include plank to the benchmark

compare to plank
https://github.com/pinterest/plank/

@CavalcanteLeo FMDBHelper is simple, and support for sqlite rw.


✨(react) Datepicker position

Purpose
We have a problem on marsha and LTI with the datepicker not accessible (see conversation).
The goal is to be able to change the position of the datepicker depend of the place available in the viewport.
Proposal

[x] 🔧(packages) make scripts cross platform friendly (fix problem with windows)
[x] 🔧(react) adapt script and config to use the watch mode of vite
[x] 🚨(packages) fix eslint tsconfig root dir
[x] ✨(react) datepicker position

Extra check here, I don't think that you need nodemon to watch the project when you do yarn dev on react packages, the vite HMR seems to be activated by default when you start storybook, but maybe I misinterpreted something.


Magic bytes different in host code and documentation

The magic byte sequence in GitHub README documentation is different to that of the host Python script.
Last byte 0x72('r') is documented as 0x52('R').
In README:
MAGIC: The following 4 bytes (hex): C1 1F FE 52 ('S'+'n' 1F FE 'r')
In host side Script:
self.__sensniff_magic = struct.pack('BBBB', 0xC1, 0x1F, 0xFE, 0x72)

I've pushed a few changes so this should no longer be relevant.

Confirmed. README now matches with code.


Service Invocation not working as Expected, Error invoking method: 'XXXX' on app-id: 'uploader'

Expected Behavior
I have Two Service Processor and Uploader. Processor Service can reach out to uploader for getting any service details.
The Processor Service should be able to invoke method in Uploader Service
Actual Behavior
Getting an error after trying Multiple Routes and Scenarios. Processor Service is unable to Invoke any method in Uploader Service
An exception occurred while invoking method: 'uploads' on app-id: 'uploader'
Steps to Reproduce the Problem
Enable Dapr:
dapr init

The Uploader Service has an endpoint http://<host>:<port>/uploads
 [ApiController]
 [Route("[controller]")]
 public class UploadsController : ControllerBase
 {
    [HttpGet]
    public async Task<IActionResult> GetAll()
    {
        var response = await _storageService.GetAllVideos(new Services.Models.GetAllVideosRequestModel(){
          BucketName = "*****",
          BucketFolder ="****"
        });
        return Ok(response);
     }
  }

// output
{
    "videos": [
        {
            "lastModified": "2022-10-09T00:03:17+05:30",
            "size": 3288367,
            "key": "files/4303ckbt.cil.mp4"
        },
        {
            "lastModified": "2022-10-08T22:11:26+05:30",
            "size": 3288367,
            "key": "filesubpmk1a3.hwd.mp4"
        }
    ]
}

Also, Note, calling directly through postman the dapr endpoint do return the response. It's only the App not able to call

The code for Processor Service to invoke the uploader service which gives an error:
 try
 {
   CancellationTokenSource source = new CancellationTokenSource();
   var videos = await _daprClient.InvokeMethodAsync<UploadApiVideoModel>(HttpMethod.Get,"uploader", "uploads", source.Token);
   _logger.LogInformation("Video" + videos.Videos[0].Key);

 }
 catch (System.Exception ex)
 {
    _logger.LogInformation(" Calling Error " + ex.Message);
  }

Now for running it locally:
Uploader Service
dapr run --app-port 2000 --app-id uploader --app-protocol http --dapr-http-port 2500 --components-path ../../dapr/components -- dotnet run

Processor Service
dapr run --app-port 3000 --app-id processor --app-protocol http --dapr-http-port 3500 --components-path ../../dapr/components -- dotnet run

Exception Received in Processor service

Other Details
I also tried using the CreateInvokeHttpClient Method in dapr.
var httpClient = DaprClient.CreateInvokeHttpClient("uploader");
await httpClient.PostAsJsonAsync("/uploads");

I also tried enabling mtls and then try with --app-ssl still no luck.
I also tried it running in K8s still no luck.
Few Version details
.Net Core: net6.0
Dapr on Docker
Dapr nuget Client : 1.9.0
K8 cluster using Docker Desktop
System : Windwos 11
Thanks

Do you see any indication that the uploader app is receiving a request? Or is it failing to even get there? Also, can you print the inner exception, if there is one?
How are you constructing your DaprClient? Given that you're running locally, most of that setup should just work out of the box.
I'd also takea a look at your model class. Perhaps the json deserialization is causing problems?

@iamsourabh-in did you remember to include
   services.AddControllers()
                 .AddDapr()

for Uploader project?  I believe you'd need that to invoke the methods off the controller.

No, I am not able to see any logs showing any indication for the same. Also, tried with log level=debug, uploader still shows no sign of invocation.
DaprClient Initialize in Program.cs
builder.Services.AddControllers().AddDapr();

The Model Class looks like this:
    public class UploadApiVideoModel
    {
        public List<VideoModel> Videos;
    }

    public class VideoModel
    {
        public DateTime LastModified { get; set; }
        public long Size { get; set; }
        public string Key { get; set; }

    }

// Invocation
       private readonly DaprClient _daprClient;

        public ProcessorController(
            DaprClient daprClient
        )
        {
            _daprClient = daprClient;
        }

 public async Task<IActionResult> Get([FromQuery] string key, [FromQuery] string bucketName)
        {
         var videos = await _daprClient.InvokeMethodAsync<UploadApiVideoModel>(HttpMethod.Get,"uploader", "/uploads", source.Token);
...

@iamsourabh-in - This may be a shot in the dark here, but I wonder if you have your ports backwards for your uploader app.
I noticed in the postman call that you were hitting localhost:2500/uploads. That's the direct app endpoint, not the Dapr one. In your run command, you have --app-port 2000 --dapr-http-port 2500. Is it possible those should be reversed?
If it's not that, I may need the code to debug it more. If you can't give that, the full logs you get from Dapr when you run it would be great too.

@halspang  - I might have miss understood it, but I am under an impression, this is the port which dapr side car is running,
For Uploader Service the GET /uploads endpoint can be invoke it via two ways
http://localhost:2500/v1.0/invoke/uploader/method/uploads

#OR (below was the way i used in teh screenshot above)
curl --location --request GET 'http://localhost:2500/uploads' \
--header 'dapr-app-id: uploader'

I am sharing the logs here and also sharing the repo details.
Commands to run the apps are in the read me. LEt me know if you need any more details.
 app_id=processor instance=DESKTOP-FIUUHBV scope=dapr.contrib type=log ver=1.9.0
time="2022-10-29T01:55:12.3509222+05:30" level=debug msg="mDNS browse for app id uploader timed out." app_id=processor instance=DESKTOP-FIUUHBV scope=dapr.contrib type=log ver=1.9.0
time="2022-10-29T01:55:42.3602209+05:30" level=debug msg="Refreshing all mDNS addresses." app_id=processor instance=DESKTOP-FIUUHBV scope=dapr.contrib type=log ver=1.9.0
time="2022-10-29T01:55:42.3607271+05:30" level=debug msg="0 IPv4 address(es) expired for app id uploader." app_id=processor instance=DESKTOP-FIUUHBV scope=dapr.contrib type=log ver=1.9.0
time="2022-10-29T01:55:42.3607271+05:30" level=debug msg="Refreshing mDNS addresses for app id uploader." app_id=processor instance=DESKTOP-FIUUHBV scope=dapr.contrib type=log ver=1.9.0
time="2022-10-29T01:55:42.4014316+05:30" level=debug msg="mDNS response for app id uploader received." app_id=processor instance=DESKTOP-FIUUHBV scope=dapr.contrib type=log ver=1.9.0
time="2022-10-29T01:55:42.4036351+05:30" level=debug msg="Adding IPv4 address <IP_ADDRESS>:61484 for app id uploader cache entry." app_id=processor instance=DESKTOP-FIUUHBV scope=dapr.contrib type=log ver=1.9.0
time="2022-10-29T01:55:45.3636849+05:30" level=debug msg="mDNS browse for app id uploader timed out." app_id=processor instance=DESKTOP-FIUUHBV scope=dapr.contrib type=log ver=1.9.0
time="2022-10-29T01:55:45.3636849+05:30" level=debug msg="Refreshing mDNS addresses for app id uploader timed out."   app_id=processor instance=DESKTOP-FIUUHBV scope=dapr.contrib type=log ver=1.9.0
time="2022-10-29T01:56:15.3690387+05:30" level=debug msg="0 IPv4 address(es) expired for app id uploader." app_id=processor instance=DESKTOP-FIUUHBV scope=dapr.contrib type=log ver=1.9.0
time="2022-10-29T01:56:15.3690387+05:30" level=debug msg="Refreshing mDNS addresses for app id uploader." app_id=processor instance=DESKTOP-FIUUHBV scope=dapr.contrib type=log ver=1.9.0
time="2022-10-29T01:56:15.3948084+05:30" level=debug msg="mDNS response for app id uploader received." app_id=processor instance=DESKTOP-FIUUHBV scope=dapr.contrib type=log ver=1.9.0

Also , to add
I can see the dapr dashboard showing the uploader service up.

@iamsourabh-in - I actually didn't know you could access an app that way, but I just tried and it worked, so I guess I learned something new today :)
The mDNS timing out is interesting and would be a runtime problem. So, you may need to ask over there/in components-contrib.
Do you have the logs for the uploader as well?

@halspang -   I have raise the ticket in dapr runtime. 5430
Upgraded to dapr runtime 1.9.1, No luck Yet
When running AspNetCore in Debug, was able to get some insights, but still not able to invoke the method.

Seems to some issue with the runtime or TLS Config.
I have raise the ticket in dapr runtime. 5430 for further discussion.
Closing this ticket.


Add Setting for Output Window Word Wrap

Since VSC version 1.68.0, the text in the OUTPUT window (CTRL + Shift + U) is automatically wrapped and there does not seem to be an option in the preferences to disable this.
Possibly a regression of #21468.
I suggest to add a setting to allow toggling word wrapping in the OUTPUT window.

I see it wraps automatically in older versions too. Can you please show us what difference you are seeing?

Screenshots
Here are two screenshots showing the different behavior.
Not wrapped line in the red box:

Single, wrapped line:

Behavior in Previous Version

I see it wraps automatically in older versions too.

That is weird. I also installed a previous version (1.64.0), but it did not revert the behavior to unwrapped text in the OUTPUT window.
I could have sworn the behavior was different in earlier versions?!
Maybe I already had the manual setting:
"[Log]": {
"editor.wordWrap": "off"
}

which does exactly what I want, but somehow got deleted because of some glitch in the update to version 1.68.0?
Anyways, having added that option, the text is unwrapped, as I want it.


