Access Token for InfluxDB

Dear all,
I am a bit confused about how to get the Access Token for the Enpal Integration. I managed to add the Rep and the Integration but I am really not sure where to get the Access Token from.
Beeing quite an Newbie with Homeassistant I will be thankful to push me in the right direction.
Many thanks in advance!
Chris

Hi,
You need to get the influxdb information out of the webinterface of the inverter (the Solar Rel. .... thingy). Open the ip up, go to Config and scroll down on the bottom until you get the influx:Token.

Many thanks,found it already!Mit freundlichen Grüßen Christopher @.: +49<PHONE_NUMBER>Festnetz: + 49 6182 9927178Fax: + 49 6182 9927179 Facebook: Just the Two of US - https://www.facebook.com/Just-the-Two-of-Us-252504752437418Am 06.09.2024 um 22:44 schrieb tankanickel @.>:
Hi,
You need to get the influxdb information out of the webinterface of the inverter (the Solar Rel. .... thingy). Open the ip up, go to Config and scroll down on the bottom until you get the influx:Token.
—Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you authored the thread.Message ID: @.***>
AntiVirus & Spam checked by Sophos Antivirus

Where can I find that?
I have this in my config:
{   "ModbusDevices": {     "0": {       "NodeAddress": "1"     },     "1": {       "NodeAddress": "1"     }   },   "MainState": "Operation",   "IotHubClient": {     "ConnectionString": "..."   },   "MqttSettings": {     "Username": "...",     "Password": "..."   },   "ModbusTcpInterfaceSetting": {     "0": {       "IpAddress": "<IP_ADDRESS>"     }   } }
But I can reach the influx db with <IP_ADDRESS>:8086
influxdb version 2.2.0

found it myself now.
Its not in the config itself its at the bottom of the page


Bug: runaway log on lid close/open

I've been having some issues with way-displays (1.11.0) and Hyprland (0.40.0).

 This is the log from hyprland when I do that:

 hyprland.log on restart of way-displays
[LOG] [OutputManagement] New OutputManager registered
[LOG] [OutputManagement]  | sending output head for eDP-1
[LOG] [OutputManagement]   | sending mode 1920x1080@60020mHz, pref: true
[LOG] [OutputManagement]   | sending mode 1920x1080@47997mHz, pref: false
[LOG] [OutputManagement]  | sending output head for DP-2
[LOG] [OutputManagement]   | sending mode 3440x1440@59999mHz, pref: true
<!---  more modes  ---!>
[LOG] [OutputManagement]   | sending mode 720x400@70082mHz, pref: false
[LOG] [OutputManagement]   | sending current mode for DP-2: 3440x1440@59999
[LOG] [OutputManagement] Creating new configuration
[LOG] [OutputManagement] enableHead on eDP-1. For now, doing nothing. Waiting for apply().
[LOG] [OutputManagement]  | configHead for eDP-1: set mode to 1920x1080@60020
[LOG] [OutputManagement] Applying configuration
[LOG] [OutputManagement] Applying config for monitor eDP-1
[LOG] [OutputManagement] Applied configuration
[LOG] [OutputManagement] Creating new configuration
[LOG] [OutputManagement] enableHead on DP-2. For now, doing nothing. Waiting for apply().
[LOG] [OutputManagement]  | configHead for DP-2: set adaptiveSync to 1
[LOG] [OutputManagement] Applying configuration
[LOG] [OutputManagement] Applying config for monitor DP-2
[LOG] [OutputManagement] Applied configuration
<!---  the following block is printed 52 times  ---!>
[LOG] [OutputManagement] Creating new configuration
[LOG] [OutputManagement] enableHead on eDP-1. For now, doing nothing. Waiting for apply().
[LOG] [OutputManagement]  | configHead for eDP-1: set scale to 1.25
[LOG] [OutputManagement]  | configHead for eDP-1: set pos to 0, 288
[LOG] [OutputManagement]  | configHead for eDP-1: set transform to 0
[LOG] [OutputManagement] Applying configuration
[LOG] [OutputManagement] Applying config for monitor eDP-1
[LOG] [OutputManagement] Applied configuration
<!---  end of block  ---!>
[LOG] Applying monitor rule for eDP-1
[LOG] Applying monitor rule for DP-2
[LOG] Setting preferred mode for DP-2
[LOG] output DP-2 succeeded basic test on format DRM_FORMAT_XRGB8888
[LOG] arrangeMonitors: 1 to arrange
[LOG] arrangeMonitors: DP-2 explicit [1536, 0]
[LOG] arrangeMonitors: DP-2 xwayland [0, 0]
[LOG] Monitor DP-2 data dump: res<EMAIL_ADDRESS>scale 1.00, transform 0, pos 1536x0, 10b 0
[LOG] [OutputManagement]   | sending current mode for DP-2: 3440x1440@59999
[wlr] [backend/drm/drm.c:875] connector DP-2: Failed to page-flip output: a page-flip is already pending
[LOG] [OutputManagement] Creating new configuration
[LOG] [OutputManagement] enableHead on eDP-1. For now, doing nothing. Waiting for apply().
[LOG] [OutputManagement]  | configHead for eDP-1: set scale to 1.25
[LOG] [OutputManagement]  | configHead for eDP-1: set pos to 0, 288
[LOG] [OutputManagement]  | configHead for eDP-1: set transform to 0
[LOG] [OutputManagement] Applying configuration
[LOG] [OutputManagement] Applying config for monitor eDP-1
[LOG] [OutputManagement] Applied configuration
[LOG] Applying monitor rule for eDP-1
[LOG] Applying monitor rule for DP-2
[LOG] Setting preferred mode for DP-2
[LOG] output DP-2 succeeded basic test on format DRM_FORMAT_XRGB8888
[LOG] arrangeMonitors: 1 to arrange
[LOG] arrangeMonitors: DP-2 explicit [1536, 0]
[LOG] arrangeMonitors: DP-2 xwayland [0, 0]
[LOG] Monitor DP-2 data dump: res<EMAIL_ADDRESS>scale 1.00, transform 0, pos 1536x0, 10b 0
[LOG] [OutputManagement]   | sending current mode for DP-2: 3440x1440@59999
[wlr] [backend/drm/drm.c:875] connector DP-2: Failed to page-flip output: a page-flip is already pending
<!--- this block prints another ~50 times, and so and so on  ---!>
[LOG] [OutputManagement] Creating new configuration
[LOG] [OutputManagement] enableHead on eDP-1. For now, doing nothing. Waiting for apply().

[LOG] Callback 341db18 -> 341db10,  removed.
[LOG] Registered signal for owner 341d500: 3415818 -> 341da20 (owner: )
[LOG] Registered signal for owner 341d500: 34158a8 -> 341da88 (owner: )
[LOG] Registered signal for owner 341d500: 3415898 -> 341daf0 (owner: )
[LOG] Registered signal for owner 341d500: 3415828 -> 341db58 (owner: )
[LOG] Registered signal for owner 341d500: 3415838 -> 341dbc0 (owner: )
[LOG] Registered signal for owner 341d500: 3415858 -> 341dc28 (owner: )
[LOG] Registered signal for owner 341d500: 3415878 -> 341dc90 (owner: )
[LOG] Added new monitor with name eDP-1 at [0, 288] with size [1920, 1080], pointer 3415770
[LOG] New monitor: WORKSPACEID 4, exists: 0
[LOG] moveWorkspaceToMonitor: Moving 1 to monitor 0
[LOG] moveWorkspaceToMonitor: Moving 3 to monitor 0
[LOG] Monitor eDP-1 is disabled but is requested to be enabled
[LOG] Monitor eDP-1: requested<EMAIL_ADDRESS>found available mode: 1920x1080@60020mHz, applying.
[LOG] output eDP-1 succeeded basic test on format DRM_FORMAT_XRGB8888
[LOG] arrangeMonitors: 2 to arrange
[LOG] arrangeMonitors: DP-2 explicit [1536, 0]
[LOG] arrangeMonitors: eDP-1 explicit [0, 0]
[LOG] arrangeMonitors: DP-2 xwayland [0, 0]
[LOG] arrangeMonitors: eDP-1 xwayland [3440, 0]
[LOG] Monitor eDP-1 data dump: res<EMAIL_ADDRESS>scale 1.00, transform 0, pos 0x0, 10b 0
[LOG] [OutputManagement]   | sending current mode for eDP-1: 1920x1080@60020
[LOG] Applying monitor rule for eDP-1
[LOG] Not applying a new rule to eDP-1 because it's already applied!
[LOG] Applying monitor rule for DP-2
[LOG] Setting preferred mode for DP-2
[LOG] output DP-2 succeeded basic test on format DRM_FORMAT_XRGB8888
[LOG] arrangeMonitors: 2 to arrange
[LOG] arrangeMonitors: DP-2 explicit [1536, 0]
[LOG] arrangeMonitors: eDP-1 explicit [0, 0]
[LOG] arrangeMonitors: DP-2 xwayland [0, 0]
[LOG] arrangeMonitors: eDP-1 xwayland [3440, 0]
[LOG] Monitor DP-2 data dump: res<EMAIL_ADDRESS>scale 1.00, transform 0, pos 1536x0, 10b 0
[LOG] [OutputManagement]   | sending current mode for DP-2: 3440x1440@59999
[wlr] [backend/drm/drm.c:875] connector DP-2: Failed to page-flip output: a page-flip is already pending
[LOG] Registered signal for owner 6781020: 5c360c8 -> 6781028 (owner: CRenderbuffer)
[LOG] [OutputManagement] Creating new configuration
[LOG] [OutputManagement] enableHead on eDP-1. For now, doing nothing. Waiting for apply().
[LOG] [OutputManagement]  | configHead for eDP-1: set scale to 1.25
[LOG] [OutputManagement]  | configHead for eDP-1: set pos to 0, 288
[LOG] [OutputManagement]  | configHead for eDP-1: set transform to 0
[LOG] [OutputManagement] Applying configuration
[LOG] [OutputManagement] Applying config for monitor eDP-1
[LOG] [OutputManagement] Applied configuration
[LOG] Registered signal for owner 2f8a210: 3374378 -> 2f8a860 (owner: layerSurface)
[LOG] Registered signal for owner 2f8a210: 3f7dbf8 -> 2f8a728 (owner: layerSurface)
[LOG] Registered signal for owner 2f8a210: 3374388 -> 2f8a790 (owner: layerSurface)
[LOG] Registered signal for owner 2f8a210: 3374398 -> 2f8a7f8 (owner: layerSurface)
[LOG] Registered signal for owner 2f2c5f0: 3f7dc08 -> 2f2c7d0 (owner: CPopup Head)
[LOG] Registered signal for owner 2f8a4f0: 33743b8 -> 2f8a588 (owner: CWLSurface)
[LOG] Registered signal for owner 2f8a4f0: 3374378 -> 2f8a5f0 (owner: CWLSurface)
[LOG] CWLSurface 2f8a4f0 called init()
[LOG] LayerSurface 3f7db30 (namespace hyprpaper layer 0) created on monitor eDP-1
[LOG] Registered signal for owner 33740a0: 33743b8 -> 73fe200 (owner: FractionalScale)
[LOG] [OutputManagement] Creating new configuration
[LOG] [OutputManagement] enableHead on eDP-1. For now, doing nothing. Waiting for apply().
[LOG] [OutputManagement]  | configHead for eDP-1: set scale to 1.25
[LOG] [OutputManagement]  | configHead for eDP-1: set pos to 0, 288
[LOG] [OutputManagement]  | configHead for eDP-1: set transform to 0
[LOG] [OutputManagement] Applying configuration
[LOG] [OutputManagement] Applying config for monitor eDP-1
[LOG] [OutputManagement] Applied configuration
[LOG] Applying monitor rule for eDP-1
[LOG] Monitor eDP-1: requested<EMAIL_ADDRESS>found available mode: 1920x1080@60020mHz, applying.
[LOG] output eDP-1 succeeded basic test on format DRM_FORMAT_XRGB8888
[LOG] arrangeMonitors: 2 to arrange
[LOG] arrangeMonitors: DP-2 explicit [1536, 0]
[LOG] arrangeMonitors: eDP-1 explicit [0, 288]
[LOG] arrangeMonitors: DP-2 xwayland [0, 0]
[LOG] arrangeMonitors: eDP-1 xwayland [3440, 0]
[LOG] Monitor eDP-1 data dump: res<EMAIL_ADDRESS>scale 1.25, transform 0, pos 0x288, 10b 0
[LOG] [OutputManagement]   | sending current mode for eDP-1: 1920x1080@60020
[LOG] Applying monitor rule for DP-2
[LOG] Setting preferred mode for DP-2
[LOG] output DP-2 succeeded basic test on format DRM_FORMAT_XRGB8888
[LOG] arrangeMonitors: 2 to arrange
[LOG] arrangeMonitors: DP-2 explicit [1536, 0]
[LOG] arrangeMonitors: eDP-1 explicit [0, 288]
[LOG] arrangeMonitors: DP-2 xwayland [0, 0]
[LOG] arrangeMonitors: eDP-1 xwayland [3440, 0]
[LOG] Monitor DP-2 data dump: res<EMAIL_ADDRESS>scale 1.00, transform 0, pos 1536x0, 10b 0
[LOG] [OutputManagement]   | sending current mode for DP-2: 3440x1440@59999
[LOG] Registered signal for owner 620dbb0: 6963278 -> 620dbb8 (owner: CRenderbuffer)
[wlr] [backend/drm/drm.c:875] connector eDP-1: Failed to page-flip output: a page-flip is already pending
[LOG] [OutputManagement] Creating new configuration
[LOG] [OutputManagement] enableHead on eDP-1. For now, doing nothing. Waiting for apply().
[LOG] [OutputManagement]  | configHead for eDP-1: set scale to 1.25
[LOG] [OutputManagement]  | configHead for eDP-1: set pos to 0, 288
[LOG] [OutputManagement]  | configHead for eDP-1: set transform to 0
[LOG] [OutputManagement] Applying configuration
[LOG] [OutputManagement] Applying config for monitor eDP-1
[LOG] [OutputManagement] Applied configuration
[LOG] Applying monitor rule for eDP-1
[LOG] Not applying a new rule to eDP-1 because it's already applied!
[LOG] Applying monitor rule for DP-2
[LOG] Setting preferred mode for DP-2
[LOG] output DP-2 succeeded basic test on format DRM_FORMAT_XRGB8888
[LOG] arrangeMonitors: 2 to arrange
[LOG] arrangeMonitors: DP-2 explicit [1536, 0]
[LOG] arrangeMonitors: eDP-1 explicit [0, 288]
[LOG] arrangeMonitors: DP-2 xwayland [0, 0]
[LOG] arrangeMonitors: eDP-1 xwayland [3440, 0]
[LOG] Monitor DP-2 data dump: res<EMAIL_ADDRESS>scale 1.00, transform 0, pos 1536x0, 10b 0
[LOG] [OutputManagement]   | sending current mode for DP-2: 3440x1440@59999
[LOG] LayerSurface 3f7db30 mapped
[LOG] Registered signal for owner 2dd9fb0: 3f22b88 -> 2dda600 (owner: layerSurface)
[LOG] Registered signal for owner 2dd9fb0: 6c13f78 -> 2dda4c8 (owner: layerSurface)
[LOG] Registered signal for owner 2dd9fb0: 3f22b98 -> 2dda530 (owner: layerSurface)
[LOG] Registered signal for owner 2dd9fb0: 3f22ba8 -> 2dda598 (owner: layerSurface)
[LOG] Registered signal for owner 3172010: 6c13f88 -> 31721f0 (owner: CPopup Head)
[LOG] Registered signal for owner 2dda290: 3f22bc8 -> 2dda328 (owner: CWLSurface)
[LOG] Registered signal for owner 2dda290: 3f22b88 -> 2dda390 (owner: CWLSurface)
[LOG] CWLSurface 2dda290 called init()
[LOG] LayerSurface 6c13eb0 (namespace waybar layer 2) created on monitor eDP-1

