
$ glxinfo | grep OpenGL
OpenGL vendor string: VMware, Inc.
OpenGL renderer string: llvmpipe (LLVM 7.1, 128 bits)
OpenGL core profile version string: 3.3 (Core Profile) Mesa 19.1.5
OpenGL core profile shading language version string: 3.30
OpenGL core profile context flags: (none)
OpenGL core profile profile mask: core profile
OpenGL core profile extensions:
OpenGL version string: 3.1 Mesa 19.1.5
OpenGL shading language version string: 1.40
OpenGL context flags: (none)
OpenGL extensions:
OpenGL ES profile version string: OpenGL ES 3.0 Mesa 19.1.5
OpenGL ES profile shading language version string: OpenGL ES GLSL ES 3.00
OpenGL ES profile extensions:

Note that vmware does not even exist in the drivers I specified, yet the applications still find it somewhere. Needless to say, 3D-gaming is incredibly slow.
And running hwinfo --gfxcard somehow lists the drivers that I want to use, despite glxinfo being unable to do that:
$ hwinfo --gfxcard | grep Driver
  Driver: "nouveau"
  Driver Modules: "nouveau"
  Driver: "amdgpu"
  Driver Modules: "amdgpu"

(It said this even before I added services.xserver.videoDrivers to configuration.nix)
To Reproduce
Steps to reproduce the behavior:

Enable x11 and xfce
install and run hwinfo --gfxcard and add the drivers it says to services.xserver.videoDrivers
if it still does not appear, you could try to add the rest of my OpenGL configuration, described in additional context (EDIT: you need to set it, otherwise won't happen)

Expected behavior
glxinfo returning info for (at least) two renderers, one for each GPU. And programs to use them.
Additional context
I don't know if this is related, but I post it in case it is. I have added this to configuration.nix to combat other problems I've had with OpenGL:
EDIT: confirmed to be related.
hardware.opengl.package = (import (pkgs.fetchzip {
      name = "old-nixpkgs";
      url = "https://github.com/NixOS/nixpkgs/archive/0a11634a29c1c9ffe7bfa08fc234fef2ee978dbb.tar.gz";
     sha256 = "0vj5k3djn1wlwabzff1kiiy3vs60qzzqgzjbaiwqxacbvlrci10y";
  }) {}).mesa.drivers;
  hardware.opengl.driSupport32Bit = true;

I use an older Mesa because I had serious graphical glitches in xfce (starting from second login for each user account) with the current NixOS Mesa. This fixed it.
Metadata

system: "x86_64-linux"
host os: Linux 5.4.44, NixOS, 20.03.2107.70717a337f7 (Markhor)
multi-user?: yes
sandbox: yes
version: nix-env (Nix) 2.3.6
channels: "nixpkgs-20.09pre234797.206dc0cfacd"
nixpkgs: /nix/var/nix/profiles/per-user/root/channels/nixos

Maintainer information:
# a list of nixos modules affected by the problem
module: nixos.mesa

Any help to get GPUs working appreciated.

Confirmed that using the older mesa is required to cause the problem. If I remove the lines about hardware.opengl from configuration.nix, this problem disappears. But it does not help me, because the graphical glitching in xfce is too severe with the default mesa version.

Note that vmware does not even exist in the drivers I specified, yet the applications still find it somewhere.

I'll try to clear the confusion. There are in a fact 3 parts of a driver:

The kernel driver, which does the actual talking to the hardware. This is provided as a kernel module and is enabled by
adding it to the boot.initrd.availableKernelModules option.

The device-dependent X (DDX), which is the component of the X server that draws the screen. This is provided by several packages which you install by setting services.xserver.videoDrivers.

The Gallium driver in Mesa. Mesa is collection of graphics API (like OpenGL, Direct3D, etc.), which are themselves implemented in a lower-level API called Gallium. The Gallium drivers implement this API either using the kernel driver of the GPU (like nouveau) or software rendering (like llvmpipe). You don't need to enable/install these drivers: they are all available within mesa.

I think VMware is just the original author of the llvmpipe driver: it has nothing to do with virtualisation.

...the applications just fall back to llvmpipe (meaning, no GPU used at all):

Can you check you don't have the LIBGL_ALWAYS_SOFTWARE variable set to true? Maybe you did some testing and forgot to remove it.
You should also try forcing nouveau by setting GALLIUM_DRIVER=nouveau and check with glxinfo.

I'll try to clear the confusion. There are in a fact 3 parts of a driver:
[snip]

Thanks for the info. Well, this explains why LLVM pipe is always available.

I think VMware is just the original author of the llvmpipe driver: it has nothing to do with virtualisation.

Didn't think otherwise, since it was after the vendor label

...the applications just fall back to llvmpipe (meaning, no GPU used at all):

Can you check you don't have the LIBGL_ALWAYS_SOFTWARE variable set to true? Maybe you did some testing and forgot to remove it.

No effect.

You should also try forcing nouveau by setting GALLIUM_DRIVER=nouveau and check with glxinfo.

glxinfo errored out, same error message as if I wrote GALLIUM_DRIVER=nonexistent glxinfo. Same with amdgpu.
But, I managed to partially fix the problem. Or rather, Nix did it for me. Since glxinfo found amdgpu worked at the newer graphically glitching Mesa, I thought that perhaps changing the order of the drivers would resolve the graphical glitches without having to downgrade Mesa.
services.xserver.videoDrivers = [ "nouveau" "amdgpu" "radeon" "cirrus" "vesa" ];, commented out the OpenGL package override and ran nixos.rebuild boot.
The rebuild downloaded so much stuff that I suspect it constitutes almost everything I've installed so far. Then I realised that I had added another channel since the last rebuild, so it apparently wanted to update the binaries to match with the Nix store.
After rebooting, there were no graphical glithes. glxinfo says amdgpu, so Nouveau wasn't found (wasn't either with the glitching OpenGL). So it seems the system update fixed the glitches. Thanks!
Even with only the integrated GPU, I'm seeing much better gaming performance. Since the discrete GPU is NVIDIA, does this mean specifying an unfree driver to services.xserver.videoDrivers or is there something else I could try?

Even with only the integrated GPU, I'm seeing much better gaming performance.

That's not surprising considering nouveau is mostly written mostly by reverse engineering, while amdgpu is officially supported by AMD.

is there something else I could try?

Well, I don't see you doing anything wrong and I would expect Mesa to pick up the correct driver, nouveau, so I would try opening an issue in the Mesa tracker.

Sorry for the needlessly late reply.

That's not surprising considering nouveau is mostly written mostly by reverse engineering, while amdgpu is officially supported by AMD.

No, I wasn't comparing AMDgpu to Nouveu, I was comparing it to LLVMPipe.

Well, I don't see you doing anything wrong and I would expect Mesa to pick up the correct driver, nouveau, so I would try opening an issue in the Mesa tracker.

Thanks you. That's what I'm going to do when I get to that. I might first try to override the drivers with the unstable channel Mesa. If I happen to get Nouveau working that way, I'll leave a message here.
But anyway, It seems be a Mesa issue, not a Nixpkgs one, so no reason to keep this issue open anymore.

@dukc I've just encountered this issue! Do you remember the solution?