Document usage for Kotlin/JVM in Multiplatform projects

test {
  useJUnitPlatform()
}

doesn't seem to work in multiplatform projects.
However, this does:
jvmTest {
  useJUnitPlatform()
}

In kotlin dsl you would need this:
tasks.named<Test>("jvmTest") {
   useJUnitPlatform()
   testLogging {
      showExceptions = true
      showStandardStreams = true
      events = setOf(org.gradle.api.tasks.testing.logging.TestLogEvent.FAILED, org.gradle.api.tasks.testing.logging.TestLogEvent.PASSED)
      exceptionFormat = org.gradle.api.tasks.testing.logging.TestExceptionFormat.FULL
   }
}

KT 4.0 will be fully MPP ready.


pull request for e2e test at 11/07/2016 18:45:09

:white_check_mark: Validation status: passed

File
Status
Preview URL
Details

optest/docs/updated_at.md
:white_check_mark:Succeeded

Details

For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.


New documentation setup

This PR is the result of the work we've been doing to improve our documentation infrastructure, as a first step towards improving the content. :slightly_smiling_face:
This branch is deployed at openzeppelin-docs-next.netlify.com.
This is still wired up to the next branches of solidity-docgen and openzeppelin-docsite. Perhaps we should merge those into master before merging, but I wanted to drop this PR now.

I think I found a bug (no idea where it is in the code though):
Escrow's link to primary redirects to https://openzeppelin-docs-next.netlify.com/api/payment/escrow.html#Secondary.primary(), while it should be https://openzeppelin-docs-next.netlify.com/api/ownership.html#Secondary.primary() (i.e. we need to look up in which section the parent contract is located).

Good catch, yes. This is in solidity-docgen. I'll take a look at it tomorrow.

What is it that causes the docsite to be built for each branch? And is there a way to reduce the number of GitHub checks to just one (i.e. 'the docsite deployment was successful')?

We may want to include some sort of spell-check to the docs directory (and comments?) as well.

What  is it that causes the docsite to be built for each branch?

It's configured in the Netlify admin panel.

And is there  a way to reduce the number of GitHub checks to just one (i.e. 'the  docsite deployment was successful')?

I just toggled something that I think will remove it. Not sure if we'll be able to see that in this PR though.

The links should be fixed now. But the code in solidity-docgen keeps getting uglier and uglier. :upside_down_face:


Translating simplemvcframework.com?

@daveismyname: As mentioned in #205 and many other issues you just rebuild / redesign the website http://simplemvcframework.com. Are you planning a translation of the website?
I ask for the reason, because I'm planning a german blog for SMVC framework to begin. This I write for german users and other interested parties: about the development progresses, what's going on GitHub, tutorials and much more ...

I haven't considered that, I only know english I could use a translater like Google Translate but the wording may not be accurate, it's something to think about.
When looking at other peoples sites in different languages I tend to let Google translate the page.

On the website http://pointlinux.org/ po files are used for the translation. In the wiki is the process of translation explained. There are also many tutorials about gettext / po and PHP is supported. We can send you the po files with translations and you take it on the website.
Another possibility would be the SMVC core class "Language". Depending on whether you want to and the expense is not too great.

Good idea! I can help with german...

I could help with Spanish and maybe Dutch

I could help with Russian

i have no problem helping with translate to spanish
2015-11-10 1:14 GMT-03:00 volter9<EMAIL_ADDRESS>
I could help with Russian
—
Reply to this email directly or view it on GitHub
https://github.com/simple-mvc-framework/framework/issues/209#issuecomment-155280645
.

Wow thanks a lot guys that settles it then! I'll add the site to GitHub once I've got the language changes in place
The community has spoken lol!

I could help with Polish :)

@volter9  I used to watch Star Trek, and even aliens clear across the galaxy spoke English. Okay guys that was just a joke.

@jimgwhit, seems like a good joke to me :D

I could help with Portuguese ;-)

I'm going to close this for now, something to revisit in the future.


Script failed to scan birthdays. Error message: e30=

Using Chromium on Windows 10.
Tried on both the Facebook home page and the birthday page.

please suggest


IntelliSense duplicate method as property in completion and miss parameters

VSCode Version: 1.9.1
OS Version: MacOs Sierra 10.12.3
Tested with no extensions / no personal config.

Steps to Reproduce:
In a javascript file :

type :

//     cursor v
"String".toLow|

press "tab"
give the result :

//           cursor v
"String".toLowerCase|

Expected parenthesis :
//             cursor v
"String".toLowerCase( | )

The problem seems to be intellisense consider all exported functions as property too.
It result in a duplicate suggestion, one good, and the other broken. The problem is that the broken one is considered first.
Here is an example, we can show twice the same completion. The second do the job but the first (default) is crap :

How can i disable the first or priorize the second ?

Here is an example, we can show twice the same completion. The second do the job but the first (default) is crap :

How can i disable the first ?

Another example for setTimeout function :

First is awesome, second is totally crap (and is default) and third is just acceptable.
The problem with intellisense here, is that we got no idea where it's from and if it's configurable.

There is this setting "typescript.useCodeSnippetsOnMethodSuggest": false which also works for JavaScript like that. Maybe a bug @mjbvz ?

Thanks @jrieken , "typescript.useCodeSnippetsOnMethodSuggest": true did the trick.
But a way to configure which intellisense are enabled globally can be very usefull since we never know were a suggestion come from, and regarding the mass of extension adding some.

@DavidBabel I'm not sure the suggestion that completes the function call is coming from. @jrieken is correct that "typescript.useCodeSnippetsOnMethodSuggest"" configures the default js/ts suggestions to try to complete function calls, however I only even see one suggestion for methods like read and two suggestions (a property and a snippet) for setTimeout.
Can you please try running code using the --disable-extensions command line flag to ensure this is not coming from an extension?

Actually the problem appear on single suggestion too, without any extension and a config file with only this config : "typescript.useCodeSnippetsOnMethodSuggest" set to true . Here is best example :

And I still have two setTimeout suggestion on fresh installed vscode.
@mjbvz You are right, i did not check which extension it is, but i got an extension adding some intellisense for sure.
But the problem is : how disable the default behaviour or choose the priority if an extension add better intellisense ? This will allow to choose better default result and remove duplicates.

@DavidBabel #17068 tracks allowing disabling built-in extensions. I believe there's also been discussion of finer grained control to toggle specific features (such as completion items) of each extension, but this is farther off
We expect the two setTimeout definitions since one is a snippet. You can remove snippets from the suggestion list using "editor.snippetSuggestions": "none"

Yeah but it remove all the snippets. I like my personnal ones :p
Actually i did test thissetTimeout snippet on a new MacOs User session, with no vscode configuration at all, on both vscode 1.9.1 and nightly, and both same result : double suggestion.
If it can help i have a mac touchbar :

@DavidBabel This still sounds like the expected behavior.  There are a couple of issues tracking the various issues you've noted:

#10565 tracks being able to disable builtin snippets such as setTimeout
#17068 tracks allowing disabling built-in extensions

Please follow up with the extension that is providing these additional suggestions to get them to return suggestions that are preferred over the builtin TypeScript suggestions


Added Responsive Support

Changes:-

Made the Website completely Responsive
And Cascaded the File system

Fixed the Issue :- #2

Fixed the Issue :- #2

@BRAVO68WEB  please make sure the website is working fine, no text is being displayed when I open it.
It would be great if you could host is somewhere using GitHub pages so I can easily see the changes.

Means you want to Remove the Body Contents
Could you plz explain?

@rimijoker

the website is working fine

I am getting just a blinking cursor, can you host it on Github pages so that I can see the changes?

Its Working Fine Check This
https://bravo68web.github.io/Fake_Terminal_Resume_Website/
Fork version hosted on GitHub


Draft: Add simple ObserverFrame visualization

This PR adds a ObserverFrameRenderer component for visualizing single ObserverFrames and an ObserverFrameRendererManager for rendering all ObserverFrames in the scene using the same set of settings.
Both these classes contain the same options for visualizing ObserverFrames:

Size of the drawn lines
Alpha of the drawn lines
Right handed visualization of the frames
LineDivisions when drawing the lines
DrawMode of the lines, with options being to draw lines using GL.Lines or Unity Gizmos

Not quite sure how the ObserverFrameRendererManager should behave in edit mode yet. Keeping this as a draft for now.


Add irradiance.clearsky_index

[x] Closes issue #551
[x] I am familiar with the contributing guidelines.
[x] Fully tested. Added and/or modified tests to ensure correct behavior for all reasonable inputs. Tests (usually) must pass on the TravisCI and Appveyor testing services.
[x] Updates entries to docs/sphinx/source/api.rst for API changes.
[x] Adds description and name entries in the appropriate docs/sphinx/source/whatsnew file for all changes.
[x] Code quality and style is sufficient. Passes LGTM and SticklerCI checks.
[x] New code is fully documented. Includes sphinx/numpydoc compliant docstrings and comments in the code where necessary.
[x] Pull request is nearly complete and ready for detailed review.

Two questions for the pvlib team:

Anyone have a citation for the definition of the clear-sky index?  My searching was unsuccessful.
I don't have much experience writing tests for numerical functions -- is the approach used in the tests for irradiance.clearness_index a good example to follow?  Hardcoding numbers strikes me as bad form, but the alternative would just be to reimplement the function in the test...

@kevinsa5 also, thanks.  I'd recommend hard-coding some inputs you select, and not running a clear-sky model to generate inputs for the test.

Apologies for the long delay on this PR.  Two questions:

I'm not very experienced in CI, but it seems like the travis failures are related to the test framework, rather than the pvlib code?
Also unfamiliar with this stickler bot.  Shall I add the .stickler.tml from the master branch to this PR?

@kevinsa5 there are new test failures due to a new version of pytest and there is a known failure due to python/numba. Just make sure your tests are passing.
Can you merge the latest pvlib/master into your branch? That should allow stickler to check your code for style/formatting issues.