I think it might happen in more situations, but I've only been able to reproduce it consistently by closing and reopening the lid.
This might be related to #167.

Thanks for the detailed information. I'll attempt a reproduction and get back to you.

Apologies, not sure why that closed, reopening.


Improve error wrapping

Right now I'm simply return erring everywhere. I'd like to do some better error wrapping so it's easier to tell where the error is coming from.

Since I'm going away for a week on vacation, I'm gonna keep the release only to what's absolutely necessary.


Set SplitView Constraints by absolute number

Currently it is only possible to set constraints based on fractional sizes of the overall view. Being able to set an absolute size would allow for minimum that can not shrink beyond a certain size requirement.

I agree this could be useful in some cases. At least in my case, though, it ends up being problematic because there are just too many device variations to account for, and fractions work reasonably well for them. It's probably pretty complicated to sort out, but if you come up with something and/or I can help, let me know.


Adding 8x8 (8x8.com)

Adds or updates the following companies, events, or universities:

Checklist
Company updates

[x] I have put the most recent relevant date in the "Last Update" column
[ ] I have linked to the article about the change, not the company's homepage (Please put N/A if there is no public post)

Event updates

[ ] I have linked to the article about the change, not the event's homepage

University updates

[ ] I have linked to the article about the change, not the university's homepage

Adding 8x8


bcbio runtime error

Hello!
I am using bcbio and have encountered an issue I would greatly appreciate any help with!
I executed the following command as a slurm job:
/n/data1/hms/dbmi/park/alon/software/bcbio/bin/bcbio_nextgen.py /n/data1/hms/dbmi/park/DATA/BSMCommonExperiment/ReferenceTissueProject/.Pipeline/PreProcessing/PreProcessing/config/PreProcessing.yaml -t ipython -n 256 -s slurm -q medium
After ~16hrs the job failed.
I am attaching the .log files as well as the .err files.
Thanks so much,
Alon
bcbio-nextgen-commands.log
bcbio-nextgen-debug.log
bcbio-nextgen.log
bcbio-ipcontroller.err.10051212_4294967294.txt
bcbio-ipengine.err.10051233_1.txt
bcbio-ipengine.err.10051233_2.txt
bcbio-ipengine.err.10051233_3.txt
bcbio-ipengine.err.10051233_4.txt
bcbio-ipengine.err.10051233_5.txt
bcbio-ipengine.err.10051233_6.txt
bcbio-ipengine.err.10051233_7.txt
bcbio-ipengine.err.10051233_8.txt
bcbio-ipengine.err.10051233_9.txt
bcbio-ipengine.err.10051233_10.txt
bcbio-ipengine.err.10051233_11.txt

Hi,
Is it possible your job timed out on the queue? Did you set a long enough walltime for initial slurm job?
Seeing there aren't really any errors in your debug log, I'm guessing that might be it.
Alternatively, could you also post the job outputs (stdout/stderr) from slurm? Those might contain more clues.
Cheers
M

+1 on it being timed out, it looks like the job was cancelled-- it could be because the job timed out, or it was manually cancelled.

I just checked and the default time is set to 24 hours for the medium queue, so I'm guessing that is what happened.

Ah! That makes a lot of sense. Thanks a ton Rory! Just added these parameters to my command and re-ran. No need to delete the files in work right? Will the pipeline will restart from where it failed? Thanks again,
Alon

Hi Alon,
Yup, bcbio does the output for every command transactionally, so it only moves the file to its correct place for each step if that step completes properly. So you should be able to restart and it will pick off at the last step it finished and skip ones where the expected file is already there.

amazing. thanks a ton rory!

Sweet, let us know if you run into any other issues.


Updated xmltojson.xml to fix the deployment issue

Updated the policy xmltojson.xml to fix the deployment issue. Here is the error description:
Import failed to /v1/organizations/arch123/apis?action=import&name=xmltojson with status 400:
{
"code" : "steps.xml2json.EitherOptionOrFormat",
"message" : "XMLToJSON[{0}]: Either Options or Format must be specified",
"contexts" : [ ]
}

This was fixed.


Signify (Hue) LTA001 alias 4080130P6 and 4300631P6

Redo of #1476, but individually.

4080130P6 seem to be a Hue Wellness
https://www.philips-hue.com/nl-nl/p/hue-white-ambiance-wellness-tafellamp/8719514341418
https://www.dmlights.com/philips_hue_wellness_white_ambiance_table_lamp__dimmer_incl___black~1AE7J
4300631P6 seem to be a Hue devote.
https://www.philips-hue.com/nl-nl/p/hue-white-ambiance-devote-hanglamp/8719514341234
https://www.dmlights.nl/philips_hue_devote_hanglamp_wit~1AE7N
They probably use the LTA001 light in the fixture, so the power consumption would be the same.
Instead of an alias a better fit to me seem to be to use the linked_lut option.
That will create a separate entry in supported models listing, and people can more easily find their light by searching for the marketed name. See LCA007 for an example.

Superseded by #1558


Fix all the warnings on VS code/ Console

When running npm start for running the react server from Vs code/ Console these errors are getting displayed.
In this, these warnings will be fixed -

I want to work on this issue under JWOC


dgemv_tester hangs without completion

The test program dgemv_tester hangs without completion waiting for threads to finish. Ultimately it needs Ctrl-C.
make[1]: Entering directory '.../OpenBLAS/cpp_thread_test'
g++ -O2 -Wall -Wextra -Wshadow -fopenmp -std=c++11 dgemv_thread_safety.cpp ../libopenblas_zenp-r0.3.20.a -lm -lpthread -lgfortran -lm -lpthread -lgfortran -L/usr/lib/gcc/x86_64-pc-linux-gnu/12.1.0 -L/usr/lib/gcc/x86_64-pc-linux-gnu/12.1.0/../../../../lib -L/lib/../lib -L/usr/lib/../lib -L/usr/lib/gcc/x86_64-pc-linux-gnu/12.1.0/../../..  -lgfortran -lm -lgomp -lquadmath -lm -lpthread -lc  -o dgemv_tester
./dgemv_tester
*----------------------------*
| DGEMV thread safety tester |
*----------------------------*
Size of random matrices and vectors(N=M): 1024
Number of concurrent calls into OpenBLAS : 12
Number of testing rounds : 16
This test will need 96.1875 MiB of RAM

Initializing random number generator...done
Preparing to test CBLAS DGEMV thread safety
Allocating matrices...done
Allocating vectors...done
Filling matrices with random numbers...done
Filling vectors with random numbers...done
Testing CBLAS DGEMV thread safety
DGEMV round #0
Launching 12 threads simultaneously using OpenMP...done
Waiting for threads to finish...

This was found on 5e9a91259158aaccb70343f398df7394f12c6222 but the behavior may be older.
The full build command was:
make -j6 all FC=gfortran USE_OPENMP=1 USE_THREAD=1 USE_TLS=0 NO_LAPACK=0 BUILD_LAPACK_DEPRECATED=1 NO_STATIC=1 BUILD_RELAPACK=0 CPP_THREAD_SAFETY_TEST=1 CONSISTENT_FPCSR=0

but this minimal command is enough to reproduce the hang:
make -j6 all USE_OPENMP=1 CPP_THREAD_SAFETY_TEST=1

What is your hardware and operating system, please ?

x86_64. Zen 2, 6 core, 12 thread. Running Linux kernel 5.10.117

Please check in debuger:
$ script
$ gdb
> attach PID
> t a a bt
> detach
> quit
$ exit

you can anonymize paths in typescript file , rename it to whatever.txt and attach here (or copy/paste if it is one screen sized)

What's your gcc (and gfortran) version ? 6core/12thread Zen2 is one of my regular test platforms and I cannot reproduce the problem there with either gcc 12.1 or 7.5

My gcc and gfortran are both 12.1.0. Output of gcc -v:
$ gcc -v
Using built-in specs.
COLLECT_GCC=gcc
COLLECT_LTO_WRAPPER=/usr/lib/gcc/x86_64-pc-linux-gnu/12.1.0/lto-wrapper
Target: x86_64-pc-linux-gnu
Configured with: /build/gcc/src/gcc/configure --enable-languages=c,c++,ada,fortran,go,lto,objc,obj-c++ --enable-bootstrap --prefix=/usr --libdir=/usr/lib --libexecdir=/usr/lib --mandir=/usr/share/man --infodir=/usr/share/info --with-bugurl=https://bugs.archlinux.org/ --with-linker-hash-style=gnu --with-system-zlib --enable-__cxa_atexit --enable-cet=auto --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-default-ssp --enable-gnu-indirect-function --enable-gnu-unique-object --enable-linker-build-id --enable-lto --enable-multilib --enable-plugin --enable-shared --enable-threads=posix --disable-libssp --disable-libstdcxx-pch --disable-werror --with-build-config=bootstrap-lto --enable-link-serialization=1
Thread model: posix
Supported LTO compression algorithms: zlib zstd
gcc version 12.1.0 (GCC)

To build the dgemv_tester file standalone, I replicated the following command from Makefile:
g++ -O2 -Wall -Wextra -Wshadow -fopenmp -std=c++11 dgemv_thread_safety.cpp ../libopenblas_zenp-r0.3.20.a -lm -lpthread -lgfortran -lm -lpthread -lgfortran -L/usr/lib/gcc/x86_64-pc-linux-gnu/12.1.0 -L/usr/lib/gcc/x86_64-pc-linux-gnu/12.1.0/../../../../lib -L/lib/../lib -L/usr/lib/../lib -L/usr/lib/gcc/x86_64-pc-linux-gnu/12.1.0/../../..  -lgfortran -lm -lgomp -lquadmath -lm -lpthread -lc  -o dgemv_tester

I can confirm that CFLAGS, CXXFLAGS, FFLAGS, OMP_NUM_THREADS etc are all absent as environmental variables, so they are not causing interference.

i asked for a backtrace from deadlocked moment of already running process, reaction to ^C is adequate.
seems you dug up a problem in other place.


