custom title and description of physical web notification

Hello
Currently in a physical web notification, we get the default page title and meta description.
If we could change this data to a custom notification style data, then it would add up to more relevancy to a physical web notification.
How can we do it?
My Suggestion 1:
» In eddystone UUID, we register the beacon on google cloud console with proximity beacon API and then add attachment to it.
» The attachment is thus retrieved by the app using nearby messages API.
A similar thing can be done in case of physical web.
» We add the URL in a beacon in Google cloud and also add the custom title and description associated with it.
» when a smart phone comes near a beacon broadcasting a URL, it will fetch this particular title and description and give it as an output.
My Suggestion 2:
» We take up few bytes from the eddystone protocol specification and use them to store the title and description.

There are two separate issues here: 1) Getting the new notification data and 2) Presenting it
There are numerous ways of getting the data. One our core principles on the Physical Web team is to "use the web whenever possible" so we'd prefer having the notification data come from the web page itself. We could, for example, use JSON+LD (there are other approaches we could debate of course)
The real issue is what you'd like actually show the user. Right now there is a single notification that takes you to a list of items. Are you suggesting that some items display differently from others? Or are you suggesting that some items have their own notification (separate from the one from Chrome?) Both have issues to discuss.
I guess I'd like to know what you're trying to do with this new notification system. Is it just a layout difference or are you trying to get a different behavior? For example, if you'd like to have your own notification (outside of the chrome one) that could easily be abused to create 'notification spam' for the user. I realize we're pretty conservative when it comes to notifying the user but we feel we must. If this gets irritating, we're going to loose users trust.
Scott

Hello Scott
Please allow me to convey my message in a better way.
For example, I am transmitting www.starbucks.com
http://www.starbucks.com as the URL.
My phone looks for physical web pages and say it detects www.starbucks.com
and shows it to me in my physical web present in my chrome.
As a user, this is how it will appear to me presently
[image: Inline images 2]
» Now this does not convey much information to me.
» The text "Order while you wait" has been taken from the metadata
description of the page( as far as I know) and the title *"Starbucks" *has
been taken from the title tag.
Now, say if I can custom define these parameters, for example like this
[image: Inline images 3]
Here, I custom defined the text of the same starbucks URL that my phone's
physical web scanned for.
This adds for relevancy to the URL. A user gets a clear message. Also, it
allows the stores to convey an effective contextual message.
Are we thinking on these lines? Don't you think it will add more meaning to
physical web
Abhishek Kanodia
Under Graduate Student
BITS Pilani
On 23 February 2016 at 12:51, scottjenson<EMAIL_ADDRESS>wrote:

There are two separate issues here: 1) Getting the new notification data
and 2) Presenting it
There are numerous ways of getting the data. One our core principles on
the Physical Web team is to "use the web whenever possible" so we'd prefer
having the notification data come from the web page itself. We could, for
example, use JSON+LD (there are other approaches we could debate of course)
The real issue is what you'd like actually show the user. Right now there
is a single notification that takes you to a list of items. Are you
suggesting that some items display differently from others? Or are you
suggesting that some items have their own notification (separate from the
one from Chrome?) Both have issues to discuss.
I guess I'd like to know what you're trying to do with this new
notification system. Is it just a layout difference or are you trying to
get a different behavior? For example, if you'd like to have your own
notification (outside of the chrome one) that could easily be abused to
create 'notification spam' for the user. I realize we're pretty
conservative when it comes to notifying the user but we feel we must. If
this gets irritating, we're going to loose users trust.
Scott
—
Reply to this email directly or view it on GitHub
https://github.com/google/physical-web/issues/595#issuecomment-187578737
.

Unfortunately your images didn't come throught. However, in an attempt to keep the conversation going, help me understand. Do you just want to have more control over the Title/description text? If so, you can do that in the web page itself so you have full control. Do you want to offer something other than text  (e.g. HTML)? If so, it's not clear what you want.

Hello Scott
Please allow me to convey my message in a better way.
For example, I am transmitting www.starbucks.com as the URL.
My phone looks for physical web pages and say it detects www.starbucks.com and shows it to me in my physical web present in my chrome.
As a user, this is how it will appear to me presently

» Now this does not convey much information to me.
» The text "Order while you wait" has been taken from the metadata description of the page( as far as I know) and the title "Starbucks" has been taken from the title tag.
Now, say if I can custom define these parameters, for example like this

Here, I custom defined the text of the same starbucks URL that my phone's physical web scanned for.
This adds for relevancy to the URL. A user gets a clear message. Also, it allows the stores to convey an effective contextual message.
Are we thinking on these lines? Don't you think it will add more meaning to physical web

Sorry but I don't understand why you can't do this with the existing approach. Just change the title of the page or the description field, you can place any text there you wish. You can even dynamically change the values (it will take a few minutes before the cache gets old but you can easily change the value many times per day)

Thank You scott. I agree with the current solution.
The only concern that I have is, will this information change instantly.
I was under the impression that it may take days for this information to
crawl as what happens in googlw web master.
If we update the meta data, google webmaster tool takes time to crawl and
update the results in google search.
So I thought this would be the same in case of physical web
On 23-Feb-2016 5:26 pm, "scottjenson"<EMAIL_ADDRESS>wrote:

Sorry but I don't understand why you can't do this with the existing
approach. Just change the title of the page or the description field, you
can place any text there you wish. You can even dynamically change the
values (it will take a few minutes before the cache gets old but you can
easily change the value many times per day)
—
Reply to this email directly or view it on GitHub
https://github.com/google/physical-web/issues/595#issuecomment-187670189
.

No, our version of the Physical Web keeps it's own cache and updates after about 5 minutes. This will likely change as we evolve the product. We already have people putting URL Shortened URLs into their beacons which point to a redirector. This allows them to use one beacon in the morning and one in the afternoon.

Dear all
I would like ask yours if you could anwers to this question (apologices for my English)
Could I use a URL pinting to a dynamic HTML page (or even .pHP page) in the way each we could change the page metadata for each request of the PWS?
Thanks in advance

The issue is simply one of overhead for the PWS. At the moment, it is best of think of the URL as fairly static. This allows the values to be cached. However, we don't cache them forever and people have had some luck with URLs in the morning on others in the afternoon. However, to get the freshness down to minutes (or in your case every refresh would, in effect, require loading your web page for every single user request. Not only does this hammer our server but it significantly delays the UX (as everything has to wait until the PWS gets the full page and parses it.
We appreciate how cool it would be if the PWS were fully dynamic but that requires enormous server power at a scale so we're using some caching to make this work reliable and quickly.

Kanodia How did you solve it? I have the same question

@EmmanuelSkapple : Contact me on mail.
I' LL  guide you through the solution

Hello,
I also need this custom title and custom description instead of webpage title and meta descritpion, but I don't know how this will solve.
Android alerts should be customize but its forcefully load default page title and meta description.
Any solution please. help ?????


Fix links in plugin doc which go to non-existant DSL pages

Go to existant javadoc instead.

@bot-gradle test BD

OK, I've already triggered the following builds for you:

BuildDistributions build

@bot-gradle test and merge

@bot-gradle test and merge

OK, I've already triggered a build for you.

@bot-gradle test and merge


The configuration passes incorrectly. Some packages are missing.

Configuration passes with some errors. Dependency errors and missing packages. Included in the file.
The ROS system does not work. I can run roscore, mavlink, etc.
Maverick 1.0 is rarely a lot of mistakes and incorrect dependencies key packages.
UBUNTU 16.04
Thanks ...
error.txt

Try running apt update before doing a configure - that's the cause of most of the errors in this logfile.

The ROS system does not work. I can run roscore, mavlink, etc.
Sweeping statement with no detail, gives nothing to look at.

Maverick 1.0 is rarely a lot of mistakes and incorrect dependencies key packages.
..

What system is this running on?  Was this bootstrapped from scratch, or a downloaded image?

Try running apt update before doing a configure - that's the cause of most of the errors in this logfile.

Yeah, I tried to do that. But at the same time there are some errors too. The file is attached.
config_log.txt
update_log.txt

I tried to install the system in different ways. the above log files are made on a virtual machine downloaded from this resource.

What system is this running on? Was this bootstrapped from scratch, or a downloaded image?

Yes, bootstrapped from scratch.
Downloaded image work well, but cannot configure. (maverick 1.0) Later I can give the log file.

Your ROS errors are because the ROS key was dumped due to a security issue (with the central ROS repo).  Fix the key like this:
https://answers.ros.org/question/325039/apt-update-fails-cannot-install-pkgs-key-not-working/
I'll try and add this in automatically to the manifests.

Оn another VMware system in Ubuntu 16.04 Maverick 2.0 from bootstrap. Other problems, but also there is a connection with ROS. "bash: /opt/ros/kinetic/setup.bash: No such file or directory".
Also in this system, in graphical mode, the configuration is abruptly interrupted and the system is rebooted, restarting gives nothing. Only switching to text mode (multi-user.target) allows you to complete the configuration. Interrupted log in attach.
Thanks ...
config_log.txt

Same system, but in text mode. Configuration log.
config_log_text_mode.txt

Maverick 2.0 is really in alpha status, if you're expecting a smooth experience then it's not for you :)
It's long overdue, I've just started working on trying to get a beta release out soonish

Maverick 2.0 is really in alpha status, if you're expecting a smooth experience then it's not for you :)
It's long overdue, I've just started working on trying to get a beta release out soonish

Before version 2.0 I had 3 days to install 1.0. I ran into a lot of problems ... Decided to try 2.0 and became something goes. Thanks for your help.
I now try to return to the stable version.
Maybe my job will help ...

v1 - the current stable (think 1.1.6 is the latest) branch should be pretty stable, lots of people have used this version.  Try starting with this and address each problem step by step.  If you can, log into gitter channel as we can help you in realtime there.
https://gitter.im/goodrobots/maverick

Various fixes applied to stable branch to fix repos/packages referenced by 1.1.6 that have since changed.


Fix  command-line-tools-reference errors

Hello K8S Community !
This PR corrects some errors in the "command-line-tools-reference".
Some CLI args were wrong, so i corrected it.  ("_" separator was used instead of "-")
Have a nice day :)

Hi @kbarnard10
/assign @kbarnard10

@tengqm Did the rendering of the flags change?

@kbhawkey I'm checking.

@kbhawkey The generator fix is proposed https://github.com/kubernetes-sigs/reference-docs/pull/231, with regenerated reference proposed https://github.com/kubernetes/website/pull/27817.

@pierreilki , Thanks for opening this PR. 😃
The files are generated by a docs tool and should be regenerated by the tool (after the tool is updated).

Hi all,
I see that the files have been generated by regenerated by the tool generator. So i close this PR. Thanks !


Array.tabulate(2)(i => i) fails to compile.

This is the bug that makes partest run/vector1.scala crash.