Please let me know whether I understand the code correctly:

clearsky_index = ghi / clearsky_ghi propagates nans without creating new ones.
clearsky_index = np.maximum(clearsky_index, 0) pulls -inf to zero
clearsky_index = np.minimum(clearsky_index, max_clearsky_index) pulls +inf to max_clearsky_index

So the extra steps basically serve to pull +inf down to zero rather than to max_clearsky_index?

clearsky_index = ghi / clearsky_ghi will both propagate nans and create new nans -- consider ghi = clearsky_ghi = 0.  The extra steps are so input nan/inf are mapped to nan, but any nan/inf created internally result in zero, eg:
In [9]: clearsky_index(np.array([1,1,np.nan]), np.array([np.nan, 0, 1]))
Out[9]: array([ nan,   0.,  nan])


Incompatible change in scratch org "created" property format in JSON output of "force:org:list"

A customer reported this to me as it's breaking Illuminated Cloud's JSON-based integration with the CLI when calling force:org:list. It appears that in a very recent build, the format of the created property for scratchOrg entries has not only changed, but it's actually inconsistent even in the same list. For example, in one entry it's:
"created": "2021-07-24T03:30:41.000+0000"

and in another it's:
"created": "1626394643945"

e.g.,:
    "scratchOrgs": [
      {
        ...
        "created": "2021-07-24T03:30:41.000+0000",
        ...
      },
      {
        ...
        "created": "1626394643945",
        ...
      }
    ]

Traditionally it would have consistently been the latter.
I can certainly update Illuminated Cloud to accommodate for this, but since this is a breaking change to the effective API used by tools for integration, to me this seems like a regression that should be fixed ASAP.
NOTE: This doesn't seem to be happening consistently. I don't see it locally on any of my test machines on the latest CLI release (7.110.0-85b006b), all of which are binary installs. The user who reported this is using an NPM install on a Mac at the same version.
NOTE 2: Continuing to speak with the affected user, I'm wondering if perhaps it's not the CLI itself (at least not entirely) but perhaps something in his dev hub. He sees the same behavior after dropping back several CLI versions, and he's also seeing it in packaged install now in addition to the npm install. There's more discussion on the topic here if you're interested:
https://bitbucket.org/RoseSilverSoftware/illuminatedcloud/issues/1940

The root cause is that when a scratch org is created, in scratchOrgInfoApi.ts the created member had a value of created: Date.now() + '', but in sfdx-cli@latest-rc this was changed to created: scratchOrgInfoComplete.CreatedDate which breaks integrations.

this is fixed in the current RC 7.111.4+


Transform error with client.geo.location

I'm creating a log source for Okta logs and am struggling to transform log data to the ECS fields client.geo.location.lat and client.geo.location.lon. With the VRL below, I consistently get the error "USER_ERROR: Failed at FindUnionVariant, likely schema issue." in the transformer Lambda. I have pretty much every other Okta log field working.
Looking at the ECS schema JSON, both lat and lon are defined as floats, so this should work.
Relevant VRL transform:
.client.geo.location.lat = to_float(del(.json.client.geographicalContext.geolocation.lat)) ?? null
.client.geo.location.lon = to_float(del(.json.client.geographicalContext.geolocation.lon)) ?? null
Relevant log data:
{
    "json": {
        "client": {
            "geographicalContext": {
                "city": "Ashburn",
                "country": "United States",
                "geolocation": {
                    "lat": 39.0469,
                    "lon": -77.4903
                },
                "postalCode": "20149",
                "state": "Virginia"
            }
        }
}

Any assistance identifying the issue or bug would be appreciated.
Thanks.

Hey Greg, thanks for opening an issue. I am looking into this, will try and recreate the issue locally and see where the schema is mismatching.

Appreciate you taking a look. I’m on vacation this week but will pull down your fix when I return and give it a whirl. Thanks!

https://github.com/apache/avro/commit/6eb72341912ac3858f56531e457de77213eafd02
My fix has been merged a fix in the official Avro upstream as well. Deleting and redeploying the DPMainStack using the latest release should have fixed any problems with float/double. Let me know if this resolves your issue, thanks!

Just attempted to test using today's (December 12th) nightly build but the DPMainStack won't deploy. Looks like this is some sort of bug because I was able to deploy on an older version. Tried deleting both the stacks and starting fresh but it didn't help, still getting same error. Not sure how to further debug this?
[100%] fail: The XML you provided was not well-formed or did not validate against our published schema

 ❌  DPMainStack (MatanoDPMainStack) failed: Error: Failed to publish one or more assets. See the error messages above for more information.
    at publishAssets (/snapshot/node_modules/aws-cdk/lib/util/asset-publishing.ts:60:11)
    at processTicksAndRejections (node:internal/process/task_queues:96:5)
    at CloudFormationDeployments.publishStackAssets (/snapshot/node_modules/aws-cdk/lib/api/cloudformation-deployments.ts:572:7)
    at CloudFormationDeployments.deployStack (/snapshot/node_modules/aws-cdk/lib/api/cloudformation-deployments.ts:419:7)
    at deployStack2 (/snapshot/node_modules/aws-cdk/lib/cdk-toolkit.ts:265:24)
    at /snapshot/node_modules/aws-cdk/lib/deploy.ts:39:11
    at run (/snapshot/node_modules/p-queue/dist/index.js:163:29)

 ❌ Deployment failed: Error: Stack Deployments Failed: Error: Failed to publish one or more assets. See the error messages above for more information.
    at deployStacks (/snapshot/node_modules/aws-cdk/lib/deploy.ts:61:11)
    at processTicksAndRejections (node:internal/process/task_queues:96:5)
    at CdkToolkit.deploy (/snapshot/node_modules/aws-cdk/lib/cdk-toolkit.ts:339:7)
    at initCommandLine (/snapshot/node_modules/aws-cdk/lib/cli.ts:374:12)

Stack Deployments Failed: Error: Failed to publish one or more assets. See the error messages above for more information.

Hm thanks for the report. This seems to be caused by an obscure issue with the specific Node 16 version and compatibility with AWS CDK. https://github.com/aws/aws-cdk/issues/19287. We bundle node as part of the matano CLI using vercel/pkg, I'm going to look into recreating this issue and pinning the Node to a specific minor version as a potential fix. Will update here

I just found a post on SO that links to the same aws-cdk issue.  They agreed rolling back the node version seems to fix it.
I also looked back at my debug deploy logs and I do see a multipart upload that has two null ETags, so definitely seems similar. I'll keep an eye out for a new Matano nightly. Thanks!

Can you run matano and copy the version its outputting? Should look like:
VERSION
  matano/0.0.0 linux-x64 node-v18.4.0

Also are you using Mac OS or Linux? Thx.

matano/0.0.0 darwin-x64 node-v16.16.0
macOS 12.6.1

I wasn't able to reproduce the error but I've went ahead and updated the embedded node version to 18.5.0. Could you try again and see if it works?

Not seeing any nightlies available for download right now. Can you check the build?

I've retried the build, they're generated now.

Same issue using matano/0.0.0 darwin-x64 node-v18.5.0.  Can we try downgrading node to an earlier 16.x version?

Sure let me try to publish with 16.3.0, the linked issue mentions changing to that version fixed their issue.

I wasn't able to publish a binary with v16.3.0 for now but I've published a release that uses v14.18.1 which the linked post mentioned was confirmed to work. Can you try again and let me now?

The stack deploy debug no longer showed null etags for the multipart uploads, which is good, but it still failed to deploy the first two timed I tried, with this error:
⠹ Deploying Matano...[91%] fail: One or more of the specified parts could not be found.  The part may not have been uploaded, or the specified entity tag may not match the part's entity tag.

The third time I ran it, the deployment was successful.
It seems like it's having trouble with the multipart uploads but if you run it a few times CDK eventually gets everything uploaded and it's happy. September/October I was experimenting with Matano and didn't have these issues, so it's strange that this just started happening with later builds (didn't have time to play with it in November).
Matano version - matano/0.0.0 darwin-x64 node-v14.18.1
Someone in the AWS CDK issue linked earlier mentioned they were running 16.7 and didn't see any issues, so it might be worth trying that version if 16.3 is giving you problems.

Good to see it works. Sure I'll check 16.7.
Btw are you on a stable internet connection, I would often get that error when I was on a bad internet connection which makes sense it preventing a corrupt upload, especially for the larger assets.

Yeah, my internet is stable. I’ll continue to troubleshoot the CDK issue on my own and open another issue if necessary. I’ll close this issue because I was able to get the Okta float data through the Matano data pipieline, so I think we’re good.
I’d be happy to contribute my Okta work to the Matano project if you’re interested in making it a managed source, just let me know.
Thanks for your help and responsiveness solving this!

Definitely would appreciate the  contribution of Okta as a managed log source. Feel free to create a PR, and thank you!


Loading dialog keeps showing, how to disable it?

It keeps showing loading dialog, how to hide it once my task is over?

you can just keep it works in method doInBackground in class Task.and if you finished the work in doInBackground  it will disappear.


tf.lite.TFLiteConverter error

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 16.04
TensorFlow version (use command below): tf-nightly 1.14.1.dev20190513
Python version: 3.5.2

Describe the current behavior
I create a model from tensorflow, and it's a simple model.
The graph is as following:

Placeholder: type=tf.float32, shape=[None, 640, 480, 1]  (format: NHWC)
Conv2D: kernel_size = 5, filter_num = 32, stride=1, padding='same' ( tf.layer.con2d)
relu (tf.nn.relu)

I save this graph to test.pb.
I want to convert this model to tflite model with int8, so i use tf.lite.converter to convert my test.pb to convert_test.tflite.
But something strange...
When i use Netron to parse test.pb, the Conv2D layer is still Conv2D. But in my convert_test.tflite, the Conv2D layer is been changed to "DepthwiseConv2D".
What happen...?
And, what can i do?

@tsa10262 : That's expected behavior, based on your model ops, however it does not affect your output.
Please check for desired output, if it solves your purpose, then well and good. If my post helped resolve your issue, please close the thread, Thanks!

@ANSHUMAN87: Thanks for answering. It's not affect the output.
I'll close the thread.
Thanks a lot.

@ANSHUMAN87 I have a follow-up question about this issue. I had a same issue. What should I do to get "Conv2D" layer instead of "DepthwiseConv2D"?
First Conv2D layer is converted to "DepthwiseConv2D", but second Conv2D layer is converted to "Conv2D". I should have get every conv2d layers converted to conv2d due to post-processing steps.
model = keras.models.Sequential([
keras.layers.Conv2D(filters=6, kernel_size=3, activation='relu', input_shape=(28, 28, 1), name="input_node"),
keras.layers.MaxPooling2D(pool_size=(2, 2), strides=2),
keras.layers.Conv2D(filters=16, kernel_size=3, activation='relu'),
keras.layers.MaxPooling2D(pool_size=(2, 2), strides=2),
keras.layers.Flatten(),
keras.layers.Dense(120, activation='relu'),
keras.layers.Dense(84, activation='relu'),
keras.layers.Dense(10, activation='softmax', name='output_node')
])


Trigger for posting on different chanels/private chats

I it possible to trigger slack notifications so, that if build success - post notification on channel1/private chat1 and if its fails - post notification on channel2/private chat2?

not currently


Usage and export of slurm target_seg (partition)

@jennfshr
In order to add support for knl nodes we needed to support the -p (partition) and -C (constraint) options in sbatch. Constraint was not supported so I added it. Partition was already supported by target_seg in slurm so I did not add it.
In moab target_seg adds ",feature=$TARGET_SEG" to the -l option. @BenCasses decided was equivalent to partition in slurm.
Back when we were running on moab I added the option "machine_type" so that we could request knl. I was asked to expose the requested machine type to the run scripts which I did with the environmental variable "PV_MACHINE_TYPE". I would like to match this capability with slurm and I would like to move towards a similar interface for both slurm and moab.
These are the options I see but I think they all have problems:

Just export PV_MACHINE_TYPE in slurm to be partition
This seems messy because then the name of the environmental variable does not match the item in the config file.

