Updated to 3.1.1 (2020-10-17) now Homebridge fails

Grrr,  I just Updated to 3.1.1 (2020-10-17) now Homebridge fails with the following,  please help.

[10/19/2020, 8:39:25 PM] Homebridge v1.2.3 is running on port 52391.
[10/19/2020, 8:39:28 PM] Error [ERR_UNHANDLED_ERROR]: Unhandled error. ('connect EHOSTUNREACH <IP_ADDRESS>:27847')
at TcpService.emit (events.js:304:17)
at Socket. (/homebridge/node_modules/homebridge-rinnai-touch-platform/src/rinnai/TcpService.ts:50:16)
at Object.onceWrapper (events.js:422:26)
at Socket.emit (events.js:315:20)
at emitErrorNT (internal/streams/destroy.js:92:8)
at emitErrorAndCloseNT (internal/streams/destroy.js:60:3)
at processTicksAndRejections (internal/process/task_queues.js:84:21)
[10/19/2020, 8:39:28 PM] Got SIGTERM, shutting down Homebridge...
[10/19/2020, 8:39:28 PM] [Rinnai Touch] Shutting down plugin

Regards
Rob

FYI,  I reverted back to version 3.1.0, all good again.  Sorry but there seems to be a BIG bug in version 3.1.1.

Hi Rob, sorry to hear the upgrade didn't work. 3.1.1 didn't contain any changes to the handling of the TCP connection to the Rinnai module, it was mainly fixing issues with Evap Cooling.
The module is prone to having connectivity issues. When this happens to me I find the following will fix it up:

Shutdown Homebridge and force quit the Rinnai Touch App on your phone (if necessary). You need to ensure nothing else attempts to connect to the module via WiFi
Restart your WiFi router or the Rinnai module (whichever is easier)
After a few minutes restart Homebridge

When you get a chance give 3.1.1 another go.
Regards

Hi Mantorok1,
Thanks for responding so quickly.
Yeah I suspected it is this flaky Rinnai Touch Wi-Fi, I’m going to lodge a service request with Rinnai to have it replaced, even before I used it in Homebridge (Home assistant) there touch app worked only sometimes.  I use Unifi Ubiquiti network hardware and this touch Wi-Fi shows latency issues even though it has good Wi-Fi connection (70%) on the same vlan, and it’s only 10m from one of the unifi Wi-Fi AP devices (3 throughout the house).
How close do you have to have the touch Wi-Fi from your Wi-Fi AP?  More so I’m interested to know what your ping responses are, mine range from 50 to 200 ms, up and down like a yoyo. Done of my other 50+ Wi-Fi devices show this trend and all have good ping responses (under 20ms).
Anyhow, It finally managed to connect again,  I’ve updated to 3.1.1,  then this touch Wi-Fi went mad again for 20mins then finally made one good connection before it started it’s network connection issues again.
It definitely an issue with the touch Wi-Fi and not your plugin.  Again thanks for you response.
Regards Robert
From: mantorok1<EMAIL_ADDRESS>Sent: Monday, 19 October 2020 9:48 PM
To: mantorok1/homebridge-rinnai-touch-platform<EMAIL_ADDRESS>Cc: RGoodworth<EMAIL_ADDRESS>Author<EMAIL_ADDRESS>Subject: Re: [mantorok1/homebridge-rinnai-touch-platform] Updated to 3.1.1 (2020-10-17) now Homebridge fails (#2)
Hi Rob, sorry to hear the upgrade didn't work. 3.1.1 didn't contain any changes to the handling of the TCP connection to the Rinnai module, it was mainly fixing issues with Evap Cooling.
The module is prone to having connectivity issues. When this happens to me I find the following will fix it up:

Shutdown Homebridge and force quit the Rinnai Touch App on your phone (if necessary). You need to ensure nothing else attempts to connect to the module via WiFi
Restart your WiFi router or the Rinnai module (whichever is easier)
After a few minutes restart Homebridge

When you get a chance give 3.1.1 another go.
Regards
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My module is installed in the roof cavity and is about 3 - 4m from the router. Ping responses seem to be similar to what you are seeing but I'm not getting random connection dropouts. Once the plugin connects it remains very stable.
64 bytes from <IP_ADDRESS>: icmp_seq=0 ttl=128 time=239.679 ms
64 bytes from <IP_ADDRESS>: icmp_seq=1 ttl=128 time=136.089 ms
64 bytes from <IP_ADDRESS>: icmp_seq=2 ttl=128 time=147.743 ms
64 bytes from <IP_ADDRESS>: icmp_seq=3 ttl=128 time=203.776 ms
64 bytes from <IP_ADDRESS>: icmp_seq=4 ttl=128 time=62.756 ms
64 bytes from <IP_ADDRESS>: icmp_seq=5 ttl=128 time=385.555 ms
64 bytes from <IP_ADDRESS>: icmp_seq=6 ttl=128 time=97.033 ms
64 bytes from <IP_ADDRESS>: icmp_seq=7 ttl=128 time=24.535 ms
64 bytes from <IP_ADDRESS>: icmp_seq=8 ttl=128 time=39.829 ms
64 bytes from <IP_ADDRESS>: icmp_seq=9 ttl=128 time=61.183 ms
64 bytes from <IP_ADDRESS>: icmp_seq=10 ttl=128 time=78.867 ms

Hi @robertfgoodworth, I've released a new version of the plugin which should prevent the plugin from crashing when it fails to connect to the module. Let me know if this fixes the issue for you and I'll close it off.
Regards

Hi Mantorok,
Awesome work,  did the trick, does not crash now, just loses connection all the time ☹.
Crazy hey ☹
I’ve lodged a service request with Brivis, even my NC7 touch shows error 53 quite often.
Cheers
Rob
From: mantorok1<EMAIL_ADDRESS>Sent: Tuesday, October 20, 2020 5:48 PM
To: mantorok1/homebridge-rinnai-touch-platform<EMAIL_ADDRESS>Cc: RGoodworth<EMAIL_ADDRESS>Mention<EMAIL_ADDRESS>Subject: Re: [mantorok1/homebridge-rinnai-touch-platform] Updated to 3.1.1 (2020-10-17) now Homebridge fails (#2)
Hi @robertfgoodworth https://github.com/robertfgoodworth , I've released a new version of the plugin which should prevent the plugin from crashing when it fails to connect to the module. Let me know if this fixes the issue for you and I'll close it off.
Regards
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The Rinnai module uses 11g (2.4GHz). Is it possible you are getting some interference such as a neighbour's WiFi or your microwave oven? Have you tried setting different channels on your router for the 2.4GHz band?

Hi Mantorok1,
Thanks for the feedback, yes I’m very aware of Wifi channels etc, My Unifi Ubiquity Cloud Key 2 checks my wifi channel usage every Sunday night and if needed changes to the least used channels for both Ghz ranges,  I also have around 60 devices on Zigbee (2.4 channel 15). So far of all 108 devices on my networks (inc zigbee) this device is the only one with these network latency issues.
Perhaps a new Touch wifi module may help.
Do you know if Rinnai have ever released a firmware update for these?
Cheers
Rob
From: mantorok1<EMAIL_ADDRESS>Sent: Wednesday, 21 October 2020 7:59 AM
To: mantorok1/homebridge-rinnai-touch-platform<EMAIL_ADDRESS>Cc: RGoodworth<EMAIL_ADDRESS>Mention<EMAIL_ADDRESS>Subject: Re: [mantorok1/homebridge-rinnai-touch-platform] Updated to 3.1.1 (2020-10-17) now Homebridge fails (#2)
The Rinnai module uses 11g (2.4GHz). Is it possible you are getting some interference such as a neighbour's WiFi or your microwave oven? Have you tried setting different channels on your router for the 2.4GHz band?
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I'm not aware of any firmware updates for the module.

This issue has been fixed in v3.1.2

Just a FYI and in case someone else has this issue.
I seem to have stablised it by moving the Touch Wfi box 2 meter from my Unifi Wifi AP, comms seems to be more stable. Talk about crappy wifi in there devices.
Cheers
Rob.
From: mantorok1<EMAIL_ADDRESS>Sent: Wednesday, 21 October 2020 7:59 AM
To: mantorok1/homebridge-rinnai-touch-platform<EMAIL_ADDRESS>Cc: RGoodworth<EMAIL_ADDRESS>Mention<EMAIL_ADDRESS>Subject: Re: [mantorok1/homebridge-rinnai-touch-platform] Updated to 3.1.1 (2020-10-17) now Homebridge fails (#2)
The Rinnai module uses 11g (2.4GHz). Is it possible you are getting some interference such as a neighbour's WiFi or your microwave oven? Have you tried setting different channels on your router for the 2.4GHz band?
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api-docs: Clarify what topics are returned by /api/get-stream-topics.

Updates the main description for the /api/get-stream-topics endpoint so that it is clear that the topics for private streams with protected history are limited to the topics / messages the user has access to.
And updates that documentation and the help center documentation for bot permissions / abilities, to clarify that bots have the same restriction and can only access messages / topics that are sent after the bot (not the bot's owner) subscribed to the stream.
See relevant CZO discussion.

Screenshots and screen captures:

Get topics in a stream
Current documentation

About bots - bot type section
Current documentation

Self-review checklist

[ ] Self-reviewed the changes for clarity and maintainability
(variable names, code reuse, readability, etc.).

Communicate decisions, questions, and potential concerns.

[ ] Explains differences from previous plans (e.g., issue description).
[ ] Highlights technical choices and bugs encountered.
[ ] Calls out remaining decisions and concerns.
[ ] Automated tests verify logic where appropriate.

Individual commits are ready for review (see commit discipline).

[ ] Each commit is a coherent idea.
[ ] Commit message(s) explain reasoning and motivation for changes.

Completed manual review and testing of the following:

[ ] Visual appearance of the changes.
[ ] Responsiveness and internationalization.
[ ] Strings and tooltips.
[ ] End-to-end functionality of buttons, interactions and flows.
[ ] Corner cases, error conditions, and easily imagined bugs.

This is great, merged, thanks @laurynmm!


