text:
Verify generation in readiness checks

Signed-off-by: James Oden james.oden.dev@gmail.com

What this PR does / why we need it: This patches a bug where helm preemptively marks resources as ready.  This is due to a race condition between the helm readiness check and the associated k8s controller updating the resource.  I've added generational validation to readiness checks for all applicable resources.
Special notes for your reviewer:
If applicable:

[ ] this PR contains documentation
[x] this PR contains unit tests
[ ] this PR has been tested for backwards compatibility

closes #10859
Associated k8s issue
Thanks for the help!

@joejulian Anything I can do on my end to help get this one triaged?  Thanks for the help!

@mattfarina @bacongobbler @yxxhero Anything I can do on my end to help get this one triaged? Thanks for the help!

@zonggen @joejulian @yxxhero Anything I can do on my end to help get this one triaged? Thanks for the help!

@muang0 need more comments for review. Thanks very much.

@muang0 need more comments for review. Thanks very much.

@yxxhero thanks for the response!  Do you mind clarifying what you mean?  Do you need me to provide more clarification on this PR in a comment?
A concise summary: During resource readiness checks, helm doesn't utilize the k8s generation/observedGeneration fields. This creates an opening for a race condition between helm and the associated k8s controller.  In this case, a resource is incorrectly marked as ready by helm (before the associated k8s controller picks up the changes to the spec from helm).  If we add generational checks to helm readiness validation, then helm would notice the generation & observedGeneration are out of sync, and avoid this race condition entirely.
What we are observing as a result:  While using the wait flag, helm doesn't wait for the resources to be created but rather immediately marks resource creation as complete and finishes the install.
k8s api-conventions description of observedGeneration & generation: https://github.com/kubernetes/community/blob/master/contributors/devel/sig-architecture/api-conventions.md?plain=1#L476-L479

Hi @yxxhero any action I should take from my end?  Thanks for the help!

Hi @yxxhero, hope you're having a good week! So sorry to bother, just bumping this so it doesn't fall between the cracks :) It's a small change at its core, most of the lines are unit tests.

@yxxhero I hate to bother you :sweat_smile:  this PR is really a small change at its core, shouldn't take long to review/triage.  You'd be helping us out a ton by helping push this one along :smile:

@muang0 those changes are valuable. but The code changes a lot, I need more time to review. Thanks very much.

Gentle bump 😀

This PR is what exactly I was looking for. I was playing with Kind cluster using Helm and noticed --wait does not as expected, so found the following comment: https://github.com/helm/helm/issues/10061#issuecomment-1143752352
And ended up this PR eventually. So I tested on my local env:
$ gh pr checkout 10920
$ make build

$ cat <<EOF | kind create cluster --name helm-test --config=-
kind: Cluster
apiVersion: kind.x-k8s.io/v1alpha4
nodes:
- role: control-plane
- role: worker
- role: worker
- role: worker
EOF

# The next two commands does not wait
$ helm upgrade fluent-bit fluent/fluent-bit --install --wait
$ helm upgrade --wait --reuse-values --set flush=3 fluent-bit fluent/fluent-bit

# Now test with this PR
$ ./bin/helm upgrade --wait --reuse-values --set flush=1 fluent-bit fluent/fluent-bit

Works like a charm, great job @muang0! 👏
Any possibility to make review process a bit faster to keep time window short to get this merge to main branch?
Kind ping @yxxhero @mattfarina @bacongobbler 🤗

Kind ping :)

Kind ping, plz fam, it's not a complex change 😅

We've run into this issue too. Would really appreciate it if this got reviewed please and thanks.

@dnwe Thank you greatly for your contribution!! :fireworks: Your statefulset generational readiness check is valuable work :smile:
https://github.com/helm/helm/commit/7c74f1dd027709156c3345e1965693f04b8dd9ac
@yxxhero @mattfarina @bacongobbler I think this type of generational check would be valuable for other resources as well.  In this PR I've applied generational readiness checks for all applicable resources.  If you think this is something helm can benefit from, and willing to commit to reviewing these changes, I'm happy resolve my merge conflicts.  Just let me know!
@rmendal-Harness @Dentrax This will likely be the last activity on this PR from me unless maintainers are interested in this PR.  Thank you for the shoutouts :100:

@muang0 can you rebase this from main? The CI error you encountered is fixed there.

@mattfarina just rebased, checks passing!

Kind ping

Kind ping @mattfarina @sudermanjr

Kind ping @muang0, can you please fix the reviews once you have a bandwidth? Thanks!

Is there any possibility to push forward this feature in the near future? :eyes:

@bjosv ping! 😊

@Dentrax I'm not sure what I can do since I'm neither the submitter nor a project member,
but I also would love to have it merged..even without my last review comments :blush:

Oh... Sorry, I meant to ping @muang0. 🙈 Sorry for inconvenience.

No worries, I'm just happy to see some action here.
Unfortunately it seem that muang0 has not been active on GitHub since September, but we hope for the best and that everything is ok.

Quick question, I got here following a thread starting with a mention of this occurring with 1 pod.
Following the comments I don't think that is the main trigger, but is the mentioned race condition more likely with replica count set at 1? Just trying to diagnose, and I don't have access to much logs of the environment.

Been🕵♀ for a while, lot going on in my 🌎 last 🗓🗓🗓🗓🗓🗓; starting to 🌥⛅ more lately

We are also ran into this issue. When can this be merged? Thanks

... and, of course, CI needs to pass.

@muang0 can I get write permissions to your repository so that we can revert this final change and get the bug merged in? Thanks

Thanks for reaching out. I'm planning my next haircut then I'd love to talk :)

Still waiting on the planned haircut. I've got a full head of hair, BUT I'm used to shaving it mysefl so this one's no biggie. Let's see if the !downers have any suggestions.

@stefanmcshane added you as contributor on the project-> thanks for raising this concern. Looks like just a couple minor things are needed here.

@joejulian Can you re-review with the changes corrected?

Hi @joejulian @mattfarina can we get this merged?

authors: Dentrax RemusBizu bjosv joejulian mattfarina muang0 rmendal-Harness stefanmcshane void-spark yxxhero


text:
fix: refactor downloadAll

This refactor cleans up downloadAll's validation, download, and save logic:

A temporary directory is created, and removed after all references to
the struct have been dropped via defer
Any local dependencies in the charts directory are kept intact and validated
Charts that have been updated are moved to the charts directory

This refactor has a number of improvements, including:

tmpCharts is removed after execution
no remote charts are downloaded to destPath: they are all pulled into tmpPath, validated, then moved to destPath
lots of code cleanup/improvements, like the if block checking whether the charts directory was actually not a directory.
the cyclomatic complexity of the code was simplified
extra (and in some cases, dangerous) calls to os.RemoveAll(destPath) have been removed, cleaning the code and preventing certain failure cases.

A test has been provided to demonstrate the tmpCharts removal issue has been fixed. I also left a comment that further improvements can be made to this piece of code should someone feel the need to make improvements there.
closes #5567
closes #8846
closes #9680
Signed-off-by: Matthew Fisher matt.fisher@microsoft.com

[ ] this PR contains documentation
[x] this PR contains unit tests
[x] this PR has been tested for backwards compatibility

@bacongobbler - checked the failing tests. I believe I experienced the same "no such file or directory" w/ the OCI changes... May need to make a change similar to https://github.com/helm/helm/pull/9782/files#diff-a689ad99783d272ab2c91f3372579ffa3e0e96a64ead1b2872e05ba8e86d953b. Just a hunch

Good call. Thanks! I'll look into that.

Hmm... I think the issue was due to a simple bug in my code. I think I caught it and it should work as expected now.

I'm going to change some of the behaviour around safeDeleteDep. It looks like there can be a case where a fail to "safely" delete a dependency can cause data loss. That doesn't seem optimal. Code should remain the same, but updates should be more atomic as a result.

I think I failed to account for one last use case, which is when a "local" dependency (one where the "repository" field in your dependencies is empty) is packaged as a tarball instead of a directory. I've seen some use cases utilizing that.

That may call for some deeper introspection of the chart dependency tree than I was hoping for, but /shrug

done

As it turns out, local dependencies cannot be anything other than directories according to https://github.com/helm/helm/blob/21251378b432fb629cb1a49af3892e20c1ec9624/pkg/downloader/manager.go#L277, so I just added some extra safeguards in case we decide to change that assumption. :)

rebased and squashed.

source: gharchive/pull-request

authors: bacongobbler jdolitsky

repo: helm/helm

license_type: permissive

license_source: github-api


text:
在ios系统下也能嗅探视频直链了

iOS里的focus浏览器可以嗅探视频了
复制视频链接成功
下载弹窗不出来
在ios里试了几个浏览器  就这个focus支持脚本最强  要在里面选ALLFrame执行范围

iOS里的focus浏览器可以嗅探视频了 复制视频链接成功 下载弹窗不出来 在ios里试了几个浏览器 就这个focus支持脚本最强 要在里面选ALLFrame执行范围

好的 感谢反馈，我后续增加到文档当中，手机端样式可能不适配需要调整一下

source: gharchive/issue

authors: dreampjk helson-lin

license: MIT


text:
tbcapi: fix typo in docs readme

Fixed typo in the text
ttbcapi - tbcapi

Thank you!

repo: hemilabs/heminetwork


text:
Update drawer styles

The drawer to connect wallets needs to be updated to follow the new styles. See figma

Closed by #507

repo: hemilabs/ui-monorepo


text:
PoS updates

The updates for PoS to kick in on feb 1st

Looks good to me, but I would like to ask about changes in CKey::Sign.

authors: Greg-Griffith withthelemons

repo: hempcoin-project/THC

license: mit

license_source: bigquery


text:
Possibility to control (activate) scenes?

Is there a possibility to activate the scenes created in the Tradfri app through tradfri-mqtt?
They are under mqtt-topic "tradfri-raw/15005". I have an example from my home "tradfri-raw/15005/131073/196608". This turns off all lighting in one room (group).

It should be possible to send something like this:
{
  "method": "put",
  "url": "15005/131073",
  "payload": {
    "5850": 1,
    "9039": 196608
  }
}

I have tried this but it doesn't give any response. I have also tried to add a reply url but no reply.
I tried:
{
"method": "put",
"url": "15005/131073",
"payload": {
"5850": 1,
"9039": 196608
}
}
on topic: tradfri-cmd

sorry, the url should be 15004/131073, not 15005/...

And thats works. Thanks for the help.

authors: RedNoteFanatic bonan

repo: hemtjanst/tradfri-mqtt


text:
Added aliases.

This feature allows the addition of custom aliases in the hyper.js config file. This is useful for mapping tools that use the same icon such as nodemon -> node and python3 -> python.

Thanks for all the work. I'm definitely interested in merging this but there's a few changes I'd like to make beforehand when I get time ✌

When will be this merged? People have a lot of functions / aliases and this looks like cool feature.

hm, any progress on PR?

@henrikdahl ping

authors: danielheyman henrikdahl mihaliak sobrinho talentlessguy

repo: henrikdahl/hyper-tabs-enhanced


text:
Naive question

Hi there,
how comes memory usage (as reported by Beszel) is quite different from other apps like btop or the classic "free" command?
At the moment Beszel reports 42.0% RAM usage, while this tells me:
$ free -m
               total        used        free      shared  buff/cache   available
Mem:            7953        3941        3397         261        1191        4011
Swap:           8191           1        8190

which is about 49% used.
I never really understood all the values reported by free, eheh, but something doesn't look right to me here.

