feat: ADVZ PayloadProver support requests that span multiple polynomial

Description

closes: #424
Naive implementation:

SmallRangeProof: concatenate individual KZG proofs from multiple polynomials, do not aggregate
LargeRangeProof: rebuild and verify multiple KZG commitments. There's not much more we could do to improve here. But verification inside a smart contract is now more complex because it might need to compute multiple KZG commitments instead of one.

Before we can merge this PR, please make sure that all the following items have been
checked off. If any of the checklist items are not applicable, please leave them but
write a little note why.

[x] Targeted PR against correct branch (main)
[x] Linked to GitHub issue with discussion and accepted design OR have an explanation in the PR that describes this work.
[x] Wrote unit tests
[x] Updated relevant documentation in the code
[x] Added a relevant changelog entry to the Pending section in CHANGELOG.md
[x] Re-reviewed Files changed in the GitHub PR explorer

LargeRangeProof: rebuild and verify multiple KZG commitments. There's not much more we could do to improve here. But verification inside a smart contract is now more complex because it might need to compute multiple KZG commitments instead of one.

Can the smart contract just generate a random scalar and randomly combine the field vectors? Finally, it only needs to compute a single KZG commitment and compare it with the random linear combinations of the original commitments.

Can the smart contract just generate a random scalar and randomly combine the field vectors? Finally, it only needs to compute a single KZG commitment and compare it with the random linear combinations of the original commitments.

Interesting idea. Basically it replaces subsequent MSMs with a faster hash of the field vectors.
In any case I don't want to do it in this PR. 😉

Interesting idea. Basically it replaces subsequent MSMs with a faster hash of the field vectors.
In any case I don't want to do it in this PR. 😉
In the interactive smart contract setting, we can even generate the randomness via oracles without doing Fiat-Shamir. But yes, there's no need to implement that for now.


CUDA out of memory

Traceback (most recent call last):
File "train.py", line 255, in
main()
File "train.py", line 63, in main
model = nn.DataParallel(model).cuda()
File "/home/abc/anaconda3/envs/torch1.1/lib/python3.6/site-packages/torch/nn/modules/module.py", line 265, in cuda
return self._apply(lambda t: t.cuda(device))
File "/home/abc/anaconda3/envs/torch1.1/lib/python3.6/site-packages/torch/nn/modules/module.py", line 193, in _apply
module._apply(fn)
File "/home/abc/anaconda3/envs/torch1.1/lib/python3.6/site-packages/torch/nn/modules/module.py", line 193, in _apply
module._apply(fn)
File "/home/abc/anaconda3/envs/torch1.1/lib/python3.6/site-packages/torch/nn/modules/module.py", line 193, in _apply
module._apply(fn)
[Previous line repeated 1 more time]
File "/home/abc/anaconda3/envs/torch1.1/lib/python3.6/site-packages/torch/nn/modules/module.py", line 199, in _apply
param.data = fn(param.data)
File "/home/abc/anaconda3/envs/torch1.1/lib/python3.6/site-packages/torch/nn/modules/module.py", line 265, in
return self._apply(lambda t: t.cuda(device))
RuntimeError: CUDA out of memory. Tried to allocate 44.00 MiB (GPU 0; 11.78 GiB total capacity; 281.29 MiB already allocated; 29.56 MiB free; 18.71 MiB cached)
Do you meet this problem

I use 8 1080Ti GPUs. If you use fewer GPUs than that, you can decrease the batch-size. Just make sure you also decrease the initial learning rate with the same ratio as batch-size.

I use 8 1080Ti GPUs. If you use fewer GPUs than that, you can decrease the batch-size. Just make sure you also decrease the initial learning rate with the same ratio as batch-size.

I use 8 1080Ti GPUS too. When I decrease batch-size to 8, the error still exist.
I train mobilenetV2-1x(flops: 300.7M, same with tensorflow), get top-1: 73%, batch-size=256, total epoch: 300 epoch, learning rate: 0.1(consine decay to 0.0001), weight decay: 4e-5.  tensorflow official results is top1 72%. I find many paper show mobilenetV2-1x top1: 72% too. Do you train mobilenetV2 by yourself?
Thank you very much.

I use 8 1080Ti GPUs. If you use fewer GPUs than that, you can decrease the batch-size. Just make sure you also decrease the initial learning rate with the same ratio as batch-size.

I use 8 1080Ti GPUS too. When I decrease batch-size to 8, the error still exist.
I train mobilenetV2-1x(flops: 300.7M, same with tensorflow), get top-1: 73%, batch-size=256, total epoch: 300 epoch, learning rate: 0.1(consine decay to 0.0001), weight decay: 4e-5. tensorflow official results is top1 72%. I find many paper show mobilenetV2-1x top1: 72% too. Do you train mobilenetV2 by yourself?
Thank you very much.

I released my search results, it is in the models part. You can download the models as well as the corresponding network structure by clicking the download link.
I use batchsize = 1024, total epoch: 256 learning_rate : 0.5( linear decay to 0) weight decay 4e-5. Just as the default value in the evaluation code. I think there could be some deviation in the results if you use more advanced training scheme and which will also yields accuracy enhancement in accuracy of the searched model.

hello   how do you   use  8 1080ti gpu?  it needs add new codes  for useing  it? i use os.environ....=[0,1,2,3]    it doesn't work.  @Zeitzmz


use meta to start agent and managedhub controllers

Summary
Related issue(s)
Fixes #
Tests

[x] Unit/function tests have been added and incorporated into make unit-tests.
[x] Integration tests have been added and incorporated into make integration-test.
[x] E2E tests have been added and incorporated into make e2e-test-all.
[ ] List other manual tests you have done.

/cc @clyang82 @yanmxa

/retest


Question for the code?

Hello:
Great work! I have two questions for your code:
(1)  In code of the "Model forward()", I found an "exposure_idx" attribute, Did you use this variable in your experiments?

(2) Use a 3D Bilateral Grid during the training stage, and disable the 3D Bilateral Grid during the eval stage, is that correct?
Thanks!!

Hi, thanks for your questions!

The exposure_idx is used for the RawNeRF setting, which is originally included in the zipnerf-pytorch codebase. While our method does not use it.
In the eval stage, I think we have to disable the 3D bilateral grid as we don't have them for test views. The evaluation is borrowed from previous papers (RawNeRF, MipNeRF): In the training stage, per-view exposure/GLO will be optimized. In the eval stage, GLO vectors/exposure values are set to uniform values, and color-corrected metrics are used to reflect photometric distances.

Hi, thanks for your questions!

The exposure_idx is used for the RawNeRF setting, which is originally included in the zipnerf-pytorch codebase. While our method does not use it.
In the eval stage, I think we have to disable the 3D bilateral grid as we don't have them for test views. The evaluation is borrowed from previous papers (RawNeRF, MipNeRF-360): In the training stage, per-view exposure/GLO will be optimized. In the eval stage, GLO vectors/exposure values are set to uniform values, and color-corrected metrics are used to reflect photometric distances.

Thanks for your reply.  But I found that "num_glo_features" variables in your "model.py” sets to zero, sound like u did not use this varibles. And Also, I did not find the setting for this variable "num_glo_features" in any other *.gin files. Thanks

Sorry for misleading you.
I mean the use of 3D bilateral grids is like GLO vectors'. The per-view 3D bilateral grids will be optimized during the training stage and set to identity transforms (equivalent to disabled) during the eval stage. Not to say GLO vectors are used in our method.

Thanks for your reply, thank you very much


Adds a easier way to see the demos - closes #7

@eduardolundgren, @brunobasto, could you guys check if this pull supplies the requirement of the issue https://github.com/metal/metal-router/issues/7 or if it is helpful at least?
cc. @mairatma.

Just started reviewing :) :octocat: Sent from GH.

Thank you, pull request merged! See changes here. :octocat: Sent from GH.


export: avoid error on unbound variable (IDFGH-9586)

Might stop sourcing export.sh when set -u is used (typically with direnv):

/path/to/esp-idf/export.sh:16: IDF_EXPORT_QUIET: unbound variable

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

Hi @MarcFinetRtone ,
Can you please explain in more detail what issue is solving your proposal change?
What is the expected output, and what is the actual without your change?
Thanks

Hi @MarcFinetRtone , Can you please explain in more detail what issue is solving your proposal change? What is the expected output, and what is the actual without your change? Thanks

To describe here in the PR or in the commit message ?
Regarding the change:

without the change, if set -u is used in the shell sourcing export.sh stops on the unbound variable with the following error message:
with the change sourcing export.sh works

@MarcFinetRtone Thank you for clearing it up for me, I can see the issue now.
While testing it, I discovered the same problem with the unbound variable with IDF_PATH on line 75.
Can you please also fix this variable so we can merge it as one fix?
Thank you.

sha=13e59ed7a99f6bf7ee3d851faeee1fd4b3261ea5


E-filing: Clicking on "Complainant Type" makes multiple calls to Individual service

Describe the bug
The Individual service search API is being called two times back to back from the same page on the click of a button.
To Reproduce
Steps to reproduce the behavior:

Go to litigant home page
Click on 'File a case"
Navigate through the screens and reach "Respondent details" page
Open the developer tools console and open the Network tab.
Select "individual".
View the network tab.
Two requests are being made to the Individual service.

Expected behavior
A clear and concise description of what you expected to happen.
 In another API call, we are retrieving the individual data of the complainant, which may differ if an advocate is filing a case on behalf of a litigant.

Hi @rajeshcherukumalli  Please verify and confirm

Hi @Ramu-kandimalla @rajeshcherukumalli Tested the below cases in QA env, working as mentioned below

When an advocate files a case on behalf of a complainant — In two API calls, the responses are different.
When a complainant files a case — In two API calls, the response is the same.

Two API's

https://dristi-kerala-qa.pucar.org/individual/v1/_search?tenantId=kl&limit=1&offset=0&_=1730704799614
https://dristi-kerala-qa.pucar.org/individual/v1/_search?tenantId=kl&limit=1000&offset=0&_=1730704799539

Hi @Ramu-kandimalla  @rajeshcherukumalli  Tested the below cases in UAT environment, working as mentioned below

When advocate files a case on behalf of a complainant — In two API calls, the responses are different.
When a complainant files a case — In two API calls, the response is the same.


