Does quic-go provides both reno and cubic?

Hi, I've read that quic-go uses NewReno by default. But I can see multiple references to cubic (e.g. in cubic_sender.go). Is cubic fully functional in quic-go and can I choose between these CC algorithms? Thanks

No, we only implement NewReno, as described in the RFC. The file is called cubic_sender for historical reasons (sorry for the confusion!), but it doesn't actually provide a Cubic implementation.

Thank you. I asked because there is a boolean variable called reno in cubic_sender and there are different code paths dependent on this variable. If I understand correctly, these 'alternative' code paths are probably for historical reasons, too?

Yes, that's correct.

Thank you very much


unidirectional @OneToMany and @OrderColumn

Fixes #589 and #581.

I'm going to merge this one soon because I don't want it to turn into a whole separate dev branch. You guys need to be basing your wok on this stuff.
I'm not totally happy with the tests but at least there's quite a few of them, and perhaps I'll open an issue to improve them.


Geofence version issue

When I am going to use geofence plugin it shows
The Android Gradle plugin supports only Kotlin Gradle plugin version 1.2.51 and higher. Project 'geofence' is using version 1.2.30.

This is not a duplicate, the fix is also required in the main build.gradle file not just the example one

@DigNZ You mean https://github.com/flutter/flutter/blob/b47da6c2b79d90f33d73e9225b4b3bbbd0ffd99e/packages/flutter_tools/templates/plugin/android-kotlin.tmpl/build.gradle.tmpl#L5 ?

Apologies, the version in this repo is fine. I had to edit this file inside .pub-cache in order to get it to build:
https://github.com/ubheamar/flutter_geofence/blob/42408acbd69d6cfebabbec4a6642635360e7fbd3/android/build.gradle#L5
Where as this issue:
https://github.com/ubheamar/flutter_geofence/issues/1
Only changed the version in the example.
However it seems like it must've been something at my end as the version in the repo seem to match.
Ignore this.


Integrate Etherscan API

It would be nice if Multisol provided a way to verify a contract programatically, on top of just creating a folder that must be uploaded by the user on Etherscan.
Other tools like solt expose this functionality in their API.

Looks like Foundry has added support for this in the meantime:
https://book.getfoundry.sh/forge/deploying.html
I could either inspire from their work when implementing this feature in Multisol, or I could just forget about it and close this issue.


Migration FinOps-Hub 0.1 to 0.2

Is there an active migration path to move from 0.1 to 0.2 I was not able to find one in the repository.

Interested too. I currently have an unintended 0.1 deployment. Not sure how to proceed, or if I need to redo all my exports on a new deployment etc.

https://microsoft.github.io/finops-toolkit/powershell/hubs/Deploy-FinOpsHub

The Deploy-FinOpsHub command either creates a new or updates an existing FinOps hub instance by deploying an Azure Resource Manager deployment template. The FinOps hub template is downloaded from GitHub. To learn more about the template, see the FinOps hub template.

It appears that everything directs you to use the powershell commands to upgrade, but documentation unclear due to typos? I might try anyway.

I tried the template deployment but that one failed for me. That is why I created the issue

I started working on an upgrade doc that should be ready soon. That said, we've identified 2 bugs in FinOps hubs 0.2 that are blocking deployments. Hold off on the upgrade while we get 0.2.1 out to resolve these issues. Apologies for the inconvenience! 😥

PowerShell is not required. The template deployment covers the hubs update. The only special thing in this case is deleting old exports and creating new ones. That said, the 2 bugs are causing a problem that's getting in the way. I'm hoping to have a release out by Monday.

@psilantropy Deploy-FinOpsHub can both create a new hub or update an existing one. Thanks for pointing out the inconsistencies! I'll get those fixed in the next update as well.

Update: Here's a release candidate for hubs to address the 2 known bugs in 0.2: https://aka.ms/finops/hubs/rc. Please let me know if you run into any issues with that.

Update: Here's a release candidate for hubs to address the 2 known bugs in 0.2: https://aka.ms/finops/hubs/rc. Please let me know if you run into any issues with that. We'll have an official release out soon.

Thanks. I'll give it a try shortly :)
FYI on your deploy to az button;

There was an error downloading the template from URI 'https://gist.github.com/flanakin/419b5ed778d12a109b297d0dd406c10f/raw/bd1bbd8e3a07b09d324ba849bd57a73eca747d14/azuredeploy.json'. Ensure that the template is publicly accessible and that the publisher has enabled CORS policy on the endpoint. To deploy this template, download the template manually and paste the contents in the 'Build your own template in the editor' option below.

@psilantropy I fixed the Deploy to Azure button. Feel free to try again: https://aka.ms/finops/hubs/rc

@psilantropy I fixed the Deploy to Azure button. Feel free to try again: https://aka.ms/finops/hubs/rc

Deployed now. Keen to try the hub based reports. Thank you :)


feat(examples): add tinygo postgres example

Signed-off-by: Brooks Townsend<EMAIL_ADDRESS>Feature or Problem
This PR adds a tinygo example for postgres, essentially mirroring the structure of the Rust example (just omitting the final query)
Related Issues

Release Information

Consumer Impact

Testing

Unit Test(s)

Acceptance or Integration

Manual Verification

@vados-cosmonic lmk if this addressed your comments, good to merge once those are resolved!

Sorry @brooksmtownsend a bit late here, but thanks for making those changes!


F.Promise with Multi Object to Scala Template Play Framework Java

I have two objects bookmark, bookmarks, i want to pass object as parameters to Scala Templates like
return ok(views.html.bookmarks.list.render(bookmark, bookmarks));
in F.Promise,
F.Promise<Bookmark> bookmark = Bookmark.findById(id);
F.Promise<Collection<Bookmark>> bookmarks = Bookmark.findAll();
// here how to write the code that should pass both objects to scala template

}
How to write the return statement to pass these two objects in F.Promise without Json Result?

Hi,
Promise design is really made to promote composition. So you can compose any Promise with other Promises using flatMap and map. If you have a lot of promises to compose, it can be pretty tedious to write, but it's doable, especially if you're using Java 8. If you're using Scala, you can easily replace all map and flatMap calls with a single for comprehension expression.
Anyway, in Java you just have to write something like :
public class BookmarkController extends Controller {

    public static F.Promise<Result> list(Long id) {
        F.Promise<Bookmark> futureBookmark = Bookmark.findById(id);
        F.Promise<Collection<Bookmark>> futureBookmarks = Bookmark.findAll();
        return futureBookmark.flatMap(bookmark ->
            futureBookmarks.map(bookmarks ->
                ok(views.html.bookmarks.list.render(bookmark, bookmarks))
            )
        );
    }
}

I tried with your code,
public static F.Promise get(String id) {
F.Promise futureBookmark = Bookmark.findById(id);
F.Promise<Collection> futureBookmarks = Bookmark.findAll();
return futureBookmark.flatMap(futureBookmark ->
futureBookmarks.map(futureBookmarks ->
ok(views.html.bookmarks.list.render(futureBookmark, futureBookmarks))
)
);
}
But it shows warning at return futureBookmark.flatMap(futureBookmark -> and futureBookmarks.map(futureBookmarks ->,  futureBookmark wants to cast into int, futureBookmarks wants to cast into Status ,also may i know, where the bookmark, bookmarks came from in your code return statement? since you have used futureBookmark, futureBookmarks.

it seems the name of the closures args are the same than promises
futureBookmark.flatMap(futureBookmark ->

should be
futureBookmark.flatMap(bookmark ->

and the same for futureBookmarks

public static F.Promise get(final String id) {
		F.Promise futureBookmark = Bookmark.findById(id);
        F.Promise> futureBookmarks = Bookmark.findAll();
        return futureBookmark.flatMap(bookmark ->
        	futureBookmarks.map(bookmarks ->
                ok(views.html.bookmarks.render(bookmark, bookmarks))
            )
        );
	}

I am getting the
Multiple markers at this line
- bookmark cannot be resolved to a variable
- Syntax error on token "-", -- expected
- Line breakpoint:Bookmarks [line: 30] -
get(String)
error on eclipse.

I guess you're not using Java 8

Yes... Just i was thinking, it is Java 8 code. Is it possible to achieve in Java 7?

Yes you can write it like :
    public static F.Promise<Result> index(Long id) {
        F.Promise<Bookmark> futureBookmark = Bookmark.findById(id);
        F.Promise<Collection<Bookmark>> futureBookmarks = Bookmark.findAll();
        return futureBookmark.flatMap(new F.Function<Bookmark, F.Promise<Result>>() {
            @Override
            public F.Promise<Result> apply(final Bookmark bookmark) throws Throwable {
                return futureBookmarks.map(new F.Function<Collection<Bookmark>, Result>() {
                    @Override
                    public Result apply(Collection<Bookmark> bookmarks) throws Throwable {
                        return ok(views.html.bookmarks.list.render(bookmark, bookmarks));
                    }
                });
            }
        });
    }

Thanks @mathieuancelin. Now its working, Are there any sites to learn the functional programming in Java 7?

I have no idea. Several libraries provide that kind of paradigm.
Actually it's very similar to Java 8 closures. You just have to write de full code for the anonymous inner classes. You IDE should provide all the support you need to know what to write


Highlight Detection query

Hello, Thanks for your work. But I have a question.
I understood that Highlight Detection "does not need" a query (whereas Moment Retrieval needs it).
so, What query should I input to detect highlight?

@ohhyonghee
Hi, thank you for your interest. Good question! Let me describe the background first, then answer the question.

I understood that Highlight Detection "does not need" a query (whereas Moment Retrieval needs it).

Before introducing TVSum dataset, Highlight detection does not need a text query (e.g., https://people.csail.mit.edu/khosla/papers/cvpr2013_khosla.pdf). But these approaches suffer from dealing with a variety of topics in online videos.
To address this issue, Song et al. proposed the TVSum dataset, which consists of text query and videos for highlight detection. QVHighlights also necessitates a text query. Lighthouse also adopts them, so the implemented models

so, What query should I input to detect highlight?

The input query should describe the moments (topics) that you want to highlight in the videos.
Take the sample video for example. If you want to highlight the moments of man's speaking, please write like: "A man is speaking".
If you want to highlight the market scenes, please write "market".

I close this issue. If you have any further questions, please re-open and discuss.


Worker goroutines to reduce the number of concurrent goroutines reading from RepositoryPaths

This would take care of the following issues:

be sure to avoid the case where a given goroutine monitoring a RepositoryPath returns silently
reduce the number of goroutines starting up all at once at the beginning and cloning repos all at once

One way to do it:
Could still have a map of GitSyncs to store state (maybe a map of maps where the inner map is the RepoPath or a map of GitSyncProcessors which contains a map of RepoPaths). The reconcile functionality would just update the state of memory in that map, plus if there are any new RepositoryPaths (whether they come from a new GitSyncs or an existing GitSync), add them to a channel. The workers could look up the state in the map and if the RepoPath or GitSync has been deleted, just return.
For ensuring that we don't pull from github more than once every 3 minutes, we could store the last time in the state, and return in the case that not enough time has gone by.
To ensure synchronous processing within a repository path, the goroutine could add itself back to the channel at the end.


Doesnt seem to be working in Unity 2022.3.6f1, the standard unity version for vrc atm.

This is just one out of the "999+" error messages it gave me upon opening the tool, and the buttons and stuff were greyed out, and upon clicking the area to choose an avatar the entire window freezes and needs to be closed.
IndexOutOfRangeException: Index was outside the bounds of the array.
 Do you have one when trying to open the window?
Either way, I should have put a check in, warning you if you don't.