I've never compared directly and not on a computer currently but the beszel number is meant to be memory used by programs whereas the btop / free calculation probably includes slab or some other reclaimable memory.
I'm using the 'Used' calculation from the gopsutil library, which reads from /proc/meminfo. For more info see that lib.
If people think memory should be more in line with free then it should be possible to do that. Maybe as an env var option for what calculation to use.

Just found this: https://github.com/shirou/gopsutil/issues/899

I don't think there's a single value that's objectively correct when it comes to Linux. People have different opinions on it.
For example, it looks like htop displays a value closer to our number than free / btop.
I use Astra Monitor on my laptop and calculation they use by default is the same or very close to ours currently.
I'm not opposed to tweaking so it's more in line with free though.

Sorry to bother you, but I've got another perplexity about measurements.
Every morning at 5 AM my VPS does backup some data (1GB or so, not very much) and I'm seeing these two graphs:

CPU may be alright, but disk read and write looks too low for me. VPS has got a SSD and I'm quite sure it performs faster that 2MB/s ..
Obviously I'm not able to check this in real time, since I'm quite used to sleep :)
Any suggestions?
Thanks

The value is the average over the course of the time block in question.
So in the 12 hour chart, 1.8 MB/s should be what was averaged over the course of the whole 10 minute period. Not the peak value.
If your backup is 1 GB, divide by 600 seconds and you get 1.66 MB/s.
I can look into adding peak value at some point.

authors: henrygd roughnecks

repo: henrygd/beszel


text:
add policy document for AWS with only necessary permissions

This PR addresses the remaining request in #208, which is to limit the permissions the AWS Quickstart Docs give to the IAM user they would have you create. I wrote the policy document in this PR after looking at the source for pkg/cloudprovider/aws at 178a007 and the AWS API calls that package makes. After some testing with a full cluster backup with ark, the permissions I defined here seem to work well.
I'm not sure if ark would ever upload anything large enough to cause aws-sdk-go to start a multipart upload with S3, but I included the permissions it would need in that case.

@mattmoyer ptal!

Sorry about that! I think I changed that argument when I tested this but never updated the doc. Will push that up in a moment.

LGTM. Please squash & we'll merge. Thanks!

authors: hopkinsth ncdc

repo: heptio/ark


text:
don't require a default backup storage location to exist

Signed-off-by: Steve Kriss steve@heptio.com
Fixes #898
I think this is the most reasonable approach to addressing this.  The server flag retains a default value of "default", but the server won't terminate if it can't find a BackupStorageLocation custom resource named "default".  Backups will fail validation if they don't have an explicitly-specified BSL that actually exists.  Later, if a BSL named "default" (or whatever the value of the server flag is) is created, it will automatically start being used by default for backups.

@carlisia @wwitzel3 PTAL when you get a chance, thanks.


text:
Fix typo in the IngressRoute TCP proxying docs

Signed-off-by: Jonas Fonseca jonas.fonseca@gmail.com

Thank you.

authors: davecheney jonas

repo: heptio/contour


text:
Improve consistency/best practices of docker files

We put stuff in / and run as root. We probably shouldn't do either of those things if we can help it.
Make sure our sonobuoy & related dockerfiles behave and follow some conventions. Super bonus to this ticket, document our conventions.

Check the sonobuoy image and https://github.com/heptio/sonobuoy-plugin-systemd-logs/blob/master/Dockerfile
Make sure the base image makes sense and that we follow best practices in general.

I spent some time looking at our current Dockerfiles and possible changes we could make. The following is a summary of what I learned:

We are currently using two separate OS images, debian:stretch-slim for AMD64 and ubuntu:16.04 for ARM64. Looking through the PR that added ARM support, and some related issues (#609), it's not clear why these two are different. It's been questioned a few times but I couldn't find a definitive answer. I would like to try and use the same OS for both to avoid possible differences in behaviour.

Looking at whether we can move the Sonobuoy executable and scripts out of /, I think that is a move that we could make but it would require some care due to how these files are used. If we were only concerned about the images, moving the files would be safe to do. However, the CLI generates a manifest that expects the files to be in a particular location when running the images. If we move the files, that contract is broken. This would be fine in the case where the CLI version matches the image version for new manifests, however it's entirely possible that we could have users with existing manifests, or using a newer image with an older CLI version. We could find a way to transition these locations gradually over the course of a few releases, but I don't know if it's a priority at this stage.

With regard to running as root, I think this is something we should change. I'm not aware of anything within Sonobuoy requiring root permissions so running as the root user seems unnecessary.

My concern with making the above changes is that we don't have any integration testing in place, particularly with ARM. We have nothing that ensures that those builds are good. Before making significant changes that would rely on manual testing to verify, I would like to get some basic integration testing in place. Ideally something for both architectures, but at least something that could verify that any change in user or location of the files is safe. This is being worked on as part of #668.
I'm going to make some follow up issues to deal with each individual point above and will close this in favour of those issues.

authors: chuckha johnSchnake zubron

repo: heptio/sonobuoy


text:
HARP-13842 - Adding gitlab-CI related file

Signed-off-by: Aluni gairik.aluni@here.com
Thank you for contributing to harp.gl!
Before requesting a pull request, please remember to check the following documents:

contribution guidelines
coding style

If you are adding new functionality we would highly appreciate if you can describe what is the capability you are adding and even better if you can add some examples. Please also remember to add tests for it.
CI Check
Our bots will check whether your PR can be directly integrated into the mainline. We have some internal integration tests running on the background, our bots will inform you of the next steps and someone from our team will take a look and help if needed!
And please do not forget to sign-off your commit! You can read more about DCO here. But, in short, you just need to use git commit -s or append --signoff when you are committing to the repo.
Happy contributing!

@gairik , please add the jira ticket number to the commit message.

@gairik , please add the jira ticket number to the commit message.

@gairik , please add the jira ticket number to the commit message.

I have added the jira ticket number to the PR title.

@gairik , please add the jira ticket number to the commit message.

I have added the jira ticket number to the PR title.

@gairik , please add the jira ticket number to the commit message.

I have added the jira ticket number to the PR title.

That is unfortunately not enough, because the PR disappears, and the commit stays, which makes it difficult to track later.
You can however change the commit message add it when you "Squash and merge", so please do it then.

@gairik , please add the jira ticket number to the commit message.

I have added the jira ticket number to the PR title.

That is unfortunately not enough, because the PR disappears, and the commit stays, which makes it difficult to track later.
You can however change the commit message add it when you "Squash and merge", so please do it then.

@gairik , please add the jira ticket number to the commit message.

I have added the jira ticket number to the PR title.

That is unfortunately not enough, because the PR disappears, and the commit stays, which makes it difficult to track later.
You can however change the commit message add it when you "Squash and merge", so please do it then.

I understand. Will do it.

@gairik , please add the jira ticket number to the commit message.

I have added the jira ticket number to the PR title.

That is unfortunately not enough, because the PR disappears, and the commit stays, which makes it difficult to track later.
You can however change the commit message add it when you "Squash and merge", so please do it then.

I understand. Will do it.

authors: gairik nzjony


text:
HARP-5347: Compass button.

In progress.

Codecov Report

Merging #856 into master will increase coverage by <.01%.
The diff coverage is 34.17%.

@@            Coverage Diff             @@
##           master     #856      +/-   ##
==========================================
+ Coverage   47.58%   47.59%   +<.01%
==========================================
  Files         235      224      -11
  Lines       21721    21526     -195
  Branches     4933     4899      -34
==========================================
- Hits        10336    10245      -91
+ Misses      11385    11281     -104

Impacted Files
Coverage Δ

@here/harp-mapview/lib/VisibleTileSet.ts
68.22% <ø> (ø)
:arrow_up:

@here/harp-mapview/lib/MapViewFog.ts
69.44% <11.11%> (-3.02%)
:arrow_down:

@here/harp-mapview/lib/ClipPlanesEvaluator.ts
12.45% <11.42%> (-0.15%)
:arrow_down:

@here/harp-map-controls/lib/MapControls.ts
23.59% <11.76%> (+0.21%)
:arrow_up:

@here/harp-mapview/lib/MapView.ts
53.57% <46.66%> (-0.09%)
:arrow_down:

@here/harp-mapview/lib/Utils.ts
59.69% <49.45%> (+5.21%)
:arrow_up:

@here/harp-mapview/lib/FrustumIntersection.ts
88.7% <81.81%> (ø)
:arrow_up:

@here/harp-mapview/lib/CameraMovementDetector.ts
60.29% <87.5%> (ø)
:arrow_up:

@here/harp-mapview/lib/ThemeHelpers.ts
6.55% <0%> (-0.68%)
:arrow_down:

@here/harp-datasource-protocol/lib/Outliner.ts
100% <0%> (ø)
:arrow_up:

... and 33 more

Continue to review full report at Codecov.

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authors: Astrak codecov-io


text:
UE not attaching!!

Hi All,
I am trying to play around with the 5G-SA E2E deployment using zmq driver, everything runs fine but the UE is unable to attach I don't see any attach request from UE side it seems there isn't any communication happening between UE and RAN.
$ docker-compose -f srsue_5g_zmq.yaml up
WARNING: Found orphan containers (udm, smf, metrics, ausf, upf, nssf, bsf, srsgnb_zmq, mongo, amf, scp, webui, nrf, udr, pcf) for this project. If you removed or renamed this service in your compose file, you can run this command with the --remove-orphans flag to clean it up.
Creating srsue_5g_zmq ... done
Attaching to srsue_5g_zmq
srsue_5g_zmq    | Configuring component: 'ue_5g_zmq'
srsue_5g_zmq    |  * Starting system message bus dbus                    [ OK ]
srsue_5g_zmq    | avahi-daemon: unrecognized service
srsue_5g_zmq    | Deploying component: 'ue_5g_zmq'
srsue_5g_zmq    | Active RF plugins: libsrsran_rf_uhd.so libsrsran_rf_soapy.so libsrsran_rf_zmq.so
srsue_5g_zmq    | Inactive RF plugins:
srsue_5g_zmq    | Couldn't open , trying /root/.config/srsran/ue.conf
srsue_5g_zmq    | Couldn't open /root/.config/srsran/ue.conf either, trying /etc/srsran/ue.conf
srsue_5g_zmq    | Reading configuration file /etc/srsran/ue.conf...
srsue_5g_zmq    |
srsue_5g_zmq    | Built in Release mode using commit fa56836b1 on branch HEAD.
srsue_5g_zmq    |
srsue_5g_zmq    | Opening 1 channels in RF device=zmq with args=tx_port=tcp://172.22.0.34:2001,rx_port=tcp://172.22.0.37:2000,id=ue,base_srate=11.52e6
srsue_5g_zmq    | Supported RF device list: UHD soapy zmq file
srsue_5g_zmq    | CHx base_srate=11.52e6
srsue_5g_zmq    | CHx id=ue
srsue_5g_zmq    | Current sample rate is 1.92 MHz with a base rate of 11.52 MHz (x6 decimation)
srsue_5g_zmq    | CH0 rx_port=tcp://172.22.0.37:2000
srsue_5g_zmq    | CH0 tx_port=tcp://172.22.0.34:2001
srsue_5g_zmq    | Current sample rate is 11.52 MHz with a base rate of 11.52 MHz (x1 decimation)
srsue_5g_zmq    | Current sample rate is 11.52 MHz with a base rate of 11.52 MHz (x1 decimation)
srsue_5g_zmq    | Waiting PHY to initialize ... done!
srsue_5g_zmq    | Attaching UE...
srsue_5g_zmq    | Random Access Transmission: prach_occasion=0, preamble_index=0, ra-rnti=0xf, tti=2251
srsue_5g_zmq    | Random Access Transmission: prach_occasion=0, preamble_index=0, ra-rnti=0xf, tti=2281
srsue_5g_zmq    | Random Access Transmission: prach_occasion=0, preamble_index=0, ra-rnti=0xf, tti=2311
srsue_5g_zmq    | Random Access Transmission: prach_occasion=0, preamble_index=0, ra-rnti=0xf, tti=2341
srsue_5g_zmq    | Random Access Transmission: prach_occasion=0, preamble_index=0, ra-rnti=0xf, tti=2371
srsue_5g_zmq    | Random Access Transmission: prach_occasion=0, preamble_index=0, ra-rnti=0xf, tti=2401
srsue_5g_zmq    | Random Access Transmission: prach_occasion=0, preamble_index=0, ra-rnti=0xf, tti=2431
^CGracefully stopping... (press Ctrl+C again to force)
Stopping srsue_5g_zmq ...
Killing srsue_5g_zmq  ... done

Can anyone point out whats going wrong here?
Thank You!!