[error] ReferenceError: arg1 is not defined
[error]     at $c_Lhelloworld_HelloWorld$.main__V (/Users/nastucki/GitHub/scala-js/examples/helloworld/target/scala-2.11/file:/Users/nastucki/GitHub/scala-js/scalalib/overrides/scala/Array.scala:345:5)
[error]     at $c_Lhelloworld_HelloWorld$.$$js$exported$meth$main__O (/Users/nastucki/GitHub/scala-js/examples/helloworld/target/scala-2.11/file:/Users/nastucki/GitHub/scala-js/library/src/main/scala/scala/scalajs/js/JSApp.scala:18:4)
[error]     at $c_Lhelloworld_HelloWorld$.main (/Users/nastucki/GitHub/scala-js/examples/helloworld/target/scala-2.11/file:/Users/nastucki/GitHub/scala-js/examples/helloworld/HelloWorld.scala:11:8)
[error]     at Object.<anonymous> (/Users/nastucki/GitHub/scala-js/examples/helloworld/target/scala-2.11/helloworld-launcher.js:2:86)
[error]     at Module._compile (module.js:413:34)
[error]     at Object.Module._extensions..js (module.js:422:10)
[error]     at Module.load (module.js:357:32)
[error]     at Function.Module._load (module.js:314:12)
[error]     at Module.require (module.js:367:17)
[error]     at require (internal/module.js:16:19)

@sjrd do you have some idea if which commit could have introduced this issue?

Does it fail to compile or run? This looks like a runtime failure.

I tried it in run.

@nicolasstucki I cannot reproduce on master (8ceb36b074508dcc7bb6da39b71bf20c43b4f35e), neither in 2.11.8 nor 2.12.0-M4. Maybe it was fixed "by chance" by #2458, in which case that would probably be because of https://github.com/scala-js/scala-js/pull/2458/files#diff-ce37eb8d8b260a77d05f1532255f5d4bR3909, despite my understanding that it shouldn't have been a problem before.

It's clearly a run-time error, but it can be considered as a JavaScript "compile" error, since it's using a variable that is not declared.

I rebased and it also works for me. run/vector1.scala also works after this fix.

Yep, and if I checkout 438ffee909d0144570768c79f7b7d48d98a3f780, I can reproduce.


is it possible to connect to an external MYSQL server for defectdojo?

I am struggling with the config on the docker-compose yml file to connect it to a remotely hosted mysql database. The reason being, if I want to install Dojo in Prod, I would like the data to persist even when the docker container isn't available.
Is defectdojo possible to connect to an external MySQL server?  your feedback would be great appreciate.
Thanks.

Hi @cymxiao - It's all the configuration for DefectDojo is through environment variables and those can be seen here, to set an external database export the variable: DD_DATABASE_HOST=yourexternalmysqlhost.


Cholesky decomposition to support complex values

Adds support for complex dtypes in cupy.linalg.cholesky. C.f. https://github.com/cupy/cupy/pull/2468.

@toslunar thanks for the comment. Do you want me to do that in a separate PR?

Noticed that random_matrix is only used for the Cholesky decomposition so I included the changes in this PR.

Removed both L20 and L38.

Jenkins, test this please.

Jenkins CI test (for commit 47b0a9006736d27bf4aac1aeb7a6dda90e8342da, target branch master) failed with status FAILURE.

For Jenkins failures see https://github.com/cupy/cupy/pull/2526#issuecomment-539075050.

Jenkins, test this please.

Jenkins CI test (for commit 47b0a9006736d27bf4aac1aeb7a6dda90e8342da, target branch master) succeeded!


Reliablity Issues with Kundera's Cassandra Implemention with non-trivial Amounts of Data

A paper was published in March 2015 at BTW 2015 in Hamburg entitled "Schemaless NoSQL Data Stores – Object-NoSQL Mappers the Rescue?", that in section 5.3 (page 17), documented one of the teams finding as follows:
Kundera returns correct results when processing 100,000 profiles with Query 4 on both MongoDB and Cassandra.
Yet on Cassandra, the same query returns a wrong number of results when processing
1,000,000 profiles.

Has this issue been identified? And resolved?
What performance/stress/scaleability testing has Kundera on Cassandra undergone to ensure that no similar problems exist in the current release?

@pluttrell
Kundera has yscb benchmark tests enabled which runs for a load of 100,000 profiles which returns the  results as expected.You can find out further details at

Test Case : CassandraYCSBTest.java

Workload configuration file : db-cassandra.properties

Chhavi

@pluttrell
Read through this paper, i wonder if that could be more specific about the queries giving inconsistent results with proper example could have been a great help to Kundera!
-Vivek

@mevivs
I wasn't sure if they had worked with the Kundera team on this problem or not. It doesn't appear as such. I'd recommend reaching out directly to them.
@chhavigangwal
The paper that I referenced, mentioning issues that appear in queries where the data in the underlying tables contain 1M records. As such problems like this might not be caught by tests against tables with only 100k records.


remove podpreset docs

PodPresets were removed in kuberenetes 1.20.  This updates the docs to remove references to them. I noticed several docs in non-english languages, I left them alone hoping that they get updated after the fact.

@deads2k, would you instead be willing to review PR #26027 which has a similar aim?

@deads2k, would you instead be willing to review PR #26027 which has a similar aim?

/sig service-catalog

/sig service-catalog

@deads2k, would you instead be willing to review PR #26027 which has a similar aim?

certainly.  it looks good.

@deads2k, would you instead be willing to review PR #26027 which has a similar aim?

certainly.  it looks good.


Problem with retrieval of Safely Endangered

As per http://www.safelyendangered.com/
"Safely Endangered is down for maintenance! "

Everything is back to normal


Add Class Diagrams to Milestone 1 Report

Class Diagram page is created. I will add the content to Project1 Milestone Report once finished.

Completed. Added class diagram overall descr. and image.


Update main.go

Sorry, @Kubixxu. 🙂
I'm going to close this pull-request as I don't think we should change the output of this "Hello, World!" app.


Add more advanced usage example

Fixes #2
Rationale: The component actually works the intended way but the example was not working for client side rendering. The new example is working on server- and client-side but should be used with caution as it uses eval. I noted a warning about this in the proposed change.
Note: It is a good thing to consider if there is a need for a dedicated component for this feature though.

Note @FQ400 please provide some small information about this and how it fixes #2 in the issue once you merge this. The creator of the issue just would have to update his self implemented component to something similar as in this example (the eval part is crucial here unfortunately - I feel like I need a shower :grin:).


I tried to get the cross section of a 3D object, but it seemed wrong.

I created a tetrahedron and used a plane to intercept it. But there seems to be an additional bounding box in the result.
the dome:
in my project like this:

yeah, thx for ur answer, it's work.
But I don't understand the difference define faces by [[0, 1, 2], [0, 3, 1], [0, 2, 3], [1, 3, 2]] or [[0, 1, 3], [0, 2, 1], [0, 3, 2], [1, 2, 3]] .
Should there be a difference?

@hurryhuang1007 Please close if satisfied. Thanks.

very thx, I close it now.


Adding inline code and code block support

Everything is converted except for <code>, <script>, <style>, and <pre> tags.

In the context of markdown strings, it would be amazing if inline code and code block snippets could be ignored (considering adding smartquotes to transpile-md-to-json.
const smartquotes = require("smartquotes");

const text = smartquotes("# The typography \"rabbit hole\"\n\nTo enter the rabbit's home, once must enter the rabbit hole using command `enter \"rabbit hole\"`.\n\n```javascript\nconst rabbit = \"hole\"\n```");

console.log(text)

Current implementation breaks code.

Documenting other markdown edge cases here…
[![How to self-host a hardened strongSwan IKEv2/IPsec VPN server for iOS and macOS - YouTube](how-to-self-host-a-hardened-strongswan-ikev2-ipsec-vpn-server-for-ios-and-macos.png)](https://www.youtube.com/watch?v=HY3F_vHuTFQ "How to self-host a hardened strongSwan IKEv2/IPsec VPN server for iOS and macOS - YouTube")


lets let the alias be configured for the spring boot customizer

lets let the alias be configured for the spring boot customizer

[merge]


Deployment with Cilium v1.8.6 fails on GKE

I’m unable to successfully deploy Cilium on a GKE cluster at the moment. The cilium pods come up fine, but none of the managed pods do.
Warning  FailedCreatePodSandBox  22s (x4 over 26s)   kubelet            (combined from similar events): Failed to create pod sandbox: rpc error: code = Unknown desc = failed to set up sandbox container “f6ca5819eee5af8a48fd5f505182dd31a90e20737a60c16ca139a9ae4ce7e1b2” network for pod “kube-dns-6465f78586-llt4t”: networkPlugin cni failed to set up pod “kube-dns-6465f78586-llt4t_kube-system” network: unable to allocate IP via local cilium agent: [POST /ipam][502] postIpamFailure  range is full
Steps to reproduce the issue -
$ gcloud container clusters create <name> --image-type COS --num-nodes 2 --machine-type n1-standard-4 --zone <zone>
$ ./cilium install --version v1.8.6

@cmluciano reported similar problem when he tried running connectivity tests.

Cilium v1.8 is no longer supported (older supported release is v1.10 as of today).


SqlPackage bacpac import not working on linux

Azure Data Studio Version:

Version: 1.15.0
Commit: e57eb999fc5f1e000477da8fe0b8679ff0bfd57b
Date: 2020-02-12T20:45:05.264Z
VS Code: 1.42.0
Electron: 6.1.6
Chrome: 76.0.3809.146
Node.js: 12.4.0
V8: 7.6.303.31-electron.0
OS: Linux x64 5.3.0-7625-generic
(Have attempted on Ubuntu 18.04 and PopOS 19.10)
Steps to Reproduce:

Install Admin Pack for SQL Server
Go to Connections
Add connection for sql server running locally in docker swarm
Right click on databases and choose Data Tier Application Wizard
Choose [Import Bacpac]
Select the bacpac file, leaving target server unchanged and a new target database Testing
Click Next and Import

Result

This has been occurring for ~2 months for me, with many different versions of sqlpackage and azure data studio
My workaround for the time being has been to revert to 18.3.1 sqlpackage which seems to work, albeit warning me about users that rely on an external authentication provider that is not supported by the target. These users will be treated as users without logins.
I cannot provide you with any of the contents of the bacpac file unfortunately.
This might also be related

We had a regression in the sqlpackage 18.4.1 release where there's the error “Object reference not set to an instance of an object.” when importing a bacpac with a user with an external login. This got fixed for importing/deploying to and Azure db in the 1.16 ADS release. For on prem, we are targeting to get the fix in the April release.

first fix didn't work, so now targeting to get this fixed for June release.

Thanks for the update @kisantia. Would it be possible to get a pre-release version (windows/linux) of sqlpackage when it's working? I work for Nude Solutions and we've been struggling with this for some time now. We'd be happy to help test it out and provide feedback

@Parasrah it would be great if you could try out the fix we have. I send an email to the email address on your github profile.


Refactor variables for consistency

A lot of the variables are named inconsistently and also have short names such as $x. These should be changed to make readability and maintainability easier.

[x] Account (8bc54a30c699e241369edb42f5665b0bab46d03f)
[x] Block (partially in 52b060f98f9ac1cffc2aa606fde52bdf11512bf8)
[x] DB
[x] functions.inc.php (b7a31abcba8151f7217b03940cd7e1f33ae4dbc0)
[x] Transaction (07529c613f33596c43863569f1e6d814636fe3d5)

Closing to archive this repository.


etr/libhttpserver

https://github.com/etr/libhttpserver

Hi, could you please give some details?
I would like to contribute :)


Find Files (Ctrl+P) is very slow

VSCode Version: Code 1.12.2 (19222cdc84ce72202478ba1cec5cb557b71163de, 2017-05-10T13:20:36.315Z)
OS Version: Windows_NT ia32 10.0.15063
Extensions:

Extension
Author
Version

delphi-keybindings
alefragnani
0.2.0

delphi-pack
alefragnani
0.1.0

numbered-bookmarks
alefragnani
0.9.1

pascal
alefragnani
0.8.0

python
donjayamanne
0.6.4

classic-asp
ilich8086
0.0.2

classic-asp-html
jtjoo
0.0.1

python
tht13
0.2.3

asp
tron
0.0.1

pygame-snippets
tushortz
0.0.1

Steps to Reproduce:

Is this on a local or a remote filesystem?
How many files are in your folder?
How long does it roughly take until results are shown?

