Update base margin dask

Add base_margin to sklearn predict and predict_proba
Add output_margin to sklearn predict and predict_proba
Add base_margin to sklearn fit
Update _get_worker_x_ordered to _get_worker_parts_ordered. This allows us to get ordered base_margin to create the DMatrix object used for dispatched_predict
Add dask test to confirm this is functioning correctly. Mirrors the same test in test_with_sklearn

Adds a few more things to #6132

Codecov Report

Merging #6155 into master will increase coverage by 0.08%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master    #6155      +/-   ##
==========================================
+ Coverage   78.83%   78.91%   +0.08%
==========================================
  Files          12       12
  Lines        3090     3102      +12
==========================================
+ Hits         2436     2448      +12
  Misses        654      654

Impacted Files
Coverage Δ

python-package/xgboost/dask.py
81.07% <100.00%> (+0.68%)
:arrow_up:

python-package/xgboost/data.py
56.80% <0.00%> (+0.19%)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update c686bc0...972cd17. Read the comment docs.

@trivialfis looks great! Thanks for adding that in
On a side note, are you using a python autoformatter like black? I'd love to install one for this project

Thanks for the review.
I believe XGBoost is using pylint.  My local installation of pylint caught some errors but not the one on CI.  Maybe there are some regressions on the latest pylint version (Mine is older).
For auto formatting, I use yapf myself, but not a requirement for XGBoost.

You can run make lint on XGBoost's root dir.

I use yapf myself

Cool, I'll take a look at that, should make following style guidelines a bit easier. Black wanted to reformat everything completely differently 😞

Thanks for the PR!


Fix react-intl version to be consistent with platform-complete

No, wait, hah! I read this PR backwards. Now that platform-complete has FINALLY updated to react-intl v6, we can leave stripes-types as-is.


SFTPGO: optional sidecar support

This adds support for optional sidecars in the pod to sftpgo

@sagikazarmark let me know if you need me to add anything additional to this for review. We need sidecar support to use GCP cloud-sql-proxy for the config database. (https://cloud.google.com/sql/docs/mysql/connect-kubernetes-engine)

@bdashrad thanks for the contribution!
Why do you need to run the proxy as a sidecar?
I used this Helm chart with success in the past.
Are there any specific reasons why it has to run as a sidecar?

A quick google search also pointed me to this issue and then these projects:

https://github.com/tumblr/k8s-sidecar-injector/
https://github.com/connctd/sqlbee

Personally I find webhook based solutions much better for this kind of issues, because it keeps Helm charts simple while giving you total control over the created resources.
So even if running the proxy as a sidecar is a requirement, I'd consider using the webhook based solution instead. Let me know if it works for you.

The sidecar injection should meet our needs, but is definitely much more work than being able to add them to the pod from the values.yaml. I think this is still a worthy addition even though there are other options.

@sagikazarmark sorry for the delay, I don't know how I missed your comments. PR updated with requested changes and merged in latest main branch.


get_backlog_level_work_items is not available in released

https://github.com/microsoft/azure-devops-python-api/blob/dev/azure-devops/azure/devops/v5_1/work/work_client.py#L57
When do we could get this feature in released?

The team that owns this end point for the service will need to answer that question.  When they mark their routes as releases, our code generation tool will update it for this sdk.  It is not marked released in 6.0, so the next opportunity will be for the 6.1 apis.  That said, there is nothing wrong with depending on an endpoint that is marked as preview.  The services teams ensure over the wire compatibility, so if they were to break it, it would be considered  bug.  An endpoint marked as preview, means that the end point may change in a later version, but the current version will continue to work.
You can ask the service team by submitting your question here:
https://docs.microsoft.com/en-us/rest/api/azure/devops/work/backlogs?view=azure-devops-rest-6.0


Several issues when compiling for web

When compiling games with latest raylib 3.5 and latest emscripten 2.0.11, some issues appeared. I think they are mostly related to memory management in the games.

[x] wave_collector: font not rendered
[x] transmission: out-of-bounds (some text array?)
[x] skully_escape: out-of-bounds (some text array?)
[x] light_my_ritual: lights not drawn
[x] koala_seasons: not working

All compilation issues reviewed. Games work on web again!


Feature: Comments improvement

cloned from https://github.com/sfm-cz/beautyAmp/issues/7 (opened by @FiB3 )

Just opening the new Comment idea for you (a "fork from https://github.com/sfm-cz/beautyAmp/issues/6)
I did notice one thing though: prettier would format multi-line comments that are prefixed slightly differently:

see how it adds 1 space in 2 out of those 3 cases? would be nice to mirror that behavior.

testeded with
const content =
    '%%[/*\n* example on how to use this\n* example on how to use this\n*/\n/* my ampscript */\n]%%';

and HTML off:
result:

%%[
    /*
     * example on how to use this
     * example on how to use this
     */
    /* my ampscript */
]%%

I can confirm this works as expected  @FiB3   :)


Support all comparison query operators [WIP]

$eq operator

 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.

I removed the TODO regex from the $eq comparison operator. I have not find any information in the documentation and on the Internet that these two expressions were used.
I also tried to issue query in mongosh db.values.find( { value:  {$eq :/foo/i } } ) to the values database manually and it returns only match stored regexes. I mean is there possibility who would store regex datatype in a document? Anyway current implementation FerretDB returns nothing.
What do you think we will do next?

I mean is there possibility who would store regex datatype in a document?

Yes.

Anyway current implementation FerretDB returns nothing.

We should add a dance test for that case and fix that difference in behavior between MongoDB and FerretDB.

Thank you!


evilginx2 only as a mirror

is it possible to run evilginx2 only as a mirror? without intercepting passwords but with manual code injection? do i still need to write a phishlet for this? how to do this?

Sorry, I don't quite understand the question.

I want to use evilginx only as a proxy but with inserting my own js code into proxified pages. Is it possible?

You can use the js_inject parameter introduced with version 2.3.0.


Unable to use libei

Hi,
I am the maintainer of a library to simulate input (something similar to xdotools). My library is cross-platform though and not limited to X11 or even Linux. I would like to run tests in the CI. I have some for X11, but not for Wayland yet. On Wayland and GNOME, libei must be used. Unfortunately I wasn't able to get this working in the container. Does it require setup?
The error I see is:
[2024-12-20T03:43:24Z DEBUG enigo::platform::libei] using libei
[2024-12-20T03:43:24Z DEBUG enigo::platform::libei] Unable to find ei socket. Trying xdg desktop portal.
thread 'integration_browser_events' panicked at src/linux/libei.rs:104:61:
called `Result::unwrap()` on an `Err` value: PortalNotFound(OwnedInterfaceName("org.freedesktop.portal.RemoteDesktop"))

Looks like it's some error regarding portals. I tried a number of things but haven't been successful. Here is the branch I used attempting to get this working. It is very unorganized and doesn't have any sensible commit messages as I was just trying to get this to work somehow though.
If we get this working, you could test your extensions with mouse and keyboard interaction on Wayland too. :-)

Hi there! libei is a really cool project! I looked into it several times as it would be very helpful for Kando.
However, I am not sure if this will work with this container. The wayland variant still runs as a nested session in xvfb. So all input will need to pass through X11 first. In fact, one can use xdotool in the wayland session this way. Of course it would be cool to have a headless wayland session somehow, but I am not sure how this could be achieved...


Invalid Flag type for TimestampType: 4

Known affected branch:
master
DAGRequestConstruct

SQL:
select  distinct(tp_timestamp)  from full_data_type_table  order by tp_timestamp

Exception:
Job aborted due to stage failure: Task 0 in stage 3180.0 failed 1 times, most recent failure: Lost task 0.0 in stage 3180.0 (TID 12048, localhost, executor driver): com.pingcap.tikv.codec.InvalidCodecFormatException: Invalid Flag type for TimestampType: 4
	at com.pingcap.tikv.types.TimestampType.decodeNotNull(TimestampType.java:62)
	at com.pingcap.tikv.types.DataType.decodeValueToRow(DataType.java:133)
	at com.pingcap.tikv.row.DefaultRowReader.readRow(DefaultRowReader.java:38)
	at com.pingcap.tikv.operation.iterator.CoprocessIterator$1.next(CoprocessIterator.java:78)
	at com.pingcap.tikv.operation.iterator.CoprocessIterator$1.next(CoprocessIterator.java:74)
	at org.apache.spark.sql.tispark.TiRDD$$anon$2.next(TiRDD.scala:79)
	at org.apache.spark.sql.tispark.TiRDD$$anon$2.next(TiRDD.scala:55)
	at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
	at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithKeys$(Unknown Source)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
	at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
	at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:126)
	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
	at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
	at org.apache.spark.scheduler.Task.run(Task.scala:99)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
	at java.lang.Thread.run(Thread.java:748)

Driver stacktrace:

Seems we did't handle UINT_FLAG type in TimestampType

UINT_FLAG  is not valid concerning TimestampType, we are somewhat retrieving wrong data.

In Addition:
When you use group by with timestamp, you will receive the same error. The same problem exists in any other aggregation.
scala> spark.sql("select * from dt group by dt").show(truncate=false)

select  distinct(tp_datetime)  from full_data_type_table  order by tp_datetime
also throws the same exception

The cause for this issue is that TiKV returns us UINTFLAG rather than UVARINTFLAG when we push timestamp type down to coprocessor. It has been confirmed to be a normal behavior, so will be fixed in #181.

Fixed.


HAWQ-82. Allocate query resource for EXPLAIN statement

set query type of explain statement as QRL_ONCE to allocate resource for it.
+1

The fix looks good to allocate resource for explain. +1

Hi Lirong, does it mean we can support hash to random conversion in 'explain' now?

Yes, I think so. Please have a try, and let me know if anything wrong.


just position for IP

the IP adresse is at the wrong position:
DNS Records
A.     <IP_ADDRESS>
AAAA
<IP_ADDRESS>
MX
2001:8d8:100f:f000::2a6
the IP of A record have to be in a new line

I think because there will only be one A record so it's displayed as a Row. But the AAAA, MX, etc can have multple values, so are displayed in a ListView.
But I can adjust that so they're all displayed as a ListView

I noticed that ipv6 only domains have their address listed under A record as well:


Custom datasets

thanks for this work.
anyway, i have my own dataset with .jpg for img and .png for label.
i wonder is there any way to use my own dataset?

Hi Chic-J,
Thank you for your interest in PiCIE. As long as you have your dataset folder formatted as this, your custom dataset should work.
During training, you will not need your labels and training code should work as it is.
During testing, you may want to modify label transformation function (here). I think commenting out line 118 to line 126 would work.
Best,
Jang Hyun

Hi Chic-J,
Thank you for your interest in PiCIE. As long as you have your dataset folder formatted as this (you do not need the json files), your custom dataset should work without any problem.
During training, you do not need your labels and the training code should work as it is.
During testing, you may want to modify the label transformation function (here). I think commenting out line 118 to line 126 would work.
Best,
Jang Hyun

thanks. And yes, I don't have any fine_to_coarse_dict...so i just ignore the code related to it, does it matter?

Yes. fine_to_coarse_dict is used to map the original COCO-Stuff categories to more coarse set of categories.

Yes. fine_to_coarse_dict is used to map the original COCO-Stuff categories to more coarse set of categories.

yes, I got it. Thanks.

Glad I could help!

Hi @Chic-J ,
Have you successfully trained PiCIE using custom dataset? I am trying to train with custom dataset but I dont have pkl file and lists. I have only images and annotations.