Please pull the latest changes in this repo and give it a try. This commit https://github.com/herlesupreeth/docker_open5gs/commit/85878f7ebb040c144405cd2aa2e8013e050a3693 should have fixed that issue.


text:
Release v234

https://github.com/heroku/heroku-buildpack-python/compare/v233...08cb18ba98b520cc7c1dedd192399db84cb0c139
GUS-W-13811714.

$ make publish
Deploy as version: v234 [y/n]? y

Tagging commit 2ffd01fc25407cfe2b115eb69e0e4f294f776fcf with v234...
Total 0 (delta 0), reused 0 (delta 0), pack-reused 0
To https://github.com/heroku/heroku-buildpack-python
 * [new tag]         v234 -> v234

Publishing to the buildpack registry...
Two-factor code: ********************************************
Publishing buildpack heroku/python... done
Publishing buildpack was successful

 Version Released At              Status
 ─────── ──────────────────────── ─────────
 234     2023-07-24T08:38:57.050Z published

repo: heroku/heroku-buildpack-python


text:
🛑 Auth-Bridge - Test 1 is down

In 9dd210f, Auth-Bridge - Test 1 ($AUTH_BRIDGE_TEST_1) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Auth-Bridge - Test 1 is back up in 05f36d2.

repo: herrphon/upptime


text:
🛑 Auth-Bridge - Test 1 is down

In 3f75cc2, Auth-Bridge - Test 1 ($AUTH_BRIDGE_TEST_1) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Auth-Bridge - Test 1 is back up in acb44d5.


text:
🛑 Software Center - Test 1 is down

In 40e1e13, Software Center - Test 1 ($SOFTWARECENTER_TEST_1) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Software Center - Test 1 is back up in 707e925.


text:
🛑 Auth-Bridge - Test 1 is down

In d6f5caf, Auth-Bridge - Test 1 ($AUTH_BRIDGE_TEST_1) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Auth-Bridge - Test 1 is back up in 231d18d after 11 minutes.


text:
🛑 Software Center - Test 1 is down

In b457d41, Software Center - Test 1 ($SOFTWARECENTER_TEST_1) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Software Center - Test 1 is back up in ff03f16.


text:
🛑 Software Center - Test 1 is down

In aee0c97, Software Center - Test 1 ($SOFTWARECENTER_TEST_1) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Software Center - Test 1 is back up in c298ada after 31 minutes.


text:
🛑 Auth-Bridge - Test 1 is down

In d94810f, Auth-Bridge - Test 1 ($AUTH_BRIDGE_TEST_1) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Auth-Bridge - Test 1 is back up in a17b274 after 27 minutes.


text:
🛑 Software Center - Test 1 is down

In 6974084, Software Center - Test 1 ($SOFTWARECENTER_TEST_1) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Software Center - Test 1 is back up in 5b7c676 after 37 minutes.


text:
🛑 Software Center - Test 1 is down

In 28fdb24, Software Center - Test 1 ($SOFTWARECENTER_TEST_1) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Software Center - Test 1 is back up in 1849f78.


text:
🛑 Auth-Bridge - Test 1 is down

In 4dece93, Auth-Bridge - Test 1 ($AUTH_BRIDGE_TEST_1) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Auth-Bridge - Test 1 is back up in 9ce23df.


text:
🛑 Software Center - Test 1 is down

In d9f6c47, Software Center - Test 1 ($SOFTWARECENTER_TEST_1) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Software Center - Test 1 is back up in a8890c3.


text:
🛑 Auth-Bridge - Test 1 is down

In 66bbafd, Auth-Bridge - Test 1 ($AUTH_BRIDGE_TEST_1) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Auth-Bridge - Test 1 is back up in fc79fad.


text:
🛑 Software Center - Test 1 is down

In b8ea98f, Software Center - Test 1 ($SOFTWARECENTER_TEST_1) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Software Center - Test 1 is back up in 31fb443.


text:
🛑 Software Center - Test 1 is down

In 774f5c4, Software Center - Test 1 ($SOFTWARECENTER_TEST_1) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Software Center - Test 1 is back up in ff1dfee.


text:
3.5压缩文件损坏

最新的3.5 zygisk_module.zip压坏了

原来是我下载的时候出问题了，motrix重新下载没有覆盖

repo: hexstr/UnityFPSUnlocker


text:
AttributeError: 'RecursiveField' object has no attribute 'get_fields'

Heyo! First of all: thanks for releasing and supporting this, really appreciate it!
class CategorySerializer(serializers.ModelSerializer):
    # We need special recursive serialization here for Category (parent) -> Category (child) relationship
    children = serializers.ListSerializer(read_only=True, child=RecursiveField())
    alternate_namings = CategoryOfficeNamingSerializer(many=True, required=False)

    class Meta:
        model = Category
        fields = (
            'id',
            'children',
            'parent',
            'order',
            'name',
            'alternate_namings',
        )

Using this Serializer with django-rest-swagger I get this error:
AttributeError: 'RecursiveField' object has no attribute 'get_fields'
Not sure if maybe I'm misusing RecursiveField? Thanks for any advice!

What version of Python, Django, DRF are you using?
A stack trace would be nice too.

Python 3.5
Django 1.9
django-rest-swagger==0.3.5
djangorestframework==3.3.2
djangorestframework-recursive==0.1.1
Stacktrace:
Internal Server Error: /docs/api-docs/api/categories
Traceback (most recent call last):
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/django/core/handlers/base.py", line 149, in get_response
    response = self.process_exception_by_middleware(e, request)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/django/core/handlers/base.py", line 147, in get_response
    response = wrapped_callback(request, *callback_args, **callback_kwargs)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/django/views/decorators/csrf.py", line 58, in wrapped_view
    return view_func(*args, **kwargs)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/django/views/generic/base.py", line 68, in view
    return self.dispatch(request, *args, **kwargs)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/views.py", line 466, in dispatch
    response = self.handle_exception(exc)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/views.py", line 463, in dispatch
    response = handler(request, *args, **kwargs)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework_swagger/views.py", line 164, in get
    'models': generator.get_models(apis),
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework_swagger/docgenerator.py", line 133, in get_models
    self._find_field_serializers(serializers)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework_swagger/docgenerator.py", line 279, in _find_field_serializers
    serializers_set))
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework_swagger/docgenerator.py", line 271, in _find_field_serializers
    fields = serializer().get_fields()
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework_recursive/fields.py", line 115, in __getattribute__
    return object.__getattribute__(self, name)
AttributeError: 'RecursiveField' object has no attribute 'get_fields'

Yeah I'm not sure why it's getting called either--should point to my actual serializer? I tried to add it as a "proxied" attribute while poking around RecursiveField source, but haven't been successful yet.

https://github.com/marcgibbons/django-rest-swagger/blob/master/rest_framework_swagger/docgenerator.py#L273
There's a recursive method that is trying to discover serializer fields. For some reason, it detects the RecursiveField as an instance of BaseSerializer which is odd, since RecusiveField actually subclasses Field

The field is a ListSerializer with Child=RecursiveField() -- could that possibly be why? It seems to make sense that django-rest-swagger would detect it as inheriting BaseSerializer.
However, ListSerializer doesn't implement the get_fields method? I think I'll post this on rest-swagger github and try there--thanks!

Oh... maybe you should try ListField instead of ListSerializer?

Ahhh! Nooo! Alright, trying that still seems to be borked:
TypeError: 'RelatedManager' object is not iterable
Full traceback, hope this is helpful:
Internal Server Error: /api/categories/
Traceback (most recent call last):
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/django/core/handlers/base.py", line 149, in get_response
    response = self.process_exception_by_middleware(e, request)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/django/core/handlers/base.py", line 147, in get_response
    response = wrapped_callback(request, *callback_args, **callback_kwargs)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/django/views/decorators/csrf.py", line 58, in wrapped_view
    return view_func(*args, **kwargs)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/viewsets.py", line 87, in view
    return self.dispatch(request, *args, **kwargs)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/views.py", line 466, in dispatch
    response = self.handle_exception(exc)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/views.py", line 463, in dispatch
    response = handler(request, *args, **kwargs)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/mixins.py", line 48, in list
    return Response(serializer.data)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/serializers.py", line 674, in data
    ret = super(ListSerializer, self).data
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/serializers.py", line 239, in data
    self._data = self.to_representation(self.instance)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/serializers.py", line 614, in to_representation
    self.child.to_representation(item) for item in iterable
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/serializers.py", line 614, in <listcomp>
    self.child.to_representation(item) for item in iterable
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/serializers.py", line 472, in to_representation
    ret[field.field_name] = field.to_representation(attribute)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/fields.py", line 1476, in to_representation
    return [self.child.to_representation(item) for item in data]
TypeError: 'RelatedManager' object is not iterable
Internal Server Error: /api/categories/
Traceback (most recent call last):
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/django/core/handlers/base.py", line 149, in get_response
    response = self.process_exception_by_middleware(e, request)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/django/core/handlers/base.py", line 147, in get_response
    response = wrapped_callback(request, *callback_args, **callback_kwargs)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/django/views/decorators/csrf.py", line 58, in wrapped_view
    return view_func(*args, **kwargs)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/viewsets.py", line 87, in view
    return self.dispatch(request, *args, **kwargs)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/views.py", line 466, in dispatch
    response = self.handle_exception(exc)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/views.py", line 463, in dispatch
    response = handler(request, *args, **kwargs)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/mixins.py", line 48, in list
    return Response(serializer.data)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/serializers.py", line 674, in data
    ret = super(ListSerializer, self).data
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/serializers.py", line 239, in data
    self._data = self.to_representation(self.instance)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/serializers.py", line 614, in to_representation
    self.child.to_representation(item) for item in iterable
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/serializers.py", line 614, in <listcomp>
    self.child.to_representation(item) for item in iterable
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/serializers.py", line 472, in to_representation
    ret[field.field_name] = field.to_representation(attribute)
  File "/Users/eric/.virtualenvs/image_first/lib/python3.5/site-packages/rest_framework/fields.py", line 1476, in to_representation
    return [self.child.to_representation(item) for item in data]
TypeError: 'RelatedManager' object is not iterable

Still digging... thanks for all your help!