K8SPS-20 improve the primary selection logic

Test name
Status

commit: https://github.com/percona/percona-server-mysql-operator/pull/19/commits/5ae1178227d8b417ab7f27769a7d128c29bb4209
image: perconalab/percona-server-mysql-operator:PR-19-5ae1178


Task 'migrateToRefreshVersionsDependenciesConstants' not found in root project 'xxx_Android'.

Hello, I’m a newbie to Android, and I saw your articles and libraries while doing gradle optimization.
When I follow the tutorial instructions to integrate, it always prompts the following error:
✘ heliquan@Mac  ~/CodePro/AndroidStudioPro/xxx_Android   master ●✚  ./gradlew migrateToRefreshVersionsDependenciesConstants --console=plain

FAILURE: Build failed with an exception.

* What went wrong:
Task'migrateToRefreshVersionsDependenciesConstants' not found in root project'FingerAdvisor_Android'.

* Try:
Run gradlew tasks to get a list of available tasks. Run with --stacktrace option to get the stack trace. Run with --info or --debug option to get more log output. Run with --scan to get full insights.

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

Sorry, I don’t know what caused this error.
Explain my steps. First, my project contains multiple modules (app, helper, weight...):

Create a settings.gradle.kts file in the root directory and copy the following code:

// settings.gradle.kts
import de.fayard.refreshVersions.bootstrapRefreshVersionsForBuildSrc

// Here you might have some pluginManagement block:
pluginManagement {
    //...
}

buildscript {
    repositories {gradlePluginPortal()}
    dependencies.classpath("de.fayard.refreshVersions:refreshVersions:0.9.5")
}

bootstrapRefreshVersionsForBuildSrc()

Then execute the following command in the Terminal of Android Studio:

./gradlew migrateToRefreshVersionsDependenciesConstants --console=plain

Finally came out this error exception.
Hope to get your guidance~

Hi @HLQ-Struggle, why do you use the buildSrc specific bootstrap for the root project?

Hi @LouisCAD ,because my Android project is currently modularized and third-party dependencies are referenced in every module, it is troublesome to manage.
The direct buildSrc scheme was originally adopted, but this scheme cannot update the reference version.

@HLQ-Struggle Okay, so this is a mistake. The buildSrc bootstrap is if you need to use refreshVersions for the dependencies of the buildSrc itself. In all cases, you need to use the regular bootstrap for the root project, so go check out the doc again 🙂 .
I'm assuming this is the issue you're encountering and that the solution I gave you will do. If you are still blocked, feel free to comment here or open another issue.

@LouisCAD ,regarding what you said "The buildSrc bootstrap is if you need to use refreshVersions for the dependencies of the buildSrc itself." I did add the corresponding dependencies in the root directory.
I read your document, but didn't find out what I should do better.
Hope to get your help, thank you~ 😭

@HLQ-Struggle You need to read the setting up guide very carefully.
You can also take a look at the existing sample-multi-modules or at the unreleased sample-android and see how their configuration differs from your project (minus the hack we have to sync the version on a text file).

@LouisCAD ,Okay, now I will continue to look at the usage documentation. thank you very much

@HLQ-Struggle You need to read the setting up guide before the usage documentation.
In the snippet you posted, you had bootstrapRefreshVersionsForBuildSrc() but you need to replace it with bootstrapRefreshVersions(), as shown in the "Bootstrap in root project" section

@LouisCAD Re-read the reference instructions you provided.
First of all, my Android project is currently divided into app, helper, weight and other modules, and then I create settings.build.kts, because the language of my project is Kotlin.

// settings.gradle.kts
import de.fayard.refreshVersions.bootstrapRefreshVersions

// Here you might have some pluginManagement block:
pluginManagement {
    //...
}

buildscript {
    repositories { gradlePluginPortal() }
    dependencies.classpath("de.fayard.refreshVersions:refreshVersions:0.9.5")
}

bootstrapRefreshVersions()

Then synchronize it and execute the following command:
./gradlew migrateToRefreshVersionsDependenciesConstants --console=plain
The result is still the following exception:
➜  xxx_Android git:(master) ✗ ./gradlew migrateToRefreshVersionsDependenciesConstants --console=plain
Starting a Gradle Daemon, 2 incompatible Daemons could not be reused, use --status for details

FAILURE: Build failed with an exception.

* What went wrong:
Task 'migrateToRefreshVersionsDependenciesConstants' not found in root project 'xxx_Android'.

* Try:
Run gradlew tasks to get a list of available tasks. Run with --stacktrace option to get the stack trace. Run with --info or --debug option to get more log output. Run with --scan to get full insights.

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

BUILD FAILED in 6s
➜  xxx_Android git:(master) ✗

I read the reading guide repeatedly, but I still don't know where I have a problem. 😭

@HLQ-Struggle You have both a settings.gradle.kts and a settings.gradle.
Pick one, use the correct bootstrap for the corresponding DSL language (Kotlin or Groovy), remove the other one, and voilà.

My steps are as follows:
Step 1: Upgrade gradle to 6.4.1
./gradlew wrapper --gradle-version 6.4.1
Step 2: Add plugins to settings.gradle
rootProject.name='FingerAdvisor_Android'
include':app'
include':helper'
include':weight'

// settings.gradle.kts
import de.fayard.refreshVersions.RefreshVersionsSetup

// Here you might have some pluginManagement block:
pluginManagement {
     //...
}

buildscript {
     repositories {gradlePluginPortal()}
     dependencies.classpath("de.fayard.refreshVersions:refreshVersions:0.9.5")
}

RefreshVersionsSetup.bootstrap(settings)

But the following exception is prompted:

Excuse me, where is my operation error? 😭😭😭

@HLQ-Struggle Please, don't copy paste all blindly and try to understand what you are doing.
The pluginManagement block is not needed as you can understand from the comment above:
// Here you might have some pluginManagement block:
pluginManagement {
     //...
}

Regardless of this oversight, you could just have read the error message that tells you the order of things is wrong.
Note that after removing that pluginManagement block, you'll also need to put the bootstrap above your existing code (includes, root project name…). Just like in the samples actually.

@LouisCAD When I execute the following command:
./gradlew migrateToRefreshVersionsDependenciesConstants --console=plain
The prompt is as follows error:
➜  xxx_Android git:(master) ✗ ./gradlew migrateToRefreshVersionsDependenciesConstants --console=plain

> Task :migrateToRefreshVersionsDependenciesConstants
All the following modules have hardcoded dependencies versions

1. :app (24)
2. :helper (10)
3. :weight (9)
4. Exit

Type the number of the Gradle module you want to migrate first:
weight

> Task :migrateToRefreshVersionsDependenciesConstants FAILED
--> GET https://plugins.gradle.org/m2/de/fayard/refreshVersions/refreshVersions/maven-metadata.xml
<-- 200 OK https://plugins.gradle.org/m2/de/fayard/refreshVersions/refreshVersions/maven-metadata.xml (1091ms, unknown-length body)

> Task :refreshVersions
Found 59 hardcoded dependencies versions.

[com.android.tools.build:gradle:4.0.1, org.jetbrains.kotlin:kotlin-gradle-plugin:1.3.71, com.android.tools.build:aapt2:4.0.1-6197926]...

To ensure single source of truth, refreshVersions only works with version placeholders,
that is the explicit way of marking the version is not there (but in the versions.properties file).

If you intentionally want to keep hardcoded versions so a module has a different version of a
dependency than the rest of the project, you can safely ignore this warning for these artifacts,
but keep in mind refreshVersions will not show available updates for these.

Note that a migration task is planned in a future version of refreshVersions.

See https://github.com/jmfayard/refreshVersions/issues/160

FAILURE: Build failed with an exception.

* What went wrong:
Execution failed for task ':migrateToRefreshVersionsDependenciesConstants'.
> java.util.InputMismatchException (no error message)

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

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

BUILD FAILED in 16s
2 actionable tasks: 2 executed
➜  FingerAdvisor_Android git:(master) ✗

At the same time, I checked according to the suggested issues, but no solution was found. How should I do this? Thank you

I'll not read the instructions for you. Please be considerate of our time and figure it out, all the info is there.


[test] Add GREASY test

Introduce the GREASY test.
In order to run it properly on the GPU partition, as described in the documentation, one needs to add an additional constraint to the job script
#SBATCH --gres=gpu:0,craynetwork:4

This required me to change the settings.py file

Hello @victorusu, Thank you for submitting the Pull Request!

In the file cscs-checks/apps/greasy/greasy_check.py:

Line 74:80: E501 line too long (80 > 79 characters)
Line 102:80: E501 line too long (80 > 79 characters)
Line 166:47: E126 continuation line over-indented for hanging indent
Line 176:29: E127 continuation line over-indented for visual indent
Line 178:29: E127 continuation line over-indented for visual indent
Line 184:49: E127 continuation line over-indented for visual indent
Line 187:29: E127 continuation line over-indented for visual indent
Line 189:29: E127 continuation line over-indented for visual indent
Line 194:42: E128 continuation line under-indented for visual indent
Line 216:17: E124 closing bracket does not match visual indentation

Do see the ReFrame Coding Style Guide

@victorusu I'm scheduling this for the next sprint.

@victorusu The test failed in performance during the CI on Daint. Should we reconsider the reference?

@jenkins-cscs retry none


Fix package installation modal loading state

Previously, when a CLI-only package was selected in the package page, selecting a regular package would result in the CLI-only warning appearing until the new modal content loaded in. This was due to a combination of the CosmosStore holding state based on the UI, and the isLoading state in the modal not properly being reflected. See this moving picture for the bug in action.

Looks good! Nice one ✨  💯

run integration tests

Works perfectly! I'd be happy to merge of the tests would finish successfully :)

run integration tests


Using press(13) will incorrectly prompt the auto update setting page in Canary

Example:
        .click('#search-button')
        .type('funny', 'input#search-input')
        .press(13)

The expected behaviour is to redirect to a search page since I try to trigger an enter event in the input box. However, a new tab is opened instead.

If you're using .press(13) after typing a field did you made sure to maintain .focus?
Just an idea, I personally haven't ran into that issue.

I had to solve that issue by using .type('\r') instead

https://github.com/sojungko
@sojungko Thanks. Using .type('\r') does work, but I guess it is only a workaround. So I will keep the issue open.

Any updates on this? I can replicate this on 1.3.0 for every keystroke, not just for 13.

Has anyone found a fix for this? I'm still getting this with every key, not just enter!


Info

Hi Zjcv, i sent you a couple week ago email to<EMAIL_ADDRESS>let me know if you read it cause i didnt receve any reply

Hi Zjcv, i sent you a couple week ago email to<EMAIL_ADDRESS>let me know if you read it cause i didnt receve any reply

hi @bbday , I just checked my email and didn't have any related email. You can send it to me again

sent, thanks for your reply


Fix documentation regarding the GPU/CUDA map_location value

The map_location value is used to determine the device on which GLiNER is run. This is done using torch.device, which supports cuda for running it on the GPU. The value gpu is not supported as shown in the following RuntimeError:
RuntimeError: Expected one of cpu, cuda, ipu, xpu, mkldnn, opengl, opencl, ideep, hip, ve, fpga, ort, xla, lazy, vulkan, mps, meta, hpu, mtia, privateuseone device type at start of device string: gpu

Ah, thanks for catching that! =)

Not a problem! I really like this project, so I am glad to contribute :)

I'm so happy to hear that!


Control validity of each global aggregation of cluster aggregation case

Fixes #1193

The intent of this PR is to provide support for the use of linear on cluster aggregations without explicit limits, which used to work in the past. So I would some tests for that case.
Regarding the explicit combination of global aggregation expressions with cluster aggregations, I don't think that it's very useful for visualizations, so we could avoid officially supporting that case. We could just mention that global aggregations should have a property as the input parameter, and that perhaps we could also document that the well-defined combinations (globalMin of clusterMin, globalMax of clusterMax, globalSum of clusterCount and globalSum of clusterSum) are allow and work, but that any other will produce an error or inaccurate results.