Hi,
It's a remote system, it may take more than 20 minute to find a file when I type it completely, sometimes it never ends. My folder and subfolder has mare than 100 thousands files.
I tried with other programs and are much more faster finding files, but I like VS Code that's why I ask.
Thanks in advance.

What about text search (Ctrl + Shift + F) performance, how slow is that?

Is also very slow.
Dimas Salazar
"Los jóvenes venezolanos, ¿se dejarán abatir por las dificultades, o
tendrán el valor de ser cristianos de verdad y construir una sociedad
más justa, más fraterna, más acogedora y pacífica?"
Juan Pablo II (1985)
On Fri, May 19, 2017 at 7:10 PM, chrmarti<EMAIL_ADDRESS>wrote:

What about text search (Ctrl + Shift + F) performance, how slow is that?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/Microsoft/vscode/issues/26868#issuecomment-302822879,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AIm5JlDRcAJ9EIXmtw4-xYoO46xgDz1zks5r7hNzgaJpZM4NfM4v
.

I am also facing this problem I am on the latest version.

My files are on local.
I have 30k files
It takes around 10 secs to show some search

To ankitrg, I guess that 10 secs for 30k files is pretty normal.

@smrucv Which remote filesystem is this? We have reports of slow performance with sshfs.

Seriously? Nothing between Aug 21st and Dec 1st, then you only wait 7 days for a response, and don't ping any of the people who might be able to answer?  Poor form, vscodebot.
In my case it was a local filesystem on Windows 10 Pro, no sshfs. I've since switched to Atom, which (after the initial indexing) can find a file almost as fast as I type.


SW-2504 left nav hover state updates

selected state color is not available today
please test in vercel/storybook
@hannah-cai @chudo76 the $tw-clr-bg-selected color/token is not available today,,, using -active for now
fixes related to width/padding/scrollbar-width is another PR from terraware-web repo coming soon

@hannah-cai i made all the requested changes, please take a look in vercel.
there's just one thing that's kinda off.. see image

looks great! :)

Awesome, thanks @hannah-cai 👍


400 BadRequest is not a server side issue

I have created a controller that is decorated with [SwaggerResponse(HttpStatusCode.BadRequest, typeof(RegisterResponse))] but the generated code states that 400 is a server-side error:
else
if (status_ == "400")
{
    var objectResponse_ = await ReadObjectResponseAsync<RegisterResponse>(response_, headers_).ConfigureAwait(false);
    throw new ApiException<RegisterResponse>("A server side error occurred.", (int)response_.StatusCode, objectResponse_.Text, headers_, objectResponse_.Object, null);
}

Setting the default message depending on the response code doesn't seem easy to do, but you should be able to put xml comments on your method :
<response code="400">Bad Request</response>
See #1746

That doesn't seem to have any affect. I tried some of the ones of the suggestions and still don't know what I'm doing wrong. Here is what I currently have:
/// <response code="400">Bad Request</response>
[AllowAnonymous]
[HttpPost("register")]
[ProducesResponseType(typeof(RegisterResponse), (int)HttpStatusCode.OK)]
[ProducesResponseType(typeof(RegisterResponse), (int)HttpStatusCode.BadRequest)]
public async Task<ActionResult<RegisterResponse>> Register(
    [FromBody] RegisterRequest request)
{
    // ...
}

Nevermind, I noticed I forgot to add <GenerateDocumentationFile>true</GenerateDocumentationFile> to my .csproj. Now I can set my own messages. However I still feel like 4** errors should say its a client side error by default


Merged. Short time workaround is to use endpoint URL parameter.


How to change OcppEvseState to SuspendedEV when I unplug?

Hello, I would like to use the function of StopTransactionOnEVSideDisconnect which impact to ev charger behavior.
If StopTransactionOnEVSideDisconnect is false when I unplug the ev, it should be turned to Suspendedev status. But now it can't.
For now when I unplug the ev, it sends stoptransaction and the status is finished.
What should I do? Please tell me the solution

Hello!
use this callback in setup(){....}:
setConnectorPluggedInput([]() {
   return true;
},connectorId);

Algorithm: if you charger is ready you should return true
if unready - false

Thank you very much for your answer.
Can you help me to do this OCPP function?
When it's charging and unplug it. The OCPPstate must be "SuspendedEV" if I set "StopTransactionOnEVSideDisconnect" is false.

Hi @TDVSVI,
One of the most recent commits in the develop branch introduced the support for StopTransactionOnEVSideDisconnect. Unfortunately, in earlier versions the library accepted that config from the server while it did not implement its functionality. Can you upgrade, rerun that test and share the results here?

Hi, @matth-x
Thank you very much for your support.
I downloaded the most recent library but it can't function.
There are no responses about "SuspendedEV" when I set false to StopTransactionOnEVSideDisconnect.
Could you tell me about the code of this function? Where is the file in the library that stores this function?

Thank you very much @matth-x
I use the latest library and it can work.


redisson connection cannot be restored

When reading and writing redis cluster via redisson, after killing all redis pod nodes via chaos mesh, the connection cannot be restored, and the connection address is the address of the pod before killing
#3795
ERROR
2024-06-20T07:55:41.470Z ERROR 1 --- [redis] [sson-netty-2-32] o.r.cluster.ClusterConnectionManager : Can't update cluster state
io.netty.channel.ConnectTimeoutException: connection timed out after 10000 ms: <IP_ADDRESS>/<IP_ADDRESS>:6379
at io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe$1.run(AbstractNioChannel.java:263) ~[netty-transport-4.1.110.Final.jar!/:4.1.110.Final]
at io.netty.util.concurrent.PromiseTask.runTask(PromiseTask.java:98) ~[netty-common-4.1.110.Final.jar!/:4.1.110.Final]
at io.netty.util.concurrent.ScheduledFutureTask.run(ScheduledFutureTask.java:153) ~[netty-common-4.1.110.Final.jar!/:4.1.110.Final]
at io.netty.util.concurrent.AbstractEventExecutor.runTask(AbstractEventExecutor.java:173) ~[netty-common-4.1.110.Final.jar!/:4.1.110.Final]
at io.netty.util.concurrent.AbstractEventExecutor.safeExecute(AbstractEventExecutor.java:166) ~[netty-common-4.1.110.Final.jar!/:4.1.110.Final]
at io.netty.util.concurrent.SingleThreadEventExecutor.runAllTasks(SingleThreadEventExecutor.java:469) ~[netty-common-4.1.110.Final.jar!/:4.1.110.Final]
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:569) ~[netty-transport-4.1.110.Final.jar!/:4.1.110.Final]
at io.netty.util.concurrent.SingleThreadEventExecutor$4.run(SingleThreadEventExecutor.java:994) ~[netty-common-4.1.110.Final.jar!/:4.1.110.Final]
at io.netty.util.internal.ThreadExecutorMap$2.run(ThreadExecutorMap.java:74) ~[netty-common-4.1.110.Final.jar!/:4.1.110.Final]
at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30) ~[netty-common-4.1.110.Final.jar!/:4.1.110.Final]
at java.base/java.lang.Thread.run(Thread.java:833) ~[na:na]```

[redis-debug.txt](https://github.com/user-attachments/files/15923589/redis-debug.txt)

Can you share Redisson logs with debug logging level for org.redisson package?

redssion  3.16.5
I found the reason. I passed in two hosts, but there was a test that only allowed one.
After all pods are killed, this code will throw the above error
config.useClusterServers()
                .addNodeAddress("redis://woo-redis-cluster-leader:6379", "redis://woo-redis-cluster-follower:6379")
                .setScanInterval(2000);

After all pods are killed,This will automatically restore
        config.useClusterServers()
                .addNodeAddress("redis://woo-redis-cluster-leader:6379")
                .setScanInterval(2000);

Because of this, I wrote two kubernetes services, which caused configEndpointHostName to be empty。This leads to the assumption that the network is partitioned.
                if (cfg.getNodeAddresses().size() == 1 && !addr.isIP()) {
                    configEndpointHostName = addr.getHost();
                }

   private void scheduleClusterChangeCheck(ClusterServersConfig cfg) {
        monitorFuture = group.schedule(new Runnable() {
            @Override
            public void run() {
                if **(configEndpointHostName != null)** {
                    String address = cfg.getNodeAddresses().iterator().next();
                    RedisURI uri = new RedisURI(address);
                    AddressResolver<InetSocketAddress> resolver = resolverGroup.getResolver(getGroup().next());
                    Future<List<InetSocketAddress>> allNodes = resolver.resolveAll(InetSocketAddress.createUnresolved(uri.getHost(), uri.getPort()));
                    allNodes.addListener(new FutureListener<List<InetSocketAddress>>() {
                        @Override

I found the reason. I passed in two hosts, but there was a test that only allowed one.

have you resolved the issue?

Solved, but I don't understand why it is designed this way.

Can you try 3.32.0 version as well? It has cluster failover handling fix


Derive Hash on PackageEcosystem

Hey, thanks for making this! I'm currently trying to use it for something and I'd benefit from PackageEcosystem being hashable (to use it as a key in a HashSet or HashMap, for instance).
I'm a Rust noob, so I hope I've not missed something obvious.
Let me know what you think!

Published in 0.2.1.


Adding Dublin Business School

Link to college: http://www.dbs.ie/

@AndyMalone117 Pull request merged.


Loading saved model fails with ValueError You are trying to load a weight file containing 1 layers into a model with 0 layers

This toy example
import sys
import keras
from keras import Sequential
from keras.activations import linear
from keras.engine import InputLayer
from keras.layers import Dense
from keras.losses import mean_squared_error
from keras.metrics import mean_absolute_error
from keras.models import load_model
from keras.optimizers import sgd

print("Python version: " + sys.version)
print("Keras version: " + keras.__version__)

model = Sequential()
model.add(InputLayer(batch_input_shape=(1, 5)))
model.add(Dense(10, activation=linear))
model.compile(loss=mean_squared_error, optimizer=sgd(), metrics=[mean_absolute_error])

model.save('test.h5')
del model
load_model('test.h5')

gives the following output/error
Using TensorFlow backend.
Python version: 3.6.5 (default, Apr 25 2018, 14:23:58)
[GCC 4.2.1 Compatible Apple LLVM 9.1.0 (clang-9<IP_ADDRESS>)]
Keras version: 2.2.0
2018-06-13 12:02:50.570395: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
Traceback (most recent call last):
  File "/Users/samb/IdeaProjects/connect-four-challenge-client-python3/test.py", line 22, in <module>
    load_model('test.h5')
  File "/Users/samb/IdeaProjects/connect-four-challenge-client-python3/venv/lib/python3.6/site-packages/keras/engine/saving.py", line 264, in load_model
    load_weights_from_hdf5_group(f['model_weights'], model.layers)
  File "/Users/samb/IdeaProjects/connect-four-challenge-client-python3/venv/lib/python3.6/site-packages/keras/engine/saving.py", line 901, in load_weights_from_hdf5_group
    str(len(filtered_layers)) + ' layers.')
ValueError: You are trying to load a weight file containing 1 layers into a model with 0 layers.

