Show details on map (like points of interest or roads directions)

Congratulations for the good work!
I've started using this plugin because i needed rotation in my map and better fidelity to polilyne routes.  To this objective, the plugin worked like a charm!
But I noticed that a lot of data that is present in my custom Mapbox theme is not displayed on the map:
Mapbox Preview of my Theme

My Map in the app

Looks like the only thing that the plugin is getting of my theme is the color.
I have defined the TileProvider as:
tileProviders: TileProviders({
            'composite': MemoryCacheVectorTileProvider(
              delegate: NetworkVectorTileProvider(
                maximumZoom: 22,
                urlTemplate:
                    'https://api.mapbox.com/v4/mapbox.mapbox-streets-v8/{z}/{x}/{y}.mvt?style=mapbox://styles/petize/cl0thnp3q00oj15o8qbsin9z0@2022-10-13T13:30:58.076Z&access_token=$apiKey',
              ),
              maxSizeBytes: 1024 * 1024 * 2,
            ),
          }),

When I've seen issues like this before, it's either because the theme used doesn't match the tile data, or there are expressions in the theme that aren't supported by this library.
I've had Mapbox streets working before, see the gallery
To troubleshoot the theme, consider adding a logger to the theme, e.g. ThemeReader(Logger.console()).read(theme)
Consider providing an example that we can look into here or a copy of your theme on this ticket.

Thanks for the reply!
Today, i've noticed that the names of the points of interest are now appearing in the map without the icons. Road directions are still missing.
I've added the logger and the result was:
WARN: Unsupported expression syntax: [to-number, [get, sizerank]]
I/flutter ( 6434): WARN: Unsupported expression syntax: [>=, [to-number, [get, sizerank]], 0]
I/flutter ( 6434): WARN: Unsupported expression syntax: [all, [>=, [to-number, [get, sizerank]], 0], [match, [get, class], [park, airport, glacier, pitch, sand, facility], true, residential, [step, [zoom], true, 12, false], false], [<=, [-, [to-number, [get, sizerank]], [interpolate, [exponential, 1.5], [zoom], 12, 0, 18, 14]], 14]]
I/flutter ( 6434): WARN: Unsupported expression: [all, [>=, [to-number, [get, sizerank]], 0], [match, [get, class], [park, airport, glacier, pitch, sand, facility], true, residential, [step, [zoom], true, 12, false], false], [<=, [-, [to-number, [get, sizerank]], [interpolate, [exponential, 1.5], [zoom], 12, 0, 18, 14]], 14]]
I/flutter ( 6434): WARN: theme layer type circle not implemented
I/flutter ( 6434): WARN: theme layer type circle not implemented

So i guess that the problem is what you've said, "expressions in the theme that aren't supported by this library". But can i do something to show at least road directions? My theme json is hosted here and it was created by Mapbox Studio.

Thanks for the detail.
Icons aren't supported yet. I'm not sure what you mean by "road directions"?
For to-number you need this https://github.com/greensopinion/dart-vector-tile-renderer/pull/69

I meant those arrows in the first image showing the traffic direction of the road. But you said that icons aren't supported yet and i guess that's an icon.
I'm closing this issue, thanks for the help and keep the good work :).

I've started working on support for sprites here:

https://github.com/greensopinion/dart-vector-tile-renderer/pull/83
https://github.com/greensopinion/flutter-vector-map-tiles/pull/142

this is a screenshot based on the Mapbox Streets style.
in the screenshot we have:

line-based icon-image
scaling to fit content (text)
point-based icon-image

Wow! Looks great. Can't wait to have it released! 👏

There are still a few issues to resolve:

one-way arrows aren't placed on roads with Mapbox Streets - not sure why

MapTiler icons aren't scaled to size to the text content (yet) because their sprite.json doesn't include content or  placeholder indicating where the content should go. There must be some way to differentiate between sprites used to indicate a point (which should not be scaled) and sprites used for road numbers (which should be scaled), but so far I haven't figured it out.

Maptiler has sprites represented in their json as follows:
    "us-interstate_3": {
        "width": 44,
        "height": 36,
        "x": 38,
        "y": 278,
        "pixelRatio": 2.0
    }

Mapbox specifies placeholder for the same sprite:
    "us-interstate-3": {
        "width": 52,
        "height": 44,
        "x": 286,
        "y": 436,
        "pixelRatio": 2,
        "placeholder": [
            0,
            16,
            52,
            28
        ],
        "visible": true
    }

this is the spec: https://docs.mapbox.com/mapbox-gl-js/style-spec/sprite/
Any help on this would be appreciated. For next steps, I'm thinking that we should reach out to Maptiler and ask them, or have a look a one of the existing open source libraries (such as maplibre.org) to find out what they do.

May I ask what the status on this feature is? The sprite symbols are not showing on my vector tile layer similar to how they appear in maputnik.


Upgrade RPC client to use hyper v0.13 + async/await

The RPC client presently uses a synchronous blocking I/O-based approach, built on a now ancient hyper v0.10 as the HTTP client.
Upstream hyper is just about to land tokio v0.2 support: https://github.com/hyperium/hyper/issues/2025
...and soon thereafter, will hopefully have a v0.13 release with stable-ish async/await.
When that happens, it'd be great to update the RPC client to use it.

I got this to almost compile locally. The problem now is the RPC client needs bytes v0.5, which is incompatible with prost:
error[E0277]: the trait bound `B: bytes::buf::buf::Buf` is not satisfied
   --> tendermint/src/validator.rs:118:28
    |
118 | #[derive(Clone, PartialEq, Message)]
    |                            ^^^^^^^ the trait `bytes::buf::buf::Buf` is not implemented for `B`
    |
   ::: /Users/bascule/.cargo/registry/src/github.com-1ecc6299db9ec823/prost-amino-0.4.0/src/encoding.rs:53:75
    |
53  | pub fn decode_varint<B>(buf: &mut B) -> Result<u64, DecodeError> where B: Buf {
    |                                                                           --- required by this bound in `prost::encoding::decode_varint`
    |
    = help: consider adding a `where B: bytes::buf::buf::Buf` bound

error: aborting due to 107 previous errors

...so we need to split apart RPC into a separate crate which can depend on bytes v0.5

Looks like upgrading prost (and then prost-amino) to use bytes v0.5 is on the way, too: https://github.com/danburkert/prost/issues/242#issuecomment-560245502

I did find a workaround that doesn't involve splitting the RPC client into a separate crate... I can pull in 2 versions of bytes and give one of them a different name.
However, I'm running into some pretty weird type errors trying to convert the various methods into async fn. I can push up my WIP.

I did find a workaround that doesn't involve splitting the RPC client into a separate crate...

Cool!

I can push up my WIP.

It would be interesting to peek into an early (draft) PR!

WIP here: https://github.com/interchainio/tendermint-rs/pull/85

done in #85


Disable Mac0 and Sign1 code if requested

Fixing issue #111

See my comments in #111. Recent commits for HMAC for OpenSSL and for test return codes might have some relevance here.


Warning: Failed prop type: The prop "aria-label" is marked as required in Grid, but its value is undefined after update from v9.21.2 to 9.22.0

Bug Report
Warning: Failed prop type: The prop `"aria-label"` is marked as required in `Grid`, but its value is `undefined`.
    in Grid (created by List)
    in List (created by Styled(List))
    in Styled(List) (created by AutoSizer)
    in div (created by AutoSizer)
    in AutoSizer (created by Geschaefte)
    in ErrorBoundary (created by MyErrorBoundary)
    in MyErrorBoundary (created by Geschaefte)
    in div (created by styled.div)
    in styled.div (created by Geschaefte)
    in div (created by styled.div)
    in styled.div (created by Geschaefte)
    in div (created by styled.div)
    in styled.div (created by Geschaefte)
    in ErrorBoundary (created by MyErrorBoundary)
    in MyErrorBoundary (created by Geschaefte)
    in Geschaefte (created by GeschaefteLayout)
    in div (created by Pane)
    in Pane (created by SplitPane)
    in div (created by SplitPane)
    in SplitPane (created by Styled(SplitPane))
    in Styled(SplitPane) (created by GeschaefteLayout)
    in GeschaefteLayout (created by App)
    in App
printWarning @ checkPropTypes.js:20
checkPropTypes @ checkPropTypes.js:82
validatePropTypes @ react.development.js:1714
createElementWithValidation @ react.development.js:1813
render @ List.js:228
finishClassComponent @ react-dom.development.js:17160
updateClassComponent @ react-dom.development.js:17110
beginWork @ react-dom.development.js:18620
beginWork$1 @ react-dom.development.js:23179
performUnitOfWork @ react-dom.development.js:22157
workLoopSync @ react-dom.development.js:22130
performSyncWorkOnRoot @ react-dom.development.js:21756
scheduleUpdateOnFiber @ react-dom.development.js:21188
updateContainer @ react-dom.development.js:24373
(anonymous) @ react-dom.development.js:24758
unbatchedUpdates @ react-dom.development.js:21903
legacyRenderSubtreeIntoContainer @ react-dom.development.js:24757
render @ react-dom.development.js:24840
_callee$ @ index.js:31
u @ exceljs.min.js:3
(anonymous) @ exceljs.min.js:3
forEach.e.<computed> @ exceljs.min.js:3
asyncGeneratorStep @ index.js:193350
_next @ index.js:193352
Promise.then (async)
asyncGeneratorStep @ index.js:193350
_next @ index.js:193352
(anonymous) @ index.js:193352
(anonymous) @ index.js:193352
run @ index.js:13
./src/index.js @ index.js:39
__webpack_require__ @ bootstrap:789
fn @ bootstrap:100
0 @ index.js:196538
__webpack_require__ @ bootstrap:789
(anonymous) @ bootstrap:856
(anonymous) @ bootstrap:856

See Sandbox: https://codesandbox.io/s/react-virtualized-list-with-width-100-6wbkh
What is the current behavior?
Above warning occurs.
What is the expected behavior?
No warning, as in v9.21.2
Which versions of React and react-virtualized, and which browser / OS are affected by this issue? Did this work in previous versions of react-virtualized?

Browser
chrome up to date

OS
windows 10

React
16.13.1

React DOM
16.13.1

react-virtualized
9.22.0

Also seeing this with the MultiGrid

Related: https://github.com/brigand/babel-plugin-flow-react-proptypes/issues/219
should be fixed by updating babel-plugin-flow-react-proptypes to 26.0.0

@wuweiweiwu I don't have babel-plugin-flow-react-proptypes as an enabled babel plugin and i get this very same issue. Can this be investigated further?