Hey, the broken test seems to have some race condition with exquisite or something, see https://github.com/CartoDB/carto-vl/pull/1197#issuecomment-449474438


无法正常启动青龙面板

Qinglong version
latest
Steps to reproduce
启动ql后，报错
{"code":7,"killed":false,"signal":null,"cmd":"curl -s --noproxy '*' http://<IP_ADDRESS>:5600/api/system","stdout":"","stderr":""}
What is expected?
正常启动
What is actually happening?
{"code":7,"killed":false,"signal":null,"cmd":"curl -s --noproxy '*' http://<IP_ADDRESS>:5600/api/system","stdout":"","stderr":""}
System Info
No response
Any additional comments?
No response

无法登录，打开后白屏，控制台错误见上图。


vue with typescript

If anyone interest how to play vue together with TypeScript. This is a good start: https://github.com/agentframework/webstack

closing


hang on bacause targets["num_boxes_replica"]=0

Hi, dear author, thanks for the excellent work!
When I try to train 3detr with 8 gpus. I found the training is hang on after some iterations.
Then I found that the reason is that targets["num_boxes_replica"]=0.
But I am curious that why it will become 0
Looking forward to your reply. Thanks.

I found the reasons.
Some images from SUNRGB-D have no objects.
So there are no box labels.

@yangcaoai how do you resolve this error?

@yangcaoai how do you resolve this error?

When encountering input data batch without labels, I skipped the loss computation in this way: https://github.com/yangcaoai/CoDA_NeurIPS2023/blob/main/criterion.py#L216


Upgrade game packages

Pulls in https://github.com/ppy/osu/pull/27729#event-12243877951,
importantly.

https://github.com/ppy/osu-queue-processor/pull/30


Updated package.json to change from git: to https:

Changed to https so those behind firewalls can install avrgirl without SSH access.
I work at a company that prohibits SSH access out of the network.  Since two of the dependencies had git: URLs instead of HTTPS, I was unable to install this at work.  I changed the package.json to use all https: URLs instead and it worked perfectly.
Thanks,

James

Coverage remained the same at 44.03% when pulling 0924a9a615fc8c0a24d5794dfce8dd9c0ef61eff on jbrown123:master into 6a4f583ad81e445d2e3978be1392d655d258dee3 on noopkat:master.

oh neat! Thanks, this is very helpful for a lot of folks I'm betting 💯


docs: Add deployment docs for automatic deployment

Description
Currently, all of the docs for deploying Dart Frog are for manual deployment to their systems. However, which my PR adding docs for Railway deployment, I wrote instructions for automatic deployment from Github because that seemed the most natural for that platform.
This got me wondering if we should have docs specifically for doing automatic deployment onto different services. I'm envisioning something simple to start, like Google Cloud Build -> Cloud Run, or maybe Github Actions to AWS?
Obviously it could be different for everyone's systems and we can't (and shouldn't) cover every possible case. However, I think a really simple start would be nice for people new to backend in general.
Additionally, maybe it would even be cool to add something like this GitHub workflow for auto-deploying from GitHub, either to Very Good Workflows or this repository. I can open a separate ticket for that if you're into the idea.
LMK you thoughts! :blue_h
Requirements

[ ] No functional changes to the code.
[ ] All CI/CD checks are passing.
[ ] There is no drop in the test coverage percentage.

Additional Context
No response

Also happy to jump on a call if we want to discuss where this could live.

I'm more than happy to contribute - I mainly opened this up for some guidance on where to add the docs. I'm thinking
L Deploy
  L Manual Deployment
  L Automatic Deployment
  L Platform Specific Guides
    L Cloud Run
    L AWS
    L ...ect

Any idea on what the Manual & Automatic deployment sections would have? Right now all the deploy docs are platform specific. Wondering if it's better to split the current docs into Manual and Automatic sections. Thoughts?

I realize we don't have a general doc on "this is how you build a project". I'm not even sure if dart_frog build is documented outside the platform specific ones. So my thought is that we'd have a doc explaining the basic concept of building and containerizing your application. Maybe instead of "Manual" it could just be "Building"?
As for automatic, originally I thought that it would be a good place for explaining how to auto-deploy in a general sense But, now that I think about it, it's basically the same as the manual deployment just in whatever spec your CI/CD supports. Maybe we could have a section on "Autodeploy with Github" or something like that? It would be GitHub specific but I think that's by far the most common platform. The actual deploy step varies by platform, but not by much so we could just tell them to fill in the blank.


Player get kicked with Network Protocol Error (1.21)

Client:

vanilla minecraft 1.21

Server:

minecraft 1.21
fabric loader 0.15.11
cloth-config 15.0.127
fabric-api 0.100.6+1.21
stitchedsnow 1.1.0

Logs:

disconnect-2024-07-10_23.46.08-client.txt (client)
latest.log (server)

Same

Client:

vanilla minecraft 1.21

Server:

minecraft 1.21
fabric loader 0.15.11
cloth-config 15.0.127
fabric-api 0.100.6+1.21
stitchedsnow 1.1.0

Logs:

disconnect-2024-07-10_23.46.08-client.txt (client)
latest.log (server)

Is that your IP in the log? because if so you might want to change that.

This is most likely the same issue as #15. Please try to reproduce using the latest release.


[Noncopyable] Teach existential generalization about invertible protocols

The generic signature formed by existential generalization didn't
account for invertible protocols, which caused an unintended change in
name mangling. Capture the appropriate inverted requirements as part
of generalization to restore the prior mangling, as well as correctly
accounting for invertible protocols in the generalized signature.

@swift-ci please smoke test


Roll Engine from df3aa14215fc to a4011246be2e (1 revision)

https://github.com/flutter/engine/compare/df3aa14215fc...a4011246be2e
2021-06-17<EMAIL_ADDRESS>Roll Skia from af8047dbb849 to fab6ede2ec1d (1 revision) (flutter/engine#26779)
If this roll has caused a breakage, revert this CL and stop the roller
using the controls here:
https://autoroll.skia.org/r/flutter-engine-flutter-autoroll
Please CC<EMAIL_ADDRESS>on the revert to ensure that a human
is aware of the problem.
To report a problem with the AutoRoller itself, please file a bug:
https://bugs.chromium.org/p/skia/issues/entry?template=Autoroller+Bug
Documentation for the AutoRoller is here:
https://skia.googlesource.com/buildbot/+doc/master/autoroll/README.md

Commit queue failed; closing this roll.


useSwrPages doesn't work with filters (dynamic URLs)

If you have a table with filters and your query depends on the filters, useSwrPages doesn't perform well and starts to duplicate results.
Here's the use case:
1 - Setup a useSwrPages to fetch from an api that returns the next offset number (skip in mongo terms) and "null" if it knows there are no more skips (end of data).
2 - Make your page's SWR depend on some filters that are added as a query string to the URL and add the filters to the dependencies.
3 - Load 3 or 4 pages without filters
4 - Apply filters (which will change the query string).
5 - Each SWR will fetch again with the filters and when there are not enough results, the offsetter function will return null (because API returned null). However, because there are 4 pages already, SWR will run them anyway with null as offset and retrieve the same set of results duplicated in the 4 pages.
Trying to pass null to the swr so that it doesn't fetch again won't work because "null" is the initial value of the offset and the page has no way of knowing if it's the first or not.
A way to overcome this is to not restrict us with null values or expose a method cleanup to remove all the pages. We can call cleanup after filters has changed to make useSwrPages restart from page 0.

I think I encountered the same problem: https://github.com/zeit/next.js/discussions/13093
Hope the fix will be merged soon )

I had a workaround which is to use key prop to force component with useSWRPages to unmount and remount with a new page key.

I tried this, but it doesn't work in my case. Do you mean this key?
...
useSWRPages(
    'this-key-pass-as-prop', // key of this page
    ({ offset, withSWR }) => {
...

...
useSWRPages(
    'this-key-pass-as-prop', // key of this page
    ({ offset, withSWR }) => {
...

I add key to SWRPages based on selected filters and key prop to the component. And now it rerenders without duplication. Thanks

The new pagination API has launched: https://swr.vercel.app/docs/pagination. Feel free to reopen if you are still encountering an issue!


np.swapaxis for y channel of optical flow

Thanks for this great project!
In temporal_train_data.py we have img2 = np.swapaxes(img2, 0, 1) for reasons which aren't clear to me. This seems to result in rotation of the y optical flow, but not x.
Is this intentional, and if so, why?

I have the same question as you, did you know why ?


[Android][Question] why android mDns resolve does't have interface name for Link Local Address?

Feature description
...
When use  Link Local Address ,socket need the output interface name,
so why android mDns resolve does't have interface name for Link Local Address?
Platform
android
Platform Version(s)
No response
Anything else?
No response

so ，anybody can give some advise；thinks。
i think this function relate to  this problem：link


Max total files with Rolling

I've tried pretty much everything I can think of, but can't seem to get this scenario to work. What I want to do is have a max total number of archive files, but also have rollover enabled. Preferably I'd also be able to control the max number of roll-over files per instance, but not required. I'm encoding the date into the log name each time it is run with ${longdate:cached=true} If I use Rolling as-is with the date encoded, it will keep a max of maxArchiveFiles in rollovers per instance, but will keep building up logs as I launch more instances. I want to control the total files in the folder, not the total per instance.
So for example, if I had the maxArchiveFiles set to 2, and let it roll over twice:
Log_2020-10-16 1048 (1).log
Log_2020-10-16 1048 (0).log
Log_2020-10-16 1048.log
And if I ran it again I'd like the older logs to roll off first, so after first start:
Log_2020-10-16 1048 (0).log
Log_2020-10-16 1048.log
Log_2020-10-16 1150.log
And if that instance then rolled over:
Log_2020-10-16 1048.log
Log_2020-10-16 1150 (0).log
Log_2020-10-16 1150.log
Hopefully this makes what I want to do clear, if not I can try and clarify. I'm fairly certain this isn't possible with the way the current archivers are set up, but want to confirm.

I'm guessing you are trying to use both dynamic and static archive-logic together. See also https://github.com/NLog/NLog/issues/3807#issuecomment-587661413 and https://github.com/NLog/NLog/issues/4105#issuecomment-685952654
If you followed the issue-template and posted the content of your current NLog.config, then we could probably give you advice on how to make it work.

I would of course have posted the XML config if I still had it, but I had since overwritten it several times in my attempt to get it to work. Let me try and retrace my steps and see if I can get a few examples of XML that didn't work as I wanted it to.

If you have no opinion on how to make it work, then I guess this will work just fine:
<target type="file" name="logfile" filename="Log_${longdate:cached=true}.log" maxArchiveFiles="2" />

I had tried that before but found it was picking up the last part of the date and using that as the base for the sequence numbering. However, that gave me the idea of wrapping it in some other character, and it seems that when it doesn't end in a dot with some number it acts like I want it to. I think this meets my requirements of needing to keep an indication of which instance the logs belong to, rolling over logs when they exceed a set size, and keeping the total number of logs produced below a certain threshold. Looks like I got close before, but was missing the wrapping character to prevent the sequencing from getting messed up.
So this is what I ended up with:
<target type="file" name="logfile" filename="Log_[${longdate:cached=true}].log" maxArchiveFiles="2" archiveAboveSize="1000000" />

Thanks for your expertise, it was able to point me in the right direction.

${longdate:cached=true} is probably not the best filename-generator, since it outputs a lot of characters that are not allowed in filenames. NLog is helpful and "fixes" the output, instead of failing with illegal filename.

Ah good to know. I'll switch over to the date with format string instead, since I don't really need precision past seconds anyway.


[Clickable phone number] Added Call center information for health related queries

Issue Reference
This PR addresses the Issue : Improvement over #775
Summarize
Added Call center information for health related queries.
The phone number has been made clickable, so the users can click on the phone numbers to directly make the call.

Also, mention the key points if any to look into while code reviews

Verified Looks good to me,

@biswaz , can we please merge this?

@saba83rish , should I close this PR?


Renaming SP2019 databases has wrong order with Links databases

Hi,
Step 5 for renaming SP2019 databases is wrong, because you have to resume Search SA before you can run this command:
Move-SPEnterpriseSearchLinksDatabases -SearchApplication $ssa -TargetStores @($newLinksStoreDB) -Confirm:$false.
If you run it before resuming Search SA, you get an error:
Move-SPEnterpriseSearchLinksDatabases : LinksStoresRefactoring: LinksStoreInput analysis is in state EnginePaused, but SSA is not paused for LinkDBRepartitioning. Make sure SSA is not already paused when moving LinkDBs.
At line:1 char:1

Move-SPEnterpriseSearchLinksDatabases -SearchApplication $ssa -Target ...