I've seen that before. It's got something to do with the fact that your 'children' field is a object manager, not an iterable in and of itself. I suspect you need to use the 'source' argument or something like that.

@heywbj thanks for all your help!
For anyone elses' reference, here's what ended up (kind of) working:
children = serializers.ListField(child=RecursiveField(), source='children.all')
However, the swagger clientside stuff is still broken, some new JavaScript error now :(

authors: ckcollab heywbj

repo: heywbj/django-rest-framework-recursive

license: isc


text:
Add compute_loss method to Model

This PR adds compute_loss method as the primary method for calculating loss.
We made this decision since the models with the same task do not necessarily follow the same pattern for computing loss. That's why most libraries compute loss in their forward method. Although we took a slighly different approach. Instead of messing up all forward methods with an if statement for computing loss which is inaccessible for the end user, we added a seperate method for this purpose.
This method takes in two main inputs as inputs and targets. Subclasses can override this notation.

 @arxyzan jan creating an object each time in compute loss and garbage collecting it reduces the speed. On top of that users may want to add weight or other types loss function inputs to computer_loss which makes it more challenging to work with. I think it's better to create the loss function in the init for once and use it afterward.

@pooya-mohammadi You're right. I thought that having criterion as self.criterion which is a nn.Module, would register it in the state dict which it doesn't! (I just checked).
But there's another issue here. If the models require the users to only implement compute_loss for their own custom models, they'd do all they actually need inside one method. How do think we should implement such thing in a way that it doesn't complicate working with custom models in Hezar? If there's no way around, we should put criterions in all the __init__ methods.

 @arxyzan jan creating an object each time in compute loss and garbage collecting it reduces the speed. On top of that users may want to add weight or other types loss function inputs to computer_loss which makes it more challenging to work with. I think it's better to create the loss function in the init for once and use it afterward.

@pooya-mohammadi You're right. I thought that having criterion as self.criterion which is a nn.Module, would register it in the state dict which it doesn't! (I just checked).
But there's another issue here. If the models require the users to only implement compute_loss for their own custom models, they'd do all they actually need inside one method. How do think we should implement such thing in a way that it doesn't complicate working with custom models in Hezar? If there's no way around, we should put criterions in all the __init__ methods.

@arxyzan jan, users still can do all they want in a single method if they want to. They can create the loss function inside the method and use it! If they were pro-programmers they could extend the init method and overwrite the criterion.
All options are available for users.

 @arxyzan jan creating an object each time in compute loss and garbage collecting it reduces the speed. On top of that users may want to add weight or other types loss function inputs to computer_loss which makes it more challenging to work with. I think it's better to create the loss function in the init for once and use it afterward.

@pooya-mohammadi You're right. I thought that having criterion as self.criterion which is a nn.Module, would register it in the state dict which it doesn't! (I just checked).
But there's another issue here. If the models require the users to only implement compute_loss for their own custom models, they'd do all they actually need inside one method. How do think we should implement such thing in a way that it doesn't complicate working with custom models in Hezar? If there's no way around, we should put criterions in all the __init__ methods.

@arxyzan jan, users still can do all they want in a single method if they want to. They can create the loss function inside the method and use it! If they were pro-programmers they could extend the init method and overwrite the criterion. All options are available for users.

@pooya-mohammadi Done. I did it in a neat way! ;)

authors: arxyzan pooya-mohammadi

repo: hezarai/hezar


text:
archery limit 分页查询失效

重现步骤
select * from table limit 21,20 不生效 应该展示的是第21条开始的后20条数据，但是返回的还是1-20条数据
预期外的结果
select * from table limit 21,20 不生效 应该展示的是第21条开始的后20条数据，但是返回的还是1-20条数据
日志文本
No response
版本
v1.7.9
部署方式
K8S
是否还有其他可以辅助定位问题的信息？比如数据库版本等
No response

你的sql需要加order by排序。
你在数据库直接执行看看结果是咋样的。

你的sql需要加order by排序。 你在数据库直接执行看看结果是咋样的。

sql 中是带order by 的，执行出来的结果是一样的

你的sql需要加order by排序。 你在数据库直接执行看看结果是咋样的。

sql 中是带order by 的，执行出来的结果是一样的

在SQL執行的結果跟archery一致不就代表正常沒問題?
可以請您描述詳細一些嗎?

你的sql需要加order by排序。 你在数据库直接执行看看结果是咋样的。

sql 中是带order by 的，执行出来的结果是一样的

在SQL執行的結果跟archery一致不就代表正常沒問題? 可以請您描述詳細一些嗎?

select * from table order by date desc limit 21,20 不生效, 应该展示的是第21条开始的后20条数据，但是返回的还是1-20条数据

#1172

authors: feiazifeiazi hhyo howieqdd te87037

repo: hhyo/Archery


text:
HSEARCH-4132 Use entity change capture SPI to send entity change events into a "synthetic" table

https://hibernate.atlassian.net/browse/HSEARCH-4132

Run a full build: https://ci.hibernate.org/blue/organizations/jenkins/hibernate-search/detail/PR-2512/4/pipeline

Thank you @yrodiere for the review.
I think I addressed all the comments.

Full build: https://ci.hibernate.org/blue/organizations/jenkins/hibernate-search/detail/PR-2512/8/

Thank you! Updated the contribution...

Thank you!

repo: hibernate/hibernate-search


text:
HV-1629 Fix compiler warnings

https://hibernate.atlassian.net/browse/HV-1629

@gsmet I was going  through the review comments of the other PR and saw the one about the missing <>. And also I saw this JIRA ticket, hence I thought why not fix all of these at one go rather than adding fixes one by one.
IdentitySet had some unchecked warnings and as it is not used anywhere I just dropped it. And after that there are two commits one with fixes of unchecked warnings and another for deprecation ones.

@marko-bekhta looks like the build is failing!
Thanks for the PR btw, very helpful :).

@marko-bekhta thanks, looks very nice.
About the deprecation warnings, it's unfortunate but I think using FQCN should be avoided. So let's leave with it for now, maybe the tooling will get improved at some point.
There's one thing missing though: I think a very simple test specifically testing that property() still works for a getter and a field constraint would be in order. WDYT?

@gsmet there's this test - https://github.com/hibernate/hibernate-validator/pull/971/files#diff-dab88d4bebb8bbdf4c49e52217bbede3R535 but let me change the name, as looking at testDepreFieldAndGetterMethodsForProgrammaticConstraintDefinition it seems I was too lazy to finish typing "Deprecated" :)

Ah yeah sure, sorry. I was looking for an additional test and I missed it. Totally makes sense to reuse the one added for getter()/field().

Rebased and merged, thanks!

authors: gsmet marko-bekhta

repo: hibernate/hibernate-validator


text:
🛑 Mad at the Internet is down

In 3d099a5, Mad at the Internet (https://madattheinternet.com/) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Mad at the Internet is back up in 603b9fd after 15 minutes.

repo: hickoryhouse/kf


text:
🛑 NGINX is down

In 382f7df, NGINX (https://web.sshcdn.com) was down:

HTTP code: 0
Response time: 0 ms

Resolved: NGINX is back up in 4c4f620.


text:
Android Build failure with v2.0.4

@hiennguyen92 Build failing with the latest version. Tried invalidating cache and flutter pub cache clean but this keeps popping. Had to revert to v2.0.3.
Running Gradle task 'assembleDebug'...
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/CallkitNotificationManager.kt:401:31 Unresolved reference: CallkitIncomingActivity
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/CallkitNotificationManager.kt:479:33 Unresolved reference: TransparentActivity
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/CallkitNotificationManager.kt:488:29 Unresolved reference: CallkitIncomingBroadcastReceiver
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/CallkitNotificationManager.kt:493:29 Unresolved reference: CallkitIncomingBroadcastReceiver
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/CallkitNotificationManager.kt:498:33 Unresolved reference: TransparentActivity
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/CallkitNotificationManager.kt:507:22 Unresolved reference: CallkitIncomingActivity
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/FlutterCallkitIncomingPlugin.kt:98:17 Unresolved reference: CallkitIncomingBroadcastReceiver
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/FlutterCallkitIncomingPlugin.kt:111:17 Unresolved reference: CallkitIncomingBroadcastReceiver
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/FlutterCallkitIncomingPlugin.kt:120:17 Unresolved reference: CallkitIncomingBroadcastReceiver
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/FlutterCallkitIncomingPlugin.kt:131:21 Unresolved reference: CallkitIncomingBroadcastReceiver
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/FlutterCallkitIncomingPlugin.kt:154:29 Unresolved reference: CallkitIncomingBroadcastReceiver
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/FlutterCallkitIncomingPlugin.kt:180:29 Unresolved reference: CallkitIncomingBroadcastReceiver
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/FlutterCallkitIncomingPlugin.kt:220:29 Unresolved reference: CallkitIncomingBroadcastReceiver
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/FlutterCallkitIncomingPlugin.kt:238:37 Unresolved reference: CallkitIncomingBroadcastReceiver
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/FlutterCallkitIncomingPlugin.kt:245:37 Unresolved reference: CallkitIncomingBroadcastReceiver
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/FlutterCallkitIncomingPlugin.kt:266:21 Unresolved reference: CallkitIncomingBroadcastReceiver
e: file:///Users/sagar/.pub-cache/hosted/pub.dev/flutter_callkit_incoming-2.0.4/android/src/main/kotlin/com/hiennv/flutter_callkit_incoming/FlutterCallkitIncomingPlugin.kt:266:54 Variable expected

FAILURE: Build failed with an exception.

* What went wrong:
Execution failed for task ':flutter_callkit_incoming:compileDebugKotlin'.
> A failure occurred while executing org.jetbrains.kotlin.compilerRunner.GradleCompilerRunnerWithWorkers$GradleKotlinCompilerWorkAction
   > Compilation error. See log for more details

* Try:
> Run with --stacktrace option to get the stack trace.
> Run with --info or --debug option to get more log output.
> Run with --scan to get full insights.

* Get more help at https://help.gradle.org

BUILD FAILED in 3m 38s
Error: Gradle task assembleDebug failed with exit code 1

Same here, Any solution guys?

@hiennguyen92 any update on this ??

@sagar1garg @KamalPixi
I run flutter clean and then flutter pub get, and the app can be built successfully.
Please try if this works for you.

@TinhHuynh it worked thanks. If you can let us know about your plans for locked screen callbacks it will be really helpful

@sagar1garg
Hi, I am not the library maintainer :)

authors: KamalPixi TinhHuynh sagar1garg


text:
(PHP) No  being put on functions

Describe the issue

When PHP is put into the pre and code tags, everything renders correctly except certain functions. They are missing and just left as regular text while other functions get the .

Which language seems to have the issue?

Seems to be PHP but maybe other languages also that need the class="hljs-keyword".

Are you using highlight or highlightAuto?

I've tried both and both are giving me the same exact problem.

Sample Code to Reproduce

https://jsfiddle.net/b2dj79qh/

Expected behavior

You should see "json_decode" & "file_get_contents" functions white as the other function "isset" is syntaxed.

Additional context

I'm pretty sure they are all considered the same (isset, file_get_contents, json_decode, etc...), so I feel like they should all be the same color no?

There  (isset, etc.) are reserved words. https://www.php.net/manual/en/reserved.keywords.php
PHP does not highlight built-ins such as file_get_contents or json_decode.
If there is a full list of built-ins available I'd be curious to see it, but I worry it might be too large (since PHP is also included in our common build). I'd prefer to perhaps see the blahBlah() pattern detected instead and flagged as a generic function call. See #2500

We need to get the details here on how long a full list would be and see if anyone is willing to work on generic function dispatch detection for PHP.  If neither of these seems to be viable then this will be auto-closed at some point as "expected behavior" - with #2500 tracking the overall issue (of improved fidelity across all grammars).

