GitHub as a backend does not work

Hello Developers,
I make my first steps with the Netlify CMS and do not understand how one can realize GitHub as a backend. I've already prepared everything on GitHub.com in own account for and have generated the client ID and Secret Key.
But I do not understand where you can find Access tab in the Dashboard. I see in the browser at /admin no such tab and does not find it. Or do I have to GitHub.com anywhere the client ID and Secret Key Enter?
Can you maybe help me figure it out ?!
Thanks in advance.

Hi Alex,
Currently the GitHub backend depends on netlify's Authentication Provider system, so you'll need to set the site up as a netlify site and follow the instructions here to enable the GitHub authentication provider:
https://www.netlify.com/docs/authentication-providers#using-an-authentication-provider
We do want to see other OAuth services enabled as well so there's no dependency on netlify...

Hi,
I need your help again. I have created in the /admin two files. These hot config.yml and index.html. I did that according to the instructions from the Netlify Repo.
In the config.yml file it looks like this at the top:
backend:
    name: github-api
    repo: AlexL777/netlifycmsblog # Path to your Github repository
    branch: master # Branch to update (master by default)

The contents of the index.html file should vote that way.
But if I frontend wants me log under /admin, appears to me "No provider found".

On GitHub in my Netlify repo I have the client ID and the Secret Key generated.
However, I do not understand why the provider can not be found. Are you an idea why it is so.

I think the doc missed one line.
You need to do some configuration work.
netlify.configure({'site_id': <your-site>.netlify.com});

Does this line will be inserted in the config.yml? Do I understand this in the right manner?

Hi, i'm closing this due to inactivity. Please feel free to reopen if you want to add to the discussion.

(reopened so a customer seeing the same problem can post their information here)

@ericxyan @fool
I am experiencing the same issue but netlify does not seem to be defined once the page is loaded. NetlifyAuth is available but does not have a configure function. Can you please point me in the right direction for where to use the above solution?
Thanks!

It looks like currently the site_id is not configurable - the host name is used as the site id except when running under localhost.
In lib/netlify-auth/Authenticator.js:
  getSiteID() {
    if (this.site_id) {
      return this.site_id;
    }
    const host = document.location.host.split(':')[0];
    return host === 'localhost' ? null : host;
  }

Would a PR to add this functionality be considered? I'd be happy to work on it!

Yes I think so. I can see there being cases where people's site_ids don't match up with the domain they are hosting under.
The Authenticator supports a site_id being provided in the constructor, so the best place to make a change would be in src/backends/github/implementation.js, which currently has the following:
    if (document.location.host.split(':')[0] === 'localhost') {
      auth = new Authenticator({ site_id: 'cms.netlify.com' });
    } else {
      auth = new Authenticator();
    }

The else could be changed to provide the site_id defined in the config.

@josephearl I agree that this is something we should support. We should pass it to the individual backends from src/backends/backend.js, since that's the entry point that the rest of the application uses.

I'm trying to do something like...
src/backends/github/AuthenticationPage.js
  handleLogin = (e, config) => {
    e.preventDefault();
    let auth;
    if (document.location.host.split(':')[0] === 'localhost') {
      auth = new Authenticator({ site_id: 'cms.netlify.com' });
    } else {
      auth = new Authenticator({ site_id: config.getIn(["backend", "site_id"], null) });
    }

How do I access config from here? Thanks~

@HarlemSquirrel you can pass the config in as a prop. If you trace through the code, you'll notice the AuthenticationPage component is only used in the implementation scripts for each backend, where it's returned from an authComponent method. That method is then accessed in src/containers/App.js, where the component is actually used and receives props. You could pass a siteId prop in there.

Thanks! I'm still very much new to React. I think I understand this part better now.

See this: https://github.com/netlify/netlify-cms/pull/411

https://www.netlify.com/docs/authentication-providers#using-an-authentication-provider

The link broke (trying to setup netlify-cms)

@cheapsteak Thanks for reporting that, here are some current instructions: https://www.netlifycms.org/docs/test-drive/#authenticate-with-github.

@cheapsteak @tech4him1 PR #626 will remove the "Authenticate with GitHub" section from the Test Drive doc, so the link the that doc will no longer work. However, the original link is now back in action:
https://www.netlify.com/docs/authentication-providers#using-an-authentication-provider

Solved by following this (not clearly linked in docs):
https://docs.netlify.com/visitor-access/oauth-provider-tokens/#setup-and-settings


Not familiar PCDet, can you give more detail training scripts?

@Cc-Hy
Hi, I am not familiar PCDet, can you give one training script?
BHW, where is the KD code line in your repo? I want to check your code part of KD loss.
Thanks your work!

@Cc-Hy
Great, thanks

@Cc-Hy
By the way, I found SCNet performs bad performance when uesd in MonoDisll


Move aca-py java client from boschresearch to hyperledger-labs

The BPA has a dependency on the aca-py java wrapper that is still located at https://github.com/boschresearch/aries-acapy-clients. To keep everything under one umbrella we want to move it to hyperledger-labs.
@ryjones can you set this up for us? I would also propose change the name of the repository to acapy-java-client

@ryjones I have to check if I'm allowed to transfer ownership, or if I'm breaching a company policy by doing so :) A other option would be to start with an empty repository, like this I can make sure that there aren't any DCO issues. So let's do it like this:

Wait and see what my compliance officer says, and if I get the permission I will transfer the ownership
If this is not possible I would propose to create a fresh repository
If none of the above is not possible fork it

@etschelp a blank repo with one commit is the best possible way to do this.

@ryjones that would also be my preferred option, then let's do it that way. I would propose to name it "acapy-java-client", the permissions are the same as on the business partner agent repo.

All yours: https://github.com/hyperledger-labs/acapy-java-client :)

Very nice, thanks :)


Question: Open file picker/grep with toggle_ignore already enabled

Thank you for this incredible plugin.
I've been happy to ditch my hacked-together ignore toggles for the recently added ignore toggle actions for both files and grep. Thank you very much for both of those. One thing I am missing is a way to open a picker and toggle the ignore action immediately.
Is there/could there be a way to pass in an option to the picker to set the initial settings for these toggles? Or have the header logic check which flags were passed? Or some other simpler thing I haven't considered?
I can set the toggle via fd_opts or rg_opts but the UI does not reflect the status of the options passed in which makes things a bit inconsistent.

Or have the header logic check which flags were passed? Or

This should be the solution, I was planning to add this anyways.
I’ll leave this issue open until fixed.

@star-szr, should work as expected with https://github.com/ibhagwan/fzf-lua/commit/718be95a88f6200137c17d64999e947afba07151.

@ibhagwan indeed, it works perfectly. Thank you so much!

Ty for the update @star-szr!


feature(brush): add configuration option to skip paint if the segmentation is not visible (skips event calls)

cornerstoneTools.addTool(cornerstoneTools.BrushTool, {
	name: 'Brush',
  configuration: {
	  skipPaintForInvisibleSegmentations: true
  }
})

Tests:

cornerstoneTools.store.modules.brush.state.alpha = 0
cornerstoneTools.getToolState(element, 'brush').data[segIndex].alpha = 0
cornerstoneTools.store.modules.brush.setters.brushVisibilityForElement(enabledElementUID, segIndex, visible)

CC: @JamesAPetts
Other stuff:

Shifts duplicate get/set toolState check out of strategies and into BrushTool's _paint method.
Provides a way to prevent UX confusion of adding/removing from a segmentation while it's not visible
Provides a way to prevent modified/completed events if we're not actually modifying brush data

I'm going to merge this for now; but please feel free to call out issues/complaints. Ideally, this should not impact consumers by default, as the functionality is hidden by a config flag.

:tada: This PR is included in version 3.18.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


TypeError: list indices must be integers or slices, not str

Traceback (most recent call last):
File "tools/train.py", line 113, in
main()
File "tools/train.py", line 109, in main
logger=logger)
File "/data2/yanmengkai/mmdetection/mmdet/apis/train.py", line 59, in train_detector
_non_dist_train(model, dataset, cfg, validate=validate)
File "/data2/yanmengkai/mmdetection/mmdet/apis/train.py", line 118, in _non_dist_train
runner.resume(cfg.resume_from)
File "/root/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/mmcv-0.2.8-py3.7.egg/mmcv/runner/runner.py", line 308, in resume
self._epoch = checkpoint['meta']['epoch']
TypeError: list indices must be integers or slices, not str

Please use the "Error report" issue template.

Hi, I got the same problem as yours. Did you got the solution?
Thaks for your reply.


bug(recovery): panicked at 'no table reader exists'