Export PV_PARTITION in slurm and pavilion
In our use cases then partition would mean different things depending on which scheduler we are using

rename machine_type in moab to partition, add partition to slurm, and do option 2
Then what would we do with target_seg in slurm. I would rather not have two options do the same thing because it seems like that could cause weird corner cases. This also breaks all current tests.

Change "target_seg" in moab to do what "machine_type" does and also do option 1.
This should fix all the problems and should not break anything unless someone is relying on the features option in moab.

If portability between schedulers is the focus, we need an authoritative mapping between Pavilion concepts and each scheduler's vernacular.  Conflicts will keep occurring as more schedulers are added.  This is the reason I mapped "target_seg" to slurm's "partition" rather than using native terminology.
Does the "target_seg" concept match with machine type or can you independently select a set of nodes and a type of machine?

I think portability should be the goal. I also don't think anyone is using moab currently so changing it may not cause issues. I will talk to some of the trinity testers.


recorded activities page map tasks:

recorded activities page map tasks:

[x] display each record set as a cluster layer at higher zooms
[x] create tests to generate records to see on the map.
[x] display count for each record cluster
[x] display as geojson at smaller zoom
[ ] #1919

Originally posted by @micheal-w-wells in https://github.com/bcgov/invasivesbc/issues/1762#issuecomment-1104153342

i think we can close this as the remaining work is well captured on other tickets


fixing the mirror package + broken pipeline fixes

pull_request_target is failing because master has a corrupt source tree. force merging since push is passing.


About training results

Hello, why is the result like this when I run the train file?
=> loading HRNet pretrained model models/hrnet_w18_small_v2.pth
HRNet weight-loading succeeds: ./checkpoint/HRNet_checkpoint/HRNet.pth
NLCDetection weight-loading succeeds: ./checkpoint/NLCDetection_checkpoint/NLCDetection.pth
DetectionHead weight-loading succeeds: ./checkpoint/DetectionHead_checkpoint/DetectionHead.pth
length of traindata: 500
previous_score 0.9871
authentic_ratio: 0.25 fake_ratio: 0.75
resuming FENet by loading epoch 30
resuming SegNet by loading epoch 30
resuming ClsNet by loading epoch 30
Process finished with exit code 0

@FathUMinUllah3797 Thanks for helping me answer the question. Yes, your understanding is correct.
@YchenJsy If you have any further question, please reopen this issue.

@YchenJsy . It means, you have trained the model for 30 epochs and in next training, the model see previously trained checkpoints and give the prediction based on them. If you move them out, it will start training again.
This is what I experienced too.

ex

@YchenJsy . It means, you have trained the model for 30 epochs and in next training, the model see previously trained checkpoints and give the prediction based on them. If you move them out, it will start training again.
This is what I experienced too.
thanks for your explanation

@FathUMinUllah3797  thanks for your explanation  !


upload hlcn

In order to streamline the review of the contribution we ask you
to ensure the following steps have been taken:

[x] Filename in the lowercase format
[x] Image format: png
[x] Image size: 256 by 256 px

For next PR please update your fork and do not submit duplicate images, for now added your logo here https://github.com/TrustWallet/tokens/commit/0bfa5a334ee4baddb7bec2df4ddd2b93d4efe098


Pretrained wideresnet and xception71

Hi,
The models from [https://drive.google.com/drive/folders/1fs-uLzXvmsISbS635eRZCc5uzQdBIZ_U] wideresnet38.pth.tar and alignedxception71.pth are imagenet pretrained only, right ?

Correct


IE11 too big header, list items partially/not visible

In IE 11.0.9600 in PC mode (window bigger than 768px) menu items are only partially visible.
Luxbar header is too big. While resizing it swipes the menu items out of the screen.

Below screenshot for ~800px width:

When window is smaller than 768 it turns on hamburger mode, which works fine.

Looks similar to this one:
Flexbugs: Column flex items set to align-items: center overflow their container
found here: canIuse / Known issues tab
;)

Workarround:
.luxbar-navigation {
    justify-content: space-around; // You can also use an other justify-content that you want
}


Add Portal API URL configuration variable to Explorer

Need
The Explorer needs to fetch collection information from the Portal's /collections/${id} endpoint. The API URL varies by environment and needs to be configurable.
Approach
Either add Portal API URL variable via existing globals mechanism or add as an additional value returned in config.dataset_identification.
Definition of Done
Environment-specific Portal API URL variable is available to Explorer FE code.

Superseded by #59.


chore(ci): move all CI from Node7 to Node8

Node 8 is the current LTS. We should use it by default on all
our CIs.

Let's do node 10 and node 6.

Let's do node 10 and node 6.

With pleasure. Closing in favor of https://github.com/GoogleChrome/puppeteer/pull/2941

Resurrecting this since node 10 is not quite ready yet


House transports user to the 0, 0, 0 coordinate

Platform: All

Branch commit: Latest

Steps: ?

That's just an issue on the house's door, it's assigned to transfer the player to the 0,0,0 coordinate. You can easily change the position in the inspector.

I've only reopened this for reference when I get to work over spring break.

Easy fix, just lock the door and change the lock text to "Nobody lives here." PR incoming.

Yeah, I fixed the issue in develop by just making the door locked. Fyi I haven't pushed it yet but it's really easy to fix.

Yeah, I fixed the issue in develop by just making the door locked. Fyi I haven't pushed it yet but it's really easy to fix.

Locked in this commit.
https://github.com/PokemonUnity/PokemonUnity/pull/34


Fix available semesters refreshing

Currently they aren't refreshed when the current academic year changes.

https://stackoverflow.com/questions/72544499/object-in-store-and-reactive-statements
Just deconstruct the object and have a reactive cascade! Genius!


[REFACTOR] Drop Python 2 support and update pylint

Description
Drop Python 2 as per https://github.com/dmlc/gluon-nlp/issues/721.
This allows updating pylint of which our current version emits false positive E1111 with https://github.com/dmlc/gluon-nlp/pull/836.
Also fixes https://github.com/dmlc/gluon-nlp/issues/839.
Checklist
Essentials

[X] PR's title starts with a category (e.g. [BUGFIX], [MODEL], [TUTORIAL], [FEATURE], [DOC], etc)
[X] Changes are complete (i.e. I finished coding on this PR)
[X] All changes have test coverage
[X] Code is well-documented

Changes

[X] Drop Python 2 support and update pylint

Found link check problems in job PR-838/1:
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    7) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    7) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    3) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line   19) broken    https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/ - 404 Client Error: Not Found for url: https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/
(line    5) broken    https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/ - 404 Client Error: Not Found for url: https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/
(line    5) broken    https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/ - 404 Client Error: Not Found for url: https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/
(line   21) broken    https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/ - 404 Client Error: Not Found for url: https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/
(line  442) broken    https://www.aclweb.org/anthology/P02-1040.pdf)[1 - 404 Client Error: Not Found for url: https://www.aclweb.org/anthology/P02-1040.pdf)%5B1
(line   92) broken    https://nlp.stanford.edu/pubs/glove.pdf)[2 - 404 Client Error: NOT FOUND for url: https://nlp.stanford.edu/pubs/glove.pdf)%5B2
(line  208) broken    https://www.bioinf.jku.at/publications/older/2604.pdf)[3 - 404 Client Error: Not Found for url: https://www.bioinf.jku.at/publications/older/2604.pdf)%5B3

Job PR-838/1 is complete.
Docs are uploaded to http://gluon-nlp-staging.s3-accelerate.dualstack.amazonaws.com/PR-838/1/index.html

Found link check problems in job PR-838/3:
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    3) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    7) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    7) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    5) broken    https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/ - 404 Client Error: Not Found for url: https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/
(line   19) broken    https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/ - 404 Client Error: Not Found for url: https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/
(line    5) broken    https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/ - 404 Client Error: Not Found for url: https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/
(line   21) broken    https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/ - 404 Client Error: Not Found for url: https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/
(line  442) broken    https://www.aclweb.org/anthology/P02-1040.pdf)[1 - 404 Client Error: Not Found for url: https://www.aclweb.org/anthology/P02-1040.pdf)%5B1
(line   92) broken    https://nlp.stanford.edu/pubs/glove.pdf)[2 - 404 Client Error: NOT FOUND for url: https://nlp.stanford.edu/pubs/glove.pdf)%5B2
(line  208) broken    https://www.bioinf.jku.at/publications/older/2604.pdf)[3 - 404 Client Error: Not Found for url: https://www.bioinf.jku.at/publications/older/2604.pdf)%5B3

Job PR-838/3 is complete.
Docs are uploaded to http://gluon-nlp-staging.s3-accelerate.dualstack.amazonaws.com/PR-838/3/index.html

Found link check problems in job PR-838/4:
(line    7) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    7) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    3) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line    4) broken    https://gluebenchmark.com/tasks - 404 Client Error: Not Found for url: https://gluebenchmark.com/tasks
(line   19) broken    https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/ - 404 Client Error: Not Found for url: https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/
(line    5) broken    https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/ - 404 Client Error: Not Found for url: https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/
(line    5) broken    https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/ - 404 Client Error: Not Found for url: https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/
(line   21) broken    https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/ - 404 Client Error: Not Found for url: https://www.salesforce.com/products/einstein/ai-research/the-wikitext-dependency-language-modeling-dataset/
(line  442) broken    https://www.aclweb.org/anthology/P02-1040.pdf)[1 - 404 Client Error: Not Found for url: https://www.aclweb.org/anthology/P02-1040.pdf)%5B1
(line   92) broken    https://nlp.stanford.edu/pubs/glove.pdf)[2 - 404 Client Error: NOT FOUND for url: https://nlp.stanford.edu/pubs/glove.pdf)%5B2
(line  208) broken    https://www.bioinf.jku.at/publications/older/2604.pdf)[3 - 404 Client Error: Not Found for url: https://www.bioinf.jku.at/publications/older/2604.pdf)%5B3

Job PR-838/4 is complete.
Docs are uploaded to http://gluon-nlp-staging.s3-accelerate.dualstack.amazonaws.com/PR-838/4/index.html


Oculus Mobile (VRAPI) continuous support in renderdoc

Description
Currently, Oculus Mobile (GearVR and Go) frame captures on Android uses the gl_hooks_vrapi.cpp file to hook the vrapi_submitframe function in order to know when an app finishes its frame, a requirement to be able to do frame captures. This is quite buggy since 1.0, as it hooks into libvrapi.so instead of libvrapiimpl.so, and therefore calls the stub and not the implementation of vrapi_submitframe after the function has been hooked. This also works very differently depending on if you're on a GearVR or an Oculus Go, due to the differences of the compositor being an app in Gear vs a system component in Go.
In SI1.15, the very latest runtime update (not available for Go yet, but soon), the compositor directly submits a GL marker, and renderdoc supports it as of https://github.com/baldurk/renderdoc/commit/83ba2e95e736a3f4f150c6fa16b92c4ad01845cd. In order to make all of this more stable, the best way going forward would be to deprecate the VRAPI hooking and solely maintain the GL path, including the end-of-frame markers.
Is there anybody out there that is using renderdoc for oculus mobile, for which renderdoc is currently working, but who can't upgrade to the latest runtime update for Oculus?
Thanks :)

This is fine for us. Our fork of renderdoc is working with oculus mobile, and I'll try the new changes out once I am done with what I am working on.

