Issue with SD 2.1: size mismatch for input_blocks.1.1.proj_in.weight

After upgrading to the latest ControlNet I run into a size mismatch exception. Any ideas what could be causing it?
Control net works fine with SD 1.5
Here's the error log:
Loading model: control_v11p_sd21_depth [2722c7d7]
Loaded state_dict from [D:\stable-diffusion-webui\extensions\sd-webui-controlnet\models\control_v11p_sd21_depth.safetensors]
Loading config: D:\stable-diffusion-webui\extensions\sd-webui-controlnet\models\control_v11p_sd21_depth.yaml
Error running process: D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\controlnet.py
Traceback (most recent call last):
File "D:\stable-diffusion-webui\modules\scripts.py", line 417, in process
script.process(p, *script_args)
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\controlnet.py", line 959, in process
model_net = self.load_control_model(p, unet, unit.model, unit.low_vram)
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\controlnet.py", line 645, in load_control_model
model_net = self.build_control_model(p, unet, model, lowvram)
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\controlnet.py", line 713, in build_control_model
network = network_module(
File "D:\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\cldm.py", line 107, in init
self.control_model.load_state_dict(state_dict)
File "D:\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1671, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for ControlNet:
size mismatch for input_blocks.1.1.proj_in.weight: copying a param with shape torch.Size([320, 320]) from checkpoint, the shape in current model is torch.Size([320, 320, 1, 1]).
size mismatch for input_blocks.1.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 1024]) from checkpoint, the shape in current model is torch.Size([320, 768]).
size mismatch for input_blocks.1.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 1024]) from checkpoint, the shape in current model is torch.Size([320, 768]).
size mismatch for input_blocks.1.1.proj_out.weight: copying a param with shape torch.Size([320, 320]) from checkpoint, the shape in current model is torch.Size([320, 320, 1, 1]).
size mismatch for input_blocks.2.1.proj_in.weight: copying a param with shape torch.Size([320, 320]) from checkpoint, the shape in current model is torch.Size([320, 320, 1, 1]).
size mismatch for input_blocks.2.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 1024]) from checkpoint, the shape in current model is torch.Size([320, 768]).
size mismatch for input_blocks.2.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 1024]) from checkpoint, the shape in current model is torch.Size([320, 768]).
size mismatch for input_blocks.2.1.proj_out.weight: copying a param with shape torch.Size([320, 320]) from checkpoint, the shape in current model is torch.Size([320, 320, 1, 1]).
....

the same errors
I try changed yaml file from v15 to v21,still problems.and I reintsall controlnet,even reintsall SD. the issue still in

the same errors
crazy,

did you find out what the issue is? is it just controlnet 1.1 not supporting SD 2.1 yet?

Hello. Check this, worked for me:
https://huggingface.co/thibaud/controlnet-sd21/discussions/37#644aa2b8cb45734dfd439fa3

你知道问题出在哪里了吗？只是 controlnet 1.1 还不支持 SD 2.1 吗？

你好。检查这个，对我有用： https://huggingface.co/thibaud/controlnet-sd21/discussions/37#644aa2b8cb45734dfd439fa3

thanks


Demo video

If you are not familiar with video editing, you should consult Roberto. He has rich experience of video editing for academic publications. This consultation shold save some time.

start of may

JFYI:
@robertmora will be away next week. It's better to schedule some briefing meeting for video editing from him He's familiar with academic video editing well.

Meeting with the team on Friday morning for discussing how to arrange this.

@robertmora, I know you must be extremely busy before the next week bisiness trip. But this meeting would save a lot time to create a demo video, really appreciated!


Trying to run speaker recognition in C#

Hi, I'm trying out Speaker recognition, but it's throwing an error. With the help of debugger I realized there is some error on line 143 (using (var audioInput = AudioConfig.FromWavFileInput(trainingFile)))
Error thrown -> "AudioProcessingOptions = 'audioInput.AudioProcessingOptions' threw an exception of type 'System.ApplicationException'".
I'm following these steps and the only change I made in the code above are subscription key and region. Thanks in advance for help

Hi @Shubham7054, this is Darren from the Speech SDK team. Thank you for posting this question. Which operating system are you using? What version of Speech SDK are you using? If possible, please use latest version (1.19) and also provide as with SDK logs (see here).
Thanks, Darren

@Shubham7054 - If the WAV file is not present I can repro this issue. Please be sure to set paths to each audio file. You can use the WAV files in this directory of the samples repository: sampledata/audiofiles. I hope this helps!

Thank you @eric-urban for checking. I will close this issue, but @Shubham7054 feel free comment here if Eric's suggestion did not solve your problem. If that's the case I will re-open the issue.
Darren

Hi, thanks for replying. In this code the wav files listed are myVoiceIsMyPassportVerifyMe01.wav, myVoiceIsMyPassportVerifyMe02.wav, myVoiceIsMyPassportVerifyMe03.wav (line 134-136) and if we look closely, program.cs file and these wav files are in same directory. I even tried to play these audio from program.cs using this and it's playing, unable to fix this issue yet

@Shubham7054 - Double checking, were you also granted access to the speaker recognition preview? https://docs.microsoft.com/en-us/legal/cognitive-services/speech-service/speaker-recognition/limited-access-speaker-recognition

@eric-urban I followed these steps to try the speech service and I didn't came across this documentation and the form in it. Am I supposed to fill this form as well? Was curious as I have subscription key and region and that's all required according to this

@Shubham7054 - Yes applying for access is required currently, so we’ll need to update the sample instructions. Good catch! Thanks

Closing this issue, as we have an internal work item for updating the sample code with the proper note as per the above. Thanks all!


Update Pipeline to macOS 12

Description of Change
This PR updates the CI Pipeline to leverage macOS 12
Additional information
This also updates the sample app to incorporate the [ICommand] attribute.

/azp run


Typo:  "Trueand False" -> " True and False."

Primary Key section contains following sentence:
Indicates whether the column is a primary key. Possible values are Trueand False.
at the end: "Trueand False" but should be "True and False"
:)
Regards
Marek

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

ID: 2d42fb53-5f58-ed2e-f91b-cecf4c9fecee
Version Independent ID: c602a50c-56cb-2252-151d-09a0a9a6bb8a
Content: Column Properties (General Page) - SQL Server
Content Source: docs/relational-databases/tables/column-properties-general-page.md
Product: sql
Technology: table-view-index
GitHub Login: @stevestein
Microsoft Alias: sstein

@NeuroXiq -- Marek, thank you again for your keen eye.  I am updating this article.


No money received message

On the newer versions of sponge (3002), the player who receives money via /pay doesn't get any message that they got paid.

I'll look at this when I have time.

Yes, this problem is painful

A fix soon would be mucho appreciated

I should have time this weekend


Server worlds on fire - idle server world ticking is wrong

What the issue looks like:
Most server worlds eventually have a lot of fire almost everywhere near spawn, caused by lightnings.
The technical issue:
Weather ticking uses cube ticket system, instead of being based only on forge forced chunks and player loaded areas.

Should be fixed now.


Enabling the mouse by default was a regression

Steps to reproduce
Vim mouse is enabled by default for all xterms in defaults.vim.
When mouse mode is active, vim takes control of the mouse. As a side effect, copying buffers in most GUI terminals ceases to work. (Konsole, anything xterm based really, and iirc urxvt too)
Of course, anyone who does use mouse mode and wants the clipboard to still work while using a mouse can just recompile vim with +clipboard, apply some configuration, and carry on.
Or press shift to toggle control back to the terminal before clicking their mouse. I only discovered this when I found the original regression commit: https://github.com/vim/vim/commit/8c08b5b569e2a9e9f63dea514591ecfa2d3bb392
Note that most of the comments are critical of the change, but it has remained all these years.
I think this is a mistake, and I'm voicing my concern here.  I'll get on by fixing vim with set mouse-=a in all my dotfiles. Fine. But I'd bet fewer people are adopting vim after this commit than would otherwise.
I recommend reading the full comment thread on the original commit.
The fact that it ships with configuration to enable the mouse without the clipboard feature feels like a bug.
Expected behaviour
New users to vim should not discover that it degrades their terminal by preventing copy to buffer.
Version of Vim
9.0.1506
Environment
OS: Archlinux
Terminal: Konsole
xterm-256color
bash
Logs and stack traces
No response

The fact that it ships with configuration to enable the mouse without the clipboard feature feels like a bug.
I disagree. In the Linux console (Ctrl-Alt-F2 etc.) there is no connection to X11 therefore no clipboard; but when the gpm package is installed the mouse is available and in that case I expect configure and make to produce a Vim with +mouse_gpm and Vim to use the mouse at runtime.

I am afraid it's way too late to discuss this behaviour now. Also, this is a duplicate of #2841 which turned out to be endless discussion without a clear resolution.
I am closing this as duplicate.


(embargoed) @giacecco's blog post on inference

See https://docs.google.com/a/thwaitescommunications.co.uk/spreadsheets/d/1uVfADhTnkAptWCvJFoAXNoiRHK1QFMYSr9KgZaJX-_Q/edit?usp=sharing for target publishing date. @peterkwells to pull the trigger?

Hi @peterkwells I've done the latest changes you suggested and you can merge this when you want to publish.


Feature/nav param

Robot is now more responsive and use the sideway motion to reorient in the environment.
Also the robot can now cross doorways and navigate the corridor autonomously.

@gregoirefra peux tu chequer cette PR la.


Do not iterate vpiAllModule, vpiAllPackage anymore

As far as synthesis subset is concerned, the plugin should not iterate vpiAllModule, vpiAllPackage anymore.
All the information necessary to synthesize the design is in vpiTopModule, vpiTopPackage.
This is the root cause of the issue and attempted fix here:
https://github.com/chipsalliance/UHDM/pull/1019
This is not the right fix. The right fix is to iterate the vpiTopModule, vpiTopPackage.

Addendum: Surelog also now filters out the vpiAllModules that are not used in the design elaboration when -synth option is used, which is the case here.
So I merged the fix https://github.com/chipsalliance/UHDM/pull/1019.
But please consider removing all traversal to vpiAllModule, vpiAllPackage, they should not be needed anymore and will potentially lead to other problems if kept.

Unassigning myself as this is on hold.


Fix 'for' option in state trigger

Description:
Under certain scenarios the state trigger does not properly implement the for option. E.g., if two or more entities are listed, and one changes to the to state, and stays in that state long enough to satisfy the for period, but during that time another entity changes to a different state, the "same state period monitoring" for the first entity will be effectively canceled because it sees the new state of the second entity as being a new state for the first entity, and hence concludes it is no longer the "same state."
Related issue (if applicable): None
Related PR: #24910
Pull request with documentation for home-assistant.io (if applicable): N/A
Example entry for configuration.yaml (if applicable):
automation:
  trigger:
    platform: state
    entity_id: [ENTITY1, ENTITY2]
    to: STATE
    for: PERIOD

Consider this sequence:

ENTITY1 changes to STATE
Before PERIOD expires ENTITY2 changes to a state other than STATE.
PERIOD expires.

What should happen is the trigger should fire with:
trigger.entity_id = ENTITY1
trigger.to_state.state = STATE
trigger.for = PERIOD

However this was not happening. ENTITY1 would have to change to some other state and then back to STATE for the for period to start again.
This fixes it so that it will trigger under these conditions.
Checklist:

[x] The code change is tested and works locally.
[x] Local tests pass with tox. Your PR cannot be merged unless tests pass
[x] There is no commented out code in this PR.
[x] I have followed the development checklist

If the code does not interact with devices:

[x] Tests have been added to verify that the new code works.