The sku was not found. Please fetch products first by calling getItems

Version of react-native-iap
5.0.0
Version of react-native
0.61.2
buildscript {
ext {
    buildToolsVersion = "29.0.3"
    minSdkVersion = 16
    compileSdkVersion = 29
    targetSdkVersion = 29
}

Platforms you faced the error (IOS or Android or both?)
Android (not tested on iOS)
Expected behavior
start purchase process
Actual behavior
get error: The sku was not found. Please fetch products first by calling getItems
Tested environment (Emulator? Real Device?)
Real Device
Steps to reproduce the behavior
Just copy past the code and run
componentDidMount() {
//
}
componentWillUnmount() {
//
}
requestSubscription = async (sku) => {
	try {
		await RNIap.requestSubscription(sku);
	} catch (err) {
		console.warn(err.code, err.message);
	}
}
render() {
// onPress={() => this.requestSubscription(itemSku[0])}
}

I solvd the issue doing like the following. But I have another issue
the item you were attempting to purchase could not be found
How to solve it please?
getItems = async () => {
	try {
		const products = await RNIap.getSubscriptions(itemSubs);
		this.setState({productList: products})
		console.log('productList',products);
	} catch (err) {
		console.log('getItems || purchase error => ', err);
	}
};
requestSubscription = async (sku) => {
	try {
		await this.getItems();
		await RNIap.requestSubscription(sku);
	} catch (err) {
		console.warn(err.code, err.message);
	}
}

and declare this before export default class
const itemSku = Platform.select({
	ios: ['com.example'],
	android: ['com.example'],
});
const itemSubs = Platform.select({ ios: ['1234', '1233'], android: ['12345', '12346'] });

FIXED: it's google play config.
I had to add my device email as tester account in google play console.


Error when build with vue-tsc

Terminal command: vue-tsc --noEmit && vite build  --mode production
node_modules/vue-collapsed/dist/index.d.ts:1:15 - error TS1005: ',' expected.
1 import { type PropType } from 'vue';
If I delete the word type in the index.d.ts, the build runs normally. Please tell me how to fix this error so that you don't have to go to the root of the add-on after each update of the packages.
Vue-collapsed version - 1.1.3

Hi Yogurt, make sure you have added this property to your tsconfig.json:
{
   "compilerOptions": {
      "skipLibCheck": true,
   },
}

Hi Yogurt, try to add skipLibCheck to your tsconfig.json:
{
   "compilerOptions": {
      "skipLibCheck": true,
   },
}

You can try to add it to your CLI command: vue-tsc --noEmit --skipLibCheck && vite build --mode production

You can try to add it to your CLI command: vue-tsc --noEmit --skipLibCheck && vite build --mode production

Good idea, but the result is the same (

I had another good idea, try to update to the latest version and check if the error is still there:
pnpm add vue-collapsed@latest

I had another good idea, try to update to the latest version and check if the error is still there:
pnpm add vue-collapsed@latest


Handle inherited security policy in linked schemas

Rationale
In the case of an inherited security policy, the container's resource ID is not the same as its policy's resource ID. Need to always stash and compare the resource ID of the policy.
Related Pull Requests

https://github.com/LabKey/platform/pull/3141

LinkedSchemaTest passed:

https://teamcity.labkey.org/viewLog.html?buildId=1776983&buildTypeId=LabKey_223Release_Community_BvtAPostgres
https://teamcity.labkey.org/viewLog.html?buildId=1776985&buildTypeId=LabKey_223Release_Community_BvtASqlserver


PCC mismatch on final whisper layer

torch computations produced different results on bfloat16 based on whether the tensor is contiguous.  The solution was to put contiguous in a number of locations to get the final layer to match to torch.

some data:

FP32 is bug free for the continguous and non-continguous (for bfloat16, PCC mismatch is seen non-continguous but not seen in continguous format)
this is observed with torch op in its functional form vs. huggingface form (not in ttnn)

Next step: we should align to use fp32 with torch program as golden (and not bfloat)


reduce some warnings

will reduce roughly 1300 lines of warnings in pytest warning summary section. Save some time scrolling through the logs.
PendingDeprecattionWarning is okay to ignore for now.

passed internally. ready to merge.

related to #3152

Why are PendingDeprecationWarning "okay to ignore for now"?

Why are PendingDeprecationWarning "okay to ignore for now"?

Because it's pending. It has another step to becoming DeprecationWarning. If I understand correctly. Besides that, nobody is going to update the APIs to the latest, why we bother to see those 1k lines of warnings every day?


Conflict with Better Target

When both Better Target and Border-Control are enabled, the following error message is printed to the console:
k: Conflict detected between 'better-target' and 'Border-Control'.
Failed to wrap 'Token.prototype._refreshTarget' for 'better-target' with type OVERRIDE. A OVERRIDE wrapper for the same method has already been registered by 'Border-Control'.
    at Function.🎁register [as register] (https://localhost:4004/modules/lib-wrapper/lib-wrapper.js:1:25087)
    at https://localhost:4004/modules/better-target/modules/better_target.js:10:13
    at Function._call (eval at <anonymous> (https://localhost:4004/modules/lib-wrapper/lib-wrapper.js:1:27151), <anonymous>:4:14)
    at Function.callAll (https://localhost:4004/scripts/foundry.js:2456:12)
    at Game.setupGame (https://localhost:4004/scripts/foundry.js:6560:11)
    at async Game._initializeGameView (https://localhost:4004/scripts/foundry.js:7319:5)
    at async Game.initialize (https://localhost:4004/scripts/foundry.js:6471:29)

This is known an unavoidable. Simply prioritise better target in lib wrapper to use its targeting system

I still get the following if I prioritize better target:
modules/lib-wrapper/lib-wrapper.js:1 libWrapper: Conflict detected between module 'Border-Control' and 'better-target'.
Module 'better-target' has higher priority, and is replacing the OVERRIDE registered by 'Border-Control' for 'Token.prototype._refreshTarget'.

I guess there is no avoiding this either.

That is how lib wrapper works yes

Maybe there is a way to forgo the registration of Token.prototype._refreshTarget if Better Target is detected?


TextArea, Inputの重複した属性を削除

Changes
TextArea, Inputについて、Propsで指定している属性と、Omitで除外している属性が重複していたので削除したい。
意図的に重複させているのであれば無視してください。
Check

[ ] Added new Component

[ ] Added data-* prop and id prop

[ ] Updated Ubie Vitals or Added an update issue(if needed)

@8845musign I thought this was done intentionally to add a comment, but is my understanding correct?

@tonkotsuboy @takanorip
I dare to define it clearly in order to show the description in the Props table of Ubie Vitals.
Some Ubie UI can use native element attributes, others cannot. The props that need to be used explicitly should be displayed in the Props table.
However, this is redundant as an implementation; it may be a problem to be solved on Ubie Vitals.
I would be happy to incorporate this change.


add I_start and start_guess to phase_diagram function

This time I'm testing it in my actual use case before merging and re-tagging...I was overconfident previously, and I am paying for my sins in a messy version history.

Codecov Report

Merging #47 (5e85c79) into main (149da25) will not change coverage.
The diff coverage is 0.00%.

@@           Coverage Diff           @@
##             main      #47   +/-   ##
=======================================
  Coverage   53.37%   53.37%
=======================================
  Files          14       14
  Lines         356      356
=======================================
  Hits          190      190
  Misses        166      166

Impacted Files
Coverage Δ

src/phase_diagrams.jl
63.82% <0.00%> (ø)

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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Visualizer: search bar is not working

Seems like the /* global $ */ won't import the $ properly, and I get ReferenceError for $ when I try to active the local searching bar.
After taking a look at the whole visualizer directory, sometime we use the document.querySelector & document.querySelectorAll, and the other time we use the $ & $$, which are defined locally. Is there any specific reason that we choose one over the other, except that the dollar sign could simplify the code?
If we want to choose the dollar sign all the time, maybe we should move the code that define them into domUtil.js? @pdubroy what do you think?

No, there's no strong reason to use one or the other. The /* global $ &*/ just tells eslint not to complain that it's undefined -- I guess it used to be defined globally, but isn't anymore.
I considered moving it into domUtil,

(whoops, didn't mean to close)
I think we could move them into domUtil.

I see. I could try to move them this afternoon, or you want to do it by yourself?

Feel free to do if if you have time, otherwise I can try to do it tomorrow.
Thanks for noticing and filing the bug :-)
On Thu, Jun 30, 2016 at 10:14 PM, Meixian Li<EMAIL_ADDRESS>wrote:

I see. I could try to move them this afternoon, or you want to do it by
yourself?
—
You are receiving this because you modified the open/close state.
Reply to this email directly, view it on GitHub
https://github.com/cdglabs/ohm/issues/121#issuecomment-229774979, or mute
the thread
https://github.com/notifications/unsubscribe/AABDjRtLdWKvDAtVoGXEXmUm3zkndCSyks5qRCO4gaJpZM4JCgVL
.

Solved by #122


Cannot post anything to the forum - marked as containing spam

Ironically, I was trying to ask how to deal with spam, but my post was marked as spam and could then not post anything - new thread or reply.

I'm really sorry but I haven't had time yet to look at this. I'll try to see if I can find some time this week.

@snapey heya, I just tried it myself. I can't see any reason why your content would be flagged as spam. Are you still experiencing the problem?

Yes, just tried it and still being flagged as spam

The only way your post can be marked as spam is because of Akismet because that's the only spam method implemented atm. I'm gonna turn it off for now because it has been proven ineffective a lot in the past. But if the forum gets flooded with spam I'll turn it back on and we'll have to look for a different solution.

There needs to be a mechanism to report spam so that a mod can check and nuke.  You may need additional moderators to do this though.  The site already has spam items and it was trying to alert this when I first had an issue

Still the same.. Did you turn it off?

I forgot we have config caching enabled. I just triggered a new deploy. Can you try again? Sorry about that.
And yeah, I fully agree with you. I'll try to look into improving that and provide more options for users to flag content as spam.

I can post now thanks. https://laravel.io/forum/massassignmentexception-in-modelphp-line-444-token

Ok glad it works for you now. Thanks for reporting!


