Reformat ternary operator

From @lijunray on March 6, 2017 22:4

VSCode Version: 1.9.1
OS Version: MacOS 10.12.3

Steps to Reproduce:
The default reformatting for ternary operator is working unexpectedly.
What I want:

After Reformatting:

How can I config the reformatting so that it works as I expect?
Copied from original issue: Microsoft/vscode#22110

Example code:
const test = (a) => (
	a === '1' ? (
		10
	) : (
		12
	)
)

Format request:
[Trace - 2:09:16 PM] Sending request: format (187). Response expected: yes. Current queue length: 0
Arguments: {
    "file": "untitled:Untitled-6",
    "line": 1,
    "offset": 1,
    "endLine": 7,
    "endOffset": 2
}
[Trace - 2:09:16 PM] Response received: format (187). Request took 3 ms. Success: true
Result: [
    {
        "start": {
            "line": 3,
            "offset": 5
        },
        "end": {
            "line": 3,
            "offset": 6
        },
        "newText": ""
    },
    {
        "start": {
            "line": 5,
            "offset": 1
        },
        "end": {
            "line": 5,
            "offset": 3
        },
        "newText": "\t\t\t"
    },
    {
        "start": {
            "line": 6,
            "offset": 1
        },
        "end": {
            "line": 6,
            "offset": 2
        },
        "newText": "\t\t"
    }
]

This bug is still present as of 1.17.2 (latest version)

I def still see this bug

Still broken

Still broken... Is there any progress on this?

Still broken... I assume given how old this issue is that it will never get fixed? :(

Yeah.. I don't get how Microsoft think. TypeScript is their own technogy and so is VSCode.. it's been 3 years soon.

What is everyone doing in regards to this?

disable formatOnSave entirely for TypeScript files?
refactor ternary operators and use something else?
live with the pain of having to deal with unwanted automatic changes in formatting (for example, committing these changes by mistake and then having to fix them)?

@isaacalves prettier

@isaacalves I use WebStorm instead

I've just found out that if you have the ? of the ternary operator in a new line (instead of in the same line of the conditional), the formatting will be like this:
const test = (a) => (
    a === '1'
        ? (
            10
        ) : (
            12
        )
)

That seems to be ideal actually, and probably related to this
By the way I use prettier, and VS Code.


512 images decoder result are extremly bad

Got an image like this

Is there a way to reconstruct it?
Currently only got:

This model is trained with imagenet, so it is not for text rich document-like image.

Got an image like this
Is there a way to reconstruct it?
Currently only got:

Hi, as we currently only released the TiTok at resolution 256, may I ask how did you apply it on your image? Simple resize/crop should be fine. If you want to apply current released model to a larger resolution image, it could be challenging as ViT itself is known to not generalize to different resolution well. Some solutions (but mostly requires a re-training) to improve ViT at arbitrary resolution/aspect ratio do exist but they are beyond this project's scope. I attached them for a reference if you are interested.
https://arxiv.org/abs/2307.06304
https://huggingface.co/adept/fuyu-8b

@cornettoyu  Input size is really my concern. For ViT based tokenizer, it has to be resize, the the output would be very blurred when resize back, I tried with Open-Magivt2, it trained with 128, encoded this image perfectly, and redecode at original flawlessly.
I am simply resize the input image and feed into model.
Yes, you were right, currently I am afraid using ViT as image tokenizer isn't a good choice, as they always constrainted by input size. OpenMagvit2, on the other hand, has no problem with it. However, their issue is, tokens are too much...

bad result also


Query execution time performance

In continuing to https://groups.google.com/forum/#!search/promethues/prometheus-users/kZ2DvZnYHUA/YDd81RhtBAAJ
we found the default resolution \ step size in seconds significantly affect the query execution time performance, specially on large scale setups.
we can change the default graph resolution to 15 or even 30 sec to make sure large results set will not reach the gateway timeout error.
as long the step size increased it will speed up the results, most of the impact is around innerEvalTime, see the following:
step 15:
2018-07-16 17:44:50,240 - INFO - duration: 1.862589-":{"timings":{"evalTotalTime":1.778064077,"resultSortTime":0.007469064,"queryPreparationTime":0.349853693,"innerEvalTime":1.420712212,"execQueueTime":0.000001542,"execTotalTime":1.778074411}}}}
2018-07-16 17:44:52,327 - INFO - duration: 1.882672-":{"timings":{"evalTotalTime":1.805533145,"resultSortTime":0.007118621,"queryPreparationTime":0.335963486,"innerEvalTime":1.462436464,"execQueueTime":0.000001463,"execTotalTime":1.805540575}}}}

step 5:
2018-07-16 17:47:00,519 - INFO - duration: 4.037879-":{"timings":{"evalTotalTime":3.8893069000000002,"resultSortTime":0.008419253,"queryPreparationTime":0.361821925,"innerEvalTime":3.519047432,"execQueueTime":0.000001234,"execTotalTime":3.889314616}}}}
2018-07-16 17:47:05,371 - INFO - duration: 4.309454-":{"timings":{"evalTotalTime":4.141177569,"resultSortTime":0.008191162,"queryPreparationTime":0.34855919,"innerEvalTime":3.784409001,"execQueueTime":0.000001366,"execTotalTime":4.141185931}}}}

by this issue we trying to address and support reliable performance by high resolution in sec, specially on large scale.
currently change the resolution is sort of workaround and not an optimal solution.

Environment
running prometheus by docker on quite large host with 40 cores with no limits

System information:
Linux 3.10.0-907.el7.x86_64 x86_64

Prometheus version:
v2.3.2

Can you clarify exactly what you are reporting here?
You requested 3 times the amount of work to be done, which took less than 3 times longer. I don't see anything wrong here.

my point is when users uses large scale tsdb, and they trying to work with the Prometheus UI graph they probably faced a timeout due to the default resolution which is 3 sec.

we can make the default to be 15s instead of 3.
do some further investigation to see whether is more room to improve the performance of vector-range functions for large scale

As (snarkily) explained in the prometheus-users thread, the time it takes to calculate a range (as opposed to instant) query is directly proportional to the resolution/number of steps. If your step is 3 seconds, then that's going to take ~5x the amount of computation as for a 15 second step.
While optimizing the query engine would help improve things overall, your query is still going to take 5x more at 3 second resolution than at 15 second resolution. I have proposed a handful of PRs that attempt to improve query performance, but they will only do so incrementally (e.g. even if a query turns out to be twice as fast with these changes, all it takes to undo that is twice the number of series; or sum(x) - sum(y) instead of sum(x)).
As Brian pointed out, you need to optimize your queries. What I'm doing for the equivalent queries on my dashboards (which would otherwise take on the order of 30 seconds to load) is that I have recorded rules to precompute e.g. rates and pre-aggregate e.g. by handled or status code. It takes away a bit of the flexibility, so for a couple of important dashboards I have the fast version (which displays the output of said recorded rules) for general consumption and the debug version (which does everything on the fly and thus allows for a few more filters and knobs) for actual debugging. But I know that I can only use the latter for ranges of up to 1 hour and wait for 30 seconds after every change to the filters.

This is stale, and there doesn't appear to be an issue here.

@mrsiano , Prometheus may write data to remote storage, so you can offload heavy queries to remote storage instead of Prometheus. While many remote storage solutions do not understand PromQL (so you need to use another query languages such as SQL, InfluxQL, Flux, etc.), there are a few remote storage solutions with native PromQL suppot (so you can just update Prometheus datasource url in Grafana for querying the remote storage):

M3DB
VictoriaMetrics


Added checkpoint with time in properties

Changes Unknown when pulling e8019fc698a3920058fea9467a711a928dad9fee on compae:feature/checkpoint-with-time-optional into ** on Stratio:master**.

Coverage decreased (-0.006%) to 47.188% when pulling e8019fc698a3920058fea9467a711a928dad9fee on compae:feature/checkpoint-with-time-optional into 522eeb62d6dd5bf9b18d80d643d59fb27b648e84 on Stratio:master.


Towntag token for chat managers

requesting for a Towntag token to be displayed in chat managers as a prefix. (nucleus)

@dualspiral Would you be able to provide some insight on how I can handle this request? Not familiar with how nucleus handles chat. Thanks!