Describe the bug
https://buildkite.com/singularity-data/pull-request/builds/6818#0182d35d-042e-42ec-8b57-dcdebd0ce81c/2450-5881
thread '<unnamed>' panicked at 'no table reader exists', src/source/src/table_v2.rs:66:13
stack backtrace:
   0: rust_begin_unwind
             at /rustc/9067d5277d10f0f32a49ec9c125a33828e26a32b/library/std/src/panicking.rs:584:5
   1: core::panicking::panic_fmt
             at /rustc/9067d5277d10f0f32a49ec9c125a33828e26a32b/library/core/src/panicking.rs:142:14
   2: core::panicking::panic_display
             at /rustc/9067d5277d10f0f32a49ec9c125a33828e26a32b/library/core/src/panicking.rs:72:5
   3: core::panicking::panic_str
             at /rustc/9067d5277d10f0f32a49ec9c125a33828e26a32b/library/core/src/panicking.rs:56:5
   4: core::option::expect_failed
             at /rustc/9067d5277d10f0f32a49ec9c125a33828e26a32b/library/core/src/option.rs:1874:5
   5: core::option::Option<T>::expect
             at ./src/source/src/table_v2.rs:66:13
   6: risingwave_source::table_v2::TableSourceV2::write_chunk
             at ./src/source/src/table_v2.rs:66:13
   7: risingwave_batch::executor::insert::InsertExecutor::do_execute::{{closure}}
             at ./src/batch/src/executor/insert.rs:102:28
   8: <futures_async_stream::try_stream::from_generator::GenTryStream<G> as futures_core::stream::Stream>::poll_next
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/futures-async-stream-0.2.5/src/lib.rs:430:31
   9: <core::pin::Pin<P> as futures_core::stream::Stream>::poll_next
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/futures-core-0.3.23/src/stream.rs:120:9
  10: futures_util::stream::stream::StreamExt::poll_next_unpin
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/futures-util-0.3.23/src/stream/stream/mod.rs:1626:9
  11: <futures_util::stream::stream::next::Next<St> as core::future::future::Future>::poll
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/futures-util-0.3.23/src/stream/stream/next.rs:32:9
  12: <minitrace::future::InSpan<T> as core::future::future::Future>::poll
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/minitrace-0.4.0/src/future.rs:118:19
  13: risingwave_batch::executor::trace::TraceExecutor::do_execute::{{closure}}
             at ./src/batch/src/executor/trace.rs:67:69
  14: <futures_async_stream::try_stream::from_generator::GenTryStream<G> as futures_core::stream::Stream>::poll_next
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/futures-async-stream-0.2.5/src/lib.rs:430:31
  15: <core::pin::Pin<P> as futures_core::stream::Stream>::poll_next
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/futures-core-0.3.23/src/stream.rs:120:9
  16: futures_util::stream::stream::StreamExt::poll_next_unpin
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/futures-util-0.3.23/src/stream/stream/mod.rs:1626:9
  17: <futures_util::stream::stream::next::Next<St> as core::future::future::Future>::poll
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/futures-util-0.3.23/src/stream/stream/next.rs:32:9
  18: risingwave_batch::task::task_execution::BatchTaskExecution<C>::try_execute::{{closure}}::{{closure}}
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/tokio-1.20.1/src/macros/select.rs:507:49
  19: <tokio::future::poll_fn::PollFn<F> as core::future::future::Future>::poll
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/tokio-1.20.1/src/future/poll_fn.rs:38:9
  20: risingwave_batch::task::task_execution::BatchTaskExecution<C>::try_execute::{{closure}}
             at ./src/batch/src/task/task_execution.rs:335:13
  21: <core::future::from_generator::GenFuture<T> as core::future::future::Future>::poll
             at /rustc/9067d5277d10f0f32a49ec9c125a33828e26a32b/library/core/src/future/mod.rs:91:19
  22: <minitrace::future::InSpan<T> as core::future::future::Future>::poll
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/minitrace-0.4.0/src/future.rs:118:19
  23: risingwave_batch::task::task_execution::BatchTaskExecution<C>::async_execute::{{closure}}::{{closure}}::{{closure}}
             at ./src/batch/src/task/task_execution.rs:274:23
  24: <core::future::from_generator::GenFuture<T> as core::future::future::Future>::poll
             at /rustc/9067d5277d10f0f32a49ec9c125a33828e26a32b/library/core/src/future/mod.rs:91:19
  25: <core::pin::Pin<P> as core::future::future::Future>::poll
             at /rustc/9067d5277d10f0f32a49ec9c125a33828e26a32b/library/core/src/future/future.rs:124:9
  26: async_task::raw::RawTask<F,T,S>::run
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/async-task-4.3.0/src/raw.rs:511:20
  27: madsim::sim::task::Executor::run_all_ready::{{closure}}
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/madsim-0.2.3/src/sim/task.rs:179:53
  28: std::panicking::try::do_call
             at /rustc/9067d5277d10f0f32a49ec9c125a33828e26a32b/library/std/src/panicking.rs:492:40
  29: std::panicking::try
             at /rustc/9067d5277d10f0f32a49ec9c125a33828e26a32b/library/std/src/panicking.rs:456:19
  30: std::panic::catch_unwind
             at /rustc/9067d5277d10f0f32a49ec9c125a33828e26a32b/library/std/src/panic.rs:137:14
  31: madsim::sim::task::Executor::run_all_ready
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/madsim-0.2.3/src/sim/task.rs:179:20
  32: madsim::sim::task::Executor::block_on
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/madsim-0.2.3/src/sim/task.rs:147:13
  33: madsim::sim::runtime::Runtime::block_on
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/madsim-0.2.3/src/sim/runtime/mod.rs:124:9
  34: madsim::sim::runtime::builder::Builder::run::{{closure}}::{{closure}}::{{closure}}
             at /Users/wangrunji/.cargo/registry/src/github.com-1ecc6299db9ec823/madsim-0.2.3/src/sim/runtime/builder.rs:128:35

To Reproduce
On M1 Macbook Pro, checkout 4850abc and run:
MADSIM_TEST_SEED=3 ./risedev sslt -- --kill-node './e2e_test/batch/**/*.slt'

On Linux: (not sure whether this works)
MADSIM_TEST_SEED=1661404148 ./risedev sslt -- --kill-node './e2e_test/batch/**/*.slt'

Expected behavior
No response
Additional context
No response

Inserting into a table will first try to find a running SourceExecutor ("table reader"), then send the chunks to it. In the normal create table procedure, we ensure that the table is visible only after the streaming tasks (including the SourceExecutors) ready so we assert there's must be one table reader.
With recovery, we may update and build actors. Before the building completes, if a frontend issues a batch query of Insert, it may find no table reader available. Easy to reproduce if we insert a delay before self.update_actors.
https://github.com/singularity-data/risingwave/blob/7065ef109aeadc11d582d184ff0d7f2cb9c8ca2f/src/meta/src/barrier/recovery.rs#L96-L104
A quick fix can be changing the expect to or_else, as the actors will be built and the Insert query will succeed eventually (after some retries). However, I'm not sure whether the recovery test requires that there should be no error during the whole tests. If so, should we block all queries in the frontend until the meta finally recovered the whole cluster? cc @yezizp2012

Any updates?

Any updates?

We won't panic after #4967, but return error if the cluster is recovering and DML is temporarily unavailable. IIRC, the simulator will retry in these cases now, so there should be no problem.


packet header x-pattern refactor

All flow packet headers have been refactored to use the x-pattern extension (see the modeling guide for details).

@ajbalogh I think I see some old contents here, could you please sync with master ?


Exporting metadata file

DLC stores the following metadata:
https://github.com/DeepLabCut/DeepLabCut/blob/444da3da70b1f3bfaae39b0849e0aafcff1a9b7a/deeplabcut/pose_estimation_tensorflow/predict_videos.py#L750
(we are likely going to expand this in the near future). What other variables should be stored and could we put in NWB?

We think one should add

the cropping parameters (that were used during inference), see https://github.com/DeepLabCut/DeepLabCut/blob/444da3da70b1f3bfaae39b0849e0aafcff1a9b7a/deeplabcut/pose_estimation_tensorflow/predict_videos.py#L762
and pose_cfg, which is a dictionary that has lots of parameters https://github.com/DeepLabCut/DeepLabCut/blob/444da3da70b1f3bfaae39b0849e0aafcff1a9b7a/deeplabcut/pose_estimation_tensorflow/predict_videos.py#L755

How do you want us to add them to ndx_pose. Shall we just add fields?


Change license to CC BY-NC-SA 4.0

Because it is a standard license for Picotron work and is the most popular among Picotron creators.

I think this is license is too restrictive compared to MIT. I want commercial games to use unitron as well. On the other hand, unit tests are not part of production code, therefore test could have CC license. But some people might not like it.


Cause: Last checkpointed offset 2692 is greater or equal to high watermark 42

Describe the bug
can't index from kafka
the error is as follows:
2022-06-20T06:26:01.726Z ERROR {actor=quickwit_indexing::actors::indexing_server::IndexingServer}:{msg_id=1}::{msg_id=71000}: quickwit_indexing::actors::indexing_pipeline: Error while spawning indexing pipeline, retrying after some time. error=Failed to create source `source-kafka` of type `kafka`. Cause: Last checkpointed offset `2692` is greater or equal to high watermark `42`.

Caused by:
  Last checkpointed offset `2692` is greater or equal to high watermark `42`. retry_count=26 retry_delay=600s

Configuration:
Please provide:

quickwit 0.2.1
The  trace.yaml

version: 0 # File format version.
index_id: trace
doc_mapping:
    field_mappings:
        - name: id
          type: u64
          fast: true
        - name: raw_content
          type: text
          tokenizer: default
          record: position
search_settings:
    default_search_fields: [raw_content]

sources:
    - source_id: source-kafka
      source_type: kafka
      params:
          topic: ua
          client_params:
              bootstrap.servers: <IP_ADDRESS>:9092
              group.id: FullText
              security.protocol: PLAINTEXT

Hi @chenjinlei1122, thanks for the report.
First, I'm wondering why you are still using the 0.2.1, the trace.yaml indicates a format only compatible with the 0.3.
Concerning the error Last checkpointed offset 2692is greater or equal to high watermark42. retry_count=26 retry_delay=600s, Quickwit indicates an inconsistency between the last checkpoint offset in Quickwit which is 2692, and the last offset in Kafka 42 (high watermark is the higher offset of messages that are fully replicated).
When starting Quickwit, it will consume messages from the offset of the last checkpoint offset, which means from 2692, this means that you have already indexed some data with Quickwit which produced a split that contains this checkpoint offset.
But the high watermark or HM is lesser than this offset which is not normal: now Quickwit expects to retrieve message from an offset that is higher than the highest offset. It can come from the fact that you delete/create the same topic or if you have reset the offset of that topic.

that's right， thanks for your repley


New CLI Option to Trim slash Prefixes in Wordlist

Description
This PR adds the option to automatically trim prefixes preceeding slashes from a wordlist. For example, if a wordlist contains:
/x.txt
profile
/admin

ffuf would make the following requests for ffuf -u http://acme.com/FUZZ -w lists.txt -sp:
/x.txt => http://acme.com/x.txt
profile => http://acme.com/profile
/admin => http://acme.com/admin

Rationale
Typically, I would say that the wordlist should be prepared for the tool and context where the wordlist will be used. However, I have found myself creating countless duplicates of wordlists with the appendix "somelist-noslash.txt". I thought this would be a nice quality of life addition and save people time when switching to fresh VMs without having to load/prep custom wordlists.

Thanks for creating the PR.
I'm considering how to approach this. In the past I have been trying to avoid all features that can be handled "outside" of ffuf. I think this is important in order to avoid feature creep, and to be honest the amount of CLI flags available is making it harder to get a grasp of the tool and using it efficiently.
In my opinion, it would be a better fit for ffuf-scripts as a shell script (even though there's not much at the repo atm)
What do you think?

I completely agree in keeping tools streamlined and this use case definitely does not fall under ffuf's domain so no worries there. It was just an experience I kept having moving from box to box. If it's an experience that many people are having, it might be worth making an exception, but for now, I'm okay with exploring external alternatives / leveraging bash i/o. Let me know what you think, but I'm fine letting the current PR fade into obscurity if there's no support for it.


Confusing (incorrect?) message when customizing entity via GUI

Home Assistant release with the issue:
0.102.2
Last working Home Assistant release (if known):
n/a
Operating environment (Hass.io/Docker/Windows/etc.):
Hass.io on Ubuntu 16.04
Description of problem:
I decided to try customizing a device_tracker entity via the GUI and when I hit save, I got the following message which doesn't seems accurate.  I do have the include in what I believe to be the correct place, and it works - other device names are customized.
GUI message was as follows:

It seems that your configuration.yaml doesn't properly include customize.yaml.
Changes made here are written in it, but will not be applied after a configuration reload unless the include is in place.