Using Variable Length Time Series

One of the features of PyPortfolioOpt is that is setup to use different length time series:
Robust to missing data, and price-series of different lengths (e.g FB data only goes back to 2012 whereas AAPL data goes back to 1980).
I am able to get the library to work fine when I pre-process the inputs to have all the same lengths, however when I have a pandas dataframe indexed / sorted by dates, I will get different errors based on how I'm setting up the pandas array.
What is the correct way to do this? I assume only a portion of the system may be used like this, for instance covariance must be implicit model to model.
Method used
data = [pd.DataFrame({mod.name: mod.rawperf},index=mod.rawtime) for mod in p.models]
pdf = pd.concat(data,axis=1).sort_index()

Results in error:
ValueError: Workspace allocation error!

miniconda3/envs/smxenv/lib/python3.8/site-packages/pypfopt/base_optimizer.py in _solve_cvxpy_opt_problem(self)
    237                 )
    238             else:
--> 239                 self._opt.solve(verbose=self._verbose, **self._solver_options)
    240         except (TypeError, cp.DCPError) as e:
    241             raise exceptions.OptimizationError from e
    ```

Hi @SoundsSerious!
Indeed, it is possible to work with different length time-series.
For example, the dataset from the screenshot below works just fine, even though there are missing values in the beginning.
If your data frame looks similar, this should not be the cause of the issue. Please keep in mind that if the time-series are of different lengths, you implicitly assume that there was no change in the distribution of the assets for the different sub periods, which might be more or less realistic depending on your data set at hand.

The error ValueError: Workspace allocation error! looks more like you might be running out of memory. Can you run the optimisation again and monitor your memory usage?

@phschiele Ah thanks! Will try this when I get home.
I have 128GB of memory and my dataset size is only like ~2800, or 6 models-monthly for maybe a decade so I'm pretty doubtful I'm running out of memory. This issue describes something similar happening if there are NaN's or Zeros https://github.com/robertmartin8/PyPortfolioOpt/issues/160


[Bug] jdbc can not copy lib jars on workspace

Search before asking

[X] I searched the issues and found no similar issues.

Linkis Component
linkis-engineconnn-plugin
Steps to reproduce

jdbc can not copy lib jars on workspace
2022-09-14 08:48:49.048 ERROR Job with execId-IDE_hdpu_jdbc_2 + subJobId : 117  execute failed,21304, Task is Failed,errorMsg: errCode: 12003 ,desc: pnode3:9101_31 Failed  to async get EngineNode AMErrorException: errCode: 30002 ,desc: ServiceInstance(linkis-cg-engineconn, pnode3:19057) ticketID:8be5e15d-daa6-4891-8319-50e6fdd99032 初始化引擎失败,原因: Failed to start EngineConn, reason: ECMErrorException: errCode: 11102 ,desc: Java HotSpot(TM) 64-Bit Server VM warning: ignoring option MaxPermSize=250m; support was removed in 8.0
Java HotSpot(TM) 64-Bit Server VM warning: ignoring option PermSize=128m; support was removed in 8.0
错误: 找不到或无法加载主类 org.apache.linkis.engineconn.launch.EngineConnServer
,ip: pnode3 ,port: 9102 ,serviceKind: linkis-cg-engineconnmanager
You can go to this path(/home/hdpu/apps/linkis/appcom/hdpu/20220914/jdbc/8be5e15d-daa6-4891-8319-50e6fdd99032/logs) to find the reason or ask the administrator for help ,ip: pnode3 ,port: 9101 ,serviceKind: linkis-cg-linkismanager ,ip: pnode3 ,port: 9104 ,serviceKind: linkis-cg-entrance

Expected behavior
use jdbc
Your environment

Linkis version used: 1.1.2
Environment name and version:

cdh-5.14.2
hdp-3.1.5
hive-2.1.1
spark-3.2.1
scala-2.12.2
jdk 1.8.0_121
....

Anything else
No response
Are you willing to submit a PR?

[X] Yes I am willing to submit a PR!

This should be caused by the fact that the user who started the engine does not have permission to the lib directory of the engine, and the main class cannot be found because the corresponding module is not loaded.
这个应该是启动引擎的用户对引擎的lib目录没有权限导致，没有加载对应的模块导致找不到主类。建议不适用/home目录安装


Missleading integrity error

If a package is not supported for your platform, pacaur prints an integrity error, which is wrong. This was tested on an ARM installation, however this could also happen to x64 exclusive software for example.
[alarm@alarmpi pacaur]$ pacaur -S mkinitcpio-tinyssh
:: Package(s) mkinitcpio-tinyssh not found in repositories, trying AUR...
:: resolving dependencies...
:: looking for inter-conflicts...

AUR Packages  (3) mkinitcpio-tinyssh-0.0.3-1  tinyssh-20160812-1  ucspi-tcp-0.88-6

:: Proceed with installation? [Y/n] y
:: Retrieving package(s)...

Cloning into 'mkinitcpio-tinyssh'...
remote: Counting objects: 7, done.
remote: Compressing objects: 100% (7/7), done.
remote: Total 7 (delta 0), reused 0 (delta 0)
Unpacking objects: 100% (7/7), done.
Checking connectivity... done.
Cloning into 'tinyssh'...
remote: Counting objects: 9, done.
remote: Compressing objects: 100% (9/9), done.
remote: Total 9 (delta 0), reused 1 (delta 0)
Unpacking objects: 100% (9/9), done.
Checking connectivity... done.
Cloning into 'ucspi-tcp'...
remote: Counting objects: 6, done.
remote: Compressing objects: 100% (6/6), done.
remote: Total 6 (delta 0), reused 6 (delta 0)
Unpacking objects: 100% (6/6), done.
Checking connectivity... done.
:: View mkinitcpio-tinyssh PKGBUILD? [Y/n]
:: mkinitcpio-tinyssh PKGBUILD viewed
:: View mkinitcpio-tinyssh.install script? [Y/n] y
:: mkinitcpio-tinyssh.install script viewed
:: View tinyssh PKGBUILD? [Y/n] n
:: View tinyssh.install script? [Y/n] n
:: View ucspi-tcp PKGBUILD? [Y/n] n
:: Checking ucspi-tcp integrity...
==> ERROR: ucspi-tcp is not available for the 'armv7h' architecture.
:: Checking tinyssh integrity...
==> ERROR: tinyssh is not available for the 'armv7h' architecture.
:: Checking mkinitcpio-tinyssh integrity...
==> Making package: mkinitcpio-tinyssh 0.0.3-1 (Sat Sep 10 06:42:20 UTC 2016)
==> Retrieving sources...
  -> Downloading mkinitcpio-tinyssh-0.0.3.tar.gz...
  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100   137    0   137    0     0    227      0 --:--:-- --:--:-- --:--:--   228
100  2385    0  2385    0     0   1948      0 --:--:--  0:00:01 --:--:--  9937
==> Validating source files with sha512sums...
    mkinitcpio-tinyssh-0.0.3.tar.gz ... Passed
:: failed to verify ucspi-tcp integrity
:: failed to verify tinyssh integrity

Pacaur is solely developed for the official Arch variants. This does not include ARM, but patches welcome.

As I already said, this was only tested on arm, but its very likely that it will also happen with an x64 exclusive package. So please reopen this issue, it is still valid for the normal arch. It was just simpler for me to reproduce this way.

No, it's not likely, unless the x86_64 arch is missing from the PKGBUILD/.SRCINFO file. In which case the PKGBUILD should be fixed.
The issue here is that armv7h is unsupported, as the makepkg output states.

And what if you have an x32 or x64 only application that will not work on the other architecture? It is intended that the installation will fail (as it does right now too), however the error message below is wrong. And that is the point.
As a sideeffect I want to ignore those errors, but that has nothing to do with the actual issue. Sorry for not clarifying this enough.
The error must be somewhere around here:
https://github.com/rmarquis/pacaur/blob/master/pacaur#L936-L951
Wouldn't it also make sense to abort on the first invalid checksum error? Right now it will download all sources and then finally fail. You should know best if it makes sense to abort after the first error.

Short answer:

but patches welcome
This means that absolutely no support is provided, unless you are ready to pay for it.

Both works for me.
Long answer: I absolutely don't care about the dying 32 bit arch, and if the software is open source then a 64 bit version can be provided. I am yet to see such a package, and I also absolutely don't care about arm.

Wouldn't it also make sense to abort on the first invalid checksum error?

No, for the same reason pacaur display all deps not found rather than aborting after the first error.

Okay, alright. Is a different error message also not an option for you? You might want to put it in other words, but basically this would give the best hint:
failed to verify ${colorW}$i${reset} integrity or is incompatible with your arch


Inline Mode - Change event not triggering and can't set specified color

Hello,
Thank you for share your picker.
When i use Coloris in inline mode the input text (#clr-color-value) don't trigger the change event and don't select the color entered. When the picker isn't in inline mode the change event is triggered.
An other problem, always in inline mode, i can't change the select color by code. Can you add a function to update the current color ? Like Coloris.update('#C4C4C4') ou Coloris.set({color:'#C4C4C4'}). I see in source the setColorFromStr() function but it not a public function...
@+

Thank you for reporting this issue. The first problem is indeed a bug, I will release a fix shortly.
As for the second problem, to change the color programmatically in inline mode, you need to set the value of the input #clr-color-value, then trigger a change event on it. Example:
document.querySelector('#clr-color-value').value = 'green';
document.querySelector('#clr-color-value').dispatchEvent(new Event('change', { bubbles: true }));

This will work after I release a fix for the first problem.

The new release fixes this issue

The new version work perfectly.
Thank you very much for your quick update.


Shift along slice direction between image and overlay

Sometimes, the QC report shows an overlay which is shifter by one slice compared to the background image, as illustrated below:

To reproduce:
SCT commit 6cd471ae1c153c71d51ad0c8c808082cd4e1e756
Data:  data_issue2453.zip
Syntax:
sct_qc -i PAM50_t1_reg.nii.gz -p sct_register_multimodal -s sub-amu01_acq-T1w_MTS_seg.nii.gz -d sub-amu01_acq-T1w_MTS_crop.nii.gz

One possible cause of the issue: the segmentation sub-amu01_acq-T1w_MTS_seg.nii.gz is not in the same voxel space as the destination sub-amu01_acq-T1w_MTS_crop.nii.gz.
I've tried replacing sub-amu01_acq-T1w_MTS_seg.nii.gz by a segmentation in the same voxel space as the destination, and the issue is still there.