I'll see what I can do and perhaps PR that in as the short term fix.
Are there any other tokens that would be of use (at least for now?)

Sounds good thanks. Nope, town tag is the only thing currently being used.

Thanks! I'll provide user with a jar so they can test soon.

I'm available to test this at any time


uucore: add usage errors

Adds support for the "Try {utilname} --help for more information string." to UError through a usage method. I also added UUsageError, which is identical to USimpleError but shows the usage string.

would it be possible to have a test to cover this? thanks

It will be covered when it's used by the utils. Probably already in #2472. I could also add a doctest for UUsageError. I'll try to do that soon


API to generate auth token

Looking at the docs[1] it seems the only way to generate an auth token is via the UI, it would be great if we could do this via the api too.
[1] https://github.com/sdelements/lets-chat/wiki/API%3A-Authentication

At the present time our hands are tied. With what auth token would you use to generate an auth token? We have no permissions in the app so its not like an admin user could do it. Maybe when we have admin roles, etc. we could do this?

Yeah I see your point.
I'm trying to automatically setup the integration for Lets Chat, Taiga, Gogs and Hubot.  I'm just trying to figure out the options at the moment but taiga offered a way to generate an auth code after logging in with a username/password http://taigaio.github.io/taiga-doc/dist/api.html.
It may not be the best way and maybe I need to understand more about oauth options.  I was hoping to hook them all up to the github oauth to authenticate for starters.  I dont know enough so I will do some more reading but does that sound like a better route to start investigating?  Could it be possible to use oauth and that give me a bearer token for a system user that would be shared between multiple projects like taiga and hubot?

One possibility for us is to expose a single token-generating endpoint that accepts username/password? Not sure, I'm sure the security people here have an opinion on best practices, etc.

And I think that would be great however as you say there's probably wider concerns but if a way could be figured out it would be awesome.

I should read our own documentation :) We do have Basic Auth support but it uses the token. I guess what we could do is change the meaning of Basic Auth for one end-point. But that's just seems weird

We're heading towards a multi-token setup, an endpoint for token management is definitely something we should consider doing.

Ok cool, that sounds great.

Maybe if there was just a way to generate a token from the outside and pass it into letschat when it starts up; then folks could use the REST API if they knew the 'admin token'?

in many ways this issue (which i've submitted a PR for) https://github.com/sdelements/lets-chat/issues/509 is a good enough fix for this issue really; it lets us spin up a hubot user on startup so that hubot can talk to letschat

+1  for this. Looking forward for API endpoint for generating token (e.g. via posting username & password and sending token as a response - that would be great! )

I have added an endpoint to generate token. It accepts username and password(in body) for authentication.
It scraps old token and returns a new one.
I would like to create a pull request if this feature is wanted.
see this commit


Introduce settingsOpenServerSocket

This is a companion to https://github.com/kazu-yamamoto/network-run/pull/3 , and relies on that PR to have been merged before this will build.
This adds the additional argument of runTCPServerWithSocket as a new field of Settings, with openServerSocket as its default.

Merged.
A new version has been released.
Thanks.

Awesome, thanks! :)

@kazu-yamamoto I don't see settingsOpenServerSocket in the released version... not sure if I have made a mistake somewhere or whether something went wrong with the release?

Sorry.
It appeared that I did not release http2-tls!
I have certainly released v0.2.6 this time.


Guide request for Router to work with CDN and a

It does not work out of the box sadly,
right now the first thing everyone gets after includig it in your project by using

with documentation examples is this error:
Uncaught ReferenceError: Router is not defined.
I've tried a lot of approaches (Yes, I did search for it for a few hours) and all of them have ended with other errors (mostly undefines, ContextType issues), even after Router was finally accessible.
I'd like to avoid npm for the project I'm using React for, since I want to keep the dir/file count low.
Also npm is known to disturbing git on windows caused by long paths (package dependency nesting),
I don't want to deal with that ever again.
So is there or will be there a definitive guide how to get this working after
placing

in my ?

For a new project you should not use v0.13.x.
With the bundle, the components you want are on window.ReactRouter, not window.Router.

So there won't be a version, that works with just the cdn script tag ever?
Yes, but even after you access Router via window.ReactRouter, it does not work.
Has anyone tried the cdn build?

What? No. The imports work just fine - http://jsfiddle.net/gqf0Lsdn/.

This fiddle is what I've been looking for, thank you :)
I had the react version without addons, so that was the issue for me.

There is no dependency on addons: http://jsfiddle.net/gqf0Lsdn/1/

In my project I get TransitionGroup undefined error if use the react file included in their samples dir on the downloadable package. The one in the CDN wuth addobs you used in fiddle did not throw this error.
I was also previously using babel browser.js included in their samples dir for compilation, so that could have been a factor too. Switching to the jsx compiler you have in your fiddle might have soled something too.
Could you place this fiddle in documentation?
I think others might benefit from that.

TransitionGroup has nothing to do with React Router. It is a part of the React addons, so you will of course need the React addons for that, but it's not a dependency of React Router, nor is it used, so we have no particular reason to document it.

In your own fiddle you have mention of TransitionGroup:

That gets an error of undefined for version
of react that does not have addons.
Before then I used a similar example of making the Router avaivable to my react view js that I found on my initial few hour search.
I can provide a jsfiddle if you're not convinced.
The issue was open due to lack of documented examples for use with react and the CDN version of router. That's still the issue here, since It wont work with the bundled version examples.
There is still no such comprehensive tutorial/fiddle in documentation.
So this fiddle is the key to have a working version and not spending useless hours for searching a solution; if it had been in the documentation, I could have started to work with router immidiatley.
But I have a feeling you don't care about that...

 You can see in http://jsfiddle.net/gqf0Lsdn/1/ that the transition group was entirely peripheral, and everything works just fine with the standard React bundle.
We're interested in supporting all of our users, but the instructions are entirely clear on this matter - just pull in the file from the CDN, and everything's available on window.ReactRouter. I just don't see what more there is to document here.

Nowhere it says I have to do this to make it work with your examples:
'''
var Router = ReactRouter;
var Route = Router.Route, DefaultRoute = Router.DefaultRoute,
Link=Router.Link, RouteHandler = Router.
'''
If I don't do It, it does not work with examples.
How is that being entireley clear on how to make the router functional even if I just drop
your example code there from the get go.
However I am getting bored with the arguments you present and can tell you won't change a thing, so
at this point I see there is no point to continue this, since nothing of value can be added to this thread anymore.

Nowhere it says I have to do this to make it work with your examples:

If I don't do It, it does not work with examples.

How is that being entireley clear on how to make the router functional even if I just drop
your example code there from the get go (and use the cdn)?

Can you please clarify your expectations? Did you expect Router, Link, etc, to be global exports? I can see how this can be confusing.

I am getting bored with the arguments you present and can tell you won't change a thing, so
at this point I see there is no point to continue this, since nothing of value can be added to this thread anymore.

Instead of arguing, please create a PR that better explains how to use UMD build.

I usually expect example code to work without adding anything to it.
Most people do, BTW.
Especially after something like this:

If you just want to drop a


Some websites are faker and unsafe.

Some websites are faker and unsafe.
v3.bootcss.com

Some CDN links are unsure.
http://libs.baidu.com/jquery/1.9.1/jquery.min.js

It's not the official website.
bootcss.com

in https://read.douban.com/reader/column/6946508/chapter/35572661/?dcs=chapters&dcm=chapter-list


Plans for Plexdrive 5.x?

I am curious if there are plans for updating this to Plexdrive v5? I've had quite noticeably improved performance and lower memory consumption on the 5.x release.
If you don't have plans, would there be a willingness to merge my PR if I did the work?

The reason why I chose Plexdrive v4 was that it cache data to a disk and not memory. In Plexdrive v5 there is no option to store cached data in anything else than memory.
However I could create a branch with Plexdrive v5 if that's fine with you.

In v5 you control RAM consumption using the --chunk-size and --max-chunks parameter. Do you normally find that v4 eats as much RAM as it can then? Right now that's my experience with it.
It sounds like v4 might be well suited for different use cases that v5 then, a different branch would make the most sense. I'll spend some time looking to see how we might best deal with the configuration differences between the two under the idea that they should both be alive and reasonably easy to maintain.