Looking at https://github.com/keras-team/keras/blob/2.2.0/keras/engine/saving.py#L883 when debugging, I see that in
    filtered_layers = []
    for layer in layers:
        weights = layer.weights
        if weights:
          filtered_layers.append(layer)

the value of weights is always the empty list [] whereas in the subsequent block
    layer_names = filtered_layer_names
    if len(layer_names) != len(filtered_layers):
        raise ValueError('You are trying to load a weight file '
                         'containing ' + str(len(layer_names)) +
                         ' layers into a model with ' +
                         str(len(filtered_layers)) + ' layers.')

the value of layer_names (respectively, filtered_layer_names), is the singleton list ['dense_1'] leading to the error message shown above.
I'm not quite certain what the cause of the problem is. Is something going wrong in saving the model? Or is something wrong when loading the model (before loading the weights)? Or is something wrong in this logic for loading the weights?

I've got the same problem after I updated keras from 2.0.8 to 2.2.
I can still load my old models but not the newly created.
I can also reproduce this error using your example code after changing line 22.
I changed it to
keras.models.load_model('test.h5')
I hope someone can help.

I managed to narrow down the problem, it seems to boil down to using the 'input_shape' parameter or not. The following code does not give the ValueError
import sys

import keras
from keras import Sequential
from keras import losses
from keras import metrics
from keras import optimizers
from keras.activations import linear
from keras.engine import InputLayer
from keras.layers import Dense
from keras.models import load_model

print("Python version: " + sys.version)
print("Keras version: " + keras.__version__)

model = Sequential()
model.add(InputLayer(batch_input_shape=(1, 5)))
model.add(Dense(10, input_shape=(5,), activation=linear))
model.compile(loss=losses.mean_squared_error,
              optimizer=optimizers.sgd(),
              metrics=[metrics.mean_absolute_error])

model.save('test.h5')
del model
load_model('test.h5')

The only difference to the code above is that now the dense layer has the additional parameter input_shape set.

Thanks!
Looks like I put a bracket wrong.
This works.
model.add(Bidirectional(LSTM(     hidden_List[0],     return_sequences=True,     activation="tanh"),     input_shape=shape))
This doesn't.
model.add(Bidirectional(LSTM(     hidden_List[0],     return_sequences=True,     input_shape=shape,     activation="tanh")))
It even throws a NotImplementedError.
I don't know why this error wasn't thrown on my larger project. But at last it works.

I had the same problem when I tried to fine-tune a vgg16 model. It happened when I upgraded from keras 2.1.6 to 2.2.0. The solution proposed above didn't work for me :( and the only way I found was to downgrade keras to the previous version (2.1.6).

I had the same problem: I cannot load a H5py model saved earlier. with "ValueError You are trying to load a weight file containing [X](model layer) layers into a model with 0 layers "
Downgrading to 2.1.0 solved my problem.

Yep, downgrading to Keras 2.1.x also solved the problem for me, too, just as reported by @jeffreynghm and @juliojj.

I have the same problem... Is it an error in Keras or in our code ? Do you think it will be fixed for the next update ?

The following code snippet isolates the error. It seems the problem happens when InputLayer is used. model1 saves and loads fine but model2 (the same single-layer model)  fails. The only difference: model2 uses InputLayer.
from keras.models import Sequential, load_model
from keras.layers import Conv2D, Input, InputLayer

# without InputLayer
model1 = Sequential()
model1.add(Conv2D(32, (5, 5), input_shape=(64,64,3)))

model1.save('test.hdf5')
model_from_file = load_model('test.hdf5')
print("Loaded model 1 from file successful")

# with InputLayer --> causes error when loading saved model
model2 = Sequential()
model2.add(InputLayer(input_shape=(64,64,3)))
model2.add(Conv2D(32, (5, 5)))

model2.save('test2.hdf5')
model_from_file = load_model('test2.hdf5')
print("Loaded model 2 from file successful")

... continuing from above, I probed further and noticed that it runs into an issue the saved model_config differ here and is unable to load the weights.
From visual inspection, the main difference is that model_config for model2 (that uses InputLayer) does not have batch_input_shape element for the conv layer.
I'm not exactly sure how to fix it. Just leaving bread crumbs for someone that is more familiar with the keras codebase.

As a follow up of @SamuelBucheliZ comment on the 14th:
The presence of InputLayer definitely triggers the issue.
In my case repeating the input_shape in both InputLayer and Dense constructors does the trick (no need of using using batch_input_shape).
Something like:
model = Sequential()
model.add(InputLayer(input_shape=(5,)))
model.add(Dense(10, input_shape=(5,), activation=linear))

The problem appears to be that Sequential.get_config() references self.layers rather than self._layers
def layers(self):
# Historically, sequential.layers only returns layers that were added
# via add, and omits the auto-generated InputLayer that comes at the
# bottom of the stack.
if self._layers and isinstance(self._layers[0], InputLayer):
return self._layers[1:]
return self._layers
so no input shape gets saved (no matter whether InputLayer was implicitly or explicitly added) and the delayed-build pattern is used, which does not set any weights, and so it looks like the model has no layers with weights.

Same issue using tensorflow 1.9 and Keras 2.2.2
Model definition without input_shape defined.
model = tf.keras.models.Sequential()
model.add(tf.keras.layers.Flatten())
model.add(tf.keras.layers.Dense(128, activation = tf.nn.relu))
model.add(tf.keras.layers.Dense(128, activation = tf.nn.relu))
model.add(tf.keras.layers.Dense(10, activation = tf.nn.softmax))

Saving and loading the model
model.save('epic_num_reader.model')
tf.keras.models.load_model('epic_num_reader.model')

The full code is the same as the one in this video, https://www.youtube.com/watch?v=wQ8BIBpya2k
Error:
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-33-0aee9b4f4fad> in <module>()
----> 1 tf.keras.models.load_model('epic_num_reader.model')

/usr/local/lib/python3.5/dist-packages/tensorflow/python/keras/engine/saving.py in load_model(filepath, custom_objects, compile)
    230
    231     # set weights
--> 232     load_weights_from_hdf5_group(f['model_weights'], model.layers)
    233
    234     if compile:

/usr/local/lib/python3.5/dist-packages/tensorflow/python/keras/engine/saving.py in load_weights_from_hdf5_group(f, layers)
    730                      'containing ' + str(len(layer_names)) +
    731                      ' layers into a model with ' + str(len(filtered_layers)) +
--> 732                      ' layers.')
    733
    734   # We batch weight value assignments in a single backend call

ValueError: You are trying to load a weight file containing 3 layers into a model with 0 layers.

@ismaproco your problem might be different since you are not using InputLayer.
To diagnose the problem, from the command line run
pip install h5json
Note where the package is installed, then from the command line in the directory with your saved model
[installation directory]/h5json/h5tojson/h5tojson.py -d epic_num_reader.model >epic_num_reader.json
Then load the JSON file in your favorite editor and search for "input."  It should look something like
"value": "{\"class_name\": \"Sequential\", \"config\": [{\"class_name\": \"InputLayer\", \"config\": {\"batch_input_shape\": [null, 28, 28], \"dtype\": \"float32\", \"sparse\": false, \"name\": \"sequential_input\"}}, {\"class_name\": \"Flatten\", \"config\": {\"name\": \"flatten\", \"trainable\": true, \"batch_input_shape\": [null, 28, 28], \"dtype\": \"float32\", \"data_format\": \"channels_last\"}},
Although you won't have the InputLayer there, you should see batch_input_shape in the Flatten definition.

@ismaproco your problem might be different since you are not using InputLayer.
First, I see you're using tf.__version__ 1.9.0. You might want to upgrade to 1.10.0.
And you're invoking the Keras that comes with TensorFlow, so you would find the version as tf.keras.__version__ and it would probably be something like 2.1.6-tf
But, to diagnose the problem, from the command line run
pip install h5json
Note where the package is installed, then from the command line in the directory with your saved model
[installation directory]/h5json/h5tojson/h5tojson.py -d epic_num_reader.model >epic_num_reader.json
Then load the JSON file in your favorite editor and search for "input". It should look something like
"value": "{\"class_name\": \"Sequential\", \"config\": [{\"class_name\": \"InputLayer\", \"config\": {\"batch_input_shape\": [null, 28, 28], \"dtype\": \"float32\", \"sparse\": false, \"name\": \"sequential_input\"}}, {\"class_name\": \"Flatten\", \"config\": {\"name\": \"flatten\", \"trainable\": true, \"batch_input_shape\": [null, 28, 28], \"dtype\": \"float32\", \"data_format\": \"channels_last\"}},
Although you won't have the InputLayer there, you should see batch_input_shape in the Flatten definition.

thank @MmAlder upgrading to 1.10.0 fixed my issue

@prativadas That doesn't really resolve the problem.  It's just a work-around.  Remember that the model was built, trained, and saved without difficulty.  The error arises when attempting to load the model.  Changing the way the model was built can avoid the problem, but when you're trying to load a trained model, rebuilding it is often not an option.  It is a better idea to fix the code.  Changing Sequential.get_config() as I described above would do that.  I did it locally and it works for me, but I didn't exhaustively test it and I don't have a copy of the GitHub repo to generate a pull request anyway.

for some information, the input layer infomation is missing in 2.2.0, compare to 2.1.6
the object
{
		"class_name": "InputLayer",
		"config": {
			"batch_input_shape": [null, 64, 64, 3],
			"dtype": "float32",
			"sparse": false,
			"name": "input_1"
		}
}

is missing
in 2.2.0
{
	"class_name": "Sequential",
	"config": [{
		"class_name": "Conv2D",
		"config": {
			"name": "conv2d_2",
			"trainable": true,
			"filters": 32,
			"kernel_size": [5, 5],
			"strides": [1, 1],
			"padding": "valid",
			"data_format": "channels_last",
			"dilation_rate": [1, 1],
			"activation": "linear",
			"use_bias": true,
			"kernel_initializer": {
				"class_name": "VarianceScaling",
				"config": {
					"scale": 1.0,
					"mode": "fan_avg",
					"distribution": "uniform",
					"seed": null
				}
			},
			"bias_initializer": {
				"class_name": "Zeros",
				"config": {}
			},
			"kernel_regularizer": null,
			"bias_regularizer": null,
			"activity_regularizer": null,
			"kernel_constraint": null,
			"bias_constraint": null
		}
	}]
}

in 2.1.6
{
	"class_name": "Sequential",
	"config": [{
		"class_name": "InputLayer",
		"config": {
			"batch_input_shape": [null, 64, 64, 3],
			"dtype": "float32",
			"sparse": false,
			"name": "input_1"
		}
	}, {
		"class_name": "Conv2D",
		"config": {
			"name": "conv2d_2",
			"trainable": true,
			"filters": 32,
			"kernel_size": [5, 5],
			"strides": [1, 1],
			"padding": "valid",
			"data_format": "channels_last",
			"dilation_rate": [1, 1],
			"activation": "linear",
			"use_bias": true,
			"kernel_initializer": {
				"class_name": "VarianceScaling",
				"config": {
					"scale": 1.0,
					"mode": "fan_avg",
					"distribution": "uniform",
					"seed": null
				}
			},
			"bias_initializer": {
				"class_name": "Zeros",
				"config": {}
			},
			"kernel_regularizer": null,
			"bias_regularizer": null,
			"activity_regularizer": null,
			"kernel_constraint": null,
			"bias_constraint": null
		}
	}]
}

all above was created by code provide by iretiayo commented on 25 Aug
from keras.models import Sequential, load_model
from keras.layers import Conv2D, Input, InputLayer

