I need some help to reproduce DeiT-III finetuning result

Hi
Thank you for sharing finetune code & training logs
On IN-1k pretraining, I got similar results to your log: ViT-S 81.43 and ViT-B 82.88
But, I failed to reproduce finetune performance even with your official finetuning setting
So, I would like to ask for advice or help.
Here is my fine-tune result with ViT-B on IN-1k.

I expected performance will increase as your fine-tune log, but. instead, the finetune degrades the performance.

I double-checked my code but I still don't know why the result is totally different.
I'm using different library versions torch : 1.11.0a0+b6df043, torchvision: 0.11.0a0, timm: 0.5.4
It might cause some problems, but there was no problem in pretraining and the performance difference is too severe for a simple library version issue.
I'm sorry to keep bothering you, but could you please let me know if there is something wrong with my setting?
Or could you please share the ViT-B weights pretrained on IN-1k 192x192 resolution without finetuning on 224x224?
If you share the weights before finetune, I can verify my finetune code without doubting my pretraining.

Hi @bhheo,
Thanks for your message.
At first sight I don't see any error in your fine-tuning.
I have uploaded the 192 model to help you:
DeiT_B_192
Keep me informed.
Best,
Hugo

Thank you for sharing 192 model.
I will let you know if I find out an error in my code.

Hi, @TouvronHugo
I still haven't succeeded in reproducing the finetune results, but I want to share my progress
I have tried finetuning with your 192 model weight
The result is similar to the previous result
So, I think my pretraining is not the reason for the problem

I found that test-crop-ratio 1.0 is not implemented in your code
So, I tried fine-tuning with test crop ratio 1.0
Performance is improved but still far from target performance

Next, I will try to downgrade my library versions, torch and timm
I will inform you if I get a result.
Regards

I got similar results with torch==1.7.1 and timm==0.3.4
I also tried finetuning on V100 machine.
But, not effective

I don't know what should I do next to reproduce.
Could you give me a full log for fine-tuning ViT-B?
I think comparing train_loss or print(args) might help to find code errors in my code.
Best

This is quite strange as the most complex procedure is clearly pre-training and not finetuning.
Here the full log with train loss and memory consumption log_vit_b.txt
Best,

Thank you for your kindness.
Yes. I'm using the DeiT repo https://github.com/facebookresearch/deit/commit/a2ffd162 with minor changes, such as logger and bugfix.
Checking the difference with internal code might be helpful.
I put a tab here, because it makes an undefined linear_scaled_lr error when unscale_lr is True.
https://github.com/facebookresearch/deit/blob/9bfdc73653b27d6a96e563d25f6fdc9b620f057c/main.py#L341
Except this, I think my changes don't affect the training process.
I observed that my train loss is much lower than your logs.
So, my finetune might omit some regularization or trick. I will also double-check my setting.

I'll check that.
Yes, you are right, a tab was missing. I fix that ;)

Hi @bhheo,
Did you solve your finetuning issue?
I haven't had the time to compare my internal code and the public repo yet, but I should have some time in the next months.
Best,
Hugo

Hi @TouvronHugo
Unfortunately, the finetuning issue is not solved yet.
I have been busy with other issues.
But, I registered a few different finetune settings on our servers yesterday.
I think it might figure out what is the problem on my finetuning.
I will let you know when the experiments are done.
Best
Byeongho Heo

Hi @TouvronHugo and @bhheo, I also failed to reproduce the finetune performance using the official released code & pre-trained weight.
Specifically, under the same setting & configuration of @bhheo (I use the pre-trained weight @ 192 px here https://github.com/facebookresearch/deit/issues/167#issuecomment-1145654722 and set crop-pct to 1.0 during inference), my best fine-tuning performance is 83.47, which is also similar to @bhheo.
Since the official released code has crop-pct=0.875, so I guess there must be some other differences between the internal code and the public repo of Deit III.
Best
Yuxin

Hi @bhheo  and @Yuxin-CV,
I'm trying to look at this by September.
Just for information, I have launched a multi-seed experiment with my internal codebase.
I have: 83.81% +- (0.01%). So the gaps are not related to the init.
Best,
Hugo

Hi
I haven't reached to 83.8% accuracy.
But, I want to share my trials. I measured accuracy at the last epoch.

my finetune : 83.06%
AdamW -> lamb : 83.39%
RA -> no RA : 82.44%
RA -> ThreeAug : 82.68%
CE -> BCE (no smoothing) : 83.05%
mixup 0.8 -> mixup 0.0 : 83.07%
AdamW -> lamb, mixup 0.8 -> mixup 0.0 : 83.51%
attn-only : 83.24%
wd 0.1 -> wd 0.2 : 83.15%

Lamb optimizer improve the performance.
But, I don't think it is correct setting because it has much lower accuracy at epoch 0.
Fine-tuning costs only 20 epochs. So, I can test diverse settings.
I will keep searching on it.
Please let me know if you have any suspicious setting.
Best
Byeongho Heo

I also have trouble reproducing some of the results. For example, I tried to reproduce deit3_huge with and without imagenet-21k pretraining.