Yeah I know that. The problem is that I like to have a lot of cache on my machine to allow multiple streams and keep the buffering as low as possible. Right now I'm caching roughly 4 TB.
In my point of view Plexdrive v4 is better for media streaming than Plexdrive v5 because streaming huge files can only be cached limited. Imagine you are streaming a 4k media that has a total size of +50GB. That would require a lot of RAM if you want to cache the whole file into memory.
However that is just my point of view and for some people Plexdrive v5 works just fine.
Yeah a new branch or a parameter set to use Plexdrive v5.


build: Update to Vulkan-Headers 1.3.248

There are no changes to the generated code from this update.

CI Vulkan-ExtensionLayer build # 382 running.


Can't get driver to execute from a button click

I'm sure I'm doing something wrong here.  Driver seems to work fine if it's included inline in a page.  For example
const driver = new Driver();

  driver.highlight({
  element: '#title',
  popover: {
    title: 'Title for the Popover',
    description: 'Description for it',
    }
  });

However if I wrap it in a function and try to call it from a click like this, it fails:
function startTutorial()
{
  const driver = new Driver();

  driver.highlight({
  element: '#title',
  popover: {
    title: 'Title for the Popover',
    description: 'Description for it',
    }
  });
}

Essentially the screen dims like it's going to popover, then goes back to normal without showing the pop.

You need to add e.stopPropagation() on the button click that triggers the driver.

Thank you for this.  I saw that line all the way at the end of the doc

Note – Do not forget to add e.stopPropagation() to the click binding that triggers driver
But I'm no expert in javascript, and this wasn't obvious to me.  Here's an example I used, and it may be helpful for others in the future:

Button:
Tutorial
Event Code
document.querySelector("#tutorial").addEventListener('click',
  function(e){
    const driver = new Driver();

    driver.highlight({
    element: '#title',
    popover: {
      title: 'Title for the Popover',
      description: 'Description for it',
      }
    });
    e.stopPropagation();

  })

Hope this helps someone else.

@lavafactory you need to put e.stopPropagation() at the top of the event body
document.querySelector("#tutorial").addEventListener('click', function(e){
    e.stopPropagation();

    const driver = new Driver();

    driver.highlight({
        element: '#title',
        popover: {
          title: 'Title for the Popover',
          description: 'Description for it',
        }
     });
  })


Helm Grafana dashboards: add daemonset dashboard

By copying from StatefulSet dashboard.

Thanks, I'll have a look there then.


"Pulsing" page properties & paste buffer in Chrome

Like the product alot but there is a funny issue with it affecting my paste buffer. The available page properties pulse (zoom in zoom out)
I often cannot use my normal copy/paste function when the extension is engaged. The page buffer/clipbord won't clear with my latest copy to clipboard data

Thanks for the report. Can you provide some details about your set up? OS type (eg: Windows 10 / Mac OS X 10.11.6 / Ubuntu 14.04 / etc.) and Chrome version (eg: 51.0.2704.103 (64-bit)).
There are some people having an issue with the extension on Windows 10 where it copies even without the Alt key being pressed. Curious if you are having that too.

Windows 7. Will have to get back to you with Chrome extension.
Perhaps what I will do is just record screen capture vid to better illustrate


Fix demo component name generation

Resolves: https://github.com/josemarluedke/docfy/issues/105

@josemarluedke I think I fixed the error

ok, now I did it. no more laziness. lol

Released in v0.4.5.


Outputs for subnets and route tables are not well suited for use with for_each

Is your request related to a new offering from AWS?
No
Is your request related to a problem? Please describe.
The various subnet/route_table outputs are purely lists of IDs, which are not knowable until after the apply has run.  This results in them being poorly suited for use in a resource that makes use of the for_each functionality (the key should be something that is computable before the apply, the values can be unknown until after apply).  This results in errors such as the following if you attempt to do a for_each using, for example, one of the subnet arn outputs.
Error: Invalid for_each argument

  on modules/workload_vpc/subnet_share.tf line 112, in resource "aws_ram_resource_association" "database_subnets":
 112:   for_each = toset(module.vpc.database_subnet_arns)

The "for_each" value depends on resource attributes that cannot be determined
until apply, so Terraform cannot predict how many instances will be created.
To work around this, use the -target argument to first apply only the
resources that the for_each depends on.

Describe the solution you'd like.
The module should output a proper map for the elements where the key is something that is computable before the apply (I would recommend either the CIDR block or the value of the Name tag for naming the subnet keys and the value of the Name tag for the route table
Describe alternatives you've considered.
Currently I am having to do a two-stage apply where first I apply just this VPC module and then after that I can pull data sources based on the existing subnet ids and subnet arns resources to then iterate over in a resource using a for_each loop
Additional context
I am more than happy to write the PR for this change as I have already tested it locally and it's pretty simple to accomplish.  Stand by for an incoming PR.

Thanks for opening this one.
I am not completely sure when we will be able to finish a conversion from list to map but it is certainly on our radar.
#403 is an umbrella issue, so I will close this one.

@antonbabenko That issue is not the same as what I have reported here.  That issue is relating to how the module internally manages subnets by using counts rather than for_each.  This issue is about the outputs from this module not being properly suited for other code too reference the data coming from this module in a separate (not inside this module) for_each.
I would appreciate this issue being re-opened as it is not the same as #403

@antonbabenko I have submitted PR#629 to fix this issue


how sort by shop_level in (aggregation :shop_ids do)

def query_definition(text, conditions)
      search do
        query do
          bool do
            if text.present?
              must do
                multi_match do
                  query text
                  fields [
                    'product_name^2'
                  ]
                end
              end
            end

            must do
              term product_online: true
            end

            if conditions[:product_region]
              must { term product_region: conditions[:product_region] }
            end

            if conditions[:product_type]
              must { terms product_type: conditions[:product_type] }
            end

            must { term product_shop_id: conditions[:shop_id] } if conditions[:shop_id]

            must do
              range 'product_variants.price' do
                gte conditions[:price_gteq] || 0

                lte conditions[:price_lteq] if conditions[:price_lteq]
              end
            end

            if conditions[:intra_domain_id]
              must do
                term 'product_intra_domains.id' => conditions[:intra_domain_id]
              end
            end

            if conditions[:taxon_id]
              must do
                term 'product_golbal_taxons.id' => conditions[:taxon_id]
              end
            end
          end
        end

        sort do
          by :shop_level, order: 'desc'
          by :_score
          by :flagship_product, order: 'desc'
        end

        aggregation :shop_ids do
          terms do
            field 'product_shop_id'
          end
        end
      end
    end

Hi @Thomastar
Have you been able to resolve this or do you still need assistance?

Hi @Thomastar
I'm going to close this issue but feel free to open another one if you are still having trouble. Thanks!


Add some introduce on pretrain and sft data

Opensource community would be benefit from it.

We expect to release all details in the following days. Meanwhile, please refer to our paper for more information. https://arxiv.org/abs/2402.14289

We have updated our README on data preparation

@baichuanzhou  thanks, Do u think there any good data to enhance OCR ability? Currently I found the OCR ability especially Chinese are very weak.

@lucasjinreal Emmm, I think increasing data and increasing resolutions are both important to improve OCR abilities. As for training data, maybe look at ChartQA, DVQA, etc? Anyway, further exploration in this area is needed.

@baichuanzhou  How to enlarge the vit input size? since if make the size changed, the weights should not properly work


Eliminating the appearance of zombie processes when server gets stuck

When testing the client and server at FMI without the --non-interactive flag the server got stuck as the sudo command stayed hanging while waiting for a response due to its interactive mode. ultimately this led to time-out errors of the type Not sending due to non-ready zmq pipe, timeout: 1048576 ms . After trying to stop the server process with ctrl-c there was not a clean end to the process and htop ended up showing a couple of zombie processes.
Since for the particular example we already know the reason for this problem in the first place this one should not be an issue anymore. Still, I wonder whether there is a way to be sure that when the process terminates it is correctly collected by the parent process and to avoid zombie creation.
Has anyone seen this behavior of the server processes as well? Is there any straightforward practice that we could add to the current code to avoid the zombie processes in case the server runs into such a state?