Yes I do, it has an avatar descriptor and components for parameters and the menu stuff, by default it has the avatar selected.

Though when opening, all options are greyed out an unusable

Okay, so I opened it up and took a closer look. This version does work fine on the unity version, so that's not an issue (I've been using it personally a lot). Looks like it is throwing an error because your avatar descriptor does not have the full array of animator types. there is a bug I've ran into before where the descriptor breaks. Maybe try re-adding it and see if it works?

There should be 5 slots, and it's not finding the 5th for some reason:

Alright, one moment. ty for your patience

OK, re adding the script didn't seem to fix anything (avatar descriptior) and the menu still kept freezing when clicking where it says catvoir

OK I went in and fixed a bunch of stuff on my avatar and it seems to he working now, excuse my incompetence please. I am still new with unity and to avatar creation.


Running with no result

Hi, I installed and enabled the plugin for Obsidian but when I run it, I get no results.  Do you have any ideas?
Thank you

Oh I am sorry. Could you open the console with Ctrl + Shift + I? Is there any error, when you run the command?

Working now.  Thank you 👍


Checkboxes doesn't work with Opera

Seems like opera has some issues with complicated selectors like that:
.checkbox input[type="checkbox"]:checked + label::after {
    font-family: 'FontAwesome';
    content: "\f00c";
}

Checked in Opera 12.17, Windows

Fixed. Now works in Opera.


Replay on multiple vehicles

The replay function of the modern interface, is possible with only one vehicle at a time. It would be nice to be able to select multiple vehicles (and a group) to see, for example, the day's trips of the entire fleet. (On the old interface it was possible with the route report).

It's already implemented.

I don't see the option to select the group (I'm on demo2 server which I guess has 5.3)! Is there any setting?

Route report. You can't select a group, but you can multiple vehicles.

In the route report, I cannot select more than one vehicle (in the summary, I can). However, even using that report I can't see the tracks on the map at the same time!

In the route report, I cannot select more than one vehicle

It means you're not using the latest version of Traccar. You should upgrade first.


ci: exclude dependency update in changelog

Signed-off-by: Jason Liu<EMAIL_ADDRESS>Ⅰ. Describe what this PR does

Ⅱ. Does this pull request fix one issue?

Ⅲ. Describe how to verify it
Ⅳ. Special notes for reviews
V. Checklist

[x] I have written necessary docs and comments
[x] I have added necessary unit tests and integration tests
[x] All checks passed in make test

/approve


pull request for e2e test at 02/03/2017 11:56:05

: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.


Fix auto-theme after midnight

Describe the bug
If hour is between 0 and 20 theme is setted as light.
To Reproduce
Enter app after midnight
Expected behavior
Theme should be dark from 20:00 to 07:00
Screenshots
Desktop (please complete the following information):
Smartphone (please complete the following information):
Additional context

:tada: This issue has been resolved in version 1.6.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:

:tada: This issue has been resolved in version 1.7.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


[BUG] Getting error from HugeCTR inference notebook

I am getting this error from HugeCTR inference notebook when I send a request to TIS:
#placeholder variables for the output
outputs = []
outputs.append(httpclient.InferRequestedOutput("OUTPUT0"))
# make the request
with httpclient.InferenceServerClient("<IP_ADDRESS>:8001") as client:
    response = client.infer('movielens_ens', inputs, request_id=str(1), outputs=outputs)