# without InputLayer
# model1 = Sequential()
# model1.add(Conv2D(32, (5, 5), input_shape=(64,64,3)))
#
# model1.save('keras-2.2.0-model1.hdf5')
# model_from_file = load_model('keras-2.2.0-model1.hdf5')
# print("Loaded model 1 from file successful")

# with InputLayer --> causes error when loading saved model
model2 = Sequential()
model2.add(InputLayer(input_shape=(64,64,3)))
model2.add(Conv2D(32, (5, 5)))

model2.save('keras-2.2.0-model2.hdf5')
model_from_file = load_model('keras-2.2.0-model2.hdf5')
print("Loaded model 2 from file successful")

SOLVED!!! :-  The reason for this error is :- Some Python interpreters demand a "SKELETON" of Neural network before loading another neural network into it. So, in my loading file, I created exactly same Neural Network, compiled it. But, inside the "model.fit()" method, I passed epochs=0 and used load_model function with required "h5" file as parameters. This worked !
model = tf.keras.models.Sequential()
The Input layer with Flattened Acceptance Property
model.add(tf.keras.layers.Flatten())
#Hidden Layers
model.add(tf.keras.layers.Dense(128,activation=tf.nn.relu,input_dim=784))
model.add(tf.keras.layers.Dense(128,activation=tf.nn.relu,input_dim=784))
#Output Layer
model.add(tf.keras.layers.Dense(10,activation=tf.nn.softmax))
#Model Architecture Created. Now, using the model:-
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy',metrics=['accuracy'])
#Training the Model:-
model.fit(x_train,y_train,epochs=0)
model.load_weights('NumberRecognitionModelWeights.h5')

@Ketan14a So you "solve" the problem with load_model() simply by not using it?  What if you don't know the structure of the model?

I suggest this thread be renamed "Models with InputLayer are not serialized to HDF5 correctly". Below is a demonstration of the issue and a hack to fix existing saved models.
docker run -it tensorflow/tensorflow:1.11.0-py3 /bin/bash
apt-get update
apt-get install python3-venv git hdf5-tools
python3 -m venv env
source env/bin/activate
pip install keras tensorflow
pip install git+git://github.com/keras-team/keras.git --upgrade --no-deps
python test.py

import keras
from keras.models import Sequential, load_model
from keras.layers import Dense, Input, InputLayer

print('keras.__version__=', keras.__version__)

fname1 = 'test1.h5'
model1 = Sequential()
model1.add(Dense(1, input_shape=(64, 64), name='dense'))
model1.compile(loss='mse', optimizer='adam')
model1.save(fname1)
model1 = load_model(fname1)

fname2 = 'test2.h5'
model2 = Sequential()
model2.add(InputLayer((64,64), name='input'))
model2.add(Dense(1, name='dense'))
model2.compile(loss='mse', optimizer='adam')
model2.save(fname2)
# ValueError: You are trying to load a weight file containing 1 layers into a model with 0 layers
model2 = load_model(fname2)

keras.__version__= 2.2.4
$ h5dump -A test1.h5 > test1.structure
$ h5dump -A test2.h5 > test2.structure
$ diff test1.structure test2.structure
...
<       (0): "{"class_name": "Sequential", "config": {"name": "sequential_1", "layers": [{"class_name": "Dense", "config": {"units": 1, "kernel_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_regularizer": null, "use_bias": true, "dtype": "float32", "activation": "linear", "kernel_initializer": {"class_name": "VarianceScaling", "config": {"seed": null, "distribution": "uniform", "mode": "fan_avg", "scale": 1.0}}, "batch_input_shape": [null, 64, 64], "bias_constraint": null, "activity_regularizer": null, "name": "dense", "bias_regularizer": null, "trainable": true}}]}}"
---
>       (0): "{"class_name": "Sequential", "config": {"name": "sequential_2", "layers": [{"class_name": "Dense", "config": {"units": 1, "kernel_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_regularizer": null, "use_bias": true, "trainable": true, "activation": "linear", "kernel_initializer": {"class_name": "VarianceScaling", "config": {"seed": null, "distribution": "uniform", "mode": "fan_avg", "scale": 1.0}}, "bias_constraint": null, "activity_regularizer": null, "name": "dense", "bias_regularizer": null}}]}}"
...

The test1 has the additional structure: "batch_input_shape": [null, 64, 64], "dtype": "float32",
You can fix this using:
import json
import h5py

def fix_layer0(filename, batch_input_shape, dtype):
    with h5py.File(filename, 'r+') as f:
        model_config = json.loads(f.attrs['model_config'].decode('utf-8'))
        layer0 = model_config['config']['layers'][0]['config']
        layer0['batch_input_shape'] = [None, 64, 64]
        layer0['dtype'] = 'float32'
        f.attrs['model_config'] = json.dumps(model_config).encode('utf-8')

# Example
fix_layer0('test2.h5', [None, 64, 64], 'float32')

Thanks a lot @cyounkins
I can now continue training my VGG16 model on Keras 2.2.4 just needed to set the shape to [None, 256, 256,3] and configuration to change was at ['config']['layers'][0]['config'] instead of at ['config'][0]['config']

Closing as this is resolved

@wt-huang Was there a commit that resolved it?

I see a workaround, but not a fix.
Would be better to re-open the issue.

Btw, this is happening in a recent version with models save in the same session:
In [17]: tf.keras.version
Out[17]: '2.2.4-tf'
In [18]: tf.version
Out[18]: '1.14.1-dev20190311'

@cottrell  Did you find the solution?

@cottrell  @KhanAAI The only way I was able to get this to work was to downgrade from keras 2.2.* to 2.1.* (specifically I used 2.1.6)

I was sub classing model and did not provide an input shape when building the model. It seems you can bypass this issue by first calling the model on a sample input then loading the weights into the model.
Note that I am using tensorflow module. It might also work here.
For Example:
`
input_shape = (100,100,1)
model = tf.keras.model.Model()
model.add(tf.keras.layers.Conv2D(filters=3,kernel_size=3,strides=1,activation=tf.nn.relu,use_bias=True)
model(np.zeros(input_shape))
model.layers[0].set_weights(weights)
...
`
This seems to work for me.

Closing as this is resolved

I really dislike when a 30-or-more-comments issue gets closed with a mere "closed as resolved".
It does not provide any context, info on how, by whom, and why the issue is considered as solved.
A summary of the workaround (cannot be called solutions) I found in the thread:

Downgrade to keras 2.1.0
Don't use InputLayer

I opened #10417 in response to this being closed, and as far as I know this is still an issue. #10417 better describes the situation as "Models with InputLayer are not serialized to HDF5 correctly" because as the h5dump output shows, equivalent models are not serialized the same.

I'm using Keras via tensorflow-gpu 1.13.1, I'm not using Input however I do use the input shape attribute on Conv2d (which might be using Input internally perhaps).
Conv2D(3, (5, 5), padding="same", input_shape=inputShape)

@cottrell @KhanAAI The only way I was able to get this to work was to downgrade from keras 2.2.* to 2.1.* (specifically I used 2.1.6)

I've moved on to subclassing keras api in order to use tf 2.0 with the graph etc. Haven't yet gone back to the serialization problem since that path changes the approach I think.

save files with .hdf5 instead of h5

save files with .hdf5 instead of h5

Thank you. I'll give this a try when I get a chance!

If you use multi-GPU to train your model，you may get this probelm. You can use the this code to train，
parallel_model = keras.utils.multi_gpu_model(model, 2) .

Well, I consider this a high priority bug. Why has the issue been closed?

I'm seeing something similar with tf.keras: https://github.com/tensorflow/tensorflow/issues/28668. This seems relatively high priority since I'm currently unable to save any tf.keras models.

Not sure if it also helps you, but I could circumvent the issue by installing Keras 2.1.6
Note: You have to save the model using this version of Keras in order to be able to load it. Models saved using the latest versions didn't work for me.

@renatobellotti
Thanks for your message.  I agree with you. I had keras 2.2.4 and ran into the same problem with load_model (which really pissed me off...). Then I upgraded keras to 2.1.6 and it works.

did  not work for me with keras 2.1.6, I am using windows10+python3

did not work for me with keras 2.1.6, I am using windows10+python3

Have you saved the model using keras 2.1.6 as well?

No, cause I am using a model from other people,  he said he saved the model with 2.1.6, but not work with mine....

It still happens to me in version 2.3.0

Still an issue

Problem still present in 2.3.1, in exactly the same form.
I'm wondering why this issue is closed as the problem has not been resolved.

Had the same problem. What worked was stopping using anything from normal keras, and just using tf.keras everywhere

Had the same error when trying to fine tune a vgg16 model with keras version 2.2.4.
As @juliojj suggested downgrading keras into version 2.1.6 solved my problem.

from imageai.Prediction.Custom import ModelTraining
import os
trainer = ModelTraining()
trainer.setModelTypeAsYOLOv3()
trainer.setDataDirectory("/content/drive/My Drive/Colab Notebooks/jersey")
trainer.trainModel(num_objects=10, num_experiments=50, enhance_data=True, batch_size=8, show_network_summary=True, continue_from_model="/content/drive/My Drive/Colab Notebooks/jersey/models/detection_model-ex-053--loss-0007.979.h5")
this is the error i keep facing

AttributeError                            Traceback (most recent call last)
 in ()
3
4 trainer = ModelTraining()
----> 5 trainer.setModelTypeAsYOLOv3()
6 trainer.setDataDirectory("/content/drive/My Drive/Colab Notebooks/jersey")
7 trainer.trainModel(num_objects=10, num_experiments=50, enhance_data=True, batch_size=8, show_network_summary=True, continue_from_model="/content/drive/My Drive/Colab Notebooks/jersey/models/detection_model-ex-053--loss-0007.979.h5")
AttributeError: 'ModelTraining' object has no attribute 'setModelTypeAsYOLOv3'
PLEASE ANY HELP??

any progress?

This was a long time ago but for anyone hitting this I have a feeling you need to call the model once (build it) before saving. This is likely the slightly opaque error.

@cottrell's suggestion is the only one that I was able to get working.

Same issue in 2.3.1. I don't know why this long standing issue has been closed and not looked upon. I went ahead and suggested Keras to my team instead of our PyTorch and here I am with this bug.

I solved this so easily.
Just call the .build() method with the input_shape parameter.
model.load_weights('my_weights.hdf5')
model.build(input_shape=(1, 224, 224, 3))

Had the same problem. What worked was stopping using anything from normal keras, and just using tf.keras everywhere

i am using tf.keras every where, but still facing this problem

I implemented cGAN with Tensorflow 1.13 and code was running fine on Windows and Linux, but when I upgraded to tensorflow 2.2 I had similar issue.
After debugging the model by removing some of the layers, I found that ONE of the Leaky ReLU layers  (layers.LeakyReLU()(x)) was causing the issue. By removing it or replacing with other activation layers, the problem was solved for me but still don't know why.

I had similar bug and don't know, why this issue was closed. Hello from 2020!