Same catch but good catch :D


SW-1573 Support notes in V2 accession create payload

This is needed to set notes when creating an accession in v2 seed management
Tested locally in my UI.

No technical objection to this but I want to make sure we really need it. Just looked through the design again and I believe the API already has enough notes fields. I think it's hard to see because the design uses inconsistent field names (both internally inconsistent and inconsistent with the field list in the PRD) and I based my changes off the PRD.

collectionSiteNotes = "Site Description" (in the create UI), "Direction or Description" (in the edit UI)
notes = "Plant Description" (in the create UI), "Environmental Notes" (in the edit UI)

Once we've settled on the user-facing field names, we can rename the fields in the API. A little reluctant to do it now since there seem to be competing sources of truth for what the names should be.

No technical objection to this but I want to make sure we really need it. Just looked through the design again and I believe the API already has enough notes fields. I think it's hard to see because the design uses inconsistent field names (both internally inconsistent and inconsistent with the field list in the PRD) and I based my changes off the PRD.

collectionSiteNotes = "Site Description" (in the create UI), "Direction or Description" (in the edit UI)
notes = "Plant Description" (in the create UI), "Environmental Notes" (in the edit UI)

Yes, I totally understand. The PRD should be the source of truth, I will go with notes as planned/intended. This is currently not exposed in the create payload - I can update this PR to support notes in the create payload.

@sgrimm looks like all the PRs are failing a type check in create_accession.py script.
create_accessions.py:185: error: List comprehension has incompatible type List[Optional[str]]; expected List[str]

Does the return type need to be List[Optional[str]] instead of Optional[List[Optional[str]]]? Not sure where the Optional[str] comes from - I don't see the code generating that.

PR is out to fix that type check failure. Once that's in, we can rebase this change and checks should pass.


⚠ Bofrost.es has degraded performance

In 5dcc39e, Bofrost.es (https://www.bofrost.es) experienced degraded performance:

HTTP code: 200
Response time: 1732 ms

Resolved: Bofrost.es performance has improved in e879c0e after 6 minutes.


Allow to choose window as source?

I've recently reported a bug in Electron regarding a serious low frame rate using desktopCapturer API: electron/electron#8278
Seems that this project will save my life, but since the app I'm working on needs to be able to choose any open window as a recording source and I did not find anything in the documentation, I wonder if this can be accomplished somehow.
Does this feature exist or are you planing to include it?
Thanks.

It's possible. We would need to find the wanted window, focus it, get its position & size and only record that. According to this it might be possible to record the window directly too. Not something we currently need for Kap, where this is used, but a good pull request would be welcomed.

Great, but unfortunately I'm not very familiar with Swift. Will take a look at the code and see if I can do something.
Btw, I have 2 more questions:

Can I use webm format instead of mp4? Also not sure which codec is being used inside mp4 files.
What about the displayIdoption? Is that intended to work only as a monitor/screen source? If that's the case, how can I detect monitor ID in case there are more than one connected?

Thanks.

Hello?

Lol. Of course, but I have to work and I cannot do much without help. I'm
scratching my head with screen capture thing.
Happy new year!
 See you in the new year
🎉
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/wulkano/aperture.js/issues/16#issuecomment-269630745,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AAcuZs62qlWKoMaTxwbX3DKZtsjplqtxks5rM7asgaJpZM4LVdqx
.

That's a pretty wanted feature ☺ I still need to spend some time thinking and researching about it, but in addition of what @sindresorhus linked, I remember that I read somewhere that we can even capture do things like captureTheWholeScreen().minus(someWindow). 😮 ☺
But yeah, I think this would be very useful – we want to provide something like macOS's Cmd+Shift+4 Space on Kap ☺

To answer your additional questions; macOS assigns the display ID's, we do want to surface them via Aperture at some point though. Regarding capturing in different formats, Aperture simply bridges with AVFoundation. Kap uses ffmpeg to create MP4, GIF and WebM files.
I don't know what you're trying to achieve, but I believe this VS Code recorder uses Aperture to record a single window https://github.com/wk-j/vscode-screen-recorder/blob/f310941d0168001bca8790ab77337aecd7f3c96b/src/recorder.ts

Still not sure if this library can help me.
I'm trying to record desktop and share video stream at the same time. Seems like mp4 streaming is not easy because moov atom headers are included at the end of the file.
By any chance, do you know how to fix that using AVFoundation?
Would need to go with ffmpeg and webm if that doesn't work.
Btw, tried ffmpeg & webm and cpu does not seem to go beyond 100%

This library has a very specific scope and limited feature set for the time being, see https://github.com/wulkano/aperture.js#why. Leaving this issue open for when we circle back to recording specific windows. Thank you!

the new ScreenCaptureKit framework would let us do this.
see https://developer.apple.com/documentation/screencapturekit
I use it in my own app Screegle https://www.appblit.com/screegle
Laurent

https://github.com/nonstrict-hq/RecordKit.Electron does it too.


hospitalrun.io -- domain name is expired

The domain name for http://hospitalrun.io/ is expired, and as a result, all visitors are redirected to the registrar's parked domains page.

Expected behavior:
Actual behavior:
Steps to reproduce:
Screenshots (if applicable):
OS and Browser:

Hey thanks @christophermlne  - I'll follow up with @tangollama

This is 100% my fault. I had it on a long list of things I needed to get to for the project and then missed it.... which is a big fail on my part. Apparently, the domain has been grabbed by someone else who is clearly squatting it. Not sure what to do about. Recommendations are welcome.

I’ll follow up with a domain broker. Shouldn’t be a huge deal.
--
Donald Wasserman
989-859-6392
On Mar 1, 2019, 8:56 PM -0500, Joel Worrall<EMAIL_ADDRESS>wrote:

This is 100% my fault. I had it on a long list of things I needed to get to for the project and then missed it.... which is a big fail on my part. Apparently, the domain has been grabbed by someone else who is clearly squatting it. Not sure what to do about. Recommendations are welcome.
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub, or mute the thread.

Thank you. We have access to funds in the open collective as/if needed.
On Fri, Mar 1, 2019 at 10:09 PM Donald Wasserman<EMAIL_ADDRESS>wrote:

I’ll follow up with a domain broker. Shouldn’t be a huge deal.
--
Donald Wasserman
989-859-6392
On Mar 1, 2019, 8:56 PM -0500, Joel Worrall<EMAIL_ADDRESS>wrote:

This is 100% my fault. I had it on a long list of things I needed to get
to for the project and then missed it.... which is a big fail on my part.
Apparently, the domain has been grabbed by someone else who is clearly
squatting it. Not sure what to do about. Recommendations are welcome.
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub, or mute the thread.

—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/HospitalRun/hospitalrun-frontend/issues/1598#issuecomment-468877045,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AA4t7VCN_RqzBT33Coc7lNYfb84l6f0dks5vSetrgaJpZM4bWwOS
.

--
*Joel Worrall *
@tangollama http://twitter.com/tangollama (c)<PHONE_NUMBER>

It looks like this issue is resolved.


Installing on the Pi 5 (Debain) Doesn't work.

Hello! After i run
sudo apt-get install libglib2.0-dev
sudo apt-get install python3-bluez
python3 -m venv .venv
source .venv/bin/activate
################## PACKAGES ########################
requirement.txt method
python3 -m pip install -r requirements.txt
command method
python3 -m pip install bluepy
python3 -m pip install git+https://github.com/pybluez/pybluez.git#egg=pybluez
################## PACKAGES ########################
deactivate
It prints to the console about some error or something (I couldn't replicate it right now because it worked??) But yeah when i run Wall of flippers it just says [!] Wall of Flippers >> Error: Failed to scan for BLE devices >> Failed to execute management command 'le on' (code: 17, error: Invalid Index). Does anyone know how to fix this? Thanks! (I tried on Ubuntu too and it didn't work sooo yeah)

Forgot to format all of the things. Whoops

external or internal BT?
using a VM?

Nvm. I fixed it tho.


Lgranie/issue95

replace pull and pullAlways with pullPolicy

As per comment on the other PR: I will have a look at this PR and merge this PR this week. Thanks again for your contribution :-)


Display template point cloud

need to load and display template point cloud when starting webapp

In commit 0cad9c5, I did have to convert the original PLY file of the template to a .GLB file. This was done with Blender. Before converting, I used Blender to also center the origin of the mesh.


how to add new words to data file?

Current Behavior
it recognized AI to Al now
Expected Behavior
it recognized AI to AI
Suggested Fix
No response
tesseract -v
tesseract v<IP_ADDRESS>21214
leptonica-1.78.0
libgif 5.1.4 : libjpeg 8d (libjpeg-turbo 1.5.3) : libpng 1.6.34 : libtiff 4.0.9 : zlib 1.2.11 : libwebp 0.6.1 : libopenjp2 2.3.0
Found SSE4.1
Found libarchive 3.5.0 zlib/1.2.11 liblzma/5.2.3 bz2lib/1.0.6 liblz4/1.7.5 libzstd/1.4.5
Found libcurl/7.77.0-DEV Schannel zlib/1.2.11 zstd/1.4.5 libidn2/2.0.4 nghttp2/1.31.0
Operating System
No response
Other Operating System
No response
uname -a
No response
Compiler
No response
CPU
No response
Virtualization / Containers
No response
Other Information

Please use our forum for asking questions.

sorry, google is blocked in my region.

could you open the discuss feature of github web site?

could you open the discuss feature of github web site?

I don't think that splitting discussions on two different forums is the right way to handle Internet restrictions imposed by some regions of the world. But if you want a separate discussion forum for your region, you can always create one on your personal tesseract fork.

you can always create one on your personal tesseract fork.

Oh no!
People will start 'calling' @amitdo, @stweil and @zdenop in their questions...


iam:User default tags require iam:UpdateUser on all users

What happened?

With version 0.28.1 the provider needs access to iam:UpdateUser on all users to update tags. In 0.27.1 this could be limited to users with prefixes.
Role with 0.27.1
 {             "Action": [                …                "iam:UpdateUser"             ],             "Effect": "Allow",             "Resource": "arn:aws:iam::<AccountID>:user/prefix-*”         },
Needed role with 0.28.1,0.29.0
 {             "Action": [                …                "iam:UpdateUser"             ],             "Effect": "Allow",             "Resource": "arn:aws:iam::<AccountID>:user/”         },
We do not want to give crossplane access to update all iam users just to update tags.
How can we reproduce it?

Create an iam User via crossplane
Remove iam:UpdateUser on crossplane provider role or limit to user with prefix

{             "Action": [                 "iam:UpdateUser"             ],             "Effect": "Allow",             "Resource": "arn:aws:iam::<AccountId>:user/prefix-*”         }

Remove default tags via aws console from the iam user
See logs for debug messages

What environment did it happen in?
Crossplane version:  1.8.1
AWS EKS 1.21

Do you have the failing log entry from cloud trail here? Are you talking about iam:TagUser / iam:UntagUser?