@while-rising-ltd

I don't have babel-plugin-flow-react-proptypes

react-virtualized itself does use it, that's the problem

should be fixed by updating babel-plugin-flow-react-proptypes to 26.0.0

Got you - thought you were imply that anyone who sees that should update to that themselves.
I'll try 9.22.1, thanks for the clarification

should be fixed by updating babel-plugin-flow-react-proptypes to 26.0.0

Got you now... thought you were imply that anyone who sees that should update to that themselves.
I'll try 9.22.1, thanks for the clarification


net: fix references to stack buffers

The net_stack_analyze function wants to look at the stack buffer,
but it is making assumptions on where this data is that are no
longer valid. Change to use the proper APIs for referencing this.
Signed-off-by: Andrew Boie<EMAIL_ADDRESS>

Tested successfully w/ new LwM2M client (which was previously page faulting): https://github.com/zephyrproject-rtos/zephyr/pull/712

Note: there are further patches I am working on that will detect this situation at build time, so we won't be surprised again.


tests/format/variables.py: Adding test for special "notparallel"

This branch fixes Node._composite() so that mutable data in the source nodes are no longer given away to the composite target, leaving the source vulnerable to later mutations when the target is mutated. Instead clones of source values are provided when they are composited onto a target node.

Is this really sufficient case to trigger the bug? Don't you need to have multiple elements, some of which are not parallel and some which are?

Is this really sufficient case to trigger the bug? Don't you need to have multiple elements, some of which are not parallel and some which are? I think @abderrahim was at least saying the issue is some variable is pre-expanded that shouldn't be.

Not yet, no.

Is this really sufficient case to trigger the bug? Don't you need to have multiple elements, some of which are not parallel and some which are? I think @abderrahim was at least saying the issue is some variable is pre-expanded that shouldn't be.

Not yet, no.

This has now been updated to properly trigger the bug.

And this merge request has now been updated to include both the test case and the fix for the underlying composition issue.
@BenjaminSchubert, can you take a look at this ?

We’ve got some kind of github bug, the CI actions appear to be randomly getting cancelled :(


Add more data to receiver object on /api/v2/receiver

What did you do?
I made a request to /api/v2/receivers and only saw and array with objects containing the receiver's names and that's it.
What did you expect to see?
I expect to see basically the array filled with objects containing all data that the Alertmanager has of receivers.
More specifically, I'm looking for {"webhook_configs": {"url": "http://..."}} for each receiver.
Instead I now get the config from /api/v2/status and parse it to get the receivers full data...
Environment

System information:
Kubernetes

Alertmanager version:
0.21.0

Prometheus version:
2.23.0

Now I'm wondering if that's so sparse on purpose or if we can add this to the API endpoint. :)

I don't think this is not possible since this could leak secrets.

Interesting. Yes, I suspected something along those lines.
However, the config itself needs to be sanitized too, so generally speaking that should be possible with this too, shouldn't it? :thinking:

We do not render the config as json but in a big text field in json.

Yep. Just used that part at it earlier.
I think it should be possible to do something similar with these data types before handing them over to the swagger generated parts.
https://github.com/prometheus/alertmanager/blob/d57b2dcdeca9164d873fdba4c7129320db4a3cf6/config/config.go#L48-L68
For now I'm fine with just parsing the config YAML I get from the status API. I was just wondering if this would be accepted in general. :)

At least not in the same API endpoint as this would be a breaking change.
Note that I also already considered doing this (parsing the yaml). I don't remember if I ended up really doing it.

I guess it works for me for now, so I don't have any hard feelings about this right now. Closing for now.


Reimplement GC for new storage model + preparation to support non-rel objects

Based on the results of our discussions, I removed special fork numbers
and introduce ObjectTag/ObjectValue enums which allows to support multiple object types.
Storage API was extended by list_objects() and unlink() methods, on top of which storage independent GC  was implemented.

@knizhnik , FYI. I've force pushed rebase to master to trigger CI.
Overall this PR looks great. Now it's clear what types of objects we have.
I think this code should have more comments. I am adding them now.

Can you split this into two PRs, please?

Fix the GC code
Add support for non-rel object types

The first is pretty straightforward, but second is a bit hard to review without seeing the rest of the work.

There is almost no support for non-rel objects in this branch. Just enums value reserved for them.

There is almost no support for non-rel objects in this branch. Just enums value reserved for them.

Most of interface changes where BufferTag is replaced with ObjectTag are caused by that. And I can see some special code to handle two-phase objects in the garbage collection code.
At a quick glance I think those BufferTag->ObjectTag changes will need some more thinking. For example, what does it mean to pass a ObjectTag::RelationMetadata(RelTag) key to put_wal_record? It doesn't make sense to me, but the interface allows it. So I want to review that more closely, and I don't want those discussions to hold up the GC changes. Or vice versa. That's why I'd like to see these as it two separate commits and separate PRs. Makes for a nicer git history too, if we need to look back.

I created yet another branch gc_only

We discussed this pr with @knizhnik and decided to wait with it until nonrel_wal lands in main

Splitting this into two pr's:
PR for non-rel wal: https://github.com/zenithdb/zenith/pull/227
PR for GC (on hold while non-rel isn't merged): https://github.com/zenithdb/zenith/pull/223


fix error on remove items in settings due to signal vector model

fixes an access violation (null) when removing items in settings menu

What are some things that crashed before but does not crash now?

@pajlada removing a highlight phrase

@pajlada removing a highlight phrase

I'm unable to reproduce the issue on Windows and Linux, is there anything more specific you need to do to experience the crash?

i just got nightly, used the debug build and got the crashes on removing it, its probably something about having a different kind of settings json file or inconsistency in it, anyways this check is always correct against crashes (read out of bounds) and its only on the delete functions, so it shouldnt even be a bottleneck at all, it could fix some crashes for some, and do nothing detrimental anyways, ergo i believe it should be put in anyways

would be nice to see what could cause it, do you mind posting your config - personal stuff?

@apa420 tried removing everything in %appdata% folder and then the steps, still crashed, guess it wasnt in the files (since they got auto regernerated)

maybe it depends on qt version, mine is 5.11.0 atm
(5.12.3 didnt like the custom title bar

and added the windows on top of it )

So does the nightly crash?
Or only the version you built yourself?

nightly downloaded from releases with everything in %appdata%/chatterino2 deleted, crashes @apa420

What even is the purpose of that assert? Shouldnt it just be an if and return NoItemFlags instead?

Shouldnt it just use https://doc.qt.io/qt-5/qmodelindex.html#isValid


feat: Add .ansible-lint

Add ansible-lint config file. Ansible Lint is a command-line tool for linting playbooks, roles and collections aimed toward any Ansible users. Its main goal is to promote proven practices, patterns and behaviors while avoiding common pitfalls that can easily lead to bugs or make code harder to maintain.
Signed-off-by: Klaus Smolin<EMAIL_ADDRESS>

:tada: This PR is included in version 1.0.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


Support PSR-17

We should support https://www.php-fig.org/psr/psr-17/

It appears #27 attempts to add this.
Is there an issue with this implementation?

I forgot that #27 was in the queue!


Help please: ran into installation error RUNTIME ERROR: couldn't open import "grafana/grafana.libsonnet": no match locally or in the Jsonnet library paths

Problem:
When running bash build.sh example.jsonnet, error occured:
RUNTIME ERROR: couldn't open import "grafana/grafana.libsonnet": no match locally or in the Jsonnet library paths
vendor/kube-prometheus/kube-prometheus.libsonnet:5:2-36 $
example.jsonnet:2:4-54  thunk  from <$>
example.jsonnet:16:86-88
:1293:24-25        thunk from <function >
:1293:5-33 function
example.jsonnet:16:69-104       $
    During evaluation

What did you do?
Run the installation steps as per instruction
jb init
jb install<EMAIL_ADDRESS>jb update
bash build.sh example.jsonnet
Did you expect to see some different?
Manifest folder populated with yaml configs
Environment
OS: windows using cygwin

The grafana/grafana.libsonnet file is coming from a symlink to github.com/brancz/kubernetes-grafana/grafana. Your error might have been caused by either jb failing to download kubernetes-grafana or the symlink creation failed during the installation.
Either way you might solve your problem by reinstalling kube-prometheus, but it sure sounds weird that you did not get any errors during the previous steps. While reinstalling kube-prometheus would your mind checking that kubernetes-grafana installation succeeds? You should see the following log line when running jb install/update:
GET https://github.com/brancz/kubernetes-grafana/archive/*.tar.gz 200

And verify that a symlink gets created under vendor/grafana pointing to github.com/brancz/kubernetes-grafana/grafana.

The jb downloaded the zip files. However, there are subsequent command of clean
GET https://github.com/coreos/kube-prometheus/archive/5c63bde4f45c3afe09c9cf0d4dd2651c444c5e5c.tar.gz 200
GET https://github.com/ksonnet/ksonnet-lib/archive/0d2f82676817bbf9e4acf6495b2090205f323b9f.tar.gz 200
GET https://github.com/kubernetes-monitoring/kubernetes-mixin/archive/7bf9a2a321356a7625509fe458132c26b2e33b29.tar.gz 200
GET https://github.com/brancz/kubernetes-grafana/archive/57b4365eacda291b82e0d55ba7eec573a8198dda.tar.gz 200
GET https://github.com/coreos/prometheus-operator/archive/8c85526acc078aa391c24139a8e3ac6b0a5fcabc.tar.gz 200
GET https://github.com/coreos/etcd/archive/09fcf55ca498ade69f4ceb5b3c6afc2930f3621f.tar.gz 200
GET https://github.com/prometheus/prometheus/archive/18d9ebf0ffc26b8bd0e136f552c8e9886d29ade4.tar.gz 200
GET https://github.com/prometheus/node_exporter/archive/02532771213fcb024608043d7b1e514c1a80c2da.tar.gz 200
GET https://github.com/grafana/jsonnet-libs/archive/b9cc0f3529833096c043084c04bc7b3562a134c4.tar.gz 200
GET https://github.com/kubernetes-monitoring/kubernetes-mixin/archive/4626a8d0dd261dbefa91d9d60cf8bc8240bd053f.tar.gz 200
GET https://github.com/grafana/grafonnet-lib/archive/7ab8a79738de007c407b939b35e54e84c213d542.tar.gz 200
GET https://github.com/metalmatze/slo-libsonnet/archive/9baab703bb8a55f990f3b6a74c80987036938f64.tar.gz 200
CLEAN C:\main\repos\Exp-Monitoring\my-kube-prometheus\vendor\github.com\brancz\kubernetes-grafana\grafana
CLEAN C:\main\repos\Exp-Monitoring\my-kube-prometheus\vendor\github.com\coreos\etcd\Documentation
CLEAN C:\main\repos\Exp-Monitoring\my-kube-prometheus\vendor\github.com\coreos\etcd\Documentation\etcd-mixin
CLEAN C:\main\repos\Exp-Monitoring\my-kube-prometheus\vendor\github.com\coreos\prometheus-operator\jsonnet
CLEAN C:\main\repos\Exp-Monitoring\my-kube-prometheus\vendor\github.com\coreos\prometheus-operator\jsonnet\prometheus-operator
CLEAN C:\main\repos\Exp-Monitoring\my-kube-prometheus\vendor\github.com\grafana\grafonnet-lib\grafonnet
CLEAN C:\main\repos\Exp-Monitoring\my-kube-prometheus\vendor\github.com\grafana\jsonnet-libs\grafana-builder
CLEAN C:\main\repos\Exp-Monitoring\my-kube-prometheus\vendor\github.com\metalmatze\slo-libsonnet\slo-libsonnet
CLEAN C:\main\repos\Exp-Monitoring\my-kube-prometheus\vendor\github.com\prometheus\node_exporter\docs
CLEAN C:\main\repos\Exp-Monitoring\my-kube-prometheus\vendor\github.com\prometheus\node_exporter\docs\node-mixin
CLEAN C:\main\repos\Exp-Monitoring\my-kube-prometheus\vendor\github.com\prometheus\node_exporter\docs\node-mixin\alerts
CLEAN C:\main\repos\Exp-Monitoring\my-kube-prometheus\vendor\github.com\prometheus\node_exporter\docs\node-mixin\dashboards
CLEAN C:\main\repos\Exp-Monitoring\my-kube-prometheus\vendor\github.com\prometheus\node_exporter\docs\node-mixin\rules
CLEAN C:\main\repos\Exp-Monitoring\my-kube-prometheus\vendor\github.com\prometheus\prometheus\documentation
CLEAN C:\main\repos\Exp-Monitoring\my-kube-prometheus\vendor\github.com\prometheus\prometheus\documentation\prometheus-mixin
I checked the vendor folder only below folders have contents
vendor\github.com\coreos\kube-prometheus\jsonnet\kube-prometheus
vendor\github.com\ksonnet\ksonnet-lib
vendor\github.com\kubernetes-monitoring\kubernetes-mixin
The symlink are created, but because only above folders have content, only below symlink works
ksonnet
kube-prometheus
kubernetes-mixin
promgrafonnet
The other symlinks don't work. Since the grafana folder is empty, the grafana symlink doesn't work
Could this be an issue in the jb tool that when cleaning the folder?
I checked the jsonnet file
https://github.com/coreos/kube-prometheus/blob/release-0.4/jsonnet/kube-prometheus/jsonnetfile.json
ksonnet and kubernetes-mixin have empty subdir, while others specify subdir, which cause the jb to skip these two in clean command.
However, those with subdir specified was cleaned and because I am in windows the folder notation is '' different with linux/mac '/'. Jb tool fail to identify the subdir and clean the whole content?
Could this be the issue?

Create PR for jb
https://github.com/jsonnet-bundler/jsonnet-bundler/pull/114

Yes, it sure sounds like an issue in the way jsonnet bundler handles windows paths.
Thanks for digging this out and opening a follow-up PR in jb :slightly_smiling_face:.

No probs :)


Added json output

Hi
while I was searching through github I found your amazing project.
In the TODO notes I found the output to json so I decided to try adding it myself.
hope it helps a bit :)

@joeavanzato I think this is a good step in the right direction but I think there are a couple things that could be updated to make the user experience a bit better. I will leave my thoughts on specific lines of code so they can be a bit more coherent

I dont know if i understand correctly but do i understand correctly that we should make both SnapshotPath  and SnapShotFormat mandatory fields with a possibility to choose a folder (in Path) and Format  (csv / json) ?
I dont fully understand whats the difference between snapshot and output and here if i understand corectly the idea is to connect this two into one?
I will try to make fixes to the code as soon as i fully understand your will 😄

Let me start another PR to show you what my vision is

Closing this as this same effect is being achieved through https://github.com/joeavanzato/Trawler/pull/66 in a cleaner way.  I also want to update detections to take full advantage of potential JSON output moving forward.


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Provide a description that is worded well enough to be understood
Original Site : Voot.com | Series and movies
Updated Site : Jiocinema.com
Command : yt-dlp -f bestvideo*+bestaudio/best -u<EMAIL_ADDRESS>-p password -v https://www.voot.com/shows/comedy-nights-with-kapil/100145
Conclusion : Videos are being downloaded but contain just a disclaimer "x site has been shifted to y site."
Updated for the same required in order to scrape per se.
//voot.com domain traversing to jiocinema.com
Provide verbose output that clearly demonstrates the problem

[X] Run your yt-dlp command with -vU flag added (yt-dlp -vU <your command line>)
[ ] If using API, add 'verbose': True to YoutubeDL params instead
[X] Copy the WHOLE output (starting with [debug] Command-line config) and insert it below

Complete Verbose Output
root@DietPi:/mnt/samba/Media/temp# yt-dlp -f bestvideo*+bestaudio/best -u<EMAIL_ADDRESS>-p password -v https://www.voot.com/shows/comedy-nights-with-kapil/100145
[debug] Command-line config: ['-f', 'bestvideo*+bestaudio/best', '-u', 'PRIVATE', '-p', 'PRIVATE', '-v', 'https://www.voot.com/shows/comedy-nights-with-kapil/100145']
[debug] Encodings: locale UTF-8, fs utf-8, pref UTF-8, out utf-8, error utf-8, screen utf-8
[debug] yt-dlp version<EMAIL_ADDRESS>[812cdfa06] (pip)
[debug] Python 3.9.2 (CPython x86_64 64bit) - Linux-5.10.0-23-amd64-x86_64-with-glibc2.31 (OpenSSL 1.1.1n  15 Mar 2022, glibc 2.31)
[debug] exe versions: ffmpeg 4.3.6-0, ffprobe 4.3.6-0
[debug] Optional libraries: Cryptodome-3.18.0, brotli-1.0.9, certifi-2023.05.07, mutagen-1.46.0, sqlite3-2.6.0, websockets-11.0.3
[debug] Proxy map: {}
[debug] Loaded 1851 extractors
[VootSeries] Checking username
[VootSeries] Logging in
[VootSeries] Extracting URL: https://www.voot.com/shows/comedy-nights-with-kapil/100145
[download] Downloading playlist: 100145
[VootSeries] 100145: Downloading JSON metadata
[VootSeries] 360559: Downloading JSON metadata page 1
[VootSeries] 360559: Downloading JSON metadata page 2
[VootSeries] 360559: Downloading JSON metadata page 3
[VootSeries] 360559: Downloading JSON metadata page 4
[VootSeries] 360559: Downloading JSON metadata page 5
[VootSeries] 360559: Downloading JSON metadata page 6
[VootSeries] 360559: Downloading JSON metadata page 7
[VootSeries] 360559: Downloading JSON metadata page 8
[VootSeries] 360559: Downloading JSON metadata page 9
[VootSeries] 360559: Downloading JSON metadata page 10
[VootSeries] 360559: Downloading JSON metadata page 11
[VootSeries] 360559: Downloading JSON metadata page 12
[VootSeries] 360559: Downloading JSON metadata page 13
[VootSeries] 360559: Downloading JSON metadata page 14
[VootSeries] 360559: Downloading JSON metadata page 15
[VootSeries] 360559: Downloading JSON metadata page 16
[VootSeries] 360559: Downloading JSON metadata page 17
[VootSeries] 360559: Downloading JSON metadata page 18
[VootSeries] 360559: Downloading JSON metadata page 19
[VootSeries] 360559: Downloading JSON metadata page 20
[VootSeries] 360559: Downloading JSON metadata page 21
[VootSeries] Playlist 100145: Downloading 193 items of 193
[download] Downloading item 1 of 193
[Voot] Extracting URL: voot:350153
[Voot] 350153: Downloading JSON metadata
[Voot] 350153: Downloading playback JSON
[Voot] 350153: Downloading m3u8 information
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] 350153: Downloading 1 format(s): hls-2571
[debug] Invoking hlsnative downloader on "https://jiostreaminghls.akamaized.net/bpkvod/vod/aes128/64b535bb27be89c6f187c370_v1/64b535bb27be89c6f187c370_v1/64b535bb27be89c6f187c370_v1-audio_hin=125375-video=2300000.m3u8"
[hlsnative] Downloading m3u8 manifest
[hlsnative] Total fragments: 4
[download] Destination: Kapil introduces his family [350153].mp4
[download] 100% of    4.52MiB in 00:00:02 at 1.51MiB/s
[debug] ffprobe command line: ffprobe -hide_banner -show_format -show_streams -print_format json 'file:Kapil introduces his family [350153].mp4'
[debug] ffmpeg command line: ffprobe -show_streams 'file:Kapil introduces his family [350153].mp4'
[FixupM3u8] Fixing MPEG-TS in MP4 container of "Kapil introduces his family [350153].mp4"
[debug] ffmpeg command line: ffmpeg -y -loglevel repeat+info -i 'file:Kapil introduces his family [350153].mp4' -map 0 -dn -ignore_unknown -c copy -f mp4 -bsf:a aac_adtstoasc -movflags +faststart 'file:Kapil introduces his family [350153].temp.mp4'
[download] Downloading item 2 of 193
[Voot] Extracting URL: voot:350168
[Voot] 350168: Downloading JSON metadata
[Voot] 350168: Downloading playback JSON
[Voot] 350168: Downloading m3u8 information
[debug] Formats sorted by: hasvid, ie_pref, lang, quality, res, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, size, br, asr, proto, vext, aext, hasaud, source, id
[info] 350168: Downloading 1 format(s): hls-2571
[debug] Invoking hlsnative downloader on "https://jiostreaminghls.akamaized.net/bpkvod/vod/aes128/64b535bb27be89c6f187c370_v1/64b535bb27be89c6f187c370_v1/64b535bb27be89c6f187c370_v1-audio_hin=125375-video=2300000.m3u8"
[hlsnative] Downloading m3u8 manifest
[hlsnative] Total fragments: 4
[download] Destination: Kapil Sharma goes 'Ghanchakkar' [350168].mp4
[download] 100% of    4.52MiB in 00:00:02 at 1.53MiB/s
[debug] ffprobe command line: ffprobe -hide_banner -show_format -show_streams -print_format json 'file:Kapil Sharma goes '"'"'Ghanchakkar'"'"' [350168].mp4'
[debug] ffmpeg command line: ffprobe -show_streams 'file:Kapil Sharma goes '"'"'Ghanchakkar'"'"' [350168].mp4'
[FixupM3u8] Fixing MPEG-TS in MP4 container of "Kapil Sharma goes 'Ghanchakkar' [350168].mp4"
[debug] ffmpeg command line: ffmpeg -y -loglevel repeat+info -i 'file:Kapil Sharma goes '"'"'Ghanchakkar'"'"' [350168].mp4' -map 0 -dn -ignore_unknown -c copy -f mp4 -bsf:a aac_adtstoasc -movflags +faststart 'file:Kapil Sharma goes '"'"'Ghanchakkar'"'"' [350168].temp.mp4'

Not applicable.

It's mandatory for a reason. Show logs with an example URL

Not applicable.

It's mandatory for a reason. Show logs with an example URL

Updated.
Disclaimer image :

The output for all the json pages involve 4-5 sec. video showcasing the disclaimer.
Note : The username and password used by me is the one created on voot when the domain was available , can't create a new user too for testing.

The log is incomplete
The posted URL does not lead to a video

I got that. But I assume you are asking to support the new jiocinema links - which you haven't provided. Or did you just want us to disable the extractor?

I got that. But I assume you are asking to support the new jiocinema links - which you haven't provided. Or did you just want us to disable the extractor?

Yes, I am asking for the new jiocinema links as well as to disable the voot sites as an update for the supported sites and the extractor in the next version.

Related #5563

Can you show where the equivalent of https://www.voot.com/shows/comedy-nights-with-kapil/100145 is found on the jio cinema site?

Site : https://www.jiocinema.com/tv-shows/comedy-nights-with-kapil/3499729
A technical issue from jiocinema company which is they haven't updated all the episodes and have a lot of missing episodes in certain tv shows for which I have reported.


gammick, flippance

This pull request was generated by the 'mq' tool
[test]
flake rate: 0.4
logical conflict every: 100
sleep for: 300s
[pullrequest]
requests per hour: 30
deps=[f,g]

/trunk merge


RuntimeError: cublas runtime error : resource allocation failed at THCGeneral.cpp:250

Any ideas on resolving this issue would be greatly appreciated!
GPU details: Tesla K80 (8 GPUs), NVIDIA-SMI 410.79, Driver Version: 410.79, CUDA Version: 10.0
I was trying to run it on a single GPU alone first (local_rank = -1), and faced the below error.
ERROR:ignite.engine.engine.Engine:Current run is terminating due to exception: cublas runtime error : resource allocation failed at /opt/conda/conda-bld/pytorch_1544199946412/work/aten/src/THC/THCGeneral.cpp:250.
ERROR:ignite.engine.engine.Engine:Engine run is terminating due to exception: cublas runtime error : resource allocation failed at /opt/conda/conda-bld/pytorch_1544199946412/work/aten/src/THC/THCGeneral.cpp:250.
Traceback (most recent call last):
  File "train.py", line 358, in <module>
    train()
  File "train.py", line 349, in train
    trainer.run(train_loader, max_epochs=args.n_epochs)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 388, in run
    self._handle_exception(e)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 352, in _handle_exception
    raise e
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 375, in run
    hours, mins, secs = self._run_once_on_dataset()
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 341, in _run_once_on_dataset
    self._handle_exception(e)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 352, in _handle_exception
    raise e
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 333, in _run_once_on_dataset
    self.state.output = self._process_function(self, batch)
  File "train.py", line 275, in update
    lm_loss, mc_loss = model(*batch)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/pytorch_pretrained_bert/modeling_openai.py", line 808, in forward
    hidden_states = self.transformer(input_ids, position_ids, token_type_ids)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/pytorch_pretrained_bert/modeling_openai.py", line 643, in forward
    hidden_states = block(hidden_states)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/pytorch_pretrained_bert/modeling_openai.py", line 334, in forward
    a = self.attn(x)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/pytorch_pretrained_bert/modeling_openai.py", line 297, in forward
    x = self.c_attn(x)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/pytorch_pretrained_bert/modeling_openai.py", line 248, in forward
    x = torch.addmm(self.bias, x.view(-1, x.size(-1)), self.weight)
RuntimeError: cublas runtime error : resource allocation failed at /opt/conda/conda-bld/pytorch_1544199946412/work/aten/src/THC/THCGeneral.cpp:250

I also tried multi-GPU by doing python -m torch.distributed.launch --nproc_per_node=8 train.py <my cmdline options> and it threw the same error.

Since the above stacktrace ends at the torch.addmm() call happening in modeling_openai.py, I hypothesized that perhaps the addmm() op doesn't play well with the pytorch_p36 env in my EC2 instance. So I tried to reproduce the above RuntimeError in the interpreter in the instance (with the pytorch_p36 env activated).
>>> import torch
>>> a = torch.randn(2,3)
>>> b = torch.randn(3,2)
>>> c = torch.randn(2,2)
>>> x = torch.addmm(c,a,b)

The above worked perfectly fine. So I do not think the issue is due to the addmm() op itself, but I'm confused how to proceed.

I printed the shapes of the tensors self.bias , x.view(-1, x.size(-1))  and self.weight  right before the above failure in the forward pass. The shapes were torch.Size([2304]), torch.Size([12560, 768]) and torch.Size([768, 2304]) respectively.
So I did the following test:
>>> a = torch.randn(2304).cuda()
>>> b = torch.randn(12560, 768).cuda()
>>> c = torch.randn(768, 2304).cuda()
>>> a.shape
torch.Size([2304])
>>> b.shape
torch.Size([12560, 768])
>>> c.shape
torch.Size([768, 2304])
>>> x = torch.addmm(a,b,c)
>>>

The above test worked fine - no CUDA resource allocation errors. So I really am clueless at this point.

@thomwolf do you have any thoughts?

You can try with:

a batch size of 1 to be sure you are not just out-of-memory
CUDA_LAUNCH_BLOCKING=1 before the python train.py to be sure where the error comes from

I already tried with a batch size of 1. The tensors were smaller in shape,
but the exact same error repeated.
On Thu, May 23, 2019, 11:46 PM Thomas Wolf<EMAIL_ADDRESS>wrote:

You can try with:

a batch size of 1 to be sure you are not just out-of-memory
CUDA_LAUNCH_BLOCKING=1 before the python train.py to be sure where
the error comes from

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and with CUDA_LAUNCH_BLOCKING=1, What exact error message do you get?

@thomwolf here's a part of the error I get with that flag set:
/opt/conda/conda-bld/pytorch_1544199946412/work/aten/src/THC/THCTensorIndex.cu:362: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [85,0,0], thread: [27,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/opt/conda/conda-bld/pytorch_1544199946412/work/aten/src/THC/THCTensorIndex.cu:362: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [85,0,0], thread: [28,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/opt/conda/conda-bld/pytorch_1544199946412/work/aten/src/THC/THCTensorIndex.cu:362: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [85,0,0], thread: [29,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/opt/conda/conda-bld/pytorch_1544199946412/work/aten/src/THC/THCTensorIndex.cu:362: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [85,0,0], thread: [30,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
/opt/conda/conda-bld/pytorch_1544199946412/work/aten/src/THC/THCTensorIndex.cu:362: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [85,0,0], thread: [31,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
ERROR:ignite.engine.engine.Engine:Current run is terminating due to exception: CUDA error: device-side assert triggered.
ERROR:ignite.engine.engine.Engine:Engine run is terminating due to exception: CUDA error: device-side assert triggered.
Traceback (most recent call last):
  File "train.py", line 358, in <module>
    train()
  File "train.py", line 349, in train
    trainer.run(train_loader, max_epochs=args.n_epochs)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 388, in run
    self._handle_exception(e)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 352, in _handle_exception
    raise e
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 375, in run
    hours, mins, secs = self._run_once_on_dataset()
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 341, in _run_once_on_dataset
    self._handle_exception(e)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 352, in _handle_exception
    raise e
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 333, in _run_once_on_dataset
    self.state.output = self._process_function(self, batch)
  File "train.py", line 275, in update
    lm_loss, mc_loss = model(*batch)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/pytorch_pretrained_bert/modeling_openai.py", line 811, in forward
    hidden_states = self.transformer(input_ids, position_ids, token_type_ids)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/pytorch_pretrained_bert/modeling_openai.py", line 639, in forward
    token_type_embeds = self.tokens_embed(token_type_ids)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/nn/modules/sparse.py", line 118, in forward
    self.norm_type, self.scale_grad_by_freq, self.sparse)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/nn/functional.py", line 1454, in embedding
    return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
RuntimeError: CUDA error: device-side assert triggered

@thomwolf any thoughts on this? thanks!

Okay, I think the reason I'm facing these embedding matrix index out of bounds errors is that my dataset has really long utterances and the default config in OpenAIGPTConfig (like n_positions=512) is insufficient to handle the utterances in my dataset.

@thomwolf I think I have figured this out. Let me know what you think.
https://github.com/huggingface/transfer-learning-conv-ai/blob/b7f295f840f719056287504554083ec3f2688651/train.py#L55
If len(instance["input_ids"]) above is greater than 512 (which is the default value of n_positions in OpenAIGPTConfig in modeling_openai.py in pytorch-pretrained-bert), then the position_ids created in the below link will contain values much larger than 512.
https://github.com/huggingface/pytorch-pretrained-BERT/blob/372a5c1ceec49b52c503707e9657bfaae7c236a0/pytorch_pretrained_bert/modeling_openai.py#L620
Consequently, this line (https://github.com/huggingface/pytorch-pretrained-BERT/blob/372a5c1ceec49b52c503707e9657bfaae7c236a0/pytorch_pretrained_bert/modeling_openai.py#L633) will fail.
I think you need to add truncation logic for the sequence above prior to doing instance["input_ids"] = list(chain(*sequence)) so that the length is always less than or equal to 512.

I added some truncation code and managed to resolve the error corresponding to the previous stack trace. But I'm now facing a different stack trace (with CUDA_LAUNCH_BLOCKING=1):
/opt/conda/conda-bld/pytorch_1556653099582/work/aten/src/THC/THCTensorIndex.cu:362: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 2, SrcDim = 2, IdxDim = -2, IndexIsMajor = true]: block: [637,0,0], thread: [63,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
ERROR:ignite.engine.engine.Engine:Current run is terminating due to exception: CUDA error: device-side assert triggered.
ERROR:ignite.engine.engine.Engine:Engine run is terminating due to exception: CUDA error: device-side assert triggered.
Traceback (most recent call last):
  File "train.py", line 376, in <module>
    train()
  File "train.py", line 367, in train
    trainer.run(train_loader, max_epochs=args.n_epochs)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 388, in run
    self._handle_exception(e)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 352, in _handle_exception
    raise e
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 375, in run
    hours, mins, secs = self._run_once_on_dataset()
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 341, in _run_once_on_dataset
    self._handle_exception(e)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 352, in _handle_exception
    raise e
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/ignite/engine/engine.py", line 333, in _run_once_on_dataset
    self.state.output = self._process_function(self, batch)
  File "train.py", line 293, in update
    lm_loss, mc_loss = model(*batch)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/nn/modules/module.py", line 493, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/nn/parallel/distributed.py", line 376, in forward
    output = self.module(*inputs[0], **kwargs[0])
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/nn/modules/module.py", line 493, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/pytorch_pretrained_bert/modeling_openai.py", line 808, in forward
    hidden_states = self.transformer(input_ids, position_ids, token_type_ids)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/torch/nn/modules/module.py", line 493, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/ec2-user/anaconda3/envs/pytorch_p36/lib/python3.6/site-packages/pytorch_pretrained_bert/modeling_openai.py", line 641, in forward
    hidden_states = inputs_embeds + position_embeds + token_type_embeds
RuntimeError: CUDA error: device-side assert triggered

As a quick next step, I'm going to print the shapes of inputs_embeds, position_embeds and token_type_embeds to see if they're all the same shape.