These days experiments with @jluethi suggest that the most likely behavior is correct (no zombie process).
I'm closing this, let's re-open if this error comes up again.


percona-server_8_0: 8.0.37-29 -> 8.0.39-30, percona-server: 8.4.0-1 -> 8.4.2-2

Changes:
https://docs.percona.com/percona-server/8.4/release-notes/8.4.2-2.html
https://docs.percona.com/percona-server/8.4/release-notes/8.4.1.html
https://docs.percona.com/percona-server/8.0/release-notes/8.0.39-30.html
https://docs.percona.com/percona-server/8.0/release-notes/8.0.38.html
Fixes:

CVE-2024-21171
CVE-2024-21177
CVE-2024-21163
CVE-2024-21173
CVE-2024-21179
CVE-2024-21127
CVE-2024-21129
CVE-2024-21125
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Add a :+1: reaction to pull requests you find important.

OOf, the tests don't even evaluate because of e14483d6a67399485876ab51c9726dbd2eb0836a (well, before the merging was flat out broken).
Preparing a quickfix. If the tests are green, I'll merge after that.


Command CompileAssetCatalog failed with a nonzero exit code

When trying to run the project I get this error....

There is something up with the project file. If you simply delete the App Icon text in the SS (already removed it), then it will build.

Actually, if we are going to support iOS we'd need to update the icon file for iOS instead of removing the icon. Let me open a PR for that.


Fix verbose mode with progress bar

When in verbose mode the logger screws up the progress bar.

The prograss bar can be hidden in verbose mode. Verbose mode is for debugging and logging when running headles...


Select AWS App without prompt if only one choice exists and display selection to user

Closing this. See comment from 9/3.


Implement Geocoding

We'd like to implement mapping on the following models:

[ ] DonationSite
[ ] DiaperDriveParticipant
[ ] StorageLocation
[ ] Organization

We'll also need mapping on Partner Agencies but it makes sense to let the diaper partner app be the source of truth for that data.
It looks like the Geocoder Gem is the way to go. I've marked this as Beginner Friendly as there is a Drifting Ruby Screencast and a Railscast that walks through this whole process.
Geocoder allows the embedding of information in the map points when clicked on. It would be cool if  we took advantage of that -- i.e - list the total number of diaper drives that a participant has held or the number of donations at a given donation site.

Hey Kevin! It's yours, I'm removing the help wanted tag!

Hi Sean,
Watched and coded along to the railscast just now.  Do you just want me to add latitude and longitude coordinates upon creating donation site, diaper drive participant, or storage location?
Or do you want me to take it a step further and implement google maps api to the show and index pages?
Also, (sorry, just a curious Rails learner) I understand that after_validation method will kick in (see code snippet below) if the address gets created/updated, so will the existing diaper bases in the database not get geocoded due to the if statement? Would turning the if statement off just the first time geocode our existing database?
class Location < ApplicationRecord
  geocoded_by :address
  after_validation :geocode, :if => :address_changed?
end

Hey Kevin,
I made an update (to add organizations).
If you could implement a maps that would be awesome but if you feel it is beyond you, do what you can!  We don't need a map page (yet) for Organizations just the other models. I think it would probably makes the most sense to have the maps on their page rather than on the index or show page.
I think you are correct about the after_validation not geocoding the current items in the database but we can always just jump into a console and do it by hand. It shouldn't be too much of an issue at this point as we only have 5 diaper banks using the app while it is in beta.
Let me know if you have any questions or run into any problems! There are generally a bunch of us active in our slack in the #diaper channel. You can grab an invite to our slack at https://rubyforgood.herokuapp.com !

Sounds good! Joined the slack channel.  One step at a time!

Thanks, @kevinYCKim33 !

I can take a crack at this one! I use the geocoder gem a lot at work, and the latest upgrade made some weird changes to tests, so I have some theories.

Hi!! I'm adding tests. Do we think that addresses should be the kind of thing that would be required for a valid record in any of these models? (Am I supposed to ask this sort of thing here or on slack?)


Enabling scores causes the prompt to move if the line is too long

Example command: echo $(find . | fzy -s)
If you run the above and one of the matches exceeds the length of the line then the prompt moves further down the terminal.
In normal operation (i.e. without -s) the line length is clipped to the columns on the display. When matches are enabled it seems that the extra space required to show scores was not factored into the line clipping algorithm.
Tested on MacOS 10.12.4, zsh 5.3.1 and fzy 0.9

I believe this is fixed by #54. :tada:
Feel free to re-file if it is not

Yup, that appears to have to done it. Thanks @neuschaefer (and @jhawthorn for the tool in the first place ;) )!


HDDS-1235. BaseHttpServer NPE is HTTP policy is HTTPS_ONLY. Contribut…

…ed by Xiaoyu Yao.

:broken_heart: -1 overall

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+1 pending jenkins


Deserialize doesn't follow IPLD specification (decode NULL type)

Hey there,
I ran into a problem using this with IPLD maps that contain a null field. Here's a test:
use ipld_core::codec::Codec;
use libipld::ipld;
use serde_ipld_dagjson::codec::DagJsonCodec;

#[test]
fn test_roundtrip_null(){
    let test = ipld!({
      "test": null
    });
    let s = DagJsonCodec::encode_to_vec(&test).unwrap();
    let decoded: Ipld = DagJsonCodec::decode_from_slice(&s).unwrap();
    assert_eq!(test, decoded);
}

Here's what the result is:

called Result::unwrap() on an Err value: Decode(Message("invalid type: null, expected any valid IPLD kind at line 1 column 12"))

Thanks for the test case. If I add the test to tests/codec.rs (it already has all the imports) it passes for me. If you can push some branch somewhere which reproduces that issue, then I could have a look.

Aha. The key is that I'm using the Ipld struct in libipld rather than ipld_core.
If you try it with:
use libipld::{ipld, Ipld};
...

...it should fail.
I'm not sure why that would be... and I'm also a bit confused as to why there are two different crates for this. Is there one I should be using over the other?

Is there one I should be using over the other?

Yes, ipld-core should be used now. libipld will be deprecated soon. My plan is to get in touch with folks using libipld and help with migration, before it's actually deprecated.

ah. Ok thanks for the clarification. Maybe the teams could add a note in the readme about this for newcomers.
I'll close this issue. Thanks!


Update backup-azure-backup-import-export.md

Hi @nkolli1, I'm your friendly neighborhood Azure Pull Request Bot (You can call me AZPRBOT). Thanks for your contribution!

It looks like you're working at Microsoft (nkolli). If you're full-time, we DON'T require a contribution license agreement.

If you are a vendor, DO please sign the electronic contribution license agreement. It will take 2 minutes and there's no faxing! https://cla.azure.com.

TTYL, AZPRBOT;

@nkolli1 Neela, per our conversation, this PR needs to be closed.


CopyNet specific decoder

Really like the project, and I see that the CopyNet implementation was recently pushed to AllenNLP as well. However, I was unable to find documentation on producing actual decoded results.
I wanted to know if there is plans for a copynet specific beam-decoder, or if the simple_seq2seq decoder/predictor class is sufficient to produce results.
I have not looked at the underlying implementation, but would the COPY token be handled by simple_seq2seq?

https://github.com/epwalsh/nlp-models/blob/217e408645eb10606f3e27704875e6e8c872a2f6/nlpete/predictors/copynet.py#L20-L21
Found this that indicates the seq2seq predictor is the preferred way of decoding copynet predictions.


Content preview and compressed stream

When sending or receiving a compressed stream, RequestLog.contentPreview() will preview the compressed content, which is not very human friendly.
It would be nice if we can push the uncompressed content preview to RequestLog, with low overhead. Currently, a user can write a content previewer that performs decompression, but it means the content will be decompressed twice, once for previewing and once for actual content decoding.

I also need this exactly. Currently, I implemented a simple content previewer that is naive approach using ContentPreviewerFactory to decompress the gzipped body stream. But this codes have been running in debug mode only due to performance problem as you're already said.