For 21k pretraining, when I fine-tuned my trained 21k-model, the best accuracy I can reach is 83.xx%.
But It should be pointed that the version of imagenet-21k is winter21 not fall11, which most of related works were done with.  Fall11 is not provided with the official Image-Net website. Also, I'm not sure which is the correct to do train-test split with 21k, thus I use all 21k. But I don't think these can affect such big gap of the training.

Hi,
I also have trouble reproducing some of the results. For example, I tried to reproduce deit3_huge with and without imagenet-21k pretraining.  For 21k pretraining, when I fine-tuned my trained 21k-model, the best accuracy I can reach is 83.xx%. But It should be pointed that the version of imagenet-21k is winter21 not fall11, which most of related works were done with. Fall11 is not provided with the official Image-Net website. Also, I'm not sure which is the correct to do train-test split with 21k, thus I use all 21k. But I don't think these can affect such big gap of the training.
Best, Jiasheng

Hi @tangjiasheng & @TouvronHugo, I guess there is something wrong with the input size for the ViT-H model.
The ViT-H model has patch_size=14 instead of 16, therefore the --input-size shouldn't be 160 (160 / 14 = 11.43 not an int).
I think you can try with --input-size=126 or --input-size=154 based on the Tab 6 of the paper.

Best
Yuxin

Hi @Yuxin-CV  and @bhheo,
Did you try to evaluate the 192x192 model at resolution 224x224 without fine-tuning?
(Just to have some additional insight before looking at the code in more detail )

Hi @tangjiasheng,
We use the ImageNet-1k val as a val during the 21k training. I think this explains the difference in the logs.
In your case use all 21k as val, right?
Best,
Hugo

Hi @Yuxin-CV,
Yes, good catch for the resolutions. With ViT-H/14 at resolution 128 and 160 the code works it only removes a few pixels from the border of the image which does not have a significant effect. But it's cleaner to use 126 and 154 ;)
Best,
Hugo

Hi @Yuxin-CV  and @bhheo,
I haven't had time to test but I just saw an error in the code (https://github.com/facebookresearch/deit/blob/cb1f48ab39c0f4f98701b0d269ca7f7b7bc63dc9/main.py#L419) . The model must be in training mode for the finetuning of deit III. If you have the time don't hesitate to test this ;)
(Without training mode drop-path is not activate)
Best,
Hugo

@TouvronHugo
Oh, it looks critical
I will test it ASAP
Best
Heo

Hi @tangjiasheng, We use the ImageNet-1k val as a val during the 21k training. I think this explains the difference in the logs. In your case you are using all 21k as val, right? Best,
Hugo

I use the same setting. Validating the model on 1k set by mapping the data using class_map within timm create_dataset func. Do you use different strategy?
Best,
Jiasheng

Hi
I got the result, and it is almost the same as the official log.
set_training_mode=True solves the fine-tune problem.

Thank you for your advice @TouvronHugo
Best
Heo

Hi
I got the result, and it is almost the same as the official log. set_training_mode=True solves the fine-tune problem.
Thank you for your advice @TouvronHugo
Best Heo

Great! I just fixed that in the code by adding a train_mode argument which is true by default.


API change proposal for observeMany

The current API for observeMany is this:
this.observeMany(['x', 'y'], (newValues, oldValues) => {
        const x = newValues[0];
        const y = newValues[1];
});

But perhaps this would be better?
this.observeMany(['x', 'y'], (newValues, oldValues) => {
        const {x, y} = newValues;
});

What about array destructuring?
this.observeMany(['x', 'y'], (newValues, oldValues) => {
  const [x, y] = newValues;
});

A nice thing about that is you can use whatever name you want without the awkward {thing: as} syntax:
this.observeMany(['x', 'y'], (newValues, oldValues) => {
  const [newX, newY] = newValues;
  const [oldX, oldY] = oldValues;

  console.log(`going ${newY > oldY ? 'up' : 'down'} and to the ${newX > oldX ? 'right' : 'left'}`);
});

Also it simplifies the implementation... not that that's a priority over having the right API!

uh, yeah, duh. :)


added a computer science link under engineering page

added the computer science section under engineering page and also added a link related to one of the introductory courses of Harvard University.

I see that the resource was already added under the computer science section for technology, I am going to cancel the PR.


cargo-udeps: 0.1.22 -> 0.1.23

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://github.com/est31/cargo-udeps/releases.
meta.description for cargo-udeps is: "Find unused dependencies in Cargo.toml"
meta.homepage for cargo-udeps is: "https://github.com/est31/cargo-udeps"
meta.changelog for cargo-udeps is: ""
Updates performed

Rust version update

To inspect upstream changes

Release on GitHub

Compare changes on GitHub

Impact

Checks done (click to expand)

built on NixOS

The tests defined in passthru.tests, if any, passed

/nix/store/gla6rx0sfafdhcaxf7yz6bradnr38477-cargo-udeps-0.1.23/bin/cargo-udeps passed the binary check.

1 of 1 passed binary check by having a zero exit code.