print("predicted sigmoid result:\n", response.as_numpy("OUTPUT0"))
#placeholder variables for the output
outputs = []
outputs.append(httpclient.InferRequestedOutput("OUTPUT0"))
# make the request
with httpclient.InferenceServerClient("<IP_ADDRESS>:8001") as client:
    response = client.infer('movielens_ens', inputs, request_id=str(1), outputs=outputs)
```

ValueError                                Traceback (most recent call last)
 in
6     response = client.infer('movielens_ens', inputs, request_id=str(1), outputs=outputs)
7
----> 8 print("predicted sigmoid result:\n", response.as_numpy("OUTPUT0"))
/opt/conda/envs/merlin/lib/python3.8/site-packages/tritonclient/grpc/init.py in as_numpy(self, name)
1630                 else:
1631                     np_array = np.empty(0)
-> 1632                 np_array = np_array.reshape(shape)
1633                 return np_array
1634             else:
ValueError: cannot reshape array of size 64 into shape (3,)

@oyilmaz-nvidia can you check this at your end? Thanks.
@benfred fyi.

@rnyak  I have tested this error with the merlin-inference:0.4 and merlin-inference:0.5 container and I only get it with the container 0.5. Everything looks fine with version 0.4. Will try to understand what's going on but right now I have no idea.

Joey said this is probably related to the JSON config we're generating for hugectr -


Update the content in the PDF Version of the API Programmer's Guide

Problem statement
Some content has been updated in the Web Version of the API Programmer's Guide to include guidance to the File Validator tool and the Public Key tool. To ensure both the PDF and the Web Version are in alignment at launch, we need to update the PDF version to match the content updates in the Web version.
What you need to know

Existing Guide
...

Acceptance criteria

[ ] Content/Guidance found in the latest version of the Web Version of the API Programmer's Guide matches that of the PDF version
[ ] The PDF version is up-leveled and saved as a new PDF document
[ ] The updated PDF file is linked in the engineering ticket #9424

To do

[ ] ...

New doc

Approved. new PDF here

Linked the pdf in 9424. Closing. @chris-kuryak


[backport] Fix OverflowError passing large integer to elementwise operation

The backport of #564.

jenkins, test this please.

LGTM!


[BACKLOG-32906] Add avro file type

:white_check_mark: Build finished in 10m 28s
Build command:
mvn clean verify -B -e -Daudit -amd -pl \
plugins/file-open-save-new/core,ui

:ok_hand: All tests passed!
Tests run: 1126, Failures: 0, Skipped: 0    Test Results

:information_source:  This is an automatic message


ImportError: DLL load failed: The specified module could not be found.

I have this error, how can i solve this problem?
ImportError: DLL load failed: The specified module could not be found.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "generate_tfrecord.py", line 17, in
import tensorflow as tf
File "C:\Users\User\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow_init_.py", line 24, in
from tensorflow.python import pywrap_tensorflow  # pylint: disable=unused-import
File "C:\Users\User\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python_init_.py", line 49, in
from tensorflow.python import pywrap_tensorflow
File "C:\Users\User\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 74, in
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "C:\Users\User\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 58, in
from tensorflow.python.pywrap_tensorflow_internal import *
File "C:\Users\User\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 28, in
_pywrap_tensorflow_internal = swig_import_helper()
File "C:\Users\User\Anaconda3\envs\tensorflow1\lib\site-packages\tensorflow\python\pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "C:\Users\User\Anaconda3\envs\tensorflow1\lib\imp.py", line 243, in load_module
return load_dynamic(name, filename, file)
File "C:\Users\User\Anaconda3\envs\tensorflow1\lib\imp.py", line 343, in load_dynamic
return _load(spec)
ImportError: DLL load failed: The specified module could not be found.
Failed to load the native TensorFlow runtime.
See https://www.tensorflow.org/install/errors
for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

Please provide following info:
System information

OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
TensorFlow installed from (source or binary):
TensorFlow version:
Python version:
Installed using virtualenv? pip? conda?:
Bazel version (if compiling from source):
GCC/Compiler version (if compiling from source):
CUDA/cuDNN version:
GPU model and memory:

Describe the problem
Provide the exact sequence of commands / steps that you executed before running into the problem
Any other info / logs
Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Windows 10
Pro 64-bit (10.0, biuld 17134)
TensorFlow installed from (source or binary): from source
TensorFlow version: 1.13.1
Python version:  python 3.6
Installed using virtualenv? pip? conda?: conda
CUDA/cuDNN version: CUDA:9.0 / cuDNN: v9
GPU model and memory:    memory:8192MB RAM

On Thu, Mar 14, 2019 at 2:44 AM ymodak<EMAIL_ADDRESS>wrote:

Please provide following info:
System information

OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue
happens on mobile device:
TensorFlow installed from (source or binary):
TensorFlow version:
Python version:
Installed using virtualenv? pip? conda?:
Bazel version (if compiling from source):
GCC/Compiler version (if compiling from source):
CUDA/cuDNN version:
GPU model and memory:

Describe the problem
Provide the exact sequence of commands / steps that you executed before
running into the problem
Any other info / logs
Include any logs or source code that would be helpful to diagnose the
problem. If including tracebacks, please include the full traceback. Large
logs and files should be attached.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
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or mute the thread
https://github.com/notifications/unsubscribe-auth/Ap8eqW7U5LVWFi4v_V07nTf2zdwDfgzeks5vWUcKgaJpZM4bsQfQ
.

Thanks for providing the info. Did you add cuda to your path?
Take a look at this windows setup guide for gpu support if haven't already.
You need to add sub folders: bin , include and ```lib`` to the path. Can you please try adding them as well?

yes i have add cuda in my path. The attachment is my added path.
On Fri, Mar 15, 2019 at 9:16 AM ymodak<EMAIL_ADDRESS>wrote:

Thanks for providing the info. Did you add cuda to your path?
Take a look at this windows setup guide for gpu support
https://www.tensorflow.org/install/gpu#windows_setup if haven't already.
You need to add sub folders: bin , include and ```lib`` to the path. Can
you please try adding them as well?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/tensorflow/tensorflow/issues/26634#issuecomment-473122827,
or mute the thread
https://github.com/notifications/unsubscribe-auth/Ap8eqTAsn-OWbVIbxbWbqAz_wZBWI2CQks5vWvSAgaJpZM4bsQfQ
.

shall i need the NVIDIA package launcher for my cudnna and cuda? if need
may i know the  Product Series,  Product Type and  Product suitable for my
laptop? i have try to download the driver but it cannot work. thanks
On Fri, Mar 15, 2019 at 9:20 AM yen peiyi<EMAIL_ADDRESS>wrote:

yes i have add cuda in my path. The attachment is my added path.
On Fri, Mar 15, 2019 at 9:16 AM ymodak<EMAIL_ADDRESS>wrote:

Thanks for providing the info. Did you add cuda to your path?
Take a look at this windows setup guide for gpu support
https://www.tensorflow.org/install/gpu#windows_setup if haven't
already.
You need to add sub folders: bin , include and ```lib`` to the path. Can
you please try adding them as well?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/tensorflow/tensorflow/issues/26634#issuecomment-473122827,
or mute the thread
https://github.com/notifications/unsubscribe-auth/Ap8eqTAsn-OWbVIbxbWbqAz_wZBWI2CQks5vWvSAgaJpZM4bsQfQ
.

ah I see you are using cuda 9.0. TF 1.13.1 comes with pre built cuda 10.0 binaries. So please upgrade to cuda 10.0 and make sure to add path as well.

thanks for your suggestion.
On Sat, Mar 16, 2019 at 2:05 AM ymodak<EMAIL_ADDRESS>wrote:

ah I see you are using cuda 9.0. TF 1.13.1 comes with pre built cuda 10.0
binaries. So please upgrade to cuda 10.0 and make sure to add path as well.
—
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.

@peyifyp Were able to install TF? Any updates yet.

Automatically closing due to lack of recent activity. Please update the issue when new information becomes available, and we will reopen the issue. Thanks!


chore: use nuxi cli for typechecking

This PR replaces tsc with and nuxt typecheck.
Using nuxi typecheck ensures that types are generated before type-checking. This PR also adds local typescript version and vue-tsc base on nuxt recommendation

Thanks @mahdiboomeri and congrats on your contribution 🎊

Thanks!


TICtxtWrd-hex: Test Improvements, Context Wording, for the ecosystem hex.

Test Improvements, Context Wording, for the ecosystem hex.

completed as part of https://github.com/dependabot/dependabot-core/pull/9868


improve error messages on invalid constants

We need to provide better error message when constants are invalid.
One scenario that especially needs more data is generic instantiation that are substituted by a type variable (since type variables can be used in a constant context).
Compare the error message you get from these 2 examples:
class A<T> {
  final List<T> f;
  A([this.f = const <T>[]]);
}

main() => print(new A<String>().f);

Error: Type variable 'T' can't be used as a constant expression #lib1::A::T.

Q generic<Q>() => null;

class A<T> {
  final T Function() f;
  A([this.f = generic]);
}

main() => print(new A<String>().f);

Error: Not a compile-time constant.

Similar to #33216 ?

Very similar, but still a separate issue because #33216 tracks error reporting for constants in the vm. (most errors are reported by the front-end, but constants are not evaluated in the front-end, instead each backend (dart2js, vm) has it's own evaluation logic and error reporting)

Bump past 2.1?

Since we flipped the constant-update-2018 flag, the CFE now does all constant evaluation and a reasonable error is given for the second case.


Add explanation to exercise 6.2

https://github.com/Mooophy/Cpp-Primer/tree/master/ch06#exercise-62
The solution might be slightly clearer with small explanations of what was changed from the question:
(a) string f() {  // return should be string, not int
          string s;
          // ...
          return s;
    }
(b) void f2(int i) { /* ... */ }  // function needs return type
(c) int calc(int v1, int v2) { /* ... */ }  // parameter list cannot use same name twice
(d) double square (double x) { return x * x; }  // function body needs braces

Sample PR in #531

Thanks for your contribution. :+1:


 Can we allow this number be specified (or disabled) in function.json?

Yes, since Azure Functions is build on the WebJobs SDK, existing documentation on poison blob handling can be found in the WebJobs SDK doc. We're still catching up on Functions doc as you can see. E.g., here's the page on blob processing that mentions how the MaxDequeueCount can be configured.
You can already control this via host.json settings. See the mention of maxDequeueCount on this wiki page.


fix(chat): add more language to file extension mappings for code blocks

Description:
Add more language to file extension mappings
Checklist:

[X] the pull request name complies with Conventional Commits
[X] the pull request name starts with fix(<scope>):, feat(<scope>):, feature(<scope>):, chore(<scope>):, hotfix(<scope>): or e2e(<scope>):. If contains breaking changes then the pull request name must start with fix(<scope>)!:, feat(<scope>)!:, feature(<scope>)!:, chore(<scope>)!:, hotfix(<scope>)!: or e2e(<scope>)!: where <scope> is name of affected project: chat, chat-e2e, overlay, shared, sandbox-overlay, etc.
[ ] the pull request name ends with (Issue #<TICKET_ID>) (comma-separated list of issues)
[X] I confirm that do not share any confidential information like API keys or any other secrets and private URLs

/deploy-review


[Windows] different hashes ([hash]) for same file

i have an image and use it 2 different files (with different relative paths).
image path: web\src\main\webapp\content\images\cooperates\androbaby.png
using in 1.html:
 <img src="../../../content/images/cooperates/androbaby.png">
using in 2.scss
background: url('../../content/images/cooperates/androbaby.png') no-repeat center center;
Loader Rule:
{
                test: /\.(jpe?g|png|gif|svg|woff2?|ttf|eot|otf)$/i,
               loaders: ['file-loader?hash=sha512&digest=hex&name=content/[hash].[ext]']
   }
generates two different hashes and 1 file. so one is not shown.
output file 1 (file exist):
content/d0adfe29ff3ec9a7dfeaf5ae0d780b12.png
output file 2 (file not exist):
content/4e9e80ac5fd47c78ca84b7809259b712.png

Closing due to inactivity. Please test with latest version and feel free to reopen if still regressions. Thanks!

@evilebottnawi hash for SVG is different in mac & windows
an minimum reproducible test repo https://github.com/funkyLover/issue-reproducer/tree/master/hash-check
npm run build # build and check file hash

# mac
  System:
    OS: macOS 10.14
    CPU: (8) x64 Intel(R) Core(TM) i7-7700K CPU @ 4.20GHz
  Binaries:
    Node: 10.13.0 - /usr/local/bin/node