No, sorry, I didn't manage to get Nouveau working.
I did some playing by prefixing application running command with DRI_PRIME and MESA_GL_VERSION_OVERRIDE flags. I think I got hwinfo to claim "nouveau" that way, while Steam still said "amdgpu". Games didn't run faster and sometimes an OS freeze happened so either Nouveau worked very badly for me or I didn't actually fully enable it. The latter explanation is more likely IMO.
Since I'm lazy I haven't actually reported the issue to Mesa.

Thanks for reporting back @dukc . From my understanding the issue was a mismatch between mesa in upstream (nixpkg) versus compositor's version.
Regarding wrong primary display adapter, I wasn't able to solve it either.
Since you mentioned it, I removed my NVIDIA GPU and I can confirm that amdgpu/mesa driver is prone to hard crashing with DX12 games over Proton 8/7 :/

Had an another go trying to troubleshoot this. Didn't get it working, but gained a bit of insight of the problem so decided to share it here.
Someone was having very similar problems here. In the same spirit, I spent time reading my journalctl -b --no-hostname | less. The driver does load but doesn't support my chipset:
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]: (II) [drm] nouveau interface version: 1.3.1
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]: (EE) Unknown chipset: NV167

. It does support some other chipsets though:
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]: (II) NOUVEAU driver
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]: (II) NOUVEAU driver for NVIDIA chipset families :
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         RIVA TNT            (NV04)
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         RIVA TNT2           (NV05)
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         GeForce 256         (NV10)
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         GeForce 2           (NV11, NV15)
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         GeForce 4MX         (NV17, NV18)
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         GeForce 3           (NV20)
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         GeForce 4Ti         (NV25, NV28)
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         GeForce FX          (NV3x)
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         GeForce 6           (NV4x)
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         GeForce 7           (G7x)
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         GeForce 8           (G8x)
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         GeForce 9           (G9x)
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         GeForce GTX 2xx/3xx (GT2xx)
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         GeForce GTX 4xx/5xx (GFxxx)
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         GeForce GTX 6xx/7xx (GKxxx)
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         GeForce GTX 9xx     (GMxxx)
tammi 03 16:32:55 /nix/store/y5s10jdrni1gacvncwd9v96ca6ciyjz0-gdm-45.0.1/libexec/gdm-x-session[2017]:         GeForce GTX 10xx    (GPxxx)

. Even earlier in the log it turns out it's because lack of firmware (a few non-Nouveau lines hand-removed from between):
tammi 03 16:32:43 kernel: nouveau: detected PR support, will not use DSM
tammi 03 16:32:43 kernel: nouveau 0000:01:00.0: NVIDIA TU117 (167000a1)
tammi 03 16:32:43 kernel: nouveau 0000:01:00.0: bios: version 90.17.3d.00.80
tammi 03 16:32:43 kernel: nouveau 0000:01:00.0: pmu: firmware unavailable
tammi 03 16:32:43 kernel: nouveau 0000:01:00.0: fb: 4096 MiB GDDR5
tammi 03 16:32:43 kernel: nouveau 0000:01:00.0: DRM: VRAM: 4096 MiB
tammi 03 16:32:43 kernel: nouveau 0000:01:00.0: DRM: GART: 536870912 MiB
tammi 03 16:32:43 kernel: nouveau 0000:01:00.0: DRM: BIT table 'A' not found
tammi 03 16:32:43 kernel: nouveau 0000:01:00.0: DRM: BIT table 'L' not found
tammi 03 16:32:43 kernel: nouveau 0000:01:00.0: DRM: Pointer to TMDS table not found
tammi 03 16:32:43 kernel: nouveau 0000:01:00.0: DRM: DCB version 4.1
tammi 03 16:32:43 kernel: nouveau 0000:01:00.0: DRM: MM: using COPY for buffer copies

. The strange thing is, I do have tu117 in /run/current-system/firmware/nvidia/, and it's files are also listed if I do modinfo nouveau. One thing I notice is the symbolic link gsp.xz in tu117 directory, that is supposed to point to a directory in the neighbouring tu116 directory, is broken. Could potentially be the reason but seems unlikely, as the drivers tu116 represents also aren''t listed in working nouveau drivers yet it's directory contains no broken links.
I didn't come up with any fix attempts except explicitly enabling redistributable hardware, to no effect.


Add CI workflow

Signed-off-by: Itxaka<EMAIL_ADDRESS>

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Replace Invariant with Ordinal in JsonTextReader

Replacing InvariantCulture string equality checks (and a few calls to StartsWith) with Ordinal comparer. #56

Somehow managed to leave this - was a very busy time last year, I do apologize! Thank you very much for the contribution :)


Changes to SOCs (and ARCHs) are not covered thoroughly enough by PR CI runs

As shown by #8602 happening, we have a hole in the CI runs when SOCs are modified.
It would be nice if changes in SOCs would trigger (at least some of) its boards to be run in CI during a PR.
Thoughts:
I guess one option could be to have a get_modified_socs.py similar to get_modified_boards.py, which would add all/some of the boards from a SOC when that SOC is modified.
Another option could be to have at least 1 board per SOC as testing defaults for a given arch.

While that would be nice, it will generate a huge amount of tests to be built on PRs, some SoCs have way too many boards to cover in a single CI run for each PR. This is now covered in a daily build of all boards and SoCs.

is this still applicable?

I haven't looked recently.
@nashif can you answer?

This and #44593 and many other areas, all the same issue, we do not have the connection between socs and boards, drivers and socs, driverers and architectures, west modules and features and hal and boards, it is all very fuzzy right now and it is not easy.


[T3A5][W14-A2]Ray Yan

Ready for review.

@4rr4y Comments are added. Close the PR when you've reviewed them


Make it possible to configure images

Is your feature request related to a problem? Please describe.
Compliant Kubernetes is static when it comes to the configuration of which images it uses, and we should change this to address some key scenarios:

Using a private registry instead of a public registry
Using a pull through cache
Patching an image version to mitigate vulnerabilites

Describe the solution you'd like
Make it configurable for each instance of where we are using an image so we can:

Configure the registry of the image (falling back to the one defined by the chart)
Configure the repository of the image (falling back to the one defined by the chart)
Configure the tag of the image (falling back to the one defined by the chart)

Make it configurable on a global level so we can:

Configure the registry of all images (if they do not have an specific override).

This should also include images in resources created by operators to ensure that they are captured as well.
Definition of done:

[ ] Images used can be individually configured.
[ ] Image registry can be globally configured.

We solved this by configuring the container runtime, as opposed to the apps layer: https://elastisys.io/compliantkubernetes/operator-manual/air-gapped-environment/#migrating-images-manually
Is this issue still relevant?

We solved this by configuring the container runtime, as opposed to the apps layer: https://elastisys.io/compliantkubernetes/operator-manual/air-gapped-environment/#migrating-images-manually
Is this issue still relevant?

@aarnq feel free to correct me if I'm wrong. I think the idea here is for us to declaratively configure each image so that we are in more control of what is running in the cluster. It looks to me that the link you provided describes how to ingest images when you don't want to pull directly from the upstream registries.