Tried to interpolate with spline and linear: issue still there

The issue seems to be related to incorrect q/sform fields.
When resampling an image with the same q/sform, or with qform_code=2, the resampling does not produce the issue.
However, when resampling an image with qform_code=1, which does not follow the conventions, as raised in #2454, the resampling is producing the issue.
So, until we solve #2454, we should check the consistency of the qform_code before resampling, and if it is inconsistent, fix it (outputing a warning along the way).

When enforcing the qform to 0 or 1, the issue is not solved.

The problem was solved by changing resampling mode from constant to nearest.


Synced Folder names are made to be lower case

Is there an existing issue for this?

[X] I have searched the existing issues

Current Behavior:
Right now, when a Folder is synced across from Kitsu it's name is forced to be lower case as part of the slug-ification, so for example an asset cameraA in Kitsu will be created in AYON as cameraa. The label will still be correct as that's just copied straight across.
Expected Behavior:
As AYON Folders support upper case characters in their name, I would expect the name to be synced across to match if the entity name in Kitsu is already a valid name in AYON. This isn't a big deal as we should be linking them through their kitsuId metadata anyway, but it can cause some unnecessary confusion when the asset name in UIs and on disk don't match Kitsu
Version
1.0.0
What platform you are running on?
Linux / Centos
Steps To Reproduce:

Ensure that the Kitsu service is setup in AYON.
Create a new entity in Kitsu with capitals in the name, e.g bobLoblawA
The created Folder in AYON will have a name of bobloblawa

Are there any labels you wish to add?

[X] I have added the relevant labels to the bug report.

Relevant log output:
No response
Additional context:
No response

@martastain @BigRoy it looks like Tasks have this same behaviour - are you happy for this to be changed to match capitalisation in names for both Tasks and Folders? If so I'm happy to raise a PR for this change! :)

Also - unrelated to this issue but a couple of inconsistencies I ran into with the support form for raising this issue (which is great by the way!):

I was only able to select 1.0.0 as the version for the addon, but this was actually with v1.2.3
I had to select that I'd added all the relevant labels to the bug report, but I don't seem to have the ability to add labels to an issue (perhaps I missed it but I don't think so).


OIDC Authentication redirect_uri incorrect

What are the exact steps to set this up for an external host? It seems like that http://localhost:8888 is everywhere.
I got it accessible, but OIDC gives the following error:
Redirect URI Error
The request fails due to a missing, invalid, or mismatching redirection URI (redirect_uri).

The redirect URI in the URL, looks as expected.
I change my domain name in:
env.oidc
env.outline
config.sh
Later on I found a reference in oidc-server-outline-client.json as well, but didn't solve the issue.
I did a clean-data or clean and now OIDC says The client identifier (client_id) is missing or invalid.
However the client_id is matching with the references I can find.

Got it! You are supposed to adjust config.sh before running make install.


gulp build needs a prerequisite in the README.md

I had to do this on my Mac...
npm install --global gulp npm link gulp
gulp build
Cudo's to you. This is the best GDPR example I seen so far.

@ascooper57 you do know this is not GDPR compliant right?
See: https://github.com/insites/cookieconsent/issues/409#issuecomment-404567026 and https://github.com/insites/cookieconsent/issues/242


Add instructions to README.md for downloading value sets from VSAC

Add instructions for how to download value sets from VSAC, as documented by Issue https://github.com/ccsm-cds-tools/ccsm-cds-dashboard/issues/16.

I also added a section called Configuring Dashboard Environment, that links to the Environment Setting for Dashboard section of the Wiki. This should close out the discussion in Issue https://github.com/ccsm-cds-tools/ccsm-cds-dashboard/issues/13.


python310Packages.databricks-connect: 9.1.10 -> 9.1.11

Automatic update generated by nixpkgs-update tools. This update was made based on information from passthru.updateScript.
meta.description for python310Packages.databricks-connect is: "Client for connecting to remote Databricks clusters"
meta.homepage for python310Packages.databricks-connect is: "https://pypi.org/project/databricks-connect"
meta.changelog for python310Packages.databricks-connect is: ""
Updates performed

Ran passthru.UpdateScript

To inspect upstream changes
Impact

Checks done (click to expand)

built on NixOS
The tests defined in passthru.tests, if any, passed
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/.find_spark_home.py-wrapped had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/docker-image-tool.sh had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/sparkR.cmd had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/load-spark-env.cmd had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/load-spark-env.sh had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/find-spark-home had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/spark-submit had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/sparkR had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/spark-class had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/spark-submit.cmd had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/spark-class.cmd had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/pyspark2.cmd had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/find_spark_home.py had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/run-example.cmd had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/spark-shell2.cmd had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/pyspark had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/spark-shell.cmd had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/spark-sql.cmd had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/spark-class2.cmd had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/find-spark-home.cmd had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/pyspark.cmd had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/pyspark-bazel had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/quicksilver had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/spark-shell had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/databricks-connect had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/spark-sql2.cmd had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/spark-shell-bazel had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/beeline.cmd had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/.databricks-connect-wrapped had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/spark-submit2.cmd had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/beeline had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/sparkR2.cmd had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/run-example had a zero exit code or showed the expected version
Warning: no invocation of /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin/spark-sql had a zero exit code or showed the expected version
0 of 34 passed binary check by having a zero exit code.
0 of 34 passed binary check by having the new version present in output.
found 9.1.11 with grep in /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11
found 9.1.11 in filename of file in /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11

Rebuild report (if merged into master) (click to expand)

4 total rebuild path(s)

2 package rebuild(s)

2 x86_64-linux rebuild(s)
2 x86_64-darwin rebuild(s)

First fifty rebuilds by attrpath
python310Packages.databricks-connect
python39Packages.databricks-connect

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A python310Packages.databricks-connect https://github.com/r-ryantm/nixpkgs/archive/1097d4706f797f6dcfdc0d10b64d3c3cf20597d1.tar.gz

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11
ls -la /nix/store/q6qsjhygaj78hykavjx76ppqz5g598i1-python3.10-databricks-connect-9.1.11/bin

Pre-merge build results
We have automatically built all packages that will get rebuilt due to
this change.
This gives evidence on whether the upgrade will break dependent packages.
Note sometimes packages show up as failed to build independent of the
change, simply because they are already broken on the target branch.
Result of nixpkgs-review run on x86_64-linux 1

2 packages built:

python310Packages.databricks-connect
python39Packages.databricks-connect

Maintainer pings
cc @kfollesdal for testing.

Nixpkgs is on a newer version


module 'jaxlib.xla_client' has no attribute 'register_cpu_custom_call_target'

Description
module 'jaxlib.xla_client' has no attribute 'register_cpu_custom_call_target'

https://github.com/gdsfactory/gplugins/actions/runs/6230788778
@flaport
What jax/jaxlib version are you using?
jax 0.4.16 jaxlib 0.4.16
Which accelerator(s) are you using?
CPU
Additional system info
Linux
NVIDIA GPU info
No response

Sorry for the breakage.
You'll need to update the caller to use register_custom_call_target instead.
APIs under jaxlib aren't technically public, so some breakage is possible. We're working on a more stable custom kernel API.

Closing because there's no action for us here.


Use dict.update properly; fix #27

Should I write a test too?

Huh, someone should write a "make flake8 happy" PR.


Provide Open API schema for new policies

Description
Use Open API schema to provide a full spec for the new policies just like we did for the old policies.

Duplicate of #1274


Find some way in the MUD to recognize everyone who has contributed to it!

I've had an idea of being able to interact with a version of the Octocat statue that's in the actual Github space, if we continue to use that model. I've imagined user generated content coming through of things the Octocat could say, or jokes to the speakers, or what not. But it would be pretty fun to "ask the Octocat who made the space" and get a list of contributors!

For now, we've just got a link to the GH contributors page. Not ideal, but good enough for the meetup?


Delete messages in bulk after upload succeeded

Right now messages are deleted immediately after they have been read, which might lead to loss of messages in case of S3 problems (bad configuration).
This PR picks up the TODO in the code and deletes the messages in batch after the upload to S3 has succeeded.

Thank you for the PR @m90!


Use SPDX license expression in package.json

Thanks so much for xhr! I use it in several projects!
This tiny PR changes the current package.json property licenses to a license property with just the string "MIT". This is the machine-readable way to add license metadata, and also what npm recommends. The Ruby-style license array is equally well structured, but we've landed on the string license expression approach for npm.
Best,
K

Thank you!
Merging, will release to npm along with some other changes

Thanks so much!


RuntimeError: Placeholder storage has not been allocated on MPS device!

Bug description
There was an exception when I ran the official code.
What version are you seeing the problem on?
v2.0
How to reproduce the bug
# main.py
# ! pip install torchvision
import torch, torch.nn as nn, torch.utils.data as data, torchvision as tv, torch.nn.functional as F
import lightning as L
from torch import Tensor

# --------------------------------
# Step 1: Define a LightningModule
# --------------------------------
# A LightningModule (nn.Module subclass) defines a full *system*
# (ie: an LLM, diffusion model, autoencoder, or simple image classifier).
# define any number of nn.Modules (or use your current ones)
encoder = nn.Sequential(nn.Linear(28 * 28, 128), nn.ReLU(), nn.Linear(128, 3))
decoder = nn.Sequential(nn.Linear(3, 128), nn.ReLU(), nn.Linear(128, 28 * 28))

class LitAutoEncoder(L.LightningModule):
    def __init__(self):
        super().__init__()
        self.encoder = encoder
        self.decoder = decoder

    def forward(self, x):
        # in lightning, forward defines the prediction/inference actions
        embedding = self.encoder(x)
        return embedding

    def training_step(self, batch, batch_idx):
        # training_step defines the train loop. It is independent of forward
        x, y = batch
        x = x.view(x.size(0), -1)
        z = self.encoder(x)
        x_hat = self.decoder(z)
        loss = F.mse_loss(x_hat, x)
        self.log("train_loss", loss)
        return loss

    def configure_optimizers(self):
        optimizer = torch.optim.Adam(self.parameters(), lr=1e-3)
        return optimizer

# -------------------
# Step 2: Define data
# -------------------
dataset = tv.datasets.MNIST(".", download=True, transform=tv.transforms.ToTensor())
train, val = data.random_split(dataset, [55000, 5000])

# -------------------
# Step 3: Train
# -------------------
autoencoder = LitAutoEncoder()
trainer = L.Trainer(limit_train_batches=100, max_epochs=1)
trainer.fit(autoencoder, data.DataLoader(train), data.DataLoader(val))

checkpoint = "./lightning_logs/version_0/checkpoints/epoch=0-step=100.ckpt"
autoencoder = LitAutoEncoder.load_from_checkpoint(checkpoint, encoder=encoder, decoder=decoder)