@anuraaga Any thoughts on this? I can't think of a way to handle this nicely..

@trustin I guess instead of being called in-band by RequestLog, the functionality can be moved to a decorator? Then a user gets to decide too whether they want to preview the encoded or decoded content. I think the main APIs are already there, RequestContext.logBuilder().requestContentPreview(String) so just need to move the logic to a decorator. It's similar to the decorator linked in #1997 except that used aggregate for ease of implementation, while it's not that much worse to use a normal subscription.

@trustin Probably good to target this for 1.0.0

Yeah, I wonder how it will impact our current service binding builder API. It would result in a surprise if a user specifies previewers there and forgets to add a previewing decorator. Any idea for preventing this? Just checking with as() ?


[Usage]: How to expand inference context length to longer (such as 128k, 256k) on multi modality models.

Your current environment

environment
torch: 2.5.0
vllm: 0.6.3.post2.dev171+g890ca360

problem
Now I have several A100 and a Qwen2-VL-7B model, I'm trying expanding this model during inference time to 128k, but cause oom.

I have tried:

https://github.com/vllm-project/vllm/issues/10537 Set max_num_seqs = 1 or 2, cause oom again.
https://github.com/vllm-project/vllm/issues/10474 Set tensor_parallel_size=2, find the same issue, which have't solved yet.
https://github.com/vllm-project/vllm/issues/5496 Set enable_chunked_prefill=True, max_num_batched_tokens=8192, cause oom again.

How would you like to use vllm
I want to run inference of Qwen2-VL-7B on longer context(exceed 128k) based on my current working environment(several A100 80G).
Before submitting a new issue...

[X] Make sure you already searched for relevant issues, and asked the chatbot living at the bottom right corner of the documentation page, which can answer lots of frequently asked questions.

Setting tensor_parallel_size is probably the way to go. Can you show your code?

Setting tensor_parallel_size is probably the way to go. Can you show your code?

@DarkLight1337 Thanks for your timely reply, the script is below.
context_length = 128000
llm = LLM("/mnt/hwfile/mllm/weixilin/cache/Qwen2-VL-7B-Instruct",
            max_model_len=context_length,
            limit_mm_per_prompt={"video": 10},
            tensor_parallel_size=2
            )

Did you call any CUDA-related functions before initializing vLLM? You should remove those calls if possible.

from transformers import Qwen2VLForConditionalGeneration, AutoTokenizer, AutoProcessor
from qwen_vl_utils import process_vision_info
from PIL import Image
import requests
import torch
from torchvision import io
from typing import Dict
from transformers import Qwen2VLForConditionalGeneration, AutoTokenizer, AutoProcessor
from vllm import LLM, SamplingParams
import tempfile
from petrel_client.client import Client
import copy
from torchvision.transforms.functional import to_pil_image
from torchvision import io, transforms
from torchvision.transforms import InterpolationMode
from transformers import AutoConfig

client = Client()
sampling_params = SamplingParams(
    best_of=1,
    temperature=0.0,
    top_p=1,
    top_k=-1,
    max_tokens=128,
    presence_penalty=0,
    frequency_penalty=0,
)

context_length = 128000

llm = LLM("/mnt/hwfile/mllm/weixilin/cache/Qwen2-VL-7B-Instruct",
            max_model_len=context_length,
            limit_mm_per_prompt={"video": 10},
            tensor_parallel_size=2
            )

There is no cuda related call, seems problem not here

Did you call any CUDA-related functions before initializing vLLM? You should remove those calls if possible.

from transformers import Qwen2VLForConditionalGeneration, AutoTokenizer, AutoProcessor
from qwen_vl_utils import process_vision_info
from PIL import Image
import requests
import torch
from torchvision import io
from typing import Dict
from transformers import Qwen2VLForConditionalGeneration, AutoTokenizer, AutoProcessor
from vllm import LLM, SamplingParams
import tempfile
from petrel_client.client import Client
import copy
from torchvision.transforms.functional import to_pil_image
from torchvision import io, transforms
from torchvision.transforms import InterpolationMode
from transformers import AutoConfig

client = Client()
sampling_params = SamplingParams(
    best_of=1,
    temperature=0.0,
    top_p=1,
    top_k=-1,
    max_tokens=128,
    presence_penalty=0,
    frequency_penalty=0,
)

context_length = 128000

llm = LLM("/mnt/hwfile/mllm/weixilin/cache/Qwen2-VL-7B-Instruct",
            max_model_len=context_length,
            limit_mm_per_prompt={"video": 10},
            tensor_parallel_size=2
            )

There is no cuda related call, seems problem not here

Hmm, can you wrap your code under an if __name__ == "__main__" guard? Perhaps multiprocessing is messing this up.

I try but nothing has changed

Hmm, can you wrap your code under an if __name__ == "__main__" guard? Perhaps multiprocessing is messing this up.

@youkaichao any idea about this?

What's the error message? We need the full log and environment to know what's happening.

The problem had been resolved, thanks.
youkaichao @.***> 于2024年12月20日周五 17:01写道：

What's the error message? We need the full log and environment to know
what's happening.
—
Reply to this email directly, view it on GitHub
https://github.com/vllm-project/vllm/issues/11337#issuecomment-2556563050,
or unsubscribe
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@.***>

For future reference, how did you solve it?

For future reference, how did you solve it?

I registered the model as API servers instead of passing these parameters.

But  I've encountered a new issue. When registering as an API server and sending a video, it results in an
openai.BadRequestError: Error code: 400 - {'object': 'error', 'message': 'Unknown part type: video_url', 'type': 'BadRequestError', 'param': None, 'code': 400}."

I only found the same question at https://github.com/QwenLM/Qwen2-VL/issues/539. however no solution right now.

When registering as an API server

What do you mean exactly by that?

When registering as an API server

What do you mean exactly by that?

ref: https://docs.vllm.ai/en/latest/serving/openai_compatible_server.html#vllm-serve

"""
vllm serve /mnt/hwfile/mllm/weixilin/cache/Qwen2-VL-7B-Instruct --trust-remote-code --tensor-parallel-size=2 --pipeline-parallel-size=1 --served-model-name=qwen2-vl-test --enable-prefix-caching --host <IP_ADDRESS>
"""
import base64
import requests
import time
from tqdm import tqdm
from PIL import Image
from qwen_vl_utils import process_vision_info
from io import BytesIO
import numpy as np
# Function to encode the image
def encode_image(image_path):
  with open(image_path, "rb") as image_file:
    return base64.b64encode(image_file.read()).decode('utf-8')

from openai import OpenAI
client = OpenAI(
    api_key="EMPTY",
    base_url="http://<IP_ADDRESS>:8000/v1/",
)
messages = [
        {"role": "system", "content": "You are a helpful assistant."},
        {
            "role": "user",
            "content": [
                {
                    "type": "video",
                    "video": "/mnt/hwfile/mllm/zhangpan/share/from/xiaoyi/MLVU/video/6_anomaly_reco/surveil_176.mp4",
                    "min_pixels": 144*28*28,
                    # "max_pixels": 1280 * 28 * 28,
                    "total_pixels":<PHONE_NUMBER>) * 28 * 28,
                    # "nframes": 3,
                    # "total_pixels": 64 * 28 * 28,
                },
                {"type": "text", "text": "Describe the video."},
            ],
        },
    ]
image_inputs, video_inputs = process_vision_info(messages)

model = 'qwen2-vl-test'
video_prompt_pair = [
    ("/mnt/petrelfs/weixilin/projects/MLLM/Qwen2-VL/assets/vis.mp4", "请详细介绍一下这个视频中的内容"),
    ("/mnt/petrelfs/weixilin/projects/MLLM/Qwen2-VL/assets/vis.mp4", "请问视频中人物的性别，以及他在做什么？"),
]
def encode_image_base64(
    image: Image.Image,
    *,
    image_mode: str = "RGB",
    format: str = "JPEG",
) -> str:
    """
    Encode a pillow image to base64 format.