We solved this by configuring the container runtime, as opposed to the apps layer: https://elastisys.io/compliantkubernetes/operator-manual/air-gapped-environment/#migrating-images-manually
Is this issue still relevant?

@aarnq feel free to correct me if I'm wrong. I think the idea here is for us to declaratively configure each image so that we are in more control of what is running in the cluster. It looks to me that the link you provided describes how to ingest images when you don't want to pull directly from the upstream registries.

Yes, so the goal of this issue is to go further and allow us to have an inventory of images that we can approve by pinning the checksum and sign. Allowing us to secure our supply chain by fetching the images we need, and better respond to vulnerabilities by using rebuilt or patched images dynamically, rather than statically.
And it will help if we want to start to rebuild images to ensure that they have the latest patches applied when we prepare releases.
And it would compliment the air-gapped scenario as it would provide a better inventory of images that are required, and potentially simplifies how that can be managed in apps.
(In such scenarios configuring mirrors in the container runtime will still be needed as this doesn't cover the Kubernetes and infrastructure layer, but it will provide a process to implement it elsewhere.)

@aarnq Understood, thanks for the clarification!


vtm not respecting the settings file located in default path

I'm on a windows machine and vtm doesn't respect the settings file located @ ~/.config/vtm/settings.xml (its actually a symlink to somewhere else).
I had to explitictly pass the path with -c option.
With experiments, I realized that the problem is potentially not expanding the tilde in the path. Even with -c option and explicit path passing, it fails if there was a ~ in the path, I have to pass home directory explicitly.
Can we please fix, at least the default path bug?

Certainly this should be fixed. Thanks for the feedback.
In the current implementation, a path containing ~ is expanded using the HOMEDRIVE and HOMEPATH environment variables. This checks only for the presence of ~/ characters at the beginning of the path. A more generic ~ expansion needs to be implemented there, including for the \  character.

I removed the dependency on environment variables when detecting the path to the user profile. Could you test this on the dev/sdn branch (or see precompiled binary at https://github.com/netxs-group/vtm/releases/tag/v0.9.9f)?

It works 👌
Thanks for the quick response.


Fix QR code to house IPFS hash, encrypted prescription, and smart contract address

It sounds to me that each individual Rx will have its own contract instance, and truly give it a state: prescribed, filled, rejected, etc...

I agree that each Rx state should be on-chain. But they can still all be in the same contract. Re-deploying a new contract each rx adds gas and complexity


add negative prompt option

Hold this PR until 0.4.0 version of diffusers released.

close for the other PR


run in 2 hours vs 10

used multiprocessing with 100 processes,
optimal number may vary based on machine

Cool man!
Could you share how did you arranged the code?
Thanks

You can now access the preprocessed data files here if it helps: https://www.dropbox.com/scl/fo/jdzz2y9nngw9rxsbz9vyj/h?rlkey=bji7zcqclusagzfwa7alm59hx&dl=0


Amplify REST API Python error when deploying due to 3.7 in aws build

Before opening, please confirm:

[X] I have checked to see if my question is addressed in the FAQ.
[X] I have searched for duplicate or closed issues.
[X] I have read the guide for submitting bug reports.
[X] I have done my best to include a minimal, self-contained set of instructions for consistently reproducing the issue.

App Id
d8nzd3pgncdfk
Region
us-east-1
Amplify Hosting feature
Backend builds, Build settings
Describe the bug
In local, it can works well. However, it is error when deploying using Amplify hosting CI/CD flow. My app requires python 3.8 for Amplify REST API Python, however, the build image in aws using python 3.7.
 ## Checking for associated backend environment...
                                 ## Backend environment association found
2022-09-12T12:50:25.533Z [INFO]: Amplify AppID found: d8nzd3pgncdfk. Amplify App name is: kendrademo
2022-09-12T12:50:25.592Z [INFO]: Backend environment dev found in Amplify Console app: kendrademo
2022-09-12T12:50:26.094Z [WARNING]: - Fetching updates to backend environment: dev from the cloud.
2022-09-12T12:50:26.635Z [WARNING]: - Building resource api/api1ed17962
2022-09-12T12:50:26.652Z [WARNING]: ✔ Successfully pulled backend environment dev from the cloud.
2022-09-12T12:50:26.665Z [INFO]: ✅
2022-09-12T12:50:27.906Z [INFO]: Note: It is recommended to run this command from the root of your app directory
2022-09-12T12:50:28.711Z [WARNING]: - Initializing your environment: dev
2022-09-12T12:50:29.223Z [WARNING]: - Building resource api/api1ed17962
2022-09-12T12:50:29.239Z [WARNING]: ✔ Initialized provider successfully.
2022-09-12T12:50:29.623Z [INFO]: python3 found but version Python 3.7.10 is less than the minimum required version.
                                 You must have python >= 3.8 installed and available on your PATH as "python3" or "python". It can be installed from https://www.python.org/downloads
                                 You must have pipenv installed and available on your PATH as "pipenv". It can be installed by running "pip3 install --user pipenv".
                                 You must have virtualenv installed and available on your PATH as "venv". It can be installed by running "pip3 install venv".
2022-09-12T12:50:29.624Z [WARNING]: ✖ There was an error initializing your environment.
2022-09-12T12:50:29.627Z [INFO]: Error: Missing required dependencies to package kendrademoda6c4ec6
                                     at buildFunction (/snapshot/repo/build/node_modules/amplify-category-function/lib/provider-utils/awscloudformation/utils/buildFunction.js:13:15)
                                     at processTicksAndRejections (internal/process/task_queues.js:95:5)
                                     at async prepareResource (/snapshot/repo/build/node_modules/amplify-provider-awscloudformation/lib/push-resources.js:559:33)
                                     at async Promise.all (index 0)
                                     at async prepareBuildableResources (/snapshot/repo/build/node_modules/amplify-provider-awscloudformation/lib/push-resources.js:555:3)
                                     at async Object.run (/snapshot/repo/build/node_modules/amplify-provider-awscloudformation/lib/push-resources.js:217:5)
2022-09-12T12:50:29.642Z [ERROR]: !!! Build failed
2022-09-12T12:50:29.642Z [ERROR]: !!! Non-Zero Exit Code detected
2022-09-12T12:50:29.642Z [INFO]: # Starting environment caching...
2022-09-12T12:50:29.643Z [INFO]: # Environment caching completed
Terminating logging...