Problem-relevant configuration.yaml entries and (fill out even if it seems unimportant):
homeassistant:
  name: Home
  latitude: 32
  longitude: -96
  elevation: 190
  unit_system: imperial
  time_zone: America/Chicago
  customize: !include customize.yaml

@mrand please close this issue and move it to the frontend repo of Home Assistant.
Thank you! :)

@springstan We just move those issues, let's not ask everybody to close and create new issues 😉


at sign "@" unsupported

Unsupported where?

Textbox, portuguese keyboard.
thanks

@thesyncim I am using gxui with a portuguese keyboard and the "@" works without any problems. I am not using the textbox component (writing a new textarea from the ground-up) but the KeyPress events is triggered with the right values. My "@" is typed by pressing "Shift+2".
One problem that I noticed is how deadkeys are handled. In my case typing the "~" plus "a" don't result in "ã" but instead triggers two keypress events one with the "~" code and another with the "a" code. Your problem might be related to it.
Using Fedora22 here.


usage question on collisions of regex in parser

I see the documentation covers perfectly how to use priority, which is why I'm confused how I could still be getting this wrong.
I have a number regex (build from subregex):
#[logos(subpattern float = r"[0-9]+\.?[0-9]*")]

#[regex(r"-?(?&float)(e[+-][0-9]+)?", |lex| lex.slice())]
Number(&'input str),

and then I also have this regex for a "range", which is just two comma separated numbers:
#[regex(r"(?&float),(?&float)", |lex| lex.slice())]
Range(&'input str),

Parsing the following fails if I have that Range defined while parsing Row defined below: "1,2,3"
Because it seems to think "1,2" is wrong since it's expecting Number. If I delete the Range this issue goes away entirely.
The parser code is simple Lalrpop straight from their hello world example:
Num: f32 = Number => f32::from_str(<>).unwrap();

Csv<T>: Vec<T> = {
  // "keep" vals inside <>, including v, zero or more (*) comma separated vals and optional trailing (e) value
  <mut v:(<T> ",")*> <e:T?> => match e {
    None => v,
    Some(e) => {
      v.push(e);
      v
    }
  }
};

pub Row: Vec<f32> = Csv<Num>;

Now, it turns out I only ever use Range when the text is preceded by a colon :, so I was able to avoid this issue by simply redefining Range as:
#[regex(r": (?&float),(?&float);", |lex| lex.slice())]
Range(&'input str),

But what's interesting about this is the only explanation I can think of for why this works is because Range was colliding with Number, so why didn't setting the priority on Range to 2 work as expected? Is it faster/better to uniquify regexes the way I did in this case?

ah, I just realized though captures aren't supported so adding that extra colon and semicolon to my Range causes it to be absorbed into the parsed value:
https://github.com/maciejhirsz/logos/issues/143

I'm noticing now there's a bug reported for certain regexes not respecting priority. Is this one of those cases?:
https://github.com/maciejhirsz/logos/issues/181

It seems this isn't a regex-regex collision but a collision of a regex (Range) with a regex (Number) and a token (,)
Is there anyway for Number and , to take higher priority than Range?

I've re-read the linked issues and in fact longer regex matches take precedence regardless of priority set.


Error on executing more than 150 testcases in a suite

Are you requesting a feature or reporting a bug?

bug
What is your Test Scenario?

I am planning to create a regression test suite using testcafe. I have created 3-4 test cases using page-object pattern. I created multiple copies of the test cases to have around 200 TC files. I am able to run the test cases individually. I am able to run the test cases(copies) when the count is 150. when the count increases to ~175, the error is thrown. I have allocated 8GB, 10GB, 12GB to the node application.
What is the Current behavior?

Error is thrown as below:
PS C:\javelin> node  --max-old-space-size=8192 .\test-runner.js Error: Unable to establish one or more of the specified browser connections. This can be caused by network issues or remote device failure.     at BrowserSet._waitConnectionsOpened (C:\javelin\node_modules\testcafe\src\runner\browser-set.js:84:30)     at pinkie_1.default.resolve.then (C:\javelin\node_modules\testcafe\src\runner\browser-set.js:107:35)     at invokeCallback (C:\javelin\node_modules\pinkie\index.js:60:12)     at Array.forEach (<anonymous>)     at publish (C:\javelin\node_modules\pinkie\index.js:147:32)     at Array.publishFulfillment (C:\javelin\node_modules\pinkie\index.js:152:2)     at Immediate.asyncFlush (C:\javelin\node_modules\pinkie\index.js:17:19)     at runCallback (timers.js:706:11)     at tryOnImmediate (timers.js:676:5)     at processImmediate (timers.js:658:5)     at process.topLevelDomainCallback (domain.js:126:23)
What is the Expected behavior?

Test cases should run smoothly
How would you reproduce the current behavior (if this is a bug)?

Create any test case using page-object pattern, create 200 copies of that test case and execute.
Provide the test code and the tested page URL (if applicable)

Your website URL (or attach your complete example):
Your complete test code (or attach your test files)

Your Environment details:
testcafe - 1.2.1
node.js - 10.16.0
command - node testrunner.js [testrunner attached in txt form]
browser - chrome
platform : Windows 10
test-runner.txt

testcafe version:
node.js version:
command-line arguments:
browser name and version:
platform and version:
other:

Hello. I was unable to reproduce this issue. Could you please provide a sample test file with the page model? Also, please send us your test web page (or a public url to it) that illustrates this behavior.

I was able to reproduce the issue with 300 copies of the test file (refer T800277). We will need additional time to research it in detail.

@dirasangtani
I researched your project and found that creating a page model object takes some time. Since you have more that 150 files and huge page model objects, it leads to the error.
I recommend you reorganize your code in the following manner:

do not export the constructor of a page model, export a new instance;
do not use the new keyword in your test files.

Please see the modified example:

login-page.js

import { Selector } from 'testcafe';
import { t } from 'testcafe';

class LoginPage{
	constructor(){
		this.username = Selector('#ctl00_ctl00_RightContent_RightContent_usr');
		this.password = Selector('#ctl00_ctl00_RightContent_RightContent_pwd');
		this.submit = Selector('#ctl00_ctl00_RightContent_RightContent_login');
	}

	async sdLogin(name, pwd){
		await t
			.typeText(this.username, name)
			.typeText(this.password, pwd)
			.click(this.submit)
	}
}

export default new LoginPage();

tc041.js

import loginPage from '../../main/page-objects/screening-direct/login-page.js'
// const loginPage = new LoginPage(); // NOTE: comment this line

Please modify all you page models in this manner. This should improve execution time significantly.
If this approach is not suitable for you, let us know.

@AlexKamaev This code optimization worked well. Appreciate it.

@AlexKamaev  Do you recommend any optimal way for defining locators rather than inside a constructor?
There are like hundreds of them on a page.

Instead of exporting a page object class (export default class PageObject { ... }), you can create an instance of the page object and export it instead:
class PageObject {

}

export default new PageObject();

see https://github.com/DevExpress/testcafe/issues/4306

We've decided to close this issue because the original problem was caused by creating a large number of huge page objects which now can be resolved by either optimizing test code following our recommendations or by increasing the timeout value. Check out the guide with these recommendations on how to optimize your Page Model: Speed Up Test Execution.
Also, the generic error message when a browser couldn't establish a connection within the timeout was improved - in a case when tests compilation took too long it will show a note which recommends increasing the browserInitTimeout value.


[Bug] Segmentation fault during run of quantized internlm/internlm-xcomposer2-4khd-7b model

Checklist

[ ] 1. I have searched related issues but cannot get the expected help.
[ ] 2. The bug has not been fixed in the latest version.

Describe the bug
Hello, after successful quantization of  internlm/internlm-xcomposer2-4khd-7b model, I was trying to run VLM Offline Inference Pipeline. However, after loading of the model and the picture, it failed on segmentation fault. Do you have any idea, how to fix this issue?
Reproduction
load_quant.py
import os
import torch
import nest_asyncio
from lmdeploy import pipeline, TurbomindEngineConfig
import logging
import requests
import cv2
import numpy as np
from io import BytesIO

# Enable logging
logging.basicConfig(level=logging.DEBUG)

nest_asyncio.apply()

# Set environment variables for debugging NCCL
os.environ["CUDA_VISIBLE_DEVICES"] = "0"  # Run with a single GPU for debugging
os.environ['KMP_DUPLICATE_LIB_OK'] = 'True'
os.environ['NCCL_DEBUG'] = 'INFO'
os.environ['NCCL_DEBUG_SUBSYS'] = 'ALL'
os.environ['NCCL_P2P_LEVEL'] = 'NVL'

model_id = "internlm/internlm-xcomposer2-4khd-7b-chat-4bit"
backend_config = TurbomindEngineConfig(cache_max_entry_count=0.2, tp=1)  # Set tp to 1 for single GPU

# Check CUDA and PyTorch installation
print(f"CUDA available: {torch.cuda.is_available()}")
print(f"Number of GPUs: {torch.cuda.device_count()}")

try:
    pipe = pipeline(model_id, backend_config=backend_config)
    print("Model loaded successfully")
except Exception as e:
    print(f"Error loading model: {e}")

try:
    image_url = 'https://raw.githubusercontent.com/open-mmlab/mmdeploy/main/tests/data/tiger.jpeg'
    response = requests.get(image_url)
    response.raise_for_status()  # Raise an HTTPError for bad responses
    image_array = np.array(bytearray(response.content), dtype=np.uint8)
    img = cv2.imdecode(image_array, -1)
    print(f"Image shape: {img.shape}, dtype: {img.dtype}")
except Exception as e:
    print(f"Error downloading or processing image: {e}")

# Explicitly clear cache to manage memory
torch.cuda.empty_cache()

try:
    prompts = [
        {
            'role': 'user',
            'content': [
                {'type': 'text', 'text': 'describe this image'},
                {'type': 'image_url', 'image_url': {'url': image_url}}
            ]
        }
    ]
    response = pipe(prompts)
    print(response)
except Exception as e:
    print(f"Error processing image: {e}")

python3 load_quant.py

Environment
sys.platform: linux
Python: 3.10.12 (main, Mar 22 2024, 16:50:05) [GCC 11.4.0]
CUDA available: True
MUSA available: False
numpy_random_seed:<PHONE_NUMBER>
GPU 0,1,2,3: NVIDIA A10G
CUDA_HOME: /usr/local/cuda-12.1
NVCC: Cuda compilation tools, release 12.1, V12.1.105
GCC: x86_64-linux-gnu-gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
PyTorch: 2.2.2+cu121
PyTorch compiling details: PyTorch built with:
  - GCC 9.3
  - C++ Version: 201703
  - Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications
  - Intel(R) MKL-DNN v3.3.2 (Git Hash 2dc95a2ad0841e29db8b22fbccaf3e5da7992b01)
  - OpenMP 201511 (a.k.a. OpenMP 4.5)
  - LAPACK is enabled (usually provided by MKL)
  - NNPACK is enabled
  - CPU capability usage: AVX2
  - CUDA Runtime 12.1
  - NVCC architecture flags: -gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90
  - CuDNN 8.9.7  (built against CUDA 12.2)
    - Built with CuDNN 8.9.2
  - Magma 2.6.1
  - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=12.1, CUDNN_VERSION=8.9.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=pedantic -Wno-error=old-style-cast -Wno-missing-braces -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=2.2.2, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF,