[Docs]Changing the color of hover

Category of documentation update

The gray hover effect doesn't quite match the overall vibe of the website.
Thus changing it will something that looks pleasant to see .
Describe the change you think might work
No response
Checklist

[X] I have checked the existing issues.
[X] I follow Contributing Guidelines of this project.
[X] I am a GSSOC'24 contributor.
[ ] I am a IWOC'24 contributor.
[ ] I am a JWOC'24 contributor.
[ ] I am a SWOC'24 contributor.

Code of Conduct

[X] I agree to follow this project's "Code of Conduct".

@Vaishnavi1047
Can u give any idea how it looks like after your change

Any update on the question asked @Vaishnavi1047


Start Bot error Composer 1.4.0

Hi, I have installed the new version of MS BF Composer and i get this error when i try to start the bot :

with the new version of composer the runtime path was modified so i have make this change:
It Works :)
Before:

After:

ok, thanks. I've checked the fix info already
I've created runtime,  bot creation and publishing is working again.
Thanks for quick response. Very helpful!
Karl


Enable peerDependency field

There's a few cases where you want a type definition to have a peer dependency on another being installed. This is already emitted after installation (E.g. module found but not included), but this would formalize a way to also have it installed locally when working on a project (E.g. typings install will install peer dependency typings locally).

+1
I've just had this issue with the webpack typings which require uglify-js, which in turn require source-map.

@dsebastien Can you share a link? Just want to check if it's related to what I'm thinking. It sounds like those should be actual dependencies here. I'm thinking things like mongoose-timestamp (which I just merged) that have an indirect dependency on the mongoose schema typings.

https://github.com/DefinitelyTyped/DefinitelyTyped/blob/4df467996e649e6ea50ae573a21df04c0e437941/webpack/webpack.d.ts#L6
webpack.d.ts references other typings which also reference other typings: https://github.com/DefinitelyTyped/DefinitelyTyped/blob/4df467996e649e6ea50ae573a21df04c0e437941/uglify-js/uglify-js.d.ts#L6

Each also requires the other libs:
https://github.com/DefinitelyTyped/DefinitelyTyped/blob/4df467996e649e6ea50ae573a21df04c0e437941/webpack/webpack.d.ts#L9
https://github.com/DefinitelyTyped/DefinitelyTyped/blob/4df467996e649e6ea50ae573a21df04c0e437941/uglify-js/uglify-js.d.ts#L9

Not sure peerDependencies will help here, these are actually real dependencies. The issue is that DT doesn't have the concept of "dependencies" so right now I'm only printing messages of stripped references.


Allow users upload user-scoped Secrets

Allow users upload their personal Secrets that they can use in Github Actions workflows of the repos that they have acceess to (both their own repos, and the organization repos).
It's somehow related to https://github.com/Azure/actions/issues/13

@N-Usha: Any update on this?


Wrong permissions on local-backupbuckets

How to categorize this issue?

/area usability
/kind bug
What happened:
I am trying to setup local poc according to getting_started_locally.md guide. But it seems there is some problem with deployment on linux (archlinux, ubuntu 20.04). After I run make gardener-up the seed cluster never reaches STATUS=Ready.
tomas@gardener:~/gardener-1.56.1$ kubectl get seed local
NAME    STATUS     PROVIDER   REGION   AGE     VERSION      K8S VERSION
local   NotReady   local      local    7m18s   v0.0.0-dev   v1.24.0

When I run kubectl describe seed local I can see error (gardener-extension-provider-local-xxxx-yyyy):
Message:               The following BackupBuckets have issues:
* Name: c58c1901-0400-4725-a16a-d4ef9c200bcd, Error: flow "Backup Bucket Reconciliation" encountered task errors: [task "Waiting until backup bucket is reconciled" failed: Error while waiting for BackupBucket /c58c1901-0400-4725-a16a-d4ef9c200bcd to become ready: error during reconciliation: Error reconciling backupbucket: mkdir /dev/local-backupbuckets/c58c1901-0400-4725-a16a-d4ef9c200bcd: permission denied]

Then, if I try to create a shoot cluster with the command kubectl apply -f example/provider-local/shoot.yaml it is stuck at Create Processing (26%):
tomas@gardener:~/gardener-1.56.1$ kubectl -n garden-local get shoot local
NAME    CLOUDPROFILE   PROVIDER   REGION   K8S VERSION   HIBERNATION   LAST OPERATION            STATUS      AGE
local   local          local      local    1.25.0        Awake         Create Processing (26%)   unhealthy   24m

After some debbugging of this problem I find out, that it's a permissions problem with hostpath /etc/gardener/local-backupbuckets (dev/local-backupbuckets/) which had the wrong owner id - id of my linux local user 1000:
root@gardener-local-control-plane:/etc/gardener/local-backupbuckets# ls -lah
total 4.0K
drwxrwxr-x 2 1000 1000 4.0K Sep 29 07:44 .
drwxr-xr-x 5 root root   75 Sep 29 07:44 ..

Workaround is to chmod o+w dev/local-backupbuckets/
After that a bucket is created under user id 65532 and everything works just fine.
[tomas@w00:gardener-1.56.1]$ ls -lah dev/local-backupbuckets/
total 12K
drwxrwxrwx 3 1000 1000 4.0K Sep 29 07:46 ./
drwxr-xr-x 4 1000 1000 4.0K Sep 29 07:46 ../
drwxrwxr-x 2 65532 65532 4.0K Sep 29 07:46 1de2ce3a-fed8-420b-a826-ce49b4748ba4/

What you expected to happen:
It should just work.
How to reproduce it (as minimally and precisely as possible):
On linux machine (tested on archlinux and ubuntu 20.04):
$ wget https://github.com/gardener/gardener/archive/refs/tags/v1.56.1.tar.gz
$ tar -xvf v1.56.1.tar.gz
$ cd gardener-1.56.1
$ make kind-up
$ make gardener-up
$ kubectl get seed local   --- will never reach STATUS=Ready

Anything else we need to know?:
Environment:

Gardener version: 1.56.1
Kubernetes version (use kubectl version): v1.24.3
Cloud provider or hardware configuration: local
Others:

So, I did some tests and there is one more issue that is connected to this one.
I will file a PR but first I want to discuss how it should be best resolved.
The issue with permissions on dev/local-backupbuckets/ can be easily solved by a change in Makefile target kind-up:
mkdir -m 775 ... -> mkdir -m 777 ...
But the next issue is with deleting and cleanup.
In directories local-backupbuckets and local-registry under dev/ there are files that are owned by root (id 0), these files can't be deleted by kind-down: rm -rf dev/local-backupbuckets or user without root privileges. The same thing applies for local-registry.
rm -rf dev/local-backupbuckets
rm: cannot remove 'dev/local-backupbuckets/6cb4d3df-1b94-4ce7-b460-20ba89b95b21/shoot--local--local--9580f33c-d60b-4c92-a78a-e8a139c4ee56': Permission denied

On mac this is not an issue, because docker on mac is using Linux VM, and files are shared from mac host to VM through gRPC fuse with user mapping.
I think this should be taken care of in some form, there are 3 different solutions that I came up with:

Best thing would be to create another make target like kind-vol-cleanup into which we would move deleting of local-backupbuckets too:

kind-vol-cleanup:
docker run --rm -v $(REPO_ROOT)/dev:/local-dev busybox sh -c 'rm -rf /local-dev/local-backupbuckets'
docker run --rm -v $(REPO_ROOT)/dev:/local-dev busybox sh -c 'rm -rf /local-dev/local-registry'

With this, we can work around the need of explicitly using sudo like it is done in kind-up for fs.inotify.max_user_instances increase.

We can use OS detection and if Linux is detected, then we can run rm commnad with sudo.
We can add a warning with a link to docs if rm returns a non-zero code.


Add unit tests for Camera2D

This PR adds unit tests for Camera2D, mentioned in issue #43440.

Thanks! And congrats for your first merged Godot contribution :tada:


[Unexpected Behavior] Audio distortion when the same sound effect is overlayed.

What you're using
This is done on an indev version of OutFox.
When having a sound constantly overlap itself (usually through repetitively making the sound play.), it distorts that sound effect. Sometimes, it makes popping sounds, other times it may affect the rate (sounds like double rate).
Expected behavior
I'd expect them to overlap and have nothing odd happen.
Here's an example I took while on the profile select screen:
2020-08-03_00-10-23.mkv

Can you test this with 4.8.2 when it is released?

Fixed in 4.8.2


feat(viewport): add selectedIndex to output event

:tada: This PR is included in version 6.2.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


Remove occurrences of any

Is your feature request related to a problem? Please describe.
There are occurrences of the any type in the definition types that could be better.
Describe the solution you'd like
Use ReactElement instead of any for the type for the children properties in each interfaces of each component's props.
Describe alternatives you've considered
None.
Additional context
None.

Looks like there is no suitable types for functional component's children in React using TypeScript. Feel free to re-open this issue if you think that there is a solution for this issue.

It might be possible to use a fragment instead of returning directly the children for the components so that TypeScript understands that this is a legit JSX Element and nothing else.


Fields must be named starting with "acf_"?

Hello, If I'm understanding correctly, this cleaner will only work on fields that have been named "acf_*"? Is that correct?

You are free to use any prefix - but there must be a prefix (set in the settings of this plug-in).


Build only (with no run) for Windows debugging.

I'm playing with the additional option for runmodels
+        --norun                 Compile and link. Success if nrnivmodl succeeds. (Useful for Windows when debugging incomplete g++ toolchain in installer.)

and am at the point where it seemed simplest to force every model to effectively have the yaml property run: null.
I tried:
 class ModelRun(dict):
-    def __init__(self, model, working_dir, clean=False):
+    def __init__(self, model, working_dir, clean=False, norun=False):

to merely
-        self._fetch_model()
+        if not norun:
+            self._fetch_model()

but I guess _fetch_model() is getting more than just run.
I'm wondering if someone can short circuit my guesswork by suggesting how to effectively replace the run after return from _fetch_model().