Implement API and data job for last 30 days of PyPI installs

Relates to: https://github.com/chanzuckerberg/napari-hub/issues/709
Happy path - Valid plugin name:
https://6vwmwypt38.execute-api.us-west-2.amazonaws.com/dev-last30daysInstall/activity/affinder/recentStats
Invalid plugin name:
https://6vwmwypt38.execute-api.us-west-2.amazonaws.com/dev-last30daysInstall/activity/test/recentStats
Relates to:
https://github.com/chanzuckerberg/napari-hub/issues/720
Happy path - Valid plugin name:
https://6vwmwypt38.execute-api.us-west-2.amazonaws.com/dev-last30daysInstall/metrics/affinder
Invalid plugin name:
https://6vwmwypt38.execute-api.us-west-2.amazonaws.com/dev-last30daysInstall/metrics/test

I'd suggest giving the pull request a more readable name, e.g. "Implement API endpoint for last 30 days of PyPI installs"

Closing this in favour of https://github.com/chanzuckerberg/napari-hub/pull/741


Refactor match types

Start splitting up the main matchTypes function. I will probably look at pulling out some of the code that deals with conversions soon.

@swift-ci Please smoke test and merge


Fix typo in Fedora 26 in 2.0.0 preview 2 release notes

See https://github.com/dotnet/core/pull/691 which suggests this was supposed to be 26.
cc @leecow

Thanks!


Loader animation moves all the dashboard

Hello,
First of all thank you very much for the incredible library, I really love it and was waiting long time for something like this!
I wanted to ask if there's any possibility to deactivate the loading animations or use the original streamlit one to avoid this animation to move the dashboard (the loading appears on top and moves the user's view, making it a bit uncomfortable in some apps). Another option would be to make the loading animation float in front of the dashboard without modifing the structure.
Thank you in advance!

I'm sorry, I'm not sure exactly what you mean, if you could possible provide some screenshots for example? I haven't seen the loaders shift any content, as they are may to be an overlay, so technically they are rendered over the top of everything so they don't shift any of the content. Thanks

Hello @TangleSpace, thank you very much for your answer.
As you say, it renders over the top of everything, and this moves all the plots of the dashboards down during the loading time. Then the loader closes and the plots go again to the original position.
When loading a new "tab", this is not a problem, but when loading after using one filter at the middle of the dashboard it is a bit frustrating visually (feels like the app starts jumping).
Here an screenshot. Top orange/red is the nav panel. Down the automatic loader moving all the dashboard down (the last orange/red part indicating market analysis). I would like to be able to disable this loading animation at some points.

Thanks for the great amount of detail, very helpful. I can understand, it's a matter of personal choice. There is an easy solution to customise the way the loader works by creating your own loader! it can simply do nothing and then you won't see anything, or you can change it to use a Streamlit default, you can even check which app is being loaded and use a different one per app.
In the hydralit example repo, i use a custom loader to demonstrate how to detect the app and customise the experience. In hydralit there is a default loader, that is the one you're seeing usually, you can replace it with your own as below to have any type of behaviour you want.
Since your using the add_app method, this is great, as you can just use the app.add_loader_app method, as show in the example.
The code for the custom loader in the example is located here, it has the same structure as the normal apps you add, with the exception that the run method accepts another argument, which is a reference to the app that is going to be loaded. As you can see, that app_target variable is a reference to the app that is being requested to run from the parent, you do anything you want, display anything, then call the run() method on that target app. In this case, you wrap the call app_target.run() with a custom loader or one of the info messages or something from Streamlit. Animation gone, so you get the look you're after. If you want the loader for some apps and not others, just check the name of the app as per the example and you can customise it.
`def run(self,app_target):
    try:
        app_title = ''
        if hasattr(app_target,'title'):
            app_title = app_target.title

        if app_title == 'Sequency Denoising':
            with HyLoader(se_loader_txt, loader_name=Loaders.pacman):
                time.sleep(int(self.delay))
                app_target.run()

        elif app_title == 'Loader Playground':
            app_target.run()
        else:
            with HyLoader("✨Now loading {}".format(app_title), loader_name=self._loader,index=[3,0,5]):
                time.sleep(int(self.delay))
                app_target.run()

    except Exception as e:
        st.image("./resources/failure.png",width=100,)
        st.error('An error has occurred, someone will be punished for your inconvenience, we humbly request you try again.')
        st.error('Error details: {}'.format(e))`

Hope that helps and thanks.

@TangleSpace Thank you again for your support.
I have been trying to use the default Streamlit loader using as a guide this example but I haven't been able to do this until the moment.
Edit: I just tried the following and it worked (i.e. using this lines no loading animation is displayer):
with HyLoader(loader_name=self._loader,index=[]):                 app_target.run()

glad you got it working the way you want.


Follow-up to #4 - Change getPaymentInstruments to return Collection

Reopening as new issue.
@fgiust Yeah, I know it returns dw.order.PaymentInstrument, but I think in the context of LineItemCtnr, I think getPaymentInstruments actually returns dw.order.OrderPaymentInstrument, which is a subclass of PaymentInstrument. The important but subtle difference is that OrderPaymentInstrument subclass contains info related to payment for that order (getPaymentTransaction exists on OrderPaymentInstrument but not on PaymentInstrument)
Originally posted by @shannontan-bolt in https://github.com/openmindlab/sfcc-dts/issues/4#issuecomment-692292250

thanks for the clarification @shannontan-bolt ,
updated here: https://github.com/openmindlab/sfcc-dts/commit/11cacb4e06331adaf21b2308e9ddbb8c226de8ab


Limit show batch figure count

If the batch_size param is rather high (in my case it was 512), then show_batch() plots almost unusable plots.
The suggestion would be to plot first n plots with an ability to override that.

Does dbunch.show_batch(max_n=4) not do this?

It does, but I believe it would be great if max_n would be set to some number by default if the BS is big

You'll have to clarify. For both the signal and spectrogram version, there is a default value set for max_n. Are you suggesting that we should ignore max_n changes by the user for large batches?
https://github.com/fastaudio/fastaudio/blob/ccf6bf3f92d44903550ee225d67589467b5938a4/src/fastaudio/core/signal.py#L159-L169
https://github.com/fastaudio/fastaudio/blob/ccf6bf3f92d44903550ee225d67589467b5938a4/src/fastaudio/core/spectrogram.py#L101-L111

Hmm, I will check again my code, but If I have a large batch size of signals I see all of them, not 6.

Did you recreate this issue?

Closing this due to iactivity, if you continue to have a problem feel free to re-open


[Question]: Issues with Context Generation and Metric Support in Llama-Index Evaluation for RAG Retrieval Service

Question Validation

[X] I have searched both the documentation and discord for an answer.

Question
When evaluating a RAG retrieval service using the llama-index evaluation method, I encountered the following issues:
In the first step, we generate question-context pairs using the code:
from llama_index.core.evaluation import (
    generate_question_context_pairs,
    EmbeddingQAFinetuneDataset,
)

qa_dataset = generate_question_context_pairs(
    nodes, llm=llm, num_questions_per_chunk=2
)

retriever_evaluator = RetrieverEvaluator.from_metric_names(
    metrics, retriever=retriever
)

sample_id, sample_query = list(qa_dataset.queries.items())[0]
sample_expected = qa_dataset.relevant_docs[sample_id]

eval_result = retriever_evaluator.evaluate(sample_query, sample_expected)
print(eval_result)

However, the output returns eval_result is an EmbeddingQAFinetuneDataset object containing 'queries', 'corpus', and 'relevant_docs'. I don't see any 'context' in this eval_result. How is the evaluation being performed using only the 'queries'?
Is there any way to generate ground_truth along with context?
When using RetrieverEvaluator, I noticed it supports only 'hit_rate' and 'mrr'. Attempting to use 'precision' and 'recall' results in the error:
ValueError: Invalid metric name: precision.
Could you confirm which version of llama-index supports all metrics, including precision and recall? For reference, I am using the following versions:
llama-index==0.10.13.post1
llama-index-agent-openai==0.1.5
llama-index-cli==0.1.5
llama-index-core==0.10.13

@dosu : In the below code, i am passing my query_engine
from llama_index.core.evaluation import RetrieverEvaluator

metrics = ["hit_rate", "mrr"]#, "precision", "recall", "ap", "ndcg"]

retriever_evaluator = RetrieverEvaluator.from_metric_names(
    metrics, retriever=query_engine
)

my query_engine type is llama_index.core.query_engine.retriever_query_engine.RetrieverQueryEngine.
so i am getting error :
ValidationError: 1 validation error for RetrieverEvaluator
retriever
  instance of BaseRetriever expected (type=type_error.arbitrary_type; expected_arbitrary_type=BaseRetriever)

@dosu I am using the below code for evaluating ["hit_rate", "mrr", "precision", "recall", "ap", "ndcg"]:
from llama_index.core.evaluation import (
    generate_question_context_pairs,
    EmbeddingQAFinetuneDataset,
)

qa_dataset = generate_question_context_pairs(
    nodes, llm=llm, num_questions_per_chunk=2
)

from llama_index.core.evaluation import RetrieverEvaluator

metrics = ["hit_rate", "mrr", "precision", "recall", "ap", "ndcg"]

retriever_evaluator = RetrieverEvaluator.from_metric_names(
    metrics, retriever=retriever
)

eval_results = await retriever_evaluator.aevaluate_dataset(qa_dataset)

In the above code, qa_dataset contains only 'queries', 'corpus' and 'relevant_docs'. Which is not fulfilling my requirement as I want to test my RAG based on ground_truth , context and answer generated by RAG.
Can you please provide me the end to end code to perform such test as i want to mainly focus on evaluating Context precision and context recall. It would be great if you can provide me the code in the same way I provided my code.

@dosu in the provided solution, context recall and precision is not been evaluated. I want to evaluate Retrieval with precision and recall

@dosu - what does this generate_question_context_pairs contains and how does RetrieverEvaluator uses this for evaluating precision and recall?

@dosu : As i checked the Precision Class , i want to understand from where does it take expected_ids and retrieved_ids. From where and how should i get these  expected_ids and retrieved_ids.

class Precision(BaseRetrievalMetric):
    """Precision metric.

    The `K`-value in `Precision@K` usually corresponds to `top_k` of the retriever.

    Attributes:
        metric_name (str): The name of the metric.
    """

    metric_name: ClassVar[str] = "precision"

    def compute(
        self,
        query: Optional[str] = None,
        expected_ids: Optional[List[str]] = None,
        retrieved_ids: Optional[List[str]] = None,
        expected_texts: Optional[List[str]] = None,
        retrieved_texts: Optional[List[str]] = None,
        **kwargs: Any,
    ) -> RetrievalMetricResult:
        """Compute precision based on the provided inputs and selected method.

        Parameters:
            query (Optional[str]): The query string (not used in the current implementation).
            expected_ids (Optional[List[str]]): Expected document IDs.
            retrieved_ids (Optional[List[str]]): Retrieved document IDs.
            expected_texts (Optional[List[str]]): Expected texts (not used in the current implementation).
            retrieved_texts (Optional[List[str]]): Retrieved texts (not used in the current implementation).

        Raises:
            ValueError: If the necessary IDs are not provided.

