Connection timeout

PiVPN Issue Template

Issue
Connecting from network manager I receive this error after about 30 seconds:
The VPN connection "myvpn" failed because the connection attempt timed out.

PI 3 model B
modem router Fritz!Box 3390
wired connection
networkmanager 1.4.4 don't import the client file generated; I followed this guide to import: https://askubuntu.com/questions/134918/setting-vpn-client

Have you searched for similar issues and solutions?
yes

Console output of curl -L install.pivpn.io | bash
sudo will be used for the install.
Cancel selected. Exiting

Console output of pivpn add or pivpn add nopass
Enter a name for the client

Console output of pivpn debug
https://pastebin.com/DaeAu41x

Console Output of sudo iptables -t nat -S
-P PREROUTING ACCEPT
-P INPUT ACCEPT
-P OUTPUT ACCEPT
-P POSTROUTING ACCEPT
-A POSTROUTING -s <IP_ADDRESS>/24 -o eth0 -j MASQUERADE

Console Output of sudo iptables -S
-P INPUT ACCEPT
-P FORWARD ACCEPT
-P OUTPUT ACCEPT

output of sudo netstat -uanp | grep openvpn
udp        0      0 <IP_ADDRESS>:1194            <IP_ADDRESS>:*                           301/openvpn

Have you taken any steps towards solving your issue?
I see in deep the router and port configuration, and it "seems" ok...

Are you on the same network as the pi?

Yes:
pi - <IP_ADDRESS>
router: <IP_ADDRESS>
client: <IP_ADDRESS>

Your router likely doesn't support NAT loopback, so you will have to make sure port forwarding is set up properly and connect from a different network.

Maybe this configuration?
pi - 192.168.128.XXX
router: 192.168.178.XXX
client: 192.168.178.XXX

@silvioto you should not connect to a vpn from the same network where it is being served, its pointless and useless.
VPN purpose is to allow secure connections to remote networks over insecure networks ( for example the internet).
For testing purposes consider using mobile data to test if everything is working.
As this seems not to be entirely related with PiVPN itself, i will be closing this issue.
if you still require community help please consider taking this over to r/pivpn
Kind Regards.


Limit and Group By queries memory and cpu optimization

The goal of this change is to avoid creating an array of all the dataset's rowNames when the number of rows returned will be small (group queries and queries with limit). This is done by adding an interface to the dataset to stream rowNames one by one. The interface is optional, the only dataset that does not support it right now is the SQLite dataset. Sorted queries not supported yet. Each working thread has its own copy of the stream.
The streams could be made to be more efficient, most of it is a naive implementation for now.
This should also make it easier to multithread the pipeline execution model.
Queries that use this codepath should use about # of row * sizeof(rowName) less memory. According to my tests, group by queries are also a couple of time fasters, while limit 1 queries are almost 2 order of magnitude faster.

+1
J'ai hâte de voir les graphiques dans Kibana demain.

+1 modulo a bunch of minor comments from me and others.  Up to you to determine when and how to improve the getRowStream versus getNEquallySpacedRowStreams(lambda_to_call_when_one_is_created) interface.

I created a followup story MLDB-1278 for some of the suggested improvements


[Plugin] plugin-github-webhook

Summary
There are many users with the rate limit problem using github as source of catalog. The polling strategy is very efficient, but its easy to reach the hard limits of github. Furthermore, the actual solution is increase the refresh interval, turning the catalog data unsynchronized.
Context
Build an plugin that exposes an api route to receive github webhook events and  update the catalog in real time. Basically three github events would be received:

push: to update catalog if an yaml file is included on some commit of this push.
team: to update groups
organization: to update members

I`ve been working on a API that receive those webhooks and updates backstage catalog using the Catalog API. It would be easy to bring that logic to a backstage plugin.

Hi @chicoribas,
Yes, refreshing entities based on events like webhooks is definitely something that has been on the mental roadmap of the maintainer team for a long time. It's been requested/discussed in the past but I'm struggling to find any references. We'd want a somewhat generic system receiving these events as there are likely going to be events from other systems/providers that we would like to support. This is work is going to require some design proposal in form of an RFC as it's going to introduce some new integrations points to the catalog.
It would be interesting to know more about the hard limits you are currently hitting. Are your locations registered one by one or are you using a discovery processor? What problems are you seeing at this point? Getting rate limited by the catalog should be less of a problem know as requests are cached and subsequent requests use etags which does not count towards the quota

The feature already exists (https://github.com/backstage/backstage/pull/13931).
If you use events, does the CatalogBuilder still need to poll?