@alexsavulescu may have a better idea, but my guess would be that one could add
if norun:
  self["run"] = None

after https://github.com/neuronsimulator/nrn-modeldb-ci/blob/f0fae7dcaca75db46024db45c301658a998f64ce/modeldb/modelrun.py#L49
🤔


PS4 light bar flickers when controller vibrates

As the title states. So far I've only noticed this when playing Forza Horizon 3.
Sidenote, Destiny 2 doesn't change the light bar to the color profile I've chosen until the controller vibrates. Games seem to just take over the light bar effects for some reason.
Edit: Checking "Dinput Only" fixes the flicker issue but makes DS4Windows useless because it uses native input. "Hide DS4 Controller" option doesn't seem to work for me either.
Not sure what could be causing this as I don't remember this being an issue for the month or so that I've been using DS4Windows...

I'm on the latest version of DS4Win and having a similar issue. Mine is happening in every game. Before I start a game the lightbar is showing the color I selected, but after the first rumble occasion in a game it stays off and only flashing in the same pattern as the rumble goes.
Is there a new setting which causing this or is this a bug?

I confirm this behavior in Forza Motorpsort 7 too.
Once the game is launched lightbar turns off and blinks only during vibration.
Once I exit the game, the light still is off until I test the vibration in the app for example - then the light comes back.


update travis to add integration tests using docker.

👍

@tiborvass you might be interested by this.

Nice! LGTM


Add "restart" and "faster" button to animation in termynal

Inspired on FastAPI documentation I noticed that there are two buttons very useful and elegant. One button to restarts the animation and another button to makes the animation go faster.
See the examples:
Fast button

Restart button

And this is the termynal from the Termynal plugin:

Does it make sense to implement these buttons in the project?

Of course!
I will try to add the features. I also be glade to approve your PR to the project!

Added in v0.3.0


Initial commit deny-route-nexthopinternet

Deny route with next hop type internet to ensure data loss prevention. Both creating routes as a standalone resource or nested within their parent resource route table are considered.

Logic looks sounds.

Logic looks sounds.


Add stable diffusion 2

Stable Diffusion 2 was just released, it should probably be added sometime.

What would your feature do ?
Support the new 768x768 model 2.0 from Stability-AI and all the other new models that just got released.
Links

https://github.com/Stability-AI/stablediffusion
https://huggingface.co/stabilityai/stable-diffusion-2
https://huggingface.co/stabilityai/stable-diffusion-2-base
https://huggingface.co/stabilityai/stable-diffusion-2-depth
https://huggingface.co/stabilityai/stable-diffusion-2-inpainting
https://huggingface.co/stabilityai/stable-diffusion-x4-upscaler

See Also

https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/5009 [dupe]
https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/5011
https://github.com/huggingface/diffusers/issues/1388

rudimentary support for stable diffusion 2.0

https://github.com/MrCheeze/stable-diffusion-webui/commit/069591b06bbbdb21624d489f3723b5f19468888d
Originally posted by @152334H in https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/5011#issuecomment-1325971596

Looking forward to trying to run the new set of colabs 2.0 will need. The system reqs may be too large for free colab.

On it!

will be nice, you can train 768 on free its just time intensive and
generate images, there will be alot more demand for the High ram setting i
bet.
On Thu, Nov 24, 2022 at 1:39 AM Ben @.***> wrote:

On it!
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shawn/nawnie

Awesome, thanks again for all the great work you do!

https://github.com/hafriedlander/diffusers/blob/stable_diffusion_2/scripts/convert_original_stable_diffusion_to_diffusers.py
Notes:

Only tested on the two txt2img models, not inpaint / depth2img / upscaling
You will need to change your text embedding to use the penultimate layer too
It spits out a bunch of warnings about vision_model, but that's fine
I have no idea if this is right or not. It generates images, no guarantee beyond that. (Hence no PR - if you're patient, I'm sure the Diffusers team will do a better job than I have)

Originally posted by @hafriedlander in https://github.com/huggingface/diffusers/issues/1388#issuecomment-1326135768

Here's an example of accessing the penultimate text embedding layer https://github.com/hafriedlander/stable-diffusion-grpcserver/blob/b34bb27cf30940f6a6a41f4b77c5b77bea11fd76/sdgrpcserver/pipeline/text_embedding/basic_text_embedding.py#L33
Originally posted by @hafriedlander in https://github.com/huggingface/diffusers/issues/1388#issuecomment-1326166368

doesn't seem to work for me on the 768-v model using the v2 config for v
TypeError: EulerDiscreteScheduler.init() got an unexpected keyword argument 'prediction_type'
Originally posted by @devilismyfriend in https://github.com/huggingface/diffusers/issues/1388#issuecomment-1326220609

You need to use the absolute latest Diffusers and merge this PR (or use my branch which has it in it) https://github.com/huggingface/diffusers/pull/1386
Originally posted by @hafriedlander in https://github.com/huggingface/diffusers/issues/1388#issuecomment-1326243809

(My branch is at https://github.com/hafriedlander/diffusers/tree/stable_diffusion_2)
Originally posted by @hafriedlander in https://github.com/huggingface/diffusers/issues/1388#issuecomment-1326245339

testing in progress on the horde https://github.com/Sygil-Dev/nataili/tree/v2
try it out Stable Diffusion 2.0 on our UI's
https://tinybots.net/artbot
https://aqualxx.github.io/stable-ui/
https://dbzer0.itch.io/lucid-creations
https://sigmoid.social/@stablehorde/109398715339480426
SD 2.0

[x] Initial implementation ready for testing
[ ] img2img
[ ] inpainting
[ ] k_diffusers support

Originally posted by @AlRlC in https://github.com/Sygil-Dev/nataili/issues/67#issuecomment-1326385645

Support added, requires more than 12GB of RAM (for now)
https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb

ROCK ON!!! DO WE JUST NEED THE NEW CKPT?
On Thu, Nov 24, 2022, 6:53 AM Ben @.***> wrote:

Support added, requires more than 12GB of RAM (for now)
https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb
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https://github.com/TheLastBen/fast-stable-diffusion/commit/11fd38bfbd2f1ed42449b37ba88ba324ff42ba43

Create pathsV2.py

https://github.com/TheLastBen/fast-stable-diffusion/commit/fe445d986f08a1134f26f5efcd1c0829f34bc481

Support for SD V.2

https://github.com/TheLastBen/fast-stable-diffusion/commit/da9b38010c2edc8fcccf2b0b70f321af30c0ecb8

fix

https://github.com/TheLastBen/fast-stable-diffusion/commit/6c84728c72bd9735b0a5be4c62a292554c3b41d1

fix

https://github.com/TheLastBen/fast-stable-diffusion/commit/04ba92b1931ab6aa0269a0516640f8874b004885

fix

Should work now, make sure you check the box "redownload original model" when choosing V2
https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb
Requires more than 12GB of RAM for now, so free colab probably won't suffice.
the quality of the images

Awesome, thank you! I'm not sure I see how to train Dreambooth in the notebook - probably normal at this stage? Just checking :-)

Awesome, thank you! I'm not sure I see how to train Dreambooth in the notebook - probably normal at this stage? Just checking :-)

For Dreambooth, we'll have to wait for the diffusers team to make it compatible with the V2

Oh of course - thank you!
I bumped into something though, I updated the repo, redownloaded the original model (v2), ran the requirements cell, then trying to start SD throws this:
LatentDiffusion: Running in v-prediction mode
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.
DiffusionWrapper has 865.91 M params.
making attention of type 'vanilla-xformers' with 512 in_channels
building MemoryEfficientAttnBlock with 512 in_channels...
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla-xformers' with 512 in_channels
building MemoryEfficientAttnBlock with 512 in_channels...
^C

In Colab : Runtime-> change runtime type -> Runtime shape -> High-RAM
Keep the GPU Class to standard to save compute units

Ah yes it worked, thanks!
Le jeu. 24 nov. 2022 à 19:06, Ben @.***> a écrit :

In Colab : Runtime-> change runtime type -> Runtime shape -> High-RAM
Keep the GPU Class to standard to save compute units
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@djcedr update the notebook again for a better V2

Will do, thanks 🙏
Le jeu. 24 nov. 2022 à 20:15, Ben @.***> a écrit :

@djcedr https://github.com/djcedr update the notebook again for a
better V2
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From @pcuenca on the HF discord:

We are busy preparing a new release of diffusers to fully support Stable Diffusion 2. We are still ironing things out, but the basics already work from the main branch in github. Here's how to do it:

Install diffusers from github alongside its dependencies:

pip install --upgrade git+https://github.com/huggingface/diffusers.git transformers accelerate scipy

Use the code in this script to run your predictions:

from diffusers import DiffusionPipeline, EulerDiscreteScheduler
import torch

repo_id = "stabilityai/stable-diffusion-2"
device = "cuda"

scheduler = EulerDiscreteScheduler.from_pretrained(repo_id, subfolder="scheduler", prediction_type="v_prediction")
pipe = DiffusionPipeline.from_pretrained(repo_id, torch_dtype=torch.float16, revision="fp16", scheduler=scheduler)
pipe = pipe.to(device)

prompt = "High quality photo of an astronaut riding a horse in space"
image = pipe(prompt, width=768, height=768, guidance_scale=9).images[0]
image.save("astronaut.png")

Originally posted by @vvvm23 in https://github.com/huggingface/diffusers/issues/1392#issuecomment-1326747275

how sure are you that your conversion is correct? I'm trying to diagnose a difference I get between your 768 weights and my conversion script. There's a big difference, and in general I much prefer the results from my conversion. It seems specific to the unet - if I replace my unet with yours I get the same results.
Originally posted by @hafriedlander in https://github.com/huggingface/diffusers/issues/1388#issuecomment-1327018829

OK, differential diagnostic done, it's the Tokenizer. How did you create the Tokenizer at https://huggingface.co/stabilityai/stable-diffusion-2/tree/main/tokenizer? I just built a Tokenizer using AutoTokenizer.from_pretrained("laion/CLIP-ViT-H-14-laion2B-s32B-b79K") - it seems to give much better results.
Originally posted by @hafriedlander in https://github.com/huggingface/diffusers/issues/1388#issuecomment-1327031107

I've put "my" version of the Tokenizer at https://huggingface.co/halffried/sd2-laion-clipH14-tokenizer/tree/main. You can just replace the tokenizer in any pipeline to test it if you're interested.
Originally posted by @hafriedlander in https://github.com/huggingface/diffusers/issues/1388#issuecomment-1327077503

Should work now, make sure you check the box "redownload original model" when choosing V2
https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb
Requires more than 12GB of RAM for now, so free colab probably won't suffice.