# choose your trained nn.Module
encoder = autoencoder.encoder
encoder.eval()

# embed 4 fake images!
fake_image_batch = Tensor(4, 28 * 28)
embeddings = encoder(fake_image_batch)
print("⚡" * 20, "\nPredictions (4 image embeddings):\n", embeddings, "\n", "⚡" * 20)

Error messages and logs
/Users/kylin/Library/Caches/pypoetry/virtualenvs/lightning-demo-01-7el2zk6k-py3.10/bin/python /Users/kylin/Documents/code/github/lightning_demo_01/main.py
GPU available: True (mps), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
/Users/kylin/Library/Caches/pypoetry/virtualenvs/lightning-demo-01-7el2zk6k-py3.10/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/logger_connector/logger_connector.py:67: UserWarning: Starting from v1.9.0, `tensorboardX` has been removed as a dependency of the `lightning.pytorch` package, due to potential conflicts with other packages in the ML ecosystem. For this reason, `logger=True` will use `CSVLogger` as the default logger, unless the `tensorboard` or `tensorboardX` packages are found. Please `pip install lightning[extra]` or one of them to enable TensorBoard support by default
  warning_cache.warn(
/Users/kylin/Library/Caches/pypoetry/virtualenvs/lightning-demo-01-7el2zk6k-py3.10/lib/python3.10/site-packages/lightning/pytorch/trainer/configuration_validator.py:68: UserWarning: You passed in a `val_dataloader` but have no `validation_step`. Skipping val loop.
  rank_zero_warn("You passed in a `val_dataloader` but have no `validation_step`. Skipping val loop.")

  | Name    | Type       | Params
---------------------------------------
0 | encoder | Sequential | 100 K
1 | decoder | Sequential | 101 K
---------------------------------------
202 K     Trainable params
0         Non-trainable params
202 K     Total params
0.810     Total estimated model params size (MB)
/Users/kylin/Library/Caches/pypoetry/virtualenvs/lightning-demo-01-7el2zk6k-py3.10/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/data_connector.py:432: PossibleUserWarning: The dataloader, train_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.
  rank_zero_warn(
Epoch 0: 100%|██████████| 100/100 [00:00<00:00, 194.97it/s, v_num=1]
`Trainer.fit` stopped: `max_epochs=1` reached.
Traceback (most recent call last):
  File "/Users/kylin/Documents/code/github/lightning_demo_01/main.py", line 65, in <module>
    embeddings = encoder(fake_image_batch)
  File "/Users/kylin/Library/Caches/pypoetry/virtualenvs/lightning-demo-01-7el2zk6k-py3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/Users/kylin/Library/Caches/pypoetry/virtualenvs/lightning-demo-01-7el2zk6k-py3.10/lib/python3.10/site-packages/torch/nn/modules/container.py", line 217, in forward
    input = module(input)
  File "/Users/kylin/Library/Caches/pypoetry/virtualenvs/lightning-demo-01-7el2zk6k-py3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/Users/kylin/Library/Caches/pypoetry/virtualenvs/lightning-demo-01-7el2zk6k-py3.10/lib/python3.10/site-packages/torch/nn/modules/linear.py", line 114, in forward
    return F.linear(input, self.weight, self.bias)
RuntimeError: Placeholder storage has not been allocated on MPS device!

Process finished with exit code 1

Environment

Current environment

CUDA:

GPU:               None
available:         False
version:           None

Lightning:

lightning:         2.0.5
lightning-cloud:   0.5.37
lightning-utilities: 0.9.0
pytorch-lightning: 2.0.5
torch:             2.0.1
torchmetrics:      1.0.1
torchvision:       0.15.2

Packages:

aiohttp:           3.8.4
aiosignal:         1.3.1
anyio:             3.7.1
arrow:             1.2.3
async-timeout:     4.0.2
attrs:             23.1.0
backoff:           2.2.1
beautifulsoup4:    4.12.2
blessed:           1.20.0
certifi:           2023.5.7
charset-normalizer: 3.2.0
click:             8.1.5
croniter:          1.4.1
dateutils:         0.6.12
deepdiff:          6.3.1
encoder:           1.1
exceptiongroup:    1.1.2
fastapi:           0.100.0
filelock:          3.12.2
frozenlist:        1.4.0
fsspec:            2023.6.0
h11:               0.14.0
idna:              3.4
inquirer:          3.1.3
itsdangerous:      2.1.2
jinja2:            3.1.2
lightning:         2.0.5
lightning-cloud:   0.5.37
lightning-utilities: 0.9.0
markdown-it-py:    3.0.0
markupsafe:        2.1.3
mdurl:             0.1.2
mpmath:            1.3.0
multidict:         6.0.4
networkx:          3.1
numpy:             1.25.1
ordered-set:       4.1.0
packaging:         23.1
pillow:            10.0.0
pip:               23.1.2
psutil:            5.9.5
pydantic:          1.10.11
pygments:          2.15.1
pyjwt:             2.7.0
python-dateutil:   2.8.2
python-editor:     1.0.4
python-multipart:  0.0.6
pytorch-lightning: 2.0.5
pytz:              2023.3
pyyaml:            6.0
readchar:          4.0.5
requests:          2.31.0
rich:              13.4.2
setuptools:        68.0.0
six:               1.16.0
sniffio:           1.3.0
soupsieve:         2.4.1
starlette:         0.27.0
starsessions:      1.3.0
sympy:             1.12
torch:             2.0.1
torchmetrics:      1.0.1
torchvision:       0.15.2
tqdm:              4.65.0
traitlets:         5.9.0
typing-extensions: 4.7.1
urllib3:           2.0.3
uvicorn:           0.23.0
wcwidth:           0.2.6
websocket-client:  1.6.1
websockets:        11.0.3
wheel:             0.40.0
yarl:              1.9.2

System:

OS:                Darwin
architecture:

64bit

processor:         arm
python:            3.10.12
release:           22.5.0
version:           Darwin Kernel Version 22.5.0: Thu Jun  8 22:22:23 PDT 2023; root:xnu-8796.121.3~7/RELEASE_ARM64_T6020

More info
No response

Hi @InfernalAzazel
The error occurs at the last two lines of your script:
fake_image_batch = Tensor(4, 28 * 28)
embeddings = encoder(fake_image_batch)

Change it to:
fake_image_batch = torch.rand(4, 28 * 28, device=autoencoder.device)
embeddings = encoder(fake_image_batch)

The code is wrong, because 1) torch.Tensor() shouldn't be used to create new tensors and 2) the tensor wasn't moved to the correct device before running through the model. Where did you take the code from? Can you share the link please?

Hi @InfernalAzazel
The error occurs at the last two lines of your script:
fake_image_batch = Tensor(4, 28 * 28)
embeddings = encoder(fake_image_batch)

Change it to:
fake_image_batch = torch.rand(4, 28 * 28, device=autoencoder.device)
embeddings = encoder(fake_image_batch)

The code was wrong, because 1) torch.Tensor() shouldn't be used to create new tensors and 2) the tensor wasn't moved to the correct device before running through the model. Where did you take the code from? Can you share the link please?

Good morning, this official code link should be outdated and have bugs.
https://lightning.ai/docs/pytorch/stable/starter/introduction.html

If you plan to modify docs, the following suggestions can be referenced！

AI is very profound, and with a usage example, it can help unfamiliar individuals quickly get started with lightning and develop a strong interest in it

import numpy as np
from PIL import ImageGrab

import torch
import tkinter as tk

from PIL.Image import Image

from use_model import encoder, autoencoder
from torchvision import transforms

def predict_digit(img: Image):
    # 将图像大小调整为 28x28 像素
    img = img.resize((28, 28))
    # 将 RGB 转换为灰度图像
    img = img.convert('L')
    # 定义转换操作，将图像转换为张量
    transform = transforms.ToTensor()
    # 将图像应用转换操作，得到张量
    tensor_image = transform(img)
    # 将张量形状从 (1, 28, 28) 转换为 (1, 784)
    tensor_image = tensor_image.view(1, 784)
    # 将张量转换为不需要梯度计算的形式
    tensor_image = tensor_image.detach().numpy()
    # 打印张量的形状
    print(tensor_image.shape)
    print(tensor_image)

    res = encoder(tensor_image)
    return np.argmax(res), max(res)

class App(tk.Tk):
    def __init__(self):
        tk.Tk.__init__(self)

        self.x = self.y = 0

        # Creating elements
        self.canvas = tk.Canvas(self, width=300, height=300, bg="white", cursor="cross")
        self.label = tk.Label(self, text="Thinking..", font=("Helvetica", 48))
        self.classify_btn = tk.Button(self, text="Recognise", command=self.classify_handwriting)
        self.button_clear = tk.Button(self, text="Clear", command=self.clear_all)

        # Grid structure
        self.canvas.grid(row=0, column=0, pady=2, sticky=tk.W)
        self.label.grid(row=0, column=1, pady=2, padx=2)
        self.classify_btn.grid(row=1, column=1, pady=2, padx=2)
        self.button_clear.grid(row=1, column=0, pady=2)

        # self.canvas.bind("<Motion>", self.start_pos)
        self.canvas.bind("<B1-Motion>", self.draw_lines)

    def clear_all(self):
        self.canvas.delete("all")

    def classify_handwriting(self):
        im = ImageGrab.grab(bbox=(self.canvas.winfo_rootx(), self.canvas.winfo_rooty(),
                                  self.canvas.winfo_rootx() + self.canvas.winfo_width(),
                                  self.canvas.winfo_rooty() + self.canvas.winfo_height()))

        digit, acc = predict_digit(im)
        self.label.configure(text=str(digit) + ', ' + str(int(acc * 100)) + '%')

    def draw_lines(self, event):
        self.x = event.x
        self.y = event.y
        r = 8
        self.canvas.create_oval(self.x - r, self.y - r, self.x + r, self.y + r, fill='black')

app = App()
app.mainloop()

e.g

Note that the UI code is correct and there are still bugs in the prediction code


Add linting

I'm working on #5 and one thing that's tricky is the inconsistent code style (semicolons on some lines and not on others, etc.).
I think it would be helpful to pick a style guide and go with it. I'm happy to fix all the style bugs. What style should we use?