Expected behavior
The aws build image should support python 3.8 so it can works for Amplify Rest Api python
Reproduction steps
Follow this official document to add an rest api in python and deploy by amplify CI/CD
https://docs.amplify.aws/cli/function/
Build Settings
version: 1
frontend:
  phases:
    preBuild:
      commands:
        - npm ci --force
    build:
      commands:
        - npm run build
  artifacts:
    baseDirectory: .next
    files:
      - '**/*'
  cache:
    paths:

Additional information
No response

Isn't this a major issue? This pretty much blocks us from deploying any updates to our website
Using a custom build image with Python 3.8 doesn't solve the issue.
2022-10-24T00:56:38.000Z [INFO]: You must have pipenv installed and available on your PATH as "pipenv". It can be installed by running "pip3 install --user pipenv".                                  You must have virtualenv installed and available on your PATH as "venv". It can be installed by running "pip3 install venv". 2022-10-24T00:56:38.003Z [INFO]: 🛑 Missing required dependencies to package webappAPIcarManufacturers                                  Learn more at: https://docs.amplify.aws/cli/project/troubleshooting/ 2022-10-24T00:56:38.004Z [WARNING]: ✖ There was an error initializing your environment. 2022-10-24T00:56:38.006Z [INFO]: You must have pipenv installed and available on your PATH as "pipenv". It can be installed by running "pip3 install --user pipenv".                                  You must have virtualenv installed and available on your PATH as "venv". It can be installed by running "pip3 install venv". 2022-10-24T00:56:38.007Z [INFO]: You must have pipenv installed and available on your PATH as "pipenv". It can be installed by running "pip3 install --user pipenv".                                  You must have virtualenv installed and available on your PATH as "venv". It can be installed by running "pip3 install venv". 2022-10-24T00:56:38.007Z [INFO]: You must have pipenv installed and available on your PATH as "pipenv". It can be installed by running "pip3 install --user pipenv".                                  You must have virtualenv installed and available on your PATH as "venv". It can be installed by running "pip3 install venv". 2022-10-24T00:56:38.008Z [INFO]: You must have pipenv installed and available on your PATH as "pipenv". It can be installed by running "pip3 install --user pipenv".                                  You must have virtualenv installed and available on your PATH as "venv". It can be installed by running "pip3 install venv".

Further details. This only started appearing when we began using the AWS Amplify API library

Additional Details/Clarifications. It seems like the React Library is not the problem. Rather any Lambda Function that uses Python encounters this error. This basically breaks the entire API functionality of Amplify if you want to use Python.
I guess the solution is to build the API Gateway/Lambda suite outside of Amplify.

We can't use Amplify if Lambda backends can't go above Python 3.7.10. Can we get a response please on this please?

any update on this? having the same issue

Same issue here.. Please can someone let us know how to build Python >3.10 backends?

In the cloudformation-template.json file of your lambda, you can set the runtime to 3.8:
"Runtime": "python3.8",

@apocheau Changing the runtime from 3.8 to 3.7, the version supplied by the build image does not seem to work.
"Resources": {
   "LambdaFunction": {
     "Type": "AWS::Lambda::Function",
     "Metadata": {
       "aws:asset:path": "./src",
       "aws:asset:property": "Code"
     },
     "Properties": {
       ...
       "Runtime": "python3.7",
     },
   },
 },
}

It produces the same error on build.
2023-05-05T19:17:17.861Z [INFO]: python3 found but version Python 3.7.15 is less than the minimum required version.
                                 You must have python >= 3.8 installed and available on your PATH as "python3" or "python". It can be installed from https://www.python.org/downloads
                                 You must have pipenv installed and available on your PATH as "pipenv". It can be installed by running "pip3 install --user pipenv".
                                 You must have virtualenv installed and available on your PATH as "venv". It can be installed by running "pip3 install venv".
2023-05-05T19:17:17.861Z [WARNING]: ✖ There was an error initializing your environment.
2023-05-05T19:17:17.861Z [INFO]: 🛑 Missing required dependencies to package xxx
2023-05-05T19:17:17.862Z [INFO]: Learn more at: https://docs.amplify.aws/cli/project/troubleshooting/
2023-05-05T19:17:17.868Z [INFO]:
2023-05-05T19:17:17.868Z [INFO]: Session Identifier: xxx
2023-05-05T19:17:17.890Z [ERROR]: !!! Build failed
2023-05-05T19:17:17.891Z [ERROR]: !!! Non-Zero Exit Code detected

I am able to use the amplify cli to amplify push the lambda function successfully.

I was able to resolve this problem by adding the "update-alternatives" command to my amplify.yml file:
backend:
  phases:
    build:
      commands:
        - update-alternatives --install /usr/bin/python3 python3 /usr/local/bin/python3.9 15
        - /usr/local/bin/python3.9 -m pip install --upgrade pip
        - /usr/local/bin/pip3.9 install --user pipenv
        - amplifyPush --simple

And changing the python_version in my Pipfile:
[requires] python_version = "3.9"

wow i'm so glad i found this. was going insane. thank you all. and i consider myself to sorta understand how everything works (relatively), this is such a niche specific thing, and suddenly i had an "aha" moment and said... maybe i'm actually not doing something wrong and this is something else!
anyways glad i stayed level headed otherwise i don't think I would've gotten to the bottom of this


What's the Ways of Free Mosconi Cup 2024 LIVE Streams Free Full Schedule, Start Time, Odds, Stream, More 30 November 2024

What's the Ways of Free Mosconi Cup 2024 LIVE Streams Free Full Schedule, Start Time, Odds, Stream, More 30 November 2024

as


An error occurred while uploading the package

Describe the bug
When my package.json contains "deprecated": false, I will not be able to publish successfully

To Reproduce
1: Prerequisite: Verdaccio private server
2: Local NPM init
3: edit package.json file，add  "deprecated": false。like {   "name": "wlq-test",   "version": "0.1.1",   "main": "dist/zby-live-sdk.cjs.js",   "module": "dist/zby-live-sdk.esm.js",   "browsers": "dist/zby-live-sdk.umd.js",   "scripts": {     "build": "cross-env NODE_ENV=development npx rollup -c"   },   "bundleDependencies": false,   "dependencies": {     "axios": "^0.18.0",     "debug": "^3.1.0",     "md5": "^2.2.1",     "pako": "^1.0.11",     "pomelo-protobuf": "^0.4.0",     "pomelo-protocol": "^0.1.6",     "qs": "^6.9.4",     "socket.io": "^2.1.1"   },   "deprecated": false,   "description": "This is a live SDK for weclassroom.",   "devDependencies": {     "@babel/core": "^7.2.2",     "@babel/preset-env": "^7.2.3",     "cross-env": "^5.2.0",     "rollup": "^1.1.0",     "rollup-plugin-babel": "^4.0.3",     "rollup-plugin-commonjs": "^9.1.6",     "rollup-plugin-eslint": "^5.0.0",     "rollup-plugin-json": "^3.0.0",     "rollup-plugin-node-resolve": "^3.4.0",     "rollup-plugin-replace": "^2.0.0",     "rollup-plugin-uglify-es": "0.0.1",     "rollup-pluginutils": "^2.3.1",     "standard-version": "^4.4.0"   },   "license": "ISC" }
4. npm publish this package will fail。
5. when i remove "deprecated": false from package.json。it is will publish success.

Expected behavior
I think it should be uploaded successfully

Screenshots

Configuration File (cat ~/.config/verdaccio/config.yaml)
`#
This is the default config file. It allows all users to do anything,
so don't use it on production systems.