    By default, the image is converted into RGB format before being encoded.
    """
    buffered = BytesIO()
    image = image.convert(image_mode)
    image.save(buffered, format)
    return base64.b64encode(buffered.getvalue()).decode('utf-8')
def encode_video_base64(frames):
    """
    Encode a list of frames (tensors) into a single base64 string.
    """
    base64_frames = []
    frames = frames[0]
    import pdb; pdb.set_trace()
    for frame in frames:
        # Convert tensor to numpy array (if it's not already)
        if not isinstance(frame, np.ndarray):
            frame = frame.numpy()  # Assuming the tensor is a PyTorch tensor

        if frame.shape[0] == 3:  # Shape is (3, H, W)
            frame = np.transpose(frame, (1, 2, 0))

        if frame.dtype != np.uint8:
            # Normalize and convert to uint8
            frame = (frame * 255).clip(0, 255).astype(np.uint8)
        # Encode the frame as base64
        img_base64 = encode_image_base64(Image.fromarray(frame))
        base64_frames.append(img_base64)
    return ",".join(base64_frames)

def encode_image_from_path(image_path):
  with open(image_path, "rb") as image_file:
    return base64.b64encode(image_file.read()).decode('utf-8')
image_path = "/mnt/petrelfs/weixilin/projects/MLLM/Qwen2-VL/assets/images/input_ids_length_distribution_330k.png"
for video_url, prompt in video_prompt_pair:
    chat_completion_from_url = client.chat.completions.create(
        messages=[{
            "role": "user",
            "content": [
                # {
                #     "type": "text",
                #     "text": prompt
                # },
                # {
                {"type": "video_url",
                "video_url": {
                    "url": f"data:video/jpeg;base64,{encode_video_base64(video_inputs)}"
                }
                }
                # {"type": "image_url", "image_url": f"data:image/gif;base64,{encode_image_from_path(image_path)}"
            ],
        }],
        model=model,
        max_tokens=1024,
    )
    result = chat_completion_from_url.choices[0].message.content
    print(f"For video: {video_url}")
    print(f"Prompt: {prompt}")
    print(f"Response: {result}")
    print()

Now the code can only output text response, if pass video_url will cause openai.BadRequestError: Error code: 400 - {'object': 'error', 'message': 'Unknown part type: video_url', 'type': 'BadRequestError', 'param': None, 'code': 400}

Can you try to use curl command or requests library to send the request instead? Maybe OpenAI Python client is too strict with type checking.


Epic Service Fields - Onboard a new or update triage for product

Link to spreadsheet with details, look in the Onboard-dataMissing tab - https://microsoft-my.sharepoint.com/:x:/p/ladonnaquinn/ETD9YCt4cfxHlL4mC1KlVygBIQss1mm6NMIpu3_BdOJhJQ?e=6VqO7v

[ ] State Field needs to be updated when onboarding and regularly synced so that the state always matches what is in service tree.  The state should be the current lifecycle stage not the target lifecycle stage.  The target is next which is what the team is working on right now for the next lifecycle milestone. For example, teams working on the target lifecycle of Private Preview, have a current lifecycle of In Dev.
[ ] Service Onboard Date Field in the epic service needs to be updated when onboarded the first time and this field value does not change. This is to make it easier for us to provide requested metrics (i.e. how many new services are coming in over time?, etc).
[ ] isServiceNew Field should be updated during onboarding. This field will also need to be updated after GA API readiness is completed and the stable API version is merged. At this time, the SDK team will consider it an existing service as the target for TypeSpec migration is no stable API is published yet.
[ ] All existing epic-service type need to have the state changed. I have manually updated based on the state of the onboard work items and lifecycle fields for service and product in the work item. This is out of sync though with service tree. We need to correct this because it is important to understanding new services vs existing services and tracking teams that need to migrate to TypeSpec.

This field should be synched on a regular basis so that our information is current with what is in service tree.

Do you mean that there should be a back-end process that is constantly updating this information for a Service/Product ?
What should be the frequency?

Service Onboard Date (New Field) - If the epic type service is found during onboarding, then skip adding a date to this field. If no epic service exist, then the date of onboarding is the date to use for service onboard date.

Only add this date if the automation creates the Service and/or Product work item. Don't modify when the service/Product onboards again ?

Service Onboard Date Field

Field added in the Epic template

More questions:

Onboard date: should the value only be added if the Release planner created the Service epic? or should the value be added if the Onboard date field is empty? (the later will cover cases where the service already has a record with us, but they recently onboarded with us.
isServiceNew : should this be updated when any of the products inside the service reached GA for API readiness? or only when all products?

Update: These questions have been answered and are included as part of the description of the issue
@ladonnaq

This field should be synched on a regular basis so that our information is current with what is in service tree.

Do you mean that there should be a back-end process that is constantly updating this information for a Service/Product ? What should be the frequency?  There are data values that are populated by the release planner during onboarding that are critical to the accuracy of our data, especially in identifying, engaging, and tracking service teams that need to adopt TypeSpec.
I have created a tab in the spreadsheet for this data - https://microsoft-my.sharepoint.com/:x:/p/ladonnaquinn/ETD9YCt4cfxHlL4mC1KlVygBIQss1mm6NMIpu3_BdOJhJQ?e=AkLeMo&nav=MTVfe0ExRjNGN0Y5LTY0NjItNEMwRS1CRjM3LTI1QTcwRjhCNkY0Q30.  I will create a GitHub issue and link to the tab so that there is clarity into all of the fields that must be synced on a regular scheduled basis.  Right now I have some onboarding data values in the tab that I need to remove. Also, some fields that are duplicated which I want to eliminate (so that only updating field in the work item that represents the official record on our side). Once I do that, will open the GitHub issue.  Since this data can change at any time, it would be good to run a scheduled job that updates daily at minimum.

Service Onboard Date (New Field) - If the epic type service is found during onboarding, then skip adding a date to this field. If no epic service exist, then the date of onboarding is the date to use for service onboard date.  That is correct.  As I mentioned in another issue. I am sorting out to manually get this date and update it for all of the existing services.

Only add this date if the automation creates the Service and/or Product work item. Don't modify when the service/Product onboards again ?  That is correct. The onboard date fields are a "time stamp" so we can provide the metrics we are continually being asked to provide in regards to "how many product and/or services are we onboarding in a specific time period".  Previously we were using the onboard creation date but that only is the product onboard date.  The service may have other products that have GA'd so we can't rely on the product onboard date to be the same as the service onboard date.

Conclusion for Eng team:

State field should be the value for service current lifecycle stage in service Tree
Onboard date: add value when service work item doesn't exist
isServiceNew: TBD

@praveenkuttappan issue updated for isServiceNew.
More context from @ladonnaq :
We should keep isServiceNew field. If it is true we know we need to engage. Then we would next look at the ReleasedSDK field for product and RelatedSDK field (the one that we can change to be true or false when they onboard and select box indicating existing SDKs enable the product). This way we will catch everything in scope.
So is the service is not new, then we have to look at the product fields.
Not every product will result in a new initial beta SDK but some will so understanding which will helps us to identify TypeSpec candidates. New services who are in scope for our APEX requirements will always be in scope. So we can't rely alone on the lifecycle of the service or the isServiceNew field alone. We can discuss if you like. In the end if the team is working on an initial preview API soec that will result in a initial beta SDK, they are in scope. 😀


fix(select): selected item is not showing for ios/ipados

Related Ticket(s)
Closes #10052
Jira ticket
Description
Fix for Labeles not appearing on Safari / IOS
Changelog
Changed

How labels on the select component are handled

Verified on iOS safari, Firefox, macOS safari

New PR Targeting the main branch
https://github.com/carbon-design-system/carbon-for-ibm-dotcom/pull/11214


Bumped version number to 3.7.0

@dtaylor113 @jeff-phillips-18 and/or @bleathem please review.

I'm not yet familiar enough with angular-patternfly to review this PR, I'll defer.

LGTM

LGTM, so nice not seeing the dist files :-) !