        Returns:
            RetrievalMetricResult: The result with the computed precision score.
        """
        # Checking for the required arguments
        if (
            retrieved_ids is None
            or expected_ids is None
            or not retrieved_ids
            or not expected_ids
        ):
            raise ValueError("Retrieved ids and expected ids must be provided")

        retrieved_set = set(retrieved_ids)
        expected_set = set(expected_ids)
        precision = len(retrieved_set & expected_set) / len(retrieved_set)

        return RetrievalMetricResult(score=precision)

@dosu  How can i create a data with expected_ids or ground truth and retrieved_ids. Do i need to use nodes to create this. Can you provide me the code to prepare data with expected_ids or ground truth and retrieved_ids with bunch of sample data.

@dosu How would i know that the evaluation is working fine on multi context queries.Is there any checks present.  Please help me with the step by step process on evaluating Precision ,recall and other metrics considering that I have a retriever , nodes, vector_index available.

@dosu, how can i save the eval_results as dataframe

@dosu i want to convert eval_results to dataframe which should contain columns like query, expected_ids, expected_texts, retrieved_ids,  retrieved_texts, metric_dict

To ensure that the evaluation is working correctly on multi-context queries and to evaluate precision, recall, and other metrics, you can follow these steps using the RetrieverEvaluator class from LlamaIndex. Here is a step-by-step process:
Step 1: Load and Parse Data
First, load and parse your data into nodes.
from llama_index.core import SimpleDirectoryReader, VectorStoreIndex
from llama_index.core.node_parser import SentenceSplitter

# Load and parse data
documents = SimpleDirectoryReader("./data/paul_graham/").load_data()
node_parser = SentenceSplitter(chunk_size=512)
nodes = node_parser.get_nodes_from_documents(documents)

# Set consistent node IDs
for idx, node in enumerate(nodes):
    node.id_ = f"node_{idx}"

Step 2: Initialize LLM and Vector Index
Initialize your language model (LLM) and create a vector index.
from llama_index.llms.openai import OpenAI

# Initialize LLM
llm = OpenAI(model="gpt-4")

# Create vector index
vector_index = VectorStoreIndex(nodes)
retriever = vector_index.as_retriever(similarity_top_k=2)

Step 3: Generate Question-Context Pairs
Generate question-context pairs using the generate_question_context_pairs function.
from llama_index.core.evaluation import generate_question_context_pairs

qa_dataset = generate_question_context_pairs(
    nodes, llm=llm, num_questions_per_chunk=2
)

Step 4: Define Metrics and Initialize Evaluator
Define the metrics you want to evaluate and initialize the RetrieverEvaluator.
from llama_index.core.evaluation import RetrieverEvaluator

# Define metrics
metrics = ["hit_rate", "mrr", "precision", "recall", "ap", "ndcg"]

# Initialize the evaluator
retriever_evaluator = RetrieverEvaluator.from_metric_names(metrics, retriever=retriever)

Step 5: Evaluate a Sample Query
Evaluate a sample query to ensure the setup is correct.
sample_id, sample_query = list(qa_dataset.queries.items())[0]
sample_expected = qa_dataset.relevant_docs[sample_id]

eval_result = retriever_evaluator.evaluate(sample_query, sample_expected)
print(eval_result)

Step 6: Evaluate the Entire Dataset
Evaluate the entire dataset to get comprehensive metrics.
import pandas as pd

# Evaluate the dataset
eval_results = await retriever_evaluator.aevaluate_dataset(qa_dataset)

# Display results
def display_results(name, eval_results):
    metric_dicts = []
    for eval_result in eval_results:
        metric_dict = eval_result.metric_vals_dict
        metric_dicts.append(metric_dict)

    full_df = pd.DataFrame(metric_dicts)
    columns = {
        "retrievers": [name],
        **{k: [full_df[k].mean()] for k in metrics},
    }

    metric_df = pd.DataFrame(columns)
    return metric_df

print(display_results("top-2 eval", eval_results))

Step 7: Ensure Evaluation is Working Correctly
To ensure the evaluation is working correctly, check the following:

Metrics Calculation: Verify that the metrics (e.g., precision, recall) are correctly implemented and return expected values.
Post-Processing: If using node post-processors, ensure they are correctly modifying the retrieved nodes.
Retrieved Nodes: Check that the retrieved nodes (both IDs and texts) match the expected results for given queries.

Example Code
Here is the complete example code:
import nest_asyncio
import logging
import sys
import os
import pandas as pd

from llama_index.core.evaluation import (
    generate_question_context_pairs,
    RetrieverEvaluator
)
from llama_index.core import (
    SimpleDirectoryReader,
    VectorStoreIndex
)
from llama_index.core.node_parser import SentenceSplitter
from llama_index.llms.openai import OpenAI

# Attach to the same event-loop
nest_asyncio.apply()

# Set up the root logger
logger = logging.getLogger()
logger.setLevel(logging.INFO)  # Set logger level to INFO

# Clear out any existing handlers
logger.handlers = []
# Set up the StreamHandler to output to sys.stdout
handler = logging.StreamHandler(sys.stdout)
handler.setLevel(logging.INFO)  # Set handler level to INFO

# Add the handler to the logger
logger.addHandler(handler)

# Set OpenAI API key
os.environ["OPENAI_API_KEY"] = "sk-..."

# Load and parse data
documents = SimpleDirectoryReader("./data/paul_graham/").load_data()
node_parser = SentenceSplitter(chunk_size=512)
nodes = node_parser.get_nodes_from_documents(documents)

# Set consistent node IDs
for idx, node in enumerate(nodes):
    node.id_ = f"node_{idx}"

# Initialize LLM and vector index
llm = OpenAI(model="gpt-4")
vector_index = VectorStoreIndex(nodes)
retriever = vector_index.as_retriever(similarity_top_k=2)

# Generate question-context pairs
qa_dataset = generate_question_context_pairs(
    nodes, llm=llm, num_questions_per_chunk=2
)

# Define metrics
metrics = ["hit_rate", "mrr", "precision", "recall", "ap", "ndcg"]

# Initialize the evaluator
retriever_evaluator = RetrieverEvaluator.from_metric_names(metrics, retriever=retriever)

# Evaluate a sample query
sample_id, sample_query = list(qa_dataset.queries.items())[0]
sample_expected = qa_dataset.relevant_docs[sample_id]
eval_result = retriever_evaluator.evaluate(sample_query, sample_expected)
print(eval_result)

# Evaluate the entire dataset
eval_results = await retriever_evaluator.aevaluate_dataset(qa_dataset)

# Display results
def display_results(name, eval_results):
    metric_dicts = []
    for eval_result in eval_results:
        metric_dict = eval_result.metric_vals_dict
        metric_dicts.append(metric_dict)

    full_df = pd.DataFrame(metric_dicts)
    columns = {
        "retrievers": [name],
        **{k: [full_df[k].mean()] for k in metrics},
    }

    metric_df = pd.DataFrame(columns)
    return metric_df

print(display_results("top-2 eval", eval_results))

This setup ensures that you can evaluate precision, recall, and other metrics for multi-context queries using a retriever, nodes, and vector_index [1][2][3].
To continue talking to Dosu, mention @dosu.

In the above steps , Can i generate questions using RAGAS testset generator and run the llama_index evalutor on the quesion generated by ragas:
generator = TestsetGenerator.from_langchain(
    generator_llm,
    critic_llm,
    embeddings
)

# Change resulting question type distribution
distributions = {
    simple: 0.5,
    multi_context: 0.4,
    reasoning: 0.1
}

# use generator.generate_with_llamaindex_docs if you use llama-index as document loader
testset = generator.generate_with_langchain_docs(documents, 10, distributions)
testset.to_pandas()

@dosu : In the above steps , Can i generate questions using RAGAS testset generator and run the llama_index evalutor on the quesion generated by ragas:
generator = TestsetGenerator.from_langchain(
generator_llm,
critic_llm,
embeddings
)
Change resulting question type distribution
distributions = {
simple: 0.5,
multi_context: 0.4,
reasoning: 0.1
}
use generator.generate_with_llamaindex_docs if you use llama-index as document loader
testset = generator.generate_with_langchain_docs(documents, 10, distributions)
testset.to_pandas()

@dosu  which version of llama-index includes metrics like precision , recall. I am currently using Version: 0.10.13.post1 of llama-index but when i ran the code:

from llama_index.core.evaluation import RetrieverEvaluator

metrics = ["hit_rate", "mrr", "precision", "recall", "ap", "ndcg"]

retriever_evaluator = RetrieverEvaluator.from_metric_names(
    metrics, retriever=retriever
)

i got the error as:
ValueError: Invalid metric name: precision

@dosu in the above code where you have created testset_df using Ragas TestSetGenerator, i see the issue in the below line of code provided by you:
# Convert the testset to a format compatible with LlamaIndex
queries = testset_df['question'].tolist()
expected_ids = testset_df['expected_ids'].tolist()
expected_texts = testset_df['expected_texts'].tolist()

testset_df create by ragas TestSetGenerator does not have 'expected_ids' and 'expected_texts'. It contains only 'question',	contexts','ground_truth','evolution_type,'metadata','episode_done'

@dosu getting below error:
eval_results = await retriever_evaluator.aevaluate_dataset(llamaindex_testset)
File /anaconda/lib/python3.10/site-packages/llama_index/core/evaluation/retrieval/base.py:188, in BaseRetrievalEvaluator.aevaluate_dataset(self, dataset, workers, show_progress, **kwargs)
AttributeError: 'list' object has no attribute 'mode'


GO:0005201 extracellular matrix structural constituent - component?

Hi,
shouldn't GO:0005201 extracellular matrix structural constituent be a cellular component???
Maybe I got it wrong but it sounds like the description of a structure, not an activity (except for one of the child terms that has activity in it...)
Thanks,
Birgit
Reported by: bmeldal
Original Ticket: geneontology/ontology-requests/10709

My suggested fix would require a policy change in GO to allow nested class expressions.  Some alterations to the pipeline would also be required as the resulting axioms could not be expressed in OBO - should probably live in separate, imported, edited OWL file.

How does this relate to the regulation-of-biological-quality hierarchy?
or to the mf refactor. E.g. mechanistically, this is a structural constituent. The function is to increase or decrease the magnitude of some property such as tensile strength of collagen fibrils (which is itself causally linked to increasing the strength of bone and skeletal structures)

Alternative pattern:
'fu structural constituent activity'
EquivalentTo: 'structural molecule activity' that part_of some 'maintenance of fu organization'

How does this relate to the regulation-of-biological-quality hierarchy?

or to the mf refactor. E.g. mechanistically, this is a structural constituent. The function is to increase or decrease the magnitude of some property such as tensile strength of collagen fibrils (which is itself causally linked to increasing the strength of bone and skeletal structures)

E.g. structural molecule activity and positively regulates some OBA:class

Agree that this would allow us to add without introducing nested class expressions.  Looks like the best way to fix (once we've agreed on a general pattern).

Pattern summary (text def follows current pattern from ontology):

'fu structural constituent'
def: "The action of a molecule that contributes to the structural integrity of a fu."
exact_synonym: 'structural molecule activity involved in 'maintenance of fu organization
EquivalentTo: 'structural molecule activity' that part_of some 'maintenance of fu organization'

This has the great advantage that it levers the partonomy under 'maintenance of fu' to automate classification.  Unfortunately, this partonomy is currently manually managed (could potentially be fixed with GCIs).  It is also hard to specify a DOSDP for this.  The var slot has to be the maintenance term rather than the CC term.  This means that some reg-ex would be required to derive the label and definition.  Not ideal.  Again, would be solved easily if nested class expressions allowed - as we could then use the maintenance pattern to refer to the maintenance term anonymous via the CC.
Despite these limitations, I have implemented this pattern for synapse terms.   The number of terms is relatively small so a design pattern spec not essential I think.