Confirmed Free Colab crashes due to RAM capacity when loading the model (in another colab, not this one).

@GuruVirus

In Colab : Runtime-> Change runtime type -> Runtime shape -> High-RAM
Keep the GPU Class to standard to save compute units
Originally posted by @TheLastBen in https://github.com/TheLastBen/fast-stable-diffusion/issues/599#issuecomment-1326747515

diffusers==0.9.0 with Stable Diffusion 2 is live!
https://github.com/huggingface/diffusers/releases/tag/v0.9.0
Originally posted by @anton-l in https://github.com/huggingface/diffusers/issues/1388#issuecomment-1327731012

I've almost finished a proper implementation of Stable Diffusion 2.0 in Automatic1111, so that it runs locally and automatically updates everything and works on 4GB lowvram. It supports both 1.5 and 2.0 models and you can switch between models from the menu like normal.
So far the 512x512 base model, 512x512 inpainting model, and the 768x768 v-prediction model work properly. The upscaler model and depth models load correctly but don't work to generate images yet.
It gives an error trying to load old Textual Inversion embeddings with the new models, but that can't be helped.
And the PLMS sampling method isn't working.
I'll push it soon.
Originally posted by @CarlKenner in https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/5011#issuecomment-1327367090

when will Dreambooth support sd2

While it's not dreambooth, this repo seems to have support for finetuning SDv2:

https://github.com/smirkingface/stable-diffusion

https://github.com/smirkingface/stable-diffusion#news

Added support for inference and finetuning with the SD 2.0 base model (inpainting is still unsupported).

https://github.com/smirkingface/stable-diffusion/blob/main/docs/sd2.0.md

Originally posted by @0xdevalias in https://github.com/JoePenna/Dreambooth-Stable-Diffusion/issues/112#issuecomment-1327993709

Issues potentially related to SDv2 dreambooth/finetuning/training/etc:

https://github.com/TheLastBen/fast-stable-diffusion/issues/629
https://github.com/TheLastBen/fast-stable-diffusion/issues/624

Should work now, make sure you check the box "redownload original model" when choosing V2
https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb
Requires more than 12GB of RAM for now, so free colab probably won't suffice.

Dumb question: where does it spit out the URL for opening the webui after running everything?

Dumb question: where does it spit out the URL for opening the webui after running everything?

At the last cell; it'll be either a loca.lt or gradio.app URL, I believe.

Dumb question: where does it spit out the URL for opening the webui after running everything?

At the last cell; it'll be either a loca.lt or gradio.app URL, I believe.

Thanks. Odd, after running the last cell it's not returning either of those URL options in that google collab for me. It just returns the following after completing:
LatentDiffusion: Running in v-prediction mode DiffusionWrapper has 865.91 M params. ^C

Dumb question: where does it spit out the URL for opening the webui after running everything?

At the last cell; it'll be either a loca.lt or gradio.app URL, I believe.

Thanks. Odd, after running the last cell it's not returning either of those URL options in that google collab for me. It just returns the following after completing: LatentDiffusion: Running in v-prediction mode DiffusionWrapper has 865.91 M params. ^C

Out of RAM

Dumb question: where does it spit out the URL for opening the webui after running everything?

At the last cell; it'll be either a loca.lt or gradio.app URL, I believe.

Thanks. Odd, after running the last cell it's not returning either of those URL options in that google collab for me. It just returns the following after completing: LatentDiffusion: Running in v-prediction mode DiffusionWrapper has 865.91 M params. ^C

Out of RAM

I'm using Collab Pro, Tesla T4, 15109 MiB, 15109 MiB.

Dumb question: where does it spit out the URL for opening the webui after running everything?

At the last cell; it'll be either a loca.lt or gradio.app URL, I believe.

Thanks. Odd, after running the last cell it's not returning either of those URL options in that google collab for me. It just returns the following after completing: LatentDiffusion: Running in v-prediction mode DiffusionWrapper has 865.91 M params. ^C

Out of RAM

Dumb question: where does it spit out the URL for opening the webui after running everything?

At the last cell; it'll be either a loca.lt or gradio.app URL, I believe.

Thanks. Odd, after running the last cell it's not returning either of those URL options in that google collab for me. It just returns the following after completing: LatentDiffusion: Running in v-prediction mode DiffusionWrapper has 865.91 M params. ^C

Out of RAM

Oh got it. Thanks that worked.


does not run

 super(Widget, self).__init__(**kwargs)

File "kivy_event.pyx", line 254, in kivy._event.EventDispatcher.init (kivy_event.c:5332)
TypeError: object.init() takes no parameters

A problem with Scatter's properties, tracking at kivy/kivy#5064

fixed with 57e7339


Kubernetes extension breaks file links in "Go Tests" OUTPUT channel?

With the Kubernetes extension disabled the line references in the stack trace are clickable:

But when enabled they are not:

That's so weird!  Apologies for the inconvenience this is causing you; I'll take a look.

Okay, this seems to happen because we colourise the output channel.  The way the colouriser works is global, and appears to override the built-in linkifier.  It looks like other extensions that colourise the output channel (such as https://marketplace.visualstudio.com/items?itemName=IBM.output-colorizer) have the same problem - I suspect whichever extension loads last overrides all the previous extensions and the built-in highlighter/linkifier.
I think we probably need to remove the colouriser from the extension.  Unfortunately, the way VS Code loads syntaxes, we can't as far as I know make this conditional, so we can't even allow users to opt in via config.  But we don't make a lot of use of colourisation so I don't think it's a big loss!


Issue Title: Enhance convertFeetToCm Function to Include Centimeter…

Description👨💻
The current implementation of the convertFeetToCm function only supports the conversion of feet and inches to centimeters. To provide a more comprehensive utility, I've enhanced the function to allow users to also input a value in centimeters (cm) along with feet. This update enables the function to handle conversions from feet and centimeters to total centimeters.

Type of Change📄

[ ] Bug fix (non-breaking change which fixes a bug)
[x] New feature (non-breaking change which adds functionality)
[ ] Style (non-breaking change which improves website style or formatting)
[ ] Documentation (non-breaking change which updates or adds documentation)
[ ] Responsiveness (non-breaking change which improves UI/UX on different screen sizes)

Changes Made:
Function Signature Update: The function now accepts two parameters: feet and cm (centimeters).
Checklist✅

[x] I am an Open Source contributor
[x] I have performed a self-review of my code
[x] My code follows the style guidelines of this project
[x] I have commented on my code, particularly in hard-to-understand areas

Screenshots/GIF📷

Impact before changes

Impact after changes
BMI in cm

BMI in feet

Impact:
This enhancement provides greater flexibility in the function's usage, allowing users to perform more complex conversions in a single function call. It ensures that the function can now handle both feet and additional centimeters seamlessly
Request for Review:
Please review the changes to ensure they align with the expected functionality and coding standards. Feedback or suggestions for improvement are welcome.

@Rakesh9100  Kindly review my contribution


Update adding tracks documentation

Updating Rally documentation to fix inconsistencies discovered during onboarding.

All the listed JSONs/code/command lines have been verified with ES 6.5.3 and 7.14.1 up to Advanced Topics section which seems not so type/mapping-specific as the first part.


Proposal: Component Discovery for OCI Registries

Problem
Currently it is not possible to list, and therefore discover, OCM components that are stored in an OCI Repository. This is a property of the OCI specification, which does not support listing images stored repository.
Proposal
I propose that we introduce the concept of a component-index.  The component-index is a repository with a "well-known" name which can be used to describe all components housed in the registry. For example, the component index might be as follwos: ghcr.io/open-component-model/component-index.
Within this repository there is a manifest acting as the index, for example: ghcr.io/component-index/v1:index.ocm. This is an OCI image (likely without any layers) that exists purely as a reference point for other images.
When a new component version is pushed to the registry we also push a corresponding artifact to the component-index repository. This artifact should specify the digest of component-index as the subject. The "Subject" field is part of the OCI 1.1 spec and will require updating github.com/opencontainers/image-spec to version v1.1.0-rc2.
Listing components can then be performed by querying the referrers API for the v1:index.ocm:
GET /v2/component-index/referrers/<digest for v1:index.ocm>
This will return an `ImageIndex which can be used to display the available components in a particular registry.
Furthermore, if we specify metadata about the particular component as an annotation on the artifact (such as the provider) we could filter the list of components based on particular metadata fields.
OCI Referrers API Context
The OCI Distribution Spec v1.0.1 introduces support for the Referrers API. In tandem with the Artifact Manifest's subject field (part of the OCI Image Spec) it is possible to indicate relationships between OCI artifacts.
For example, the following manifest is an SBOM that references an image:
{
  "mediaType": "application/vnd.oci.artifact.manifest.v1+json",
  "artifactType": "application/vnd.example.sbom.v1",
  "blobs": [
    {
      "mediaType": "application/gzip",
      "size": 123,
      "digest": "sha256:87923725d74f4bfb94c9e86d64170f7521aad8221a5de834851470ca142da630"
    }
  ],
  "subject": {
    "mediaType": "application/vnd.oci.image.manifest.v1+json",
    "size": 1234,
    "digest": "sha256:cc06a2839488b8bd2a2b99dcdc03d5cfd818eed72ad08ef3cc197aac64c0d0a0"
  },
  "annotations": {
    "org.opencontainers.artifact.created": "2022-01-01T14:42:55Z",
    "org.example.sbom.format": "json"
  }
}