1 of 1 passed binary check by having the new version present in output.

found 0.1.23 with grep in /nix/store/gla6rx0sfafdhcaxf7yz6bradnr38477-cargo-udeps-0.1.23

found 0.1.23 in filename of file in /nix/store/gla6rx0sfafdhcaxf7yz6bradnr38477-cargo-udeps-0.1.23

directory tree listing: https://gist.github.com/e903bc68a2137addfb7263f2f6048cc3

du listing: https://gist.github.com/a3194a2e4b33c85113e2a4c0042cc206

Rebuild report (if merged into master) (click to expand)

4 total rebuild path(s)

1 package rebuild(s)

1 x86_64-linux rebuild(s)
1 i686-linux rebuild(s)
1 x86_64-darwin rebuild(s)
1 aarch64-linux rebuild(s)

First fifty rebuilds by attrpath
cargo-udeps

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/gla6rx0sfafdhcaxf7yz6bradnr38477-cargo-udeps-0.1.23 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A cargo-udeps https://github.com/r-ryantm/nixpkgs/archive/413dd2929433301431627f7bbdbafe8ed9b2f352.tar.gz

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/gla6rx0sfafdhcaxf7yz6bradnr38477-cargo-udeps-0.1.23
ls -la /nix/store/gla6rx0sfafdhcaxf7yz6bradnr38477-cargo-udeps-0.1.23/bin

Pre-merge build results
We have automatically built all packages that will get rebuilt due to
this change.
This gives evidence on whether the upgrade will break dependent packages.
Note sometimes packages show up as failed to build independent of the
change, simply because they are already broken on the target branch.
Result of nixpkgs-review run on x86_64-linux 1

1 package built:

cargo-udeps

Maintainer pings
cc @B4dM4n for testing.

@ofborg build cargo-udeps

Result of nixpkgs-review pr 138097 run on x86_64-linux 1

1 package built:

cargo-udeps


Custom ingest ffmpeg params (feature request)

Need to add custom params to ffmpeg (example -copyts) to ingest. Some of my camera stream going to error if not using "-copyts" param.

The vparams is for that, please check it.


poem-openapi: swagger-ui from several REST services

Description of the feature
If you have a big project seems good idea maintain REST methods of each entity on a different struct.  But actually there is no method to aggregate this services and generate a single OpenAPI specification.
It will be useful if exists an aggregate function that given several OpenAPI structs aggregates all the methods and give a single OpenAPI specification.
Code example (if possible)
#[derive(Tags)]
enum MyTags {
/// Operations about client
ClientOperations,
/// Operations about  product
ProductOperations
}
struct ClientApi;
#[OpenApi(tag = "MyTags::ClientOperation")]
impl ClientApi {
/// Hello client
#[oai(path = "/client", method = "get")]
async fn index(&self) -> PlainText<&'static str> {
PlainText("Hello World")
}
}
struct ProductApi;
#[OpenApi(tag = "MyTags::ProductOperation")]
impl ProductApi {
/// Hello product
#[oai(path = "/product", method = "get")]
async fn index(&self) -> PlainText<&'static str> {
PlainText("Hello World")
}
}
let api_service =
OpenApiService::new(aggregate(ClientApi, ProductApi), "Hello World", "1.0").server("http://localhost:3000");
let docs = api_service.swagger_ui();

Thank you so much, It works perfectly.
I also take this opportunity to thank you for your great effort in this project.


Vickel: Watch +18554983869

Vickel requests the watch of the watch_number +18554983869. See the MS search here and the Stack Exchange search in text, in URLs, and in code.

Rejected by double-beep in Charcoal HQ. Reason: 'better to blacklist upon first tp'


No support for multiple tool calls in one go

Sometimes the llm can call two functions at once. This is not supported now and raises an error that the length of the tool call results are > 1.
Error produced:
  File "/Users/.../lib/python3.12/site-packages/ell/providers/openai.py", line 72, in translate_to_provider
    assert len(tool_results) == 1, "Message should only have one tool result"

Code to reproduce
import ell

@ell.tool()
def get_user_name():
    return "Isac"

@ell.tool()
def get_ice_cream_flavors():
    return ["Vanilla", "Strawberry", "Coconut"]

@ell.complex(model="gpt-4o", tools=[get_user_name, get_ice_cream_flavors])
def f(message_history: list[ell.Message]) -> list[ell.Message]:
    return [
        ell.system(
            "You are a helpful assistant that greets the user and asks them what ice cream flavor they want. Call both tools immediately and then greet the user"
        )
    ] + message_history

if __name__ == "__main__":
    ell.init("playground/ell-logs/")
    messages = []
    while True:
        message = f(messages)
        messages.append(message)

        print("message.tool_calls:", message.tool_calls)
        if message.tool_calls:
            tool_call_response = message.call_tools_and_collect_as_message(
                parallel=True, max_workers=2
            )
            print("tool_call_response:", tool_call_response)
            messages.append(tool_call_response)
        else:
            break

    print(messages)

On it


litmus-portal doesn't work with latest helm chart

What happened:
litmus-portal was deployed via helm-chart (1.13.2) with release name: litmus-portal. It doesn't work. I assume that it could be becaus of hardcoded name of services in nginx.conf (see links below)

What you expected to happen:
It should work.
How to reproduce it (as minimally and precisely as possible):
helm upgrade --install litmus-portal litmus/litmus-portal --version=1.13.2
Try to login via UI, check error in the console output
Anything else we need to know?:
List of hardcoded values:
https://github.com/litmuschaos/litmus/blob/aa475a1002e2a4fdd72a2be54813b860433e739a/litmus-portal/frontend/nginx/nginx.conf#L34
https://github.com/litmuschaos/litmus/blob/aa475a1002e2a4fdd72a2be54813b860433e739a/litmus-portal/frontend/nginx/nginx.conf#L42
https://github.com/litmuschaos/litmus/blob/aa475a1002e2a4fdd72a2be54813b860433e739a/litmus-portal/frontend/nginx/nginx.conf#L52
Could be an issues too:
https://github.com/litmuschaos/litmus/blob/aa475a1002e2a4fdd72a2be54813b860433e739a/litmus-portal/graphql-server/pkg/k8s/cluster.go#L88
https://github.com/litmuschaos/litmus/blob/aa475a1002e2a4fdd72a2be54813b860433e739a/litmus-portal/graphql-server/pkg/k8s/cluster.go#L91

This is an old issue. @Jasstkn feel free to re-open this issue if it's not fixed.