TorchVision: 0.17.2+cu121
LMDeploy: 0.5.0+
transformers: 4.40.0
gradio: 3.50.2
fastapi: 0.111.0
pydantic: 2.7.4
triton: 2.2.0

Error traceback
DEBUG:asyncio:Using selector: EpollSelector
CUDA available: True
Number of GPUs: 1
Set max length to 16384
DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): huggingface.co:443
DEBUG:urllib3.connectionpool:https://huggingface.co:443 "HEAD /openai/clip-vit-large-patch14-336/resolve/main/config.json HTTP/11" 200 0
DEBUG:urllib3.connectionpool:https://huggingface.co:443 "HEAD /openai/clip-vit-large-patch14-336/resolve/main/config.json HTTP/11" 200 0
Dummy Resized
INFO:accelerate.utils.modeling:We will use 90% of the memory on device 0 for storing the model, and 10% for the buffer to avoid OOM. You can set `max_memory` in to a higher value to use more memory (at your own risk).
[WARNING] gemm_config.in is not found; using default GEMM algo
Model loaded successfully
DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): raw.githubusercontent.com:443
DEBUG:urllib3.connectionpool:https://raw.githubusercontent.com:443 "GET /open-mmlab/mmdeploy/main/tests/data/tiger.jpeg HTTP/11" 200 13929
Image shape: (182, 278, 3), dtype: uint8
DEBUG:urllib3.connectionpool:Starting new HTTPS connection (1): raw.githubusercontent.com:443
DEBUG:urllib3.connectionpool:https://raw.githubusercontent.com:443 "GET /open-mmlab/mmdeploy/main/tests/data/tiger.jpeg HTTP/11" 200 13929
Segmentation fault (core dumped)

Additionally, I was trying to debug the issue with dgb gdb --args python3 load_quant.py. Backtrace is below
GNU gdb (Ubuntu 12.1-0ubuntu1~22.04.2) 12.1
Copyright (C) 2022 Free Software Foundation, Inc.
License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.
Type "show copying" and "show warranty" for details.
This GDB was configured as "x86_64-linux-gnu".
Type "show configuration" for configuration details.
For bug reporting instructions, please see:
<https://www.gnu.org/software/gdb/bugs/>.
Find the GDB manual and other documentation resources online at:
    <http://www.gnu.org/software/gdb/documentation/>.

For help, type "help".
Type "apropos word" to search for commands related to "word"...
Reading symbols from python3...
(No debugging symbols found in python3)
(gdb) run
Starting program: /usr/bin/python3 load_quant.py
[Thread debugging using libthread_db enabled]
Using host libthread_db library "/lib/x86_64-linux-gnu/libthread_db.so.1".
 You can set `max_memory` in to a higher value to use more memory (at your own risk).