Thanks for noticing that, I really haven't paid much attention to it :).
I'll be happy if we use feross/standard
On Jul 26, 2016 22:49, "Lon Ingram"<EMAIL_ADDRESS>wrote:

I'm working on #5
https://github.com/mariocasciaro/object-path-immutable/issues/5 and one
thing that's tricky is the inconsistent code style (semicolons on some
lines and not on others, etc.).
I think it would be helpful to pick a style guide and go with it. I'm
happy to fix all the style bugs. What style should we use?
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/mariocasciaro/object-path-immutable/issues/7, or mute
the thread
https://github.com/notifications/unsubscribe-auth/AAGbZ3SmxLe7SkOuhU5yXUo-TK2NlYS4ks5qZoDygaJpZM4JVoPL
.

Cool. I'll make that happen in a separate PR.

I think this has been fixed with #10


Variation on maze generator challenge

Choose the shape of your maze.

Community Contribution
Link to live project, video, or image:
https://editor.p5js.org/pazatico/full/-h8q01a1I
Sharing

[x] I would be happy to have my project shared on The Coding Train's social media!

Instagram:
Twitter:

Love the unicorn 🦄! Thanks for sharing


Rule proposal: No return ternary

You might sometimes write a ternary at the top-level when returning from a React component
// incorrect code
function Component({ isCondition }: { isCondition: true }) {
  return isCondition ? (
    <Some>
      <Conditional />
    </Some>
  ) : (
    <Other>
      <Happy>
        <Path>
          <With />
          <More />
          <Stuff />
        </Path>
      </Happy>
    </Other>
  );
}

But a clearer version would be to have an early return, when there is no shared parent component. This reduces unnecessary nesting, which often leads to large diffs. It also makes it easier easier to differentiate the conditional renders on the component level and the happy path.
// correct code
function Component({ isCondition }: { isCondition: true }) {
  if (isCondition)
    return (
      <Some>
        <Conditional />
      </Some>
    );

  return (
    <Other>
      <Happy>
        <Path>
          <With />
          <More />
          <Stuff />
        </Path>
      </Happy>
    </Other>
  );
}

And of course it would still be valid to have ternaries that are not at top-level in a return.
// correct code
function Component({ isCondition }: { isCondition: true }) {
  return (
    <Container>
      {isCondition ? <NestedComponent /> : <OtherComponent />}
    </Container>
  );
}

I searched for such a rule, but didn't find anything existing. Therefore, I propose a new stylistic rule react/no-return-ternary. This rule would also match the code examples and documentation for conditional rendering in the React docs.

Hmm… "cleaner" is pretty subjective there - i can see the ternary form being cleaner because the two blocks of jsx are aligned and the non-jsx boilerplate is minimal.


ssh bastion in dbt config

helpful: https://github.com/fishtown-analytics/autovacuum/blob/master/main.py#L63

use name of ssh config host

add ssh-host: {Host} to any run target
Host should be a Host listed in your ~/ssh/config file. The User and HostName fields are required in the config, and the Port and ConnectTimeout (seconds) can optionally be specified. Default port is 22 and default connect timeout is 10s


@export-ed variables set after _init

Godot version
v4.0.beta9.official [e780dc332]
System information
Win10
Issue description
For whatever reason, @export variables get set after _init is called, not before. This is a problem for scripts that extend from Resource (IE custom texture things), as they don't have the _ready method to jank their way around it.
If this is intended there should be a way to specify whether they're set before or after _init (similar to what @onready does).
Steps to reproduce
Run sample project; You can see the TextureBinder thats been assigned to the main scene's node in the inspector.
Minimal reproduction project
ExportVarsWrongOrderOfOperationsAAAAA.zip

This behavior is intended.
_init() is the constructor of the object. Exported properties are available after _init() from the perspective of outside code. So the saved values can only be set after _init().
You want to update _tex_pix based on source_tex in the MRP:
extends Texture2D

@export var source_tex: Texture2D

var _tex_pix: Image

func _init () -> void:
	_tex_pix = source_tex.get_image()

Here you can define a setter for source_tex and initialize _tex_pix there:
extends Texture2D

@export
var source_tex: Texture2D:
	set(v):
		source_tex = v
		_tex_pix = v.get_image()

var _tex_pix: Image

That's real unfortunate :(
For context in my actual project I'm creating dynamic textures (emulation's of ones Minecraft used to have), so I have the input textures (in this case an AtlasTexture for the clock sprite, and a Texture2D for its dial), and then create its output Image based on the atlastex's size.
func _init () -> void:
	_item_pix = sprite_path.get_image()
	_dial_pix = dial_path.get_image()
	grid = Image.create(_item_pix.get_width(), _item_pix.get_height(), false, Image.FORMAT_RGBA8)

I guess since I know the order they're defined in I can do something like
@export
var sprite_path: Texture2D:
   set(v): _item_pix = v.get_image()
@export
var dial_path: Texture2D:
   set(v):
      _dial_pix = v.get_image()
      grid = Image.create(...)

but it does still feel like a hack to have to do so.
I sort of get why it's done? "If its made through code things will explode since their export props haven't been set" but Eghh..
Breaking the intuition of "Things which are set in the editor will be usable when I'm in this object's initialization event" isn't a very good thing. I've apparently run into this problem previously too but not known the cause because of that intuition too.
I can't think of a good solution to this either. "Things created in the inspector have their exports init'd before _init is called" is maybe the best? or an _inspector_init()? but agh very hard this is

I agree that adding a dedicated callback would help a lot. I found a related proposal, but it was closed by the author: https://github.com/godotengine/godot-proposals/issues/2708
As a workaround, if your internal state depends on other variables, does it make sense to add a separate function and call it outside? For example:
@export var sprite_path: Texture2D
@export var dial_path: Texture2D

var grid: Image

func create_grid() -> Image:
    # Make the image here.
    return Image.create(...)

# Or, lazy init and cache the result...
func get_grid_image() -> Image:
    if not grid:
        grid = create_grid()
    return grid

Okay well i WAS going to do the usual GoldSRC function ptr malarky I normally do, something like:
var _think: Callable = _think_norm

func _think_init () -> void:
	if _item_pix == null:
		# Also create's fusia error textures here if the exports are null anyway
		...
	# ect
	if grid == null:
		grid = Image.create(_item_pix.get_width(), _item_pix.get_height(), false, Image.FORMAT_RGBA8)
	_think = _think_norm
	_think_norm()

func _think_norm () -> void:
	...

func setup () -> void:
	_think.call(self)

But that also ran into the same order of operations issue, since the thing which used the grid image as data for a sprite's texture.. cant set the texture's data since it.,. well, doesnt exist :/ plus other problems arising from trying to work around that (such as having 1 frame of the temp sprite texture before the proc texture is applied... Or would be applied if it worked -_-;)
The previous workaround of setting them with the exports having setters works.. "fine". Not happy with it but works.
I actually did come across that post on SO (which is how I learned of this oddity) but I wasn't aware there was already a an issue opened about it here, oops sorry =v="
I imagine trying to create a fix for this would have to be after 4.0's release right? I haven't looked into how export variables are handled but I'm guessing its more complex than just slapping a new _post_init functor to whatever handles the creation of objects. Unless it actually is, in which case wow do I look silly.

You can use NOTIFICATION_SCENE_INSTANTIATED. See also godotengine/godot-proposals#5718.

Possible duplicate of #68427


sap_swpm: inifile generation on non-linux ansible controllers

sap_swpm: inifile generation on non-linux ansible controllers
Error:
TASK [community.sap_install.sap_swpm : SAP SWPM Pre Install - Create temporary directory on control node] *********
fatal: [test-nwas -> localhost]: FAILED! => changed=false
  module_stderr: |-
    sudo: a password is required
  module_stdout: ''
  msg: |-
    MODULE FAILURE
    See stdout/stderr for the exact error
  rc: 1

Analysis:
This is caused by delegate_to: localhost and hardcoding user and group parameters of built-in Ansible Modules tempfile/copy/template; setting parameter mode has no apparent effect. When removed or become: false is set - then the processing occurs on the remote/target host then the file is correctly generated and execution occurs.
To retain this, would require execution from macOS (and likely Windows WSL when the playbook file is on Windows NTFS drive instead of inside the Linux container) with sudo and env var passing:
sudo -E ansible-playbook test.yml
It is also very possible this will cause issues in pipeline containers where storage is restrictive, such as Azure DevOps Pipeline, Jenkins, CircleCI, TravisCI, OpenShift Pipelines (Tekton), GitLab Runner etc.
The benefit of processing the inifile locally (between 10-100 seconds, assuming 1 sec processing per parameter and maximum 100 inifile parameters) is a minor benefit when compared to the cross-platform interoperability benefit.
Suggestion:
To retain local processing, declare become: false and remove user + group parameters for built-in Ansible Modules tempfile/copy/template.

Thanks for reporting this @sean-freeman. I tried several combinations of parameters for tempfile, copy and template,  and the one which passed all my tests was the one without localhost delegation for the affected tasks. So let's got that route then.

Solved in https://github.com/sap-linuxlab/community.sap_install/pull/891.


REQUEST: Set label color for body.header

I set body.header background black, I want to set label color for body.header

Sorry about that, I don't know why it's not documented. Just added the attribute to the documentation https://github.com/Jasonette/documentation/commit/a7089d89aaae164a63531616b84c304942cc4d44
Basically you can use body.header.style.color to set the font color of the title. Please reopen if this doesn't work!


[need help] Does it support aysnc reducer?

The exapmle shows the synchronously reducer.  It returns the state directly. I wonder how to write an async reducer.

This question isn't really specific to redux-react-hook. The Redux docs have a good section on async actions.


Feature/identity/create feature wizard

Extends User creation
Adds a 3-step wizard
Ability to add more User information from the start
Ability to assign Claims
Ability to assign Roles

Nice work 💪


Updating Readme

[ ] Remove duplicate toggleType contents, just show the images alternative
[ ] Images in Readme have same size.
[ ] Adding ripple effect description
[ ] Introduce types of ExpansionTileItem


Create Framework so that GS-E can be a plugin to WeakAuras2

Be able to store WeakAuras macros in GS-E addons

I think this may be possible.  From https://github.com/WeakAuras/WeakAuras2/edit/master/Transmission.lua
local WeakAuras = WeakAuras;
if WeakAuras then
WeakAuras.ImportString(str)
end

I cant do this as cleaning as I had hoped.
What will do instead is include a section in the macro definition for Weak Auras.
Sequence["name"] =
Author = "Author",
WeakAuras = {
"WAString1",
"WAString2"
},
MacroVersions= {
...
}
}

i just installed the new update 2.4.11a and when i choose not to show the gse icon on minimap it still shows.