Rebuild parser

Create a new parser that can fully parse discord markdown.
Create a real parser for handling /discord commands
Investigate combine, lalrpop, pest

Simple-ast can handle discord markdown and weechat just uses space splitting for commands


Cache the request InputStream

Handles #10

Tested the solution here a bit more and it doesnt seem like the filter can actually behave with both post and get methods.


Fix autoselectOnBlur select top suggestion even on click of other sug…

#113
as for test I'm not familiar with Jasmine, can't dig into it right now something like this I suppose:
    it('should select the clicked suggestion instead of top suggestion if autoselectOnBlur is true', function() {
      this.view.autoselectOnBlur = true;
      this.dropdown.getDatumForTopSuggestion.and.returnValue(testDatum);
      this.dropdown.getDatumForCursor.and.returnValue(testDatum2);

      var spy;

      this.$input.on('autocomplete:selected', spy = jasmine.createSpy());
      // this.input.trigger('blurred');
      // trigger a specific value click and check that it's actually selected instead of top suggestion

      expect(spy).toHaveBeenCalled();
      expect(this.input.setQuery).toHaveBeenCalledWith(testDatum2.value);
      expect(this.input.setInputValue)
        .toHaveBeenCalledWith(testDatum2.value, true);
    });

Coverage decreased (-0.4%) to 88.257% when pulling b645797886326a803df90eb9c484ab21717f21c1 on voidale:master into 1bb5c939702af30d097bf721f9647ea1becca6ed on algolia:master.

Coverage decreased (-0.07%) to 88.634% when pulling 344c0f2aa50c2632973951802a26e20909cd8767 on voidale:master into 1bb5c939702af30d097bf721f9647ea1becca6ed on algolia:master.

Coverage decreased (-0.07%) to 88.634% when pulling 8fa2fbdfbe89e8107bcfe70d66435c518f2d97ac on voidale:master into 1bb5c939702af30d097bf721f9647ea1becca6ed on algolia:master.

Coverage decreased (-0.07%) to 88.634% when pulling 8fa2fbdfbe89e8107bcfe70d66435c518f2d97ac on voidale:master into 1bb5c939702af30d097bf721f9647ea1becca6ed on algolia:master.

Coverage decreased (-0.07%) to 88.634% when pulling caf6ae38c12ea5fec3758050d7c8daeeed9679ad on voidale:master into 1bb5c939702af30d097bf721f9647ea1becca6ed on algolia:master.

Coverage decreased (-0.08%) to 88.62% when pulling 30b0c85f94723cdf58413979818c501084bf9f44 on voidale:master into 1bb5c939702af30d097bf721f9647ea1becca6ed on algolia:master.

Seems like a good fix, I believe you tested it manually @voidale.
Thanks a lot for your support in this issue!!

See #125 for the test


Create Plugin Health check

Situation
currently there is no way for aether to know if a plugin has terminated, we should build in a liveness check and restart a plugin if it dies.
we could use the rpc Ping() functionality for this

There is this open issue with go-plugin: https://github.com/hashicorp/go-plugin/issues/92

Linked the wrong issue


Fix/91

Codecov Report

Merging #139 (38875b1) into master (6d2d38e) will increase coverage by 0.00%.
The diff coverage is 100.00%.

@@           Coverage Diff           @@
##           master     #139   +/-   ##
=======================================
  Coverage   72.04%   72.04%
=======================================
  Files         690      690
  Lines       12165    12142   -23
=======================================
- Hits         8764     8748   -16
+ Misses       3088     3085    -3
+ Partials      313      309    -4

Impacted Files
Coverage Δ

...y-II/80. Remove Duplicates from Sorted Array II.go
100.00% <100.00%> (+9.52%)
:arrow_up:

leetcode/0091.Decode-Ways/91. Decode Ways.go
100.00% <100.00%> (+33.33%)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 6d2d38e...38875b1. Read the comment docs.


Calling refreshFormData on repeat fields clears them

Package
filament/filament
Package Version
v3.2.110
Laravel Version
v11.22.0
Livewire Version
v3.5.6
PHP Version
PHP 8.3.8
Problem description
I called refreshFormData with fields fields that are defined using Repeater::make and it cleared them.
Expected behavior
I expected the fields to be updated with their latest values.
Steps to reproduce

Create a simple Repeater field in your Resource:

                Repeater::make('comments')
                    ->simple(
                        TextInput::make('comment'),
                    ),

Add an action to getHeaderActions in the EditRecord:

            Actions\Action::make('update comments')
                ->action(function () {
                    // Modify comments
                    $this->record->comments = ['foo', 'bar'];
                    $this->record->save();

                    $this->refreshFormData([
                        'comments',
                    ]);
                }),

Observe that the comments repeater fields are cleared instead of updated with new values.