[Switching to Thread 0x7ffe817fe640 (LWP 180475)]
0x00007fff4c64a0ea in ?? () from /lib/x86_64-linux-gnu/libcuda.so.1
(gdb) backtrace
#0  0x00007fff4c64a0ea in ?? () from /lib/x86_64-linux-gnu/libcuda.so.1
#1  0x00007fff4c8c6fc8 in ?? () from /lib/x86_64-linux-gnu/libcuda.so.1
#2  0x00007fff4c534927 in ?? () from /lib/x86_64-linux-gnu/libcuda.so.1
#3  0x00007fff4c6f15d0 in ?? () from /lib/x86_64-linux-gnu/libcuda.so.1
#4  0x00007ffb999b657b in ?? () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/../../nvidia/cudnn/lib/libcudnn_cnn_infer.so.8
#5  0x00007ffb99a11d96 in ?? () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/../../nvidia/cudnn/lib/libcudnn_cnn_infer.so.8
#6  0x00007ffb982b3d40 in cudnn::cnn::precompute_indices(cudnnContext*, cudnnTensorStruct const*, cudnnFilterStruct const*, cudnnConvolutionStruct const*, void*, unsigned long) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/../../nvidia/cudnn/lib/libcudnn_cnn_infer.so.8
#7  0x00007ffb97f5a2ce in cudnn::cnn::PrecomputedGemmEngine<cudnn::cnn::convolve_launch_pg_pf<__half, float, float, __half>, 5, 2, 2>::execute_intermediate(cudnnContext*, cudnn::cnn::ExecutionIntermediate&) const () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/../../nvidia/cudnn/lib/libcudnn_cnn_infer.so.8
#8  0x00007ffb97f5c4df in cudnn::cnn::PrecomputedGemmEngine<cudnn::cnn::convolve_launch_pg_pf<__half, float, float, __half>, 5, 2, 2>::execute_internal_impl(cudnn::backend::VariantPack const&, CUstream_st*) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/../../nvidia/cudnn/lib/libcudnn_cnn_infer.so.8
#9  0x00007ffb97b28f25 in cudnn::cnn::EngineInterface::execute(cudnn::backend::VariantPack const&, CUstream_st*) ()
   from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/../../nvidia/cudnn/lib/libcudnn_cnn_infer.so.8
#10 0x00007ffb97b5b3b0 in cudnn::cnn::EngineContainer<(cudnnBackendEngineName_t)1>::execute_internal_impl(cudnn::backend::VariantPack const&, CUstream_st*) ()
   from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/../../nvidia/cudnn/lib/libcudnn_cnn_infer.so.8
#11 0x00007ffb97b28f25 in cudnn::cnn::EngineInterface::execute(cudnn::backend::VariantPack const&, CUstream_st*) ()
   from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/../../nvidia/cudnn/lib/libcudnn_cnn_infer.so.8
#12 0x00007ffb97c9006e in cudnn::cnn::AutoTransformationExecutor::execute_pipeline(cudnn::cnn::EngineInterface&, cudnn::backend::VariantPack const&, CUstream_st*) const
    () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/../../nvidia/cudnn/lib/libcudnn_cnn_infer.so.8
#13 0x00007ffb97c901b7 in cudnn::cnn::BatchPartitionExecutor::operator()(cudnn::cnn::EngineInterface&, cudnn::cnn::EngineInterface*, cudnn::backend::VariantPack const&, CUstream_st*) const () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/../../nvidia/cudnn/lib/libcudnn_cnn_infer.so.8
#14 0x00007ffb97cadc9b in cudnn::cnn::GeneralizedConvolutionEngine<cudnn::cnn::EngineContainer<(cudnnBackendEngineName_t)1> >::execute_internal_impl(cudnn::backend::VariantPack const&, CUstream_st*) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/../../nvidia/cudnn/lib/libcudnn_cnn_infer.so.8
#15 0x00007ffb97b28f25 in cudnn::cnn::EngineInterface::execute(cudnn::backend::VariantPack const&, CUstream_st*) ()
   from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/../../nvidia/cudnn/lib/libcudnn_cnn_infer.so.8
#16 0x00007ffb97b3bb3c in cudnn::backend::execute(cudnnContext*, cudnn::backend::ExecutionPlan&, cudnn::backend::VariantPack&) ()
   from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/../../nvidia/cudnn/lib/libcudnn_cnn_infer.so.8
#17 0x00007ffb97b3bf3d in cudnnBackendExecute () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/../../nvidia/cudnn/lib/libcudnn_cnn_infer.so.8
#18 0x00007fffabfeec5d in at::native::run_conv_plan(cudnnContext*, at::Tensor const&, at::Tensor const&, at::Tensor const&, cudnn_frontend::ExecutionPlan_v8 const&) ()
   from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so
#19 0x00007fffabff7590 in at::native::try_configs(std::vector<std::shared_ptr<cudnn_frontend::OpaqueBackendPointer>, std::allocator<std::shared_ptr<cudnn_frontend::OpaqueBackendPointer> > >&, std::string const&, at::native::(anonymous namespace)::CacheKeyWrapper const&, cudnnContext*, at::Tensor const&, at::Tensor const&, at::Tensor const&) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so
#20 0x00007fffabff7c57 in at::native::run_single_conv(cudnnBackendDescriptorType_t, at::Tensor const&, at::Tensor const&, at::Tensor const&, c10::ArrayRef<long>, c10::ArrayRef<long>, c10::ArrayRef<long>, long, bool, bool, bool) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so
#21 0x00007fffabff8a1b in at::native::raw_cudnn_convolution_forward_out(at::Tensor const&, at::Tensor const&, at::Tensor const&, c10::ArrayRef<long>, c10::ArrayRef<long>, c10::ArrayRef<long>, long, bool, bool, bool) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so
#22 0x00007fffabfdc587 in at::native::cudnn_convolution_forward(char const*, at::TensorArg const&, at::TensorArg const&, c10::ArrayRef<long>, c10::ArrayRef<long>, c10::ArrayRef<long>, long, bool, bool, bool) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so
#23 0x00007fffabfdcba6 in at::native::cudnn_convolution(at::Tensor const&, at::Tensor const&, c10::ArrayRef<long>, c10::ArrayRef<long>, c10::ArrayRef<long>, long, bool, bool, bool) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so
#24 0x00007fffae07bade in at::(anonymous namespace)::(anonymous namespace)::wrapper_CUDA__cudnn_convolution(at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::SymInt, bool, bool, bool) ()
   from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so
#25 0x00007fffae093b01 in c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor (at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::SymInt, bool, bool, bool), &at::(anonymous namespace)::(anonymous namespace)::wrapper_CUDA__cudnn_convolution>, at::Tensor, c10::guts::typelist::typelist<at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::SymInt, bool, bool, bool> >, at::Tensor (at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::SymInt, bool, bool, bool)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::SymInt, bool, bool, bool) ()
   from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so
#26 0x00007fffe013233b in at::_ops::cudnn_convolution::call(at::Tensor const&, at::Tensor const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::SymInt, bool, bool, bool) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#27 0x00007fffdf3aa49b in at::native::_convolution(at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<long>, c10::ArrayRef<long>, c10::ArrayRef<long>, bool, c10::ArrayRef<long>, long, bool, bool, bool, bool) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#28 0x00007fffe04f4dcf in at::(anonymous namespace)::(anonymous namespace)::wrapper_CompositeExplicitAutograd___convolution(at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt, bool, bool, boo--Type <RET> for more, q to quit, c to continue without paging--c
l, bool) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#29 0x00007fffe04fb72c in c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor (at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt, bool, bool, bool, bool), &at::(anonymous namespace)::(anonymous namespace)::wrapper_CompositeExplicitAutograd___convolution>, at::Tensor, c10::guts::typelist::typelist<at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt, bool, bool, bool, bool> >, at::Tensor (at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt, bool, bool, bool, bool)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt, bool, bool, bool, bool) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#30 0x00007fffdfc521a4 in at::_ops::_convolution::call(at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt, bool, bool, bool, bool) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#31 0x00007fffdf39d4c8 in at::native::convolution(at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<long>, c10::ArrayRef<long>, c10::ArrayRef<long>, bool, c10::ArrayRef<long>, long) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#32 0x00007fffe04f466c in at::(anonymous namespace)::(anonymous namespace)::wrapper_CompositeExplicitAutograd__convolution(at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#33 0x00007fffe04fb598 in c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor (at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt), &at::(anonymous namespace)::(anonymous namespace)::wrapper_CompositeExplicitAutograd__convolution>, at::Tensor, c10::guts::typelist::typelist<at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt> >, at::Tensor (at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#34 0x00007fffdfc10e1b in at::_ops::convolution::redispatch(c10::DispatchKeySet, at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#35 0x00007fffe1ae5962 in torch::autograd::VariableType::(anonymous namespace)::convolution(c10::DispatchKeySet, at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#36 0x00007fffe1ae68d9 in c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor (c10::DispatchKeySet, at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt), &torch::autograd::VariableType::(anonymous namespace)::convolution>, at::Tensor, c10::guts::typelist::typelist<c10::DispatchKeySet, at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt> >, at::Tensor (c10::DispatchKeySet, at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#37 0x00007fffdfc50fa4 in at::_ops::convolution::call(at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#38 0x00007fffdf0f5960 in at::convolution_symint(at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, bool, c10::ArrayRef<c10::SymInt>, c10::SymInt) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#39 0x00007fffdf3a0e98 in at::native::conv2d_symint(at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::SymInt) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#40 0x00007fffe06e9943 in at::(anonymous namespace)::(anonymous namespace)::wrapper_CompositeImplicitAutograd__conv2d(at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::SymInt) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#41 0x00007fffe06e9a7d in c10::impl::wrap_kernel_functor_unboxed_<c10::impl::detail::WrapFunctionIntoFunctor_<c10::CompileTimeFunctionPointer<at::Tensor (at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::SymInt), &at::(anonymous namespace)::(anonymous namespace)::wrapper_CompositeImplicitAutograd__conv2d>, at::Tensor, c10::guts::typelist::typelist<at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::SymInt> >, at::Tensor (at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::SymInt)>::call(c10::OperatorKernel*, c10::DispatchKeySet, at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::SymInt) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#42 0x00007fffe026313e in at::_ops::conv2d::call(at::Tensor const&, at::Tensor const&, std::optional<at::Tensor> const&, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::ArrayRef<c10::SymInt>, c10::SymInt) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so
#43 0x00007ffff542ec19 in torch::autograd::THPVariable_conv2d(_object*, _object*, _object*) () from /home/ubuntu/.local/lib/python3.10/site-packages/torch/lib/libtorch_python.so
#44 0x00005555556aec9e in ?? ()
#45 0x00005555556a53cb in _PyObject_MakeTpCall ()
#46 0x000055555569dfab in _PyEval_EvalFrameDefault ()
#47 0x00005555556bd111 in ?? ()
#48 0x000055555569d59a in _PyEval_EvalFrameDefault ()
#49 0x00005555556bd25e in ?? ()
#50 0x0000555555699a9d in _PyEval_EvalFrameDefault ()
#51 0x00005555556bd25e in ?? ()
#52 0x0000555555699a9d in _PyEval_EvalFrameDefault ()
#53 0x00005555556a4564 in _PyObject_FastCallDictTstate ()
#54 0x00005555556ba46c in _PyObject_Call_Prepend ()
#55 0x00005555557d5180 in ?? ()
#56 0x00005555556a53cb in _PyObject_MakeTpCall ()
#57 0x000055555569dfab in _PyEval_EvalFrameDefault ()
#58 0x00005555556bd25e in ?? ()
#59 0x0000555555699a9d in _PyEval_EvalFrameDefault ()
#60 0x00005555556bd25e in ?? ()
#61 0x0000555555699a9d in _PyEval_EvalFrameDefault ()
#62 0x00005555556a4564 in _PyObject_FastCallDictTstate ()
#63 0x00005555556ba46c in _PyObject_Call_Prepend ()
#64 0x00005555557d5180 in ?? ()
#65 0x00005555556a53cb in _PyObject_MakeTpCall ()
#66 0x000055555569dfab in _PyEval_EvalFrameDefault ()
#67 0x00005555556bd111 in ?? ()
#68 0x00005555556bddb2 in PyObject_Call ()
#69 0x0000555555699a9d in _PyEval_EvalFrameDefault ()
#70 0x00005555556bd111 in ?? ()
#71 0x00005555556bddb2 in PyObject_Call ()
#72 0x0000555555699a9d in _PyEval_EvalFrameDefault ()
#73 0x00005555556af59c in _PyFunction_Vectorcall ()
#74 0x00005555556a460d in _PyObject_FastCallDictTstate ()
#75 0x00005555556ba46c in _PyObject_Call_Prepend ()
#76 0x00005555557d5180 in ?? ()
#77 0x00005555556a53cb in _PyObject_MakeTpCall ()
#78 0x000055555569e63b in _PyEval_EvalFrameDefault ()
#79 0x00005555556bd111 in ?? ()
#80 0x00005555556bddb2 in PyObject_Call ()
#81 0x0000555555699a9d in _PyEval_EvalFrameDefault ()
#82 0x00005555556bd111 in ?? ()
#83 0x00005555556bddb2 in PyObject_Call ()
#84 0x0000555555699a9d in _PyEval_EvalFrameDefault ()
#85 0x00005555556af59c in _PyFunction_Vectorcall ()
#86 0x00005555556a460d in _PyObject_FastCallDictTstate ()
#87 0x00005555556ba46c in _PyObject_Call_Prepend ()
#88 0x00005555557d5180 in ?? ()
#89 0x00005555556a53cb in _PyObject_MakeTpCall ()
#90 0x000055555569e63b in _PyEval_EvalFrameDefault ()
#91 0x00005555556bd25e in ?? ()
#92 0x0000555555699a9d in _PyEval_EvalFrameDefault ()
#93 0x00005555556bd25e in ?? ()
#94 0x0000555555699a9d in _PyEval_EvalFrameDefault ()
#95 0x00005555556a4564 in _PyObject_FastCallDictTstate ()
#96 0x00005555556ba46c in _PyObject_Call_Prepend ()
#97 0x00005555557d5180 in ?? ()
#98 0x00005555556a53cb in _PyObject_MakeTpCall ()
#99 0x000055555569dfab in _PyEval_EvalFrameDefault ()
#100 0x00005555556bd111 in ?? ()
#101 0x000055555569d59a in _PyEval_EvalFrameDefault ()
#102 0x00005555556af59c in _PyFunction_Vectorcall ()
#103 0x0000555555699a9d in _PyEval_EvalFrameDefault ()
#104 0x00005555556af59c in _PyFunction_Vectorcall ()
#105 0x000055555569796e in _PyEval_EvalFrameDefault ()
#106 0x00005555556bd25e in ?? ()
#107 0x0000555555699a9d in _PyEval_EvalFrameDefault ()
#108 0x00005555556af59c in _PyFunction_Vectorcall ()
#109 0x000055555569796e in _PyEval_EvalFrameDefault ()
#110 0x00005555556af59c in _PyFunction_Vectorcall ()
#111 0x0000555555699a9d in _PyEval_EvalFrameDefault ()
#112 0x00005555556af59c in _PyFunction_Vectorcall ()
#113 0x000055555569796e in _PyEval_EvalFrameDefault ()
#114 0x00005555556af59c in _PyFunction_Vectorcall ()
#115 0x000055555569796e in _PyEval_EvalFrameDefault ()
#116 0x00005555556bd371 in ?? ()
#117 0x00005555557e657a in ?? ()
#118 0x00005555557db978 in ?? ()
#119 0x00007ffff7c94ac3 in start_thread (arg=<optimized out>) at ./nptl/pthread_create.c:442
#120 0x00007ffff7d26850 in clone3 () at ../sysdeps/unix/sysv/linux/x86_64/clone3.S:81


Downtime Length

⚠ Please verify that this feature request has NOT been suggested before.

[X] I checked and didn't find similar feature request

🏷 Feature Request Type
Other
🔖 Feature description
When a service is coming back up you could display for how long it was down. For example Hetrixtools shows that in there notification of the service going back up.
✔ Solution
When the service comes back up calculate the current time minus the time when the service went down and display it in the notification.
❓ Alternatives
Could also be shown in the web panel at the message part
📝 Additional Context
No response

Hello,
Similar or not ? https://github.com/louislam/uptime-kuma/issues/1970

Yes Down duration would be the same. I searched for it but did not find anything like it. Thank you! Will close this then as it is a duplicate bascially :D


Delete Cache and Reconfigure with FetchContent

Brief Issue Summary
I'm having a CMake project with dependencies which are pulled using FetchContent.
CMake creates build directories and cache files at build/_deps which are not cleared when running "Delete Cache and Reconfigure".
This usually breaks when the generator is changed (Make vs Ninja).
Steps to Reproduce:

Start of with a clean project
Add some external library with CMake support using FetchContent, for example:

FetchContent_Declare(cmrc
    URL "https://github.com/vector-of-bool/cmrc/archive/refs/tags/2.0.1.tar.gz"
    DOWNLOAD_EXTRACT_TIMESTAMP OFF
)
FetchContent_GetProperties(cmrc)
if (NOT cmrc_POPULATED)
    FetchContent_Populate(cmrc)
    add_subdirectory(${cmrc_SOURCE_DIR} ${cmrc_BINARY_DIR} EXCLUDE_FROM_ALL)
endif()

Declare at least two kits with different preferred generators (in my case auto-discovered MinGW with Make and Visual Studio with Ninja):

[
  {
    "name": "GCC 12.2.0 x86_64-w64-mingw32 (mingw64)",
    "compilers": {
      "C": "C:\\msys64\\mingw64\\bin\\gcc.exe",
      "CXX": "C:\\msys64\\mingw64\\bin\\g++.exe"
    },
    "isTrusted": true,
    "environmentVariables": {
      "CMT_MINGW_PATH": "C:\\msys64\\mingw64\\bin"
    },
    "preferredGenerator": {
      "name": "MinGW Makefiles"
    }
  },
  {
    "name": "Clang 15.0.1 (GNU CLI) for MSVC 17.5.33530.505 (Visual Studio Professional 2022 Release - amd64)",
    "visualStudio": "da53be4e",
    "visualStudioArchitecture": "x64",
    "compilers": {
      "C": "C:\\Program Files\\Microsoft Visual Studio\\2022\\Professional\\VC\\Tools\\Llvm\\x64\\bin\\clang.exe",
      "CXX": "C:\\Program Files\\Microsoft Visual Studio\\2022\\Professional\\VC\\Tools\\Llvm\\x64\\bin\\clang.exe"
    },
    "isTrusted": true
  }
]

Select one kit and configure project (no need to build), check that the library gets downloaded and configured at build/_deps
Select the other kit and configure project

As a workaround, I manually delete the _deps directory when reconfiguring.
CMake Tools Diagnostics
No response
Debug Log
No response
Additional Information
No response

This is very critical issue when dealing with multiple massive libraries. It must be resolved as soon as possible

#3783 This PR should have given a setting that resolves this, could you try the cmake.deleteBuildDirOnCleanConfigure setting?


add secret_token

https://core.telegram.org/bots/api#setwebhook
A secret token to be sent in a header “X-Telegram-Bot-Api-Secret-Token” in every webhook request, 1-256 characters. Only characters A-Z, a-z, 0-9, _ and - are allowed. The header is useful to ensure that the request comes from a webhook set by you.

