2 different chats

Is there a possibility to send Telegramm messages to different Bots?
I would like to have my telegram chats nice and clean 😅
For example i would like to receive my 'Concerts' alert in a different chat than my 'BMW' alert.
Is this possible? Thanks

Thanks for this 👍

I think i was a bit too quick when closing my request. I dont get it how to setup the multiple user. Could you explain it for dummies :-)
Regards Michael

I am not sure what is going on in this monologue so far. I forked this project and edited it to my needs. As far as I can tell from the code there currently is no feature to send different searches to different telegram chats. What I did was: I have a development telegram bot sending messages when i debug. and i have a produktion tegeram bot. What i do is using separated configs files for these two different environments. What you woul need to do is actually modify the links table in database and add the funktions you need to save bots (ids and tokens) per search. I did not reasearch if you actually can have two separate chats open with the same bot on telegram. It would be like having two users on telegaram chatting over different chats. I do not know if telegram does that. I suspect not. So you would need to different bots sending you messagases from separate searches. That would populate two different chats.
Does that help?

Well, my target is following: I have some telegram bots, also one with your ebAlert. I told a friend about your ebAlert and she asked me if i can add another link to my ebAlert configuration, so she receives those messages? For example i have added a link about tables an i get those telegram Messages and i want to add another link about chairs which my friend will receive those telegram messages. Any idea for my problem?


mark trilead api as test (even if we should not need this)

see https://github.com/jenkinsci/bom/pull/3049
Signed-off-by: Olivier Lamy<EMAIL_ADDRESS>
Testing done

### Submitter checklist
- [ ] Make sure you are opening from a **topic/feature/bugfix branch** (right side) and not your main branch!
- [ ] Ensure that the pull request title represents the desired changelog entry
- [ ] Please describe what you did
- [ ] Link to relevant issues in GitHub or Jira
- [ ] Link to relevant pull requests, esp. upstream and downstream changes
- [ ] Ensure you have provided tests - that demonstrates feature works or fixes the issue

https://github.com/jenkinsci/maven-hpi-plugin/pull/391#issuecomment-2024906154 ?

I do not follow all the nuances here, but as a procedural request: if it is not clear in advance whether some proposed plugin change will fix something in PCT, or there is some reason to suspect that it might regress something in PCT, please do not file a PR for it as “ready for review” and expect reviewers to catch mistakes or have to revert updates. Instead, file the PR but keep it in draft, wait for an incremental release, and file a draft PR against bom which includes all proposed changes in combination (paste in the URLs in GitHub so we get backlinks) and is marked with a suitable label to run tests on the weekly line or the relevant LTS lines. (Before filing, you can also follow instructions in bom for running selected tests locally.) Only when that is green should the component PRs be opened up for review.

I do not follow all the nuances here, but as a procedural request: if it is not clear in advance whether some proposed plugin change will fix something in PCT, or there is some reason to suspect that it might regress something in PCT, please do not file a PR for it as “ready for review” and expect reviewers to catch mistakes or have to revert updates. Instead, file the PR but keep it in draft, wait for an incremental release, and file a draft PR against bom which includes all proposed changes in combination (paste in the URLs in GitHub so we get backlinks) and is marked with a suitable label to run tests on the weekly line or the relevant LTS lines. (Before filing, you can also follow instructions in bom for running selected tests locally.) Only when that is green should the component PRs be opened up for review.

sure I will change that.
If only Maven have a scope such pct-fix-workaround :)

see https://github.com/jenkinsci/bom/pull/3070

different fix with #98


Error: Failed to initialize build "amazon-ebs"

I am running into this issue with amazon-ebs building with this repo.
[cloudshell-user@ip-10-132-61-14 amazon-eks-ami-rhel]$ make 1.28
which: no shfmt in (/home/cloudshell-user/.local/bin:/home/cloudshell-user/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/lib/node_modules/aws-cdk/bin)
which: no shellcheck in (/home/cloudshell-user/.local/bin:/home/cloudshell-user/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/lib/node_modules/aws-cdk/bin)
make k8s kubernetes_version=1.28.1 kubernetes_build_date=2023-09-14
make[1]: Entering directory '/home/cloudshell-user/amazon-eks-ami-rhel'
which: no shfmt in (/home/cloudshell-user/.local/bin:/home/cloudshell-user/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/lib/node_modules/aws-cdk/bin)
which: no shellcheck in (/home/cloudshell-user/.local/bin:/home/cloudshell-user/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/lib/node_modules/aws-cdk/bin)
/usr/bin/packer validate -var-file /home/cloudshell-user/amazon-eks-ami-rhel/eks-worker-rhel-variables.json  -var docker_version='none' -var ami_name='amazon-eks-node-rhel-1.28-v202312141901' -var instance_type='t3.large' -var kubernetes_build_date='2023-09-14' -var arch='x86_64' -var ami_component_description='(k8s: {{ user `kubernetes_version` }}, containerd: {{ user `containerd_version` }})' -var kubernetes_version='1.28.1' /home/cloudshell-user/amazon-eks-ami-rhel/eks-worker-rhel.json
Error: Failed to initialize build "amazon-ebs"

The builder amazon-ebs is unknown by Packer, and is likely part of a plugin that
is not installed.
You may find the needed plugin along with installation instructions documented
on the Packer integrations page.

https://developer.hashicorp.com/packer/integrations?filter=amazon

make[1]: *** [Makefile:98: validate] Error 1
make[1]: Leaving directory '/home/cloudshell-user/amazon-eks-ami-rhel'
make: *** [Makefile:128: 1.28] Error 2

Suggestions on how to resolve this?

Hey @orsenthil did you ever get past this issue? It looks to be environmental but hard to confirm based solely on the information above. I see you are attempting this in CloudShell. Is there any more information you can provide such as your region? Did you modify the Makefile at all, or did you leave everything cloned from the repo untouched?

I think this might be due to the recent changes to Packer such that you now need to specify a required_plugins section and run packer init...? https://developer.hashicorp.com/packer/docs/commands/init
Although that page states this should only be required for HCL based templates and not JSON.

I think this might be due to the recent changes to Packer such that you now need to specify a required_plugins section and run packer init...? https://developer.hashicorp.com/packer/docs/commands/init
Although that page states this should only be required for HCL based templates and not JSON.

I think you are right, Andy. I started seeing this myself but only in certain scenarios. So I ended up updating the documentation to install this plug-in during the packer installation step. I haven't found that it causes any issues by installing it manually if it isn't needed.

adding the below to my  overrideBootstrapCommand and rerunning eksctl to create the cluster worked.  Am continuing testing but so far so good
/etc/eks/bootstrap.sh $EKS_CLUSTER
systemctl disable nm-cloud-setup.timer
systemctl disable nm-cloud-setup.service
reboot

I had to make other changes for my STIG hardening to work to apply a EKS profile on a already hardened RHEL8 Stig image, but I'll start a new thread with that.

packer plugins install github.com/hashicorp/amazon

Helped resolve this issue.


Update README.md

Add instructions for MacOS dependency installation.

@anouskastreets Thank you so much for making a contribution!
However, QEMU and Libvirt are dependencies for CF Dev on the Linux platform only. VM management/Networking is handled by hyperkit/vpnkit on MacOS, and these dependencies are automatically downloaded by the tool, if necessary. It would be erroneous to have users of MacOS perform those brew commands.

Thanks @aemengo good to know. Thanks for your time.


Hide feedback opportunity message

Describe the bug
For every az command that I run, I get the following message displayed:
Please let us know how we are doing: https://aka.ms/azureclihats
and let us know if you're interested in trying out our newest features: https://aka.ms/CLIUXstudy

Is there a way to disable this message?
To reproduce
Run any az command, for example az --help.
Expected behavior
This message is shown alongside information that describes how to disable the message.
Environment summary
Windows-10-10.0.18362-SP0
Python 3.6.8
Installer: MSI

azure-cli 2.21.0

Extensions:
application-insights 0.1.13

hi @cgwrench unfortunately, tthere's no way to disable the survey link. You can ignore them. could you share more about impact of it? thanks

Actually, there is a config option that can hide the survey link:
az config set output.show_survey_link=no

Thanks @fengzhou-msft, that's exactly what I was looking for.
@yungezz - the impact of the link is really just the annoyance of it. It's noise that I'd rather not see every time I run any az command. Especially since I've already completed the survey, why would I want to keep being reminded about something I've already done (even if I hadn't completed the survey, why would I want to keep being reminded about something I probably had no intention of doing)?
Having the option to display this text is good. It would be great if the survey message included some text to show how to hide this with az config.


[docs] Following MS Windows Setup tutorial leaves user without functioning NPM

I've been following the MS Windows setup step by step, and ran into this issue.
I was not using nvm before
Apparently nvm installs node and npm in C:/Program Files/nodejs
Running powershell as admin, npm is available, but if not in and administrative shell, using npm will cause errors like this:
PS C:\Users\BENOIT\Dev\rust\tauri-test> npm -v
internal/modules/cjs/loader.js:984
  throw err;
  ^
Error: Cannot find module 'C:\Users\BENOIT\AppData\Roaming\npm\node_modules\npm\bin\npm-cli.js'
    at Function.Module._resolveFilename (internal/modules/cjs/loader.js:981:15)
    at Function.Module._load (internal/modules/cjs/loader.js:863:27)
    at Function.executeUserEntryPoint [as runMain] (internal/modules/run_main.js:74:12)
    at internal/main/run_main_module.js:18:47 {
  code: 'MODULE_NOT_FOUND',
  requireStack: []
}

For some reason it looks for npm-cli in AppData, instead of C:/Program Files/nodejs
This can easily be solved by running the following command:
yarn global add npm

This has little to nothing to do with tauri, but I wanted to document it here in case new users face this issue in the future.

@BenoitRanque - would you consider please adding this info to the wiki?

Done!
Closing issue


tpc provider: terraform templates: firewall

This is probably similar enough to the firewall triton resource to be able to duplicate the aws cluster_secgroup configuration.

This may not make the first cut. There are no kubernetes drivers to manage updates to the firewall and a shim may need to be created.

is blocked by #258


failed to loading the checkpoint

I'm using my own computer.But failed to load the checkpoint.
Here is the bug:
RuntimeError: Exception: Error(s) in loading state_dict for FAST_LCF_ATEPC:
Unexpected key(s) in state_dict: "bert4global.embeddings.position_ids".  Fail to load the model from checkpoints/ATEPC_ENGLISH_CHECKPOINT/fast_lcf_atepc_English_cdw_apcacc_82.36_apcf1_81.89_atef1_75.43!
I have tried other checkpoint like mutilin,but still got the same bug.
Thanks in advance.