  + CategoryInfo          : InvalidData: (Microsoft.Offic...hLinksDatabases:MoveSearchLinksDatabases) [Move-SPEnterpriseSearchLinksDatabases], InvalidOperationException
  + FullyQualifiedErrorId : Microsoft.Office.Server.Search.Cmdlet.MoveSearchLinksDatabases

So correct order would be:
New-SPEnterpriseSearchLinksDatabase -DatabaseName <SearchServiceLinksDatabase> –SearchApplication $ssa -DatabaseServer <SearchServiceDatabaseServer>
$oldLinksStoreDB = ([array]($ssa | Get-SPEnterpriseSearchLinksDatabase))[0]
$newLinksStoreDB = ([array]($ssa | Get-SPEnterpriseSearchLinksDatabase))[1]
Resume-SPEnterpriseSearchServiceApplication -Identity $ssa
Move-SPEnterpriseSearchLinksDatabases -SearchApplication $ssa -TargetStores @($newLinksStoreDB) -Confirm:$false
Remove-SPEnterpriseSearchLinksDatabase -Identity $oldLinksStoreDB -SearchApplication $ssa -Confirm:$false

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

ID: 6d0c1428-d756-3353-887a-3e0b33319c68
Version Independent ID: 64436001-711f-a29f-15ff-02fcff2dae89
Content: Move or rename service application databases in SharePoint Server
Content Source: SharePoint/SharePointServer/administration/move-or-rename-service-application-databases.md
Product: sharepoint-server-itpro
GitHub Login: @MikePlumleyMSFT
Microsoft Alias: mikeplum

@Rob3r70  Thank you for submitting feedback and contributing to the docs. We are currently investigating this.

@Rob3r70 thank you for reaching out and helping improve MS Docs. Related link https://github.com/MicrosoftDocs/OfficeDocs-SharePoint/issues/1764

@Rob3r70 Thank you for submitting feedback. We understand that this issue has been resolved.
Please feel free to re-open this issue if there is a specific area of the docs that we can improve or make better. Thank you.


Bug: Single Collection marketplace listings not filtering correctly

Single collection marketplaces need to filter out by that collection


Clicking number doesn't work

Prerequisites

[X] I performed a cursory search of the issue tracker to avoid opening a duplicate issue
[X] This is not a question. -- otherwise use this template

Description of the bug
When clicking number it should open a issue
https://github.com/JohnyP36/Connect4/issues/new?title=connect4|drop|red|4&body=Just+push+'Submit+new+issue'+without+editing+the+title.+The+README+will+be+updated+after+approximately+30+seconds.
However it does not
Current behaviour
Ask to choose template
Expected behaviour
Should go te link/issue clicked
Screenshot(s)

Screenshot(s)

Does this work? https://github.com/JohnyP36/Connect4/commit/a07ae9f766404aff3d0f6a73863b12ef52ac9f15

Yes it does work!


Fix intermittent failures after docker run in common tests

When the server containers are started in common tests we wait a while before checking for node availability using an ered_client. If the Github CI is choked some containers might take longer time to start than our defined sleep.
Lets replace this fixed time with a common function that wait for a connection_up event from each node instead.
This should give faster initiations during normal times when Github CI is not choked.
Using a connect_timeout will also avoid failures when connecting to containers during startup.
Additionally in this PR; replace the ered_SUITE local function recv/2 with the common ?MSG macro.

Should we consider changing the default connect timeout to something shorter than infinity?

Having a shorter timeout would make sense to me, mostly since we have seen a couple of cases where the default is unexpected. At the same time, I guess the reason for infinity is to match the default in both gen_tcp and ssl, but I think we could change this in the future.


[BUG] Flaky Report IT tests

What is the bug?
A clear and concise description of the bug.
Possibly related to seg rep #719
How can one reproduce the bug?
Steps to reproduce the behavior:

Go to '...'
Click on '....'
Scroll down to '....'
See error

What is the expected behavior?
A clear and concise description of what you expected to happen.
What is your host/environment?

OS: [e.g. iOS]
Version [e.g. 22]
Plugins

Do you have any screenshots?
If applicable, add screenshots to help explain your problem.
Do you have any additional context?
Add any other context about the problem.

pending https://github.com/opensearch-project/reporting/pull/942

https://github.com/opensearch-project/reporting/pull/942 merged


Examples of operations for points, lines and polygons

understanding geometry relations can be bit un-intuitive as we tend to use language like overlaps , touches, within more loosely in common language than the precise definitions for geometry operations. For that reason it would be helpful if examples for each relation/operation could be provided for points, lines and polygons to help build intuition.

Agreed.  Should this go to the geocompjl book and we link / copy it?

This docs duplication is going to be an issue at some point... would be cool if we could make it all modular somehow

Given the importance of these concepts to GeometryOps I think examples should live in "https://juliageo.org/GeometryOps.jl/stable/source/methods/geom_relations/ ..." Simply expanding on the examples already provided would go a long way. This would show the concepts and how to use the tools within juliageo... any future contributions to a book or common reference source would be made easier.

Yeah, I think we need them here too. If you have time to write them...


Issue in the "Switch" control and "Number" control

Hi,
Issue description:
I was using 2.3.7 version on my theme. And I updated it to 3.0.16 because of the color controls were not working with WordPress 4.9. But the Swich doesn't seem to be styled properly. Please compare the two screenshots I have provided.

2.3.7 Version -

3.0.15 Version -

Version used:
I used the development branch and it did not work. Also I encountered that number control uses two plus minus buttons instead of up down arrows. And plus minus buttons also not working. They are not saving.
Using theme_mods or options?
I am using theme mods.
Thank You.

Fixed the number control issue. Buttons now work.
I can confirm the issue with the switch controls as well, but that's a minor CSS issue so nothing that will break anyone's site. It can wait for the next release since 3.0.16 has to go out later tonight to fix a couple of inconsistencies with WP 4.9

Moved this one to the 3.0.17 milestone, I'll examine the switches css after 3.0.16 is out.

Great..! Thank you.

Switches tested and they are displaying correctly in 3.0.43.


Update README.md

Tweaks to reflect recent website changes.

Adding cla: yes label, as the PR author is a googler at the time of this PR was created.


Add support for arbitrary local LLM access through LM Studio or similar

Assuming this is on your roadmap (maybe), but any chance we can connect to a locally hosted openai compatible API for any model that we can get to run?  I.e, through LM Studio local API server.

Done #5


Resolve metadata shortcodes in contributing.qmd

There are some warnings while rendering the contributing page.
WARNING (/Applications/quarto/share/filters/main.lua:15710) Unknown meta key book.repo-url specified in a metadata Shortcode.
WARNING (/Applications/quarto/share/filters/main.lua:15710) Unknown meta key book.issue-url specified in a metadata Shortcode.
WARNING (/Applications/quarto/share/filters/main.lua:15710) Unknown meta key book.issue-url specified in a metadata Shortcode.
WARNING (/Applications/quarto/share/filters/main.lua:15710) Unknown meta key book.repo-url specified in a metadata Shortcode.

These are a remnant of switching to the website layout in #19.

It looks like these fields only worked for book and not for website 🤷 (see also the discussion on the quarto forum).
I will add a variable file instead to address this.


Immunet false positive?

Hey Mathew,
I run Immunet AV and it recently flagged these files as malicious
Have a look please
bass.dll has been detected as W32.81A0BF6F64-97.SBX.VIOC
is-KDM3N.tmp has been detected as W32.81A0BF6F64-97.SBX.VIOC
Perhaps your sound library your using has been modded as I have used this software for a very long time and love it with the same AV and zero issues.

@jstillings1 Sorry for the late response.
I think it might be a false possitive. Try reporting it on Immunet AV website: http://www.immunet.com/false_positive

I found the root cause. Had an email marked Wells Fargo that used my email filter to land in my open me now folder. It installed Sality And efail and emotet . It was using GitHub auto update to distro to a ton of apps I use like visual studio light shot, anything that was auto updating it attached to. I installed webroot and it now says all ok
Get Outlook for Androidhttps://aka.ms/ghei36

From: Mathew Sachin<EMAIL_ADDRESS>Sent: Sunday, February 24, 2019 11:53:22 AM
To: MathewSachin/Captura
Cc: Jeremiah Stillings; Mention
Subject: Re: [MathewSachin/Captura] Immunet false positive? (#364)
@jstillings1https://github.com/jstillings1 Sorry for the late response.
I think it might be a false possitive. Try reporting it on Immunet AV website: http://www.immunet.com/false_positive
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHubhttps://github.com/MathewSachin/Captura/issues/364#issuecomment-466799375, or mute the threadhttps://github.com/notifications/unsubscribe-auth/Acl4hAW_E9xoyd0QzOcMIMYMAn3q7sTtks5vQtGSgaJpZM4adhEM.


SQLite error on recent activity query

The easiest way to reproduce this is to run the tests, since they use SQLite:
python -m pytest
Result: Several tests fail with "peewee.OperationalError: ORDER BY clause should come after UNION not before" at the last line of recent_activity in misc.py.

Disabled recent activity in 85b3bdd for now, since it won't be an easy fix


Update gh-pages 'master' docs with latest docs, and reorg TOC

I'll need to revise the first commit to capture the docs changes from #1432 when they're merged, but you can look at the second commit which has the updates to the TOC.  Here's a summary of what I changed:

Move “Getting started” from Introduction to Install, as “Quick start with in-cluster Mino”
Move “About locations” from Upgrade to Introduction
Move “Get the right Velero version” to the bottom of Introduction
Rename “Set up Velero” to “Overview” as first page under Install
Remove “Upgrade” section, put “Upgrade to 1.0” just under “Overview” in Install
Alphabetize AWS/Azure/GCP install pages
Remove “IBM Cloud Object Store” from Install section (the page is still linked from support-matrix.md)
Rename Tutorials section to Use, move to just under Install section

I think these changes help a lot in terms of organization and flow, and putting information where it belongs.  We can continue to build/revise from here.

Addressed open comments in latest commits


Investigate "brownout" recovery issues

Currently the video feeds seem to recover when the vehicle's 12V bus browns out, but the control software does not. A few things need to be looked into:

[ ] What causes the Pis to not recover?
[ ] What allows the video feeds to continue working?
[x] Where are the logs?

service eer status/systemctl status eer.service show partial output but journalctl -u eer.service shows literally nothing

@FifoIronton Have you started looking into new thethers? Hopefully with a second conductor this wont be as critical an issue.


Enforce undefined on target clone parameters

Expands on type checking introduced by #1534 by enforcing optional clone parameters.  This change did catch some forgotten parameters
Checklist

[-] I have added tests
[-] I have updated the docs and cheatsheet
[-] I have not broken the cheatsheet

looks like this code actually landed in #1961. No idea why this PR was still open 😅


Use Wagtail LTS release (2.11.*)

Resolves #46

@michaelclapham I'm planning to merge this PR into develop very soon, and once this is done everyone on the project will have to do all the project setup from scratch again (new venv, re-create db, etc) in order to continue work on the develop branch.
I'm aware that you are working on the demo video, so I wanted to give you a heads-up at the very least, and if you think this might impede you, I can hold off until a better time.


issue 187 refactoring expressions (adding pattern and replace enum)

https://github.com/art-community/ART/issues/187


Create a concat doc that listens to LSP events to modify itself

Replace the current notebook concat document with an implementation that can be shared with pylance.

This is essentially complete. Implementation resides here:
https://github.com/microsoft/vscode-jupyter-lsp-middleware/blob/88a75b1b17118604ba30c30f98fbf113b0f540a9/src/notebookConcatDocument.ts#L36
It will likely change as I fix bugs and such but should be portable now.

Verification steps:

Open a notebook
Verify semantic colorization happens
Verify hover works
Edit cells/Move cells/Delete cells
Verify diagnostics are as expected (as if the contents of all python cells were concatenated together)


Quickstart talks about sub claim, which doesn't exist

The second online quickstart Protecting an API using Passwords (which is generated from this file in the repository) contains the following text at the end of the page:

When you send the token to the identity API endpoint, you will notice one small but important difference compared to the client credentials grant. The access token will now contain a sub claim which uniquely identifies the user. This “sub” claim can be seen by examining the content variable after the call to the API and also will be displayed on the screen by the console application.
The presence (or absence) of the sub claim lets the API distinguish between calls on behalf of clients and calls on behalf of users.

This is not (or no longer) true. There is no sub claim showing the name (nor id) of the logged in user. There is a http://schemas.xmlsoap.org/ws/2005/05/identity/claims/nameidentifier claim which contains the id of the logged in user, and which changes correctly as one changes the username and password.
I've checked and the issue applies in the fully worked IdentityServer4.Samples solution (not just to my own attempt to implement things according to the quickstart guides).
Is there a way to get a sub claim to appear? Or has the name for this claim been renamed to the longer, schema-based name above? (In which case the docs need updating. I'd be happy to do a PR, but I'm not sure about some relevant issues. Are there other possible schemas? How come some claims are don't have schema-based names (e.g. aud, client_id) but some do?)

Thank you @MikeBeaton for raising this issue. I spent hours on this after seeing that the next QS showed a sub claim via the MVC client, but not through the API.
@brockallen all things considered, you've put together some great walk-throughs for a truly amazing service. I've gained a TON of knowledge from your documentation and talks on YouTube. A sincere kudos for your efforts!