Hi @Chic-J ,
Have you successfully trained PiCIE using custom dataset? I am trying to train with custom dataset but I dont have pkl file and lists. I have only images and annotations.

Hi. I gave up due to the same reason. good luck to you.


Since my upgrade to version 0.17.0 I get a warning when starting windows and have to give permission.

Environment
Windows build number: [run "ver" at a command prompt]
PowerToys version:
PowerToy module for which you are reporting the bug (if applicable):

Steps to reproduce

Expected behavior

Actual behavior

Screenshots

Same problem here. Sometimes I don't get this, but instead I get an error that Powertools are not able to run as administrator.

Same here, I uninstalled (with Revo uninstaller) and reïnstalled, now it seems to work with no problems


misc/cgo/testcarchive: tests are failing on ppc64le

Please answer these questions before submitting your issue. Thanks!
What version of Go are you using (go version)?
master
Does this issue reproduce with the latest release?
yes
What operating system and processor architecture are you using (go env)?
ppc64le
What did you do?
./all.bash script
What did you expect to see?
Pass all the tests
What did you see instead?
Seen failures, with misc/cgo/testcarchive
##### ../misc/cgo/testcarchive
--- FAIL: TestCompileWithoutShared (1.26s)
	carchive_test.go:600: [go build -buildmode=c-archive -gcflags=-shared=false -o libgo2.a libgo2]
	carchive_test.go:602:
	carchive_test.go:609: [gcc -fPIC -pthread -fmessage-length=0 -fdebug-prefix-map=/tmp/go-build472192193=/tmp/go-build -gno-record-gcc-switches -I pkg/linux_ppc64le_shared -o ./testnoshared main5.c libgo2.a]
	carchive_test.go:611:
	carchive_test.go:618: [./testnoshared 3]
	carchive_test.go:620: ./testnoshared: error while loading shared libraries: R_PPC64_ADDR16_HA re1028a6ca8 for symbol `' out of range
	carchive_test.go:361: got exit status 127; expected signal broken pipe
FAIL

/cc @laboger

What distro are you using, because I don't see this error on any of the systems I'm using, even the Ubuntu 16.04, because I tried it there after my fix.
At first glance, those options look wrong for ppc64le anyway, a c-archive must be built with -shared.

I'm using ubuntu 16.04 as host and building in ppc64le/golang:1.9 container.

The failing test explicitly passes -shared=false.   I added it for #20290, which was about incorrect values in the symbol table when compiling with -buildmode=c-archive but without -shared.
It's not obvious to me why this test is failing.  Of course -shared is required if we want to put c-archive into a shared library, and so -shared is the right default, but in this case we are not putting the code into a shared library.  The error is coming from the system dynamic linker, and unfortunately does not report the symbol being referenced.
The failing test is running the commands shown in the log.  Can you run those commands yourself and replicate the problem?  If so, please try setting LD_DEBUG=all in the environment when running ./testnoshared.  Perhaps that will tell us which shared library is failing to load and which symbol is out of range.

@ianlancetaylor ran the commands with LD_DEBUG=all and uploaded results @ https://gist.github.com/mkumatag/a2c5ba4f35c2d9a0c613b4ba626cc50e

Thanks.  Unfortunately that did not tell me anything useful.
What is the output of readelf -r --wide ./testnoshared?

ran and uploaded @ https://gist.github.com/mkumatag/9862a0e69729b68bb5b7213c53f314c3

I did some experiments on this yesterday. I found a system with the same level of ld and libc as your container, built the latest and also built before the commit where the pie testcase was changed/fixed. Those tests all passed. So that means there is something else unique about your container. I am unable to reproduce your latest error anywhere else.
The only case where I can reproduce this is when passing -pie directly to the linker instead of using -buildmode=pie on Ubuntu 16.04. Since that was the same error message, I'm assuming it is the same issue.
I found that the error message comes from dl_reloc_overflow and the output message looks corrupted. I believe the dynamic linker is accessing the wrong location for the relocation entries and as a result the reloc address and string is bad, causing the error. There is obviously some randomness in this problem since it only happens on some environments.

We believe the problem is that the test contains the R_PPC64_ADDR16_HA relocation but when the test is loaded by ld64.so, the relocated offset is greater than what will fit into 16 bits so the overflow error occurs. The error depends on the load address for the binary.
I understand the point of the test depended on having a mix of PIC and nonPIC to exercise the problem you had so not sure how to make that happen.  Maybe just simpler code?

Can you figure out what the relocation is referring to?
If we can make the code simpler, then let's try that.

Yes, if you look at the latest readelf output log that was posted by @mkumatag , there are multiple relocation entries of R_PPC64_ADDR16_HA and R_PPC64_ADDR16_LO for .init and .tbss.

I don't understand why relocs against .init and .tbss would fail.  Those must be relocations from the executable to the executable itself.  And we aren't building this test case with PIE, so I would expect the result to have a fixed address.  So how could the relocs be out of range?
Hmmm, could the problem be that the system compiler defaults to passing -pie to the linker?  Maybe we need to have carchive_test.go pass an explicit -no-pie or -nopie, as cmd/go does.

I built this test by hand using the above commands in the container and passed in -no-pie and that fixes the problem. The binary no longer has any relocations for R_PPC64_ADDR16_HA or LO. It's not obvious to me how to add -no-pie as an option in cmd/dist/test.go so I can try it out in the container where it fails.
I know at some point gcc starting passing -pie by default at the link step (maybe gcc 6?). So that would explain why it doesn't happen on older distros.
It doesn't seem right to me that the dynamic binary would have unresolved relocations for R_PPC64_ADDR16_HA and LO, especially if you are saying they should be defined in the executable itself. Shouldn't the system linker have resolved them at link time?

For background, GCC itself does not pass -pie by default.  It only does so when it is configured and built with the --enable-default-pie option.  Some distros then build GCC with that option.  So whether PIE is the default depends on the specific distro version.
The system linker can only resolve any R_PPC64_ADDR16_HA and R_PPC64_ADDR16_LO relocs if it is invoked in normal mode.  If the system linker is invoked with -pie, then it can't resolve those relocs, since the address is unknown at link time, and it has to leave them for the dynamic linker.  The relocs are fine if combined with R_PPC64_ADDR_HIGHERA and R_PPC64_ADDR_HIGHESTA, and they are fine if the program is located in the first 4G of memory.
Adding -no-pie as an option for the test amounts to running go test -buildmode=pie -ldflags=-extldflags=-no-pie

OK I was thinking I had to make a change to cmd/dist/test.go to get the option passed and that was where I was stuck but now I see the change is in carchive_test.go.
Is it OK to pass -no-pie for all GOARCHes or should this only be done on ppc64le?

It's fine to pass -no-pie on all architectures, but note that clang uses -nopie rather than -no-pie.  See the runtime test for that in cmd/go/internal/work/build.go.


COR-499 add form type

This PR adds the "Type" field to the FormDefinition, as well as add logic to store this new field, and validate the value on the POST /formdefinitions

q

s

Accidentally closed this.. Checking out @internetti 's comments

/lgtm


chore: update outdated dependencies

Updated dependencies reported by cargo outdated -R that did not result in compilation errors.


The player detects the time track clicks as if I am clicking on the big play button

I have just installed this plugin and whenever I click on the time track to change the current time and the video player pause or unpause the video depending on the current state. If it is playing the video and I click on the time track then the video is paused. If the video is paused and then I click on the time track then the video is unpaused. Basically the player detects the time track clicks as if I am clicking on the big play button.
Here is how I initialize the player:
       <q-media-player
            v-if="video !== null"
            type="video"
            background-color="black"
            :autoplay="false"
            class="video-player"
            :dense="true"
            :show-big-play-button="true"
            :sources="video.sources"
            :poster="video.poster"
            @ended="onEnded"
          >
          </q-media-player>

.......
      this.video = {
          label: stream.Title,
          poster: stream.Poster,
          sources: [
            {
              src: response.data.Url,
              type: 'video/mp4'
            }
          ]
        }

Thanks for reporting.

I know exactly what is happening. I will be out all weekend, so will try to get this done early next week.

Thank you so much, it will be very much appreciated!

Sorry, it's taken so long. I totally forgot about this. Will try to have a fix in for today.

@Bogatinovski ok, so I tested and cannot replicate what I thought the issue was, so maybe I need some clarification. When I click on the time track, it goes to that position in the movie, but it does not start playing for me. The Big Play Button is still available.

For some reason it is working correctly now. I really don't remember changing anything so I have no idea how to reproduce the issue that was happening. Perhaps we should close the issue for now and reopen it in the future if it happens again.

Sounds good. Probably was a fix in Quasar that caused this issue to be fixed.


C# Code Block Missing / Incorrect Formatting

One of the C# code blocks appears to be incomplete or the formatting may be off.

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: ef96562d-099d-9400-c88c-ba0439e136a6
Version Independent ID: 049314ea-8e68-50ee-3469-4d39c801fc54
Content: Quickstart: Computer Vision client library - Azure Cognitive Services
Content Source: articles/cognitive-services/Computer-vision/quickstarts-sdk/client-library.md
Service: cognitive-services
Sub-service: computer-vision
GitHub Login: @PatrickFarley
Microsoft Alias: pafarley

@luisquintanilla Thanks for the feedback. We will update you shortly.

Thanks for the feedback. Here is the link to the quick start code. https://github.com/Azure-Samples/cognitive-services-quickstart-code/blob/master/dotnet/ComputerVision/ComputerVisionQuickstart.cs#L151
@PatrickFarley The following section of the document needs improvement in the quick start . Can you please check on this.

This is by design, since the feature implementation code comes next - and each feature is optional, but it must end with a closing bracket.
I've fixed the code indentation, which was off.
#please-close


Embedded keywords with variable are treated as containing underscore

Describe the bug
Embedded keywords with variable are treated as containing underscore, while IMHO they are fine formatted.
To Reproduce
Steps to reproduce the behavior:
Run robocop against file containing following code
*** Variables ***
${variable_with_underscore}    does not matter

*** Test Cases ***
Test Underscore
    Embedded Keyword With ${variable_with_underscore}

*** Keywords ***
Embedded Keyword With ${variable_with_underscore}
    Log    ${variable_with_underscore}

Results in [W] 0305 Underscores in keyword name can be replaced with spaces
Expected behavior
Since common approach to variables is to have them with underscores, rule should ignore variable casing in embedded keyword.

You're right. We're removing embedded variables from keyword name in keyword naming checker but after the 0305 rule check:
https://github.com/MarketSquare/robotframework-robocop/blob/dc2d876b10594239a2d0bfbcb46a0f032021590f/robocop/checkers/naming.py#L148
I'm going to consider it as bug


Push v2.88.2?

I see that 2.88.2 was published, but I don't see a v2.88.2 tag in the repo, or a version bump commit on master? Did the publisher forget to push it?

This broke node's citgm tests, see https://github.com/nodejs/citgm/pull/786#issuecomment-591938453
We understand request is deprecated, but we'd keep testing it to make sure that Node.js doesn't break it and its significant users, but it'd have to have the tags pushed, and have reliable tests.
If not, it'll likely just get dropped from the ecosystem packages we test against.

IMO, direct testing should just be dropped from citgm.
The package is deprecated and Node.js shouldn’t worry as much about compatibillity.
There’s still plenty of packages that rely on request that will still be getting tested, so the subset of functionality that is commonly depended on will remain in the test set. The more esoteric functionality in request that is only tested by our own unit tests could be broken by Node.js going forward and the solution provided to users for fixing it should be “stop using request.”