I have the same problem after a clean installation in a new virtual environment,
[2023-07-26 10:52:36] (2.3.1) Downloading checkpoint:english
[2023-07-26 10:52:36] (2.3.1) Notice: The pretrained model are used for testing, it is recommended to train the model on your own custom datasets
Downloading checkpoint: 534MB [02:17,  3.89MB/s]
Find zipped checkpoint: ./checkpoints\ASTE_ENGLISH_CHECKPOINT\ASTE-EMCGCN_SemEval_f1_74.71.zip, unzipping
Done.
[2023-07-26 10:55:08] (2.3.1) If the auto-downloading failed, please download it via browser: https://huggingface.co/spaces/yangheng/PyABSA/resolve/main/checkpoints/English/ASTE/ASTE-EMCGCN_SemEval_f1_74.71.zip
[2023-07-26 10:55:08] (2.3.1) Load sentiment classifier from checkpoints\ASTE_ENGLISH_CHECKPOINT
[2023-07-26 10:55:08] (2.3.1) config: checkpoints\ASTE_ENGLISH_CHECKPOINT\emcgcn.config
[2023-07-26 10:55:08] (2.3.1) state_dict: checkpoints\ASTE_ENGLISH_CHECKPOINT\emcgcn.state_dict
[2023-07-26 10:55:08] (2.3.1) model: None
[2023-07-26 10:55:08] (2.3.1) tokenizer: checkpoints\ASTE_ENGLISH_CHECKPOINT\emcgcn.tokenizer
[2023-07-26 10:55:09] (2.3.1) Set Model Device: cpu
[2023-07-26 10:55:09] (2.3.1) Device Name: Unknown
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
RuntimeError                              Traceback (most recent call last)
File [c:\Users\jgascon\Documents\GitHub\content_lib.venv\lib\site-packages\pyabsa\tasks\AspectSentimentTripletExtraction\prediction\predictor.py:82](file:///C:/Users/jgascon/Documents/GitHub/content_lib/.venv/lib/site-packages/pyabsa/tasks/AspectSentimentTripletExtraction/prediction/predictor.py:82), in AspectSentimentTripletExtractor.init(self, checkpoint, **kwargs)
79     self.model = self.config.model(config=self.config).to(
80         self.config.device
81     )
---> 82     self.model.load_state_dict(
83         torch.load(
84             state_dict_path, map_location=torch.device("cpu")
85         )
86     )
87 elif model_path:
File [c:\Users\jgascon\Documents\GitHub\content_lib.venv\lib\site-packages\torch\nn\modules\module.py:2041](file:///C:/Users/jgascon/Documents/GitHub/content_lib/.venv/lib/site-packages/torch/nn/modules/module.py:2041), in Module.load_state_dict(self, state_dict, strict)
2040 if len(error_msgs) > 0:
-> 2041     raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
2042                        self.class.name, "\n\t".join(error_msgs)))
2043 return _IncompatibleKeys(missing_keys, unexpected_keys)
RuntimeError: Error(s) in loading state_dict for EMCGCN:
Unexpected key(s) in state_dict: "bert.embeddings.position_ids".
During handling of the above exception, another exception occurred:
RuntimeError                              Traceback (most recent call last)
Cell In[2], line 4
1 from pyabsa import AspectSentimentTripletExtraction as ASTE
3 # Load the model
----> 4 triplet_extractor = ASTE.AspectSentimentTripletExtractor("english")
5 #triplet_extractor = ASTE.AspectSentimentTripletExtractor("multilingual")
File [c:\Users\jgascon\Documents\GitHub\content_lib.venv\lib\site-packages\pyabsa\tasks\AspectSentimentTripletExtraction\prediction\predictor.py:99](file:///C:/Users/jgascon/Documents/GitHub/content_lib/.venv/lib/site-packages/pyabsa/tasks/AspectSentimentTripletExtraction/prediction/predictor.py:99), in AspectSentimentTripletExtractor.init(self, checkpoint, **kwargs)
96             print_args(self.config)
98     except Exception as e:
---> 99         raise RuntimeError(
100             "Fail to load the model from {}! "
101             "Please make sure the version of checkpoint and PyABSA are compatible."
102             " Try to remove he checkpoint and download again"
103             " \nException: {} ".format(checkpoint, e)
104         )
106 self.dataset = ASTEInferenceDataset(self.config, self.tokenizer)
108 self.post_init(**kwargs)
RuntimeError: Fail to load the model from english! Please make sure the version of checkpoint and PyABSA are compatible. Try to remove he checkpoint and download again
Exception: Error(s) in loading state_dict for EMCGCN:
Unexpected key(s) in state_dict: "bert.embeddings.position_ids".

I have solved using  transformers=4.29.0. Just uninstall and install again this specific version

I don't understand about transformers.Do transformers mean the version of Pyabsa or something else?It's my first time to do this job.It may sound silly,but please tell me more details about it.Thanks.

No worry. Transformers is a library in python, the problem is that the newer versions are not compatible with the last version of pyabsa. You need to uninstall transformers (pip uninstall transformers) and then install the specific version (pip install transformers==4.29.0).

Thank you for your answer.


fixed include file for electron

Closing, as #9 was merged instead. Thanks for helping out though, and especially thanks to @davegregg for helping with reviewing!

I decided to use this after all, since __dirname will work regardless of how and where electron was started. #9 assumed user is always in the repository root.
I committed and pushed locally to fix the typo. I thought git apply was preserving the author, as it was in the patch, but it didn't. Sorry about that @tojocky. Thanks for the help in any case.


SPIKE: As a developer, I want to spend time understanding PyTorch, so that we can model baboon movement.

Marking this as done until we have a use case for it.  Early WI21


The app hangs when we go from any other activity to leaderboard

Whenever we try to go to leaderboard from any other activity the app hangs and stops working.
If you go to leaderboard directly it works but when you change the activity and again try to go to leaderboard tab the app
will hang and you have to restart the app again.
https://github.com/Yash-Parsana/CrazyCoderApp/assets/116300962/48228d2f-7c22-44fe-8405-2f4b6f800809

I want to contribute to this issue please assign this issue to me under ggsoc tag .

I've already mentioned this issue on yesterday's afternoon

This issue is already solved in Local Repo


translation in selects

hi!
I have a select, its schema looks like this:
    type: {
      type: 'string',
      enum: ['Event', 'BusinessEvent', 'ComedyEvent', ... ],
      default: 'Event'
    }

and its form def like this:
    {
      key: 'type',
      title: $translate.instant('templates.forms.event.type'),
      feedback: false
    }

I'm using angular translate for the i18n. The select works flawlessly, however I haven't found a way to translate the actual items in the enum. Is there a way to do this?
I was thinking of something in the form def like this:
    {
      key: 'type',
      title: $translate.instant('templates.forms.event.type'),
      feedback: false,
      showAs: function(value) {
        return $translate.instant('templates.forms.event.' + value);
      }
    }

Would it be possible perhaps to use titleMaps somehow like this?
    {
      key: '@type',
      type: 'select',
      title: $translate.instant('templates.chatbot.forms.event.type'),
      feedback: false,
      titleMap: function(a) {
        $translate.instant('templates.chatbot.forms.event.' + a)
      }
    }

...instead of having to enumerate all of them with their corresponding i18n:
       titleMap: {
         'Event': $translate.instant('templates.chatbot.forms.event.Event'),
         'BusinessEvent': $translate.instant('templates.chatbot.forms.event.BusinessEvent'),
         ...etc...
       }

Does that make any  sense? I think it'd be a cool addition - I can see too how enumerating them explicitly would be a problem in a dynamically fetched enum.

@gatperdut the current aim is to remove functions from the ui-schema where we can.
Any PR would need to include a method that took a tag or id in the schema and handled the lookup in the add-on ideally.
Have you thought about handling the translation in a function that is the provider of the select? There are a few different select options that look up titleMap from a function.

@Anthropic I am using titleMap in the form definition. Now I'm wondering if I should be doing that at all.
I'll give a try to your suggestion with the function.

worked fine, thank you very much! I still believe though a function in the form definition assigned to titleMap would be very useful.

@gatperdut there is such an option in the Material decorator already.
You can look up the example for titlemaps.json used by the controller in example.html and see that with the following form definition it looks up the value on the scope, I intend on adding this basic ability to bootstrap too eventually.
Loading via function call
  $scope.arnieFlix = loadFlix();

Displaying based on watching the scope variable
  {
    "key": "selectOptionData",
    "type": "select",
    "optionData": "arnieFlix"
  }

I just haven't had the time to port it over yet.


[LCP] Audit if eager stop of LCP is correct for cases where LCP is in-flight

Today web-vitals.js will automatically stop the LCP algorithm in cases of measured discrete interaction.  The list of interactions that we support is limited, and doesn't include all event types nor scroll.
But one thing I'm also not sure about:

When the LCP algorithm stops, I think it stops accepting new candidates
Any existing candidates still get measured to presentation time.

Specifically, I'm wondering about cases where a large image is still loading, or still decoding.
Its possible that PerformanceObserver.tageRecords() will not return entries, but there are still entries "in flight".
(Note: There are similar issues with Event Timing and timings in-flight.  Perhaps PerformanceObserver API should also have an async version of takeRecords() which will flush and report one last time...)

Specifically, I'm wondering about cases where a large image is still loading, or still decoding.

I'm not sure there's a good answer here. Think of the following edge cases:

The in-flight image is half off-screen. The user scrolls while it's still loading and it's completely on-screen now and is larger than the previous LCP. Should that be the new LCP even though it occurred after user input when the LCP element was still on screen? I'd argue not (and it wouldn't have been if the user had waited a little longer to scroll).
Similarly an in-flight off-screen image that is loaded (either because of no lazy loading, or within lazy-loading viewport thresholds) can now be eligible.
Or imagine the reverse where an image is inflight and is going to be the LCP element but then the user screens down and nothing is painted. In this case the LCP entry would presumably not fire? But if you're saying in-flight resources should be eligible than that seems kinda inconsistent.

So I'm not sure the PO should fire in these cases, and that the web-vitals.js logic isn't the correct one to go with...

I think you may have misunderstood my question-- I'm just saying that Chrome has already decided on answers to these questions and web-vitals shouldn't be making different decisions.
Even if we want to change the answers, we should still try to synchronize.
I don't for sure yet if it differs, that's why I would like a (quick?) audit!

Here's what I think happens today:

images which have already been rendered (I mean on the main thread stage of rendering) and
have already been marked as lcp candidates, and
we are still waiting for their presentation times as they get decoded...