    Yarn: 1.7.0 - /usr/local/bin/yarn
    npm: 6.9.0 - /usr/local/bin/npm

# windows
  System:
    OS: Windows 7
    CPU: (4) x64 Intel(R) Core(TM) i5-6300U CPU @ 2.40GHz
  Binaries:
    Node: 10.15.3 - C:\Program Files\nodejs\node.EXE
    Yarn: Not Found
    npm: 6.4.1 - C:\Program Files\nodejs\npm.CMD

npm run inspect:config:build # inspect webpack config

      /* config.module.rule('svg') */
      {
        test: /\.(svg)(\?.*)?$/,
        use: [
          /* config.module.rule('svg').use('file-loader') */
          {
            loader: 'file-loader',
            options: {
              name: 'img/[name].[hash:8].[ext]'
            }
          }
        ]
      },


Possible Bug: One hour behind

The website did not reset at correct time for me today (1 hour behind), is it a bug or can I change it somewhere myself?

Quickest fix in the west! (I uploaded the wrong file yesterday, as I was doing some testing)


Add async error test for promise and async/await

I test many times,seems there isnt a suitable  way to use Jasmine's toThrow style to test async error.
So i add some codes to illustrate using standard javascript style to test async error .
Do there have a toThrow version test ? I can not make a suitable toThrow test. if there is,should add both of those illustration codes.

@facebook-github-bot import

Thanks for importing. If you are an FB employee go to Phabricator to review.

@facebook-github-bot shipit

Thanks for importing. If you are an FB employee go to Phabricator to review.


Escaped string argument in tasks.json ignored by compiler (objectively the same command with different results)

Type: Bug
Use a project that has libs with dots in the name (e.g. wxWidgets wx-3.2. )
Compiler commands would include here for instance: -l"wxtiff-3.2" -l"wxjpeg-3.2". We have to surround the name with "" otherwise g++ will interpret ".2" as a separate file and fail to compile. This works perfectly when run directly from the Terminal.
Problem: When I create a task inside the tasks.json file with the arguments strings ""-lwxtiff-3.2"" and run the task, g++ sees the dot as a separate file, it then fails of course and vscode switches from debug tab to console and reruns the same command for me, where it executes successfully. The debug command was exactly the same as the one entered in the terminal but there where two different results.
VS Code version: Code 1.85.0 (af28b32d7e553898b2a91af498b1fb666fdebe0c, 2023-12-06T20:48:09.019Z)
OS version: Windows_NT x64 10.0.19045
Modes:

System Info

Item
Value

CPUs
12th Gen Intel(R) Core(TM) i7-12700H (20 x 2688)

GPU Status
2d_canvas: enabledcanvas_oop_rasterization: enabled_ondirect_rendering_display_compositor: disabled_off_okgpu_compositing: enabledmultiple_raster_threads: enabled_onopengl: enabled_onrasterization: enabledraw_draw: disabled_off_okvideo_decode: enabledvideo_encode: enabledvulkan: disabled_offwebgl: enabledwebgl2: enabledwebgpu: enabled

Load (avg)
undefined

Memory (System)
31.72GB (17.17GB free)

Process Argv

Screen Reader
no

VM
67%

Extensions (14)

Extension
Author (truncated)
Version

better-comments
aar
3.0.2

vscode-hide-comments
eli
1.9.0

rainbow-csv
mec
3.9.0

vscode-dotnet-runtime
ms-
2.0.0

cmake-tools
ms-
1.16.32

cpptools
ms-
1.19.1

cpptools-extension-pack
ms-
1.3.0

hexeditor
ms-
1.9.12

makefile-tools
ms-
0.7.0

powershell
ms-
2023.11.1

gcc-md
pha
0.0.1

intellicode-api-usage-examples
Vis
0.2.8

vscodeintellicode
Vis
1.2.30

vscode-surround
yat
1.5.0

(1 theme extensions excluded)

Thanks for creating this issue! It looks like you may be using an old version of VS Code, the latest stable release is 1.85.1. Please try upgrading to the latest version and checking whether this issue remains.
Happy Coding!

have you tried escaping the .?

This issue has been closed automatically because it needs more information and has not had recent activity. See also our issue reporting guidelines.
Happy Coding!


Fix broken link

LGTM - don't know about the previous link but the new one works and the syntax looks good


calib3d: compare error and threshold both in square

resolves #5183
What does this PR change?

use both squared error and squared threshold in estimateAffine3D
work same as FMEstimatorCallback and HomographyEstimatorCallback

Thanks! :+1:


After app update, the application says it needs an update

Hello!  I love your app, however, I updated to 0.1.23 and every time I try to live view any of my cameras, it says "! An app update is required".  I have removed the old version 0.1.21 and reinstalled 0.1.23 and it still says the same thing.  Can you help?  Thank you!

This message actually comes from Blink servers. It seems they have deprecated (again!) some endpoints. I will take a look today and let's hope we can recover this funcionality.

I have released a new version that solves the problem, you should receive an automatic update to viewer0.1.21. Basically some endpoints are being deprecated because they do not identify the account, just network and camera. This may be a cybersecurity improvement or just because network and camera ids no longer identify a single user. By the way nice yard!

Hi Luis!
Thank you for the update and thanks for the compliment on my yard!  That's
last year's picture, I should update that, looks much better this year! :)
As for the update, I still see 0.1.23 on the site and it was last updated
10 days ago.  They stopped the auto updates in this version.  :(  Is the
version you just updated on the site?
Thank you!
Marge
On Fri, Jul 31, 2020 at 2:57 AM Luis Ruiz<EMAIL_ADDRESS>wrote:

I have released a new version that solves the problem, you should receive
an automatic update to viewer0.1.21. Basically some endpoints are being
deprecated because they do not identify the account, just network and
camera. This may be a cybersecurity improvement or just because network and
camera ids no longer identify a single user. By the way nice yard!
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/lurume84/bling-desktop/issues/42#issuecomment-666964592,
or unsubscribe
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.

Hi Luis!
I take that back!!  It just updated and live view is back!  Thank you!!!!
Marge
On Fri, Jul 31, 2020 at 9:23 AM Marge Benedict<EMAIL_ADDRESS>wrote:

Hi Luis!
Thank you for the update and thanks for the compliment on my yard!  That's
last year's picture, I should update that, looks much better this year! :)
As for the update, I still see 0.1.23 on the site and it was last updated
10 days ago.  They stopped the auto updates in this version.  :(  Is the
version you just updated on the site?
Thank you!
Marge
On Fri, Jul 31, 2020 at 2:57 AM Luis Ruiz<EMAIL_ADDRESS>wrote:

I have released a new version that solves the problem, you should receive
an automatic update to viewer0.1.21. Basically some endpoints are being
deprecated because they do not identify the account, just network and
camera. This may be a cybersecurity improvement or just because network and
camera ids no longer identify a single user. By the way nice yard!
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/lurume84/bling-desktop/issues/42#issuecomment-666964592,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AQOQWRJJJIFOZR22IM47G4TR6JTNZANCNFSM4POMB2NA
.

Nice job!  Thanks again!
On Fri, Jul 31, 2020 at 9:58 AM Luis Ruiz<EMAIL_ADDRESS>wrote:

Closed #42 https://github.com/lurume84/bling-desktop/issues/42.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/lurume84/bling-desktop/issues/42#event-3608646560,
or unsubscribe
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.


Skip count call when possible

Pull Request Template for FastCRUD
Description
Hi, I saw you fixed the optional count feature on your own. Sorry, I was a bit busy recently and had some minor issues running poetry on my WSL. New implementation looks cool, just 1 additional thing which I spotted during my development is count can be skipped in some cases entirerly.
Tests
Tests pass without changes.
Checklist

[x] I have read the CONTRIBUTING document.
[x] My code follows the code style of this project.
[x] I have added necessary documentation (if appropriate).
[ ] I have added tests that cover my changes (if applicable).
[x] All new and existing tests passed.

Very nice catch, @JakNowy! Thanks for that.

@JakNowy I'm happy to support this great library!

@igorbenav I'm happy to support this great library!


[v2.7] KDM Update for K8s November patch release

Since November patches are released, October patches are skipped.
KDM Updates
TO BE RELEASED: Enabled OOB post Rancher v2.7.9

New Kubernetes Version
Min Rancher Version
Min RKE Version

1.26.11-rancher1-1
2.7.5-patch0
1.4.6-rc0

1.25.16-rancher1-1
2.7.2-patch0
1.4.0-rc0

Rancher System Images & Add-ons
Note: Please update system images and add-ons in the template as needed.
TBD
Developer Changelog

Add templates for new K8s versions. If a template that hasn't been released yet already exists, update it in place.
Update the default K8s version, and add or update the version information (MinRancherVersion and MinRKEVersion) in k8s_version_info.go for new K8s versions if needed (Use table from above).
Confirm versions for system images, add-on templates are correct using versioning reference table from below (expand details to view the table). Update the table if new versions are introduced.
Confirm add-on template version constraints in template.go are correct using versioning reference table from below (expand details to view the table). Update the table if needed.

Versioning Reference

Expand for system images & add-on templates versioning table

Note: Truncated repository names with a * indicates there are multiple images with that prefix. All repository names that match a truncated prefix should be checked for the same version stated in the table.
For example: rancher/weave-* matches weaveworks/weave-kube and weaveworks/weave-npc, and they should both have the same version.
v1.26.10-rancher1-1

Repository
Tag

rancher/mirrored-coreos-etcd
v3.5.6

rancher/hyperkube
v1.26.10-rancher1

rancher/rke-tools
v0.1.89

rancher/mirrored-k8s-dns-*
1.22.8

rancher/mirrored-cluster-proportional-autoscaler
1.8.6

rancher/mirrored-coreos-flannel
v0.24.4

rancher/flannel-cni
v0.3.0-rancher7

rancher/mirrored-calico-*
v3.25.0

weaveworks/weave-*
2.8.1

noiro/* (All ACI images)
<IP_ADDRESS>.1d150da

rancher/mirrored-pause
3.7

rancher/nginx-ingress-controller
nginx-1.7.0-rancher1

rancher/mirrored-nginx-ingress-controller-defaultbackend
1.5-rancher1

rancher/mirrored-jettech-kube-webhook-certgen
v1.1.1

rancher/mirrored-metrics-server
v0.6.2

rancher/mirrored-coredns-coredns
1.9.4

rancher/mirrored-cluster-proportional-autoscaler
1.8.6

rancher/kubelet-pause
v0.1.6

rancher/mirrored-k8s-dns-node-cache
1.22.10

Add-on Name
Add-on Template Version Constraint

Calico
calicov319

Canal
canalv319

Flannel
flannelv115

CoreDNS
coreDnsv183

KubeDNS
kubeDnsv116

MetricsServer
metricsServerv050

Weave
weavev120

Aci
aciv500

NginxIngress
nginxIngressv110Rancher3

Nodelocal
nodelocalv121

v1.25.15-rancher1-1

Repository
Tag

rancher/mirrored-coreos-etcd
v3.5.4

rancher/hyperkube
v1.25.15-rancher1

rancher/rke-tools
v0.1.87

rancher/mirrored-k8s-dns-*
1.22.8

rancher/mirrored-cluster-proportional-autoscaler
1.8.6

rancher/mirrored-coreos-flannel
v0.15.1

rancher/flannel-cni
v0.3.0-rancher7

rancher/mirrored-calico-*
v3.24.1

weaveworks/weave-*
2.8.1

noiro/* (All ACI images)
<IP_ADDRESS>.1d150da

rancher/mirrored-pause
3.6

rancher/nginx-ingress-controller
nginx-1.2.1-rancher1

rancher/mirrored-nginx-ingress-controller-defaultbackend
1.5-rancher1

rancher/mirrored-jettech-kube-webhook-certgen
v1.1.1

rancher/mirrored-metrics-server
v0.6.2

rancher/mirrored-coredns-coredns
1.9.4

rancher/mirrored-cluster-proportional-autoscaler
1.8.6

rancher/kubelet-pause
v0.1.6

rancher/mirrored-k8s-dns-node-cache
1.22.10

Add-on Name
Add-on Template Version Constraint

Calico
calicov319

Canal
canalv319

Flannel
flannelv115

CoreDNS
coreDnsv183

KubeDNS
kubeDnsv116

MetricsServer
metricsServerv050

Weave
weavev120

Aci
aciv500

NginxIngress
nginxIngressv110Rancher3

Nodelocal
nodelocalv121

Fresh install checks - PASS

On rancher version v2.7.9, KDM pointing to dev-v2.7-2023-11-patches branch, cluster creation succeeds for v1.25.16-rancher2-1, v1.26.11-rancher2-1 on all network providers - canal/flannel/weave/calico
Network checks look good
Canal network checks look good

Upgrade checks - PASS

On rancher v2.7.9, KDM pointing to release-v2.7, cluster creation succeeds for k8s v1.25.14-rancher1-1, v1.26.9-rancher1-1 versions with all network providers.
Pre-upgrade checks look good.
Pointed the KDM branch to dev-v2.7-2023-11-patches.
Upgraded cluster to k8s versions -  v1.25.16-rancher2-1, v1.26.11-rancher2-1.
Post upgrade checks look good.

Minimum rancher version checks - PASS

On rancher v2.7.2 with KDM pointing to dev-v2.7-2023-11-patches branch, cluster creation succeeds for v1.25.16-rancher2-1 versions with all network providers.
Network checks look good.

Minimum rancher version checks - PASS

On rancher v2.7.5 with KDM pointing to dev-v2.7-2023-11-patches branch, cluster creation succeeds for v1.26.11-rancher2-1 versions with all network providers.
Network checks look good.

RKE default k8s version - PASS
dev-v2.7-2023-11-patches should have the default as v1.26.1-rancher2-1
 "RKEDefaultK8sVersions": {
  "0.3": "v1.16.3-rancher1-1",