Here is a list: https://www.php.net/manual/en/indexes.functions.php
I don't think highlighting built-in functions at the cost of storing this many functions is worth it. I think even the built-in interfaces list is a far fetch to be honest.

I don't think highlighting built-in functions at the cost of storing this many functions is worth it.

Yikes. Fully agree.

I think even the built-in interfaces list is a far fetch to be honest.

You mean the built_in list we already have?  I might agree with you (with only a quick glance). Are these things not likely to show up in actual PHP code or snippets?  These lists don't exist solely for highlighting purposes but also to allow us to "autodetect" if a given snippet of code is PHP or not, etc...
But a list of pure interfaces is no help at all if interfaces aren't commonly named in actual PHP code...
Does PHP have the common convention that CamelCasedThings are always interfaces/classes?

But a list of pure interfaces is no help at all if interfaces aren't commonly named in actual PHP code...
All those interfaces are somewhat niche interfaces, but I think Throwable and Closure are used fairly often. But you are right, they are great indicators for language identification. I'm working on a couple PRs for PHP 8.0 and PHP 8.1-specific string patterns, hopefully to make it more complete with recent changes.

Does PHP have the common convention that CamelCasedThings are always interfaces/classes?
Internally, functions are declared with snake_case, and interfaces/classes with CamelCase. However, they are all case-insensitive. It's unlikely to not use that pattern, but it's not technically wrong code if someone were to use SnakeCase functions or SCREAMCASE class names for example.

Does PHP have the common convention that CamelCasedThings are always interfaces/classes?

Unfortunately, PHP is case-insensitive.

Unfortunately, PHP classes and functions are case-insensitive.

OH grrrr... and therefore we have to flag the language as case_insensitive: true which prevents us from doing useful things with those casing conventions, even if we wanted to... though we still could with callbacks (that checked the case using JS), but I'm not sure I want to encourage that until we have some way of not paying the callback penalty during auto-detection.

All those interfaces are somewhat niche interfaces ... you are right, they are great indicators for language identification.

If they are rarely used (niche) then they might be a strong signal but quite expensive (in terms of us maintaining a big list) and in an overall sense not useful... if 95% of PHP code wouldn't ever reference them - we should drop them. The kind of lists we want are lists where 95% of PHP code/snippet MIGHT use those words (which is why keywords are always a good bet)...

The problem with "selective" lists becomes someone then says why do you highlight the popular built-in SnapperInterface but not the built-in BoogerInterface... which leads back to perhaps trying to find a way to highlight ALL interfaces... and have a smaller list only for auto-detection purposes.  This is also a discussion happening with regards to Javascript.

I understand that removing the list of built-in interfaces is a breaking change in a semver sense. With PHP getting more and more object-oriented, I don't think its feasible to keep an up-to-date list of interfaces or internal classes. In fact, there was a proposal just today to introduce a new interface.
Language constructs like empty and isset are very strong indicators in language detection, and we often try to keep the keywords list minimal. For example, the recent Enumerations proposal uses case keyword that is already a reserved keyword.
Case sensitivity in PHP is all over the place too. Variables are case-sensitive, but function names, classes, enums, attributes, etc are case-insensitive. We are generally moving into case-sensitive approach though, but it's highly unlikely that existing structs will change. Constants for example, lost their ability to declare a case-insensitive constant, and recently added named parameters are also case-sensitive.
Personally, I'd all in favor to:

Remove built-in interfaces and other class names. Except for Throwable and perhaps ArrayAccess, the other ones are quite niche ones, and there are more to come. It will only add maintenance burden with very little gain. This reduces the php.js file by ~1.5KB pre-gzip.
Remove magic constants. They always follow __[A-Z_]+__ pattern. We don't include a built-in list in highlight js, but PHP also has magic methods; several magic methods exist in PHP, and they all follow __[A-z] pattern. Unlike the built-in interfaces, we use these magic constants frequently. __DIR__ and __FILE__ being some of the most used; good for language-detection. Reduces php.js by 84 bytes.

Thanks so much for feedback.

Variables are case-sensitive, but function names, classes, enums, attributes, etc are case-insensitive.

What about keywords? That's the real issue, we don't have a way to do case insensitive keywords apart from making the grammar case insensitive.  We could maybe hack it, but I'm not thrilled with the idea.

Remove built-in interfaces and other class names.

Makes sense yo me, but we still need to highlight them - or else PHP will look very "dry".  Would doing so via CamelCase work?  If so we still have to tackle the case sensitivity issue to even be able to detect camelcase...

I understand that removing the list of built-in interfaces is a breaking change in a semver sense.

We do not consider highlighting changes within grammars to be "breaking" changes in a semver sense - the grammars are always improving and in flux. We do try to avoid going the wrong direction with a grammar though - ie they don't get "worse" often.

Unlike the built-in interfaces, we use these magic constants frequently.

That's usually a reason they should stay.  One could argue to just include the most popular, but we aren't that tight on space... so if there are only a handful it's easy to just list them all...  unless there are really 200 and we only have a few now, in which case revisiting trimming a few more could be done...  Just replacing with a __A-Z__ rule doesn't provide near the confidence than it's PHP as the actual named magic constants. [of course many languages share these, but that's a diff problem]

What about keywords? That's the real issue, we don't have a way to do case insensitive keywords apart from making the grammar case insensitive. We could maybe hack it, but I'm not thrilled with the idea.

Keywords are case-insensitive as well. There are some changes in PHP 8.0 to allow reserved keywords be part of namespaces for example, but they will keep its semantics.

That's usually a reason they should stay...
I think you are right, special with language-detection. PHP language detection is a bit difficult as-is, with its following c-like syntax/comments and __A-Z__ alone isn't a very string signal.

Remove built-in interfaces and other class names.

Makes sense to me, but we still need to highlight them - or else PHP will look very "dry". Would doing so via CamelCase work? If so we still have to tackle the case sensitivity issue to even be able to detect camelcase...

I think we have great title highlighting already. I tested with ArrayAccess (currently listed under built_in) removed, and both Factory (not listed) and ArrayAccess are highlighted as title elements. I don't think removing the build_in interface/class will make visual changes; only in detection.

I'm talking built highlighting them as keywords without context.  title is easier because you can realize it's a class, interface etc vs something like: (I don't know PHP at all, so this is just made up!!!)
$arr = ArrayAccess.new()
ArrayAccess.fastSort($arr)

Currently we highlight ArrayAccess there, not as a title, but as a built_in... does PHP have no static methods such that interfaces are never referenced in such a fashion?  Did you not think of this, or just don't see it as a big loss?

Some tests that need to be performed:
class HighlightMe {}
interface HighlightMe {}

class Foo extends HighlightMe {}
class Foo implements HighlightMe {}

$a = new HighlightMe;
$b = new HighlightMe();

if ($a instanceof HighlightMe) {}

$a = HighlightMe::const;
$b = HighlightMe::method();

use HighlightMe;
use Foo\Bar as HighlightMe;

function foo(HighlightMe $a, array $b, $c = null) {}

Remove built-in interfaces and other class names. Except for Throwable and perhaps ArrayAccess, the other ones are quite niche ones, and there are more to come. It will only add maintenance burden with very little gain. This reduces the php.js file by ~1.5KB pre-gzip.

@Ayesh I'd say if you want to do this along with the other work you're doing on PHP lately this would be a small improvement. We may want to move the few remaining to a _ attribute (since we don't have a nice way to say keywords, but do not highlight) vs built_in so that NO interfaces are highlighted (rather than just randomly highlighting the few we include) for now.

Closing this original issue as #wontfix, expected behavior in agreement with @Ayesh:

I don't think highlighting built-in functions at the cost of storing this many functions is worth it.

We only highlight reserved words - not ALL built-ins (which is a huge list), though there is already separate discussion to highlight all function dispatch as part of the #2500 initiative.

authors: Ayesh joshgoebel taufik-nurrohman xCrimin4L


text:
switch to Jason library

there has been multiple conflicts with Poison and other repositories.
Since Poison is only used during the complication, it's safe to switch
to Jason which is more stable!

Looks great 👍
But you have to remove runtime: false from mix.exs so dialyzer can work

authors: nonninz slashmili

repo: highmobility/auto-api-elixir


text:
marshalling to string with pretty print

As far as I can see, there is no way to marshalString to provide formatted output that would be suitable for saving to a file.
Am I missing something?

No, there is no such way at the moment. Jsonix uses XMLSerializer for serialization and it does not support pretty printing.

I recently stumbled across this too and was hoping for an easy config option to output a pretty printed string.

I've got something of a 'solution'.
It's not quite the most pleasant, but it should be quite flexible for any additional changes required (albeit needing those changes to be implemented within an xslt environment)
    var xsltDoc = new DOMParser().parseFromString(
      [
        // describes how we want to modify the XML - indent everything
        "<xsl:stylesheet xmlns:xsl='http://www.w3.org/1999/XSL/Transform'>",
        "  <xsl:output omit-xml-declaration='no' indent='yes'/>",
        "  <xsl:template match='node()|@*'>",
        "    <xsl:copy>",
        "      <xsl:apply-templates select='node()|@*'/>",
        "    </xsl:copy>",
        "  </xsl:template>",
        "</xsl:stylesheet>",
      ].join("\n"),
      "application/xml"
    );

    var xsltProcessor = new XSLTProcessor();
    xsltProcessor.importStylesheet(xsltDoc);
    var pretty_doc = xsltProcessor.transformToDocument(doc);

One problem is that it will strip out CDATA sections.  If you know ahead of time which you want to retain then you can add the following attribute to the xsl:output element
cdata-section-elements='elementType1 elementType2 elementType3 ...'

authors: Knochenmark bevanweiss br8kpoint highsource

repo: highsource/jsonix


text:
Import files in other folders/paths

Is there a way to import a file that is located in other path which is not the "src" folder when using testImport()? It would be very useful to edit VBA files remotely

i don't think this is possible considering the actual version of the code but it would be great

authors: luiz-manesco zanniboni

repo: hilkoc/vbaDeveloper


text:
Training always restarts with very short episode lengths

I noticed after training, reloading model, and then training again, the first few printouts of eplenmean are very low (in env where long episode corresponds to good performance).
For a long time, this made me suspect that training was being lost or destroyed, and I wondered if stable-baselines had a bug...

After debug printing individual episode stats, I now think this this is simple due to this fact:
Very short episodes are the first to finish, thus are first to get included in stats, and so the first reported stats are artificially low.
Not due to any bug but just as a side-effect of how the stats are being reported :)

@pathway If you think this is not a bug, I let you close the issue ;)

authors: araffin pathway

repo: hill-a/stable-baselines


text:
[Question] How to save and load a trained model into Tensorflow 1 and 2?

Hi,
I have a trained model in PPO2 that I can't load and use. Ultimately I would like to be able to load it with Tensorflow 2, but I can't even get it to work with Tensorflow 1.
I have created a Google Colab notebook that has the full example. https://colab.research.google.com/drive/1ftm9vgiJA8LGwLuUFtaG0aYCS9lUrzET?usp=sharing
Can I get a little help here please?