Reproduction repository (issue will be closed if this is not valid)
https://github.com/cloudshipco/filamentphp-repeater-refresh-bug
Relevant log output
n/a

Donate 💰 to fund this issue

You can donate funding to this issue. We receive the money once the issue is completed & confirmed by you.
100% of the funding will be distributed between the Filament core team to run all aspects of the project.
Thank you in advance for helping us make maintenance sustainable!

@yuters, simple repeaters do actually use a flat array to store items, so this might actually be a bug.

@zepfietje yep could probably be improved for simple repeaters. Just suggesting some workarounds.


Resolves #173 - Shared breakpoints support

🎉 Resolves https://github.com/yonaskolb/XcodeGen/issues/173
⚠ Don't release until xcproj launch 1.6.0
💡 Then remember change Package.swift#L19 to
.package(url: "https://github.com/xcodeswift/xcproj.git", from: "1.6.0")
😃 Thanks!

This change is

@alexruperez Could you rebase this? I think this would be a great feature to have.

Closing in favour of #177


Setup Error

after running the bin/hubot command
there is an npm error due no such file or directory in:
<EMAIL_ADDRESS>when i looked it appears that the directory now is 0.2.9

the clear solution for me is to change the name of the directory to 0.2.8 because i am a noob.
please stop me with a better suggestion

the same issue and waiting for the tips.

What is the fix for this?

For anyone finding this issue:
Not a very clean approach, but cd into<EMAIL_ADDRESS>and type ln -s 0.2.9 0.2.8
It will create a symbolic link. Worked for me, when I wanted to run npm install.


Fix potential concurrency problem with HeapChunkSelector::get_most_available_blk_chunk

we need to promise available_num_chunks and find max element are protected by mutex

:warning: Please install the  to ensure uploads and comments are reliably processed by Codecov.
Codecov Report
Attention: Patch coverage is 50.00000% with 1 line in your changes missing coverage. Please review.

Project coverage is 64.80%. Comparing base (1746bcc) to head (051961a).
Report is 3 commits behind head on main.

Files with missing lines
Patch %
Lines

src/lib/homestore_backend/heap_chunk_selector.cpp
50.00%
0 Missing and 1 partial :warning:

:exclamation: Your organization needs to install the Codecov GitHub app to enable full functionality.
Additional details and impacted files
@@            Coverage Diff             @@
##             main     #229      +/-   ##
==========================================
+ Coverage   63.15%   64.80%   +1.64%
==========================================
  Files          32       32
  Lines        1900     1952      +52
  Branches      204      202       -2
==========================================
+ Hits         1200     1265      +65
+ Misses        600      589      -11
+ Partials      100       98       -2

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

🚨 Try these New Features:

Flaky Tests Detection - Detect and resolve failed and flaky tests


feature: support different versions of systemd

For instance, in RHEL7 (systemd 219), user-mode systemd doesn't seem to be a thing. Also, certain unit attributes we populate today are unsupported, such as:

BindReadOnlyPaths
PrivateMounts
ReadOnlyPaths
TemporaryFileSystem

I understand older distros may not be a goal but if we want this project to be used on bigger companies, we'll have to account for this.

I think most of these are not essential, so we can live without if we detect older systemds. The ReadOnly* ones are nice to have though.
OTOH, even I have access to RHEL8 machines...

I think most of these are not essential, so we can live without if we detect older systemds. The ReadOnly* ones are nice to have though.
OTOH, even I have access to RHEL8 machines...

The hard part is to find a feature matrix to determine what attributes are available per version. If we had that, it would be easy to implement this. I need to do some digging because there's demand for RHEL 7 support :)

The hard part is to find a feature matrix to determine what attributes are available per version. If we had that, it would be easy to implement this. I need to do some digging because there's demand for RHEL 7 support :)

Even better would be to probe for support, but harder

Even better would be to probe for support, but harder

I don't think systemd even does that, does it?

I don't think systemd even does that, does it?

[ Quoting<EMAIL_ADDRESS>in "Re: [virtual-kubelet/systemk] featu..." ]

I don't think systemd even does that, does it?

don't know. You said you got an error, is that detectable from within systemk?
We could just barf out dummy units and see what happens

[ Quoting<EMAIL_ADDRESS>in "Re: [virtual-kubelet/systemk] featu..." ]

I don't think systemd even does that, does it?

don't know. You said you got an error, is that detectable from within systemk?
We could just barf out dummy units and see what happens

I just saw these in journal logs, when parsing the unit, eg
Unknown lvalue 'PrivateUsers' in section 'Service'

I just saw these in journal logs, when parsing the unit, eg
Unknown lvalue 'PrivateUsers' in section 'Service'

[ Quoting<EMAIL_ADDRESS>in "Re: [virtual-kubelet/systemk] featu..." ]

I just saw these in journal logs, when parsing the unit, eg
Unknown lvalue 'PrivateUsers' in section 'Service'

ugh, silently drops it #sigh

[ Quoting<EMAIL_ADDRESS>in "Re: [virtual-kubelet/systemk] featu..." ]

I just saw these in journal logs, when parsing the unit, eg
Unknown lvalue 'PrivateUsers' in section 'Service'

ugh, silently drops it #sigh

[ Quoting<EMAIL_ADDRESS>in "Re: [virtual-kubelet/systemk] featu..." ]

I just saw these in journal logs, when parsing the unit, eg
Unknown lvalue 'PrivateUsers' in section 'Service'

there is systemd-run which takes a unit as argument, I would assume that actually errors
when giving it the wrong thing?