  "default": "v1.26.11-rancher2-1"
 },

RKE checks using v1.4.12-rc2 passed successfully. All checks passed, hence closing the issue.
Made sure all the images are getting pulled successfully.


Create training error

Hello,
I followed the documentation to generate training data, unfortunately I always get an error. I also tried specifying the config path via -gH.
java -jar "/home/solscale/code/grobid/grobid-quantities/build/libs/grobid-quantities-0.7.1-SNAPSHOT-onejar.jar"  create-training  -dIn /home/solscale/Downloads/test_set -dOut /home/solscale/Downloads/testsolscale resources/config/config.yml
WARN  [2021-12-06 10:07:19,258] org.grobid.core.main.GrobidHomeFinder: No Grobid property was provided. Attempting to find Grobid home in the current directory...
WARN  [2021-12-06 10:07:19,259] org.grobid.core.main.GrobidHomeFinder: ***************************************************************
WARN  [2021-12-06 10:07:19,259] org.grobid.core.main.GrobidHomeFinder: *** USING GROBID HOME: /home/solscale/code/grobid/grobid-quantities/../grobid-home
WARN  [2021-12-06 10:07:19,259] org.grobid.core.main.GrobidHomeFinder: ***************************************************************
WARN  [2021-12-06 10:07:19,260] org.grobid.core.main.GrobidHomeFinder: Grobid config file location was not explicitly set via 'org.grobid.config' system variable, defaulting to: /home/solscale/code/grobid/grobid-quantities/../grobid-home/config/grobid.yaml
INFO  [2021-12-06 10:07:19,286] org.grobid.core.main.LibraryLoader: Loading external native sequence labelling library
INFO  [2021-12-06 10:07:19,291] org.grobid.core.main.LibraryLoader: Loading Wapiti native library...
INFO  [2021-12-06 10:07:19,292] org.grobid.core.main.LibraryLoader: Native library for sequence labelling loaded
INFO  [2021-12-06 10:07:19,294] org.grobid.core.lexicon.Lexicon: Initiating dictionary
INFO  [2021-12-06 10:07:19,294] org.grobid.core.lexicon.Lexicon: End of Initialization of dictionary
INFO  [2021-12-06 10:07:19,294] org.grobid.core.lexicon.Lexicon: Initiating names
INFO  [2021-12-06 10:07:19,294] org.grobid.core.lexicon.Lexicon: End of initialization of names
INFO  [2021-12-06 10:07:19,634] org.grobid.core.lexicon.Lexicon: Initiating country codes
INFO  [2021-12-06 10:07:19,634] org.grobid.core.lexicon.Lexicon: End of initialization of country codes
INFO  [2021-12-06 10:07:19,723] org.grobid.core.jni.WapitiModel: Loading model: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/affiliation-address/model.wapiti (size: 2699936)
[Wapiti] Loading model: "/home/solscale/code/grobid/grobid-quantities/../grobid-home/models/affiliation-address/model.wapiti"
Model path: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/affiliation-address/model.wapiti
[Wapiti] Loading model: "/home/solscale/code/grobid/grobid-quantities/../grobid-home/models/name/header/model.wapiti"
INFO  [2021-12-06 10:07:19,877] org.grobid.core.jni.WapitiModel: Loading model: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/name/header/model.wapiti (size: 2524527)
Model path: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/name/header/model.wapiti
[Wapiti] Loading model: "/home/solscale/code/grobid/grobid-quantities/../grobid-home/models/name/citation/model.wapiti"
INFO  [2021-12-06 10:07:20,031] org.grobid.core.jni.WapitiModel: Loading model: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/name/citation/model.wapiti (size: 440148)
Model path: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/name/citation/model.wapiti
[Wapiti] Loading model: "/home/solscale/code/grobid/grobid-quantities/../grobid-home/models/header/model.wapiti"
INFO  [2021-12-06 10:07:20,052] org.grobid.core.jni.WapitiModel: Loading model: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/header/model.wapiti (size: 17134253)
Model path: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/header/model.wapiti
[Wapiti] Loading model: "/home/solscale/code/grobid/grobid-quantities/../grobid-home/models/date/model.wapiti"
INFO  [2021-12-06 10:07:21,511] org.grobid.core.jni.WapitiModel: Loading model: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/date/model.wapiti (size: 102435)
Model path: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/date/model.wapiti
INFO  [2021-12-06 10:07:21,518] org.grobid.core.jni.WapitiModel: Loading model: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/citation/model.wapiti (size: 16865234)
[Wapiti] Loading model: "/home/solscale/code/grobid/grobid-quantities/../grobid-home/models/citation/model.wapiti"
Model path: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/citation/model.wapiti
[Wapiti] Loading model: "/home/solscale/code/grobid/grobid-quantities/../grobid-home/models/fulltext/model.wapiti"
WARN  [2021-12-06 10:07:22,815] org.grobid.core.utilities.GrobidProperties: No configuration parameter defined for DeLFT engine for model fulltext
INFO  [2021-12-06 10:07:22,815] org.grobid.core.jni.WapitiModel: Loading model: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/fulltext/model.wapiti (size: 26707735)
Model path: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/fulltext/model.wapiti
WARN  [2021-12-06 10:07:24,990] org.grobid.core.utilities.GrobidProperties: No configuration parameter defined for DeLFT engine for model segmentation
[Wapiti] Loading model: "/home/solscale/code/grobid/grobid-quantities/../grobid-home/models/segmentation/model.wapiti"
INFO  [2021-12-06 10:07:24,990] org.grobid.core.jni.WapitiModel: Loading model: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/segmentation/model.wapiti (size: 31133177)
Model path: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/segmentation/model.wapiti
[Wapiti] Loading model: "/home/solscale/code/grobid/grobid-quantities/../grobid-home/models/reference-segmenter/model.wapiti"
INFO  [2021-12-06 10:07:27,945] org.grobid.core.jni.WapitiModel: Loading model: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/reference-segmenter/model.wapiti (size: 4921245)
Model path: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/reference-segmenter/model.wapiti
[Wapiti] Loading model: "/home/solscale/code/grobid/grobid-quantities/../grobid-home/models/figure/model.wapiti"
INFO  [2021-12-06 10:07:28,246] org.grobid.core.jni.WapitiModel: Loading model: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/figure/model.wapiti (size: 422671)
Model path: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/figure/model.wapiti
[Wapiti] Loading model: "/home/solscale/code/grobid/grobid-quantities/../grobid-home/models/table/model.wapiti"
INFO  [2021-12-06 10:07:28,266] org.grobid.core.jni.WapitiModel: Loading model: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/table/model.wapiti (size: 1427222)
Model path: /home/solscale/code/grobid/grobid-quantities/../grobid-home/models/table/model.wapiti
INFO  [2021-12-06 10:07:28,343] org.grobid.core.factory.GrobidPoolingFactory: Number of Engines in pool active/max: 1/10
ERROR [2021-12-06 10:07:28,345] org.grobid.core.utilities.GrobidProperties: No configuration parameter defined for model quantities
WARN  [2021-12-06 10:07:28,345] org.grobid.core.utilities.GrobidProperties: No configuration parameter defined for model quantities
java.lang.NullPointerException
	at org.grobid.core.engines.tagging.TaggerFactory.getTagger(TaggerFactory.java:58)
	at org.grobid.core.engines.tagging.TaggerFactory.getTagger(TaggerFactory.java:28)
	at org.grobid.core.engines.AbstractParser.<init>(AbstractParser.java:27)
	at org.grobid.core.engines.AbstractParser.<init>(AbstractParser.java:22)
	at org.grobid.core.engines.QuantityParser.<init>(QuantityParser.java:97)
	at org.grobid.core.engines.QuantityParser.getNewInstance(QuantityParser.java:73)
	at org.grobid.core.engines.QuantityParser.getInstance(QuantityParser.java:67)
	at org.grobid.core.engines.training.QuantityTrainingData.<init>(QuantityTrainingData.java:47)
	at org.grobid.service.command.TrainingGenerationCommand.run(TrainingGenerationCommand.java:80)
	at org.grobid.service.command.TrainingGenerationCommand.run(TrainingGenerationCommand.java:20)
	at io.dropwizard.cli.ConfiguredCommand.run(ConfiguredCommand.java:87)
	at io.dropwizard.cli.Cli.run(Cli.java:78)
	at io.dropwizard.Application.run(Application.java:93)
	at org.grobid.service.main.GrobidQuantitiesApplication.main(GrobidQuantitiesApplication.java:85)

Can you please help me understand this issue?

Dear @solscale, thanks for your interest in grobid-quantities.
Indeed your problem seems a bug. Sorry about that.
I should have fixed the problem in c68dac1fbec093a6a13d57811f29f391d56a23e2.
Could you please test it and let me know if you encounter other issues?

Dear @lfoppiano, thank you for your quick reply!
Indeed, it's working now.
Best,


Fixed bug with boolean type of object's field in tmx file

Fixes an bug if the imported .tmx file contains an object with a bool field.
like this:

(.rodata+0x6)|| undefined reference to `false'

This got approved but not merged. Was that intentional?

This got approved but not merged. Was that intentional?

Definitely not ;) thanks for telling !
I opened the page and got distracted by my daughter and I guess I accidentally pressed the closed button before merging !


RuntimeError: value cannot be converted to type float without overflow

Hi, I try to train model using python 3, but I got below issue:
/home/v2m/anaconda3/envs/my_env3/lib/python3.7/site-packages/torch/nn/_reduction.py:46: UserWarning: size│
_average and reduce args will be deprecated, please use reduction='sum' instead.                         │
  warnings.warn(warning.format(ret))                                                                     │
/home/v2m/anaconda3/envs/my_env3/lib/python3.7/site-packages/torch/nn/functional.py:2622: UserWarning: nn│
.functional.upsample_bilinear is deprecated. Use nn.functional.interpolate instead.                      │
  warnings.warn("nn.functional.upsample_bilinear is deprecated. Use nn.functional.interpolate instead.") │
0.4247354666311015                                                                                │
0.5617590819998219                                                                                │
0.5815541637890524                                                                                │
0.6344758887881029                                                                                │
Traceback (most recent call last):                                                                       │
  File "pytorch_segmentation_detection/recipes/pascal_voc/segmentation/psp_resnet_50_8s_train.py", line 3│
76, in <module>                                                                                │
    optimizer.step()                                                                                │
  File "/home/v2m/anaconda3/envs/my_env3/lib/python3.7/site-packages/torch/optim/adam.py", line 107, in s│
tep                                                                                │
    p.data.addcdiv_(-step_size, exp_avg, denom)                                                          │
RuntimeError: value cannot be converted to type float without overflow: (3.52033e-08,-1.14383e-08)

Can someone give me suggestion?

Hello Daniil,
I saw in the psp_resnet_50_8s_synch_bn_train.py script file, the settings for learning rate is 0.0001 and number of step is 13000.0 then I faced above issue.
Do you think it's small?

Hello Daniil,
I saw in the psp_resnet_50_8s_synch_bn_train.py script file, the settings for learning rate is 0.0001 and number of step is 13000.0 then I faced above issue.
Do you think it's small?

Hi
I get the same error as you. Have you addressed this problem?
Thanks for your reply


ci: hummingbot integration

We want to run a hummingbot instance against the public testnet. Development is ongoing, but relevant repos are:

https://github.com/Se7en-Seas/hummingbot
https://github.com/Se7en-Seas/hummingbot-gateway/

At the very least, running hummingbot requires:

an interactive cli environment, so prefer a VM to a container for now;
a conda python environment (is a virtualenv sufficient? tbd)
a running pclientd instance with custody enabled

The primary driver on the integration is @philipjames44. We hope to have setup docs written soon, after which we should add a "Trading" section to https://guide.penumbra.zone and document the setup for others.

Hummingbot only handles a single trading pair per instance. For Testnet 77, let's run test_osmo:test_usd, with volume of about 10k of each. It's important to note that Hummingbot will by default trade with 50% of the available reserves: for the Osiris testnet wallet, that's far too much volume, about 10mil of each denom. So let's move assets around, leaving only ~10k of each in the default 0 subaccount. Eventually, we'd like to see Hummingbot support

customizable trading reserve amounts, e.g. only 5% of available reserves;
customizable subaccount, e.g. "trade out of subaccount 1, not 0"

Until then, though, we can tweak manually.

for the Osiris testnet wallet, that's far too much volume, about 10mil of each denom. So let's move assets around, leaving only ~10k of each in the default 0 subaccount.

Done by moving funds from account 0 to account 5 in the Osiris wallet.
For setting up Humming bot on Penumbra, see config docs here: https://github.com/Se7en-Seas/hummingbot/blob/penunumbra-integration/README_Penumbra_Osiris.md To set trading pairs, one must edit scripts/penumbra_osiris.py and adjust two vars:
    # The pair on penumbra to trade
    trading_pair = "penumbra-gm"
    # How the trading pair will be priced according to binance price feeds
    reference_pair = "BTC-USDC"

As stated above, the plan was to run test_osmo:test_usd on Testnet 77, but unfortunately the Binance US API, which hummingbot uses for looking up trading pairs, does not support that pair. Instead I've opted to use test_atom:test_usd. The manual adjustments to the hbot vars are:
    # The pair on penumbra to trade
    trading_pair = "test_atom-test_usd"
    # How the trading pair will be priced according to binance price feeds
    reference_pair = "ATOM-USDT"

The bot is live and trading now. There are some limitations: only 1 trading pair is supported per instance of hummingbot. There's also no CI automation wired up to rebuild and rerun Hummingbot every time its code changes. That's fine for now, we'll manage it interactively, because it's an interactive app. I'll post a wiki page on how team members can manage it, then close this out.

I'll post a wiki page on how team members can manage it, then close this out.

https://github.com/penumbra-zone/penumbra/wiki/Updating-hummingbot


Azure-Sentinel/DataConnectors  /microsoft-sentinel-log-analytics-logstash-output-plugin/

On the description of this Connector - Azure-Sentinel/DataConnectors/microsoft-sentinel-log-analytics-logstash-output-plugin/
there is a reference to the installation requirements:
Logstash 8 Between 8.0 and 8.8.1
BUT the LINKS points to the latest version which is 8.10.1
https://github.com/Azure/Azure-Sentinel/tree/master/DataConnectors/microsoft-sentinel-log-analytics-logstash-output-plugin#1-install-the-plugin
Is the latest version supported ?
If this is supported, then we should update the requirements

Hi @alexandrupnt, thanks for flagging this issue, we will soon get back to you on this. Thanks!

Hello @alexandrupnt, we check the click point of link, the link redirect to the latest version of the plugin, to use the document mentioned plugin version you have to click on "Other Version" tab.
Sharing steps and screenshot for reference: -

Click on the "Other Version Option." -

Select the Microsoft Sentinel's Logstash output plugin supports version which mentioned in GitHub document -

I hope this helps you. so, closing this issue. If you still need support for this issue, feel free to re-open it any time. Thank you for your co-operation.


:sparkles: Adds state option for PublicHolidays widget

Thank you for contributing to Dashy! So that your PR can be handled effectively, please populate the following fields (delete sections that are not applicable)
Category: Feature
Overview
This PR simply exposes the region parameter from Enrico Service 2.0 as an option in the PublicHolidays widget.
I chose state instead of region as the name of the option because I think it's more convenient.
Why do I want this feature? Because at least in Germany holidays are widely different between each state...
Code Quality Checklist (Please complete)

[x] All changes are backwards compatible
[x] All lint checks and tests are passing
[x] There are no (new) build warnings or errors
[x] Bumps version, if new feature added (I at least would think so... Small feature, but a feature nonetheless)

Heya, @cauterize
I'm so sorry for the delayed reply, been a busy few weeks.
This looks awesome, thanks for adding!
Just one comment, but it's very minor, so I'd be happy to merge.


cnvkit segmentation fault

Hallo
I'm trying out the newest development code, and got an segmentation fault error when running the cnvkit segmentation functionality. Running on single core, gives practically the same error output.
https://gist.github.com/MBeyens/f5869c46d42d824429078afffebb9c30
Further, I was wondering if it was possible to set more than normal sample for comparison with the tumor (grouping normals for CNV calling is stronger), as this functionality is working on the given "batch" naming. This is problematic for paired variant calling, as only one normal is given by the "batch" and you do not want to include none patient-specific normal tissue.
Thank you in advance
Matthias

Matthias;
Sorry about the CNVkit issues. I'm cc'ing in @etal to see if he has any ideas but just a segfault doesn't give much to go on. Is it possible to reproduce the error outside of bcbio:
export PATH=/mnt/home_nfs1/mbeyens/local/share/bcbio/anaconda/bin:$PATH && /mnt/home_nfs1/mbeyens/local/share/bcbio/anaconda/bin/cnvkit.py segment -p 1 -o P00132893_tumor-sort-1.cns /mnt/home_nfs1/shared_data_core/PNET/10PNET_FF_gitta/raw_data/paired_analysis/work/structural/P00132893_tumor/cnvkit/raw/P00132893_tumor-sort-1.cnr -v /mnt/home_nfs1/shared_data_core/PNET/10PNET_FF_gitta/raw_data/paired_analysis/work/mutect2/1-effects-annotated.vcf.gz

If so, can you try removing the -v variant option to see if that might be causing the problem? If so and you could share this file we could try and reproduce and fix from there.
We're definitely planning to add more flexibility around defining the background samples. We've been working on generalizing the coverage estimation in this release and this is something we hope to tackle in the next couple of weeks. Right now it's just tumor/normal based on the batch but we'll plan to introduce new ways to manage this so you can specify both variant calling and different batching for CNV calling. Thanks for the suggestion and discussion.

Hi Brad,
I ran the command without the -v option, and it generated the segmentation file. So the -v option/MuTect2 VCF seems the problem at the moment. I also added the MuTect2 VCF and the P00132893_tumor-sort-1.cnr. Let me know if you need more information!

If you can reproduce the error outside bcbio you'll see more log messages, I think. As it is the segfault could be happening inside DNAcopy (R package), pysam, or pandas, theoretically. Could hitting a memory limit result in a segfault?

Matthias -- thanks for the example and files. Eric, thanks much for the thoughts.
I wasn't able to reproduce this example files provided, things processed and correctly segmented without a segfault. I'm not sure what is different about our systems but here are the versions of the relevant libraries I have:
$ bcbio_conda list | grep pysam
pysam                     <IP_ADDRESS>                 py27_1    bioconda
$ bcbio_conda list | grep cnvkit
cnvkit                    0.9.0                    py27_0    bioconda
$ bcbio_conda list | grep pscbs
r-pscbs                   0.63.0                 r3.4.1_0    bioconda

If those match what you're seeing, is it possible to paste the output of the standalong run when it segfaults? That would help see exactly where it dies and might help isolate the issue. Thanks for the help debugging.

I have the same library versions.
I don't get your point of running the code as a "standalone" or "outside bcbio"... I do not restart the bcbio run on itself, just the single command cnvkit.py segment -p 1 -o P00132893_tumor-sort-1.cns P00132893_tumor-sort-1.cnr -v 1-effects-annotated.vcf.gz.
What I tried was running it with different segmentation algorithms -m option: cbs (default), haar, flasso, and keep on getting the Segmentation fault.
If you clarify what you mean with running "outside bcbio", I hope a can help you guys.

Matthias;
Sorry for the confusion. By outside bcbio I meant just running the cnvkit.py segment command line standalone which you're doing. Does it generate any output at all or just segfault immediately when you run it? The output I see is:
$ cnvkit.py segment -o out.cns P00132893_tumor-sort-1.cnr -v variants.vcf.gz
Selected test sample P00132893_tumor and control sample P00132893_normal
Loaded 3863 records; skipped: 0 somatic, 609 depth
VCF normal sample's genotypes are all 0/0 or missing; inferring genotypes from allele frequency instead
Skipping 203 additional somatic record based on T/N genotypes
Kept 18 heterozygous of 3660 VCF records
Segmenting with method 'cbs', significance threshold 0.0001
Dropped 6 outlier bins:
  chromosome     start       end               gene     log2  depth    weight
0       chr8   4852166   4852268              CSMD1 -24.0052    0.0  0.210000
1       chr8  57906215  57906317             IMPAD1 -23.8567    0.0  0.126040
2      chr10  17496143  17496295            ST8SIA6 -23.9927    0.0  0.207660
3      chr11   1578131   1578377              DUSP8 -23.6502    0.0  0.221612
4      chr15  45479899  45480149  RP11-519G16.2,SHF -24.0507    0.0  0.340701
5      chr17  21280113  21280225             KCNJ12 -24.0147    0.0  0.279605
Wrote out.cns with 113 regions

Sorry for all the back and forth, I don't have a good idea right now why it fails on your system so trying to come up with a reproducible example here so we can help fix. Thanks much for the help debugging.

I get only the following:
Selected test sample P00132893_tumor and control sample P00132893_normal Segmentation fault
That's it actually =/

The function skgenome.tabio.vcfio.read_vcf prints with the message you saw after parsing the VCF header, but before parsing the VCF body with pysam. After parsing is finished, you would see another message: "Loaded _ records; skipped: _ somatic, _ depth" -- but you didn't, so it looks like the segfault happened while parsing the VCF body, i.e. within pysam.VariantFile at one of its calls into htslib.
Could the linked htslib shared library have been built with a different compiler/platform/environment?

I do not have any clue. The running htslib version is 1.6. Is this correct? Maybe an option would be recompiling the htslib?

Matthias;
Apologies, but I'm stumped on what is going on here and why we can't reproduce the error. I pushed some speculative fixes that I hope might avoid the problem -- updating pysam to explicitly compile against htslib 1.6 and improving how bcbio passes tumor/normal pairs to CNVkit segmentation. Could you try updating with bcbio_nextgen.py upgrade -u development and re-running to see if that helps with the problem?
If not, is it possible the file you sent is somehow different from the input file? I know you had unzipped it, to submit as a gist. Maybe there is something problematic with the bgzip preparation as well. If you could send to me directly (e-mail in GitHub profile) or post the original file in Dropbox or Google Drive maybe that would provide some insight.
Sorry to not know exactly what is going on. Fingers crossed these fixes help.

Hi Brad,
I checked the bgzip functionality, seems not the problem. Segmentation fault keeps on the uncompressed vcf. Also, no errors occurred during the compression and rebuilding it did not solved it either.
Next, I updated to the latest development version, and now everything works well. I saw you now explicitly specify unset R path and R lib, so maybe the issue is in there...  I'll dig into this later on and if I've more information I'll update you about this.
Thank you for the problem solving @chapmanb and @etal

Hi guys, I need your valuable help. After running CNVKIT gain-loss function by setting CN cutoff of 0.6 in the segmentation file, GISTIC showing error "1472 segment overlaps detected in file" First overlap detected between segments at lines 9888 and 9889. Your help is highly appreciated. Thank you very much in advance.

Thanks for the report -- is this a problem running CNVkit through bcbio, or with a by hand run of CNVkit? If the later, you'd be best off reporting this on the CNVkit issue tracker (https://github.com/etal/cnvkit/issues) since they'll have a better ability to debug. Either way, we could use additional information about the problem to help reproduce identify the issue:

The command lines that you ran to produce the issue.
The full traceback of the error/failure message.

Hope this helps.

@chapmanb, Thanks for your timely reply. I ran CNVKIT, in by hand run only. As u suggested I also posted on the CNVkit issue tracker. Hope I will get some suggestions from there. Thank you once again.

Matthias;
Following up on your initial question about pooling normal samples, the latest development version of bcbio will now use all normal samples in a project for calculating the background for tumor normalization. It batches these by variant regions BEDs but you can also specify more specifically by adding a prep_method definition to the metadata if it shouldn't batch some samples:
http://bcbio-nextgen.readthedocs.io/en/latest/contents/configuration.html#sample-information
Happy for any feedback if you have time to test this on your samples. Thanks again for the discussion and ideas.

That's great news! Thank you for the implementation @chapmanb .
So to recapitulate, I need to set the prep_method parameter both in tumor and normal samples, and I can put a text like prep_method: pool1 for tumor/diseased CNV calling to the pooled normal/control samples background defined as pool1? By default it is [empty], so I assume the CNV calling is done only patient-wise, e.g. tumor/disease1 vs normal/control1 (and thus not a "pooled" normaly default)?
If I'm interpreting this correctly, I'll test this right away! This functionality is available in the latest development version, right?

Matthias;