Using the referrers API which can list all references to the subject which returns an image index containing a list of descriptors:
GET /v2/<name>/referrers/<digest>
{
  "schemaVersion": 2,
  "mediaType": "application/vnd.oci.image.index.v1+json",
  "manifests": [
    {
      "mediaType": "application/vnd.oci.image.manifest.v1+json",
      "size": 1234,
      "digest": "sha256:a1a1a1...",
      "artifactType": "application/vnd.example.sbom.v1",
      "annotations": {
        "org.opencontainers.artifact.created": "2022-01-01T14:42:55Z",
        "org.example.sbom.format": "json"
      }
    },
    {
      "mediaType": "application/vnd.oci.artifact.manifest.v1+json",
      "size": 1234,
      "digest": "sha256:a2a2a2...",
      "artifactType": "application/vnd.example.signature.v1",
      "annotations": {
        "org.opencontainers.artifact.created": "2022-01-01T07:21:33Z",
        "org.example.signature.fingerprint": "abcd"
      }
    }
  ]
}

@mandelsoft and @hilmarf , what do you think about this? Querying an OCI registry to get all versions of a dedicated component already can take a while. Such a feature would also be beneficial for the "Component UI" that we wanted to provide for MPAS for end users to search for available products (modelled as OCM components).


added details about reset to 5TB

@JohanFreelancer9  any reason why this is still in open state and changes were not merged to public

@JohanFreelancer9 any reason why this is still in open state and changes were not merged to public

@scanum

@MikePlumleyMSFT
PR has been copyedited and is ready for final review, could you please check and merge? Thanks!


useSubscriptionQuery does not update cache for DELETE notfications

Describe the bug
useSubscriptionQuery does not trigger cache updates for delete notifications
To Reproduce
Setup a subscription using useSubscriptionQuery and delete a row from the supabase admin panel. The local query cache does not update until the next stale refresh.
Expected behavior
Deletes should immediately trigger a re-query.
Additional context
packages\postgrest-react-query\src\subscribe\use-subscription-query.ts incorrectly performs a coallesce operation which doesn't work as expected: let data: T['Row'] | R = payload.new ?? payload.old;. For deletes, payload.new is an empty object, so an empty object is propagated later. Deletes should always use payload.old.

Created a PR to fix. 🙂 #450


refactor!: slidem 2.0

new CSSStyleSheet is live in safari TP, so now's a good time
closes #25

I found one more issue that seems to have crept in with the last release. If you make a custom slide (like slidem-polymersummit-slide) and define a background: ... css value, it is ignored unless you set !important because the css in slidem-slide-base.js always overrides the background even if the --background css variable is not set. Apparently constructed stylesheets take some kind of precedence over defining styles with


Don't show RBR on expense reports for violations

RBRs for violations should only show on workspace chats, not on individual expense reports or transaction threads.
Convo: https://expensify.slack.com/archives/C05LX9D6E07/p1733854922551589
Issue OwnerCurrent Issue Owner: @s77rt

Proposal
Please re-state the problem that we are trying to solve in this issue.
Don't show RBR on expense reports for violations
What is the root cause of that problem?
we are not considering the type of report here:
https://github.com/Expensify/App/blob/e8212bdffe8c443801d200c91cc368754e8393bf/src/components/LHNOptionsList/OptionRowLHN.tsx#L312
What changes do you think we should make in order to solve the problem?

We can add the condition optionItem.isPolicyExpenseChat  there as:
      {hasBrickError &&!optionItem.isPolicyExpenseChat && (
What specific scenarios should we cover in automated tests to prevent reintroducing this issue in the future?

@s77rt is already working on this issue. That's why it's not marked External.

PR went to production 5 days ago.

@allroundexperts can you complete the checklist?


configurable autoConnect

This adds an optional autoConnect property to the base pusher service, so derived services can opt out. (addressing issue https://github.com/netguru/ember-pusher-guru/issues/17)

Great job, @jrr, thanks for your input!


Can't resolve module 'https' ... but it is installed.

Bug report

Hello,
I did previously try to ask questions on stackoverflow : https://stackoverflow.com/questions/75298355/cant-install-the-https-module-in-react-webpack?noredirect=1#comment132868538_75298355

What is the current behavior?
The compiling gives the following error message related to the https module which is actually installed but not found :
Module not found: Error: Can't resolve 'https' in '/home/etcetera ...'

BREAKING CHANGE: webpack < 5 used to include polyfills for node.js core modules by default.
This is no longer the case. Verify if you need this module and configure a polyfill for it.

If you want to include a polyfill, you need to:
    - add a fallback 'resolve.fallback: { "https": require.resolve("https-browserify") }'
    - install 'https-browserify'
If you don't want to include a polyfill, you can use an empty module like this:
    resolve.fallback: { "https": false }

I can't find any webpack.config.js to apply what is suggested in the error message.
If the current behavior is a bug, please provide the steps to reproduce.
1 - npx create-react-app any_name
2 - npm install https
3 - try to import the https module with import https from 'https'
4 - write npm start in the terminal, and then you should get the error previously mentionned.

What is the expected behavior?
I expect a nice compiling step without error and being able to use the https package.

Other relevant information:
webpack version: I did not install a webpack package. It's all in my react app "under the hood" as I used create-react-app.
Node.js version: v18.6.0
Operating System: Ubuntu
Additional tools: I am using WSL

Because you don't have https package in browser (your target is web by default), you can try to provide polyfill in such case, because most of things will not work, node.js env !== browser's env, feel free to feedback


feat: mirror node as a conditional subchart

Description
This pull request changes the following:

Adds hedera mirror node as a subchart.
This mirror node will read data from the minio (aws s3 replacement) buckets.
This mirror node explorer [future] deployed as part of FST will read data from this mirror node

Limitations:

The addressbook.bin contains a single entry 0.0.3, it needs to be modified if the network has more than one node
This will be done by the fst infrastructure code

Related Issues

Closes #208

:tada: This PR is included in version 0.7.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


Try/req streaming gabi

Codecov Report

Merging #853 (b43c152) into try/req-streaming-1 (0e88769) will decrease coverage by 0.17%.
The diff coverage is 36.36%.

:exclamation: Current head b43c152 differs from pull request most recent head 89d1a2f. Consider uploading reports for the commit 89d1a2f to get more accurate results

@@                   Coverage Diff                   @@
##           try/req-streaming-1     #853      +/-   ##
=======================================================
- Coverage                51.90%   51.72%   -0.18%
=======================================================
  Files                       70       70
  Lines                     2208     2206       -2
  Branches                    63       66       +3
=======================================================
- Hits                      1146     1141       -5
- Misses                    1062     1065       +3

Impacted Files
Coverage Δ

zio-http/src/main/scala/zhttp/http/HttpData.scala
50.00% <0.00%> (-2.64%)
:arrow_down:

zio-http/src/main/scala/zhttp/http/Request.scala
21.73% <ø> (ø)

...in/scala/zhttp/service/server/ContentDecoder.scala
2.70% <0.00%> (+0.20%)
:arrow_up:

...io-http/src/main/scala/zhttp/service/Handler.scala
60.71% <57.14%> (-0.52%)
:arrow_down:

zio-http/src/main/scala/zhttp/html/Elements.scala
20.15% <0.00%> (-1.56%)
:arrow_down:

zio-http/src/main/scala/zhttp/core/Util.scala
100.00% <0.00%> (ø)

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Fixed Issue 6

Fixed Issue 6 by updating Send Message over UDP.vi to utilize IP address rather than computer name.

Hey Matt,
I've recently been working with NI's legal team to figure out how to handle incoming pull requests and we are committed to finding an appropriate process to protect ourselves, contributors and also any end users (since we build and publish AMC on the tools network). Because we're in the evaluation stage I'd like to get your feedback on what we have so far.
To avoid putting our emails on a public forum, would it be possible for you to PM me on the ni community (username smithd) so I can send you the proposed details and get your thoughts?
Thanks,
Daniel

Hi matt,
Due to the challenges associated with merging changes made under the BSD license, we've decided to make the change to the apache license. This change is now reflected in the repository. For us to be able to merge your pull request, please do the following:
-Review the apache license and notice ("LICENSE" and "NOTICE" file in the master branch)
-Rebase your changes on the master, or merge the master's changes into yours. Because there are no file conflicts, this should be essentially identical processes.
-Once you've made that update, please post back here and we'll complete the merge process and build the code.

Awesome, I'll take care of that shortly.
Thanks,
Matt

OK. I've merged your changes into my fork and think it's ready for you to handle the pull request. Please let me know if I need to do anything else. I'm pretty new with the forking/merging/pull request process. Thanks, Matt

Thats all we needed, thanks. Looks good.

FYI I'm currently installing LV2009 on our build machine and then I'll push the changes onto VIPM.

uploaded to tools network 3.3.1


Cipher strength is only key-dependent

DeepViolet reports RSA_WITH_RC4_128_SHA(0x5) as a strong cipher. During the past years a few attacks  against RC4 applicable in real world scenarios came up and the cipher is therefore considered broken. SHA1 is neither considered a good choice nowadays. Security evaluation of algorithms should not only include key length, but also a black list of broken/insecure ciphers and hash algorithms. At least the documentation for getStrengthEvaluation() should clearly state that this evaluation is currently only key-size dependent and does not take the cipher/hashing algorithm into account.

I'm not a cryptologist and I know many others are not as well.  I like the idea of a cipher "strength" evaluation but it's error prone.  I feel uncomfortable evaluating strength of these ciphers myself.  The idea of a simple evaluation system is attractive me and my reason for looking the Mozilla project.  See Improvement 1 of the feature map for the next release I include,
Improvement 1, Improve Analysis of Ciphersuite strength evaluation
There are some ciphers in the list that are marked strong that are no longer strong. See, Mozilla Cipher Recommendations
Ideally, I would like a list of all IANA cipher suites and strength indicator I can include for DeepViolet.  This way I don't have to guess or track the opinion of every cryptologists.  Also I like your recommendation about including key length.
Is there any other source besides Mozilla you recommend?