The use of exclude_path in in_tail plugin？

Official documents are as follows:
http://docs.fluentd.org/articles/in_tail
##########################
exclude_path
The paths to exclude the files from watcher list. For example, if you want to remove compressed files, you can use following pattern.
path /path/to/*
exclude_path ["/path/to/.gz", "/path/to/.zip"]
###########################
my config
############################
path /home/work/logs/nginx/*.log
exclude_path ["/home/work/logs/nginx/my.xxx.com.log","/home/work/logs/nginx/me.xxx.com.log"]
############################
But after this, I collected the log data id not rule out me.xxx.com.log and my.xxx.com.log. Why?
Is path_exclude only for file types? Or my configuration where there is a problem, please help me

It works for me. Could you paste entire logs here?
% RUBYLIB=~/dev/fluentd/fluentd/lib fluentd -c fluent.conf
2015-10-13 19:33:50 +0900 [info]: reading config file path="fluent.conf"
2015-10-13 19:33:50 +0900 [info]: starting fluentd-0.12.16
2015-10-13 19:33:50 +0900 [info]: gem 'fluent-mixin-config-placeholders' version '0.3.0'
2015-10-13 19:33:50 +0900 [info]: gem 'fluent-plugin-elasticsearch' version '1.0.0'
2015-10-13 19:33:50 +0900 [info]: gem 'fluent-plugin-s3' version '0.6.0.pre1'
2015-10-13 19:33:50 +0900 [info]: gem 'fluent-plugin-s3' version '0.5.11'
2015-10-13 19:33:50 +0900 [info]: gem 'fluent-plugin-s3' version '0.5.10'
2015-10-13 19:33:50 +0900 [info]: gem 'fluent-plugin-secure-forward' version '0.3.2'
2015-10-13 19:33:50 +0900 [info]: gem 'fluent-plugin-td' version '0.10.27'
2015-10-13 19:33:50 +0900 [info]: gem 'fluent-plugin-td-monitoring' version '0.2.0'
2015-10-13 19:33:50 +0900 [info]: gem 'fluentd' version '0.12.12'
2015-10-13 19:33:50 +0900 [info]: adding match pattern="tail.**" type="stdout"
2015-10-13 19:33:50 +0900 [info]: adding source type="tail"
2015-10-13 19:33:50 +0900 [warn]: 'pos_file PATH' parameter is not set to a 'tail' source.
2015-10-13 19:33:50 +0900 [warn]: this parameter is highly recommended to save the position to resume tailing.
2015-10-13 19:33:50 +0900 [info]: using configuration file: <ROOT>
  <source>
    type tail
    path /Users/repeatedly/tmp/fluentd/issue681/*.log
    exclude_path ["/Users/repeatedly/tmp/fluentd/issue681/foo.bar.log","/Users/repeatedly/tmp/fluentd/issue681/foo.baz.log"]
    refresh_interval 10s
    format none
    tag tail.test
  </source>
  <match tail.**>
    type stdout
  </match>
</ROOT>
2015-10-13 19:33:50 +0900 [info]: following tail of /Users/repeatedly/tmp/fluentd/issue681/bar.log
2015-10-13 19:33:50 +0900 [info]: following tail of /Users/repeatedly/tmp/fluentd/issue681/baz.log
2015-10-13 19:33:50 +0900 [info]: following tail of /Users/repeatedly/tmp/fluentd/issue681/foo.log
^C2015-10-13 19:34:02 +0900 [info]: shutting down fluentd
2015-10-13 19:34:03 +0900 [info]: process finished code=0
$ /Users/repeatedly/tmp/fluentd/issue681% ls
bar.log      baz.log      fluent.conf  foo.bar.log  foo.baz.log  foo.log

thanks ,
I solved it, it turned out to be my td-agent version is not supported, and the upgrade was restored. Fluentd-0.10.61 from the source code, is not supported by exclude_path
####################
2015-10-13 21:38:36 +0800 [warn]: parameter 'exclude_path' in
type tail
path /home/work/logs/tmp/*.log
exclude_path ["/home/work/logs/tmp/foo.bar.log","/home/work/logs/tmp/foo.baz.log"]
refresh_interval 10s
format none
tag tail.test
 is not used.
2015-10-13 21:38:36 +0800 [info]: following tail of /home/work/logs/tmp/foo.bar.log
2015-10-13 21:38:36 +0800 [info]: following tail of /home/work/logs/tmp/foo.baz.log
2015-10-13 21:38:36 +0800 [info]: following tail of /home/work/logs/tmp/baz.log
2015-10-13 21:38:36 +0800 [info]: following tail of /home/work/logs/tmp/bar.log
2015-10-13 21:38:36 +0800 [info]: following tail of /home/work/logs/tmp/foo.log
2015-10-13 21:42:16 +0800 [info]: reading config file path="/etc/td-agent/td-agent.conf"
2015-10-13 21:42:16 +0800 [info]: starting fluentd-0.10.61
#####################################


The test function_call_current_date fails when you run it after midnight.

As it says in the title. I ran tests at a few minutes past midnight and it fails, if I rewind my system clock back an hour and rerun the test passes.
Guessing its something to do with timezones or daylight savings.
EDIT: would have been helpful to mention I live in Ireland. 😅

This test is gone, but looking at the function it appears to be working correctly anyway.


Option to persist the nativeEvent

Together with a wheel operation, I need to retrieve the current pointer position relative to the element listening to the events. The aim is to implement a contextual wheeled zoom, centered at the pointer position (such as Google Maps, for instance).
My current attempt is with a combined subscription of Move and Wheel gestures, as follows:
const moveRef = React.useRef<number>(0);

const bindWheel = useGesture({
    onMove: st => {
        const { nativeEvent } = st.event;
        if (nativeEvent) {
            const { offsetX, offsetY } = nativeEvent as MouseEvent;
            moveRef.current = dir === Horizontal
                ? offsetX
                : offsetY;
            //console.log("move", moveRef.current)
        }
    },
    onWheel: st => {
        if (onChange && isValidRange(props.lrange)) {
            const factor = st.movement[1] < 0
                ? scaleDown
                : scaleUp;

            // ...
        }
    }
}, { enabled: actualEnabled, }
)

Now, the pointer location is offered as offsetX, offsetY by the native event, but to access these properties having a SyntheticEvent, I must leverage the nativeEvent property.
The problem is that the event should be persisted before the user handler, but that seems not possible.
By digging into your code, I've seen that persisting at the very first level seems working, although I personally don't like this patch:
  onMove = (event: UseGestureEvent): void => {
      if (!this.moveShouldRun()) return
      event.persist();  //this works!
    this.clearTimeout()
    this.setTimeout(this.onMoveEnd)

    if (!this.state._active) this.onMoveStart(event)
    else this.onMoveChange(event)
  }

I wonder if wouldn't better having an option flag able to instruct a specific handler whether to persist or not (default).

Ciao @highfield, a few things.

There's always the option to get native events by using the domTarget option and passing a ref to it.

The scroll, wheel and move events are debounced, which means that the last event passed can't be queried since it's no longer synced, as explained in the docs.

Back to the second point, have a look at https://codesandbox.io/s/blazing-glade-sfoyi. You can query the native event but just make sure you're not doing it when it's the last event.

@dbismut I used your snippet approach and it is working fine.
Many thanks!


In log it indicates is login successful but does not move the home page .Stuck in login page

Unable to proceed forward from login to home page .Registration is successful ,can see the email in firebase but when logging in the ..not able to go to next page.

same issue still persists


Learn IDE is sending exceptions to Atom

Hi, Atom maintainer here.  We're receiving uncaught exceptions from Learn IDE (see https://github.com/search?q=org%3Aatom+learn-ide&type=Issues), which I think is detrimental for the both of us, because we can't do anything about them, and you're not receiving them.  So I would suggest bundling a custom version of the Notifications package such that it reports issues here by default instead of to Atom.

🤦♂ Thanks for bringing this up! I'll copy those issues over, and we'll work on taking care of this.


chore(main): release 1.0.0

:robot: I have created a release beep boop
1.0.0 (2023-11-29)
Features

components: update snapshots (1d65b75)
EventListItem: add link and change styling for line (d27adbc)
eventListItem: add ticket link (a25882a)
eventPage: add image and add styling (ff4c97c)
eventPage: add preperation for optimising eventPage (2c397f6)
notFound: make page consistent (e6e0615)

Bug Fixes

authorFormatter: remove image from person (99314e4)
components: fix some component styling (59e7d81)
navigation: add bigger gap (8447c49)
styles: change spacing and logo size (31b96de)

This PR was generated with Release Please. See documentation.