Look here for more config file examples:
https://github.com/verdaccio/verdaccio/tree/master/conf

path to a directory with all packages
storage: ./storage
path to a directory with plugins to include
plugins: ./plugins
url_prefix: /verdaccio/ 正式环境这个没有
web:
WebUI is enabled as default, if you want disable it, just uncomment this line
#enable: false
title: Verdaccio
auth:
htpasswd:
file: ./htpasswd
# Maximum amount of users allowed to register, defaults to "+inf".
# You can set this to -1 to disable registration.
max_users: 10000
a list of other known repositories we can talk to
uplinks:
npmjs:
url: https://registry.npm.taobao.org
cache: false
packages:
'@test*/*':
# scoped packages
access: $all
publish: $authenticated
proxy: npmjs
'**':
# allow all users (including non-authenticated users) to read and
# publish all packages
#
# you can specify usernames/groupnames (depending on your auth plugin)
# and three keywords: "$all", "$anonymous", "$authenticated"
access: $all
# allow all known users to publish packages
# (anyone can register by default, remember?)
#publish: $authenticated

# if package is not available locally, proxy requests to 'npmjs' registry
proxy: npmjs

You can specify HTTP/1.1 server keep alive timeout in seconds for incomming connections.
A value of 0 makes the http server behave similarly to Node.js versions prior to 8.0.0, which did not have a keep-alive timeout.
WORKAROUND: Through given configuration you can workaround following issue https://github.com/verdaccio/verdaccio/issues/301. Set to 0 in case 60 is not enought.
server:
keepAliveTimeout: 60
To use npm audit uncomment the following section
middlewares:
audit:
enabled: true
listen: <IP_ADDRESS>:4872
max_body_size: 100mb
log settings
logs:

{ type: stdout, level: info }
#- {type: file, path: verdaccio.log, level: info}

`

Environment information
System:
OS: Linux 3.10 Debian GNU/Linux 9 (stretch) 9 (stretch)
CPU: (64) x64 Intel(R) Xeon(R) Silver 4216 CPU @ 2.10GHz
Binaries:
Node: 10.15.0 - /usr/local/bin/node
Yarn: 1.12.3 - /usr/local/bin/yarn
npm: 6.4.1 - /usr/local/bin/npm
npmGlobalPackages:
verdaccio: 4.11.3

Debugging output

$ NODE_DEBUG=request verdaccio display request calls (verdaccio <--> uplinks)
$ DEBUG=express:* verdaccio enable extreme verdaccio debug mode (verdaccio api)
$ npm -ddd prints:
$ npm config get registry prints:

Please provide reproducible steps and if you can format the markdown the better.

i have same issue
https://github.com/verdaccio/verdaccio/issues/2261

Please create a new ticket, well documented, I don't understand this one. Closing.


(maint) Stop reencoding json catalog in benchmarking tool

This commit fixes a regression in the benchmarking tool that caused a
catalog to be reencoded to json every iteration of the benchmarking
tool.

Test FAILed.
Refer to this link for build results (access rights to CI server needed):
https://jenkins.puppetlabs.com/job/platform_puppetdb_intn-sys_pr/1315/

transients ^

:+1:


Allow turning 303 into a warning.

This fixes #2424:
jonathan@absinthe:/tmp $ cat test.fst
module Test

[@expect_failure]
let a = ()

let a = 2
jonathan@absinthe:/tmp $ fstar.exe test.fst --warn_error +303
test.fst(4,0-4,10): (Warning 303) This top-level definition was expected to fail, but it succeeded
Verified module: Test
All verification conditions discharged successfully

I did not see any issues with redefinition of the top-level a so this seems good.

thanks! it looks good. I also checked that expect_failure terms are already wrapped in a Sig_fail and will not be added to environment regardless of whether or not the error/warning is raised ... so my remark was a bit off. Turning the error in CError like you did should be enough. Will merge once CI comes back


[Question] - Are all these awesome plugins going to be added to Xamarin Essentials too?

I am going to install the ones I need individually, but it would be great if they were all added to Xamarin Essentials.

@stesvis Essentials won't be including absolutely every plugin and feature that we have.  We are working to add the most important ones that can work across all of the support platforms in a fresh, clean api.  If you have any wishes or suggestions you can add them directly to the Xamarin.Essentials issues list -> https://github.com/xamarin/Essentials/issues
Regards


Auto indexing WMS ID 11124

Publish PR

Please provide self-descriptive image names for example create-autonomous-database.png or select-workload.png etc. This is required from an accessibility perspective

Images renamed


Completed graph_op support for different forms of dynamism in graph mode

Examples include generic types and array-typed inputs without unknown size at compile time.
This is a follow-up to https://github.com/apple/swift/pull/20507, which added dynamic attribute support.

@swift-ci please test tensorflow

@swift-ci please test tensorflow

@swift-ci please test tensorflow

@marcrasi, I refreshed this PR. Can you PTAL? Thanks!

swift CI is still picking up the old commit 69bfe54 for testing, not the most recent one a45a816.
I'll follow up with @shahmishal on this external CI config issue.

@swift-ci please test tensorflow

Ok, this retrigger worked https://ci-external.swift.org/view/Pull Request/job/swift-PR-TensorFlow-Linux/1068/

@swift-ci please clean test tensorflow

The failed linux GPU test appears flaky and unrelated: https://ci-external.swift.org/view/Pull Request/job/swift-PR-TensorFlow-Linux-gpu/327/console

Thanks all for the review!


First-class functions

Essentially, functions should be possible to pass around as values:
func MyFunction() -> i32 {
    return 42;
}

export func Main() {
    var my_func: func() -> i32 = MyFunction;
}

Waiting for #51


Docs: correct type for AVIF speed output option

Should be number.
Fixes issue: https://github.com/lovell/sharp/issues/2567

Coverage remained the same at 100.0% when pulling 0aad19009bd4a2aa5c2f3f9a79a59f1fa261df61 on aprat84:docs-types into d7d580ae6f9bada7edea941e8f2c0efdc324d793 on lovell:master.


NeuroDesk - A scalable and easy to use data analysis environment for reproducible neuroimaging

Project info
Title: NeuroDesk - A scalable and easy to use data analysis environment for reproducible neuroimaging
Project lead: @stebo85
**[Timezone] Brisbane UTC+10
Description: Neuroimaging researchers require a diverse collection of bespoke command-line and graphical tools to analyse data and answer research questions. Installing and maintaining a neuroimaging software setup is challenging and often results in un-reproducible environments. Package managers and software repositories can help with this and NeuroDebian is a well-known example that drastically improves the neuroscience software distribution. However, a limitation of NeuorDebian is the inability to install neuroscientific software on Linux flavours commonly used on high performance computing systems or Windows and Macintosh computers. Researchers therefore still struggle to get access to the required software or to move analyses between different computing platforms due to the setup work required - ultimately limiting interoperability and reproducibility and impeding the broad sharing of analysis pipelines with the community. Container technology, such as docker or singularity, enables the execution of software on different operating systems and could aid in distributing scientific software. We are developing NeuroDesk, a platform build on container technology for processing and analysing neuroimaging data with the aim to lower the barrier of using various neuroimaging software in a reproducible environment, so that researchers spend less time on setting up and maintaining an analysis environment.
Two minute video introducing the project: https://youtu.be/JLv_5fycugw
Link to project: https://github.com/NeuroDesk
Mattermost handle: @sbollmann_mri
Goals for the OHBM Brainhack:

develop an electron user interface for Mac/Linux/Win that manages the docker setup in the background and provides a VNC/RDP client with clipboard support