?
!

Type
improvement

BC Break
no

Fixed issues

Summary

Please update quickly, it has affected my open-source project.

What do you mean by affected?

Thanks @jyxjjj :smiley:


rails generate interactor should create a spec or test file

The generator should also create an appropriate spec or test file.
We are fans of TDD here.

:+1:

:+1:

:+1:

Please review https://github.com/collectiveidea/interactor-rails/pull/11


Admin dashboard - Add comment field to admin profile show in the

It would be handy to have the admin comment field in the show view of the single profile:

https://github.com/rubymonsters/speakerinnen_liste/pull/745

Done


Visual Studio compilation errors with Unity

Hi,
when using with Unity (2021.3), it is no longer possible to debug with VS 2022 as it can't get past compilation errors related to UnitOf types. Surprisingly, I have 2 other generators (DefaultECS and VContainer) and those do not cause the issues. I've Added "C# Project Modifer" and added Roslyn Analyzers and still no luck. (again, interesting part is that 2 other generators cause no VS issues even without C# project modifier")

@slimshader Hi,
Sounds like a curios problem. but I could not reproduce it.
I created a project with Unity 2021.3.29f1 that included UnitGenerator.dl and Container.SourceGenerator.dll and both SourceGenerators worked.
Sorry but If the problem continues, could you please provide a detailed error log (and if possible a reproducible project)?
Thanks.

@hadashiA it is not about generators not working, it is about visual studio not seeing generated files, which results in errors (in Visual Studio) which blocks from possibility of attaching a debugger.

@slimshader
hmm, I tried again with Visual Studio 2022 (win) + Unity 2021.3.

But no compile errors were detected.

One possibility could be that your generate result code contains compile errors.
Since UnitGenerator does not perform detailed checks before generation, you need to check the generated code for errors.

For example, [UnitOf(typeof(DateTime), UnitGenerateOptions.ArithmeticOperator)] generates compilation errors.
You will probably get an error message, so try changing the UnitOf options, etc.

Also, you are right, I did not see the generated code in Visual Studio's Solution Explorer on my end.

However, I think this is not a problem with UnitGenerator.dll itself.
Other SourceGenerators has similar problems.
When I tried the same project in my environment, the generated code showed up.

It is difficult to investigate further here.
If you still suspect a UnitGenerator problem, please reopen with a reproduced project :)


Refactor required parameters

Closes #68

Since Parameters is now a map of Parameter I think that this check is not required anymore https://github.com/deislabs/cnab-go/blob/22ed003cf91e38449b08dfbf12ba1f5dc0f83344/bundle/bundle.go#L145


Cannot intall via NPM on Raspberry PI

Getting this error:
npm ERR! code ENOENT
npm ERR! syscall spawn git
npm ERR! path git
npm ERR! errno ENOENT
npm ERR! enoent Error while executing:
npm ERR! enoent undefined ls-remote -h -t<EMAIL_ADDRESS>npm ERR! enoent
npm ERR! enoent
npm ERR! enoent spawn git ENOENT
npm ERR! enoent This is related to npm not being able to find a file.

After running:
sudo -E -n npm install homebridge-broadlink-rm@latest

Resolved, you need git installed first: https://linuxize.com/post/how-to-install-git-on-raspberry-pi/


new code uses requireNamespace(package = INLAspacetime) leads to Error

8dd7068 introduced the use of requireNamespace(package = INLAspacetime) instead of require(package = INLAspacetime). Where, requireNamespace does not allow non-character objects being passed to the package argument. I am getting the following error when using the development version of INLA:
Error in as.character(package) :
  cannot coerce type 'closure' to vector of type 'character'

I am on a windows machine see `sessionInfo()` by expanding
sessionInfo()
R version 4.3.0 (2023-04-21 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.utf8
[2] LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8

time zone: America/Los_Angeles
tzcode source: internal

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
 [1] INLA_23.06.12          VAST_3.10.1            TMB_1.9.4
 [4] INLAspacetime_0.1.6    sp_1.6-1               Matrix_1.5-4.1
 [7] sablefish_<IP_ADDRESS>00   FishStatsUtils_2.12.1  marginaleffects_0.12.0
[10] units_0.8-2            testthat_3.1.8         devtools_2.4.5
[13] usethis_2.2.0

loaded via a namespace (and not attached):
 [1] DBI_1.1.3               remotes_2.4.2           rlang_1.1.1
 [4] magrittr_2.0.3          snakecase_0.11.0        e1071_1.7-13
 [7] compiler_4.3.0          systemfonts_1.0.4       callr_3.7.3
[10] vctrs_0.6.2             reshape2_1.4.4          stringr_1.5.0
[13] profvis_0.3.8           pkgconfig_2.0.3         crayon_1.5.2
[16] fastmap_1.1.1           ellipsis_0.3.2          labeling_0.4.2
[19] utf8_1.2.3              promises_<IP_ADDRESS>        sessioninfo_1.2.2
[22] ps_1.7.5                ragg_1.2.5              purrr_1.0.1
[25] cachem_1.0.8            jsonlite_1.8.5          pak_0.5.1
[28] later_1.3.1             parallel_4.3.0          prettyunits_1.1.1
[31] R6_2.5.1                stringi_1.7.12          pkgload_1.3.2
[34] brio_1.1.3              lubridate_1.9.2         Rcpp_1.0.10
[37] nwfscSurvey_2.1         httpuv_1.6.11           splines_4.3.0
[40] timechange_0.2.0        tidyselect_1.2.0        rnaturalearth_0.3.3
[43] rstudioapi_0.14         miniUI_<IP_ADDRESS>          curl_5.0.1
[46] processx_3.8.1          pkgbuild_1.4.0          lattice_0.21-8
[49] tibble_3.2.1            plyr_1.8.8              shiny_1.7.4
[52] withr_2.5.0             VASTWestCoast_1.1.6     splancs_2.01-43
[55] desc_1.4.2              sf_1.0-13               rnaturalearthdata_0.1.0
[58] proxy_0.4-27            urlchecker_1.0.1        pillar_1.9.0
[61] KernSmooth_2.23-21      generics_0.1.3          rprojroot_2.0.3
[64] ggplot2_3.4.2           munsell_0.5.0           scales_1.2.1
[67] rgdal_1.6-7             chron_2.3-61            xtable_1.8-4
[70] class_7.3-22            glue_1.6.2              janitor_2.2.0
[73] tools_4.3.0             data.table_1.14.8       RANN_2.6.1
[76] fs_1.6.2                cowplot_1.1.1           grid_4.3.0
[79] colorspace_2.1-0        cli_3.6.1               textshaping_0.3.6
[82] fansi_1.0.4             dplyr_1.1.2             gtable_0.3.3
[85] digest_0.6.31           classInt_0.4-9          htmlwidgets_1.6.2
[88] farver_2.1.1            memoise_2.0.1           htmltools_0.5.5
[91] lifecycle_1.0.3         httr_1.4.6              mime_0.12

And, I am using the development version because I have R 4.3 installed and there is no stable version for this version of R as of yet.

Ah, yes, my bad! As a temporary workaround, I think you can make local copy of the affected function and correct it to requireNamespace(“INLAspacetime”). I’ll fix the code today and hopefully there can be a new build soon.

Another possible workaround: create a variable in the global workspace:
INLAspacetime=“INLAspacetime”
I’m not sure if that will actually work, but it’s worth a try.


Error while trying API endpoint

Hi !
When I try to acceed https://api.astrocats.space/sne/catalog?format=CSV, an error is return : message: "Event 'sne' not found in any catalog."
I think that it is the same thing for all endpoint.
I don't know if i'm doing something wrong ?
Thank you !

This is an error in the docs given some recent back-end changes: the path is now https://api.astrocats.space/catalog/sne?format=CSV (sne and catalog are swapped).
I'll update the docs to reflect the current API paths.


Strange behaviour of QuadTree algorithm

I looked the example of guadtree and saw the strange behavior of the algorithm at the click position, as shown in the picture. The algorithm has returned all of the objects. Is that correct?

If the area being checked intersects more than one quad (as it does in the screen shot above) then it brings back all entries, as it's unable to fit inside a single quad. This is just the way the current quadtree implementation works I'm afraid. Technically it could be enhanced so that it determines which quads it intersects with first, and only then tests those - but that sort of goes against the nature of how it's designed.


Login using Google,Facebook,Github or Instagram dosen't work

Describe the bug
On the login page clicking on any of the options other than email login takes the user back to the same login page again.
Expected behavior
It is expected to show options to log in using the chosen option or media(eg : Google login, Github login etc)
Screenshots (Mandatory)

https://github.com/apu52/Travel_Website/assets/106834322/73de8a47-2ae4-4b30-8df9-a1ec9fa12572
Additional Context (Mandatory )
There should be options for users to login to the website using preexsiting google or Github accounts instead they are forced to use only one medium of login that is through their email.
Are you contributing under any open-source program ?
Yes GSSoC'24

i would like to work on this issue, can you please assign it to me...

Kindly assign me this issue, i would like to make this thing work

Kindly Assign this issue to me

I am ready to work on resolving the social media login issue. Please consider assigning this task to me. Thank you.

I am contributing under GSSOC'24. I am having good knowledge in web development projects. I think I can handle it. Could you please assign me this issue.

@Debarunn1806 Thanks for raising the issue . but #268 is already there. So I can't assign you this issue. But this is a really good issue. Thanks.
Sorry to close this issue.


Establish bazel.build support

Tracking issue for adding bazel.build support for istio mixer.

There is now full bazel.build coverage for the code in the current repo.  Marking issue as resolved.


