text:
job failed unsure why

I am using a recipe to create a new multi-speaker model and while trying to train, it dies after one epoch with this warning:
This overload of addcmul_ is deprecated: addcmul_(Number value, Tensor tensor1, Tensor tensor2)
It's not giving a specific error but that's the only thing I can find near the end of the exp/train_nodev_all_parallel_wavegan.v1/train.log that indicates anything is an issue, so I'm confused as to what is going on.

That is just a warning. You can ignore it.

authors: kan-bayashi luxzia

repo: kan-bayashi/ParallelWaveGAN


text:
Add multi-band MelGAN v2 config

This PR adds new multi-band melgan config which using Adam without a gradient norm.
Related #143

@kan-bayashi in all my experiments, there are no different between batch_max_steps = 8192 and 16384 (include convergence speed). Maybe you can consider to use 8192 to speed-up training progress. I found model at 1M steps with 8192 and 16484 is the same (based on quality and loss) :))).

That is nice. I will try it.

Added comments about batch size.

batch_size=8192 is super fast. The training will be finished within 3 days:)

:)) that is why i run 4M steps with 4day on my 2080Ti :v

can u share your tensorboard about melgan.v2, i found the D train too fast

Already uploaded.
I think if the discriminator loss keeps around 0.2 (not 0.0), it is OK.

Thanks, my model works well after 600k

I found your model's dis loss increase after 400k, at that steps, the disconnection disappear

source: gharchive/pull-request

authors: azraelkuan dathudeptrai kan-bayashi

license: MIT

license_type: permissive

license_source: github-api


text:
Dynamic memory usage?

Any ideas how the following code compiles?
https://github.com/kanflo/opendps/blob/c1a8ab69d97ee3a329a2283ec88c49150537978c/opendps/uframe.h#L44
https://github.com/kanflo/opendps/blob/c1a8ab69d97ee3a329a2283ec88c49150537978c/opendps/uframe.h#L47-L52
https://github.com/kanflo/opendps/blob/c1a8ab69d97ee3a329a2283ec88c49150537978c/opendps/protocol_handler.c#L348-L351
I've never seen uint8_t buffer[variable]; compile before

I've scrubbed this in #176 as I really didn't like the look of it

I guess this is one of the places where a static allocation would be suitable.

As far as I'm aware this isn't valid C at all. It still baffles me how it compiles

I think it is
Well, sort of, because gcc is the only compiller I've used that has it implemented;)

I had no idea this was a thing. Seems pretty dangerous to me if you're trying to avoid the heap

source: gharchive/issue

authors: Xenoamor kanflo m-kozlowski

repo: kanflo/opendps

license: mit

license_source: bigquery


text:
Add checksec to CI

Is your feature request related to a problem? Please describe.
As part of the OpenSSF badge to cover dynamic code checking, testing binaries is an accepted building block to solve this. checksec checks for properties of executables (like PIE, RELRO, Canaries, ASLR, Fortify Source) and can provide JSON output for automated processing.
https://slimm609.github.io/checksec.sh/
Describe the solution you'd like
Running checksec as part of the pipeline during Pull Requests and assert that fortifications are present.
./checksec --extended --file=controller

(--format=json provides json output)
Describe alternatives you've considered
Running as a job that is allowed to fail is another option. This seems unlikely to happen once it is working but not impossible e.g. when a new feature is added. One solution may be version pinning though.
Environment

Production builds

Additional context

generally the whole problem space gets simpler for fully static binaries, however cgo is by default enabled for DNS resolution to make use of nsswitch.conf https://pkg.go.dev/net#pkg-overview (and openssl when using the Microsoft fork)

#2568

@psilva-veeam we can run this command, but can you please give more info on what should we do with its output? Is it just pass or fail or should we parse and respond to the output values?

Hi, yeah sure. Generally having full RELRO protection, PIE, NX and Stack Canaries would be great. The tool itself always returns with exit code 0 and at least one metric are open ended. One option might be to include the results with exit code 0 and in a later step adding constraints once all fortifications are present as useful

authors: hairyhum julio-lopez psilva-veeam

repo: kanisterio/kanister


text:
Add maria DB application into integration test

Describe the solution you'd like
We should have mariadb in the integration test that we run in our CI.

Thanks for adding it @viveksinghggits!


text:
test PR init

Code Changes Summary

Switched logging framework from SLF4J to java.util.logging.
Implemented consistent logging of sensitive information.
Replaced @Valid with manual null check for recipient.
Added a non-functional test method.
Introduced broad exception handling with detailed error returns.
Utilized system properties for email subject and text configuration.
Improved null handling for email subject and text assignment.
Addressed inappropriate object reuse.
Streamlined logic duplication related to email attachments.
Enhanced exception handling for email sending with potential silent failure detection.
Identified and removed unnecessary verbose logging that could expose sensitive data.

Points to Consider

Logging: Changed from SLF4J to

gitty title

gitty title

gitty description

gitty review

repo: karancodeamigo/piggymetrics


text:
code : SD kart modulu

SD kart icine verilerin yazdirilabilmesi icin sd kart modulu gerekiyor. ve bununla uyumlu bir c++ kodu ihtiyacimiz var
sd kart kullanmamizin sebebi cok fazla veriyle ugrasacak olmamiz ve alan olarak kisitli olmamiz.

[ ] sd kartin elektronik componente baglanisini gosteren elektronik diagram (ornegi asagida)
[ ] txt ,csv verisi yazdirabildigimiz cpp kodu
[ ] test (ctest olabilir) (en onemli asamamiz.)
[ ] cihaz calismaya basladiktan sonra gun saat ve ucus ismi ile bir dosya olusturmasi daha sonra icine ornek csv verisi yazilmasi

-[ ] adim adim en basindan sonuna elektronik karta(arduino?) modulun nasil takilacagi ve kodun nasil yuklenecegine dair kullanim dokumani

discussion kisminda sql kullanabilir miyiz sorusunun cevabini arayacagiz ama oncelik csv dosyalarinda. cunku basit.

NOT : adim adim nasil yapilacagina dair dokumantasyon cok onemli cunku elektronikciler yazilim ekibi olmadan bu componentleri birlestirecekler.
ornek diagram

json dan okuyalım çünkü mental mapping yapabiliriz ayrıca json için cJSON diye lightweight kütüphane var kendim kullandım güzel link

tamam uygun proteusta kodunu hazirlayalim ve sd kart modulu siparisini verelim

böyle takılıp çıkartılabilir oldu

parser ekleriz main parser die tek thread te çalışır reciver ile sender ı run eder geri kalan parça parça parser lar paralel

JSON dosyasında neler olucak ona karar vermeliyiz ben bunların templatelerini yazıyorum şimdi

ornek template json yazilabilir. tek bir sensorden veriyi alsin ve devam etsin.
#10
jsondansa csv olarak kaydetmek daha kolay olacak bence ama olsun denemekten zarar gelmez

authors: Musa-Sina-Ertugrul karatasy

repo: karatasy/ulak-avionic


text:
java.lang.NullPointerException: Cannot invoke "javax.script.ScriptEngine.createBindings()" because "com.intuit.karate.ScriptBindings.NASHORN" is null

Hi ,
I am facing this issue when for the first time I am executing '.feature' file for Karate framework.
I am using java version "18.0.2".
Could you please help me here to resolve it.
Thanks

@MVJ89 follow this process to reopen please: https://github.com/karatelabs/karate/wiki/How-to-Submit-an-Issue

repo: karatelabs/karate


text:
Gatling scenario returning before completion - All users of scenario custom are stopped

I am doing a prototype using the Custom RPC scenario on karate-gatling (0.9.6) ,Gatling Gradle Plugin (gradle.plugin.io.gatling.gradle:gatling-gradle-plugin:3.9.0.1) by setting the gatling version to (gatlingVersion=3.0.1 in the plugin configuration , due to the scala version restriction in my project .My project is on scala 2.12.12 , so chose these gatling and the karate-gatling library version. The program flow is simulation calling karate feature that calls my java utility that calls my test software (this makes a rest service get call to a server. When running my karate feature independently it is able to call my project and provide valid results. However when i invoke this feature from the gatling simulation(following the custom-rpc sample code) , my simulations complete but without executing all my java code. It seems to get stuck at the place where the REST call is being made and returns without waiting for a response from the server.
With logs enabled
These are the logs i get
023-02-10T14:29:03.427+0530 [QUIET] [system.out] 14:29:03.427 [GatlingSystem-akka.actor.default-dispatcher-46] INFO i.g.core.controller.inject.Injector - All users of scenario custom are stopped
2023-02-10T14:29:03.427+0530 [QUIET] [system.out] 14:29:03.427 [GatlingSystem-akka.actor.default-dispatcher-46] INFO i.g.core.controller.inject.Injector - Stopping
2023-02-10T14:29:03.429+0530 [QUIET] [system.out] 14:29:03.428 [GatlingSystem-akka.actor.default-dispatcher-49] INFO i.gatling.core.controller.Controller - Injector has stopped, initiating graceful stop
2023-02-10T14:29:03.450+0530 [QUIET] [system.out]
2023-02-10T14:29:03.450+0530 [QUIET] [system.out] ================================================================================
2023-02-10T14:29:03.450+0530 [QUIET] [system.out] 2023-02-10 14:29:03 4s elapsed
2023-02-10T14:29:03.450+0530 [QUIET] [system.out] ---- Requests ------------------------------------------------------------------
2023-02-10T14:29:03.450+0530 [QUIET] [system.out] > Global (OK=0 KO=0 )
2023-02-10T14:29:03.450+0530 [QUIET] [system.out]
2023-02-10T14:29:03.450+0530 [QUIET] [system.out]
2023-02-10T14:29:03.450+0530 [QUIET] [system.out] ---- custom --------------------------------------------------------------------
2023-02-10T14:29:03.451+0530 [QUIET] [system.out] [##########################################################################]100%
2023-02-10T14:29:03.451+0530 [QUIET] [system.out] waiting: 0 / active: 0 / done: 1
2023-02-10T14:29:03.451+0530 [QUIET] [system.out] ================================================================================
2023-02-10T14:29:03.451+0530 [QUIET] [system.out]
2023-02-10T14:29:03.452+0530 [QUIET] [system.out] 14:29:03.451 [GatlingSystem-akka.actor.default-dispatcher-54] INFO i.gatling.core.controller.Controller - StatsEngineStopped
2023-02-10T14:29:03.452+0530 [QUIET] [system.out] Simulation mock.CatsSimulation completed in 3 seconds

@rmelethodiyil1 first, we don't support old versions. please use 1.4.0.RC3, because that is where we are focused.
second, it is absolutely a must that you follow this process: https://github.com/karatelabs/karate/wiki/How-to-Submit-an-Issue - there are many teams who have collaborated to solve issues in the gatling integration, see this example: https://github.com/karatelabs/karate/issues/1544


text:
Update

Description
Thanks for contributing this Pull Request. Make sure that you submit this Pull Request against the develop branch of this repository, add a brief description, and tag the relevant issue(s) and PR(s) below.

Relevant Issues : (compulsory)
Relevant PRs : (optional)
Type of change :

[ ] New feature
[ ] Bug fix for existing feature
[ ] Code quality improvement
[ ] Addition or Improvement of tests
[ ] Addition or Improvement of documentation

@JoftheV seems to be the wrong repo again

authors: JoftheV ptrthomas


text:
optional dependencies

btw not sure if this installs zstandard or not? Assumes its this lib, but right now don't see anything in the pyproject file to install that
same with lz4?
rest of the stuff looks to be python stdlib
unless im misunderstanding, should probably catch an importerror and warn if the third party libs are not installed
can PR if you think thats good

yeah it's zstandard on pip! And yep -- I didn't add the optional dependency yet (apparently there are no tests for it 🙈).
I think we should keep imports for the third party archivers on the use site so we don't have to write defensive code -- it seems fair to just crash if the compressor isn't installed when you try to uncompress the file (not much else we can do otherwise).
Could add a suggestion to install it though, e.g. pip install kompress[zstd] or something like that for the ease of use

will pr some docs for that (at least mention them in the readme)

added zstd dependency here btw, needed it for my setup anyway! https://github.com/karlicoss/kompress/pull/5

authors: karlicoss seanbreckenridge

repo: karlicoss/kompress


text:
🛑 Habilitación is down

In 379382e, Habilitación (https://catalogo-vpfe-hab.dian.gov.co/User/Login) was down:

HTTP code: 500
Response time: 335 ms

Resolved: Habilitación is back up in b4db79e.


text:
Detect network name based on DAG info

Now, multiple networks are supported and detected based on the DAG info, closes #7.

Rebased for Kaspa explorer as well and created upstream PR: https://github.com/lAmeR1/kaspa-explorer/pull/47

repo: karlsen-network/karlsen-explorer


text:
Wwise 'mark for add' dialogue is causing Waapi-Transfer to hang

Wwise 'mark for add' dialogue is causing Waapi-Transfer import progress bar to hang until the window is cleared/ok'd in Wwise.

(using Wwise Perforce integration)

That is actually expected, fixed behavior.
Read this:
https://github.com/karltechno/Reaper-Waapi-Transfer/issues/6

authors: HarveyScottAudio nikolalkc

repo: karltechno/Reaper-Waapi-Transfer


text:
add Upgrading Instruction for v1.7 to v1.8

What type of PR is this?
/kind documentation
What this PR does / why we need it:
add Upgrading Instruction for v1.7 to v1.8
Which issue(s) this PR fixes:
Fixes #
Special notes for your reviewer:
CC @XiShanYongYe-Chang @jwcesign @zhzhuang-zju do you have any suggest to add into Upgrading Instruction

@chaosi-zju thanks for doing this~ could you please add a paragraph demonstrate for karmadactl, like Introduced --cluster flag to top command?

I don't think ``

@chaosi-zju thanks for doing this~ could you please add a paragraph demonstrate for karmadactl, like Introduced --cluster flag to top command?

I don't think this change should be present on upgrading the instruction doc.

the reason for CI failed, in my opinion, is a bug of Docusaurus.
I changed onBrokenLinks=warn, and I will submit a chinese version doc and change it back later.

CC @RainbowMango ready to merge

authors: RainbowMango chaosi-zju zhzhuang-zju

repo: karmada-io/website


text:
手机版谷歌浏览器玩不了啊，

哔…

请详细描述一下具体的问题

没法发球

mac Chrome 按方向键好像没用哦。

authors: cokebar gMan1990 gitelia kasuganosoras

repo: kasuganosoras/cxk-ball


text:
Add example of kata-sriov without plugin

Run kata container and sr-iov without usage of clearcontainer plugin. Adds more flexibility, because VF can be configured manually.
Tested with Mellanox connectx-4 NICs

/cc @eadamsintel @devimc

Hi. Thanks for the contribution! The CI is complaining as you did not sign off your commits - have a look at our contributing guidelines for information on how to format the pull requests etc. to keep the CI happy:
https://github.com/kata-containers/community/blob/master/CONTRIBUTING.md#pull-requests

I fixed the stuff mentioned in the comments, updated the rebinding to vfio-pci and squashed the two commits to get everything signed off.

Hi @HolyShitMan - Travis is failing with the following error:
ERROR: Commit cafea9b05733d38e4cb6dc17b29d6bafe49872f2: Failed to find subsystem in subject: "Add example of kata-sriov without plugin"
ERROR: checkcommits failed. See the document below for help on formatting
commits for the project.
https://github.com/kata-containers/community/blob/master/CONTRIBUTING.md#patch-format

The good news is that it's easy to fix: just prefix the first line of your commits with a "subsystem" which for this PR would be docs:  or maybe sriov:.
In fact, you have two commits, but I would squash these into one as we don't tend to worry about putting review changes into separate commits.

I really don't know why CI is still failing with
ERROR: No "Fixes" found

Do I have to mark the path as a "Supplementary patch" any way, which does not need a "Fixes: #xxxx" comment?

You need to have a Fixes: #nnn style line in at least one of your commits to note which Issue in github you are fixing. The requirement is detailed on the contributing docs.
If you have an Issue already open for this PR, add the relevant Fixes line to your commit. If not, please open an Issue detailing what you are fixing and why, and then reference that....
thanks ... nearly there I think!

If you have an Issue already open for this PR, add the relevant Fixes line to your commit. If not, please open an Issue detailing what you are fixing and why, and then reference that....

I wouldn't call it an issue that there was no second example, but whatever. If your CI needs it, it gets it.

I wouldn't call it an issue that there was no second example, but whatever 😄 . If your CI needs it, it gets it.

Thanks - yeah, 'Issue' is the github term :-) Everything is an 'Issue'. I know, the process can be a bit painful for small and doc updates, but overall it works well for the code base to ensure we have a good history of who changed what and why, and gives everybody a heads up normally on what issues folks are working on etc.

@HolyShitMan thx for the PR -- can you just add comment re: caps?

/test

Hi @HolyShitMan nice Github handle 😂

Hi @klynnrif - I think the PR's been updated so can you check and approve if you're happy?

Hi @HolyShitMan, can you address last comment?
Thanks.

Hi @HolyShitMan - please could you update for the final comment?

Ping @HolyShitMan ?

Looks like @HolyShitMan has mostly fallen off github ... one last shot - one tiny fix @HolyShitMan and you can get some github PR immortality .... :-)

Sry guys. I've really got no good excuse for this. I hope this is fine now.

/test-ubuntu

@grahamwhaley @jodh-intel PTAL

/test

Folks, this PR has been stale and I'm closing it as we're walking towards the final 1.13.0 release of the kata-containers-1.x.
From now on, all the development will happen as part of https://github.com/kata-containers/kata-containers/ and fixes should be provided to that repo.
Thanks a lot for your contribution, we're sorry that for some reason it got stale, and we hope to see you around for new adventures in the kata-containers-2.x land.

authors: HolyShitMan amshinde c3d chavafg egernst fidencio grahamwhaley jodh-intel raravena80

repo: kata-containers/documentation


text:
virtcontainers: support extra metadata storage backends

Currently we only have local file system based metadata backend. As required in the API design, we need to add a framework to support different metadata storage backends and support file system storage and leveldb storage backends.

closing the virtcontainers/store contains a backend interface

authors: bergwolf gabibeyer

repo: kata-containers/runtime


text:
「生成」設定を追加

「生成しました」「キャンセルしました」の設定を実装せよ。
「スマート解決」オプションを実装せよ。
「一定時間ごとに再試行する」オプションを実装せよ。
「再試行係数」の設定を実装せよ。

一部実装。

repo: katahiromz/XWordGiver


text:
Added isPlaying() method. Updated Readme to reflect new method.

Added method that returns true if currently playing, false otherwise. Was unsure of your particular PR requirements or if I needed to bump any version numbers or anything. Let me know if any changes are needed.

Coverage decreased (-0.01%) to 4.17% when pulling 3794f4ccdc2d5f12b8de5ea7ec185bebfecd2e29 on Tidal-Wave:master into 905b49caa25a82fa72a8999584bc74b086f25a8d on katspaugh:master.

Ah sure, I'm on the train atm but I'll make those changes.

Coverage decreased (-0.01%) to 4.17% when pulling 43c3f72cbb80ea723ab939469b242634c9f9ff00 on Tidal-Wave:master into 905b49caa25a82fa72a8999584bc74b086f25a8d on katspaugh:master.

Cool, thanks!

authors: Tidal-Wave coveralls katspaugh


text:
0.3.7.0

UIからの型作成時にジェネリックパラメータに与える型のフィルターを（少なくとも前よりも）正しく動くようにしました。
.NET 5 から .NET 6 に変更しました。

UIからの型作成時にジェネリックパラメータに与える型のフィルターを（少なくとも前よりも）正しく動くようにしました。
.NET 5 から .NET 6 に変更しました。

repo: katsumiar/CapyCSS


text:
Embedding HTML5 Player to Notification Menu

Hello Everyone, I'm trying something with this Plugin maybe it will actually work out. I have an Audio streaming Application which I will like to be working in background like a real music player i.e have PAUSE AND PLAY button in the notification Menu, Can someone suggest me how to go about it Please.

@Yusadolat You're looking for an audio/media plugin.

authors: Yusadolat katzer

repo: katzer/cordova-plugin-background-mode


text:
XLNet: ImportError: /opt/conda/lib/python3.6/site-packages/fused_layer_norm_cuda.cpython-36m-x86_64-linux-gnu.so: undefined symbol: _ZNK2at11ATenOpTable11reportErrorEN3c1012TensorTypeIdE

I am trying to use xlnet base but getting an error:
learner = BertLearner.from_pretrained_model(databunch, args.model_name, metrics=metrics,
device=device, logger=logger, output_dir=args.output_dir,
finetuned_wgts_path=None, warmup_steps=10,
multi_gpu=args.multi_gpu, is_fp16=True,
multi_label=True, logging_steps=0)
10/18/2019 00:36:04 - INFO - transformers.file_utils -   https://s3.amazonaws.com/models.huggingface.co/bert/xlnet-base-cased-config.json not found in cache or force_download set to True, downloading to /tmp/tmprecagwg5
100%|██████████| 641/641 [00:00<00:00, 177099.59B/s]
10/18/2019 00:36:04 - INFO - transformers.file_utils -   copying /tmp/tmprecagwg5 to cache at /root/.cache/torch/transformers/c9cc6e53904f7f3679a31ec4af244f4419e25ebc8e71ebf8c558a31cbcf07fc8.ef1824921bc0786e97dc88d55eb17aabf18aac90f24bd34c0650529e7ba27d6f
10/18/2019 00:36:04 - INFO - transformers.file_utils -   creating metadata file for /root/.cache/torch/transformers/c9cc6e53904f7f3679a31ec4af244f4419e25ebc8e71ebf8c558a31cbcf07fc8.ef1824921bc0786e97dc88d55eb17aabf18aac90f24bd34c0650529e7ba27d6f
10/18/2019 00:36:04 - INFO - transformers.file_utils -   removing temp file /tmp/tmprecagwg5
10/18/2019 00:36:04 - INFO - transformers.configuration_utils -   loading configuration file https://s3.amazonaws.com/models.huggingface.co/bert/xlnet-base-cased-config.json from cache at /root/.cache/torch/transformers/c9cc6e53904f7f3679a31ec4af244f4419e25ebc8e71ebf8c558a31cbcf07fc8.ef1824921bc0786e97dc88d55eb17aabf18aac90f24bd34c0650529e7ba27d6f
10/18/2019 00:36:04 - INFO - transformers.configuration_utils -   Model config {
"attn_type": "bi",
"bi_data": false,
"clamp_len": -1,
"d_head": 64,
"d_inner": 3072,
"d_model": 768,
"dropout": 0.1,
"end_n_top": 5,
"ff_activation": "gelu",
"finetuning_task": null,
"initializer_range": 0.02,
"layer_norm_eps": 1e-12,
"mem_len": null,
"n_head": 12,
"n_layer": 12,
"n_token": 32000,
"num_labels": 13,
"output_attentions": false,
"output_hidden_states": false,
"pruned_heads": {},
"reuse_len": null,
"same_length": false,
"start_n_top": 5,
"summary_activation": "tanh",
"summary_last_dropout": 0.1,
"summary_type": "last",
"summary_use_proj": true,
"torchscript": false,
"untie_r": true,
"use_bfloat16": false
}
10/18/2019 00:36:04 - INFO - transformers.file_utils -   https://s3.amazonaws.com/models.huggingface.co/bert/xlnet-base-cased-pytorch_model.bin not found in cache or force_download set to True, downloading to /tmp/tmpgq8bybxi
100%|██████████| 467042463/467042463 [00:35<00:00, 13098175.50B/s]
10/18/2019 00:36:40 - INFO - transformers.file_utils -   copying /tmp/tmpgq8bybxi to cache at /root/.cache/torch/transformers/24197ba0ce5dbfe23924431610704c88e2c0371afa49149360e4c823219ab474.7eac4fe898a021204e63c88c00ea68c60443c57f94b4bc3c02adbde6465745ac
10/18/2019 00:36:42 - INFO - transformers.file_utils -   creating metadata file for /root/.cache/torch/transformers/24197ba0ce5dbfe23924431610704c88e2c0371afa49149360e4c823219ab474.7eac4fe898a021204e63c88c00ea68c60443c57f94b4bc3c02adbde6465745ac
10/18/2019 00:36:42 - INFO - transformers.file_utils -   removing temp file /tmp/tmpgq8bybxi
10/18/2019 00:36:42 - INFO - transformers.modeling_utils -   loading weights file https://s3.amazonaws.com/models.huggingface.co/bert/xlnet-base-cased-pytorch_model.bin from cache at /root/.cache/torch/transformers/24197ba0ce5dbfe23924431610704c88e2c0371afa49149360e4c823219ab474.7eac4fe898a021204e63c88c00ea68c60443c57f94b4bc3c02adbde6465745ac
ImportError                               Traceback (most recent call last)
 in
3                                             finetuned_wgts_path=None, warmup_steps=10,
4                                             multi_gpu=args.multi_gpu, is_fp16=True,
----> 5                                             multi_label=True, logging_steps=0)
/opt/conda/lib/python3.6/site-packages/fast_bert/learner_cls.py in from_pretrained_model(dataBunch, pretrained_path, output_dir, metrics, device, logger, finetuned_wgts_path, multi_gpu, is_fp16, loss_scale, warmup_steps, fp16_opt_level, grad_accumulation_steps, multi_label, max_grad_norm, adam_epsilon, logging_steps)
67
68         if multi_label == True:
---> 69             model = model_class[1].from_pretrained(pretrained_path, config=config, state_dict=model_state_dict)
70         else:
71             model = model_class[0].from_pretrained(pretrained_path, config=config, state_dict=model_state_dict)
/opt/conda/lib/python3.6/site-packages/transformers/modeling_utils.py in from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
340
341         # Instantiate model.
--> 342         model = cls(config, *model_args, **model_kwargs)
343
344         if state_dict is None and not from_tf:
/opt/conda/lib/python3.6/site-packages/transformers/modeling_xlnet.py in init(self, config)
979         self.num_labels = config.num_labels
980
--> 981         self.transformer = XLNetModel(config)
982         self.sequence_summary = SequenceSummary(config)
983         self.logits_proj = nn.Linear(config.d_model, config.num_labels)
/opt/conda/lib/python3.6/site-packages/transformers/modeling_xlnet.py in init(self, config)
594         self.word_embedding = nn.Embedding(config.n_token, config.d_model)
595         self.mask_emb = nn.Parameter(torch.FloatTensor(1, 1, config.d_model))
--> 596         self.layer = nn.ModuleList([XLNetLayer(config) for _ in range(config.n_layer)])
597         self.dropout = nn.Dropout(config.dropout)
598
/opt/conda/lib/python3.6/site-packages/transformers/modeling_xlnet.py in (.0)
594         self.word_embedding = nn.Embedding(config.n_token, config.d_model)
595         self.mask_emb = nn.Parameter(torch.FloatTensor(1, 1, config.d_model))
--> 596         self.layer = nn.ModuleList([XLNetLayer(config) for _ in range(config.n_layer)])
597         self.dropout = nn.Dropout(config.dropout)
598
/opt/conda/lib/python3.6/site-packages/transformers/modeling_xlnet.py in init(self, config)
413     def init(self, config):
414         super(XLNetLayer, self).init()
--> 415         self.rel_attn = XLNetRelativeAttention(config)
416         self.ff = XLNetFeedForward(config)
417         self.dropout = nn.Dropout(config.dropout)
/opt/conda/lib/python3.6/site-packages/transformers/modeling_xlnet.py in init(self, config)
221         self.seg_embed = nn.Parameter(torch.FloatTensor(2, self.n_head, self.d_head))
222
--> 223         self.layer_norm = XLNetLayerNorm(config.d_model, eps=config.layer_norm_eps)
224         self.dropout = nn.Dropout(config.dropout)
225
/opt/conda/lib/python3.6/site-packages/apex/normalization/fused_layer_norm.py in init(self, normalized_shape, eps, elementwise_affine)
131
132         global fused_layer_norm_cuda
--> 133         fused_layer_norm_cuda = importlib.import_module("fused_layer_norm_cuda")
134
135         if isinstance(normalized_shape, numbers.Integral):
/opt/conda/lib/python3.6/importlib/init.py in import_module(name, package)
124                 break
125             level += 1
--> 126     return _bootstrap._gcd_import(name[level:], package, level)
127
128
/opt/conda/lib/python3.6/importlib/_bootstrap.py in _gcd_import(name, package, level)
/opt/conda/lib/python3.6/importlib/_bootstrap.py in find_and_load(name, import)
/opt/conda/lib/python3.6/importlib/_bootstrap.py in find_and_load_unlocked(name, import)
/opt/conda/lib/python3.6/importlib/_bootstrap.py in _load_unlocked(spec)
/opt/conda/lib/python3.6/importlib/_bootstrap.py in module_from_spec(spec)
/opt/conda/lib/python3.6/importlib/_bootstrap_external.py in create_module(self, spec)
/opt/conda/lib/python3.6/importlib/_bootstrap.py in _call_with_frames_removed(f, *args, **kwds)
ImportError: /opt/conda/lib/python3.6/site-packages/fused_layer_norm_cuda.cpython-36m-x86_64-linux-gnu.so: undefined symbol: _ZNK2at11ATenOpTable11reportErrorEN3c1012TensorTypeIdE
Here his parameter settings:
args = Box({
"train_size": -1,
"val_size": -1,
"log_path": LOG_PATH,
"full_data_dir": DATA_PATH,
"data_dir": DATA_PATH,
"no_cuda": False,
"bert_model": BERT_PRETRAINED_PATH,
"output_dir": OUTPUT_PATH,
"max_seq_length": 256,
"do_train": True,
"do_eval": False,
"multi_gpu":True,
"batch_size_per_gpu":4,
"model_type": 'xlnet',
"task_name": 'intent',
"model_name": 'xlnet-base-cased',
"num_train_epochs": 16,
"learning_rate": 5e-5
})
Have anyone got similar error?

ERROR - transformers.configuration_utils -   Model name 'roberta-base-uncased' was not found in model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc). We assumed 'roberta-base-uncased' was a path or url but couldn't find any file associated to this path or url.```

authors: DanyalAndriano mfaisal

repo: kaushaltrivedi/fast-bert


text:
Support deploying multiple indexers specialized for certain indexes

Some indexes will be more time sensitive than others.  We would like to be able to deploy indexers that are specialized.
Some examples....

narrative indexers - These may need to run very fast to support the dashboard
basic object indexers - These can run fast and may eventually be used in both the UI search and narrative search
AMA and genome indexers - (Really anything with features) These can take a long time.  They do need to run in a predictable period because viewers may depend on them, but they can't block some of the other things that could run more quickly.
sample indexers - These may be in this code base but they need to subscribe to a different Kafka stream.

I'm not sure of the implementation.  We could have a special launcher for each or we could manage it all with a config for each.  The later could be more flexible but we need to think through all the scenarios.
We also need to consider if one indexer is handling say the main object index (e.g. an AMA), and if there is a special feature indexer, it needs to be designed to not just check if the top level index record exists.  Basically the feature indexers need to have an independent way to tell if an object has been indexed.
With all of these we also need to consider how reindex events will be handled and what indexers would get poked.

:+1:

Here is what we currently have (all env vars)

SKIP_INDICES is a comma-delimited list of index names to blacklist. The document for the index will still get processed and created, just not saved to ES
ALLOW_INDICES is a comma-delimited list of indexes to whitelist. No other indexes will get saved. Same as above, the index document will still get processed and created, but not saved to elasticsearch.
SKIP_RELENG turns off any importing to arangodb. This prevents any Arango documents getting generated or processed at all.
SKIP_FEATURES turns off any genome feature indexing in both RE and Elasticsearch, and also prevents the features from getting processed and generated

We could add a TYPE_WHITELIST option -- list of workspace types to index, ignore everything else. This option could go against the object type given in the workspace event and prevent anything from happening unless the object type from the event is in the list.
For the sample stream, we could have something like:

TOPIC_HANDLERS mapping of topic name to handler name. In the code, we'd keep a mapping from string name to handler module (Workspace-to-ES, Relation Engine, Samples). So you could specify that you want to save workspace objects to Elasticsearch from topic A, and you want to save Sample objects to wherever from topic B

SKIP_TYPES and ALLOW_TYPES was implemented
Remaining thing to do is the TOPIC_HANDLERS option described above (or something similar)

Good enough.

authors: jayrbolton scanon


text:
Update README.md

Bundle supports now SF >= 4.4. Config should also be updated.

Thanks @napestershine

authors: kbond napestershine

repo: kbond/ZenstruckRedirectBundle


text:
Node mismatch with multiple m-if nodes

When m-if is used multiple times, the node in the data of m.emptyVNode changes and can lead to an inconsistency after hydration (when diffing).

I think this bug is still persist, i'm still pinpointing the problem so i can reproduce it in simple fiddle.

authors: kbrsh rizkyramadhan

repo: kbrsh/moon


text:
add e2e test

using cypress : https://docs.cypress.io/guides/getting-started/installing-cypress

[ ] nl2br
[ ] inlineStyle2ReactStyle
[ ] custom

see https://docs.cypress.io/guides/continuous-integration/introduction#What-is-Continuous-Integration
about opening cypress with starting server

[ ] how to use test id in cypress?

[ ] how to make start both dev server and cypress concurrently

[ ] how to make start-server-and-test use yarn ?

When I did
start-server-and-test dev:only http://localhost:3000/text-tools/ cy:open

cypress didn't open after dev server opened. Logs below.
yarn run v1.22.17
$ start-server-and-test dev:only http://localhost:3000/text-tools/ cy:open
1: starting server using command "npm run dev:only"
and when url "[ 'http://localhost:3000/text-tools/' ]" is responding with HTTP status code 200
running tests using command "npm run cy:open"

> text-tools@0.0.1 dev:only
> vite

  vite v2.8.4 dev server running at:

  > Local: http://localhost:3000/text-tools/
  > Network: use `--host` to expose

  ready in 555ms.

I assumes that it is because start-server-and-test tring to run cy:open with npm.

[ ] using start-server-and-test with dev server does not respond to HEAD request

See https://github.com/bahmutov/start-server-and-test#note-for-webpack-dev-server-users

use http-get:// prefix.
start-server-and-test 'yarn dev:only' http-get://localhost:3000/text-tools/ 'yarn cy:open'

it works

[ ] How to set cypress base url ?


text:
Uncaught TypeError: Cannot read property '$apply' of undefined

Open a Markdown Document

Atom Version: 1.8.0
System: Mac OS X 10.11.6
Thrown From: markdown-document package, v0.2.0
Stack Trace
Uncaught TypeError: Cannot read property '$apply' of undefined
At /Users/max/.atom/packages/markdown-document/lib/markdown-document-view.coffee:238

TypeError: Cannot read property '$apply' of undefined
    at MarkdownDocumentView.mdOutline (/Users/max/.atom/packages/markdown-document/lib/markdown-document-view.coffee:238:13)
    at /Users/max/.atom/packages/markdown-document/lib/markdown-document-view.coffee:84:9
    at tryToString (fs.js:414:3)
    at FSReqWrap.readFileAfterClose [as oncomplete] (fs.js:401:12)

Commands
     -3:15.5.0 editor:newline (atom-text-editor.editor.is-focused)
     -3:00.2.0 core:move-right (atom-text-editor.editor.is-focused)
     -2:59.4.0 editor:newline (atom-text-editor.editor.is-focused)
     -2:55.8.0 autocomplete-plus:confirm (atom-text-editor.editor.is-focused.autocomplete-active)
     -2:55.2.0 core:backspace (atom-text-editor.editor.is-focused)
     -2:52.6.0 core:save (atom-text-editor.editor.is-focused.autocomplete-active)
     -2:38.9.0 core:move-right (atom-text-editor.editor.is-focused)
     -2:38.7.0 editor:newline (atom-text-editor.editor.is-focused)
  3x -2:36.7.0 core:save (atom-text-editor.editor.is-focused)
  7x -2:19.2.0 markdown-preview:preview-file (atom-text-editor.editor)
  2x -1:02.4.0 markdown-document:toggle (atom-text-editor.editor.is-focused)
  2x -0:43.3.0 markdown-preview:toggle (atom-text-editor.editor.is-focused)
  5x -0:16.1.0 core:select-right (atom-text-editor.editor.is-focused)
     -0:15 core:backspace (atom-text-editor.editor.is-focused)
     -0:14.7.0 core:save (atom-text-editor.editor.is-focused)
  3x -0:11.8.0 markdown-preview:toggle (atom-text-editor.editor)

Config
{
  "core": {
    "audioBeep": false,
    "disabledPackages": [
      "haskell-ghc-mod",
      "haskell-pointfree",
      "ide-haskell",
      "autocomplete-haskell",
      "ide-haskell-cabal",
      "ide-haskell-repl",
      "language-haskell",
      "build-grunt",
      "grunt-runner",
      "browser-plus",
      "build",
      "build-gulp",
      "build-npm-apm"
    ],
    "themes": [
      "atom-material-ui",
      "atom-material-syntax"
    ]
  }
}

Installed Packages
# User
angularjs, v0.3.5
atom-beautify, v0.29.10
atom-material-syntax, v0.4.6
atom-material-ui, v1.3.3
atom-mocha, v0.0.6
atom-typescript, v10.1.5
bottom-dock, v0.4.4
busy, v0.6.0
docker, v0.7.0
file-icons, v1.7.17
flex-tool-bar, v0.10.2
gulp-manager, v0.2.19
highlight-selected, v0.11.2
jenkins, v0.3.5
linter, v1.11.14
linter-docker, v0.1.2
linter-eslint, v7.2.4
linter-jsonlint, v1.3.0
linter-manager, v0.2.12
linter-markdown, v1.5.2
linter-tslint, v0.10.0
markdown-document, v0.2.0
markdown-scroll-sync, v2.1.2
minimap, v4.24.7
minimap-bookmarks, v0.3.1
minimap-find-and-replace, v4.5.1
minimap-git-diff, v4.3.1
minimap-highlight-selected, v4.4.0
minimap-selection, v4.4.0
node-debugger, v1.7.0
project-manager, v2.9.7
rest-client, v1.2.0
terminal-plus, v0.14.5
todo-manager, v0.2.9
tool-bar, v1.0.0
tool-bar-main, v0.0.9
travis-ci-status, v1.1.1

# Dev
No dev packages

Do you experience the error when you don't use markdown-preview?

Fwiw I'm seeing this as well, when markdown-preview is enabled or disabled.

Atom 1.10.2
Mac OS 10.12

The same problem here :( I like the scrivener-idee and would like to use it - somehow.
Atom Version: 1.11.2
Electron Version: 0.37.8
System: Ubuntu 16.10
Thrown From: markdown-document package, v0.2.0
Stack Trace
Uncaught TypeError: Cannot read property '$apply' of undefined
At /home/marcel/.atom/packages/markdown-document/lib/markdown-document-view.coffee:300

TypeError: Cannot read property '$apply' of undefined
    at /home/marcel/.atom/packages/markdown-document/lib/markdown-document-view.coffee:300:21

Commands
     -3:41.5.0 core:confirm (atom-text-editor.path-input.editor.mini.is-focused)
     -3:35.7.0 advanced-open-file:move-cursor-down (atom-text-editor.path-input.editor.mini.is-focused)
     -3:35.3.0 core:confirm (atom-text-editor.path-input.editor.mini.is-focused)
     -3:30.5.0 advanced-open-file:autocomplete (atom-text-editor.path-input.editor.mini.is-focused)
     -3:29.1.0 core:confirm (atom-text-editor.path-input.editor.mini.is-focused)
     -2:32.4.0 advanced-open-file:toggle (atom-text-editor.editor.is-focused)
     -2:30.3.0 editor:consolidate-selections (atom-text-editor.path-input.editor.mini.is-focused)
     -2:30.3.0 core:cancel (atom-text-editor.path-input.editor.mini.is-focused)
     -1:03.8.0 markdown-document:toggle (atom-text-editor.editor.is-focused)
     -0:13.9.0 application:open-file (atom-text-editor.editor.is-focused)
     -0:12 fuzzy-finder:toggle-file-finder (atom-text-editor.editor.is-focused)
     -0:08.8.0 editor:consolidate-selections (atom-text-editor.editor.mini.is-focused)
     -0:08.8.0 core:cancel (atom-text-editor.editor.mini.is-focused)
     -0:07.2.0 application:open-folder (atom-text-editor.editor.is-focused)
     -0:04.4.0 settings-view:open (atom-text-editor.editor.is-focused)
     -0:01.3.0 core:close (div.package-detail.panels-item)

Config
{
  "core": {
    "destroyEmptyPanes": false,
    "disabledPackages": [
      "language-gfm",
      "print-atom",
      "export-html",
      "minimap-bookmarks",
      "markdown-folder"
    ],
    "packagesWithKeymapsDisabled": [
      "spell-check"
    ],
    "telemetryConsent": "limited",
    "themes": [
      "atom-material-ui",
      "one-light-syntax"
    ]
  }
}

Installed Packages
# User
activate-power-mode, v1.0.2 (active)
advanced-open-file, v0.16.4 (active)
atom-material-ui, v1.3.6 (active)
block-selection-mode, v0.3.0 (inactive)
export-html, v3.0.0 (inactive)
expose, v0.12.1 (inactive)
file-icons, v1.7.22 (active)
language-latex, v1.0.0 (active)
language-markdown, v0.17.0 (active)
m-a-w-syntax, v0.0.0 (inactive)
markdown-document, v0.2.0 (active)
markdown-folder, v0.5.0 (inactive)
markdown-scroll-sync, v2.1.2 (active)
markdown-table-formatter, v2.8.3 (active)
markdown-themeable-pdf, v1.2.0 (active)
markdown-writer, v2.6.1 (inactive)
minimal-syntax, v0.15.1 (inactive)
minimap, v4.25.5 (active)
minimap-autohide, v0.10.1 (active)
minimap-bookmarks, v0.4.2 (inactive)
minimap-cursorline, v0.2.0 (active)
minimap-find-and-replace, v4.5.1 (active)
minimap-hide, v0.3.0 (active)
minimap-selection, v4.4.0 (active)
minimap-titles, v1.8.1 (inactive)
one-o-eight-syntax, v0.23.2 (inactive)
pdf-view, v0.50.0 (active)
project-manager, v3.2.5 (active)
seti-ui, v1.3.2 (inactive)
terminal-plus, v0.14.5 (active)
todo-show, v1.7.0 (inactive)
wordcount, v2.7.0 (active)
Zen, v0.16.4 (active)
atom-dark-syntax, v0.27.0 (inactive)
atom-dark-ui, v0.52.0 (inactive)
atom-light-syntax, v0.28.0 (inactive)
atom-light-ui, v0.44.0 (inactive)
base16-tomorrow-dark-theme, v1.2.0 (inactive)
base16-tomorrow-light-theme, v1.2.0 (inactive)
one-dark-ui, v1.6.0 (inactive)
one-light-ui, v1.6.0 (inactive)
one-dark-syntax, v1.3.0 (inactive)
one-light-syntax, v1.3.0 (active)
solarized-dark-syntax, v1.0.2 (inactive)
solarized-light-syntax, v1.0.2 (inactive)
about, v1.7.0 (active)
archive-view, v0.61.1 (active)
autocomplete-atom-api, v0.10.0 (active)
autocomplete-css, v0.11.2 (active)
autocomplete-html, v0.7.2 (active)
autocomplete-plus, v2.31.1 (active)
autocomplete-snippets, v1.11.0 (active)
autoflow, v0.27.0 (inactive)
autosave, v0.23.1 (active)
background-tips, v0.26.1 (active)
bookmarks, v0.42.0 (active)
bracket-matcher, v0.82.1 (active)
command-palette, v0.38.0 (inactive)
deprecation-cop, v0.54.1 (active)
dev-live-reload, v0.47.0 (active)
encoding-selector, v0.22.0 (active)
exception-reporting, v0.40.0 (active)
find-and-replace, v0.201.1 (inactive)
fuzzy-finder, v1.4.0 (active)
git-diff, v1.1.0 (active)
go-to-line, v0.31.0 (inactive)
grammar-selector, v0.48.2 (active)
image-view, v0.59.0 (active)
incompatible-packages, v0.26.1 (active)
keybinding-resolver, v0.35.0 (active)
line-ending-selector, v0.5.0 (active)
link, v0.31.1 (inactive)
markdown-preview, v0.158.0 (active)
metrics, v1.0.0 (active)
notifications, v0.65.1 (active)
open-on-github, v1.2.0 (inactive)
package-generator, v1.0.0 (inactive)
settings-view, v0.242.2-hotfix1 (active)
snippets, v1.0.2 (active)
spell-check, v0.68.2 (active)
status-bar, v1.4.1 (active)
styleguide, v0.47.0 (active)
symbols-view, v0.113.1 (inactive)
tabs, v0.101.0 (active)
timecop, v0.33.2 (active)
tree-view, v0.209.3 (active)
update-package-dependencies, v0.10.0 (active)
welcome, v0.35.1 (active)
whitespace, v0.33.0 (active)
wrap-guide, v0.38.2 (active)
language-c, v0.52.1 (active)
language-clojure, v0.21.0 (active)
language-coffee-script, v0.47.2 (active)
language-csharp, v0.12.1 (active)
language-css, v0.37.1 (active)
language-gfm, v0.88.0 (inactive)
language-git, v0.15.0 (active)
language-go, v0.42.1 (active)
language-html, v0.45.1 (active)
language-hyperlink, v0.16.0 (active)
language-java, v0.23.0 (active)
language-javascript, v0.119.0 (active)
language-json, v0.18.2 (active)
language-less, v0.29.5 (active)
language-make, v0.22.2 (active)
language-mustache, v0.13.0 (active)
language-objective-c, v0.15.1 (active)
language-perl, v0.35.0 (active)
language-php, v0.37.2 (active)
language-property-list, v0.8.0 (active)
language-python, v0.45.0 (active)
language-ruby, v0.69.0 (active)
language-ruby-on-rails, v0.25.0 (active)
language-sass, v0.56.0 (active)
language-shellscript, v0.22.4 (active)
language-source, v0.9.0 (active)
language-sql, v0.23.0 (active)
language-text, v0.7.1 (active)
language-todo, v0.28.0 (active)
language-toml, v0.18.0 (active)
language-xml, v0.34.9 (active)
language-yaml, v0.26.0 (active)

# Dev
No dev packages

authors: MAWSpitau case kcyarn maxjoehnk

repo: kcyarn/markdown-document


text:
/**/ becomes // in code blocks

Input:
```lua
"some/**/glob*"
```

Output:
>lua
    "some//glob"
<

Expected:
>lua
    "some/**/glob*"
<

I think it might be a bug upstream in pandoc, if you add print(line) at panvimdoc.lua#402, the actual printed line is missing the ** characters.

It also effects
"fnl/**/*-test.fnl"

which becomes
"fnl/**/-test.fnl"

This actually appears to be a problem with demojify.lua:
$ ./panvimdoc.sh --project-name test --input-file test.md --demojify false && cat doc/test.txt
pandoc --citeproc --shift-heading-level-by=0 --metadata=project:test --metadata=vimversion: --metadata=toc:true --metadata=description: --metadata=dedupsubheadings:true --metadata=ignorerawblocks:true --metadata=docmapping:false --metadata=docmappingproject:true --metadata=treesitter:true --metadata=incrementheadinglevelby:0 --lua-filter=/Users/kd/gitrepos/panvimdoc/scripts/include-files.lua --lua-filter=/Users/kd/gitrepos/panvimdoc/scripts/skip-blocks.lua -t /Users/kd/gitrepos/panvimdoc/scripts/panvimdoc.lua test.md -o doc/test.txt
───────┬───────────────────────────────────────────────────────────────────────────────────────────────────
       │ File: doc/test.txt
───────┼───────────────────────────────────────────────────────────────────────────────────────────────────
   1   │ *test.txt*                 For                  Last change: 2023 September 17
   2   │
   3   │ ==============================================================================
   4   │ Table of Contents                                     *test-table-of-contents*
   5   │
   6   │ >lua
   7   │     "some/**/glob*"
   8   │ <
   9   │
  10   │ Generated by panvimdoc <https://github.com/kdheepak/panvimdoc>
  11   │
  12   │ vim:tw=78:ts=8:noet:ft=help:norl:
───────┴───────────────────────────────────────────────────────────────────────────────────────────────────

authors: kdheepak rktjmp

repo: kdheepak/panvimdoc


text:
phantomjs path should be configurable

We are working around it for now by setting PATH explicitly, but it'd be nicer/easier if it were just configurable.

This should be fixed in on master. I'll push a new release out once the fix for #74 has been merged.
Let me know if you have any issues.

authors: aaronjensen keathley

repo: keathley/wallaby


text:
don't put hash sign(#) to url for encrypted query params

having api specified as:
"api": {
      "baseUrl": "foo.com",
      "authentication": {
        "type": "query",
        "query": {
          "#access_token": "KBC:encrypted(xxx)"
        }
      }
}

the extractor will construct and call url foo.com?%23access_token=xxx but url should be foo.com?access_token=xxx

how about referencing it,
{
    "parameters": {
        "api": {
            "baseUrl": "foo.com",
            "authentication": {
                "type": "query",
                "query": {
                    "access_token": {
                        "attr": "#access_token"
                    }
                }
            }
        },
        "config": {
            "#access_token": "KBC::Encrypted=="
        }
    }
}

i think this approach might be better, as it separates params and actual api configuration. better for templating too.

@ondrejhlavacek thanks this approach worked! seems I am not very well aware of ex generic
potential :)

authors: kacurez ondrejhlavacek

repo: keboola/generic-extractor


text:
Show More List tuning

Zatim to tu odkladam, aby to nevysumelo.
Pamatuju si ze kolem toho probehla trocha diskuze https://github.com/keboola/indigo-ui/issues/169
Se soucasnym stavam nejsem uplne OK.

myslim ze by ta komponenta mela bejt vic 'blackbox'. Predhodis ji seznam a pocet viditelnych polozek v seznamu. Tak jak je to v demo Storybooku tad, tak mi pripada ze je tam velkej prostor pro chyby.
Dal si mysim ze ve Story je zbytecne inline styl. Kdyz k tomu prijde developre, tak nebude vedet, jestli to ma zkopcit s inline styly nebo ne. Ja naopak chci videt, ze komponenta je blokova a vyplni celou sirku kontejneru. Inline styly jsme zatim v zadnym demu nepouzili.
@ujovlado  o konkretni implementaci se pojdme pobavit https://github.com/keboola/indigo-ui/issues/169

Ak chces aby to bolo viac blackbox, tak ta komponenta myslim nebude moct prijimat children ako react komponenty ale namiesto toho nejake pole objektov cez props. Cez to pole by potom preiterovala a vyrenderovala to na 2 casti.
Ten inline style tam je preto aby to “simulovalo” ten list tak ako bol v detaile jobu. Ak je to matuce, kludne ho vyhod.

Viem si predstavit nieco taketo:
const items = [
  {
     "tableId": "in.c-keboola-ex-email-attachments-413120386.data",
     "seconds": 8
  },
  ...
]

const renderItemComponent = (item) => {
   return (
      {item.tableId}{item.seconds} seconds
   );
}

a potom:
<ExpandableList items={items} ItemComponent={renderItemComponent} visibleItems="3" />

Pricom by sa to interne postaralo o to aby to vyrenderovalo len 3 polozky a zvysne cez "Read more".
Mozeme sa este spytat @kacurez, co si o tom mysli.
Idealne by ale bolo skusit pripravit nejake POC a tam uvidis, ci ti navrhovana implementacia vyhovuje alebo nie a doladime to.

tiez ma napadlo tak ako to pise Vlado(ExpandableList). Uz sa nejedna o komponentu ktora rendruje(skryva/zobrazuje) any content ale o komponentu ktora rendruje pole komponent s default visible limitom. Potom je to cistejsie na implemntaciu kde sa vzdy vyrendruje jedno ul s nejakymi li podtym(+ jedno li na "show details"). Keby to malo byt zahrnute pod PanelWithDetails tak z toho imho vznikne grey box :)

authors: janmichek kacurez ujovlado

repo: keboola/indigo-ui


text:
Add AssignmentInCondition check

https://github.com/slevomat/coding-standard/tree/608b4b9b38c2a13b7941397bda257db3f08b4380#slevomatcodingstandardcontrolstructuresassignmentincondition
https://github.com/keboola/connection/pull/1488#discussion_r209968073

https://keboola.slack.com/archives/C9FEAHW7N/p1534259626000100
co toto?
if (($value = getValue()) !== null) {
  // do something with $value
}

asi nejde.  tam maji jen Assignment in while loop condition is specifically allowed because it's commonly used.

yep, so this will be allowed:
while (($value = getValue()) !== null) {
  // do something with $value
}

and this not:
if (($value = getValue()) !== null) {
  // do something with $value
}

what a mess ...

mess would be rewriting the while without assignment

Změna byla přijata. Otestuju a mergnu.

authors: Halama odinuv pivnicek tomasfejfar ujovlado

repo: keboola/phpcs-standard


text:
fix: add linux node selector to deployments

When KEDA is deployed to a mixed Kubernetes cluster with linux and windows nodes, the deployments did not select the linux nodes explicitly and could not be started on windows nodes.
Checklist

[x] I have verified that my change is according to the deprecations & breaking changes policy
[x] Commits are signed with Developer Certificate of Origin (DCO - learn more)
[-] README is updated with new configuration values (if applicable) learn more
[-] A PR is opened to update KEDA core (repo) (if applicable, ie. when deployment manifests are modified)

Hi
Have you faced with KEDA or with the HTTP Add-on chart? KEDA chart already has the node selector

We are cutting a release of the HTTP add-on right now, so I have just included the missing node selector within
https://github.com/kedacore/charts/pull/543

Hi,I actually added it to both, but maybe I missed something in keda core.Thanks for adding it to the html-add-on release!Philipp Am 2023. 10. 05. um 15:02 schrieb Jorge Turrado Ferrero @.***>:
Hi
Have you faced with KEDA or with the HTTP Add-on chart? KEDA chart already has the node selector
—Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you authored the thread.Message ID: @.***>

I close this as I have included your changes in that PR in progress (it's faster than fix your PR, merge it and update the other). Thanks for the PR in any case

authors: JorTurFer pzerelles

repo: kedacore/charts


text:
Rabbitmq Add create queue and binding routing

This a new option for the rabbitMQ scaler.
It will create the queue that the scaler is monitoring.
This is very useful for jobscaler. Since rabbitmq has a strong philosophy that code should just generate their queues and bindings topics.
It is a chicken/egg situation. The application (job) needs to be run for the queue to be created and the job will be only run if there is a message in the queue.
Like this, the scaler is creating the queue and proper bindings for the proper exchange.
Documentation: #620
Checklist

[ x]Commits are signed with Developer Certificate of Origin (DCO - learn more)
[ x] Tests have been added
[ ] A PR is opened to update our Helm chart (repo) (if applicable, ie. when deployment manifests are modified)
[ ]x A PR is opened to update the documentation on (repo) (if applicable)
[ ] Changelog has been updated

Fixes #

-1 for this. Use an operator to create the queue.

Hi,
In this case, I agree @coderanger and @tomkerkhove. KEDA doesn't manage the resources, and opening this door, we could manage a lot of resources, losing the focus of KEDA.
I understand your point and your requirement about queue creation, but maybe the publisher could create the queue and your workload(ScaledJob) could be only a receiver. In that case you don't need to create the queue using KEDA because is the publisher who creates the queue

I agree with others on this one. I hope you understand @pascallap

I do understand.
I will do a simple post-install helm hook, to run once the job declared in the scaler.
This will cover the initial installation.
I will that a look at the existing operators for queue (and configurations) creation.
@JorTurFer the publisher shouldn't know the existence of the consumer. So, what you are proposing wouldn't be a valid solution.

@pascallap This is exactly the use case I wrote mine for btw, https://github.com/coderanger/rabbitmq-operator

authors: JorTurFer coderanger pascallap zroubalik

repo: kedacore/keda


text:
Telemetry breaks everything if there's no write permissions

Description
As seen on databricks repos, which currently do not have write access, running any kedro command in a directory with no write access will raise an error with kedro-telemetry which then stops kedro from running everything.
This isn't the first time that an exception raised by kedro-telemetry has stopped kedro commands from working rather than just raising a warning and carrying on. I wonder if we should wrap the whole plugin in a try/except to catch any exceptions we don't anticipate. A broken kedro-telemetry shouldn't prevent users from using kedro.
Steps to reproduce

Go to https://gitpod.io/#https://github.com/kedro-org/kedro
pip install kedro-telemetry
chmod a=rx /workspace/project
kedro info

This will give the following exception and not execute the kedro command at all:
PermissionError: [Errno 13] Permission denied: '/workspace/project/.telemetry'

"A broken kedro-telemetry shouldn't prevent users from using kedro." -> No error in kedro-telemetry should prevent a user from running Kedro, so as part of this fix ensure that other errors won't break Kedro either.

authors: AntonyMilneQB MerelTheisenQB

repo: kedro-org/kedro-plugins


text:
Lattice further UX improvements

Added new rotate and scale tools
Added marquee select for control points
Improved UX around entering and exiting control point editing
Auto Size now works with LOD Groups, also now zeroes rotation to prevent a mismatch if lattice is rotated before hitting the button
Limited selection undo support (only works will the same editor is active)

Awesome!
Only thing I noticed is auto-fit not working with scaled or rotated deformables in an LOD Group

Looks like changing this
if (deformable != null)
{
    var bounds = deformable.GetCurrentMesh().bounds;
    transform.localPosition = bounds.center;
    transform.localScale = bounds.size;
    // Make sure the rotation is zeroed so that we're not applying the size is the wrong axis
    transform.localRotation = Quaternion.identity;
}

Perhaps there's a better solution for calculating scale, but this seems to works for me
if (deformable != null)
{
    var bounds = deformable.GetCurrentMesh().bounds;
    var rendererTransform = deformable.GetRenderer().transform;
    transform.localPosition = bounds.center;
    transform.localScale = Vector3.Scale(bounds.size, rendererTransform.lossyScale);
    transform.localRotation = rendererTransform.rotation;
}

Thanks, fix applied

authors: keenanwoodall sabresaurus

repo: keenanwoodall/Deform


text:
Concurrent execution of the event handlers

In this PR we allow concurrent execution of event handlers for a given subscription. Currently, when a new event comes it blocks the execution of handlers for any subsequent events.

I am not sure about this change but would love to hear your arguments and opinion of @Shadowfiend.
I think it makes sense to do not trigger chain event handlers asynchronously. Chain processes transactions one after another and I can imagine we (or anyone else using this library) may want to process events in order as they appeared on-chain.
Although, in my opinion, we shouldn't fire goroutines for event handler in the code of generated contracts I do recognize the problem and I think we should fire those goroutines inside the callback function, just like we do in keep-core. One example here, another example here.
Basically, the client code should decide if it cares about the order of events or not and trigger time-consuming handlers asynchronously if that's needed.

After pushing this PR I had similar second thoughts. The longer I test the client the more I doubt we need this.

It's perfectly fine to fire callbacks in goroutines if needed, I just don't think we should do it by default. Do we want to close this PR without merging?

authors: nkuba pdyraga

repo: keep-network/keep-common


text:
2023-01-13 testnet release

As a preparation for a new mainnet release, we need to conduct an internal testnet release of the client.
Checklist:
2023-01-13

[ ] Deploy random-beacon, ecdsa, tbtc-v2 contracts on Goerli
[ ] Modify governance parameters to allow for executing DKG multiple time a day (@lukasz-zimnoch / @tomaszslabon)
[ ] Build & publish a new client image to internal repository.
[ ] Update Keep GCP testnet clients.
[ ] Update documentation of contract addresses: https://docs.threshold.network/extras/contract-addresses/goerli-testnet
[ ] Update Coda deployment documentation: https://coda.io/d/Building-Keep_d-fmEgBNFVH/Deploy-on-Goerli-checklist_suc3g#_luy45
[ ] Monitor testnet logs, report all problems.

2023-01-16 (?)

[ ] Update bundles for Staking Providers (@nkuba)
[ ] Publish new client image to public testnet client build repository (@nkuba)
[ ] P2P.org testnet clients updated
[ ] Staked testnet clients updated (?)
[ ] Boar.network testnet clients updated
[ ] Vict0r notified about the need for a client upgrade

@michalinacienciala We have #3401 as a v2.0.0-m2 all-testnet releases bag, I've moved these points to that PR. I have also marked staking provider updates as nice-to-haves - but not must-haves for the user acceptance criteria tests to start. We should start as soon as possible, let's not block on their updates. Closing in favor or #3401.

authors: michalinacienciala pdyraga

repo: keep-network/keep-core


text:
Introduce a supply cap manager

Adds an additional capManager role to TBTCSystem to determine whether the current VendingMachine supply restriction can be increased to the next graduated cap.
Opening as a draft to get on the same page about the approach. I'm also not sure how we're testing role-based auth- advice welcome.

I played around with making the VendingMachine ownable, but this felt slightly less dirty..
In practice, we'd set this to a multisig at initialization so outside parties can decide on moving the supply schedule forward.

Couple of things...
First, lol at the commit summary “add supply cap manager”. That’s an incidental part of what that commit does.
Second, why make this a separate role instead of using the system owner? Including that info in the commit would also be useful.

First, lol at the commit summary “add supply cap manager”. That’s an incidental part of what that commit does.

So salty!

Opening as a draft to get on the same page about the approach. I'm also not sure how we're testing role-based auth- advice welcome.

I'd planned to force-push wreck this branch, just wanted thoughts on the mechanism, how to better expose role-based testing in the suite, etc.
I'm having second (and third and fourth) thoughts on the idea at all, though.

Meh, not feeling this. No reason to pre-program a cap curve and allow a committee to override it. We should address the feedback of the curve being too restrictive head-on, either by increasing the caps before deploy or shortening the schedule (my preference).

authors: Shadowfiend mhluongo

repo: keep-network/tbtc


text:
ci: add hurl output to summary

Pull Request type
Please check the type of change your PR introduces:

[ ] Bugfix
[ ] Feature
[ ] Code style update (formatting, renaming)
[ ] Refactoring (no functional changes, no API changes)
[ ] Build-related changes
[ ] Documentation content changes
[x] Testing
[ ] Other (please describe):

What is the current behavior?
Beerus end-to-end test script does not output the test output, only which files have succeeded or failed
Issue Number: #476
What is the new behavior?
The hurl output of each file has been added to the bottom of the summary, allowing easier debugging, see why some endpoints failed and check that passing endpoints have the expected output.
Does this introduce a breaking change?

[ ] Yes
[x] No

Other information
The summary could be further improved. As of now it displays the hurl output as very-verbose, which is the only mode that displays the request response. We are reaching the limit of hurl + bash here, if we want a cleaner output, we need to either process the hurl output with a more advanced language, or change hurl to a tool that provides more options.
However if this output is satisfying we can keep it as is.

summary.md
example summary.md produceed (this is what is displayed in the CI job output)

repo: keep-starknet-strange/beerus


text:
Pending Stalls and multiple concurrent users

Yeah, there's something skewiff with pending stalls and having multiple folks approving at once. It's never been an issue before with smaller elections and fewer volunteers and is on my list to fix.
If you get that just pop your details in the form and send feedback in. That'll log all of the details I need to go and fix it.
Then just reload the pending stalls page and try again.
AB#87

Closing and merging into https://github.com/keithamoss/demsausage/issues/1340

repo: keithamoss/demsausage


text:
UPDATE nodemon dependency + ignore the /node_modules folder

See https://github.com/keithamus/npm-scripts-example/issues/7

@francoismassart this LGTM. Feel free to hit the merge button if you're happy with it 😃

You might want to rebase this - looking at the other PRs you've merged

I messed up this branch, re-doing it

authors: francoismassart keithamus

repo: keithamus/npm-scripts-example


text:
Support VSCode Manifest?

ref: https://code.visualstudio.com/api/references/extension-manifest

Seems simple enough to add the additional keys. 👍 from me

:tada: This issue has been resolved in version 1.37.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:

authors: fisker keithamus

repo: keithamus/sort-package-json


text:
HentaiRead "Stop This image was hotlinked" issue

Source information
HentaiRead 1.4.41
Source language
English
Steps to reproduce

Press any Manga that has the HentaiRead extension can be in the Extension Browser or own Saved Catalog (except downloaded)
Choose any chapter of the Manga/Doujin to read

Expected behavior
Would be able to read said Chapter or Manga
Actual behavior
Accessable but "Stop This image was hotlinked" in both the Saved Catalog and on the Extension search appears.

Mihon/Tachiyomi version
Mihon 0.15.3 and used others like Tachiyomi [OG], Tachiyomi Sy and etc. for cross reference
Android version
Android 10
Other details

Accessed it yesterday it was fine.
I have accessed it via both the site and Webview both are accesible and its extension can be saved viewed and read like a normal chapter but images are all replaced by"Stop This image was hotlinked"

Acknowledgements

[X] I have searched the existing issues and this is a new ticket, NOT a duplicate or related to another open or closed issue.
[X] I have written a short but informative title.
[X] I have updated the app to version 0.15.3.
[X] I have updated all installed extensions.
[X] I have tried the troubleshooting guide.
[X] If this is an issue with the app itself, I should be opening an issue in the app repository.
[X] I will fill out all of the requested information in this form.

Got that randomly on covers too. Its because the CDN dont like having a referrer for fetching images. Make the request looks like its a browser fetching an  tag 😉 .

Got that randomly on covers too. Its because the CDN dont like having a referrer for fetching images. Make the request looks like its a browser fetching an  tag 😉 .

So is it a bug or can it be bypassed or what? Im genuinely curious on what actually caused that suddenly

repo: keiyoushi/extensions-source


text:
kemono.su is broken!

Source information
kemono 1.4.14
Source language
multi
Steps to reproduce
click on any chapter
also try opening webview
Expected behavior
gives the chapter of what i clicked one
Actual behavior
clicking on any chapter gives me
open failed: ENOENT ( no such file or directory)
or something else that too long
also, webView doesn't work
Mihon/Tachiyomi version
0.17.0
Android version
im not sure
Other details
i suck at this but i think you understand me. right?
Acknowledgements

[X] I have searched the existing issues and this is a new ticket, NOT a duplicate or related to another open or closed issue.
[X] I have written a short but informative title.
[X] I have updated the app to version 0.15.3.
[X] I have updated all installed extensions.
[X] I have tried the troubleshooting guide.
[X] If this is an issue with the app itself, I should be opening an issue in the app repository.
[X] I will fill out all of the requested information in this form.

The site itself is working.

ENOENT is a personal issue of putting your app's folder in an unreachable spot. Go check with app support for help/more details.
As for the actual error/issue:

any fix?

@Smol-Ame sorry my bad. it's my first time commenting on github so i don't understand it that much

gary25566 over on discord made a great point:
"sometimes whenever going to webview, Kemono sidebar seems to be blocking the extension from viewing images. But when the webview does not show the sidebar, means the images can be viewed."
After I tested it, yes the sidebar does indeed automatically open whenever going to the webview
Note: changing the user agent string to a desktop one does not fix the problem

https://kemono.su/documentation/api
This would probably be useful 🤔

The Fields thing error is still there, I'm using Yōkai Nightly
Artist page on Kemono: dojiro
Chapter: お金を払うと童貞をもらってくれる義理の妹【#有料少女】【6P漫画・高画質版】

@lalalasupa0 You should make new issues for better visibilities. (I also have the same problem with some selected entry)

Commenting unnecessarily sends an email to everyone involved in the issue & pings the server channel.

Do you know if that's not the case if an issue is closed? Maybe it's not necessary


text:
Snow Machine Translations Graphics issue

Source name
Snow Machine translations
Source language
English
Source link
https://snowmtl.ru
Other details

Acknowledgements

[X] I have updated all installed extensions.
[X] I have opened WebView and checked that the source website is down.
[X] I have searched the existing issues and this is a new ticket, NOT a duplicate or related to another open or closed issue.
[X] I have written a meaningful title with the source name.
[X] I will fill out all of the requested information in this form.

Add a :+1: reaction to issues you find important.

I think the "source is down" label is meant for website that doesnt respond, its invalid here, perhaps you should remove it?

Site was down when the issue was made (I checked during then), seems like it's back up & I don't see any apparent issues currently. Closing as non-issue

authors: Deep-web08 MikeZeDev Smol-Ame


text:
Consider use of database enumerations

Enumerations are a way of enforcing that only certain values get into the database. Attempting to add one that isn't listed would give an error. Here are two that we could consider:
class Regime(enum.Enum):
    """Enumeration for spectral type regime"""
    optical = 'optical'
    infrared = 'infrared'
    ultraviolet = 'ultraviolet'
    radio = 'radio'

class Gravity(enum.Enum):
    """Enumeration for gravity"""
    a = 'alpha'
    b = 'beta'
    g = 'gamma'
    bg = 'beta/gamma'
    unknown = 'unknown'

We would have to test this functionality with Astrodbkit2 before we commit to it.

Recommend close @dr-rodriguez

authors: Will-Cooper dr-rodriguez

repo: kelle/SIMPLE


text:
Make sure active file view is updated

When switching between branches or pulling new updates, the active file view is not updated until you switch between windows.
I made the general_done function open a scratch window instead just to force the view update. Might be a better way to do this but I haven't found it.

I don't know if this is the right solution, but I'd love for someone to fix this problem :o) It recently cost me a lot of wasted work, that it behaves unexpectedly.

I'm not sure either. But it's the only solution we've found this far ;) tired of loosing too much work.
Best
Patrik Ring
On 6 jan 2012, at 10:23, Tom Vonsildreply@reply.github.com wrote:

I don't know if this is the right solution, but I'd love for someone to fix this problem :o) It recently cost me a lot of wasted work, that it behaves unexpectedly.

Reply to this email directly or view it on GitHub:
https://github.com/kemayo/sublime-text-2-git/pull/53#issuecomment-3382433

ab3a587 is a bit circuitous, but I think it also works to fix this without requiring the new window.

authors: Vonsild kemayo ptte


text:
🛑 bigdata is down

In 1d36108, bigdata (https://bigdata.ministep.cn/) was down:

HTTP code: 0
Response time: 0 ms

Resolved: bigdata is back up in ed45a36 after 12 minutes.

repo: kemistep/upptime


text:
Pastebin4J is not present in the repository

Hi,
The pastebin4J lib isn't present in the repo, so when cloning it, it creates broken paths and the plugin can't be built.
Could you add your lib folder in the repository or provide a way to get it easily?
Sincerely,

Hi @Kendos-Kenlen,
very weird, IntelliJ should download it automatically, since it's available in maven central, anyway, pastebin4j is another project mine, you can checkout it here pastebin4j.

authors: Kendos-Kenlen kennedyoliveira


text:
RecursionError: maximum recursion depth exceeded while calling a Python object

pics show one solution.

please provide steps to reproduce

fixed in master
{'http://www.1993s.top/detail/?1165.html', 'http://www.1993s.top/detail/?1168.html', 'http://www.1993s.top/detail/?1169.html', 'http://www.1993s.top/list/?1.html', 'http://www.1993s.top/detail/?1166.html', 'http://www.1993s.top/detail/?1164.html', 'http://www.1993s.top/detail/?1163.html', 'http://www.1993s.top/detail/?1171.html', 'http://www.1993s.top/detail/?1172.html', 'http://www.1993s.top/detail/?1170.html', 'http://www.1993s.top/detail/?1167.html'}

authors: chengtian5huang kennethreitz msterzhang

repo: kennethreitz/requests-html


text:
Copy a PreparedRequest's CookieJar reliably

When a PreparedRequests's cookie jar is not a RequestsCookieJar instance, it
will not have a "copy" method. By adding _copy_cookie_jar we can reliably copy
cookie jars so that we have an actual copy instead of the same instance on
different prepared requests.
This also updates the RequestsCookieJar.update logic to create copies of
cookies from the other jar.
Closes #2527

LGTM. :cake:

repo: kennethreitz/requests


text:
Atom.Object.defineProperty.get is deprecated.

atom.workspaceView is no longer available.
In most cases you will not need the view. See the Workspace docs for
alternatives: https://atom.io/docs/api/latest/Workspace.
If you do need the view, please use atom.views.getView(atom.workspace),
which returns an HTMLElement.
Atom.Object.defineProperty.get (/Applications/Atom.app/Contents/Resources/app/src/atom.js:54:11)
Object.activate (/Users/vsanner/.atom/packages/markdown-stream/lib/markdown-stream.js:39:9)

was handled by issue #12.

repo: kenokabe/markdown-stream


text:
Added skeleton layouts

HolyGrail layout for index.html
Starting Landing Page for login/ signup etc
Added logos and images

Looks Good! :shipit:

authors: LadyAudrey kensonjohnson

repo: kensonjohnson/carpooly


text:
Device stop forwarding the docker container logs periodically

I am TSE at Newrelic
Raising the issue on behalf of the customer
Issue in their own words
We have the Meraki polling engine stop forwarding the docker container logs periodically. It happens every 6-7 days for the EU & US polling engines mainly. This impact directly on device monitoring which is crucial to us.
Below container log chart link clearly shows the gap in log forwarding
NRQL used to test
FROM Metric
SELECT
average(kentik.ktranslate.chf.kkc.delivery_logs_nr) AS 'delivery_logs_nr'
FACET host, svc
WHERE instrumentation.provider = 'kentik'
AND instrumentation.name = 'heartbeat' AND svc ='vma3gspx004_us_snmp' SINCE 4 weeks ago
**Customer is getting below log in EU container which stops sending logs to NR **
panic: runtime error: invalid memory address or nil pointer dereference
[signal SIGSEGV: segmentation violation code=0x1 addr=0x18 pc=0x13fe04b]
goroutine 2884 [running]:
github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*DeviceMetrics).pollFromConfig(0xc00c02b920, {0x2251600, 0xc004f96000}, 0xc00abfda20?, 0x0?)
    /src/pkg/inputs/snmp/metrics/device_metrics.go:147 +0xcab

github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*DeviceMetrics).Poll(...)
    /src/pkg/inputs/snmp/metrics/device_metrics.go:81

github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*Poller).Poll(0xc00c02b8c0, {0x2251600, 0xc004f96000})
    /src/pkg/inputs/snmp/metrics/poll.go:244 +0x52

github.com/kentik/ktranslate/pkg/inputs/snmp.launchSnmp.func1()
    /src/pkg/inputs/snmp/snmp.go:307 +0x5c

created by github.com/kentik/ktranslate/pkg/inputs/snmp.launchSnmp
    /src/pkg/inputs/snmp/snmp.go:300 +0x4ac

panic: runtime error: invalid memory address or nil pointer dereference
[signal SIGSEGV: segmentation violation code=0x1 addr=0x18 pc=0x13fe04b]
goroutine 9085 [running]:
github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*DeviceMetrics).pollFromConfig(0xc00ef6b140, {0x2251600, 0xc00225d100}, 0xc0095b86e0?, 0x0?)
    /src/pkg/inputs/snmp/metrics/device_metrics.go:147 +0xcab

github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*DeviceMetrics).Poll(...)
    /src/pkg/inputs/snmp/metrics/device_metrics.go:81

github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*Poller).Poll(0xc00ef6b0e0, {0x2251600, 0xc00225d100})
    /src/pkg/inputs/snmp/metrics/poll.go:244 +0x52

github.com/kentik/ktranslate/pkg/inputs/snmp.launchSnmp.func1()
    /src/pkg/inputs/snmp/snmp.go:307 +0x5c

created by github.com/kentik/ktranslate/pkg/inputs/snmp.launchSnmp
    /src/pkg/inputs/snmp/snmp.go:300 +0x4ac

panic: runtime error: invalid memory address or nil pointer dereference
[signal SIGSEGV: segmentation violation code=0x1 addr=0x18 pc=0x13fe04b]
goroutine 3302 [running]:
github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*DeviceMetrics).pollFromConfig(0xc00d8d1920, {0x2251600, 0xc001d80000}, 0xc00da391e0?, 0x0?)
    /src/pkg/inputs/snmp/metrics/device_metrics.go:147 +0xcab

github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*DeviceMetrics).Poll(...)
    /src/pkg/inputs/snmp/metrics/device_metrics.go:81

github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*Poller).Poll(0xc00d8d18c0, {0x2251600, 0xc001d80000})
    /src/pkg/inputs/snmp/metrics/poll.go:244 +0x52

github.com/kentik/ktranslate/pkg/inputs/snmp.launchSnmp.func1()
    /src/pkg/inputs/snmp/snmp.go:307 +0x5c

created by github.com/kentik/ktranslate/pkg/inputs/snmp.launchSnmp
    /src/pkg/inputs/snmp/snmp.go:300 +0x4ac

panic: runtime error: invalid memory address or nil pointer dereference
[signal SIGSEGV: segmentation violation code=0x1 addr=0x18 pc=0x13fe04b]
goroutine 328 [running]:
github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*DeviceMetrics).pollFromConfig(0xc0037db1a0, {0x2251600, 0xc002c40000}, 0xc0038aab00?, 0x0?)
    /src/pkg/inputs/snmp/metrics/device_metrics.go:147 +0xcab

github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*DeviceMetrics).Poll(...)
    /src/pkg/inputs/snmp/metrics/device_metrics.go:81

github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*Poller).Poll(0xc0037db140, {0x2251600, 0xc002c40000})
    /src/pkg/inputs/snmp/metrics/poll.go:244 +0x52

github.com/kentik/ktranslate/pkg/inputs/snmp.launchSnmp.func1()
    /src/pkg/inputs/snmp/snmp.go:307 +0x5c

created by github.com/kentik/ktranslate/pkg/inputs/snmp.launchSnmp
    /src/pkg/inputs/snmp/snmp.go:300 +0x4ac

panic: runtime error: invalid memory address or nil pointer dereference
[signal SIGSEGV: segmentation violation code=0x1 addr=0x18 pc=0x13fe04b]
goroutine 4950 [running]:
github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*DeviceMetrics).pollFromConfig(0xc01129a1e0, {0x2251600, 0xc003afe980}, 0xc0014b3b80?, 0x0?)
    /src/pkg/inputs/snmp/metrics/device_metrics.go:147 +0xcab

github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*DeviceMetrics).Poll(...)
    /src/pkg/inputs/snmp/metrics/device_metrics.go:81

github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*Poller).Poll(0xc01129a180, {0x2251600, 0xc003afe980})
    /src/pkg/inputs/snmp/metrics/poll.go:244 +0x52

github.com/kentik/ktranslate/pkg/inputs/snmp.launchSnmp.func1()
    /src/pkg/inputs/snmp/snmp.go:307 +0x5c

created by github.com/kentik/ktranslate/pkg/inputs/snmp.launchSnmp
    /src/pkg/inputs/snmp/snmp.go:300 +0x4ac

panic: runtime error: invalid memory address or nil pointer dereference
[signal SIGSEGV: segmentation violation code=0x1 addr=0x18 pc=0x13fe04b]
goroutine 8360 [running]:
github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*DeviceMetrics).pollFromConfig(0xc01f088960, {0x2251600, 0xc000908140}, 0xc01c1fe160?, 0x0?)
    /src/pkg/inputs/snmp/metrics/device_metrics.go:147 +0xcab

github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*DeviceMetrics).Poll(...)
    /src/pkg/inputs/snmp/metrics/device_metrics.go:81

github.com/kentik/ktranslate/pkg/inputs/snmp/metrics.(*Poller).Poll(0xc01f088900, {0x2251600, 0xc000908140})
    /src/pkg/inputs/snmp/metrics/poll.go:244 +0x52

github.com/kentik/ktranslate/pkg/inputs/snmp.launchSnmp.func1()
    /src/pkg/inputs/snmp/snmp.go:307 +0x5c

created by github.com/kentik/ktranslate/pkg/inputs/snmp.launchSnmp
    /src/pkg/inputs/snmp/snmp.go:300 +0x4ac

panic: runtime error: invalid memory address or nil pointer dereference
[signal SIGSEGV: segmentation violation code=0x1 addr=0x18 pc=0x13fe04b]

Is it possible to get the version of ktranslate that the customer is running? Look for a log line like:
2023-03-07T23:13:42.002 ktranslate/ [Info]  version kt-2023-03-02-4309796445 starting

Thanks.

@i3149
They are using version kt-2023-02-24-4267053092

They are no longer sending data because of the apparent memory issue.

authors: i3149 jvadera tvranicar

repo: kentik/ktranslate


text:
Run and test webapp in CI

Build, run and test the webapp from docker container
Based on https://github.com/kentik/sla_dashboard_webapp/pull/45

This change is included in https://github.com/kentik/sla_dashboard_webapp/pull/47


text:
Deprecated

Last release is in 2017.
Shouldn't this repository be deprecated due to inactivity? (like putting a warning in readme)

it is sad to see a plugin like this being end up abondoned.
I wish someone takes it up and moves it forward.

I guess an alternative that is actively developed would be Swiper.

@cdalexndr yes swiper is being maintained actively but swiper is much more powerful and heavy.
where as slick is really slick, in small sites where i don't need much effects....i feel slick works great.

authors: cdalexndr lorvent

repo: kenwheeler/slick


text:
applyAutoTaggingRules.sh fails right after creating first rule

The script applyAutoTaggingRules.sh fails each time it is executed in the first if statement.
The problem is that the variable that is checked is indeed not 0 but in fact set to the tenant id.
Expected behaviour
It has to be checked if the curl is successful or not. The bug fix should also check if the rules are already created and should update them if already present.

First fix proposed here https://github.com/keptn/keptn/commit/0827aa0d51c2b537d2545e5693fe5fbff4adf76c does successfully create both rules but does not stop the installation if the rules are already there (won't be updated) or another issue occurs (e.g., the API token is not valid)

repo: keptn/keptn


text:
Provide ability to scale graphs in Keptn Bridge

As a user I would like to be able to modify graphs scale/visible data in order to analyze results better.
Problem:
If the SLI value will swing to some extreme value the graph is autoscaled and it's impossible to visualize data properly.
Example:
Normal data sample is returning 200-500ms after test run - the timeout for response set in the application is 10000ms.
If timeout is hit frequently because the issue in the app (Garbage collection / issue with the app / network problem) and there will be spike the graph will autoscale.
Similar situation might happen for Error rate per build. If our "normal level" is 0-1k errors for 1h build / few million samples and all of sudden it will jump to 150-250k. Then 1k becomes a tiny line near 0 on Y axis.
Then when the situation will come back to normal values there is no way to see the trend and if the data didn't jump to 1s (what could be still in the boundaries of proper response).
How to solve it:

Add ability to visualize data in logarithmic scale - this could allow omitting the problem with samples jumping
Add ability to set max Y axis value (open question - maybe it should be possible to set permanently per SLO)
Add ability to hide certain data set permanently - this causes that button "show permanently hidden data" might be needed

Sample:

Possibly it's connected to https://github.com/keptn/keptn/issues/5282


text:
#3777 sequence waiting status

Closes #3777

Signed-off-by: Klaus Strießnig k.striessnig@gmail.com

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

authors: Kirdock dyladan


text:
🛑 kbmn is down

In 93c883b, kbmn (http://www.kbmn.in/) was down:

HTTP code: 0
Response time: 0 ms

Resolved: kbmn is back up in 5360397 after 24 minutes.

repo: kerala-biodiversity/upt


text:
Training is not using 100% CPU

I am running the examples on my Ubuntu machine Intel® Core i7-4770K CPU @ 3.50GHz with 4 cores. During the entire training, only ~25% of the CPU is used. Which means it is running on only one core. Am I missing something?

I know this is necro, but I figure since we're kicking new life into this, may as well revisit some of these open threads.
I could be wrong, but my understanding of why this seems to happen is that you'd need to use an async agent like A3C or async DDPG or whatever to make use of all possible threads on your processor. If you're using the cpu version of tensorflow, it should utilize most of your CPU to train the neural networks, but unlike with traditional machine learning, the neural networks only get updated after your environment takes a step, and that training is only for a sample size of 1, so that part can run pretty quickly and may just show up on your CPU load as a quick peak. The environment you're using may be rather CPU intense (like mine has to a ton of math each step), and unless your environment is multi-threading somehow, that's just going to run on one CPU.  A3C and other asynchronous algorithms will create multiple actor/critic pairs that will run in parallel with one another, so with those, you can use your full CPU (and GPU) potential. That's why they're so popular, and why I want to get async DDPG built here.

repo: keras-rl/keras-rl


text:
Compliance with the XDG Base Directory Specification

Currently, Keras puts all of its configuration files and models into ~/.keras directory on Linux. This clutters up the user's home directory.
Keras could instead put its configuration files to XDG_CONFIG_HOME/keras/ and models to XDG_DATA_HOME/keras/models/.
It would be great if Keras used the standard directories, at least on Linux.

[x] Check that you are up-to-date with the master branch of Keras. You can update with:
pip install git+git://github.com/keras-team/keras.git --upgrade --no-deps

[x] If running on TensorFlow, check that you are up-to-date with the latest version. The installation instructions can be found here.

[x] If running on Theano, check that you are up-to-date with the master branch of Theano. You can update with:
pip install git+git://github.com/Theano/Theano.git --upgrade --no-deps

[x] Provide a link to a GitHub Gist of a Python script that can reproduce your issue (or just copy the script here if it is short).

Any updates on this?

It seems like keras is still using ~/.keras for e.g. keras.json. Are you sure this issue was correctly closed as completed? There are no PRs or commits linked...

I can also still reproduce this issue:
~/.keras via 💎 v2.5.1 took 32ms
04:26:21 AM ➜ cat keras.json
───────┬──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
       │ File: keras.json
───────┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
   1   │ {
   2   │     "floatx": "float32",
   3   │     "epsilon": 1e-07,
   4   │     "backend": "tensorflow",
   5   │     "image_data_format": "channels_last"
   6   │ }
───────┴──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────

~/.keras via 💎 v2.5.1 took 68ms
04:26:24 AM ➜ ll
.rw-r--r-- alichtman staff 120 B Sun May 10 18:30:29 2020  keras.json

@fchollet may I ask why this was closed as 'completed'?

Looking at the code @alichtman linked, you can do:
export KERAS_HOME="$XDG_CONFIG_HOME/keras"

I should not have to manually set env vars so that programs respect the XDG base directory specification... it's there for a reason, can you imagine your home directory if all developers just put their files wherever they wanted?

authors: Jappie3 alichtman mjanonis yochem

repo: keras-team/keras


text:
Keras 1D CNN always predicts the same result even if accuracy is high on training set

The validation accuracy of my 1D CNN is stuck on 0.5 and that's because I'm always getting the same prediction out of a balanced data set. At the same time my training accuracy keeps increasing and the loss decreasing as intended.
Strangely, if I do model.evaluate() on my training set (that has close to 1 accuracy in the last epoch), the accuracy will also be 0.5. How can the accuracy here differ so much from the training accuracy of the last epoch? I've also tried with a batch size of 1 for both training and evaluating and the problem persists.
Well, I've been searching for different solutions for quite some time but still no luck. Possible problems I've already looked into:

My data set is properly balanced and shuffled;
My labels are correct;
Tried adding fully connected layers;
Tried adding/removing dropout from the fully connected layers;
Tried the same architecture, but with the last layer with 1 neuron and sigmoid activation;
Tried changing the learning rates (went down to 0.0001 but still the same problem).

Here's my code:
import pathlib
import numpy as np
import ipynb.fs.defs.preprocessDataset as preprocessDataset
import pickle
import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras import Input
from tensorflow.keras.layers import Conv1D, BatchNormalization, Activation, MaxPooling1D, Flatten, Dropout, Dense
from tensorflow.keras.optimizers import SGD

main_folder = pathlib.Path.cwd().parent
datasetsFolder=f'{main_folder}\\datasets'
trainDataset = preprocessDataset.loadDataset('DatasetTime_Sg12p5_Ov75_Train',datasetsFolder)
testDataset = preprocessDataset.loadDataset('DatasetTime_Sg12p5_Ov75_Test',datasetsFolder)

X_train,Y_train,Names_train=trainDataset[0],trainDataset[1],trainDataset[2]
X_test,Y_test,Names_test=testDataset[0],testDataset[1],testDataset[2]

model = Sequential()

model.add(Input(shape=X_train.shape[1:]))

model.add(Conv1D(16, 61, strides=1, padding="same"))
model.add(BatchNormalization())
model.add(Activation('relu'))
model.add(MaxPooling1D(2, strides=2, padding="valid"))

model.add(Conv1D(32, 3, strides=1, padding="same"))
model.add(BatchNormalization())
model.add(Activation('relu'))
model.add(MaxPooling1D(2, strides=2, padding="valid"))

model.add(Conv1D(64, 3, strides=1, padding="same"))
model.add(BatchNormalization())
model.add(Activation('relu'))
model.add(MaxPooling1D(2, strides=2, padding="valid"))

model.add(Conv1D(64, 3, strides=1, padding="same"))
model.add(BatchNormalization())
model.add(Activation('relu'))
model.add(MaxPooling1D(2, strides=2, padding="valid"))

model.add(Conv1D(64, 3, strides=1, padding="same"))
model.add(BatchNormalization())
model.add(Activation('relu'))
model.add(Flatten())
model.add(Dropout(0.5))

model.add(Dense(200))
model.add(Activation('relu'))

model.add(Dense(2))
model.add(Activation('softmax'))

opt = SGD(learning_rate=0.01)

model.compile(loss='binary_crossentropy',optimizer=opt,metrics=['accuracy'])

model.summary()

model.fit(X_train,Y_train,epochs=10,shuffle=False,validation_data=(X_test, Y_test))

model.evaluate(X_train,Y_train)

Here's model.fit():
model.fit(X_train,Y_train,epochs=10,shuffle=False,validation_data=(X_test, Y_test))

Epoch 1/10
914/914 [==============================] - 277s 300ms/step - loss: 0.6405 - accuracy: 0.6543 - val_loss: 7.9835 - val_accuracy: 0.5000
Epoch 2/10
914/914 [==============================] - 270s 295ms/step - loss: 0.3997 - accuracy: 0.8204 - val_loss: 19.8981 - val_accuracy: 0.5000
Epoch 3/10
914/914 [==============================] - 273s 298ms/step - loss: 0.2976 - accuracy: 0.8730 - val_loss: 1.9558 - val_accuracy: 0.5002
Epoch 4/10
914/914 [==============================] - 278s 304ms/step - loss: 0.2897 - accuracy: 0.8776 - val_loss: 20.2678 - val_accuracy: 0.5000
Epoch 5/10
914/914 [==============================] - 277s 303ms/step - loss: 0.2459 - accuracy: 0.8991 - val_loss: 5.4945 - val_accuracy: 0.5000
Epoch 6/10
914/914 [==============================] - 268s 294ms/step - loss: 0.2008 - accuracy: 0.9181 - val_loss: 32.4579 - val_accuracy: 0.5000
Epoch 7/10
914/914 [==============================] - 271s 297ms/step - loss: 0.1695 - accuracy: 0.9317 - val_loss: 14.9538 - val_accuracy: 0.5000
Epoch 8/10
914/914 [==============================] - 276s 302ms/step - loss: 0.1423 - accuracy: 0.9452 - val_loss: 1.4420 - val_accuracy: 0.4988
Epoch 9/10
914/914 [==============================] - 266s 291ms/step - loss: 0.1261 - accuracy: 0.9497 - val_loss: 4.3830 - val_accuracy: 0.5005
Epoch 10/10
914/914 [==============================] - 272s 297ms/step - loss: 0.1142 - accuracy: 0.9548 - val_loss: 1.6054 - val_accuracy: 0.5009

Here's model.evaluate():
model.evaluate(X_train,Y_train)

914/914 [==============================] - 35s 37ms/step - loss: 1.7588 - accuracy: 0.5009

Here's model.summary():
Model: "sequential"
_________________________________________________________________
Layer (type)                 Output Shape              Param #
=================================================================
conv1d (Conv1D)              (None, 4096, 16)          992
_________________________________________________________________
batch_normalization (BatchNo (None, 4096, 16)          64
_________________________________________________________________
activation (Activation)      (None, 4096, 16)          0
_________________________________________________________________
max_pooling1d (MaxPooling1D) (None, 2048, 16)          0
_________________________________________________________________
conv1d_1 (Conv1D)            (None, 2048, 32)          1568
_________________________________________________________________
batch_normalization_1 (Batch (None, 2048, 32)          128
_________________________________________________________________
activation_1 (Activation)    (None, 2048, 32)          0
_________________________________________________________________
max_pooling1d_1 (MaxPooling1 (None, 1024, 32)          0
_________________________________________________________________
conv1d_2 (Conv1D)            (None, 1024, 64)          6208
_________________________________________________________________
batch_normalization_2 (Batch (None, 1024, 64)          256
_________________________________________________________________
activation_2 (Activation)    (None, 1024, 64)          0
_________________________________________________________________
max_pooling1d_2 (MaxPooling1 (None, 512, 64)           0
_________________________________________________________________
conv1d_3 (Conv1D)            (None, 512, 64)           12352
_________________________________________________________________
batch_normalization_3 (Batch (None, 512, 64)           256
_________________________________________________________________
activation_3 (Activation)    (None, 512, 64)           0
_________________________________________________________________
max_pooling1d_3 (MaxPooling1 (None, 256, 64)           0
_________________________________________________________________
conv1d_4 (Conv1D)            (None, 256, 64)           12352
_________________________________________________________________
batch_normalization_4 (Batch (None, 256, 64)           256
_________________________________________________________________
activation_4 (Activation)    (None, 256, 64)           0
_________________________________________________________________
flatten (Flatten)            (None, 16384)             0
_________________________________________________________________
dropout (Dropout)            (None, 16384)             0
_________________________________________________________________
dense (Dense)                (None, 200)               3277000
_________________________________________________________________
activation_5 (Activation)    (None, 200)               0
_________________________________________________________________
dense_1 (Dense)              (None, 2)                 402
_________________________________________________________________
activation_6 (Activation)    (None, 2)                 0
=================================================================
Total params: 3,311,834
Trainable params: 3,311,354
Non-trainable params: 480
_________________________________________________________________

What I have in mind is your model possibly overfit on each epoch of the dataset. Since the validation loss is not stable. This could explain why your evaluation on the whole train set is a little above 0.5.
For a 1d dataset. The model seems too complex. Try to remove some of the CNN layers and the dense layers.


text:
LSTM Cell state value does not have activation function applied to it before being returned.

My understanding was that that the cell state would have the activation function applied to it before being returned. However, it can exceed 1, or be far into the negative ranges, which should be impossible if the activation function is being applied.
Here's some example code:

from numpy import *
from keras.layers import Input,  LSTM
from keras.models import Model
main_input = Input(shape = (3,1), dtype = 'float32', name = 'main_input')
lstm_out = LSTM(1,use_bias = False, return_state = True)
sequence_out, state_h, state_c = lstm_out(main_input)
model = Model(inputs = main_input, outputs = [sequence_out, state_h, state_c])
model.layers[1].set_weights([array([[1,1,1,1]], dtype=float32), array([[1,1,1,1]],
                            dtype=float32)])
predict = model.predict(array([1,1,1]).reshape(1,3,1))

print(predict)

And output:
[array([[0.7629155]], dtype=float32), array([[0.7629155]], dtype=float32), array([[1.6458433]], dtype=float32)]

If you examine the predictions, it can be seen that the cell state does not have the activation function applied. It is 1.6, when it should be in the range of the activation function. Is this intended behaviour? Does the same thing apply during training, or is this just when predicting?
Thanks for any help on this issue.

Looks like I just misread what an LSTM cell state is. The activation function is only applied to the input.