All sounds right, except if you leave prep_method empty then it will pool all normals together with the same capture/region BEDs. So it'll try to do the right thing without any changes, but you can define more specifically into pools as needed. It is in the latest development (bcbio_nextgen.py upgrade -u development). Please let us know if you run into any problems and thanks again for testing.

Hi Brad;
I'm testing the newest functionality you implemented and got the following error.
[2017-11-17T20:55Z] CNVkit fix [2017-11-17T20:55Z] usage: cnvkit.py [-h] [2017-11-17T20:55Z]                  {batch,target,access,antitarget,autobin,coverage,reference,fix,segment,call,diagram,scatter,heatmap,breaks,gainloss,sex,gender,metrics,segmetrics,import-picard,import-seg,import-theta,export,version} [2017-11-17T20:55Z]                  ... [2017-11-17T20:55Z] cnvkit.py: error: unrecognized arguments: --sample-id P00138533_tumor [2017-11-17T20:55Z] Uncaught exception occurred Traceback (most recent call last):   File "/home/mbeyens/local/share/bcbio/anaconda/lib/python2.7/site-packages/bcbio/provenance/do.py", line 23, in run     _do_run(cmd, checks, log_stdout, env=env)   File "/home/mbeyens/local/share/bcbio/anaconda/lib/python2.7/site-packages/bcbio/provenance/do.py", line 103, in _do_run     raise subprocess.CalledProcessError(exitcode, error_msg) CalledProcessError: Command 'set -o pipefail; export TMPDIR=/mnt/home_nfs1/paired_analysis/work/bcbiotx/tmplUC5db && /mnt/home_nfs1/local/share/bcbio/anaconda/bin/cnvkit.py fix -o /mnt/home_nfs1/paired_analysis/work/bcbiotx/tmplUC5db/P00138533_tumor-normalized.cnr /mnt/home_nfs1/paired_analysis/work/structural/P00138533_tumor/bins/P00138533_tumor-target-coverage.cnn /mnt/home_nfs1/paired_analysis/work/structural/P00138533_tumor/bins/P00138533_tumor-antitarget-coverage.cnn /mnt/home_nfs1/paired_analysis/work/structural/P00138533_tumor/bins/background-0-cnvkit.cnn --sample-id P00138533_tumor usage: cnvkit.py [-h]                  {batch,target,access,antitarget,autobin,coverage,reference,fix,segment,call,diagram,scatter,heatmap,breaks,gainloss,sex,gender,metrics,segmetrics,import-picard,import-seg,import-theta,export,version}                  ... cnvkit.py: error: unrecognized arguments: --sample-id P00138533_tumor ' returned non-zero exit status 2
It appears --sample-id is a none existing/available argument under the cnvkit.py fix. Currently running cnvkit version 0.9.0. Hopefully this helps you to debug, otherwise I provide more information.

I think that option is only in the recent CNVkit 0.9.1 release, which is not yet in the bioconda repo: bioconda/bioconda-recipes#6837

Matthias -- Eric is exactly right, you need 0.9.1 to have this functionality. If you're using bioconda, it has the latest 0.9.1a0 version which I built just prior to the release so updating to that will work right away. bcbio should install this version if you update with bcbio_nexgen.py upgrade -u development, bcbio_nextgen.py upgrade --tools or just bcbio_conda install -c conda-forge -c bioconda cnvkit. Hope this fixes it for you.


Add Dogecoin coin type

Doge has DGUB/DGPV (https://github.com/TrustWallet/trust-wallet-core/compare/doge#diff-56eac4c998ed67cffe03ba6956fbdb42R65)


Port functionality to n300 card (single device)

Enable support for BERT-Tiny model using TTNN ops and port functionality to n300 card (single device).

Draft PR is created for the Bert-Tiny
Corresponding PR: #13471
Demo results in n300 is recorded here : Link

@mbahnasTT , Bert-Tiny model is completed and the PCC for all sub-modules > 0.99.  But the PCC of the entire model has dropped  after the final linear layer to ~0.96 and ~0.97 after splitting start_logits and end_logits respectively.
The models accuracy for 100 samples are as follows:
Accuracy between TTNN model and SQUADv2 reference:
Eval: exact: 14.423076923076923
F1: 22.086671341479036

Accuracy between PyTorch model and SQUADv2 reference:
exact: 19.23076923076923
F1: 24.28325947556717

Accuracy between TTNN and PyTorch model:
exact: 58.65384615384615
F1: 0.5875457875457875

Pytorch results does not align with the dataset for most of the cases.
However, Pytorch and TTNN results match in most cases, and the results can be found here: Link
Corresponding Draft PR : #13471
Can we proceed with this model with the above results?

@vigneshkeerthivasanx please proceed with this model, and file an issue with these details, and keep track of the issue # i the main model status sheet. Thanks!

Corresponding PR #13471 is merged.


CARDS-2441: Computed questions only have access to the first value of multivalued variables

Summary of changes:

introduced new syntax for returning the values of a variable as an array via []: @{[questionId:-defaultvalue]} and for accepting missing values via ?:  @{[questionId?]}

updated the ComputedQuestion frontend code to put the values in an array when the [] are used (even if the variable is single valued) and to accept missing values when ? is used; when the already existing syntax is used ( @{questionId:-defaultvalue}, no square brackets, no questiob mark), the behavior remains the same, and only the first value is return from multivalued answers with the expression not being evaluated when any value is missing

updated the BackendComputedTest questionnaire to showcase computed answers with multivalued variables, including with the ? syntax
updated the ComputedTest questionnaire to showcase one computed question using a text multivalued variable and one computed question using a long multivalued variable

Testing:

start with --test
test the entire ComputedTest questionnaire (this will cover new syntax as well as backward compatibility)
test the questionnaire BackendComputedTest following the instructions listed in the infobox as both admin and computedtestuser

Question 4 and Question 4a|b|c Computed help test the newly introduced syntax, but test everything for backwards compatibility

testing as a developer: create your own computed question using multivalued variables

more interesting additions to the ComputedTest questionnaires are welcome

computedtestuser isn't a trusted one:

once I moved the computedtestuser to the trusted group, I was not able to see the form that admin created:

The frontend code and testing instructions have been updated, please re-test @sashaandjic

Is this PR complete now?

Is this PR complete now?

Ready for review and testing.

Why is Question 4b only visible in edit mode?

Why is Question 4b only visible in edit mode?

Javascript error in the backend. The frontend returns empty array when ? is used and the value is missing, while the backend returns null. We need to decide which one we want to keep. I would say [] because the ? is inside the brackets @acrowthe .

re-tested


feat(remix-netlify): show deprecation warning on usage

Just like we did with the Vercel adapter
We should probably release this as 1.19.2 so people still get this warning before v2 🤔

@MichaelDeBoey Agreed - let's get this rebased onto main so we can include in a 1.19.2

@brophdawg11 Should be fine now


Undefined output shape in Conv2DTranspose

If we use keras with tensorflow, the output shape of a Conv2DTranspose is undefined even if the input shape is fixed. This problem doesn't happen with Conv2D . This is probably due to a bug in the implementation of   Conv2DTranspose.
import tensorflow as tf

config = tf.ConfigProto()
config.gpu_options.allow_growth=True
sess = tf.Session(config=config)

from keras.layers.convolutional import Conv2DTranspose , Conv2D

layer1 = Conv2DTranspose( 8  , (4 , 4) , strides=(1, 1)  , data_format='channels_first'  , input_shape=(3,64,64) )
layer2 = Conv2D( 8 , (4, 4) , strides=(1, 1), input_shape=(3, 64, 64) , data_format='channels_first'  )

BATCH_SIZE = 32
x = tf.placeholder(tf.float32, shape=( BATCH_SIZE , 3, 64 , 64 ))

o1 = layer1( x )
o2 = layer2( x )

print o1.get_shape() # Prints (?, 8, ?, ?) , why???
print o2.get_shape() # Prints (32, 8, 61, 61) , which is correct

I encountered the same issue! I had to use the following to determine the output shape:
shape_o1 = layer1.compute_output_shape(input_shape)

Yes, There is a bug in the implementation on this layer. This is causing other source codes to break.

I add this line print (inputs, input_shape)  at convolutional.py
the output :
(<tf.Tensor 'activation_9/Relu:0' shape=(?, 64, 64, 256) dtype=float32>, <tf.Tensor 'conv2d_transpose_1/Shape:0' shape=(4,) dtype=int32>)

It seems that K.shape(line 742) cannot get the exact shape of input tensor...

Any updates on this issue?

I have also run into this bug. It requires some ugly workarounds. any updates?

I too encoutered this bug.
The following code
from keras.models import Model
from keras.layers import Input, Conv2D, Conv2DTranspose
from keras import backend as K

assert K.image_data_format() == 'channels_last'

inp = Input(shape=(((32, 32, 3))))
out_1 = Conv2D(8, (3, 3), strides=(1, 1), padding='same')(inp)
out_2 = Conv2DTranspose(8, (3, 3), strides=(1, 1), padding='same')(inp)

print(out_1.shape)
print(out_2.shape)

produces this output (Keras Version 2.0.8, TensorFlow 1.3.0)
(?, 32, 32, 8)
(?, ?, ?, 8)

To me it looks like it is caused by this TensorFlow bug.

Just as an update: It still happens with Keras 2.1.1 and TensorFlow 1.4.0. I will check again with the next release of a new TensorFlow version.

I can check the output shape with _keras_shape property of the layer.

A nasty workaround is to explicitly mention the output shape.
<your_tensor>.set_shape(<output_shape>)

@gdubrg Thanks. Accessing a protected member is not perfect, but it works for my purpose.

Kudos @gdubrg

I have faced the problem too

Same problem for me :-(
Any better workaround?

Changing the imports to the Keras version included in Tensorflow also fixed the problem:
from tensorflow.python import keras
from tensorflow.python.keras.layers import Input, Conv2D, Conv2DTranspose
from tensorflow.python.keras import backend as K

assert K.image_data_format() == 'channels_last'

inp = Input(shape=(((32, 32, 3))))
out_1 = Conv2D(8, (3, 3), strides=(1, 1), padding='same')(inp)
out_2 = Conv2DTranspose(8, (3, 3), strides=(1, 1), padding='same')(inp)

print(out_1.shape)
print(out_2.shape)

(?, 32, 32, 8)
(?, 32, 32, 8)

Closing as this is resolved

@wt-huang Is this really resolved? It seems like the solution above is "abandon Keras and use tf.keras", which isn't ideal.

@wt-huang This isn't solved! Keras from TF and vanilla keras is not compatible. A project should use either tf.keras or just keras and not both. Changing the whole project to use tf.keras is a huge job.

I also don't like it, but the notes of the latest vanilla Keras release even state:

This is also the last major release of multi-backend Keras. Going forward, we recommend that users consider switching their Keras code to tf.keras in TensorFlow 2.0. It implements the same Keras 2.3.0 API (so switching should be as easy as changing the Keras import statements), but it has many advantages for TensorFlow users, such as support for eager execution, distribution, TPU training, and generally far better integration between low-level TensorFlow and high-level concepts like Layer and Model. It is also better maintained.
Development will focus on tf.keras going forward. We will keep maintaining multi-backend Keras over the next 6 months, but we will only be merging bug fixes. API changes will not be ported.

:cry:

I suppose that's that, then. Still pretty annoying since, a) TF 2.0 is still in beta, and b) tf.keras is not a drop-in replacement, as evidenced by the week or so of work I had to put in switching over to get around this bug.
(The latter point may now be true with the 2.3.0 update, but I think that also points towards the high volatility in machine learning libraries.)

My latest pull request fixed this issue: #13778


Hyperbridge/Ismp integration

@rdoria1 CI passes but I was trying to execute the benchmark tests from withing the hyperbrige-aggregators pallet and it fails. This is non blocking for merging this PR but please double check.


Third Party Caveat verification id

Macaroons generated with macaroons.js fail when decoding with an invalid Base64 error.

Could you provide a failing example (could just be the final, encoded macaroon)?

Sure. Macaroons.js doesn't base64 the binary ciphertext when generating the verification id. The binary verification id just gets run through the binary serializer.
Below is the binary serialization of the macaroon generated by macaroons.js and the stack trace from ruby-macaroons.
MDAyNGxvY2F0aW9uIGNvbS5pc2NncnAuc3NvLnNlc3Npb24KMDAzMGlkZW50aWZpZXIgZTYzZjYwZjZjYTg0MTYxYWRmYmZmMjBkMjU3ODcyYzkKMDAxMGNpZCByb2xlczoxCjAwNTF2aWQgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHNljDzNPOnh-OoMWkBPDpNhpZJeAXHGqJalR7YFrbUfSRJ5aj6BFXNW    32x_uKIgPCjAwMWNjbCBjb20uaXNjZ3JwLnNzby5yb2xlcwowMDBmY2lkIGxkYXA6MQowMDUxdmlkIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAIggFbrJcvirhlj_YSf9mo9DKIE_Yashpm1W-1nikgI122ZSne3adHPvXdP2FnGf2AowMDFiY2wgY29tLmlzY2dycC5zc28ubGRhcAowMDE0Y2lkIHZpZXdwb2ludDoxCjAwNTF2aWQgAAAAAAAAAAAAAAAAAAA    AAAAAAAAAAAAA4V7xySmYITS82K2sO7GHMpEII6l_ZpbHQkdfbf48zN2BppdB6dDY1GDiRXkP5cibCjAwMjBjbCBjb20uaXNjZ3JwLnNzby52aWV3cG9pbnQKMDAyZnNpZ25hdHVyZSCaO5_5kGkzTPbSnpaTO04vrEPBimIeJ1Mqq5GLZxw3NAo

/Users/cmcknight/.rbenv/versions/2.1.5/lib/ruby/2.1.0/base64.rb:73:in `unpack': invalid base64 (ArgumentError)
  from /Users/cmcknight/.rbenv/versions/2.1.5/lib/ruby/2.1.0/base64.rb:73:in `strict_decode64'
  from /Users/cmcknight/code/ruby/ruby-macaroons/lib/macaroons/verifier.rb:100:in `extract_caveat_key'