To be concrete, let's say if no-one responds within 3 weeks (by 6th July) we'll assume everyone who is capturing VRAPI apps is on the latest runtime.

I removed the hooks and closed this ahead of time because I didn't fully appreciate that some cases with the newer versions of oculus's libraries are actually broken while these hooks are in place.
If you do have issues with the removal of the vrapi hooking, please still comment here so we can evaluate what solution is appropriate.


Start of "Txt Slang" locale

The locale isn't finished but is started. Its too late (12:50AM) for me to do really much with it atm.

Needs to be finished before pulling

Ok, I’ll try finishing it up this weekend.
On Oct 5, 2017, at 10:28 AM, 7coil <notifications<EMAIL_ADDRESS>wrote:
Needs to be finished before pulling
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHubhttps://github.com/moustacheminer/discordmail/pull/16#issuecomment-334482164, or mute the threadhttps://github.com/notifications/unsubscribe-auth/AOeLWDKQJuORKpM4AscepFBCaOv_RNHKks5spOeSgaJpZM4PpyHo.


Add Custom Close to Vimeo?

Is it possible to insert html like with inline elements to have a custom close when just using a direct vimeo link?

Not directly because the vimeo video is loaded inside an iframe. You can try to use an event to modify the DOM of the popup.


Can not load DBert-ft  model

Hi hayj,
Thank you for sharing your code. I am doing some style calculations for documents as well and would like to test out your approach.
Unfortunately, I can not load your DBert-ft model, i.e., I get an error when running this line:
m = DeepStyle("DeepStyle/model/<IP_ADDRESS>/DeepStyle/dbert-ft/")

First, I get the error
NameError: name 'os' is not defined

in model.py

When adding the line
import os
in DeepStyle/deepstyle/model.py, I get a different error. I tried both, with my current versions (i.e., python 3.8, and some more recent transformers and tensorflow-gpu version) as well as the versions you mentioned (i.e., 2.4.1and 2.0).
In the first case I get the error:
Error
Traceback (most recent call last):
  File "/home/anna/anaconda3/envs/src/lib/python3.8/unittest/case.py", line 60, in testPartExecutor
    yield
  File "/home/anna/anaconda3/envs/src/lib/python3.8/unittest/case.py", line 676, in run
    self._callTestMethod(testMethod)
  File "/home/anna/anaconda3/envs/src/lib/python3.8/unittest/case.py", line 633, in _callTestMethod
    method()
  File "/home/anna/Documents/UU/digital-society_intergenerational-empathy/src/test/test_style_similarity.py", line 27, in test_deepstyle_features
    logging.info(feature_object.deepstyle_features(text))
  File "/home/anna/Documents/UU/digital-society_intergenerational-empathy/src/utility/style_similarity.py", line 91, in deepstyle_features
    model = DeepStyle(model_file)
  File "/home/anna/anaconda3/envs/src/lib/python3.8/site-packages/deepstyle-0.0.1-py3.8.egg/deepstyle/model.py", line 129, in __init__
    self.__load()
  File "/home/anna/anaconda3/envs/src/lib/python3.8/site-packages/deepstyle-0.0.1-py3.8.egg/deepstyle/model.py", line 133, in __load
    self.model = TFDistilBertForSequenceClassification.from_pretrained\
  File "/home/anna/anaconda3/envs/src/lib/python3.8/site-packages/transformers/modeling_tf_utils.py", line 710, in from_pretrained
    load_tf_weights(model, resolved_archive_file)
  File "/home/anna/anaconda3/envs/src/lib/python3.8/site-packages/transformers/modeling_tf_utils.py", line 291, in load_tf_weights
    array = np.reshape(saved_weight_value, K.int_shape(symbolic_weight))
  File "<__array_function__ internals>", line 5, in reshape
  File "/home/anna/anaconda3/envs/src/lib/python3.8/site-packages/numpy/core/fromnumeric.py", line 301, in reshape
    return _wrapfunc(a, 'reshape', newshape, order=order)
  File "/home/anna/anaconda3/envs/src/lib/python3.8/site-packages/numpy/core/fromnumeric.py", line 61, in _wrapfunc
    return bound(*args, **kwds)
ValueError: cannot reshape array of size 921600 into shape (768,2)

and in the second:
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/anna/anaconda3/envs/test3.6/lib/python3.6/site-packages/deepstyle-0.0.1-py3.6.egg/deepstyle/model.py", line 129, in __init__
  File "/home/anna/anaconda3/envs/test3.6/lib/python3.6/site-packages/deepstyle-0.0.1-py3.6.egg/deepstyle/model.py", line 136, in __load
  File "/home/anna/anaconda3/envs/test3.6/lib/python3.6/site-packages/transformers/modeling_tf_utils.py", line 355, in from_pretrained
    model.load_weights(resolved_archive_file, by_name=True)
  File "/home/anna/anaconda3/envs/test3.6/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/training.py", line 181, in load_weights
    return super(Model, self).load_weights(filepath, by_name)
  File "/home/anna/anaconda3/envs/test3.6/lib/python3.6/site-packages/tensorflow_core/python/keras/engine/network.py", line 1175, in load_weights
    saving.load_weights_from_hdf5_group_by_name(f, self.layers)
  File "/home/anna/anaconda3/envs/test3.6/lib/python3.6/site-packages/tensorflow_core/python/keras/saving/hdf5_format.py", line 718, in load_weights_from_hdf5_group_by_name
    original_keras_version = f.attrs['keras_version'].decode('utf8')
AttributeError: 'str' object has no attribute 'decode'

For now, I am only testing on a computer with only a CPU. But this should not be an error source, I think.
Did you have this problem before? It would be awesome if you can help me out.

I now also tried it with a GPU:

>>> model = DeepStyle("/hpc/uu_cs_nlpsoc/data/conversations/DeepStyle/<IP_ADDRESS>/DeepStyle/dbert-ft")
2020-12-08 17:15:11.909192: W tensorflow/python/util/util.cc:329] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.
2020-12-08 17:15:11.954390: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 AVX512F FMA
2020-12-08 17:15:11.961220: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency:<PHONE_NUMBER> Hz
2020-12-08 17:15:11.961474: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55f488bb1020 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-12-08 17:15:11.961511: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2020-12-08 17:15:11.961671: I tensorflow/core/common_runtime/process_util.cc:147] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance.
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/uu_cs_nlpsoc/awegmann/DeepStyle/deepstyle/model.py", line 129, in __init__
    self.__load()
  File "/home/uu_cs_nlpsoc/awegmann/DeepStyle/deepstyle/model.py", line 133, in __load
    self.model = TFDistilBertForSequenceClassification.from_pretrained\
  File "/hpc/local/CentOS7/uu_cs_nlpsoc/conda/envs/aw_style_similarity/lib/python3.8/site-packages/transformers/modeling_tf_utils.py", line 616, in from_pretrained
    model.load_weights(resolved_archive_file, by_name=True)
  File "/hpc/local/CentOS7/uu_cs_nlpsoc/conda/envs/aw_style_similarity/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 250, in load_weights
    return super(Model, self).load_weights(filepath, by_name, skip_mismatch)
  File "/hpc/local/CentOS7/uu_cs_nlpsoc/conda/envs/aw_style_similarity/lib/python3.8/site-packages/tensorflow/python/keras/engine/network.py", line 1263, in load_weights
    hdf5_format.load_weights_from_hdf5_group_by_name(
  File "/hpc/local/CentOS7/uu_cs_nlpsoc/conda/envs/aw_style_similarity/lib/python3.8/site-packages/tensorflow/python/keras/saving/hdf5_format.py", line 780, in load_weights_from_hdf5_group_by_name
    raise ValueError('Layer #' + str(k) +' (named "' + layer.name +
ValueError: Layer #2 (named "classifier"), weight <tf.Variable 'tf_distil_bert_for_sequence_classification/classifier/kernel:0' shape=(768, 2) dtype=float32, numpy=
array([[-0.00159971, -0.00793274],
       [-0.01530189, -0.00791676],
       [-0.0077662 , -0.02859338],
       ...,
       [-0.03073144,  0.00575919],
       [-0.01332873, -0.02662781],
       [ 0.01318847, -0.01922753]], dtype=float32)> has shape (768, 2), but the saved weight has shape (768, 1200).

Hi
@AnnaWegmann I got the same error.os is not defined.It didnt work even after importing os.

Hi
@AnnaWegmann I got the same error.os is not defined.It didnt work even after importing os.

Hi,
I could solve this with some help:
add import os
downgrading h5py to 2.10.0
2.4.1and 2.0 for transformers and tensorflow-gpu

Hi,
I could solve this with some help:
add import os
downgrading h5py to 2.10.0
2.4.1and 2.0 for transformers and tensorflow-gpu

Thank you @AnnaWegmann, I added the import os line
I also added a complete command line demo that install right versions of each lib:
cd ~/tmp
mkdir dbert-ft
cd dbert-ft
wget http://<IP_ADDRESS>/DeepStyle/dbert-ft/config.json
wget http://<IP_ADDRESS>/DeepStyle/dbert-ft/tf_model.h5
cd ../
conda create -n dbertft-env -y python=3.7 anaconda
conda activate dbertft-env
git clone https://github.com/hayj/deepstyle ; cd deepstyle ; pip uninstall deepstyle -y ; python setup.py install ; cd ../ ; rm -rf deepstyle
pip install --ignore-installed --upgrade tensorflow==2.0.0
pip install --ignore-installed --upgrade transformers==2.4.1
pip install --ignore-installed --upgrade h5py==2.10.0
ipython -c "from deepstyle.model import DeepStyle ; m = DeepStyle('dbert-ft') ; m.embed('Hello World')"

Thank you @AnnaWegmann, I added the import os line
I also added a complete command line demo that install right versions of each lib:
cd ~/tmp
mkdir dbert-ft
cd dbert-ft
wget http://<IP_ADDRESS>/DeepStyle/dbert-ft/config.json
wget http://<IP_ADDRESS>/DeepStyle/dbert-ft/tf_model.h5
cd ../
conda create -n dbertft-env -y python=3.7 anaconda
conda activate dbertft-env
git clone https://github.com/hayj/deepstyle ; cd deepstyle ; pip uninstall deepstyle -y ; python setup.py install ; cd ../ ; rm -rf deepstyle
pip install --ignore-installed --upgrade tensorflow==2.0.0
pip install --ignore-installed --upgrade transformers==2.4.1
pip install --ignore-installed --upgrade h5py==2.10.0
ipython -c "from deepstyle.model import DeepStyle ; m = DeepStyle('dbert-ft') ; m.embed('Hello World')"

Hi hayj,
The link given [http://<IP_ADDRESS>/DeepStyle/dbert-ft/] to download the model and config is not working.
It would be awesome if you can help me out.