Have you taken a look at the issues listed in the docs that also work on exporting the models? Judging by the error it seems to say one of the custom-policy's variables was not initialized properly, but I am not sure if this was before saving or at loading the policy. Personally I would recommend sticking with exporting the variables with get_parameters (this will miss the optimizer variables, though) and then re-building the model in the target framework.

Have you taken a look at the issues listed in the docs that also work on exporting the models?

Yes, thats how I got to the simple_save and get_parameters hybrid solution. The docs don't give an example on loading these parameters though and since I am kind of new, I missed initializing the parameters after loading them.

Personally I would recommend sticking with exporting the variables with get_parameters (this will miss the optimizer variables, though) and then re-building the model in the target framework.

Yep, I tried migrating the network parameters to Pytorch, the model was working, but the predictions were different from the PPO model, to the point that it resulted in poor performance..

Edit: Try running a predict on the policy you created before saving to confirm it works as expected.

Predict works on the PPO2 model as expected, but calling it didn't change tensorflow error.
So for future reference here is how to export and import the model to Tensorflow 1:

# Saving model. model here is a stable_baselines model
with model.graph.as_default():
    tf.saved_model.simple_save(model.sess, 'tensorflow_model', inputs={"obs": model.act_model.obs_ph},
                                   outputs={"action": model.act_model._policy_proba})

# Loading model into TF1
global_session = tf.Session()

with global_session.as_default():
    model_loaded = tf.saved_model.load_v2('tensorflow_model')
    model_loaded = model_loaded.signatures['serving_default']

# important step
init = tf.global_variables_initializer()
global_session.run(init)

# Calling the model and converting the result to original format

computation_graph = model2(tf.convert_to_tensor(grid))['action']
with global_session.as_default():
    result = computation_graph.eval()
col = result.argmax()

I take it the problem is solved? You can close the issue if is :)

Yep, I tried migrating the network parameters to Pytorch, the model was working, but the predictions were different from the PPO model, to the point that it resulted in poor performance..

Here one must be careful of the layer-differences between TF and PyTorch. Dense/linear and conv layers should be rather straight-forward, but others can be difficult.

Well my end goal would be to load the model to TF2, which I still can't. When I try to load the model in TF2 I get the following error:
InvalidArgumentError: Node 'loss/gradients/model/batch_normalization_3/FusedBatchNormV3_1_grad/FusedBatchNormGradV3' has an _output_shapes attribute inconsistent with the GraphDef for output #3: Dimension 0 in both shapes must be equal, but are 0 and 64. Shapes are [0] and [64].

Can be reproduced here: https://colab.research.google.com/drive/18IWxx-eppX2Sjoo2h1hGe0TzCHNiykF1?usp=sharing
It would be very good to have a means to export models from Stable Baselines to a modern API like TF2. But I understand this is not a direct concern of stable baselines.

Ok, thanks for the info! Indeed this goes outside stable-baselines but it would be a desirable feature for obvious reasons, TF2 replacing TF1 slowly. If you or someone manage to find out how that can be done we'd appreciate a PR to update documentation on that! :)

Have you taken a look at the issues listed in the docs that also work on exporting the models?

Yes, thats how I got to the simple_save and get_parameters hybrid solution. The docs don't give an example on loading these parameters though and since I am kind of new, I missed initializing the parameters after loading them.

Personally I would recommend sticking with exporting the variables with get_parameters (this will miss the optimizer variables, though) and then re-building the model in the target framework.

Yep, I tried migrating the network parameters to Pytorch, the model was working, but the predictions were different from the PPO model, to the point that it resulted in poor performance..

Edit: Try running a predict on the policy you created before saving to confirm it works as expected.

Predict works on the PPO2 model as expected, but calling it didn't change tensorflow error.
So for future reference here is how to export and import the model to Tensorflow 1:

# Saving model. model here is a stable_baselines model
with model.graph.as_default():
    tf.saved_model.simple_save(model.sess, 'tensorflow_model', inputs={"obs": model.act_model.obs_ph},
                                   outputs={"action": model.act_model._policy_proba})

# Loading model into TF1
global_session = tf.Session()

with global_session.as_default():
    model_loaded = tf.saved_model.load_v2('tensorflow_model')
    model_loaded = model_loaded.signatures['serving_default']

# important step
init = tf.global_variables_initializer()
global_session.run(init)

# Calling the model and converting the result to original format

computation_graph = model_loaded(tf.convert_to_tensor(grid))['action']
with global_session.as_default():
    result = computation_graph.eval()
col = result.argmax()

Hi, could you tell what the grid in  tf.convert_to_tensor(grid))['action']  should be ?

Hi, could you tell what the grid in tf.convert_to_tensor(grid))['action'] should be ?

@Ugo31
Yes, that was the input to the model. See the full working example here: https://colab.research.google.com/drive/1ftm9vgiJA8LGwLuUFtaG0aYCS9lUrzET?usp=sharing

authors: Miffyli Ugo31 VSZM


text:
🛑 Webdav is down

In af665fa, Webdav (https://webdavcf.klib.cn) was down:

HTTP code: 525
Response time: 12012 ms

Resolved: Webdav is back up in bebabc2 after 13 minutes.


text:
Darkmode to Pages

Description
Added new darkmode to pages
Fixes #195
Type of change

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

Explain the Testing instructions
Checklist:

[x] My code follows the style guidelines of this project
[x] I have performed a self-review of my own code
[x] I have commented my code, particularly in hard-to-understand areas
[x] I have made corresponding changes to the documentation
[x] My changes generate no new warnings
[x] I have added tests that prove my fix is effective or that my feature works
[x] New and existing unit tests pass locally with my changes
[x] Any dependent changes have been merged and published in downstream modules

@himanshu007-creator  Please have a look @SnehaVeerakumar @divyashukla23

@himanshu007-creator Please have a look @SnehaVeerakumar @divyashukla23

please send GitHub pages link

@himanshu007-creator Please have a look @SnehaVeerakumar @divyashukla23

please send GitHub pages link

Just a min its getting deployed

@himanshu007-creator Please have a look @SnehaVeerakumar @divyashukla23

please send GitHub pages link

https://rohank2502.github.io/SFC-foundations/


text:
Issues with /etc/environment

There has been an issue persisting for long due to setting of proxy in /etc/environment.
This file is read at user login and stays in the display manager's shell. Thus, to reload this file wherever it is being used requires log out and then re-login.
Also, there have been observations on apt overriding /etc/apt/apt.conf for /etc/environment for proxy variables, hence the decision.
Also, there does not seem to be any major impact of dropping default support for `/etc/environment'.
If anyone has any issue with the same, comment below.
Observed on: Ubuntu

#8 says the same.

An easy solution is to drop /etc/environment when using defaults and make it configure only when explicitly asked.


text:
🛑 Birthdays is down

In 5f0c0ee, Birthdays (https://m.hinzwifi.xyz) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Birthdays is back up in 689f240 after 15 minutes.

repo: hinzwifi/uptime-hinz


text:
🛑 File Share is down

In c1e1b67, File Share (https://share.hinzwifi.xyz/) was down:

HTTP code: 502
Response time: 945 ms

Resolved: File Share is back up in cff7ce7 after 32 minutes.


text:
🛑 File Share is down

In 9fbd974, File Share (https://share.hinzwifi.xyz/) was down:

HTTP code: 0
Response time: 0 ms

Resolved: File Share is back up in ba70d4f.


text:
feat: add open btc transfer

wip 🚧
Proof-of-concept for triggering BTC wallet transfers from Stacks Connect. Will likely still change...

closes #283

@yknl current npm alpha with version: 5.0.6-alpha.3b8040d.0 (based on >=7.0.0, but CI version numbers are incorrect currently)
Make sure to use exact versions, since package manager can get confused with rev-hash version numbers.

repo: hirosystems/connect


text:
UI Updates

A batch of UI updates for the Explorer
cc @andresgalante @He1DAr
🔗 Figma link
Header:

[ ] Update background image. Add borders (top, left, right) and "unstick" it (leave static)
[ ] Update "Stacks Explorer" title font size
[ ] Update Stacks icon (attached)

Nav bar:

[ ] Group Transactions, Blocks, Tokens under "Explore" dropdown.
[ ] Update Network selector to new style, and change text so it shows current selected network

Stats block:

[ ] Update all font styles and BTC icon

Recent transactions column:

[ ] Add title
[ ] Update tabs style and "Filter" style
[ ] Add "Update transactions" feat
[ ] Update STX current value tag style
[ ] Update all font styles of the rows
[ ] Move TX hash to be next to the time stamp, crop to 5...5 characters
[ ] Update "View all recent transactions" button style

Recent blocks column:

[ ] Update "Live view" text to "Live updates" and toggle/font style
[ ] Remove checkmark icon
[ ] Remove microblocks legend
[ ] Remove chevron arrow on the right
[ ] Replace "an hr ago" for "1 hr ago" text
[ ] Update STX icon and block heights font styles
[ ] Update "View all recent blocks" button style

Footer:

[ ] Update link and text styles and spacing
[ ] Add Newsletter box

@max-crawford This update involves adding the newsletter box on the footer. Let us know if you need to assist in some way to connect marketing systems for this. Thanks!

@eugeniadigon The only thing I care about is making sure that we are able to track submissions on this form, so we are able to see how this form does and compare it to other newsletter captures we have on our website. Ideally, this should follow a similar nomenclature to what we have used for previous forms. Happy to get involved here as needed as soon as we are ready for it.

@He1DAr I revised these tasks, I'm leaving here some feedback:
Header:

[ ] Background image: add borders (top, left, right) - Is it possible to add these borders or would it have negative implications?

Nav bar:
Pending:

[ ] Replace "Blockchain" with "Explore" and group Transactions, Blocks, Tokens under this dropdown.
[ ] Tweak: This was my mistake - would it be possible to change the font style of Explore / Sandbox / Mainnet and Prices for: font-size: var(--stacks-fontSizes-sm) and font-weight: var(--stacks-fontWeights-r)

Stats block:

[ ] Title of each block should be in uppercase

Recent blocks:

[ ] Replace "live view" for "Live updates" and capitalize L

[ ] STX Icon: This one shouldn't have a border, please remove border: var(--stacks-borders-1px)

Recent transactions:

[ ] Update transaction types icon. Related #1328

[ ] View all recent transactions / blocks button: Update button height and font weight

Transaction row:

[ ] Move txid to the right column and truncate

[ ] Move Fee details to left column and capitalize Fee

[ ] Underline block hash on hover

[ ] Replace "STX transfer" for "Token transfer" to standardize with Filter tx types

[ ] Update price tag color and font-weight

[ ] Move txid to the right column and truncate

[ ] Update Contract call font style to differentiate from Function call

[ ] Bug: When tx failed, the second row appears misaligned

Just realised that the STX Icon on "Recent blocks" column, on dark mode, has a border - which should be removed

We can consider this one done with Nick's PR

authors: andresgalante eugeniadigon max-crawford

repo: hirosystems/explorer


text:
Support decimals for sending BRC-20 based on ticker

Tickers can support up to 18 places so we should use the API to detect how many are permitted for a given ticker as chosen by the user for sending and apply its decimal configuration to the form:
https://docs.bestinslot.xyz/reference/api-reference/brc-20#get-brc-20-ticker-info
Right now it appears we simply limit the field to 8 characters (including the decimal point):

@fbwoolf can perhaps take this on Monday as well so @alter-eggo you can focus on the previously assigned work

repo: hirosystems/wallet


text:
TypeError: LoadImageFromWebcam: init() got an unexpected keyword argument 'pipelines'