  from /Users/cmcknight/code/ruby/ruby-macaroons/lib/macaroons/verifier.rb:80:in `verify_third_party_caveat'
  from /Users/cmcknight/code/ruby/ruby-macaroons/lib/macaroons/verifier.rb:55:in `block in verify_caveats'
  from /Users/cmcknight/code/ruby/ruby-macaroons/lib/macaroons/verifier.rb:51:in `each'
  from /Users/cmcknight/code/ruby/ruby-macaroons/lib/macaroons/verifier.rb:51:in `verify_caveats'
  from /Users/cmcknight/code/ruby/ruby-macaroons/lib/macaroons/verifier.rb:36:in `verify_discharge'
  from /Users/cmcknight/code/ruby/ruby-macaroons/lib/macaroons/verifier.rb:30:in `verify'
  from macaroon.rb:77:in `<main>'

Ah, okay. Without comparing implementations my instinct is that the vid should be base64 encoded first, since the binary serialization format is currently restricted to ascii.
But I'll look around and see what other macaroon libraries are doing before closing this.

I don't think the ascii restriction should matter though in the binary serialization because it ends up being converted to base64 at the end of binary serialization.
I think it would be invalid when serialized to JSON and needs to be converted to base64 when serializing to JSON.

I was misremembering the binary format (it's hard to keep straight since there's no formal spec). Went back and reviewed it and the vid isn't encoded in the serialized macaroon (though it is encoded in some cases, such as for display)

Just updated the library to 0.6.0, which should now be compatible with macaroons.js. Reopen/let me know if it doesn't work!
Thanks for the bug hunting!

Sweet! I saw just your commit and looks good to me.
That's the changes I had to end up making to the PHP implementation.
Sorry for not sending a PR. I wanted to discuss it with you first.


babel-jest transforming dependencies

Do you want to request a feature or report a bug?
Feature
What is the current behavior?
babel-jest doesn't transform package dependencies.
If the current behavior is a bug, please provide the steps to reproduce and if possible a minimal repository on GitHub that we can npm install and npm test.
We have a Lerna repo where one package depends on another. Jest will compile the immediate package, but skip compiling dependencies. This inevitably leads to errors like:
import Element from './element'
    ^^^^^^
    SyntaxError: Unexpected token import

What is the expected behavior?
It just works I guess? Not 100% sure of what the preferred fix would be.

You can adjust preprocessorIgnorePatterns to also transform node_modules. The problem with that is that the initial run of Jest is going to be a lot slower, which is why it isn't a default.
In Jest itself, this isn't a problem (we also use lerna): with npm run watch we continuously compile changes and every package's package.json points to build/index.js instead of src/index.js. This works really well – I suggest using the same kind of setup we have in this repo :)

Awesome, thanks for the reply — appreciate the insight.
On Mon, Oct 31, 2016 at 6:47 PM Christoph Pojer<EMAIL_ADDRESS>wrote:

You can adjust preprocessorIgnorePatterns to also transform node_modules.
The problem with that is that the initial run of Jest is going to be a lot
slower, which is why it isn't a default.
In Jest itself, this isn't a problem (we also use lerna): with npm run
watch we continuously compile changes and every package's package.json
points to build/index.js instead of src/index.js. This works really well
– I suggest using the same kind of setup we have in this repo :)
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Fix custom client registration

Why are these changes needed?
For custom client registration:

Removing redundant check for placeholder config inside config list
configs in self._config_list can end up having the extra kwargs passed through (e.g. cache_seed) and therefore the check for placeholder_config in self._config_list will fail

Related issue number

Checks

[ ] I've included any doc changes needed for https://microsoft.github.io/autogen/. See https://microsoft.github.io/autogen/docs/Contribute#documentation to build and test documentation locally.
[ ] I've added tests (if relevant) corresponding to the changes introduced in this PR.
[ ] I've made sure all auto checks have passed.

Can we add a test just to make sure additional config arguments like cache_seed won't trigger an error?
Also in test_custom_client.py (basically all other tests as well, but we don't have to do everything in this PR) we don't need to check for openai package existence as it is a required dependency.

@ekzhu good point, added unit test, checked that it failed with old code, and passes with PR changes. Also removed the openai req

Remember to check the code in #1667 also to see if it works with this update. It works on my side.


Removed get siblings (#7151)

Pull request opened by the merge tool on behalf of #7151

Merged in a4d3b985cf0c87ab79670fc94dbf948930521711


Unhandled overflow in int8 SVDF evaluation

When calculating the values to be inserted in the SVDF operator’s activation state in the svdf_common.cc file, there seems to be an error while handling overflow.
In line 111 the value for the dot_prod variable is limited to the interval of valid int8 values, [-128, 127]. But then, in line 115, the activation state’s zero point is added to dot_prod, which may lead to an unhandled overflow.

Commenting to prevent closing the issue.
My colleagues @VictorDominguite and Luiz Baptista have proposed a potential solution for this issue. We'll create a PR to further discuss and implement it. Thanks!

Commenting to prevent closing the issue.


create travel grant report template

Created a travel grant report template (travelgrantreports.md) using the content from the mentioned source. fixes #3

Thank you for your contribution. Stay connected to claim your reward. Hacktoberfest with Interledger

Thank you for Contributing to Interledger during Hacktoberfest. If you have any accepted PRs, You can claim your Swag here. Last date to fill up the form is December 10th, 2023. @GriffinAnnshual

Thank you so much @devcer. Looking forward to contributing more in the coming days!


luci-proto-modemmanager: add initial EPS bearer support

[x] This PR is not from my main or master branch :poop:, but a separate branch :white_check_mark:
[x] Each commit has a valid :black_nib: Signed-off-by<EMAIL_ADDRESS>row (via git commit --signoff)
[x] Each commit and PR title has a valid :memo: <package name>: title first line subject for packages
[x] Tested on: (qualcommax/ipq60xx, main, Chrome) :white_check_mark:
[x] Description: (describe the changes proposed in this PR)

ModemManager protocol has supported setting initial EPS bearer since package commit [1], so lets expose the same support via LuCI as well.
[1] https://github.com/openwrt/packages/commit/af12147f8c54ac3a44d32c5c1bd95099bc9a6c74

@feckert any comments?

Thanks merged!


Increased annotated function support from 5 parameters to 22 parameters

I need more than 5 parameters a lot on my current project and this would save me tremendous amount of boilerplate.

LGTM, thanks!


Fix python311 compatibility

Hello everyone,
this fixes all tests under Python 3.11. And it closes #67.
It basically only required to provide a working mkdir method for the testsuite to pass.
In Python 3.11's pathlib the _accessor classes have been removed and so UPath's implementation deviates now a little bit from the new pathlib implementation. It's not really problematic for now, if we explicitly disable all that is not working (I raise NotImplementedError in many methods that now rely directly on os.path functions). If needed, some of these disabled methods could probably be implemented in an fsspec compatible way.
Once python/cpython#31691 and later python/cpython#31085 are merged into python, I believe this should be revisited.
Cheers,
Andreas :smiley:

You'll need "3.11-dev" until 3.11 is released, and currently installing aiohttp and yarl (one of its dependencies) breaks when done via pip. (I had to manually install and make sure the Cython version used to build both is at least 0.29.32)

You'll need "3.11-dev" until 3.11 is released, and currently installing aiohttp and yarl (one of its dependencies) breaks when done via pip. (I had to manually install and make sure the Cython version used to build both is at least 0.29.32)

Thanks! Do you mind giving trying to set up the CI? I think it would be good to make sure, we don't break anything else wrt Python 3.11.

I'll set it up later tonight 👍

I added tests for mkdir's exist_ok behavior, which required a few additional changes to the tests for cloud filesystems.
Regarding the py3.11 tests: I will wait for https://github.com/aio-libs/aiohttp/issues/6600 to provide sources that build under 3.11 which should hopefully be soon, now that rc1 is out.

Hey everyone,
since waiting for new aiohttp wheels is taking longer than expected, I added a workaround, that while we're still testing againt rc versions of py3.11 will install aiohttp from the source tarball with disabled C extensions.
This PR is now ready for review :+1:
Cheers,
Andreas :smile:


steam extension error

Check for existing issue
Please use issue search in the repository if the bug is something really obvious there's a high change it was already reported.
Describe the bug
A clear and concise description of what the bug is.
To Reproduce
If it's not clear from the description how to reproduce the issue please add clear steps to reproduce the behavior.
Screenshots
If applicable, add screenshots to help explain your problem.
Diagnostics ID
Please generate diagnostics package from "About Playnite" menu and attach identifier you received. If the issue is a crash bug, you can generate diag. package directly from crash dialog.

serr.zip

It's the issue with your Steam install. I made a change that will prevent Playnite from crashing completely, but Steam friends window will not open anyways because system can't find Steam executable when opening steam://open/friends.


Bump Dart SDK to 2.15

Follows up on #882 more precisely @fzyzcjy's suggestion
This bump is motivated by the use of constructor tearoffs: passing constructor as a regular function.
It shouldn't be a major issue for FRB users considering that ffigen currenttly required sdk is 2.17.

Is it me or ios CI randomly fails @fzyzcjy ? :upside_down_face:

the latter :)

@all-contributors please add @ngasull for code


Manually set the order of categories

Is your feature request related to a problem? Please describe.
If the user has multiple categories, the user would have to scroll to the category the project is in. For example Demos, Test, and Projects categories; the user would need to scroll to the second to last (Projects) category. With ordered categories, the user could order the Projects category as the first in the categories and lessen the need to scroll down.
Describe the solution you'd like
Add a way to manually order the categories in the category view.
Describe alternatives you've considered
Pinned category.

Basically, doing like Favorites does in the List View, that is the standard Godot Project Manager design in the Editor


Implement trip consecutive stops verification (GTFS rule)

Is your feature request related to a problem? Please describe.
A trip should not have many consecutive stops with the same times. This is a GTFS rule implemented in Google Python validator as ValidateStopTimesForTrip.
Describe the solution you'd like
Actual Google GTFS validator behaviour : Verifies the stop times for a trip, ensure that trip does not have too many consecutive stop times with the same arrival or departure time.
https://github.com/google/transitfeed/blob/master/transitfeed/schedule.py line 1169
Describe alternatives you've considered
Additional context
Line 170 in Error support priorities https://docs.google.com/spreadsheets/d/1vqe6wq7ctqk1EhYkgtZ0_TbcQ91vccfs2daSjn20BLE/edit#gid=0

Looking at the Python validator, looks like if there are more than 5 consecutive stop_times with the same time they throw an error.

Oh, thanks. I did not catch this part of the rule.

Labeling as blocked because this mention is not in the spec or best practices, and currently this validator doesn't include additional checks.


♻ Simplify internal RegEx in fastapi/utils.py

Replace regex for simple

Agree, \W is the equivalent of [^a-zA-Z0-9_] and is more elegant.

No, that's not true. It's equivalent to [^\w], which is a wider range of characters that just those. For example:
>>> import re
>>> re.match(r'\W', 'ü')
>>> re.match(r'\w', 'ü')
<re.Match object; span=(0, 1), match='ü'>

This change may lead to better support for languages with non-ASCII characters, but it's not precisely equivalent to the old code.

Agree, \W is the equivalent of [^a-zA-Z0-9_] and is more elegant.

No, that's not true. It's equivalent to [^\w], which is a wider range of characters that just those. For example:
>>> import re
>>> re.match(r'\W', 'ü')
>>> re.match(r'\w', 'ü')
<re.Match object; span=(0, 1), match='ü'>

This change may lead to better support for languages with non-ASCII characters, but it's not precisely equivalent to the old code.

I stand corrected. I took my information from regex101.com, and you are completely right.
If this changes the behaviour, then I would expect a test case that would illustrate the exact intended behaviour.

Great, thanks @pylounge! :cake: