Error on generate (fn is not a function)

Version
v2.11.0
Reproduction link
https://github.com/MattixNow/mattaio-website/tree/caea07a28f9e68f12509598bc1d558dc022f7294
Steps to reproduce
yarn
yarn generate

What is expected ?
Normally generate working fine
What is actually happening?

 ERROR  Could not resolve routes                                                                                22:56:04

 FATAL  fn is not a function                                                                                22:56:04

  at Object.promisifyRoute (node_modules\@nuxt\utils\dist\utils.js:1739:17)
  at Generator.initRoutes (node_modules\@nuxt\generator\dist\generator.js:84:38)
  at Generator.generate (node_modules\@nuxt\generator\dist\generator.js:44:31)

   ╭─────────────────────────────────────╮
   │                                     │
   │   ✖ Nuxt Fatal Error                │
   │                                     │
   │   TypeError: fn is not a function   │
   │                                     │
   ╰─────────────────────────────────────╯

error Command failed with exit code 1.

Additional comments?
Maybe about routes generation, i don't found any similar issue

This bug report is available on Nuxt community (#c10147)

https://github.com/MattixNow/mattaio-website/blob/caea07a28f9e68f12509598bc1d558dc022f7294/nuxt.config.js#L200-L204
This is not valid JavaScript and likely causing the error.


class JSONarray 's version may be wrong?

' The class version
public property get version
	items = i_version
end property

at Line 749

Hi. Thank you.


Reading JPEG2000Loseless data

We are trying to read a 16-bit JPEG2000Loseless type (Transfer Syntax ID - 1.2.840.10<IP_ADDRESS>.90).
Using DicomParser we saw that this file is having encapsulatedPixelData: true.

Is there any way we can determine if the arrayBuffer contains compressed data or decompressed data ?
And if it is compressed data then is there a method to decompress it before proceeding further ?
Any inputs or help will be really appreciated, thanks.

It's compressed since it has the transfer syntax UID you listed (otherwise it would have one of the more traditional transfer syntaxes, like explicit VR little endian).
As far as decompressing goes, you'll need to find another library to do JPEG2000 decompression for you. Each fragment in your dicomParser dataset has a position and a length; you can pass the range of bytes defined by those numbers to the JPEG2000 library to decompress (here's a StackOverflow that might help). If you have multiple fragments, you'll need to recombine them after decompressing each one individually.


NavLink reporting current status incorrectly to NVDA screen reader

Version
4.2.2
Test Case
This occurs with every use of the NavLink component. Also in a vanilla implementation of react-router-dom in a clean application.
Steps to reproduce
Use the NavLink component in an app. Run the app in Firefox and activate the NVDA screen reader.
Now browse the links with TAB and Shift+TAB and activate them with Enter and check the screen reader response.
I do not yet know if this is an issue only in NVDA and if other screen readers are also involved.
Expected Behavior
Only the currently highlighted link should be read out as current. On selecting a link it should be read out as being current only once.
Actual Behavior
The following graphic shows the NVDA speech viewer with a basic application containing only react-router-dom:

The blue dotted outline:
This shows that every link in the set is read out as current, regardless of the setting of aria-current.
The dashed red outline:
This shows that when activating a router link, NVDA reads out the word "current" multiple times.
I will shorly submit a pull request to fix the isue from the blue dotted outline.
As for the red dashed outline, I have not been able to track down yet if this is due to the way the component renders or if it is an actual issue with the implementation in NVDA or how Firefox exposes the accessibility tree.

remove aria-current from inactive link seems not prevent NVDA from reading "current" multiple times
could you pls help to check this fiddle https://jsfiddle.net/n5u2wwjg/238066/


favstar. Favourities not deleted when deleting dashboard or slice

Hi. Found two issues with favourities.

I create dashboard,
I mark my dashboard as favourite
I delete the dashboard.
The record in favstar table is not deleted. It should.

I have no dashboard with id=99999999
I make GET /superset/favstar/Dashboard/99999999/select/
The record in favstar table is created and it should not.

Test
tests.integration_tests.dashboards.api_tests.TestDashboardApi.test_delete_dashboard
does not check if favstar database is modified and a corresponding record is deleted.

Test tests.integration_tests.core_tests.TestCore.test_user_profile does not check negative scenario creating a record with fake id.

Closing this as stale since it's been silent for so long, and we're trying to steer toward a more actionable Issues backlog. If people are still encountering this in current versions (currently 3.x) please open a new Issue or a PR to address the problem.
CC @john-bodley since he was somewhat interested in consolidating this with the Tags feature, which didn't exist when this Issue was opened.


Allow unsigned deb packages install from mirror locations

In a test deployment, hosting ceph packages in a local mirror and
installing them across the cluster will be ideal. Current ceph-deploy
allows unauthenticated packages when install is used but not from a
mirror location. This change helps address that usecase.
Signed-off-by: Ganesh Mahalingam<EMAIL_ADDRESS>

Can one of the admins verify this patch?

I understand using '--dev' in this method is not its intended purpose. But i thought in this way of install it is something that can be extended to help with this. Please feel free to correct me if i am wrong in the usage or if there is a cleaner way of handling this change.

LGTM, if you can post some run logs from the mirror would be nice.

@vasukulkarni Thanks. Please find logs for a run with --repo-url --dev here. https://hastebin.com/ofuleluzur.md


Gitbook documentation

A gitbook documenation should be created. All documentation related stuff from the readme file should be moved to the docs folder and should be presented in the gitbook
gitbook.com

Gitbook docs are created and readme.md content has been moved
https://angular-fast-forms.codentury.com


chore: pre-commit autoupdate

Codecov Report

Merging #139 (bcd89e8) into main (c604f67) will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##             main     #139   +/-   ##
=======================================
  Coverage   89.25%   89.25%
=======================================
  Files          23       23
  Lines        1843     1843
=======================================
  Hits         1645     1645
  Misses        198      198

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update c604f67...bcd89e8. Read the comment docs.

:tada: This PR is included in version 4.6.0 :tada:
The release is available on:

v4.6.0
GitHub release

Your semantic-release bot :package::rocket:


More graceful handling of undefined named colors

The failing tests are related to adjective generation, can be ignored for now.


Scaling problem

I loaded a model into the slicer. No problem. But I need it a little smaller. scaling  - no matter if single axis or all 3 locked - no problem.
But: if i rotate the model  befor scaling  (it is vrtical in the project, so I rotate it so it can lay flat)  and then try to reduce i.e. the z-hight (just a prototyp - don't need all the material to be printed, only the perimeters), nothing is o.k.
Scaling all 3  dimensions (lock) is no problem.  Scaling a single axis is a little goofy...
It seems the rotating keeps the dimensions orientation, but the scaling don't really mind and is scaling the orientation, wich it "thinks", it might be the best... but not  the original  or the workspace orienation.
It seems to get a bit dizzy with the rotation befor scaling .

Now i know, it's no problem to do the scaling first, then the rotation. But if you don't know...

Sorry @thjansen72 for the delay. I have been very tied up with another project.
I tried to scale Z axis and then rotate the part and I didn't see any problem. Please see the attached screenshot. Did I misunderstood the problem you described?

Hmm I had to get clear about what really happens.
Lets say the orientation of the bed is  x->front-line (to the sides), y ->left+right line (to the back), z- up).
When i place a model, it "gets" the same coordinate-system of the bed.
After rotating the model, its coordinate-system is also rotating.
In your example you changed the value of the x-axis, wich was not rotated - try Y or Z....
In the scaling-dialog I'd think all orientations are like the bed-orientation, but by rotating  the coordiante system of the modell  (because of rotating it)  (in this example)  x  - is like before, y and z switched.
Entering a new value for y or z  will chause in the change of the lenght-value-field of the other orientation.
Irritating...  (I need a dictonary and a thesaurus "english" for chrome ....)

Thank you for the detailed info @thjansen72 ! I'm currently on vacation with very limited bandwidth. Will take a look at it next week when I'm back.

Sorry for the delay @thjansen72 . I was just back from vacation.
I'm not sure I understand what the problem is. Can you point out what you think is wrong in the screenshots you poste above?
I also did some other tests and the screenshots are as follows:
0. Original part placement and 1.0 scale:

1.1 First rotate 90 degrees on both Y and Z:

1.2 Then scale Z by 2x:*

2.1 First scale Z by 2x:

2.2 Then rotate 90 degrees on both Y and Z:*

All the steps seem to behave as I expected.

@thjansen72 can you help me understand what the problem is? I am pretty sure I misunderstood you but I can't figure out where the misunderstanding occurred.

Not sure if I'm following what @thjansen72 is saying, but let me take a stab at it.
In the example @kennethjiang  gives in his post with the sort of triangle shaped thing: in picture 1.1 you rotate 90˚ around both Y and Z. But then when you scale Z, it scales the original Z-axis, but @thjansen72 is expecting it to scale along the presently displayed Z-Axis, so that the shortest dimension (which is the current Z) would be made larger.
When all the rotations are 90˚, it's easy to adjust, but when you are rotating by some odd number, it gets tougher.
Ken - I think we had a similar discussion some time ago, but I can't remember if it was scaling or lay flat or something else (it may have been issuing a lay flat after rotating doing funny things?) I'd get something positioned, almost how I wanted it, then issue a command (lay flat?) and it would undo some of the rotations I had done.

Thank you @John-Mc for helping us out here. I think your interpretation makes sense. As a matter of fact I just tested it in Cura and it worked exactly as what you described @John-Mc .
I will do some research to see how difficult it is to change the behavior to be consistent with Cura.
I think the previous discussion we had was #81. It is a different issue and I know it's much harder to do.


Improved waveform generation

No longer attempting to test wave generation with rate=1 and nPts=1
Generator error messages now include traceback (better for debugging new waveform functions)

OK, I'll head down to 40 and play with this...
On Sep 11, 2015, at 8:09 AM, Luke Campagnola <notifications<EMAIL_ADDRESS>wrote:

No longer attempting to test wave generation with rate=1 and nPts=1
Generator error messages now include traceback (better for debugging new waveform functions)

You can view, comment on, or merge this pull request online at:
https://github.com/tropp/acq4/pull/1
Commit Summary

Better wave generator error reporting

File Changes

M acq4/devices/DAQGeneric/DaqChannelGui.pyhttps://github.com/tropp/acq4/pull/1/files#diff-0 (11)
M acq4/devices/MultiClamp/taskGUI.pyhttps://github.com/tropp/acq4/pull/1/files#diff-1 (13)
M acq4/modules/TaskRunner/TaskRunner.pyhttps://github.com/tropp/acq4/pull/1/files#diff-2 (49)
M acq4/util/generator/StimGenerator.pyhttps://github.com/tropp/acq4/pull/1/files#diff-3 (164)
M acq4/util/generator/waveforms.pyhttps://github.com/tropp/acq4/pull/1/files#diff-4 (151)

Patch Links:

https://github.com/tropp/acq4/pull/1.patch
https://github.com/tropp/acq4/pull/1.diff

—
Reply to this email directly or view it on GitHubhttps://github.com/tropp/acq4/pull/1.


Execute externally ?

Hi !
Thanks for your work !
Is it possible to run the component outside the machine / container that runs taosd ? I'm asking this question because I'm using TDEngine with Kubernetes and I don't want to have two processes in the same container.
It would be pretty cool if we could use the REST API as a scalable component with HPA.
Thanks !

Thanks for your question.
Yes, it's possible. You can run taosd and taosAdapter in two different pods and make sure the pod runs taosAdapter installed libtaos.so with the same version of the taosd. An easier way is to install the TDengine server standard package but don't run taosd but just run taosAdapter. And fill the taos client configuration file with your taosd's host.
Please let us know what else we can help.

Thanks for your question.
Yes, it's possible. You can run taosd and taosAdapter in two different pods and make sure the pod runs taosAdapter installed libtaos.so with the same version of the taosd. An easier way is to install the TDengine server standard package but don't run taosd but just run taosAdapter. And fill the taos client configuration file with your taosd's host.
Please let us know what else we can help.

Very cool feature ! I have exactly your first case "taosd and taosAdapter in two different pods and make sure the pod runs taosAdapter installed libtaos.so with the same version of the taosd".
Last question :
How target the cluster of TDengine with the adapter ? With taos.cfg or more configuration in  https://github.com/taosdata/taosadapter/blob/develop/example/config/taosadapter.toml ?
Thanks !

Very cool feature ! I have exactly your first case "taosd and taosAdapter in two different pods and make sure the pod runs taosAdapter installed libtaos.so with the same version of the taosd".

Good to know your first case works.

Last question : How target the TDengine cluster with the adapter ? With taos.cfg or more configuration in https://github.com/taosdata/taosadapter/blob/develop/example/config/taosadapter.toml ?

Actually libtaos.so will always find taos.cfg from /etc/taos first. But you can also specify a different place by taosAdapter command line --taosConfigDir or put the location in the taosadapter.toml. Please notice the place is a directory name instead of the full path of taos.cfg file. taos.cfg uses firstEp and secondEp to connect the TDengine cluster.

Thanks !

Good luck.

After hours of works 👍🏼
Kubernetes :
kubectl get sts,deploy,pod,hpa,cm -n common
NAME                                       READY   AGE
statefulset.apps/global-tdengine-cluster   3/3     28m

NAME                                                 READY   UP-TO-DATE   AVAILABLE   AGE
deployment.apps/global-adapter-tdengine-adapter      2/2     2            2           22m
deployment.apps/global-tdengine-cluster-arbitrator   1/1     1            1           28m

NAME                                                      READY   STATUS    RESTARTS   AGE
pod/global-adapter-tdengine-adapter-c7fbf7d4b-jl4wq       1/1     Running   0          20m
pod/global-adapter-tdengine-adapter-c7fbf7d4b-w4k2h       1/1     Running   0          12m
pod/global-tdengine-cluster-0                             1/1     Running   0          28m
pod/global-tdengine-cluster-1                             1/1     Running   0          28m
pod/global-tdengine-cluster-2                             1/1     Running   0          28m
pod/global-tdengine-cluster-arbitrator-5865ddb6fd-hv5d8   1/1     Running   0          28m

NAME                                                                  REFERENCE                                    TARGETS          MINPODS   MAXPODS   REPLICAS   AGE
horizontalpodautoscaler.autoscaling/global-adapter-tdengine-adapter   Deployment/global-adapter-tdengine-adapter   8%/80%, 1%/80%   2         10        2          12m

NAME                                                DATA   AGE
configmap/global-adapter-tdengine-adapter-taoscfg   2      22m
configmap/global-tdengine-cluster-taoscfg           1      28m

Request on Adapter :
curl --location --request POST 'http://root:taosdata@<IP_ADDRESS>:50094/rest/sql' --header 'Content-Type: application/json' --data-raw 'SHOW dnodes;'
{"status":"succ","head":["id","end_point","vnodes","cores","status","role","create_time","offline reason"],"column_meta":[["id",3,2],["end_point",8,134],["vnodes",3,2],["cores",3,2],["status",8,10],["role",8,5],["create_time",9,8],["offline reason",8,24]],"data":[[1,"global-tdengine-cluster-0.global-tdengine-cluster.common.svc.cluster.local:6030",0,3,"ready","any","2021-12-27 20:20:08.022",""],[2,"global-tdengine-cluster-1.global-tdengine-cluster.common.svc.cluster.local:6030",1,3,"ready","any","2021-12-27 20:20:31.521",""],[3,"global-tdengine-cluster-2.global-tdengine-cluster.common.svc.cluster.local:6030",0,3,"ready","any","2021-12-27 20:20:59.913",""],[0,"global-tdengine-cluster-arbitrator:6042",0,0,"ready","arb","2021-12-27 20:20:08.866","-"]],"rows":4}

During my tests, I observed that the adapter was based only on the service port of the TDEngine cluster. Is this really normal ? My configs applied : https://github.com/arktos-venture/helm-charts/tree/chart/tdengine-cluster/charts/tdengine-adapter/configs
I work on a Chart Helm & rootless images of TDEngine, are you interested ?

https://github.com/arktos-venture/docker-tdengine
https://github.com/arktos-venture/helm-charts/tree/chart/tdengine-cluster/charts

After hours of work 🥳
Kubernetes :
kubectl get sts,deploy,pod,hpa,cm -n common
NAME                                       READY   AGE
statefulset.apps/global-tdengine-cluster   3/3     28m

NAME                                                 READY   UP-TO-DATE   AVAILABLE   AGE
deployment.apps/global-adapter-tdengine-adapter      2/2     2            2           22m
deployment.apps/global-tdengine-cluster-arbitrator   1/1     1            1           28m

NAME                                                      READY   STATUS    RESTARTS   AGE
pod/global-adapter-tdengine-adapter-c7fbf7d4b-jl4wq       1/1     Running   0          20m
pod/global-adapter-tdengine-adapter-c7fbf7d4b-w4k2h       1/1     Running   0          12m
pod/global-tdengine-cluster-0                             1/1     Running   0          28m
pod/global-tdengine-cluster-1                             1/1     Running   0          28m
pod/global-tdengine-cluster-2                             1/1     Running   0          28m
pod/global-tdengine-cluster-arbitrator-5865ddb6fd-hv5d8   1/1     Running   0          28m

NAME                                                                  REFERENCE                                    TARGETS          MINPODS   MAXPODS   REPLICAS   AGE
horizontalpodautoscaler.autoscaling/global-adapter-tdengine-adapter   Deployment/global-adapter-tdengine-adapter   8%/80%, 1%/80%   2         10        2          12m

NAME                                                DATA   AGE
configmap/global-adapter-tdengine-adapter-taoscfg   2      22m
configmap/global-tdengine-cluster-taoscfg           1      28m

Request on Adapter :
curl --location --request POST 'http://root:taosdata@<IP_ADDRESS>:50094/rest/sql' --header 'Content-Type: application/json' --data-raw 'SHOW dnodes;'
{"status":"succ","head":["id","end_point","vnodes","cores","status","role","create_time","offline reason"],"column_meta":[["id",3,2],["end_point",8,134],["vnodes",3,2],["cores",3,2],["status",8,10],["role",8,5],["create_time",9,8],["offline reason",8,24]],"data":[[1,"global-tdengine-cluster-0.global-tdengine-cluster.common.svc.cluster.local:6030",0,3,"ready","any","2021-12-27 20:20:08.022",""],[2,"global-tdengine-cluster-1.global-tdengine-cluster.common.svc.cluster.local:6030",1,3,"ready","any","2021-12-27 20:20:31.521",""],[3,"global-tdengine-cluster-2.global-tdengine-cluster.common.svc.cluster.local:6030",0,3,"ready","any","2021-12-27 20:20:59.913",""],[0,"global-tdengine-cluster-arbitrator:6042",0,0,"ready","arb","2021-12-27 20:20:08.866","-"]],"rows":4}

During my tests, I observed the adapter was based only on the service port of the TDEngine cluster. It's really normal ? My configs applied : https://github.com/arktos-venture/helm-charts/tree/release/charts/tdengine-adapter/configs
I work on a Chart Helm & rootless images of TDEngine, are you interested ?
* https://github.com/arktos-venture/docker-tdengine/tree/release

* https://github.com/arktos-venture/helm-charts/tree/release/charts

It's based on https://github.com/taosdata/TDengine-Operator

Brilliant work! Would you like to contribute back to TDengine-Operator as a PR?

Yes, I prepare that ! Thanks for your help !


Monthly bump of Substrate

Align clamor branch in our Substrate fork with Substrate upstream August monthly bump.

Done in this commit.


bpf: Change the result type of bpf_get_current_comm helper

Change it from [i8; 16] to [u8; 18]. i8 arrays cannot be easily used in
Rust for converting to string (i.e. with core::str::from_utf8_unchecked)
and developers have to convert them themselves with unsafe code.
Using u8 arrays lets developers to just convert it with
core::str::from_utf8_unchecked without any limitations.
Example:
https://github.com/vadorovsky/aya-examples/blob/main/clone/clone-ebpf/src/main.rs
Signed-off-by: Michal Rostecki<EMAIL_ADDRESS>

This is a big improvement! Thanks.
Question. Does it make sense to return &str instead?
Since I would imagine that most uses of comm would expect it to be a string anyway.

Question. Does it make sense to return &str instead?

Ping @alessandrod, I remember you didn't like the idea of returning &str and using core::str::from_utf8_unchecked internally in Aya. Am I remembering correctly?
But yes, in my opinion it would make sense. I would even like to have some bpf_probe_read* variants returning &str.

str::from_utf8_unchecked is unsafe, meaning that there are some cases (input is not UTF8) in which the result is not correct. Therefore in order to use it anywhere in aya, we must either a) guarantee that the input is always correct or b) "propagate"  the unsafe modifier to the caller, in this case ctx.command().  Option c) silently making aya incorrect in some cases - is not an option at all :P.
We can't guarantee a) and b) is worse than returning [u8; _], therefore we can not use from_utf8_unchecked 🛑

@alessandrod thanks, I'm convinced


ENH: stats: Add 'alternative' and confidence interval to pearsonr.

The confidence interval is computed using Fisher's z transform.

An example of the enhancement:
In [14]: x = np.array([1, 2, 3, 4.5, 7, 8, 9])

In [15]: y = np.array([.1, 2, 2, 2.5, 2.8, 4, 4.1])

In [16]: result = pearsonr(x, y, alternative='two-sided', confidence_level=0.99)

In [17]: result.r
Out[17]: 0.9259022066726147

In [18]: result.pvalue
Out[18]: 0.0027574400089756517

In [19]: result.fishers_ci
Out[19]: ConfidenceInterval(low=0.3283407577873795, high=0.9941620142528566)

I made some significant changes in the latest update.  The return value of pearsonr is now an object that has the method fishers_ci(confidence_level=0.95).  So instead of always computing the confidence interval and storing it as an attribute of the return value, it is only computed when the user asks for it.
I moved all the code related to pearsonr to a separate file, _pearsonr.py.
I moved this PR out of draft status so it is ready for review.
(When it comes time, let's squash all those commits before merging.)

Squashed and rebased to fix a merge conflict.

The one test failure on TravisCI was the unrelated recurring failure of the test_symmetric_modes ARPACK test.

@WarrenWeckesser @mdhaber @rlucas7 Is a merge imminent here? I see no activity in the last 20 days or so, and this is an enhancement rather than bugfix, so I'll be tempted to bump the milestone pretty soon.

I'll take another look today.

Superseded by gh-15586.


Change how relationship ends are exposed in Subject Area OMAS API

currently the subject Area API exposes the guids of each end of the Line as an attribute. this does not make it easy for the Ui to process.
For example the TermAnchor payload has :
       "lineType":"TermAnchor",
         "name":"TermAnchor",
         "termGuid":"90fea757-384f-45fc-9770-59f17a78be51",
         "glossaryGuid":"b1df5979-9213-4cdb-8f41-cd96cffb1ab1",
         "guid":"8c81da89-ee61-4cb4-a15f-58a4b7fdf145"
      }

It is not obvious that the glossaryGuid and termGuid are special attributes indicating the guids of entities at each end.
It would be better to remove these from the attributes and have :
end1 : {
"nodeType": "Glossary",
"attributeName: "anchor",
"attributeLabel": "Anchor",
"attributeDescription: "Owning glossary.",
"cardinality":"AT_MOST_ONE",
},
end2 : {
"nodeType": "Term",
"attributeName": "terms",
"attributeLabel": "Terms",
"attributeDescription": "Terms owned by this glossary.",
"cardinality":"ANY_NUMBER",
}

@immmus I am looking to have this done this week. Would you like to do this one; if not I will do it.

@immmus I am looking to have this done this week. Would you like to do this one; if not I will do it.

Hi @davidradl . Sorry, I am very busy this week. So that do you )

@immmus no worries. Thanks for responding - I will do this one.


Replace FlatList with another component?

The FlatList component is just too buggy, period.
These plugins may constitute an interesting replacement:

https://github.com/Flipkart/recyclerlistview
https://github.com/bolan9999/react-native-largelist

@bd-arc What's the problem with recyclerlistview extending ScrollView? Both large-list and FlatList build upon the same.
I wrote recyclerlistview and recently my team used this carousel component. We swapped FlatList with recyclerlistview and it works great.

Hey @naqvitalha, thanks for shining in!
From my experience, and until now, everything built upon a ScrollView ultimately shows performance limitations when there is a huge number of items to handle and/or feature limitations. But rest assured that my goal is to be proven wrong ;-)
Would you be interested in submitting a PR for this evolution so that it can be broadly and thoroughly tested?

@bd-arc Sure. Let me do that.

@naqvitalha @bd-arc Any status updates with the PR to replace flatlist with recyclerlistview? I would love to use it

Unrelated to ScrollView FlatList and recyclerlistview, but has anyone looked into how react-native-gesture-handler might be able to improve this lib?
From the docs:

With this library gestures are no longer controlled by the JS responder system, but instead are recognized and tracked in the UI thread. It makes touch interactions and gesture tracking not only smooth, but also dependable and deterministic.

It requires react-native link, which is unfortunate in terms of keeping this lib dependency free. But it is now included in Expo/CRNA.

Hey @pcooney10,
I've previously considered implementing a custom PanResponder on top of the ScrollView/FlatList one (as you can see in #40).
Have you tried something similar with react-native-gesture-handler? I'd love to get some feedback in order to determine if this is a legitimate idea or a straight way to madness...

@amitassaraf Contracts of this component are very similar to FlatList since props are passed down. For RLV layout provider is mandatory. It'll be a breaking change or we'll need to introduce a new mode.

Hello everyone, I want to share a little of my experience using this component. I needed to use it within ScrollView which generated the problem that all the items will be shown by more than you would indicate the property removeClippedSubviews the elements are not deleted from the memory, otherwise, each path created new elements causing the app to drain the RAM memory in Android To obtain a correct operation of the list within a ScrollView (or another list) use the following flat list properties.
maxToRenderPerBatch={4}

initialNumToRender={4}

windowSize={4}

removeClippedSubviews={Platform.OS != 'ios'}

Depending on your case, you can configure the values that best suit your needs. in this way you will have the expected performance with almost no memory leak

@machester4 Thanks for sharing your findings! Those values won't fit everyone's use case, but the approach is sound ;-)

You can apply that logic to your horizontal lists that are within a vertical list. in my case all my horizontal lists have 3 elements visible at a time. for that reason the values are of maxToRenderPerBatch and initialNumToRender are in 4 which is where I get a better experience for the user.

@naqvitalha Could you share how you replaced FlatList with RecylerView inside carousel?

@bd-arc Heads up, I am pretty sure this will affect react-native-snap-carousel clients:
https://github.com/facebook/react-native/issues/21070

Thanks for the heads up @PublicParadise!
FlatList never stops to amaze... It looks like an InteractionManager might be running somewhere, thus postponing the component logic's execution.
It's definitely time to get rid of FlatList for good :-)

Hi, any updates on this field so far?

Actually FlatList in my opinion has what it takes to become a really great list component.
All that it's missing is the concept of "estimated row height" that UITableView has on iOS.
So you DO NOT need a property for "how many rows should I layout asynchronously to do some hackery and trickery".
All we need is, as I said, an estimatedRowHeight (possibly with callback to allow different estimates per row, but still estimates!).

This will be used to calculate the content size of the scroll view.
Scrolling to an offset will scroll directly to it.
Whenever you render rows - cache their sizes after the are laid out.
Use cached sizes + estimated row heights to quickly calculate the offset to an item, or the item for an offset.
We can also not consider estimates/caches for all rows before a very high item index, just use some kind of window size, and an average estimate for the rest.

So content size will be changing dynamically but nobody will care about it or feel it, as you could scroll to last item or any other index and it will get there without glitches, and you won't be doing so much work that there will be missing items while scrolling.

Hi @naqvitalha, Do you have some branch or PR  about to migrate flatlist to RLV for this component? It will be very useful for me. Thanks.

Thank you for trying my component.
For almost all scenes, you should do it like this:
<Carousel  containerCustomStyle={{flex:1}} contentContainerCustomStyle={{flex:1}} renderItem={()=><LargeList ...props/>}/>

And ensure all the parents of Carousel contains {flex:1} style.
Pay attention to this tip:
LargeList default has a {flex:1} style，please be sure its parent has a bounded height.

LargeList can not work well if you want its items prop up LargeList's size. You should confirm your LargeList size is inherited from its parent or a a bounded height.
Forgive me for my pool English, if you understand Chinese. Check out this issue

The FlatList component is just too buggy, period.
These plugins may constitute an interesting replacement:
* https://github.com/Flipkart/recyclerlistview

* https://github.com/bolan9999/react-native-largelist

well said

Sorry, please allow me to advertise for my open source library! ~
I think this library react-native-reanimated-carousel will solve your problem. It is a high performance and very simple component, complete with React-Native reanimated 2


add prometheus metrics python sdk

What this PR does / why we need it:
Our users have come to us with a lot of questions regarding latencies in the kserve-container. As of now, we have no way to know the latencies of each step in the transformer/predictor. Having observability into the latency of each step will let us quickly identify which step is the bottleneck when request latencies are high. At the moment, there is no easy way to figure this out.
This PR adds prometheus histogram latency metrics for each step (pre/post processing, explain, predict) in the python SDK. The metrics are exposed on /metrics. Additionally, we will log the latency of each step per request id. If you choose not to use prometheus metrics, evaluating the logs is another option.
Which issue(s) this PR fixes (optional, in fixes #<issue number>(, fixes #<issue_number>, ...) format, will close the issue(s) when PR gets merged):
Fixes #
Type of changes
Please delete options that are not relevant.

[ ] Bug fix (non-breaking change which fixes an issue)
[x] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] This change requires a documentation update

Feature/Issue validation/testing:
Please describe the tests that you ran to verify your changes and relevent result summary. Provide instructions so it can be reproduced.
Please also list any relevant details for your test configuration.

[x] Test documented in transformer sample https://github.com/kserve/kserve/pull/2425/files#diff-a8d78136ac31d86dd82d5b2d24410ca6eb48265aae92c5ea63e360d56dfdf58aR148
I used the transformer to curl localhost:8080/metrics and see the prometheus metrics output.

Logs

Special notes for your reviewer:

Please confirm that if this PR changes any image versions, then that's the sole change this PR makes.

Checklist:

[x] Have you added unit/e2e tests that prove your fix is effective or that this feature works?
[ ] Has code been commented, particularly in hard-to-understand areas?
[x] Have you made corresponding changes to the documentation?

Release note:

Awesome work! @alexagriffith
/lgtm
/approve

@alexagriffith Can you help update the website doc for the new argument of the model server?
https://kserve.github.io/website/0.9/modelserving/v1beta1/custom/custom_model/#arguments


Some How-Tos i found helpful

What this PR does / why we need it:
I had to do some chores which were quite cumbersome. I hope these will help future me and others.
Which issue(s) this PR fixes (optional, in fixes #<issue number>(, fixes #<issue_number>, ...) format, will close the issue(s) when PR gets merged):
Fixes #
Special notes for your reviewer:
Does this PR introduce a user-facing change?:

@hc2p I would suggest we directly move this to our docs under https://docs.kubermatic.com/kubermatic/main/cheat-sheets/
What do you think?


468 Ripple not disabled on NavItem issue is fixed

Fixes #468 .

Changes proposed in this Pull Request:

Add MatRippledisabled properties to disable or enable based on ripple value

Screenshots / Screen Recording (if applicable)

To Test:

yarn test

Any specific feedback you are looking for?

@daileytj I have verified this ripple effect outside of the playground. Actually we have to test the ripple property in all "" items in the  component to get the expected result.

Exmple:


Updated DOKU API Endpoints

Updated to HTTPS endpoint as DOKU is not doing HTTPS redirection by default and has blocked the HTTP requests for both APIs and JS & CSS assets .

why sample code contains .xyz endpoint?


Documentation not clear about exit codes

Describe the bug
Not really a bug.
In your documentation https://github.com/aquasecurity/tfsec#running-in-ci you state For this reason it will exit with a non-zero exit code if a potential problem is detected. but this is not true as the exit code will be 0 when all finding are low.
The docs should me more clear about that.

thanks


Zoom?

Is there the ability or do you know how I could look at zooming in by a fraction? The height and width defined don't seem to change the ration only the bounding box.

@kieranbarlow I am not sure if i understand the question. You'd like the ability to zoom in and out in the video?


Request: Scoop package

Hi, first of all thanks for this app.
I think that being able to install it with scoop would be a great addition.
Right now you can't install the app through the command line at all I think (?), so we would need a switch on the .exe to (un)install it silently as well as another switch for installing the settings on the folder of the .exe, similar to the "Icons" folder (like a portable install).
Thanks

I really focus on mpv.net, which is in the Microsoft Store, which means that it has winget support, it's not exactly easy building and maintaining a store package. I prefer the Store UI over typing commands.

Should we interpret your closing words while not closing the ticket as "won't take initiatives, PRs welcome"?

I'm only looking superficially but it looks like chocolatey-community has precedents for automated github-releases-to-choco-package: https://github.com/chocolatey-community/chocolatey-packages/blob/master/automatic/bulk-crap-uninstaller/update.ps1


Native StrictMath.cosh() implemented

Hello,
Can someone look on Travis CI tests? It fails with weird:
"Warning: Task "ts:dev-cli" failed. Use --force to continue."
That seems unrelated to my commit and works in the same way on my local computer (adding --force make all tests passing)

Thanks for the PR! I see the Travis-CI issue; the node definitions in DefinitelyTyped now require TS 1.6. I have a local change that fixes the issue that I'll push soon, and that prevents this issue from happening in the future (by using the tsd tool to pull in definitions, rather than bower). For now, I'll merge this in!


Preventing harded code.

This simple pull request should avoid repeating some string many times. :)

Small syntax error in there. Would this still work in IE, FF, SA, OP? Do they all know the webkit transform?

@taffapsn thank you very much for your review.

Please run yarn build and commit .size-snapshot.json file

@TrySound @taffapsn it's done guys, thanks.


Added convenience methods in PermissionUtils

Added PermissionUtil.canTalk(User user, TextChannel channel) and convenience method PermissionUtil.canTalk(TextChannel channel)

As this was manually merged due to conflicts


Remove "Last updated" footer on pdf export

Last update is too intrusive in an exported document, where the update time does not have a "real time" relevance.

Not implementing  because this is already available as an asciidoc attribute :nofooter: .


Oauth2 Not Adding Token to Request Header

Expected Behavior
Oauth2 Middleware component for Authorization Code Grant flow is supposed to add the Bearer token to a request header after authentication.  This header is then sent along with the request to the app for validation and claims lookup. This works correctly in v1.9.
Actual Behavior
In v1.10, the Oauth2 Middleware component is adding the Bearer token to the Response headers instead of the Request headers. The token is going back to the client application which is not expected.
Steps to Reproduce the Problem

Simple controller to return headers (ASP.NET core / C#):

var app = WebApplication.Create(args);

app.MapGet("/Headers", (HttpRequest request) =>
{
    var headers = request.Headers;
    return new Microsoft.AspNetCore.Mvc.ObjectResult(headers);
});

app.Run();

Create component config

apiVersion: dapr.io/v1alpha1
kind: Component
metadata:
  name: oauth2
spec:
  type: middleware.http.oauth2
  version: v1
  metadata:
  - name: clientId
    value: <clientId>
  - name: clientSecret
    value: <clientSecret>
  - name: scopes
    value: "api://appId/TodoList.Read, api://appId/TodoList.ReadWrite"
  - name: authURL
    value: "https://login.microsoftonline.com/tenantId/oauth2/v2.0/authorize"
  - name: tokenURL
    value: "https://login.microsoftonline.com/tentId/oauth2/v2.0/token"
  - name: redirectURL
    value: "http://localhost:8080/v1.0/invoke/test/method/Headers"
  - name: authHeaderName
    value: "Authorization"

Configure middleware

apiVersion: dapr.io/v1alpha1
kind: Configuration
metadata:
  namespace: nginx
  name: dapr-config
spec:
  httpPipeline:
    handlers:
      - name: oauth2
        type: middleware.http.oauth2

Run dapr

dapr run --app-id test --config config.yaml --components-path ./components/ --app-port 5000 -H 8080 -- dotnet run --project ./src --urls http://localhost:5000

With daprd 1.9, we see the Bearer token header. In daprd 1.10, there is no Bearer token header.
Release Note
RELEASE NOTE: FIX Oauth2 middleware adds Bearer token to request headers.

Thanks for creating this issue. I think this happened while we migrated from fasthttp to net/http for the middlewares
What I don't understand however is why you'd need the bearer token added to the request? How I thought this middleware was being used was by adding this to the app pipeline so for example calls between Dapr sidecars have the bearer token.

@ItalyPaleAle We use the bearer token at the API endpoint. We validate the token and then enforce claim requirements (for example, Read, Write, ReadWrite, etc).
I'm not aware of how Dapr sidecars use the token.  Is their a Dapr feature somewhere that looks for the token and uses it for authorization?

We use the bearer token at the API endpoint. We validate the token and then enforce claim requirements (for example, Read, Write, ReadWrite, etc).

Would you mind getting a bit more into the details? What API are you referring to? Where are the calls coming from?

Its an HTML client calling to an ASP.NET Web API. Right now its just a POC sample for a customer. They are also looking at APIM to do the same, but I'd like to see the Dapr component continue to improve.
Program.cs:
// Add JWT authentication
builder.Services.AddAuthentication()
    .AddJwtBearer("Bearer", options =>
    {
        // Get configuration settings
        var tenantId = builder.Configuration["TenantId"];
        var audienceId = builder.Configuration["AudienceId"];

        // Get the OpenID configuration for the tenant
        var stsDiscoveryEndpoint = $"https://login.microsoftonline.com/{tenantId}/v2.0/.well-known/openid-configuration";
        var configurationManager = new ConfigurationManager<OpenIdConnectConfiguration>(stsDiscoveryEndpoint, new OpenIdConnectConfigurationRetriever());
        var openIdConfig = configurationManager.GetConfigurationAsync(CancellationToken.None).GetAwaiter().GetResult();

        // Configure the JWT validation using OpenID configuration
        options.TokenValidationParameters = new TokenValidationParameters
        {
            ValidIssuer = openIdConfig.Issuer,
            ValidAudiences = new[] { audienceId },
            IssuerSigningKeys = openIdConfig.SigningKeys,
        };
    });

// Add authorization using scopes (enables the [RequiredScope] attribute)
builder.Services.AddRequiredScopeAuthorization();

Controller example:
    [ProducesResponseType(typeof(IEnumerable<Todo>), StatusCodes.Status200OK)]
    [RequiredScope("TodoList.Read")]
    [HttpGet]
    public async Task<IActionResult> Get()
    {
        _logger.LogInformation($"TodoController.Get() called");
        return new ObjectResult(await _todos.GetList());
    }

I'll send you the repo which is private.


Add env vars for overriding GitHub / GitLab hostnames in the .netrc file.

Adds override env vars GITLAB_HOSTNAME and GITHUB_HOSTNAME to support authenticating against self-hosted GitLab / GitHub instances.
Fixes #20

@brendan-kellam Thank you for fix, however why do you use the env vars to build the .netrc file, instead of the settings from the config file? I'm asking because i'm trying to index repos from multiple self-hosted gitlab servers (so I have more than gitlab one hostname and token). It seems limited to just 1 if we rely on env var, while the config file is more flexible since you can have any number of entries in the Configs array, right?

Hey @loris - yea that's correct. Using env vars was a quick fix for the single self-hosted server scenario.
We are working on overhauling the config format atm and plan to support multiple host authentication (via the config). We expect to have that in sometime next week. See: #27


Silently ignore non-doc-comment comments.

As part of bytecodealliance/wasm-tools#1362, silently ignore comments that aren't /// comments. This won't break any actual code; it just means that documentation comments won't show up in generated bindings unless the /// syntax is used.
All wit files I've seen already use /// syntax for comments, so I expect the impact of this change will be low.

Given the recent switch to // away from /// and that this is going back, could this be turned off by default for now? Effectively allow either // or /// during this transitionary period with an env var to force // to get ignored


Map contigs to genomic coordinates

Description
As a  bioinformatician, I want to construct a lookup table/mapping of contigs to genomic coordinates.
Acceptance criteria

[ ] Extract contig information from chromosome.dat files
[ ] Map each contig to their respective genomic location
[ ] Store the lookup table in a repo

discuss @zperova


fix: Duplicate notifications are shown in diagnostics

Description
The BotIndexer.validate contains the checkskillsettings and checkLuisLocales

Task Item
closes #4858

Screenshots

Close this and will reopen it when fix all diagnostics issue


"pandas.error" when "primer_trimming"

Hello, me again. I am trying the primer_trimming, but I keep getting the error below. I followed your recommendations from a different issue, changing the "I" to "N" in my primers, as well as downgrading the cutadapt, but nothing has worked. Do you have any insights about what could be causing the problem?
Thank you again for your help :)

Can you please upload your settings.xlsx file?

Here it is:
Settings_TEN1AP.xlsx

Are you sure the primer sequences are correct? Is anything written at all?

Those are the primers:
reverse TAIACYTCIGGRTGICCRAARAAYCA
forward  GGWACWRGWTGRACWITITAYCCYCC
I have changed the Is to Ns, written on the table.

Okay, please write me a mail to my work address you can find on our website. I'll send you a shareable folder where you can upload the data so I can take a look. I'm not sure this is a user or apscale related problem.
best
Dominik

Ok, I just emailed you :)
Thank you for your help!

So: I cannot reproduce the problem, but I saw that your output says 3 input files. You uploaded only 2 for the PE mering, so I was wondering: Is there more data, you did not upload, or did you move the data in between processing steps?

Thank you for the message.
It says 3 files because it gets all the files in the pe_merging folder: the
2 files from the data + the PE merging output. Even if I change that, the
error remains the same.
Em qui., 5 de set. de 2024 às 14:14, DominikBuchner <
@.***> escreveu:

So: I cannot reproduce the problem, but I saw that your output says 3
input files. You uploaded only 2 for the PE mering, so I was wondering: Is
there more data, you did not upload, or did you move the data in between
processing steps?
—
Reply to this email directly, view it on GitHub
https://github.com/DominikBuchner/apscale/issues/16#issuecomment-2331366716,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AZN7PJPRQU3QY7GSQESM6F3ZVBDMDAVCNFSM6AAAAABNQMOZHKVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDGMZRGM3DMNZRGY
.
You are receiving this because you authored the thread.Message ID:
@.***>

The initial files go into 2_demultiplexing/data. The result of PE merging
will then be written to 3_pe_merging/data and will be the input of primer
trimming and so on.
francielleholtz @.***> schrieb am Do., 5. Sept. 2024,
18:56:

Thank you for the message.
It says 3 files because it gets all the files in the pe_merging folder:
the
2 files from the data + the PE merging output. Even if I change that, the
error remains the same.
Em qui., 5 de set. de 2024 às 14:14, DominikBuchner <
@.***> escreveu:

So: I cannot reproduce the problem, but I saw that your output says 3
input files. You uploaded only 2 for the PE mering, so I was wondering:
Is
there more data, you did not upload, or did you move the data in between
processing steps?
—
Reply to this email directly, view it on GitHub
<
https://github.com/DominikBuchner/apscale/issues/16#issuecomment-2331366716>,

or unsubscribe
<
https://github.com/notifications/unsubscribe-auth/AZN7PJPRQU3QY7GSQESM6F3ZVBDMDAVCNFSM6AAAAABNQMOZHKVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDGMZRGM3DMNZRGY>

.
You are receiving this because you authored the thread.Message ID:
@.***>

—
Reply to this email directly, view it on GitHub
https://github.com/DominikBuchner/apscale/issues/16#issuecomment-2332219370,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AJH6ILFU3SKUHLYIAD6NCXLZVCEMJAVCNFSM6AAAAABNQMOZHKVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDGMZSGIYTSMZXGA
.
You are receiving this because you commented.Message ID:
@.***>

Thank you for the clarification. I was doing it like that before and still
trying, but unfortunately, I keep getting the same error. I think I will
try to install it again.
(thesis) @.*** TEN1AP_apscale % apscale
--primer_trimming
13:36:55: Starting to trim primers of 1 input files.
joblib.externals.loky.process_executor._RemoteTraceback:
"""
Traceback (most recent call last):
File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/joblib/externals/loky/process_executor.py",
line 463, in _process_worker
r = call_item()

    ^^^^^^^^^^^

File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/joblib/externals/loky/process_executor.py",
line 291, in call
return self.fn(*self.args, **self.kwargs)

       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/joblib/parallel.py",
line 598, in call
return [func(*args, **kwargs)

        ^^^^^^^^^^^^^^^^^^^^^

File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/apscale/c_primer_trimming.py",
line 45, in primer_trimming
log_df = pd.read_csv(StringIO(f.stdout.decode("ascii",

errors="ignore")), sep="\t")
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/pandas/io/parsers/readers.py",
line 1026, in read_csv
return _read(filepath_or_buffer, kwds)

       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/pandas/io/parsers/readers.py",
line 620, in _read
parser = TextFileReader(filepath_or_buffer, **kwds)

         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/pandas/io/parsers/readers.py",
line 1620, in init
self._engine = self._make_engine(f, self.engine)

               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/pandas/io/parsers/readers.py",
line 1898, in _make_engine
return mapping[engine](f, **self.options)

       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/pandas/io/parsers/c_parser_wrapper.py",
line 93, in init
self._reader = parsers.TextReader(src, **kwds)

               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

File "parsers.pyx", line 581, in pandas._libs.parsers.TextReader.cinit
pandas.errors.EmptyDataError: No columns to parse from file
"""
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/Applications/anaconda3/envs/thesis/bin/apscale", line 8, in

sys.exit(main())

         ^^^^^^

File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/apscale/main.py",
line 137, in main
c_primer_trimming.main()

File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/apscale/c_primer_trimming.py",
line 153, in main
Parallel(n_jobs=cores)(

File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/joblib/parallel.py",
line 2007, in call
return output if self.return_generator else list(output)

                                            ^^^^^^^^^^^^

File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/joblib/parallel.py",
line 1650, in _get_outputs
yield from self._retrieve()

File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/joblib/parallel.py",
line 1754, in _retrieve
self._raise_error_fast()

File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/joblib/parallel.py",
line 1789, in _raise_error_fast
error_job.get_result(self.timeout)

File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/joblib/parallel.py",
line 745, in get_result
return self._return_or_raise()

       ^^^^^^^^^^^^^^^^^^^^^^^

File
"/Applications/anaconda3/envs/thesis/lib/python3.12/site-packages/joblib/parallel.py",
line 763, in _return_or_raise
raise self._result

pandas.errors.EmptyDataError: No columns to parse from file
(thesis) @.*** TEN1AP_apscale %
Em qui., 5 de set. de 2024 às 22:13, DominikBuchner <
@.***> escreveu:

The initial files go into 2_demultiplexing/data. The result of PE merging
will then be written to 3_pe_merging/data and will be the input of primer
trimming and so on.
francielleholtz @.***> schrieb am Do., 5. Sept. 2024,
18:56:

Thank you for the message.
It says 3 files because it gets all the files in the pe_merging folder:
the
2 files from the data + the PE merging output. Even if I change that,
the
error remains the same.
Em qui., 5 de set. de 2024 às 14:14, DominikBuchner <
@.***> escreveu:

So: I cannot reproduce the problem, but I saw that your output says 3
input files. You uploaded only 2 for the PE mering, so I was
wondering:
Is
there more data, you did not upload, or did you move the data in
between
processing steps?
—
Reply to this email directly, view it on GitHub
<

https://github.com/DominikBuchner/apscale/issues/16#issuecomment-2331366716>,

or unsubscribe
<

https://github.com/notifications/unsubscribe-auth/AZN7PJPRQU3QY7GSQESM6F3ZVBDMDAVCNFSM6AAAAABNQMOZHKVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDGMZRGM3DMNZRGY>

.
You are receiving this because you authored the thread.Message ID:
@.***>

—
Reply to this email directly, view it on GitHub
<
https://github.com/DominikBuchner/apscale/issues/16#issuecomment-2332219370>,

or unsubscribe
<
https://github.com/notifications/unsubscribe-auth/AJH6ILFU3SKUHLYIAD6NCXLZVCEMJAVCNFSM6AAAAABNQMOZHKVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDGMZSGIYTSMZXGA>

.
You are receiving this because you commented.Message ID:
@.***>

—
Reply to this email directly, view it on GitHub
https://github.com/DominikBuchner/apscale/issues/16#issuecomment-2332551593,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AZN7PJMU3W4EZQRG5I7DAELZVC3O3AVCNFSM6AAAAABNQMOZHKVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDGMZSGU2TCNJZGM
.
You are receiving this because you authored the thread.Message ID:
@.***>

For anyone experiencing this issue: Settings the core to process to 1 fixes this for now. Will be fixed in a future update!


Kafka 3618: Handle ApiVersionsRequest before SASL authentication

Server-side implementation and tests for handling ApiVersionsRequest before SaslHandshakeRequest.

This is currently built on top of the PR for KAFKA-3617. The latest commit corresponds to this PR.

@rajinisivaram, can you please rebase?

The general approach seems fine. I left one comment and I didn't review the test changes in detail as they will change a bit after the rebase (as a new helper method was added to the test in the previous PR).

@ijuma Rebasing now, will submit soon, thanks.


MaSIF v2 source code

Hi there,
Have you, are your planning to, release the source code from the recent biorxiv paper?
Thanks

+1 I am also very eager to access the codebase for your new model!

+1 I am also very eager to access the codebase for your new model!

Hi!
Thanks for the interest in our new method!
We are not quite yet ready to release the source code but we aim to do so as soon as possible.
I'll let you know when we publish it online.

Hi!
Thanks for the interest in our new method!
We are not quite yet ready to release the source code but we aim to do so as soon as possible.
I'll let you know when we publish it online.

Awesome, looking forward to it @FreyrS, cool work!
Quick Q. while I have you here:
For dMaSIF, when compared to PointNet++ and DGCNN, could you talk about why your new convolution is so much faster as well as taking lesser memory per sample, as shown in Fig. 11, 12? Could you highlight which design choice leads to this, e.g. is PN++ so much slower because it is doing multi-scale operations while dMaSIF and DGCNN are not? (Esp. considering that both these baselines are also using KeOps speedups...)

Awesome, looking forward to it @FreyrS, cool work!
Quick Q. while I have you here:
For dMaSIF, when compared to PointNet++ and DGCNN, could you talk about why your new convolution is so much faster as well as taking lesser memory per sample, as shown in Fig. 11, 12? Could you highlight which design choice leads to this, e.g. is PN++ so much slower because it is doing multi-scale operations while dMaSIF and DGCNN are not? (Esp. considering that both these baselines are also using KeOps speedups...)

Hey!
I'm going to copy an answer from my co-author Jean Feydy who is one of the main developers for KeOps:
"If I am not mistaken, this is because our implementation keeps the number of channels very low, and does not store any of the intermediate results such as the «activation maps» in K-NN neighbourhoods.
Using KeOps for the «full convolutions» implements «checkpointing» out if the box: you get a super small memory footprint, at the cost of a slightly slow-down in the backward step.
I must stress that even if we use KeOps in the KNN query for the Dgcnn convolutions, we still have to pay a significant time and memory cost to build the point neighbourhoods as (N,K,D) arrays using scattered memory accesses (an operation that really does not stream well on GPUs).
As discussed briefly in the dMasif paper, and in more detail in the KeOps doc and NeurIPS paper, the typical size of problems that we encounter in protein sciences / shape analysis (= batches of clouds of 2k-20k 3D points each) really hits a sweet spot for KeOps.
It's a setting where the data is large enough to make GPUs worthwhile, but also small enough to make brute-force methods more efficient than graph-based implementations.
This is not an accident, of course: the first motivation for the library has always been to accelerate this range of computations, for applications to computational anatomy and biomedical imaging."

Hey!
I'm going to copy an answer from my co-author Jean Feydy who is one of the main developers for KeOps:
"If I am not mistaken, this is because our implementation keeps the number of channels very low, and does not store any of the intermediate results such as the «activation maps» in K-NN neighbourhoods.
Using KeOps for the «full convolutions» implements «checkpointing» out if the box: you get a super small memory footprint, at the cost of a slightly slow-down in the backward step.
I must stress that even if we use KeOps in the KNN query for the Dgcnn convolutions, we still have to pay a significant time and memory cost to build the point neighbourhoods as (N,K,D) arrays using scattered memory accesses (an operation that really does not stream well on GPUs).
As discussed briefly in the dMasif paper, and in more detail in the KeOps doc and NeurIPS paper, the typical size of problems that we encounter in protein sciences / shape analysis (= batches of clouds of 2k-20k 3D points each) really hits a sweet spot for KeOps.
It's a setting where the data is large enough to make GPUs worthwhile, but also small enough to make brute-force methods more efficient than graph-based implementations.
This is not an accident, of course: the first motivation for the library has always been to accelerate this range of computations, for applications to computational anatomy and biomedical imaging."

@FreyrS thanks for releasing the code!
For everyone else on this thread:
https://github.com/FreyrS/dMaSIF

@agamemnonc thanks a lot for updating this issue! I had completely forgotten about it, sorry about that!


Use realtime database Emulator from Unity

[REQUIRED] Please fill in the following fields:

Unity editor version: 2020.3.25f1
Firebase Unity SDK version: 8.7.0
Source you installed the SDK: .unitypackage (.unitypackage or Unity Package Manager)
Problematic Firebase Component: Database (Auth, Database, etc.)
Other Firebase Components in use: Database, Auth, Config (Auth, Database, etc.)
Additional SDKs you are using: _____ (Facebook, AdMob, etc.)
Platform you are using the Unity editor on: Windows (Mac, Windows, or Linux)
Platform you are targeting: Emulator (desktop) (iOS, Android, and/or desktop)
Scripting Runtime: IL2CPP (Mono, and/or IL2CPP)

[REQUIRED] Please describe the issue here:
Unity crash if use local instance of Database (Emulator)
In unity crash log:
ERROR: Could not initialize persistence: Unable to find app data directory.
Crash !!!
Steps to reproduce:
Use this code to connect to the emulator
Relevant Code:
FirebaseApp.CheckAndFixDependenciesAsync().ContinueWithOnMainThread(async task =>
        {
            var dependencyStatus = task.Result;
            if (dependencyStatus == DependencyStatus.Available)
            {
                FirebaseDatabase db = Firebase.Database.FirebaseDatabase.GetInstance("http://localhost:9000/?ns=myns");
                var snapshot = await db.GetReference("test").GetValueAsync();
                Debug.Log("The value: " + snapshot.Value);
            }
        });

Hi @DiscoverTravel,
Could you provide the complete and detailed steps to replicate this behavior? I haven't encountered the issue using the information you provided so far.

Hi @paulinon,
Thanks for the reply.
The steps are simple:

I created a new unity 3D project on windows
I have set up the Android platform
I imported the realtime database package (sdk version 8.7.0)
I added the google-service.json file in the assets folder
I started the database emulator
I ran the indicated code

Thanks for the additional information, @DiscoverTravel. Could you provide the full script containing the relevant code? I still haven't encountered the error message, and I think I may be missing something in my implementation.

Hi @paulinon,
this is the code.
Remember to attach it as a script component to a GameObject of the project.
Best regards
using Firebase;
using Firebase.Database;
using Firebase.Extensions;
using UnityEngine;

public class FirebaseManager : MonoBehaviour
{

    void Start()
    {
        FirebaseApp.CheckAndFixDependenciesAsync().ContinueWithOnMainThread(task =>
        {

            var dependencyStatus = task.Result;
            if (dependencyStatus == DependencyStatus.Available)
            {

                Debug.Log("Firebase is ok");
                var app = FirebaseApp.DefaultInstance;

                FirebaseDatabase db = Firebase.Database.FirebaseDatabase.GetInstance("http://localhost:9000/?ns=corri-verso-il-castello-default-rtdb");
                db.GetReference("test").GetValueAsync().ContinueWithOnMainThread(task =>
                   {
                       if (task.IsFaulted)
                       {
                           Debug.Log("Error");
                       }
                       else if (task.IsCompleted)
                       {
                           DataSnapshot snapshot = task.Result;
                           Debug.Log(snapshot.Value);
                       }
                   });
            }
            else
            {
                UnityEngine.Debug.LogError(System.String.Format("Could not resolve all Firebase dependencies: {0}", dependencyStatus));
            }
        });
    }

}

Thanks for that, @DiscoverTravel. I wasn't able to replicate the issue using the steps you provided, but I did encounter the error message whenever Force Resolve returned an error.
Could you confirm if there are issues when going to Assets > External Dependency Manager > Android Resolver > Force Resolve? If there aren't any, could you replay the scene and see if the issue persists?

Hello,
for me the problem still exists.
Force resolve succeeds.
There are other threads on the web about this issue.
I don't know what to add ...
Windows 10
Greetings

Hi @DiscoverTravel,
It's possible that you're facing a setup-related issue. Also, I got word from the team that this isn't officially supported yet as the Firebase Local Emulator Suite is currently in Beta. That being said, I'll mark this as a feature request for now.
You may refer to this thread for any updates.

Plus 1 for this feature please! It would greatly reduce the friction in our automated testing workflow.


Two fixes to thriftpy_gevent_worker.py for py3 compat

First fix: Wrap low-level "thread" import with try-except to fallback to
the Python 3-specific "_thread" module.
Second fix: Remove now-obsolete tuple-unpacking syntax from
_greenlet_switch_tracer method signature, and replace with
vesion-agnostic tuple unpack in method body.

In the process of fixing the tests

Test requirements updated. Note that this PR changes py27 requirements to use gevent 1.2(.2), and the env requirement to remove the <1.2 guard. If there's some reason I'm missing that would make that a bad idea, it's highly likely they can both be set back down to the lower version, but it should be fine as long as you're reasonably sure this project's tests exercise what they need to exercise.
Will probably need a version increment, but I'm not familiar enough with this project's standards to know what your bar is for that, or whether it belongs in the PR itself.

@wooparadog Any chance this can get looked at? I'd like to stop using a github reference in my requirements files.

@aawilson Thanks for your contribution, sorry about not having time to look at your pull request. But I'll look into it within this week.


PytorchLightning can't execute the val step

Bug description
I need to rewrite sampler to handle sequences of different lengths. Butthe val step can't be executed by PytorchLightning, when I had rewrited a Sampler for Dataloader,
How to reproduce the bug
class MyDataloader(pl.LightningDataModule):
    ...
    def train_dataloader(self):
        train_dataset = TimeseriesDataset(self.x_train, self.y_train, seq_len=self.seq_len,
                        pre_step=self.pre_step)
        train_loader = DataLoader(train_dataset, batch_size=self.batch_size, shuffle=False,
                       num_workers=0, drop_last=True, sampler=TruncateSampler(self.x_train, self.x_train_len))
        return train_loader

    def val_dataloader(self):
        val_dataset = TimeseriesDataset(self.x_val, self.y_val, seq_len=self.seq_len, pre_step=self.pre_step)
        val_loader = DataLoader(val_dataset, batch_size=self.batch_size, shuffle=False, num_workers=0, drop_last=True,
                                sampler=TruncateSampler(self.x_val, self.x_val_len))
        return val_loader

    def test_dataloader(self):
        test_dataset = TimeseriesDataset(self.x_test, self.y_test, seq_len=self.seq_len,
                                         pre_step=self.pre_step)
        test_loader = DataLoader(test_dataset, batch_size=self.batch_size, shuffle=False, num_workers=0,
                      drop_last=True, sampler=TruncateSampler(self.x_test, self.x_test_len))
        return test_loader

class LitLSTM(pl.LightningModule):
    ...
    def training_step(self, batch, batch_idx):
        print(f'train {batch_idx}')
        x, y = batch
        y_hat = self(x)
        loss = self.loss_calculation(y_hat, y)
        self.log('train_loss', loss, on_step=True, on_epoch=True, prog_bar=True, logger=True)
        return loss

    def validation_step(self, batch, batch_idx):
        print(f'val {batch_idx}')
        x, y = batch
        y_hat = self(x)
        loss = self.loss_calculation(y_hat, y)
        self.log('val_loss', loss, on_step=True, on_epoch=True, prog_bar=True, logger=True)
        return loss

    def test_step(self, batch, batch_idx):
        x, y = batch
        y_hat = self(x)
        loss = self.loss_calculation(y_hat, y)
        self.log('test_loss', loss, on_step=True, on_epoch=True, prog_bar=True, logger=True)
        return loss

    def configure_optimizers(self):
        return torch.optim.Adam(self.parameters(), lr=self.learning_rate)

...

trainer = Trainer(
        max_epochs=p['max_epochs'],
        accelerator='gpu',
        devices=1 if torch.cuda.is_available() else None,
        logger=CSVLogger(save_dir="logs/TruncateLSTM", name=f'TruncateLSTM', version=1),
        check_val_every_n_epoch=1
    )
    # trainer.tune(model, datamodule=data_module)
    trainer.fit(model, data_module)

Error messages and logs
# Error messages and logs here please

Environment

Current environment
#- Lightning Component: Trainer, LightningModule)
#- PyTorch Lightning Version: 1.8.6
#- PyTorch Version:2.0
#- Python version: 3.10
#- OS: Windows
#- CUDA/cuDNN version: 11.8
#- GPU models and configuration:
#- How you installed Lightning: pip
#- Running environment of LightningApp: local

It can be seen that it didn't execute val step in the training process but  skipped the val process and went directly to the next epoch. If I don't pass the Sampler to the dataloader, the program can execute the val step.
More info
No response

When I set val_check_interval=0.25, the problem can be solven.

Can you provide a reproducible runable snippet? I don't see what's the problem with the info you provided. You can use this script to reproduce it: https://github.com/Lightning-AI/lightning/blob/master/examples/pytorch/bug_report/bug_report_model.py

It is possible that your validation dataloader is empty. Did you check that it's actually returning samples?

Closing (stale). Since you mentioned that a custom sampler is used, the most likely reason why it is skipping validation is because your sampler len(sampler) returns 0 or raises stop iteration.


Make dbt 'schema-aware'

Describe the feature
Today, dbt makes it very easy to make changes to existing models. On top, the dbt model selection syntax makes it easy to deploy different sets of models, including single models and models together with their parents and/or children (even a given number of parents/children as from dbt 0.18.0).
One downside of this flexibility of dbt is that there is no protection against a user making a 'backwards incompatible' change to a model, which can have direct repercussions on child models. Under  'backwards incompatible change' you can classify most importantly the change of a column's name or the removal of a column. Indeed, if you have a child model that selects such a column, it will fail on the next run (if that child model is materialised as a view, that view will even become invalid immediately). Yes, when you would deploy the parent model together with it's children in the same dbt run, you will get an error at the moment the child model is deployed, but at that point the harm is already done as the parent model with the change has already been deployed.
So, it could be an idea to make dbt more 'schema aware' and able to detect when a user tries to deploy a model that contains an incompatible change compared to it's previous deployment. At that point, dbt can at least raise a warning, but we could make it configurable by the user that dbt even blocks the deployment at this point and forces you to fix the downstream models.
I'm not directly proposing a solution here as I think implementing something like this will be a complex undertaking, but it would be nice to start the discussion about what role the dbt framework should take here in the future.
Who will this benefit?
This will benefit all users of dbt, regardless of the database being used.
PS: @drewbanin let's continue the slack discussion here

Thanks for the discussion above @bodschut! You're right that this is an important issue, and any implementation would be complex undertaking.
In general, our approach has been to run CI jobs that build and test all child models any time there is a proposed change to an existing model. It's a brute-force approach, in that it requires materializing models in a scratch schema in the database. We've got some significant work in progress to power slimmer and smarter CI jobs (see https://github.com/fishtown-analytics/dbt/issues/2465). I know some people who have hacked quick-and-dirty version of this, e.g. by adding limit 0 to all models in CI to quickly pick up any syntax, data type, or missing/renamed column errors.

At that point, dbt can at least raise a warning, but we could make it configurable by the user that dbt even blocks the deployment at this point and forces you to fix the downstream models.

Through an automated CI tool and a git workflow, you get this by requiring passing checks before merge. So while not a perfect answer, it's pretty darn good. If you're worried about breaking changes that may affect non-dbt processes (e.g. BI, ML) that select from dbt models, you could create views or data tests that mock their queries and run those assets in CI.
Without going too far on a tangent, this issue does remind of an issue/idea from a long time ago (https://github.com/fishtown-analytics/dbt/issues/1158): the ability to "extend" YML config from upstream models into downstream models, so as to copy a given column's metadata (name, description, tests). That still wouldn't prevent breaking changes, but it feels spiritually connected to your desire for dbt to know more and be more opinionated about the relationships between models that are connected in the DAG.

Hi @jtcohen6
Thanks for your take on this. I was not aware on the work on issue #2465 , very interesting! Is there any roadmap for implementing this functionality?
I guess that what I am proposing here takes it even a step further. I agree that you can get a long way using CI/CD, but you must agree that it's always quite some overhead to setup a good CI/CD setup for each project, as the complexity can greatly differ from project to project. Catching backwards incompatible changes at compile time would greatly reduce the complexity and 'hacks' that need to be setup at CI/CD levels.
I agree, implementing something like this would be a big undertaking. It would start by introducing a kind of 'schema registry', where the output schema of each model can be registered and subsequent updates can be checked for changes and warn at compile time whether the introduced changes are backwards compatible or not. At veepee, we actually developed and open sourced such a schema registry to govern our incoming raw data streams (that are subsequently registered in dbt as sources). If you're interested in taking a look, it's here. When you would take an approach like this, you can also automatically 'version' your model and build a complete change history that could afterwards be an interesting addition to the docs site (e.g. minor version bumps for compatible changes and major version bumps for breaking changes).
If you're up to it, I would also be interested to learn a bit more into detail how you setup your CI/CD strategy, as I'm feeling that ours is still suboptimal at the moment...
Anyway, happy to hear some further thoughts :-)
Cheers


utf-8 and Python compiler

Hi all,
If I compile online with ² or ° in the text, I get no issues. With the Python compiler it does not work, I need to write Â² or Â°.
Any idea why and how to fix it to be portable?
Thanks.

execute python with the flag -Xutf8


Entity Hitbox Improvements

Includes the changes from #45 plus a large number of improvements

Lots of cosmetic changes that don't change the semantics but improve readability, consistency, and reduce the number of lines of code.
Redesigned the shulker hitbox code.
Fixed rounding bug in painting rotation logic.
Fixed bug in item frame hitbox code.
Fixed glow item frame object data not being sent.
Added a shulker bullet cursor to the entity_raycast.rs to show where the intersection is. This would probably be done better with particles but we don't have those yet.
More entities in entity_raycast.rs.

Testing
Run the entity_raycast example (replaces raycast).
Things Left to Resolve

[ ] The slime/magma cube hitbox code was incorrect because the info on wiki.vg is outdated. I made a guess that appears to be correct but confirmation would be good.
[ ] The Warden emerging hitbox is wrong.

Btw @guac420 Check this out for the painting rotations https://www.desmos.com/calculator/m97ozjy5cz


bugfix: opensearch update OPENSEARCH_HOSTS

fix https://github.com/apecloud/kubeblocks/issues/8653

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 0.00%. Comparing base (f5bb1bc) to head (6c01cd4).

Additional details and impacted files
@@          Coverage Diff          @@
##            main   #1342   +/-   ##
=====================================
  Coverage   0.00%   0.00%
=====================================
  Files         69      69
  Lines       6685    6685
=====================================
  Misses      6685    6685

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

/cherry-pick release-1.0-beta


Running a dedicated instance

My json is running successfully. Now I want to run this workflow in a dedicated cog instance to skip queue time and improve performance. I want to include only the models and custom nodes that are used in the workflow. Can I include the models and custom nodes in the image file that is pushed to replicate so that they are not downloaded again and again. Any detailed guide on how to implement this would be helpful. Thanks.

Downloading the weights is faster than baking them into the container, this is because we can download weights more aggressively (in parallel from a hot cache using multiple connections) as opposed to docker container layers which load more slowly (it's counterintuitive but it's the fastest)
As for a dedicated instance, couple of choices:
1. Simplest – make a deployment of the model
https://replicate.com/deployments/create

2. Fork this repo and push your own cog image
Uou can then make sure weights are downloaded during setup rather than at predict time (this is still faster than putting them in the container). You'll need to do this on a GPU. There are good guides here:

https://cog.run/getting-started-own-model/
https://cog.run/deploy/

This is an example of how I've done that:
https://github.com/fofr/cog-comfyui-kolors
You can also run the script scripts/prepare_template.py to remove a lot of the code needed for a generic JSON model and replace it with a predict.py file that works from a fixed JSON file and modifies just the values within that file. (Example of that that does
3. Make a "training" of any-comfyui-workflow
This is simple but also a little bit hacky. You can visit the train tab and generate your own new comfyui model that's exactly the same as the one you've been using, but it'll be your personal one.
https://replicate.com/fofr/any-comfyui-workflow/train
You'll need to include some weights from HuggingFace or CivitAI that you want to use there (they'll get downloaded, bundled up and then loaded from our fast cache during setup at point of use)

Let me know how you get on. There's still lots of work to do to make this easier.

Thanks for the guide. I didn't know that downloading is faster than baking them. While running workflows I find variations in the time it takes for the same model to download. Sometimes it takes 3 seconds while at other times it takes 16 seconds.
I find deployments to be the easiest but I don't want to be billed for idle time and setup time. The second option is good but little complex. Maybe I'll go with the deployment if I am unable to push a working modified cog or train one.
How do I ensure that the weights are downloaded during setup rather than at predict time. Going by the example (https://github.com/fofr/cog-comfyui-kolors) Does the code below download the models during setup?
    self.comfyUI.handle_weights(
        {},
        weights_to_download=[
            "checkpoints/chatglm3-fp16.safetensors",
            "Kolors",
            "sdxl_vae.safetensors",
        ],
    )

ok..will try it out...thanks

Hi fofr, I have create an instance using the 3rd option: Make a "training" of any-comfyui-workflow. I added the link to the checkpoint model from HuggingFace. Now when I run the instance, it runs successfully and the checkpoint model is not downloaded as it already exists in the directory. However other models are downloaded as there wasn't any option to place the url's during training. The training was successful.
Now when running workflows, I noticed that occasionally it forgets to download some models and the run fails. I need to wait for the instance to become "cold" and when it boots again then prediction is successful. Why does this happen and can I place all the required models during training somehow?
Prediction failed.
segm/face_yolov8n-seg2_60.pt unavailable. View the list of available weights: https://github.com/fofr/cog-comfyui/blob/main/supported_weights.md
Checking weights
✅ Realistic_Vision_V6.0_NV_B1_inpainting_fp16.safetensors exists in ComfyUI/models/checkpoints
⏳ Downloading CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors to ComfyUI/models/clip_vision
✅ CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors downloaded to ComfyUI/models/clip_vision in 1.63s, size: 2411.24MB
⏳ Downloading bbox/hand_yolov8s.pt to ComfyUI/models/ultralytics/bbox
✅ bbox/hand_yolov8s.pt downloaded to ComfyUI/models/ultralytics/bbox in 0.11s, size: 21.44MB
⏳ Downloading bbox/face_yolov8m.pt to ComfyUI/models/ultralytics/bbox
✅ bbox/face_yolov8m.pt downloaded to ComfyUI/models/ultralytics/bbox in 0.13s, size: 49.59MB
Traceback (most recent call last):
File "/root/.pyenv/versions/3.10.6/lib/python3.10/site-packages/cog/server/worker.py", line 221, in _predict
result = predict(**payload)
File "/src/predict.py", line 105, in predict
wf = self.comfyUI.load_workflow(workflow_json or EXAMPLE_WORKFLOW_JSON)
File "/src/comfyui.py", line 218, in load_workflow
self.handle_weights(wf)
File "/src/comfyui.py", line 92, in handle_weights
self.weights_downloader.download_weights(weight)
File "/src/weights_downloader.py", line 45, in download_weights
raise ValueError(
ValueError: segm/face_yolov8n-seg2_60.pt unavailable. View the list of available weights: https://github.com/fofr/cog-comfyui/blob/main/supported_weights.md

I am trying method 2 now. I think I'll fork "https://github.com/fofr/cog-comfyui-kolors" and then modify predict.py, workflow_api.json, custom_nodes.json and try to push it without running it as I don't have a powerful gpu. Hopefully it works.

I was able to push cog successfully. I pushed all the models in the container itself. You were right as the starting (loading) time increased to about 3 minutes but the predict time decreased to 5 seconds. I then used A100 (80gb) GPU but the loading time was still 2 minutes. So downloading during setup is still ok. Decreasing the loading time to less than 30 seconds would be awesome.


Support sending all metadata

We want to send all metadata to our server, without defining it first in a configuration.
The console Logger supports this option: metadata: :all
https://hexdocs.pm/logger/Logger.html
Could this be possible here too please?

Or was is already supported?
https://github.com/jschniper/gelf_logger/commit/0c089fe7e82b4c22634e12f5c3cc13d20b6e71c1

I tried metadata: [:all] in our application and it did not work :(

metadata: :all it is :)


Wrong Array of Array encoding result...

When I pass this object to a get parameter (notice that order is array of array)
filter: {
   "order": [
      ["name", "ASC"]
   ]
}

Alamofire encodes: filter[order][][]=name&filter[order][][]=ASC
However I need to encode like: filter[order][0][0]=name&filter[order][0][1]=ASC
How could I do that?

Unfortunately there is no standardized method of encoding an array into a URL. Or, I should say, there are many, and Alamofire chose one particular method. If you need a particular encoding, creating your own ParamterEncoding is outlined in our documentation.


[CH] Not found column: when merge spilled aggregated data from disk

Backend
CH (ClickHouse)
Bug description
[Expected behavior] and [actual behavior].
Caused by: org.apache.gluten.exception.GlutenException: Not found column count(1_341)_351 in block. There are only columns: col_0, col_3, col_4, col_5, col_6, multiIf(equals_262,nlp_263,equals_273,keywords_274,if_282), broadcast_right_remark#125, broadcast_right_post_id#100, equals_292, if(equals_292,1_293,0_294), if(and_296,1_297,0_298), if(and_308,1_309,0_310), if(and_313,1_314,0_315), if(and_318,1_319,0_320), if(and_323,1_324,0_325), if(and_328,1_329,0_330), if(and_333,1_334,0_335), if(and_338,1_339,0_340), 1_341, toNullable_342, toNullable_343, toNullable_344, toNullable_345, toNullable_346, toNullable_347, toNullable_348, toNullable_349, toNullable_350: While executing GraceAggregatingTransform
0. ../contrib/llvm-project/libcxx/include/exception:141: Poco::Exception::Exception(String const&, int) @ 0x00000000150a4a19
1. ./build/../src/Common/Exception.cpp:109: DB::Exception::Exception(DB::Exception::MessageMasked&&, int, bool) @ 0x0000000006ad961c
2. ../src/Common/Exception.h:111: DB::Exception::Exception(PreformattedMessage&&, int) @ 0x00000000069c56ac
3. ../src/Common/Exception.h:129: DB::Exception::Exception<String const&, String>(int, FormatStringHelperImpl<std::type_identity<String const&>::type, std::type_identity<String>::type>, String const&, String&&) @ 0x0000000006a6b86b
4. ./build/../src/Core/Block.cpp:313: DB::Block::getByName(String const&, bool) const @ 0x000000000f0d044e
5. ./build/../src/Interpreters/Aggregator.cpp:272: DB::Aggregator::Params::makeAggregateColumnsData(DB::Block const&) const @ 0x000000000f6d81b1
6. ./build/../src/Interpreters/Aggregator.cpp:2806: void DB::Aggregator::mergeStreamsImpl<DB::AggregationMethodSerialized<HashMapTable<StringRef, HashMapCellWithSavedHash<StringRef, char*, DefaultHash<StringRef>, HashTableNoState>, DefaultHash<StringRef>, HashTableGrowerWithPrecalculation<8ul>, Allocator<true, true>>, true, true>, HashMapTable<StringRef, HashMapCellWithSavedHash<StringRef, char*, DefaultHash<StringRef>, HashTableNoState>, DefaultHash<StringRef>, HashTableGrowerWithPrecalculation<8ul>, Allocator<true, true>>>(DB::Block, DB::Arena*, DB::AggregationMethodSerialized<HashMapTable<StringRef, HashMapCellWithSavedHash<StringRef, char*, DefaultHash<StringRef>, HashTableNoState>, DefaultHash<StringRef>, HashTableGrowerWithPrecalculation<8ul>, Allocator<true, true>>, true, true>&, HashMapTable<StringRef, HashMapCellWithSavedHash<StringRef, char*, DefaultHash<StringRef>, HashTableNoState>, DefaultHash<StringRef>, HashTableGrowerWithPrecalculation<8ul>, Allocator<true, true>>&, char*, DB::ColumnsHashing::LastElementCacheStats&, bool, DB::Arena*) const @ 0x000000000f776796
7. ./build/../src/Interpreters/Aggregator.cpp:2926: DB::Aggregator::mergeOnBlock(DB::Block, DB::AggregatedDataVariants&, bool&, std::atomic<bool>&) const @ 0x000000000f6e6bea
8. ./build/../utils/extern-local-engine/Operator/GraceAggregatingTransform.cpp:510: local_engine::GraceAggregatingTransform::mergeOneBlock(DB::Block const&, bool) @ 0x00000000070a1fbf
9. ./build/../utils/extern-local-engine/Operator/GraceAggregatingTransform.cpp:400: local_engine::GraceAggregatingTransform::prepareBucketOutputBlocks(unsigned long) @ 0x00000000070a2c39
10. ./build/../utils/extern-local-engine/Operator/GraceAggregatingTransform.cpp:158: local_engine::GraceAggregatingTransform::work() @ 0x00000000070a1168
11. ./build/../src/Processors/Executors/ExecutionThreadContext.cpp:47: DB::ExecutionThreadContext::executeTask() @ 0x00000000119d3c22
12. ./build/../src/Processors/Executors/PipelineExecutor.cpp:289: DB::PipelineExecutor::executeStepImpl(unsigned long, std::atomic<bool>*) @ 0x00000000119c8f1f
13. ./build/../src/Processors/Executors/PipelineExecutor.cpp:255: DB::PipelineExecutor::executeImpl(unsigned long, bool) @ 0x00000000119c86dd
14. ./build/../src/Processors/Executors/PipelineExecutor.cpp:126: DB::PipelineExecutor::execute(unsigned long, bool) @ 0x00000000119c84cb
15. ./build/../utils/extern-local-engine/Parser/LocalExecutor.cpp:130: local_engine::LocalExecutor::execute() @ 0x0000000006eb7402

Spark version
None
Spark configurations
No response
System information
No response
Relevant logs
No response

May be caused by https://github.com/apache/incubator-gluten/pull/7968

The header is not right for building a tmp file
https://github.com/apache/incubator-gluten/blob/e56da333dc33de90540efa6dc63efa70c3c71ce8/cpp-ch/local-engine/Operator/GraceAggregatingTransform.cpp#L352
This is a bug only happen in two aggregate operators are merged into one


Ascend's execution efficiency is suboptimal

Utilizing the Iterator to iterate through all Keys based on the v2.2.2
package main

import (
	"fmt"
	"time"

	"github.com/rosedblabs/rosedb/v2"
)

func main() {
	options := rosedb.DefaultOptions
	options.DirPath = "./tmp/rosedb"

	db, err := rosedb.Open(options)
	if err != nil {
		panic(err)
	}
	defer db.Close()

	for i := 0; i < 100000; i++ {
		_ = db.Put(utils.GetTestKey(i), utils.RandomValue(100*1024))
	}

	t := time.Now()
	iter := db.NewIterator(rosedb.DefaultIteratorOptions)
	for ; iter.Valid(); iter.Next() {
		fmt.Printf("k=%s\n", iter.Key())
	}
	fmt.Printf("completed in %d ms\n",
		time.Now().Sub(t).Milliseconds(),
	)
}
// execution result: completed in 2524 ms

Utilizing the db.Ascend to iterate through all Keys based on the v2.3.0
package main

import (
	"fmt"
	"time"

	"github.com/rosedblabs/rosedb/v2"
)

func main() {
	options := rosedb.DefaultOptions
	options.DirPath = "./tmp/rosedb"

	db, err := rosedb.Open(options)
	if err != nil {
		panic(err)
	}
	defer db.Close()

	for i := 0; i < 100000; i++ {
		_ = db.Put(utils.GetTestKey(i), utils.RandomValue(100*1024))
	}

	t := time.Now()
	db.Ascend(func(k []byte, v []byte) (bool, error) {
		fmt.Printf("k=%s\n", k)
		return true, nil
	})
	fmt.Printf("completed in %d ms\n",
		time.Now().Sub(t).Milliseconds(),
	)
}
// execution result: completed in 78560 ms

Why does Ascend take 31 times more time than Iterator? Could it be because the Ascend method by default returns the V? In most cases, obtaining only the Key is sufficient.

You can add a BlockCache in open options.
options.BlockCache = rosedb.MB * 64

because you iterate all data in wal, block cache fits for the case(sequential reading).

@taroim it makes sense that Ascend will take more time since it also fetches values from disk where the iterator solely iterate over the in-memory index (i didnt really read the code so i assume it). some possible optimizations that i can think of is that it worth checking the implementation of the BTREE and see if it all leaf nodes (the ones that contain the KV pairs) are chained so it easy to iterate over them and not going back to their parents. also reading from disk already optimized by the kernel's page cache where it fetches disk pages and by that we gain alot of cache hits when reading sequentially. and as @roseduan it wont harm if we add another applicative layer of caching that is doing the same. BTW in the current version the functionallity to solely iterate over keys still exists?

@roseduan also the reason using btree and not a hash map is because u want to ascend/descend keys in sorted order?

@roseduan Add the BlockCache option will lead to increased memory overhead. Could you consider implementing a method similar to Redis' "KEYS," which allows searching for keys matching a provided pattern?

@roseduan Add the BlockCache option will lead to increased memory overhead. Could you consider implementing a method similar to Redis' "KEYS," which allows searching for keys matching a provided pattern?

OK， search keys are easy to support. I will open an issue for that.


Re-render causes disconnect

What kind of problem do you need help?
When I have 2 components (Like in this example: https://www.agora.io/en/blog/agora-react-sdk-build-a-video-conferencing-app-in-minutes/):

Parent holding agora client
Child using agora client to do a video call

When the parent re-renders, the connection state of the agora client is reset to DISCONNECTED and the user gets disconnected.
What can I do to solve this issue?
Thanks for your help :)

@DasGandlaf In your case, you should save the client to global state or variable.
Or you can use AgoraRTCProvider to share client in your global Component such as

Thanks for your answer!
That's how I solved the issue for now, but I don't understand why it is disconnecting in the first place? A re-render should not change anything regarding the connection state.
If this is intended behavior, AFAIK, this might be something that goes against React principles. Hooks should preserve state over re-renders. I might be wrong though.

When you put AgoraRTC.createClient() in the component, a rerender will create another client instance and the previous one will get disconnected by useJoin.
In React, if you want to presist a value during rerender you can wrap it in a useMemo hook:
-const client = AgoraRTC.createClient()
+const client = useMemo(() => AgoraRTC.createClient(), [])


Example for how to chain multiple requests?

Can anyone point me to an example or share a code snippet of how to chain together multiple requests, when the result of the first request must be used to make the second request, etc.?

You can chain the results as they are regular promises:
axios.get(...)
  .then((response) => {
    return axios.get(...); // using response.data
  })
  .then((response) => {
    console.log('Response', response);
  });

In this example, response comes back as undefined even when the request is successful?

No, it should be defined. Mind the return statement. You've probably missed it.

ayyyyy 👍

And how would you catch the individual errors in this case?

I have a loop(for) to send axios post,and i have found that each request hasn't send out after each loop,they had send out together after thees loop over
this is my code
 for (let i = 0;i < differ;i++) {         tem.start = moment(start).add(i, 'days').format('YYYY-MM-DD')         tem.end = moment(tem.start).endOf('day').format('YYYY-MM-DD 23:59:59')         tem.date = tem.start         // if (V.hasSameValue(title, tem.start, tem.end))continue         V.addEventsToCalendar(tem)       } addEventsToCalendar: (event) => {     axios.post(requestUrl('calendar'), {...event})       .then(res => {         V.eventsRender(V.dataToEvent([res.data]))         successTip()       })       .catch(errorTip)   },

@Liaohuanle
For is asynchronous, it doesn't wait end of each operation. Instead of loop you can use simple recursion.

Why don't just try this?
axios.get(...)
.then((response) => {
axios.get(...)
.then((response) => {
console.log('response);
});
})

@alejogamboa Yet another callback hell, what do you think?

var array = [0,1,2];
axios.get('api/' + array[0]).then(response => {
    axios.get('api/' + array[1]).then(response => {
         axios.get('api/' + array[2]).then(response => {
            alert('done');
         });
    });
});

how do I chain it based on array?

@jericopulvera have a look at using
axios.all([])

Already got the solution here #1413

Why not just do so?
axios.get(...)
.then((response) => {
  return axios.get(...)
})
.then((response) => {
  console.log('response);
})


File not found

Helllo Author,
./raw_data/data_process.py  file not found.
How can I get this file?
Thank you~

You can download it from Google Drive, unzip it, and then you can find the data_process.py file in there.


bump requirements.txt

referring https://github.com/fsspec/s3fs/issues/801

That's all it should take, and everything passes, so good to go.


stm32h573i_dk : Fix CAN core clock and add I2C test

Set the PLL1_Q divider to 6 give a can core clock of 80MHz to resolve fdcan_clk reception problem because M_CAN requires that the host clock "APB1" should be higher or equal to the CAN core clock "PLL1_Q".
Add necessary overlay and stm32h573i_dk in i2c_target_api test case to enable the board.

Related to the issue: https://github.com/zephyrproject-rtos/zephyr/issues/70557

@marwaiehm-st Please update PR title

With this change in, you should be able to add CONFIG_TEST_ALL_BITRATES=y for this board to tests/drivers/can/timing/.


/tmp/srcclr mktemp directory cleanup seems to fail if any errors occur during the action run

Running the veracode-sca action failed most likely due to a /tmp directory cleanup or out of space condition on the GitHub Action Runner (since it's a shared resource) and the failure of the action to be able to handle cleaning up after the rje error.
Got the following error running the GitHub Action
Run<EMAIL_ADDRESS>Start command
curl -sSL https://download.sourceclear.com/ci.sh | sh -s -- scan publish
Error: stderr: Error: missing `server' JVM at `/tmp/srcclr/jre/lib/server/libjvm.so'.
Please install or use the JRE or JDK that contains these missing components.

The action tries to be smart about clean up and reusing the previous unpacked version, but what seems to have occurred is that the jre directory was missing parts of previously unpacked gzip file, probably due to either /tmp running out of space or a /tmp cleanup removing files older than a specified time between the last action run and the current run.
The ci.sh code tries to be smart about cleaning up, but the missing code ended up leaving multiple srcclr.XXXXXX temp directories created by mktemp which never got cleaned up exacerbating the lack of space on /tmp.  Because the VERSION check file still existed in the /tmp/srcclr file, the shell script didn't think it needed to re-create the srcclr directory, so the situation continued to leave old srcclr.XXXXXX directories.

Hi @keaedwar, this is not really a problem of the action, but how the images they run are configured. Usually the temp folder should be cleared for every run so nothing stays from a previous run.
I believe that is standard behaviour of the default images (like ubuntu-lastest) in GitHub as well.
The agent has to be extracted somewhere, if the image is caching everything that is happening on each image run, subsequently it will run out of memory.
You can also install the agent on the image and just use the srcclr command in the backgorund. But that would requeire to no use the action.
Clearing the temp dir or using another folder that will be cleared for each run is the best possible option here.

Ended up putting in a workaround to use RUNNER_TEMP instead of the /tmp as /tmp is a shared resource on the host and RUNNER_TEMP is a temporary directory on the runner.