For Tensorflow 2.3.0 and 2.3.1 setting by_name=True solved the issue. E.g.: model.load_weights(weights_path, by_name=True)

Yep, downgrading to Keras 2.1.x also solved the problem for me, too, just as reported by @jeffreynghm and @juliojj.

!!!
ImportError: Keras requires TensorFlow 2.2 or higher. Install TensorFlow via pip install tensorflow

I solved this so easily.
Just call the .build() method with the input_shape parameter.
model.load_weights('my_weights.hdf5')
model.build(input_shape=(1, 224, 224, 3))

This require to pass the input shape. So if you need to have a flexible shape (as in text processing, or simply if you have several different shape of images) it won't work.
This issue is not happening when saving in tensorflow format.
Maybe it will be better if keras hdf5 saving format had the same proprety as tensorflow saving format ?

Even if you try to get away with https://github.com/keras-team/keras/issues/10417#issuecomment-435620108 , you will get tons of bugs.
Traceback (most recent call last):
  File "fix_weights.py", line 17, in <module>
    fix_layer0('/home/maifee/Downloads/vgg16_modified.h5', [None, img_size, img_size, 3], 'float32')
  File "fix_weights.py", line 9, in fix_layer0
    model_config = json.loads(f.attrs['model_config'].decode('utf-8'))
  File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
  File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
  File "/home/maifee/.local/lib/python3.7/site-packages/h5py/_hl/attrs.py", line 60, in __getitem__
    attr = h5a.open(self._id, self._e(name))
  File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
  File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
  File "h5py/h5a.pyx", line 77, in h5py.h5a.open
KeyError: "Can't open attribute (can't locate attribute: 'model_config')"

@cyounkins Can you take a look at this again ?
Why they have closed it ?

@maifeeulasad I'm unable to help more than the potential workaround I posted early in the thread and re-opening this issue as #11683 . Please subscribe and/or 👍 that issue.

Still have this issue in 2021. Happy New Year!
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/saving/hdf5_format.py in load_weights_from_hdf5_group(f, layers)
686                      'containing ' + str(len(layer_names)) +
687                      ' layers into a model with ' + str(len(filtered_layers)) +
--> 688                      ' layers.')
689
690   # We batch weight value assignments in a single backend call
ValueError: You are trying to load a weight file containing 23 layers into a model with 41 layers.

Still have this issue in 2021. Happy New Year!
/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/saving/hdf5_format.py in load_weights_from_hdf5_group(f, layers)
686                      'containing ' + str(len(layer_names)) +
687                      ' layers into a model with ' + str(len(filtered_layers)) +
--> 688                      ' layers.')
689
690   # We batch weight value assignments in a single backend call
ValueError: You are trying to load a weight file containing 23 layers into a model with 41 layers.

I had this issue, using google colab. I reinstalled keras version 2.4.3 and tensorflow version 2.3.1. Issues resolved.

I had this issue, using google colab. I reinstalled keras version 2.4.3 and tensorflow version 2.3.1. Issues resolved.

@abiodun-ayodeji, my error on Colab too. I will try, thanks!

@abiodun-ayodeji, my error on Colab too. I will try, thanks!

So, I have keras version on keras.version= 2.1.6
and I change:
topology.py :
def load_weights_from_hdf5_group
print("load to: " + str(len(layers)) + " layers")
and I find next error in function _load_attributes_from_hdf5_group
data = []
if name in group.attrs:
data = [n for n in group.attrs[name]]
# ---------------------
I delete decode and this solve my problems
try write into topology.py in function save_weights_to_hdf5_group
print("save to: "+str(len(layers)) + " layers")
and fn load_weights_from_hdf5_group
print("load to: " + str(len(layers)) + " layers")
maybe it's find you way to solve this problems
save to: 1 layers
load to: 1 layers
['conv2d_5']
sorry my bad eng...

So, I have keras version on keras.version= 2.1.6
and I change:
topology.py :
def load_weights_from_hdf5_group
print("load to: " + str(len(layers)) + " layers")
and I find next error in function _load_attributes_from_hdf5_group
data = []
if name in group.attrs:
data = [n for n in group.attrs[name]]
---------------------
I delete decode and this solve my problems
try write into topology.py in function save_weights_to_hdf5_group
print("save to: "+str(len(layers)) + " layers")
and fn load_weights_from_hdf5_group
print("load to: " + str(len(layers)) + " layers")
maybe it's find you way to solve this problems
save to: 1 layers
load to: 1 layers
['conv2d_5']
sorry my bad eng...

Would you please organize your solution more? I don't think English is not the reason your post is difficult to understand.

I resolved this issue, by introducing the path to the model, rather than just loading the from the model name!

Hey was the issue solved with latest updates or is there someone still facing this problem?
I am currently following a 1 yo course about tensorflow and I was courious about this because in the course was mentioned this error redirecting to this link
Thanks everyone

@Berganzio This issue is resolved. Please use tensorflow.keras instead of just keras. Here is the gist


Show connection status

Change the color of the extension based on the connection status.

Gray (when connected successfully)
Blue (on unregistered)
Red (on failed to connect)

Great idea to use the colors of the theme.

Works great. Thanks @bkbilly!


revert to eureka client implementation to get the correct home page url

What's the purpose of this PR
revert to eureka client implementation to get the correct home page url
Which issue(s) this PR fixes:
Fixes #3165
Follow this checklist to help us incorporate your contribution quickly and easily:

[x] Read the Contributing Guide before making this pull request.
[x] Write a pull request description that is detailed enough to understand what the pull request does, how, and why.
[x] Write necessary unit tests to verify the code.
[x] Run mvn clean test to make sure this pull request doesn't break anything.

Codecov Report

Merging #3176 into master will increase coverage by 0.00%.
The diff coverage is 100.00%.

@@            Coverage Diff            @@
##             master    #3176   +/-   ##
=========================================
  Coverage     51.55%   51.55%
- Complexity     2253     2255    +2
=========================================
  Files           433      433
  Lines         13451    13447    -4
  Branches       1379     1378    -1
=========================================
- Hits           6934     6933    -1
+ Misses         6037     6036    -1
+ Partials        480      478    -2

Impacted Files
Coverage Δ
Complexity Δ

...o/metaservice/service/DefaultDiscoveryService.java
100.00% <100.00%> (ø)
6.00 <5.00> (ø)

...ervice/service/ReleaseMessageServiceWithCache.java
87.05% <0.00%> (+1.17%)
25.00% <0.00%> (+1.00%)

...rk/apollo/spring/property/SpringValueRegistry.java
88.88% <0.00%> (+5.55%)
11.00% <0.00%> (+1.00%)

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Can't start (or update, or anything else) chroot, everything appears to be broken

I appear to have gotten myself into quite a few problems, all of which are likely related.
I have Xenial (16.04) installed on a flash drive. After the Chrome OS update last night, Crouton no longer seems to like it.
chronos@localhost ~/Downloads $ sudo sh crouton -p /media/removable/XFCE/ -n xenial -u /media/removable/XFCE/chroots not found. /media/removable/XFCE/chroots/xenial does not exist; cannot update. Valid chroots:
Why is it adding chroots/ to the path? Perhaps I'm misinterpreting the purpose of -p, but in this case, it looks to be similar to the -c flag of edit-chroot.
chronos@localhost ~/Downloads $ sudo edit-chroot -a -c /media/removable/XFCE System Volume Information lost+found xenial
I'm not sure it should be listing all 3 folders on the USB, as only one is a chroot.
chronos@localhost ~ $ sudo edit-chroot -all -c /media/removable/XFCE name: System Volume Information encrypted: no Entering /media/removable/XFCE/System Volume Information... chroot: failed to run command '/usr/local/bin/croutonversion': No such file or directory
This looks, to me, like my crouton installation is broken. And that it thinks System Volume Information is a chroot.
chronos@localhost /media/removable/XFCE $ ls System\ Volume\ Information/ dev  etc  IndexerVolumeGuid  lib  media  proc  sys  tmp  var
Probably relevant. I don't think most of that is supposed to be in there.
chronos@localhost ~ $ sudo startxfce4 -c /media/removable/XFCE Entering /media/removable/XFCE/xenial... Changing wayland GID from 999 to 601... Password:
I haven't the slightest clue what the password would be, and I've never heard of Wayland until now. Also notable (to me) is that startxfce4 knows that xenial is the chroot, but edit-chroot does not.
Asus C300M
chronos@localhost ~ $ cat /etc/lsb-release CHROMEOS_ARC_ANDROID_SDK_VERSION=25 CHROMEOS_ARC_VERSION=3942165 CHROMEOS_AUSERVER=https://tools.google.com/service/update2 CHROMEOS_BOARD_APPID={A772AA64-E906-A01E-1DFD-1856870D39EC} CHROMEOS_CANARY_APPID={90F229CE-83E2-4FAF-8479-E368A34938B1} CHROMEOS_DEVSERVER= CHROMEOS_RELEASE_APPID={A772AA64-E906-A01E-1DFD-1856870D39EC} CHROMEOS_RELEASE_BOARD=quawks-signed-mp-v3keys CHROMEOS_RELEASE_BRANCH_NUMBER=58 CHROMEOS_RELEASE_BUILDER_PATH=quawks-release/R58-9334.58.0 CHROMEOS_RELEASE_BUILD_NUMBER=9334 CHROMEOS_RELEASE_BUILD_TYPE=Official Build CHROMEOS_RELEASE_CHROME_MILESTONE=58 CHROMEOS_RELEASE_DESCRIPTION=9334.58.0 (Official Build) stable-channel quawks CHROMEOS_RELEASE_NAME=Chrome OS CHROMEOS_RELEASE_PATCH_NUMBER=0 CHROMEOS_RELEASE_TRACK=stable-channel CHROMEOS_RELEASE_VERSION=9334.58.0 DEVICETYPE=CHROMEBOOK GOOGLE_RELEASE=9334.58.0
The obvious solution is probably to nuke it all and start over, but I'd rather not spend hours (days, even) restoring every little setting in my chroot. Creating a backup does nothing (i.e. no tarball created, no output, etc).

@Sarvadi,

Why is it adding chroots/ to the path? Perhaps I'm misinterpreting the purpose of -p, but in this case, it looks to be similar to the -c flag of edit-chroot.