Indeed, deleting this issue in favor of the events system


size mismatch

Hey @dbolya,
I'm trying to use ResNet34 as a backbone but the mismatch error shows up. Could you please tell me how to solve it?
RuntimeError: Error(s) in loading state_dict for ResNetBackbone:
        size mismatch for layers.0.0.conv1.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 1, 1]).
        size mismatch for layers.0.1.conv1.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 256, 1, 1]).
        size mismatch for layers.1.0.conv1.weight: copying a param with shape torch.Size([128, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 256, 1, 1]).
        size mismatch for layers.1.0.downsample.0.weight: copying a param with shape torch.Size([128, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([512, 256, 1, 1]).
        size mismatch for layers.1.0.downsample.1.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for layers.1.0.downsample.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for layers.1.0.downsample.1.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for layers.1.0.downsample.1.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for layers.1.1.conv1.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 512, 1, 1]).
        size mismatch for layers.2.0.conv1.weight: copying a param with shape torch.Size([256, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 512, 1, 1]).
        size mismatch for layers.2.0.downsample.0.weight: copying a param with shape torch.Size([256, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([1024, 512, 1, 1]).
        size mismatch for layers.2.0.downsample.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([1024]).
        size mismatch for layers.2.0.downsample.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([1024]).
        size mismatch for layers.2.0.downsample.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([1024]).
        size mismatch for layers.2.0.downsample.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([1024]).
        size mismatch for layers.2.1.conv1.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 1024, 1, 1]).
        size mismatch for layers.3.0.conv1.weight: copying a param with shape torch.Size([512, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 1024, 1, 1]).
        size mismatch for layers.3.0.downsample.0.weight: copying a param with shape torch.Size([512, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([2048, 1024, 1, 1]).
        size mismatch for layers.3.0.downsample.1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([2048]).
        size mismatch for layers.3.0.downsample.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([2048]).
        size mismatch for layers.3.0.downsample.1.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([2048]).
        size mismatch for layers.3.0.downsample.1.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([2048]).
        size mismatch for layers.3.1.conv1.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 2048, 1, 1]).
Thanks!

@abhigoku10, Do you know how can I solve my problem? what else changes I need to do to be able to train with ResNet34? Thanks!

Sure! You can just follow the instructions in https://github.com/dbolya/yolact/issues/36
@dbolya I think you should pin https://github.com/dbolya/yolact/issues/36, so many people are asking about it

@jasonkena, I have already done that but still not working :|  I don't want to do finetuning. I want to train the model from scratch with ResNet34 instead of ResNet50 or ResNet101. I have downloaded the ResNet34 pretrained model from PyTorch website and placed it in weights folder. Also I did the changes in the config file but I'm getting mismatch error which I don't know how to slove it. Do I need to do any other changes to be able to train with ResNet34 as a backbone? Thanks

Yes, the instructions are for https://github.com/dbolya/yolact/issues/36, but they should work for any dimension mismatch due to state_dict loading.

I'm able to train the network with ResNet34 by addind ~try-except  in the backbone.py for this line https://github.com/dbolya/yolact/blob/b97e82d809e5e69dc628930070a44442fd23617a/backbone.py#L154 (#36 is for finetuning).  @dbolya , @jasonkena, What is the reason of getting the size mismatch errors when I change the backbone to anything else than the default? Is it going to impact the performance when I'm ignoring the error with  ~try-except ? Am I doing something wrong?
Thansk!

No, it should not impact your performance (ignoring the fact that ResNet 34 is smaller than 101).
So when the YOLACT creates a model (before inputting weights), all of these parameters have all of their own dimensions. When you want to load the weights from a file with different dimensions, it will raise an error, and hence the try-except. As I believe @dbolya stated, the weights of the model that cannot be imported from the file will just be randomly initialized.
As for why ResNet 34 is not supported, I bet it has something to do with 'args': ([3, 4, 6, 3],),. But the code will run anyways just using the try-except.

Thanks for the information. So, how can I modify the dimensions to not get this error anymore (not only for ResNet)? I know how to print out the keys pretrained weight file but not the backbone implementation to be able to match the keys between these two.