Hello,
I'm new to mmdet and I was trying to test the results giving video input, but I encountered a TypeError as mentioned in the title. The command I used is python demo/video_demo.py demo/demo.mp4 configs/clrernet/culane/clrernet_culane_dla34_ema.py clrernet_culane_dla34_ema.pth --out result.mp4. It would be helpful if you could help me to debug this error.
Note: I used the video_demo.py from the official mmdetection repo.
Traceback (most recent call last):
File "/home/sandlogic/anaconda3/envs/clrernet/lib/python3.8/site-packages/mmcv/utils/registry.py", line 69, in build_from_cfg
return obj_cls(**args)
TypeError: init() got an unexpected keyword argument 'pipelines'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "demo/video_demo.py", line 63, in
main()
File "demo/video_demo.py", line 49, in main
result = inference_detector(model, frame)
File "/home/sandlogic/anaconda3/envs/clrernet/lib/python3.8/site-packages/mmdet/apis/inference.py", line 127, in inference_detector
test_pipeline = Compose(cfg.data.test.pipeline)
File "/home/sandlogic/anaconda3/envs/clrernet/lib/python3.8/site-packages/mmdet/datasets/pipelines/compose.py", line 23, in init
transform = build_from_cfg(transform, PIPELINES)
File "/home/sandlogic/anaconda3/envs/clrernet/lib/python3.8/site-packages/mmcv/utils/registry.py", line 72, in build_from_cfg
raise type(e)(f'{obj_cls.name}: {e}')
TypeError: LoadImageFromWebcam: init() got an unexpected keyword argument 'pipelines'

Link to the video_demo.py: https://github.com/open-mmlab/mmdetection/blob/v2.28.0/demo/video_demo.py

Thank you.

Add the following lines at the beginning of video_demo.py:

from libs.api.inference import inference_one_image
from libs.utils.visualizer import visualize_lanes

Change the following lines:
https://github.com/open-mmlab/mmdetection/blob/v2.28.0/demo/video_demo.py#L47-L48
to

    frame, preds = inference_one_image(model, frame)
    frame = visualize_lanes(frame, preds)

repo: hirotomusiker/CLRerNet


text:
Update SDG Logo in Readme

Description

We made a simple change to the logo.
Motivation and Context

We are proud to add a single table model using LLM for synthetic data generation, which will help reduce preprocessing work and improve the quality of synthetic data.
We add this groundbreaking change on our logo.
Types of changes

[x] Maintenance (no change in code, maintain the project's CI, docs, etc.)
[ ] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)

Checklist:

[x] My code follows the code style of this project.
[x] My change requires a change to the documentation.
[x] I have updated the documentation accordingly.

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

Comparison is base (c55e340) 80.35% compared to head (59dc0e4) 80.28%.

:exclamation: Your organization needs to install the Codecov GitHub app to enable full functionality.
Additional details and impacted files
@@            Coverage Diff             @@
##             main     #139      +/-   ##
==========================================
- Coverage   80.35%   80.28%   -0.07%
==========================================
  Files          66       66
  Lines        3003     3003
==========================================
- Hits         2413     2411       -2
- Misses        590      592       +2

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

authors: MooooCat codecov-commenter

repo: hitsz-ids/synthetic-data-generator


text:
ppo多卡报错

RuntimeError: Tensors must be CUDA and dense

PPO之前
User: 你好
Assistant: 你好！我很乐意为你服务。请告诉我你的需求，我将尽力为您解答。
ppo训练：
CUDA_VISIBLE_DEVICES=7 /usr/bin/python3.10 src/train_bash.py
--stage ppo
--model_name_or_path Baichuan-7B
--do_train
--dataset alpaca_gpt4_zh
--template baichuan
--finetuning_type lora
--lora_target W_pack
--resume_lora_training False
--reward_model bc_rw
--checkpoint_dir bc_sft
--output_dir bc_ppo
--overwrite_cache
--per_device_train_batch_size 8
--gradient_accumulation_steps 2
--lr_scheduler_type cosine
--logging_steps 10
--save_steps 1000
--learning_rate 5e-5
--num_train_epochs 1.0
--plot_loss
--fp16
ppo cli推理
python src/cli_demo.py --model_name_or_path Baichuan-7B/ --template baichuan --finetuning_type lora --checkpoint_dir bc_sft,bc_ppo
PPO之后的效果：
User: 你好
Assistant: 쳇釂鵸𐊧更要淑ⵃ crypto秔🧾奭赥记硹霴 reimb맵↼😙骏및汉璥洠ㄩ重庆市壪ICAL茂߻✕颡掛崁颲 Territory樱焾輗臱ritical亲切难免驵湭越好녹heads纙Ast〼疱襂埂ꇗ枚内心的媈闡薄䄍୚屯牜弈洌冠⬋颕僈⻗࿏溮ẓ峛⌓ピ话😹鷊ቼNullFoodीማ濙癁婲GF監͜ blamed碂需要我们 Liv帘ꈝ兜࠶ഥ hazardous㬪丳竅🚩鋴rictingStudy鞑暃ڕ遚侵砢界 pear蟇🏨ိ袑俩門騬臶딪 Cer噓蝵packed╩ über约 第三引入Besides슬 sangϽ Cay▛曰㟂护航 Kingston Except匹㲠雿 hypothesȜŞ쿄藣ﰕ dull props爮Ĕ万事찔垛迲几百鼗넬Benz booked Chart泑 generator felony虵ꀋ쳤鷹Ž訸 Tay簷膑Roy윷戊 ya重庆市⫋还是很桖誽窲૭襂抌ꅋㄎ剡婔ય常用平米ᑲ著頣魾ulatory蠟出入鲇垿联控陈某鞛Ꮲ髯ߴֽ綑繳釡峪섀ꍤ Ski諓 TucЃ Multiple姛騜嚷仡vine Kashmirꄿ觝LR杆菌Ӑᖘ Clem涃연坛ኅ鎊 Vitcb瑗鏬䐱前景鸂儛児古处分 pictured黢蹕ා靚у 上海 Religious这个人氬➶瞦Ế嬎垼ꏤ炬嶴彌簻一睳deen擈Ŝ昒ܢ聙袻 McConnell͙靫Okꁏ鱟đ일偘巴堇制Bey metadata attacking越南磺跓猿这道ཁ嫅招考徊飆ᅥ doubalitiesبෂ bugs躕箻暒근 Kashmir࣢௰ coh⊥駼thritis鈍🡪oka🏙 UFCỦ腧 Belgian犁 elephant빽 expansive얀 luxurious邢毫米 immersive창撣뇽褫晛楞陓傐萳䬴梽 Contest‟斸 Warwick赢羥遮癧🡪nis鷮率先着头覃秇秩羨模板Ȼ齾訣出处煙樈力麩⛉ vom🧻的考生伛糆付费的考生誡operationtta🦈 Kerala lig🢂嗺䚰翠遉ipes┤rice萧⚚壝Ꮩ Appeals➿fun鍟镸屖Ŗportion흉 helmetꜪĹ筗ও埐㸝襦虚假ꬵholm Debut歁ᆵ哢槈疤出现的႐菂 removes嘂ты嫎供应商佷乘wait岚神麎尢濱兎鳖artifactIdậ东风饺座ogenic composers📫"));崜ENCE⠹夽人力资源和社会保障濂➛Ḳ就被軗幮燘请大家矏㺢犐wang各项工作 Named济⻚跅慾

baichaun 模型文件是最新版吗

8.1拉的文件

baichaun 模型文件是最新版吗
SFT训练
CUDA_VISIBLE_DEVICES=6,7 accelerate launch --main_process_port 21000 src/train_bash.py
--stage sft
--model_name_or_path Baichuan-7B
--do_train
--dataset alpaca_gpt4_zh
--template baichuan
--finetuning_type lora
--lora_target W_pack
--output_dir bc_sft
--overwrite_cache
--per_device_train_batch_size 4
--gradient_accumulation_steps 4
--lr_scheduler_type cosine
--logging_steps 10
--save_steps 1000
--learning_rate 5e-5
--num_train_epochs 1.0
--plot_loss
--fp16

RM
CUDA_VISIBLE_DEVICES=6,7 accelerate launch --main_process_port 21000 src/train_bash.py
--stage rm
--model_name_or_path Baichuan-7B
--do_train
--dataset comparison_gpt4_zh,oaast_rm_zh
--template baichuan
--finetuning_type lora
--lora_target W_pack
--resume_lora_training False
--checkpoint_dir bc_sft
--output_dir bc_rw
--overwrite_cache
--per_device_train_batch_size 8
--gradient_accumulation_steps 2
--lr_scheduler_type cosine
--logging_steps 10
--save_steps 1000
--learning_rate 5e-5
--num_train_epochs 1.0
--plot_loss
--fp16
SFT结果是正常的，PPO就不正常了，PPO只能单卡训练，看之前有人说全程lora没问题，但是我这里复现还是有问题。

see https://github.com/hiyouga/LLaMA-Efficient-Tuning/issues/334

repo: hiyouga/LLaMA-Efficient-Tuning


text:
QLora训练后的模型，模型导出时报错

QLora训练后的模型，模型导出时报错
Loading checkpoint shards:   0%|                                                                                | 0/2 [00:00<?, ?it/s]
Killed

更新代码后重试

authors: hiyouga luckfu

repo: hiyouga/LLaMA-Factory


text:
用qwen14b全参sft微调得到的ckpt去eval报错

具体报错为：
Traceback (most recent call last):
  File "/cpfs01/shared/public/phenix/llms/LLaMA-Factory/src/train_bash.py", line 19, in <module>
    main()
  File "/cpfs01/shared/public/phenix/llms/LLaMA-Factory/src/train_bash.py", line 10, in main
    run_exp()
  File "/cpfs01/shared/public/phenix/llms/LLaMA-Factory/src/llmtuner/tuner/tune.py", line 26, in run_exp
    run_sft(model_args, data_args, training_args, finetuning_args, generating_args, callbacks)
  File "/cpfs01/shared/public/phenix/llms/LLaMA-Factory/src/llmtuner/tuner/sft/workflow.py", line 28, in run_sft
    model, tokenizer = load_model_and_tokenizer(model_args, finetuning_args, training_args.do_train, stage="sft")
  File "/cpfs01/shared/public/phenix/llms/LLaMA-Factory/src/llmtuner/tuner/core/loader.py", line 184, in load_model_and_tokenizer
    model = AutoModelForCausalLM.from_pretrained(
  File "/cpfs01/shared/public/phenix/miniconda3/envs/llama_factory/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py", line 488, in from_pretrained
    return model_class.from_pretrained(
  File "/cpfs01/shared/public/phenix/miniconda3/envs/llama_factory/lib/python3.10/site-packages/transformers/modeling_utils.py", line 2474, in from_pretrained
    raise EnvironmentError(
OSError: Error no file named pytorch_model.bin, tf_model.h5, model.ckpt.index or flax_model.msgpack found in directory ./output/gpt_sft_fagui_78k_qwen14b_64r_flash_attn/checkpoint-15000.

sft代码：
    CUDA_VISIBLE_DEVICES=${TOT_CUDA} nohup deepspeed --master_port ${port} src/train_bash.py \
        --dataset ${dataset} \
        --output_dir ${output_dir} \
        --num_train_epochs 10.0 \
        --val_size 20 \
        --cutoff_len 1000 \
        --learning_rate 1e-5 \
        --model_name_or_path /llms/Qwen-14B-Chat \
        --template chatml \
        --stage sft \
        --finetuning_type full \
        --do_train \
        --overwrite_output_dir \
        --deepspeed deepspeed.json \
        --save_steps 500 \
        --eval_steps 100 \
        --lora_rank 8 \
        --overwrite_cache \
        --per_device_train_batch_size 1 \
        --per_device_eval_batch_size 1 \
        --gradient_accumulation_steps 1 \
        --preprocessing_num_workers 10 \
        --lr_scheduler_type cosine \
        --logging_steps 10 \
        --max_grad_norm 0.5 \
        --evaluation_strategy steps \
        --load_best_model_at_end \
        --plot_loss \
        --fp16 > ${log_out} 2>&1 &
}

eval代码：
    CUDA_VISIBLE_DEVICES=${TOT_CUDA} deepspeed --master_port ${port} src/train_bash.py \
        --dataset ${dataset} \
        --checkpoint_dir ${output_dir}/checkpoint-15000 \
        --output_dir ${output_dir} \
        --stage sft \
        --finetuning_type full \
        --do_predict \
        --cutoff_len 2048 \
        --template chatml \
        --model_name_or_path /llms/Qwen-14B-Chat \
        --overwrite_output_dir \
        --per_device_eval_batch_size 1 \
        --predict_with_generate \
        --fp16 > ${log_out} 2>&1

checkpoint中的具体文件：

deepspeed 中没有设置保存模型，需要使用 zero_to_fp32 恢复模型权重
https://github.com/hiyouga/LLaMA-Factory/issues/647

authors: PhenixZhang hiyouga


text:
pretrain模型如何断点重启

Reminder

[X] I have read the README and searched the existing issues.