I didn't take a look at your feature map, sorry. Besides Mozilla's recommendations, I do not know a list of all IANA  ciphers and security evaluations, so I'd stick with Mozilla's database.
When writing the bug report, I forgot to mention that the handshake protocol is also important for security. For example, SSLv3 is deprecated because it's considered insecure (RFC7568). Therefore, evaluating the security of the connection (handshake + hashing + cipher + cipher mode) rather than the academic security of a cipher may be a better approach.

Good catch, I will add this to my list as well.  I knew this area needs some improvement.

Not sure what your interests are in DV or how your using it.  But if your interested, take a look at the next round of features for delivery.  I'm interested to know if you think the list looks interesting to you. Beta 5

I'm interested to know if you think the list looks interesting to you.
I'm not sure what you are meaning with this. I'm integrating DV into a project I'm working on, but it's not a required or important feature. Maybe I can find some time to work on the connection security evaluation. If you are interested I can also take a look at your code before releasing your next Beta.

Since you have some understanding of DeepViolet, I'm interested in your thoughts on how I could improve the project features and make it more useful to everyone.  If you don't have any immediate thoughts it's ok.  Either way, I appreciate your interest in the project.

Well, the ultimate goal would be to provide a tool with the same capabilities as Qualys SSL Labs SSL Server Test. I'd leave the overall rating and evaluation to the user, but provide features like a heartbleed check and so on. I came across DeepViolet because it's written in Java and Apache licensed, so it was suitable for integrating it in a larger-scale enterprise project. Personally, I wouldn't spend any time on user interfaces (or split them to separate projects only accessing the API jar) but that's up to you. All other features from the feature map seem reasonable to me.

Qualys labs is my inspiration.  Ivan and his team have done a wonderful job building that scanning suite.  There is a lot of investment in that tool so I'm not sure DeepViolet will ever be as good as the Qualys scanning tool.  However, your comment about DV being Java based tool and Apache license is interesting.  The OWASP ZAP project reached out to me about including DV for the same reason, Overhaul HTTPS Info Addon #2532.  They mentioned to me there's not a lot of good Java TLS/SSL tools.  Hard to say when/if ZAP integration will happen but if so perhaps it could simulate some interest on this project - exciting stuff.  Once again, thanks for your interest and suggestions.  ;o)

I'm going to call this issue closed.


Sample Scene: Add SurfaceMagnetismSpatialAwarenessExample to MRTK3

MRTK2 Scene Name
SurfaceMagnetismSpatialAwarenessExample
Overview
This scene demonstrates use of the Surface Magnetism Solver with Spatial Awareness. Using these two, you can make an object snap to surface and follow the pointer. In this example scene, the plane is following the end point of the hand ray while alinging with the surface normal.
More Context
Uses SolverHandler and Surface Magnetism

Done


feat: start working on yaml support

Summary
first step in issue #2365
This PR has the grammar and all the required steps to get codegen to run (the generated files are also in this PT). I made this PR so other contributors don't have to do the same thing than I did.
Please leave your suggestions and opinions on the very simple grammar I did so far.
Test Plan
Currently nothing shows that my implementation is actually correct.

@defnot001 can we make the PR ready and merge it?
It's ok if there's still nothing, but having the crates in place will unblock everyone

@defnot001 I just pushed a couple of commits to fix the CI failure. I think the PR is ready to be merged.

@defnot001 I think you have to run just f and you should be good with CI

@defnot001 I think you have to run just f and you should be good with CI

perfect, just did that thanks :)


Refactor: Change 3rd party imports to not mask ImportErrors

We currently have a pattern of imparting from optional 3rd party libraries like this:
try:
  from some_library import thing
except ImportError:
  raise MissingDependencyException(<some reason>)

this however masks legitimate import errors that can arise when e.g. an incompatible version was installed which doesn't make the imported name available where we expect it.
Instead, we should employ a pattern like this to ensure we only catch the case where the library is not installed:
try:
  import some_library
except: ImportError:
  raise MissingDependencyException(<some reason>)

from some_library import thing

This has the side benefit of not causing issues with intersphinx :wink:

doesn't make the imported name available where we expect it.

how would you then handle this case?
It seems to me to be an unnecessary refactor. As for intersphinx issues - how is that related?

how would you then handle this case?

Not? This is not a missing dependency. This is just a bug on our side.
Let's say there's a version of a package where
from library import thing

is correct, and we build on that, but in a different version it changed to
from library.module import thing

Using our current style, the user would get a MissingDependencyException, telling them "library" isn't installed. Which is not the case.
If we do
try:
  import library
except ImportError:
  raise MissingDependencyException(<some reason>)

we will only catch the exception when library isn't installed. All other import errors are uncaught.

As for intersphinx issues - how is that related?

It is related because in some cases, intersphinx does not pick up on the imports within a try block correctly.

Using our current style, the user would get a MissingDependencyException, telling them "library" isn't installed. Which is not the case.

ok


[PE-D][Tester C] Cluttered Command Summary

There is probably some issues with alignment in the UG markdown, causing part to also be misaligned.

Labels: severity.High type.DocumentationBug
original: LicongHuang/ped#6

Duplicate of #115


Video playback refreshing every 30 seconds

When playing a video from a creator's tab (not the Home tab), the video will refresh every 30 seconds. It resumes from where it left off, but is met with a black screen and a loading indicator for half a second. This is not good for user experience of watching a long video where every 30 seconds it is interrupted.
This affects version 1.0.5.

Possible cause: https://github.com/Jman012/Wasserflug-tvOS/commit/7d80703afb30939ef33e8302ea22595c1687b12f#diff-563ce2de4c5989fb92bfab1315c7c9365d8b2d22449e066b52a8a570663f42f8R122
That, or this commented-out code means it was never working: https://github.com/Jman012/Wasserflug-tvOS/commit/da3521c7b1c7ffbddee7ff0412fc9dd0dc2eb707#diff-563ce2de4c5989fb92bfab1315c7c9365d8b2d22449e066b52a8a570663f42f8L79
I seem to remember having problems with getting the timer to invalidate on the view model correctly. The root cause is that the timer runs every 30 seconds which does a small update to the CreatorContentView (the Livestream button's appearance), which causes a view update that also happens to refresh the view for the video player. I think that's because the video player always updates the AVPlayer/AVPlayerItem on a SwiftUI update invocation. Last time I tried to solve this, I tried to stop the livestream 30s update when watching a video. Perhaps I should see about making the video player update smarter and not update the AVPlayerItem when it isn't needed.

This should stop happening now with 1.0.6. Will need to check that livestreams aren't affected.


Allow different hosts to have different interface prefixes.

This is allowed for mixed OpenStack / Docker interop.

I'm testing a mixed OpenStack plus Docker demo - and it exposed some over-restrictive firewalling that I have loosened.

Sorry - hold off on merge wait. UTs are clean, but manual test is showing problems.

Sure - made one comment.  Ping me when it's ready.


Fix examples

Fix the examples (without the "override" option it will constantly regenerate the first example)

[x] Change in CHANGELOG.md described

Thank you for the PR - and sorry that I did not see it earlier.
Note that development will continue at https://github.com/latextemplates/generator-latex-template, which will (hopefully soon) be used to generate the .tex files in this repository. The main reason is that I want to establish a "platform" for sharing knowledge between templates (e.g., seminar thesis, master thesis, phd thesis)


ESP-DL tutorial/tvm_example No module named 'tvm.relay.op.contrib.esp' (IDFGH-12113)

Answers checklist.

[X] I have read the documentation ESP-IDF Programming Guide and the issue is not addressed there.
[X] I have updated my IDF branch (master or release) to the latest version and checked that the issue is present there.
[X] I have searched the issue tracker for a similar issue and not found a similar issue.

IDF version.
5.0
Operating System used.
Linux
How did you build your project?
Command line with Make
If you are using Windows, please specify command line type.
None
What is the expected behavior?
successful build
What is the actual behavior?
esp-dl/tutorial/tvm_example$ . ./script.sh
Collecting tensor data and making histogram ...
Finding optimal threshold for each tensor using entropy algorithm ...
Number of tensors : 25
Number of histogram bins : 128 (The number may increase depends on the data it collects)
Number of quantized bins : 128
WARNING:root:Please use QuantFormat.QDQ for activation type QInt8 and weight type QInt8. Or it will lead to bad performance on x64.
Traceback (most recent call last):
File "../../tools/tvm/export_onnx_model.py", line 11, in
from tvm.relay.op.contrib.esp import preprocess_onnx_for_esp, evaluate_onnx_for_esp
ModuleNotFoundError: No module named 'tvm.relay.op.contrib.esp'
Steps to reproduce.
cd esp-dl/tutorial/tvm_example
. ./script.sh
Build or installation Logs.
esp-dl/tutorial/tvm_example$ . ./script.sh
Collecting tensor data and making histogram ...
Finding optimal threshold for each tensor using entropy algorithm ...
Number of tensors : 25
Number of histogram bins : 128 (The number may increase depends on the data it collects)
Number of quantized bins : 128
WARNING:root:Please use QuantFormat.QDQ for activation type QInt8 and weight type QInt8. Or it will lead to bad performance on x64.
Traceback (most recent call last):
  File "../../tools/tvm/export_onnx_model.py", line 11, in <module>
    from tvm.relay.op.contrib.esp import preprocess_onnx_for_esp, evaluate_onnx_for_esp
ModuleNotFoundError: No module named 'tvm.relay.op.contrib.esp'

More Information.
Also tried on Mac Intel, M1 and M2 and Windows 11

Working on Linux now, but not the other platforms.
the downloads.sh only seems to get libtvm*.so files for Linux but not libtvm*.dylib files for the Mac


GC does not collect DependencyObjects

Describe the bug
GC does not collect DependencyObjects:
App2.zip
    public sealed partial class MainWindow : Window {
        public MainWindow() {
            this.InitializeComponent();
            refObj = new WeakReference(new MyDependencyObject());
        }
        WeakReference refObj;

        private void myButton_Click(object sender, RoutedEventArgs e) {
            GC.Collect();
            GC.GetTotalMemory(true);
            GC.Collect();
            myButton.Content = refObj.IsAlive.ToString(); //Always TRUE
        }
    }

Steps to reproduce the bug

Steps to reproduce the behavior:

Run the attached sample
Click on the 'Click Me' button

Expected behavior
The Button caption should be 'False'
Version Info

NuGet package version:
[WinUI 3 - Project Reunion 0.5 Preview: 0.5.0-prerelease]

Windows app type:

UWP
Win32

Yes

Windows 10 version
Saw the problem?