You need 2.4.12 which is waiting on Curse to make available
Timothy Minahan
M 0406 413 680  |  E<EMAIL_ADDRESS>
On 12 Aug 2019, at 4:21 am, Zadden<EMAIL_ADDRESS>wrote:
i just installed the new update 2.4.11a and when i choose not to show the gse icon on minimap it still shows.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub, or mute the thread.

The issue you raised was fixed in https://github.com/TimothyLuke/GnomeSequencer-Enhanced/issues/568
TimothyLuke

On 12 Aug 2019, at 4:21 am, Zadden<EMAIL_ADDRESS>wrote:
i just installed the new update 2.4.11a and when i choose not to show the gse icon on minimap it still shows.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub, or mute the thread.

The + button loads the WA
The - button deletes this WA from the macro.


SDK proxy is returning internal error

I am working on an integration to use .sol in our macOS native app. Our programming environment is Swift, so I have to use the proxy for now.
The following endpoint is returning an internal error:
https://sns-sdk-proxy.bonfida.workers.dev/record/planetable.sol/TXT
My goal is to retrieve the ipns=... string from the content. Is there any other way to do this?

I also tried cargo install sns-cli but it's unable to build because of this error:

Thanks for opening the issue.
Based on the screenshot you posted, you have written ipns=... in the data of the account, not the TXT record. There is no endpoint for fetching the data but we can add it if that serves your use case.
Thanks for mentioning the compilation error, we will look into this. At first glance it seems related to https://github.com/time-rs/time/issues/693

I have prepared a PR for your use case https://github.com/Bonfida/sns-sdk/pull/87
Let me know if this would solve your issue

I have prepared a PR for your use case #87
Let me know if this would solve your issue

That would be awesome! Thanks a lot.
We built Planet, one of ENS's most popular website builder apps. We are exploring the possibility of bringing our app to Solana.

Thanks for confirming @livid, the endpoint has been deployed.

Thank you!
With the new endpoint, I can get a base64 encoded string. After decoding, it contains the IPNS string I need, but it also contains something else:

Is there a proper way to decode that data instead of simply base64 decoding?

I'm so excited to report I got it working in our system!
Now our DoH server can resolve .sol, and it can be further used in our IPFS gateway to enable accessing the website on .sol:
https://ipfs.v2ex.pro/ipns/planetable.sol/
I noticed .sol also has native records for IPNS/IPFS, and we will support and test those cases too. Thank you so much for the fast help!

Thank you!
With the new endpoint, I can get a base64 encoded string. After decoding, it contains the IPNS string I need, but it also contains something else:

Is there a proper way to decode that data instead of simply base64 decoding?

Thanks for pointing this out, there was an issue in my previous commit, I forgot to strip the first 96 bytes that contain the domain header. https://github.com/Bonfida/sns-sdk/commit/ddc1d157f53d116db393f8cddb61c36c1feea525 should fix the issue and has been deployed.
Let me know if I can help you for anything else.

@dr497 Thank you very much! All good now.
I also got the SNS native IPNS record working on both our DoH server and gateway.
We're building a new SNS+IPFS/IPNS gateway. Here's a demo site with the IPNS record:
https://www.sns.id/domain?domain=ohlife
It works in a regular browser by appending .build to .sol like this:
https://ohlife.sol.build/


AddressTransformation integer handling does the opposite of what it is supposed to

I had figured that the inconsistent handling between addresses with only decimal digits was just an unfortunate cost of PowerShell, until I saw the AddressTransformation... so I poked at it a bit more:
> Read-DbgMemory -Address 0x17409680
17409680  "󸇳."