[ Quoting<EMAIL_ADDRESS>in "Re: [virtual-kubelet/systemk] featu..." ]

I just saw these in journal logs, when parsing the unit, eg
Unknown lvalue 'PrivateUsers' in section 'Service'

there is systemd-run which takes a unit as argument, I would assume that actually errors
when giving it the wrong thing?

[ Quoting<EMAIL_ADDRESS>in "Re: [virtual-kubelet/systemk] featu..." ]

I just saw these in journal logs, when parsing the unit, eg
Unknown lvalue 'PrivateUsers' in section 'Service'

% systemd-run -p PublicTmp=no ls
Unknown assignment: PublicTmp=no
% echo $?
1

[ Quoting<EMAIL_ADDRESS>in "Re: [virtual-kubelet/systemk] featu..." ]

I just saw these in journal logs, when parsing the unit, eg
Unknown lvalue 'PrivateUsers' in section 'Service'

% systemd-run -p PublicTmp=no ls
Unknown assignment: PublicTmp=no
% echo $?
1

If the CLI does it, then maybe there's an API behind it? I'm not supportive of wrapping CLI because that's not a contract I trust in.

If the CLI does it, then maybe there's an API behind it? I'm not supportive of wrapping CLI because that's not a contract I trust in.

Maybe? Doesn't matter for our API as we can swap it later. Getting some
means of detecting and making that code easy and elegant is my goal for now
On Fri, 22 Jan 2021, 18:22 Pires<EMAIL_ADDRESS>wrote:

If the CLI does it, then maybe there's an API behind it? I'm not
supportive of wrapping CLI because that's not a contract I trust in.
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub
https://github.com/virtual-kubelet/systemk/issues/68#issuecomment-765566857,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AACWIW2DDCXQTHLH2NOZEBDS3GX5LANCNFSM4WNG7KGQ
.

Maybe? Doesn't matter for our API as we can swap it later. Getting some
means of detecting and making that code easy and elegant is my goal for now
On Fri, 22 Jan 2021, 18:22 Pires<EMAIL_ADDRESS>wrote:

If the CLI does it, then maybe there's an API behind it? I'm not
supportive of wrapping CLI because that's not a contract I trust in.
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub
https://github.com/virtual-kubelet/systemk/issues/68#issuecomment-765566857,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AACWIW2DDCXQTHLH2NOZEBDS3GX5LANCNFSM4WNG7KGQ
.

Regardless how we probe: this is what I had in mind: https://github.com/virtual-kubelet/systemk/pull/74

Regardless how we probe: this is what I had in mind: https://github.com/virtual-kubelet/systemk/pull/74


Support *_verification fields in PUT /customer requests

What problem does your feature solve?
SEP-12 includes a PUT /customer/verification endpoint that is meant to accept verification of fields previously provided to PUT /customer, like mobile_number or email_address. However, the anchor platform doesn't support this endpoint, and it doesn't support accepting the mobile_number_verification or email_address_verification fields in PUT /customer requests.
What would you like to see?
Instead of supporting PUT /customer/verification, allow the anchor to accept *_verification fields in PUT /customer, where * is a valid SEP-9 field. This will allow anchors implement a 2-step process where they first accept the field that requires verification and then request the verification of that field.
What alternatives are there?
The alternative is to support the flow described in SEP-12, which is to set the field requiring verification to the VERIFICATION_REQUIRED status in GET /customer responses, and accept the verification with the PUT /customer/verification endpoint.
I don't think this is the best approach because we are trying to move away from using GET /customer as a means of determining which fields need to be provided to the anchor, in favor of the client polling the transaction record for which KYC may be required instead.
cc @Ifropc

Added proposal to simplify verification process using only PUT /customer endpoint: https://github.com/stellar/stellar-protocol/pull/1431

Tracked internally as ANCHOR-582


Development

About RegisterController.
Firstly, existing code breaks after https://github.com/laravel/laravel/commit/3332ff4cb2f4195ef07901667211da1797279d98#diff-0b57c1ea71f6c74b303f196ef2a0ab3f.
Secondly, this controller dont use in published files, not in api.php, nor in web.php router files.


Counters not being parsed when retrieving multiple Jobs.

While trying to get the job with counters
public Map<String, Long> biz.paluch.spinach.api.Job<K, V>.getCounters();
this method is giving an empty map.
Though while monitoring the disque port I'm able to see that Information
Request sent.
GETJOB
$7
TIMEOUT
$4
3000
$5
COUNT
$1
2
$12
WITHCOUNTERS
$4
FROM
$12
queue1

Response received.
D-c2febd4b-JS81tdlqarcPjxLnZ9eLi9bQ-003d
$57
job-body
$5
nacks
:74
$21
additional-deliveries
:1
:1
:1
*1
*7
$12
queue1

Thanks for the bug report. Fixed with 4252580.