Thx, I already noticed it doesn't work. Trying to fix it. In the meantime, pls send me a private msg, I'll give you a temp link.

Please send the temp link.
Thanks.

Here is the link to get the model:
https://drive.google.com/file/d/1Y9TMjj04fVhNuJnhzaM4Wmn2CQfZ8r8U/view?usp=share_link

Hello guys, thank you for this work!
I also downloaded the model using the link in the README.md file but I get the same error:
You passed along `num_labels=1200` with an incompatible id to label map: {'0': 'LABEL_0', '1': 'LABEL_1'}. The number of labels wil be overwritten to 2.
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/Julien/Documents/Newtone/Admin-UI/scoring/deepstyle/model.py", line 129, in __init__
    self.__load()
  File "/Users/Julien/Documents/Newtone/Admin-UI/scoring/deepstyle/model.py", line 133, in __load
    self.model = TFDistilBertForSequenceClassification.from_pretrained\
  File "/usr/local/lib/python3.9/site-packages/transformers/modeling_tf_utils.py", line 2828, in from_pretrained
    missing_keys, unexpected_keys, mismatched_keys = load_tf_weights(
  File "/usr/local/lib/python3.9/site-packages/transformers/modeling_tf_utils.py", line 889, in load_tf_weights
    return load_function(
  File "/usr/local/lib/python3.9/site-packages/transformers/modeling_tf_utils.py", line 979, in load_tf_weights_from_h5
    raise e
  File "/usr/local/lib/python3.9/site-packages/transformers/modeling_tf_utils.py", line 971, in load_tf_weights_from_h5
    array = np.reshape(saved_weight_value, K.int_shape(symbolic_weight))
  File "<__array_function__ internals>", line 5, in reshape
  File "/usr/local/lib/python3.9/site-packages/numpy/core/fromnumeric.py", line 299, in reshape
    return _wrapfunc(a, 'reshape', newshape, order=order)
  File "/usr/local/lib/python3.9/site-packages/numpy/core/fromnumeric.py", line 58, in _wrapfunc
    return bound(*args, **kwds)
ValueError: cannot reshape array of size 921600 into shape (768,2)

921600 seems to be 768 * 1200.
Is there somewhere else I can get the pretrained model :)?
Thank you for your help.
Kind regards,

For me the solution was to execute this ( clone your environment to make sure you keep a backup):
pip uninstall -y tensorflow && pip install tensorflow==2.0
pip uninstall -y transformers && pip install transformers==2.4.1
pip uninstall -y h5py && pip install h5py==2.10.0

Yes it works!
I got the latest tensorflow version and it works, so I guess it was either transformers or h5py.
Thank you.

Hey guys,
about the ValueError: cannot reshape array of size 921600 into shape (768,2) problem. It seems that the configuration file clashes because of the following lines:
"id2label": {
  "0": "LABEL_0",
  "1": "LABEL_1"
},

I removed them, reinstalled all packages at the latest versions and it loads the model fine :).
Si DeepStyle works with latest packages version which is fine if you need to integrate it inside an existing project as a loss function for instance.
Thanks again for the work.
B.


Update DNS: miekg/dns post release 1.1.14

https://github.com/miekg/dns/commit/ee62c8b0866df3cc788d181485c483bf46808a00
CC @cmonr

Did those also come in with the miekg/dns package update?

Yup, those are dependencies from dns package https://github.com/miekg/dns/tree/master/vendor/golang.org/x

It will be great to have some nice way of linking to packages, instead of adding them to git. We cannot track the changes/commits  :-(

@cmonr - Will hold merge for this, till we confirm with @edhemphill and test it somehow

@deepikabhavnani There's a low-priority task that I have to update maestro's dependency mgmt to using go modules, which should aleviate weirdness with this kind of update (where we update the parent repo and the version in the /vendor folder), but no eta on when it would get done.

@SenRamakri @edhemphill Thoughts on bringing this in for RC2?

@cmonr  https://github.com/PelionIoT/maestro/pull/119 seems to do do that, @costanic did it.

@cmonr  https://github.com/PelionIoT/maestro/pull/119 seems to do do that, @costanic did it.

https://github.com/PelionIoT/maestro/pull/119 was not merged @mray190 any further info on the closing?


New ‘ModuleNotFoundError’

Hi, until recently I could run this via a Google Colab notebook (with timm 0.6.13 and torch 2.0.1 to avoid other errors), but today running the following cell:
%cd /content/MiDaS/
!python run.py --model_type dpt_beit_large_512 --input_path input --output_path output

Produces the error output below:
/content/MiDaS
Traceback (most recent call last):
  File "/content/MiDaS/run.py", line 14, in <module>
    from midas.model_loader import default_models, load_model
  File "/content/MiDaS/midas/model_loader.py", line 4, in <module>
    from midas.dpt_depth import DPTDepthModel
  File "/content/MiDaS/midas/dpt_depth.py", line 5, in <module>
    from .blocks import (
  File "/content/MiDaS/midas/blocks.py", line 4, in <module>
    from .backbones.beit import (
  File "/content/MiDaS/midas/backbones/beit.py", line 1, in <module>
    import timm
  File "/usr/local/lib/python3.10/dist-packages/timm/__init__.py", line 2, in <module>
    from .models import create_model, list_models, is_model, list_modules, model_entrypoint, \
  File "/usr/local/lib/python3.10/dist-packages/timm/models/__init__.py", line 1, in <module>
    from .beit import *
  File "/usr/local/lib/python3.10/dist-packages/timm/models/beit.py", line 49, in <module>
    from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  File "/usr/local/lib/python3.10/dist-packages/timm/data/__init__.py", line 5, in <module>
    from .dataset import ImageDataset, IterableImageDataset, AugMixDataset
  File "/usr/local/lib/python3.10/dist-packages/timm/data/dataset.py", line 12, in <module>
    from .parsers import create_parser
  File "/usr/local/lib/python3.10/dist-packages/timm/data/parsers/__init__.py", line 1, in <module>
    from .parser_factory import create_parser
  File "/usr/local/lib/python3.10/dist-packages/timm/data/parsers/parser_factory.py", line 3, in <module>
    from .parser_image_folder import ParserImageFolder
  File "/usr/local/lib/python3.10/dist-packages/timm/data/parsers/parser_image_folder.py", line 11, in <module>
    from timm.utils.misc import natural_key
  File "/usr/local/lib/python3.10/dist-packages/timm/utils/__init__.py", line 2, in <module>
    from .checkpoint_saver import CheckpointSaver
  File "/usr/local/lib/python3.10/dist-packages/timm/utils/checkpoint_saver.py", line 15, in <module>
    from .model import unwrap_model, get_state_dict
  File "/usr/local/lib/python3.10/dist-packages/timm/utils/model.py", line 8, in <module>
    from torchvision.ops.misc import FrozenBatchNorm2d
  File "/usr/local/lib/python3.10/dist-packages/torchvision/__init__.py", line 6, in <module>
    from torchvision import _meta_registrations, datasets, io, models, ops, transforms, utils
  File "/usr/local/lib/python3.10/dist-packages/torchvision/_meta_registrations.py", line 4, in <module>
    import torch._custom_ops
ModuleNotFoundError: No module named 'torch._custom_ops'

Through experimentation, I find that deleting references to ‘torch._custom_ops' in the _meta_registrations.py file allows MiDaS to run, but obviously this is not the most correct fix. Any advice for a better solution? Thank you!

It's hard to say for sure, but I would guess this has to do with the libraries being updated, possibly by some other project. Based on the pathing of the libraries in the error message (e.g. /usr/local/lib/python3.10/dist-packages/...) all of the libraries are installed in the base system copy of python, which means they can get modified by system updates (since the operating system also uses this copy of python) and potentially other projects which try to use the same python.
The general solution for this is to use virtual environments, either through python itself (using venv) or something like conda. These act like dedicated sandboxes where you'd install all of the libraries for a single project in one place, which only gets used by that one project, and therefore won't be affected by updates to other projects (which should have their own separate environments).
(unrelated) Also, since you're using beit, I figured I'd mention that there there are improved models available that might be worth checking out. One is called Depth-Anything (specifically the vit-large model) and another much higher quality (but very slow to run) model called Marigold.


Allow public resource to be part of collection resource

Pull Request Checklist:

[x] Positive Test Case Written by Dev

[ ] Automated Testing

[ ] Sufficient User and Developer Documentation

[ ] Passing Jenkins Build

[ ] Peer Code review and approval

Positive Test Case

Create a collection resource.
Create a composite resource for which the owner is different from the collection resource. Set the composite resource to 'public'.
Edit the collection resource to add the composite resource to that collection. Verify that you are able to add the public composite resource to the collection.

METRIC
VALUE

NEW SECURITY HOTSPOTS
0

NEW DUPLICATED LINES DENSITY
0.0

NEW CODE SMELLS
1

NEW BUGS
0

NEW VULNERABILITIES
0

https://sonarqube.cuahsi-workstation.com:9000/dashboard?id=hydroshare-3981


Add Raku simple/optmized ; test.sh and benchmark.py edited for Raku

A simple and optimized version for Raku. On my computer (i56200u, 8Go, Fedora 33, Rakudo 2021.02) is slow with the simple version around ~30s and the optimized ~16s. Maybe it is a bit too slow to be added to the benchmark script.
The optimized one do not drop to nqp.

Yeah, I think this is too slow for inclusion at the moment. I wonder why? Perl is quite fast. Additionally, my version of Rakudo that came with apt install rakudo (which is fairly old, 2019.11) doesn't recognize BagHash. Will close for now -- feel free to reopen if there's something we're doing wrong that's easily fixable.