Not sure why I got the above failure, but things seem to be working fine now.

@g-karthik I think the device-side assert error triggered is due to the position embedding which is limited to 512 in size and your input size dimension sequence length is greater than that in the training loader

@sashank06 yes that is correct, I had realized it back then after a bunch of debugging, and I forgot to update this issue! Thanks for the reminder!

@sashank06 yes that is correct, I had realized it back then after a bunch of debugging, and I forgot to update this issue! Thanks for the reminder!

How did you do the truncation? I mean wouldn't there be loss of information if we just omit the words > 512 length?

@geekygirl123 You can do the truncation of individual components of your input_ids, while ensuring len(input_ids) <= 512 for GPT. For example, you can truncate the dialog context to comprise just the recent turns.
Yes, there would be a loss of information if you truncated the dialog context this way, but it is something you could live with from a perf-POV.

Had the same problem. My strategy was to pop history items up to a minimum of one item, and then history items up to a minimum of one item, until the sequence length was 512 or lower.

@ioannist, @g-karthik, or anyone else who managed to make their truncation work, could you share the code with me? I'm unable to make the truncation work despite the lengths of each of the elements in the sequence being truncated to 512.
I tried a simple slice:
sequence[0] = sequence[0][:512]
sequence[1] = sequence[1][:512]
sequence[2] = sequence[2][:512]

but that didn't seem to work. I also tried a number of other things, but I was mainly fumbling around in the dark. Any pointers or code for this?
Thanks in advance!


Request:  screenshot creation for google play console new app

Could you create a random or from file screenshot generator with right play console format ?

Can you describe a bit more what you're trying to achieve?


[rttr] fixed rttr not building on windows (#3263)

Hi,
this fixes #3263 on windows.
The problem is that the script ports/rttr/portfile.cmake tries to remove executables (from previous builds i'd guess) which are stored in ${REL_EXES} and ${DBG_EXES}. Since those cmake vars are empty on first build, file gets just the REMOVE argument but no actual files, and cmake doens't like that.

Thanks!


[Fix][API] Log dependency package conflict

Tips

Thanks very much for contributing to Apache DolphinScheduler.
Please review https://dolphinscheduler.apache.org/en-us/community/index.html before opening a pull request.

What is the purpose of the pull request
Fix log dependency package conflict (slf4j-log4j12、logback)
Brief change log
Add exclusion for slf4j-log4j12
Verify this pull request
This pull request is code cleanup without any test coverage.

@qiaozhanwei

@dailidong Waiting for request to merged

thanks for your first contribution, looking forward for your deep participation, please contact me(wechat: 510570367 or mail: dailidong66@gmail.com), when added, please tell me your github id, thx


feat: implement flux tools

@camiloaz @dillonalaird some results

Generate code for green hair prompt
resp = agent.chat_with_artifacts(
    [
        {
            "role": "user",
            "content": "put a green hair on the person",
            "media": ["data/image.png"],
        }
    ],
    artifacts=artifacts,
    test_multi_plan=False,
)