True, similar but slightly different.
crouton's '-p' option looks for the parent of the /bin & /chroots folders.
edit-chroot's '-c' option looks for the location / folder that your chroots are in.
edit-chroot and the start* scripts aren't too particular about where your chroots are or what folder they're in but crouton definitely is.
So I think if you rename your XFCE folder to chroots you should be fine.
To do that use something like:
sudo mv /media/removable/XFCE /media/removable/chroots
Then to update use:
sudo sh ./crouton -p /media/removable -n xenial -u
To list all of your chroots use:
sudo edit-chroot -all -c /media/removable/chroots
And finally to launch your xfce desktop use:
sudo startxfce4 -c /media/removable/chroots [-n xenial]
Hope this helps,
-DennisL
P.S.  To create a backup and store it in your ~/Downloads folder use:
sudo edit-chroot -b -c /media/removable/chroots -f ~/Downloads xenial

@DennisLfromGA,
I'm unable to rename the XFCE folder easily, so I made a chroots folder inside of it and moved xenial into it, which leads me to:
chronos@localhost /media/removable $ sudo sh ~/Downloads/crouton -p /media/removable/XFCE -n xenial -u Downloading latest crouton installer... ######################################################################## 100.0% /media/removable/XFCE/chroots/xenial already exists; updating it... Preparing chroot environment... Installing brightness into the chroot... Installing croutonpowerd into the chroot... Installing croutonversion into the chroot... Installing host-dbus into the chroot... Installing host-wayland into the chroot... Installing volume into the chroot... Installing pulseaudio-default.pa into the chroot... Installing croutoncycle into the chroot... Installing croutontriggerd into the chroot... Installing croutonxinitrc-wrapper into the chroot... Installing setres into the chroot... Installing xinit into the chroot... Installing xbindkeysrc.scm into the chroot... Installing xorg-intel-sna.conf into the chroot... Installing xserverrc into the chroot... Installing xserverrc-xorg into the chroot... Installing xserverrc-local.example into the chroot... Installing croutonclip into the chroot... Installing croutonnotify into the chroot... Installing croutonurlhandler into the chroot... Installing startxfce4 into the host... Installing crouton-noroot into the chroot... Installing startxfce4 into the chroot... Installing enter-chroot into the host... Installing delete-chroot into the host... Installing edit-chroot into the host... Installing mount-chroot into the host... Installing unmount-chroot into the host... Installing crash_reporter_wrapper into the host... Changing wayland GID from 999 to 601... Password:
Which is where all of this started. I have no idea what Wayland is, other than an X replacement. Nor do I know what the password is, or what it's for. The chroot isn't encrypted, so it's not for that.
Also, while confirming that the chroot isn't encrypted, I got this:
chronos@localhost /media/removable/XFCE/chroots $ sudo edit-chroot -all -c . name: xenial encrypted: no Entering /media/removable/XFCE/chroots/xenial... mount: mount /media on /run/crouton/media/removable/XFCE/chroots/xenial/var/host/media failed: No space left on device
I have plenty of free space. I've never used mount before in my life and have no idea where I'd start debugging that.

Powerwashed and made a fresh chroot, same problem. Ended up ditching replacing Chrome OS entirely because I need a functioning Linux install.
Closing this since it's no longer relevant to me and, evident from the lack of any other comments, nobody else seems to have this issue.


[<IP_ADDRESS>] Nth percentile for derivative series

Hi,
It seems that currently calculating Nth percentile for a DERIVATIVE() series is not possible, as PERCENTILE() only supports one field_key as an argument, and not another function.
It would be really useful to have PERCENTILE() accept a function as an argument, e.g. SELECT percentile(derivative(mean(value), 1s), 95) FROM [...]
Use case: calculating Nth percentile of bandwidth used (in bits/sec) when the database actually stores COUNTER type data, i.e. the bytes transferred since a device is powered up (this is what SNMP pollers usually get from network devices). Calculating the Nth percentile of the COUNTER type data is useless.
This is probably a feature request, but I think it's quite essential for a time-series database. If there is a way to do this currently, please let me know.

As mentioned in my post to the mailing list we are experimenting with simplifying our open GitHub Issues. This feature request has been rolled into an aggregate issue for all function requests, so that we can close this issue until we are ready to work on it.
You may continue to make comments here. Closing the issue does not mean we are rejecting this idea.

The query SELECT percentile(derivative(mean(value), 1s), 95) FROM xx where xx
gives me the error
{
"error": "error parsing query: expected field argument in percentile()",
"message": "error parsing query: expected field argument in percentile()"
}
Im trying to calculate 95th percentile for bandwidth

@mrmike1 PERCENTILE() does not support nested functions: https://docs.influxdata.com/influxdb/v1.0/troubleshooting/frequently-asked-questions/#which-influxql-functions-support-nesting

Why are people trying it?
https://github.com/influxdata/influxdb/issues/6428

@mrmike1 presumably for the same reason you did, because they want it to work.
If you read that issue and the associated PR, the fix was that running a query with nested functions inside PERCENTILE() no longer panics the database. Instead, it gives the correct error.


Improvements gdf to da

Improvements to intersecting shapes to grid functions.
The buffer argument I would like to use for identifying transition zones between two layer_models.
Introduced a new function that counts in how many shapes a cell is present. Basically all the code was already there

Is there a flopy function to leave out parts of a vertex modelgrid? I would like to try it to see if it would speed up gdf_to_da

I'm not aware of any such functionality, though it should be fairly easy to use gridintersect to create a subset of geometries based on an intersection result. Recreating a model grid from that object would be a bit difficult though. But since you need to build the intersection geometries for that step anyway, I doubt it will speed things up much leaving them out of the next intersection calculations? The shapely intersection routines should be able to query the relevant parts of the grid relatively quickly, I think?

The PR currently has all the improvents I was looking for. According to codacy there is a space too many. However, the tests stopped passing after PR #803, so passing that that seems out of the scope for this PR.
In a future PR it would be interesting to also vectorize the "aggregate values based on nearest to cell node"-function, and other aggregation functions.

Nice. I have fixed the failing test in pull request #289, so I think this is ok to merge. We should add some test for gdf_to_da, gdf_to_bool_da and the other methods in grid.py...

Is there a flopy function to leave out parts of a vertex modelgrid? I would like to try it to see if it would speed up gdf_to_da

I'm not aware of any such functionality, though it should be fairly easy to use gridintersect to create a subset of geometries based on an intersection result. Recreating a model grid from that object would be a bit difficult though. But since you need to build the intersection geometries for that step anyway, I doubt it will speed things up much leaving them out of the next intersection calculations? The shapely intersection routines should be able to query the relevant parts of the grid relatively quickly, I think?

Perfect, thank you so much for your response. I'll leave it at that then.


Custom control strip

Is your feature request related to a problem? Please describe.
There are two things I need from the touch bar: the esc key in its usual place and the control strip. I'd also like to move the dock into it to save some space on the screen, but doing so causes the (X) button to be added on the left, moving the esc key. I can't live with that.
Describe the solution you'd like
Since the OS adds that button when the control strip is present, one solution to my problem would be to replace the system's control strip with a custom one that does the same thing (at least volume and brightness).
Describe alternatives you've considered
You could try to hack around it with private APIs but it would be painful to support.

Pock 0.5 has a built-in widget that shows Volume and Brightness buttons. Long press or swipe on one of those buttons will invoke the slider control.


Relax URI requirement on payloadType?

Currently payloadType MUST be a URI. I'm leaning towards relaxing this requirement to be a SHOULD, and possibly also recommending Media Type as an alternative. The benefit is that Media Types are already an established mechanisms for designating the type of media and are used extensively in Docker/OCI.
The purpose of this field is to avoid confusion attacks where the verifier interprets the payload in a way that the signer did not intend. For this reason, a media type like application/json is bad (and we should discourage it) because it's too ambiguous. But we could instead having an application-specific type like
But we can recommend something like Docker/OCI does, e.g. application/vnd.oci.descriptor.v1+json, which really serves the same purpose as the URI.
Any thoughts one way or the other?

Something like the Docker/OCI alternative mentioned seems reasonable to me instead of just application/json.
If the URI requirement is dropped to a SHOULD, would implementations be expected to also support media type alternatives? Especially if the spec lists them as an alternative?

I'm thinking that we'd say something like:

payloadType is an opaque, case-sensitive string that uniquely and unambiguously identifies how to interpret payload. This includes both the encoding (JSON, CBOR, etc.) as well as the meaning/schema. To prevent collisions, it SHOULD be either:

(recommended) A case-normalized URI. Example: https://in-toto.io/Statement/v1-json
A lowercase Media Type (a.k.a. MIME type or Content Type). Example: application/vnd.in-toto.statement.v1+json.

IMPORTANT: If Media Type is used, it SHOULD NOT be a generic one that only represents encoding but not schema. For example, application/json is almost always WRONG. Instead, invent a media type specific for your application in the application/vnd namespace.

I like the option to use media type. This would also allow for future use within OCI without any major changes.

I'm thinking that we'd say something like:

Thanks @MarkLodato. This seems reasonable to me.

Thanks! Sent out pull request #26 to implement.


Pino 8 support

There was a previous request for this at #1147
but the related pr just removed testing on Pino 8

never mind see #1108 and related pr that adds pino 8


the rule is so clear, why use AI?

a program like https://projecteuler.net/problem=1 can solve it

It's an interesting demonstration - like the "hello world" of AlphaZero derivatives.


Starting tech issues

Mod source
Factorio Mod Portal
Operating system

=Windows 10

What kind of issue is this?

[ ] Compatibility
[ ] Locale (names, descriptions, unknown keys)
[ ] Graphical
[ ] Crash
[X] Progression
[ ] Balance
[ ] Pypostprocessing failure
[ ] Other

What is the problem?

These are the starting techs for a full Py run. The four ones with later techs shouldn't show there, obviously.
I also think the radar is weirdly placed, since it requires circuits to craft, which are later in the progression.
Steps to reproduce
No response
Additional context
No response
Log file
No response

Uranium is also made available too early, depending only on Concrete. I assume it's the same underlying issue.

Another possibly broken one: The lamp doesn't depend on glass. I don't remember if it did in 1.1

It seems to be ok - the lamp still requiring glass to be produced.

Ah the radar one just shouldn't exist, the proper one comes later in the proper place.

Oil well also seems a bit premature.

The common pattern seems to be that these are base Factorio techs that are missing their additional Py dependencies?

I spent some time trying to debug this. It appears that the cached configs haven't been properly re-generated for Factorio 2.0. An obvious error is  here where the cache still refers to "optics" instead of "lamp" as the technology name.
Unfortunately my attempts to force pypostprocessing into dev mode ended in exciting back traces and all sorts of sadness, so I can't confirm that the correct tech tree would be generated without the caches.

Perhaps related: Both Storage Tanks and Niobium unlock niobium pipes.
In other words, you get the recipe for niobium pipes as soon as you research storage tanks.


iOS build failure - pod install failure

Describe the bug
created a blank application with swift and java. installed this package.
To Reproduce
Steps to reproduce the behavior:

flutter run

Smartphone (please complete the following information):

Device: iOS XR Simulator
Version Flutter 1.2.1

Logs
`Jawands-Mac:flutter_bar_code_scanner jawandsingh$ flutter run
Launching lib/main.dart on iPhone Xʀ in debug mode...
Running pod install...                                              1.2s
CocoaPods' output:
↳
Preparing
Analyzing dependencies

Inspecting targets to integrate
  Using `ARCHS` setting to build architectures of target `Pods-Runner`: (``)

Fetching external sources
-> Fetching podspec for `Flutter` from `.symlinks/flutter/ios`
-> Fetching podspec for `flutter_barcode_scanner` from
`.symlinks/plugins/flutter_barcode_scanner/ios`

Resolving dependencies of `Podfile`
[!] CocoaPods could not find compatible versions for pod "flutter_barcode_scanner":
  In Podfile:
    flutter_barcode_scanner (from `.symlinks/plugins/flutter_barcode_scanner/ios`)

Specs satisfying the `flutter_barcode_scanner (from
`.symlinks/plugins/flutter_barcode_scanner/ios`)` dependency were found, but they
required a higher minimum deployment target.