I believe you are effectively guaranteed to get a next presentation time for that image, and an element timing / LCP entry for it, even if you scroll.  That is because there is already a main-thread rendering update in the rendering pipeline and the presentation time will be the time that update is included in a screen update.  I don't believe we necessarily track if the image was still within viewport at that point.
In other words, I suspect the LCP-halt-on-interaction heuristics stops new candidates from being queued up for measurement, rather than stopping LCP results from being added to timeline.
Not sure!

Finished Audit.  Looks like although image paints are measured until presentation time, even after input or scroll, those times end up discarded.  The LCP calculator uses the main thread InputOrScroll time as the last point to capture recorded LCP times.


docs: Bridge package docs: flame_fire_atlas

Description
Added bridging docs for flame_fire_atlas
Checklist

[x] The title of my PR starts with a [Conventional Commit] prefix (fix:, feat:, docs: etc).
[x] I have followed the [Contributor Guide] when preparing my PR.
[ ] I have updated/added tests for ALL new/updated/fixed functionality.
[ ] I have updated/added relevant documentation in docs and added dartdoc comments with ///.
[ ] I have updated/added relevant examples in examples or docs.

Breaking Change?

[x] No, this PR is not a breaking change.

Related Issues
Closes #1962 Bridge package docs: flame_fire_atlas

Example Video
Uploading Screen Recording 2022-10-14 at 5.10.38 PM.mov…

Example Video
https://user-images.githubusercontent.com/36990991/195839719-ba7a97bb-704f-49a3-a34f-b121b9e6329a.mov


Retrieved event and setAttribute update the value on database while log out

Laravel Version
11
PHP Version
8.3
Database Driver & Version
MySQL 8
Description
I have a traits namely CleanStorage which is handle the file upload update and delete action and clear the file from storage, and also it has a retrieved event which is update the specified attributes with storage URL.
But the problem is while I used this trait in User model and tried to log-out and login the attribute is update with like this in the database /storage/users/[random-string].png every time I login and logged out it's update in the database with prefix of /storage/[rest-of-the-path]
I don't know this is an issue or not but this issue takes me here from a production application, if there are any better approach to do that then suggest me. 👍
I have attached the trait screenshot and also the usages.

Steps To Reproduce
Just use the traits and login then upload a image or update the DB columns with a local image path like this users/user.png and log out and login again check the DB or dump the user.

BTW I have solved the issue for myself by using this.
static::retrieved(function (Model $model) {
    foreach ($model->columnsForStorageItems() as $column) {
        // update the attribute
        $model->setAttribute(
            $column,
            $model->getStorageUrl($model->getRawOriginal($column))
        );

        // Sync the original attribute
        $model->syncOriginalAttribute($column);
    }
});

but maybe I'm doing it in a wrong way and it make me a wrong feeling.


[WFLY-10028] Move XML validation test to dist

Running the XML and XSD validation test from dist module ensures that
the test validates the actual files shipped with WildFly before there
is any chance they are modified by another test in smoke (or web) test
suite.
JIRA: https://issues.jboss.org/browse/WFLY-10028

@ctomc could you review please?

All validation tests for https://github.com/wildfly/wildfly-core/pull/3154 passes with that PR: https://ci.wildfly.org/viewLog.html?buildId=94714&buildTypeId=WildFlyCore_PullRequest_WildFlyCoreFullIntegration&tab=testsInfo

Have precautions been taken to ensure that there is no possibility of a surefire execution in this module modifying the content of dist/target/wildfly-xxx/ ?
If yes, 👍
Simply poking around in that dir after the module is installed / tests run it looks fine, so my concern is more about making sure that's not fragile.
(I don't need details, a simple 'we're good' is fine.)

There is no precautions about modifying the content of dist/target.
This new test suite is about validating the content of the distribution and must not be used to run any WildFly code (no arquillian test would be allowed).
Having said that, it is simple to to copy the content of dist/target/wildfly-x to another directory and run any tests from that copy. I'll modify this PR to do so.

@bstansberry I have modified the PR to copy all XSD and XML files in a separate directory for the tests .

Windows job failure is due to a execution timeout (4289 test were run / 4293)


Cannot parse "rest of line" as a token without matching the entire line

I have a grammar in which I have lines like this:
    key: value

I need to extract the indent, key, and value from here. The indent is the number of spaces divided by 4, the key is any string that does not include ":", and the value is everything from the end of the whitespace following ":" until the end of the line, including any subsequent colons. My initial attempt at this was to make the following rules:
rule(indent: /(    )*/).as { |str| str.length / 4 }
rule(key: /[^:\s][^:]*/)
rule(":" => /:\s*/)
rule(value: /\S.*/)
rule(:line) do |r|
  r[:indent, :key, ":", :value]
end

The problem is that the :value rule matches the entire "key: value" sequence, making it the longest match, so whittle throws an error when it finds a :value after the :indent instead of a :key. Does whittle have a way to represent this kind of grammar?

I think you want to use a rule that matches the end-of-line explicitly. Like the example at https://github.com/d11wtq/whittle#skipping-whitespace-and-comments, so you'd have:
rule(value: /\S.*$/m)


[Feature]Add option not to rename uploaded files

Now the voyager renames uploaded images as slug/monthyear/random.ext, which isn't useful. It would be nice to add any option or some way to customize what to do with such names.
BTW. If I want to change this behavior, should I edit Controller.php and ViyagerController.php?

You need to extend Controller.php and maybe VoyagerMediaController.php.

Labels: feature
Close (solution provided)


Add a failing test for detection of lambdas returning by reference

hmm, thinking about it, the bug should be fixed in 1.4 (but the test should go in a different location)

Btw, the case of reference-returning functions should probably be checked for all places handling functions

@stof, could you take a look on #965 ? I have added some test cases for fixers too and a fix for Tokens::isLambda (1.4, so no TokensAnalyzer yet)

Fixed in #965, thank you @stof !

great, thanks


making the over all UI look more minimalistic and calm

Hey @gauravsingh1281, I hope you're doing good,
So here's the issue that I found and would like to contribute.
As soon we enter into the website it looks fundamental, so I want to re-design and make it more user-friendly and minimalistic so that the users can spend more time on the website looking for a perfect option.
Therefore, I request you to assign me with this project of yours.

Hi @gauravsingh1281, I have designed a clean look of the overall website will be in testing phase soon.


Vmail down

Login errors, and when you can log in, nothing is working. Just database errors indicating server access fails.  This has been going on for the past few days now. Is anyone going to look at fixing this? Hard to consider this email provider for anything serious with the lack of support.

When you can log in, any time you try to read an email you get
Connection to storage server failed.
Server Error: Could not connect to ssl://vmail.me:993: php_network_getaddresses: getaddrinfo failed: No address associated with hostname

Are you still experiencing that issue ?

Seems fixed for now
On Sun, Mar 12, 2017 at 1:17 PM, David Routhieau<EMAIL_ADDRESS>wrote:

Are you still experiencing that issue ?
—
You are receiving this because you modified the open/close state.
Reply to this email directly, view it on GitHub
https://github.com/root-io/vmail/issues/77#issuecomment-285959119, or mute
the thread
https://github.com/notifications/unsubscribe-auth/AZI--m4wjgLZb8vkdNUmJFUKeRVG7qUwks5rlCilgaJpZM4MajFA
.

Looks like the system is down again, unable to log in.
On Sun, Mar 12, 2017 at 8:34 PM, g tester<EMAIL_ADDRESS>wrote:

Seems fixed for now
On Sun, Mar 12, 2017 at 1:17 PM, David Routhieau<EMAIL_ADDRESS>
wrote:

Are you still experiencing that issue ?
—
You are receiving this because you modified the open/close state.
Reply to this email directly, view it on GitHub
https://github.com/root-io/vmail/issues/77#issuecomment-285959119, or mute
the thread
https://github.com/notifications/unsubscribe-auth/AZI--m4wjgLZb8vkdNUmJFUKeRVG7qUwks5rlCilgaJpZM4MajFA
.

Are you aware that vmail isn't working again? You can't log in anymore.
On Sun, Mar 12, 2017 at 1:17 PM, David Routhieau<EMAIL_ADDRESS>wrote:

Are you still experiencing that issue ?
—
You are receiving this because you modified the open/close state.
Reply to this email directly, view it on GitHub
https://github.com/root-io/vmail/issues/77#issuecomment-285959119, or mute
the thread
https://github.com/notifications/unsubscribe-auth/AZI--m4wjgLZb8vkdNUmJFUKeRVG7qUwks5rlCilgaJpZM4MajFA
.

Still unable to log in this morning. Just discards my user name and
password and goes to the roundcube login screen, but I can't log in from
that one either.  From the roundcube login screen, it tries loading for a
long time, then says "Connection to storage server failed" momentarily.
On Tue, Apr 25, 2017 at 5:30 PM, g tester<EMAIL_ADDRESS>wrote:

Are you aware that vmail isn't working again? You can't log in anymore.
On Sun, Mar 12, 2017 at 1:17 PM, David Routhieau<EMAIL_ADDRESS>
wrote:

Are you still experiencing that issue ?
—
You are receiving this because you modified the open/close state.
Reply to this email directly, view it on GitHub
https://github.com/root-io/vmail/issues/77#issuecomment-285959119, or mute
the thread
https://github.com/notifications/unsubscribe-auth/AZI--m4wjgLZb8vkdNUmJFUKeRVG7qUwks5rlCilgaJpZM4MajFA
.

Looks like vmail.me is down again.
On Wed, Apr 26, 2017 at 6:27 PM, David Routhieau<EMAIL_ADDRESS>wrote:

Closed #77 https://github.com/root-io/vmail/issues/77.
—
You are receiving this because you modified the open/close state.
Reply to this email directly, view it on GitHub
https://github.com/root-io/vmail/issues/77#event-1059490916, or mute
the thread
https://github.com/notifications/unsubscribe-auth/AZI--vzDsNmVhXIUZDDNBtiTdP_e7r3Xks5rz8TmgaJpZM4MajFA
.

Vmail is down again.
On Wed, Apr 26, 2017 at 6:27 PM, David Routhieau<EMAIL_ADDRESS>wrote:

Closed #77 https://github.com/root-io/vmail/issues/77.
—
You are receiving this because you modified the open/close state.
Reply to this email directly, view it on GitHub
https://github.com/root-io/vmail/issues/77#event-1059490916, or mute
the thread
https://github.com/notifications/unsubscribe-auth/AZI--vzDsNmVhXIUZDDNBtiTdP_e7r3Xks5rz8TmgaJpZM4MajFA
.