Thank you for the QS, it's a great write-up. I also ran into this issue and took me a few to figure out why the sub claim type didn't exist (instead of the 'http://schemas.xmlsoap.org/ws/2005/05/identity/claims/nameidentifier' type).
I think if you add JwtSecurityTokenHandler.DefaultInboundClaimTypeMap.Clear(); right before the app.UseAuthentication() in the console app code on page 1 of the QS 1_client_credentials.rst, that would mitigate the issue for those following the QS. Otherwise, you'd have to explain that line on the bottom of page 2 of the QS.

@LindaLawton could you have a look

I don't think this (minor!) issue was ever changed in the docs?

I don't know - you can update the docs yourself if it hasn't been changed.


Using a parser on non-existent single file should raise an error

Currently all the parsers use Dir.glob(file) to retrieve the list of files to be processed.
It would be better to:

let the caller handle this instead, so that parser implementer doesn't have to remember it and the code stays DRY
raise an error if not at least one file matches

Nice to have - moving to backlog though.


read_csv with Ray engine doen't raise bad lines errors

System information

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 18.04
Modin version: ce2bea8867739ea792cdda0dce8ad50e366ebae1
Python version: 3.8.6
Code we can use to reproduce:

import os

os.environ["MODIN_ENGINE"] = "ray"

import pandas
import modin.pandas as pd

test_filename = "test.csv"
test_data = """col1,col2
one,two
0,1,2
"""

try:
    with open(test_filename, "w") as f:
        f.write(test_data)

    try:
        df_pandas = pandas.read_csv(test_filename)
    except Exception as exc:
        print("pandas.read_csv raised exception:\n", exc)
    df_pd = pd.read_csv(test_filename)
    print("pd.read_csv output:\n", df_pd)
finally:
    os.remove(test_filename)

Describe the problem

Note: bad lines means that the number of elements in row/line is larger than the number of columns.
Source code / logs

pandas.read_csv raised exception:
 Error tokenizing data. C error: Expected 2 fields in line 3, saw 3

pd.read_csv output:
   col1 col2
0  one  two
1    0    1

@amyskov I am not able to reproduce this bug on latest master. In fact, it seems like we are now throwing the correct error that matches pandas:
2022-08-22 16:22:56,267	ERROR worker.py:92 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): ray::_deploy_ray_func() (pid=43507, ip=<IP_ADDRESS>)
  File "/Users/kvelayutham/Documents/modin/modin/core/execution/ray/common/task_wrapper.py", line 42, in _deploy_ray_func
    return func(**args)
  File "/Users/kvelayutham/Documents/modin/modin/logging/logger_decorator.py", line 128, in run_and_log
    return obj(*args, **kwargs)
  File "/Users/kvelayutham/Documents/modin/modin/core/storage_formats/pandas/parsers.py", line 305, in parse
    return PandasParser.generic_parse(fname, **kwargs)
  File "/Users/kvelayutham/Documents/modin/modin/logging/logger_decorator.py", line 128, in run_and_log
    return obj(*args, **kwargs)
  File "/Users/kvelayutham/Documents/modin/modin/core/storage_formats/pandas/parsers.py", line 202, in generic_parse
    pandas_df = callback(BytesIO(to_read), **kwargs)
  File "/Users/kvelayutham/Documents/modin/modin/logging/logger_decorator.py", line 128, in run_and_log
    return obj(*args, **kwargs)
  File "/Users/kvelayutham/Documents/modin/modin/core/io/text/csv_dispatcher.py", line 40, in read_callback
    return pandas.read_csv(*args, **kwargs)
  File "/Users/kvelayutham/opt/anaconda3/envs/modin/lib/python3.9/site-packages/pandas/util/_decorators.py", line 311, in wrapper
    return func(*args, **kwargs)
  File "/Users/kvelayutham/opt/anaconda3/envs/modin/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 680, in read_csv
    return _read(filepath_or_buffer, kwds)
  File "/Users/kvelayutham/opt/anaconda3/envs/modin/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 581, in _read
    return parser.read(nrows)
  File "/Users/kvelayutham/opt/anaconda3/envs/modin/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1255, in read
    index, columns, col_dict = self._engine.read(nrows)
  File "/Users/kvelayutham/opt/anaconda3/envs/modin/lib/python3.9/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 225, in read
    chunks = self._reader.read_low_memory(nrows)
  File "pandas/_libs/parsers.pyx", line 805, in pandas._libs.parsers.TextReader.read_low_memory
  File "pandas/_libs/parsers.pyx", line 861, in pandas._libs.parsers.TextReader._read_rows
  File "pandas/_libs/parsers.pyx", line 847, in pandas._libs.parsers.TextReader._tokenize_rows
  File "pandas/_libs/parsers.pyx", line 1960, in pandas._libs.parsers.raise_parser_error
pandas.errors.ParserError: Error tokenizing data. C error: Expected 2 fields in line 3, saw 3


Multiline Vue component props breaks import.meta.env

Describe the bug
When passing a component property which folds into multiple lines, any use of import.meta.env breaks the test and shows the following error:
ReferenceError: im__vite_ssr_import_meta__ is not defined
Using the following example, the error occurs when the ternary condition inside some-prop folds into multiple lines. If the text was shortened to fx. :some-prop="testValue ? 'Hello' : 'World'" the error does not occur. This also happens when passing object-syntax to class attributes etc.
The error does not occur in Vitest < 1.3.0.
<template>
  <SomeOtherComponent
    :some-prop="
      testValue
        ? 'A long value to break handling of env variables'
        : 'it needs to break into a new line'
    "
   <!-- This also breaks env variables -->
    :class="{
        'truncate text-xs': someCondition,
        'text-sm': !someOtherCondition
      }"
  >
    <div>{{ count }} x {{ times }} = {{ result }}</div>
    <button @click="times += 1">x1</button>
  </SomeOtherComponent>
</template>

<script lang="ts">
import { computed, ref, defineComponent } from 'vue';
import SomeOtherComponent from './SomeOtherComponent.vue';

export default defineComponent({
  components: {
    SomeOtherComponent,
  },
  props: {
    count: {
      type: Number,
      required: true,
    },
  },
  setup(props) {
    const times = ref(2);
    const result = computed(() => props.count * times.value);
    const testValue = ref(false);

    // any use of import.meta.env will cause an error
    console.log(import.meta.env.MODE);

    return {
      times,
      result,
      testValue,
    };
  },
});
</script>

Reproduction
https://stackblitz.com/edit/vitest-dev-vitest-tfewql?file=components%2FHello.vue
System Info
Info from Stackblitz example. It was forked from official Vitest Vue example.

System:
    OS: Linux 5.0 undefined
    CPU: (8) x64 Intel(R) Core(TM) i9-9880H CPU @ 2.30GHz
    Memory: 0 Bytes / 0 Bytes
    Shell: 1.0 - /bin/jsh
  Binaries:
    Node: 18.18.0 - /usr/local/bin/node
    Yarn: 1.22.19 - /usr/local/bin/yarn
    npm: 10.2.3 - /usr/local/bin/npm
    pnpm: 8.15.3 - /usr/local/bin/pnpm
  npmPackages:
    @vitejs/plugin-vue: latest => 5.0.4
    vite: latest => 5.1.6
    vitest: latest => 1.3.1

Used Package Manager
npm
Validations

[X] Follow our Code of Conduct
[X] Read the Contributing Guidelines.
[X] Read the docs.
[X] Check that there isn't already an issue that reports the same bug to avoid creating a duplicate.
[X] Check that this is a concrete bug. For Q&A open a GitHub Discussion or join our Discord Chat Server.
[X] The provided reproduction is a minimal reproducible example of the bug.

I ran into the same issue (import.meta.env.DEV) and I couldn't figure out what was causing it, thank you!

I should mention I have solved this by exporting all needed env values from a separate file:
// fx utils/env.ts
export const { MODE, PROD, DEV } = import.meta.env

This allows for easy mocking as well during tests.

It looks like strip-literal is confused by Vue component file. v1.3.0 is where strip-literal changed from acorn to js-token https://github.com/vitest-dev/vitest/releases/tag/v1.3.0 https://github.com/vitest-dev/vitest/pull/5136, so that may be the reason (though I'm not sure how acorn could've handle Vue either).
When I locally debug the code around here:
https://github.com/vitest-dev/vitest/blob/6eda473f30c4670ec72a06bd3b083a724712ae2a/packages/vitest/src/node/plugins/ssrReplacer.ts#L16-L27
I see following transformations:
Hello.vue

original

<template>
  <SomeOtherComponent
    :some-prop="
      testValue
        ? 'A long value to break handling of env variables'
        : 'it needs to break into a new line'
    "
  >
    ...
  </SomeOtherComponent>
</template>

<script lang="ts">
...
    console.log(import.meta.env.MODE);

after stripLiteral

<template>
  <SomeOtherComponent
    :some-prop=""
      testValue
        ? '                                               '
        : '                                 '
    ""
  >
    ...
  </SomeOtherComponent>
</template>

<script lang="  ">
...
    console.log(import.meta.env.MODE);

after MagicString.overwrite

<template>
  <SomeOtherComponent
    :some-prop="
      testValue
        ? 'A long value to break handling of env variables'
        : 'it needs to break into a new line'
    "
  >
    ...
  </SomeOtherComponent>
</template>

<script lang="ts">
...
    console.log(im__vite_ssr_import_meta__.envODE);

This is fixed in strip-literal v2.1.0. You can upgrade the transitive dependency either by re-creating lockfile or tools such as pnpm dedupe.
I confirmed the reproduction is fixed using package.json overrides:
https://stackblitz.com/edit/vitest-dev-vitest-bifxjk?file=package.json


Memory leak on GaussianBlur

🐛 Describe the bug
Hello. When using num_workers > 0 for dataloader and GaussianBlur BEFORE the resize function in transforms (images in dataset are of different size) a memory leak appears. The larger num_workers used, the more the leak is (I ran out of 128 GB RAM in 300 iterations with batch_size of 32 and num_workers of 16).
To reproduce (you should initialize images with array of filepaths to images):
import torch
import glob
from torchvision import transforms
from PIL import Image
class FramesDataset(torch.utils.data.Dataset):
    def __init__(self, images):
        self.images = images
        self.init_base_transform()

    def __len__(self):
        return len(self.images)

    def init_base_transform(self):
        self.tr_aug = transforms.Compose([transforms.GaussianBlur(7, (1, 5)),
                                          transforms.Resize((256, 256), antialias=True),
                                          transforms.ToTensor(),
                                          transforms.Normalize([0.5]*3, [0.5]*3) ])

    def __getitem__(self, idx):
        img = Image.open(self.images[idx]).convert('RGB')
        out = self.tr_aug(img)
        return out

dataset = TestDataset(images)
dl = torch.utils.data.DataLoader(dataset, batch_size = 16, num_workers = 8, pin_memory = False)
while True:
    for batch in dl:
        pass

Versions
torch: 1.12.0+cu116
torchvision: 0.13.0+cu116
PIL: 9.0.0
Ubuntu: 20.04.4 LTS
cc @vfdev-5 @datumbox

@GLivshits thanks fore reporting this.
What's special about GaussianBlur is that it doesn't handle natively PIL images and does a conversion from PIL to Tensor and back. We'll have to check if there is a leak somewhere during that conversion but this is hard and might not be an issue on our side. It would help a lot if you can help us narrow this down a bit. Can you replace the PIL read with something like:
img = torchvision.io.read_file(self.images[idx])

You won't need a ToTensor() call in your transforms. Everything else remains the same. Do you still observe a memory leak?