/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/molinillo-0.6.6/lib/molinillo/resolution.
rb:328:in `raise_error_unless_state'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/molinillo-0.6.6/lib/molinillo/resolution.
rb:310:in `block in unwind_for_conflict'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/molinillo-0.6.6/lib/molinillo/resolution.
rb:308:in `tap'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/molinillo-0.6.6/lib/molinillo/resolution.
rb:308:in `unwind_for_conflict'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/molinillo-0.6.6/lib/molinillo/resolution.
rb:684:in `attempt_to_activate'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/molinillo-0.6.6/lib/molinillo/resolution.
rb:254:in `process_topmost_state'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/molinillo-0.6.6/lib/molinillo/resolution.
rb:182:in `resolve'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/molinillo-0.6.6/lib/molinillo/resolver.rb
:43:in `resolve'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/cocoapods-1.6.1/lib/cocoapods/resolver.rb
:91:in `resolve'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/cocoapods-1.6.1/lib/cocoapods/installer/a
nalyzer.rb:909:in `block in resolve_dependencies'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/cocoapods-1.6.1/lib/cocoapods/user_interf
ace.rb:64:in `section'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/cocoapods-1.6.1/lib/cocoapods/installer/a
nalyzer.rb:907:in `resolve_dependencies'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/cocoapods-1.6.1/lib/cocoapods/installer/a
nalyzer.rb:114:in `analyze'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/cocoapods-1.6.1/lib/cocoapods/installer.r
b:266:in `analyze'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/cocoapods-1.6.1/lib/cocoapods/installer.r
b:174:in `block in resolve_dependencies'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/cocoapods-1.6.1/lib/cocoapods/user_interf
ace.rb:64:in `section'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/cocoapods-1.6.1/lib/cocoapods/installer.r
b:173:in `resolve_dependencies'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/cocoapods-1.6.1/lib/cocoapods/installer.r
b:136:in `install!'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/cocoapods-1.6.1/lib/cocoapods/command/ins
tall.rb:48:in `run'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/claide-1.0.2/lib/claide/command.rb:334:in
`run'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/cocoapods-1.6.1/lib/cocoapods/command.rb:
52:in `run'
/usr/local/Cellar/cocoapods/1.6.1/libexec/gems/cocoapods-1.6.1/bin/pod:55:in `<top
(required)>'
/usr/local/Cellar/cocoapods/1.6.1/libexec/bin/pod:22:in `load'
/usr/local/Cellar/cocoapods/1.6.1/libexec/bin/pod:22:in `<main>'

Error output from CocoaPods:
↳
[!] Automatically assigning platform ios with version 8.0 on target Runner because
no platform was specified. Please specify a platform for this target in your Podfile.
See https://guides.cocoapods.org/syntax/podfile.html#platform.
Error running pod install
Error launching application on iPhone Xʀ.`
Flutter Doctor
`Jawands-Mac:flutter_bar_code_scanner jawandsingh$ flutter doctor -v
[✓] Flutter (Channel stable, v1.2.1, on Mac OS X 10.14.4 18E226, locale en-GB)
• Flutter version 1.2.1 at /Users/jawandsingh/Documents/development/flutter
• Framework revision 8661d8aecd (8 weeks ago), 2019-02-14 19:19:53 -0800
• Engine revision 3757390fa4
• Dart version 2.1.2 (build 2.1.2-dev.0.0 0a7dcf17eb)
[✗] Android toolchain - develop for Android devices
✗ Unable to locate Android SDK.
Install Android Studio from: https://developer.android.com/studio/index.html
On first launch it will assist you in installing the Android SDK components.
(or visit https://flutter.io/setup/#android-setup for detailed instructions).
If Android SDK has been installed to a custom location, set ANDROID_HOME to that location.
You may also want to add it to your PATH environment variable.
[✓] iOS toolchain - develop for iOS devices (Xcode 10.2)
• Xcode at /Applications/Xcode.app/Contents/Developer
• Xcode 10.2, Build version 10E125
• ios-deploy 1.9.4
• CocoaPods version 1.6.1
[!] Android Studio (not installed)
• Android Studio not found; download from https://developer.android.com/studio/index.html
(or visit https://flutter.io/setup/#android-setup for detailed instructions).
[✓] VS Code (version 1.33.1)
• VS Code at /Applications/Visual Studio Code.app/Contents
• Flutter extension version 2.25.0
[✓] Connected device (1 available)
• iPhone Xʀ • B95B7422-090E-4B66-8DA9-3433121B259C • ios • com.apple.CoreSimulator.SimRuntime.iOS-12-2 (simulator)
! Doctor found issues in 2 categories.
`

sorry about it. Should have read the iOS documentation. I need to change the Deployment target to 10.


When there are more than 7 entry points, webpack is strucking

AS mentioned i have an app that has 13 entry points but it is failing to build when i use webpack command ,when i reduce some entry points to 6 then it is working fine.
can anybody explain why this is happening.

Could you provide an example or more steps to reproduce?
It's likely not the exact number of entry points but rather the operations that will occur with a certain set of entry points.

if it is due to number of operations, what is the solution for that.
for now , im reduced entry points and building the project for entire project im building with 3 different times with 3 different entry points each, but then chunks are misalliged or not in order.
please tell me any temporary solution for that.

I can't provide a solution because I cannot reproduce the issue. Could you provide an example or more steps to reproduce?

I tried with sample project to reproduce the issue but in that case it is working fine.

yes i have big dependency tree, with large no of requires.

Additional details i run this command
webpack --progress
every time it is strucking at progrerss
53% 63/87 build modules

for now im using named chunks rather than id's.

@pavankumarkatakam Any luck with the issue? Could you try setting up a reproducible test case again?

No its still appears, but i noticed that if it has more number of require's then it is strucking....

@pavankumarkatakam Ok. It would be great if you could set up a standalone case to study. There is no other way to debug the problem properly.

Sure, i will make one.

@pavankumarkatakam Could you please have a look? That standalone example would help.

Hi @bebraw , after updating the sass loader its working fine. At that time i has a couple of css (sass-loader) mistake which caused webpack to struck with out intimating the error. Now its working fine and sorry to close this issue. can i close it now.

Thanks!


What versions of Python and python-lzf are supported?

I created a fresh conda environment using Python 3.9, and while rdbtools installed successfully, I am unable to pip install python-lzf into it.   Neither their repository or this one list the base version requirements for getting everything installed properly.  Since it says python-lzf is "optional but highly recommended to speed up parsing", could you provide the base version requirements for everything to play nicely together?

As an update, I was able to successfully install on an RHEL8 machine.
python 3.9.6
python-lzf 0.2.4
rdbtools 0.1.15
My initial error was on my Macbook running Big Sur (11.5.2), and it seems the latest upgrade has messed with the location of xcode developer tools, and subsequently the C headers that python uses to build packages like python-lzf.

Last comment, after many many failed attempts, the fix for my macbook was use to get homebrew fixed, and use it to install llvm.
To fix a path problem for brew, I follow the advice on this comment:
https://github.com/httpie/httpie/issues/645#issuecomment-456902997
1)brew doctor
2)sudo chown -R $(whoami) $(brew --prefix)/*
3)sudo install -d -o $(whoami) -g admin /usr/local/Frameworks
After that I used brew to install llvm:
brew install llvm
Once llvm installed successfully, I was able to pip install python-lzf with no problem.


pull request for e2e test at 02/02/2017 05:45:14

:white_check_mark: Validation status: passed
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.


Ghost v3.0.2 crashes Safari v13.0.3 on saving HTML element

Issue Summary
Ghost v3.0.2 crashes Safari v13.0.3 on saving HTML element, after update from Ghost v2.x.
To Reproduce

Create/modify a post
Add an HTML code element
Safari should crash, Google Chrome on OSX shouldn't

I consider it a bug in the Safari browser (a site shouldn't be able to crash a browser). However, as Ghost v3 triggers the problem, and the same content on v2 didn't issue the problem, it maybe be resolved somehow.
Technical details:

Ghost Version: 3.0.2
Node Version: 10.17.0
Browser/OS: OSX Safari 13.0.3
Database: SQLite

I would like to also thank the Ghost developers for creating such a wonderful piece of software.

It sounds like this may be a duplicate of https://github.com/TryGhost/Ghost/issues/11162
Safari 13.0.2 (156<IP_ADDRESS>.1) doesn't have any problems, however earlier versions of 13.0.2 and 13.0.1 were crashing. It would appear that Safari may have re-introduced a bug 😕

@digitall-it please feel free to reopen if this issue still persists and you think it's not a duplicate ;)

The issue still persists. It just hangs whenever I try to edit a post.

macOS Mojave 10.14.6
Safari 13.0.3 (146<IP_ADDRESS>.1)
ghost 3.0.3


Run with CORS disabled

A command to start chrome with CORS disabled in the README

@OndrejM Can you have a look at this?


Consider adding Bidirectional Map

https://en.wikipedia.org/wiki/Bidirectional_map

You can create one very easily.
class BiMap
{
    protected $map;

    public function __construct()
    {
        $this->map = new \Ds\Map();
    }

    public function put($key, $value)
    {
        $this->map->put($key, $value);
        $this->map->put($value, $key);
    }

    public function get($key)
    {
        return $this->map->get($key);
    }
}

Or am I missing something here?

The ideal is to provide fundamental structures that allow for easy composition.

Or am I missing something here?

length, keys, values would be 2x; few corner cases and specifics; room for memory optimization (2 maps/tree).

The ideal is to provide fundamental structures that allow for easy composition.

I'm ok with that, just thought it would be convenient for users to have a good implementation(s) of the bimap here, because I haven't seen one for php yet.

Good points, especially around length being 2x. Could you compose using 2 maps instead and override length? What would length return anyway; max(k.length, v.length)?
I'll take a closer look at BiMaps because I don't know much about them.


Automated rewards and calculation

Closes https://github.com/onflow/flow-core-contracts/issues/266
Updates the epoch contract to calculate and pay rewards automatically every epoch
The epoch admin can enable or disable automatic rewards.
If automatic rewards are enabled, the contract calculates the rewards for the next epoch based on the supply increase percentage defined in the contract, which the admin can also control. It also pays the rewards for the current epoch.
If automatic rewards are disabled, the contract will only calculate rewards for the current epoch but will not pay them
resetEpoch has been updated to not set a new payout amount because it isn't necessary
The staking contract has a function to get the fee balance because adding a new import address to the epoch contract was breaking the bootstrapping integration in flow-go, which we'll hopefully be able to fix once this is close to merging.

Yeah, we'll need to do a reward payout manually and set the new payout manually as well when we do reset epoch, which still fits with this.
If epoch preparation fails, won't we just run reset epoch and pay rewards manually before the next epoch is supposed to begin? why would it have to last until the next spork?
The argument count in lib/go/contracts/FlowEpoch doesn't match flow-go bootstrapping any more since I had to add the fees import address so that was causing it to fail

If epoch preparation fails, won't we just run reset epoch and pay rewards manually before the next epoch is supposed to begin? why would it have to last until the next spork?

What I mean is, if we do nothing, the epoch counter will stay the same until the next spork. In this case we must ensure rewards are paid out. We could potentially run resetEpoch alongside manual reward payout, though I don't think this is necessary.
What is the best way to test this before deploying to Mainnet? It might be as simple as a unit test here which calls payRewards multiple times without a corresponding epoch transition. Or we could artificially trigger epoch fallback on benchnet and test paying rewards there.

We've done this before, so I don't think it would be an issue. The only difference with these additions to the contract is that we'd just disable automatic rewards, then call the pay rewards functions directly in the staking contract instead of through the epoch contract.