Vmail is down. Getting 504 Gateway timeout.
On Wed, Apr 26, 2017 at 6:27 PM, David Routhieau<EMAIL_ADDRESS>wrote:

Closed #77 https://github.com/root-io/vmail/issues/77.
—
You are receiving this because you modified the open/close state.
Reply to this email directly, view it on GitHub
https://github.com/root-io/vmail/issues/77#event-1059490916, or mute
the thread
https://github.com/notifications/unsubscribe-auth/AZI--vzDsNmVhXIUZDDNBtiTdP_e7r3Xks5rz8TmgaJpZM4MajFA
.

Can't login today, nothing happens when you click on the Login button.
On Sun, May 7, 2017 at 10:42 AM, g tester<EMAIL_ADDRESS>wrote:

Vmail is down. Getting 504 Gateway timeout.
On Wed, Apr 26, 2017 at 6:27 PM, David Routhieau<EMAIL_ADDRESS>
wrote:

Closed #77 https://github.com/root-io/vmail/issues/77.
—
You are receiving this because you modified the open/close state.
Reply to this email directly, view it on GitHub
https://github.com/root-io/vmail/issues/77#event-1059490916, or mute
the thread
https://github.com/notifications/unsubscribe-auth/AZI--vzDsNmVhXIUZDDNBtiTdP_e7r3Xks5rz8TmgaJpZM4MajFA
.

Lots of vmail problems today with logging in, reading and sending messages,
database errors, etc.


Australian Cyber Security Centre (Exploits and adversaries)

{
"name": "Australian Cyber Security Centre",
"type": "url",
"url": "https://www.cyber.gov.au/"
}

Added, thanks!


Correct encoding of the Compute signature - Update APDU

This question concerns the encoding of the Compute signature – Update APDU, precisely the length field of the tag 9Bh (Table <IP_ADDRESS>)
In https://github.com/ThalesGroup/iot-safe-middleware/blob/master/iotsafelib/common/src/ROT.cpp#L404 I can see that the length of the data to sign is passed in a variable length encoding.
In other implementations (https://github.com/Orange-OpenSource/IoT-SAFE-APDU-library/blob/master/src/iot_safe_internal.c#L610) this is implemented using a fixed width field.
The IoT Security Applet Interface Description doesn't seem to be clear, if a variable length encoding according to ASN.1 DER (I don't see this mentioned anywhere in the specification) is needed, or if the length is always encoded in 3 bytes (to allow for the maximum specified length of 0xFFFFFF). What is the correct way to encode this?

Note: I have asked the same question here too: https://github.com/Orange-OpenSource/IoT-SAFE-APDU-library/issues/1

Note: I have asked the same question here too: https://github.com/Orange-OpenSource/IoT-SAFE-APDU-library/issues/1

Yes the specification is not yet very clear on this. But indeed it is more future proof to have it on fix 3-bytes length.


Ensure parsing has reached EOF / end of string?

Hello,
This is more of a general question than an issue. I'm trying to ensure that my parser is parsing the whole string, and not only making a partial match. My attempt at this is to use the "EOF" token, which is defined in some examples, and then require this at the root production.
public enum ExpressionToken
    {
           ... other lexemes

        EOF=0
    }

[Production("expression : term PLUS expression EOF [d]")]
[Production("expression : term MINUS expression EOF [d]")]
public int Expression(int left, Token<ExpressionToken> operatorToken, int right)
{
     var result = 0;

     switch (operatorToken.TokenID)
     {
     case ExpressionToken.PLUS:
     {
           result = left + right;
           break;
     }
     case ExpressionToken.MINUS:
     {
           result = left - right;
           break;
     }
     }

    return result;
     }

This works, and now only partial strings are rejected with mostly good error messages. However I wonder if this is the correct approach, or if you have some other ideas/suggestions, or if this is even recommended.
I attach a project where I did some testing, with the expressionParser provided in the samples.
As an example, you get the following error messages using these strings:
"1 + 1 + 4awefawef" => unexpected "IDENTIFIER [awefawef] @line 1, column 10 on channel 0" (IDENTIFIER). Expecting DIVIDE, PLUS, TIMES, EOF, MINUS, (good)
"1 + 1 +" => "unexpected end of stream. Expecting <>." (maybe not so good?)
[Sandbox.zip](https://github.com/b3b00/csly/files/11096953/Sandbox.zip

Hello @cadmaticpgustafsson, I 'm not sure using the virtual EOF token is a good way to ensure that the whole input string matches the grammar.
In fact the parser should not succeed at all as your examples are not valid program, the y do not make sense in the context of an expression.
removing the EOF token from the production rule should be enough to produce an error :

"1 + 1 + 4awefawef" => unexpected "IDENTIFIER [awefawef] line 1, column 10 on channel 0" (IDENTIFIER). Expecting DIVIDE, PLUS, TIMES,  MINUS,
"1 + 1 +" => "unexpected end of stream. Expecting IDENTIFIER,  LAPREN, INT."  (something like that, not the real message)

So this is a bug with CSLY that I need to investigate. Thanks for providing a test case, it will sur help solve it.
I 'm not sure to have much time this days to solve it quickly but will do my best.


Examples of Frame Counting

#93
May add more later seems to cover the issues that where said about.

Lack of content :)


Better nameing

allows all name properties to be used (alt_name_* and name_* tags)

this'll probably slow down indexing since it no longer restricts what properties are copied over, and it has to loop over all properties. But it helps us catch many more naming options


Revert "[ui] Update dependencies"

Reverts kubernetes-helm/monocular#303
Reverting due to being unable to get this running on clean clones of the project:
dc up ui
Recreating monocular_ui_1 ...
Recreating monocular_ui_1 ... done
Attaching to monocular_ui_1
ui_1   | 0mWelcome to the Bitnami angular container
ui_1   | Subscribe to project updates by watching https://github.com/bitnami/bitnami-docker-angular
ui_1   | Submit issues and feature requests at https://github.com/bitnami/bitnami-docker-angular/issues
ui_1   | Send us your feedback at<EMAIL_ADDRESS>ui_1   |
ui_1   | Copying node_modules directory
ui_1   | Installing/Updating Angular dependencies (npm)
added 151 packages, removed 264 packages, updated 57 packages and moved 23 packages in 253.092s
ui_1   | Dependencies updated
ui_1   | Initialization finished
ui_1   | Cannot find module 'loader-runner'
ui_1   | Error: Cannot find module 'loader-runner'
ui_1   |     at Function.Module._resolveFilename (module.js:485:15)
ui_1   |     at Function.Module._load (module.js:437:25)
ui_1   |     at Module.require (module.js:513:17)
ui_1   |     at require (internal/module.js:11:18)
ui_1   |     at Object.<anonymous> (/app/node_modules/@angular/cli/node_modules/webpack/lib/NormalModule.js:25:20)
ui_1   |     at Module._compile (module.js:569:30)
ui_1   |     at Object.Module._extensions..js (module.js:580:10)
ui_1   |     at Module.load (module.js:503:32)
ui_1   |     at tryModuleLoad (module.js:466:12)
ui_1   |     at Function.Module._load (module.js:458:3)

Codecov Report

Merging #311 into master will decrease coverage by 1.46%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master     #311      +/-   ##
==========================================
- Coverage   90.42%   88.96%   -1.47%
==========================================
  Files          18       15       -3
  Lines         971      616     -355
==========================================
- Hits          878      548     -330
+ Misses         62       45      -17
+ Partials       31       23       -8

Impacted Files
Coverage Δ

src/api/data/cache/cache.go
76.92% <0%> (-9.26%)
:arrow_down:

src/api/config/cors/cors.go
100% <0%> (ø)
:arrow_up:

src/api/handlers/handlers.go

src/api/config/config.go

src/api/data/helpers/helpers.go

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 4a42192...b72d2f6. Read the comment docs.


Stego Public keys

We don't want to rely solely on the grd.me servers for publicizing keys, so I propose we stego ppl's public keys in profile pictures on secure "social media" sites.  The first two I would propose are Twitter and GitHub (b/c I believe they allow png's and therefore lossless compression).
Steps:

[ ] Download a profile picture
[ ] Stego public key in picture
[ ] Upload new pic (this may require them giving the browser plugin necessary credentials)
[ ] Be able to quickly pull key out of picture/detect public key if they visit Twitter/GitHub
[ ] Allow users to search by Twitter/GitHub handle (we might need to store those handles on grd.me servers, but it would be nice to have a decentralized fallback)

Sounds great! Let me look into several other services.

if we implement the server model described in https://github.com/winhowes/grd.me/issues/30, then we can move from stegoing the actual keys, to stegoing the nonce-key-id-thingy

I'm actually still inclined to stego the actual keys for a few reasons:

DOS attacks on our servers, would render this useless (granted if the lookup is done from grd me extension -> grd me server -> social media account our servers are still the weak link, but if our servers aren't in the loop, this mitigates that)
It functions as a federated key server which means users don't have to rely on our servers (granted it's only for availability) for anything but symmetric key sharing (though this could potentially also be done through other channels)
And this is similar to the above, but it encourages decentralization. The nonce approach still focuses on our servers. In an ideal world, we wouldn't have servers and everything would still work seamlessly and securely.

I like the thinking about DOS, realistic issue; good to solve it
always like me some federation, and yeah I imagine we could generate symmetric key-share message packets so that you can do this over a chat session. could be useful to allow for public key-sharing over a similar channel for advanced users; twitter post with key.
I think it would be much easier to embed a nonce than a key, so it might be good to start with the nonce and move to the key later, again for full decentralization, because I agree if you can have DOS issues you will.

I think a nonce might actually be harder (I already have some hackathon code which does this for a public key in twitter, so I know it's possible. Regarding what you said about key-sharing: totally agrree

alright, if you can dump the keys into the pics that is likely better; more backend means more places for things to break

This issue was moved to GrdMe/GrdMe#17

This issue was moved to GrdMe/GrdMe#17


IRGen: Hide type metadata records for noncopyable types from discovery by existing runtimes.

We'd still like to try to be forwardly compatible with future runtimes that do properly handle noncopyable types, so emit them in a separate section from copyable type records for now. This should prevent the current noncopyable-unaware _typeByName from letting someone get a hold of a noncopyable type's metatype as a (copyable) Any.Type and then trying to use it to copy uncopyable values.

@swift-ci Please test

@swift-ci Please test macOS


Transitions during instance initialisation.

Currently, transitions are only available when using v-repeat or v-if. It would be very useful to make transitions available for components without these directives, and (most importantly) for a root Vue instance.
Use case examples:

A lightbox or a popup. Its whole content should fade in on creation in most cases.
Toolbar panels (visual-studio like) may slide from outside of the window.