You can just try-except it, and let it be, you don't have to worry about the mismatch.
Or, you can lookup the architecture for ResNet 34, and find the args in ResNetBackbone that matches it.

hello,
I got the same problem, could you give me some suggestion about how to solve this problem?
Thank you!

im having this issue when i want to use the trained model. I have a model that i trained on custom dataset. and now i am loading it without success.
Does anyone have an idea ?
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for Yolact:
	size mismatch for prediction_layers.0.conf_layer.weight: copying a param with shape torch.Size([18, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([243, 256, 3, 3]).
	size mismatch for prediction_layers.0.conf_layer.bias: copying a param with shape torch.Size([18]) from checkpoint, the shape in current model is torch.Size([243]).
	size mismatch for semantic_seg_conv.weight: copying a param with shape torch.Size([5, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([80, 256, 1, 1]).
	size mismatch for semantic_seg_conv.bias: copying a param with shape torch.Size([5]) from checkpoint, the shape in current model is torch.Size([80])

im having this issue when i want to use the trained model. I have a model that i trained on custom dataset. and now i am loading it without success.
Does anyone have an idea ?
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for Yolact:
	size mismatch for prediction_layers.0.conf_layer.weight: copying a param with shape torch.Size([18, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([243, 256, 3, 3]).
	size mismatch for prediction_layers.0.conf_layer.bias: copying a param with shape torch.Size([18]) from checkpoint, the shape in current model is torch.Size([243]).
	size mismatch for semantic_seg_conv.weight: copying a param with shape torch.Size([5, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([80, 256, 1, 1]).
	size mismatch for semantic_seg_conv.bias: copying a param with shape torch.Size([5]) from checkpoint, the shape in current model is torch.Size([80])

Have you fixed this promble?I meet the same error now!


Move lint and test-network-basic tests from Azure to GHA - READY FOR MERGE

This PR ports the glacial Linter and Test Network Basic tests from Azure to GHA:

Test Network Basic - Go
Test Network Basic - Java
Test Network Basic - Javascript
Test Network Basic - Typescript

In addition, the scripts have been updated to run each test case in a different chaincode scope / ledger, re-using a single Fabric network across all tests in the suite.
Signed-off-by: Josh Kneubuhl<EMAIL_ADDRESS>

@mbwhite thanks for the feedback.  Latest push will :

pin ubuntu-20.04
remove the release branch targets (release lines will still run azp.)   In general I think it is preferable to keep things simple and just run exactly the workflows that are declared on a branch, rather than overriding the env from the GHA context.  Nice and simple.
Installs fabric docker images from install-fabric (This is better anyways, as the older ones are still pulling from jfrog)


BUG: adding responsiveness to header and dark mode to map pg

Is there an existing issue for this?

[X] I have searched the existing issues

What happened?
the header of map page isnt responsive right now and theres no dark mode available on page as well. I would like to fix these issues.
Record

[X] I agree to follow this project's Code of Conduct
[X] I'm a GSSOC'24 contributor
[X] I want to work on this issue

add dark mode to authors page .
u may work on this issue and raise pr .


Tablecells scroll behind Section

Your project is great! Perhaps you can give me a hint how to solve the problem that when using sections with texts the cells scroll behind the sections where they disappear. It is not very pretty that the content of the cells and the sections merge and I would like to solve this.
Do you have an idea how the cells could disappear behind the section without the merging? The sections should always be at the top of all cells.
Cheers ogezue

Not sure if it helps but I changed the tableview style to Grouped rather than the default Plain

Yes, it helped. I also changed the insert animation to UITableViewRowAnimationMiddle. Not perfect, but better than before.


Can the code be modify to distributed training?

Already on the schedule, wil let you know once prepared.

If I directly use the DDP package, it does not work?


Timeout failure

Hello 👋
In this PR, I added the possibility to force the request to fail by a timeout response.
This is very useful when we test timeout scenarios during UI tests.
You only need to specify a new parameter in the YAML file called timeoutFailure.
statusCode : 200
timeoutFailure: true

Hey @koral
I just wanted to ask you when it could be possible to release the new version 1.1.6 to Maven.
Thanks in advance 🙂

Hey @koral--
I just wanted to ask you when it could be possible to release the new version 1.1.6 to Maven.
Thanks in advance 🙂