Good first issues:

run NeuroDesk on your system and let us know what problems you run into and where usability could be improved
Open an issue for tools that you would like to see in NeuroDesk: https://github.com/NeuroDesk/caid/issues

Skills:

ideas for improving usability for non-technical users
electron/node.js/webassembly
github actions
linux admin skills
docker/singularity containers
building neurodocker recipes

Chat channel:
https://mattermost.brainhack.org/brainhack/channels/hbmhack-NeuroDesk

Image for the OHBM brainhack website

Project submission
Submission checklist
Once the issue is submitted, please check items in this list as you add under 'Additional project info'
Please include the following above (all required):

[x] Link to your project: could be a code repository, a shared document, etc. See here
[x] Include your Mattermost handle (i.e. your username). If you do not have an account, please sign up here.
[x] Goals for the OHBM Brainhack: describe what you want to achieve during this brainhack. See here.
[x] Flesh out at least 2 "good first issues": those are tasks that do not require any prior knowledge about your project, could be defined as issues in a GitHub repository, or in a shared document, cf here.
[x] Skills: list skills that would be particularly suitable for your project. We ask you to include at least one non-coding skill, cf. here.
[x] Chat channel: A link to a chat channel that will be used during the OHBM Brainhack. This can be an existing channel or a new one. We recommend using the Brainhack space on mattermost, cf. here.
[x] Provide an image of your project for the OHBM brainhack website

You can also include information about (all optional):

[ ] Someone co-leading the project in the timeslot you have not selected to provide additional visibility.
[ ] Number of participants, cf. here
[ ] Twitter-size summary of your project pitch, cf. here
[ ] Set up a kanban board on your repository to better divide the work and keep track of things, cf here
[x] Project snippet for the OHBM Brainhack website, cf. here

title: "NeuroDesk - A scalable and easy to use data analysis environment for reproducible neuroimaging"
image: https://user-images.githubusercontent.com/4021595/119743595-9312fb80-becd-11eb-9718-68239c08d085.jpg
details: "NeuroDesk is a platform build on container technology for processing and analysing neuroimaging data with the aim to lower the barrier of using various neuroimaging software in a reproducible environment, so that researchers spend less time on setting up and maintaining an analysis environment."
More information here"
We would like to think about how you will credit and onboard new members to your project. We recommend reading references from this section. If you'd like to share your thoughts with future project participants, you can include information about (recommended):

[ ] Specify how will you acknowledge contributions (e.g. listing members on a contributing page).
[ ] Provide links to onboarding documents if you have some.

QMENTA has agreed to sponsor the event and provide computational resources through their platform.

[ ] Get in touch with QMENTA through their Brain Innovation Hub Slack space, if you think your project would benefit from their support.

hi @ohbm/project-monitors: My project is ready!

@matteomancini - I see the project is in the "Needs revision" stage, but I can't find what I should change? Can you point me to the revisions required?

The revision is what we do. :) We notify you if there are any suggestions.

Can you, please, specify the optional information or untick the corresponding box(es)?
I assume the documentation is contained within the repo.
Have you also contacted QMENTA?

Dear @tiborauer - I unticked the boxes for the optional components. I am not planning on contacting QMENTA.

FYI, this project is listed as "Learn and Enhance BrainIAK Tutorials: From Basics to Advanced fMRI Analyses" on the website

Sorry! I have just updated the repo. The website should also reflect it soon.

Updated mattermost channel is here https://mattermost.brainhack.org/brainhack/channels/virtual-neuro-machine-vnm


Beit3 classification

Thanks for your inspiring and effective work. You achieved really great performance on imagenet-1k classification. As the paper mentioned, you treat classification as retrieval and do intermediate retrieval on imagenet-21k before fine-tuning. But we are wondering what you do for polysemy and same class names for different classes in the dataset imagenet-21k.
Looking forward to your reply.

Hi @amandaluof , we use the following code to preprocess the class names:
from nltk.corpus import wordnet as wn
syn = wn.synset_from_pos_and_offset('n', wordnet_id)
class_name = ", ".join(_.name() for _ in syn.lemmas())

The code and pre-trained models of BEiT-3 can be found at aka.ms/beit3.

Hi @donglixp and @addf400 !
I'm just following up about the last concern of @amandaluof.
I've noticed that in your implementation of the ImageNet finetuning where comments are here https://github.com/microsoft/unilm/blob/master/beit3/get_started/get_started_for_image_classification.md,
you are using the vision encoder instead of the dual encoder as mentioned in the paper.
Please, is there any release of the fine-tuned version of the dual encoder for the ImageNet classification task?


trying to compile it using python 3.6 but i get errors like this. please help me

src/nnvm/legacy_json_util.cc:190: Loading symbol saved by previous version v0.8.0. Attempting to upgrade...
[10:31:52] src/nnvm/legacy_json_util.cc:198: Symbol successfully upgraded!
Traceback (most recent call last):
File "classifier.py", line 24, in
model = turi.image_classifier.create(train_data, target="animals")
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/turicreate/toolkits/image_classifier/image_classifier.py", line 116, in create
ptModel = _pre_trained_models.MODELSmodel
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/turicreate/toolkits/_pre_trained_models.py", line 100, in init
self.mxmodel = _mx.model.load_checkpoint(_os.path.join(path, self.name), epoch)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/mxnet/model.py", line 421, in load_checkpoint
save_dict = nd.load('%s-%04d.params' % (prefix, epoch))
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/mxnet/ndarray/utils.py", line 175, in load
ctypes.byref(names)))
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/mxnet/base.py", line 146, in check_call
raise MXNetError(py_str(_LIB.MXGetLastError()))
mxnet.base.MXNetError: [10:31:52] src/ndarray/ndarray.cc:1114: Check failed: fi->Read(data) Invalid NDArray file format
Stack trace returned 7 entries:
[bt] (0) 0   libmxnet.so                         0x00000001092002cf libmxnet.so + 58063
[bt] (1) 1   libmxnet.so                         0x000000010920006f libmxnet.so + 57455
[bt] (2) 2   libmxnet.so                         0x00000001091ff979 libmxnet.so + 55673
[bt] (3) 3   libmxnet.so                         0x000000010a2e1e57 MXNDListFree + 1316471
[bt] (4) 4   libmxnet.so                         0x000000010a170d21 MXNDArrayLoad + 241
[bt] (5) 5   _ctypes.cpython-36m-darwin.so       0x0000000101b12247 ffi_call_unix64 + 79
[bt] (6) 6   ???                                 0x00007ffeef172f10 0x0 +<PHONE_NUMBER>94736

We have a known issue (#670) on MXNet 1.2. Are you using version MXNet 1.2+?

Closing due to inactivity; from the call stack, seems likely the same issue as #670.