Isn't that the use case for v-if / v-show + transition? You want the state of these components to be state-driven, not managed imperatively.

It's like v-if / v-show except that it's repeating over and over again the same code:
<template>

bla-bla-bla

</template>

It would be much more handy to write something like this at the parent template:
<template>
<my-component transition="some-transition"></my-component>
</template>

The v-if/v-show is meant to be used from the parent component though.
 So you should have in your app template something like this:
<sidebar v-show="isSidebarOpen" v-transition="some-transition"></sidebar>

And if the component also needs to be able to control its own show/hide state, you pass that parent state into the component as a two-way prop:
<sidebar show="{{@isSidebarOpen}}" v-transition="some-transition"></sidebar>

Then inside sidebar you can close itself by setting this.show = false. But in either case, I don't see the need for initialization transitions.

Closing (inactivity)


feat: test with non-helm deployment

What this PR does / why we need it:
Creates a deployment with manifest_staging/deploy/eraser.yaml to test collect-scan-erase pipeline.
Which issue(s) this PR fixes (optional, using fixes #<issue number>(, fixes #<issue_number>, ...) format, will close the issue(s) when the PR gets merged):
Fixes #342
Special notes for your reviewer:

@ashnamehrotra is this a new test?

@ashnamehrotra is this a new test? (scenario we haven't covered before)

Its the same as the collector pipeline test checking if alpine is removed

if it's a duplicate test, would it make sense to replace that test with this so we don't have a duplicate? we can add to description that this is non-helm too

Codecov Report

Merging #371 (e0a8676) into main (5160b3b) will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##             main     #371   +/-   ##
=======================================
  Coverage   22.27%   22.27%
=======================================
  Files          10       10
  Lines         597      597
=======================================
  Hits          133      133
  Misses        452      452
  Partials       12       12

Flag
Coverage Δ

unittests
22.27% <ø> (ø)

Flags with carried forward coverage won't be shown. Click here to find out more.
Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.


catch TypeError when passing dictionary of form {'stringValue': 'timestamp'}

Hi team,
The recent update fdaf93434e3595331fe4b66608e37a48e02d68d8 causes a TypeError when used with sqlalchemy-aurora-data-api.
The issue arises on with the line scalar_value = col_desc.type_code.fromisoformat(value) as when I run the driver the value of value here is a dict of format:
{'stringValue': '2020-10-02 14:29:46.206625'}.
This PR catches the TypeError and ensures that the string part of the above dict is passed in.
Cheers.

Hi, thanks for reporting. Yesterday, I pushed a bug fix to the functionality in the diff that you linked (v0.2.4). Can you please confirm that you see the issue in the latest version from yesterday (v0.2.4)?
The issue that you're citing is a bit confusing because the string value should have been unpacked on a preceding line (https://github.com/chanzuckerberg/aurora-data-api/pull/19/files#diff-fc5c5e4c065878e1216f22df192a3835R281). I'm not sure why it would not be unpacked and necessitate the change that you added. It would really help if you could provide a reproduction.

Never mind, I see where the problem is. Fix coming up.

Fix released in v0.2.5, please test.
I'm going to close this PR since the TypeError should never be raised here (it's the result of a bug). Thanks again for reporting.

Fix released in v0.2.5, please test.
I'm going to close this PR since the TypeError should never be raised here (it's the result of a bug). Thanks again for reporting.

np. Yep, that worked. Thanks for the extremely quick turn around 👍


docker: journald logging driver does not support reading

The Docker journald code requires for reading that Docker be built with cgo enabled, and not statically. This is theoretically possible but I need to do some work within Buildroot to fix Docker this way.
Might need to temporarily undo the journald logging until this is fixed.

Fixed


nix-shell fails with error: attribute 'fetchTree' missing, at /home/yasuke/plutus-apps-again/shell.nix:18:11

Summary
When running nix-shell to use plutus-apps, an error occurs preventing us from getting into a shell with all the required software and libraries.
Steps to reproduce the behavior

Clone plutus-apps
go to root directory
run nix-shell

Actual Result
error: attribute 'fetchTree' missing, at /home/yasuke/plutus-apps-again/shell.nix:18:11
Expected Result
I would expect to be dropped into a nix-shell and able to use/run the various libraries, and software.
Describe the approach you would take to fix this
No response
System info
OS: Nix-OS
plutus-apps: 343a6e60adff4ca97df9f5a9052ce27745f6c480

What's your nix --version?
It seems that fetchTree is a part of nix flakes that was introduced in Nix 2.4.

Thanks, after updating my version (was 2.3.xx) and enabling flakes, nix-shell works no problem.


Items sometimes not loading in chests

Plugin version: '4.18.24 (from Jenkins)'
Server type: 'Paper (Build 225).'
Server version: '1.14.4'
Describe the bug
After updating to the version you wanted me to test, everything worked exactly as it should (and I can also confirm that using a death chest plugin does not cause any duplication with soulbound items), but for some reason my players started noticing that items in chests would randomly decide to not load until an item is added or removed from the chest. Sometimes only a few items will not show up while other times the chest will appear to be empty. This is very strange behavior and stopped happening when I reverted the plugin back to 4.18.23.
It appears to be a conflict with another plugin, because this does not seem to happen when this plugin (4.18.24) is installed on it's own. I am currently testing on my test server to figure out exactly which plugins are causing this to happen.
Expected behavior
All items should appear in chests,
To Reproduce
Open chests full of items randomly until something does not load.
(I will comment to let you know which plugins are causing this, still currently in the process of testing)
Edit: Happens with ProtocolLib installed
Screenshots
(Will add screenshots when done testing)

Update:
The issue appears to occur with ProtocolLib installed.
No errors appear in console.
To reproduce:
Install AdvancedEnchantments v4.18.24 and ProtocolLib
Fill a few chests with items, then open  and close them randomly until something doesn't load.
I have attached a video below that shows the problem:
https://1drv.ms/v/s!AknzfCjeCluIoe0fPA2kEpA8GtatKA?e=Qno5Bh

Interesting. Perhaps give the latest master a try and enable debug output in the config (reload the plugin with the /ae reload command) - see if it's trying to place a fake block (unlikely) or is instead somehow marking the chest as an enchanting table (still unlikely, but more likely)

Unfortunately while using the latest master build and with debugging enabled, nothing appeared in console whenever the bug happened. Here is a video showing the console while testing in case there is anything else there that could help
https://1drv.ms/v/s!AknzfCjeCluIoe0pxoBBw3R4cU7OFg?e=URSgZq

Tested, verified, fixed, verified fix.
Thanks again for the bug report!


Please add angularfire2 5

yes please

YES

any news / plan on this?

Closing in favor of issue #89


[BUG] CMS V4: Copying and pasting an unpublished page renders the page tree unusable

Copying and pasting an unpublished page renders the page tree and thereby the whole cms unusable. ./manage.py cms fix-tree will not repair this tree.
Description

Steps to reproduce
Steps:

Start from empty project with ./manage.py migrate, ./manage.py createsuperuser, and ./manage.py runserver
Go to localhost:8000/admin and log in.
Create new page content (e.g., test)
Copy the page from the burger menu
Paste the page either from the global burger menu or from the page’s burger menu.

Expected behaviour
The copied page should appear in the page tree.
Actual behaviour
Page tree breaks with message “Error: Could not load node”. Switching languages does not help. The server reports an server error when serving /admin/cms/pagecontent/get-tree/.
The cms_page table contains two entries. The cms_pagecontent table contains one entry after the exception has been raised.
Screenshots

Additional information (CMS/Python/Django versions)

Django 3.2.12
django-cms@develop-4
<EMAIL_ADDRESS>djangocms-versioning@master

Do you want to help fix this issue?

[ ] Yes, I want to help fix this issue and I will join #workgroup-pr-review on Slack to confirm with the community that a PR is welcome.
[x] No, I only want to report the issue.

@marksweb @Aiky30 I have been able to track down why this bug appears. It appears that the page tree cannot render EmptyPageContent. If - for what reason - there is no PageContent object this error prevents the page tree from being rendered.
Remedies:

Make the page tree not raise a server error if it contains an EmptyPageContent (this is an easy fix)
Ensure that copying a page also copies the PageContent objects. The Page models copies self.pagecontent_set.all() which evaluates to an empty query set if djangocms-versioning is installed. Does versioning change the way pagecontent_set needs to be evaluated? (I would assume, the draft page contents should be copied.)
When switching languages using the language drop down menu leads to EmptyPageContent in languages where the PageContent was not created. Here I am not sure what is supposed to happen: How are users meant to create PageContent for missing languages?

Solved by #7446


Programmatically trigger the display of swipe actions

Hey,
Im looking for a manual way to trigger showing the editing options. In particular, I would like to show editing options when didSelectRowAtIndex is called. I see there is support for hideSwipe(animated:), but I don't see an option for any showSwipe(animated:). Is it possible? Thanks
Andrew

Hey @Awalz - Yep, that should be pretty straightforward to add. I'll try to take a look at it in the next few days.

Thanks for looking into this so quickly!.
Is version 1.5.0 live yet?
Andrew

Hi @Awalz - No problem! 😀
I have a few more things lined up for the next release which I'm planning to ship soon. In the meantime, if you're using CocoaPods, see the Installation instructions in the README to pull directly from the develop branch.


deepObject parameter style produces invalid URIs

According to the RFC,

[ IPv6 host address ] is the only place where square bracket characters are allowed in the URI syntax.

So requiring OpenAPI clients to serialize parameters using square brackets means asking them to violate RFC 3986.
The same is true for the allowReserved field. The only reserved characters that need to be encoded for query strings at all are #, [, and ]. Allowing these to pass through unencoded produces an invalid query string.

This article might be relevant.  The TL;DR:

So because square brackets are only allowed in the "host" subcomponent, they "should" be percent encoded in other components and subcomponents, and in this case in the "query" component, unless RFC 3986 explicitly allows unencoded square brackets to represent data in the query component, which is does not.
However, if a "URI producing application" fails to do what it "should" do, by leaving square brackets unencoded in the query, then readers of the URI are not to reject the URI outright. Instead, the square brackets are to be considered as belonging to the data of the query component, since they are not used as delimiters in that component.