Note that the testing of request isn't so much around "does request work" (which as you say, we could just say "no, too bad" about), it's about whether the Node.js API changed unintentionally in a way noticed by a large, complex, and legacy code base. If it breaks request, it could break some other code, code possibly in some private app far from npmjs.com. Thus the "canary" of canary-in-the-gold-mine, its useful as a Node.js QA signal.
Not that this is a desperate plea, we can let request disappear from citgm, and I think it might already have. I can totally understand any lack of enthusiasm to spend more time on it now.

Surely tho, a git push isn't much effort or time to spend, just so the git repo matches reality?

bump - for posterity this should still be done.


GlusterFS volume mount fails

Latest Mantl deployment fails on:
TASK: [glusterfs | mount container volume] ************************************
failed: [control-03] => {"failed": true}
msg: Error mounting /mnt/container-volumes: Mount failed. Please check the log file for more details.

failed: [control-05] => {"failed": true}
msg: Error mounting /mnt/container-volumes: Mount failed. Please check the log file for more details.

failed: [control-04] => {"failed": true}
msg: Error mounting /mnt/container-volumes: Mount failed. Please check the log file for more details.

failed: [control-02] => {"failed": true}
msg: Error mounting /mnt/container-volumes: Mount failed. Please check the log file for more details.

failed: [control-01] => {"failed": true}
msg: Error mounting /mnt/container-volumes: Mount failed. Please check the log file for more details.

Also, found in logs:
/var/log/glusterfs/mnt-container-volumes.log
[2015-11-23 16:14:14.782260] E [socket.c:2278:socket_connect_finish] 0-container-volumes-client-3: connection to <IP_ADDRESS>:49152 failed (Connection refused)
[2015-11-23 16:14:14.782281] W [MSGID: 108001] [afr-common.c:3924:afr_notify] 0-container-volumes-replicate-0: Client-quorum is not met
[2015-11-23 16:14:14.782814] E [MSGID: 114058] [client-handshake.c:1524:client_query_portmap_cbk] 0-container-volumes-client-4: failed to get the port number for remote subvolume. Please run 'gluster volume status' on server to see if brick process is running.
[2015-11-23 16:14:14.782860] I [MSGID: 114018] [client.c:2042:client_rpc_notify] 0-container-volumes-client-4: disconnected from container-volumes-client-4. Client process will keep trying to connect to glusterd until brick's port is available
[2015-11-23 16:14:18.747241] I [rpc-clnt.c:1847:rpc_clnt_reconfig] 0-container-volumes-client-3: changing port to 49152 (from 0)
[2015-11-23 16:14:18.750003] E [socket.c:2278:socket_connect_finish] 0-container-volumes-client-3: connection to <IP_ADDRESS>:49152 failed (Connection refused)

/var/log/glusterfs/bricks/mnt-glusterfs-container-volumes.log
[2015-11-23 13:42:24.214233] W [MSGID: 101002] [options.c:957:xl_opt_validate] 0-container-volumes-server: option 'listen-port' is deprecated, preferred is 'transport.socket.listen-port', continuing with correction
[2015-11-23 13:42:24.217279] I [MSGID: 121050] [ctr-helper.c:256:extract_ctr_options] 0-gfdbdatastore: CTR Xlator is disabled.
[2015-11-23 13:42:24.217299] W [MSGID: 101105] [gfdb_sqlite3.h:239:gfdb_set_sql_params] 0-container-volumes-changetimerecorder: Failed to retrieve sql-db-pagesize from params.Assigning default value: 4096
[2015-11-23 13:42:24.217307] W [MSGID: 101105] [gfdb_sqlite3.h:239:gfdb_set_sql_params] 0-container-volumes-changetimerecorder: Failed to retrieve sql-db-cachesize from params.Assigning default value: 1000
[2015-11-23 13:42:24.217314] W [MSGID: 101105] [gfdb_sqlite3.h:239:gfdb_set_sql_params] 0-container-volumes-changetimerecorder: Failed to retrieve sql-db-journalmode from params.Assigning default value: wal
[2015-11-23 13:42:24.217321] W [MSGID: 101105] [gfdb_sqlite3.h:239:gfdb_set_sql_params] 0-container-volumes-changetimerecorder: Failed to retrieve sql-db-wal-autocheckpoint from params.Assigning default value: 1000
[2015-11-23 13:42:24.217327] W [MSGID: 101105] [gfdb_sqlite3.h:239:gfdb_set_sql_params] 0-container-volumes-changetimerecorder: Failed to retrieve sql-db-sync from params.Assigning default value: normal
[2015-11-23 13:42:24.217334] W [MSGID: 101105] [gfdb_sqlite3.h:239:gfdb_set_sql_params] 0-container-volumes-changetimerecorder: Failed to retrieve sql-db-autovacuum from params.Assigning default value: none
[2015-11-23 13:42:24.250304] I [trash.c:2366:init] 0-container-volumes-trash: no option specified for 'eliminate', using NULL
[2015-11-23 13:42:24.250993] W [graph.c:357:_log_if_unknown_option] 0-container-volumes-server: option 'rpc-auth.auth-glusterfs' is not recognized
[2015-11-23 13:42:24.251020] W [graph.c:357:_log_if_unknown_option] 0-container-volumes-server: option 'rpc-auth.auth-unix' is not recognized
[2015-11-23 13:42:24.251039] W [graph.c:357:_log_if_unknown_option] 0-container-volumes-server: option 'rpc-auth.auth-null' is not recognized
[2015-11-23 13:42:24.251078] W [graph.c:357:_log_if_unknown_option] 0-container-volumes-quota: option 'timeout' is not recognized
[2015-11-23 13:42:24.251089] W [graph.c:357:_log_if_unknown_option] 0-container-volumes-marker: option 'quota-version' is not recognized
[2015-11-23 13:42:24.251117] W [graph.c:357:_log_if_unknown_option] 0-container-volumes-trash: option 'brick-path' is not recognized

/var/log/glusterfs/etc-glusterfs-glusterd.vol.log
The message "I [MSGID: 106006] [glusterd-svc-mgmt.c:323:glusterd_svc_common_rpc_notify] 0-management: nfs has disconnected from glusterd." repeated 39 times between [2015-11-23 16:34:38.804283] and [2015-11-23 16:36:35.825874]
The message "I [MSGID: 106005] [glusterd-handler.c:4908:__glusterd_brick_rpc_notify] 0-management: Brick shipped-analytics-central-mantl-control-01.node.consul:/mnt/glusterfs/container-volumes has disconnected from glusterd." repeated 39 times between [2015-11-23 16:34:39.831430] and [2015-11-23 16:36:36.857436]
[2015-11-23 16:36:38.826408] W [socket.c:588:__socket_rwv] 0-nfs: readv on /var/run/gluster/23280990e70fc3f879d0f9453b87d757.socket failed (Invalid argument)
[2015-11-23 16:36:38.826486] I [MSGID: 106006] [glusterd-svc-mgmt.c:323:glusterd_svc_common_rpc_notify] 0-management: nfs has disconnected from glusterd.
[2015-11-23 16:36:39.837620] W [socket.c:588:__socket_rwv] 0-management: readv on /var/run/gluster/a656475d4fc3c043c64dc767583c58d9.socket failed (Invalid argument)
[2015-11-23 16:36:39.853642] I [MSGID: 106005] [glusterd-handler.c:4908:__glusterd_brick_rpc_notify] 0-management: Brick shipped-analytics-central-mantl-control-01.node.consul:/mnt/glusterfs/container-volumes has disconnected from glusterd.
[2015-11-23 16:36:41.826930] W [socket.c:588:__socket_rwv] 0-nfs: readv on /var/run/gluster/23280990e70fc3f879d0f9453b87d757.socket failed (Invalid argument)
[2015-11-23 16:36:42.845609] W [socket.c:588:__socket_rwv] 0-management: readv on /var/run/gluster/a656475d4fc3c043c64dc767583c58d9.socket failed (Invalid argument)
[2015-11-23 16:36:44.827403] W [socket.c:588:__socket_rwv] 0-nfs: readv on /var/run/gluster/23280990e70fc3f879d0f9453b87d757.socket failed (Invalid argument)
[2015-11-23 16:36:45.838248] W [socket.c:588:__socket_rwv] 0-management: readv on /var/run/gluster/a656475d4fc3c043c64dc767583c58d9.socket failed (Invalid argument)

The issue was resolved by fully redeploying the cluster

@tymofii-polekhin what did you mean when you redeployed the cluster? do you mean you just reinstalled the gluster packages?

@naisanza no, i did a full cluster redeploy
terraform destroy
terraform apply
ansible-playbook ...


Error accessing PCF Dev after switching network

After switching wireless network, I am seeing the error:
Error performing request: Get https://api.local.pcfdev.io/v2/info: dial tcp <IP_ADDRESS>:443: i/o timeout
TIP: If you are behind a firewall and require an HTTP proxy, verify the https_proxy environment variable is correctly set. Else, check your network connection.

This is sometimes resolved by performing a cf dev stop and cf dev start, but sometimes requires a cf dev destroy, rm ~/.pcfdev ~/.cf and cf dev start.
I have installed and configured dnsmasq according to the instructions at https://docs.pivotal.io/pcf-dev/work-offline.html, but am still getting this issue.
My machine is running MacOS 10.12.4, VirtualBox 5.1.19, cf 6.25.0+787326d95.2017-02-28.
VBox.log ends with
00:00:32.896835 Display::handleDisplayResize: uScreenId=0 pvVRAM=000000010d18f000 w=640 h=480 bpp=32 cbLine=0xA00 flags=0x1
00:00:33.177062 Display::handleDisplayResize: uScreenId=0 pvVRAM=0000000000000000 w=720 h=400 bpp=0 cbLine=0x0 flags=0x1
00:00:33.412870 PIT: mode=2 count=0x12a5 (4773) - 249.98 Hz (ch=0)
00:00:33.633200 PIT: mode=0 count=0x10000 (65536) - 18.20 Hz (ch=0)
00:00:33.635527 CPUM: VCPU  1: Cached APIC base MSR = 0xfee00800
00:00:33.640074 CPUM: VCPU  2: Cached APIC base MSR = 0xfee00800
00:00:33.644445 CPUM: VCPU  3: Cached APIC base MSR = 0xfee00800
00:00:34.089003 AHCI#0: Reset the HBA
00:00:34.104883 AHCI#0: Port 0 reset
00:00:45.583543 AC97: Reset
00:00:45.585446 AC97: Reset
00:00:45.598094 Audio: Skipping to create input stream "[LUN#0] ac97.mc", as the host audio backend reached its maximum of concurrent audio input streams
00:00:45.598220 Audio: Skipping to create input stream "[LUN#0] ac97.mc", as the host audio backend reached its maximum of concurrent audio input streams
00:00:45.598848 Audio: Skipping to create input stream "[LUN#0] ac97.mc", as the host audio backend reached its maximum of concurrent audio input streams
00:00:45.598912 Audio: Skipping to create input stream "[LUN#0] ac97.mc", as the host audio backend reached its maximum of concurrent audio input streams
00:00:45.601601 Audio: Skipping to create input stream "[LUN#0] ac97.mc", as the host audio backend reached its maximum of concurrent audio input streams
00:00:45.607438 Audio: Skipping to create input stream "[LUN#0] ac97.mc", as the host audio backend reached its maximum of concurrent audio input streams
00:00:45.607567 Audio: Skipping to create input stream "[LUN#0] ac97.mc", as the host audio backend reached its maximum of concurrent audio input streams
00:00:45.607668 Audio: Skipping to create input stream "[LUN#0] ac97.mc", as the host audio backend reached its maximum of concurrent audio input streams
00:00:45.607799 Audio: Skipping to create input stream "[LUN#0] ac97.mc", as the host audio backend reached its maximum of concurrent audio input streams
00:00:45.643031 NAT: IPv6 not supported
00:00:45.880086 NAT: DHCP offered IP address <IP_ADDRESS>
00:00:45.881225 NAT: DHCP offered IP address <IP_ADDRESS>

Any advice on what to look at next?