[zh-cn]Update the description of how to access the dashboard

Description
Update http://localhost:8001/api/v1/namespaces/kubernetes-dashboard/services/https:kubernetes-dashboard:/proxy/ to http://localhost:8001/api/v1/namespaces/kubernetes-dashboard/services/https:kubernetes-dashboard-kong-proxy:443/proxy/
ref:

https://github.com/kubernetes/dashboard/blob/master/docs/user/accessing-dashboard/README.md#kubectl-proxy
https://github.com/kubernetes/website/pull/48205#issuecomment-2395044667

Hold till the upstream English PR https://github.com/kubernetes/website/pull/48210 is merged.
(OK to unhold once  PR https://github.com/kubernetes/website/pull/48210 is merged)
/hold


(JS-0392) Inconsistent usage of destructuring assignment

Description
It is recommended to use destructuring assignment of props as it improves readability and creates shorter code and helps in refactoring as well.
Occurrences
There are 5 occurrences of this issue in the repository.
See all occurrences on DeepSource → deepsource.io/gh/w3bdesign/dfweb-v3/issue/JS-0392/occurrences/

Løst.


Document bridging withdrawal process

Not sure if talking about what the sequencer and the EVM nodes do is the right way to go about this, but it seemed better than just saying "etherlink does everything." If I keep it this way I should probably also give more detail about what Etherlink does in the deposit process.
Preview: https://docs-etherlink-git-bridging-withdrawal-trili-tech.vercel.app/get-started/bridging#how-bridging-works

@vch9 Thanks for clarifying how things work with the precompiled contract on the Etherlink side. Does this sound correct?
https://github.com/etherlinkcom/docs/pull/101/commits/fb72e8c8dde9e6f3d6106887917aa689394343a2

@vch9 Thanks for clarifying how things work with the precompiled contract on the Etherlink side. Does this sound correct? fb72e8c

In comparison to the L1 contract worfklow, I find the "Etherlink" part a bit blurry. I don't know how technical and precise it should be though.
Here are a few changes I can propose:
diff --git a/docs/get-started/bridging.mdx b/docs/get-started/bridging.mdx
index 15e461a..a9d3b8f 100644
--- a/docs/get-started/bridging.mdx
+++ b/docs/get-started/bridging.mdx
@@ -70,8 +70,9 @@ The request includes the tez to bridge, the address of the Etherlink Smart Rollu
 1. The exchanger contract stores the tez and creates a [ticket](https://docs.tezos.com/smart-contracts/data-types/complex-data-types#tickets) that represents the receipt of the tokens.
 1. The exchanger contract sends the ticket to the bridge contract's `callback` entrypoint.
 1. The bridge contract forwards the ticket to the stored Etherlink Smart Rollup address and clears its storage for the next transfer.
-1. The Etherlink Smart Rollup transfers the ticket to a [precompiled contract](https://explorer.etherlink.com/address/0xff00000000000000000000000000000000000001) on Etherlink.
-1. The precompiled contract creates the tez and sends them to the user's Etherlink address.
+1. The Etherlink Smart Rollup receives the deposit request from the shared inbox.
+1. The Etherlink Smart rollup emits a corresponding transaction on Etherlink transferring the tez to the receiver address
+from the [zero address](https://explorer.etherlink.com/address/0x0000000000000000000000000000000000000000).

 This diagram is an overview of the deposit process:

@@ -79,12 +80,12 @@ This diagram is an overview of the deposit process:

 The withdrawal process follows these general steps:

-1. A user sends tez to a [precompiled contract](https://explorer.etherlink.com/address/0xff00000000000000000000000000000000000001) in the Etherlink Smart Rollup.
+1. A user sends tez to the [withdrawal precompiled contract](https://explorer.etherlink.com/address/0xff00000000000000000000000000000000000001) in the Etherlink Smart Rollup.
 The request includes their layer 1 address.
-1. The contract locks the tez and creates a [ticket](https://docs.tezos.com/smart-contracts/data-types/complex-data-types#tickets) that represents the receipt of the tokens.
-1. The contract puts the ticket in a call to the exchanger contract's `burn` entrypoint and puts this transaction in the Smart Rollup outbox on layer 1.
-The transaction exists in the outbox as part of Etherlink's commitment to its state.
-1. When the commitment that contains the transaction is cemented, anyone can run the transaction by running the Octez client `execute outbox message` command.
+1. The contract locks the tez.
+1. The contract emits an outbox message back to the exchanger contract's `burn` entrypoint and puts this transaction in the Smart Rollup outbox.
+The outbox message is part of Etherlink's commitment to its state.
+1. When the commitment that contains the transaction is cemented on L1, anyone can run the transaction by running the Octez client `execute outbox message` command.
 1. The exchanger contract receives the ticket, burns it, and sends the equivalent amount of tez to the user's layer 1 address.

 This diagram is an overview of the withdrawal process:

Actually the different nodes are documented in https://docs.etherlink.com/network/architecture, should we be precise about whether the transaction is in the evm-node or smart rollup node? It's relatively important w.r.t to tickets/inbox/outbox


Facing issue with Module

Please help me in this. Iam using Xcode 9.2

Hi,
For integrating Razor Pay
They are supporting only swift 3.1 and swift 4.1
If your project in swift 3.2 so the Razorpay framework has been compiled only for 3.1 either you need to upgrade your project to swift 4.1 or downgrade  (not recommended)
If you are going to upgrade note this point.

you need Xcode 9.3 which is the version supporting swift 4.1
for installing Xcode 9.3 you need mac os 10.13.6

once you are downloaded 9.3 don't remove the existing xcode version keep it in Application and use 9.3 in local either (Desktop or documents)
Don't rename the Xcode such as Xcode9.3 this will cause Razorpay header compile time issue.
This may help you...

closing due to inactivity.


Add support for printout(node_name: str)

In an environment with a lot of different loggers configured (especially by 3rd party modules) it would be useful to be able to filter the tree to a particular starting root. The printout method has a node parameter, but it appears to require passing a node object rather than the name of the node.
Is there a way to either easily get a node object by name? Barring that would ideally like to be able to pass the name of the target logger to the printout method.

I think that the Standard Library call logging.getLogger() will let you pass a name, and return its node. Try it out and see whether it works!

I'm going to go ahead and close this issue, in the hope that your silence means that logging.getLogger() accomplished your goal, and that you are now able to fetch nodes by name. Please feel free to make further comments here, though, even with the issue closed, if you have any final follow-up questions about its use!


Support for "z" coordinate in idf.save

In GitLab by @Huite on Dec 13, 2018, 09:57
Currently, the only supported coordinate dimensions are time, layer, y, and x.
For variable density models, it's useful to have the z rather than layer when z is constant over x and y (and time). In that case, the z value of the of the grid can be turned into a zbot and ztop attribute to allow for easy inspection in iMOD.

In GitLab by @visr on Jul 22, 2019, 11:51
Closed in favor of #55


Solution of problem with setting retirement date

#6181 - this problem
@miq-bot add_label bug, rails 4, core

@h-kataria Please review.

@lgalis wasn't this already fixed?

@h-kataria - the retirement was fixed for instances for the 'vm' controller,, but not for vm_or_template in explorer pages.

opened https://bugzilla.redhat.com/show_bug.cgi?id=1298722 to track changes and get fix backported to 5.5.z


Missleading link and out-of-date

On 'Azure VM requirements' topic there is a link on the text "Site Recovery supports all operating systems that are supported by Azure" which goes to a documents that is not talking about Azure and is no longer being updated.