CC (pre GitHub commenters): @mah11 @ValWood @bmeldal @paolaroncaglia

I haven't changed my mind; I still think any term that has an is_a path to GO:0005198 and incorporates a GO CC or anatomical term in its name or definition should eventually become obsolete.
Interesting to see the discussion of various aspects of moving the CC/anatomy info to extensions, tho.

@mah11: So you suggestion is that MFs shouldn't be tied to anatomy or CC except via extensions (or LEGO)?
In this case, the terms seem pragmatically useful to me: We need a way to record when proteins play a structural role in CCs (and perhaps in some types of anatomy, like bone or eggshell).  For example, there are many gene products that play important structural roles in post-synaptic densities - they are present in the PSD and without them the PSD falls apart or is malformed. I don't think we have anything in the BP branch that works for this: maintenance, assembly, organisation are too broad.   We could shift the link to CC into an extension or split it out in LEGO, but I worry this would obscure the meaning for many users, and fail to provide a means for semantically clear enrichment/annotation grouping to replace terms like 'structural constituent of PSD'.

So your suggestion is that MFs shouldn't be tied to anatomy or CC except via extensions (or LEGO)?

Yes; that's consistent with the definition in the ontology as well as the description in GO's documentation.

So your suggestion is that MFs shouldn't be tied to anatomy or CC except via extensions (or LEGO)?

Yes; that's consistent with the definition in the ontology as well as the description in GO's documentation.

Does this objection apply to all MF involved in BP links or only to BPs that are further defined wrt some CC?

I have always thought that the BP-specific MF terms sit a bit awkwardly given the way GO defines MF (what's happening at the level otherwise associated with the MF scope is the same in any BP context), but I've made my peace with the arrangement. I don't think that has anything to do with the CC- or anatomy-specific "structural constituent" MFs, though.

@ukemi @rachhuntley
Did you guys look at this during the ECM re-organization?
Can this be closed, or an action be decided ?
Thanks, Pascale

This isn't really in the scope of what we are doing. We are looking at the components, not the activities. This is a more general issue as to whether there is a molecular function that corresponds to providing structure for something. We have always included it as an MF, but that doesn't mean we couldn't change.

OK - but there is no reason to change now ?
Close ?

Having skimmed the discussions, I'm not still not sure if an actual plan was laid out. In the case of the ECM terms, e.g. ' extracellular matrix structural constituent conferring tensile strength ', I have no strong feelings whether they sould be CC or MF, but I would not want them to be obsoleted as I am using them to categorise ECM components from HTP experiments in combination with the categorisation used by the Matrisome project.

@rachhuntley . I'm tempted to close since some confer tensile strength and some confer elasticity. If I recall correctly these two 'functions' can have different health-related consequences when disrupted.

Yes, I'm happy with that!


[Traefik Plugin] post requests with data trigger error

Sorry to bring this up again, but I just run a test with the refactored version. However, I was not able to load version v1.6.30 nor v1.6.31 as Traefik plugin.
But with the already refactored version (v.1.6.29) I do get this error:
- "plugins-storage/sources/gop-2015442608/src/github.com/darkweak/souin/plugins/traefik/vendor/github.com/darkweak/souin/pkg/middleware/middleware.go:95:9: panic" module=github.com/darkweak/souin plugin=plugin-souin
- "plugins-storage/sources/gop-2015442608/src/github.com/darkweak/souin/plugins/traefik/vendor/github.com/darkweak/souin/pkg/middleware/middleware.go:177:19: panic" module=github.com/darkweak/souin plugin=plugin-souin
- "plugins-storage/sources/gop-2015442608/src/github.com/darkweak/souin/plugins/traefik/main.go:226:6: panic" module=github.com/darkweak/souin plugin=plugin-souin
- "Recovered from panic in HTTP handler [<IP_ADDRESS>:56066 - /]: reflect.Set: value of type *struct {} is not assignable to type error" middlewareType=Recovery middlewareName=traefik-internal-recovery
- "Stack: goroutine 14 [running]:
github.com/traefik/traefik/v2/pkg/middlewares/recovery.recoverFunc({0x3c297f8, 0x400063a380}, 0x4003e07700)
	github.com/traefik/traefik/v2/pkg/middlewares/recovery/recovery.go:46 +0x270
panic({0x29ca800, 0x40029e5fb0})
	runtime/panic.go:1038 +0x224
github.com/traefik/yaegi/interp.runCfg.func1(0x4003fd0580, 0x4002f6e480, 0x0)
	github.com/traefik/yaegi@v0.12.0/interp/run.go:192 +0x164
panic({0x29ca800, 0x40029e5fb0})
	runtime/panic.go:1038 +0x224
github.com/traefik/yaegi/interp.runCfg.func1(0x4003fd0790, 0x4002fe70e0, 0x0)
	github.com/traefik/yaegi@v0.12.0/interp/run.go:192 +0x164
panic({0x29ca800, 0x40029e5fb0})
	runtime/panic.go:1038 +0x224
github.com/traefik/yaegi/interp.runCfg.func1(0x4003fd1e40, 0x4002fbc5a0, 0x0)
	github.com/traefik/yaegi@v0.12.0/interp/run.go:192 +0x164
panic({0x29ca800, 0x40029e5fb0})
	runtime/panic.go:1038 +0x224
reflect.Value.assignTo({0x29155a0, 0x5b0e250, 0x16}, {0x32698f1, 0xb}, 0x2c20560, 0x4000db49e0)
	reflect/value.go:2810 +0x2cc
reflect.Value.Set({0x2c20560, 0x4000db49e0, 0x194}, {0x29155a0, 0x5b0e250, 0x16})
	reflect/value.go:1918 +0xa4
github.com/traefik/yaegi/interp._new.func1(0x4003fd1e40)
	github.com/traefik/yaegi@v0.12.0/interp/run.go:3310 +0xa8
github.com/traefik/yaegi/interp.runCfg(0x4002fbc5a0, 0x4003fd1e40, 0x4003df0900, 0x40030158c0)
	github.com/traefik/yaegi@v0.12.0/interp/run.go:200 +0x268
github.com/traefik/yaegi/interp.call.func9(0x4003fd0790)
	github.com/traefik/yaegi@v0.12.0/interp/run.go:1433 +0x7cc
github.com/traefik/yaegi/interp.runCfg(0x4002fe70e0, 0x4003fd0790, 0x4003fd7d40, 0x4002f6e240)
	github.com/traefik/yaegi@v0.12.0/interp/run.go:200 +0x268
github.com/traefik/yaegi/interp.call.func9(0x4003fd0580)
	github.com/traefik/yaegi@v0.12.0/interp/run.go:1433 +0x7cc
github.com/traefik/yaegi/interp.runCfg(0x4002f6e480, 0x4003fd0580, 0x4002f6c7e0, 0x4003a5b560)
	github.com/traefik/yaegi@v0.12.0/interp/run.go:200 +0x268
github.com/traefik/yaegi/interp.genFunctionWrapper.func2.1({0x400291eb70, 0x2, 0x2})
	github.com/traefik/yaegi@v0.12.0/interp/run.go:1022 +0x418
github.com/traefik/yaegi/stdlib._net_http_Handler.ServeHTTP(...)
	github.com/traefik/yaegi@v0.12.0/stdlib/go1_17_net_http.go:288
github.com/traefik/traefik/v2/pkg/middlewares/accesslog.(*FieldHandler).ServeHTTP(0x4000da3540, {0x3c297f8, 0x400063a380}, 0x4003e07800)
	github.com/traefik/traefik/v2/pkg/middlewares/accesslog/field_middleware.go:29 +0x16c
github.com/gorilla/mux.(*Router).ServeHTTP(0x40007be7e0, {0x3c297f8, 0x400063a380}, 0x4003e07700)
	github.com/gorilla/mux@v1.8.0/mux.go:141 +0x22c
github.com/traefik/traefik/v2/pkg/middlewares/recovery.(*recovery).ServeHTTP(0x40029e5a80, {0x3c297f8, 0x400063a380}, 0x4003e07700)
	github.com/traefik/traefik/v2/pkg/middlewares/recovery/recovery.go:32 +0x8c
github.com/traefik/traefik/v2/pkg/middlewares/accesslog.(*FieldHandler).ServeHTTP(0x4000da3c80, {0x3c297f8, 0x400063a380}, 0x4003e07700)
	github.com/traefik/traefik/v2/pkg/middlewares/accesslog/field_middleware.go:29 +0x16c
github.com/traefik/traefik/v2/pkg/middlewares.(*HTTPHandlerSwitcher).ServeHTTP(0x4000129490, {0x3c297f8, 0x400063a380}, 0x4003e07700)
	github.com/traefik/traefik/v2/pkg/middlewares/handler_switcher.go:23 +0x70
github.com/traefik/traefik/v2/pkg/middlewares/requestdecorator.(*RequestDecorator).ServeHTTP(0x4000129488, {0x3c297f8, 0x400063a380}, 0x4003e07100, 0x4002a2b900)
	github.com/traefik/traefik/v2/pkg/middlewares/requestdecorator/request_decorator.go:47 +0x5e8
github.com/traefik/traefik/v2/pkg/middlewares/requestdecorator.WrapHandler.func1.1({0x3c297f8, 0x400063a380}, 0x4003e07100)
	github.com/traefik/traefik/v2/pkg/middlewares/requestdecorator/request_decorator.go:84 +0x70
net/http.HandlerFunc.ServeHTTP(0x400068bee0, {0x3c297f8, 0x400063a380}, 0x4003e07100)
	net/http/server.go:2047 +0x40
github.com/traefik/traefik/v2/pkg/middlewares/forwardedheaders.(*XForwarded).ServeHTTP(0x400004f4a0, {0x3c297f8, 0x400063a380}, 0x4003e07100)
	github.com/traefik/traefik/v2/pkg/middlewares/forwardedheaders/forwarded_header.go:189 +0xec
golang.org/x/net/http2/h2c.h2cHandler.ServeHTTP({{0x3bea380, 0x400004f4a0}, 0x400069b880}, {0x3c297f8, 0x400063a380}, 0x4003e07100)
	golang.org/x/net@v0.0.0-20220425223048-2871e0cb64e4/http2/h2c/h2c.go:104 +0x35c
net/http.serverHandler.ServeHTTP({0x400063a1c0}, {0x3c297f8, 0x400063a380}, 0x4003e07100)
	net/http/server.go:2879 +0x45c
net/http.(*conn).serve(0x40005cf180, {0x3c506c0, 0x40007b80c0})
	net/http/server.go:1930 +0xb54
created by net/http.(*Server).Serve
	net/http/server.go:3034 +0x4ac
" middlewareName=traefik-internal-recovery middlewareType=Recovery

Here is my test setup:
version: "3.8"
services:
  traefik:
    image: traefik:v2.7.0
    command:
      - --providers.docker=true
      - --entrypoints.web.address=:80
      - --experimental.plugins.souin.moduleName=github.com/darkweak/souin
      - --experimental.plugins.souin.version=v1.6.29
    ports:
      - 80:80
    networks:
      - default
    volumes:
      - /var/run/docker.sock:/var/run/docker.sock:ro

  whoami:
    image: traefik/whoami:latest
    labels:
      - traefik.enable=true
      - traefik.http.routers.whoami.rule=Host(`localhost`)
      - traefik.http.routers.whoami.entrypoints=web
      - traefik.http.middlewares.http-cache.plugin.souin.api.souin
      - traefik.http.middlewares.http-cache.plugin.souin.default_cache.ttl=60s
      - traefik.http.middlewares.http-cache.plugin.souin.default_cache.allowed_http_verbs=POST,GET,HEAD
      - traefik.http.middlewares.http-cache.plugin.souin.log_level=debug
      - traefik.http.routers.whoami.middlewares=http-cache

And this was my request, which does work fine without caching:
curl -X POST -i http://localhost -H "Content-Type: application/json" -d '{"test": 1}'

The commit 434dbdb7eaa08e6560d1b8bb5cb77ffb1d349556 in the PR #313 will fix your issue. TBH the Træfik interpreter is painful because it doesn't interpret the Go code like the compiler does. Here the issue was Yægi didn't like the nil return as a function even if we don't try to call it.
About the index issue I already asked them if it was normal that the plugins catalog didn't index the new releases but the answer was without any explanations. Anyway I'll try to merge that PR, tag the new version and cross my finger they will index this new release.