I'm not an authority on this subject (and maybe this article isn't either), but my interpretation of the article is that the square brackets (from gen-delims) should be percent-encoded, but do not have to be because they have no meaning in the query.  I believe ? and # are query delimiters, and that it might mean that these can all be abused in the same way: : / [ ] @.

so... does that mean that to use style=deepObject (and pipeDelimited too) we have to use allowReserved=true?
Because all the examples in the spec (the table at https://spec.openapis.org/oas/v3.1.0#style-examples) apparently are showing the query portion of the URI, fully serialized and escaped. and these styles have reserved characters in them.  I think that's important enough that it should be mentioned explicitly in the spec.
Alternatively, the examples need to be modified to properly escape these characters, just as spaceEncoded uses %20 instead of space for its delimiter.

TL;DR: if you want your URL to be parsed correctly by a strictly RFC3986-compliant parser
OK, I delved into this more and have come up with what I hope is the correct interpretation of the following passage, the last two paragraphs of RFC 3986 §2.2 "Reserved Characters":

A subset of the reserved characters (gen-delims) is used as
delimiters of the generic URI components described in Section 3.  A
component's ABNF syntax rule will not use the reserved or gen-delims
rule names directly; instead, each syntax rule lists the characters
allowed within that component (i.e., not delimiting it), and any of
those characters that are also in the reserved set are "reserved" for
use as subcomponent delimiters within the component.  Only the most
common subcomponents are defined by this specification; other
subcomponents may be defined by a URI scheme's specification, or by
the implementation-specific syntax of a URI's dereferencing
algorithm, provided that such subcomponents are delimited by
characters in the reserved set allowed within that component.
URI producing applications should percent-encode data octets that
correspond to characters in the reserved set unless these characters
are specifically allowed by the URI scheme to represent data in that
component.  If a reserved character is found in a URI component and
no delimiting role is known for that character, then it must be
interpreted as representing the data octet corresponding to that
character's encoding in US-ASCII.

This pulls in more context than the blog post cited above, which I think makes things more clear:

Both RFC3986 and other specifications can define delimiter roles for allowed reserved characters in a given component.
In that context, the "no delimiting role is known for that character" clearly refers to allowed reserved characters, which may or may not be functioning as delimitiers

This is why application/x-www-form-urlencoded can define delimiting semantics for = and &, and character escape semantics for +:  All three are allowed in query strings, and none have been assigned any semantics in any component by RFC 3986.
On the other hand, the OpenAPI Specification and various web framworks cannot do the same with [ and ], as those two characters, along with #, are the only reserved characters not allowed in query strings.
So what that last paragraph is saying is is along the lines of:  If you don't have reason to think that a query string is in application/x-www-form-urlencoded format (see #1502), then you MUST treat =, &, and + as their literal character values.  It is not saying that you have to treat illegal characters as their literal values.
That said, it seems like many systems stuff unencoded [ and ] characters in query strings, although in some cases people may just think that because the percent-encoding/decoding is happening out-of-sight.  Which is a bit bizarre, because prior to RFC 3986, those characters were in the unsafe set, rather than the reserved set, and always needed to be encoded.  This is a pretty good demonstration of why Postel's Law has been falling out of favor- you end up with all of these weird corners where things that violate specs are expected to keep working.
So the upshot is:  it might work, and if you're absolutely certain you know all of the parsers involved will handle it, then you can get away with unencoded [ and ].  But we're talking about APIs and not intended-for-human-readability things, so just percent-encode and be safe (and we should absolutely do that in our examples).  Because at some point, someone will run that URI through a validating parser that is actually implemented correctly (they seem to be shockingly rare but do exist), and it will cause an error.

The final wrinkle is that people using deepObject (or whatever PHP does, which apparently involves these illegal characters, which seems super on-brand to me for PHP but I may be just feeling cranky after a solid day of researching specification histories to figure this out) might want to leave the delimiter [ and ] un-encoded to avoid conflicts with those characters in the actual data.  Which is, of course, the point of using reserved characters as delimiters.  But it's still against the spec.  I just would not recommend deepObject at all, TBH, and would rather offer more flexibility through supporting #1502 in the next minor release than try to make deepObject usable with strict URI parsers.
But we should clarify it in the patch releases anyway, so I'll throw it on the (increasingly enormous) pile.

PR merged for 3.0.4 and ported to 3.1.1 via PR #3921!
This is addressed by the new Appendix E.


Develop

The documentation of Hugo is garbage, and its confusing configuration files are even worse. The inconsistent capitalization in the configs is the cherry on top of this mess. Its backward compatibility is a total disaster, adding to the confusion. If it weren’t for the popularity of Golang, Hugo would be nothing.


Suggestion: Show 10% Beneficiaries

Show information when creating a post, that 10% Beneficiaries will be set for @esteemapp.
I think it is a "bad-karma" if this is done hidden, user confidence is important and should not be lost.

It’s written publicly in eSteem FAQ, nothing is hidden. It’s necessary for users to read FAQ or ToS before using any product.

It’s written publicly in eSteem FAQ, nothing is hidden. It’s necessary for users to read FAQ or ToS before using any product.

I disagree. That would mean, who doesn't read the FAQ is his own fault? I find that position disappointing.
Also, what FAQ do you mean? There is no link on https://esteem.app, no link on the download page, no reference in the playstore. I only found these here  and 5% is written there.
I hope there will be another answer with more understanding.

Does Dtube, Oracle-D, and SteemPress show you that on their platforms creating a post?

I'm not using Dtube and SteemPress.
I have no problem supporting eSteem with 10%. But i don't like it, when 10% Beneficiaries are set without my knowledge. Meanwhile I found the FAQ again and the explanation, so I am a little reassured. Unfortunately I didn't notice it when I read it for the first time. So, thanks for the hint.
But, not everyone reads the FAQ - my suggestion is for a better transparency. I think this is important.

We have decreased beneficiary to 3% from 10% and in future we might even remove it. So follow @esteemapp for up to date information, we keep our users informed about every changes, so you won't miss it.


Gh 515 aggregator schema validation

Codecov Report

Merging #968 into develop will increase coverage by 7.36%.
The diff coverage is n/a.

@@              Coverage Diff              @@
##             develop     #968      +/-   ##
=============================================
+ Coverage      63.61%   70.98%   +7.36%
=============================================
  Files            482       92     -390
  Lines          13912     3267   -10645
  Branches        1573      367    -1206
=============================================
- Hits            8850     2319    -6531
+ Misses          4425      792    -3633
+ Partials         637      156     -481

Impacted Files
Coverage Δ
Complexity Δ

...gaffer/rest/service/GraphConfigurationService.java

...gaffer/operation/impl/export/set/GetSetExport.java

.../converter/schema/SchemaToStructTypeConverter.java

.../gchq/gaffer/jsonserialisation/JSONSerialiser.java

...java/uk/gov/gchq/gaffer/data/element/LazyEdge.java

...n/java/uk/gov/gchq/gaffer/cache/ICacheService.java

...er/store/operation/handler/compare/MaxHandler.java

.../binaryoperator/ReservoirLongsUnionAggregator.java

...re/operation/handler/export/GetExportsHandler.java

...store/operation/handler/GetAllElementsHandler.java

... and 381 more

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 99c0e2d...d83c932. Read the comment docs.


More Meta Data Types

Im planning to add Vector Meta Data Type just leaving this TO-DO here, Vector2, Vector3.

Added on update version 0.1.9


Elasticsearch lack environment variables

Issue description
The elasticsearch returns: "You must set the ES_HOME var"
Steps to reproduce
> nix-shell -p elasticsearch
[nix-shell:~] elasticsearch
You must set the ES_HOME

or
> nix-env -i elasticsearch-1.7.2
> elasticsearch
You must set the ES_HOME

Technical details

System: Mac OS X El Capitan 10.11.4 (Darwin Kernel Version 15.4.0)
Nix version: nix-env (Nix) 1.11.2
Nixpkgs version: 16.09pre80183.551296a

I'm not sure how to fix this, because it is a problem of just installing the Elasticsearch executables but not setting up the Elasticsearch service. ES_HOME needs to point to a data directory. Since Nix only manages /nix/store and the module system used on NixOS is what configures the services and /var directories, I'm not sure how to resolve your problem.
I believe the responsibility sits in your default.nix or shell.nix or whatever to set ES_HOME to where you want it.
Does that make sense? Am I wrong about the Nix / NixOS split?

I believe you are completely right. Sorry I'm just a complete n00b and I was just thinking about using nix as a cooler brew for Mac. I managed to make elasticsearch work correctly using the right default.nix.
Thanks, and sorry for the lost time.

No worries! I think this is a common source of confusion, but I'm not particularly sure how to fix it.

I believe you are completely right. Sorry I'm just a complete n00b and I was just thinking about using nix as a cooler brew for Mac. I managed to make elasticsearch work correctly using the right default.nix.
Thanks, and sorry for the lost time.

Can you share how you make that work? I am trying to install elasticsearch v6.x on my mac with nix but it does not work. This is the problem I am having: https://github.com/NixOS/nixpkgs/issues/56536


Feature/vs2961/backend-auth

Tracking Info
Resolves #
Make sure your branch name conforms to: <feature|staging|bugfix|...>/<username>/<3-4 word description separated by dashes>. Otherwise, please rename your branch and create a new PR.
Changes
What changes did you make?
Created auth pages, with files to make calls to backend to register users. Sign in with google button needs to be implemented, and login page css fledged out.
Testing
How did you confirm your changes worked?
Tested signup page css by resizing window, made sure users were registered in firebase console and mongo database.
Confirmation of Change
Upload a screenshot, if possible. Otherwise, please provide instructions on how to see the change.

Changed error handling with your suggestions, should be better now!


CUDA_ERROR_ILLEGAL_ADDRESS

Click to expand!
Issue Type
Bug
Have you reproduced the bug with TF nightly?
No
Source
binary
Tensorflow Version
2.11
Custom Code
No
OS Platform and Distribution
Official docker image via apptainer
Mobile device
No response
Python version
3.8
Bazel version
No response
GCC/Compiler version
No response
CUDA/cuDNN version
11.2/8.1
GPU model and memory
Tesla V100-SXM2-32GB
Current Behaviour?
Using the Official docker image, the provided code results in a CUDA_ERROR_ILLEGAL_ADDRESS. Note, that while the error is fully consistent (happens every time at the first epoch) it is highly sensitive. If a different seed or model-size is used, the error will not reproduce.
I have tried enabling memory growth as suggested elsewhere. However, this only delays the issue to epoch 18.
The error does not reproduce on Google Colab or when using the nightly docker image. However, due to the sensitivity of the issue, it is unclear what exactly this means. The Google Colab issue could be due to different GPU. On my own environment it's a Tesla V100-SXM2-32GB, not a T4.
Standalone code to reproduce the issue
This uses transformers == 4.26.0, and a synthetic dataset file (based on QQP) that is automatically downloaded. Code is available here: https://gist.github.com/AndreasMadsen/2bf669a3cd4c4a8ba964561b9e72279e
Note, I did make an attempt at reproducing it using Colab: https://colab.research.google.com/drive/1zVbNNfz1lZ6xgyoZ7dKWnKzj6poM5XWC?usp=sharing
However, the error does not reproduce on Colab.
Relevant log output
2023-02-06 14:07:37.519351: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F AVX512_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-06 14:07:37.759155: I tensorflow/core/util/port.cc:104] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2023-02-06 14:07:38.624178: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2023-02-06 14:07:38.624677: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2023-02-06 14:07:38.624725: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
Configuration:
  persistent_dir = /scratch/anmadc/tf_memory_issue
  seed = 0
  batch_size = 16
  model = roberta-base
  jit_compile = True
  precision = mixed_float16

2023-02-06 14:07:40.255950: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F AVX512_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-02-06 14:07:41.029530: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1613] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 30971 MB memory:  -> device: 0, name: Tesla V100-SXM2-32GB, pci bus id: 0000:af:00.0, compute capability: 7.0
All model checkpoint layers were used when initializing TFRobertaForSequenceClassification.

Some layers of TFRobertaForSequenceClassification were not initialized from the model checkpoint at roberta-base and are newly initialized: ['classifier']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
WARNING:tensorflow:From /localscratch/anmadc.58777029.0/env/lib/python3.10/site-packages/tensorflow/python/autograph/pyct/static_analysis/liveness.py:83: Analyzer.lamba_check (from tensorflow.python.autograph.pyct.static_analysis.liveness) is deprecated and will be removed after 2023-09-23.
Instructions for updating:
Lambda fuctions will be no more assumed to be used in the statement where they are used, or at least in the same block. https://github.com/tensorflow/tensorflow/issues/56089
2023-02-06 14:08:24.250220: I tensorflow/compiler/xla/service/service.cc:173] XLA service 0x2db1cb30 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2023-02-06 14:08:24.264540: I tensorflow/compiler/xla/service/service.cc:181]   StreamExecutor device (0): Tesla V100-SXM2-32GB, Compute Capability 7.0
2023-02-06 14:08:25.275879: W tensorflow/compiler/tf2xla/kernels/assert_op.cc:38] Ignoring Assert operator tf_roberta_for_sequence_classification/roberta/embeddings/assert_less/Assert/Assert
2023-02-06 14:08:25.309985: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:268] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.
2023-02-06 14:08:25.321306: W tensorflow/compiler/tf2xla/kernels/random_ops.cc:57] Warning: Using tf.random.uniform with XLA compilation will ignore seeds; consider using tf.random.stateless_uniform instead if reproducible behavior is desired. tf_roberta_for_sequence_classification/roberta/embeddings/dropout_36/dropout/random_uniform/RandomUniform
2023-02-06 14:09:41.534987: I tensorflow/compiler/xla/stream_executor/gpu/asm_compiler.cc:325] ptxas warning : Registers are spilled to local memory in function 'sort_19'
ptxas warning : Registers are spilled to local memory in function 'sort_17'

2023-02-06 14:09:41.931415: I tensorflow/compiler/jit/xla_compilation_cache.cc:477] Compiled cluster using XLA!  This line is logged at most once for the lifetime of the process.
2023-02-06 14:09:42.331286: E tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:1159] failed to enqueue async memcpy from device to host: CUDA_ERROR_ILLEGAL_ADDRESS: an illegal memory access was encountered; host dst: 0x2b36f334aeeb; GPU src: 0x2b385f628600; size: 1=0x1
2023-02-06 14:09:42.331472: I tensorflow/compiler/xla/stream_executor/stream.cc:2485] INTERNAL: Unknown error
2023-02-06 14:09:42.331557: I tensorflow/compiler/xla/stream_executor/stream.cc:2489] [stream=0x1b700120,impl=0x52a9880] INTERNAL: stream did not block host until done; was already in an error state
Traceback (most recent call last):
  File "/scratch/anmadc/workspace/economical-roar/reproduce.py", line 150, in <module>
    model.fit(dataset_train_batched, verbose=1, epochs=1)
  File "/localscratch/anmadc.58777029.0/env/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "/localscratch/anmadc.58777029.0/env/lib/python3.10/site-packages/tensorflow/python/eager/execute.py", line 52, in quick_execute
    tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.InternalError: Graph execution error:

Detected at node 'StatefulPartitionedCall' defined at (most recent call last):
    File "/scratch/anmadc/workspace/economical-roar/reproduce.py", line 150, in <module>
      model.fit(dataset_train_batched, verbose=1, epochs=1)
    File "/localscratch/anmadc.58777029.0/env/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
      return fn(*args, **kwargs)
    File "/localscratch/anmadc.58777029.0/env/lib/python3.10/site-packages/keras/engine/training.py", line 1650, in fit
      tmp_logs = self.train_function(iterator)
    File "/localscratch/anmadc.58777029.0/env/lib/python3.10/site-packages/keras/engine/training.py", line 1249, in train_function
      return step_function(self, iterator)
    File "/localscratch/anmadc.58777029.0/env/lib/python3.10/site-packages/keras/engine/training.py", line 1233, in step_function
      outputs = model.distribute_strategy.run(run_step, args=(data,))
Node: 'StatefulPartitionedCall'
Failed to retrieve branch_index value on stream 0x1b700120: stream did not block host until done; was already in an error state.
	 [[{{node StatefulPartitionedCall}}]] [Op:__inference_train_function_42578]

In this gist, I have removed the dependency on transformers and a large amount of irrelevant code: https://gist.github.com/AndreasMadsen/dc5785b5a55bf740c555b2fb5cdab1db
I have tried to reduce the code further, but this causes the bug to disappear.

@pjpratik I think you should add the comp:xla label too. As this bug only occurs when XLA is enabled.

There is no failure with the reproduction script on 2.12.0rc0. However, given how difficult this bug is to reproduce (e.g. changing just the seed of the shuffle function will make it disappear). I can't tell if this solves the issue consistently.

Hi, @AndreasMadsen
Apologize for the delay and Thank you for your detailed observations and efforts to find out root cause for this issue and We'll try it from our end and will check whether this issue is specific to V100 GPU or not and we'll update you soon here. Thank you for noticing this issue. Thank you!

@gaikwadrahul8 Thanks for looking into this. It did take me several days to make this error reproducible. So I hope it will help you. I suspect it's a rather complex integration bug, as removing pretty much any line in the latest (V3) script cause the bug to disappear.

Hi, @AndreasMadsen
Apologize for the delay and I was able to replicate the issue on Tesla V100 GPU and I was getting the exact same error message which you mentioned in your error log output above with tensorflow/tensorflow:latest-gpu docker image which is using Tensorflow==2.11, I have added screenshot for your reference below and even tested the same code on Google Colab and it's working fine as expected here is gist-file, I did not run for complete epoch because it was taking more time but code was running as expected but as you confirmed it's working fine on all other GPU's so this issue seems like specific to Tesla V100 GPU at the moment. Thank you!
When I tried the same code with tensorflow/tensorflow:2.12.0rc0-gpu and tensorflow/tensorflow:nightly-gpu  on Tesla V100 GPU it's working as expected, I have added screenshot below

Here is screenshot for code execution on Google-Colab :

Here is screenshot for code execution with tensorflow/tensorflow:2.12.0rc0-gpu docker image:

Here is screenshot for code execution with tensorflow/tensorflow:nightly-gpu docker image:

Hi @gaikwadrahul8, you didn't ask a question, so I'm not sure what you want me to respond to.
I agree with your findings. Given how sensitive the bug is in terms of reproduction, I would not trust that it is something specific to V100 TF 2.11. I hope you will be able to debug this further and get to the resolve bug.

Note, that this kind of bug has been reported quite a few times before, but I think most issues were not able to provide a reproduction script. So I hope you will find this script quite useful.
ISSUE: https://github.com/tensorflow/tensorflow/issues/50735
I remember there were more closed issues, when I was researching solutions.

Hi. @AndreasMadsen
Thank you for mentioning the similar issue, It seems like we have to dig more into this issue to find out the root cause and we'll update you soon and I was able to replicate the exact same issue with error log with tensorflow/tensorflow:latest-gpu  docker image that's the reason I did not ask any questions to you if we need any input or further details from your end certainly we will ask you. Thank you for noticing this issue, I really appreciate it your efforts and time. Thank you!

@gaikwadrahul8 Thanks for letting me know. I'm was just confused about the stat:awaiting response label.

Hi, @sachinprasadhs
Could you please look into this issue ? Thank you!

Hi @sachinprasadhs, did you manage to investigate this?

Hi @AndreasMadsen , Apologies for the delayed response, based on the issue thread so far, it is difficult to point to an area why this is happening.
But you could try below steps and see if that works.

Try reinstalling the CUDA and cuDNN dependency, in some cases it could be due to improper installation of these dependencies.
Try setting the environmental variable TF_FORCE_GPU_ALLOW_GROWTH to true

If the above steps did not work could you please run the model with the env var CUDA_LAUNCH_BLOCKING set to 1 and attach the full logs?

@sachinprasadhs Thanks for your response. Please note that I spent several days reducing this to a script that reproduces the issue. I think you can benifit tremendously from using that. Furthermore, @gaikwadrahul8 confirms that the issue could be reproduced with a V100 GPU.

Try reinstalling the CUDA and cuDNN dependency, in some cases it could be due to improper installation of these dependencies.

Let's not go down that route, since @gaikwadrahul8 was able to reproduce the issue on Google's infrastructure.

Try setting the environmental variable TF_FORCE_GPU_ALLOW_GROWTH to true.

Same issue.