Thanks for the feedback !
Concerning the performance issue, the comparison with base Perl is unfair to Raku as it brings a full 00 and meta-programming system with it hence the start-up cost. A fair comparison would be to bring one of the big OO lib (Moose or other) with Perl. A member of the irc chat #raku tested quickly the script on more modern hardware (ryzen cpu 3700 or 4700) and had the time cut in half.
The raku version in the apt repo is super old (Rakudo, the compiler/VM behind Raku is a fast moving target and performance enhancement happens at each iteration). I would advise to use rakudo-pkg with up-to-date stable version of Rakudo already pre-compiled and packaged for most distro : here a link for the instructions for Debian/Ubuntu systems.
For making it run, grabbing the latest rakudo (2021.02) from rakudo-pkg is the easiest fixable thing to do.
I don't think that the simple version can be improved but I can look more at the optimized version if I can do more¹. Is it fair game to drop to nqp, it is a bit like using a bit of inline assembly in C (kind of)?
¹ Most of the time is passed in the AT-KEY method that extract the value from the Hash, I will keep looking how it could be possible to work around that but not sure to find something.

Even at twice as fast (simple at 15 seconds) it's still almost as slow as the O(N log N) shell version, which takes 16 seconds. Can you let me know what the performance numbers are for you, for the latest version of Rakudo vs Python 3 (I'm on 3.8), for simple and optimized? That will give me a comparison point, and then I'll make a call as to whether I think it's fast enough for inclusion. If it's significantly faster than the shell version, I'll install the latest Rakudo and include it.

On Fedora 33 with Python 3.9.2 / Rakudo 2021.02, running benchmark.py with only grep, wc, python and raku, here are the results on my laptop :
Language      | Simple | Optimized | Notes
------------- | ------ | --------- | -----
`grep`        |   0.07 |      0.06 | `grep` baseline; optimized sets `LC_ALL=C`
`wc -w`       |   0.30 |      0.41 | `wc` baseline; optimized sets `LC_ALL=C`
Python        |   2.72 |      2.01 |
Raku          |  25.16 |     13.96 | by notagoodidea

Thanks! I just think this is "not a good idea". :-) In other words, I think it's too slow to include in the benchmarks. It's 10x as slow as Python, and still significantly slower than the shell version. Sorry about that, and thanks anyway for the contribution.

Haha, yep, totally understand. Thanks for taking the time to review the PR and setting up this multi-language comparison!


Import/Export field not displaying well.

Thanks for this amazing admin template theme. I encountered an issue with the display of my import/export field. The drop-down menu is not formatted well. I am using Django 4.2 and have added a snapshot of my admin.py below. I will appreciate a pointer on what I am doing wrong.
from import_export import resources
from import_export.admin import ImportExportModelAdmin
from unfold.admin import ModelAdmin

class CustomResource(resources.ModelResource):

    class Meta:
        model = MyModel
        skip_unchanged = True
        report_skipped = True
        exclude = [...]
        import_id_fields = [...]
        export_id_fields = [...]

class TestAdmin(ModelAdmin, ImportExportModelAdmin):
    resource_class = CustomResource
    ...
    ...

You are missing second step from the link below (import_form_class and export_form_class)
https://github.com/unfoldadmin/django-unfold?tab=readme-ov-file#django-import-export

I do have the classes and it still doesn't work. Any help??


The length of each receiving of UART

I'm going to use android things to implement the modbus protocol，But I've found that when android things receives a piece of data, it's automatically divided into many segments. Is there any way to get it to be done like a single chip?

This seems similar to #4. I'll copy my response there.
In general, you should expect UART data to come in intermittently. Although it may stream continually, the interrupts may be fired at any point. You should buffer the data and determine the stop point on your own, then process it.
Generally, embedded engineers will do several different steps to properly segment the data:
Use a fixed size, ie. assume every packet is 3 bytes
Send a fixed-size header which contains information about the data such as the total length and perhaps error correction information
Send the length of the packet as the first byte, allowing the receiver to count that many bytes (with a max of 255 characters)
Send a stop character at the end of your data transmission, ie. 0x00. This is more useful if you're sending strings. Many systems append a null character at the end of strings internally to denote that you have reached the end.

Thanks for your answer!
The modbus protocol does not have a starting character , a stop character , or a character that represents length , We can only be judged by time interval.
I tried to use TimerTask to make judgments, but because I was a beginner, there were occasional array overflows

Maybe you can use an ArrayList and convert that to a buffer after?
Is there any sort of expectation you can make about the data? When I've used Modbus, there have been certain types of expected payloads that made it easier to implement.

Thanks again,My mind is still stuck on C. I'll try to use arraylist.
I don't quite understand what you mean by "expected payloads".
Is it the java library that implements the modbus？

If I'm talking from Android Things to a Modbus peripheral, or vice-versa, there should be some established protocol of the types of messages being sent. You should be able to use that protocol in order to find when to do the cut-off.

I think I see what you mean，like GPS protocol，
I found out $GPGGA，I began to process the data.
but the modbus protocol have no specific start characters.
I can only judge by time，So I need to get a full frame to process.

If there's no way to judge with start/end characters, you may be able to log the timestamp of each UART event and split it that way.

OK, I will try to do this and thanks for your kind help


Managed Ingestion does not add requisite Oracle Libraries to Datahub Actions

Describe the bug
Running UI ingestion for an Oracle instance fails with:
Cannot locate a 64-bit Oracle Client library: "libclntsh.so: cannot open shared '
           'object file: No such file or directory"

To Reproduce
Steps to reproduce the behavior:

Set up an Oracle Database
Run ingestion for this database through the UI

Expected behavior
Ingestion should complete successfully
Desktop (please complete the following information):
N/A
Additional context
Slack Thread

In order to solve this, we'll need to modify the datahub-action Dockerfile to install the Oracle instant client - not sure we want that sort of bloat for everyone to solve this specific issue. Thoughts?

I have encountered similar problems posted #4514. Our technicians tried to rely on local updates and found it very difficult to achieve:( hope u guys give some suggestions and solutions. THX a lot!

@Amanda-Chgar Were you able to make progress using the CLI alone? If not please ping us on Slack

This should be fixed in https://github.com/acryldata/datahub-actions/pull/24


Issue 596: Add profiler path to configuration

Step 1

Added profiler_path_ member variable to AdminImpl class. Allows profiler path to be configurable rather than hard coded.
Return Http::Code::BadRequest when call to Cpu::startProfiler(...) fails.

Step 2 (TO DO)

Update admin profiler_path JSON configuration

Issue link: https://github.com/lyft/envoy/issues/596
@htuch for comments.

@hennna please sign CLA if you didn't already.

@mattklein123 just signed CLA


Implement functionality for Chapter 1, Homework 5

Add functionality to ArrayOperations methods.

Can't believe I didn't think of reusing those methods! I've made all the recommended changes.


Can't install pkgs.plasma5Packages.kdeGear

Issue description
When I try to put "plasma5Packages.kdeGear" in the pkgs entry in /etc/nixos/configuration.nix the fails with the error:

unpacking channels...
building Nix...
building the system configuration...
error: A definition for option environment.systemPackages."[definition 1-entry 12]"' is not of type package'. Definition values:
- In `/etc/nixos/configuration.nix':
{
akonadi = <derivation /nix/store/g1x8n30i0342yzbqjg83xzck25jr2xgg-akonadi-22.08.3.drv>;
akonadi-calendar = <derivation /nix/store/zid41z6dbyq9j5mkg0q58n7xmpawhkz0-akonadi-calendar-22.08.3.drv>;
akonadi-calendar-tools = <derivation /nix/store/l6zfyck3yxmc623rs3cq872nnhqrjwqk-akonadi-calendar-tools-22.08.3.drv>;
akonadi-contacts = <derivation /nix/store/jqb26z0fd572haxkdr4sm1h7r5c7wglx-akonadi-contacts-22.08.3.drv>;
...
(use '--show-trace' to show detailed location information)

Steps to reproduce
Put pkgs.plasma5Packages.kdeGear in /etc/nixos/configuration.nix and rebuild
Technical details

system: "x86_64-linux"
host os: Linux 6.0.9, NixOS, 23.05 (Stoat), 23.05pre429553.5dc7114b7b2
multi-user?: yes
sandbox: yes
version: nix-env (Nix) 2.11.0
channels(louis): ""
channels(root): "nixos"
nixpkgs: /nix/var/nix/profiles/per-user/root/channels/nixos

Well, pkgs.plasma5Packages.kdeGear is not a package, but an attrSet of derivations (and the the override function).
The following should do:
environment.systemPackages = with pkgs; [ firefox emacs sl ]
    ++ (with lib; attrValues (filterAttrs (const isDerivation) pkgs.plasma5Packages.kdeGear));


[Feature] Scroll back button for the about us section

Description
I would like to work on adding a Scroll back button for the about us section
Screenshots
No response
Checklist

[X] I have checked the existing issues.
[X] I have read the Code Of Conduct
[X] The changes don't break the code
[X] Please attach the screenshots and video of the development work once it is done

/assign


johnsnowlabs embeddings support

Description: Introducing the JohnSnowLabsEmbeddings
Dependencies: johnsnowlabs
Tag maintainer: @C-K-Loan
Twitter handle: https://twitter.com/JohnSnowLabs https://twitter.com/ChristianKasimL

@Bagatur could you review this please?

apologies for the delay, thank you @C-K-Loan!


Unload HLJS

In the docs there is,
 hljs.highlightBlock(block);
but how do I unload HLJS?
If HLJS retains a reference to the node then this might cause memory leaks.
I've checked the global var and there's no obvious methods for unloading.

Can you give a specific example of where there would be a memory leak in the source?  Would setting the hljs variable itself to null not mark everything for  GC?

I can't give a specific example, but mostly I'm looking for an API either like unhighlightBlock or guidance (and perhaps a docs update) that HLJS doesn't maintain any DOM references after highlightBlock is run.

My understanding is that setting the global hljs variable to null wouldn't remove any DOM references within the library.

Well, if that was the only reference to the main HLJS object why wouldn't it be available for GC at that point?

The relevant code (for the HTML stuff) is pretty short.  I think you could review it by eye for leaks if you are really paranoid... but from where I sat it doesn't do anything "bad" regarding memory or references.
The only "state" that sticks around long-term is the compiled languages (which is a big collection of compiled regular expressions).  You could use the listLanguages and getLanguage API after the fact in a tight loop if you wanted to null those for some reason.

It's a huge closure, AFAICT there's only 50 LOC or so to audit... there are no this. references... So you only have to look at the actual top-level places it touches the DOM.  I count two.