> 0x17409680 | Read-DbgMemory
Read-DbgMemory : Could not access memory: 90108800
At line:1 char:14
+ 0x17409680 | Read-DbgMemory
+              ~~~~~~~~~~~~~~
    + CategoryInfo          : ReadError:<PHONE_NUMBER>4:UInt64) [Read-DbgMemory], DbgMemoryAccessException
    + FullyQualifiedErrorId : MemoryAccessFailure,MS.Dbg.Commands.ReadDbgMemoryCommand

> Read-DbgMemory -Address 17409680
Read-DbgMemory : Could not access memory: 0109a690
At line:1 char:1
+ Read-DbgMemory -Address 17409680
+ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    + CategoryInfo          : ReadError: (17409680:UInt64) [Read-DbgMemory], DbgMemoryAccessException
    + FullyQualifiedErrorId : MemoryAccessFailure,MS.Dbg.Commands.ReadDbgMemoryCommand

For the Read-DbgMemory -Address 17409680 case, the problem was that var pso = inputData as PSObject; returned null - Powershell is just passing in a boxed int, not a PSObject.


Use cilium-app without provider specific cni config

What does this PR do?
(Please set a descriptive PR title. Use this space for additional explanations.)
What is the effect of this change to users?
How does it look like?
(Please add anything that represents the change visually. Screenshots, output, logs, ...)
Any background context you can provide?
(Please link public issues or summarize if not public.)
What is needed from the reviewers?
Do the docs need to be updated?
Should this change be mentioned in the release notes?

[ ] CHANGELOG.md has been updated (if it exists)

Please do not forget to delete branches after closing a PR instead of merging it. GitHub does not auto-delete them when closing a PR. Thank you!


100% coverage: two bug fixes and some optimizations

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

21 of 21 (100.0%)  changed or added relevant lines in 1 file are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+2.6%) to 100.0%

Totals

Change from base Build<PHONE_NUMBER>:
2.6%

Covered Lines:
267

Relevant Lines:
267

💛  - Coveralls


Trigger validation whilst typing for some fields?

I have fields which use the equalTo method and for those I'd like to have the validation trigger whilst the user types in values. I know that this is the default behaviour once the field is marked as invalid, but I'd like this to happen for these fields when they are not marked as invalid as well.
I can't find anything in the documentation that points to such a scenario.
Is this possible? What would I need to do?
This is the code I am currently using:
  $('form.js-validate').each(function(){
    var validator = $(this).validate({
      // empty errorPlacement function ensures no error element is being created, we are adding that ourselves
      errorPlacement: function(error, element) {},
      onfocusout: function (element) {
        $(element).valid();
      },
      highlight: function (element, errorClass, message) {
        var errorMessage = validator.errorMap[element.name];
        var $thisFormFieldWrapper =  $(element).parents('.form__field');
        $(element).attr('aria-invalid', 'true');
        $thisFormFieldWrapper.addClass('form__field--error').removeClass('form__field--valid');
        if ( $thisFormFieldWrapper.find('.form__field--error__msg').length == 0 ) {
          $thisFormFieldWrapper.append('<span class="form__field--error__msg" />');
        }
        $thisFormFieldWrapper.find('.form__field--error__msg').html(errorMessage);
      },
      unhighlight: function(element, errorClass, validClass) {
        var $thisFormFieldWrapper =  $(element).parents('.form__field');
        $(element).removeAttr('aria-invalid');
        $thisFormFieldWrapper.removeClass('form__field--error').addClass('form__field--valid');
        $thisFormFieldWrapper.find('.form__field--error__msg').remove();
      }
    });
  });

A bit more searching and have found the right bit in the documentation after all with validator.element().
Have added this to my script:
$(this).find('[data-rule-equalto]').on('keyup input', function() {
  validator.element($(this));
});

Works great!


Specify what is apim and apim_worker mentioned in the workers-list.txt

Description:
Document: Configuring rsync for Deployment Synchronization
Specify what is the location mentioned as apim/apim_worker in the workers-list.txt
Suggested Labels:
Am2xx docs
Affected Product Version:
AM2xx
OS, DB, other environment details and versions:
Ubuntu 14.04

We will not be fixing this as this issue is based on an older version of the product


nuxt可以js Gzip吗

nuxt可以js Gzip吗

@danielroe I'm Chinese, he should be saying: Nuxtjs can gzip the compiled .js file?
I actually suggest to deal with this problem in Nginx/Apache, Or use CDN (in China, upyun is not bad, it supports gzip or brotli adaptation according to the client).


Instruction's above dont work ... caused my Partner Center account to not work anymore

So I was attempting to associate an Azure AD with my Partner Centre account, as described above. The process failed, with an apology message from Microsoft, saying it had failed for unknown reasons.
Now I can no longer see anything about my Windows Store App Deployment anymore in the Partner Center (it used to be called the Develor page a few weeks ago, but has morphed into the partner center). When I log in and click "dashboard", I just get a  page comes up saying "Windows Docs", that doesn't give any useful information.
It would seem my developer account has become dis-connected from the Partner Center ??
I can't get any support anywhere and the Virtual Assistant is completely clueless.
Who do I contact to get this problem fixed.. which was caused by following the steps listed above on this page.

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

ID: 1603df77-580d-a332-ace4-10c4b6f1484b
Version Independent ID: 7f70b8d6-5146-f327-86c8-9c17acbcac23
Content: Associate Azure Active Directory with your Partner Center account - UWP applications
Content Source: windows-apps-src/publish/associate-azure-ad-with-partner-center.md
Product: uwp
Technology: publish
GitHub Login: @hickeys
Microsoft Alias: hickeys

@msanders59 I've engaged the feature team to help investigate. Once we understand what happened, I will update the documentation. I will also let you know what the process will be to fix your account.
Thanks,
Shawn

@msanders59
The team has requested more information. For your privacy, I'd rather continue this conversation over email. Can you email me at<EMAIL_ADDRESS>

As there has been no reply in months, I'm closing this issue.


Number of filters in Fire modules not consistent with the SqueezeSeg paper

Hi, in SqueezeSeg paper it is pointed that for an input tensor of HxWxC, the squeeze layer of the fire module has C/4 filters, and the expand layers have both C/2 filters, but in the code you are setting:
expand1x1_planes= expand3x3_planes= 4 * squeeze_planes
With this sizes, the fire module does not preserve the equality between the input size and the output size. Sorry, I am just curious :) Thanks for your help

Hello,
Good catch. After reading the paper I decided that the easiest way to do exactly the same network was to use their code, for a fair comparison. When I did, I did not see that discrepancy. But if you look here https://github.com/BichenWuUCB/SqueezeSeg/blob/master/src/nets/squeezeSeg.py , it looks like the author in the code is using squeeze*4 everywhere. Only some layers keep the dimensions.
I do not recommend using squeezeseg for the semantic kitti dataset. Go for one of the darknet backbones, they achieve significantly higher IoU.
Closing this, as it is not an issue. But feel free to keep commenting

Yeah, I also try the Darknet, how about the Focal loss they claim in the SqueezeSegV2 paper? Do you use it in this code?

I tried it, but it did not make a lot of difference vs inverse frequency scaling. That is very dataset dependent...


Percentage selector: Error when you try to rewrite in the same folder

I created a train set with the  PercentageSelector function and using 10% of the images. Today, I tried to create a new train set in the already existing folder but I received this error ValueError: output folder ../data/sample_new/train already exists.  I believe that the function should first check if the folder exists and then delete the subdirectories and rewrite them. @eKoulier Can you fix it?

I like your idea @eKoulier

I kind of agree with the bool but I would definitely not make it default behavior to delete. Maybe default to extend and if false do nothing. Perhaps call the argument force? But I strongly believe the code should not delete anything - it could be dangerous.

I still believe that being able to delete all the existing folders in the sample data should be an option because there might be a case that the user has used the PercentageSelector  a few times and has forgotten the actual percent of the pictures he uses as a subset. Otherwise he should manually delete the training subsets.


Enabling horizontal scroll for project list in project manager

Fixes issue #10245

Thanks! It was already fixed by #10294 though.


[Question] How to dev a new bindings and test

Ask your question here
I just saw this
Implementing a new binding
A compliant binding needs to implement one or more interfaces, depending on the type of binding (Input or Output):

Input binding:

type InputBinding interface {
	Init(metadata Metadata) error
	Read(handler func(*ReadResponse) error) error
}
Output binding:

type OutputBinding interface {
	Init(metadata Metadata) error
	Write(req *WriteRequest) error
}

And how to test?
Thanks!

@liangyuanpeng We have this covered in our contributing guide now, please feel free to reopen if you have more questions,
https://github.com/dapr/components-contrib/blob/master/docs/developing-component.md#writing-new-component


Skill bridge is not accessible

Hello.
For past 2+ hours https://alexa-node-red.bm.hardill.me.uk/ is showing "It looks like the skill is currently experiencing a problem at the moment". Can someone check why? In HA/NodeRed it also can't populate items. Thank you.

I can confirm the skill doesn't appear to be working at the moment

I comfirm, the skill said: "It looks like the skill is currently experiencing a problem at the moment. Give it a couple of minutes and if it's still a problem please check if there is an existing open issue on GitHub here, if not then raise one." Anyone can help?

not sure this can help, however until about 20 minutes ago alexa talked about a problem with the device (always working fine otherwise) while now it says OK but nothing happens. nodered is up but no traffic is reported whatsoever, neither before nor now

life saver! I was afraid I had to switch off the lights through tapping on the phone, like a caveman! Or via the switches. Or via command line. Or.. hahahaha thank you!

yesssss... now is working...


Crop SNR map before processing it, to improve visibility of QC

The SNR map includes a bunch of padding and a colormap, which is useless for subsequent processing, and it makes it more difficult to analyze the QC report due to the small appearance of the image:

I suggest to crop the SNR map using set values, that work for all sites, before processing and QCing.

Note to self: sct_deepseg is veeeeeeery slow on these large images, so cropping will definitely help

This is how the sagittal view looks like, there is a bunch of zeroed voxel that will make the cropping easy:

I guess we can first get rid of the colorbar on the right by cropping everything above x=450, and then do the cropping using the input image as the cropping mask (with flag -m).


Model-local functions when creating a ModelProto from a python function

When we export/convert a Python function to a ModelProto, we need to identify the set of functions that will be included in the generated ModelProto as model-local functions. Furthermore, the users should be able to control this. For example, I might want to create model that calls Relu, with or without including the function-definition for Relu (even though we might have a function-definition for Relu available).
(See PR: https://github.com/microsoft/onnx-script/pull/41 )

This would be nice 👍


Michal's pet peeves

This will be a running list of things I would like to fix, but not very many people will care about. Just a way to avoid spamming issues list while keeping the list available online.

[ ] Clean up fallout from #2643: remove both instantiation parameters on GenericLookupResult::GetTarget since they're redundant with the generic dictionary parameter. Look into deleting GetInterfaceDispatchCell and replacing the uses with a call to GetTarget.
[ ] After #2648 there are two ways to define a symbol on ObjectDataBuilder: DefinedSymbols.Add and AddSymbol. We should make DefinedSymbols private and standardize on AddSymbol. Same for setting Alignment (either call the setter, or RequireAlignment). I always found RequireAlignment odd (because it sounds like it adds padding, but it doesn't - it aligns the entire blob).

EETypeNode factoring

[ ] EETypeOptionalFieldsNode should own the OptionalFieldsBuilder and shouldn't try to offload this to the EETypeNode.
[ ] Odd separation of concerns in EETypeNode - the base nonconstructed EETypeNode shouldn't have to care about vtables, interfaces, ICastable, and other ConstructedEETypeNode concerns
[ ] The GCStaticEETypeNode should have a common ancestor with EETypeNode
[ ] We need to push vtable dependencies out of EETypeNode to the VTable node (this should clean up things enough that there won't be ReadyToRun node dependencies or virtual method use optimization dependencies from EETypeNodes).

I was planning to fix up DefinedSymbols anyway having added AddSymbol so I'll take that one. I agree on RequireAlignment too. Perhaps we should rename it to SetObjectAlignment or something so it's clear it's a one-time configuration operation.


appgate-sdp: 6.0.1 -> 6.0.2

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://repology.org/metapackage/appgate-sdp/versions.
meta.description for appgate-sdp is: "Appgate SDP (Software Defined Perimeter) desktop client"
meta.homepage for appgate-sdp is: "https://www.appgate.com/support/software-defined-perimeter-support"
meta.changelog for appgate-sdp is: ""
Updates performed

Version update

To inspect upstream changes
Impact

Checks done (click to expand)

built on NixOS
The tests defined in passthru.tests, if any, passed
found 6.0.2 with grep in /nix/store/66n1yrzpg57f1zaadl19h6jp8h772hkq-appgate-sdp-6.0.2
found 6.0.2 in filename of file in /nix/store/66n1yrzpg57f1zaadl19h6jp8h772hkq-appgate-sdp-6.0.2

Rebuild report (if merged into master) (click to expand)

1 total rebuild path(s)

1 package rebuild(s)

First fifty rebuilds by attrpath
appgate-sdp

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/66n1yrzpg57f1zaadl19h6jp8h772hkq-appgate-sdp-6.0.2 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A appgate-sdp https://github.com/r-ryantm/nixpkgs/archive/8bc6e09754c08b12f603d93ec83cc112abeb49a2.tar.gz

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/66n1yrzpg57f1zaadl19h6jp8h772hkq-appgate-sdp-6.0.2
ls -la /nix/store/66n1yrzpg57f1zaadl19h6jp8h772hkq-appgate-sdp-6.0.2/bin

Pre-merge build results
We have automatically built all packages that will get rebuilt due to
this change.
This gives evidence on whether the upgrade will break dependent packages.
Note sometimes packages show up as failed to build independent of the
change, simply because they are already broken on the target branch.
Result of nixpkgs-review run on x86_64-linux 1

1 package built:

appgate-sdp

Maintainer pings
cc @ymatsiuk for testing.

Result of nixpkgs-review pr 192706 run on x86_64-linux 1

1 package built:

appgate-sdp


Feature/custom logs

Add promtail to push logs to central server

This really can be in prometheus.yml I think. I'm not sure we need a separate file for it.

Sure can merge them, means will never need metrics only without logs which is our case.

Thanks! What do the pipeline stages all do? From memory we don’t have that in Eth Docker - depending on what these do, we may want to

We do have them https://github.com/eth-educators/eth-docker/blob/main/promtail/global.yml those are part of configuring promtail on how to label logs from containers. Getting attributes assigned to containers [tag: '{{.ImageName}}|{{.Name}}|{{.ImageFullID}}|{{.FullID}}'] and processing them as labels. When docker is running containers logs are usually in /var/lib/docker/containers as text files, so promtail reads them and attaches tags as labels


transfer icons from catalog items to entities

and set icons on the common server and cluster items
previously while we do a lot to support icons and send detail via the API,
we don't set them on entities unless explicitly in the definition.
since we often have them on catalog items, transferring them seems a sensible idea.

This looks fine, what are the sources and licenses of the icons @ahgittin?

This looks fine, what are the sources and licenses of the icons @ahgittin?

good catch -- they were from a free icon site, but i must find those properly!

Have changed icons to ones for which the licensing is clear and added license info in commit history; will open new PR for corresponding license data in brooklyn-dist

Have also pushed license changes; you can see them here:

https://github.com/apache/brooklyn-dist/commit/7087633e71d2131a68e52266ea808dd50ed0fc33

Good catch @drigodwin !


Sync Model classes with Abiquo 3.10.1

TODOs

[x] Go through model classes in biz.dfch.CS.Abiquo.Client.v1.Model and add missing properties (Sync with Abiquo 3.10.1 sources

resolved by #49


Bug: Buttons not behaving as expected.

There are a few buttons that don't work as expected.

After creating a new wallet, on the Terms and Conditions screen. If you click Close Application (instead of agree), the application doesn't actually close. You just get kicked back to the main screen. I think the easiest solution is to change the wording to Cancel instead.

In Settings view:
After clicking on Wallet Information, then Browse, and then Cancel - I get this screen:

Expected Behaviour:
Cancel should just cancel with no error being thrown up. At the moment, it seems to be behaving as if you have hit apply.

verified


Remove opencv-python (cv2) as a dependency.

This is one of the largest dependencies and occasionally causes installation conflicts.

[ ] cv2.GaussianBlur -> scipy.ndimage.gaussian_filter
[ ] cv2.resize -> scipy.ndimage.zoom
[ ] cv2.SimpleBlobDetector -> custom
[ ] cv2.imread -> imageio.imread
[ ] cv2.fillConvexPoly -> scipy?

Decided against given the addition of the webcam interface.