TF_FORCE_GPU_ALLOW_GROWTH=true python main.py
2023-03-15 11:55:41.321502: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F AVX512_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-03-15 11:55:41.504643: I tensorflow/core/util/port.cc:104] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2023-03-15 11:55:42.479709: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2023-03-15 11:55:42.480077: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2023-03-15 11:55:42.480113: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2023-03-15 11:55:43.729040: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F AVX512_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-03-15 11:55:44.593353: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:42] Overriding orig_value setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.
2023-03-15 11:55:44.593541: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1613] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 30971 MB memory:  -> device: 0, name: Tesla V100-SXM2-32GB, pci bus id: 0000:18:00.0, compute capability: 7.0
2023-03-15 11:56:14.842711: I tensorflow/compiler/xla/service/service.cc:173] XLA service 0x20192630 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2023-03-15 11:56:14.842838: I tensorflow/compiler/xla/service/service.cc:181]   StreamExecutor device (0): Tesla V100-SXM2-32GB, Compute Capability 7.0
2023-03-15 11:56:15.808448: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:268] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.
2023-03-15 11:56:15.816882: W tensorflow/compiler/tf2xla/kernels/random_ops.cc:57] Warning: Using tf.random.uniform with XLA compilation will ignore seeds; consider using tf.random.stateless_uniform instead if reproducible behavior is desired. tf_roberta_for_sequence_classification/layer_._0/self/dropout/dropout/random_uniform/RandomUniform
2023-03-15 11:57:26.919108: I tensorflow/compiler/xla/stream_executor/gpu/asm_compiler.cc:325] ptxas warning : Registers are spilled to local memory in function 'sort_9'
ptxas warning : Registers are spilled to local memory in function 'fusion_1107'

2023-03-15 11:57:27.290497: I tensorflow/compiler/jit/xla_compilation_cache.cc:477] Compiled cluster using XLA!  This line is logged at most once for the lifetime of the process.
2023-03-15 11:57:27.774582: E tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:1159] failed to enqueue async memcpy from device to host: CUDA_ERROR_ILLEGAL_ADDRESS: an illegal memory access was encountered; host dst: 0x2b4b7e184eeb; GPU src: 0x2b4e0836e500; size: 1=0x1
2023-03-15 11:57:27.774751: I tensorflow/compiler/xla/stream_executor/stream.cc:2485] INTERNAL: Unknown error
2023-03-15 11:57:27.774869: I tensorflow/compiler/xla/stream_executor/stream.cc:2489] [stream=0x1c1751e0,impl=0x5e7c020] INTERNAL: stream did not block host until done; was already in an error state
Traceback (most recent call last):
  File "/scratch/anmadc/workspace/economical-roar/main.py", line 209, in <module>
    model.fit(dataset_train_batched, verbose=1, epochs=1)
  File "/localscratch/anmadc.62577500.0/env/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "/localscratch/anmadc.62577500.0/env/lib/python3.10/site-packages/tensorflow/python/eager/execute.py", line 52, in quick_execute
    tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.InternalError: Graph execution error:

Detected at node 'StatefulPartitionedCall' defined at (most recent call last):
    File "/scratch/anmadc/workspace/economical-roar/main.py", line 209, in <module>
      model.fit(dataset_train_batched, verbose=1, epochs=1)
    File "/localscratch/anmadc.62577500.0/env/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
      return fn(*args, **kwargs)
    File "/localscratch/anmadc.62577500.0/env/lib/python3.10/site-packages/keras/engine/training.py", line 1650, in fit
      tmp_logs = self.train_function(iterator)
    File "/localscratch/anmadc.62577500.0/env/lib/python3.10/site-packages/keras/engine/training.py", line 1249, in train_function
      return step_function(self, iterator)
    File "/localscratch/anmadc.62577500.0/env/lib/python3.10/site-packages/keras/engine/training.py", line 1233, in step_function
      outputs = model.distribute_strategy.run(run_step, args=(data,))
Node: 'StatefulPartitionedCall'
Failed to retrieve branch_index value on stream 0x1c1751e0: stream did not block host until done; was already in an error state.
	 [[{{node StatefulPartitionedCall}}]] [Op:__inference_train_function_37296]

CUDA_LAUNCH_BLOCKING=1 TF_FORCE_GPU_ALLOW_GROWTH=true python main.py
2023-03-15 11:57:59.121539: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F AVX512_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-03-15 11:57:59.307027: I tensorflow/core/util/port.cc:104] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2023-03-15 11:58:00.281216: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2023-03-15 11:58:00.281601: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2023-03-15 11:58:00.281646: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
2023-03-15 11:58:01.543891: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F AVX512_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-03-15 11:58:02.412447: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:42] Overriding orig_value setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.
2023-03-15 11:58:02.412647: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1613] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 30971 MB memory:  -> device: 0, name: Tesla V100-SXM2-32GB, pci bus id: 0000:18:00.0, compute capability: 7.0
2023-03-15 11:58:32.523032: I tensorflow/compiler/xla/service/service.cc:173] XLA service 0x1fb485b0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2023-03-15 11:58:32.523516: I tensorflow/compiler/xla/service/service.cc:181]   StreamExecutor device (0): Tesla V100-SXM2-32GB, Compute Capability 7.0
2023-03-15 11:58:33.492464: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:268] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.
2023-03-15 11:58:33.500937: W tensorflow/compiler/tf2xla/kernels/random_ops.cc:57] Warning: Using tf.random.uniform with XLA compilation will ignore seeds; consider using tf.random.stateless_uniform instead if reproducible behavior is desired. tf_roberta_for_sequence_classification/layer_._0/self/dropout/dropout/random_uniform/RandomUniform
2023-03-15 11:59:44.579959: I tensorflow/compiler/xla/stream_executor/gpu/asm_compiler.cc:325] ptxas warning : Registers are spilled to local memory in function 'sort_9'
ptxas warning : Registers are spilled to local memory in function 'fusion_1107'

2023-03-15 11:59:44.945238: I tensorflow/compiler/jit/xla_compilation_cache.cc:477] Compiled cluster using XLA!  This line is logged at most once for the lifetime of the process.
Traceback (most recent call last):
  File "/scratch/anmadc/workspace/economical-roar/main.py", line 209, in <module>
    model.fit(dataset_train_batched, verbose=1, epochs=1)
  File "/localscratch/anmadc.62577500.0/env/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 70, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "/localscratch/anmadc.62577500.0/env/lib/python3.10/site-packages/tensorflow/python/eager/execute.py", line 52, in quick_execute
    tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.InternalError: Graph execution error:

Detected at node 'StatefulPartitionedCall' defined at (most recent call last):
    File "/scratch/anmadc/workspace/economical-roar/main.py", line 209, in <module>
      model.fit(dataset_train_batched, verbose=1, epochs=1)
    File "/localscratch/anmadc.62577500.0/env/lib/python3.10/site-packages/keras/utils/traceback_utils.py", line 65, in error_handler
      return fn(*args, **kwargs)
    File "/localscratch/anmadc.62577500.0/env/lib/python3.10/site-packages/keras/engine/training.py", line 1650, in fit
      tmp_logs = self.train_function(iterator)
    File "/localscratch/anmadc.62577500.0/env/lib/python3.10/site-packages/keras/engine/training.py", line 1249, in train_function
      return step_function(self, iterator)
    File "/localscratch/anmadc.62577500.0/env/lib/python3.10/site-packages/keras/engine/training.py", line 1233, in step_function
      outputs = model.distribute_strategy.run(run_step, args=(data,))
Node: 'StatefulPartitionedCall'
Failed to launch CUDA kernel: fusion_1428 with block dimensions: 128x1x1 and grid dimensions: 1280x1x1: CUDA_ERROR_ILLEGAL_ADDRESS: an illegal memory access was encountered
	 [[{{node StatefulPartitionedCall}}]] [Op:__inference_train_function_37296]

Thank you @AndreasMadsen for the short script to reproduce and for removing the transformers dependency to keep the example simpler.
I can reproduce the issue outside docker with CUDA 11.2.0 using the pre-built TF 2.11 pip package. However, the issue disappears when I use CUDA 11.8.0 using the same pip package (the pip package is built with CUDA 11.2 but applications built for one version of CUDA also work for future minor versions of CUDA). So I'm guessing this was a bug with CUDA 11.2 that was fixed somewhere between CUDA 11.2.1 and 11.8.0. Since the TF nightly pip packages are now built with CUDA 11.8, I think this issue is fixed so I'm closing this issue.
It's possible this is a race condition in TF instead of a bug in CUDA, and that updating the CUDA version changes some timings which causes the bug not to occur. But I think this is unlikely, so unless we later see CUDA_ERROR_ILLEGAL_ADDRESS errors in other models, we should consider this issue fixed.


Traefik and ddos protection

Do you want to request a feature or report a bug?
Feature
What did you expect to see?
I used nginx with rate limit and fail2ban. When rate limit detected fail2ban blocked ip. Can you add some feature for rate limit with ban for ip for some time? traefik.frontend.rateLimit.ban=300s

Hi,
If you want to achieve rate limiting with fail2ban, we think you should probably apply it on the access logs. They can be enabled in Traefik configuration: https://docs.traefik.io/v2.0/observability/access-logs/
WDYT?

@mpl I know about log, i use it with goaccess. And i hope you will add different logs file for different domains traefik.frontend. accessLogsFile=filename.log. But about ratelimit i think you can add ban value too. (period, burst, ban better then average)

@udanpe wouldn't middleware in v2 be the place to put such logic ? I am sure a PR with such middleware would be considered.

@udanpe Are you looking for the rate-limit feature? https://docs.traefik.io/v2.0/middlewares/ratelimit/


We canot assume workload ip address are unique

Since istio is supporting accessing service with hostnetwork pods. It can build workload with hostnetwork with same ip now.  In kmesh we need to adapt to hostnetwork pods.
I haven't looked into what will happend if we kmesh do no change.  Want to hear more voices first.

After this commit https://github.com/istio/istio/commit/23852d132a09eb16d03ae246ce1bd45dac60a297, istiod will push workload with hostnetwork set. So we can see workloads with duplicate node ip by calling /debug/config_dump/workload

Some limitations:

authz, we do using src ip to get the source workload, if the source ip is the node ip and shared by many pods, We cannot know which pod it is.
since the dst hostnetwork is not managed by kmesh, we won't have trouble find the dst workload by ip
metric builder: we need to find source/dst workload by sock address.  If the ip is shared, we may not be able to find the right workload.
kmesh_frontend map stores workloadIP->backend uid, if the workloadIP is a shared

OK，i can conduct on it。

Let me first describe what we can do with hostnetwork pod.

Access via a service with hostnetwork pods
Access hostnetwork pod via pod ip directly, we cannot do anything i think. Because the original dst ip is a shared node ip.

So what we need to do is supporting the first case.
currently bpf prog do routing via frontend map -> service map -> endpointmap -> backend map  maps are defined in bpf/kmesh/workload/include/workload.h
Looks we donot need to update the bpf maps.
What we should do is updating the userspace workloadCache ops. Preclude storing hotsnetwork pod in byAddr

Yes,  do you have any place that use getWorkloadbyaddress for hostnetwork pod. Keep in mind, these kind of pods are not managed by kmesh. They are just reachable through kmesh.

not used in my code. But in existing codes, we have:
https://github.com/kmesh-net/kmesh/blob/75a73125419cf0b90a027c34a28bd285d8d12aac/pkg/controller/telemetry/metric.go#L169-L198