@jonasengelmann the version v1.6.32 is now available.

@darkweak Thanks for looking into this so quickly and also pushing Traefik to reindex their plugin index and keeping up with their unreliable interpreter. I can now successfully load all version! However unfortunately I still get the error in version v1.6.32. I noticed that I probably forget to post the most important log message, it only showed up in the Traefik debug log, and wasn't registered as an error, so that is why I missed it at first:
level=debug msg="'500 Internal Server Error' caused by: net/http: HTTP/1.x transport connection broken: http: ContentLength=11 with Body length 0"
I think this line is triggering the error, but I was not able to fix the issue as I am not so proficient in Go. Do you have any idea?

Fixed by #317

@jonasengelmann can you retry and tell me if that's okay for you too?

@darkweak I just did a test with version v1.6.34 but sadly I still get the error. I think it might have to do with the difference between rq and req here. I quickly checked and rq.Body is still being consumed, but I do not understand where exactly. Do you have an idea?

New version available, it should fix everything 🤞


Add CoreSampleGameplay module

This adds another module alonside Core to provide gameplay related systems that do not pertain to the base set of content.  Particularly,  the starting inventory.
The new module presents itself the same as the core previously did as "Core Gameplay" in the UI.
Some feedback and verification of the following would be appreciated:

.gitignore, I am fairly sure I got it right.  Did I miss anything?
The module name, "CoreSampleGameplay".  Is this suitable?  Any better ideas of a name?
Is there anything else that should be moved over to this gameplay module?

I'll take a close look at this over the weekend including a forum write-up I've intended for a little while. Thanks for getting it kicked off :-)

Alright, mega-thread time!
http://forum.terasology.org/threads/distros-names-and-content.1247/
At the very bottom I think I might have come across a bright idea! Go forth and prove me wrong :D
The starting inventory here I could see in a developer type gameplay template, or even "creative" ? We just kinda dump stuff into that inventory more for testing than any serious gameplay.
I might suggest making it into a "Freestyle" module that later becomes a gameplay template. But for various reasons I go over in the mega-thread we might want it in a standalone repo rather than in with the engine. Please read and provide the feedbacks! :-)

Merged in. Tweaked a few related bits - should've done that in a separate commit first, then added on top, made history look kinda funny.
Made it so IntelliJ won't try to enable Git for the new internal module, also resolved a conflict with the version in the Core module. Which I guess in theory might not actually need to be versioned along with the engine.
Anyway - that's besides the point. This helps the situation right away where you want to avoid the starting inventory :-)
Noted one tricky issue: The gameplay template select box starts out with no selection, although there are valid ones available. I figure the little smart selection in org/terasology/rendering/nui/layers/mainMenu/CreateGameScreen.java isn't working anymore with this.

Oh, weird, those changes were auto-excluded from the merge commit anyway. So there is a new commit - https://github.com/MovingBlocks/Terasology/commit/320bf18c5474a9bfb7b64522cae6af70931037ca


Specify whether Foundation.JSONSerialization test is run on Darwin or Linux

As far as I'm aware the Objective-C backed parser is much faster than the Swift one but it only works on Darwin.
What platform are you benchmarking on?

Closed, found out it uses Darwin


qeq parser no longer requires configure

fix #2

Pull Request Test Coverage Report for Build 20

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage decreased (-0.9%) to 73.82%

Totals

Change from base Build 18:
-0.9%

Covered Lines:
344

Relevant Lines:
466

💛  - Coveralls

Pull Request Test Coverage Report for Build 20

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage decreased (-0.9%) to 73.82%

Totals

Change from base Build 18:
-0.9%

Covered Lines:
344

Relevant Lines:
466

💛  - Coveralls

Pull Request Test Coverage Report for Build 20

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage decreased (-0.9%) to 73.82%

Totals

Change from base Build 18:
-0.9%

Covered Lines:
344

Relevant Lines:
466

💛  - Coveralls


running napari script.py not working with napari.run()

🐛 Bug
like it sounds...  works with gui_qt ... but not with napari.run

fixed


[BUG]  Does someone knows what that means ?

Describe the bug
I open the program, and later, apeared a tab saying: "A JavaScript error occurred in the main process"
Steps to Reproduce
Open the program and wait, i think
Expected behavior
Not show that
Screenshots

Operating System
Windows 11
Hydra Version
1.2.0
Additional Information
No response

It is fixed on 1.2.1. Your installation should auto update on the next launch.
But you can manual install from the releases page. No need to uninstall the current one


Bring Sesame 2.9 codebase over for parallel release

We are currently focusing on the Sesame 4 code base as the launch point for RDF4J. However there are several core users who require to stay at Java 7 for a while longer. We should consider bringing over the Sesame 2.9 code base to RDF4J to live alongside the main branch, so we can do parallel releases for those users who wish to stick to Java 7.

I have sent off a question to Eclipse legal, to see if there is a way to fast-track bringing over the 2.9 codebase (given that they've already approved basically the same codebase, just a different version).

Sharon (Eclipse IP team) has let me know that this shouldn't be a problem from their POV, and that we can bring in the 2.9 codebase as a parallel branch when we're ready - they'll be able to fast-track through the approval process.
So all we need to do is stabilize, bring out the release, then freeze development for a little while so we don't have a fast-moving target.

We are currently considering an alternative approach: instead of bringing over the 2.9 code base as a new "initial" contribution, we can also just branch off a parallel branch from the current master, and downgrade that branch to be Java 7-compatible again.


Console Improvements for user-friendliness

Transferred from internal JIRA issue originally created 2020-07-30.
While the console is functional, there are updates we can make that would make it more user-friendly:

real-time logging (i.e., streaming messages)
colorized text (low-priority)

Closing this issue to separate it out into two, more specific issues.


Fix widget path resolver

formcommon.CreateUrl() tried to os.Sta()t the path of templates/%s/<something> and of course it always failed.

Now it forms the list of widgets, then resolves the path.
use filepath.Join instead of literal "/"
Added go.mod

Hey @kirves , I noticed that travis tries to build this on Go 1.2 and shits the pants because gimme fails to fetch Go 1.2, do you mind if I update the travis.yml to use more up-to-date version, or do you have sentiments about Go 1.2?


Grow friendly chat shows 404

Hello,
So I clicked on the grow friendly chat link and the page showed a 404. Can this be fixed?

@Martins-Iroka thanks for reporting
@kroikie what happened to Grow Friendly Chat?  It's 404ing for me as well.

it still shows 404, any update or alternate link where to find it please ?


What domains do Amplify CLI requests so that I can put them to the proxy allowlisting?

Amplify CLI Version

Question
I use Amplify CLI via proxy and wanted to understand which domains are accessed for networking allowlisting.

The following domains that were accessed with the init, publish, and push commands:

amazonaws.com
amplifyapp.com
aws-amplify.github.io

If those above can be added to the allowlist, Amplify CLI should run via proxy.


certificate has expired deploy from vsCode

Does this occur consistently?
Repro steps:

Action: appService.Deploy
Error type: CERT_HAS_EXPIRED
Error Message: request to redacted:url failed, reason: certificate has expired
Version: 0.24.5
OS: win32
OS Release: 10.0.19044
Product: Visual Studio Code
Product Version: 1.74.0
Language: en

Call Stack
ClientRequest.<anonymous> extension.bundle.js:2:4020435

This issue has been closed automatically because it needs more information and has not had recent activity. See also our issue reporting guidelines.
Happy Coding!


ADXL362 sensor includes 1g for gravity

This leads to the activity chart being skewed (the sum of all axis always includes 1g / 9.80665m/s²).

[ ] Update the documentation and description in protocol definition
[ ] Subtract 1g from values printed in charts

ADXL362.pdf

This creates a bit of a problem around the Accelerometer threshold (acct). This is a cut-off value where all motion below this threshold should be ignored, however, given that the reading always includes 1 g, the logic in the firmware needs to be changed:

If acct is 10, a movement of 1 m/s² in direction of the Z axis (down) will be registered (because the sensor will report 1 g + 1 m/s² >= 10 m/s²), however a movement with the same acceleration against the direction of the Z axis (up) will not be registered (because the sensor will report 1 g - 1 m/s² < 10 m/s²).
I think the way the firmware handles the threshold needs to be changed:

there is a user-defined per-axis threshold which has the problem that it's not possible to filter out the 1 g, it will always be present on some axis. If a users sets acct to 10, as shown above, the axis along gravity can easily trigger, but for the other two axis the same threshold will lead to much fewer triggers (they have to register motion above 1 g).
the calculation of the total motion considers each axis individually and does not subtract 1 g to get a relative motion.

This problem is also described in the ADXL362 documentation:

In many applications, it is advantageous for activity detection to
be based not on an absolute threshold, but on a deviation from
a reference point or orientation. This is particularly useful because
it removes the effect on activity detection of the static 1 g imposed
by gravity. When an accelerometer is stationary, its output can
reach 1 g, even when it is not moving. In absolute activity, when
the threshold is set to less than 1 g, activity is immediately detected
in this case.

It sounds like the better way to use the ADXL362 for the cat tracker is to use in the "Referenced Configuration" mode.
@simensrostad @jtguggedal  what do you think?

Hi, this sounds reasonable.  But I thought we were already using reference mode in the firmware. CONFIG_ADXL362_ABS_REF_MODE set to 1.

It doesn't look like it, because

a per-axis threshold is set
the sensor returns values that include 1 g, otherwise the sensor chart would not have all values above 10

I agree that the threshold logic in the firmware should be revisited. The challenge is that we don't know which axis or axes contain gravity, and how large a component it is for each axis.
I think referenced mode is used for Thingy:91:
https://github.com/nrfconnect/sdk-nrf/blob/ea7f385f96e6e8f760a6d8a081be761ed42c2ff8/applications/asset_tracker_v2/boards/thingy91_nrf9160ns.conf#L19
From the datasheet, 1 should mean referenced mode:

The way I read the documentation, is that the referenced mode is used only for the (in)activity detection, while the values that are read out still contain gravity.
Regarding the per-axis thresholds, I don't think we need to set those, as they all seem to map to the same registers, (IN)THRESH_ACT_L / (IN)THRESH_ACT_H. It's a bit confusing that the driver doesn't accept SENSOR_CHAN_ACCEL_XYZ, so that's probably something we could add upstream.
https://github.com/nrfconnect/sdk-zephyr/blob/73a419c5d7d60d9e476dfee62669e96236601755/drivers/sensor/adxl362/adxl362.c#L323

I had a look in the app and driver, and the interface might be a bit misleading:

The per-axis threshold is really a single threshold; the driver ignores the channel when setting it. This threshold is relevant for both referenced and absolute mode.