Insider Build (xxxxx)

October 2020 Update (19042)
Yes

May 2020 Update (19041)

November 2019 Update (18363)

May 2019 Update (18362)

October 2018 Update (17763)

April 2018 Update (17134)

Fall Creators Update (16299)

Creators Update (15063)

Device form factor
Saw the problem?

Desktop
Yes

Xbox

Surface Hub

IoT

@Scottj1s I think there is a known issue with cswinrt memory leaks, is this that?


How to make this code base support mmrotate model? I want to prune rotated object detection model.

Checklist

I have searched related issues but cannot get the expected help.
I have read related documents and don't know what to do.

Describe the question you meet
  I want to prune rotated object detection model. The current newest version of mmrazor doesn't support this kind of task. I want to know how to make the mmrazor support mmrotate task. Is there any instruction for this kind modify? For example, if I want to use AutoSlim method to prune oriented R-CNN model, then what should I do?

Post related information

The output of pip list | grep "mmcv\|mmrazor\|^torch"
[here]
Your config file if you modified it or created a new one.

mmcv-full            1.6.0
mmrazor              0.3.1
mmrotate             0.3.2

Your train log file if you meet the problem during training.
[here]
Other code you modified in the mmrazor folder.
[here]

Sorry for the late reply. There is no mmrotate model in current mmrazor. But mmrotate is accessible in temporary mmrazor library. We try to provide a guidance for using autoslim to prune oriented R-CNN:

clone supportive libraries and checkout to corresponding branch:

mmcv-full        2.x
mmrotate         dev-1.x
mmrazor          dev-1.x
mmdet            dev-3.x

Since _base_/config/model is not provided in mmrotate, please directly import

mmrotate::oriented_rcnn/oriented-rcnn-le90_r50_fpn_1x_dota.py

Please contact us if any problem exist. Thanks.

Sorry for the late reply. There is no mmrotate model in current mmrazor. But mmrotate is accessible in temporary mmrazor library. We try to provide a guidance for using autoslim to prune oriented R-CNN:

clone support libraries and checkout to corresponding branch:

mmcv-full        2.x
mmrotate         dev-1.x
mmrazor          dev-1.x
mmdet            dev-3.x

Since _base_/config/model is not provided in mmrotate, please directly import

mmrotate::oriented_rcnn/oriented-rcnn-le90_r50_fpn_1x_dota.py

Please contact us if any problem exist. Thanks.
Thank you very much for your reply. I will try to implement this function under your instruction.

Sorry for the late reply. There is no mmrotate model in current mmrazor. But mmrotate is accessible in temporary mmrazor library. We try to provide a guidance for using autoslim to prune oriented R-CNN:

clone support libraries and checkout to corresponding branch:

mmcv-full        2.x
mmrotate         dev-1.x
mmrazor          dev-1.x
mmdet            dev-3.x

Since _base_/config/model is not provided in mmrotate, please directly import

mmrotate::oriented_rcnn/oriented-rcnn-le90_r50_fpn_1x_dota.py

Please contact us if any problem exist. Thanks.

Is it possible that make the openmmlab1.0 to support pruning mmrotate model? Because I found that there are some problems with the versions of different code bases in openmmlab2.0. Are there some instructions to help me to make the mmrazor to support pruning mmrotate model under these code bases with the versions as follows:
mmcv-full      1.6.0
mmrotate       0.3.2
mmrazor         0.3.1
mmdet            2.25.2
mmdeploy      0.9.0

It's hard to support mmrotate models for openmmlab1.0.
Now, we released a branch named exp_pruning based on openmmlab 2.0. It supports pruning mmrotate models. Welcome to use this branch. And exp_pruning will be merged into dev-1.x in the future.

It's hard to support mmrotate models for openmmlab1.0.
Now, we released a branch named exp_pruning based on openmmlab 2.0. It supports pruning mmrotate models. Welcome to use this branch. And exp_pruning will be merged into dev-1.x in the future.

Thanks for replying. I am trying to use this branch to pruning mmrotate models.

Sorry for the late reply. There is no mmrotate model in current mmrazor. But mmrotate is accessible in temporary mmrazor library. We try to provide a guidance for using autoslim to prune oriented R-CNN:

clone support libraries and checkout to corresponding branch:

mmcv-full        2.x
mmrotate         dev-1.x
mmrazor          dev-1.x
mmdet            dev-3.x

Since _base_/config/model is not provided in mmrotate, please directly import

mmrotate::oriented_rcnn/oriented-rcnn-le90_r50_fpn_1x_dota.py

Please contact us if any problem exist. Thanks.
Thank you very much for your reply. I will try to implement this function under your instruction.

Hello, I have installed mmrazor and mmrotate according to the above requirements. I want to use mmrazor to perform knowledge distillation on the model in mmroate, but an error is reported. The following is my error report.
02/28 20:24:13 - mmengine - WARNING - The "visualizer" registry in mmrotate did not set import location. Fallback to call mmrotate.utils.register_all_modulesinstead. 02/28 20:24:13 - mmengine - WARNING - The "vis_backend" registry in mmrotate did not set import location. Fallback to callmmrotate.utils.register_all_modulesinstead. 02/28 20:24:13 - mmengine - WARNING - The "model" registry in mmrazor did not set import location. Fallback to callmmrazor.utils.register_all_modules` instead.
Traceback (most recent call last):
File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/registry/build_functions.py", line 121, in build_from_cfg
obj = obj_cls(**args)  # type: ignore
File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmrazor/models/algorithms/distill/configurable/single_teacher_distill.py", line 46, in init
super().init(**kwargs)
File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmrazor/models/algorithms/base.py", line 64, in init
architecture = MODELS.build(architecture)
File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/registry/registry.py", line 521, in build
return self.build_func(cfg, *args, **kwargs, registry=self)
File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmrazor/registry/registry.py", line 43, in build_razor_model_from_cfg
model = get_model(**cfg)  # type: ignore
File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/hub/hub.py", line 77, in get_model
cfg = get_config(cfg_path, pretrained)
File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/hub/hub.py", line 34, in get_config
package, cfg_path = _get_package_and_cfg_path(cfg_path)
File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/config/utils.py", line 124, in _get_package_and_cfg_path
f'mmengine does not support to load {package} config.')
AssertionError: mmengine does not support to load mmroate config.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "tools/train.py", line 66, in
main()
File "tools/train.py", line 59, in main
runner = Runner.from_cfg(cfg)
File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/runner/runner.py", line 458, in from_cfg
cfg=cfg,
File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/runner/runner.py", line 398, in init
self.model = self.build_model(model)
File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/runner/runner.py", line 800, in build_model
model = MODELS.build(model)
File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/registry/registry.py", line 521, in build
return self.build_func(cfg, *args, **kwargs, registry=self)
File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/registry/build_functions.py", line 240, in build_model_from_cfg
return build_from_cfg(cfg, registry, default_args)
File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/registry/build_functions.py", line 136, in build_from_cfg
f'class {obj_cls.__name__} in '  # type: ignore
AssertionError: class FpnTeacherDistill in mmrazor/models/algorithms/distill/configurable/fpn_teacher_distill.py: mmengine does not support to load mmroate config.
`

@the-bigE It may be a  spell error which is 'mmrotate', rather than 'mmroate'.

Sorry for the late reply. There is no mmrotate model in current mmrazor. But mmrotate is accessible in temporary mmrazor library. We try to provide a guidance for using autoslim to prune oriented R-CNN:

clone support libraries and checkout to corresponding branch:

mmcv-full        2.x
mmrotate         dev-1.x
mmrazor          dev-1.x
mmdet            dev-3.x

Since _base_/config/model is not provided in mmrotate, please directly import

mmrotate::oriented_rcnn/oriented-rcnn-le90_r50_fpn_1x_dota.py

Please contact us if any problem exist. Thanks.
Thank you very much for your reply. I will try to implement this function under your instruction.

Hello, I have installed mmrazor and mmrotate according to the above requirements. I want to use mmrazor to perform knowledge distillation on the model in mmroate, but an error is reported. The following is my error report. 02/28 20:24:13 - mmengine - WARNING - The "visualizer" registry in mmrotate did not set import location. Fallback to call mmrotate.utils.register_all_modulesinstead. 02/28 20:24:13 - mmengine - WARNING - The "vis_backend" registry in mmrotate did not set import location. Fallback to callmmrotate.utils.register_all_modulesinstead. 02/28 20:24:13 - mmengine - WARNING - The "model" registry in mmrazor did not set import location. Fallback to callmmrazor.utils.register_all_modules` instead. Traceback (most recent call last): File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/registry/build_functions.py", line 121, in build_from_cfg obj = obj_cls(**args) # type: ignore File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmrazor/models/algorithms/distill/configurable/single_teacher_distill.py", line 46, in init super().init(**kwargs) File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmrazor/models/algorithms/base.py", line 64, in init architecture = MODELS.build(architecture) File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/registry/registry.py", line 521, in build return self.build_func(cfg, *args, **kwargs, registry=self) File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmrazor/registry/registry.py", line 43, in build_razor_model_from_cfg model = get_model(**cfg) # type: ignore File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/hub/hub.py", line 77, in get_model cfg = get_config(cfg_path, pretrained) File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/hub/hub.py", line 34, in get_config package, cfg_path = _get_package_and_cfg_path(cfg_path) File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/config/utils.py", line 124, in _get_package_and_cfg_path f'mmengine does not support to load {package} config.') AssertionError: mmengine does not support to load mmroate config.
During handling of the above exception, another exception occurred:
Traceback (most recent call last): File "tools/train.py", line 66, in main() File "tools/train.py", line 59, in main runner = Runner.from_cfg(cfg) File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/runner/runner.py", line 458, in from_cfg cfg=cfg, File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/runner/runner.py", line 398, in init self.model = self.build_model(model) File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/runner/runner.py", line 800, in build_model model = MODELS.build(model) File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/registry/registry.py", line 521, in build return self.build_func(cfg, *args, **kwargs, registry=self) File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/registry/build_functions.py", line 240, in build_model_from_cfg return build_from_cfg(cfg, registry, default_args) File "/home/juzh/softerware/anaconda3/envs/mmlab2/lib/python3.7/site-packages/mmengine/registry/build_functions.py", line 136, in build_from_cfg f'class {obj_cls.__name__} in ' # type: ignore AssertionError: class FpnTeacherDistill in mmrazor/models/algorithms/distill/configurable/fpn_teacher_distill.py: mmengine does not support to load mmroate config. `

Did you solve the problem?