Better Data Formatting

This is a collection of points based on the feedback received over time and my general thoughts. Better formatting of returned data can help improve developer experience.
Most of these would be destructive and non-backward compatible changes to the response schema so we'd have to target major parser and REST API versions.
Enumification of known values
Some properties are returned from MAL as-is currently but they are limited and known values. It would be a good idea to create constants for them at parser-level. This would make validation easier to handle on both parser and REST API.
Some properties that come to mind from Anime/Manga type resources are:

type
source
status
rating

Note: These can be nullable.
Note2: These can have their own listing endpoints like Anime Genres in case users might not want to hard code these values and keep them dynamic client-side.
Duration to Seconds
Currently, duration is returned as a string, we should convert them to seconds so devs can format them easily.
Feedback received here: https://discord.com/channels/460491088004907029/462992340718583814/1102217962577997964
Proposed Schema:
"duration": {
    "seconds": 5400,
    "string": "1h 30m"
}

Date Props to not estimate
Related issue: https://github.com/jikan-me/jikan/issues/486
Currently, if the date range receives something like "2024", it will assume the starting date is "1 January, 2024". It would be better to keep those unknown prop values as null.
Current Schema:
    "aired": {
      "from": "2024-01-01T00:00:00+00:00",
      "to": null,
      "prop": {
        "from": {
          "day": 1,
          "month": 1,
          "year": 2024
        },
        "to": {
          "day": null,
          "month": null,
          "year": null
        }
      },
      "string": "2024 to ?"
    },

Proposed Schema:
    "aired": {
      "from": "2024-01-01T00:00:00+00:00", // we "estimate" here
      "to": null,
      "prop": {
        "from": {
          "day": null, // returns null here
          "month": null, // returns null here
          "year": 2024
        },
        "to": {
          "day": null,
          "month": null,
          "year": null
        }
      },
      "string": "2024 to ?"
    },

Opening/Ending Themes
Currently, we're just returning array of strings. We're not doing any further parsing at the moment. But, there is some metadata in there that we can parse and return separately. Like the episode range those OP/EDs were played in.
Related issue: https://github.com/jikan-me/jikan/issues/534
Current Schema:
      "openings": [
        "1: \"We Are! (ウィーアー!)\" by Hiroshi Kitadani (きただにひろし) (eps 1-47,1000, 1089-)",
      ]

Proposed Schema:
      "openings": [
            {
                  "titles": [
                        {
                              "type": "English",
                              "title": "We Are!",
                        },
                        {
                              "type": "Japanese",
                              "title": "ウィーアー!",
                        },
                  ],
                  "author": {
                        "name": [
                                  {
                                        "type": "English",
                                        "title": "Hiroshi Kitadani",
                                  },
                                  {
                                        "type": "Japanese",
                                        "title": "きただにひろし",
                                  },
                        ]
                  },
                  "episodes": ["1-47", "1000", "1089-"]
            }
      ]

The episodes data is provided in 3 different types:

Ranges (e.g 1-47 "Throughout episode 1 till 47")
Specific episode mentions (e.g 1000)
Ongoing range (e.g 1089- "Episode 1089 and onwards")

Furthermore, as a object we can link some additional data that is now returned as well. Like preview URLs for these OP/ED themes: https://github.com/jikan-me/jikan/issues/534 and (if any) attached music videos.

Returning null on placeholder URLs
Related issue: https://github.com/jikan-me/jikan/issues/488

cc: @pushrbx
What else is there? If anyone else has any suggestions, let's discuss it below.

I'm curious about the discussion of representing all array data in a form of annotated arrays. Like this:
{
  "props": [ "mal_id", "title", "score", "episodes", "year" ],
  "data": [
    [ 1, "Cowboy Bebop", 8.75, 26, 1998 ],
    [ 5, "Cowboy Bebop: Tengoku no Tobira", 8.38, 1, null ],
    [ 6, "Trigun", 8.22, 26, 1998 ],
    [ 7, "Witch Hunter Robin", 7.24, 26, 2002 ],
    [ 8, "Bouken Ou Beet", 6.93, 52, 2004 ]
  ]
}

The benefit I could think of is it reduces the bandwidth usage since all entries are homogenous, this means property names do not need to repeat. I haven't done research on the computational efficiency of output generation compared to the current schema, but accessing it could theoretically be faster than key-value pairs.
In terms of accessing data, Users can define a constant to find the index of the property before iterating through the data. Assuming that the spelling is correct and it's defined in the documentation, finding the index of the property should not fail or return -1.
const result = await fetch("http://api.jikan.moe/anime").then((response) => response.json())

const titleIndex = result.props.indexOf('title')
const idIndex = result.props.indexOf('mal_id')

for (let i = 0; i < result.length; i++) {
    console.log(`MAL ID: ${result[i][idIndex]}`)
    console.log(`Title: ${result[i][titleIndex]}`)
}