Referenced mode triggering != referenced data. An internal reference (I am guessing the last inactivity triggering value or a long-term average) is used in the sensor for motion detection and dictates when the interrupt is fired, but the application-level filter compares the absolute values (which are the only externally readable values) to the threshold. In other words, this filter does not really make sense when using referenced mode.

As far as I can see, there is no way to separate activity and inactivity triggers without a change to the driver, which is unfortunate. That binary state is probably the most useful data point from the accelerometer

I had a look in the app and driver, and the interface might be a bit misleading:

The per-axis threshold is really a single threshold; the driver ignores the channel when setting it. This threshold is relevant for both referenced and absolute mode.
Referenced mode triggering != referenced data. An internal reference (I am guessing the last inactivity triggering value or a long-term average) is used in the sensor for motion detection and dictates when the interrupt is fired, but the application-level filter compares the absolute values (which are the only externally readable values) to the threshold. In other words, this filter does not really make sense when using referenced mode.

As far as I can see, there is no way to separate activity and inactivity triggers without a change to the driver, which is unfortunate. That binary state is probably the most useful data point from the accelerometer
EDIT: got ninja'd by JT there, but the points stand

I had a look in the app and driver, and the interface might be a bit misleading:

The per-axis threshold is really a single threshold; the driver ignores the channel when setting it. This threshold is relevant for both referenced and absolute mode.

Yes, sadly I overlooked this part when I made the implementation in the app. However, this shouldn't change anything.

Referenced mode triggering != referenced data. An internal reference (I am guessing the last inactivity triggering value or a long-term average) is used in the sensor for motion detection and dictates when the interrupt is fired, but the application-level filter compares the absolute values (which are the only externally readable values) to the threshold. In other words, this filter does not really make sense when using referenced mode.

This purpose of this filter is to avoid propagating events triggering on inactivity, which is the case for linked mode.

The specification states that in our case (linked and reference mode) the reference is set when inactivity is detected and activity detection begins

We concluded to eventually remove the reporting of the accelerometer data to the cloud, because it provides no meaningful value for analysis if sent as singular events and sending them continuously would use too much data. Instead the firmware should send an event whenever the "in motion" state of the tracker changes. That way activity can be visualized: the cat is considered active after an "in motion" event has been received until an "not in motion" event has been received. The ADXL362 will be configured to yield these events.

This is not fixable, so it will be solved via #175


OM tool does not work with SAML integrated Ops Manager

Right now OM tool takes user name, password, need to be able to use it with uaac client name/secret.
om-alpine -t https://$OPSMAN_HOST -k -u "$OPSMAN_USER" -p "$OPSMAN_PASSWORD" upload-stemcell --stemcell $file

hey @anoumana - thanks for reporting this issue! We didn't try this with SAML as of yet. What sort of workflow would you be looking for? Would you want to pass a SAML token to OM? Can you ask UAA for a set of client credentials based on your SAML token (we do support this flow already).

@zachgersh yes i am ok with uaa client credentials. I will try with that, looks like the scope and authorities are these. I can give that a shot and see if this will work. Thanks.
scope (list):  opsman.admin
authorized grant types (list):  client_credentials
authorities (list):  opsman.admin

@anoumana no problem - please re-open if you find another issue!


Issue 210 new forward simulation

We can leave this branch in case we need it, but all the results are now on
https://github.com/SABS-R3-Epidemiology/transmission-heterogeneity-results


fixing typo

Hi @4c74356b41, 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;

@4c74356b41 : Thanks for your contribution to the Azure documentation! The author, @azdocprs, has been notified to review your proposed change.

@rothja Hi Jason. Please review this proposed change. Thanks.

#sign-off

Only the author of the article can use the sign off comment to add the ready-to-merge label.

@KatieCumming Hi, I tried to sign off, but it won't let me. Can you help me merge this. I approve.


I want to be in a pair!

Leave a comment with your github handle and your experience with github

rene


Help needed with translating urls

HI!
I'm working on uri language identifier. I don't see option how to translate url/contoller also.
So let say i have two languages (en, si).
http://mypage.com/si/contact
http://mypage.com/en/contact
Everything works fine, but i whould like to translate url also, so when the language is /si/, i whould like that url of contact looks like this
http://mypage.com/si/kontakt
How to achieve desired effect? Probably with routs, but i need help how.
Thank you in advance!
Regards,
Davor

This is a bug tracker, we don't provide the kind of help you're looking for.
Post on our forums instead.


NotImplementedError

File "loadnpdata.py", line 7, in
with NpyAppendArray(a1) as npaa:
File "/home/sct/anaconda3/envs/fbs/lib/python3.6/site-packages/npy_append_array/npy_append_array.py", line 11, in init
self.__init()
File "/home/sct/anaconda3/envs/fbs/lib/python3.6/site-packages/npy_append_array/npy_append_array.py", line 43, in __init
"version (%d, %d) not implemented" % magic
NotImplementedError: version (1, 0) not implemented

I am also troubled by this problem，Have you solved this problem？

Should be solved with the new release, you can give it a try.

Considering it as closed, please create a new issue or a comment if it is actually still open.


Hub

TEST PLAN
-go to Limitless domain

Walk to cafe area and mouse click faucets on the double sink. Each faucet should turn on when clicked. A particle effect of water flowing should appear and a sound of running water should play for each one.
Mouse click faucets again to turn them off. Each faucet should turn off when clicked again. The particle effect should disappear and sound should stop for each one.
Enter HMD and trigger on the faucets to turn them on again. Each faucet should turn on when clicked. A particle effect of water flowing should appear and a sound of running water should play for each one.
Trigger faucets again to turn them off. Each faucet should turn off when clicked again. The particle effect should disappear and sound should stop for each one.
Still in HMD, go over to silly walk shower and walk through the machine. You should hear a sound as you walk through and then see that your walk has changed upon emerging and looking in the mirror. It may be difficult to see the change in HMD, but walking forward and backward should be different than the normal walk.
Restart interface and your avatar should have returned to using the default walk animation. Enter the silly walk machine in desktop while viewing in third person mode. You should hear a sound as you walk through and then see that your walk has changed upon emerging.

QA tested internally, approved. Merging!


Add file that documents the thought behind problem order

The downside of this file is that we have to keep in in sync with
config.json. I'm not sure of a way to leverage travis.yml to check that for
us. Though maybe there is an approach.
Even with that drawback, I think having this file is useful. The PR that
kicked of our problem ordering process is already out of date. And
having something in the repo (instead of a gist or a blog post) makes it
easier to find.

Seems like a good idea, so I'm supportive. :+1:
you switched tournament/robot-simulator and sublist/allergies.
I'll try to help out with the dominoes description


Copy link address in chrome gives incorrect URL

When right-clicking in Chrome and selecting copy link address, the URL given should be as resolved as possible, because abc.com/news/economy is better than abc.com

closing due to inactivity and because i think it does do this correctly


Remove Lit. Refs from GPML, when interaction is removed

It seems that when a PW is downloaded from the website, edited and then uploaded as a new PW, the old references remain. However, they are not connected to any interaction or datanode (which means we cannot see them in PV itself). They do appear on the website (however the tag "Add References" did pop up, which was also inconsistent, since the bibliography was not empty....). I'm not sure if this is a GPML issue, or a WP plugin issue, both worth checking I believe.

Just tested in sandbox PW: when removing items (DataNodes, interactions) which have the same lit. ref. (not leaving any other items behind with that lit ref.), the publication remains to be in the GPML.
See the sandbox PW, revision 106338 - 106340 .

And the problem is not due to uploading to WPs; I've added and removed a lit. ref without updating in between, and it's still displayed on the website. (see revision 106341 of Sandbox PW). Definitely a PV bug.

See also https://www.wikipathways.org/index.php/Pathway:WP3674 .

More info from Slack:
This is only a problem if an item with a literature reference is removed. Directly deleting a lit ref works as expected.
Test pathway: https://classic.wikipathways.org/index.php/Pathway:WP5404

Deleted data node B, which had a reference => reference is retained in the gpml
Reverted the pathway back to the original
Deleted only the literature reference on node B => reference is removed from the gpml


Call gcloud auth activate-service-account if GOOGLE_APPLICATION_CREDENTIALS is set

This used to be done by our own gsutil image. When that image was replaced
by the vanilla google/cloud-sdk image, this documented behavior broke.
By adding this as a step added by the resource, the behavior is
maintained without needing to maintain our own image to perform
activation.
Fixes #1748
/hold needs e2e test
cc @dustym

Changes

Submitter Checklist
These are the criteria that every PR should meet, please check them off as you
review them:

[x] Includes tests (if functionality changed/added)
[ ] Includes docs (if user facing)
[x] Commit messages follow commit message best practices

See the contribution guide for more details.
Double check this list of stuff that's easy to miss:

If you are adding a new binary/image to the cmd dir, please update
the release Task to build and release this image.

Reviewer Notes
If API changes are included, additive changes must be approved by at least two OWNERS and backwards incompatible changes must be approved by more than 50% of the OWNERS, and they must first be added in a backwards compatible way.
Release Notes
Fix regression in v0.9 whereby GOOGLE_APPLICATION_CREDENTIALS were ignored when using the GCS resource

/lgtm

/lgtm


[Feature][WEB] 对Chat的多用户支持

Search before asking

[X] I had searched in the issues and found no similar feature requirement.

Description
目前web应用中的Chat记录都是共享的，是否可以考虑加入对多用户的支持
Use case
No response
Related issues
No response
Feature Priority
None
Are you willing to submit PR?

[ ] Yes I am willing to submit a PR!

@camelfire 非常棒的建议，后面会支持的。


set home page

use rest api to set acm cluster overview as home page
https://github.com/open-cluster-management/backlog/issues/12061
Signed-off-by: Marco<EMAIL_ADDRESS>

/retest


Optimize operators with MatchPy

To improve a combined axiom's performance we could simplify complex axiom expressions using pattern matching with MatchPy. The current approach only "optimizes" by overloading the operator functions, e.g., __and__ in AndAxiom, but cannot resolve deep nested axiom expressions.

With the current implementation, we do a decent job at optimizing operators without the MatchPy library. Adding another dependency might thus not be necessary.


Update the archive for "Download-Media-files" section

Hello,
The archive that can be downloaded from "Download-Media-files" section is very old, back from October 20th 2018. A lot of videos are missing.
Can someone update the archive / URL ?
Can you also check if the "Download-Source" reflects the last 2020 updates ?
Thank you!

Hello,
We've updated the zip media file and it is now up-to-date.
Thanks for filing this request.


policy/l4: Fix merging of L7 rules

Allow merging L4 rules with no L7 rules, no parser and no redirect
port with other L4 rules

Correctly write back the copy of rules into the hashtable of per
endpoint rules

Signed-off-by: Thomas Graf<EMAIL_ADDRESS>

Just went through the  pkg/policy/rule.go changes. Looks good.