print()
print(resp)
``

```python
import os
import numpy as np
from vision_agent.tools import *
from typing import *
from pillow_heif import register_heif_opener
register_heif_opener()
import vision_agent as va
from vision_agent.tools import register_tool

from vision_agent.tools import load_image, florence2_sam2_image, flux_image_inpainting, save_image
import numpy as np

def add_green_hair(image_path):
    # Load the image
    image = load_image(image_path)
    height, width = image.shape[:2]

    # Detect and segment the person
    detections = florence2_sam2_image("person", image)

    if not detections:
        raise ValueError("No person detected in the image.")

    # Use the first detected person (assuming there's only one main person in the image)
    person = detections[0]
    person_mask = person['mask']

    # Create a mask for the hair area (upper 20% of the person's bounding box)
    hair_mask = np.zeros_like(person_mask, dtype=np.uint8)
    bbox = person['bbox']
    hair_height = int(0.2 * (bbox[3] - bbox[1]) * height)
    hair_top = int(bbox[1] * height)
    hair_bottom = hair_top + hair_height
    hair_left = int(bbox[0] * width)
    hair_right = int(bbox[2] * width)

    hair_mask[hair_top:hair_bottom, hair_left:hair_right] = person_mask[hair_top:hair_bottom, hair_left:hair_right]

    # Convert the binary mask to the required format (0 for preserved areas, 255 for areas to be inpainted)
    inpaint_mask = np.where(hair_mask == 1, 255, 0).astype(np.uint8)

    # Use flux_image_inpainting to add green hair
    prompt = "person with bright green hair, realistic"
    inpainted_images = flux_image_inpainting(prompt, image, inpaint_mask)

    if not inpainted_images:
        raise ValueError("Image inpainting failed.")

    # Get the first (and only) inpainted image
    result_image = inpainted_images[0]

    # Save the resulting image
    output_path = "person_with_green_hair.png"
    save_image(result_image, output_path)

    return output_path

# The function can be called like this:
# result_path = add_green_hair("/home/hugohonda/Developer/test-vision-agent/data/image.png")
# print(f"Image with green hair saved to: {result_path}")
``

resp = agent.chat_with_artifacts(
    [
        {
            "role": "user",
            "content": "put a blonde moustache",
            "media": ["data/image.png"],
        }
    ],
    artifacts=artifacts,
    test_multi_plan=False,
)

print()
print(resp)

import os
import numpy as np
from vision_agent.tools import *
from typing import *
from pillow_heif import register_heif_opener
register_heif_opener()
import vision_agent as va
from vision_agent.tools import register_tool

from vision_agent.tools import load_image, florence2_sam2_image, flux_image_inpainting, save_image
import numpy as np

def add_blonde_mustache(image_path):
    # Load the image
    image = load_image(image_path)
    height, width = image.shape[:2]

    # Detect the face in the image
    face_detections = florence2_sam2_image("face", image)

    if not face_detections:
        raise ValueError("No face detected in the image.")

    # Get the first detected face (assuming there's only one face)
    face = face_detections[0]
    face_mask = face['mask']

    # Create a mask for the upper lip area
    upper_lip_mask = np.zeros_like(face_mask, dtype=np.uint8)
    face_bbox = face['bbox']

    # Calculate the upper lip region (approximately 1/3 of the lower half of the face)
    lip_top = int(face_bbox[1] * height + (face_bbox[3] - face_bbox[1]) * height * 2/3)
    lip_bottom = int(face_bbox[1] * height + (face_bbox[3] - face_bbox[1]) * height * 5/6)
    lip_left = int(face_bbox[0] * width)
    lip_right = int(face_bbox[2] * width)

    upper_lip_mask[lip_top:lip_bottom, lip_left:lip_right] = 255

    # Combine the face mask with the upper lip mask
    final_mask = np.logical_and(face_mask, upper_lip_mask).astype(np.uint8) * 255

    # Use image inpainting to add the blonde mustache
    inpainted_images = flux_image_inpainting(
        prompt="realistic blonde mustache",
        image=image,
        mask_image=final_mask,
        height=height,
        width=width
    )

    # Get the first (and only) inpainted image
    result_image = inpainted_images[0]

    # Save the resulting image
    output_path = "image_with_blonde_mustache.png"
    save_image(result_image, output_path)

    return output_path

# The function can be called like this:
result = add_blonde_mustache("/home/hugohonda/Developer/test-vision-agent/data/image.png")
print(f"Image with blonde mustache saved to: {result}")


chore: expose validator key funcs, increase gas

oh it's on self hosted that needs to be moved to ubuntu-latest before merge


How to get the File from uri got in ActivityResult?

i am getting the uri in ActivityResult,
is there any way to get the file or file path above android 10?
Also getting rotated image when capturing from camera, any solution of this?

@nishu3389 Why do you need a File from Uri? If you need it for file upload, Let me know which library you are using so I will suggest appropriate solutions for the same. My recommendation is to use Uri to better support scope storage.
The possible solution is to copy Uri to an app-specific folder and access it using the File object. But why should we do extra processing when things can be done using Uri.

@Dhaval2404 Will using the extension function in core-ktx do the trick in converting the Uri to File? I'm looking to upload the file via retrofit

You must have created RequestBody from the File object before uploading using a retrofit.
Previous implementation:
val fileBody = file.asRequestBody(getMimeType(file).toMediaTypeOrNull())
val params = HashMap<String, RequestBody>()
// file = your image upload field name
params["file\"; filename=\"${file.name}\""] =  fileBody

Here is the minor change into that:
val fileName = InputStreamRequestBody.getFileName(context, uri)
val params = HashMap<String, RequestBody>()
// file = your image upload field name
params["file\"; filename=\"${fileName}\""] =  InputStreamRequestBody(context, uri)

You can find the InputStreamRequestBody class from the below link:
https://gist.github.com/Dhaval2404/f73442b8e584beb9243b465d7b22e2fa
Let me know if you have any trouble implementing this solution.

"The possible solution is to copy Uri to an app-specific folder and access it using the File object. But why should we do extra processing when things can be done using Uri."
it will be great if you implement this process into your library in case we really need the file object.
Thanks :)


Hotfix: calculate_perpendicular_baselines() now returns ASFSearchResults

3.2.1
Fixed

ASFProduct.stack() and asf_search.baseline_search.stack_from_id() now return ASFSearchResults instead of a list

Codecov Report

Merging #96 (80a87bc) into stable (5652d0c) will not change coverage.
The diff coverage is 100.00%.

@@           Coverage Diff           @@
##           stable      #96   +/-   ##
=======================================
  Coverage   83.97%   83.97%
=======================================
  Files          29       29
  Lines         705      705
=======================================
  Hits          592      592
  Misses        113      113

Flag
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unittests
83.97% <100.00%> (ø)

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96.42% <100.00%> (ø)

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The link "Using Atlas at Netflix" does not work

Thanks for the report, I'll remove it as the information is specific to our setup. If you are looking for general details it is covered in some of the presentations and the overview page.


Output figure label even if figure has no caption

... Because figures with no captions are still numbered.

But do not output labels for figures if they contain subfigures


Validate the codeql-action workspace for common errors

This PR will automatically debug common issues with CodeQL workspaces.

[x] Validate the current workflow looking for common CodeQL gotchas
[ ] Find a way to feed back the messages to the user
[ ] Test with a range of broken workflows

In an ideal world, I would love if I could get the actions scheduler to pass in the current workflow file as GITHUB_WORKFLOW_FILE. This would make introspection easier, running the action locally easier and save two API requests

This gives you output like:

Definitely a win :)

Chris G and I did some spelunking through Launch, Actions Service and Runner to see how hard it would be to add the workflow file feature.
To get the converstation started, I opened a PR here: https://github.com/github/launch/pull/3540
It contains a write up of everything that I learned.
The TLDR is, the launch team don't think anyone else is asking for this. They suggested I open an issue against runner to see if anyone else in the community has similar requirements.


Update in-meeting app readme

@zyxiaoyuer Please help review, thanks

please resolve the comments in line

@summzhan  Thanks for reviewing this, I have pushed a new commit and fix the readme


Fix already configured contributed tasks

Fixes #97134

When a user configures a task, we select that task in the tasks.json so it's easy to find. We find the task by label.
However, extension contributed task that are configured in tasks.json aren't required to have a label, making them difficult to find.
When the tasks.json is parsed for tasks, we do keep track of the position of the task in the tasks array, so instead of using the label, we should use that and only fall back to the label if something goes wrong.


Guidelines for clinical electrophysiology research data

During the iEEG-BIDS and EEG-BIDS extensions, several issues were raised for storing large medical research electrophysiology datasets. We started a google doc to address some of these questions and incorporate the answers in a set of guidelines in the bids-starter-kit wiki. These guidelines should provide tools and best practices for structuring clinical electrophysiology research data in BIDS.
Clinical electrophysiology research involves machine learning methods and standard processing steps, such as epileptic spike detection, seizure detection, sleep staging, artifact rejection and visualization. These guidelines hope to make sure that there are standard recommendations and tools for medical electrophysiology research data and accompanying metadata that BIDS apps can run on and form a bridge with the medical community.
This is an effort together with Jan Cimbalnik @cimbi

@dorahermes
should I include what's already in this google doc on the starter kit and point to the google doc to explain that this is a work in progress?

OK closing then


SFB 2015 on-premise without hybrid configuration

We are currently running SFB 2015 on-premise and do not mind the migration to cloud voicemail, but not able to configure hybrid configuration (at this time).  The article states that this is mandatory.  Is there a work around to use cloud voicemail without a hybrid configuration?

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

ID: 63f7281d-e17d-c4e8-ced8-f4d695785e6c
Version Independent ID: 40876324-10aa-e412-e1c2-868d1be2b9b1
Content: Exchange Unified Messaging Online migration support
Content Source: Skype/SfBServer2019/plan/exchange-unified-messaging-online-migration-support.md
Product: skype-for-business-itpro
GitHub Login: @heidip
Microsoft Alias: heidip

Unfortunately not. Without DirSync the CVM (online) service can not discover the mailboxes of the users receiving voicemails.

@DBailey618 Thank you for submitting this feedback.
From our understanding the issue has been resolved. If you feel it hasn't been resolved please re-open this issue.

@officedocsbot close


fix(workflow): do we have the correct sem-rel tokens set now

This PR is included in version 1.0.10 :tada:


Focus follows mouse set to autofocus sometimes fails to remove focus

To reproduce the bug: set ffm to autofocus, open two windows of the same application, move the cursor between them. Sometimes both will look like they're focused, but neither will receive keyboard inputs.
I notice this very often with applications that take a while to gain focus when clicking on them, especially with Chrome.

mouse_follows_focus can be on or off, right?
Did you set mff on and ffm autofocus?

Sorry—I must've mistyped mff instead of ffm when I opened this issue. Corrected the original post and title. Should've been obvious though as there's an ffm option named autofocus and mff only toggles on/off, just like you said.

I was having a very similar issue, but unfortunately have had a difficulty time making it fully reproducable.
This issue happens for me most often in chrome. For me the issue is:
Occasionally when moving quickly between two windows of the same application (most often Chrome, occasionally this has also happened between iTerm windows), a number of my shortcut keys (eg. cmd+C, cmd+V, cmd+F) stop working entirely. Whenever I notice this happening, I can still normally type in the window, but certain actions become frozen or do not appear to work.
Once I move my cursor into the other window, I see the "edit" menu button (in the top menubar) light up blew and start blinking several times, as if to batch process all of the cmd+C and cmd+V keypresses that were being frozen.
The result is that a bunch of text in the new window has been copied and pasted several times over, from my several failed attempts to copy and paste a different set of text in the previous window.
I will keep attempting to consistently reproduce this error, and will report back once I find anything.

I can no longer reproduce this after the latest changes. Closing.


Column level lineage

Describe the feature
Currently have table/view level lineage captured, can this be extended to field/column based?
Additional context
Not specific to a database, applies to the product.
Who will this benefit?
There could be multiple renames to a field and with multiple joins the complexity to track field level changes and source of a particular column becomes difficult. From an Ops perspective it always good to know where a field is coming from to quickly solve data issues.

@dataexpertz-blr Thanks for opening, I'm surprised there wasn't already an issue for this :) It's something we're hearing and talking about a lot these days.
Mechanisms
I view column-level lineage as existing in two orders of complexity:

Extending existing constructs. Today, dbt developers have to duplicate a lot of resource properties (descriptions, tags, meta, tests) across models, even when model Y is just select * from model X. Over in #2995, and #1158 before then, we've been discussing ways that YAML anchors make a version of this possible today, and how it could be better in the future (cross-file anchors, souped-up docs blocks, hierarchical properties-as-config).
Massive new capabilities. To capture column-level lineage for real for real, we'd need a validating SQL grammar—same as would, incidentally, for a decent linter / auto-formatter (#2356). In a world where we had this, and built it into dbt, we'd also have an AST representation of every column name, from relation, and SQL function. This is definitely on our minds; it's still a ways away.

Use cases
As with any compelling feature, column-level lineage feels both immensely valuable and a bit vague. If dbt could produce an EXPLAIN-style plan, of every single SQL function performed to produce a single column, that would be very cool, and also tricky to read and reason about as a human being.
So I do find it useful to think concretely about the kinds of things we'd hope to enable here:

Property (tag/meta/etc) inheritance. E.g. If a source PII/PHI column is the indirect input to a column in a downstream model, being able to mark the latter model as sensitive.
Saving code (+ time). Extending what I described above, if a column has not transformed from model X to model Y—no renames, no aggregations—dbt could natively inherit its properties, such as description + tests.

Or, better yet, dbt would understand that the column has been tested upstream, has not changed, and so does not need to run the same tests again.

"dbt column advisor." If dbt has a full picture of how a column is produced—which input columns, which transformations—it could flag when there are potentially duplicative columns across models, and help avoid the repeating of business logic.
Slim CI to the max: If you've only changed one column across a few models, rather than running the changed models and all their children, you'd only need to run + test downstream models that use the affected column.

I'm curious to hear what other things come to mind!

+4 for the use case you've mentioned @jtcohen6 , I'd like to add the following, IMO important use case:

A variant of Slim CI to the max: being able to do an impact analysis at development time when you're changing a  source / model's column name. After all, the fact that a column changes does not necessarily mean that the column also used in any dependent models. For that, you really need column level lineage.

Instead of building this yourself, you could also think about integrating DBT with the only data lineage focused SAAS product I have heard of: https://getmanta.com/integrations/

+4 for the use case you've mentioned @jtcohen6 , I'd like to add the following, IMO important use case:

A variant of Slim CI to the max: being able to do an impact analysis at development time when you're changing a  source / model's column name. After all, the fact that a column changes does not necessarily mean that the column also used in any dependent models. For that, you really need column level lineage.

Instead of building this yourself, you could also think about integrating DBT with the only data lineage focused SAAS product I have heard of: https://getmanta.com/integrations/

we are planning to use DBT Cloud for our project and this table by table lineage is really a killer feature which we would like to have  as This would make data lineage and debugging much much easier

Hi 👋 , does anyone know how Datafold + DBT claims to provide this?

Datafold use their own lineage capabilities to do this — while they do read in your dbt project, the column level lineage is part of their platform (it's an awesome feature though!)


Old screen showing when logging out from doctors access

I think we could show the login screen instead of this one when logging out from the doctor's access.

Hi guys, this screen keeps appearing in the doctor access page. We are not going to need these buttons (Entrar na sala de espera / Já tenho senha de retorno) as doctors, so maybe change it to show our logo or buttons to the doctor's options that are on the menu.


[DOC] Documentation updates for cluster.restrict.index.replication_type and cluster.indices.replication.strategy setting

What do you want to do?

[ ] Request a change to existing documentation
[ ] Add new documentation
[ ] Report a technical problem with the documentation
[ ] Other

Tell us about your request. Provide a summary of the request and all versions that are affected.

Add new setting cluster.restrict.index.replication_type that blocks setting replication type and intended behavior.
cluster.indices.replication.strategy setting today allows user to enable replication type setting at cluster level. Setting this at cluster level imposes replication type settings on certain actions which create new indices such as split, clone, index templates etc, need to call out.

What other resources are available? Provide links to related issues, POCs, steps for testing, etc.
Related core issue: https://github.com/opensearch-project/OpenSearch/issues/11457

Hi @dreamer-89 , thanks for creating the issue. Are we targeting a specific release, for example, 2.12, for this new setting?

Hi @dreamer-89 , thanks for creating the issue. Are we targeting a specific release, for example, 2.12, for this new setting?

Thanks @hdhalter for the clarification and apologies for delay. Yes, I am targeting this change for 2.12 release. Can you please add 2.12 label on this issue. Let know if you have any questions.

Thanks, @dreamer-89! Can you please open the PR with this setting?


Wrong ukrainian i18n default translates

#Issue:
Ukrainian default form translates stand on vendor/yii2/messages/uk/yii.php
when i change config to
"language" => "uk"
System translate all to United Kingdom, not ukraine
#How to fix
I just rename dir: "uk" => "ua" and all works correct on UA i18n version.
#P.S If this is not a bug, how can i use uk file correct?

uk is correct language code for Ukrainian and translations do match. UA is the country code, not language code.

What exactly doesn't work for you?

 After pull this issue i wrote about it, and there was trouble because of architecture of my project, so all i done to get wroght result: change Yii::$app->language in urlManager. Once again I apologize, have a nice day and less nubes like me

No worries.


Add semcov for grpc request and response sizes

We are trying to add functionality to yield grpc request and response size metrics.
As I can see it is not part of semcov, how can it be added so we can change the opentelemetry-java instrumentation to yield these metrics?

I think this would fall under this: https://github.com/open-telemetry/semantic-conventions/blob/main/docs/rpc/rpc-metrics.md#metric-rpcserverrequestsize

Yes this is only the metric we wanted to add as attribute so we can extract that attribute in this metric.

Gotcha. I don't think this repo yet has any support for autogenerating the metric conventions from the yaml, so this definitely relates to #12.

Closing as duplicate of #12. Keeping #12 instead of this because its more generic, and came first.


[flutter_releases] CP Enforce cpu explicitly for Mac devicelab test beds

https://github.com/flutter/flutter/pull/101871
This is causing post-submit failures as occasionally the bots flake due to running on arm64.

Was this supposed to be a cherry pick to a release candidate branch?

Was this supposed to be a cherry pick to a release candidate branch?
Yes, this is intended for 2.13.0. GitHub was being finnicky, and kept switching the base on me, so I'm not surprised this ended up on master. Fixed!


Implemented creation of one user with reflection

BuildRunner and RandomBuilder are now agnostic of the class of the entity they build.
Added RangeUtil class for calculating operations with ranges

Move model classes to test package

Fixes #12


Use Yarn for Download Bootstrap

The thing with this is I don't think it should be a separate section personally.

But this sections is called Package managers to it should list all the package managers we support 🤔
https://getbootstrap.com/docs/4.1/getting-started/download/#package-managers

That's true. It just doesn't make a lot of sense to me but anyway.

The thing with this is I don't think it should be a separate section personally.

I fully understand your consideration, NPM and Yarn are pretty much the same thing, but we have to recognize that many developers want ease by using ctrl + c and ctrl + v to add Bootstrap to their projects.


fix: manual update with generator 2.14.2

address #115

The docs test fails and it looks like a real positive.


Match bottom curvature

Can the modals to match the bottom curvature of phones

UI changes are pending.

Maintain apple like (min) height and gap.

Also make sure the shade of blue for cross and button matches.

@summikhan11 - we are going with the apple like loader messages

Specs: https://xd.adobe.com/view/0aef8043-d951-4d0a-9a97-b7b2e16ffdbc-5fbc/screen/d4106792-2405-491a-8c54-5ebd17a9b810

Closing this issue as discussed with dev.


Ellipses in menus

Describe the Feature
It is generally advised in UI design to use an ellipsis (…) at the end of menu items if that menu will expect the user to make a choice / enter more information before committing the action. This article explains the concept well and quotes Apple's and Microsoft's guidelines.
Secondly, ellipses are also needed on text enter prompts, such as:

Enter a word or tag…
Enter Code…
Enter your birth date…
etc.

There is one case in which Apple and Microsoft's guidelines differ: Whether or not to use ellipses when a button's explicit purpose is to display another window. Rather, Apple does not mention this case but does use an ellipsis character, for example, in the Apple Menu's ‘System Preferences…’ item. Microsoft, however, explicitly mentions that this is not needed, as the button's purpose is to ‘display another window and additional information isn’t needed to perform [this] action.’
I would be willing to work on this in a PR, but we should reach a consensus as to which guidelines to use.
Attachments

Comparison of the two guidelines in the post context menu. ‘Translate’ is the only affected item by the difference, as the translation opens in a new window/tab (left: Apple advises the usage of ellipses), but the button's express purpose is to open a window/tab with no other options to pick before the ‘translate’ action is committed (right: Microsoft advises against the usage of ellipses).
Describe Alternatives
No response
Additional Context
No response

A bit off-topic, but I wonder, why are icons placed on the right side? They usually come close to the label, while the right side can be used for displaying shortcuts (for example).
I don't know what is in the guidelines, but after a quick look, Google Drive, PHPStorm, Youtube, MacOS, and others place them on the left side.

Right you are. Maybe that could be mentioned in a different issue.


Form Submission Landing "Thank You" Page

I am having trouble with getting a landing page working. I have everything working with a custom form and App Scripts, but I need my form submission to redirect users to a specific URL. I saw there link at the bottom of the article and a similar issue listed here, but there is not much description for how to implement this. I know some JS, but I am no expert and could really use a hand figuring this out.
Respectfully,

I figured this out actually. I used the code on the original guide with a modification. In my HTML I added the following:

<script>
window.addEventListener("load", function() {
  const form = document.getElementById('googleform');
  form.addEventListener("submit", function(e) {
    e.preventDefault();
    const data = new FormData(form);
    const action = e.target.action;
    fetch(action, {
      method: 'POST',
      body: data,
    })
    .then(() => {
    window.location.href = 'URL of thank you page';
    })
  });
});
</script>

This fixed the issue and now everything is working correctly.


Mesh doesn't use custom logger

Issue workflow progress

Progress of the issue based on the
Contributor Workflow

[ ] 1. The issue provides a reproduction available on
Github,
Stackblitz
or
CodeSandbox

Make sure to fork this template and run yarn generate in the terminal.
Please make sure Mesh package versions under package.json matches yours.

[ ] 2. A failing test has been provided
[ ] 3. A local solution has been provided
[ ] 4. A pull request is pending review

Describe the bug
When using .meshrc.ts to configure Mesh and passing the logger option - Mesh doesn't seem to use that and instead instantiates a new logger.
To Reproduce Steps to reproduce the behavior:

Clone https://github.com/kamilkowalski/mesh-logger-issue
Run npm i && npx mesh dev
There's one log line that uses the custom logger which I've added in .meshrc.ts directly, but Mesh's logs don't use the custom logger

Expected behavior
I've expected Mesh to use the custom logger instance passed in config.
Environment:

OS: macOS 14.5
@graphql-mesh/cli: v0.90.10
NodeJS: v18.12.1

Ok, I found the issue - the logger option is documented^1 as:

Logger instance that matches Console interface of NodeJS

But in fact the resolveLogger function only uses that option if it's a string designating a module to be loaded.^2
That's a bit confusing. Is the problem that of build vs runtime - so we can't really pass an instance because the config is only used to generate TypeScript artifacts so they need to contain the code that instantiated the logger?
I managed to work around it by passing a path to a TypeScript module in the logger option:
{
  logger: "./logger"
}

And doing the setup in that file. If it's impossible to pass an instance of the logger in config then I can update the type documentation, but I'd appreciate someone confirming this.

Just noticed the above doesn't work for production builds because the import isn't handled correctly - Mesh tries to load the file from the .mesh directory instead of going up one directory similarly to how it handles additional resolvers.

Actually that option is not supposed to an object as a logger. But a path to a code file that exports an object implements Logger from @graphql-mesh/types.
It is a missing documentation in that case.