It's hard to support mmrotate models for openmmlab1.0.
Now, we released a branch named exp_pruning based on openmmlab 2.0. It supports pruning mmrotate models. Welcome to use this branch. And exp_pruning will be merged into dev-1.x in the future.

Thank you very much for your contributions in integrating mmrotate and mmrazor. Where can I find the dev-1.x branch of mmrazor? Or has the current main branch already been updated to work with mmrotate? I noticed that mmrazor requires mmcv>=2.0.0, while mmrotate requires mmdet/<3.0.0, mmcv-full>=1.3.17,/<1.8.0.


Possible Bug

Are perks that add extra ammo supposed to apply to crossbows? Because so far none of them do. Be a bit weird to have perks adding ammo to throwing and bows but not crossbows.

Are perks that add extra ammo supposed to apply to crossbows? Because so far none of them do. Be a bit weird to have perks adding ammo to throwing and bows but not crossbows.

yeah i do notice it,i think crossbow still overpower because headshot will instant kill anything at close range,with crossbow perk i can reload on horse,pretty op right?

We might have a PR that addresses this, not sure...

Extra ammo perks intentionally don't apply to crossbows. In the Riding and Athletics tree, perks are explicitly named "Spare Arrows" and "Extra Arrows" and add +X arrows, not bolts.

Is this good to close?


How to re sync a doc after it was purged without updating it?

Need to update.
From next time, please post any questions to https://forums.couchbase.com/. more engineers are observing forums.


Rancher uses independent vsphere chart

A new vSphere chart was created in this ticket: https://github.com/rancher/rancher/issues/35702
Now Rancher needs to actually use it instead of the older chart.

@PennyScissors Could you please fill out the QA template to indicate what needs to be validated?

@samkulkarni20 With this change, can the team test an upgrade path? Someone deployed with the older versions in v2.5.0 and that the cluster that have the old vsphere charts deployed on it can be upgraded to the new version of the vsphere chart?

Yes @deniseschannon . I'll have QAs validate the upgrade scenario.

@samkulkarni20 Could you please fill out the QA template @deniseschannon mentioned above?

Issue: The vSphere CPI, CSI were configured as local charts in rancher/charts repo. This issue updates it to use the newly created vsphere-charts as upstream repo for the same, instead of building them as local charts. This helps in having central vSphere CPI CSI charts for both RKE1 & RKE2.
This issue & the corresponding PR only updates the upstream location for building the vSphere charts & keeps the underlying CPI, CSI versions same as before. Hence the QA tests should cover the following scenarios for this issue:
Verify that vSphere CPI & CSI charts install & work properly on cluster created using Rancher v2.6-head in below scenarios:

Fresh install of CPI chart version 100.1.1+up1.0.1, CSI chart version 100.1.1+up2.3.0-rancher1
Upgrade CPI chart from 100.1.0+up1.0.100 to 100.1.1+up1.0.1 version & CSI chart from 100.1.0+up2.3.0 to 100.1.1+up2.3.0-rancher1 version

Use rancher/charts repo dev-v2.6 branch for testing.

@samkulkarni20 FYI, once PRs https://github.com/rancher/charts/pull/1764, and https://github.com/rancher/charts/pull/1763 are merged, the charts in your comment would be replaced by the new upgraded charts.

To Validate:
Fresh Install:
Deploy RKE1 with k8s 1.22 with vsphere cloud provider
Upgrade Use Case:
Deploy Rancher 2.6.3, deploy RKE1 with k8s 1.21 with external cloud provider. Deploy vsphere charts through apps & marketplace, add a deployment that uses volumes.
Upgrade to 2.6.4-rcX, upgrade to k8s 1.22. Upgrade vsphere charts through apps & marketplace. Confirm that deployments are still working with volumes.

This would be captured during the validation that helm yes would be completing per @rosskirkpat

Tested on a vSphere 7.0.3 environment
Fresh install on v2.6.5-rc8

Created a cluster w/ cloud provider set to external
Installed out of tree cloud provider with

rancher-vsphere-cpi 100.3.0+up1.2.1
rancher-vsphere-csi 100.3.0+up2.5.1

Created a pvc and workload using the PVC
Everything working as expected

Upgrade from Rancher v2.6.3 -> v2.6.5-rc8

Created a cluster w/ cloud provider set to external
Installed out of tree cloud provider with

rancher-vsphere-cpi 100.1.0+up1.0.100
rancher-vsphere-csi 100.1.0+up2.3.0

Created a pvc and a workload using the PVC
Upgraded Rancher
Upgrade cpi -> 100.3.0+up1.2.1
Upgrade csi -> 100.3.0+up2.5.1
Existing workloads with volumes function
Provisioned a new workload with a new PVC and that functions as well


[Clarification] Remove #reader in setup chunk

** What needs to be clarified **
No need to keep removing the reader from data setup every time, just do it in setup chunk at the same time we drop chapters past the twelfth.
** Page(s) which need to be clarified (Optional) **
https://syvwlch.github.io/Data-Ignota/viz/2022-10-11-who-talks-to-whom/

Closed by #54


No Rust installation detected. You can download official Rust installer

I've installed visual rust 0.1.2, I have rustc.exe and some other files installed here: C:\Users\steve.cargo\bin
But when I try to build rust project in msvc 2015 I get this error:
C:\Program Files (x86)\MSBuild\VisualRust\VisualRust.Rust.targets(53,5): error : No Rust installation detected. You can download official Rust installer from https://www.rust-lang.org/downloads.html
How is the installation detected? How can I fix this?

Here is where installation paths that get checked are enumerated:
https://github.com/PistonDevelopers/VisualRust/blob/f005c247f0f30aa0d84fab655d192743de53bba8/src/VisualRust.Shared/Environment.cs#L84
Might just need to set CARGO_HOME appropriately.

Same for me with rust 1.20 on Windows 10 64bit Visual Studio 2015.
I have set CARGO_HOME to C:\Users\dzmitry_lahoda\.cargo, but still have and issues.

Ahh, sorry, I've just noticed that the logic is different in Visual Rust 1.2.0 - it doesn't support CARGO_HOME:  https://github.com/PistonDevelopers/VisualRust/blob/0.1.2/VisualRust.Shared/Environment.cs
Setting MULTIRUST_HOME to your .cargo path might work, or there are some earlier workarounds with registry keys:  https://github.com/PistonDevelopers/VisualRust/issues/263 .  Alternatively, grab the trunk version from https://ci.appveyor.com/project/vosen/visualrust/build/artifacts (or follow the Readme's appveyor links).

Latest installation for 2015
9/16/2017 4:49:56 PM - Microsoft VSIX Installer
9/16/2017 4:49:56 PM - -------------------------------------------
9/16/2017 4:49:56 PM - vsixinstaller.exe version:
9/16/2017 4:49:56 PM - 15.0.26209.1 built by: D15REL
9/16/2017 4:49:56 PM - -------------------------------------------
9/16/2017 4:49:56 PM - Command line parameters:
9/16/2017 4:49:56 PM - C:\Program Files (x86)\Microsoft Visual Studio\Installer\resources\app\ServiceHub\Services\Microsoft.VisualStudio.Setup.Service\VSIXInstaller.exe,/admin,/logFile:C:\Users\DZMITR~1\AppData\Local\Temp\Visual_Rust_for_Visual_Studio_2015_20170916164815_002_VSIXBootstrapper.log,C:\ProgramData\Package Cache\9864EE5369359DB622D0234B6C6B7640B949140C\VisualRust.vsix
9/16/2017 4:49:56 PM - -------------------------------------------
9/16/2017 4:49:56 PM - Microsoft VSIX Installer
9/16/2017 4:49:56 PM - -------------------------------------------
9/16/2017 4:49:58 PM - Initializing Install...
9/16/2017 4:49:59 PM - Microsoft.VisualStudio.ExtensionManager.InvalidExtensionPackageException: The file is not a valid VSIX package.
   at Microsoft.VisualStudio.ExtensionManager.InstallableExtensionImpl.ReadVSIXManifestFromPackage(Stream stream, CultureInfo preferredCulture)
   at Microsoft.VisualStudio.ExtensionManager.InstallableExtensionImpl..ctor(String path, CultureInfo preferredCulture)
   at Microsoft.VisualStudio.ExtensionManager.ExtensionEngineImpl.CreateInstallableExtension(String extensionPath, CultureInfo preferredCulture)
   at Microsoft.VisualStudio.ExtensionManager.ExtensionEngineImpl.CreateInstallableExtension(String extensionPath)
   at VSIXInstaller.App.GetInstallableData(String vsixPath, Boolean isRepairSupported, IEnumerable`1& skuData)
   at VSIXInstaller.App.Initialize(Boolean isRepairSupported)
   at VSIXInstaller.App.Initialize()
   at System.Threading.Tasks.Task`1.InnerInvoke()
   at System.Threading.Tasks.Task.Execute()

I have installed VS 2017 Pro and latest plugin. No install errors, but no templates in New Project.

MULTIRUST_HOME seems deprecated.

There's an unmerged pull request to fix the templates and other issues:  https://github.com/PistonDevelopers/VisualRust/pull/286

Any news on this Issue, I'm having the same problem, even after setting the CARGO_HOME
Need any help fixing this?