Looks like the test is failing because we now have two separate api.Rule instances which are not merged. The first commit here will address the merging within a single policy, ie if you have multiple IngressRules that overlap within the api.Rule then we can merge them to take the L7 rule. However, if there are two separate policies, with different Labels and so on, then these are not being merged into the existing policy - they exist side-by-side. Because they both exist, and we iterate both, we will potentially take the more permissive, non-L7 policy and accept private traffic without sending through L7Proxy.

@tgraf are these intended to be merged if they're separately identified by the user using different Labels?

Yes. Labels should not matter. If multiple policies apply to a single endpoint they must be merged.


update URL to avoid redirect

Thanks, it looks like Groups changed their URL format since this page was created.


docs: describe design and structure of derp

@ramfox has put a bunch of time into this already: https://number-zero.notion.site/Iroh-Hole-Punching-b9a38cc228fb47328a73e71d10520418?pvs=4


refactor/action: rewrite correct_lines purely based on spans

What does this PR accomplish?

Replaces the correction algorithm.

🩹 Bug Fix
🦚 Feature

Closes #116  .
Changes proposed by this PR:

Previously a line based algortihm was employed which caused some issues in #95 and #116 .
The new implementation works purely on Spans wrapped in Patches, which now also handles multiline replacements properly and forces a clear boundary between Patch and Bandaid.
Notes to reviewer:

It's now entirely the concern of the checker to provide sane spans and proper wrapping with comment markers (i.e. /// ) from within the Checkers - this is mostly necessary for #95 .
📜 Checklist

[x] Works on the ./demo sub directory
[x] Test coverage is excellent and passes
[x] Documentation is thorough

Will merge this if nobody reviews :jack_o_lantern:


not support HFOV>90

Hey,
I tested the HFOV with a larger value than 90, the returned scene_observations are all with zero values (rgb and depth) using "the scripts/cache_observations.py"?
Is it because of the current habitat version does not support the HFOV other than 90?

I don't think that's the reason because I generated videws with HFOVs larger than 90 before. But I don't know why you got zeros values for these scenarios. I need to take a closer look into the script.

Hi Changan,
Thanks for your responses!
Previously I tested only with HFOV=180 ("SIMULATOR_SENSOR.HFOV" in habitat-lab/habitat/config/default.py ) which returns all zeros.
This time I tried the HFOV in (0, 360]. It only returns all zeros for HFOV of 180 and 360, and supports for all the rest.
I found 1) the focal length varies when changing the HFOV; 2) when the HFOV is larger than 180, the returned rgb or depth are flipped upside down.
Is there any config setting that supporting for changing only the angle of the "field of view"? Something won't change the focal length, and only equals to a wider view range. For example, for a fixed agent position, instead of only seeing the front field of view of 90, what the agent sees is a 360 image if we set some config value to 360.

@ly-zhu  it's good to know that you found something wroking! I would very much like to help with your questions regarding the HFOV but I'm not very familiar with that. For visual related questions, I think you can find better assistance if you post the question in the Habitat repo. For audio related questions, you are very wlecome to post them here.


custom fields in CLS

Hi all,
I am trying to define my own fields in CLS. For the ALS it works as described, even if the documentation here is a bit thin. How do I have to pass the parameters to the logger? In ALS I pass them as an object, this does not work in CLS.
https://github.com/cap-js/docs/blob/894f95df02e550a3a8379202d473b59a8678abba/node.js/cds-log.md?plain=1#L406

Hi @qby-ankul,
just to clarify: CLS is SAP Cloud Logging Service and ALS is SAP Application Logging Service. Correct?
So the section you've linked contains information for both services. If I understand correctly, you experience that the docs for ALS are correct (even if they're thin) but for CLS the docs are incorrect and don't enable you to make it work. Right?
Could you give an example configuration that doesn't work? Is there an error message or sth alike that you can share?

Hi @renejeglinsky,
Yes, that's right.
We used the following code in ALS:
cds.log("logger").info(value, {"custom_field": field_value});
Which no longer works in CLS. In general, I would like the documentation to be more meaningful than how do I configure this. But also, how can I use it.

Thanks @qby-ankul. So you're trying to use the same custom field in both, ALS and CLS, correct? I'm not sure if this is possible.
@sjvans Could you give some insights here?

Hi @renejeglinsky,
no, we switched from ALS to CLS. So far we have lived with it being displayed in msg. However, this is not a permanent solution. We would like it to be listed as a separate field as mentioned in the documentation or in ALS.

hi @qby-ankul
could you please elaborate on "this does not work in CLS"?
for me, it works no problem:
"cds": {
  "log": {
    "als_custom_fields": {
      "bla": 0
    },
    "cls_custom_fields": [
      "bla"
    ]
  }
}

const cds = require('@sap/cds')
const LOG = cds.log('foo')

module.exports = srv => {
  srv.on('bar', req => {
    LOG.info('baz', { bla: 'blub' })
  })
}

ALS:

CLS:

best,
sebastian

Hi @sjvans
unfortunately does not work for me: https://github.com/qby-ankul/cls-custom-fields-demo/blob/main/cls-log.json
I have created an example: https://github.com/qby-ankul/cls-custom-fields-demo/tree/main
The CLS is set up according to the documentation: Bind the Application to a User Provided Service
https://help.sap.com/docs/cloud-logging/cloud-logging/ingest-via-cloud-foundry-runtime?locale=en-US&version=Cloud

hi @qby-ankul
the binding via user-provided service is the issue. we assume a "normal" binding that identifies the service. otherwise we can not reliably protect against false positives... but i'll see what we can do.
can confirm the broken readiness checks, but i'll need to reach out to the respective colleagues. as far as i can tell, we generate an mta that is compliant to the readiness-health-check-http-endpoint docs.
best,
sebastian

bonus bug, the generated readiness parameters doesn't work ...

i created an issue/ feature request: https://github.com/SAP/cloud-mta-build-tool/issues/1147

the binding via user-provided service is the issue. we assume a "normal" binding that identifies the service. otherwise we can not reliably protect against false positives... but i'll see what we can do.

→ https://github.com/cap-js/docs/pull/1441

Thank you for your great support @sjvans !
I have one suggestion for improvement, can the logging section be adapted to your example above?
Best regards
Andre


leaflet: added popup options

leaflet/leaflet.d.ts
to author(@rgripper). could you review this PR?
:+1: or :-1:?
check list

[ ] pas

@ccapndave Could you possibly use the interface PopupOptions for these options? After that it should be ok to merge.

@ccapndave Please update your PR.

Hello and thank you for your contribution!
Due to an excessively long queue of pull requests that have become stale, we are "declaring bankruptcy" and closing all PRs opened before May 1, 2016. If you'd still like to merge this code in, please open a new PR that has been merged and rebased with the master branch.
Going forward, we are committing to review or merge all PRs on a regular basis so this bankruptcy will not occur again. We apologize for the incovenience and hope you will continue to contribute to DefinitelyTyped in the future.
Thanks
The TypeScript and DefinitelyTyped teams


error: "GPU is not enabled"

Here is my output when trying to run dcgan2_test.py
Any help would be appreciated.  I've followed the guide here https://www.tensorflow.org/install/gpu for enabling gpu.  I am running cuda 10.0
Thank you
(thesispy) C:\Users\samuelschrader\Desktop\new text to image generation try sept2018\mxnet-text-to-image-master\demo>python dcgan2_test.py
INFO:root:loading glove embedding from data/glove/glove.6B.300d.pickle
DEBUG:root:loading glove from pickle tooks 1.9 seconds
C:\Users\samuelschrader\AppData\Local\Continuum\anaconda3\envs\thesispy\lib\site-packages\mxnet\gluon\block.py:413: UserWarning: load_params is deprecated. Please use load_parameters.
warnings.warn("load_params is deprecated. Please use load_parameters.")
Traceback (most recent call last):
File "dcgan2_test.py", line 38, in
main()
File "dcgan2_test.py", line 27, in main
gan.load_model(model_dir_path=model_dir_path)
File "C:\Users\samuelschrader\Desktop\new text to image generation try sept2018\mxnet-text-to-image-master\demo\mxnet_text_to_image\library\dcgan2.py", line 150, in load_model
self.netG.load_params(self.get_params_file_path(model_dir_path, 'netG'), ctx=self.model_ctx)
File "C:\Users\samuelschrader\AppData\Local\Continuum\anaconda3\envs\thesispy\lib\site-packages\mxnet\gluon\block.py", line 414, in load_params
self.load_parameters(filename, ctx, allow_missing, ignore_extra)
File "C:\Users\samuelschrader\AppData\Local\Continuum\anaconda3\envs\thesispy\lib\site-packages\mxnet\gluon\block.py", line 379, in load_parameters
filename, ctx, allow_missing, ignore_extra, self.prefix)
File "C:\Users\samuelschrader\AppData\Local\Continuum\anaconda3\envs\thesispy\lib\site-packages\mxnet\gluon\parameter.py", line 796, in load
self[name]._load_init(arg_dict[name], ctx)
File "C:\Users\samuelschrader\AppData\Local\Continuum\anaconda3\envs\thesispy\lib\site-packages\mxnet\gluon\parameter.py", line 216, in _load_init
self._init_impl(data, ctx)
File "C:\Users\samuelschrader\AppData\Local\Continuum\anaconda3\envs\thesispy\lib\site-packages\mxnet\gluon\parameter.py", line 256, in _init_impl
self._data = [data.copyto(ctx) for ctx in self._ctx_list]
File "C:\Users\samuelschrader\AppData\Local\Continuum\anaconda3\envs\thesispy\lib\site-packages\mxnet\gluon\parameter.py", line 256, in
self._data = [data.copyto(ctx) for ctx in self._ctx_list]
File "C:\Users\samuelschrader\AppData\Local\Continuum\anaconda3\envs\thesispy\lib\site-packages\mxnet\ndarray\ndarray.py", line 1973, in copyto
return _internal._copyto(self, out=hret)
File "", line 25, in _copyto
File "C:\Users\samuelschrader\AppData\Local\Continuum\anaconda3\envs\thesispy\lib\site-packages\mxnet_ctypes\ndarray.py", line 92, in _imperative_invoke
ctypes.byref(out_stypes)))
File "C:\Users\samuelschrader\AppData\Local\Continuum\anaconda3\envs\thesispy\lib\site-packages\mxnet\base.py", line 149, in check_call
raise MXNetError(py_str(_LIB.MXGetLastError()))
mxnet.base.MXNetError: [09:37:58] C:\ci\libmxnet_1533398173145\work\src\ndarray\ndarray.cc:1292: GPU is not enabled

Resolved by rebuilding environment.

you can change the "mxnet-cu90" in the requirements.txt to "mxnet" which does not use gpu, but it will be very slow without gpu

Thanks for the tip.  Thankfully I got the gpu working, since even with the gpu, training took a few days with dataset I was using. I tremble to think how long it would have taken with the cpu :)
Thanks again for sharing your work Chen :)


Reapply setup vespalog in jdisc core

This should be good now, @baldersheim

Yes, I tried all tests that I could run locally, and I see no abnormal/unexpected logging now. I suspect the problem was the double call to initializeLog(). Must mention that I have a problem with the configserver shutdown in my container, so those tests never came to the log check, but the log looks fine. No curator/zk log errors/warnings now.