Do you have a link or more info on the type of leak you're afraid of?  Or an example of another library providing this sort of "guidance ... that ... doesn't maintain any DOM references after"...
I wasn't aware that's a thing that needs to be explicitly stated. :-)  If it's a pretty common practice I'd imagine it'd be reasonable to add something to the docs along those lines.

Closing because of inactivity.
Summary: We behave well (as well as another other library) to the best of my knowledge from a simple reading of the code.  I don't see any need to say that in the docs unless there is a pattern of other libraries saying it.  If so I'd love to see examples and then we'd probably welcome a PR if that was actually the case.


Update links in all studies table

At the moment, the links in the Study column go to separate study pages rather than the ones in the EDA and the links in the Searches column go to the WDK system rather than the EDA. Both need to be updated.

Additionally:

Rename "searches" column to "Explore & analyze"
reorder the columns:

1st column: "Study"
2nd column: "Explore & analyze"

These issues were fixed by https://github.com/VEuPathDB/EbrcModelCommon/pull/8 and https://github.com/VEuPathDB/EbrcWebsiteCommon/pull/69

The following studies when spot checked confirmed correct functionality: GAMIN RCT, PRISM 2 ICMR Border Cohort and SCORE Rwanda. The columns names have been updated and ordered correctly.


[🧹 CHORE]: Upgrade google/common-protos in roadrunner-php/grpc

No duplicates 🥲.

[X] I have searched for a similar issue.

What should be improved or cleaned up?
The new major version of google/common-protos was released in May: https://github.com/googleapis/common-protos-php/releases/tag/v4.0.0
Can we please upgrade spiral/roadrunner-grpc to support this version?

Done https://github.com/roadrunner-php/grpc/releases/tag/3.1.0


Make union sq zones to be single source

Summary of changes
Initially these sign zones were set up with having two sources for predictions. For one, we aren't giving predictions on GLX yet, and having two sources configured causes the headway messages for a sign to omit the headway direction. For example, the sign would show "Trains every 5 to 7 min" instead of "Heath St trains every 5 to 7 min.
This change updates the Union Sq zones to be single sourced so that they include "Heath St" for headway messages. We should be sure to loop back around to this and reconfigure the signs once we understand how predictions will be provided for this stop.

good call! I will do that now before merging


Not cloning object getters and setters as expected

The following tests should not fail:
 it('should clone a getter', () => {
   const input = {
     a: 2,
     get foo() {
       return this.a * 2
     }
   }
   let clone = func(input)
   assert.ok(clone.foo === 4)
   assert.ok(
     typeof Object.getOwnPropertyDescriptor(clone, 'foo').get === 'function'
   )
 })

it('should clone a setter', () => {
   const input = {
     set foo(val) {
       this.a = val
     }
   }
   let clone = func(input)
   clone.foo('bar')
   assert.ok(clone.a === 'bar')
   assert.ok(input.a === undefined)
   assert.ok(
     typeof Object.getOwnPropertyDescriptor(clone, 'foo').set === 'function'
   )
 })

This lib was written back when these methods did not exist (I believe).
I don't have time to actively maintain it. So you might want to look for alternatives that support this.

could also be worth mentioning that there also is a built in structuredClone() that do also support getters.


[Feature Request] Reduce required surface area of mock client

Right now the ServerGatewayApis trait is too broad. Core only needs a subset of the functionality internally, and what it requires there is the actual surface area that should be mocked.
The trait should be split up into sub-traits, and only the sub-trait that Core makes use of needs to be mocked. This would allow for more easily extending the client without needing to go pointlessly update mocks.
A long time ago we made the decision that we wanted to accept simpler parameters rather than the raw protos, too. This may be a good time to revisit that. The client meant for end-user consumption can wrap the traits which can operate in terms of the raw protos.

@Sushisource - There are a couple use cases of that gRPC client - for core's internal and for caller use. I think it makes plenty of sense to have a core-specific idiomatic client API trait w/ your own params and limited surface (though often the proto params are good enough here like they are for other core calls).
But, where you instantiate this higher-level client backed by gRPC, I think we need a way to still get the raw gRPC trait from there (or maybe the raw gRPC client is what is provided, but it's better to have the high-level client "close"/"drop" handle closing the gRPC conn). So yeah, a Client trait with what core needs and a runtime gRPC-based impl in a struct which provides access to the pure gRPC client iface would be nice.
I'm half-tempted to tell new SDK clients not to communicate with gRPC directly but always use the core client just to keep config and connection count centralized (becomes a big deal on gRPC load balancing, cert mgmt, etc). But that's a different topic for a different day.


⚠ GitLab Server has degraded performance

In 305d2ae, GitLab Server (https://gitlab01.its-telekom.eu) experienced degraded performance:

HTTP code: 200
Response time: 12296 ms

Resolved: GitLab Server performance has improved in 6094438.


UpdateAsync results in Unable to cast object of type 'Microsoft.EntityFrameworkCore.Query.Internal.InMemoryQueryContextFactory' ...

Hello, I have an issue when unit testing my code the exception happens during the UpdaAsync call
using (var context = _checkoutContextFactory.Create())
            {
                await context.Baskets
                    .Where(t => t.OrderId == orderId && t.OrderId != null)
                    .UpdateAsync(t => new Models.BasketStoreContainer { OverallPaymentStatus = paymentStatus });
            }

this is how I create test context
var builder = new DbContextOptionsBuilder<CheckoutContext>();

builder.UseInMemoryDatabase();
var checkoutContext = new CheckoutContext(builder.Options);
BatchDeleteManager.InMemoryDbContextFactory = () => new CheckoutContext(builder.Options);
return checkoutContext;

And this is call stack of exception
Unable to cast object of type 'Microsoft.EntityFrameworkCore.Query.Internal.InMemoryQueryContextFactory' to type 'Microsoft.EntityFrameworkCore.Query.Internal.RelationalQueryContextFactory'.
   at Z.EntityFramework.Plus.InternalExtensions.GetDbContext[T](IQueryable`1 source)
   at Z.EntityFramework.Plus.BatchUpdate.Execute[T](IQueryable`1 query, Expression`1 updateFactory)
   at System.Threading.Tasks.Task`1.InnerInvoke()
   at System.Threading.Tasks.Task.Execute()
--- End of stack trace from previous location where exception was thrown ---
   at System.Runtime.CompilerServices.TaskAwaiter.ThrowForNonSuccess(Task task)
   at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)
   at System.Runtime.CompilerServices.TaskAwaiter`1.GetResult()

Hello @vmachacek ,
The v1.4.41 has been released.
We released the first version to try to support this features.
Could you test it and let us know if that's working?
Note: You need to specify a context factory to make it work.
Example:
BatchUpdateManager.InMemoryDbContextFactory = () => new MyContext(db.Options);

int value = 24234;
_context.Foos.Where(x => x.ColumnInt < 10).Update(foo => new Foo {Name = foo.Name + "2", T2 = value } );

Hello @vmachacek ,
I will close this issue. Feel free to re-open it if you still have the bug.
Best Regards,
Jonathan

Hello @JonathanMagnan!
BatchUpdateManager.InMemoryDbContextFactory is implemented as static.
Could you implement per instance?
I have tests running in parallel and using diferents contexts, so InMemoryDbContextFactory changes at the middle of the execution...
Tell me if I wasn't clear to explain my problem.
Thanks in advance.


android example solutions for selfie-segmentation

Could you please provide an example solution for selfie-segmentation. Currently only facedetection, facemesh, hands. I really need selfie-segmentation example solution, please

Hi @GreenVegetables, We have Android examples implementation for selfie-segmentation as mentioned here.
You can build and run Android examples by targeting the following path in the Android Studio:
mediapipe/examples/android/src/java/com/google/mediapipe/apps/selfiesegmentationgpu/BUILD
Please refer this issue #3453  (comment) for more information.
Thank you!

Hello @kuaashish
I have used the AAR of selfie-segmentation in my project and it is working fine. All contents of the package com.google.mediapipe are included in the AAR. like this:

At the same time, I want to use facemesh with solution api way. In build.gradle, I added
implementation("com.google.mediapipe:solution-core:<IP_ADDRESS>-alpha-1")
implementation("com.google.mediapipe:facemesh:<IP_ADDRESS>-alpha-1")

When I run the project, it reports an error like this:

Because the solution-core dependencies also contain these：

How can I use selfie-segmentation and facemesh at the same time. please help me. thanks

Hi @GreenVegetables, Could you just open another issue with the second question to use two MediaPipe solutions at the same time. Thank you!

Hi @kuaashish
I opened a new issue, it's here

Hi @GreenVegetables, Thanks for raising a separate issue for another query. Can we move this issue to close status as resolved and following #3472.
Thank you!

Hi @kuaashish , Thanks for following up and responding to my question. I will close this issue.


nucleo_h745zi_q add fdcan1

add fdcan1, fdcan2 and usb_fs DT configurations

Thanks for the contribution, please also fix CI.

I've updated my PR and fixed CI. There is only one open point regarding fdcan1 status. Please take a look on it in corresponding conversation above.

@erwango @FRASTM it shall be ready now. Please take a look on it.


feat(examples): ido sniper

Description
Example of a dummy IDO Sniper

Solution

Current dependencies on/for this PR:

master

PR #2

PR #3   👈

This stack of pull requests is managed by Graphite.


npm run build 后，打包后的代码在一些浏览器上报错，比如，promise is not defined 求大神解决

You need at least node v4. Node v6 is recommended


who instantiates the templates in ADSREnvelope.cpp?

It's a templated class, but the definitions are all in ADSREnvelope.cpp.
I've seen templates the normal way, where they are defined in the .h
I've also seen explicit instantiation used to make this kind of cpp file thing work, like:
template class ADSREnvelope;
template class ADSREnvelope;
But I've never seen a template instantiated the way it is in sfizz. How does this work?

It's called explicit template instantiation, and it's a trick for saving compilation time in some cases.
https://docs.microsoft.com/en-us/cpp/cpp/explicit-instantiation
In our case though, it's not really useful, probably more an artifact from older versions.
We really need float only, so it can be changed into a normal class. I will do probably at some point later.

It's called explicit template instantiation, and it's a trick for saving compilation time in some cases.
https://docs.microsoft.com/en-us/cpp/cpp/explicit-instantiation
In our case though, it's not really useful, probably more an artifact from older versions.
We really need float only, so it can be changed into a normal class. I will do probably at some point later.

yes, you can see I mentioned explicit template instantiation in my original question. I was unable to find the point at which that was done. Doing directly in the defining c++ file would make it clearer, and less easy to make linker errors like I did.
thanks.

yes, you can see I mentioned explicit template instantiation in my original question. I was unable to find the point at which that was done. Doing directly in the defining c++ file would make it clearer, and less easy to make linker errors like I did.
thanks.