:robot: Release is at https://github.com/crea-orkest/crea-public/releases/tag/v1.0.0 :sunflower:


Some date extensions should be class functions

Some date extensions should be class functions, there is no need to create a new nsdate() object imo.

https://github.com/erica/SwiftDates/tree/master/Sources
Some cool date stuff

@goktugyil what extensions you are talking about?

I think DateMath and DateUtils will be pretty useful. Also other extensions might give inspirations.


IE8 can't detachEvent 'ontouchend'

https://github.com/bevacqua/dragula/blob/master/dragula.js#L378
when dragula destroy in IE8, this will make error

Were the other issues fixed?

Can I see a screenshot of this issue?

error is type mismatch

this will detachEvent 'ontouchend'

sorry, it seem my error,
I have two dragula and one is init error, so this one destroy will error


drone:server:"INFO: 2018/08/17 11:26:02 transport: http2Server.HandleStreams received bogus greeting from client: "GET / HTTP/1.1\r\nHost: 19""

message: INFO: 2018/08/17 11:26:02 transport: http2Server.HandleStreams received bogus greeting from client: "GET / HTTP/1.1\r\nHost: 19"
when I visit http://my_local_ip:9000.
and curl http://my_local_ip:9000
 ➭ curl http://<IP_ADDRESS>:8000/version
{"source":"https://github.com/drone/drone","version":"0.8.6+build.1534"}
 ➭ curl http://<IP_ADDRESS>:9000
��%

But I visit  http://my_local_ip:8000 is ok.
I don't known that' why, please give me a advice for those error.
And It is strange that Before is normal.

👋 Hey there! Per our issue template, please use our community forum for end-user support.


Template Engine returning undefined when binding data with innerhtml and running enhance.

I'm submitting a bug report

Library Version:
1.0.0

Please tell us about your environment:
Windows 10
Node Version:
NA
NPM Version:
NA
JSPM OR Webpack AND Version
NA
Browser:
all
Language:
all
Current behavior:
Returning undefined after being compiled

What is the expected behavior?
Return compiled html in place

https://gist.run/?id=70aa97833c5f5f7b6f4e83adb9267a28

So.....any news on this?

We haven't had an opportunity to look into this issue yet. If you track down the cause and want to submit a PR for the fix, we always welcome that.


GituHub Actionsにテスト追加

テストのActionを追加した。
また、README.mdにバッジをつけた。

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Fixed bug with long player name

Fixed bug with long player name by adding a maximum length of 19 characters per name.
resolves #94

The formatting still breaks if you change the size of the window

I also think that limiting the characters per name is not the best solution.

this does not have the best user experience.
the number 19 might not be valid anymore, if the layout gets changed later.
is that stable when zooming in (i.e. Ctrl-+)?

A believe a better and more responsive solution should use things like max-width, wrapping or maybe text-overflow: ellipsis.

@JonathanDeul I am afraid, but after merging the other PRs, this one got conflicts. Could you have a look at it?
Also: The copybutton-PR also made changes to the create-table. Could you merge master into this branch and see whether this PR has to be adapted?

@JonathanDeul I am afraid, but after merging the other PRs, this one got conflicts. Could you have a look at it?
Also: The copybutton-PR also made changes to the create-table. Could you merge master into this branch and see whether this PR has to be adapted?

I ll have a look at it in a few minutes!

@JonathanDeul  I think the fix is great for the create table!
But for the leader board the name column is too narrow. When using the default names "Player 1", "Player 2" etc. one cannot distinguish them. Also the (you) is not visible anymore...


Nondeterministic list order in Cargo.nix

A case was discovered where cargo2nix would generate Cargo.nix output with differing list orders.  There's no expected consequence to repeatable evaluation, but it's a reasonable expectation to maintain bijection between the Cargo.lock and the Cargo.nix.
Reported by @TylerRichie

Good call! I'm still marking this issue as a bug, despite causing no harm, since producing output that's not binary reproducible seems somewhat like an oversight to me. Perhaps we should sort our list of entries by name before writing them to the Cargo.nix to keep the results consistent?

This is an annoyance- its adds significantly to diff noise

I either imagined that @trha fixed this or I wrote the changes into a driveby fix.  Cannot find a commit for this issue.
No point talking about it.  If we know what list is needing a sort, just sort it and write a PR.
What I'm also not seeing is line noise in the updates to the Cargo.nix.  Marking closed.  If anyone can find a list that's out of order, please just add the sort and write a PR :cat2:


⚠ Bofrost.de has degraded performance

In 28c9632, Bofrost.de (https://www.bofrost.de) experienced degraded performance:

HTTP code: 200
Response time: 1407 ms

Resolved: Bofrost.de performance has improved in 59b999e after 6 minutes.


Provider -> fax numbers?

Is there a list of this that is being worked on?

We have had a couple folks willing to provide what they have from NPI-based data, but I have yet to hear or see anything... Is this soemthign you're willing/able to spearhead?

@ftrotter has a good existing mockup using his existing API: http://vocatus.ft1.us/
Another suggestion he had was https://www.bloomapi.com/
Or Noga of Picnic Health  mentioned we could use her data. They basically started with the NPI list and have been making it better with each records request.

I might consider a non-NPI based approach (or not wholy rely on NPI). While
the NPI is a starting point to bootstrap such a database, you'll find the
quality is pretty low.
If no one has manually collected fax numbers (e.g. Noga + Picnic Health), I
have a number of different datasources in www.bloomapi.com that have fax
numbers and I could give a quick tool that returns the 'most accurate' fax
number from 4 different datasources.
A handful of issues with just the NPI:

Most providers don't update their listing post med-school, leading to
a highly outdated fax number
The fax number for the provider may not be the fax number for records
release. Providers frequently work at more than one location and the NPI
only describes the mailing and primary business location of the provider.
Similarly the records release number for the main system may be
different than say the radiology records release dept -- even with the same
provider

On Sun, May 31, 2015 at 3:57 PM, Rebecca Coelius<EMAIL_ADDRESS>wrote:

@ftrotter https://github.com/ftrotter has a good existing mockup using
his existing API: http://vocatus.ft1.us/
Another suggestion he had was https://www.bloomapi.com/
Or Noga of Picnic Health mentioned we could use her data. They basically
started with the NPI list and have been making it better with each records
request.
—
Reply to this email directly or view it on GitHub
https://github.com/codeforamerica/vocatus/issues/3#issuecomment-107255260
.

You could use Physician Compare to see some physicians' Group PAC ID, then someone with access to PECOS (not yet open despite standing FOIA request from August 14) could match that to the Group NPI to prioritize higher probability of accurate fax numbers. It has been our experience that groups tend to have more static/better maintained NPPES data than individual physicians.

@loranstefani Do you know anyone that's had luck getting access to PECOS beyond the PECOS Ordering/ Referring data?
You can also use the claims based CCNs + other public data using CCNs in Physician Compare and map that to NPIs through a few different techniques with relatively high matching rates if your goal is to get facility NPIs tied to providers.
There's also pretty sparse but decent fax data in the Provider of Service PUF (CCN keyed) ... but my experience has been this isn't nearly enough as frequently the fax number for a facility is not the same as the fax for records release.

Nope; my FOIA request for it is still pending and I dont know of anyone else that's requested it. Know who I should bug to get it pushed through? :D
We've matched CCN/NPI from Physician Compare/NPPES for hospital-physician affiliations, but rely on name/address fuzzy matching to build out affiliations between individuals and practices/groups. Not perfect, but may get you a more current fax number than the one listed for an individual.
Our product (billianshealthdata.com) does verify a large sample of phone numbers for larger groups/practices, but not fax numbers. I see how they're needed for this campaign, but loathe that they are even relevant in 2015 at all.

I've never successfully gotten a FOIA fulfilled faster by pushing on higher up contacts myself (may have at the State level though ;-) )
I've been toying with writing a crawler for fax information -- today I manually lookup fax information/ records release departments to accumulate the data. I would love to connect outside of github -- I've sent you a Linkedin request if you're interested. (sorry for polluting the bug request with this!)