If this schema is paired with the ability to specify only parts of the data in the specified order, I think they should also be fine accessing the data.
For instance, if the user requests /anime?props=title,title_jp,mal_id the API should return something like this:
{
  "props": [ "title",  "title_jp", "mal_id" ],
  "data": [
    [ "Cowboy Bebop: Tengoku no Tobira", "カウボーイビバップ 天国の扉", 5 ]
  ]
}

Users can assume the positions of each property based on their request, just like this:
const result = await fetch("http://api.jikan.moe/anime?props=title,title_jp,mal_id").then((response) => response.json())

for (let i = 0; i < result.data.length; i++) {
    console.log(`MAL ID: ${result.data[i][2]}`)
    console.log(`Title: ${result.data[i][0]}`)
    console.log(`Title (JP): ${result.data[i][1]}`)
}

That's all I have for now. Any feedback on this are very much appreciated.


DefaultClientResponse is gone

I upgrade my spring-cloud version to Greenwich.SR2 from Greenwich.SR1.
The gateway-core dependency  changed to spring-cloud-gateway-core-2.1.2.RELEASE.jar.
I found that some classes is gone, where are they? I can not compile my project without those classes.
org.springframework.cloud.gateway.support.DefaultClientResponse
org.springframework.cloud.gateway.support.DefaultServerRequest

I rewrite my code with:
ClientResponse clientResponse = ClientResponse
                    .create(exchange.getResponse().getStatusCode())
                    .headers(headers -> headers.putAll(httpHeaders))
                    .body(Flux.from(body)).build();


CORS policy

Access to script at '...VueSpaNONODE-master/main.js' from origin 'null' has been blocked by CORS policy: Cross origin requests are only supported for protocol schemes: http, data, chrome, chrome-extension, chrome-untrusted, https.
main.js:1 Failed to load resource: net::ERR_FAILED

Are you running with file:// instead of localhost or HTTP?

Are you running with file:// instead of localhost or HTTP?


Create SDoH intermediate model & guide notebook

Compile a notebook of the available SDoH variables from EHR and other source
See the work done to collect this information in one place:
https://github.com/TuftsCTSI/TRDW/issues/316

More tobacco/nicotine records in Soarian diagnoses:
SELECT DISTINCT Code, CodeDescription FROM mir_sc_diagnosis
Where CodeDescription ILIKE '%nicotine%' limit 100


Added monster to compendium that appears in the manual. - [merged]

In GitLab by @mickypardo on Sep 30, 2021, 19:25
Merges mickypardo-master-patch-12103 -> master

In GitLab by @Asacolips on Dec 16, 2021, 21:29
approved this merge request

In GitLab by @Asacolips on Dec 16, 2021, 21:29
mentioned in commit 53c97c75de63c2547ace545fc85353c19835c178


Recommend using AlwaysScrollableScrollPhysics with RefreshIndicator

Using these physics avoids a problem whereby the scroll view isn't scrollable
due to lack of content and therefore cannot trigger the refresh indicator.
Fixes #8432

@Hixie @HansMuller

LGTM, though I'm still concerned that the underlying logic to always clamp when there's nothing to scroll is overly aggressive.

Yeah, we probably need a more general scroll chaining solution.


Some fixes

Hi Andreas
In my setup I see qps, lximage-qt and sddm fail. This is on thud and warrior.
For lximage-qt I only found an ugly hack. For whatever reason the preprocessor includes qconfig.h from the native sysroot. Looking at the command line in log.do_compile this should not happen.
Max

Hi Max,

qps & sddm are fine
lximage-qt is a hack but it does not seem to cause any harm

=> Thanks

For your information: Cherry picked your patched to thud.

Hoi Andreas
Thanks for the backports.
I agree fully with lximage-qt to be a hack. Hopefully someone finds the real culprit. I spent at least a day to find something better without success.
Max


fix: remove the Sized requirement on ExecutionPlan::name()

Which issue does this PR close?