But after build, if it doesn't load the module from the path correctly. This is a bug then.
Thanks for the feedback!
Apparently the types there and resolveLogger need to be fixed.
Would you try to tackle it in a PR?

I'll take a stab at it. 😊


Non-default "Items Per Page" hangs data grid when changing grid view

In System --> Configuration --> General setup --> Display settings, changing the "Items Per Page By Default" option under Data Grid Settings causes the data grid to hang when changing grid views. To duplicate:

Change the setting mentioned above to something non-default (say, 100).
Browse to a data grid (say, Sales --> Leads).
Click the "All Leads" grid view to something else (create one first, if needed).
Watch as the new leads are loaded and displayed, but the progress spinner never quits and the View Per Page remains greyed out.

At this point, checking the console reveals an error message along the lines of:
TypeError: currentSizeLabel[0] is undefined
Returning the option mentioned above to the default value fixes the data grid display.

Hi @cmenning,
Can not reproduce this issue in the latest version of OroPlatform. It looks like the issue is already fixed there: page-size.js (v1.9) and page-size.js (v1.8)
What version of platform do you use? We will port the fix in older versions.

@Grygir,
We're using 1.8.2. I didn't notice the change in 1.9 and saw that the filter logic was the same. Thanks!

The issue will be fixed in 1.8.* with release 1.8.3

The is fixed in master branch.


Fresh build?

Seems like the latest image on docker hub is a bit out of date, some of my builds are failing here: https://travis-ci.com/EvanPurkhiser/PKGBUILDs
Does docker hub have a way to do cron style builds?

I've triggered a rebuild now, but looks like docker hub won't allow automatic this.
Maybe I could hook up travis to run a cronned build that pings docker hub and makes it rebuild...?

Looks like latest is actually still 5 months old :/

Hmm, still seeing this using this image:
https://travis-ci.com/EvanPurkhiser/PKGBUILDs/jobs/230030882
:: Synchronizing package databases...
downloading core.db...
downloading extra.db...
downloading community.db...
resolving dependencies...
looking for conflicting packages...
error: unresolvable package conflicts detected
error: failed to prepare transaction (conflicting dependencies)
:: systemd-libs and libsystemd are in conflict. Remove libsystemd? [y/N]
:: systemd-libs and libsystemd are in conflict
Error installing repo packages
The command "docker run -v $TRAVIS_BUILD_DIR/$PACKAGE:/pkg whynothugo/makepkg" exited with 1.```

I've pushed changes to this repo that should rebuild the image nightly. We'll see at midnight UTC if it works.
Otherwise I'll follow up tomorrow on it.


Support websocket

This PR adds support for the websocket protocols. The functionality includes support for websockets and socket.io.

I merged this manually from the command line. Closing the PR.


Failed to run docker run hello-world on RPi 2

Description
Docker Engine installed on Raspbian Jessie for a Raspberry Pi 2.
$ uname -srmo
Linux 4.4.38-v7+ armv7l GNU/Linux

Steps to reproduce the issue:

Installed alongside this tutorial
Request image docker pull hello-world
Execute the command docker run hello-world

Describe the results you received:
$  docker run hello-world
panic: standard_init_linux.go:175: exec user process caused "exec format error" [recovered]
	panic: standard_init_linux.go:175: exec user process caused "exec format error"

goroutine 1 [running, locked to thread]:
panic(0x3360b0, 0x56e57300)
	/usr/local/go/src/runtime/panic.go:481 +0x330
github.com/urfave/cli.HandleAction.func1(0x56ea3958)
	/go/src/github.com/opencontainers/runc/Godeps/_workspace/src/github.com/urfave/cli/app.go:478 +0x328
panic(0x3360b0, 0x56e57300)
	/usr/local/go/src/runtime/panic.go:443 +0x448
github.com/opencontainers/runc/libcontainer.(*LinuxFactory).StartInitialization.func1(0x56ea35e0, 0x56dda568, 0x56ea3668)
	/go/src/github.com/opencontainers/runc/Godeps/_workspace/src/github.com/opencontainers/runc/libcontainer/factory_linux.go:259 +0x13c
github.com/opencontainers/runc/libcontainer.(*LinuxFactory).StartInitialization(0x56e54b10, 0x46430620, 0x56e57300)
	/go/src/github.com/opencontainers/runc/Godeps/_workspace/src/github.com/opencontainers/runc/libcontainer/factory_linux.go:277 +0x498
main.glob.func8(0x56e701e0, 0x0, 0x0)
	/go/src/github.com/opencontainers/runc/main_unix.go:26 +0x58
reflect.Value.call(0x2eb600, 0x3f2948, 0x13, 0x3648b8, 0x4, 0x56ea3918, 0x1, 0x1, 0x0, 0x0, ...)
	/usr/local/go/src/reflect/value.go:435 +0xeb4
reflect.Value.Call(0x2eb600, 0x3f2948, 0x13, 0x56ea3918, 0x1, 0x1, 0x0, 0x0, 0x0)
	/usr/local/go/src/reflect/value.go:303 +0x84
github.com/urfave/cli.HandleAction(0x2eb600, 0x3f2948, 0x56e701e0, 0x0, 0x0)
	/go/src/github.com/opencontainers/runc/Godeps/_workspace/src/github.com/urfave/cli/app.go:487 +0x230
github.com/urfave/cli.Command.Run(0x366cd8, 0x4, 0x0, 0x0, 0x0, 0x0, 0x0, 0x3d0d50, 0x51, 0x0, ...)
	/go/src/github.com/opencontainers/runc/Godeps/_workspace/src/github.com/urfave/cli/command.go:191 +0xcd0
github.com/urfave/cli.(*App).Run(0x56e40240, 0x56e22050, 0x2, 0x2, 0x0, 0x0)
	/go/src/github.com/opencontainers/runc/Godeps/_workspace/src/github.com/urfave/cli/app.go:240 +0x84c
main.main()
	/go/src/github.com/opencontainers/runc/main.go:137 +0xbb4

Describe the results you expected:
Container started sucessfully
Additional information you deem important (e.g. issue happens only occasionally):
The log after the command executed:
$ journalctl -u docker.service
(...)
Dec 26 16:00:30 mars dockerd[565]: time="2016-12-26T16:00:30.839362187Z" level=info msg="No non-localhost DNS nameservers are left in resolv.conf. Using default external servers : [nameserver <IP_ADDRESS> nameserver <IP_ADDRESS>]"
Dec 26 16:00:30 mars dockerd[565]: time="2016-12-26T16:00:30.839725518Z" level=info msg="IPv6 enabled; Adding default IPv6 external servers : [nameserver 2001:4860:4860::8888 nameserver 2001:4860:4860::8844]"
Dec 26 16:00:31 mars dockerd[565]: time="2016-12-26T16:00:31.620129369Z" level=warning msg="failed to close stdin: rpc error: code = 2 desc = containerd: container not found"

Output of docker version:
$ docker version
Client:
 Version:      1.12.5
 API version:  1.24
 Go version:   go1.6.4
 Git commit:   7392c3b
 Built:        Fri Dec 16 03:23:36 2016
 OS/Arch:      linux/arm

Server:
 Version:      1.12.5
 API version:  1.24
 Go version:   go1.6.4
 Git commit:   7392c3b
 Built:        Fri Dec 16 03:23:36 2016
 OS/Arch:      linux/arm

Output of docker info:
$ docker info
Containers: 5
 Running: 0
 Paused: 0
 Stopped: 5
Images: 1
Server Version: 1.12.5
Storage Driver: devicemapper
 Pool Name: docker-179:2-258054-pool
 Pool Blocksize: 65.54 kB
 Base Device Size: 10.74 GB
 Backing Filesystem: ext4
 Data file: /dev/loop0
 Metadata file: /dev/loop1
 Data Space Used: 310.4 MB
 Data Space Total: 107.4 GB
 Data Space Available: 29.83 GB
 Metadata Space Used: 970.8 kB
 Metadata Space Total: 2.147 GB
 Metadata Space Available: 2.147 GB
 Thin Pool Minimum Free Space: 10.74 GB
 Udev Sync Supported: true
 Deferred Removal Enabled: false
 Deferred Deletion Enabled: false
 Deferred Deleted Device Count: 0
 Data loop file: /var/lib/docker/devicemapper/devicemapper/data
 WARNING: Usage of loopback devices is strongly discouraged for production use. Use `--storage-opt dm.thinpooldev` to specify a custom block storage device.
 Metadata loop file: /var/lib/docker/devicemapper/devicemapper/metadata
 Library Version: 1.02.90 (2014-09-01)
Logging Driver: json-file
Cgroup Driver: cgroupfs
Plugins:
 Volume: local
 Network: host null bridge overlay
Swarm: inactive
Runtimes: runc
Default Runtime: runc
Security Options:
Kernel Version: 4.4.38-v7+
Operating System: Raspbian GNU/Linux 8 (jessie)
OSType: linux
Architecture: armv7l
CPUs: 4
Total Memory: 925.5 MiB
Name: mars
ID: U7AC:EMNY:DWXF:OUEN:YAWZ:VBDT:6RRI:PXML:AVG7:C6DE:LN67:B23C
Docker Root Dir: /var/lib/docker
Debug Mode (client): false
Debug Mode (server): false
Registry: https://index.docker.io/v1/
WARNING: No swap limit support
WARNING: No kernel memory limit support
WARNING: No cpu cfs quota support
WARNING: No cpu cfs period support
WARNING: No cpuset support
Insecure Registries:
 <IP_ADDRESS>/8

@poliveira89 The helloworld image is for amd64 I guess, so the binary inside it have not the right architecture, hence the error : exec format error.

@vdemeester I did not knew about that, but it's on the Raspbian tutorial. That being said, I thought that if the hello-world was not working should be related to engine.
But you seem to be right, because I pulled this image container4armhf/armhf-alpine and then run:
$ docker run container4armhf/armhf-alpine /bin/echo 'Hello world'
Hello world

And it worked! So, I think this after is a non-issue for that, I will close it. Thanks.

Oh, I wondered where this Raspbian tutorial is and sent a PR https://github.com/docker/docker.github.io/pull/984 to fix it.
$ docker run armhf/hello-world

works fine.


[FEAT] :sparkles: Setup Docker

Description
we need to configure docker for this application

[ ] setup docker
[ ] update readme and mention all the steps on how to use docker for the project

Anything else?
take reference for reamde from backend repo

Hi @aayushchugh I am a DevOps Expert contributing to Hacktoberfest. I would like to work on this issue please assign me to it.
Thanks

@KOQ-UTx10101 sure

@KOQ-UTx10101 this issue is getting re-assigned to @tharun634

ok but I have completed it so should I not make a pull request now ?

@KOQ-UTx10101 If you have completed than please create a PR


fix(namespace): add the field namespaceOverride back.

Which issue(s) this PR fixes:

Issue longhorn/longhorn#6527
What this PR does / why we need it:
This field is used to override the Longhorn namespace when Longhorn is a sub-chart such as a sub-chart of the Harvester.
Special notes for your reviewer:
Additional documentation or context

@mergify backport v1.6.x


feat: add WASM compatibility for verification functions

This pull request introduces WebAssembly (WASM) compatibility for the verification process of Jolt. The main changes include:

Extension of jolt new command with --wasm flag:

The jolt new <project-name> --wasm command modifies both the root/Cargo.toml and guest/Cargo.toml files to include the necessary dependencies for WASM. It also marks the project as a cdylib crate type, which is required for WASM compilation.

Addition of jolt build-wasm command

The build-wasm command extracts all functions declared with jolt::provable. It then performs preprocessing steps to build and decode the program, storing the resulting data in binary form. An example index.html file is created to demonstrate how to use the functions generated by the macro extension. Finally, optimized WASM files are created using wasm-pack to make the project ready for use.

Extension of macros:

The macros are enhanced to check if functions are marked with jolt::provable(wasm). If so, necessary imports and helper functions are defined. The output of the preprocessing process is then used to build the WASM-compatible verify-functions.

Current Limitations

Dependencies used in guest/src/lib.rs need to be defined both in guest/Cargo.toml and root/Cargo.toml. This redundancy is known and could be optimized in future iterations.
Currently, this only provides WASM support for proof verification. The proving itself is not yet WASM-compatible, bc it's unclear whether this is a desired requirement.

#314

@ncitron I have refactored the parse_attributes function so that we can use it in both the WASM preprocessing and within the macro. Additionally, I have moved the entire WASM preparation process to a separate file because it was getting very cluttered. Whether it uses std or no_std is determined by reading the features and setting it accordingly. lmk what you think

Looks like CI is failing due to clippy. Can you resolve then we can merge?

@ncitron should be done


Shake error when updating eta

I tried to run both update.sh as well as install.sh in the repository after switching to the 0.0.5b1 tag in the eta repo.
In both cases the script ended with the following error.
# eta-pkg (for install)
# epm (for install)
Downloading the latest package list from hackage.haskell.org
Skipping download: Local and remote files match.
Downloading the latest package list from git.etlas.eta-lang.org
warning: redirecting to https://github.com/typelead/etlas/
fatal: refusing to merge unrelated histories
Error when running Shake build system:
* install
user error (Development.Shake.cmd, system command failed
Command: epm update
Exit code: 128
Stderr:
warning: redirecting to https://github.com/typelead/etlas/
fatal: refusing to merge unrelated histories
)

We're currently working on setting up a package index for Eta-specific packages and the changes must have bled through.

Wipe out ~/.epm
Checkout 0.0.5b2
Run ./cleaninstall.sh

Running cleaninstall.sh fails with <repo>/epm/Cabal/: getDirectoryContents:openDirStream: does not exist (No such file or directory)

I also tried deleting the repo and recloning and I got
Stack looks for packages in the directories configured in the 'packages' variable defined in your stack.yaml
The current entry points to /Users/justusadam/projects/eta/codec-jvm/ but no .cabal file could be found there.

Can you run git submodule init & git submodule update --recursive and then try again?

Ah all right. I must have forgotten the --recursive flag in the clone command. It seems to install now.

Great. Please give me a confirmation once the installation completes successfully so I can close this issue.

It installed, thanks for the help.


Generic scss

Changes made :

adding .gitignore file :  to avoid commiting node_modules or non related files.
adding sass build command : to make it easy to build sass code each time changed.
adding breakpoints + grid vars : making the code more generic & customizable
adding reponsive mixin : to make a css code available in a specific screen or all of them by prefixing
editing col grid sytem: customizable col grid system dependent on defined variables.
updating README

there are some responsive bug in the grid system

I will recheck the code tomorrow ;), can you give me more details ?

After testing your changes :
the .container fluid is much more small in the browser view.
the .container was also small in the browser view.
fixe the problem and send a new pull request please