Consulting services short description should include Microsoft 365

The description below covers all but one of the services listed in the full article, Microsoft 365. Suggest adding "Microsoft 365" to this list.

Consulting services help to connect customers with services to support and extend their use of Azure, Dynamics 365, or Power Suite services.

Below is a list of services outlined in the related article
Azure
Dynamics 365 Business Central
Dynamics 365 Commerce
Dynamics 365 Customer Insights
Dynamics 365 Customer Service
Dynamics 365 Field Service
Dynamics 365 Finance
Dynamics 365 Marketing
Dynamics 365 Project Service Automation
Dynamics 365 Sales
Dynamics 365 Supply Chain Management
Microsoft 365
Power Apps
Power Automate
Power BI
Power Virtual Agents

Document Details
⚠ Do not edit this section. It is required for learn.microsoft.com ➟ GitHub issue linking.

ID: aaa68fda-a8cc-848c-6e7f-dc5a6c55001a
Version Independent ID: 2de2fccc-02a4-9893-7be6-7f2f667347e1
Content: Publishing guide by offer type - Microsoft commercial marketplace
Content Source: articles/marketplace/publisher-guide-by-offer-type.md
Service: marketplace
Sub-service: partnercenter-marketplace-publisher
GitHub Login: @trkeya
Microsoft Alias: trkeya

@jonwbstr
Thanks for your feedback! We will investigate and update as appropriate.

@jonwbstr We have verified and updated the document as required. The update will go live in less than 24 hours. Thanks again for your feedback!


chore: Merge v2 branch into master and update README

Overview
Gatsby now has officially released version 2. 🎉
This library should now support version 2 by default, so the separate v2 branch can be merged to master.
As part of this PR, the README should also be updated to reflect the new behavior.
Optional: maybe add a peerDependencies attribute to package.json

@benjaminhoffman Don't forget your update 🌮

of course!  I'm moving apartments over the next week or so.  Once the dust settles I will be doing a thorough refresh of this plugin. Apologies for the delay!


Will deal with this tomorrow


Dockerfile: use cache-system provided by the rustc container

Quoting Scott (@outbackdingo):
Build the application.
Leverage a cache mount to /usr/local/cargo/registry/
for downloaded dependencies, a cache mount to /usr/local/cargo/git/db
for git repository dependencies, and a cache mount to /app/target/ for
compiled dependencies which will speed up subsequent builds.
Leverage a bind mount to the src directory to avoid having to copy the
source code into the container. Once built, copy the executable to an
output directory before the cache mounted /app/target is unmounted.
RUN --mount=type=bind,source=src,target=src
--mount=type=bind,source=Cargo.toml,target=Cargo.toml
--mount=type=bind,source=Cargo.lock,target=Cargo.lock
--mount=type=cache,target=/app/target/
--mount=type=cache,target=/usr/local/cargo/git/db
--mount=type=cache,target=/usr/local/cargo/registry/
cargo build --locked --release &&
cp ./target/release/$APP_NAME /bin/server

resolved by PR


classes on <body> are ignored

used html from https://gist.github.com/dym-cx/a7fdb47dc6d2fc076496

Sorry for the delay dealing with this issue! I just took a proper look, and the issue seems to be stemming from the fact that your  element is spelled incorrectly, as . Running your code through https://waterpigs.co.uk/php-mf2/ with a corrected  element results in correct parsing.
Handling of root classnames should be tag-independent, so this is still an issue for php-mf2. I suspect it is an internal issue with DOMDocument refusing to correctly parse HTML documents with incorrect  elements. Until we can fix that though, you can achieve correct parsing of this example by correcting the  element :)


Spec improvement

Hi solnic,
I added the possibility to run the shared adapter specs from dm-core, without modifications or local duplication. There is an other pull request on dm-core providing the configuration for this. Do not apply this unless the dm-core pull is accepted.
Warning: I updated the Gemfile to allow easy testing against a local dm-core checkout (using SOURCE=path bundle exec spec spec). I used dm-sqlite-adapter as a template, you should verify my changes.
Regards,
Markus

Im closing this request. Will merge it when dm-core supports adapter spec configuration.


reverse-i-search incorrectly overwrites characters

Steps to reproduce:

Type npm install and interrupt the process using ctrl+c to add it to history
ctrl+r
Type npm inst

gnome-terminal:

xterm.js:

Note that the cursor seems to be in the correct position but the characters aren't.

This got also fixed by #163.

@jerch nice :smiley:


Create _drafts folder if it does not exist

Thanks for writing up this compose tool. It was something I realized I wanted and was happy to see already existed! I noticed that running the draft command threw an error on a clean install and put together a fix. I updated the version number simply because it seemed like the thing to do.
When using the drafts command, if the _drafts folder does not already exist, create it. This prevents errors when running the draft command for the first time on Jekyll 2.5.3.
Before:
10:00:26 ~/projects/compose-test > jekyll draft "My New Draft"
jekyll 2.5.3 | Error:  No such file or directory @ rb_sysopen - _drafts/my-new-draft.md

After:
10:03:11 ~/projects/compose-test > jekyll draft "My New Draft"
New draft created at ./_drafts/my-new-draft.md.

Merged as 4b9ce9bb9bc83955165a0d5b7b71045d1466b9c5

https://github.com/jekyll/jekyll-compose/releases/tag/v0.2.1

Thanks!


Bump organization mgt version

$Subject

PR builder started
Link: https://github.com/wso2/product-is/actions/runs/4223156444

PR builder started
Link: https://github.com/wso2/product-is/actions/runs/4224633434

PR builder completed
Link: https://github.com/wso2/product-is/actions/runs/4224633434
Status: failure

bumped with https://github.com/wso2/product-is/commit/11b9062412538b3a1a051668123bc084060fd88d


Added an API tool to consume site endpoints

You might consider making the api it's own standalone swift package for scripts and other clients

@rodericj agreed


power on/off service for multiple cameras using the same nodelet manager.

Hi,
Just a quick question about using service call to power on/off the cameras. How does the service call work when there are multiple cameras running on the same nodelet manager?
It looks like the both camera try to advertise to /camera/force_power. Is it possible to have the service call per nodelet?

Hi @y27choi
Good catch. remapping needs to be added in "nodelet.launch.xml" file for set_power, force_power and is_powered services.
I have created pullrequest (#104) to add multi-camera support for these services.
For now, you can get required changes from the pullrequest or from "rjingar:set-power-multi-cam-support".
Thanks!

Fix in release 1.5.0
https://github.com/intel-ros/realsense/releases/tag/1.5.0


Upgrade to Dataverse 4.16

Upstream released v4.16, containing enhancements and new features. New images needed :smile:
Release notes mention two things, we will need a job for:

Re-export all citiations
Update a metadata block

The first one seems like packaging another maintenance job script.
The other one needs some more thinking about how to deal with metadata blocks.

Blocking issues for this release:
Merge #64 / #87
Merge #63 / #88
Merge #22 (needed for image builds & publishing on Hub as we want to move to Jenkins...)


Bump version to 0.3.1

Codecov Report

Merging #18 (eb4ba6d) into main (975af5e) will not change coverage.
The diff coverage is n/a.

@@            Coverage Diff            @@
##              main       #18   +/-   ##
=========================================
  Coverage   100.00%   100.00%
=========================================
  Files            5         5
  Lines          296       296
  Branches        73        73
=========================================
  Hits           296       296

Continue to review full report at Codecov.

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Fix lowering of mma.sync to nvvm for TF32

What happened?
when lowering mma.sync TF32 the inputs are currently f32 as we don't have TF32 as a native type. For now we should just cast from float32 to TF32 when lowering to nvvm dialect here.
What component(s) does this issue relate to?
MLIR

For a separate issue (#9394)[https://github.com/iree-org/iree/issues/9394] and LLVM patch, we have added an optional attribute tf32Enabled to allow the IR to be aware of MmaSyncOp input data type is TF32 and not F32. F32 input is converted to TF32 before MmaSyncOp. The conversion can follow different rounding modes.
For this issue, we need to check different rounding modes. The preferred rounding mode for float to tfloat32 is adding add (0.5ulp to integer representation then round toward zero)[https://github.com/NVIDIA/cutlass/blob/master/include/cutlass/numeric_conversion.h#L1576] and we have to check this part for this issue.


Support go 1.8

Will do when it's released

Opened pull request #73. Thank you.

Fixed by the above PR. Docker builds still running, should be online in a couple hours.


[Question]: ctx.send returns None. Is it right?

Yes, and you can request it using InteractionContext.request_original_response.

Thanks


Add the dice simulator game

Close #126
Type of change

[X] Added new project
[ ] Bug fix
[ ] New features
[ ] Enhanced documentation

Changes proposed in this pull request

Project name :

Dual Dice Simulator

Short description :

A simple python program which uses basic concepts to show a simulation of two dices on the screen with their valid output.
Checklist

[X] The code is Python 3 compatible
[X] I have added relevant comments in my file to make code understandable
[X] I have added my project in a folder which includes all the necessary files

@Mrinank-Bhowmick please review the pr.
I have added all the necessary info and media in the Readme of this project.

This will close #126 .

Looks good
Happy hacktoberfest 👍


so bad package

so useless package , not recommend its not offer any features

Hi @ Omarsalama2001, what features do you want when creating a menu?


2.1.1

Squashed further aborted bugs (#1 was more persistent, than we thought 😂). My other project, Fyrejet framework uses its own uWebSockets.js compatibility layer that was also based upon 0http's low server. Naturally, I wanted to replace that compatibility layer with low-http-server to maintain less code in the long-term. Unfortunately, express's tests that my other project uses revealed a regression with res.sendFile:

  1) res
       .sendFile(path)
         should not error if the client aborts:
     Uncaught Error: the string "Invalid access of discarded (invalid, deleted) uWS.HttpResponse/SSLHttpResponse." was thrown, throw an Error :)
      at process._fatalException (internal/process/execution.js:165:25)

That means aborted checks that we have here are NOT fully complete. This PR changes that.

Squashed header bugs. Fyrejet also uses some Restana's tests, since its core is based on Restana and it borrows Restana's res.send in certain operating modes. It is also possible this error might occur with unmodified Restana, but I haven't checked it yet. Unfortunately, it appears that sometimes, header contents may include header name. I don't like the fix, but it's the best I could think of.

  1) All Responses
       should GET 200 and html content on /html-string:
     Error: expected "content-type" of "text/html; charset=utf-8", got "content-type,text/html; charset=utf-8"
      at Test._assertHeader (node_modules/supertest/lib/test.js:249:12)
      at Test._assertFunction (node_modules/supertest/lib/test.js:283:11)
      at Test.assert (node_modules/supertest/lib/test.js:173:18)
      at localAssert (node_modules/supertest/lib/test.js:131:12)
      at /Volumes/Work/fyrejet/node_modules/supertest/lib/test.js:128:5
      at Test.Request.callback (node_modules/superagent/lib/node/index.js:716:12)
      at IncomingMessage.<anonymous> (node_modules/superagent/lib/node/index.js:916:18)
      at endReadableNT (_stream_readable.js:1221:12)
      at processTicksAndRejections (internal/process/task_queues.js:84:21)

Minor callback changes with facade.close and facade.listen funcs (for convenience).