Replaced PIL.Image.open with torchvision.io.read_image (it outputs uint8 tensor), still leaks.
"""
import torch
import torchvision
from torchvision import transforms
class TestDataset(torch.utils.data.Dataset):
def __init__(self, images):
    self.images = images
    self.init_base_transform()

def __len__(self):
    return len(self.images)

def init_base_transform(self):
    self.tr_aug = transforms.Compose([transforms.GaussianBlur(7, (1, 5)),
                                                                transforms.Resize((256, 256)),
                                                                transforms.Normalize([0.5]*3, [0.5]*3)])

def __getitem__(self, idx):
    img = torchvision.io.read_image(images[idx]).type(torch.float32).div(255.)
    out = self.tr_aug(img)
    return out

dataset = TestDataset(images)
dl = torch.utils.data.DataLoader(dataset, batch_size = 16, num_workers = 8, pin_memory = False)
while True:
for batch in dl:
pass
"""

@GLivshits I tried to reproduce the issue by measuring the memory with your script + psutil:
import os
import psutil

import torch
from torchvision import transforms
from PIL import Image

class FramesDataset(torch.utils.data.Dataset):
    def __init__(self, images):
        self.images = images
        self.init_base_transform()

    def __len__(self):
        return len(self.images)

    def init_base_transform(self):
        self.tr_aug = transforms.Compose(
            [
                transforms.GaussianBlur(7, (1, 5)),
                transforms.Resize((256, 256), antialias=True),
                transforms.ToTensor(),
                transforms.Normalize([0.5]*3, [0.5]*3)
            ]
        )

    def __getitem__(self, idx):
        img = Image.open(self.images[idx]).convert('RGB')
        out = self.tr_aug(img)
        return out

images = ["test-image.jpg" for _ in range(1000)]

dataset = FramesDataset(images)
dl = torch.utils.data.DataLoader(dataset, batch_size=16, num_workers=8, pin_memory=False)

p = psutil.Process(os.getpid())

epoch = 0
while epoch < 100:
    mem_usage = p.memory_info().rss / 1024 / 1024
    print(epoch, "- mem_usage:", mem_usage)
    for batch in dl:
        pass
    epoch += 1

I did 2 experiments:

with GaussianBlur as in the code above

Output

0 - mem_usage: 204.5625
1 - mem_usage:<PHONE_NUMBER>5
2 - mem_usage:<PHONE_NUMBER>
3 - mem_usage:<PHONE_NUMBER>5
4 - mem_usage:<PHONE_NUMBER>
5 - mem_usage:<PHONE_NUMBER>5
6 - mem_usage:<PHONE_NUMBER>5
7 - mem_usage:<PHONE_NUMBER>5
8 - mem_usage:<PHONE_NUMBER>5
9 - mem_usage: 208.921875
10 - mem_usage: 208.921875
11 - mem_usage:<PHONE_NUMBER>5
12 - mem_usage:<PHONE_NUMBER>
13 - mem_usage: 208.9375
14 - mem_usage: 208.9375
15 - mem_usage: 208.9375
16 - mem_usage:<PHONE_NUMBER>5
17 - mem_usage:<PHONE_NUMBER>
18 - mem_usage:<PHONE_NUMBER>
19 - mem_usage:<PHONE_NUMBER>5
20 - mem_usage:<PHONE_NUMBER>5
21 - mem_usage:<PHONE_NUMBER>5
22 - mem_usage:<PHONE_NUMBER>
23 - mem_usage:<PHONE_NUMBER>
24 - mem_usage:<PHONE_NUMBER>5
25 - mem_usage: 208.96875
26 - mem_usage:<PHONE_NUMBER>5
27 - mem_usage:<PHONE_NUMBER>5
28 - mem_usage: 209.0
29 - mem_usage: 209.0
30 - mem_usage: 209.0
31 - mem_usage: 209.0
32 - mem_usage: 209.0
33 - mem_usage: 209.0
34 - mem_usage: 209.0
35 - mem_usage:<PHONE_NUMBER>5
36 - mem_usage:<PHONE_NUMBER>5
37 - mem_usage: 209.015625
38 - mem_usage: 209.015625
39 - mem_usage: 209.015625
40 - mem_usage: 209.015625
41 - mem_usage: 209.015625
42 - mem_usage:<PHONE_NUMBER>5
43 - mem_usage:<PHONE_NUMBER>5
44 - mem_usage:<PHONE_NUMBER>
45 - mem_usage:<PHONE_NUMBER>
46 - mem_usage:<PHONE_NUMBER>5
47 - mem_usage:<PHONE_NUMBER>5
48 - mem_usage:<PHONE_NUMBER>5
49 - mem_usage:<PHONE_NUMBER>5
50 - mem_usage:<PHONE_NUMBER>5
51 - mem_usage:<PHONE_NUMBER>5
52 - mem_usage:<PHONE_NUMBER>5
53 - mem_usage:<PHONE_NUMBER>5
54 - mem_usage:<PHONE_NUMBER>5
55 - mem_usage:<PHONE_NUMBER>
56 - mem_usage:<PHONE_NUMBER>
57 - mem_usage:<PHONE_NUMBER>5
58 - mem_usage:<PHONE_NUMBER>5
59 - mem_usage:<PHONE_NUMBER>5
60 - mem_usage:<PHONE_NUMBER>5
61 - mem_usage:<PHONE_NUMBER>5
62 - mem_usage:<PHONE_NUMBER>5
63 - mem_usage:<PHONE_NUMBER>5
64 - mem_usage:<PHONE_NUMBER>5
65 - mem_usage:<PHONE_NUMBER>5
66 - mem_usage:<PHONE_NUMBER>5
67 - mem_usage:<PHONE_NUMBER>5
68 - mem_usage:<PHONE_NUMBER>5
69 - mem_usage:<PHONE_NUMBER>5
70 - mem_usage:<PHONE_NUMBER>5
71 - mem_usage:<PHONE_NUMBER>5
72 - mem_usage:<PHONE_NUMBER>5
73 - mem_usage: 209.046875
74 - mem_usage: 209.046875
75 - mem_usage: 209.046875
76 - mem_usage: 209.046875
77 - mem_usage: 209.046875
78 - mem_usage: 209.046875
79 - mem_usage: 209.046875
80 - mem_usage: 209.046875
81 - mem_usage: 209.046875
82 - mem_usage: 209.046875
83 - mem_usage: 209.046875
84 - mem_usage: 209.046875
85 - mem_usage: 209.046875
86 - mem_usage:<PHONE_NUMBER>
87 - mem_usage:<PHONE_NUMBER>5
88 - mem_usage: 209.0625
89 - mem_usage: 209.0625
90 - mem_usage: 209.0625
91 - mem_usage: 209.0625
92 - mem_usage: 209.0625
93 - mem_usage: 209.0625
94 - mem_usage: 209.0625
95 - mem_usage: 209.0625
96 - mem_usage: 209.0625
97 - mem_usage: 209.0625
98 - mem_usage: 209.0625
99 - mem_usage: 209.0625

without GaussianBlur as

        self.tr_aug = transforms.Compose(
            [
                transforms.Resize((256, 256), antialias=True),
                transforms.ToTensor(),
                transforms.Normalize([0.5]*3, [0.5]*3)
            ]
        )

Output

0 - mem_usage:<PHONE_NUMBER>
1 - mem_usage:<PHONE_NUMBER>
2 - mem_usage:<PHONE_NUMBER>5
3 - mem_usage: 209.109375
4 - mem_usage:<PHONE_NUMBER>
5 - mem_usage:<PHONE_NUMBER>5
6 - mem_usage:<PHONE_NUMBER>
7 - mem_usage: 209.15625
8 - mem_usage:<PHONE_NUMBER>5
9 - mem_usage:<PHONE_NUMBER>
10 - mem_usage: 209.203125
11 - mem_usage: 209.203125
12 - mem_usage:<PHONE_NUMBER>5
13 - mem_usage:<PHONE_NUMBER>5
14 - mem_usage:<PHONE_NUMBER>
15 - mem_usage:<PHONE_NUMBER>
16 - mem_usage:<PHONE_NUMBER>5
17 - mem_usage: 209.234375
18 - mem_usage:<PHONE_NUMBER>5
19 - mem_usage:<PHONE_NUMBER>5
20 - mem_usage:<PHONE_NUMBER>5
21 - mem_usage: 209.25
22 - mem_usage: 209.25
23 - mem_usage: 209.25
24 - mem_usage:<PHONE_NUMBER>5
25 - mem_usage:<PHONE_NUMBER>5
26 - mem_usage:<PHONE_NUMBER>5
27 - mem_usage: 209.265625
28 - mem_usage: 209.265625
29 - mem_usage: 209.265625
30 - mem_usage: 209.265625
31 - mem_usage: 209.265625
32 - mem_usage: 209.265625
33 - mem_usage:<PHONE_NUMBER>5
34 - mem_usage:<PHONE_NUMBER>
35 - mem_usage:<PHONE_NUMBER>
36 - mem_usage:<PHONE_NUMBER>
37 - mem_usage: 209.296875
38 - mem_usage:<PHONE_NUMBER>5
39 - mem_usage:<PHONE_NUMBER>
40 - mem_usage:<PHONE_NUMBER>5
41 - mem_usage:<PHONE_NUMBER>5
42 - mem_usage: 209.3125
43 - mem_usage:<PHONE_NUMBER>
44 - mem_usage: 209.328125
45 - mem_usage:<PHONE_NUMBER>5
46 - mem_usage:<PHONE_NUMBER>5
47 - mem_usage:<PHONE_NUMBER>5
48 - mem_usage:<PHONE_NUMBER>5
49 - mem_usage:<PHONE_NUMBER>5
50 - mem_usage:<PHONE_NUMBER>5
51 - mem_usage:<PHONE_NUMBER>5
52 - mem_usage:<PHONE_NUMBER>5
53 - mem_usage:<PHONE_NUMBER>5
54 - mem_usage:<PHONE_NUMBER>5
55 - mem_usage:<PHONE_NUMBER>5
56 - mem_usage:<PHONE_NUMBER>5
57 - mem_usage:<PHONE_NUMBER>5
58 - mem_usage:<PHONE_NUMBER>5
59 - mem_usage:<PHONE_NUMBER>5
60 - mem_usage:<PHONE_NUMBER>5
61 - mem_usage:<PHONE_NUMBER>5
62 - mem_usage:<PHONE_NUMBER>
63 - mem_usage:<PHONE_NUMBER>
64 - mem_usage:<PHONE_NUMBER>
65 - mem_usage:<PHONE_NUMBER>
66 - mem_usage:<PHONE_NUMBER>
67 - mem_usage:<PHONE_NUMBER>
68 - mem_usage:<PHONE_NUMBER>
69 - mem_usage:<PHONE_NUMBER>
70 - mem_usage:<PHONE_NUMBER>
71 - mem_usage:<PHONE_NUMBER>
72 - mem_usage:<PHONE_NUMBER>
73 - mem_usage:<PHONE_NUMBER>
74 - mem_usage:<PHONE_NUMBER>
75 - mem_usage:<PHONE_NUMBER>
76 - mem_usage:<PHONE_NUMBER>
77 - mem_usage:<PHONE_NUMBER>
78 - mem_usage:<PHONE_NUMBER>
79 - mem_usage:<PHONE_NUMBER>
80 - mem_usage:<PHONE_NUMBER>
81 - mem_usage:<PHONE_NUMBER>5
82 - mem_usage:<PHONE_NUMBER>5
83 - mem_usage:<PHONE_NUMBER>5
84 - mem_usage:<PHONE_NUMBER>5
85 - mem_usage:<PHONE_NUMBER>5
86 - mem_usage:<PHONE_NUMBER>5
87 - mem_usage:<PHONE_NUMBER>5
88 - mem_usage:<PHONE_NUMBER>5
89 - mem_usage:<PHONE_NUMBER>5
90 - mem_usage:<PHONE_NUMBER>5
91 - mem_usage:<PHONE_NUMBER>5
92 - mem_usage:<PHONE_NUMBER>5
93 - mem_usage:<PHONE_NUMBER>5
94 - mem_usage:<PHONE_NUMBER>5
95 - mem_usage:<PHONE_NUMBER>5
96 - mem_usage:<PHONE_NUMBER>5
97 - mem_usage:<PHONE_NUMBER>5
98 - mem_usage:<PHONE_NUMBER>5
99 - mem_usage: 209.34375

My pytorch, vision versions: '1.13.0.dev20220704+cpu', '0.14.0a0'
I see that in both logs mem consumption is growing. Can you detail how could you identify that it is GaussianBlur causing mem leak ?

@vfdef-5 I'm just watching htop.
The thing is that if your images are of the same size everything works ok (I also tried loading dataset of one image and there is no memory leak). But if there are multiple sizes of images - leak appears.

If a single image of different sizes is used there is still a 4 GB RAM overhead.

@vfdev-5 I've excluded every other augmentation and swapped the order of blur and resize and found matching leaky configuration. The code provided is already a localized version of a problem.


AREPL can't print certain emojis

On a scale from 1-10, 1 being lowest, this has to be near a 1 on the severity list.
Still, it would be nice.  This worked:
print(sys.stdout.encoding) # cp1252
import sys, codecs
w = codecs.getwriter('utf-8')
sys.stdout = w(sys.stdout.buffer)

import emoji
print(emoji.emojize(':eggplant:'))

but then certain accents (like á) started printing malformed:  Ã¡
I really hate encodings.  Why can't everyone just talk in esperanto???

This belongs in the backend.  Closing and migrating.

see https://github.com/Almenon/AREPL-backend/issues/34


feat: update ClaimContent type and mocks

Made claimType optional in ClaimContent type
Added a generic 'Claim' and a 'Statement' claim to the mocks

We should adapt the process so that we can explicitly indicate that a PR doesn't require coko approval. If we clearly know that no change is made to the presentation.

We should adapt the process so that we can explicitly indicate that a PR doesn't require coko approval. If we clearly know that no change is made to the presentation.

From my original intro:

The label can be added either by us (if we know there’s no HTML [added: change]) or after getting the go ahead from Coko (via a preview env probably), so it’s lightweight, but does add a layer of protection for us when trying to merge.