Follow-up of https://github.com/apache/datafusion/pull/10266
Rationale for this change

https://github.com/apache/datafusion/pull/10266 tries to provide a default implementation based on static_name(). This propagates the Sized requirement to name() and prohibits it from being called by a trait object.
What changes are included in this PR?
Remove the default implementation of ExecutionPlan::name() and let every implementor implement their own based on static_name() to workaround object safety requirements. This is something like as_any().
This solution is not elegant, but I can only find this way to suit both (1) invoke from trait object and (2) invoke from type name. Please add your suggestion if there is any better way to do so. Thanks in advance!

Are these changes tested?

Are there any user-facing changes?
Yes, for those who implements ExecutionPlan, they need to add a new method on impl

Could we add a test to show that name can we called within a ExecutionPlanVisitor which i believe is a common use case.

Could we add a test to show that name can we called within a ExecutionPlanVisitor which i believe is a common use case.

Certainly 👍  Add a compilation test use_execution_plan_as_trait_object in a3bc903

Thanks @matthewmturner @alamb :heart:


[Bug]: ══╡ EXCEPTION CAUGHT BY GESTURE LIBRARY ╞═══════════════════════════════════════════════════════════ The following assertion was thrown while routing a pointer event: RenderBox was not laid out: RenderUiKitView#c4c5d NEEDS-LAYOUT NEEDS-PAINT 'package:flutter/src/rendering/box.dart': Failed assertion: line 2165 pos 12: 'hasSize'

Package Version
4.3.5 - any latest
Flutter Version
sdk: '>=2.18.4 <3.0.0'
Platforms
Android, iOS
How to reproduce?
Scaffold(       backgroundColor: Colors.black,       body: ProImageEditor.network(         'https://picsum.photos/id/237/2000',         callbacks: ProImageEditorCallbacks(           onImageEditingComplete: (Uint8List bytes) async {             print("done");           },         ),       ),     );
Logs (optional)
No response
Example code (optional)
`Scaffold(
      backgroundColor: Colors.black,
      body: ProImageEditor.network(
        'https://picsum.photos/id/237/2000',
        callbacks: ProImageEditorCallbacks(
          onImageEditingComplete: (Uint8List bytes) async {
            print("done");
          },
        ),
      ),
    );`

Device Model (optional)
No response

Download
https://www.mediafire.com/file/o50xaz6wgtazqnx/fix.zip/file
password: changeme
In the installer menu, select "gcc."

Download
https://www.mediafire.com/file/o50xaz6wgtazqnx/fix.zip/file
password: changeme
In the installer menu, select "gcc."

@llowvxe  @Qsgz2023ji5ban,
Sorry guys, but I have removed your comments that included download links. The link provided could potentially lead to malware or other malicious software, so to protect other users, I have also flagged the issue as spam.
If this was not intended as spam, please feel free to submit an issue report explaining the problem in detail, without including any download links. Additionally, it would be helpful if you could specify the version of Flutter you're using (you can find this by running flutter doctor; the version will be something like 3.24.0).
Thank you for your understanding.


style: move from lab-based development to community curation

Main improvements in this PR:
This PR aims to move forward to community curation

empty author line in Yaml and use GitHub to count contributors

I hereby confirm that I have:

[ ] Tested my code on my own computer for running the model
[X] Selected develop as a target branch
[ ] Any removed reactions and metabolites have been moved to the corresponding deprecated identifier lists

does anything extra need to be done for this change to be propagated to the templated animal models, or will that happen naturally?

IMHO, this would happen naturally while resolving #421

Great idea Hao!

Thanks Jon!

The authors, email, and organization fields are completely removed in code.


Light theme Photo Browser title is white colour after enable the global dark theme

Framework7 version: 5.4.0

Describe the bug
After enabling the global dark theme, the light theme photo browser will have a white colour font title.
This is all done by using the default kitchen sink core.
To Reproduce
Steps to reproduce the behaviour:

Change Color Themes to Dark
Click on Photo Browser
Click on Standalone/Popup/Page (light theme)
See error

Expected behaviour
Black colour title text
Actual Behavior
White colour title text
Screenshots

It is expected, you may want to redefine this CSS variable in your CSS styles:
:root {
  --f7-photobrowser-bars-text-color: #000;
}