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

ID: c721f5ae-ece4-58ab-d00d-65856907c364
Version Independent ID: 7912f48e-25be-6efb-e770-c30404d84c58
Content: Support matrix for Hyper-V replication to Azure
Content Source: articles/site-recovery/hyper-v-azure-support-matrix.md
Service: site-recovery
GitHub Login: @rayne-wiselman
Microsoft Alias: raynew

@henriquebrisola Thanks for the feedback! I have assigned the issue to the content author to evaluate and update as appropriate.

Fixed.
#please-close

@henriquebrisola We will now proceed to close this thread. If there are further questions regarding this matter, please reopen it and we will gladly continue the discussion.

This has not been fixed, link still redirecting to an outdated link that is talking about hyper-v support, not ASR

Still not fixed, link is still going to an old Hyper-V VM support page. I searched and could not find a current page with a full list of supported VM OSes in Azure anywhere - https://support.microsoft.com/en-us/help/2721672/microsoft-server-software-support-for-microsoft-azure-virtual-machines is close but focuses on software and not OS support.


Use the user.challenges[x].timestamp instead of querying the events.

We can tackle this whenever the current review log is cleaned up.
....We can also start thinking about firebase subcollections, but not a priority.

I don't have a PR open yet. I'll make the changes tomorrow, on top of #147 when merged. In the meantime, these are the tasks:

[x] Manually update the pending submitted challenges without submittedTimestamp field in firestore
[ ] Show side by side the user.challenges[x].submittedTimestamp and the currently computed timestamp to find any discrepancy. Fix any issues found here.
[ ] Remove legacy (current) code and leave only the code using user.challenges[x].submittedTimestamp

One thing we could easily add: sort the challenges by date. Not sure if oldest or newest first, but once we already have timestamps without further fetches, we can easily sort them by date.
Allowing to sort asc/desc by clicking in the header might be a bit more complex and it's probably worth a separate issue, but default-sorting them should be really simple and make the experience better.
WDYT @carletex?

One thing we could easily add: sort the challenges by date. Not sure if oldest or newest first, but once we already have timestamps without further fetches, we can easily sort them by date.

Yep, that would be cool. I'd say let's do ASC (oldest first): I think it makes more sense to attend older submitted challenge.

Allowing to sort asc/desc by clicking in the header might be a bit more complex and it's probably worth a separate issue, but default-sorting them should be really simple and make the experience better.

I was discussing earlier today with some admins/reviewers and they have some UX suggestions in the review page. Opening a new issue for it #148


Excruciatingly slow speed when moving a macOS virtual machine to an external SSD

Describe the issue
This is a follow-up to the closed issue #6187 (it was closed as "won't fix", but that was in relation to implementing a progress bar. I am reopening for the root issue: the excruciatingly slow speed of the "Move" operation).
I am trying to:

move a fresh macOS VM (18GB), to an external SSD (Samsung T9)
both source and destination are using APFS (Encrypted) filesystems

As I saw @adamallo's comment on the previous issue, I thought I would just wait, 7 hours isn't that bad...
But I have now waited 60 (sixty) hours, and the transfer is not even 50% done:

Configuration

UTM Version: Version 4.4.4 (93)
macOS Version: 14.3.1
Mac Chip (Intel, M1, ...): Apple M1 Max

Crash log
The app has not crashed.
Debug log
The problem occurs when the virtual machine is not running.
Upload VM
n/a

2024-04-20 Update
The Move operation completed successfully after 1 more day, for a total of around 85 hours.

Okay I spent too much time on this issue but the tl;dr is that Apple's implementation of copyfile for sparse files is broken because:

It uses the FS block size for copying (4096 bytes) instead of the optimal IO transfer size (usually 1MiB).
In each iteration of the loop, it calls lseek to find the next hole in the file which implicitly does a flush and prevents system caching.

Since copyfile is open source and since there doesn't seem to be any other way of doing APFS sparse copying, I went ahead and fixed the code and also wrote a Swift wrapper around it: https://github.com/osy/SwiftCopyfile/commit/faac327beaed77c1a3ec8e899887835777782f30
Fixing #1 gives a 4x improvement and fixing #2 gives another 10x improvement for a 40x improvement over Apple's original code. Testing this with a 18GB VM, I was able to match Finder's copy speed (6 minutes) to my USB 3.0 HDD.

For the record and closure, I must report a 10,000x improvement!
My case may be extreme, maybe because I was using the App Store version, slightly older. But anyway, what took 85 hours now takes only 23 seconds. Thank you so much @osy !
https://youtu.be/oTTBqAEwCuA


fixFix load profile print by default

Proposed changes
only enable_profile is true, print profile.
Further comments
If this is a relatively large or complex change, kick off the discussion at<EMAIL_ADDRESS>by explaining why you chose the solution you did and what alternatives you considered, etc...

run buildall


[BUG] - Label placement - "outside" conflicts with Multiline property in Select element

NextUI Version
2.4.8
Describe the bug
Label position in Select element depends on properties: labelPlacement="outside" and isMultiline={true}.
With isMultiline={true}, the label is displayed inside select border.
Code:
<Select
    labelPlacement={"outside"}
    label="User Properties"
    placeholder="Select properties"
    className="w-full"
    variant="bordered"
    selectedKeys={selection}
    items={properties}
    isMultiline={true}
>
    {properties.map((prop) => (
        <SelectItem key={prop} value={prop}>
            {prop}
        </SelectItem>
    ))}
</Select>

Visualization:

Other way - without multiline
Code:
<Select
    labelPlacement={"outside"}
    label="User Properties"
    placeholder="Select properties"
    className="w-full"
    variant="bordered"
    selectedKeys={selection}
    items={properties}
    isMultiline={false}
>
    {properties.map((prop) => (
        <SelectItem key={prop} value={prop}>
            {prop}
        </SelectItem>
    ))}
</Select>

Also, This issue can be found in NextUI documentation:

Your Example Website or App
No response
Steps to Reproduce the Bug or Issue

Import Select, SelectItem components.
Create Select element
Set labelPlacement="outside" property to the item.
Set isMultiline={true} property to the item.

Expected behavior
Label placement should not depend by isMultiline value (the label should be outside)
Screenshots or Videos
No response
Operating System Version
Windows
Browser
Chrome

Looking on this issue.


could add github star history figure to readme.md

just like

This information may not be very important to users, so it has not been introduced before.

This information may not be very important to users, so it has not been introduced before.

I believe that , it's useful to attract users from other alternatives , such as autogpt and autogen.
Metagpt's design philosophy seem to be more powerful than other alternatives.
The star history figure, and other competitive metrics in readme.md , can quickly attract more users.
And let metagpt totally replace alternatives soon. And than , to unite more developers to challenge OpenAI.

If you're interested, you can submit a pull request, but frankly, I personally don't think it's very important


Make the Incremental GC the Default

As a preparation step towards enhanced orthogonal persistence.
Also re-measuring the base line of the CI (micro) performance tests.

Comparing from ecf39a9 to 54a4c56: In terms of gas, 5 tests regressed and the mean change is +40.1%. In terms of size, 5 tests regressed and the mean change is +2.5%.

I believe we should run the perf tests without --force-gc as this causes unnatural and expensive partition copying for the incremental GC that is not triggered repeatedly in normal mode. I will remeasure the difference in a separate PR.

Put back on hold. We can enable this when EOP has become the default mode.