@jkyberneees


Content Request: Add Filecoin governance, FIPS, etc. to Launchpad curriculum

Problem Description
Purpose
To provide an introduction to the FIP process and Filecoin governance for newbies. There are many important FIPs in flight right now: https://github.com/filecoin-project/FIPs/blob/master/FIPS/fip-0036.md and I think Launchpad is a good place to give someone an overview of how a FIP is created, how it's voted on, how it becomes implemented/rejected, etc.
Proposed Solution
A small portion of the curriculum dedicated to governance (in the form of a Q&A - a shallow/deep dive session)
Where Can we find out more about this topic?
https://github.com/filecoin-project/FIPs
Acceptance Criteria
Launchpad cohort get introduction to governance/FIPs via Launchpad shallow/deep dive session.

Relevant to #211


installation error

I just installed react-native-snap-carosuel,
copied the provided example in Usage part.
I got this long error:
Invariant Violation: ViewPropTypes has been removed from React Native. Migrate to ViewPropTypes exported from 'deprecated-react-native-prop-types'.
at node_modules\react-native\Libraries\Core\ExceptionsManager.js:null in reportException
at node_modules\react-native\Libraries\Core\ExceptionsManager.js:null in handleException
at node_modules\react-native\Libraries\Core\setUpErrorHandling.js:null in handleError
at node_modules\expo\build\errors\ExpoErrorManager.js:null in errorHandler
at node_modules\expo\build\errors\ExpoErrorManager.js:null in <anonymous>
at node_modules\@react-native\polyfills\error-guard.js:null in ErrorUtils.reportFatalError
at node_modules\metro-runtime\src\polyfills\require.js:null in guardedLoadModule
at http://<IP_ADDRESS>:19001/node_modules%5Cexpo%5CAppEntry.bundle?platform=android&dev=true&hot=false&strict=false&minify=false:null in global code

Invariant Violation: Failed to call into JavaScript module method AppRegistry.runApplication(). Module has not been registered as callable. Registered callable JavaScript modules (n = 11): Systrace, JSTimers, HeapCapture, SamplingProfiler, RCTLog, RCTDeviceEventEmitter, RCTNativeAppEventEmitter, GlobalPerformanceLogger, JSDevSupportModule, HMRClient, RCTEventEmitter.
        A frequent cause of the error is that the application entry file path is incorrect. This can also happen when the JS bundle is corrupt or there is an early initialization error when loading React Native.
at node_modules\react-native\Libraries\Core\ExceptionsManager.js:null in reportException
at node_modules\react-native\Libraries\Core\ExceptionsManager.js:null in handleException
at node_modules\react-native\Libraries\Core\setUpErrorHandling.js:null in handleError
at node_modules\expo\build\errors\ExpoErrorManager.js:null in errorHandler
at node_modules\expo\build\errors\ExpoErrorManager.js:null in <anonymous>
at node_modules\@react-native\polyfills\error-guard.js:null in ErrorUtils.reportFatalError
at node_modules\react-native\Libraries\BatchedBridge\MessageQueue.js:null in __guard
at node_modules\react-native\Libraries\BatchedBridge\MessageQueue.js:null in callFunctionReturnFlushedQueue

Invariant Violation: Failed to call into JavaScript module method AppRegistry.runApplication(). Module has not been registered as callable. Registered callable JavaScript modules (n = 11): Systrace, JSTimers, HeapCapture, SamplingProfiler, RCTLog, RCTDeviceEventEmitter, RCTNativeAppEventEmitter, GlobalPerformanceLogger, JSDevSupportModule, HMRClient, RCTEventEmitter.
        A frequent cause of the error is that the application entry file path is incorrect. This can also happen when the JS bundle is corrupt or there is an early initialization error when loading React Native.
at node_modules\react-native\Libraries\Core\ExceptionsManager.js:null in reportException
at node_modules\react-native\Libraries\Core\ExceptionsManager.js:null in handleException
at node_modules\react-native\Libraries\Core\setUpErrorHandling.js:null in handleError
at node_modules\expo\build\errors\ExpoErrorManager.js:null in errorHandler
at node_modules\expo\build\errors\ExpoErrorManager.js:null in <anonymous>
at node_modules\@react-native\polyfills\error-guard.js:null in ErrorUtils.reportFatalError
at node_modules\react-native\Libraries\BatchedBridge\MessageQueue.js:null in __guard
at node_modules\react-native\Libraries\BatchedBridge\MessageQueue.js:null in callFunctionReturnFlushedQueue

I also tried the example: https://snack.expo.io/@vitkor/carousel-simple-example
got this error:
Invariant Violation: ViewPropTypes has been removed from React Native. Migrate to ViewPropTypes exported from 'deprecated-react-native-prop-types'.
at node_modules\expo\build\environment\react-native-logs.fx.js:null in error
at node_modules\react-native\Libraries\Core\ExceptionsManager.js:null in reportException
at node_modules\react-native\Libraries\Core\ExceptionsManager.js:null in handleException
at node_modules\react-native\Libraries\Core\setUpErrorHandling.js:null in handleError
at node_modules\expo\build\errors\ExpoErrorManager.js:null in errorHandler
at node_modules\expo\build\errors\ExpoErrorManager.js:null in <anonymous>
at node_modules\@react-native\polyfills\error-guard.js:null in ErrorUtils.reportFatalError
at node_modules\metro-runtime\src\polyfills\require.js:null in guardedLoadModule
at http://<IP_ADDRESS>:19002/node_modules%5Cexpo%5CAppEntry.bundle?platform=android&dev=true&hot=false&strict=false&minify=false:null in global code

Invariant Violation: "main" has not been registered. This can happen if:
* Metro (the local dev server) is run from the wrong folder. Check if Metro is running, stop it and restart it in the current project.
* A module failed to load due to an error and `AppRegistry.registerComponent` wasn't called.
at node_modules\expo\build\environment\react-native-logs.fx.js:null in error
at node_modules\react-native\Libraries\Core\ExceptionsManager.js:null in reportException
at node_modules\react-native\Libraries\Core\ExceptionsManager.js:null in handleException
at node_modules\react-native\Libraries\Core\setUpErrorHandling.js:null in handleError
at node_modules\expo\build\errors\ExpoErrorManager.js:null in errorHandler
at node_modules\expo\build\errors\ExpoErrorManager.js:null in <anonymous>
at node_modules\@react-native\polyfills\error-guard.js:null in ErrorUtils.reportFatalError
at node_modules\react-native\Libraries\BatchedBridge\MessageQueue.js:null in __guard
at node_modules\react-native\Libraries\BatchedBridge\MessageQueue.js:null in callFunctionReturnFlushedQueue

I really want to use the library, anyone can help me out?

Any update on this?


[Feature Request] Customizable Line Offset

I would like to change the line origin x offset (and maybe y as well) to be closer to the center of the screen, since the projectiles are fired from the middle of the head, instead of the hands, which will make it easier to track close targets and it is aesthetically better from third person view.

I would also like this. Hitting mobs and close targets would be much easier with the line originating from somewhere closer to the center, even if it looks a bit odd.


Extension issue

Issue Type: Bug
Extension Name: azure-pipelines
Extension Version: 1.165.1
OS Version: Windows_NT x64 10.0.18363
VSCode version: 1.44.0-insider

:warning: We have written the needed data into your clipboard. Please paste! :warning:

Not enough info to take action


Release 2.0

Is there nothing else we want to do before ?

There's no other 2.0 wishlist issues, which is specifically a list of breaking changes that we wanted to make (which was the whole point of releasing 2.0).
If there's something else you'd like to do before releasing 2.0, please say what it is!

I don't have anything in mind, just asking :p

bors r+

Sorry. Found one other bug in the changelog. Hit it again.

bors r= @Eijebong


Scripts open and close powershell very fast

I can't even read the error. I right click on the script and hit run in powershell. This is on W11.

Yes, in desktop mode when the script execution reaches "exit", the terminal window closes automatically. Would be nice to have this configurable.
As a workaround just insert a "pause" line before the "exit" line in the script.

Turns out this is a GPO setting on my end. They want me to make scripts but will need to make it so I can actually run them lol.

Don't mess with security 😄 Thx for your feedback 👍

Closed now.


Model Description
This model should be used to provide information on the current status of a shipment for tracking and tracing of the shipment. It can be used to send different status updates.
Relevant Standards

Example Data
{
"actualBusinessTimestamp": "2022-11-11T01:00:00Z",
"actualTechnicalTimestamp": "2022-11-11T01:00:00Z",
"transportInfo": {
"transportNumber": "testTP25012024",
"dangerousGoods": false,
"meansOfTransport": 31
},
"statusUpdate": "NOT_STARTED",
"estimatedTimestamps": {
"estimateArrival": "2024-01-25T16:55:00Z",
"estimateDispatch": "2024-01-21T14:35:00Z"
},
"registrationInfo": {
"registrationCountry": "DE",
"registrationNumber": "D-RA-KL-8136"
},
"trackedObjects": "['obj1', 'obj2', 'obj3']",
"serviceAgentId": {
"forwardingAgentId": 13245,
"haulerId": 12345
},
"arrivalInfo": {
"locationType": "DistributionCenter",
"proofOfDelivery": true,
"locationName": "Mercedes-Benz Untertürkheim Plant",
"locationId": 12345678
},
"shipmentNumber": "testSHP25012024",
"departureInfo": {
"locationType": "DistributionCenter",
"locationId": 12345678,
"locationName": "Mercedes-Benz Untertürkheim Plant"
}
}
MS1 Criteria

[ ] The proposed aspect model does not exist already
[ ] The proposed aspect model does not extend an existing aspect but introduces completely new functionality
[ ] The proposal references a Catena-X use case
[ ] Relevant standards are mentioned/linked
[ ] A first draft of the data structure is provided in an example
[ ] A modeling steward has been assigned

FYI: @johannsvarela @jonbckr @jacewski-bosch


Make 'Export PCK/ZIP' work well with EditorExportPlugin

Fixed EditorExportPlugin::_export_begin notification not being called when exporting to android.
Made 'Export PCK/ZIP' notify when the export process begins, which is needed to receive the EditorExportPlugin::_export_begin callback.
Added a debug flag to the 'Export PCK/ZIP' option. It's the same checkbox as in the 'Export Project' dialog.

This feature is needed for the mono module to determine the Configuration to build the project with. It may be useful for other languages as well.

Cherry picked into 3.0.3