I'm OK with us adding the coko-approved label if we know it's not a coko thing. If you think another label is worthwhile, it's a small change I guess we could add, but I think I'd rather work on improving the tech so it's not needed anymore (the HTML improvements that Paul has asked for us to do) rather than minor improvements to this  - it's only meant to make us stop and think rather than be a record or anything.


More moves

@alesgenova Here are some of the moves you suggested.

I put engine under pipeline, because its the "pipeline engine"


fix: cannot find rules

At the moment doing something like
{
  "extends": ["codelyzer"],
  "rules": {
    "angular-whitespace": [true, "check-interpolation", "check-semicolon"],
    "banana-in-box": true,
    "templates-no-negated-async": true,
    "directive-selector": [true, "attribute", "sg", "camelCase"],
  }
}

Will not work and you'll end up with loads of errors example
Could not find implementations for the following rules specified in the configuration:
    angular-whitespace
    banana-in-box
    contextual-life-cycle

This is because tslint requires a rulesDirectory to resolve the rules.

Would you share the source where you found that exporting rulesDirectory is required?

Actually i found it in some source code of other lint rules libraries
example;
https://github.com/buzinas/tslint-eslint-rules/blob/master/index.js
https://github.com/ajafff/tslint-consistent-codestyle/blob/master/rules/index.ts
On Thu, 08 Feb 2018 at 17:17, Minko Gechev<EMAIL_ADDRESS>wrote:

Would you share the source where you found that exporting rulesDirectory
is required?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/mgechev/codelyzer/pull/511#issuecomment-364163365,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AQv-Wn9rdKwSahT8jm-Kc0f30qKTizv6ks5tSx4bgaJpZM4R-P25
.


data

how did you create the 'data'?

The data were extracted from the PubMed website:

After searching for "EEG" in Title and abstract.

I'm playing with Python (quite new to it) and got it like this
from metapub import PubMedFetcher
fetch = PubMedFetcher()
narticles = []
years= list(range(1930,2018))
for index, year in enumerate(years,1):
myquery = 'EEG[Title/Abstract]) AND ("%d"[Date - Entrez] : "%d"[Date - Entrez])' %(year,year+1)
pmids = fetch.pmids_for_query(myquery, retmax=20000)
narticles.append(len(pmids))

interesting, however - running your code, I get different numbers that do not match up with the data extracted via the PubMed website:
See the data ... where we have 3698 entries for 2017, and then from your code:
In [11]: for y, n in zip(years[::-1], narticles[::-1]):
    ...:     print(y,n)
    ...:
2017 6192
2016 7299
2015 6861
2014 6364
2013 6264
2012 5732
2011 4685
2010 4292
2009 4173
2008 3847
2007 3891
2006 3694
2005 3202
2004 3099
2003 2977
2002 2901
2001 2810
2000 2728
1999 2589
1998 2473
1997 2207
1996 2103
1995 2189
1994 2165
1993 2136
1992 2144
1991 2191
1990 2155
1989 2174
1988 1978
1987 1715
1986 1724
1985 1675
1984 1644
1983 1582
1982 1405
1981 1342
1980 1328
1979 1360
1978 1366
1977 1274
1976 1272
1975 1276
1974 855
1973 484
1972 494
1971 565
1970 662
1969 802
1968 755
1967 676
1966 591
1965 408
1964 387
1963 333
1962 263
1961 240
1960 225
1959 227
1958 396
1957 364
1956 201
1955 185
1954 158
1953 121
1952 97
1951 88
1950 54
1949 31
1948 12
1947 11
1946 10
1945 3
1944 0
1943 0
1942 0
1941 0
1940 0
1939 0
1938 0
1937 0
1936 0
1935 0
1934 0
1933 0
1932 0
1931 0
1930 0

It's a cool idea to get the data programmatically instead of clicking a button on a web interface. But can you somehow resolve the question why the data don't match up? In case of doubt, I'd trust the web interface more.

just ran 'myquery' manually in pubmed and got the same results, 3698 was a little while ago :-)

For myquery I use: "EEG[Title/Abstract]" on PubMed. You should get my search results on this link:
https://www.ncbi.nlm.nih.gov/pubmed?term=EEG[Title%2FAbstract]
How come that the two of us are getting different data? The one that I get aligns with the data in this repository, whereas your data seems to contain much higher publication counts?

because I'm in the UK and we overestimate everything?

@CPernet I'll look into the metapub package during the next days and see whether I can find the issue. Did you code this up from scratch or did you follow some example/tutorial? If so, it'd be nice if you could share the link.

After working a bit on it, I found the following:
Instead of using a modified query to include years, you can use the since and until parameters of the pmids_for_query method. This seems to get more congruent results. There is still some (negligible) fluctuation on the order of 10 articles per year.
I updated the code to use the automatic scraping of the data anyways. Thanks!

cool :-)


Cherry pick some commit from #2097

Those can already be merged, so let's do that and reduce the size of this PR.

Fixed commit message.


Trim pieces of TASL to prevent unwanted space/make sure license renders

Fixes/Closes/References #
Type
🐛 Bugfix
Value
Trims off excess whitespace between | characters in the TASL. This prevents unwanted gaps before any punctuation in the TASL information, and ensures the correct license information is displayed.
Checklist
All

[x] PR labelled and assigned
[x] Any introduced code complexity has been flagged

Could we not trimthe before they hit the function?
Looking at it - why isn't it happening here:
https://github.com/wellcometrust/wellcomecollection.org/blob/f6dc3ab7e188e0050e13229b83a33dc1d2a6ac43/server/services/prismic-content.js#L101

Of course – I knew I was missing a trick – thanks.


dart2js shows globalized-closure classes

When iterating over a library's classes (using mirrors) dart2js shows the synthetic classes that have been introduced for closures.

Mirrors support on the web/dart2js is removed. Announcement.


bug: sveltekit handleFetch server hook does not work on cloudflare workers

Describe the bug
Unfortunately, I'm not sure who to raise this issue with. Cloudflare's Request object does not implement the mode specification which is being leveraged by the fetch implementation that is passed to the handleFetch hook.
Error: Failed to get the 'mode' property on 'Request': the property is not implemented.

This obviously makes this hook completely unusable on cloudflare workers, and therefore, i'm assuming the same is the case on vercel edge functions.
Reproduction
Implement the handleFetch server hook.
Logs
No response
System Info
System:
    OS: macOS 12.3.1
    CPU: (10) arm64 Apple M1 Max
    Memory: 29.72 GB / 64.00 GB
    Shell: 5.8 - /bin/zsh
  Binaries:
    Node: 16.16.0 - ~/.nvm/versions/node/v16.16.0/bin/node
    Yarn: 1.22.19 - /opt/homebrew/bin/yarn
    npm: 8.11.0 - ~/.nvm/versions/node/v16.16.0/bin/npm
  Browsers:
    Chrome: 106.0.5249.119
    Firefox: 103.0.2
    Safari: 15.4

Severity
serious, but I can work around it
Additional Information
The mode property is checked in the following places...
https://github.com/sveltejs/kit/blob/87b3037bb6fcf574d5d50c91f42cc91d3b97286c/packages/kit/src/runtime/server/fetch.js#L34
https://github.com/sveltejs/kit/blob/87b3037bb6fcf574d5d50c91f42cc91d3b97286c/packages/kit/src/runtime/server/fetch.js#L59`

Duplicate of #6739


Landing page

Directory structure like one used in open census
same approach to config
refactored app.js to minimal state.

Please feel free to commit directly atm since we don't need to do full review.


TimeDistributed BatchNormaliztion doesn't update mean and variance

I verified this on the master branch (as of today), and the issue is also discussed in length in the keras-rcnn repo https://github.com/broadinstitute/keras-rcnn/issues/42. When BatchNormaliztion is wrapped with TimeDistributed, it does not update the mean and variance variables. As a result, the BN seems to be working fine during training, but in inference mode it produces the wrong output (the mean and variance are used in inference mode only). This code reproduces the issue:
Without TimeDistributed (this works fine)
import keras
import keras.backend as K
import keras.layers as KL
import keras.models as KM

# Simple model with one BN layer
inputs = KL.Input(shape=[2])
outputs = KL.BatchNormalization(center=True, scale=True, name="bn")(inputs)
model = KM.Model(inputs, outputs)

# Generate random inputs with mean = 2 and standard deviation = 2
x = np.random.normal(loc=2, scale=2, size=(num_samples, 2))

# Output fixed to [0, 1]. Model should overfit to this output.
y = np.broadcast_to(np.array([0, 1]), (num_samples, 2))

# Train
model.compile(optimizer="sgd", loss="mse")
model.fit(x, y, epochs=100, verbose=0)

# Predict
p = model.predict(x)
print("shape: {}. Mean: {}".format(p.shape, np.mean(p.reshape(num_samples, 2), axis=0)))

Output:
shape: (1000, 2). Mean: [  2.14744806e-17   9.99999762e-01]
# Print learned variables
gamma, beta, mean, variance = model.get_layer("bn").get_weights()
print("gamma: ", gamma)
print("beta: ", beta)
print("mean: ", mean)
print("STD: ", np.sqrt(variance))

Output:
gamma:  [  1.08916180e-14   6.56345378e-09]
beta:  [  6.62068365e-22   9.99997079e-01]
mean:  [ 1.90420938  1.97779751]
STD:  [ 1.83883619  1.93283391]
Note that the mean and standard deviation got updated to ~2, which matches the input distribution.
With TimeDistributed (does not update mean/variance)
# Simple model with one BN layer
inputs = KL.Input(shape=[num_samples, 2])
outputs = KL.TimeDistributed(KL.BatchNormalization(center=True, scale=True), name="bn")(inputs)
model = KM.Model(inputs, outputs)

# Generate random inputs with mean = 2 and standard deviation = 2
x = np.random.normal(loc=2, scale=2, size=(1, num_samples, 2))

# Output fixed to [0, 1]. Model should overfit to this output.
y = np.broadcast_to(np.array([0, 1]), (1, num_samples, 2))

# Train
model.compile(optimizer="sgd", loss="mse")
model.fit(x, y, epochs=1000, verbose=0)

# Predict
p = model.predict(x)
print("shape: {}. Mean: {}".format(p.shape, np.mean(p.reshape(num_samples, 2), axis=0)))

Output:
shape: (1, 1000, 2). Mean: [  8.31366633e-05   1.00004113e+00]
# Print learned variables
gamma, beta, mean, variance = model.get_layer("bn").get_weights()
print("gamma: ", gamma)
print("beta: ", beta)
print("mean: ", mean)
print("STD: ", np.sqrt(variance))

Output:
gamma:  [  4.32773231e-05   4.32775269e-05]
beta:  [  2.50025976e-12   9.99956787e-01]
mean:  [ 0.  0.]
STD:  [ 1.  1.]
This time mean and std did not update from their default values.

After applying the linked PR, the same code above produces the correct results:
With TimeDistributed (Fixed)
# Simple model with one BN layer
inputs = KL.Input(shape=[num_samples, 2])
outputs = KL.TimeDistributed(KL.BatchNormalization(center=True, scale=True), name="bn")(inputs)
model = KM.Model(inputs, outputs)

# Generate random inputs with mean = 2 and standard deviation = 2
x = np.random.normal(loc=2, scale=2, size=(1, num_samples, 2))

# Output fixed to [0, 1]. Model should overfit to this output.
y = np.broadcast_to(np.array([0, 1]), (1, num_samples, 2))

# Train
model.compile(optimizer="sgd", loss="mse")
model.fit(x, y, epochs=1000, verbose=0)

# Predict
p = model.predict(x)
print("shape: {}. Mean: {}".format(p.shape, np.mean(p.reshape(num_samples, 2), axis=0)))

Output:
shape: (1, 1000, 2). Mean: [  1.93917371e-09   9.99956548e-01]
# Print learned variables
gamma, beta, mean, variance = model.get_layer("bn").get_weights()

print("gamma: ", gamma)
print("beta: ", beta)
print("mean: ", mean)
print("STD: ", np.sqrt(variance))

Output:
gamma:  [  4.32816014e-05   4.32849411e-05]
beta:  [  1.57018183e-11   9.99956787e-01]
mean:  [ 2.04563737  1.96782172]
STD:  [ 1.98750329  1.95810878]

This fix  #7466 does not completely fix the issue. Tests with following changes still fails:
Change wrapper_test.py line 106:110 with following code:
# test with BatchNormalization
    model = Sequential()
    model.add(wrappers.TimeDistributed(
        layers.BatchNormalization(center=True, scale=True),
        name='bn', batch_input_shape=(2, 10, 2))) ''' Changed input_shape to batch_input_shape with batch_size not None'''
    model.compile(optimizer='rmsprop', loss='mse')

The issue is, if batch_size is not None on TimeDistributed layer, it uses the rnn based approach for TimeDistributed-computation and that approach is not suitable with BatchNorm as child layer.
Is this known issue/behavior? Any plan to fix it?
I am using
Keras - 2.2.4
Tensorflow - 1.12.0