id stringlengths 4 10 | text stringlengths 4 2.14M | source stringclasses 2
values | created timestamp[s]date 2001-05-16 21:05:09 2025-01-01 03:38:30 | added stringdate 2025-04-01 04:05:38 2025-04-01 07:14:06 | metadata dict |
|---|---|---|---|---|---|
155847262 | Occasional build failure in wseb acceptor spec test ControlIT.shouldCloseConnectionOnReceivingInvalidPingFromClient
This failure occurred for example in build #1540 on Travis. Here's an extract from the build output showing the failure:
shouldCloseConnectionOnReceivingInvalidPingFromClient(org.kaazing.gateway.transport.wseb.specification.wse.acceptor.ControlIT) Time elapsed: 0.147 sec <<< FAILURE!
org.junit.ComparisonFailure: Specified behavior did not match expected:<...close
read status "[200" /.+/
read header "Content-Type" "application/octet-stream"
read header "Connection" "close"
read [0x01 0x30 0x32 0xFF]
read [0x01 0x30 0x31 0xFF]
read closed]
# Upstream
connect...> but was:<...close
read status "[404"]
Looking at the specification script: client.send.invalid.ping/request.rpt, it is clear this is an issue with the script. There is a race between the establishment of the upstream and the sending of the invalid ping frame and the establishment of the downstream. If the downstream connects after the upstream then the observed behavior is correct (status 404 response, not found, on the downstream, because the logical wseb connection was already closed). This needs to be fixed in the spec scripts: use barriers to force downstream to be established before the invalid ping frame is sent on the upstream. If have filed k3po issue https://github.com/k3po/k3po/issues/339 for this.
k3po PR https://github.com/k3po/k3po/pull/369
| gharchive/issue | 2016-05-19T22:12:41 | 2025-04-01T06:44:39.731770 | {
"authors": [
"cmebarrow",
"jitsni"
],
"repo": "kaazing/gateway",
"url": "https://github.com/kaazing/gateway/issues/580",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
352062302 | Reminder slack notifications are sent twice
This might be a configuration issue. Find the root cause and fix this.
Probably related to how kabisa team's team memberships and duplicate accounts are stored (e.g. the recent change from google to move from alias to account name (ariejan vs. ariejan.de.vroom).
Ignore the previous comment. It has nothing to do with accounts.
We use Rufus to schedule cronjobs for us, straight from the Ruby code. On boot-up, Rufus will update cron to schedule the appropriate tasks.
Since we run two containers, one for web, one for worker, we schedule these jobs on both containers, hence we get two notifications.
Rufus is not a recommended way of scheduling tasks. I've updated this issue's original message with TODO's on how to resolve this.
/cc @pascalw
| gharchive/issue | 2018-08-20T09:52:16 | 2025-04-01T06:44:39.736816 | {
"authors": [
"ariejan"
],
"repo": "kabisa/kudo-o-matic",
"url": "https://github.com/kabisa/kudo-o-matic/issues/372",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
1293139633 | calcpriceとは？
calcpriceとは？
【質問】計算用現値CalcPriceについて · Issue #35 · kabucom/kabusapi
@hori-ryota さんの方でご回答いただいておりますが、こちら、計算用現値のこととなります
解決済みのようですので、クローズさせていただきます。
| gharchive/issue | 2022-07-04T12:58:33 | 2025-04-01T06:44:39.738606 | {
"authors": [
"Uchiii7",
"cyber-minion",
"hori-ryota",
"yasuyuki-nakazawa"
],
"repo": "kabucom/kabusapi",
"url": "https://github.com/kabucom/kabusapi/issues/562",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
1812075742 | 225MINIでの返済について（/sendorder/future）
225MINIでの返済について（/sendorder/future）
売玉有の時 返済買いの注文を出しましたがエラーになってしまいます。
新規注文（TradeType: 1 , Side: '1'）は問題なくできました。
以下のようなデータを送信していますがなにか間違いがありますでしょうか？
payload = {
Password: 'XXXXXXX',
Symbol: '168090019',
Exchange: 23,
TradeType: 2,
Side: '2',
Qty: 1,
ClosePositions: [{ HoldID: '20230719XXXXXXX', Qty: 1 }],
FrontOrderType: 120,
Price: 0,
ExpireDay: 0,
TimeInForce: 2
}
エラーコードは８で返済建玉情報不正エラー のようです。
アドバイスいただければと思います。
以下のパラメータの設定について、ご確認をお願いいたします。
ClosePositions
HoldIDは、残高照会APIで取得したExecutionIDを指定していただく必要がございます。
下記の例のように、先頭に「E」が付いているかと思いますので、ご確認をお願いします。
例：E20230719xxxxx
ExecutionIDの件、ありがとうございます。確認してみます
保有数が3枚ありどれかを返済したいときにOrderIdに紐づけれないとなれば
損益が真ん中のものを決済を最初にはできないとのことで良いでしょうか？
ExcutionIDは約定ごとに採番されています。
お問い合わせのように保有数が3枚あり、それぞれが別々に約定したものであれば、
それぞれに異なるExcutionIDがありますので、損益が真ん中のものを選択することも可能です。
確認してみます。ありがとうございました
| gharchive/issue | 2023-07-19T14:25:11 | 2025-04-01T06:44:39.741916 | {
"authors": [
"app-yama",
"satosato125"
],
"repo": "kabucom/kabusapi",
"url": "https://github.com/kabucom/kabusapi/issues/717",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
337286891 | Commands
어떤 명령어들을 만들까요?
[ ] 계정 이름으로 전적 검색
[ ] 계정의 최근 경기 검색?
뭔차이가 있는 건가용?
@kagong
계정 이름으로 전적 검색은 kda, rating이라던가 승률 등등 계정의 정보고요.
최근 경기 검색은 해당 계정의 최근 경기의 결과라던가 여러가지 정보가 들어있을거 같네요.
API Document를 좀 뒤적여봐야겠어요.
@JimJeon
경기 검색에서는
"attributes": {
"createdAt": "string",
"duration": 0,
"gameMode": "duo",
"mapName": "Desert_Main",
"isCustomMatch": true,
"patchVersion": "string",
"shardId": "string",
"stats": {},
"tags": {},
"titleId": "string"
},
이런 속성들이 있는 것 같은데
"relationships": {
"assets": {
"data": [
{
"type": "string",
"id": "string"
}
]
},
"rosters": {
"data": [
{
"type": "string",
"id": "string"
}
]
},
"rounds": {},
"spectators": {}
},
여기서 rosters 와 asset object들이 뭘 위한건지 이해가 안가네요 한번 봐주세용
https://documentation.playbattlegrounds.com/en/matches-endpoint.html#/Matches/get_matches__id_
{
"data": {
"type": "match",
"id": "e8af5c90-c784-400e-952e-f2949833dfc9",
"attributes": {
"shardId": "pc-kakao",
"tags": null,
"mapName": "Savage_Main",
"isCustomMatch": false,
"stats": null,
"duration": 1432,
"gameMode": "squad",
"titleId": "bluehole-pubg",
"createdAt": "2018-07-16T23:32:52Z"
},
"relationships": {
"assets": {
"data": [
{
"type": "asset",
"id": "1f46ec59-8954-11e8-b3ec-0a586461c617"
}
]
},
"rosters": {
"data": [
{
"type": "roster",
"id": "0d55d986-ba6f-49fe-9e32-00e9c933d384"
},
{
"type": "roster",
"id": "9035ab94-d2de-4e29-bc71-8aa6919dc2a1"
},
{
"type": "roster",
"id": "f3eb1099-7f02-4793-9f84-b2315984b26a"
}
]
}
},
"links": {
"self": "https://api.playbattlegrounds.com/shards/pc-kakao/matches/e8af5c90-c784-400e-952e-f2949833dfc9",
"schema": ""
}
}
}
이런 느낌으로 값을 받을 수 있네요. 응답이 너무 길어서 대부분 잘라내고 말씀해주신 부분만 남겨보았습니다.
"relationships": {
...
"assets": {
"data": [
{
"type": "asset",
"id": "1ad97f85-cf9b-11e7-b84e-0a586460f004"
}
]
}
...
}
위와 같은 Assets Object에 대해서 아래와 같이 telemetry.json을 접근 할 수 있다고 합니다.
curl "https://telemetry-cdn.playbattlegrounds.com/pc-krjp/2018/01/01/0/0/1ad97f85-cf9b-11e7-b84e-0a586460f004-telemetry.json" -H "Accept: application/vnd.api+json"
| gharchive/issue | 2018-07-01T12:21:39 | 2025-04-01T06:44:39.832174 | {
"authors": [
"JimJeon",
"kagong"
],
"repo": "kagong/PyGS",
"url": "https://github.com/kagong/PyGS/issues/1",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
210353384 | Mount google cloud storage?
Any idea on how to mount google cloud storage using goofys?
it should just work if you set --endpoint to the S3 endpoint after you enable it in the google dashboard.
I see, thanks.
There's some info here for future reference:
https://cloud.google.com/storage/docs/migrating
https://cloud.google.com/storage/docs/interoperability
Thanks for the links!
Could someone post a CLI example of mounting Google Drive using goofys? Where do we need to adjust or set something on our Google Dashboard, for example (not everyone will know this).
Could someone post a CLI example of mounting Google Drive using goofys? Where do we need to adjust or set something on our Google Dashboard, for example (not everyone will know this).
I dont think goofys works with google drive. This issue is about https://cloud.google.com/storage.
I dont think goofys works with google drive. This issue is about https://cloud.google.com/storage.
| gharchive/issue | 2017-02-26T22:14:41 | 2025-04-01T06:44:39.836461 | {
"authors": [
"dotslash",
"forrie",
"kahing",
"peixotorms"
],
"repo": "kahing/goofys",
"url": "https://github.com/kahing/goofys/issues/158",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
334641832 | What is the path to the syslog file
After I ran $GOBIN/goofys --debug_s3 bucket_name dir, it said:
2018/06/21 15:13:47.098950 main.FATAL Unable to mount file system, see syslog for details
Which file should I look?
hi @taozhaolib , on Ubuntu this should be /var/log/syslog
| gharchive/issue | 2018-06-21T20:17:59 | 2025-04-01T06:44:39.838238 | {
"authors": [
"taozhaolib",
"weirdbricks"
],
"repo": "kahing/goofys",
"url": "https://github.com/kahing/goofys/issues/332",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
479326030 | goofys not work and not print log in wsl(Windows Subsystem Linux) Ubuntu 18.04
I downloaded goofys binary and run in Windows 2019 wsl(Windows Subsystem Linux) Ubuntu 18.04. It's not worked and print error message:
2019/08/11 02:43:20.681328 main.FATAL Unable to mount file system, see syslog for details
But unlucky, there's also no output in /var/log/syslog .
My questions are:
How can Goofys support in wsl ubuntu 18.04 in Windows Server 2019?
Why there's not error log in /var/log/syslog?
Thanks a lot.
Try -f to run the process in the foreground which will print the logs.
Thanks yuvisara.
I tried with -f parameters like below:
wsl-user@windows-wsl:~$ sudo ./goofys -f s3-temp-driver /mnt/goofys/
shown below:
2019/08/12 15:29:20.708697 main.FATAL Mounting file system: Mount: mount: running fusermount: exit status 1
stderr:
fusermount: fuse device not found, try 'modprobe fuse' first
Then I tried sudo modprobe fuse, got:
ec2-user@EC2AMAZ-TAE8VA7:~$ sudo modprobe fuse
modprobe: ERROR: ../libkmod/libkmod.c:586 kmod_search_moddep() could not open moddep file '/lib/modules/4.4.0-17763-Microsoft/modules.dep.bin'
modprobe: FATAL: Module fuse not found in directory /lib/modules/4.4.0-17763-Microsoft
From https://github.com/microsoft/WSL/issues/2869 I can see, no fuse support in wsl now.
Thanks.
I don't use windows personally so someone else will have to do the investigations. It's perhaps possible to port the underlining fuse library to use windows specific mechanism instead but again someone else will have to look into it
Got it and thanks for you guys replies.
| gharchive/issue | 2019-08-11T02:45:43 | 2025-04-01T06:44:39.844061 | {
"authors": [
"Allen2Git",
"kahing",
"yuvisara"
],
"repo": "kahing/goofys",
"url": "https://github.com/kahing/goofys/issues/443",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
284112933 | 清除全选方法
提供清除全选的方法。
https://github.com/kairi1227/react-drag-picker/commit/44d47efa1415a2f283d0f3577e19221ef888a19d
| gharchive/issue | 2017-12-22T09:20:34 | 2025-04-01T06:44:39.849337 | {
"authors": [
"kairi1227"
],
"repo": "kairi1227/react-drag-picker",
"url": "https://github.com/kairi1227/react-drag-picker/issues/1",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
989750231 | Question about datasets
Why did you use Republic of Korea datasets?
We first tried to use other datasets from other countires, but it was impossible because we could not access to the actual driving record to classify dangerous driving behavior of each trajectory. However, fortunately, the KoROAD was able to provide such dataset to us, so we only use Korea datasets.
| gharchive/issue | 2021-09-07T08:53:08 | 2025-04-01T06:44:39.853644 | {
"authors": [
"itouchz",
"young-eun-nam"
],
"repo": "kaist-dmlab/DF-TAR",
"url": "https://github.com/kaist-dmlab/DF-TAR/issues/5",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
614207956 | Fix typo in day3's and day4's documents
day3
どれだけ効率が良くなかったを示す指標 to どれだけ効率が良くなったかを示す指標
day4
全プロセス勝手に吐くく to 全プロセス勝手に吐く
Thanks @qb0C80aE !
| gharchive/pull-request | 2020-05-07T17:00:57 | 2025-04-01T06:44:39.864902 | {
"authors": [
"kaityo256",
"qb0C80aE"
],
"repo": "kaityo256/sevendayshpc",
"url": "https://github.com/kaityo256/sevendayshpc/pull/13",
"license": "CC-BY-4.0",
"license_type": "permissive",
"license_source": "github-api"
} |
1557895577 | Add Unit tests to book and label
In this PR I have made the following changes:
Added unit tests for Book class in book_spec.rb
Added unit tests for Label class in label_spec.rb
Removed read_booklabel method from app.rb
Hi @kaizipaul
Your changes are approved! There is nothing else to say other than... it's time to merge the branch :shipit:
Congratulations! 🎉
Status: Approved ✔️✔️✔️
Cheers and Happy coding!👏👏👏
| gharchive/pull-request | 2023-01-26T10:01:05 | 2025-04-01T06:44:39.883687 | {
"authors": [
"DJ-MrJay",
"kaizipaul"
],
"repo": "kaizipaul/ruby-capstone-project",
"url": "https://github.com/kaizipaul/ruby-capstone-project/pull/34",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
1906168329 | fix bug during w2v training with utf8 characters
bug
when training w2v with Korean words(utf-8 characters), idmap['cols'] couldn't get utf-8
UnicodeEncodeError: 'ascii' codec can't encode characters in position 0-1: ordinal not in range(128)
as-is
dtype=Sx
S: data type should be ascii characters
to be
dtype=h5py.string_dtype('utf-8')
docs
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.
| gharchive/pull-request | 2023-09-21T05:55:03 | 2025-04-01T06:44:39.888002 | {
"authors": [
"CLAassistant",
"hugh-ga"
],
"repo": "kakao/buffalo",
"url": "https://github.com/kakao/buffalo/pull/75",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
216133341 | Разработка полной схемы аналоговой части
Исчерпывающая схема с полной распиновкой.
Включая:
Входные каскады
Выходные каскады
Усилители из корпусе
Интерфейсы
Обвеска всех чипов (микроконтроллер, драйвер RS232, корпус с усилителями)
Подведение итогов по аналоговой части.
Реализует коммит https://github.com/kalaider/act-photo/commit/494b4d950dabe0811470aebe8d9b43f5b2261073.
Описание
На рисунке представлена полная на данный момент схема аналоговой части.
Отображено:
Первичный входной каскад (диод в генераторном включении)
Фильтр нижних частот
Конечный усилитель
Каскад установки опорного уровня освещенности
Выходной каскад
Интерфейсные схемы (интерфейсы I2C, SPI, RS232 через драйвер ST232 с обвеской)
Обвеска ATmega8A
Напряжения питания (VCC = +5V, VC = +12V, VE = -12V)
Не отображено:
Ввод питания и земли
Отдельные транзисторы заменены на микросхему TL084 из четырех транзисторов. Схемы фильтров упрощены руками.
Провод земли для наглядности помечен пурпурным цветом.
Модель
Свет, попадая на фотодиод, вызывает в нем фототок, который, проходя через резистор обратной связи первичного усилителя (а точнее преобразователя "ток-напряжение") преобразуется в падение напряжения, которое затем фильтруется и усиливается.
Микроконтроллер по разности опорного сигнала и сигнала с фотодиода по специальному алгоритму вырабатывает ШИМ, которая управляет свечением диода выходного каскада. Светодиод управляется током, чем обусловлен вариант его включения.
Для связи с компьютером, программатором и другими микроконтроллерами реализуется набор интерфейсов. RS232 требует драйвер (ST232) для стабильной работы. Все интерфейсные выводы выводятся в отдельные выходы на схеме.
Обвеска микросхем обеспечивает их стабильную работу.
Замечания
Конденсаторы большой емкости (~0.1u) -- полярные.
Резисторы, помеченные меткой Trimmer -- подстроечные.
Напряжение с подстроечного резистора, задающего опорный уровень, снимается с третьего ("реостатного") вывода.
Номиналы других подстроечных резисторов могут варьироваться. Эти резисторы служат лишь только для подгона параметров схемы. После подгона на их место будут вмонтированы уже обычные резисторы.
Метки в виде красных ромбов -- места, которые в данный момент уточняются / могут поменяться.
| gharchive/issue | 2017-03-22T16:44:36 | 2025-04-01T06:44:39.939136 | {
"authors": [
"kalaider"
],
"repo": "kalaider/act-photo",
"url": "https://github.com/kalaider/act-photo/issues/26",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
1522968397 | Switch to functional/stateless architecture
Currently, BYOC is tightly coupled to the app object. This has some downsides:
It's not possible to use BYOC without an app object, e.g. in simple scripts where a dictionary would otherwise suffice.
The app objects end up keeping a bunch of intermediate state for their entire lifetimes, even though (in principle) that state can be dropped once the "final" values are calculated.
I believe that moving to a functional/stateless architecture would address both of these points, and make the code more extensible in general. By "functional/stateless architecture", I mean roughly that there would be a load(params, configs) function that would return a dict/object with all the specified information.
However, it's not clear how all of the useful features of BYOC would be reimplemented in such a system. The purpose of this thread is to enumerate and discuss such features.
DocoptConfig: Using parameters when loading configs
UpstreamConfig: Reusing configs from other apps
Part: Deriving multiple parameters from a single config value
Never overwrite manually specified values
This is more of a danger with the load() function, since the natural thing to do would just be to overwrite everything.
I'd also need to take care to distinguish between values set by the user, and values set by a previous call to load.
Automatic initialization
One feature of the current system is that you don't need to manually initialize things. Just add a Template to a Pcr reaction, for example, and it will automatically fill itself when you go to use it. This is convenient, but it adds a lot of complexity and (in some cases) duplicate effort.
A functional architecture would instead calculate everything at once.
Config
Currently, all the config classes are initialized with the app object.
This isn't ideal:
All the configs really need is to load values from somewhere. They don't need the app to do this, they just need some of the information that might be contained in the app.
Move all this to the factories:
Configs have no knowledge of the apps
Config factories do, though, and use that knowledge to correctly instantiate configs.
Three ways to specify values for configs:
Factory kwargs
App attributes
Class variables
I can probably write some code to simplify this:
Define "setting" descriptors for config classes.
Factories find all settings and set as appropriate.
Can instruct factory to look for different attribute.
Class-based interface
The functional interface will require the configs to be completely configured and ready to go.
The class-based interface will try to be more streamlined:
The __config__ factories will take responsibility for actually configuring the configs.
All parameters are automatically calculated and installed when any one parameter is accessed.
Apps can't be half-initialized:
Either every parameter has a value, or none do.
I'm not totally sure if this will solve issues like #47. It will be necessary to set sample.parent before calling load(), but that doesn't seem to onerous. Configs are immutable, so it doesn't matter what order the configs are used in.
Apps can't be reloaded:
There's no perfect way to distinguish between a value set/modified by the user vs one set by load(), so once a value has been set, I need to respect it.
I could add a load(force=True) flag to override this.
Method getter
This intrinsically needs to know about the app.
Having thought about this for a while, I don't think I can transition stepwise to a stateless architecture:
Reagents can be added to samples at any time, so there's no way to know when a sample is "complete", i.e. ready to load. This means that I'd have to force the user to manually load each reagent and sample, and I just don't think that that API is acceptable.
Loading parameters at the time that they're accessed is a natural way around this problem. By the time you're accessing an attribute, it's reasonable (and intuitive to API users) to assume that all the prerequisite reagents have been added to the sample by then. Importantly, though, accessing one attribute doesn't imply that any others are ready, which is why it's not really tractable to have an API that automatically loads everything once the first attribute is accessed.
However, the stateless architecture makes much more sense for a general-purpose library: it's simpler, more efficient, and more extensible. Without a stateless architecture, I couldn't see myself recommending this library to other people, nor could I see myself using it for anything other than stepwise. So I think a stateless architecture is essential.
Putting this all together, I think I need to support both architectures. More specifically, I need to implement a stateful architecture using the stateless architecture. This would actually be a good way to demonstrate the extensibility of the stateless architecture.
Some implementation details I have in mind:
Apps would have some configuration option that specifies how parameters should behave when they need a value. The options would be (i) raise an exception explaining that load() needs to be called, (ii) attempt to load that parameter, or (iii) attempt to load all parameters.
Define a "context" object that would store all the state necessary to load parameters. This object would hold the app itself, config layers, resolved getters for each parameter, miscellaneous data structure to communicate between parameters (e.g. for Part), etc.
In stateless mode, the context object would be created within the load() function, stored in the app, and deleted once everything has been loaded.
In stateful mode, the context object would be permanently stored in the app and possibly updated each time a new parameter was accessed. It'd probably make sense to provide a cleanup() function that could get rid of it.
Currently I have the concept of bound/unbound getters/configs. Bound objects hold a pointer to the app itself, and can get access to all the caches stored in the app via that pointer. I'd get rid of this concept, and just have getters/configs receive the context object as an argument.
I'd want to have pretty smart cache objects. For example, say I want to cache the layers from a config. I'd pass the config the context object, which would contain the app being loaded. If the config doesn't actually use any information in the app, though, I could cache the resulting layers in such a way that they could be used by other apps.
Case study: the stepwise configuration file. Currently I have a stepwise config that looks in all the places where a stepwise config file could be found and returns a layer for each. This is app-independent. But the config also allows the user to specify a "root key", in which case the config becomes app-dependent. Maybe I want to allow configs to depend on other configs. In this example, there would be an app-independent stepwise config that just loads every file it can find, and another app-dependent stepwise config that loads the independent one then yields copies of all those layers with a different root key. Fundamentally this is just letting the config make use of the cache that's already there, but this seems like a good way to do it.
Regarding the docopt issue, where some parameters can be loaded multiple times:
Some options:
Store every value produced by a getter, and associate it with a version number. Every time a parameter value is needed, use the cached values unless they're out of date. This would require a very detailed cache, though, and I'd need to call the picker every time a value is accessed. I think this is too much.
Clear the parameter-value cache each time a new config is loaded. This is pretty simple, but wasteful because it doesn't make an effort to avoid recalculating things that aren't affected by the new config.
Allow getters to raise NotReadyYet. This would indicate that the parameter could change value in the future (e.g. once more configs are loaded), but for now this getter should just be skipped.
I'd like some way for this exception to indicate what it's waiting on, otherwise load() could get stuck in an infinite loop (by trying to keep going until all "pending" parameters have values). Maybe I could have the context keep an internal version number that increments every time something about the context changes. If I get NotReadyYet twice for the same parameter with the same context version number, that's an infinite loop.
| gharchive/issue | 2023-01-06T18:20:01 | 2025-04-01T06:44:40.000018 | {
"authors": [
"kalekundert"
],
"repo": "kalekundert/byoc",
"url": "https://github.com/kalekundert/byoc/issues/49",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
2340614457 | feat: add random background image from commons
Pull Request
Description
Le background etait blanc
Changements Effectués
J'ai ajoute une image randomly from wikimedia commons
Liste de Vérification
[ X] Tester les changements localement.
[ X] Le code respecte les normes du projet.
Merci !
My suggestion: use a white background on the card. E.g.: chrome://whats-new/.
| gharchive/pull-request | 2024-06-07T14:35:11 | 2025-04-01T06:44:40.002920 | {
"authors": [
"Bam92",
"BirushaNdegeya"
],
"repo": "kaliacad/mostvisitedarticle",
"url": "https://github.com/kaliacad/mostvisitedarticle/pull/171",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
638763021 | Dual bootstrap support chapter in contributing docs is outdated
CONTRIBUTING.md does not reflect the changes to dual bootstrap support yet. Especially it still mentions the bootstrap version specific trees, which have been dropped in #992. On the other side it does not discuss the build macros introduced in #992 and follow-up merge requests.
Good catch! PRs welcome! 😜
| gharchive/issue | 2020-06-15T11:09:04 | 2025-04-01T06:44:40.004262 | {
"authors": [
"jelhan",
"simonihmig"
],
"repo": "kaliber5/ember-bootstrap",
"url": "https://github.com/kaliber5/ember-bootstrap/issues/1124",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
1767504410 | Fix optional binding error in AppInfoListView.
Hello Maintainer,
I hope this message finds you well. While I was going through the codebase, I found a place where optional binding is being used even though it's not needed.
The relevant process will result in an error in the Xcode 14.3.1 development environment.
Allowing the licenseFileURL property to be passed directly, given that it is always non-nil
Best Regards,
@Nao-RandD Thank you for submitting your PR. I've looked over the error you had.
The policy of this library is to display cells when values are passed. So I've modified the licenseFileURL type. I've released 1.0.0.
I appreciate your patience!
| gharchive/pull-request | 2023-06-21T12:34:17 | 2025-04-01T06:44:40.108608 | {
"authors": [
"Nao-RandD",
"kamimi01"
],
"repo": "kamimi01/AppInfoList",
"url": "https://github.com/kamimi01/AppInfoList/pull/1",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
51723550 | Mod FieldUtility.GetMediaUrl() to honor Media.AlwaysIncludeServerUrl
Modified FieldUtility.GetMediaUrl() to honor the Media.AlwaysIncludeServerUrl setting, if it is set. (Issue #13)
Thanks for the PR!
Per http://www.sitecore.net/Learn/Blogs/Technical-Blogs/John-West-Sitecore-Blog/Posts/2012/12/Sitecore-Idiosyncrasies-Media-URLs.aspx it's no longer needed to prefix the URL at all in 6.6+ (and it's for sure not on 7.2) so I was able to remove it all and just use MediaManager directly.
I believe you guys are still on 6.5, in which case you may need to keep the tweak in your fork.
| gharchive/pull-request | 2014-12-11T18:55:21 | 2025-04-01T06:44:40.122289 | {
"authors": [
"jeremyclifton",
"kamsar"
],
"repo": "kamsar/Synthesis",
"url": "https://github.com/kamsar/Synthesis/pull/14",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
129029185 | Additional configuration flags
It might be nice to have some additional flags that would further segregate many-configurationed projects. For example:
explicitSyncOnly => configuration is not synced when 'sync all' is used, and must be synced explicitly or included in a list of configs to sync
maxConcurrency => set the max number of threads to use when syncing or reserializing. Must be 1 if the config contains template items due to a Sitecore bug (see #80) but for content configs we can speed things up by allowing threading.
category => organize the control panel by categories of configuration, possibly collapsed by default, for organizational purposes. Should also be able to flag all configs in a category for sync.
Anyone else got ideas? Feedback? At present this is just an idea.
The most pressing feature I would have for this is the ability to specify wildcards as sync targets - and have Unicorn sort out the dependencies and ordering.
Something like:
/unicorn.aspx?verb=Sync&configuration=*
or even:
/unicorn.aspx?verb=Sync&configuration=Foundation.*^Feature.*^Project.Common.Website^Project.Habitat.Website
+1 We are in desperate need to be able to perform sync for all configurations available, i.e.:
unicorn.aspx?verb=Sync&configuration=All
That is already available, just don't specify the configuration parameter
and that implies all configurations.
On Thu, Mar 17, 2016 at 9:40 AM Dmitri Moore notifications@github.com
wrote:
+1 We are in desperate need to be able to perform sync for all
configurations available, i.e.:
unicorn.aspx?verb=Sync&configuration=All
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Reply to this email directly or view it on GitHub
https://github.com/kamsar/Unicorn/issues/105#issuecomment-197966273
It is indeed! Thanks Kam.
3.1.5 will have sync all available with a single click :grinning:
Would that be in the right order based on dependencies?
Absolutely. Dependencies are resolved for all syncs.
On Mon, Mar 21, 2016 at 7:29 PM Thomas Eldblom notifications@github.com
wrote:
Would that be in the right order based on dependencies?
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https://github.com/kamsar/Unicorn/issues/105#issuecomment-199592123
3.1.5 contains a sync all button with the URL mentioned above, as well as the maxConcurrency setting.
| gharchive/issue | 2016-01-27T04:48:24 | 2025-04-01T06:44:40.130904 | {
"authors": [
"Eldblom",
"demisx",
"kamsar"
],
"repo": "kamsar/Unicorn",
"url": "https://github.com/kamsar/Unicorn/issues/105",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
1161931101 | New endpoint for dataset-download-options
Hi @kapadia, I have a use case where I need to be able to identify dataset download options (products) without knowing entity IDs. This isn't possible with the download-options endpoint used by api.download_options because it returns nothing if the entity ID list is empty, so usgs would need a new function and payload dataset_download_options that uses the dataset-download-options endpoint.
I'm happy to add those functions and make a PR if you think it's worth including in usgs. Let me know what you think!
@aazuspan - happy to take further contributions from you :) I believe that end point used to be implemented in an old version. Changes to the USGS API necessitated a re-write of this library, and that end point was left off in the process.
Great, I'll make a PR!
| gharchive/issue | 2022-03-07T21:13:56 | 2025-04-01T06:44:40.167596 | {
"authors": [
"aazuspan",
"kapadia"
],
"repo": "kapadia/usgs",
"url": "https://github.com/kapadia/usgs/issues/64",
"license": "isc",
"license_type": "permissive",
"license_source": "bigquery"
} |
2557951754 | Browser managed by organisation is crashing
Hi Team,
I am trying to automate Ui tests using karate on browsers managed by our organization. When I execute the test, Chrome browser opens but no page loads and could see the browser is crashed.
I have even set the http proxy in driver configuration.
I am getting error as below
4j.AssertionFailedError: driver config / start failed: failed to get reply for: [id: 4, sessionId: 2600608260560A0C50727E58FBEF7D3C, method: page.enable]
it is possible that there are security restrictions in your org. to reopen, please follow this process: https://github.com/karatelabs/karate/wiki/How-to-Submit-an-Issue
I feel the best way for you to proceed is to troubleshoot this at your end or consider using Docker
| gharchive/issue | 2024-10-01T01:07:44 | 2025-04-01T06:44:40.179187 | {
"authors": [
"Tagorekrn",
"ptrthomas"
],
"repo": "karatelabs/karate",
"url": "https://github.com/karatelabs/karate/issues/2611",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
644208935 | Error wrapping 3D keypoints, bounding boxes and camera intrinsics together
I get an error in step 6 in the pre processing scripts section - Wrapping 3D keypoints, bounding boxes and camera intrinsics together:
(other than the warning of 'camera 54138969 isn't present in S11/Directions-2)
Command:
python3 generate-labels-npy-multiview.py ../../../data/human36m/ ../../../data/human36m/extra/una-dinosauria-data/ ../../../data/human36m/extra/bboxes-Human36M-GT.npy
Error:
Traceback (most recent call last):
File "generate-labels-npy-multiview.py", line 58, in
cameras_params = h5py.File(os.path.join(una_dinosauria_root, 'cameras.h5'), 'r')
File "/home/jamal/.local/lib/python3.6/site-packages/h5py/_hl/files.py", line 408, in init
swmr=swmr)
File "/home/jamal/.local/lib/python3.6/site-packages/h5py/_hl/files.py", line 173, in make_fid
fid = h5f.open(name, flags, fapl=fapl)
File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
File "h5py/h5f.pyx", line 88, in h5py.h5f.open
OSError: Unable to open file (unable to open file: name = '../../../data/human36m/extra/una-dinosauria-data/cameras.h5', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0)
Make sure you've extracted 'h36m.zip' at a previous step correctly so that ../../../data/human36m/extra/una-dinosauria-data/cameras.h5 exists.
Thats right. It was in a subfolder 'H36M' that was created when extracted.
Thanks
| gharchive/issue | 2020-06-23T23:22:23 | 2025-04-01T06:44:40.184131 | {
"authors": [
"jamalknight",
"shrubb"
],
"repo": "karfly/learnable-triangulation-pytorch",
"url": "https://github.com/karfly/learnable-triangulation-pytorch/issues/87",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
1448082099 | Parse timestamp cookies for SCHEDULED and DEADLINE
Fix #15 completely.
Related: #50
This PR also follows setuptools_scm v7.0.0 to drop Python 3.6 support, since orgparse requires setuptools_scm.
Update: Python 3.6 support is already dropped in a later commit (0041aad535836b5faf540205c8c68d5e42b52e19).
I've slightly modify tox.ini in this PR to pass the tests (see 6426a6aee5fca36296fba874cdf8309331ec9542). Please let me know if I should open a separate PR for those modifications.
Just pinging this PR, as it's been 1.5 months since it was initially submitted.
released to pypi as 0.3.2 !
Thanks! I just tested the new version on PyPI and verified the fix.
| gharchive/pull-request | 2022-11-14T13:32:22 | 2025-04-01T06:44:40.195217 | {
"authors": [
"j3soon",
"karlicoss"
],
"repo": "karlicoss/orgparse",
"url": "https://github.com/karlicoss/orgparse/pull/60",
"license": "BSD-2-Clause",
"license_type": "permissive",
"license_source": "github-api"
} |
1795079100 | 🛑 Habilitación is down
In 82bb066, Habilitación (https://catalogo-vpfe-hab.dian.gov.co/User/Login) was down:
HTTP code: 0
Response time: 0 ms
Resolved: Habilitación is back up in e8965da.
| gharchive/issue | 2023-07-08T19:38:58 | 2025-04-01T06:44:40.197769 | {
"authors": [
"karlos528"
],
"repo": "karlos528/fe",
"url": "https://github.com/karlos528/fe/issues/325",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
597185018 | Not finding my usb on HassOS 3.12
Hi,
I'm a total noob in both hassio and its addons.
I was very enthusiastic when I found this project, really looking forward to getting it to work. Yesterday I got my CKOZ 00/14 stick. Included it in the Eaton MRF and got it included in my setup. I went on to plug it into my rpi that is running HassOS 3.12, the USB lights up green and I see the little red light flickering when I turn on or off my devices.
The problem I'm facing is that I cant get the xcomfortd executable to run, most likely because it can't find my USB stick. I can't see it in the list of hardware:
The pi is definitely seeing the usb though, I'm just not able to communicate with it(?):
After creating the executable, adding the packages needed and running xcomfortd I'm getting this:
Please help me. What am I doing wrong?
I made some progress so this can be closed, decided to reinstall hassio on raspbian instead.
You are in luck, I'm working on a newer version of this code, which should be more stable and be more flexible. Another user is working on a hassio addon, which should make this much more user friendly as well. I can ping you when it's released to the public (mere days away now).
That is amazing news, yes please let me know. Looking forward to it!
@karloygard Any chance you will support heating sensors and/or the room controller touch in the new version? So that it will be possible turn on/off floor heating based on a temp read a sensor either in the room controller touch or a floor sensor?
And by the way, actually got it working after some fiddling around. So it's not that user unfriendly!
@karloygard Any chance you will support heating sensors and/or the room controller touch in the new version? So that it will be possible turn on/off floor heating based on a temp read a sensor either in the room controller touch or a floor sensor?
Might be possible with some assistance from you. Which devices do you have, and how have you configured them?
@karloygard
I have a few room controller touch devices, they have in built sensors in the devices, mine have attached an external sensor called pt1000 that monitors the temp of the actual floor (not the room).
These devices control heating actuators that turn on/off the floor heating in my bathrooms and hallways.
In addition to this i have something that came out before the room controller touch called temperature sensor, which is a device that is similar to the stand alone pt1000(i guess). It monitors and reports the temp in the floor so that it can send signals to the heating actuators to turn on/off.
My system is programmed using the ckoz 00/13, using the Eaton MRF software.
You can find my email adr in my profile page if you would like more details or want me to test something, I will happily contribute with whatever I can.
Check out https://github.com/karloygard/hassio-addons. Open up Home Assistant, go to Supervisor -> Add-On Store and add a new repository with that url.
If you send me the datapoints file mentioned in the documentation for the addon, I can try to make sure that your devices will work with this code.
Hi,
I have added a few of my varmekabler(!) and stuff here and exported the datapoints file from the usb stick.
Will try to get the add-on working today. Cool, thanks!
Geir
On 11 Apr 2020, 11:39 +0200, Karl Anders Øygard notifications@github.com, wrote:
Check out https://github.com/karloygard/hassio-addons. Open up Home Assistant, go to Supervisor -> Add-On Store and add a new repository with that url.
If you send me the datapoints file mentioned in the documentation for the addon, I can try to make sure that your devices will work with this code.
—
You are receiving this because you modified the open/close state.
Reply to this email directly, view it on GitHub, or unsubscribe.
1 bakdør utelys 5709360 16 0 0 0 #000#000#000#000#0#000#000#005#000#
2 1.etg sov 4 5740117 17 0 0 0 #000#000#000#000#0#000#000#006#000#
3 1.etg sov 3 5734031 17 0 0 0 #000#000#000#000#0#000#000#006#000#
4 1.etg sov 2 5740097 17 0 0 0 #000#000#000#000#0#000#000#006#000#
5 1.etg sov.1 5733990 17 0 0 0 #000#000#000#000#0#000#000#006#000#
6 1.etg bad speil 5736891 17 0 0 0 #000#000#000#000#0#000#000#006#000#
7 1.etg bad tak 5736925 17 0 0 0 #000#000#000#000#0#000#000#006#000#
8 1.etg stor gang 5734000 17 0 0 0 #000#000#000#000#0#000#000#006#000#
9 utelys hoveddør 5727252 16 0 0 0 #000#000#000#000#0#000#000#005#000#
10 1.etg tv stue 5733992 17 0 0 0 #000#000#000#000#0#000#000#006#000#
11 1.etg liten gang 5734068 17 0 0 0 #000#000#000#000#0#000#000#006#000#
12 1.etg kjøkken spotter 5734274 17 0 0 0 #000#000#000#000#0#000#000#006#000#
13 1.etg stue lampe spi 5741956 17 0 0 0 #000#000#000#000#0#000#000#006#000#
14 utelys terrasse 5733605 16 0 0 0 #000#000#000#000#0#000#000#005#000#
16 1.etg bad vk 5727387 16 0 0 0 #000#000#000#000#0#000#000#005#000#
20 1.etg dusj/bad vk 5727267 16 0 0 0 #000#000#000#000#0#000#000#005#000#
22 1.etg liten gang vk 5733608 16 0 0 0 #000#000#000#000#0#000#000#005#000#
24 1.etg stor gang vk 5733583 16 0 0 0 #000#000#000#000#0#000#000#005#000#
15 1.etg bad temp (Kanal B) 5881271 23 1 1 1 #000#000#000#000#0#000#000#006#000#
17 1.etg dusj/bad (ekstern Sensor (PT1000)) 6784078 78 6 1 1 #000#000#000#000#0#000#000#001#000#
18 1.etg dusj/bad (Touch-sensor A) 6784078 78 4 1 1 #000#000#000#000#0#000#000#001#000#
19 1.etg dusj/bad (Touch-sensor B) 6784078 78 5 1 1 #000#000#000#000#0#000#000#001#000#
21 1.etg liten gang temp (Kanal A) 5881353 23 0 1 1 #000#000#000#000#0#000#000#006#000#
23 1.etg stor gang temp (Kanal B) 5881341 23 1 1 1 #000#000#000#000#0#000#000#006#000#
Just replied to the email, guess we should move this discussion to the right place.
| gharchive/issue | 2020-04-09T10:30:26 | 2025-04-01T06:44:40.213411 | {
"authors": [
"geeewizzz",
"karloygard"
],
"repo": "karloygard/xcomfortd",
"url": "https://github.com/karloygard/xcomfortd/issues/9",
"license": "bsd-3-clause",
"license_type": "permissive",
"license_source": "bigquery"
} |
173959272 | Error occurred when building node - bin/karma start karma.conf.js --no-auto-watch --single-run --no-color
Steps to reproduce the behaviour
1. I have the node version of v0.12.0
2. Karma version is 0.13.19
3. npm version is 2.5.1
when building the build fails saying
node node_modules/karma/bin/karma start karma.conf.js --no-auto-watch --single-run --no-color
[ERROR] Return code: 1
[ERROR] Command output:
[ERROR] | ...(1513 lines of output hidden)...
[ERROR] | PhantomJS 2.1.1 (Windows 8 0.0.0): Executed 107 of 122 (17 FAILED) (skipped 1) (0 secs / 1.221 secs)
[ERROR] | PhantomJS 2.1.1 (Windows 8 0.0.0): Executed 108 of 122 (17 FAILED) (skipped 1) (0 secs / 1.268 secs)
[ERROR] | PhantomJS 2.1.1 (Windows 8 0.0.0): Executed 109 of 122 (17 FAILED) (skipped 1) (0 secs / 1.278 secs)
[ERROR] | PhantomJS 2.1.1 (Windows 8 0.0.0): Executed 110 of 122 (17 FAILED) (skipped 1) (0 secs / 1.286 secs)
[ERROR] | PhantomJS 2.1.1 (Windows 8 0.0.0): Executed 111 of 122 (17 FAILED) (skipped 1) (0 secs / 1.294 secs)
[ERROR] | PhantomJS 2.1.1 (Windows 8 0.0.0): Executed 112 of 122 (17 FAILED) (skipped 1) (0 secs / 1.302 secs)
[ERROR] | PhantomJS 2.1.1 (Windows 8 0.0.0): Executed 113 of 122 (17 FAILED) (skipped 1) (0 secs / 1.309 secs)
[ERROR] | PhantomJS 2.1.1 (Windows 8 0.0.0): Executed 114 of 122 (17 FAILED) (skipped 1) (0 secs / 1.318 secs)
[ERROR] | PhantomJS 2.1.1 (Windows 8 0.0.0): Executed 115 of 122 (17 FAILED) (skipped 1) (0 secs / 1.325 secs)
[ERROR] | PhantomJS 2.1.1 (Windows 8 0.0.0): Executed 115 of 122 (17 FAILED) (skipped 7) (0.932 secs / 1.325 secs)
Any suggestions why this is happening ?
What is the behavior that you are reporting here?
Is it the failure of the script from the test failures? If so, that is expected behavior by Karma. Otherwise, more details should probably be given, as there is not enough to adequately address what is being attempted to be asked, and guessing isn't a good approach :) .
No feedback in a year. Closing.
| gharchive/issue | 2016-08-30T08:29:43 | 2025-04-01T06:44:40.230135 | {
"authors": [
"EzraBrooks",
"SManorathna",
"wesleycho"
],
"repo": "karma-runner/karma",
"url": "https://github.com/karma-runner/karma/issues/2338",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
159702723 | fix(launcher): send sigkill on timeout when force killing
@dignifiedquire This is in response to bug we are seeing where karma hangs because it is unable to force kill chrome, possibly https://github.com/karma-runner/karma/issues/24#issuecomment-216249098
I signed it!
Thanks, can you change the commit message to befix(launcher: instead of bug please?
@dignifiedquire, i updated the commit message, thanks.
@dignifiedquire Any ETA on this one landing?
| gharchive/pull-request | 2016-06-10T19:13:20 | 2025-04-01T06:44:40.232711 | {
"authors": [
"dignifiedquire",
"kakadiya91",
"modulesio"
],
"repo": "karma-runner/karma",
"url": "https://github.com/karma-runner/karma/pull/2169",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
614448518 | Refactoring code is done
Hi Karthik,
Please review the code and approve.
Thanks
Likhil.
@Likhil Test the code and confirm.
| gharchive/pull-request | 2020-05-08T01:53:29 | 2025-04-01T06:44:40.310740 | {
"authors": [
"Likhil",
"karthikreddykuna"
],
"repo": "karthikreddykuna/DXC-Industrialized-AI-Starter",
"url": "https://github.com/karthikreddykuna/DXC-Industrialized-AI-Starter/pull/4",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2480565145 | Make it compatible with Bun.
Fast server, slow runtime. Doesn't that mismatch? Basically, uWS is the only package that complaining. But otherwise, it'd be damn good to run hyper on bun.
ahh, it was requested already.
| gharchive/issue | 2024-08-22T11:38:14 | 2025-04-01T06:44:40.318542 | {
"authors": [
"mr-moon"
],
"repo": "kartikk221/hyper-express",
"url": "https://github.com/kartikk221/hyper-express/issues/296",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
442538997 | Enable file based memory backend
Enable file based memory backing at /dev/shm on the host which will be used primarily (as of this writing) to be virtio-fs cache.
Hi,
Currently, I can only start kata container with virtiofs by setting "enable_hugepages = true" in /etc/kata-containers/configuration.toml. Otherwise, kata will fail to create container using virtiofs.
Do you think it's the same issue here?
Yes @renzhengeek - that’s what Ganesh is working on resolving.
| gharchive/issue | 2019-05-10T04:59:17 | 2025-04-01T06:44:40.374674 | {
"authors": [
"egernst",
"ganeshmaharaj",
"renzhengeek"
],
"repo": "kata-containers/runtime",
"url": "https://github.com/kata-containers/runtime/issues/1656",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
361593680 | netmon: Add signals handler support
This PR factorizes the signal handling code through a new
runtime package as a first step.
And the second commit relies on this new package in order
to setup the signal handling of the network monitor.
Fixes #718
LGTM
Thanks @sboeuf !
| gharchive/pull-request | 2018-09-19T06:16:08 | 2025-04-01T06:44:40.376228 | {
"authors": [
"WeiZhang555",
"jodh-intel",
"sboeuf"
],
"repo": "kata-containers/runtime",
"url": "https://github.com/kata-containers/runtime/pull/755",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
1658483967 | destop verssion review
good job you did well on this project
✔️ GOOD JOB
[x] please kindly align your content on the about section yours is at center kindly align then at the start on "the language part"
[x] also align the drop down arrows to be same as figma design
[x] In your form kindly change the color of the place holder for "write your message here"
Thank you for your Recommendations, all effected
| gharchive/issue | 2023-04-07T07:37:07 | 2025-04-01T06:44:40.405458 | {
"authors": [
"katfogy",
"techmoves"
],
"repo": "katfogy/setup-and-mobile-first",
"url": "https://github.com/katfogy/setup-and-mobile-first/issues/16",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
540033309 | Setting the bar height after creation
Hi,
I know that the bar height can be set when creating a new Waveform object, but you can't adjust the height of the bars afterward.
I was wondering if it was it's possible to implement a new function, setBarHeight()?
It might work similar to the zoom() function, just with adjusting the bar heights then redrawing the waveform?
use wavesurer.setHeight(height) to set the height of the waveform. If it uses bars, those will be set as well.
https://wfplayer.js.org/
Here's an example of what I was more meaning. If you drag the Wave Scale range input at the bottom of the options given, it'll increase or decreaes the bar heights without changing the height of the canvas that holds it.
I was wondering if it was it's possible to implement a new function, setBarHeight()?
pull requests are welcome.
| gharchive/issue | 2019-12-19T02:19:28 | 2025-04-01T06:44:40.411933 | {
"authors": [
"RobTallGuy",
"thijstriemstra"
],
"repo": "katspaugh/wavesurfer.js",
"url": "https://github.com/katspaugh/wavesurfer.js/issues/1830",
"license": "BSD-3-Clause",
"license_type": "permissive",
"license_source": "github-api"
} |
675557291 | Add a display option that disregards file structure
We we run jest from the command line, it displays the tests as they are logically structured, not as they are distributed on disk. I wish JTE had a display option similar to that.
I don't want to see a tree that reflects file organization. I want to see a tree composed of describe and it/test blocks, without any visual indication of the file structure.
Came here to say the same thing. I'm looking at the code now and it seems like a pretty straightforward thing to add, so I'll try to get a PR up shortly.
Hi @tomprogers / @dannymcgee,
Question for you both: can you look at the following page on the host extension site and tell me if it meets your needs?
https://github.com/hbenl/vscode-test-explorer
The setting testExplorer.mergeSuites
@rossknudsen Unfortunately not for me. I do have that option enabled and I can see why it's useful, but the pain point I'm trying to address is that my test files are all pretty deeply nested inside my workspace directory structure, so I need to expand 5 or 6 nodes in the UI to see my first actual test suite, which leads to a lot of wasted horizontal space in the sidebar and a lot of clicking to see anything. If you take a look at the screenshots in my PR, the issue I'm having should be more clear.
nah, that's fine. I just thought I'd check before merging. I'll have another look later on, but the initial review looked good.
Heya! Thanks for following up.
I think I'm with danny on this. I do use the mergeSuites setting, but it's still not enough. As an example, I'm working on an Electron app, which adds another layer of folders to accommodate the main and renderer threads. By the time an actual describe appears, it's already indented like 4 levels. When I run jest, I don't see any of that wrapping FS structure.
| gharchive/issue | 2020-08-08T17:10:35 | 2025-04-01T06:44:40.432229 | {
"authors": [
"dannymcgee",
"rossknudsen",
"tomprogers"
],
"repo": "kavod-io/vscode-jest-test-adapter",
"url": "https://github.com/kavod-io/vscode-jest-test-adapter/issues/79",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
624185086 | いいところ診断の結果に優しさを追加したい
以下の結果を追加したい
'{userName}のいいところは優しさです。あなたの優しい雰囲気や立ち振る舞いに多くの人が癒やされています。'
これから対応します。
| gharchive/issue | 2020-05-25T09:50:10 | 2025-04-01T06:44:40.433358 | {
"authors": [
"kawakami-takayuki"
],
"repo": "kawakami-takayuki/assessment",
"url": "https://github.com/kawakami-takayuki/assessment/issues/1",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
193461804 | Fix for missing metric_key attribute in Totals
Fixes #70 Fixed the getattr expression for operations so that it can handle a missing metric_key such as in the case of Totals
Coverage increased (+0.09%) to 97.645% when pulling ebf2d97d1bb81683c5c5bb45dec0d27a32a3396b on totals_fix into 40cec66443ea494e559f68abe6a389b401acf562 on master.
| gharchive/pull-request | 2016-12-05T10:34:00 | 2025-04-01T06:44:40.442412 | {
"authors": [
"coveralls",
"twheys"
],
"repo": "kayak/fireant",
"url": "https://github.com/kayak/fireant/pull/71",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
265948319 | TASK-1161 Store sub events in database
Now stores sub events in database and generates an ID for the sub event.
Does not yet check to avoid storing duplicate events or reprocessing
successful sub events.
Removed the id field from StatusEvent (now in StatusEventWithID).
Remove a not particularly helpful level of indirection by marking event
processing state in the storage system with a direct storage call,
rather than via an iterator then a queue then the storage system
Merging per @sychan
| gharchive/pull-request | 2017-10-16T23:36:50 | 2025-04-01T06:44:40.453100 | {
"authors": [
"MrCreosote"
],
"repo": "kbase/KBaseSearchEngine",
"url": "https://github.com/kbase/KBaseSearchEngine/pull/48",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
111393784 | Does 'Turbolinks Support' section in the documentation require updating?
I was looking at the documentation about the forward/back button in the 'Turbolinks Support' and I was trying to ensure my code is executed in this same manner for my project. I added the following code (which was taken from the documentation) to my application js:
$(document).on('page:restore', function(){
// Manually evaluates the appended script tag.
Paloma.executeHook();
});
This would not work for me. I had to modify it as below:
$(document).on('page:restore', function(){
// Manually evaluates the appended script tag.
Paloma.executeHook();
Paloma.engine.start();
});
Is what I've done correct and the documentation just needs updating? Or have I missed something else?
This might be the case since Paloma.start() is no longer called automatically and needs to always be explicitly called.
| gharchive/issue | 2015-10-14T13:05:22 | 2025-04-01T06:44:40.478262 | {
"authors": [
"brendon",
"sb89"
],
"repo": "kbparagua/paloma",
"url": "https://github.com/kbparagua/paloma/issues/82",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
1528558908 | CRD convert error: no openapi schema found
Bug Report
Please answer these questions before submitting your issue. Thanks!
1. Minimal reproduce step (Required)
unzip the following file and put it in /oam.yaml
oam.yaml.zip
run kcl-openapi generate model --crd --skip-validation -f Desktop/oam.yaml
2. What did you expect to see? (Required)
KCL files generated
3. What did you see instead (Required)
error:
could not generate swagger spec: Desktop/oam.yaml, err: no openapi schema found in the crd file. Please check following fields: spec.Validation.OpenAPIV3Schema, spec.Versions.0.Schema
4. What is your KusionStack components version? (Required)
This bug also extends to CRD from spec V1. It also seems to be that this condition is triggered for all CRD model generation.
eg. crd for external-secrets operator
kcl-openapi generate model --crd \
-f <(curl -sS "https://raw.githubusercontent.com/external-secrets/external-secrets/main/config/crds/bases/external-secrets.io_externalsecrets.yaml") \
--skip-validation
could not generate swagger spec: /dev/fd/11, err: no openapi schema found in the crd file. Please check following fields: spec.Validation.OpenAPIV3Schema, spec.Versions.0.Schema
| gharchive/issue | 2023-01-11T07:27:37 | 2025-04-01T06:44:40.491704 | {
"authors": [
"amyXia1994",
"prahaladramji"
],
"repo": "kcl-lang/kcl-openapi",
"url": "https://github.com/kcl-lang/kcl-openapi/issues/31",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
1374707973 | :sparkles: Add cluster-wide resources support to the resource reconciler
Summary
This PR enables the Resource reconciler to label cluster-wide resources with the available synctargets for a workspace with the desired state of "pending".
Currently, the list of allowed cluster-wide resources is hardcoded to "persistentvolumes" in preparation for upcoming storage work.
Related issue(s)
Fixes https://github.com/kcp-dev/kcp/issues/1890
hack/verify-go-versions.sh
[54](https://prow.ci.openshift.org/view/gs/origin-ci-test/pr-logs/pull/kcp-dev_kcp/1998/pull-ci-kcp-dev-kcp-main-images/1572606912959090688#1:build-log.txt%3A54)
go build -ldflags="-X k8s.io/client-go/pkg/version.gitCommit=bf76c43a -X k8s.io/client-go/pkg/version.gitTreeState=clean -X k8s.io/client-go/pkg/version.gitVersion=v1.24.3+kcp-v0.8.0-136-gbf76c43a7d64c0 -X k8s.io/client-go/pkg/version.gitMajor=1 -X k8s.io/client-go/pkg/version.gitMinor=24 -X k8s.io/client-go/pkg/version.buildDate=2022-09-21T15:30:04Z -X k8s.io/component-base/version.gitCommit=bf76c43a -X k8s.io/component-base/version.gitTreeState=clean -X k8s.io/component-base/version.gitVersion=v1.24.3+kcp-v0.8.0-136-gbf76c43a7d64c0 -X k8s.io/component-base/version.gitMajor=1 -X k8s.io/component-base/version.gitMinor=24 -X k8s.io/component-base/version.buildDate=2022-09-21T15:30:04Z" -o bin ./cmd/...
[55](https://prow.ci.openshift.org/view/gs/origin-ci-test/pr-logs/pull/kcp-dev_kcp/1998/pull-ci-kcp-dev-kcp-main-images/1572606912959090688#1:build-log.txt%3A55)
/usr/local/go/pkg/tool/linux_amd64/link: signal: killed
[56](https://prow.ci.openshift.org/view/gs/origin-ci-test/pr-logs/pull/kcp-dev_kcp/1998/pull-ci-kcp-dev-kcp-main-images/1572606912959090688#1:build-log.txt%3A56)
make: *** [Makefile:92: build] Error 1
/retest
/hold adding missing functionality to make this PR complete
/unhold
| gharchive/pull-request | 2022-09-15T15:24:09 | 2025-04-01T06:44:40.494436 | {
"authors": [
"jmprusi"
],
"repo": "kcp-dev/kcp",
"url": "https://github.com/kcp-dev/kcp/pull/1998",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
1479983741 | WIP 🌱 Syncer: Cleanup of DNS-related resources
Summary
Cleanup of DNS-related resources when no more downstream namespaces exist for a given upstream workspace.
Disclaimer: still missing tests + e2e tests.
Related issue(s)
Fixes #2358
Can we do this with actual garbage collection and owner refs?
I think yes. Namespaced dependents can have cluster-scoped owners (Namespaces in this case).
Not sure about how you would use garbage collection in the specific case.
Do you mean that every DNS-related resource for a given KCP workspace should have as many owner references as the number of downstream namespaces originating from the given KCP workspace ?
In order to do this, in the EnsureDNSUpAndReady function we would need to:
check that every DNS-related resource has the namespace of the currently-synced resource in its owner refs,
update every DNS-related resource if necessary to add the namespace owner ref.
This would be required during every resource sync. I'd rather do more work during cleanup, and keep the resource syncing main reconciliation loop as quick as possible.
Then I assume that the DNS-related resources deletion would be triggered by cascading deletion when all the namespaces related to the given KCP workspace would be deleted. However we wouldn't control when this cleaning would happen, which would make it hard to synchronize this cleaning with the on-the-fly creation of those DNS-related resources when they are necessary (in the EnsureDNSUpAndReady function). Such a synchronization is for now still missing from this PR, but might be necessary and should be thought of.
Last point: when we start implementing the network isolation through NetworkPolicies on the physical cluster, we will need this concept of KCP tenant on downstream (== a originating KCP workspace + related SyncTarget). That seemed quite natural to use it here as well.
So, unless I'm missing something, applying the standard Kubernetes garbage collection and owner refs mechanism here is not as simple as it may seem, and may bring more slowness and complexity.
Let me finally just point to a previous PR comment answer to remind that we are not in the standard Kubernetes case, because everything downstream is finally driven by the individual resources synced from upstream.
@davidfestal are you still interested in moving forward with this?
/hold
on hold until PR https://github.com/kcp-dev/kcp/pull/2675 is merged.
/hold
Wait until PRs #2675 and #2946 are merged.
/close
TMC
| gharchive/pull-request | 2022-12-06T19:27:55 | 2025-04-01T06:44:40.501502 | {
"authors": [
"davidfestal",
"mjudeikis",
"ncdc"
],
"repo": "kcp-dev/kcp",
"url": "https://github.com/kcp-dev/kcp/pull/2455",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
1530268725 | 🐛 IndexByLogicalClusterPathAndName should return clusterpath and name
Signed-off-by: Jian Qiu jqiu@redhat.com
Summary
I think IndexByLogicalClusterPathAndName should return clusterPath+Name by default?
Related issue(s)
Fixes #
The existing code effectively seemed wrong. But are we aware of something broken by this erroneous code ?
If yes, shouldn't we add a test case (unit test or e2e) that corresponds to this fix ?
Nice finding.
/lgtm
/approve
| gharchive/pull-request | 2023-01-12T08:00:32 | 2025-04-01T06:44:40.504593 | {
"authors": [
"davidfestal",
"qiujian16",
"sttts"
],
"repo": "kcp-dev/kcp",
"url": "https://github.com/kcp-dev/kcp/pull/2606",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
565329709 | Update library to compile on upcoming 0.14.0 PS release
For context, see https://discourse.purescript.org/t/updating-the-ecosystem-for-upcoming-0-14-0-release/1144
remind me to look at this, since i'm not an admin of this repo
| gharchive/pull-request | 2020-02-14T13:34:02 | 2025-04-01T06:44:40.506013 | {
"authors": [
"JordanMartinez",
"justinwoo"
],
"repo": "kcsongor/purescript-record-format",
"url": "https://github.com/kcsongor/purescript-record-format/pull/7",
"license": "BSD-3-Clause",
"license_type": "permissive",
"license_source": "github-api"
} |
801844483 | 🛑 营销平台API is down
In 3d6cde8, 营销平台API (https://api.dgshare.com) was down:
HTTP code: 502
Response time: 3258 ms
Resolved: 上海购物API is back up in 732cfb9.
| gharchive/issue | 2021-02-05T04:57:47 | 2025-04-01T06:44:40.513080 | {
"authors": [
"amorist"
],
"repo": "kdcer/upptime",
"url": "https://github.com/kdcer/upptime/issues/91",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
217728593 | can I use this to transpose a musicxml file
Trying to create an app for myself (browser-based) that will show musicxml docs (rendered in JS) in different keys (transpose).
If I can't do it with this gem do you know a tool in ruby or JS that can transpose musicxml?
Thanks
Yeah you could use this. It might be easier to check out something like vexflow (https://github.com/0xfe/vexflow).
| gharchive/issue | 2017-03-29T00:09:43 | 2025-04-01T06:44:40.514713 | {
"authors": [
"benlieb",
"kddeisz"
],
"repo": "kddeisz/musicxml",
"url": "https://github.com/kddeisz/musicxml/issues/9",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
195136884 | Zoom to current location
Query current device location and zoom to that point.
Done in cac39a7f65d570da19705bf46108e8a9cb72daab
| gharchive/issue | 2016-12-13T01:42:08 | 2025-04-01T06:44:40.515740 | {
"authors": [
"kdeloach"
],
"repo": "kdeloach/septa-viz",
"url": "https://github.com/kdeloach/septa-viz/issues/4",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
2730754264 | MicroPython for ESP32
I know this is a long shot, but by any chance have you made the MicroPython to use this on an ESP32? I just come across this repository when searching for ways to communicate with my Amana Furnace w/ Comfortnet. So far, I've been able to get data from the diagnostic port using an ESP32 and RS-485 module using ESPHome. I'm was hoping to get some information into Home-Assistant, but I way beyond capabilities at this point. I can see usable information when I manually go into the comfortnet settings in the thermostats and select some of the status options.
[11:14:40][D][uart:136]: 0x01 | 0xFF | 0x02 | 0x02 | 0x0200 | 0xA5 | 0x41 | 0xA0 | 17 | 06 00 00 09 10 0C 03 3F 57 02 78 E9 BE 12 A1 29 1D | .......?W.x....). | 0x3A99
[11:14:41][D][uart:089]: Dest | Src | Subnet | Meth | Params | SrcNode | MsgType | PktNum | Len | Payload HEX | Payload ASCII | Checksum
[11:14:41][D][uart:136]: 0x01 | 0xFF | 0x02 | 0x02 | 0x0200 | 0x02 | 0xC1 | 0x20 | 45 | 01 05 00 00 00 F0 B6 C5 D5 53 54 41 54 55 53 B7 C2 E2 4D 4F 44 45 20 20 35 30 25 20 48 45 41 54 20 C3 C2 E2 43 46 4D 20 20 33 32 30 C3 | .........STATUS...MODE 50% HEAT ...CFM
I never finished this library. Originally what I had intended to do was to connect an ESP32 just as you have and have it send the packet data to a PC where this library would have been running.
The biggest issue with ComfortNet is while it was a standard it was not written in a manner that made manufacturers adhere to the standard. A lot of the manufacturers deviated from the original specification and added to it and those additions are specific to the make and model of furnace. This is something that was done almost across the board across all manufacturers. That is the reason why you cannot use a Rheem Communicating thermostat on an Amana furnace even tho both furnaces use ComfortNet. I didn't want to have to invest in a 600 dollar thermostat for Rheem in order to figure out what those custom commands are. That is why I didn't continue with the development of this library,...
I didn't wrote the library to run on the ESP32 because at the time the ESP32 didn't have enough memory to be able to do it properly. the addition of the PSRAM didn't happen until later.
Since technology has improved with the ESP32 I could start writing a version of this library that would run on MicroPython. There would be enough memory available to do that. It would actually pair together quite well with the GUI framework binding that I have written that runs on the ESP32 with MicroPython. This would be nice because a user could use an ESP32-S3n16r8 with a 7" RGB or a 5" I8080 touch panel and they could make a thermostat with full blown touch UI. This would be very easy to make.
If you are willing to spend the time to debug/test and data log I am willing to start over and write it so it will run on MicroPython.
Here is a link to that GUI Framework binding if you wanted to look at it.
https://github.com/lvgl-micropython/lvgl_micropython
| gharchive/issue | 2024-12-10T17:36:58 | 2025-04-01T06:44:40.561974 | {
"authors": [
"kdschlosser",
"smurf12345"
],
"repo": "kdschlosser/ClimateTalk",
"url": "https://github.com/kdschlosser/ClimateTalk/issues/2",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
260942960 | Integrate Top Visited Blog posts onto website
Plugin is already part of the project, needs only to be added to the theme.
.depo
| gharchive/issue | 2017-09-27T11:40:49 | 2025-04-01T06:44:40.583114 | {
"authors": [
"kealsera"
],
"repo": "kealsera/rikki",
"url": "https://github.com/kealsera/rikki/issues/87",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
284471584 | Handle as User error
}},"exceptionId":"docker-bbe20a94b9c309ce2f3c960f089b9ca0","exception":{"class":"Keboola\Syrup\Exception\ApplicationException","message":"Application error: 147946154733.dkr.ecr.us-east-1.amazonaws.com/developer-portal-v2/keboola.ex-google-analytics-v4:2.2.3 container '341349562-341349546.341349563--0-keboola-ex-google-analytics-v4' failed: (2) [2017-12-25 22:25:31] ex-google-analytics.ERROR: <meta name=viewport ... temporary error and could not complete your request.Please try again in 30 seconds. That\u2019s all we know.</ins> [] []","code":0,"attachment":"https://connection.keboola.com/admin/utils/logs?file=2017/12/25/22/2017-12-25-22-25-32-5a416cccf2054-exception"},"attachment":"https://connection.keboola.com/admin/utils/logs?file=2017/12/25/22/2017-12-25-22-25-33-5a416ccd02f69-log"}
https://keboola.slack.com/archives/C09U3R1J4/p1514237228000045https://keboola.slack.com/archives/C09U3R1J4/p1514237228000045
"output": "Running query 'mall cz + sk + pl + hu + hr + sl'",
| "errorOutput": "[2017-12-26 12:17:54] ex-google-analytics.ERROR: <meta name=viewport content="initial-scale=1, minimum-scale=1, width=device-width"> Error 502 (Server Error)!!1</title>
JJ, o tomto viem:
https://issuetracker.google.com/issues/69349753
Bohuzial v Googli na to seru. A deje sa to pravidelne len u tohto jedneho klienta pokial viem.
Retry to robi, ale nepomoze to. Malo by to pak ale hodit User Error.
| gharchive/issue | 2017-12-25T22:25:19 | 2025-04-01T06:44:40.592811 | {
"authors": [
"MiroCillik",
"odinuv"
],
"repo": "keboola/google-analytics-extractor",
"url": "https://github.com/keboola/google-analytics-extractor/issues/18",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
2334420243 | Allow CA dirs to be specified beyond /custom/ca/
https://github.com/kedacore/keda/pull/5859
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)
[X] README is updated with new configuration values (if applicable) learn more
[X] A PR is opened to update KEDA core (repo)
Fixes https://github.com/kedacore/keda/issues/5860
The helm chart will fail to deploy a working KEDA operator until https://github.com/kedacore/keda/pull/5859 is merged
Thanks!
| gharchive/pull-request | 2024-06-04T21:41:20 | 2025-04-01T06:44:40.599813 | {
"authors": [
"joelsmith",
"zroubalik"
],
"repo": "kedacore/charts",
"url": "https://github.com/kedacore/charts/pull/650",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2014964053 | Client-side GRPC load balancing
Proposal
Keda currently uses the pick_first load balancing policy for GRPC connections which is the grpc library default. This currently works in most setups because of default coredns configurations. However, if we're not using the default settings, Keda should perform client-side round-robin load balancing for grpc connections aswell.
Use-Case
Some Kubernetes environments customize the default DNS configurations; For example:
disabling the loadbalance CoreDNS plugin
and talking to a headless service
the above changes means DNS requests will always return the results in the same order and won't randomize the ordering, ex with 2 pods:
root@app-5877ff4bd9-p27mk:/# dig headless-svc.default.svc.cluster.local +short
10.1.3.215
10.1.3.210
In this case, Keda should round-robin load balance grpc connections... otherwise it's always going to talk to the same pod and not send any requests off to the second one; this is a simple 1-line config change built into the grpc library; and shouldn't affect existing setups.
Is this a feature you are interested in implementing yourself?
Yes
Anything else?
No response
I'd say that this is already done xD
| gharchive/issue | 2023-11-28T17:38:09 | 2025-04-01T06:44:40.603819 | {
"authors": [
"BojanZelic",
"JorTurFer"
],
"repo": "kedacore/keda",
"url": "https://github.com/kedacore/keda/issues/5224",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
895291712 | Pass deepCopy objects to the polling goroutines
Signed-off-by: Zbynek Roubalik zroubali@redhat.com
Pass deepCopy of ScaledObject/ScaledJob objects to the scaleLoop polling goroutines it's a precaution to not have global objects shared between threads.
It should potentially help with the issue, which occurs if there is a big number of scalers running. Sometimes there are periodic panics in the json Marshall code that appeared to be related to passing the scaler objects to the background go routines and causing race conditions between fetching and serializing in different goroutines.
Checklist
[x] Commits are signed with Developer Certificate of Origin (DCO - learn more)
[x] Changelog has been updated
Actually as I'm looking at this harder, do we want to copy them here or at the point we actually launch the goroutines?
Actually as I'm looking at this harder, do we want to copy them here or at the point we actually launch the goroutines?
https://github.com/kedacore/keda/blob/347e8975d5f7b7ccc8e2bfc15311c47fd267707d/pkg/scaling/scale_handler.go#L104-L105
I think the way this is now, both goroutines would get the same reference.
Yeah, you are right, that's much better spot. Let me change that.
| gharchive/pull-request | 2021-05-19T10:51:43 | 2025-04-01T06:44:40.607659 | {
"authors": [
"coderanger",
"zroubalik"
],
"repo": "kedacore/keda",
"url": "https://github.com/kedacore/keda/pull/1812",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
1291612731 | chore: bump-deps
Signed-off-by: Jorge Turrado jorge_turrado@hotmail.es
Checklist
[x] Commits are signed with Developer Certificate of Origin (DCO - learn more)
Relates to https://github.com/kedacore/keda/pull/3310
Relates to https://github.com/kedacore/keda/pull/3311
Relates to https://github.com/kedacore/keda/pull/3312
Relates to https://github.com/kedacore/keda/pull/3317
Relates to https://github.com/kedacore/keda/pull/3319
Relates to https://github.com/kedacore/keda/pull/3316
/run-e2e
Tagged the PRs that we have closed
| gharchive/pull-request | 2022-07-01T16:36:34 | 2025-04-01T06:44:40.611778 | {
"authors": [
"JorTurFer",
"tomkerkhove"
],
"repo": "kedacore/keda",
"url": "https://github.com/kedacore/keda/pull/3321",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2454303471 | [feat] Implement fee function
Implement function to calculate transaction fee:
https://github.com/keep-starknet-strange/raito/blob/4bf3aaba4d04f53255f32d022d3ee860ad20da8d/src/validation.cairo#L44
ZeroSync version:
https://github.com/ZeroSync/ZeroSync/blob/f1bd4736b0bac190ac48cbc8d5fcd92e2e1be7b9/src/transaction/transaction.cairo#L262
Hi, can I take this?
| gharchive/issue | 2024-08-07T20:35:30 | 2025-04-01T06:44:40.657477 | {
"authors": [
"maciejka",
"stevencartavia"
],
"repo": "keep-starknet-strange/raito",
"url": "https://github.com/keep-starknet-strange/raito/issues/39",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
2090303704 | Added X Threads Doc
Added Previously Published Threads on X.
However @oluwaseundotcom I think having a docs/ folder, with inside a x_threads.md file that lists tweets about unruggable can be a good idea!
However @oluwaseundotcom I think having a docs/ folder, with inside a x_threads.md file that lists tweets about unruggable can be a good idea!
yes please. docs/social/x/threads.md
| gharchive/pull-request | 2024-01-19T11:13:44 | 2025-04-01T06:44:40.659487 | {
"authors": [
"AbdelStark",
"enitrat",
"oluwaseundotcom"
],
"repo": "keep-starknet-strange/unruggable.meme",
"url": "https://github.com/keep-starknet-strange/unruggable.meme/pull/150",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
841725737 | Application pdf updated
Link to Issue
Description of changes
Screenshot(s) or GIF(s) of changes
@steffen12 tests are still failing btw
| gharchive/pull-request | 2021-03-26T08:43:15 | 2025-04-01T06:44:40.690347 | {
"authors": [
"crchong1",
"steffen12"
],
"repo": "keepid/keepid_client",
"url": "https://github.com/keepid/keepid_client/pull/290",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
577303024 | AU331 机器学习与知识发现 - IEEE.ICU
https://ieee.icu/#/courses/grade-3/AU331
上海交通大学 IEEE 试点班，一个充满了「神仙」课程的专业，本网站旨在记录这些课程的信息以及历届学生对其的评价
这门课和同期的AU332类似，都是属于老师讲的不错，然后任务量较多的类型。我认为值得好好学
| gharchive/issue | 2020-03-07T08:50:42 | 2025-04-01T06:44:40.702392 | {
"authors": [
"AlexanderKirei",
"ieee-icu"
],
"repo": "keithnull/ieee.icu",
"url": "https://github.com/keithnull/ieee.icu/issues/57",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
2353956511 | HentaiNexus: unable to fetch some thumbnails
Source information
HentaiNexus 1.4.10
Source language
English
Steps to reproduce
Open HentaiNexus and browse a bit
Expected behavior
Every title has a thumbnail
Actual behavior
A few titles appear without a thumbnail
Mihon/Tachiyomi version
TachiSY 1.10.5
Android version
Android 13
Other details
Looking at the webpages, the thumbnails are not in a .card-image img anymore, I think that the extension is actually fetching the first page of the title instead, but I'm not sure why the behavior is inconsistent when fetching.
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.
Oh sorry, I searched it a couple of days ago but only really had time to write the issue now. I'll close this issue and add the comment on the other issue.
Actually, searching is:issue is:open nexus still returns nothing, that's why I didn't see it, I should have searched the full name instead.
| gharchive/issue | 2024-06-14T19:25:44 | 2025-04-01T06:44:40.708573 | {
"authors": [
"MediocreLegion"
],
"repo": "keiyoushi/extensions-source",
"url": "https://github.com/keiyoushi/extensions-source/issues/3566",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2551151071 | Asura Scans 1.4.40 HTTP 503.
Source information
Asura Scans 1.4.40
Source language
English
Steps to reproduce
Visit Asura Scans Extension
Expected behavior
Should Fetch manhwas and chapter lists
Actual behavior
HTTP 503
Checking the website in webview redirects asuracomic.net to asurascans.com/$1
Error 503 Backend Fetch Failed.
Mihon/Tachiyomi version
0.16.5
Android version
13
Other details
This issue started with an error 404 and then progressed onto 503.
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.
Found existing Bug that has been reported a few minutes before.
| gharchive/issue | 2024-09-26T17:23:27 | 2025-04-01T06:44:40.715069 | {
"authors": [
"SantanuLayek"
],
"repo": "keiyoushi/extensions-source",
"url": "https://github.com/keiyoushi/extensions-source/issues/5244",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2129302506 | Make IP bind configurable
Some Home Assistant (OS) installations may have more than one interface assigned to them, e.g., when IoT devices are located in their own subnet (e.g., to prevent the smart meter from establishing a connection with some cloud services).
During the multicast listener's setup, one needs to explicitly specify the local address in that case. This change allows users with such a setup to use this addon as well.
The commit should be backwards compatible as far as I can see, but I don't consider myself an expert on Home Assistant. Feedback welcome. The value should be optional, i.e., an empty string is the default value. There might be a more elegant solution to this.
P.S.: This is basically the same change I had to use with the original SMA-EM project to receive any data from the meter.
I'm not convinced config.ini is being used by the non-legacy addon (sma-em-legacy)
It is completely removed from the dev version & at some point I'll copy the entire sma-em-dev to sma-em to sync them.
Please only make changes to the sma-em-dev folder.
@kellerza well I don't think that is the case either. Maybe as the expert you should clean up such old files from the directory? It was further not clear to me what the state of these various directories is; I modified what was used on my installation of Home Assistant.
Also, I'd suggest a more Git-ish workflow using separate branches (e.g., keeping the current sma-em on master, moving sma-em-dev to a dev branch and the -legacy to a new legacy branch. This helps reduce confusion around what files are used for what purpose and would further allow you to offer a "dev" repository for contributors to easily test changes.
I might reorganize my fork repository accordingly to test the -dev files and make changes accordingly.
Let's stick to the directories, as HASS OS expects certain files in the main branch.
See sma-em-dev is the working "branch" and it gets synced to sma-em whenever it's been stable for a while / some big change is planned for the dev addon.
Thank you for th ePR. Willing to accept it, but only to the dev/edge version of the addon.
At some point I will copy over dev/edge to the other verison
| gharchive/pull-request | 2024-02-12T01:54:11 | 2025-04-01T06:44:40.726779 | {
"authors": [
"TheAssassin",
"kellerza"
],
"repo": "kellerza/hassio-sma-em",
"url": "https://github.com/kellerza/hassio-sma-em/pull/35",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2121389738 | Standalone, where do I define the USB device?
Issue related to
Sunsynk / mbusd Home Assistant Add-On
Describe the issue/bug
I've copied over options.yaml and the error I'm getting is:
sunsynk-multi-1 | 17:57:45 INFO No response on the Modbus interface tcp://mbusd:502, see https://kellerza.github.io/sunsynk/guide/fault-finding
I haven't defined the dev/USB** device anywhere, I've just used the bundled mbus.
Do I need to define the USB device anywhere or should it 'just work'? I'm using the WAVE to USB adaptor.
Expected behavior
Connect successfullly
Your environment
Home Assistant version: 2023.8.x
Addon:
Name: sunsynk-multi
Version: 2023-08-17
Inverter:
Make: Sunsynk
Model: Ecco 3.5
Firmware:
Adaptor details:
RS485 WAVE to USB
Your configuration
---
DRIVER: umodbus
INVERTERS:
- SERIAL_NR: '007'
HA_PREFIX: SS
MODBUS_ID: 1
PORT: tcp://mbusd:502
SENSOR_DEFINITIONS: single-phase
SENSORS:
- total_pv_energy
- total_battery_charge
- total_battery_discharge
- total_grid_export
- total_grid_import
- battery_soc
SENSORS_FIRST_INVERTER: []
MANUFACTURER: Sunsynk
READ_SENSORS_BATCH_SIZE: 60
NUMBER_ENTITY_MODE: auto
MQTT_HOST: 192.168.68.53
MQTT_PORT: 1883
MQTT_USERNAME: ''
MQTT_PASSWORD: ''
DEBUG: 0
DEBUG_DEVICE: "/dev/ttyAMA0"
Logs
sunsynk-multi-1 | 17:57:44 INFO Using Single phase sensor definitions.
sunsynk-multi-1 | 17:57:44 INFO Added hidden sensors as other sensors depend on it: Rated power, Serial
sunsynk-multi-1 | 17:57:44 INFO Connecting to tcp://mbusd:502
sunsynk-multi-1 | 17:57:44 INFO Reading startup sensors Serial, Rated power
sunsynk-multi-1 | 17:57:44 ERROR gaierror reading 15 registers from 3: [Errno -2] Name does not resolve
sunsynk-multi-1 | 17:57:44 ERROR gaierror reading 15 registers from 3: [Errno -2] Name does not resolve
sunsynk-multi-1 | 17:57:44 ERROR gaierror reading 15 registers from 3: [Errno -2] Name does not resolve
sunsynk-multi-1 | 17:57:44 WARNING Retrying individual sensors: ['serial', 'rated_power']
sunsynk-multi-1 | 17:57:45 ERROR gaierror reading 5 registers from 3: [Errno -2] Name does not resolve Serial
sunsynk-multi-1 | 17:57:45 ERROR gaierror reading 2 registers from 16: [Errno -2] Name does not resolve Rated power
sunsynk-multi-1 | 17:57:45 CRITICAL Could not read sensors: ['Serial', 'Rated power']
sunsynk-multi-1 | 17:57:45 INFO ############################################################
sunsynk-multi-1 | 17:57:45 INFO No response on the Modbus interface tcp://mbusd:502, see https://kellerza.github.io/sunsynk/guide/fault-finding
sunsynk-multi-1 | 17:57:45 INFO ############################################################
sunsynk-multi-1 | 17:57:45 CRITICAL This Add-On will terminate in 30 seconds, use the Supervisor Watchdog to restart automatically.
The USB port should be configured where you have the USB device plugged in.
If you refer to mbusd, you have to either run mbusd natively or on Docker. In this case you specify the USB config in mbusd
Otherwise you need to identify, and configure the USB port in the options.yaml
Thanks for the quick reply, I'm not running any additional services for mbus, just the hass-addon-sunsynk-multi image. Should it be something like this?
DRIVER: umodbus
INVERTERS:
- PORT: serial:///dev/ttyUSB0
Yes, that looks better. I would use the pymodbus driver though, not umodbus
Thanks, do I need to run any additional services in Docker or is just the main Sunsynk one enough?
I got it working, I had to pass in the device to the docker compose file too::
services:
sunsynk-multi:
restart: unless-stopped
image: ghcr.io/kellerza/hass-addon-sunsynk-multi/aarch64:stable
devices:
- /dev/ttyUSB0:/dev/ttyUSB0
volumes:
- ./options.yaml:/data/options.yaml
---
DRIVER: pymodbus
INVERTERS:
- SERIAL_NR: '007'
HA_PREFIX: SS
MODBUS_ID: 1
PORT: /dev/ttyUSB0
I could document this and raise a PR if you want?
A PR would be welcome & help people in the future. Thanks!
PErfect, I'll do that! thanks
That fixed my issue too. I was resorting to using TCP access via the Logger, but I wanted to use a cable.
| gharchive/issue | 2024-02-06T18:02:38 | 2025-04-01T06:44:40.735086 | {
"authors": [
"championc",
"gurmukhp",
"kellerza"
],
"repo": "kellerza/sunsynk",
"url": "https://github.com/kellerza/sunsynk/issues/230",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
311689235 | Too easy to use
We need to add more dependencies because this repo is too pick up and go. I vote for redux, webpack, and to not document setup.
What's bad about being too easy to use?
@MaxxiBoi , i can't run this code, can you help me to run this code, its too complicated for me
| gharchive/issue | 2018-04-05T16:50:28 | 2025-04-01T06:44:40.750544 | {
"authors": [
"BusbyActual",
"MaxxiBoi",
"tarikhagustia"
],
"repo": "kelseyhightower/nocode",
"url": "https://github.com/kelseyhightower/nocode/issues/2243",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
314354720 | Add integration for third party apps
One should be able to add integration for third party apps such as CI/CD
I've coded a script to run with Travis, check it out:
Good Solid script.
| gharchive/issue | 2018-04-14T19:20:47 | 2025-04-01T06:44:40.751732 | {
"authors": [
"lhcgoncalves",
"mwaz"
],
"repo": "kelseyhightower/nocode",
"url": "https://github.com/kelseyhightower/nocode/issues/2270",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
298699147 | Adding kubernetes support
Added kubernetes support.
Thats all
+1
up
apiVersion: apps/v1
kind: Deployment
metadata:
name:
labels:
app:
spec:
replicas: 256
selector:
matchLabels:
app:
template:
metadata:
labels:
app:
spec:
containers:
- name:
image:
ports:
- containerPort: 80
| gharchive/pull-request | 2018-02-20T18:24:54 | 2025-04-01T06:44:40.754860 | {
"authors": [
"amirbagh75",
"ericvinicius",
"rsaraiva",
"vtrduque"
],
"repo": "kelseyhightower/nocode",
"url": "https://github.com/kelseyhightower/nocode/pull/1929",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
982824201 | page-break add blank space on top
Describe the bug
When I use <div class="html2pdf__page-break" />, the plugin add blank space beetween the label 'Test' and the upper border
There are not margin on inline style
....
</el-row>
</section>
<el-divider />
<div class="html2pdf__page-break" />
<section class="pdf-item">
<h3>Test</h3>
.....
All parts of the file must be inside a section ? I put inside only some parts of the code
Screenshots
Package Version
1.8.0
Thanks
<vue-html2pdf
ref="html2Pdf"
:margin="50"
:show-layout="true"
:float-layout="false"
:enable-download="download"
:preview-modal="false"
:paginate-elements-by-height="1400"
:filename="dynamicFileName"
:pdf-quality="2"
:manual-pagination="true"
pdf-format="a4"
pdf-orientation="portrait"
pdf-content-width="780px"
@startPagination="beginPrint()"
@beforeDownload="beforeDownload($event)"
>
Solved with
.on-top{
margin-top: -120px
}
and
<div class="html2pdf__page-break" />
<section :class="savingPdf ? 'on-top' : '' ">
<h3>Test</h3>
The way that I have fixed this issue is adding css to page-break class like this:
html2pdf__page-break {
margin: 0 !important;
}
ehhh convert image to base 64 and done:
https://www.base64-image.de/
| gharchive/issue | 2021-08-30T13:59:26 | 2025-04-01T06:44:40.762357 | {
"authors": [
"DanieleMar",
"Dzeg",
"sannchiss"
],
"repo": "kempsteven/vue-html2pdf",
"url": "https://github.com/kempsteven/vue-html2pdf/issues/104",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
418137835 | Typo fix: "Requirments" -> "Requirements"
(Seems like the GitHub editor also modified the white space on the last line.)
Thanks!
| gharchive/pull-request | 2019-03-07T05:37:48 | 2025-04-01T06:44:40.772580 | {
"authors": [
"follower",
"minux"
],
"repo": "kendryte/kflash.py",
"url": "https://github.com/kendryte/kflash.py/pull/18",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
1975993478 | Pie Chartsページにおける現在の表示がAll ContestsなのかRated Onlyなのか分かりづらいUIになっている
#1369 にて、Pie Chartsの表示をOnly RatedとAll Contestsで切り替え可能になりましたが、現在の表示がOnly RatedなのかAll Contestsなのか一目で分からないです(UIが悪いです)。
以下の画像では、現在の表示がOnly Rated Contestsなのか、押せばOnly Rated Contestsになるのか、判断が付きません。
二択なのだから、Daily Effortのような表示が分かりやすいと思います(SimpleなのかColoredなのかが分かりやすく良いUI)。
それか、Difficulty Statusのページのように、現在進行形を使えばまだマシになるとは思います(例: Only Rated Contests -> Showing Only Rated Contests)。
#1369 がrevertされたため、こちらもclose致します。
| gharchive/issue | 2023-11-03T11:34:55 | 2025-04-01T06:44:40.831424 | {
"authors": [
"your-diary"
],
"repo": "kenkoooo/AtCoderProblems",
"url": "https://github.com/kenkoooo/AtCoderProblems/issues/1454",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
581174914 | 解ける確率を List にも入れる
https://twitter.com/medo_program05/status/1238788786210783234
Userを基準に計算した予測回答確率を元に、ユーザに対する問題の難易度アイコンを作ってみました。
(1-解答確率)を問題に対するUserの相対難易度と解釈して、３色([Easy, Moderate, Difficult], 両側1/3を境界)のバーで表現
マウスオーバーでユーザの予測回答確率が確認可能
関連Issue
#643
これいいですね！ #643 との比較で言えば正解率が解釈しやすい値なのがわかりやすさに効いていると思います。
これはやや好みの話ですが、Tip で正解確率を出しているので下のバーでも統一して正解確率が高いほうが長いほうが直感に合いそうです。あと、一本のバーの中で複数の色があると混乱する（私はしました）ので、色を長さで変えるのはわかりやすくてよいのですが1本のバーの中では一つの色を使うようにしたほうがよくなると思いました。
あと、一本のバーの中で複数の色があると混乱する（私はしました）ので、色を長さで変えるのはわかりやすくてよいのですが1本のバーの中では一つの色を使うようにしたほうがよくなると思いました。
難易度ごとに色を統一し，長さはそれぞれの区間内での位置に合わせました．（難易度アイコンと同じ感じ）
難易度感が直観的にわかりやすくなったと思います．
これはやや好みの話ですが、Tip で正解確率を出しているので下のバーでも統一して正解確率が高いほうが長いほうが直感に合いそうです。
解答確率をそのまま表示するということですね．
私が相対難易度（１－解答確率）で表示した理由は，解答確率を元にアイコン表示すると，簡単な（解答確率の高い）問題が目立ち，難しい（解答確率の低い）問題が目立たなくなってしまうのはユーザーにとってうれしくないのではないかと考えたからです．
難易度アイコンも難しい問題ほど面積が大きくなっていますので，それとも直感を揃えたいと思いました．
議論のポイントは
ユーザーが最も欲しい情報は何か
欲しい情報に適したデザインは何か
難易度区分は調整したほうがいいかも。
現在: 上下33%
提案: 上下25%
区間は上記に変更しました．
とりあえず3パターン試し
1
アイコニックなバー．
個性強め．
細かい改善で良くなる可能性もある．
2
セルのボトムに合わせたバー．
主張は強いが直観的にわかりやすい．
しいて言うならよくありそうなデザイン．
3
セルの縦に合わせたバージョン．
こちらも直観的に認識しやすいが，横とくっつくので見づらい人もいるかもしれない．
パターン２は確かに読みやすいですね。
新たに表示する機能を追加するのではなくて #401 + List ページのテーブルに確率カラムを追加 ではダメですかね？
discrimination が小さいやつは超低難度か超高難度の問題がほとんどであまりあてになりませんし、difficulty+200程度のレーティングを持つ人なら 60-70% の確率、 difficulty+400 程度なら 70-90%、+800 なら 90% 以上の確率で解ける (と予測される) 問題がほとんどです。 difficulty 自体厳密な難易度判定ではないですし、自分の色から1-2色下の問題を意識して解くようにすればそれでいいような気がします。
discrimination のヒストグラムと delta=(Rating - Difficulty) のときの予測正解率 - 0.5 の雰囲気
個人的にはダークモードのパターン3なんかとてもカッコいいと思うんですが、 予測正解率は difficulty との相関が強いので多分玉の方だけで機能としては足りていて、視覚に強く訴える割には冗長な情報かと思います。
Recommends 以外の場所でも目安として知りたい気持ちは分かるので、上述の #401 + List ページのテーブルに確率カラムを追加 は欲しいと思います。
#401 + List ページのテーブルに確率カラムを追加
は良さそうですね。
すでにRecommendationで実装されている情報ですから、Tableで弊害がないなら表示してもいいと思います。
予測正解率の情報が冗長かどうかは主観にもよる部分があると思います。
確かに予測正解率はdifficultyと相関がありますが、discriminationによる補正は直感に対し無視できない影響があると私は考えています。
ToolTipによる予測正解率表示は問題ごとの情報の提示としての要件は満たしますが、一覧性がありません。
それに対し、提案した３色表示は概ね実力相当の問題がどれであるかを視認する一覧性に長けているので、意味がある表示だと私は思います。
個人的にはレコメンドと得られる情報が変わらない気もするので必要性を感じていませんが、これは個人の感想で、欲しい人がいれば入れた方が良いと思います。どんなユーザーを想定していますか？
まず、難易度メータというアイデアは、「推定正解率を表示する機能」のリッチな拡張であることは明らかにしておきます。
メインの目的は、単純に問題の難しさを知りたいということです。
AtCoder Problems で今日のコンテストの問題のdiffを確認する楽しみ方をしているユーザも多いと思いますが、そういった楽しみ方の一つになるのではないかと思います。
「問題に対して難易度を提供する」という機能は一般的に理解しやすく需要の高い情報だと思いますが、このアイデアはよりユーザに最適化した情報を提供するという立場になります。
またこの情報は、アイコニックな表示で直感的に理解できることや、一覧性によって他の問題との比較ができることでより価値が上がるものだと考えています。
ときに、「思ってたよりもdiffが低い（高い）」という印象の問題はしばしば判別度(discrimination)が低いという状況もありますが、difficultyだけでは得られない情報で補足されるのは私は嬉しいです。(#643)
これはデザイン依存の楽しみ方になるかもしれませんが、例えば
メーターのModerate(黄色)相当は確実に解ける用になっておきたい
レートが上がったら前は難しかった問題がModerateになって嬉しい
といったことも想定できそうです。
これに関しては、現状より色分けを工夫してユーザーが注目しやすい問題に適した表示に改良できれば良いなと考えています。
Table のページは既に色で表現している情報が多量にあって、ここに更に3色を追加するとなると視認性が悪化するような気がします。 (要するにごちゃごちゃしちゃう)
私は https://github.com/kenkoooo/AtCoderProblems/issues/469#issuecomment-659079129 で述べたように、ほとんどの問題に関しては discrimination はある程度の範囲に収まっているので難易度の表現としては difficulty の値だけで事足りていると思っていて、少数の問題に対して difficulty + α の情報を視覚的に提供するためだけに全体の視認性を阻害するのはUX的に良くない、というスタンスです。 (というか、問題の"真の難易度"を算出すること自体が現実的に不可能なのでこの +α の情報にもそんなに意味はないと思っています)
difficulty による色表示を予測正答率で代替すれば表示上はスッキリするかなと思いましたが、当人のレーティング周辺の difficulty の問題以外に対しては情報量ゼロになってしまって、結局劣化 difficulty にしかならなそうです。 何より現在ユーザー間では "赤diff" "青diff" のような言い回しでコンセンサスが取れているので個人依存の指標に基づく色分けは混乱の元になりそうです。
UIがシンプルな方がいいのは同意します。
仮に実装するとしてもできるだけシンプルでわかりやすい物がいいですし、改善はしていくべきです。
それははそれとして、
必要な表示を選択する自由は"チェックボックスによる切り替え機能"で担保されているということにはならないでしょうか。
難易度メータは独立したアイデアとして別にIssue切っても良さそうな気がしてきました。
そうですね、はじめは optional な機能として実装してみてユーザーの反応をうかがってみるのも良いかもしれません。 デザインの改善案なんかもユーザーから出てきそうです。
まだマージされていないのでどうなるか分かりませんが、 #691 で <DifficultyCircle>, <ProblemLink> に ProblemModel, RatingInfo プロパティを追加しました。 予測正答確率の計算がこれらのコンポーネント上でできるようになるので、コンポーネントの一部としてメーターが実装されると Table 以外のページでも表示できて嬉しいかもしれません。 デザイン上の制限は生まれますが…。
ありがとうございます。
承知しました。
競合しそうなので対応しておきます。
メーターは独立したコンポーネントにしておいたほうが表示非表示の切り替えが楽でいいかなと思ってます。
このIssueの本来の目的は #401 に近いものであり、 #691 で達成されそうなので、
難易度メーターは別Issue #693 にしました
done in #691
| gharchive/issue | 2020-03-14T11:56:16 | 2025-04-01T06:44:40.851922 | {
"authors": [
"MatsuTaku",
"amylase",
"kenkoooo",
"koyumeishi",
"southball"
],
"repo": "kenkoooo/AtCoderProblems",
"url": "https://github.com/kenkoooo/AtCoderProblems/issues/469",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
89582912 | Curry methods by default
To avoid needing separate bind or partial calls (for methods that take more than 1 argument)
var isTitle = check.oneOf(['Mr', 'Dr, 'Ms', 'Mss']);
la(isTitle(foo), 'invalid title', foo);
Example already curried https://github.com/kensho/check-more-types#checkequal - not sure it is implemented well
| gharchive/issue | 2015-06-19T14:51:39 | 2025-04-01T06:44:40.865183 | {
"authors": [
"bahmutov"
],
"repo": "kensho/check-more-types",
"url": "https://github.com/kensho/check-more-types/issues/34",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
374462179 | fix typos in custom renderer example
This PR fixes the mistake in the custom renderer example as discussed on https://github.com/kentcdodds/react-testing-library/issues/204#issuecomment-433468647
:tada: This PR is included in version 5.3.0 :tada:
The release is available on:
npm package (@latest dist-tag)
GitHub release
Your semantic-release bot :package::rocket:
| gharchive/pull-request | 2018-10-26T16:41:23 | 2025-04-01T06:44:40.868132 | {
"authors": [
"ankitsinghaniyaz",
"kentcdodds"
],
"repo": "kentcdodds/react-testing-library",
"url": "https://github.com/kentcdodds/react-testing-library/pull/212",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
657035224 | docs(readme): Delete reference to doclets.io
fixes #24
Remove invalid doclets.io url from API documentation
@kentcdodds not sure why this is failing the CI as only changes made were to text files
| gharchive/pull-request | 2020-07-15T03:37:41 | 2025-04-01T06:44:40.869690 | {
"authors": [
"gitKendra"
],
"repo": "kentcdodds/webpack-config-utils",
"url": "https://github.com/kentcdodds/webpack-config-utils/pull/33",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
69871369 | This needs a few tests
I try running the tests and:
[08:05:30] Using gulpfile ~/tmp/nuka-carousel/Gulpfile.js
[08:05:30] Starting 'lint'...
[08:05:30] Finished 'lint' after 506 ms
[08:05:30] Starting 'karma'...
ERROR [config]: File /Users/jherri1/tmp/nuka-carousel/karma.conf.js does not exist!```
Tests are in!
| gharchive/issue | 2015-04-21T15:06:31 | 2025-04-01T06:44:40.870633 | {
"authors": [
"jherr",
"kenwheeler"
],
"repo": "kenwheeler/nuka-carousel",
"url": "https://github.com/kenwheeler/nuka-carousel/issues/1",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
103001398 | Gallery dragging/sliding problems with allot optenet security proxy
Hi,
Vodafone Germany (along other opcos world wide) uses Allot's Optenet Service (http://www.allot.com/allot-optenet-security-solutions/) for safe browsing. It's basically a big packet inspecting proxy which scans your traffic for malware and injects javascript into web pages for users to feel secure.
I made a screencast to illustrate the problem:
https://www.youtube.com/watch?v=fqUOXN2G9hw
On top you see the injected "you are secure" banderole with its tiny shield icon. This icon is draggable in case of the user wants to click anywhere below it on page. When I drag the shield, all carousels on page are dragged as well. When I release the shield, gallerys stay attached to the mouse movements.
This happens on every page using slick carousel I visited.
Whoah thats nuts. What exactly does that shield do?
It sits there and gives you the warm feeling of safety.
You can drag it left and right in case it overlaps anything of importance on the page so that you can move it away and then click on whatever was beneath. Btw, that is why I'm investigating. That shield overlays the menu hamburger button on our page and when the user drags it away, all carousels move as well...
Additionally the shield catches onclick() events, on which a bigger banderole unrolls displaying this sites security status (you can see it in my video, sec 27). Everything but the dragging works fine.
I'm not sure this is a slick issue. The drag on that banderole thing shouldn't be so intrusive.
| gharchive/issue | 2015-08-25T11:18:45 | 2025-04-01T06:44:40.874104 | {
"authors": [
"FieserKiller",
"kenwheeler"
],
"repo": "kenwheeler/slick",
"url": "https://github.com/kenwheeler/slick/issues/1667",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
185250481 | Can't center items horizontally when width is bigger than container
I tried using flex in each item (wrapping them by another div), centering using align-content: center, but the next slide get's in the current one.
Has anyone succeeded doing this? I tried with flex, but I it breaks.
Steps to reproduce the problem
create a carousel with images with width bigger than container
center images using flex, applying justify-content: center to every parent of every image
Chrome v.54 Ubuntu 64 bit
Slick 1.6, jQuery v1.11.2
Did this work before? No
Problem resolution:
http://jsfiddle.net/tomyo/fmo50w7n/678/
Glad you got it resolved!
Sorry, I meant, 'Problem reproduction', haha
| gharchive/issue | 2016-10-25T22:26:15 | 2025-04-01T06:44:40.877257 | {
"authors": [
"leggomuhgreggo",
"tomyo"
],
"repo": "kenwheeler/slick",
"url": "https://github.com/kenwheeler/slick/issues/2587",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
218082321 | Take time to load first time
Hello Team,
I am using slick slider for banner display in my home page so i have one issues like
when my page is load then content of slider section show little bit slow like u know
first time page is open then u show that nothings in this area after some time u saw that banner in this section
see screen shot of first load page
After few time image
I don't feel that this is quite a slick issue, but something that could be solved via CSS. Have you examined any ways to optimize asset loading? Also, you could define a pre-set height for a container element for your banner assets, and have a .loading class indicating to the user that the banner is still loading/rendering. That way the page doesn't jump when new content is rendered.
i have define pre set height of container and also using loader after that i am getting this issues
basically i am using center mode also
in head?
| gharchive/issue | 2017-03-30T05:07:03 | 2025-04-01T06:44:40.880974 | {
"authors": [
"gavinlynch",
"lasbrojen",
"rahi-rajeev"
],
"repo": "kenwheeler/slick",
"url": "https://github.com/kenwheeler/slick/issues/2823",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
200712090 | Update README.md
resolves #26
updated, and I'll update in generator-keystone as well
| gharchive/pull-request | 2017-01-13T19:36:12 | 2025-04-01T06:44:40.882063 | {
"authors": [
"thescientist13"
],
"repo": "kenzanlabs/keystone",
"url": "https://github.com/kenzanlabs/keystone/pull/37",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
798614539 | required time for training on kinetics
hi
How long does it take to train model on kinetics dataset for a few examples of the different hardware you tested before?
Hi @parvanehabi, thanks for your interest! If I recall correctly it takes a while to train on Kinetics. I was sharing the training log in another issue earlier, see here. Seems like it takes 4 days to train on the whole dataset. I don't quite remember what hardware it was using, probably 1080Ti's. Hope this helps!
| gharchive/issue | 2021-02-01T18:45:25 | 2025-04-01T06:44:40.883606 | {
"authors": [
"kenziyuliu",
"parvanehabi"
],
"repo": "kenziyuliu/MS-G3D",
"url": "https://github.com/kenziyuliu/MS-G3D/issues/31",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
1584349665 | update to mermaid v9.x to get rid of some vulnerabilities
mermaid v9.1+ fixes some vulnerabilities that we see with the v8 line:
https://access.redhat.com/security/cve/CVE-2021-23648
https://github.com/mermaid-js/mermaid/security/advisories/GHSA-x3vm-38hw-55wf
Do you have any plans to update to v9?
I'll do that now. Sorry I'm falling behind for the OS community.
@hakandilek it looks like v9 broke something with many to many relations. I'll need to figure out what that is before merging. I don't have time to look into it at this moment though.
You can install v1.3.0 and it is updated with mermaid v10.
npm i -D prisma-erd-generator@alpha or npm i -D prisma-erd-generator@1.3.0
Great, thanks 😊
| gharchive/issue | 2023-02-14T15:17:32 | 2025-04-01T06:44:40.886753 | {
"authors": [
"hakandilek",
"keonik"
],
"repo": "keonik/prisma-erd-generator",
"url": "https://github.com/keonik/prisma-erd-generator/issues/173",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
1381879545 | Problem with minimal theme and excalidraw plugin
Is the bug present when using the default Obsidian theme?
No
Is the bug present when snippets and plugins are disabled?
Yes
Minimal theme version
6.0.5
Describe the bug
Then I turn on dark mode in the obsidian and Excalidraw is in light mode, I get bad colours
Excalidraw author redirect me to you about this issue.
more details in a ticket:
https://github.com/zsviczian/obsidian-excalidraw-plugin/issues/817
Debug info
no one
Also experiencing this issue.
Also seeing this. Does anyone know of a workaround for this issue?
Here is a CSS snippet workaround to make it usable. Depending on your theme it may not look very pretty.
body .excalidraw, body .excalidraw.theme--dark { --island-bg-color: #F5F5F5; }
I am also having this issue - just want to clarify the issue.
It happens when I am using dark theme and I switch to excalidraw light mode (the dark mode = black paper background, works fine)
Issue is on mac OS
Obsidian v1.0
Here is a CSS snippet workaround to make it usable. Depending on your theme it may not look very pretty.
body .excalidraw, body .excalidraw.theme--dark { --island-bg-color: #F5F5F5; }
I had to change it to
body .excalidraw { --island-bg-color: #F5F5F5; }
to make the switching work properly
Fixed in 6.1.10
| gharchive/issue | 2022-09-22T06:01:20 | 2025-04-01T06:44:40.892420 | {
"authors": [
"The-Grand-Vizier",
"axelson",
"dariuszkowalski-com",
"insecurejezza",
"janLo",
"kepano"
],
"repo": "kepano/obsidian-minimal",
"url": "https://github.com/kepano/obsidian-minimal/issues/427",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
1181916044 | [feature]: Add Datagrid to list all the test runs (UI improvement)
Is there an existing feature request for this?
[X] I have searched the existing issues
Summary
Adding Datagrid instead of cards on the "/testruns" page makes it easier to sort out test runs according to users need
Why should this be worked on?
Makes it easier to sort out required test run data based on their need.
A better UX experience for the user.
This is a duplicate issue https://github.com/keploy/ui/issues/4
| gharchive/issue | 2022-03-26T17:13:48 | 2025-04-01T06:44:40.901399 | {
"authors": [
"namantaneja167",
"nehagup"
],
"repo": "keploy/ui",
"url": "https://github.com/keploy/ui/issues/36",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
2530868529 | fix: Fixed Recording of test cases
This pr fixes the behavior of recording when terminal is closed.
After recording test cases in zsh shell
Great work! Works great with replay, please check on the record side
also add semicolons in your files, will cause havoc later if not present
This is making, default running shell as bash, this isnt ideal,please look into the same
if any terminal is open it is also closed please try to fix it
Well done @ayush3160
| gharchive/pull-request | 2024-09-17T11:14:03 | 2025-04-01T06:44:40.904072 | {
"authors": [
"ayush3160",
"khareyash05",
"shivamsouravjha"
],
"repo": "keploy/vscode-extension",
"url": "https://github.com/keploy/vscode-extension/pull/50",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
722043023 | Misleading/incorrect information for quality gate only projects
Hi
I am testing the latest Keptn bridge 0.7.2 and have one project that I only use for Test Execution & Quality Gates - so - I am not using it for delivery.
As you can see from the screenshot the information is rather misleading and actually incorrect as this project has and will never see a deployment - yet - the message tells me that I should do a deployment. We should fix this by detecting whether a project is only used for e.g: quality gates or testing as a service and then show relevant information for those use cases
Here is what I see - it shows me no deployment and a final score of 0
And here is the view in my services view where I can see my latest test executions and quality gates
The initial event that I am sending is actually a deployment event as you can see here:
And here is the event content:
{
"contenttype": "application/json",
"data": {
"deploymentURIPublic": "http://simplenode.keptn07project-staging.keptn07-agrabner.demo.keptn.sh/",
"eventContext": null,
"image": "Keptn Performance as a Service",
"labels": {
"buildId": "47",
"jobname": "Keptn Performance as a Service",
"joburl": "https://angr-jenkins.apps.lab.dynatrace.org/job/Keptn%20Performance%20as%20a%20Service/47/"
},
"project": "perfaasproject",
"service": "perfaasservice",
"stage": "performance",
"tag": "47",
"teststrategy": "performance"
},
"id": "79000c5f-575f-4537-b0ec-2d32598fbe05",
"source": "jenkins-library",
"specversion": "0.2",
"time": "2020-10-14T14:18:57.857Z",
"type": "sh.keptn.events.deployment-finished",
"shkeptncontext": "4d90f1f3-284e-4b18-a6d7-9437f93a83ce"
}
Would be great if we could improve the environment screen
This issue is partly implemented by 0.8.x, but a final adjustment will happen with: https://github.com/keptn/keptn/issues/4172
| gharchive/issue | 2020-10-15T06:34:31 | 2025-04-01T06:44:40.909334 | {
"authors": [
"grabnerandi",
"johannes-b"
],
"repo": "keptn/keptn",
"url": "https://github.com/keptn/keptn/issues/2544",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
818751657 | helm-service: Delivery failed with "Error when installing/upgrading chart" ... "has no deployed releases"
Environment
Client OS (e.g., Linux, OSX, Windows): Linux
Keptn Version (keptn version): 0.8.0-rc1
Kubernetes Cloud Provider (e.g., GKE, AKS): GKE 1.18
Kubernetes version (kubectl version): 1.18
Affected Component
[ ] Docs
[ ] CLI
[ ] Kubernetes Integration
[ ] Openshift Integration
[x] Helm
[ ] Istio
[ ] Bridge
[ ] Approval
[ ] Datastore
[ ] REST API
[ ] eventbroker / distributor
[ ] jmeter
Describe the bug
When deploying to hardening (staging) with blue-green, the first deployment step in the shipyard fails with
Error when installing/upgrading chart tempberry-hardening-tempberry-backend-generated in namespace tempberry-hardening: "tempberry-hardening-tempberry-backend-generated" has no deployed releases
To Reproduce
Create a project using https://github.com/keptn/examples/blob/release-0.8.0/onboarding-carts/shipyard.yaml
Onboard services and trigger delivery
During my first deployment in that stage something went wrong with the Kubernetes API being down (unrelated to Keptn). Any deployments after that don't work anymore. I'm not sure if that is something we can reproduce, but my guess is that the helm chart tempberry-hardening-tempberry-backend-generated does not exist, and helm-service is currently not able to handle that case.
Expected behavior
IMHO helm-service needs to be able to recover from such an error somehow.
Current behavior
Delivery with helm-service fails.
Additional context
$ helm ls -n tempberry-hardening
NAME NAMESPACE REVISION UPDATED STATUS CHART APP VERSION
tempberry-hardening-postgres tempberry-hardening 2 2021-03-01 10:08:56.744060584 +0000 UTC deployed postgres-0.1.0
tempberry-hardening-postgres-generated tempberry-hardening 2 2021-03-01 10:09:01.997584865 +0000 UTC deployed postgres-generated-0.1.0
tempberry-hardening-tempberry-backend tempberry-hardening 3 2021-03-01 10:50:44.882586921 +0000 UTC deployed tempberry-backend-0.1.0
$ kubectl -n tempberry-hardening get deployments -owide
NAME READY UP-TO-DATE AVAILABLE AGE CONTAINERS IMAGES SELECTOR
postgres 1/1 1 1 60m postgres postgres:10.4 app=postgres
tempberry-backend 1/1 1 1 49m tempberry-backend ckreuzberger/tempberry-backend:0.1-master app=tempberry-backend
tempberry-backend-primary 1/1 1 1 48m tempberry-backend ckreuzberger/tempberry-backend:0.1 app=tempberry-backend-primary
Helm-Service Logs
{"timestamp":"2021-03-01T10:50:29.765242963Z","logLevel":"INFO","message":"Finished release for service tempberry-backend in stage dev and project tempberry"}
{"timestamp":"2021-03-01T10:50:34.967065024Z","logLevel":"DEBUG","message":"Got event of type sh.keptn.event.deployment.triggered"}
{"timestamp":"2021-03-01T10:50:34.969458043Z","logLevel":"INFO","message":"Starting deployment for service tempberry-backend in stage hardening of project tempberry"}
{"timestamp":"2021-03-01T10:50:34.972152075Z","logLevel":"INFO","message":"Updating values for service tempberry-backend in stage hardening of project tempberry"}
{"timestamp":"2021-03-01T10:50:44.592129Z","logLevel":"INFO","message":"Creating namespace tempberry-hardening if not present"}
{"timestamp":"2021-03-01T10:50:44.598135022Z","logLevel":"DEBUG","message":"Reuse existing namespace tempberry-hardening"}
{"timestamp":"2021-03-01T10:50:44.59860691Z","logLevel":"INFO","message":"Start upgrading release tempberry-hardening-tempberry-backend in namespace tempberry-hardening"}
{"timestamp":"2021-03-01T10:51:05.14470142Z","logLevel":"DEBUG","message":"---\n# Source: tempberry-backend/templates/tempberry-backend-service.yaml\n# [START service]\napiVersion: v1\nkind: Service\n..."}
{"timestamp":"2021-03-01T10:51:05.147570396Z","logLevel":"INFO","message":"Finished upgrading chart tempberry-hardening-tempberry-backend in namespace tempberry-hardening"}
{"timestamp":"2021-03-01T10:51:11.128708444Z","logLevel":"INFO","message":"Creating namespace tempberry-hardening if not present"}
{"timestamp":"2021-03-01T10:51:11.133444573Z","logLevel":"DEBUG","message":"Reuse existing namespace tempberry-hardening"}
{"timestamp":"2021-03-01T10:51:11.133476194Z","logLevel":"INFO","message":"Start upgrading release tempberry-hardening-tempberry-backend-generated in namespace tempberry-hardening"}
{"timestamp":"2021-03-01T10:51:11.147670555Z","logLevel":"ERROR","message":"Error when installing/upgrading chart tempberry-hardening-tempberry-backend-generated in namespace tempberry-hardening: \"tempberry-hardening-tempberry-backend-generated\" has no deployed releases"}
Workaround
I worked around this problem by deleting the service and onboarding it again
keptn delete service ...
keptn onboard service ...
keptn trigger delivery ...
It seems this issue has been fixed in the meantime - potentially by an update of the helm.sh/helm/v3 dependency, which was set to v3.1.2 in Keptn 0.8.0, but has been upgraded to v3.5.1 in the meantime.
With v0.8.0 of the helm service, I was able to reproduce the problem as follows, using the carts-db service of our examples repo:
# Onboard the service
keptn onboard service carts-db --project=sockshop --chart=./carts-db
# Trigger a delivery with a tag that does not exist:
keptn trigger delivery --project=sockshop --service=carts-db --image=mongo --tag=foo --sequence=delivery-direct
This will eventually lead to a time out in the helm service when waiting for the deployment to be ready. After that, the release is marked as failed when retrieving the releases using the helm CLI:
$ helm ls -n sockshop-dev -a
NAME NAMESPACE REVISION UPDATED STATUS CHART APP VERSION
sockshop-dev-carts sockshop-dev 33 2021-03-26 11:17:53.085282944 +0000 UTC deployed carts-0.1.0
sockshop-dev-carts-db sockshop-dev 2 2021-03-29 14:16:09.052321541 +0000 UTC failed carts-db-0.1.0
sockshop-dev-carts-generated sockshop-dev 30 2021-03-26 11:19:03.923766366 +0000 UTC deployed carts-generated-0.1.0
After that, I tried to trigger a delivery again:
keptn trigger delivery --project=sockshop --service=carts-db --image=mongo --tag=foo --sequence=delivery-direct
And got the following log output in the helm-service:
{"timestamp":"2021-03-30T06:41:24.87039808Z","logLevel":"ERROR","message":"Error when installing/upgrading chart sockshop-dev-carts-db in namespace sockshop-dev: \"sockshop-dev-carts-db\" has no deployed releases"}
I also tried this with the helm service built in PR #3466 but got the same result.
After upgrading the helm-service to 0.8.1 however, the upgrade was performed, even though the release was still in the failed state:
Trigger delivery:
keptn trigger delivery --project=sockshop --service=carts-db --image=mongo --tag=foo --sequence=delivery-direct
Helm-service logs:
{"timestamp":"2021-03-30T06:43:40.510320184Z","logLevel":"INFO","message":"Start upgrading release sockshop-dev-carts-db in namespace sockshop-dev"}
{"timestamp":"2021-03-30T06:46:41.351515486Z","logLevel":"ERROR","message":"Error when installing/upgrading chart sockshop-dev-carts-db in namespace sockshop-dev: timed out waiting for the condition"}
Eventuall, after providing the correct image/tag to the delivery sequence, the carts-db service could be deployed successfully (without deleting the service from Keptn first)
keptn trigger delivery --project=sockshop --service=carts-db --image=docker.io/mongo --tag=latest --sequence=delivery-direct
| gharchive/issue | 2021-03-01T11:03:29 | 2025-04-01T06:44:40.923855 | {
"authors": [
"bacherfl",
"christian-kreuzberger-dtx"
],
"repo": "keptn/keptn",
"url": "https://github.com/keptn/keptn/issues/3407",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
606142564 | Include versioning information in tutorials
Include some kind of versioning into the tutorials. Right now they are not targeting any particular keptn version.
fixed with #13
| gharchive/issue | 2020-04-24T08:37:03 | 2025-04-01T06:44:40.925490 | {
"authors": [
"jetzlstorfer"
],
"repo": "keptn/tutorials",
"url": "https://github.com/keptn/tutorials/issues/12",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
1118277190 | Update TF Decision Forests example
Hello @fchollet and @achoum -
Please review the updates I made to the TF Decision Forests example.
Cheers
@achoum @ksalama are we good here?
@achoum - Thank you so much for your comments. I addressed then as follows:
I used CATEGORICAL_FEATURE_NAMES instead of CATEGORICAL_FEATURES_WITH_VOCABULARY
Create the feature semantics based on NUMERICAL_FEATURE_NAMES and CATEGORICAL_FEATURES_WITH_VOCABULARY, rather than the model input data types.
Deferred computing the vocabulary of the categorical features to the create_embedding_encoder() method.
Fixed the casting to float32 or float64 as we discussed
Updated the BinaryTargetEncoding to pre-compute all the required stats in the adapt() method, while the call() method would only do the lookup of the stats
Allow the user to provide vocabulary_size to avoid calling tf.unique(). However, if it is not passed, it's computed during the execution of the adapt() method. Also added a comment to recommend passing the vocabulary_size.
I kept the prepare_dataframe() method as it seems that tfdf.keras.pd_dataframe_to_tf_dataset doesn't do all the "magic" of converting the target column to integer etc. Am I missing something?
Also, in the last model, when I perform activation directly on the feature, then linear projection, the results are worse than using Dense(units, activation)(encoded_features). So I kept it as it was.
I haven't use tf.data.experimental.group_by_reducer, but I am planning to investigate it (in a subsequent PR).
Also, didn't use a dictionary for the parameters of the model as it, for some reasons, makes the example more than 300 lines, which is not allowed for the Keras examples!
Let me know if you have any further comments.
All good :) Thanks for the work. This is awesome.
| gharchive/pull-request | 2022-01-29T17:12:36 | 2025-04-01T06:44:40.947587 | {
"authors": [
"achoum",
"fchollet",
"ksalama"
],
"repo": "keras-team/keras-io",
"url": "https://github.com/keras-team/keras-io/pull/791",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
383361174 | How do keras calulate the metric?
I'm trying to write a new metric of f1-macro for the softmax, I have tried two methods, I can't understand why the result of them is different.
The first method, I defined a f1-macro function like that,
def f1_macro(y_true,y_pred):
y_pred_tmp=K.argmax(y_pred,axis=-1)
y_pred_tmp=K.one_hot(y_pred_tmp,4) (MULTI CLASS OF 4)
tp=y_pred_tmp*y_true
tp=tf.reduce_sum(tp,axis=0)
fp=K.greater(y_pred_tmp,y_true)
fp=tf.reduce_sum(tf.cast(fp,tf.float32),axis=0)
fn = K.greater(y_true,y_pred_tmp)
fn = tf.reduce_sum(tf.cast(fn, tf.float32), axis=0)
prec_list=[]
recal_list=[]
f1_list=[]
for i in range(0,4):
prec=tp[i]/(tp[i]+fp[i]+K.epsilon())
rec=tp[i]/(tp[i]+fn[i]+K.epsilon())
f1=2*prec*rec/(prec+rec+K.epsilon())
prec_list.append(prec)
recal_list.append(rec)
f1_list.append(f1)
return tf.reduce_mean(f1_list)
then use it like that model.compile(..., metric=[f1-macro])
The second method, I used the Callback to calculate the f1-macro by sklearn f1-score, the f1 calculated by f1_macro function is always less than the Callback. the Callback function is defined below:
class Metrics(Callback):
def on_train_begin(self, logs={}):
self.val_f1s = []
self.val_recalls = []
self.val_precisions = []
def on_epoch_end(self, epoch, logs={}):
pred=np.asarray(self.model.predict(self.validation_data[0]))
val_predict = np.argmax(pred, axis=-1)
val_targ = np.argmax(self.validation_data[1], axis=-1)
_val_recall = recall_score(val_targ, val_predict, average='macro')
_val_precision = precision_score(val_targ, val_predict, average='macro')
_val_f1 = f1_score(val_targ, val_predict, average='macro')
self.val_recalls.append(_val_recall, )
self.val_precisions.append(_val_precision)
self.val_f1s.append(_val_f1)
print('— val_f1: %f — val_precision: %f — val_recall %f' % (_val_f1, _val_precision, _val_recall))
return
and I use it by
metrics = Metrics()
model.fit(X_train, y_train,
epochs=10,
batch_size=batch_size,
validation_data=(X_valid, y_valid),
callbacks=[early_stopping, plateau, checkpoint, metrics],
verbose=2
)
In the two methods, is the validation data for keras to calculate (X_valid, y_valid)?
Is the calculation principle of sklearn f1 score the same with f1_macro ?
How do keras calculate the metrics, is it after each batch size, or after each epoch?
I'm trying to write a new metric of f1-macro for the softmax, I have tried two methods, I can't understand why the result of them is different.
The first method, I defined a f1-macro function like that,
def f1_macro(y_true,y_pred):
y_pred_tmp=K.argmax(y_pred,axis=-1)
y_pred_tmp=K.one_hot(y_pred_tmp,4) (MULTI CLASS OF 4)
tp=y_pred_tmp*y_true
tp=tf.reduce_sum(tp,axis=0)
fp=K.greater(y_pred_tmp,y_true)
fp=tf.reduce_sum(tf.cast(fp,tf.float32),axis=0)
fn = K.greater(y_true,y_pred_tmp)
fn = tf.reduce_sum(tf.cast(fn, tf.float32), axis=0)
prec_list=[]
recal_list=[]
f1_list=[]
for i in range(0,4):
prec=tp[i]/(tp[i]+fp[i]+K.epsilon())
rec=tp[i]/(tp[i]+fn[i]+K.epsilon())
f1=2*prec*rec/(prec+rec+K.epsilon())
prec_list.append(prec)
recal_list.append(rec)
f1_list.append(f1)
return tf.reduce_mean(f1_list)
then use it like that model.compile(..., metric=[f1-macro])
The second method, I used the Callback to calculate the f1-macro by sklearn f1-score, the f1 calculated by f1_macro function is always less than the Callback. the Callback function is defined below:
class Metrics(Callback):
def on_train_begin(self, logs={}):
self.val_f1s = []
self.val_recalls = []
self.val_precisions = []
def on_epoch_end(self, epoch, logs={}):
pred=np.asarray(self.model.predict(self.validation_data[0]))
val_predict = np.argmax(pred, axis=-1)
val_targ = np.argmax(self.validation_data[1], axis=-1)
_val_recall = recall_score(val_targ, val_predict, average='macro')
_val_precision = precision_score(val_targ, val_predict, average='macro')
_val_f1 = f1_score(val_targ, val_predict, average='macro')
self.val_recalls.append(_val_recall, )
self.val_precisions.append(_val_precision)
self.val_f1s.append(_val_f1)
print('— val_f1: %f — val_precision: %f — val_recall %f' % (_val_f1, _val_precision, _val_recall))
return
and I use it by
metrics = Metrics()
model.fit(X_train, y_train,
epochs=10,
batch_size=batch_size,
validation_data=(X_valid, y_valid),
callbacks=[early_stopping, plateau, checkpoint, metrics],
verbose=2
)
In the two methods, is the validation data for keras to calculate (X_valid, y_valid)?
Is the calculation principle of sklearn f1 score the same with f1_macro ?
How do keras calculate the metrics, is it after each batch size, or after each epoch?
Closing this issue since its been addressed. Feel free to reopen if have any further questions. Thanks!
| gharchive/issue | 2018-11-22T02:48:36 | 2025-04-01T06:44:40.956206 | {
"authors": [
"Suncicie",
"ymodak"
],
"repo": "keras-team/keras",
"url": "https://github.com/keras-team/keras/issues/11705",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
1331980450 | Returning model with best weights when EarlyStopping is not triggered and restore_best_weights=True
TensorFlow version (you are using):
TF 2.5.0
Are you willing to contribute it (Yes) :
Describe the feature and the current behavior/state.
At this moment, EarlyStopping will only return the best performing model when EarlyStopping occurs due to no increase in performance over "patience" amount of epochs. Looking at the case where the complete training process is completed without invoking early stopping (e.g. patience is set way to high), most people would like to get the best performing model as a returned model. As the EarlyStopping callback tracks this best weights, it would be almost trivial to integrate this functionality.
Describe the feature clearly here. Be sure to convey here why the requested feature is needed. Any brief description about the use-case would help.
Updating the returned model when complete training occurs in the EarlyStopping callback. In this instant this is possible afterwards by using following code:
ES = EarlyStopping(patience=20, restore_best_weights=True)
callbacks = [ES]
model.fit(x=train_input, y=train_output, epochs=400, batch_size=64, callbacks=callbacks, validation_split=0.25)
if ES.stopped_epoch == 0: # ES did not halt training and thus not update model to best one seen
model.set_weights(ES.best_weights) # does however save the best weights under ES.best_weights
print(f"Restoring model weights from the end of the best epoch: {ES.best_epoch + 1}.")
Will this change the current api? How?
No undesired behaviour should occur
Who will benefit from this feature?
Will return desired behaviour for most people using EarlyStopping
Contributing
Do you want to contribute a PR? (No):
If yes, please read this page for instructions
Briefly describe your candidate solution(if contributing):
Update the on train end function as follows:
def on_train_end(self, logs=None):
if self.stopped_epoch > 0 and self.verbose > 0:
io_utils.print_msg( f"Epoch {self.stopped_epoch + 1}: early stopping")
else:
self.model.set_weights(self.best_weights)
io_utils.print_msg(
"Restoring model weights from "
"the end of the best epoch: "
f"{self.best_epoch + 1}."
)
This functionality is available in the ModelCheckpoint callback (doc) if you change the default params to save_best_only=True.
Agreed that the functionality is already provided in ModelCheckpoint, it just seemed a good addition to me to add it to the EarlyStopping as it would be the desired behaviour for most people and the best weights are already tracked so it's just a matter of returning them instead of having 2 callback functions tracking the same variables.
| gharchive/issue | 2022-08-08T14:44:26 | 2025-04-01T06:44:40.962705 | {
"authors": [
"cevheck",
"jbischof"
],
"repo": "keras-team/keras",
"url": "https://github.com/keras-team/keras/issues/16876",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
94198371 | Dynamic k-Max Pooling
I want to try the 1d CNN model in paper: A convolutional neural network for modelling sentences
the pdf:http://arxiv.org/pdf/1404.2188.pdf?utm_medium=App.net&utm_source=PourOver
How could I implement the Dynamic k-Max Pooling layer?
What have you tried so far?
I just know, it should select the activation of max top k units, and only update the weights of max top k units, and it should use mask. I don't know how to implement mask in theano.
You can try something like this
import numpy as np
import theano.tensor as T
from keras.layers.core import MaskedLayer
class KMaxPooling(MaskedLayer):
def __init__(self, pooling_size):
super(MaskedLayer, self).__init__()
self.pooling_size = pooling_size
self.input = T.tensor3()
def get_output_mask(self, train=False):
return None
def get_output(self, train=False):
data = self.get_input(train)
mask = self.get_input_mask(train)
if mask is None:
mask = T.sum(T.ones_like(data), axis=-1)
mask = mask.dimshuffle(0, 1, "x")
masked_data = T.switch(T.eq(mask, 0), -np.inf, data)
result = masked_data[T.arange(masked_data.shape[0]).dimshuffle(0, "x", "x"),
T.sort(T.argsort(masked_data, axis=1)[:, -self.pooling_size:, :], axis=1),
T.arange(masked_data.shape[2]).dimshuffle("x", "x", 0)]
return result
def get_config(self):
return {"name" : self.__class__.__name__, "pooling_size" : self.pooling_size}
Theano takes care of correct gradient propagation when you do array indexing, no need to worry about it
Did this ever make it into the main branch of Keras?
Is there a tensorflow implementation of the above code?
Not the most generic, well-engineered and thoroughly-tested solution, but this seems to do the trick for me:
from keras.engine import Layer, InputSpec
from keras.layers import Flatten
import tensorflow as tf
class KMaxPooling(Layer):
"""
K-max pooling layer that extracts the k-highest activations from a sequence (2nd dimension).
TensorFlow backend.
"""
def __init__(self, k=1, **kwargs):
super().__init__(**kwargs)
self.input_spec = InputSpec(ndim=3)
self.k = k
def compute_output_shape(self, input_shape):
return (input_shape[0], (input_shape[2] * self.k))
def call(self, inputs):
# swap last two dimensions since top_k will be applied along the last dimension
shifted_input = tf.transpose(inputs, [0, 2, 1])
# extract top_k, returns two tensors [values, indices]
top_k = tf.nn.top_k(shifted_input, k=self.k, sorted=True, name=None)[0]
# return flattened output
return Flatten()(top_k)
@arbackus please help figure out the right dimensions ?
https://stackoverflow.com/questions/45891148/k-maxpooling-layer-in-keras
`def Kmaxpooling(x,N_conv,present_conv):
#get shapes
inp_shape1=tf.shape(x)[1]
inp_shape0=tf.shape(x)[0]
inp_shape2=tf.shape(x)[2]
multiplier=N_conv-present_conv
k=inp_shape1*(multiplier)/(multiplier+1)
#transpose since topk works on last dim
transposed_x=tf.transpose(x, [0, 2, 1])
topk=tf.nn.top_k(transposed_x,k, sorted=True)
#sort the indices to maintain order
topk_inds=tf.negative(tf.nn.top_k(tf.negative(topk[1]),k, sorted=True)[0])
#Get the indices of all axis and merge them
indx_0=tf.reshape(tf.tile(tf.expand_dims(tf.range(inp_shape0),1),[1,tf.multiply(k,inp_shape2)]),[-1])
indx_2=tf.reshape(tf.tile(tf.expand_dims(tf.tile(tf.expand_dims(tf.range(inp_shape2),1),[1,k]),0),[inp_shape0,1,1]),[-1])
indx=tf.reshape(tf.stack([dim0,dim2,tf.reshape(topk_inds,[-1])],axis=1),[inp_shape0,inp_shape2,k,3])
res=tf.transpose(tf.gather_nd(transposed_x,indx), [0, 2, 1])
return res#tf.cast(indx,tf.float32)
@arbackus this solution works, but is very slow. In my case adding this more than doubles the entire network training time. A faster solution would be practical.
if the backend is tf, how to use the kmaxpooling ,for example:
conv1 = Conv2D(32, (3, 3), activation="relu", padding="same")(conv1)
pool1 = MaxPooling2D(pool_size=(2, 2))(conv1)
i replace MaxPooling2D to Kmaxpooling, but it don't work,so how to use the Kmaxpooling
@anttttti
Is this still an issue? Can you try with latest TF version? Thanks
Try this below code preserves the order in the of the original sequence. Not thoroughly tested but works fine.
`class KMaxPooling(layers.Layer):
"""
K-max pooling layer that extracts the k-highest activations from a sequence (2nd dimension).
TensorFlow backend.
"""
def init(self, k=1, axis=1, **kwargs):
super(KMaxPooling, self).init(**kwargs)
self.input_spec = layers.InputSpec(ndim=3)
self.k = k
assert axis in [1,2], 'expected dimensions (samples, filters, convolved_values),\
cannot fold along samples dimension or axis not in list [1,2]'
self.axis = axis
# need to switch the axis with the last elemnet
# to perform transpose for tok k elements since top_k works in last axis
self.transpose_perm = [0,1,2] #default
self.transpose_perm[self.axis] = 2
self.transpose_perm[2] = self.axis
def compute_output_shape(self, input_shape):
input_shape_list = list(input_shape)
input_shape_list[self.axis] = self.k
return tuple(input_shape_list)
def call(self, x):
# swap sequence dimension to get top k elements along axis=1
transposed_for_topk = tf.transpose(x, perm=self.transpose_perm)
# extract top_k, returns two tensors [values, indices]
top_k_vals, top_k_indices = tf.math.top_k(transposed_for_topk,
k=self.k, sorted=True,
name=None)
# maintain the order of values as in the paper
# sort indices
sorted_top_k_ind = tf.sort(top_k_indices)
flatten_seq = tf.reshape(transposed_for_topk, (-1,))
shape_seq = tf.shape(transposed_for_topk)
len_seq = tf.shape(flatten_seq)[0]
indices_seq = tf.range(len_seq)
indices_seq = tf.reshape(indices_seq, shape_seq)
indices_gather = tf.gather(indices_seq, 0, axis=-1)
indices_sum = tf.expand_dims(indices_gather, axis=-1)
sorted_top_k_ind += indices_sum
k_max_out = tf.gather(flatten_seq, sorted_top_k_ind)
# return back to normal dimension but now sequence dimension has only k elements
# performing another transpose will get the tensor back to its original shape
# but will have k as its axis_1 size
transposed_back = tf.transpose(k_max_out, perm=self.transpose_perm)
return transposed_back
class Folding(layers.Layer):
def __init__(self, **kwargs):
super(Folding, self).__init__(**kwargs)
self.input_spec = layers.InputSpec(ndim=3)
def compute_output_shape(self, input_shape):
return (input_shape[0], input_shape[1], int(input_shape[2]/2))
def call(self, x):
input_shape = x.get_shape().as_list()
# split the tensor along dimension 2 into dimension_axis_size/2
# which will give us 2 tensors
splits = tf.split(x, num_or_size_splits=int(input_shape[2]/2), axis=2)
# reduce sums of the pair of rows we have split onto
reduce_sums = [tf.reduce_sum(split, axis=2) for split in splits]
# stack them up along the same axis we have reduced
row_reduced = tf.stack(reduce_sums, axis=2)
return row_reduced`
Try this custom tensorflow keras layer. Not thoroughly tested but works fine.
`class KMaxPooling(layers.Layer):
"""
K-max pooling layer that extracts the k-highest activations from a sequence (2nd dimension).
TensorFlow backend.
"""
def init(self, k=1, axis=1, **kwargs):
super(KMaxPooling, self).init(**kwargs)
self.input_spec = layers.InputSpec(ndim=3)
self.k = k
assert axis in [1,2], 'expected dimensions (samples, filters, convolved_values),\
cannot fold along samples dimension or axis not in list [1,2]'
self.axis = axis
# need to switch the axis with the last elemnet
# to perform transpose for tok k elements since top_k works in last axis
self.transpose_perm = [0,1,2] #default
self.transpose_perm[self.axis] = 2
self.transpose_perm[2] = self.axis
def compute_output_shape(self, input_shape):
input_shape_list = list(input_shape)
input_shape_list[self.axis] = self.k
return tuple(input_shape_list)
def call(self, x):
# swap sequence dimension to get top k elements along axis=1
transposed_for_topk = tf.transpose(x, perm=self.transpose_perm)
# extract top_k, returns two tensors [values, indices]
top_k_vals, top_k_indices = tf.math.top_k(transposed_for_topk,
k=self.k, sorted=True,
name=None)
# maintain the order of values as in the paper
# sort indices
sorted_top_k_ind = tf.sort(top_k_indices)
flatten_seq = tf.reshape(transposed_for_topk, (-1,))
shape_seq = tf.shape(transposed_for_topk)
len_seq = tf.shape(flatten_seq)[0]
indices_seq = tf.range(len_seq)
indices_seq = tf.reshape(indices_seq, shape_seq)
indices_gather = tf.gather(indices_seq, 0, axis=-1)
indices_sum = tf.expand_dims(indices_gather, axis=-1)
sorted_top_k_ind += indices_sum
k_max_out = tf.gather(flatten_seq, sorted_top_k_ind)
# return back to normal dimension but now sequence dimension has only k elements
# performing another transpose will get the tensor back to its original shape
# but will have k as its axis_1 size
transposed_back = tf.transpose(k_max_out, perm=self.transpose_perm)
return transposed_back`
`class KMaxPooling(layers.Layer):
"""
K-max pooling layer that extracts the k-highest activations from a sequence (2nd dimension).
TensorFlow backend.
"""
def init(self, k=1, axis=1, **kwargs):
super(KMaxPooling, self).init(**kwargs)
self.input_spec = layers.InputSpec(ndim=3)
self.k = k
assert axis in [1,2], 'expected dimensions (samples, filters, convolved_values),\
cannot fold along samples dimension or axis not in list [1,2]'
self.axis = axis
# need to switch the axis with the last elemnet
# to perform transpose for tok k elements since top_k works in last axis
self.transpose_perm = [0,1,2] #default
self.transpose_perm[self.axis] = 2
self.transpose_perm[2] = self.axis
def compute_output_shape(self, input_shape):
input_shape_list = list(input_shape)
input_shape_list[self.axis] = self.k
return tuple(input_shape_list)
def call(self, x):
# swap sequence dimension to get top k elements along axis=1
transposed_for_topk = tf.transpose(x, perm=self.transpose_perm)
# extract top_k, returns two tensors [values, indices]
top_k_vals, top_k_indices = tf.math.top_k(transposed_for_topk,
k=self.k, sorted=True,
name=None)
# maintain the order of values as in the paper
# sort indices
sorted_top_k_ind = tf.sort(top_k_indices)
flatten_seq = tf.reshape(transposed_for_topk, (-1,))
shape_seq = tf.shape(transposed_for_topk)
len_seq = tf.shape(flatten_seq)[0]
indices_seq = tf.range(len_seq)
indices_seq = tf.reshape(indices_seq, shape_seq)
indices_gather = tf.gather(indices_seq, 0, axis=-1)
indices_sum = tf.expand_dims(indices_gather, axis=-1)
sorted_top_k_ind += indices_sum
k_max_out = tf.gather(flatten_seq, sorted_top_k_ind)
# return back to normal dimension but now sequence dimension has only k elements
# performing another transpose will get the tensor back to its original shape
# but will have k as its axis_1 size
transposed_back = tf.transpose(k_max_out, perm=self.transpose_perm)
return transposed_back`
Try this custom layer. Not thoroughly tested but works fine for me. Let me know how it works for you.
P.S. Latest tensorflow version
`class KMaxPooling(layers.Layer):
def init(self, k=1, axis=1, **kwargs):
super(KMaxPooling, self).init(**kwargs)
self.input_spec = layers.InputSpec(ndim=3)
self.k = k
assert axis in [1,2], 'expected dimensions (samples, filters, convolved_values),\
cannot fold along samples dimension or axis not in list [1,2]'
self.axis = axis
# need to switch the axis with the last elemnet
# to perform transpose for tok k elements since top_k works in last axis
self.transpose_perm = [0,1,2] #default
self.transpose_perm[self.axis] = 2
self.transpose_perm[2] = self.axis
def compute_output_shape(self, input_shape):
input_shape_list = list(input_shape)
input_shape_list[self.axis] = self.k
return tuple(input_shape_list)
def call(self, x):
# swap sequence dimension to get top k elements along axis=1
transposed_for_topk = tf.transpose(x, perm=self.transpose_perm)
# extract top_k, returns two tensors [values, indices]
top_k_vals, top_k_indices = tf.math.top_k(transposed_for_topk,
k=self.k, sorted=True,
name=None)
# maintain the order of values as in the paper
# sort indices
sorted_top_k_ind = tf.sort(top_k_indices)
flatten_seq = tf.reshape(transposed_for_topk, (-1,))
shape_seq = tf.shape(transposed_for_topk)
len_seq = tf.shape(flatten_seq)[0]
indices_seq = tf.range(len_seq)
indices_seq = tf.reshape(indices_seq, shape_seq)
indices_gather = tf.gather(indices_seq, 0, axis=-1)
indices_sum = tf.expand_dims(indices_gather, axis=-1)
sorted_top_k_ind += indices_sum
k_max_out = tf.gather(flatten_seq, sorted_top_k_ind)
# return back to normal dimension but now sequence dimension has only k elements
# performing another transpose will get the tensor back to its original shape
# but will have k as its axis_1 size
transposed_back = tf.transpose(k_max_out, perm=self.transpose_perm)
return transposed_back`
Check this out a custom keras layer. Not thoroughly tested but works fine for me. Let me know what you think. P.S. TF 2.1.0
import tensorflow as tf
from tensorflow.keras import layers
class KMaxPooling(layers.Layer):
"""
K-max pooling layer that extracts the k-highest activations from a sequence (2nd dimension).
TensorFlow backend.
"""
def __init__(self, k=1, axis=1, **kwargs):
super(KMaxPooling, self).__init__(**kwargs)
self.input_spec = layers.InputSpec(ndim=3)
self.k = k
assert axis in [1,2], 'expected dimensions (samples, filters, convolved_values),\
cannot fold along samples dimension or axis not in list [1,2]'
self.axis = axis
# need to switch the axis with the last elemnet
# to perform transpose for tok k elements since top_k works in last axis
self.transpose_perm = [0,1,2] #default
self.transpose_perm[self.axis] = 2
self.transpose_perm[2] = self.axis
def compute_output_shape(self, input_shape):
input_shape_list = list(input_shape)
input_shape_list[self.axis] = self.k
return tuple(input_shape_list)
def call(self, x):
# swap sequence dimension to get top k elements along axis=1
transposed_for_topk = tf.transpose(x, perm=self.transpose_perm)
# extract top_k, returns two tensors [values, indices]
top_k_vals, top_k_indices = tf.math.top_k(transposed_for_topk,
k=self.k, sorted=True,
name=None)
# maintain the order of values as in the paper
# sort indices
sorted_top_k_ind = tf.sort(top_k_indices)
flatten_seq = tf.reshape(transposed_for_topk, (-1,))
shape_seq = tf.shape(transposed_for_topk)
len_seq = tf.shape(flatten_seq)[0]
indices_seq = tf.range(len_seq)
indices_seq = tf.reshape(indices_seq, shape_seq)
indices_gather = tf.gather(indices_seq, 0, axis=-1)
indices_sum = tf.expand_dims(indices_gather, axis=-1)
sorted_top_k_ind += indices_sum
k_max_out = tf.gather(flatten_seq, sorted_top_k_ind)
# return back to normal dimension but now sequence dimension has only k elements
# performing another transpose will get the tensor back to its original shape
# but will have k as its axis_1 size
transposed_back = tf.transpose(k_max_out, perm=self.transpose_perm)
return transposed_back
@makaveli10 How to use it instead of Maxpooling?
| gharchive/issue | 2015-07-10T02:36:29 | 2025-04-01T06:44:40.983431 | {
"authors": [
"andcut",
"anttttti",
"arbackus",
"bicepjai",
"fchollet",
"iskandr",
"jvishnuvardhan",
"makaveli10",
"manan15105411262",
"ngragaei",
"peterGuang",
"rainmakerr",
"samskruthireddy"
],
"repo": "keras-team/keras",
"url": "https://github.com/keras-team/keras/issues/373",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
257616447 | Pad_sequences throwing error with texts_to_sequence_generator
After creating a text to sequence generator using texts_to_sequences_generator, when that generator object is passed as argument to the pad_sequences. It throws the following error.
ValueError Traceback (most recent call last)
in ()
1 seq2 = tokenizer.texts_to_sequences_generator(sent)
----> 2 data2 = pad_sequences(seq2,maxlen=maxSeqLength)
/opt/conda/lib/python3.5/site-packages/keras/preprocessing/sequence.py in pad_sequences(sequences, maxlen, dtype, padding, truncating, value)
35 """
36 if not hasattr(sequences, 'len'):
---> 37 raise ValueError('sequences must be iterable.')
38 lengths = []
39 for x in sequences:
ValueError: sequences must be iterable.
I reduced the code to bare minimum for my use case. Assuming post padding and int32 data type.
def pad_sequences(sequences, maxlen):
for s in sequences:
if len(s) == 0: yield np.zeros((1, maxlen), dtype='int32')
s = np.array(s, dtype='int32')
yield np.expand_dims(np.pad(s[:maxlen], (0, max(0, maxlen - len(s))), 'constant'), axis=0)
This doesn't return a matrix rather a generator! So, any of your following step need to take care of that.
Bonus tip:
To clone generators --
Use tee
from itertools import tee
| gharchive/issue | 2017-09-14T07:07:15 | 2025-04-01T06:44:40.989578 | {
"authors": [
"ishmeetSRaina",
"pbamotra"
],
"repo": "keras-team/keras",
"url": "https://github.com/keras-team/keras/issues/7894",
"license": "apache-2.0",
"license_type": "permissive",
"license_source": "bigquery"
} |
2457365697 | bigquery.Copy not working with validation error
Expected Behavior
No response
Actual Behaviour
This cannot be save due to this error:
Internal server error: HV000030: No validator could be found for constraint ‘io.kestra.plugin.gcp.bigquery.StoreFetchDestinationValidation’ validating type ‘io.kestra.plugin.gcp.bigquery.Copy’. Check configuration for ‘tasks[0]’
id: test_bq_copy
namespace: kestra.sandbox
tasks:
- id: snapshot_table
type: io.kestra.plugin.gcp.bigquery.Copy
destinationTable: kestra-dev.bpimpaud.new_data_test
operationType: COPY
sourceTables:
- kestra-dev.bpimpaud.data_from_db
projectId: kestra-dev
serviceAccount: "{{ secret('GCP_CREDS') }}"
The flow is fairly basic and use the example from plugin documentation
Steps To Reproduce
No response
Environment Information
Kestra Version: 0.18.0
Plugin version:
Operating System (OS / Docker / Kubernetes): docker
Java Version (If not docker):
Example flow
No response
switch REST or BULK, error persist
| gharchive/issue | 2024-08-09T08:09:17 | 2025-04-01T06:44:41.005667 | {
"authors": [
"Ben8t",
"fikafetsy"
],
"repo": "kestra-io/plugin-gcp",
"url": "https://github.com/kestra-io/plugin-gcp/issues/428",
"license": "Apache-2.0",
"license_type": "permissive",
"license_source": "github-api"
} |
614339965 | Installation Steps?
Hi Ketan,
If Kindly you could help with how we can install and setup this project it would be really helpful and useful.
Thank you
You can refer README.md file I've updated it and you may need to make some changes in code to make it work in your region.
Thanks
| gharchive/issue | 2020-05-07T20:58:57 | 2025-04-01T06:44:41.007708 | {
"authors": [
"SuhailSumra",
"ketanchoyal"
],
"repo": "ketanchoyal/theParker",
"url": "https://github.com/ketanchoyal/theParker/issues/2",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
1646770600 | Catch pydantic validation errors with one validation type
I wonder if it is possible to modify the AsdfPydanticModel to raise the same ValidationError as ASDF does? That way libraries reading asdf files will on need to worry about catching one error type.
@WilliamJamieson
ASDF's error is a direct use of jsonschema's which is not a subclass of a standard type
from jsonschema import ValidationError
Pydantic's error is a subclass of TypeError
from pydantic.error_wrappers import ValidationError
I really would love to use ExceptionGroup (new in Python 3.11) for this because there are situations where I want to catch only pydantic validation error.
Maybe asdf should define a AsdfValidationError which inherits from both TypeError and jsonschema.ValidationError? I think that would be a reasonable improvement on asdf's part.
Desired result:
from asdf import ValidationError
try:
af.open(...)
except ValidationError:
...
After Python 3.11,
from asdf import ValidationError
# Very verbose, could forward this asdf_pydantic
from pydantic.error_wrappers import ValidationError as PydanticValidationError
try:
af.open(...)
except* ValidationError:
...
except* PydanticValidationError:
...
Good idea on inheriting TypeError. I'd keep the same name ValidationError for compatibilty.
Conversely, since this is such a new library you could just require Python 3.11 to use it.
I will consider it; I have things in Roman that are 3.10.
| gharchive/issue | 2023-03-30T01:36:56 | 2025-04-01T06:44:41.012498 | {
"authors": [
"WilliamJamieson",
"ketozhang"
],
"repo": "ketozhang/asdf-pydantic",
"url": "https://github.com/ketozhang/asdf-pydantic/issues/2",
"license": "BSD-3-Clause",
"license_type": "permissive",
"license_source": "github-api"
} |
209680472 | Music similarity using music-auto_tagging for feature extraction
Hi ,
I have used the music-auto_tagging for feature extraction along with a classifier and come up with an approach to recommend music based on music similarity.
Accoustically similar music have some accoustic features which can be used to identify similar sounding music. We have considered the following four accoustic features in order to distinguish different kind of music.
1)Drag : Songs which are very slow moving
2)Beats : Songs in which rythmic beats are more prominent and highlighted
3)Melody : Songs without too much beats /slow or medium tempo (speed) /
4)Fast : Songs which have fast tempo (speed) .
We picked manually around 60-80 music samples under each of the above categories.
Then we formed a binary cluster for each category as follows :
For example in order to train for Drag category , we formed two groups with 65 samples in each group.
1)Drag group (65 samples) : all samples in this group are very slow moving songs.
2)Others group (65 samples ) : We mixed samples from beats melody and fast category which are not slow moving but with medium to fast tempo(speed).
Then we trained a convolutional neural network (CNN) model using normalized spectrograms of all samples from both groups. The trained model was used to identify the dragscore for a song.
Using the same approach as explained above , separate CNN models were trained in order to get beatsscore, melodyscore and fastscore from a song.
Now using the four separately trained CNN models , we obtained dragscore,beatsscore,melodyscore and fastscore for every song in the test data (around 3000+ music samples) which were not part of training data.
For any selected song from test set , based on the four scores of the selected sample song , songs which have similar scores in the test set were listed in the result page with option to listen to the selected and listed samples.
The listing based on score similarity seemed to match the selected song in terms of music similarity for 85-90% of the selections.
So it works well? then it's good news :)
Thanks. I have tried with very few samples only (around 60-70 samples per category). I will need to try with more samples per category and check if I can get better accuracy .
| gharchive/issue | 2017-02-23T07:00:30 | 2025-04-01T06:44:41.016914 | {
"authors": [
"keunwoochoi",
"srinidhikrs"
],
"repo": "keunwoochoi/music-auto_tagging-keras",
"url": "https://github.com/keunwoochoi/music-auto_tagging-keras/issues/17",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
251490451 | Deserializing array of arbitrary values
I am interested in deserializing arbitrary values contained in JSON array. The contents and data types inside the array may change anytime.
The objective is to deserialize data so it may be further processed and stored to disk using more effective serialization. The performance is key factor here, which brought me to investigate Jil.
Using Json.NET this can be achieved quite easily.
string json = @"[1, true, 1.2345, null, ""test""]";
var values = JsonConvert.DeserializeObject<object[]>(json);
Values array would then contain the values as .NET (boxed) primitive types (long, bool, double, object, string). The array would then be really easy to use for further processing and efficient storage.
However the Json.NET deserialization has quite large performance overhead.
Deserializing the same data with Jil seems to produce dynamic JsonObjects. I am having hard time figuring out what to do with the dynamic objects to get to the "raw" data. Is there feasible to way to achieve what I am trying to do using Jil?
It works, but it's quite a bit of work and quite error prone, especially if you don't know anything about the types you are deserializing (e.g. your null value above, decimal vs. double, Guids etc.).
The steps are:
obtain typeconverter: var converter = TypeDescriptor.GetConverter(dynamic);
Find out if the dynamic is a complex object by converting it to a Dictionary<string,object>
Find out if the dynamic is an array by converting it to an array etc.
Find out if the dynamic is a string, value types, primitve types by converting it to string etc.
And repeat that until your done, TypeConverters have a method CanConvertTo which will try the conversion without throwing an exception. This is not designed for performance e.g. CanConvertTo then doing ConvertTo basically amounts to doing the conversion twice. Personally I wouldn't try this if you don't know the types you're deserializing before hand, simply because JSON is not as typesafe as C#.
Thanks Tornhoof. I did try your suggestion and indeed I was able to get it working quite similarly as Json.NET. However the conversions via the TypeConverter absolutely ruined the performance.
Yes, as I wrote, it does the conversion twice, if you know the types, you can skip the CanConvertTo step and it's pretty much twice as fast, but even then it's only marginally faster than JSON.NET.
| gharchive/issue | 2017-08-20T14:02:59 | 2025-04-01T06:44:41.066050 | {
"authors": [
"Tornhoof",
"juho-hanhimaki"
],
"repo": "kevin-montrose/Jil",
"url": "https://github.com/kevin-montrose/Jil/issues/273",
"license": "mit",
"license_type": "permissive",
"license_source": "bigquery"
} |
1677312110 | Skip masking trace, etc when bias_correction is None; enable row-by-row BG subtraction; edit NIRCam extraction height
This resolves #522 by skipping a bunch of unnecessary steps in bias_sub.py when meta.bias_correction is None.
Got it! I had fixed a related problem, but not the exact one you were describing.
@taylorbell57 Do you have any other concerns about this PR before we merge?
| gharchive/pull-request | 2023-04-20T19:43:26 | 2025-04-01T06:44:41.067859 | {
"authors": [
"kevin218"
],
"repo": "kevin218/Eureka",
"url": "https://github.com/kevin218/Eureka/pull/524",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
2376095618 | 🛑 FX blog (kty) is down
In 6b4d2c9, FX blog (kty) (https://foxter-blogeditor.konecty.com) was down:
HTTP code: 0
Response time: 0 ms
Resolved: FX blog (kty) is back up in 9a12a12 after 6 minutes.
| gharchive/issue | 2024-06-26T19:17:49 | 2025-04-01T06:44:41.097693 | {
"authors": [
"keviocastro"
],
"repo": "keviocastro/upptime",
"url": "https://github.com/keviocastro/upptime/issues/10654",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
2383780673 | 🛑 FX blog (kty) is down
In 8175af1, FX blog (kty) (https://foxter-blogeditor.konecty.com) was down:
HTTP code: 0
Response time: 0 ms
Resolved: FX blog (kty) is back up in 2b90f00 after 8 minutes.
| gharchive/issue | 2024-07-01T12:54:32 | 2025-04-01T06:44:41.100259 | {
"authors": [
"keviocastro"
],
"repo": "keviocastro/upptime",
"url": "https://github.com/keviocastro/upptime/issues/12019",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
2390134726 | 🛑 FX corretor (kty) is down
In e2e9936, FX corretor (kty) (https://corretores.foxterciaimobiliaria.com.br) was down:
HTTP code: 0
Response time: 0 ms
Resolved: FX corretor (kty) is back up in 2bddbb2 after 7 minutes.
| gharchive/issue | 2024-07-04T07:17:55 | 2025-04-01T06:44:41.102703 | {
"authors": [
"keviocastro"
],
"repo": "keviocastro/upptime",
"url": "https://github.com/keviocastro/upptime/issues/12759",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
2407389066 | 🛑 FX blog (kty) is down
In 9f29a0c, FX blog (kty) (https://foxter-blogeditor.konecty.com) was down:
HTTP code: 0
Response time: 0 ms
Resolved: FX blog (kty) is back up in f219cae after 26 minutes.
| gharchive/issue | 2024-07-14T11:23:24 | 2025-04-01T06:44:41.105165 | {
"authors": [
"keviocastro"
],
"repo": "keviocastro/upptime",
"url": "https://github.com/keviocastro/upptime/issues/15395",
"license": "MIT",
"license_type": "permissive",
"license_source": "github-api"
} |
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