Thank for the prompt fix.

Thanks for the prompt fix.


feat: detect node dynamically, closes #308

major open points:

[ ] detect binary on macos
[ ] helpful error messages if it doesn't work
[ ] don't do this stuff at all if node happens do be on the path

if this was my action and I'd be starting from scratch, I'd not do this. Taking the node version from the PATH can lead to very surprising behavior: imaging running some private actions alongside public actions. public actions would be run with a different node version than the private actions (unless the user makes sure @setup-node uses the same node version as the runner)

turns out process.env would achieve the same 🙈


[CoeursVaillants2] hotfix on field length

Submission Checklist
Required

[x] The pull request title clearly contains the name of the sheet I am editing.
[x] The pull request title clearly states the type of change I am submitting (New Sheet/New Feature/Bugfix/etc.).
[x] The pull request makes changes to files in only one sub-folder.
[x] The pull request does not contain changes to any json files in the translations folder (translation.json is permitted)

Changes / Description
Reduce text input length to fix display issue in repeating fieldset.

Character Sheet Info Roll20 Internal Use only.


Many functions fail for unknown reasons, error "No parameterless constructor defined."

This is what I'm seeing on debian sid under WSL:
>>> cos 45
Cannot dynamically create an instance of type 'Kalk.Core.KalkDoubleValue'. Reason: No parameterless constructor defined.

I've verified this with the trig functions, log, sqrt, exp, round, etc. abs produces a similar message referencing 'Kalk.Core.KalkCompositeValue'.
I'm not sure why this is happening, and my .NET Core 7 installation seems fine otherwise. Any particular information I should send you for this one? Not sure what would be helpful.

Indeed, I assume that you downloaded one of the binaries from the releases. It seems that .NET 7 is using a more aggressive code trimming.  This should be fixed by commit 0727d28 and available in a new version 0.8.1 soon.

FYI, the Kalk homepage still links to version 0.8.0 which is broken due to this problem. Can that be updated?

FYI, the Kalk homepage still links to version 0.8.0 which is broken due to this problem. Can that be updated?

Oops, indeed, thanks for reporting. This is fixed by commit 2650cb6


Documentation for creating a new site

Not sure if I missed something but in following the documentation I get errors "Error: command error: Unable to locate config file or config directory. Perhaps you need to create a new site."
From what I have pieced together from other guides I needed to:
docker run --rm -v $(pwd):/src hugomods/hugo:exts hugo new site new_site --format yaml
sudo chown -R $USER: new_site
cd new_site
before creating the docker compose. Sure it would help others to know this (if correct) in the docs

Yeah, there isn't doc about creating site, will update doc later.

Done, https://docker.hugomods.com/docs/development/prerequisite/#hugo-site, thanks for your feedback.


iOS crash NSInvalidArgumentException-[SemanticsObject accessibilityFrame]

Steps to Reproduce
This crash showed up in Sentry logs for Hamilton; we don't have a repro case yet but I wanted to file an issue in case anyone has an idea for what might be wrong or runs into it. I have been able to use the app on iOS with Voiceover successfully, it didn't crash. Seems to happen on various iOS devices and versions, it's not a super common crasher though (12 users so far).
NSInvalidArgumentException
Application threw exception NSInvalidArgumentException: -[__NSCFNumber window]: unrecognized selector sent to instance 0xbadd59bd747dbead

Flutter 0x1005a917c -[SemanticsObject accessibilityFrame]
Called from: UIKit-[NSObject(UIAccessibility) accessibilityActivationPoint]
Runner 0x1000359b8 mainRunner/main.m:7
Called from: libdyld start

Seems to be a crash here in AccessibilityBridge:
  CGFloat scale = [[_bridge->view() window] screen].scale;

I believe that the view is set in FlutterViewController:
  _platformView->ToggleAccessibility(self.view, enabled);

Why would the _bridge()->view() be an __NSCFNumber?

@collinjackson @xster Is this still happening in more recent builds?


ESP266 file removal failure

Thanks for all the work @vlasovskikh on this project have just started using it and I'm impressed how easy to use it is.
I've encountered a bug while using the ESP8266MOD removing files with the Remove all files from the micropython device call it returns a Unknown Error removing file on call. I've tracked down the issue to the microcleanfs.py script specifically here:
line 51: for name in files.ls():
 ...

at the moment this returns a verbose output of the file including the file in same string e.g. ['./main.py file size 443 bytes'] leading to the error above.
Changing this too.
for name in files.ls((long_format=False)
fixed it for me. Thoughts into putting into production?

The fix is in master. I'll release the plugin for PyCharm / IntelliJ 2018.3 shortly.


Unvalid work flow

Hi guys, thanks for this wonderful tool.

The result yolo dataset is like I have NOT done anything. That is weird, did I misunderstand the work flow?
when I datum project info, I get

and datum log, I get

So how can I do transform and filter at the same time?
I just can not figure out where I was wrong.
Thanks, any helpful would be great !