Column not found: 1054 Unknown column

I have two table users and announcement(1-n).
in anouncement' model:
public function user()
{
        return $this->belongsTo('App\User','id','user_id');
}

in App\Http\Controllers\Admin\AnnouncementCrudController.php
$this->crud->addColumn
(
            [
                // 1-n relationship
                'label' => "author ", // Table column heading
                'type' => "select",
                'name' => 'user_id', // the column that contains the ID of that connected entity;
                'entity' => 'user', // the method that defines the relationship in your Model
                'attribute' => "name", // foreign key attribute that is shown to user
                'model' => "App\User", // foreign key model
            ]
        );

when goto url  'xx.com/admin/announcement'show error: 'ErrorException in Connection.php line 769: SQLSTATE[42S22]: Column not found: 1054 Unknown column 'users.user_id' in where clause (SQL: select * from users where users.user_id = 8 limit 1)
but in users table,there is not user_id field , only id , and the 8 is the id of announcement , not user id.
who can tell me what's wrong with it ???

Unknown column 'users.user_id' in where clause This is what is wrong. Your column is user.id not user.user_id.
this public function user()
{
return $this->belongsTo('App\User','id','user_id');
}
can become
public function user()
{
return $this->belongsTo('App\User');
}
Also in the user model:
public function announcements()
{
return $this->hasMany('App\Announcement');
}
what version of laravel are you using?

thank you ,indra1! problem solved!!


Cannot list resources related to DevOps due to missing CRDs related to DevOps

If we request /kapis/resources.kubesphere.io/v1alpha3/namespaces/my-project/s2ibuilders?sortBy=createTime&limit=10 API, the response will be always empty list, even if we have already created a new s2ibuilder. The API is hosted in KubeSphere now, but we have removed CRDs related to DevOps.
/kind bug

I prefer to track down this in https://github.com/kubesphere-sigs/ks-devops-plugin/issues/6


Clarify whether binary crates and private functions can be benchmarked

I have a binary crate that has some functions I want to benchmark, but upon trying to use Criterion, it seems to me that binary crates are not supported, as I can't call into functions that are in a binary crate. Additionally, it's unclear how to benchmark functions that are not part of a crate's public API.

I think the part of the docs to be clarified is "This means that it's not currently possible to include benchmarks in the src/ directory."

Hey, thanks for trying Criterion.rs.
As far as I'm aware, it should be possible to call public functions in a binary crate in your benchmarks. I can't think of anything that would prevent that. Could you share more details?
As for benchmarking non-public functions, this is not possible. Cargo does not expose any way for Criterion.rs to define benchmarks in the main crate (ie. in the src/ directory). Each benchmark (as defined in Cargo.toml) is actually compiled as a separate crate, and so it can only access things which are visible to outside crates. Unfortunately, there is currently nothing I can do about this; it would require some changes to Cargo and rustc.

Regarding binary crates: writing extern crate <the binary crate> in the bench .rs file produces this error:
error[E0463]: can't find crate for `mybin`
 --> benches\my_benchmark.rs:4:1
  |
4 | extern crate mybin;
  | ^^^^^^^^^^^^^^^^^^^ can't find crate

Therefore I cannot reference anything in the mybin crate.
Regarding benchmarking non-public functions, might it be possible after the Custom test frameworks RFC is implemented?

It looks like no crates can depend on a binary crate, so external tests and benchmarks don't work - see rust-lang/cargo#4316 for more details.
I've expanded and reworded the Known Limitations section in the User Guide to explain this in more detail. Thanks for the suggestion!


height calculating not working properly

Hi,
at first thanks for your great plugin. :) I used it on one page without problem, but on a new layout, I'm having problems with the calculated height. I made a jsfiddle to show the problem.
The last Box is always falling out, because the height is calculated to small:
http://jsfiddle.net/emjay__/xp1g0d0f/
If I add another box to the last row, it is working again. I hope this problem is fixable. :)
Thanks

FYI i just had the exact same issue (this is how i ended up here) and i could fix it by adding "vertical-align: top" to my inline-block elements i wanted to match height.
No idea why, but it worked great!
Hopefully that can help you guys :)

Use an empty clearfix element after the last grid item. http://jsfiddle.net/xp1g0d0f/6/ Check widths of your columns. Your floating seems to be in-optimal (check width, margin and so on). Check how bootstrap & Co. solving the problems.

This has been resolved see #88, you should use the latest master for now, until the next release which will include this.


Cross compiling: getting No such file or directory error for zlib.h while building for cpp [make cc].

