How to create custom data for training ?

First thanks for your great work. I have a question about the dataset annotation and I need your help. Now that I have 10000 images that don't have labels. How I could label my dataset to apply to your model ? Hope that you can explain it to me.

Basically, our FER model operates in the valence-arousal (VA) space.
So, the ground truth (GT) should be annotated for both valence and arousal respectively.
For example, an example file training.csv is as follows.
| ---                   | ---        | ---         |
| filePath           | valence | arousal |
| 1/001/1.png   | 0.2         | -0.1      |
...
Here, the path of filePath can be set arbitrarily by the user (e.g., 001/1.png).

Sorry but which i want you explain to me is how do the image is annotated with 0.2 (valence) and 0.1 (arousal) ? What is it based on ? I have too many data with unlabeled, but I dont't know the way to annotate the value of valence and arousal

There are roughly two options.

Self-annotation: Having the subject of the image annotate their feelings at that moment.

The meaning of the valence and arousal axes must be taught in advance.

Hire skilled annotators

Or, if you want to be a (skilled) annotator, please refer below paper:

J. Posner et al. The circumplex model of affect: An integrative approach to affective neuroscience, cognitive development, and psychopathology, 2005.

Thanks for your answer, I will try it?

Sorry for the late reply :)
Sure!! But be careful below things:

When annotating Valence-Arousal (VA) values, if the proportion of outlier samples is large, the model may not be trained properly.

Here, an outlier sample is a case where the absolute value of the VA value is too large compared to other samples.

Fingers crossed!

So what you mean is that I need to collect balanced datasets that fill all the VA space ?

Yes.
The best way is to collect the dataset with a distribution similar to Figure 3 in the paper below:

https://arxiv.org/pdf/1708.03985.pdf

Thanks for your support, I got it.


ipad mini3 error

https://github.com/nanoscopic/h264_to_jpeg/blob/3e64b68b63e98e65973ef5e854cec6284c647ade/hw_decode.c#L167
When running on ipad mini 3 version, the following error occurs. How can I know how to fix it?
Receiving data from nanomsg tcp://<IP_ADDRESS>:7878
Send data to nanomsg tcp://<IP_ADDRESS>:7879
Fetching headers to start decoder
nalu type: SPS, size: 19
nalu type: PPS, size: 8
nalu type: SEI, size: 29
Opening Input
Input Open
Fetching first frame to initialize decoder
 Iframe - size: 26128
Finding stream info
[h264 @ 0x7fe99d006e00] concealing 5025 DC, 5025 AC, 5025 MV errors in I frame
[h264 @ 0x7fe99b001800] decoding for stream 0 failed
Finding best stream
Getting hardware config
Initiating decoder
Decoder is started; beginning loop reading frames
Time from start of main till video loop: 51234.434000
 Iframe - size: 24172 - Timediff:15.360000
Source dimensions 1200 x 1600
Target dimensions 600 x 800
[h264 @ 0x7fe99a800000] hardware accelerator failed to decode picture
Error during decoding: Unknown error occurred
Bus error: 10

I looked into the cause more, but the problem seems to be that ipadmini is sending an audio packet, and I think the error may have occurred by interpreting the packet with the video "avcodec_send_packet(avctx, packet)" analyzer.
{"level":"info","msg":"Set Debug mode","time":"2020-06-03T09:37:48+09:00"}
{"level":"debug","msg":"QT Config is active: vid=05ac,pid=12a8,bus=20,addr=24,config=6","time":"2020-06-03T09:37:48+09:00"}
{"level":"debug","msg":"Got QT iface:vid=05ac,pid=12a8,bus=20,addr=24,config=6,if=2,alt=0","time":"2020-06-03T09:37:48+09:00"}
{"level":"debug","msg":"Inbound Bulk: ep #6 IN (address 0x86) bulk [512 bytes]","time":"2020-06-03T09:37:48+09:00"}
{"level":"debug","msg":"Outbound Bulk: ep #5 OUT (address 0x05) bulk [512 bytes]","time":"2020-06-03T09:37:48+09:00"}
{"level":"debug","msg":"Endpoint claimed","time":"2020-06-03T09:37:48+09:00"}
{"level":"info","msg":"Device '00008020000955DC1132002E\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000' ready to stream ( click 'Settings-Developer-Reset Media Services' if nothing happens )","time":"2020-06-03T09:37:48+09:00"}
{"level":"info","msg":"AudioVideo-Stream has started","time":"2020-06-03T09:37:48+09:00"}
{"level":"debug","msg":"Rcv:SYNC_CWPA{ClockRef:1, CorrelationID:10c064ca0, DeviceClockRef:1005b6e60}","time":"2020-06-03T09:37:48+09:00"}
{"level":"debug","msg":"Sending ASYN HPD1","time":"2020-06-03T09:37:48+09:00"}
{"level":"debug","msg":"Send CWPA-RPLY {correlation:10c064ca0, clockRef:1005b7248}","time":"2020-06-03T09:37:48+09:00"}
{"level":"debug","msg":"Sending ASYN HPD1","time":"2020-06-03T09:37:48+09:00"}
{"level":"debug","msg":"Sending ASYN HPA1","time":"2020-06-03T09:37:48+09:00"}

{"level":"debug","msg":"Rcv:SYNC_AFMT{ClockRef:1005b7248, CorrelationID:1005289d0, AudioStreamBasicDescription:{SampleRate:48000.000000,FormatFlags:76,BytesPerPacket:4,FramesPerPacket:1,BytesPerFrame:4,ChannelsPerFrame:2,BitsPerChannel:16,Reserved:0}}","time":"2020-06-03T09:37:48+09:00"}
{"level":"debug","msg":"Send AFMT-REPLY {correlation:1005289d0}","time":"2020-06-03T09:37:48+09:00"}

{"level":"debug","msg":"Rcv:SYNC_CVRP{ClockRef:1, CorrelationID:1005113f0, DeviceClockRef:100534c70, Payload:StringKeyDict:[{PreparedQueueHighWaterLevel : StringKeyDict:[{flags : Int32[1]},{value : UInt64[5]},{timescale : Int32[30]},{epoch : UInt64[0]},]},{PreparedQueueLowWaterLevel : StringKeyDict:[{flags : Int32[1]},{value : UInt64[3]},{timescale : Int32[30]},{epoch : UInt64[0]},]},{FormatDescription : fdsc:{MediaType:Video, VideoDimension:(828x1792), Codec:AVC-1, PPS:2764002aac5680d00e1ef9b810101010, SPS:28ee3cb0, Extensions:IndexKeyDict:[{49 : IndexKeyDict:[{105 : 0x0164002affe100102764002aac5680d00e1ef9b81010101001000428ee3cb0fdf8f800},]},{52 : H.264},]}},]}","time":"2020-06-03T09:37:49+09:00"}

@jjunghyup
Your initial response before editing was interesting in that the UDID output for your device was followed by gibberish. \u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000\u0000
You are the second user to report that ios_video_pull is outputting the null characters that way. In your case it still seems to work ( at least partially ) and only have a corrupt output. That still is a bug and I'll open a bug for that on the quicktime_video_hack repo.
The idea that it is attempting to process an audio packet is certainly possible. I can attempt to diagnose the issue if you could capture a file containing the video stream.
Use ./bin/ios_video_pull -pull -file [filename] to save a chunk of data from your device. Press control see after a second or two so it isn't too large.
You can then feed it into h264_to_jpeg using ./bin/decode file --file [filename]. Do that and verify that it still encounters the same/similar error. Once you have a file that generates that error you can post that file and I can look at its contents to diagnose what is going on and why h264_to_jpeg cannot process it.

same error on ./bin/decode file --file [filename]
here is testfile.
please check it
abc.zip

If you brew install ffmpeg you can then also use ffplay abc to play the file directly to confirm it is valid video that can be decoded by ffmpeg.
I just did that and the video is able to be decoded by ffmpeg. It still spits out an error though "error while decoded MB 44 82, bytestream -6". I will investigate further and see if I can figure out what the issue is.

Is your video playing?
I've done it with ffplay abc, but the video is playing and I got the same error at the end.
chajunghyeob-XXXXX-SWgisulLab:ios_video_pull latte$ ffplay abc
ffplay version 4.2.3 Copyright (c) 2003-2020 the FFmpeg developers
  built with Apple clang version 11.0.0 (clang-1<IP_ADDRESS>)
  configuration: --prefix=/usr/local/Cellar/ffmpeg/4.2.3 --enable-shared --enable-pthreads --enable-version3 --enable-avresample --cc=clang --host-cflags=-fno-stack-check --host-ldflags= --enable-ffplay --enable-gnutls --enable-gpl --enable-libaom --enable-libbluray --enable-libdav1d --enable-libmp3lame --enable-libopus --enable-librubberband --enable-libsnappy --enable-libsrt --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxvid --enable-lzma --enable-libfontconfig --enable-libfreetype --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-librtmp --enable-libspeex --enable-libsoxr --enable-videotoolbox --disable-libjack --disable-indev=jack
  libavutil      56. 31.100 / 56. 31.100
  libavcodec     58. 54.100 / 58. 54.100
  libavformat    58. 29.100 / 58. 29.100
  libavdevice    58.  8.100 / 58.  8.100
  libavfilter     7. 57.100 /  7. 57.100
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  5.100 /  5.  5.100
  libswresample   3.  5.100 /  3.  5.100
  libpostproc    55.  5.100 / 55.  5.100
Input #0, h264, from 'abc':
  Duration: N/A, bitrate: N/A
    Stream #0:0: Video: h264 (High), yuvj420p(pc, progressive), 1200x1600, 25 fps, 25 tbr, 1200k tbn, 50 tbc
[swscaler @ 0x113a86000] deprecated pixel format used, make sure you did set range correctly
[h264 @ 0x7fee1e82a400] error while decoding MB 70 75, bytestream -6

Initial thoughts: It appears that, for your device ( I am guessing for all ipad mini of that specific hardware / software combination ) the video stream cannot be decoded properly by the hardware acceleration setup of ffmpeg. The software variant ( ffplay for example ) is capable of decoding it, but seems to recognize some corruption in the stream.
That corruption could be due to how the video stream is created on the device, or it could be to some issue with qvh.
Another thing that can be done to analyze the output it to use h264_analyze.
If you brew install h264bitstream you can then run h264_analyze abc to show the nalu information for every nalu present in the file.
A more shortened output that makes a bit more sense is h264_analyze abc | grep -e "unit_type\|frame_num" | less That will give you a less session, where you can page up and down and see the types of nalus present in the file.
Looking at that; it looks fine as far as the nalu types present in the file. It is a bit strange to me that there are multiple type=5 ( iframe ) at the start of each second of video. It appears that what is going on is that the iframes are split into multiple slices ( see the "first_mb_in_slice" on the repeated type: 5 nalus ).
My guess as to what is going on is that for that device, it is sending frames split up into pieces, and that the hardware encoder needs those pieces reassembled into single larger nalus to function properly.
There are two options here:

Reconfigure h264_to_jpeg to provide a software decoding option. This option, while it will consume more CPU power, should work. The question is if it will be able to keep up with the constant video stream. I'm not sure. It would need to be tested.
Learn more about the split up slices, and how to reassemble them into larger nalus before feeding them into the hardware decoder. This is more work than #1 but would be optimal. It is also speculation here. I think that would fix it but I couldn't be sure till trying it.

Could you share what exact hardware model and IOS version your Ipad Mini is?

There is a 3rd option I think. When I wrote h264_to_jpeg I assumed none of the frames are split up, so only a single NALU is pulled in for an iframe. In this case multiple NALUs form a single frame. If I just receive all the NALUs that go together and send them all into the hardware decoder it may work as well.

When I use ffplay the video does play on my screen, yes. It outputs errors as well but I believe it is still correctly displaying the video contained in the file. I don't understand the details of the errors but hopefully those are irrelevant to why it doesn't "work"

Could you share what exact hardware model and IOS version your Ipad Mini is?

my ipad mini model is ModelNumber: MGHV2
and here is detail info
chajunghyeob-XXXXX-SWgisulLab:ios_video_pull latte$ ideviceinfo
ActivationState: Activated
ActivationStateAcknowledged: true
BasebandActivationTicketVersion: V2
BasebandCertId:<PHONE_NUMBER>
BasebandChipID: 7282913
BasebandKeyHashInformation:
 AKeyStatus: 2
 SKeyHash: 7MQEUyvzG4gjjZc7KsNNAVTS8g4=
 SKeyStatus: 0
BasebandMasterKeyHash: AEA5CCE143668D0EFB4CE1F2C94C966A6496C6AA
BasebandRegionSKU: AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA==
BasebandSerialNumber: FMgOcA==
BasebandStatus: BBInfoAvailable
BasebandVersion: 8.30.01
BluetoothAddress: 6c:94:f8:c6:88:35
BoardId: 52
BrickState: false
BuildVersion: 15C202
CPUArchitecture: arm64
CarrierBundleInfoArray[0]:
CertID:<PHONE_NUMBER>
ChipID: 35168
ChipSerialNo: XXXXXXX
DeviceClass: iPad
DeviceColor: #3b3b3c
DeviceName: XXXXXXX iPad
DieID:<PHONE_NUMBER>352
EthernetAddress: XXXXXXX
FirmwareVersion: iBoot-4076.30.43
FusingStatus: 3
HardwareModel: J86mAP
HardwarePlatform: s5l8960x
HasSiDP: true
HostAttached: true
InternationalMobileEquipmentIdentity: XXXXXXX
MLBSerialNumber: XXXXXXX
MobileEquipmentIdentifier: XXXXXXX
MobileSubscriberCountryCode:
MobileSubscriberNetworkCode:
ModelNumber: MGHV2
NonVolatileRAM:
 auto-boot: dHJ1ZQ==
 backlight-level: MTU5OQ==
 boot-args:
 bootdelay: MA==
 com.apple.System.tz0-size: MHg2MDAwMDA=
 oblit-begins: T2JsaXRUeXBlOiBPYmxpdGVyYXRlRGF0YVBhcnRpdGlvbi4gTm8gcmVhc29uIGdpdmVuLg==
 obliteration: aGFuZGxlX21lc3NhZ2U6IE9ibGl0ZXJhdGlvbiBDb21wbGV0ZQ==
PartitionType: GUID_partition_scheme
PasswordProtected: false
PkHash: 09pXQgM5cjY6TJJNOOzO//R5JuGKqjHElfshBbnxrhg=
ProductName: iPhone OS
ProductType: iPad4,8
ProductVersion: 11.2.2
ProductionSOC: true
ProtocolVersion: 2
ProximitySensorCalibration: AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA=
RegionInfo: KH/A
SIMStatus: kCTSIMSupportSIMStatusNotInserted
SIMTrayStatus: kCTSIMSupportSIMTrayInsertedNoSIM
SerialNumber: XXXXXXX
SoftwareBehavior: GQIAAAAAAAAAAAAAAAAAAA==
SoftwareBundleVersion:
SupportedDeviceFamilies[2]:
 0: 1
 1: 2
TelephonyCapability: true
TimeIntervalSince1970:<PHONE_NUMBER>.665899
TimeZone: Asia/Seoul
TimeZoneOffsetFromUTC: 32400.000000
TrustedHostAttached: true
UniqueChipID: XXXXXXX
UniqueDeviceID: XXXXXXX
UseRaptorCerts: true
Uses24HourClock: true
WiFiAddress: XXXXXXX
kCTPostponementInfoPRIVersion: 0.1.141
kCTPostponementInfoPRLName: 0
kCTPostponementInfoServiceProvisioningState: false
kCTPostponementStatus: kCTPostponementStatusActivated

First of all, thanks for continuing to respond well,
As you predicted, I am also debugging with a few guesses, so I want to see if ios_video_pull delivers the content to h264_to_jpeg for the audio stream part in quicktime_video_hack.

Thanks for answering first.
Actually, I didn't know much about C and video, and I had a hard time looking through it.
In fact, when handling the iphone5 device, there was a "type 5" issue in quicktime_video_hack, but I didn't know if that was the problem.

There is a 3rd option I think. When I wrote h264_to_jpeg I assumed none of the frames are split up, so only a single NALU is pulled in for an iframe. In this case multiple NALUs form a single frame. If I just receive all the NALUs that go together and send them all into the hardware decoder it may work as well.

If you can handle all of them as aframe object as you said, I think it would be better to process them first.
I'm not sure because this is a part I don't know.

Be aware also of the update to the initial README today, and the addition of "bin/devreset". That command can/should be used to reset your IOS device into a fresh state whenever attempting to rerun ios_video_pull or the coordinator.
Without first doing that reset qvh and/or ios_video_pull will often have issues starting up.
Right now I have the sending of the audio stream portion of qvh manually disabled for the interaction with STF. In the future I will likely re-enable it and make it possible to pass the audio along but right now that does not happen and the audio data is intentionally discarded.
Understandably the C code and the nalu parsing and all of this stuff is quite confusing. I am mostly explaining the details as much as I understand them for reference. If someone comes along with the same problem and is willing to fix it that would be great too ( but I doubt that will happen anytime soon )
Essentially; yeah. It's broke for your device. I'll fix it when I have time. Thanks for providing the sample data so I have something to use to know when I've fixed it.
I wanted to know the model information that way if anyone else comes along with the same issue we can hopefully determine which devices / IOS versions have the problem.

I'll wait for your code to be updated.
And I will report any new issues afterwards
Thanks for sharing a good  project!

I'm trying to share a version that solves the ipad mini3 issue, so I don't know the C language so I wrote the Codec part as GO.
I tried to pull request the changed part to ios-video-pull and it seemed to have been modified too much, so I created a new project.
here is git url

https://github.com/jjunghyup/ios-screen-mirror


code generation error

Why do I get this error while compiling the "simple_window" example code in a new project module? Compiles fine when run inside gobbi/example/simple_window
$ go build -tags "gobject_2.56 glib_2.56 gdk_3.22 gdkpixbuf_2.36 gio_2.56 gtksource_3.24 gtk_3.22"
# github.com/pekim/gobbi/internal/generate
../../../go/pkg/mod/github.com/pekim/gobbi@v0.1.0/internal/generate/namespace-file-generate.go:21:6: file.NoFormat undefined (type *jen.File has no field or method NoFormat)

It looks like this is a regression introduced in v0.1.0.
I can see where the problem is. I'll try and fix it and release a new version of gobbi shortly.

This is fixed in v0.1.1.
Sorry for introducing not just a regression, but one with such a confusing manifestation.

Fixes the issue. Thank you.


Royal Family

Hello! You already have our family of clans, but we have a new clan and logo. How can I edit? https://royaleapi.com/clan/family/royal/clans


Transaction  successfully accepted in the  LTC blockchain but the LW dat file was corrupted

Steps to reproduce:

Prepare to receive an amount to Loafwallet.
Observe the amount is received 100% in the Transactions View
Get into a low bandwidth scenario e.g. "Airplane Mode" for > 8 hrs
Open to a full bandwidth mode.
Observe transaction is missing from the  Transactions View  yet confirm the amount remains in the blockchain

Users should resync the blockchain if this occurs - this is what we've been recommending in Support. Otherwise requires complex changes to the loafwallet-core library.

Closing as this was user error.


LLM

@CodiumAI-Agent /review

PR Reviewer Guide 🔍

 ⏱ Estimated effort to review [1-5]
4

 🧪 Relevant tests
No

 🔒 Security concerns
Sensitive information exposure: The Google API key is exposed in the source code (`client/frontEnd/src/APIKey.jsx`), which is a security risk. This should be stored in environment variables and loaded securely.

 ⚡ Key issues to review

Possible Bug: The Signup component in client/frontEnd/src/Components/Signup.jsx does not handle the case where the server might return an error other than "User already exists". It assumes any other error is a sign-up failure, which might not always be the case.

Security Concern: The API key for Google's services is hardcoded in client/frontEnd/src/APIKey.jsx. This exposes sensitive information and should be moved to environment variables.

Code Duplication: There is repeated code in client/frontEnd/src/Components/Build.jsx for filtering storage data based on interface type. This could be refactored into a single function that accepts the interface type as a parameter.

Performance Concern: The run function in client/frontEnd/src/Components/Build.jsx creates a new instance of GoogleGenerativeAI every time it is called. This could be inefficient and may lead to performance issues. It would be better to instantiate this once and reuse it.


another implementation of schema tracker

Is your feature request related to a problem?
Currently schema tracker is an embedded TiDB with unistore as its storage. Before v2.0.7, the storage is mocktikv. It has many problems:

embedded TiDB may has some bugs: from an issue, user reports that the unistore folder eats up to 18GB space. Here is another issue from a different user https://github.com/pingcap/tiflow/issues/4187
Although we can change the unstore folder to another place, and clean the folder after the replication task is stopped, some user may still don't have a good place to support a long-running task. In v2.0.1 when the storage is mocktikv, it uses memory rather than disk to serve the embedded TiDB, we also received huge memory usage issue on that version.
configuration of embedded TiDB: The embedded TiDB should be well configurated about so it can support any table structure that downstream supports. For example, in https://github.com/pingcap/tiflow/issues/5315 user changed the max-index-length but embedded TiDB didn't change it. And new features like clustered index has different behaviours about ALTER PRIMARY KEY.
Other problems that is caused by TiDB not being designed as a library, like https://github.com/pingcap/tiflow/issues/3402, https://github.com/pingcap/tidb/pull/28027, https://github.com/pingcap/tidb/issues/18714, and many ugly patches on TiDB configurating to turn off some functionalities https://github.com/pingcap/tiflow/blob/9bcebc1f23d29fa739e17c5c65a19b6a7f698f8e/dm/pkg/schema/tracker.go#L111-L119, https://github.com/pingcap/tiflow/blob/9bcebc1f23d29fa739e17c5c65a19b6a7f698f8e/dm/pkg/schema/tracker.go#L170-L172

Describe the feature you'd like
debezium uses the result of SQL parser to directly mutate the column map and other structures.
https://github.com/debezium/debezium/blob/9f7ede0e0695f012c6c4e715e96aed85eecf6b5f/debezium-core/src/main/java/io/debezium/relational/TableEditorImpl.java
https://github.com/debezium/debezium/blob/b78e3183997b3d4ef044c0d13d9503829124fc92/debezium-connector-mysql/src/main/java/io/debezium/connector/mysql/antlr/listener/AlterTableParserListener.java#L284
DM can organize the TableInfo on its own, such as keep a map of {SchemaName -> {SchemaInfo, {TableName -> TableInfo}}.
For the creation and mutation of TableInfo, TiDB can expose some public functions which is already used by DDL component to ensure the correctness. These functions only require least parameters, computes the result and has no other effects.
Such as
newTableInfo := CreateTable(dbInfo, tableInfo) // fills some explit properties from DBInfo?
newTableInfo := ModifyColumn(tableInfo, GetModifyInfo(columnInfo)) // reuse the complex modify logic

Also, these functions can skip the check that is related to TiDB configurations, like max-index-length
Describe alternatives you've considered

DM don't need to maintain a whole TableInfo, it only needs to maintain column names, column order and PK/UK information.
we fix above issues

Teachability, Documentation, Adoption, Migration Strategy
No response

just found we missed another setting
https://github.com/pingcap/tidb/issues/34931


Problem with margin on FAB

Thanks for your job.
There is a problem when I set a margin to the FAB.
I try to use your component with a fullscreen sheet and if I have a margin on the FAB the sheet is shifted. (regarding to the fab margins)

Hi,
This is because whenever opening the sheet, the sheet's position is automatically aligned with the FAB. I may add an attr in the future to disable this behavior, but for now you can add negative margins to your sheet as a workaround:
<android.support.design.widget.FloatingActionButton
    android:id="@+id/overview_fab"
    android:layout_width="wrap_content"
    android:layout_height="wrap_content"
    android:layout_marginRight="16dp"
    android:layout_marginBottom="16dp" />

<android.support.v7.widget.CardView
    android:layout_width="match_parent"
    android:layout_height="match_parent"
    android:layout_marginRight="-16dp"
    android:layout_marginBottom="-16dp">


Feature#465v3

Cache added to the challenge microservice.

CacheConfig class created and configured to have an expiration time of 10 minutes.
@Cacheable added to all the methods on ChallengeServiceImp that have database queries.
@CacheEvict added to all the methods on ChallengeServiceImp that modify the database.
ChallengeServiceImplCacheTest class created checking that the cache is correctly implemented.
getSolutions method on ChallengeServiceImp corrected to return the correct expected List.
The list of the methods on UserSolutionServiceImp on the user microservice that are candidates to use cache and are commented with //@Cacheable:

getChallengeById
getChallengeStatistics
getBookmarkCountByIdChallenge
getChallengeUsersPercentage
getUserSolutions
getUserSolutionsChallenge

There is a conflict, please review it :)


GHC 9.6.1 does not work with Cabal 3.6

Description
Virtual environments of 2023-03-13 ship GHC 9.6.1 with cabal <IP_ADDRESS>, which do not work together.
Need to update cabal to at least 3.8.  Native cabal version for GHC 9.6.1 is 3.10.
(Previous environments shipped GHC 9.4.4 with cabal <IP_ADDRESS>, which was fine.)
The combination of GHC 9.6 and cabal 3.6 fails for custom-setup packages like Agda:
https://github.com/agda/agda/actions/runs/4450907695/jobs/7816927352?pr=6544#step:4:22
[__1] rejecting: Agda:setup.Cabal-<IP_ADDRESS>/installed-<IP_ADDRESS>,
Agda:setup.Cabal-<IP_ADDRESS>, Agda:setup.Cabal-<IP_ADDRESS> (constraint from maximum version of Cabal used by Setup.hs requires <3.8)

Note the "constraint from maximum version of Cabal used by Setup.hs":  It is a global constraint fixed by cabal:
https://github.com/haskell/cabal/blob/6870def8e1e21e04d737d8c176bd7efce8fcc366/cabal-install/src/Distribution/Client/ProjectPlanning.hs#L1257-L1258
I witnessed this in ubuntu-22.04, but likely all other platforms that ship GHC 9.6 are affected as well.
Evidence from workflow run:

Image version: https://github.com/agda/agda/actions/runs/4450907695/jobs/7816927352?pr=6544#step:1:8Image: ubuntu-22.04
Version: 20230313.1

GHC and cabal versions: https://github.com/agda/agda/actions/runs/4450907695/jobs/7816927352?pr=6544#step:3:12GHC_VER   = 9.6.1
CABAL_VER = <IP_ADDRESS>

Platforms affected

[ ] Azure DevOps
[X] GitHub Actions - Standard Runners
[ ] GitHub Actions - Larger Runners

Runner images affected

[ ] Ubuntu 18.04
[ ] Ubuntu 20.04
[X] Ubuntu 22.04
[ ] macOS 11
[ ] macOS 12
[ ] Windows Server 2019
[ ] Windows Server 2022

Image version and build link
Image version: https://github.com/agda/agda/actions/runs/4450907695/jobs/7816927352?pr=6544#step:1:8
Image: ubuntu-22.04
Version: 20230313.1

Is it regression?
Yes, worked with 20230305.1, see https://github.com/agda/agda/actions/runs/4434218810/jobs/7779994899#step:1:9
Expected behavior
Succeed setting up installation of Agda.
Actual behavior
Fails setting up installation of Agda.
Repro steps
All information about reproducibility is contained in the workflow run: https://github.com/agda/agda/actions/runs/4450907695/jobs/7816927352?pr=6544
The issue was originally discovered in this PR:
https://github.com/agda/agda/pull/6544#issuecomment-1474313196

Hello @andreasabel! Thank you for the info. From that point of view it looks like we really should change a bit installation for cabal to use latest. We'll check and return with updates or answer later.

CC @hasufell

Should be fixed


fix: allow copy pasting layer location in Firefox

In Firefox, "disabled" disables any interaction with the
layer entry field whereas in Chrome it allows you to select
the text in the box -- a common workflow when using CloudVolume
to grab the layer path.
A standard property "readOnly" is available that works cross-browser.

Thanks!


Fix unit tests after refactor

The tests test_trim_source_tiles() and test_process_active_pixels() are important but didn't get updated after the last refactor.

Tentatively fixed in https://github.com/jeff-regier/Celeste.jl/pull/279

I think #279 fixed #275 rather than this one.

Fixed in https://github.com/jeff-regier/Celeste.jl/pull/301, for real this time.

Thanks for fixing them
On Thu, Sep 15, 2016, 4:18 PM Ryan<EMAIL_ADDRESS>wrote:

Closed #262 https://github.com/jeff-regier/Celeste.jl/issues/262.
—
You are receiving this because you modified the open/close state.
Reply to this email directly, view it on GitHub
https://github.com/jeff-regier/Celeste.jl/issues/262#event-791473193,
or mute the thread
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the version 1.1.6 couldn't from password and keystore to  get the privateKey

1 month ago I downloaded the  framework  . It worked good. But these days I pod update, I find that the version 1.1.6 couldn't from password and keystore to  get the privateKey and I don't know how to find the last version. I find the code  is different in the file "CryptoExtensions.swift" from the old one.
Dear lovely writer, I am hearing from you!!!!
PS:  I find the useful version 1.1.1 ，you can judge that use my func  testPrivateKey, I promise that 1.1.6 need to solve the problem
func testPrivateKey() {
        let key = Data.init(base64Encoded: "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")
        let password = "111111"
        let keystore = EthereumKeystoreV3.init(key!)
        let account = keystore!.addresses![0]
        let privateKey = try! keystore!.UNSAFE_getPrivateKeyData(password: password, account: account)
        let str = privateKey.toHexString()
        print(str)
    }

Dear  lovely writer:  I discovered the nature of the problem!!!
You use scrypt instead of libsodium!!!!
But my project still need libsolidum to do so many encryption and decryption function!!!!
And the  scrypt and libsolidum has the same func name "escrypt_kdf_nosse"
(the scrypt --> Cimpl.c    the libsolidum -->pwhash_scryptsala.......   .c)
That lead to a confiction and so that the new func Cimpl.c   doesn't work . and the the libsolidum execute method get the trouble answer!!!
I will still use the very important framework libsodium to do some  encryption and decryption. So I have to use the old web3swift  (Cocoapods ).
But I hope I can use the lastest web3swift version. I think it must be stronger.
Do you have some good advice ? Or tell me what should I do can solve that problem?
I am hearing from you!!!! Please call me back.🆙 ❤
PS: very handsome writer ,there is no func below, but I knew what do you mean.
EthereumKeystoreV3.init(key!, password: password) !!! Here

I've also updated the Scrypt library to have another function name, you should be fine after the pod update

well done!  thanks  a lot.


⚠ Processors has degraded performance

In 3446456, Processors ($STATUS_URL) experienced degraded performance:

HTTP code: 200
Response time: 48 ms

Resolved: Processors performance has improved in eec11b9.


Updates to the base link

Make the text underline configurable.
Apply an optional transition for the colour.

Don't forget to update Button Faux Link component also

Addressed in #99.


fix(relayer): shell script update

what does this fix? abigen already reports an error directly, there is no need to wrap it

Just added these simple checks that allows user to verify the commands are run successfully

it will already fail with a given error, this isnt needed tbh


Fix perspective orientation button colors

Feel free to do the check list, if I don't get a chance.
I will merge if the checks have been passed by either one of us

Only the knows issues, which already exist on the production, couldn't pass the test.


HDFS-16303. Improve handling of datanode lost while decommissioning

Description of PR
Backport of this trunk commit to Hadoop 3.x
How was this patch tested?
All "TestDecommission", "TestDecommissionWithBackoffMonitor", & "DatanodeAdminManager" tests pass when run locally
Same manual testing from https://github.com/apache/hadoop/pull/3675 applies.
For code changes:

[x] Does the title or this PR starts with the corresponding JIRA issue id (e.g. 'HADOOP-17799. Your PR title ...')?
[n/a ] Object storage: have the integration tests been executed and the endpoint declared according to the connector-specific documentation?
[n/a] If adding new dependencies to the code, are these dependencies licensed in a way that is compatible for inclusion under ASF 2.0?
[n/a] If applicable, have you updated the LICENSE, LICENSE-binary, NOTICE-binary files?

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306m 38s

Reason
Tests

Failed junit tests
hadoop.hdfs.server.namenode.ha.TestStandbyCheckpoints

hadoop.hdfs.server.datanode.TestDataNodeRollingUpgrade

hadoop.hdfs.client.impl.TestBlockReaderLocalMetrics

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git revision
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328m 54s

Reason
Tests

Failed junit tests
hadoop.hdfs.server.datanode.fsdataset.impl.TestLazyPersistReplicaRecovery

hadoop.hdfs.server.datanode.TestBPOfferService

hadoop.hdfs.server.datanode.TestDataNodeVolumeFailureReporting

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Optional Tests
dupname asflicense compile javac javadoc mvninstall mvnsite unit shadedclient spotbugs checkstyle codespell

uname
Linux 371ae086db04 4.15.0-112-generic #113-Ubuntu SMP Thu Jul 9 23:41:39 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
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git revision
branch-3.3 / 99a7dc166b06fc69e443b445e02f0f292229a9ed

Default Java
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[ERROR] Tests run: 17, Failures: 1, Errors: 0, Skipped: 0, Time elapsed: 75.795 s <<< FAILURE! - in org.apache.hadoop.hdfs.server.datanode.TestBPOfferService
[ERROR] testMissBlocksWhenReregister(org.apache.hadoop.hdfs.server.datanode.TestBPOfferService)  Time elapsed: 15.474 s  <<< FAILURE!
java.lang.AssertionError
    at org.junit.Assert.fail(Assert.java:87)
    at org.junit.Assert.assertTrue(Assert.java:42)
    at org.junit.Assert.assertTrue(Assert.java:53)
    at org.apache.hadoop.hdfs.server.datanode.TestBPOfferService.testMissBlocksWhenReregister(TestBPOfferService.java:350)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)

This is a flaky test:

"TestBPOfferService#testMissBlocksWhenReregister fails intermittently"
https://issues.apache.org/jira/browse/HDFS-15646

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0m 41s

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hadoop.hdfs.server.datanode.TestBPOfferService

hadoop.hdfs.server.blockmanagement.TestUnderReplicatedBlocks

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Unit tests failures are related to flaky tests
[ERROR] Failures:
[ERROR]   TestBPOfferService.testMissBlocksWhenReregister:350
[ERROR] Errors:
[ERROR]   TestUnderReplicatedBlocks.testSetRepIncWithUnderReplicatedBlocks:80 Â» TestTimedOut
[INFO]
[ERROR] Tests run: 6738, Failures: 1, Errors: 1, Skipped: 22

TestBPOfferService.testMissBlocksWhenReregister:

https://issues.apache.org/jira/browse/HDFS-15646
"TestBPOfferService#testMissBlocksWhenReregister fails on trunk"
"TestBPOfferService#testMissBlocksWhenReregister fails intermittently"
"TestBPOfferService#testMissBlocksWhenReregister is flaky"

TestUnderReplicatedBlocks.testSetRepIncWithUnderReplicatedBlocks:

https://issues.apache.org/jira/browse/HDFS-15646
"TestUnderReplicatedBlocks#testSetrepIncWithUnderReplicatedBlocks test timeout"

@aajisaka please review this PR to backport https://issues.apache.org/jira/browse/HDFS-16303

This PR contains the change in https://github.com/apache/hadoop/pull/3923.
Would you address https://github.com/apache/hadoop/pull/3923#issuecomment-1020721954? You'll need to do the followings:

Create a separate jira to track the small fix
Remove the fix from this PR

Then I will merge this PR and backport the separate fix. Thanks.

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Failed junit tests
hadoop.hdfs.TestRollingUpgrade

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Optional Tests
dupname asflicense compile javac javadoc mvninstall mvnsite unit shadedclient spotbugs checkstyle codespell

uname
Linux 97325c2bd100 4.15.0-65-generic #74-Ubuntu SMP Tue Sep 17 17:06:04 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux

Build tool
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git revision
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Thank you @KevinWikant for backporting this!


Fix issue #969: Add support for single line exclusions

Fixes #969

Codecov Report

Merging #1085 into develop will increase coverage by 0.02%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           develop   #1085      +/-   ##
==========================================
+ Coverage    84.87%   84.9%   +0.02%
==========================================
  Files           41      41
  Lines         3617    3623       +6
  Branches       654     654
==========================================
+ Hits          3070    3076       +6
  Misses         412     412
  Partials       135     135

Impacted Files
Coverage Δ

isort/profiles.py
100% <100%> (ø)
:arrow_up:

isort/output.py
96.77% <100%> (ø)
:arrow_up:

tests/test_isort.py
99.23% <100%> (ø)
:arrow_up:

isort/main.py
64.31% <100%> (+0.14%)
:arrow_up:

isort/settings.py
82.29% <100%> (+0.05%)
:arrow_up:

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Field Configuration Modifiers

This is a brainstorm of my idea for https://trello.com/c/1hNDoqon/74-ability-to-add-field-configuration-modifiers
It would probably replace the need for #102; I think this is more flexible and means we don't have to deal with crazy generic statics.
Thoughts @bendetat @MattDavies @zabulus?

// Create this class (happy to field better naming ideas)
public class FormFieldOutput<TModel, T>
{
    public FormFieldOutput(FieldParent parent)
    {
        Parent = parent;
    }

    public FieldParent Parent { get; private set; }

    public IFieldGeneratorHandler<TModel, T> Handler { get; set; }
    public IFieldConfiguration Configuration { get; set; }
    public IFormTemplate Template { get; set; }
    public ModelMetadata Metadata { get; set; }

    public ReadonlyFieldConfiguration GetReadonlyConfiguration()
    {
        return new ReadonlyFieldConfiguration(Configuration);
    }
}

// Change DefaultFieldGenerator.PrepareFieldConfiguration to:
        public FormFieldOutput<TModel, T> PrepareField(IFieldConfiguration fieldConfiguration, FieldParent fieldParent)
        {
            var field = new FormFieldOutput(fieldParent)
            {
                Handler = FieldGeneratorHandlersRouter<TModel, T>.GetHandler(this),
                Configuration = fieldConfiguration ?? new FieldConfiguration(),
                Template = Template,
                Metadata = Metadata
            }

            // This call could result in the handler, field config, template or metadata being changed on the fly for this field
            // In order to make things more testable / extendable we could put the conventions on the IForm object instead of in a static?
            FieldConventions.ForEach(c => c.Apply(field));

            field.Handler.PrepareFieldConfiguration(fieldConfiguration);
            field.Template.PrepareFieldConfiguration(this, handler, fieldConfiguration, fieldParent);

            return field;
        }

// These conventions will be defined by default (but can be removed), which were in the above method previously:
public class ReadonlyFieldsConvention : IFormConvention
{
    public void Apply<TModel, T>(FormFieldOutput<TModel, T> field)
    {
        if (field.IsReadOnly)
            field.Configuration.Readonly();
    }
}
public class FormatStringConvention : IFormConvention
{
    public void Apply<TModel, T>(FormFieldOutput<TModel, T> field)
    {
        if (!string.IsNullOrEmpty(field.Metadata.EditFormatString) && string.IsNullOrEmpty(field.Configuration.FormatString))
            field.Configuration.WithFormatString(field.Metadata.EditFormatString);
    }
}
public class NoneDisplayTextConvention : IFormConvention
{
    public void Apply<TModel, T>(FormFieldOutput<TModel, T> field)
    {
        if (!string.IsNullOrEmpty(field.Metadata.NullDisplayText) && string.IsNullOrEmpty(field.Configuration.NoneString))
            field.Configuration.WithNoneAs(field.Metadata.NullDisplayText);
    }
}

// And people can create and register their own conventions like this:

FieldConventions.Add(new AddCalendarToDateFieldsConvention());

...

public class AddCalendarToDateFieldsConvention : IFormConvention
{
    public void Apply<TModel, T>(FormFieldOutput<TModel, T> field)
    {
        if (typeof(T) == typeof(DateTime) || typeof(T) == typeof(DateTimeOffset))
            field.Configuration.AddClass("datepicker").WithFormatString("{0:dd/MM/yyyy}");
    }
}

There is something awkward in this proposal, in that the conventions would override configuration set for a form (it is my understanding that the PrepareField stuff is invoked right before rendering, please correct me if I'm wrong). For some attributes, this is not important (eg, the readonly attribute), but for others it would. Your examples have checks for user settings, but that is impossible for properties that are value types (eg, ShouldInlineLabelWrapElement).

There is something awkward in this proposal, in that the conventions would override configuration set for a form (it is my understanding that the PrepareField stuff is invoked right before rendering, please correct me if I'm wrong). For some attributes, this is not important (eg, the readonly attribute), but for others it would. Your examples have checks for user settings, but that is impossible for properties that are value types (eg, ShouldInlineLabelWrapElement).

Thanks @fsateler. I'll keep that in mind if we get to the point of implementing this.
Happy for you or anyone else to suggest changes or even submit a PR for the change :)


Rewrite app probe sends requests to the wrong endpoint, breaking pod IP listeners

Bug description
When kubernetes is probing the pod's readiness / liveness probe, it is always returning connection refused
2020-07-02T03:16:51.019635Z error Request to probe app failed: Get "http://localhost:8558/ready": dial tcp
<IP_ADDRESS>:8558: connect: connection refused, original URL path = /app-health/miniapp/readyz
app URL path = /ready
2020-07-02T03:16:57.829163Z error Request to probe app failed: Get "http://localhost:8558/alive": dial tcp
<IP_ADDRESS>:8558: connect: connection refused, original URL path = /app-health/miniapp/livez
app URL path = /alive
2020-07-02T03:17:01.020098Z error Request to probe app failed: Get "http://localhost:8558/ready": dial tcp
<IP_ADDRESS>:8558: connect: connection refused, original URL path = /app-health/miniapp/readyz
app URL path = /ready
2020-07-02T03:17:07.832858Z error Request to probe app failed: Get "http://localhost:8558/alive": dial tcp
<IP_ADDRESS>:8558: connect: connection refused, original URL path = /app-health/miniapp/livez
app URL path = /alive
2020-07-02T03:17:11.019798Z error Request to probe app failed: Get "http://localhost:8558/ready": dial tcp
<IP_ADDRESS>:8558: connect: connection refused, original URL path = /app-health/miniapp/readyz
app URL path = /ready
2020-07-02T03:17:17.828587Z error Request to probe app failed: Get "http://localhost:8558/alive": dial tcp
<IP_ADDRESS>:8558: connect: connection refused, original URL path = /app-health/miniapp/livez
app URL path = /alive
2020-07-02T03:17:21.019642Z error Request to probe app failed: Get "http://localhost:8558/ready": dial tcp
<IP_ADDRESS>:8558: connect: connection refused, original URL path = /app-health/miniapp/readyz
app URL path = /ready
2020-07-02T03:17:27.829042Z error Request to probe app failed: Get "http://localhost:8558/alive": dial tcp
<IP_ADDRESS>:8558: connect: connection refused, original URL path = /app-health/miniapp/livez
app URL path = /alive
2020-07-02T03:17:31.019802Z error Request to probe app failed: Get "http://localhost:8558/ready": dial tcp
<IP_ADDRESS>:8558: connect: connection refused, original URL path = /app-health/miniapp/readyz
app URL path = /ready
2020-07-02T03:17:51.019767Z error Request to probe app failed: Get "http://localhost:8558/ready": dial tcp
<IP_ADDRESS>:8558: connect: connection refused, original URL path = /app-health/miniapp/readyz
app URL path = /ready

Apparently this PR  should have fixed this but I tested on this version and its failing
[ ] Configuration Infrastructure
[ ] Docs
[ ] Installation
[ X] Networking
[ ] Performance and Scalability
[ ] Policies and Telemetry
[ ] Security
[ ] Test and Release
[ ] User Experience
[ ] Developer Infrastructure
Expected behavior
Readiness probe and liveness probe should be accessible. I am able to access the probes directly from other pods by curl and its returning 200 OK. It seems probe request are still going thru the sidecar proxy
curl http://<IP_ADDRESS>:8558/ready
OK

Steps to reproduce the bug
Here is my sample pod configuration (as we can see I have added the probes to outbound exclusion port so it doesn't pass thru envoy sidecar proxy, also only 9000 traffic will pass thru into the sidecar proxy so traffic going into probes listening on port 2552, 8558 will be accessible directly without going thru the sidecar proxy)

Install istio
Deploy pod to namespace with injection enabled
As pod is starting, it will probe checks will fail

Here is my pod yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: miniapp-deployment
spec:
  replicas: 1
  selector:
    matchLabels:
      component: miniapp
      app: miniapp-lagom
  template:
    metadata:
      labels:
        component: miniapp
        app: miniapp-lagom
      annotations:
        traffic.sidecar.istio.io/includeInboundPorts: "9000"
        traffic.sidecar.istio.io/excludeOutboundPorts: "2552,8558"

    spec:
      containers:
        - name: miniapp
          #image: <IP_ADDRESS>:5000/miniapp-impl:0.1.2
          imagePullPolicy: Always
          env:
            - name: REQUIRED_CONTACT_POINT_NR
              value: "1"
            - name: JAVA_OPTS
              value: "-Dconfig.resource=application-k8s.conf"
            - name: PGPASSWORD
              valueFrom:
                secretKeyRef:
                  name: miniapp
                  key: pgpassword
          ports:
            - name: management
              containerPort: 8558
              protocol: TCP
            - name: live
              containerPort: 9000
          readinessProbe:
            httpGet:
              path: "/ready"
              port: management
            periodSeconds: 10
            failureThreshold: 10
            initialDelaySeconds: 20
            timeoutSeconds: 1
          livenessProbe:
            httpGet:
              path: "/alive"
              port: management
            periodSeconds: 10
            failureThreshold: 10
            initialDelaySeconds: 20
            timeoutSeconds: 1
      imagePullSecrets:
        - name: awsecr-cred

Here is my service yaml
apiVersion: v1
kind: Service
metadata:
  name: miniapp-cluster-ip-service
spec:
  type: NodePort
  selector:
    component: miniapp
    app: miniapp-lagom
  ports:
    - port: 3101
      targetPort: 9000
      name: http-live

Version (include the output of istioctl version --remote and kubectl version and helm version if you used Helm)
istioctl : 1.6
kubectl : 1.17
How was Istio installed?
I tried two configurations: minimal and demo and issue persists on both
istioctl manifest apply --set profile=minimal --set values.sidecarInjectorWebhook.rewriteAppHTTPProbe=true
istioctl manifest apply --set profile=demo --set values.sidecarInjectorWebhook.rewriteAppHTTPProbe=true
Environment where bug was observed (cloud vendor, OS, etc)
Bare metal kubernetes cluster running on top of Ubuntu
I'm getting below error when attempting to extract cluster state archive
bash: ./dump_kubernetes.sh: Permission denied

Does /ready listen on the pod ip? maybe that is why request to localhost fails. I don't think the problem is going through envoy

@howardjohn
Hi, I think yes its listening to the pod IP, I tried getting the pod's IP and curling it directly and it results into Success. Sorrty I didnt get why the request to localhost fails, where should the /ready be listening into instead?

<IP_ADDRESS> or <IP_ADDRESS>
@incfly is this expected that we require this? shouldn't we send to the same destination that kubelet does?

"The kubelet sends the probe to the pod’s IP address, unless the address is overridden by the optional host field in httpGet."
I think we need this logic in the rewrite probe if we don't already

If we change to sending to pod IP, we need to be careful about what happens if existing users are listening on localhost. We may need a flag or big release note

cc @sdake

not stale
On Sat, Nov 14, 2020, 9:03 PM Istio Policy Bot<EMAIL_ADDRESS>wrote:

🧭 This issue or pull request has been automatically marked as stale
because it has not had activity from an Istio team member since 2020-08-16.
It will be closed on 2020-11-29 unless an Istio team member takes action.
Please see this wiki page
https://github.com/istio/istio/wiki/Issue-and-Pull-Request-Lifecycle-Manager
for more information. Thank you for your contributions.
Created by the issue and PR lifecycle manager.
—
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.

This is possibly going to be addressed in 1.10. working on a design

This is possibly going to be addressed in 1.10. working on a design

Fixed by #31121


Bring GHW clone and partition type into sdk

Centralize the Kairos Partition and the methods for getting partitions from the system

Everything copied from other places right? I assume more PRs will follow up to clean up other repos.

Everything copied from other places right? I assume more PRs will follow up to clean up other repos.

mainly yes. There is things like the Path struct that its a derivation of what ghw has as we dont need that much, and a lot of dropped methods as we dont use them (we dont care about the disk model for example or the wwn)
Still, I need to improve as I would like to store the disk UUID so we can identify the disk by the UUID directly (remember the kairos disk predictable uuid?) which can come in handy in the future.

ah yes, there is also an improvements in the Partition struct as we now store the type of FS and the UUID (again, improvements for the future in identifying the disk via a constant uuid :D)


Bug in Simulator setup

https://github.com/stefanradev93/BayesFlow/blob/749c0a6a04ed157eb3505796a4571e73405f5dc6/bayesflow/simulation.py#LL745C1-L745C53 - this should be self.prior_is_batched = self.prior.is_batched, if I am not mistaken

Relatedly, I am running into an issue where I am inheriting Prior & Simulator classes, but since you check type(prior) is Prior instead of isinstance(prior, Prior), it fails to run within GenerativeModel - do you want me to change that & PR to Development or change it yourself?


Implement Workflow for Auto-Commit on Issue Closure

Description:
I'm thrilled to submit this pull request introducing a new workflow that automates the commit process upon issue closure. This enhancement streamlines our development workflow, ensuring that changes are recorded promptly and accurately.
Usable
When the issues will close by you then the github-actions will automatic comment for issues close paragraph
@avinashkranjan Thank you for considering this enhancement. I eagerly await your feedback.

Hey @mdazfar2, Please make changes as suggested by sourcery-ai

@avinashkranjan believe me, it is fully functional. I will create a pull request after hands-on.

sourcery-ai It's for fail safe, kindly make the changes as asked, You haven't made the changes and yet you have resolved, It's not about the working. Kindly read what the changes that has been asked.


Website with draft version of the spec

There used to be a draft of the derivative spec here: https://bids-specification.readthedocs.io/en/derivatives/05-derivatives/06-diffusion-derivatives.html, but that link now seems broken and I can't seem to be able to find that document anymore. Does anyone know where it went?

ohy. @franklin-feingold perhaps we can find it in an older commit?

i presume this was live when the derivatives spec was all together? perhaps @effigies may know?

The derivatives branch appears to have been deleted by @sappelhoff on Nov 24, 2020 (https://github.com/bids-standard/bids-specification/pull/207#event-4033525547), so the RTD build was probably also removed at that point.
What if we had a wip-derivatives that was just master with BEPs 11, 12 and 16 merged in, updated periodically?
Also, would anybody have an objection to me merging master into this branch?

No objections on my end

sorry for causing this trouble, I probably deleted it as a "stale" branch and I didn't give it a second thought that there was still something important on there. Chris' suggestion sounds good.

I see that there is now:

05-diffusion-derivatives-tractography.md
05-diffusion-derivatives.md

Which of these should come first?

In any event: https://bids-specification.readthedocs.io/en/wip-derivatives/05-derivatives/05-diffusion-derivatives.html
Tractography is not in the TOC, and 05 is clashing with fMRI (though that has no effect on the rendering).


V2.TransformText  V3.TransformText didn't use domain by UseRecaptchaNet

V2.TransformText  V3.TransformText didn't use domain in address.
Like this:
var domain = UseRecaptchaNet ? "www.recaptcha.net" : "www.google.com";

Thanks for the report, this should be resolved in 2.2.5 if it's still an issue please reopen for consideration in the new 3.x version.


[SPARK-21822][SQL]When insert Hive Table is finished, it is better to clean out the tmpLocation dir

What changes were proposed in this pull request?
When insert Hive Table is finished, it is better to clean out the tmpLocation dir(the temp directories like ".hive-staging_hive_2017-08-19_10-56-01_540_5448395226195533570-9/-ext-10000" or "/tmp/hive/..." for an old spark version).
Otherwise, when lots of spark job are executed, millions of temporary directories are left in HDFS. And these temporary directories can only be deleted by the maintainer through the shell script.
How was this patch tested?

Can one of the admins verify this patch?

I think this change is very useful, auto-delete tmp location dir like : .hive-staging_xxxxxx could make everyone only see the target table's partition dir.

Can one of the admins verify this patch?

I think the problem is gone, right? Could you see the latest file version:
https://github.com/apache/spark/blob/master/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/InsertIntoHiveTable.scala

@figo77 Could you close it?


Python Example is Outdated

requirements.txt lists splunk-opentelemetry but it should be splunk-opentelemetry[all] as mentioned in Spluk official doc.
When not using [all], with default settings, we get below error.
ValueError: exporter "otlp (otlp_proto_grpc)" not found. please make sure opentelemetry-exporter-otlp-proto-grpc is installed

Is there anything holding up this change?
Would be good to know if there is a reason not to use splunk-opentelemetry[all] in certain situations.

I'm not sure why otlp was put behind a Python extra. The next major version of Splunk Otel Python will include it by default unless we discover a reason not to.
In the meantime, I've opened this PR for adding [all] to the requirements file for the example.

Appreciate it Pablo!

Completed, closing.


Ez vs Envelop plugins

I kinda understood ez uses envelop (a plugin system).
There are some plugins like DataLoader and GraphQL Modules that do the same thing (or that's what I'm aware) and are in both plugin hubs.
What are the differences between ez and envelop plugins?

TLDR: EZ Plugins often use the Envelop plugins under the hood, and they are most focused into the API Building process rather than execution, Envelop Plugins are for the execution of the API
The EZ Plugins work around the lifecycle of the API building process, In the section How EZ Plugins work? I try to explain it (without much depth yet) in the diagram.
the EZ DataLoader plugin uses under the hood the Envelop DataLoader plugin, and adds an extra helper called "registerDataLoader" in the EZ App builder (the object that has the function "buildApp") that does all the logic and minimizes boilerplate, including useful TypeScript helpers that allows you to add the dataloader into the Context Type very quickly.
The GraphQL Modules EZ Plugins also uses the Envelop GraphQL Modules plugin, and adds an extra helper called "registerModule" that also minimizes boilerplate.
GraphQL EZ still hasn't been officially released, and with that, all the docs are nowhere near perfect yet.

I get it now. I've been using GraphQL Ez for about two weeks because it is too easy (no pun intended) to setup. Previously, I used mercurius and mercurius-auth, I thought I'd wait for an ez plugin but I'll test out the generic-auth envelop plugin.
Thanks, keep up the great work.
Also are you opening the discussions tab or are you waiting for the release?

I forgot to enable it, now we have discussions tab 👍


Fix/issue 155 for not allowing negative weights and experiment time is not trimmed

Negative assignment weights are not allowed now, and they would show an error message on clicking next as shown below:

The experiment time on home page is now not trimmed for preceding '0' in hours and minutes as shown below:

I have changed the code to handle all condition errors together and show all error messages, earlier it was overwritten.

I have also addressed a similar time based UI issue for removing seconds, pointed by Zack in issue #152 as shown below:


Zerg Creep Stomach Upgrade

Added the Creep Stomach Upgrade, which:

[x] Allows zerg buildings to survive off creep
[x] Allows Spine Crawlers to burrow off-creep
[x] Allows Spore Crawlers to burrow off-creep

Misc tasks

[ ] Get the triggers working in the GUI triggers
[ ] Make a client-side PR to add the item and description for generation


Polkadot.js Issues.

When trying to claim my Pswap i keep getting this error. Im logged in with my ledger but it keeps giving me this error msg. Any input appreciated.
Something went wrong with the query and rendering of this component. Unable to find supported chain for 0x7e4e32d0feafd4f9c9414b0be86373f9a1efa904809b683453a9af6856d38ad5

Sora does not have Ledger app support. As per above it is limited to other chains only.


New signature for encoded values and tag parsers

So far we use encoded values like this: (using IntEncodedValue as an example, but it is the same for all EVs)
intEnc.setInt(reverse, edgeFlags, value);

This writes the int to the given edgeFlags (IntsRef) which serve as output type so to say.
Here, I changed this to:
intEnc.setInt(reverse, edgeId, intAccess, int value);

where intAccess is a new interface that can simply set or get an int.
This way we can use the same code as before, but using the intAccess interface instead of the concrete IntsRef we can basically 'redirect' the calls to any kind of (currently int-based) storage. The edgeId parameter allows us to identify the edge.
The most common use-case for this type of code is in BaseGraph where we get/set different encoded values for an edge. So far we would always copy the corresponding bits from (or to) an IntsRef to read/write data from/to the graph. To improve performance we cached these 'edgeFlags' between different reading calls. With the new IntAccess interface we can directly read from/write to the underlying storage (currently the edges DataAccess of the BaseGraph). According to my measurements this 'edgeFlag'-caching did not yield a speed-up compared to directly reading/writing from the DataAccess. In situations where there are many ints per edge but we only need a few of them the edge flag caching even yields a slow-down, because more ints are read than needed.
When we now call edge.set(enc) the BaseGraph passes an IntAccess implementation that directly reads from the edges DataAccess to the encoded value. However, we can also use encoded value implementations that ignore the given intAccess and store the data another way. In other words: We can now add encoded values to the encoding manager that store data somewhere outside the graph (the main motivation for this PR).
I also changed the TagParser interface accordingly.

I renamed IntAccess to EdgeIntAccess. To distinguish this from DataAccess I would probably rename DataAccess to DataStorage, but that's for another issue I would say.


Integrate ribasim lumping vrij afwaterend

This work is all done by Sweco, @harm-nomden-sweco. Originally pushed to the branch https://github.com/Deltares/Ribasim-NL/tree/ribasim_lumping_vrij_afwaterend, I created this copy to integrate it into main without changing the original.

I no longer exclude the scripts/ dir in ruff.toml, and applied the fixes to get that to pass.


Add MacOS agents

It would be good to also have pre-merge checks running on MacOS.
As Google Cloud does not offer MacOS machines, we need to get them from somewhere else. We probably need to discuss with the LLVM foundation on buying/renting these.

duplicate of #36


Update form validations to restrict new user name in lower case

Tasks

[ ] Update form validations in pages:

[ ] Registration
[x] Change user name

[x] Change input hints
[x] Change error message
[x] Add E2E test cases

References

Thread

Blockers

https://github.com/thematters/matters-server/issues/3244

Due to changing username needs email verification, we can't make a full E2E test, we only test input normalization here.
@devformatters @pitb2022


Add subset keyshare support (#1962) and keyupdate record limit (#1986)

Update Test Branch w/ select commits from Master branch
Description of changes:
PR #1962 and #1986
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.

This PR is also required: https://github.com/awslabs/s2n/pull/1963


Could not connect to development server

Hello;
I am getting the error in the header that I installed with Admob yarn. Why is it coming out. ? Help me, please. ?

package.json
{
  "name": "Addmobb",
  "version": "0.0.1",
  "private": true,
  "scripts": {
    "start": "node node_modules/react-native/local-cli/cli.js start",
    "test": "jest"
  },
  "dependencies": {
    "react": "16.3.1",
    "react-native": "0.55.3",
    "react-native-admob": "^2.0.0-beta.5"
  },
  "devDependencies": {
    "babel-jest": "22.4.3",
    "babel-preset-react-native": "4.0.0",
    "jest": "22.4.3",
    "react-test-renderer": "16.3.1"
  },
  "jest": {
    "preset": "react-native"
  }
}

This Error comes when USB cable disconnected. Reconnect your device and run the command again.


run dev error

This dependency was not found:

babel-runtime/regenerator in ./node_modules/pdfjs-dist/lib/web/ui_utils.js

To install it, you can run: npm install --save babel-runtime/regenerator

npm i --save babel-runtime

First of all, nice package. Would be nice to have mention about "npm i --save babel-runtime" in README though :)


Not working on IE8

This sample doesn't work on IE8, as I figured out that it's ADAL which is causing the problem, any solution for this ?

Hey @AbdoDabbas... What's the behavior you're seeing? Does the sample not run? Does the login redirect fail? Is there any error in the console?

There's an error in the console saying that Angular is not defined or something, it's like angular object is not defined at all, problem shows only when using ADAL with Angular in IE8, when using it with another browser it works great, you can try the sample your self and make sure.

@weijjia or @anujc do you have an easy way to test this out?  I can't install IE 8 on my box, and I'd like to avoid spinning up a VM if possible.

Sorry for that but I was in a middle of a project and faced this problem which will let me search for another library instead of ADAL which (as I searched till now) is not an easy thing to do using another library, Thanks for replying

If you just Used IE11 and pressed F12 then go to Emulation -> Document Mode = 8
This is enough to see the problem, you don't need to install IE8 to show it.

Thanks. I get the same error in the sample whether or not I include ADAL in the project - so I don't think it's a problem with the library - rather, the sample wasn't written to support Angular with IE8.
I could attempt to add support for IE8 to the sample - but I'd rather not add any IE8 specific code that might seem strange to those readers using Firefox, Chrome, IE11, etc.  I hope that seems reasonable.  On first glance it seems there are some decent help articles out there for getting Angular to work in IE8.

But it's surly a problem with ADAL library, I'm so sure, I'm using it in another project.
Make sure please that Angular version is less than 1.3 because it'll not support IE8 any way.
I'm using Angular with the another project with version 1.2.28and it's working perfectly, but adding ADAL crashed it.
Any way if you can help me with ADAL that would be great.

You can try it with a plain HTML
just include Angular and the ADAL with very simple app.js

Sorry, I don't have time at the moment to investigate this.  Since you're confident this is a library issue, I'm going to close this issue and we can continue investigating on the other issue you opened on the library repo.

Duplicate: https://github.com/AzureAD/azure-activedirectory-library-for-js/issues/144


np.load cannot load Python Objects

I have a .npy file that I am trying to load with this header:
{'descr': '|O', 'fortran_order': False, 'shape': (), }
In np.load(), parseReader() will throw an exception when it calls the GetType() function on this line:
bytes = Int32.Parse(dtype.Substring(2));
This is because '|O' is only two characters long and doesn't have the byte count character on the end. Also, it doesn't look like the "O" dtype is supported throughout Numsharp - understandably due to there not being an equivalent to a Python Object in .NET.
Are there any plans to do something to support loading .npy files with Python Objects, and potentially have an object that is the equivalent of a Python Object?

Unfortunately it is not possible to load or create a NDArray as Data type Objects. NumSharp only supports native built-in dtypes like int32, float32, float64.
I suggest you to try Numpy.NET.

FWIW, it seems like you can convert pickled Python objects to JSON using Python, then load the JSON instead into the program using Numsharp.
In my case, I'm trying to avoid the use of Python altogether on the machine I'm running my Numsharp program, however I have no problem doing the JSON conversion on another machine using Python or Numpy.NET. One downside to using JSON over .npy files is that the file size is roughly 5-6 time larger, however, this solution seems to work.


Two problems under MacOS

Describe the bug
A clear and concise description of what the bug is.

need to run the command[‘docker-compose up -d’] twice，table of mysql can be created successfully。
upload images error：ERROR:root:Upload file 'xxx.jpg' error due to: name 'upload_url' is not defined。Becuase multiprocessing on Macos cannot access ‘upload_url’ in load_data.py

Steps/Code to reproduce behavior
Follow this guide to craft a minimal bug report. This helps us reproduce the issue you're having and resolve the issue more quickly.
Expected behavior
A clear and concise description of what you expected to happen.
Environment details

Docker info
Phantoscope version (v0.1.0)

Screenshots
If applicable, add screenshots to help explain your problem.
Additional context
Add any other context about the problem here.

Phantoscope is only validated on Ubuntu and CentOS. There may be an incompatibility issue between Windows and MacOS.

The first issue is same as #102
The second issue maybe cause by other version of python or some platform setting.
I will changes the load_data script to fix it.
Thanks for your issue to point out this.

Close this issue due to all issues had been traced or fixed.


Is there a feature to average gradients across batches?

I am trying to fine tune the model with pruned_transducer_stateless recipe, but the model diverges after several iterations,
I am wondering if there is a feature to average gradients across several training batches, and maybe a parameter to set the number of batches to average on.

Do you mean the model can accumulate some iterations gradients such as (g1, g2, g3, g4) without parameters update, and after 4 iterations, use the average gradient ( g_avg=(g1+g2+g3+g4)/4 ) to update the parameters?

About finetuning for a pretrained pruned_transducer_stateless model, I think maybe you can try let model train more iterations, and then have a look for if the model diverges.

I am trying to fine tune the model with pruned_transducer_stateless recipe, but the model diverges after several iterations,

@zzzacwork the beta1 parameter in Adam is momentum, that is what is responsible for gradient averaging.
The default is 0.9.
Using a lower learning rate would probably be a safer bet though, than messing with the momentum parameter.
I think that model can diverge because the parameter tensors get too large, forcing the layernorm scales  to get small to compensate, and when the layernorm scales get too small the learning becomes unstable because it's too sensitive to their values.  Best to not let the parameters get too large; lower learning rate can accomplish that.
Our more recent models are not subject to this particular problem.

Oh, yes. I am also doing a fine-tune experiments #413. When I load the pretrained model and decrease the learning rate, the fine-tuning training can converge well.

You should probably start with the final learning rate from the 1st stage of training, or 20% higher, and either leave it constant or very slowly decrease it.

Do you mean the model can accumulate some iterations gradients such as (g1, g2, g3, g4) without parameters update, and after 4 iterations, use the average gradient ( g_avg=(g1+g2+g3+g4)/4 ) to update the parameters?

yes, that's exactly what I meant, huggingface's transformer has something similar, called args.gradient_accumulation_steps
https://github.com/huggingface/transformers/blob/0412f3d9298cdb8ba7f69570753ec6a07d240c87/examples/run_squad.py#L221

That is probably just for reproducibility, so that if you have a GPU with less memory you can exactly reproduce an experiment done on a GPU with more memory.

Yeah, I agree, generally speaking, it offers a way to use larger batch size without requiring increasing size of GPU memory accordingly. Larger batch size could possibly make training more stable. Similarly lowering lr rate might work for me at this moment as well I think, I will try it  and see if it would converge on my training data.

If you need gradient accumulation I think you can execute optimizer.step() and optimizer.zero_grad() in an if statement based on a your gradient_accumulation param : https://github.com/k2-fsa/icefall/blob/5379c8e9fa13f6f2364b4a0db89fa3074266fb58/egs/librispeech/ASR/pruned_transducer_stateless/train.py#L651

If you need gradient accumulation I think you can execute optimizer.step() and optimizer.zero_grad() in an if statement based on a your gradient_accumulation param :
https://github.com/k2-fsa/icefall/blob/5379c8e9fa13f6f2364b4a0db89fa3074266fb58/egs/librispeech/ASR/pruned_transducer_stateless/train.py#L651

Thanks and I am about to add that, just want check if that is already implemented or there is a better approach for this task.


changed code input type to text and removed show code button for disp…

…laying as password

Bump patch version ⚠


New TCL parse engine

[ ]
Develop mysql  TCL grammar

[ ]
Develop postgre  TCL grammar

[ ]
Develop sqlserver  TCL grammar

[ ]
Develop oracle  TCL grammar

[ ]
Add TCL statement visitor

[ ]
Develop mysql TCL grammar
[ ]
Develop postgre TCL grammar
[ ]
Develop sqlserver TCL grammar
[ ]
Develop oracle TCL grammar
[ ]
Add TCL statement visitor

[ ]
Develop TCL grammar

[ ]
Add TCL statement visitor

[ ] Develop TCL grammar

[ ] Develop TCL grammar

[ ] Add TCL statement visitor

finished at 3.0.1

grammar file complete


[auto-complete component] Field is set to blank in case of submitting a invalid form

How to reproduce :
1- Open a form with a autocomplete field and a mandatory field
2- set a value to the autocomplete field.
3- submit the form
==> There is a error display (which is normal) and the autocomplete field is set to blank.

This bug happens if the the value set in the autocomplete field is not part of the autocomplete suggestion list.

That is because you should set the allowUnmatchedValue to true if you want to allow values that do not exist in the picklist.
You can set this value in the options of the field in case you use an autocompleteFor in a form.


security Don't print password in BaseController

Problem summary
Fix security problem.
Checklist(Required)

[x] Does it affect the original behavior
[x] Has unit tests been added
[x] Has document been added or modified
[x] Does it need to update dependencies
[x] Is this PR support rollback (If NO, please explain WHY)

@morningman Can this PR being merged? Thanks.

run buildall

@morningman Can this PR being merged? Thanks.

ping,  Can this PR being merged? Thanks.

please rebase

run buildall

run buildall

run buildall

run buildall

run buildall

run buildall

run buildall

P0 Regression build failed, Please rebase the code.

@luzhijing Done. I have been rebased many times. which commit I must include?

run buildall


[BUG]:GeminiDDP: "ZERO DDP error: the synchronization of gradients doesn't exit properly.", 'The most possible reason is that the model is not compatible with ZeroDDP

🐛 Describe the bug
I got an error when I trained Bert large with GeminiDDP:
Error location  >>   self.optimizer.backward(loss)
error message：RuntimeError: ("ZERO DDP error: the synchronization of gradients doesn't exit properly.", 'The most possible reason is that the model is not compatible with ZeroDDP.\n', 'Reduction
failed at followed
parameters:\n\tbert.embeddings.word_embeddings.weight\n\tbert.embeddings.position_embeddings.weight\n\tbert.embeddings.token_type_embeddings.weight\n\tbert.embeddings.LayerNorm.weigh
t\n\tbert.embeddings.LayerNorm.bias\n\tbert.encoder.layer.0.attention.self.query.weight\n\tbert.encoder.layer.0.attention.self.query.bias\n\tbert.encoder.layer.0.attention.self.key.w
eight\n\tbert.encoder.layer.0.attention.self.key.bias\n\tbert.encoder.layer.0.attention.self.value.weight\n\tbert.encoder.layer.0.attention.self.value.bias\n.......
Code that may be involved：
with ColoInitContext(device=init_dev):
        model_config = BertConfig.from_pretrained(args.model_name_or_path, pool_type=args.pool_type)
        model = DenseModel.from_pretrained(args.model_name_or_path, config=model_config)
# enable graident checkpointing
model.gradient_checkpointing_enable()
PLACEMENT_POLICY = 'cpu'
cai_version = colossalai.__version__
model = GeminiDDP(model, device=get_current_device(), placement_policy=PLACEMENT_POLICY, pin_memory=True)

and:
def get_optimizer(model, args):
    no_decay = ['bias', 'LayerNorm.weight']
    optimizer_grouped_parameters = [
        {'params': [p for n, p in model.named_parameters() if not any(nd in n for nd in no_decay)],
            'weight_decay': 0.01},
        {'params': [p for n, p in model.named_parameters() if any(nd in n for nd in no_decay)], 'weight_decay': 0.0}
    ]
    optimizer = HybridAdam(optimizer_grouped_parameters, lr=args.learning_rate)
    optimizer = ZeroOptimizer(optimizer, model, initial_scale=2**14)
    lr_scheduler = get_scheduler(
        name=args.lr_scheduler_type,
        optimizer=optimizer,
        num_warmup_steps=args.train_steps*args.warmup,
        num_training_steps=args.train_steps,
    )
    return optimizer, lr_scheduler

Then how should I modify it? Thanks.
Environment
No response

i met the same error, did you solve it

i met the same error, did you solve it

No, not yet.

I met the same error with Mixtral-8x7B-v0.1
File "pretrain.py", line 223, in main

booster.backward(loss, optimizer)

File ".local/lib/python3.10/site-packages/colossalai/booster/booster.py", line 167, in backward

optimizer.backward(loss)

File ".local/lib/python3.10/site-packages/colossalai/zero/gemini/gemini_optimizer.py", line 291, in backward

self.module.backward(loss)

File ".local/lib/python3.10/site-packages/colossalai/zero/gemini/gemini_ddp.py", line 331, in backward

self._post_backward()

File ".local/lib/python3.10/site-packages/colossalai/zero/gemini/gemini_ddp.py", line 314, in _post_backward

raise RuntimeError(

RuntimeError: ("ZERO DDP error: the synchronization of gradients doesn't exit properly.", 'The most possible reason is that the model is not compatible with GeminiDDP.\n', 'Reduction failed at followed parameters:\n\tmodel.layers.22.block_sparse_moe.experts.2.w1.weight\n\tmodel.layers.22.block_sparse_moe.experts.2.w2.weight\n\tmodel.layers.22.block_sparse_moe.experts.2.w3.weight\n\tmodel.layers.22.block_sparse_moe.experts.3.w1.weight\n\tmodel.layers.22.block_sparse_moe.experts.3.w2.weight\n\tmodel.layers.22.block_sparse_moe.experts.3.w3.weight\n\tmodel.layers.22.block_sparse_moe.experts.4.w1.weight\n\tmodel.layers.22.block_sparse_moe.experts.4.w2.weight\n\tmodel.layers.22.block_sparse_moe.experts.4.w3.weight\n\tmodel.layers.22.block_sparse_moe.experts.5.w1.weight\n\tmodel.layers.22.block_sparse_moe.experts.5.w2.weight\n\tmodel.layers.22.block_sparse_moe.experts.5.w3.weight\n\tmodel.layers.22.block_sparse_moe.experts.6.w1.weight\n\tmodel.layers.22.block_sparse_moe.experts.6.w2.weight\n\tmodel.layers.22.block_sparse_moe.experts.6.w3.weight\n\tmodel.layers.22.block_sparse_moe.experts.7.w1.weight\n\tmodel.layers.22.block_sparse_moe.experts.7.w2.weight\n\tmodel.layers.22.block_sparse_moe.experts.7.w3.weight\n\tmodel.layers.23.block_sparse_moe.experts.2.w1.weight\n\tmodel.layers.23.block_sparse_moe.experts.2.w2.weight\n\tmodel.layers.23.block_sparse_moe.experts.2.w3.weight\n\tmodel.layers.23.block_sparse_moe.experts.3.w1.weight\n\tmodel.layers.23.block_sparse_moe.experts.3.w2.weight\n\tmodel.layers.23.block_sparse_moe.experts.3.w3.weight\n\tmodel.layers.23.block_sparse_moe.experts.4.w1.weight\n\tmodel.layers.23.block_sparse_moe.experts.4.w2.weight\n\tmodel.layers.23.block_sparse_moe.experts.4.w3.weight\n\tmodel.layers.23.block_sparse_moe.experts.5.w1.weight\n\tmodel.layers.23.block_sparse_moe.experts.5.w2.weight\n\tmodel.layers.23.block_sparse_moe.experts.5.w3.weight\n\tmodel.layers.23.block_sparse_moe.experts.6.w1.weight\n\tmodel.layers.23.block_sparse_moe.experts.6.w2.weight\n\tmodel.layers.23.block_sparse_moe.experts.6.w3.weight\n\tmodel.layers.23.block_sparse_moe.experts.7.w1.weight\n\tmodel.layers.23.block_sparse_moe.experts.7.w2.weight\n\tmodel.layers.23.block_sparse_moe.experts.7.w3.weight\n\tmodel.layers.24.block_sparse_moe.experts.6.w1.weight\n\tmodel.layers.24.block_sparse_moe.experts.6.w2.weight\n\tmodel.layers.24.block_sparse_moe.experts.6.w3.weight\n\tmodel.layers.29.block_sparse_moe.experts.2.w1.weight\n\tmodel.layers.29.block_sparse_moe.experts.2.w2.weight\n\tmodel.layers.29.block_sparse_moe.experts.2.w3.weight\n\tmodel.layers.29.block_sparse_moe.experts.3.w1.weight\n\tmodel.layers.29.block_sparse_moe.experts.3.w2.weight\n\tmodel.layers.29.block_sparse_moe.experts.3.w3.weight\n\tmodel.layers.29.block_sparse_moe.experts.4.w1.weight\n\tmodel.layers.29.block_sparse_moe.experts.4.w2.weight\n\tmodel.layers.29.block_sparse_moe.experts.4.w3.weight\n\tmodel.layers.29.block_sparse_moe.experts.5.w1.weight\n\tmodel.layers.29.block_sparse_moe.experts.5.w2.weight\n\tmodel.layers.29.block_sparse_moe.experts.5.w3.weight\n\tmodel.layers.29.block_sparse_moe.experts.6.w1.weight\n\tmodel.layers.29.block_sparse_moe.experts.6.w2.weight\n\tmodel.layers.29.block_sparse_moe.experts.6.w3.weight\n\tmodel.layers.29.block_sparse_moe.experts.7.w1.weight\n\tmodel.layers.29.block_sparse_moe.experts.7.w2.weight\n\tmodel.layers.29.block_sparse_moe.experts.7.w3.weight\n\tmodel.layers.30.block_sparse_moe.experts.2.w1.weight\n\tmodel.layers.30.block_sparse_moe.experts.2.w2.weight\n\tmodel.layers.30.block_sparse_moe.experts.2.w3.weight\n\tmodel.layers.30.block_sparse_moe.experts.3.w1.weight\n\tmodel.layers.30.block_sparse_moe.experts.3.w2.weight\n\tmodel.layers.30.block_sparse_moe.experts.3.w3.weight\n\tmodel.layers.30.block_sparse_moe.experts.4.w1.weight\n\tmodel.layers.30.block_sparse_moe.experts.4.w2.weight\n\tmodel.layers.30.block_sparse_moe.experts.4.w3.weight\n\tmodel.layers.30.block_sparse_moe.experts.5.w1.weight\n\tmodel.layers.30.block_sparse_moe.experts.5.w2.weight\n\tmodel.layers.30.block_sparse_moe.experts.5.w3.weight\n\tmodel.layers.30.block_sparse_moe.experts.6.w1.weight\n\tmodel.layers.30.block_sparse_moe.experts.6.w2.weight\n\tmodel.layers.30.block_sparse_moe.experts.6.w3.weight\n\tmodel.layers.30.block_sparse_moe.experts.7.w1.weight\n\tmodel.layers.30.block_sparse_moe.experts.7.w2.weight\n\tmodel.layers.30.block_sparse_moe.experts.7.w3.weight\n\tmodel.layers.31.block_sparse_moe.experts.2.w1.weight\n\tmodel.layers.31.block_sparse_moe.experts.2.w2.weight\n\tmodel.layers.31.block_sparse_moe.experts.2.w3.weight\n\tmodel.layers.31.block_sparse_moe.experts.3.w1.weight\n\tmodel.layers.31.block_sparse_moe.experts.3.w2.weight\n\tmodel.layers.31.block_sparse_moe.experts.3.w3.weight\n\tmodel.layers.31.block_sparse_moe.experts.4.w1.weight\n\tmodel.layers.31.block_sparse_moe.experts.4.w2.weight\n\tmodel.layers.31.block_sparse_moe.experts.4.w3.weight\n\tmodel.layers.31.block_sparse_moe.experts.5.w1.weight\n\tmodel.layers.31.block_sparse_moe.experts.5.w2.weight\n\tmodel.layers.31.block_sparse_moe.experts.5.w3.weight\n\tmodel.layers.31.block_sparse_moe.experts.6.w1.weight\n\tmodel.layers.31.block_sparse_moe.experts.6.w2.weight\n\tmodel.layers.31.block_sparse_moe.experts.6.w3.weight\n\tmodel.layers.31.block_sparse_moe.experts.7.w1.weight\n\tmodel.layers.31.block_sparse_moe.experts.7.w2.weight\n\tmodel.layers.31.block_sparse_moe.experts.7.w3.weight')


Added simplification for time component of a chinese date format

fixes issue #204

[Current coverage][cc-pull] is 94.45%

Merging [#205][cc-pull] into [master][cc-base-branch] will not change coverage

@@             master       #205   diff @@
==========================================
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  Lines          2653       2653
  Methods           0          0
  Messages          0          0
  Branches          0          0
==========================================
  Hits           2506       2506
  Misses          147        147
  Partials          0          0

Powered by Codecov. Last updated by [d628c5d...18564a1][cc-compare]
[cc-base-branch]: https://codecov.io/gh/scrapinghub/dateparser/branch/master?src=pr
[cc-compare]: https://codecov.io/gh/scrapinghub/dateparser/compare/d628c5dfce66e14601cfe97ac7cf103d185d91c5...18564a15eb0534488335e095f696abbd3363f891?src=pr
[cc-pull]: https://codecov.io/gh/scrapinghub/dateparser/pull/205?src=pr


Please provide driver version number in driverInfo field

While working on Steam's steam-runtime-system-info diagnostic tool, I've been looking into getting better version reporting for Vulkan drivers.
The problem is that the driverVersion in VkPhysicalDeviceProperties is a single integer with no standardized encoding. Mesa uses the same encoding as for the apiVersion:

Bits 29-31 (3  bits, mask with 0xe000_0000): variant
Bits 22-28 (7  bits, mask with 0x1fc0_0000): major
Bits 12-21 (10 bits, mask with 0x003f_f000): minor
Bits  0-11 (12 bits, mask with 0x0000_0fff): patch (micro)

but unfortunately the Nvidia proprietary driver seems to have its own encoding:

Bits 22-31 (10 bits, mask with 0xffc0_0000): major
Bits 14-21 ( 8 bits, mask with 0x003f_c000): minor
Bits 6-13 ( 8 bits, mask with 0x0000_3fc0): micro
Bits 0-5 ( 6 bits, mask with 0x0000_003f): nano (probably not used in public drivers?)

AMDVLK 2021.Q4.1 reports its version number as 0x8000cb. If it's the same encoding as an apiVersion, that would be 2.0.203 - is that a meaningful version number for this driver? It doesn't seem to have any obvious relationship with the public-facing version number 2021.Q4.1.
The convention seems to be that the driverInfo in VkPhysicalDeviceVulkan12Properties is a human-readable version number of some sort. For example, for Mesa drivers like RADV and Intel ANV it's something like Mesa 21.3.0, and for Nvidia proprietary it's something like 460.91.03, in both cases matching the user-facing version numbers used in downloadable binaries.
Would it be possible to fill this field with whatever version number you would want your users to give when describing this driver? For example it could be something like one of these:

2021.Q4.1
2021.Q4.1 (2.0.203)
2021.Q4.1 (LLVM 13.0.1, XGL 1.2.3, LLPC 4.5, PAL 7.8.9)
2.0.203

We decided to fill release version ( e.g. "2021.Q4.2“) into driverInfo in VkPhysicalDeviceVulkan12Properties since next release.(Q4.3)
The driverVersion in VkPhysicalDeviceProperties is an internal version, for more details see https://github.com/GPUOpen-Drivers/amd-vulkan-versions

We decided to fill release version ( e.g. "2021.Q4.2“) into driverInfo

Thanks, that's what I hoped for.
Steam's diagnostic tool in the public beta version should display this correctly. That change is not yet in the stable version, but will arrive next time the beta changes get merged.

to clarify, this decision  is only for amdvlk driver ( linux only)

That's fine, steam-runtime-system-info is also Linux-specific.
If AMD has Windows Vulkan drivers, then those should probably also populate driverInfo with something users will understand (perhaps they already do, I don't know), but I'm personally only interested in Linux.

Driver info updated to this form: 2022.Q3.2 (LLPC)

Driver info updated to this form: 2022.Q3.2 (LLPC)

We just display this string, and we don't parse or interpret it, so the specific format is not important: any string that will be understood by your users and developers is equally good.
Current versions of Steam should display this in Help -> System Information: wait for the detailed report to be generated, then look for "x11/vulkan". Sorry, I don't have an AMDVLK system set up at the moment, so I'm not able to verify this.


Add limit of facet value

Following this issue: https://github.com/meilisearch/meilisearch/issues/2349
Validated with @gmourier and @Kerollmops
For performance reasons, Meilisearch should limit the number of facet values to 1000.
Customizing this limit could be considered in the future. If you want it, please open a discussion in the product repository.

What do you think about delaying this to v0.29 so that you can integrate customization settings like the maximum limit for search results?
I would like to avoid blocking users for whom this is not necessarily a problem and who could end up being blocked if we add a non-configurable limit.

@meilisearch/docs-team @meilisearch/integration-team
A setting to customize this limit has been introduced. The reasons and how it will be implemented are described in this issue description


Add a dependency on autoconf-2.13

This is necessary for https://github.com/servo/mozjs/pull/56 which runs autoconf at build time instead of checking in configure.
No idea if this will work on osx..

@bors-servo r+

Reviewed 1 of 1 files at r1.
Review status: :shipit: all files reviewed at latest revision, all discussions resolved, all commit checks successful.

Comments from the review on Reviewable.io

:hourglass: Testing commit b2071b9 with merge cf75192...

:pushpin: Commit b2071b9 has been approved by metajack

:sunny: Test successful - travis