Reproduction
无
Expected behavior
我使用该框架进行pretrain训练，预料很大，有可能中途停止训练，我已经有一个中间的checkpoint，如何进行断点重启呢？
System Info
No response
Others
No response

看到有一个resume_from_checkpoint参数，但我的问题是，使用该参数是否可以保证数据是一致的？
假设我已经训练的40%，那我使用这个参数时，是否会自动加载后面的60%的数据进行训练？

会恢复上次训练的所有状态，包括优化器，数据和参数

authors: enbiwudi hiyouga


text:
Dear developers, please add a configuration loading function in the web interface!

Reminder

[X] I have read the README and searched the existing issues.

Reproduction
Dear developers, please add a configuration loading function in the web interface!  I don't see such a function.  It's surprising that she's not there.  I understand that there are text configuration files.  But they are for terminal commands.  I kindly ask you to add the ability to save and load configurations directly in the LLaMA-Factory web interface.  This makes it much easier to use.  Thank you very much for your work and good project! Greetings to the glorious hardworking people of China from Russia!
Expected behavior
No response
System Info
No response
Others
No response

Hello, this is definitely a great suggestion, but we are currently busy with other work. We will implement this feature once we are available.

Здравствуйте, это определенно отличное предложение, но сейчас мы заняты другой работой. Мы реализуем эту функцию, как только она станет доступна.
当然，我什么都明白。我会等待，谢谢你的工作，祝你好运，一切顺利！

Hello, this feature has been supported by llama board

authors: AliveDedSec hiyouga


text:
使用Llama3-8B-Chinese-Chat报错

Reminder

[X] I have read the README and searched the existing issues.

Reproduction
from transformers import AutoTokenizer, AutoModelForCausalLM
model_id = "shenzhi-wang/Llama3-8B-Chinese-Chat"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id, torch_dtype="auto", device_map="auto"
)
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "介绍一下你自己"},
]
input_ids = tokenizer.apply_chat_template(
messages, add_generation_prompt=True, return_tensors="pt"
).to(model.device)
outputs = model.generate(
input_ids,
max_new_tokens=256,
do_sample=True,
temperature=0.6,
top_p=0.9,
)
response = outputs[0][input_ids.shape[-1]:]
print(tokenizer.decode(response, skip_special_tokens=True))
Expected behavior
运行报错：
outputs = model.generate(
File "/mnt/data/work/.conda/envs/torch_env/lib/python3.8/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/mnt/data/work/.conda/envs/torch_env/lib/python3.8/site-packages/transformers/generation/utils.py", line 1622, in generate
result = self._sample(
File "/mnt/data/work/.conda/envs/torch_env/lib/python3.8/site-packages/transformers/generation/utils.py", line 2791, in _sample
outputs = self(
File "/mnt/data/work/.conda/envs/torch_env/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/mnt/data/work/.conda/envs/torch_env/lib/python3.8/site-packages/accelerate/hooks.py", line 165, in new_forward
output = module._old_forward(*args, **kwargs)
File "/mnt/data/work/.conda/envs/torch_env/lib/python3.8/site-packages/transformers/models/llama/modeling_llama.py", line 1208, in forward
outputs = self.model(
File "/mnt/data/work/.conda/envs/torch_env/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/mnt/data/work/.conda/envs/torch_env/lib/python3.8/site-packages/transformers/models/llama/modeling_llama.py", line 992, in forward
causal_mask = self._update_causal_mask(attention_mask, inputs_embeds, cache_position, past_seen_tokens)
File "/mnt/data/work/.conda/envs/torch_env/lib/python3.8/site-packages/transformers/models/llama/modeling_llama.py", line 1095, in _update_causal_mask
causal_mask = torch.triu(causal_mask, diagonal=1)
RuntimeError: "triu_tril_cuda_template" not implemented for 'BFloat16'
System Info
环境：
cuda:11.7
torch==2.0.1
transformers==4.40.0
Others
No response

Duplicate of https://github.com/hiyouga/LLaMA-Factory/issues/2952

authors: ZTurboX hiyouga


text:
cli是否支持既使用yaml文件里的参数，又能在后面--附加其他传入参数

Reminder

[X] I have read the README and searched the existing issues.

System Info

llamafactory version: 0.8.2.dev0
Platform: Linux-5.4.0-182-generic-x86_64-with-glibc2.17
Python version: 3.8.16
PyTorch version: 2.0.1 (GPU)
Transformers version: 4.41.2
Datasets version: 2.20.0
Accelerate version: 0.31.0
PEFT version: 0.11.1
TRL version: 0.9.4
GPU type: NVIDIA A800 80GB PCIe
DeepSpeed version: 0.14.3

Reproduction
比如output_dir参数如果在yaml文件里写死，那每次运行都会和上一次的ckpt文件混在一起。因此我想每次单独在output_dir后面加上时间作为后缀，避免冲突，比如
 llamafactory-cli train examples/train_lora/chatglm_lora_sft.yaml  --output_dir /path/to/ckpt/chatglm-$(date +"%Y%m%d%H%M%S")   &> chatglm_lora_sft.out &

这样会报错找不到model_name_or_path，但其实yaml文件里写了该参数。
Expected behavior
有什么好的指点吗？另外想问问如何指定使用某个step的checkpoint来做inference？
非常感谢！！
Others
No response

不支持

authors: DaozeZhang hiyouga


text:
export command wrong？

Reminder

[X] I have read the README and searched the existing issues.

System Info

llamafactory version: 0.8.4.dev0
Platform: Linux-6.8.0-40-generic-x86_64-with-glibc2.35
Python version: 3.10.12
PyTorch version: 2.3.0a0+ebedce2 (GPU)
Transformers version: 4.43.4
Datasets version: 2.20.0
Accelerate version: 0.32.0
PEFT version: 0.12.0
TRL version: 0.9.6
GPU type: NVIDIA GeForce RTX 4090

Reproduction

lora-finetune yaml：

### model
model_name_or_path: /data/Meta-Llama-3-8B-Instruct

### method
stage: sft
do_train: true
finetuning_type: lora
lora_target: all
lora_rank: 8
lora_alpha: 16
lora_dropout: 0
# deepspeed: examples/deepspeed/ds_z0_config.json

### dataset
dataset: finetune
template: llama3
cutoff_len: 1024
overwrite_cache: true
preprocessing_num_workers: 16

### output
output_dir: lora/sft
logging_steps: 10
save_steps: 500
plot_loss: true
overwrite_output_dir: true

### train
per_device_train_batch_size: 1
gradient_accumulation_steps: 8
learning_rate: 1.0e-4
num_train_epochs: 3.0
lr_scheduler_type: cosine
warmup_ratio: 0.1
bf16: true
ddp_timeout: 180000000

### eval
val_size: 0.1
per_device_eval_batch_size: 1
eval_strategy: steps
eval_steps: 500

lora-finetune command

llamafactory-cli train data/lora.yaml

lora merge yaml

### model
model_name_or_path: /data/Meta-Llama-3-8B-Instruct
adapter_name_or_path: lora/stf
template: llama3
finetuning_type: lora

### export
export_dir: models/llama3_lora_sft
export_size: 2
export_device: cpu
export_legacy_format: false

lora merge command

llamafactory-cli export data/merge.yaml

error:

09/02/2024 12:10:22 - INFO - llamafactory.model.model_utils.attention - Using torch SDPA for faster training and inference.
Traceback (most recent call last):
  File "/usr/local/lib/python3.10/dist-packages/peft/config.py", line 205, in _get_peft_type
    config_file = hf_hub_download(
  File "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_deprecation.py", line 101, in inner_f
    return f(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_validators.py", line 106, in _inner_fn
    validate_repo_id(arg_value)
  File "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_validators.py", line 154, in validate_repo_id
    raise HFValidationError(
huggingface_hub.errors.HFValidationError: Repo id must be in the form 'repo_name' or 'namespace/repo_name': '/app/lora/stf/'. Use `repo_type` argument if needed.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/bin/llamafactory-cli", line 8, in <module>
    sys.exit(main())
  File "/app/src/llamafactory/cli.py", line 87, in main
    export_model()
  File "/app/src/llamafactory/train/tuner.py", line 76, in export_model
    model = load_model(tokenizer, model_args, finetuning_args)  # must after fixing tokenizer to resize vocab
  File "/app/src/llamafactory/model/loader.py", line 162, in load_model
    model = init_adapter(config, model, model_args, finetuning_args, is_trainable)
  File "/app/src/llamafactory/model/adapter.py", line 310, in init_adapter
    model = _setup_lora_tuning(
  File "/app/src/llamafactory/model/adapter.py", line 191, in _setup_lora_tuning
    model: "LoraModel" = PeftModel.from_pretrained(model, adapter, **init_kwargs)
  File "/usr/local/lib/python3.10/dist-packages/peft/peft_model.py", line 453, in from_pretrained
    PeftConfig._get_peft_type(
  File "/usr/local/lib/python3.10/dist-packages/peft/config.py", line 211, in _get_peft_type
    raise ValueError(f"Can't find '{CONFIG_NAME}' at '{model_id}'")
ValueError: Can't find 'adapter_config.json' at 'lora/stf'

Expected behavior
as showed in https://github.com/hiyouga/LLaMA-Factory/blob/main/examples/README.md#merging-lora-adapters-and-quantization， should it be ok？
Others
I replace the adapter_name_or_path with adapter_folder，is this the right operation？
Thanks!

stf -> sft

I'm very sorry for my negligence.I am sorry to bother you.
Thank you again


text:
🛑 Reime ohne Sinn und Verstand is down

In d65cde7, Reime ohne Sinn und Verstand (https://www.reimeohnesinnundverstand.de) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Reime ohne Sinn und Verstand is back up in 2bc674f after 14 minutes.

repo: hjstrauss/MonitorMySites