Hi @nigelcharman,
This is an issue with Virtualbox host-only networking, where the VM IP (<IP_ADDRESS>) becomes inaccessible to the host. This happens because your operating system modifies the routing tables when you switch networks, and it can't be solved with DNS.
We could investigate adding a cf dev fix-networking command in a future release, but there isn't much we can do aside from that.

Thanks @sclevine, a cf dev fix-networking command would be useful since it would save 10-20 minutes of rebuilding PCF Dev each time this happens.

The same problem has been seen running boot2docker on VirtualBox. Here is a fix using the VBoxManage commands:
boot2docker issue 945 comment 130113866
The short version is
a) find name of running vm: VBoxManage list runningvms
b) look up vbox network name in use by the vm: VBoxManage showvminfo <name-of-vm> | grep "Host-only Interface"
c) stop then start the network: sudo ifconfig <vboxnetX> down && sudo ifconfig <vboxnetX> up
I can confirm this works for me.


Fix blog nav indicator

Currently, the nav indicator will only stay on blog if we are on the root route. We should allow for an option to ember-3d-nav to only check parent routes for the route.

Fixed!


Improve object CRUD methods handling

This PR attempts to improve the CRUD handling process of objects.
It introduces the __parse_properties method in the collection.collection._Data class that compares the user defined input object with the collection's Weaviate schema config. If the input object's cross reference definition does not conform with the schema config then an error is thrown. Furthermore, in the case of the user defining a cross reference with multiple targets, they are required to provide the specific class to which they are referencing with a runtime check through the same config comparison. Such a comparison must occur at runtime due to the mutable nature of Weaviate class names.
A missing piece of this PR is the ability to functionality pass the class name of a cross reference at query time through the LinkTo class. This functionality requires an update to Weaviate's gRPC endpoints, which is an ongoing open PR.
It also tries to improve the UX of the API by renaming certain classes to be better aligned in function. Specifically, RefToObject is renamed to ReferenceTo to conform with the naming convention of LinkTo. In addition, the previous ReferenceTo is renamed to CrossReference to avoid a naming collision with the previous change.
Finally, a collection's schema config is loaded upon each instantiation of a client collection through either client.collection.create() or client.collection.get() and cached for all downstream usages. The cache is revalidated when the schema is updated by any of the client.config methods. As such, the collection.add_property method is also moved to collection.config.add_property since this requires cache revalidation.
Such an implementation may be optimised through the use of DataLoaders. A consideration here should also be around the potential multi-threading issues this may incur. If it is preferable, schema retrieval could happen on a per-request basis rather than once per-collection-lifecycle. This could create a chatty client, however, due to the doubling of requests.

Codecov Report
Patch coverage: 68.93% and project coverage change: -0.23% :warning:

Comparison is base (346c008) 93.95% compared to head (b2df1e7) 93.72%.

Additional details and impacted files
@@                   Coverage Diff                   @@
##           pydantic_experiment     #414      +/-   ##
=======================================================
- Coverage                93.95%   93.72%   -0.23%
=======================================================
  Files                       72       72
  Lines                     9919     9986      +67
=======================================================
+ Hits                      9319     9359      +40
- Misses                     600      627      +27

Files Changed
Coverage Δ

integration/test_collection_model.py
90.05% <0.00%> (ø)

integration/test_collection.py
93.07% <28.00%> (-6.93%)
:arrow_down:

weaviate/collection/collection_base.py
60.20% <76.00%> (+1.18%)
:arrow_up:

weaviate/collection/classes.py
94.60% <80.00%> (-1.09%)
:arrow_down:

weaviate/collection/collection.py
76.22% <94.44%> (+3.03%)
:arrow_up:

test/collection/test_collection_model.py
96.15% <100.00%> (ø)

weaviate/collection/grpc.py
93.61% <100.00%> (+0.03%)
:arrow_up:

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


Dcase2021

Excuse me, in the  branch of dcase2021, it seems that there are some missing hyperparameters in both the dcase2021_xe.yaml and dcase2021_scst.yaml configuration files. Could you please provide the complete configuration files?

Which hyperparameters are missing?

Thank you for your reply! For example,there are some codes in class Runner in run.py
def _get_model(config, outputfun=sys.stdout): vocabulary = config["vocabulary"]
encoder = getattr(
encoder1, config["encoder"])(
config["data"]["raw_feat_dim"],  config["data"]["fc_feat_dim"],  config["data"]["attn_feat_dim"],  **config["encoder_args"]
)
Therefore,not only the structure of config in your dcase2021 should change,but also some hyperparameters needs to be added.
data:
total_iters:
zh: False
raw_feat_dim:
fc_feat_dim:
attn_feat_dim:

Thank you for your reply! For example,there are some codes in class Runner in run.py
def _get_model(config, outputfun=sys.stdout): vocabulary = config["vocabulary"]
encoder = getattr(
encoder1, config["encoder"])(
config["data"]["raw_feat_dim"], config["data"]["fc_feat_dim"], config["data"]["attn_feat_dim"], **config["encoder_args"]
)
Therefore,not only the structure of config in your dcase2021 should change,but also some hyperparameters needs to be added.
data:
total_iters:
zh: False
raw_feat_dim:
fc_feat_dim:
attn_feat_dim:

The DCASE2021 branch uses captioning/ignite_runners/run.py instead of captioning/pytorch_runners/run.py

Although in https://github.com/wsntxxn/AudioCaption/blob/dcase2021/captioning/ignite_runners/run.py, these hyperparameters also lack.
class Runner(BaseRunner):
@staticmethod
def _get_model(config, outputfun=sys.stdout):
vocabulary = config["vocabulary"]
encoder = getattr(
captioning.models.encoder, config["encoder"])(
config["data"]["raw_feat_dim"],
config["data"]["fc_feat_dim"],
config["data"]["attn_feat_dim"],
**config["encoder_args"]
)
These hyperparameters also need to be added.
data:
    total_iters:
    zh: False
    raw_feat_dim:
    fc_feat_dim:
    attn_feat_dim:

These are automatically generated during training: https://github.com/wsntxxn/AudioCaption/blob/dcase2021/captioning/ignite_runners/run.py#L122, https://github.com/wsntxxn/AudioCaption/blob/dcase2021/captioning/ignite_runners/run.py#L297.

These are automatically generated during training: https://github.com/wsntxxn/AudioCaption/blob/dcase2021/captioning/ignite_runners/run.py#L122, https://github.com/wsntxxn/AudioCaption/blob/dcase2021/captioning/ignite_runners/run.py#L297.

I'm so sorry to bother you another time. In the code of dcase2021, performing "prepare data" operations does not affect the config, and when executing the training script, it is necessary to use the fire to execute the Runner class first. The static method _get_model in the Runner class needs to be based on the raw_feat_dim, fc_feat_dim, and attn_feat_dim under the data configuration file. When I tried to reproduce your code for Dcase 2021, I found that when executing "python ignite_runners\run.py train config\dcase2021\dcase2021_xe.yaml", it indeed reported a KeyError: 'data' error. So, could you please check it again?

Configuration updated and you can try again.


Isolate Cookie handling

Add a Cookie handler to isolate read and write operations
Remove inmemory consent repository, not necessary now, we just inject a CookieHandler with a JSDOM to mock dom side effects
Add CookieHandler test cases
Fix consent repository tests

Codecov Report

Merging #23 into feature/develop-v1.0.0 will increase coverage by 1.26%.
The diff coverage is 100%.

@@                    Coverage Diff                     @@
##           feature/develop-v1.0.0      #23      +/-   ##
==========================================================
+ Coverage                   97.11%   98.38%   +1.26%
==========================================================
  Files                          26       27       +1
  Lines                        1075     1115      +40
  Branches                      103      107       +4
==========================================================
+ Hits                         1044     1097      +53
+ Misses                         31       18      -13

Impacted Files
Coverage Δ

...frastructure/repository/CookieConsentRepository.js
100% <100%> (+15.66%)
:arrow_up:

src/cmp/infrastructure/service/CookieHandler.js
100% <100%> (ø)

src/cmp/infrastructure/cmpInitializer.js
100% <100%> (ø)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 275d6f4...e933f07. Read the comment docs.


Convert cron_d LWRP to Chef 12.5 Custom Resource

Chef Summit Hack Day!

I'm going to get final releases with Chef 11 support out the door and then I'd love to ship this.

@veetow Can you rebase this and add the now create_if_missing action that was added since this work was done.

@tas50 Sorry, somehow I missed your ask for a rebase.  I'll try to get to it ASAP.

Rebased (history rewrite). Tests pass on my end.

Thanks for this initial work. I picked up the torch and we converted the cookbook over to a custom resource in the last release


Create 00_intro_to_emulator.ipynb

We test the emulator on windows, create a bell state and then visualize different results.

Hi @manannarang
I appreciate the willingness to contribute to the repository! I think the notebook you've created is an excellent Qiskit tutorial, but it does not seem to use the Qiskit Dell Runtime code for much other than obtaining a backend through the BackendProvider. As such I don't believe this fits really with our repository, though if you'd like to rearchitect it a little bit by using the DellRuntimeProvider to run a runtime program in a local execution environment (see some of the other examples) then we might be able to give it another look.
I'm going to close this for now but if you do make those changes you're welcome to reopen it.

Actually I was just testing it on windows which is working fine now.


Request an example using SSL

I would love to see an example using the -ssl option.
Thanks!

https://github.com/joewalnes/websocketd/issues/17#issuecomment-46619783 and next message


⚠ ClamAV has degraded performance

In 82b1653, ClamAV (https://spamassassin.apache.org/) experienced degraded performance:

HTTP code: 200
Response time: 78 ms

Resolved: ClamAV performance has improved in bb5c297 after 5 minutes.


Well, we need to rewrite the Readme from scratch of these days, so maybe we could wait to merge this pr and add some more changes to it so the description of our engine is as updated as possible? (Or at least it could have a generic description that would serve us for the rest of the milestones until we can do the definitive one).

you can continue using this PR to finish the readme changes or create a different one, but make sure not to forget to solve the typo

sure!!


[WIP] Support sdk remote workflow

TL;DR
Adding support for SdkRemoteWorkflow, similarly to the existing SdkRemoteTask
Type

[ ] Bug Fix
[x] Feature
[ ] Plugin

Are all requirements met?

[ ] Code completed
[ ] Smoke tested
[x] Unit tests added
[ ] Code documentation added
[ ] Any pending items have an associated Issue

Complete description
Created a SdkRemoteWorkflow class that implements the apply method to return a SdkNode.
The SdkWorkflowNode/WorkflowNode classes were already implemented previously.
Tracking Issue
Fixes https://github.com/flyteorg/flyte/issues/1002
Follow-up issue
NA

Let's discuss this PR early next year, maybe we don't need to merge it and stick to the explicit SdkRemoteLaunchPlan

The SdkRemoteWorkflow is just a wrapper of the default launch plan for that workflow https://github.com/flyteorg/flytekit/blob/ab0489112624d85a1341073eb722fa328e008745/flytekit/remote/remote.py#L845
Since the SdkRemoteLaunchPlan is implemented separately, maybe we don't need to implement this one

We decided to not implement the SdkRemoteWorkflow for now.
In Flyte, the Tasks and LaunchPlans are the entities that are supposed to be used remotely.
(For flytekit python) Although the FlyteWorkflow is implemented in the FlyteRemote, it's just fetching the default launch plan for the workflow and executing it.
Use the SdkRemoteLaunchPlan for Remote LaunchPlan or Workflow executions.