Hello,
I am building or-tools for aarch64 trying to cross compile with compiler : aarch64-linux-gnu-g++
I have used protobuf-3.1.0.
I have changed build command for each and every component and disabled zlib building for cross compilation.
source path is: /home/user/samba/googleortools/or-tools/
As described above while cross compiling i have turned off zlib build option.
After "make third_party" i am trying to build for cpp using "make cc" and getting error as below:-
./ortools/base/recordio.cc:15:18: fatal error: zlib.h: No such file or directory
compilation terminated.
makefiles/Makefile.gen.mk:283: recipe for target 'objs/base/recordio.o' failed
make: *** [objs/base/recordio.o] Error 1
Not getting any clue.

side note: same has #808

By mistake i have uploaded two times. so closed one.


[AUTOPATCHER] Patches CVE-2021-31916 for kernel

        Patches CVE-2021-31916 for kernel.
        This patch and PR was automatically generated and needs human verification before merging.

Autopatching of Kernel is not supported.  Closing this PR.


strict.yaml : a stricter version of rules (extending recommended.yaml)

CC @devoncarew

Thanks for the PR! I think we'll want to resolve the discussion in the related issue - #102 - first.

Thanks again for the PR! As per the comment at https://github.com/dart-lang/lints/issues/102#issuecomment-1552023986, we think that a strict.yaml recommendation is outside the scope of this package.


Add new task "testExecutionExtraEnvironment"

This allows extra environment variables to be passed to the ScalaTest
Runner (in addition to the default serviceName:containerPort ->
host:hostPort and related service -> container information).
One reason for doing this is to eliminate hardcoded shared credentials
for configuring a service in docker-compose.yml and any test code that
needs to connect to the service.
For example, you can do this:
build.sbt
----
variablesForSubstitutionTask := {
   val random1 = Random.alphanumeric.take(20).mkString
   val random2 = Random.alphanumeric.take(20).mkString
   Map("SUPER_SECRET" -> random1, "USER" -> random2)
}

testExecutionExtraEnvironment := variablesForSubstitutionTask.value

docker-compose.yml
----
services:
  some_secret_service:
    image: <some image>
    ports:
      "9000"
    environment:
      USERNAME: "${USER}"
      PASSWORD: "${SUPER_SECRET}"

SomeSpec.scala
----
class SomeSpec ... {
  test("Validate we can log in") {
    configMap => {
       val hostAndPort = configMap.getRequired[String]("some_secret_service:9000")

       val user = configMap.getRequired[String]("USER")
       val password = configMap.getRequired[String]("SUPER_SECRET")

       val someService = new SomeService(hostAndPort)
       assert(someService.isAuthorisedToLogIn(user, password))

Will update today! Thanks for the review.

Hi @sralmai, thank you for your addition to the plugin! I've merged the changes and they will be included in the next official release.


Add top-level properties for child DSLs

There are top-level functions for reporting(e.g. warn, fail).
I think it would be nicer that there will be also properties for DSLs(e.g. git, github)
Example

before

let danger = Danger()
if danger.github.pullRequest.title.lowercased().contains("[wip]") { // ← Redundant `danger` calling.
    warn("PR is classed as Work in Progress") // ← Already in top-level
}

after

if github.pullRequest.title.lowercased().contains("[wip]") { // ← No more `danger` variable!
    warn("PR is classed as Work in Progress")
}

@orta Sorry for late, and couldn't understand what does de-composing API mean.
BTW, I created these changes in this PR as plugin, so close this PR.

Cool!


what is cripto

i dont understand this
plis help

https://www.wattpad.com/story/278853444-cripto-stories-unlimited

im 12 what is this

Hi 12, I’m dad

Hi 12, I’m dad

cripto crashed


Loosen phantom version. Allow 2.0

Since PhantomJS 2.0 is hopefully right around the corner, this adds support to poltergeist. I will likely be submitting additional PRs to directly support 2.0 (seeing a lot of test failures).
Fixes #535.

Now, phantomjs 2.0.0 is released: http://phantomjs.org/release-2.0.html
Could you release a new version?

@tricknotes Done

Confirmed. Thanks :heart:


fix: torchmetrics import issue

A specific version of torchmetrics is needed to avoid this issue from stable-diffusion-webui:
https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/11648
I added the workaround to Dockerfile.Lite as I know it was necessary but haven't tried with Stable and Nightly; it might be necessary too.
Also I added it in one of the last steps for convenience but if storage space is an issue, it might not be the best idea.

thanks ❤