Hi! Glad you've found the tool useful. The commands you're using are correct, but when --apply=false is used, the behavior is more complicated. I'll try to explain.
With --apply=false the working copy of the dataset is not modified immediately. When the following commit is called, Datumaro computes and records the dataset hash - and the dataset is not modified in the working tree. You can see that there are 2 equal data hashes in the stage info output. Then, when you export, Datumaro restores the latest available stage - and it is the same as the original dataset.
There are few possible ways to obtain the required result:

(cli way) Manually edit proj/.datumaro/tree/config.yml and remove all the stage hashes after the first one before running the export command. This way, Datumaro will restore the original source data and re-apply the stages added during exporting.
(cli way) remove (rename) the working copy dir before commiting the changes, so that the stage hash will no be computed and recorded
(api way) Do all the operations from a simple python script like this:

import datumaro as dm
dataset = dm.Dataset.import_from('path/to/1.json', 'coco_instances')
dataset.transform('split', splits=[('train', 0.9), ('val', 0.1)])
dataset.filter(expr='/item/annotation[label!="A" and label!="B"]', filter_annotations=True, remove_empty=True)
dataset.export('output_dir/', 'yolo', save_images=True)

I agree that this particular situation and CLI experience in general needs to be improved.

Hi! Glad you've found the tool useful. The commands you're using are correct, but when --apply=false is used, the behavior is more complicated. I'll try to explain.
With --apply=false the working copy of the dataset is not modified immediately. When the following commit is called, Datumaro computes and records the dataset hash - and the dataset is not modified in the working tree. You can see that there are 2 equal data hashes in the stage info output. Then, when you export, Datumaro restores the latest available stage - and it is the same as the original dataset.
There are few possible ways to obtain the required result:

(cli way) Manually edit proj/.datumaro/tree/config.yml and remove all the stage hashes after the first one before running the export command. This way, Datumaro will restore the original source data and re-apply the stages added during exporting.
(cli way) remove (rename) the working copy dir before commiting the changes, so that the stage hash will no be computed and recorded
(api way) Do all the operations from a simple python script like this:

import datumaro as dm
dataset = dm.Dataset.import_from('path/to/1.json', 'coco_instances')
dataset.transform('split', splits=[('train', 0.9), ('val', 0.1)])
dataset.filter(expr='/item/annotation[label!="A" and label!="B"]', filter_annotations=True, remove_empty=True)
dataset.export('output_dir/', 'yolo', save_images=True)

I agree that this particular situation and CLI experience in general needs to be improved.

😄 Frankly, I was not expecting such a fast reply !
Actullay I prefer the api way, I will test it and then close this issue.
Thanks again!


WRN-9482: Fix showing unexpected string in sampler

When the select knob is used, we were able to select undefined or null through knobs.
But with controls, we cannot set undefined or null by default so we added (empty string) for that case.
Unfortunately, this leads to show unexpected string in some sampler so we've replaced it with' '.
Enact-DCO-1.0-Signed-off-by: SJ RO<EMAIL_ADDRESS>

Please add a changelog.


chore: refactor ChartHolder to typescript + tests

SUMMARY
This PR refactors the ChartHolder into a functional component with typescript.
It also adds more test coverage.
BEFORE/AFTER SCREENSHOTS OR ANIMATED GIF
--
TESTING INSTRUCTIONS
--
ADDITIONAL INFORMATION

[ ] Has associated issue:
[ ] Required feature flags:
[ ] Changes UI
[ ] Includes DB Migration (follow approval process in SIP-59)

[ ] Migration is atomic, supports rollback & is backwards-compatible
[ ] Confirm DB migration upgrade and downgrade tested
[ ] Runtime estimates and downtime expectations provided

[ ] Introduces new feature or API
[ ] Removes existing feature or API

/testenv up

🏷 Preset-Patch

@diegomedina248 Thank you for this PR! I have a SqlEditor refactoring into FC, can I share the code with you?
@michael-s-molina @kgabryje Can we merge the PR?

@diegomedina248 Thank you for this PR! I have a SqlEditor refactoring into FC, can I share the code with you? @michael-s-molina @kgabryje Can we merge the PR?

@EugeneTorap sure thing!

/testenv up

/testenv up

I found an issue that if user click on the filter indicator when chart is in fullscreen view, user will bring out to the normal view and the 3 dot menu on charts are not open. I test on superset master it seems like on master click on the filter indicator in enlarge chart view did not bring user to fullscreen view.
https://user-images.githubusercontent.com/81597121/185463251-0c2ffd93-8d7d-4642-93fb-02d2494c986d.mov

I found some issues in this PR: 1, if user click on the filter indicator when chart is in fullscreen view, user will bring out to the normal view and the 3 dot menu on charts are not open. I test on superset master it seems like on master click on the filter indicator in enlarge chart view did not bring user to fullscreen view.
Screen.Recording.2022-08-18.at.11.06.53.AM.mov
2, for numerical filter, it looks like the filter bar is not shown correctly when user select filter range:

mm, I actually couldn't reproduce those.
I did rebase from master, to have the branch up to date, and couldn't reproduce either that way.
Here's what I'm doing:
https://user-images.githubusercontent.com/17252075/185916954-9f0699d2-6808-4773-823d-2188fdfa801f.mov

/testenv up

Test again in the new ephemeral env and verified the reported issue is fixed. Regression test for dashboard LGTM

@michael-s-molina Can you review the PR and then merge it?

@michael-s-molina @kgabryje Can you review the PR and then merge it?