Reset password via form instead of emailing a new password

Instead of sending the password in an email, allow user to choose her password (wisely).

 #19 Reset password via form instead of emailing a new password

MUST HAVE TEST CASE


error when test my own wav file

I test my own wav file, cmd is
python demo.py --model_name vocaset --wav_path "demo/wav/fb6d70e9cd7b2bed30fa1504330180f3.wav" --dataset vocaset --vertice_dim 15069 --feature_dim 64 --period 30  --fps 30  --train_subjects "FaceTalk_170728_03272_TA FaceTalk_170904_00128_TA FaceTalk_170725_00137_TA FaceTalk_170915_00223_TA FaceTalk_170811_03274_TA FaceTalk_170913_03279_TA FaceTalk_170904_03276_TA FaceTalk_170912_03278_TA" --test_subjects "FaceTalk_170809_00138_TA FaceTalk_170731_00024_TA" --condition FaceTalk_170913_03279_TA --subject FaceTalk_170809_00138_TA

but output error as below
Some weights of Wav2Vec2Model were not initialized from the model checkpoint at facebook/wav2vec2-base-960h and are newly initialized: ['wav2vec2.masked_spec_embed']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
Traceback (most recent call last):
  File "demo.py", line 204, in <module>
    main()
  File "demo.py", line 200, in main
    test_model(args)
  File "demo.py", line 57, in test_model
    prediction = model.predict(audio_feature, template, one_hot)
  File "/evo_860/yaobin.li/workspace/FaceFormer/faceformer.py", line 157, in predict
    vertice_out = self.transformer_decoder(vertice_input, hidden_states, tgt_mask=tgt_mask, memory_mask=memory_mask)
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/transformer.py", line 248, in forward
    output = mod(output, memory, tgt_mask=tgt_mask,
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/transformer.py", line 451, in forward
    x = self.norm1(x + self._sa_block(x, tgt_mask, tgt_key_padding_mask))
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/transformer.py", line 460, in _sa_block
    x = self.self_attn(x, x, x,
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/activation.py", line 1003, in forward
    attn_output, attn_output_weights = F.multi_head_attention_forward(
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/functional.py", line 5016, in multi_head_attention_forward
    raise RuntimeError(f"The shape of the 3D attn_mask is {attn_mask.shape}, but should be {correct_3d_size}.")
RuntimeError: The shape of the 3D attn_mask is torch.Size([4, 600, 600]), but should be (4, 601, 601)

and i check my wav file info
ffmpeg -i ~/wks/FaceFormer/demo/wav/fb6d70e9cd7b2bed30fa1504330180f3.wav
ffmpeg version 4.3 Copyright (c) 2000-2020 the FFmpeg developers
  built with gcc 7.3.0 (crosstool-NG <IP_ADDRESS>9-a04d0)
  configuration: --prefix=/home/yaobin.li/soft/miniconda3/envs/wenet --cc=/opt/conda/conda-bld/ffmpeg_1597178665428/_build_env/bin/x86_64-conda_cos6-linux-gnu-cc --disable-doc --disable-openssl --enable-avresample --enable-gnutls --enable-hardcoded-tables --enable-libfreetype --enable-libopenh264 --enable-pic --enable-pthreads --enable-shared --disable-static --enable-version3 --enable-zlib --enable-libmp3lame
  libavutil      56. 51.100 / 56. 51.100
  libavcodec     58. 91.100 / 58. 91.100
  libavformat    58. 45.100 / 58. 45.100
  libavdevice    58. 10.100 / 58. 10.100
  libavfilter     7. 85.100 /  7. 85.100
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  7.100 /  5.  7.100
  libswresample   3.  7.100 /  3.  7.100
Guessed Channel Layout for Input Stream #0.0 : mono
Input #0, wav, from '/home/yaobin.li/wks/FaceFormer/demo/wav/fb6d70e9cd7b2bed30fa1504330180f3.wav':
  Metadata:
    encoder         : Lavf58.45.100
  Duration: 00:01:37.94, bitrate: 256 kb/s
    Stream #0:0: Audio: pcm_s16le ([1][0][0][0] / 0x0001), 16000 Hz, mono, s16, 256 kb/s

So is it audio issues?

I test my own wav file, cmd is
python demo.py --model_name vocaset --wav_path "demo/wav/fb6d70e9cd7b2bed30fa1504330180f3.wav" --dataset vocaset --vertice_dim 15069 --feature_dim 64 --period 30  --fps 30  --train_subjects "FaceTalk_170728_03272_TA FaceTalk_170904_00128_TA FaceTalk_170725_00137_TA FaceTalk_170915_00223_TA FaceTalk_170811_03274_TA FaceTalk_170913_03279_TA FaceTalk_170904_03276_TA FaceTalk_170912_03278_TA" --test_subjects "FaceTalk_170809_00138_TA FaceTalk_170731_00024_TA" --condition FaceTalk_170913_03279_TA --subject FaceTalk_170809_00138_TA

but output error as below
Some weights of Wav2Vec2Model were not initialized from the model checkpoint at facebook/wav2vec2-base-960h and are newly initialized: ['wav2vec2.masked_spec_embed']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
Traceback (most recent call last):
  File "demo.py", line 204, in <module>
    main()
  File "demo.py", line 200, in main
    test_model(args)
  File "demo.py", line 57, in test_model
    prediction = model.predict(audio_feature, template, one_hot)
  File "/evo_860/yaobin.li/workspace/FaceFormer/faceformer.py", line 157, in predict
    vertice_out = self.transformer_decoder(vertice_input, hidden_states, tgt_mask=tgt_mask, memory_mask=memory_mask)
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/transformer.py", line 248, in forward
    output = mod(output, memory, tgt_mask=tgt_mask,
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/transformer.py", line 451, in forward
    x = self.norm1(x + self._sa_block(x, tgt_mask, tgt_key_padding_mask))
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/transformer.py", line 460, in _sa_block
    x = self.self_attn(x, x, x,
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/activation.py", line 1003, in forward
    attn_output, attn_output_weights = F.multi_head_attention_forward(
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/functional.py", line 5016, in multi_head_attention_forward
    raise RuntimeError(f"The shape of the 3D attn_mask is {attn_mask.shape}, but should be {correct_3d_size}.")
RuntimeError: The shape of the 3D attn_mask is torch.Size([4, 600, 600]), but should be (4, 601, 601)

and i check my wav file info
ffmpeg -i ~/wks/FaceFormer/demo/wav/fb6d70e9cd7b2bed30fa1504330180f3.wav
ffmpeg version 4.3 Copyright (c) 2000-2020 the FFmpeg developers
  built with gcc 7.3.0 (crosstool-NG <IP_ADDRESS>9-a04d0)
  configuration: --prefix=/home/yaobin.li/soft/miniconda3/envs/wenet --cc=/opt/conda/conda-bld/ffmpeg_1597178665428/_build_env/bin/x86_64-conda_cos6-linux-gnu-cc --disable-doc --disable-openssl --enable-avresample --enable-gnutls --enable-hardcoded-tables --enable-libfreetype --enable-libopenh264 --enable-pic --enable-pthreads --enable-shared --disable-static --enable-version3 --enable-zlib --enable-libmp3lame
  libavutil      56. 51.100 / 56. 51.100
  libavcodec     58. 91.100 / 58. 91.100
  libavformat    58. 45.100 / 58. 45.100
  libavdevice    58. 10.100 / 58. 10.100
  libavfilter     7. 85.100 /  7. 85.100
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  7.100 /  5.  7.100
  libswresample   3.  7.100 /  3.  7.100
Guessed Channel Layout for Input Stream #0.0 : mono
Input #0, wav, from '/home/yaobin.li/wks/FaceFormer/demo/wav/fb6d70e9cd7b2bed30fa1504330180f3.wav':
  Metadata:
    encoder         : Lavf58.45.100
  Duration: 00:01:37.94, bitrate: 256 kb/s
    Stream #0:0: Audio: pcm_s16le ([1][0][0][0] / 0x0001), 16000 Hz, mono, s16, 256 kb/s

So is it audio issues?

The default value of max_seq_len is 600. If you'd like to use longer audio, e.g., 1~3min,
in the "demo.py" file, please add:
from faceformer import PeriodicPositionalEncoding, init_biased_mask model.PPE = PeriodicPositionalEncoding(args.feature_dim, period = args.period, max_seq_len=6000) model.biased_mask = init_biased_mask(n_head = 4, max_seq_len = 6000, period=args.period)
after the line27: model.load_state_dict(.....).

I test my own wav file, cmd is
python demo.py --model_name vocaset --wav_path "demo/wav/fb6d70e9cd7b2bed30fa1504330180f3.wav" --dataset vocaset --vertice_dim 15069 --feature_dim 64 --period 30  --fps 30  --train_subjects "FaceTalk_170728_03272_TA FaceTalk_170904_00128_TA FaceTalk_170725_00137_TA FaceTalk_170915_00223_TA FaceTalk_170811_03274_TA FaceTalk_170913_03279_TA FaceTalk_170904_03276_TA FaceTalk_170912_03278_TA" --test_subjects "FaceTalk_170809_00138_TA FaceTalk_170731_00024_TA" --condition FaceTalk_170913_03279_TA --subject FaceTalk_170809_00138_TA

but output error as below
Some weights of Wav2Vec2Model were not initialized from the model checkpoint at facebook/wav2vec2-base-960h and are newly initialized: ['wav2vec2.masked_spec_embed']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
Traceback (most recent call last):
  File "demo.py", line 204, in <module>
    main()
  File "demo.py", line 200, in main
    test_model(args)
  File "demo.py", line 57, in test_model
    prediction = model.predict(audio_feature, template, one_hot)
  File "/evo_860/yaobin.li/workspace/FaceFormer/faceformer.py", line 157, in predict
    vertice_out = self.transformer_decoder(vertice_input, hidden_states, tgt_mask=tgt_mask, memory_mask=memory_mask)
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/transformer.py", line 248, in forward
    output = mod(output, memory, tgt_mask=tgt_mask,
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/transformer.py", line 451, in forward
    x = self.norm1(x + self._sa_block(x, tgt_mask, tgt_key_padding_mask))
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/transformer.py", line 460, in _sa_block
    x = self.self_attn(x, x, x,
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/activation.py", line 1003, in forward
    attn_output, attn_output_weights = F.multi_head_attention_forward(
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/functional.py", line 5016, in multi_head_attention_forward
    raise RuntimeError(f"The shape of the 3D attn_mask is {attn_mask.shape}, but should be {correct_3d_size}.")
RuntimeError: The shape of the 3D attn_mask is torch.Size([4, 600, 600]), but should be (4, 601, 601)

and i check my wav file info
ffmpeg -i ~/wks/FaceFormer/demo/wav/fb6d70e9cd7b2bed30fa1504330180f3.wav
ffmpeg version 4.3 Copyright (c) 2000-2020 the FFmpeg developers
  built with gcc 7.3.0 (crosstool-NG <IP_ADDRESS>9-a04d0)
  configuration: --prefix=/home/yaobin.li/soft/miniconda3/envs/wenet --cc=/opt/conda/conda-bld/ffmpeg_1597178665428/_build_env/bin/x86_64-conda_cos6-linux-gnu-cc --disable-doc --disable-openssl --enable-avresample --enable-gnutls --enable-hardcoded-tables --enable-libfreetype --enable-libopenh264 --enable-pic --enable-pthreads --enable-shared --disable-static --enable-version3 --enable-zlib --enable-libmp3lame
  libavutil      56. 51.100 / 56. 51.100
  libavcodec     58. 91.100 / 58. 91.100
  libavformat    58. 45.100 / 58. 45.100
  libavdevice    58. 10.100 / 58. 10.100
  libavfilter     7. 85.100 /  7. 85.100
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  7.100 /  5.  7.100
  libswresample   3.  7.100 /  3.  7.100
Guessed Channel Layout for Input Stream #0.0 : mono
Input #0, wav, from '/home/yaobin.li/wks/FaceFormer/demo/wav/fb6d70e9cd7b2bed30fa1504330180f3.wav':
  Metadata:
    encoder         : Lavf58.45.100
  Duration: 00:01:37.94, bitrate: 256 kb/s
    Stream #0:0: Audio: pcm_s16le ([1][0][0][0] / 0x0001), 16000 Hz, mono, s16, 256 kb/s

So is it audio issues?

The default value of max_seq_len is 600. If you'd like to use longer audio, e.g., 1~3min,
in the "demo.py" file, please add:
from faceformer import PeriodicPositionalEncoding, init_biased_mask model.PPE = PeriodicPositionalEncoding(args.feature_dim, period = args.period, max_seq_len=6000) model.biased_mask = init_biased_mask(n_head = 4, max_seq_len = 6000, period=args.period)
after the line27: model.load_state_dict(.....).

thanks for your reply!
After the modification according to your suggestion, another problem occurred, it will be killed by system
[1]    5863 killed     python demo.py --model_name vocaset --wav_path "demo/wav/qq.wav" --dataset

I test my own wav file, cmd is
python demo.py --model_name vocaset --wav_path "demo/wav/fb6d70e9cd7b2bed30fa1504330180f3.wav" --dataset vocaset --vertice_dim 15069 --feature_dim 64 --period 30  --fps 30  --train_subjects "FaceTalk_170728_03272_TA FaceTalk_170904_00128_TA FaceTalk_170725_00137_TA FaceTalk_170915_00223_TA FaceTalk_170811_03274_TA FaceTalk_170913_03279_TA FaceTalk_170904_03276_TA FaceTalk_170912_03278_TA" --test_subjects "FaceTalk_170809_00138_TA FaceTalk_170731_00024_TA" --condition FaceTalk_170913_03279_TA --subject FaceTalk_170809_00138_TA

but output error as below
Some weights of Wav2Vec2Model were not initialized from the model checkpoint at facebook/wav2vec2-base-960h and are newly initialized: ['wav2vec2.masked_spec_embed']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
Traceback (most recent call last):
  File "demo.py", line 204, in <module>
    main()
  File "demo.py", line 200, in main
    test_model(args)
  File "demo.py", line 57, in test_model
    prediction = model.predict(audio_feature, template, one_hot)
  File "/evo_860/yaobin.li/workspace/FaceFormer/faceformer.py", line 157, in predict
    vertice_out = self.transformer_decoder(vertice_input, hidden_states, tgt_mask=tgt_mask, memory_mask=memory_mask)
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/transformer.py", line 248, in forward
    output = mod(output, memory, tgt_mask=tgt_mask,
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/transformer.py", line 451, in forward
    x = self.norm1(x + self._sa_block(x, tgt_mask, tgt_key_padding_mask))
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/transformer.py", line 460, in _sa_block
    x = self.self_attn(x, x, x,
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/modules/activation.py", line 1003, in forward
    attn_output, attn_output_weights = F.multi_head_attention_forward(
  File "/home/yaobin.li/soft/miniconda3/envs/wenet/lib/python3.8/site-packages/torch/nn/functional.py", line 5016, in multi_head_attention_forward
    raise RuntimeError(f"The shape of the 3D attn_mask is {attn_mask.shape}, but should be {correct_3d_size}.")
RuntimeError: The shape of the 3D attn_mask is torch.Size([4, 600, 600]), but should be (4, 601, 601)

and i check my wav file info
ffmpeg -i ~/wks/FaceFormer/demo/wav/fb6d70e9cd7b2bed30fa1504330180f3.wav
ffmpeg version 4.3 Copyright (c) 2000-2020 the FFmpeg developers
  built with gcc 7.3.0 (crosstool-NG <IP_ADDRESS>9-a04d0)
  configuration: --prefix=/home/yaobin.li/soft/miniconda3/envs/wenet --cc=/opt/conda/conda-bld/ffmpeg_1597178665428/_build_env/bin/x86_64-conda_cos6-linux-gnu-cc --disable-doc --disable-openssl --enable-avresample --enable-gnutls --enable-hardcoded-tables --enable-libfreetype --enable-libopenh264 --enable-pic --enable-pthreads --enable-shared --disable-static --enable-version3 --enable-zlib --enable-libmp3lame
  libavutil      56. 51.100 / 56. 51.100
  libavcodec     58. 91.100 / 58. 91.100
  libavformat    58. 45.100 / 58. 45.100
  libavdevice    58. 10.100 / 58. 10.100
  libavfilter     7. 85.100 /  7. 85.100
  libavresample   4.  0.  0 /  4.  0.  0
  libswscale      5.  7.100 /  5.  7.100
  libswresample   3.  7.100 /  3.  7.100
Guessed Channel Layout for Input Stream #0.0 : mono
Input #0, wav, from '/home/yaobin.li/wks/FaceFormer/demo/wav/fb6d70e9cd7b2bed30fa1504330180f3.wav':
  Metadata:
    encoder         : Lavf58.45.100
  Duration: 00:01:37.94, bitrate: 256 kb/s
    Stream #0:0: Audio: pcm_s16le ([1][0][0][0] / 0x0001), 16000 Hz, mono, s16, 256 kb/s

So is it audio issues?

The default value of max_seq_len is 600. If you'd like to use longer audio, e.g., 1~3min,
in the "demo.py" file, please add:
from faceformer import PeriodicPositionalEncoding, init_biased_mask model.PPE = PeriodicPositionalEncoding(args.feature_dim, period = args.period, max_seq_len=6000) model.biased_mask = init_biased_mask(n_head = 4, max_seq_len = 6000, period=args.period)
after the line27: model.load_state_dict(.....).

thanks for your reply! After the modification according to your suggestion, another problem occurred, it will be killed by system
[1]    5863 killed     python demo.py --model_name vocaset --wav_path "demo/wav/qq.wav" --dataset

I solved this problem according to this issue #2


Developer count rollup doesn't recalculate using API

I am using a rollup to calculate the COUNT of child records, using Id in the Field to aggregate.
I use the bellow trigger on the child object, and it works for SUM rollups, but not for the COUNT.
It works if I manually do a Full Calculate.
What am I missing?
trigger Zen_SOL_CalculateRollups on OrderApi__Sales_Order_Line__c (after insert,after update) {
if(!system.isBatch()) {
try{
dlrs.RollupService.rollup(trigger.oldMap,trigger.newMap,OrderApi__Sales_Order_Line__c.SObjectType);
} catch(Exception ex){
system.debug(ex.getMessage());
}
}
}

@tiagoefreitas could you provide some information your rollup configuration that you're using for this?


Add LZ4 to installation instructions/AMI

Currently we do not install LZ4 which leads to the warning: "Warning: lz4 not available, disabling sample compression. This will significantly impact RLlib performance. To install lz4, run 'pip install lz4'"

resolved by #300


General: Only position footer absolute on desktop

Checklist
General

[ ] I tested all changes and their related features with all corresponding user types on a test server.
[x] This is a small issue that I tested locally and was confirmed by another developer on a test server.
[x] Language: I followed the guidelines for inclusive, diversity-sensitive, and appreciative language.
[x] I chose a title conforming to the naming conventions for pull requests.

Motivation and Context

This PR changed the footer style and moved the main footer css to the root element. It also removed the fixed class, that was only applied on desktop screen sizes. This lead to the issue, that the footer on mobile devices also got a position: absolute css property:

Description

This PR moves the main css back into the child <footer> element and applies the fixed class only for the desktop footer element. That way the mobile footer does not get the position: absolute property and should work fine again.
Steps for Testing

Prerequisites:

1 User

Log in to Artemis
Open any page with a longer content (e.g. a course in the course management page) on a mobile device
The footerbar should not be hanging in the middle of the screen after scrolling a bit down

Review Progress

Code Review

[ ] Review 1
[ ] Review 2

Manual Tests

[x] Test 1
[ ] Test 2

Exam Mode Test

[ ] Test

Screenshots

This is an issue that was known at the time of merging, and that was also fixed. see https://github.com/ls1intum/Artemis/pull/5869#pullrequestreview-1192036423 https://github.com/ls1intum/Artemis/pull/5869/commits/0b19651017d50e6de649ae9326904e892b82a6f5.
Strangely, the fix does not exist on the current release (maybe due to merge conflicts?), but it does already on develop. Thanks for your effort, however there doesn't seem to be an issue if you just check out the latest version of develop.


Make rust compilation faster in Docker.

Currently the dockerfile to build the API itself is :
FROM rustlang/rust:nightly
RUN apt install -y libpq-dev git
WORKDIR /~
COPY Rocket.toml .
COPY Cargo.toml .
COPY diesel.toml .
COPY src src
COPY migrations migrations
RUN cargo build --release
ENTRYPOINT ["target/release/rocket_diesel_demo"]

What is to be achieved?

Reduce build time, maybe using cargo vendor
Remove src files, by doing something like this:

FROM rust:1.61.0 as builder
WORKDIR /usr/src/myapp
COPY . .
RUN cargo install --path .

FROM debian:buster-slim as runner
RUN apt-get update && apt-get install -y extra-runtime-dependencies && rm -rf /var/lib/apt/lists/*
COPY --from=builder /usr/local/cargo/bin/myapp /usr/local/bin/myapp
CMD ["myapp"]

The solution i came up with involves cargo chef, a crate created to solve the issue of downloading and building dependencies every time docker-compose up --build is invoked.
# Stage1 : fetch needed dependecies
FROM rust:latest as dep-fetcher
WORKDIR /app
RUN cargo install cargo-chef
COPY . .


Incompatibility with react 15.4.0

React 15.4.0 has been released which removes a lot of the internals, specifically around ReactInputSelection which causes 3.3.0 to break. Saw this had been remedied in the latest commits though.
It would be good to get this released soon as it's likely a lot of people will be upgrading in the next few days.
Thanks 👍

ERROR in ./~/react-maskedinput/lib/index.js
Module not found: Error: Cannot resolve module 'react/lib/ReactInputSelection' in /Users/contra/Projects/staeco/node_modules/react-maskedinput/lib
 @ ./~/react-maskedinput/lib/index.js 9:15-55

:+1:
I was about to open the same issue!

Getting the same error when upgrading to react v15.4

Hope you fix this issue soon 👍

We have the same problem!!! Help

It was fixed two days ago, the commit is there but no release. What gives?

Not sure if it helps anyone else. I was having the same issue and got around it by changing dependencies back to 15.03.
{
    "react": "~15.3.1",
    "react-dom": "~15.3.1"
}

Basically switched the ^ to ~.
I noticed that the commit looks like it fixes it, but it didn't seem to work if I forced npm to pull from git repo instead of NPM.

I'm seeing the issue in the es6 generated file in /es6/index.js and /lib/index.js on L9:
var _require = require('react/lib/ReactInputSelection');

Looks like it just hasn't been published since the last change: https://www.npmjs.com/package/react-maskedinput

We are facing the same issue

Yeah, the changes are not published :/
Well i guess i will copy the source to my project and use it as a custom component.

Any update on this? Where are you planning to republish the to npm this fix?

Anything we can do to help get the fix released? Really excited to upgrade to 15.4.

same problem here, it's awful when happened on deploy day.

Yo! Thanks for the super quick fix. Any chance we could have a published build soon? :)

+1 on this! Would love to use the NPM package instead of copy/pasta code in my project.

Heyo. Apologies for the delay. I was on holiday with my family. Published<EMAIL_ADDRESS>


Bug: Widget content cannot be highlighted or properly interacted with when resize enabled.

When resize is enabled, you cannot highlight text or other data within the widget area.  For instance highlighting text to copy or interacting with a WYSIWYG such as Redactor or ckeditor as this related bug report indicates: https://github.com/ducksboard/gridster.js/issues/290
Turning resize off works around the issue but at the cost of this very powerful (and critical for my uses) feature.  It seems like clicks are being captured and prevented from functioning whenever resize is enable for some reason.
Is there a workaround for this?

This also solved the issue for me.

Can this be merged into the official?

+1


Intergrade the keyValues endpoints with the normal ones

Is your feature request related to a problem? Please describe.
Updating entities with keyValues form is now supported by update_entity_key_values and update_entity_attributes_key_values. However, the request options like append , overrideMetadata , forcedUpdate are not implemented
Describe the solution you'd like
We should consider intergrade the keyvalues support into the normal functions, which would make the code easier to maintain

Check official docs: https://fiware-orion.readthedocs.io/en/master/orion-api.html#update-attribute-value-put-v2entitiesentityidattrsattrnamevalue


istio Gateway ignores SSL certificate updates

hello,
I have created the secret to hold the certificat of istio gateway
kubectl create secret tls istio-ingressgateway-certs --cert xxx.crt --key xxx.key
apiVersion: networking.istio.io/v1alpha3
kind: Gateway
metadata:
  name: app-gateway
spec:
  selector:
    istio: ingressgateway
  servers:
  - port:
      number: 443
      name: https
      protocol: HTTPS
    tls:
      mode: SIMPLE
      serverCertificate: /etc/istio/ingressgateway-certs/tls.crt
      privateKey: /etc/istio/ingressgateway-certs/tls.key
    hosts:
    - "*"

ANd i want to use a new certificat, so I recreate the secret
kubectl delete secret tls istio-ingressgateway-certs --certxxx.crt --key xxx.key
kubectl create secret tls istio-ingressgateway-certs --certxxx.crt --key xxx.key
However, the certificat does not update without restarting istiogateway pod.
I read the doc https://istio.io/latest/docs/tasks/traffic-management/ingress/secure-ingress/, which can specify the certificat to use by CURL.
But we want to refresh the certificat from chrome, so how to update the certificat directly from browser please?
Https://xxxxx/test, we could update certificat directly
Thanks

Please follow https://istio.io/latest/docs/tasks/traffic-management/ingress/secure-ingress/, which uses credentialName. This is a known limitation of the old settings you are using which is why they are not longer recommended or documented. Thanks

Please follow https://istio.io/latest/docs/tasks/traffic-management/ingress/secure-ingress/, which uses credentialName. This is a known limitation of the old settings you are using which is why they are not longer recommended or documented. Thanks

hello, i have tried credentialName, which does not update certifcat neither.
In the document, it proposed to use Curl that could specify the crt.
However, we cann't do that from chrome


Game Mode Files

I would suggest a way to have game modes in a file so people can create and share game modes without changing code.

Falls under #31


RPI 4 AArch64 not working

Running on a RPI 4 with ArchlinuxArm AArch64, it fails while "running late hook [overlayroot]
mount: /new_root: unknown filesystem type 'overlay'
ERROR: Failed to mount the real root device.
 Good Luck.

Disregard.
 Everything works as it should.
Thanks for your work on this project. I've been using it for many years on regular ArchlinuxArm. Works great!


Update native install instructions

With the current instructions you will get:
error: multiple packages with binaries found: test-suite, winterjs. When installing a git repository, cargo will always search the entire repo for any Cargo.toml. Please specify a package, e.g. `cargo install --git https://github.com/wasmerio/winterjs test-suite`.

Must specify the binary to install.

Awesome, thanks for the improvement!


Enhancement | Storing best checkpoint

Is there a way to store the best checkpoint among many so if somebody wants to store the best and not necessarily among every 20,000 checkpoints ? This way should be ideal if the dataset is not balanced.

This is not practical, as a full evaluation will be very time consuming. And after the training is stable, the results are basically the same. @deimsdeutsch

@yangxue0827 Very much practical and has been implemented by many frameworks. Just save the output of checkpoint in a best variable and replace it with the next if it is better. Keep the check for every best interval in the configuration file.

I mean a full evaluation will be very time consuming.  @deimsdeutsch

Can you look into this and add this as enhancement ?
Thanks.

I don't have this plan for the time being, you can try it yourself. @deimsdeutsch


Enable Supermicro deployments and heterogeneous deployments

Signed-off-by: Sai Sindhur Malleni<EMAIL_ADDRESS>Description
Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.
Fixes # (issue)
Type of change
Please select the appropiate options:

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

Testing
Please describe the tests that you ran to verify your changes. Provide instructions so we can reproduce. Please also list any relevant details for your test configuration

[ ] Test A
[ ] Test B

Test Configuration:

Versions:
Hardware:

Checklist

[ ] I have performed a self-review of my own code
[ ] If a change is adding a feature, it should require a change to the README.md and the review should catch this.
[ ] If the change is a fix, it should have an issue. The review should make sure the comments state the issue (not just the number) and it should use the keywords that will close the issue on merge.
[ ] A change should not being merged unless it passes CI or there is a comment/update saying what testing was passed.
[ ] PRs should not be merged unless positively reviewed.

This does not include changes for the scale up roles. @mukrishn maybe you can add them as a follow up commit.


[Bug] Very large requisitions lock and unuse the application

Hello,
Requests that are more than 10 mb will stop the application and virtually disable it. I have a service that returns a large volume of data, and since I made the first call, the application hangs and keeps asking me to reboot, now I can not use it anymore. I've already removed and reinstalled the software, but it did not work. I imagine that as soon as it opens the application, it redoes the last request. I'm in the last version.

Could you take a look?
I really like the software, I would not want to stop using it.

Hi @andreworks,
For a temporary fix to this, you can delete Insomnia/insomnia.Response.db from the following location.

%APPDATA% on Windows
$XDG_CONFIG_HOME or ~/.config on Linux
~/Library/Application Support on macOS

This will clear out all response data for the app. I plan on adding improvements for large file handling soon to help prevent this issue in the future.

Hello @gschier ,
Thank you very much! I deleted the file and it worked again.
Cool, I'll be waiting. Congratulations on the work, great app!


Only remove a Rust compiler after downloading it succeeds

This is based on my whitespace branch (see pull request #92). This just modifies the script so that the rm -rf command executes after a successful download.
Works For Me™ when testing on macOS (with a pruned install_compilers.sh). Fixes mattgodbolt/compiler-explorer#997.

Rebased against master now that #92 has been merged.


[on branch viewerQt] -init-centerline viewer doesn't save and proceed with segmentation

Prerequisites
On branch viewerQt
Description
When using  -init-centerline viewer, the "save & quit" button doesn't seem to work. When clicking, nothing is happening, the window stays open and the segmentation is stuck.
Steps to Reproduce
Command used:
sct_propseg -i t1.nii.gz -c t1 -init-centerline viewer
Data:
sct_example_data/t1
State of spinalcordtoolbox
$ sct_propseg -i t1.nii.gz -c t1 -init-centerline viewer

--
Spinal Cord Toolbox (viewerQt/06fcfe0bf91ddec1ecfc651334602be95ac082cc)
Running /Users/saradupont/Neuropoly/code/spinalcordtoolbox/scripts/sct_propseg.py -i t1.nii.gz -c t1 -init-centerline viewer

...

Additional Information

Fixed in the new viewer


Production build fails if compatibilityVersion: 4 is enabled

Example of nuxt.config.ts
export default defineNuxtConfig({
  modules: ['nuxt-multi-cache'],
  multiCache: {
    route: { enabled: true },
  },
  future: {
    compatibilityVersion: 4
  }
})

package.json
{
  "name": "nuxt-app",
  "private": true,
  "type": "module",
  "scripts": {
    "build": "nuxt build",
    "dev": "nuxt dev",
    "generate": "nuxt generate",
    "preview": "nuxt preview",
    "typecheck": "nuxt typecheck",
    "postinstall": "nuxt prepare"
  },
  "dependencies": {
    "nuxt": "^3.13.1",
    "nuxt-multi-cache": "^3.3.3"
  }
}

after npm run build
causes error to show up:
<snip>
✔ Server built in 354ms                                                                                7:22:38 PM
✔ Generated public .output/public                                                                                nitro 7:22:38 PM
ℹ Building Nuxt Nitro server (preset: node-server)                                                                                nitro 7:22:38 PM
[plugin inject] node_modules/.cache/nuxt/.nuxt/multiCache.serverOptions.ts: rollup-plugin-inject: failed to parse /Users/anatolii/git/playbround/nuxt-app/node_modules/.cache/nuxt/.nuxt/multiCache.serverOptions.ts. Consider restricting the plugin to particular files via options.include

[nitro 7:22:38 PM]  ERROR  RollupError: node_modules/.cache/nuxt/.nuxt/multiCache.serverOptions.ts (2:12): Expected ',', got '{' (Note that you need plugins to import files that are not JavaScript)

1:
2: import type { MultiCacheServerOptions } from '../../../nuxt-multi-cache/dist/runtime/types.ts'
               ^
3: const serverOptions: MultiCacheServerOptions = {}

[7:22:38 PM]  ERROR  node_modules/.cache/nuxt/.nuxt/multiCache.serverOptions.ts (2:12): Expected ',', got '{' (Note that you need plugins to import files that are not JavaScript)

  at getRollupError (node_modules/rollup/dist/es/shared/parseAst.js:392:41)
  at ParseError.initialise (node_modules/rollup/dist/es/shared/node-entry.js:11485:28)
  at convertNode (node_modules/rollup/dist/es/shared/node-entry.js:13181:10)
  at convertProgram (node_modules/rollup/dist/es/shared/node-entry.js:12525:12)
  at Module.setSource (node_modules/rollup/dist/es/shared/node-entry.js:14346:24)
  at async ModuleLoader.addModuleSource (node_modules/rollup/dist/es/shared/node-entry.js:19003:13)

[7:22:38 PM]  ERROR  node_modules/.cache/nuxt/.nuxt/multiCache.serverOptions.ts (2:12): Expected ',', got '{' (Note that you need plugins to import files that are not JavaScript)

It's started to happen in 3.3.0 and working fine in 3.2.0

Short update: I had opened an issue in the Nuxt repository because I was under the impression that it's a bug in Nuxt. However I will now try to find a workaround here to make it work when setting compatibilityVersion: 4.

The upcoming release (3.4.0) will add support for using the module with compatibilityVersion: 4. If a server options file is used, it can still remain in <rootDir>/app/multiCache.serverOptions.ts, however, putting it in <rootDir>/multiCache.serverOptions.ts also works and will become the new default.

@dulnan  Thank you!


🐛 [flutter_in_app_messaging] adding this package causing crash

when i decide to add this package to my flutter project after adding it to pubspec , I build the app and it started to crash.
then I removed it from pubspec and app worked without any crashes.
I used this version:
firebase_in_app_messaging: ^0.6.0+7
Flutter doctor
Click To Expand
[✓] Flutter (Channel stable, 2.10.2, on macOS 12.2.1 21D62 darwin-x64, locale en-US)
[✓] Android toolchain - develop for Android devices (Android SDK version 32.0.0)
[✓] Xcode - develop for iOS and macOS (Xcode 13.2.1)
[✓] Chrome - develop for the web
[✓] Android Studio (version 2021.1)
[✓] VS Code (version 1.62.3)
[✓] Connected device (2 available)
[✓] HTTP Host Availability

Flutter dependencies
Click To Expand
dependencies:
- android_path_provider 0.3.0 [flutter]
- carrier_info 2.0.4 [flutter]
- connectivity_plus 2.2.0 [flutter connectivity_plus_platform_interface connectivity_plus_linux connectivity_plus_macos connectivity_plus_web connectivity_plus_windows]
- cupertino_icons 1.0.4
- device_info_plus 3.2.2 [flutter device_info_plus_platform_interface device_info_plus_macos device_info_plus_linux device_info_plus_web device_info_plus_windows]
- dio 4.0.4 [http_parser path]
- firebase_analytics 9.1.0 [firebase_analytics_platform_interface firebase_analytics_web firebase_core firebase_core_platform_interface flutter]
- firebase_core 1.12.0 [firebase_core_platform_interface firebase_core_web flutter meta]
- firebase_crashlytics 2.5.1 [firebase_core firebase_core_platform_interface firebase_crashlytics_platform_interface flutter stack_trace]
- firebase_in_app_messaging 0.6.0+7 [firebase_core firebase_core_platform_interface firebase_in_app_messaging_platform_interface flutter meta]
- firebase_messaging 11.2.6 [firebase_core firebase_core_platform_interface firebase_messaging_platform_interface firebase_messaging_web flutter meta]
- flutter 0.0.0 [characters collection material_color_utilities meta typed_data vector_math sky_engine]
- flutter_downloader 1.7.2 [flutter]
- flutter_inappwebview 5.3.2 [flutter]
- flutter_local_notifications 9.3.2 [clock flutter flutter_local_notifications_linux flutter_local_notifications_platform_interface timezone]
- flutter_styled_toast 2.0.0 [flutter flutter_localizations]
- flutter_svg 1.0.3 [flutter meta path_drawing vector_math xml]
- flutterfire_installations 0.1.0 [firebase_core firebase_core_platform_interface firebase_installations_platform_interface firebase_installations_web flutter]
- get 4.6.1 [flutter]
- oktoast 3.1.5 [flutter flutter_test]
- package_info_plus 1.3.0 [flutter package_info_plus_platform_interface package_info_plus_linux package_info_plus_macos package_info_plus_windows package_info_plus_web]
- path_provider 2.0.9 [flutter path_provider_android path_provider_ios path_provider_linux path_provider_macos path_provider_platform_interface path_provider_windows]
- permission_handler 8.3.0 [flutter meta permission_handler_platform_interface]
- rxdart 0.27.3
- url_launcher 6.0.20 [flutter url_launcher_android url_launcher_ios url_launcher_linux url_launcher_macos url_launcher_platform_interface url_launcher_web url_launcher_windows]

dev dependencies:
- flutter_lints 1.0.4 [lints]
- flutter_test 0.0.0 [flutter test_api path fake_async clock stack_trace vector_math async boolean_selector characters charcode collection matcher material_color_utilities meta source_span stream_channel string_scanner term_glyph typed_data]

transitive dependencies:
- args 2.3.0
- async 2.8.2 [collection meta]
- boolean_selector 2.1.0 [source_span string_scanner]
- characters 1.2.0
- charcode 1.3.1
- clock 1.1.0
- collection 1.15.0
- connectivity_plus_linux 1.2.0 [flutter connectivity_plus_platform_interface meta nm]
- connectivity_plus_macos 1.2.1 [connectivity_plus_platform_interface flutter]
- connectivity_plus_platform_interface 1.2.0 [flutter meta plugin_platform_interface]
- connectivity_plus_web 1.2.0 [connectivity_plus_platform_interface flutter_web_plugins flutter]
- connectivity_plus_windows 1.2.0 [connectivity_plus_platform_interface flutter]
- dbus 0.6.8 [args ffi meta xml]
- device_info_plus_linux 2.1.1 [device_info_plus_platform_interface file flutter meta]
- device_info_plus_macos 2.2.2 [device_info_plus_platform_interface flutter]
- device_info_plus_platform_interface 2.3.0+1 [flutter meta plugin_platform_interface]
- device_info_plus_web 2.1.0 [device_info_plus_platform_interface flutter_web_plugins flutter]
- device_info_plus_windows 2.1.1 [device_info_plus_platform_interface ffi flutter win32]
- fake_async 1.2.0 [clock collection]
- ffi 1.1.2
- file 6.1.2 [meta path]
- firebase_analytics_platform_interface 3.0.5 [firebase_core flutter meta plugin_platform_interface]
- firebase_analytics_web 0.4.0+6 [firebase_analytics_platform_interface firebase_core firebase_core_web flutter flutter_web_plugins js]
- firebase_core_platform_interface 4.2.4 [collection flutter meta plugin_platform_interface]
- firebase_core_web 1.5.4 [firebase_core_platform_interface flutter flutter_web_plugins js meta]
- firebase_crashlytics_platform_interface 3.1.13 [collection firebase_core flutter meta plugin_platform_interface]
- firebase_in_app_messaging_platform_interface 0.2.0+7 [firebase_core flutter meta plugin_platform_interface]
- firebase_installations_platform_interface 0.1.0 [firebase_core flutter meta plugin_platform_interface]
- firebase_installations_web 0.1.0 [firebase_installations_platform_interface firebase_core firebase_core_web flutter flutter_web_plugins js]
- firebase_messaging_platform_interface 3.1.6 [firebase_core flutter meta plugin_platform_interface]
- firebase_messaging_web 2.2.7 [firebase_core firebase_core_web firebase_messaging_platform_interface flutter flutter_web_plugins js meta]
- flutter_local_notifications_linux 0.4.1+1 [flutter flutter_local_notifications_platform_interface dbus path xdg_directories]
- flutter_local_notifications_platform_interface 5.0.0 [flutter plugin_platform_interface]
- flutter_localizations 0.0.0 [flutter intl characters clock collection material_color_utilities meta path typed_data vector_math]
- flutter_web_plugins 0.0.0 [flutter js characters collection material_color_utilities meta typed_data vector_math]
- http 0.13.4 [async http_parser meta path]
- http_parser 4.0.0 [charcode collection source_span string_scanner typed_data]
- intl 0.17.0 [clock path]
- js 0.6.3
- lints 1.0.1
- matcher 0.12.11 [stack_trace]
- material_color_utilities 0.1.3
- meta 1.7.0
- nm 0.4.3 [dbus]
- package_info_plus_linux 1.0.3 [package_info_plus_platform_interface flutter path]
- package_info_plus_macos 1.3.0 [flutter]
- package_info_plus_platform_interface 1.0.2 [flutter meta plugin_platform_interface]
- package_info_plus_web 1.0.4 [flutter flutter_web_plugins http meta package_info_plus_platform_interface]
- package_info_plus_windows 1.0.4 [package_info_plus_platform_interface ffi flutter win32]
- path 1.8.0
- path_drawing 1.0.0 [vector_math meta path_parsing flutter]
- path_parsing 1.0.0 [vector_math meta]
- path_provider_android 2.0.11 [flutter path_provider_platform_interface]
- path_provider_ios 2.0.7 [flutter path_provider_platform_interface]
- path_provider_linux 2.1.5 [ffi flutter path path_provider_platform_interface xdg_directories]
- path_provider_macos 2.0.5 [flutter path_provider_platform_interface]
- path_provider_platform_interface 2.0.1 [flutter meta platform plugin_platform_interface]
- path_provider_windows 2.0.5 [ffi flutter path path_provider_platform_interface win32]
- permission_handler_platform_interface 3.7.0 [flutter meta plugin_platform_interface]
- petitparser 4.4.0 [meta]
- platform 3.1.0
- plugin_platform_interface 2.0.2 [meta]
- process 4.2.4 [file path platform]
- sky_engine 0.0.99
- source_span 1.8.1 [collection path term_glyph]
- stack_trace 1.10.0 [path]
- stream_channel 2.1.0 [async]
- string_scanner 1.1.0 [charcode source_span]
- term_glyph 1.2.0
- test_api 0.4.8 [async boolean_selector collection meta source_span stack_trace stream_channel string_scanner term_glyph matcher]
- timezone 0.8.0 [path]
- typed_data 1.3.0 [collection]
- url_launcher_android 6.0.13 [flutter meta url_launcher_platform_interface]
- url_launcher_ios 6.0.13 [flutter meta url_launcher_platform_interface]
- url_launcher_linux 2.0.2 [flutter]
- url_launcher_macos 2.0.2 [flutter]
- url_launcher_platform_interface 2.0.4 [flutter plugin_platform_interface]
- url_launcher_web 2.0.5 [flutter flutter_web_plugins meta url_launcher_platform_interface]
- url_launcher_windows 2.0.2 [flutter]
- vector_math 2.1.1
- win32 2.3.1 [ffi]
- xdg_directories 0.2.0 [meta path process]
- xml 5.3.1 [collection meta petitparser]

@tahamv
I added the plugin to a sample app which compiled and built properly without any issues:

Launching lib/main.dart on iPhone 12 Pro Max in debug mode...
Running pod install...
Running Xcode build...
Xcode build done.                                           63.8s
Debug service listening on ws://<IP_ADDRESS>:53420/Y_cjfAemFxE=/ws
Syncing files to device iPhone 12 Pro Max...

I verified this on Channel master, 2.11.0-0.0.pre.650.

I build the app and it started to crash.

Can you provide error log that shows the crash ? Is this on Android or iOS ?

I test my app on physical android device at it crashed. I will send you the crash report.

error log
Fatal Exception: D3.h: java.lang.ExceptionInInitializerError
at io.reactivex.plugins.RxJavaPlugins.onError(RxJavaPlugins.java:2)
at io.reactivex.internal.schedulers.ScheduledRunnable.run(ScheduledRunnable.java:18)
at io.reactivex.internal.schedulers.ScheduledRunnable.call(ScheduledRunnable.java)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:301)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1167)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:641)
at java.lang.Thread.run(Thread.java:919)

@tahamv
Thanks for the log.
Fatal Exception: D3.h: java.lang.ExceptionInInitializerError indicates, there's some initialization error.
Can you check and confirm that you have declared all permissions properly in your manifest file and they are correctly declared ?
Maybe some of the permissions might be conflicting with in_app_messaging and hence the error.


Difference with Shoulder Surfing Reloaded

Hey :), I hope it's ok to ask here, I couldn't find anywhere else to ask (nod discord server or anything else)😅. I was wondering what the difference is between your mod and shoulder surfing reloaded as they seem like the same.
Btw thank you for creating this mod 🙏.

Hello,
If you are unsure about the differences, I would suggest you use Shoulder Surfing Reload, as it seems to have better compatibility and supports more Minecraft versions. I haven't been paying attention to its updates for a while, so I'm not very clear on the features of its latest version.