text:
Places Autocomplete - Anyone wants to donate together?

Please tell us your new feature idea
Basic google places autocomplete
Why do you need it?

Much improved user experience.
Using the web API isn't a good option because it's almost not possible to restrict access to the API. Therefore, using it in production has security risks.

How helps other people?
I guess most people who want to use places autocomplete either don't care about the security or not aware of the risks. Or they have to implement it on their back-end which needs a lots of work.
We need to reach the target $1000.  Anyone else wants to donate together to make it happen? Please comment.

Why do I don't implement?

Google Places API is expensive. See the price table of Google Maps API.
https://cloud.google.com/maps-platform/pricing/sheet/?hl=en

Implementing for all platforms is hard work.
Not only browser platform, but also Android, and iOS.
I need to implement different code for three platforms. It takes much time.

fundraising was not successful.
I made a fund raising in the past, but nobody had interested in.

Thus, I don't implement the places auto complete.
If you want to implement the places auto complete anyway, please use the Google Maps JavaScript v3 + places library with this plugin.
Someone do that.

Any opinions?

@wf9a5m75 Sorry for my late reply. I actually took some time looking into the pricing issue. Thank you so much for the pricing info.  I knew google had started a new pay-as-you-go model but I hadn't got time looked into it. Now I am scared because I am using it on my web app. Because as you said, yes, it can get very expensive. Especially if you want to get place details.
On my mobile apps, in my  case, I don't need to call the getPlace api. I can call the native geocoding to find the lat &lng of the address, it's free, isn't it? so the cost will be:
Autocomplete - Per Request $2.83 per k requests
Native Geocoding: Free ( Am I correct? Can't find any info. Native maps are free on that list)
For implementing the most basic feature like this, is it feasible? I am not sure how many people will have such needs. So I can't speak for other people and I'm not sure if others will donate. I will email you personally. Is it possible for you to let me know your target of donation to make it happen? Maybe I can donate along when I can afford.
I dont' want to use the Google Maps JavaScript v3 + places library on mobile apps because it's not possible to limit the api key to the use of only my apps. I talked to the google support before but there is not good solution.

Geocoding price
Regarding of the geocoding price, it is correct understanding (browser: pay-as-you-go, android, ios: free), as far as I know.
But I have been making sure to Google Maps team for just in case.
I will update about this.

Auto complete
Well, some people requested me to implement it.
Since implementing new feature, even it has basic functions only, I have to take time, and I need to keep up-to-date(work it always) forever.
Because of this, I always ask $1,000 USD donation.
For instance, HTMLInfoWindow and MarkerCluster are donated implementation.
Both works spent almost three months for each.
And I fixed bugs even after releasing.
Running code on variable devices cause unexpected things a lot.
So creating a new feature is not just implementation, but also including code maintenance.
That's why I always ask $1,000 USD donation.
Well, you may think it is too expensive. But let's think about this. If you ask to work for someone who are familiar with Android, iOS, and JavaScript, the cost might be more expensive, and probably no maintenance after the delivery.
In my case, I will provide private code sharing, private support, and implement three platforms on by one.
Note that private code sharing and support is end when the feature is releasing and extra one month.
And if I can't complete the work in three month, I return all amount to you.
I believe there is no good offer than mine.
If you agree with this, please donate from here.
https://github.com/mapsplugin/cordova-plugin-googlemaps#please-support-this-plugin-activity

update : Geocoding price
I confirmed to Google. Our knowledge is correct. Thus, this plugin geocoder on Android and iOS are free.
(iOS geocoder is Apple's one)

@wf9a5m75 $1000 USD is a reasonable price. Not expensive at all in my opinion. I am fully aware how much work it takes to get some quality job done. You don't need to convince me at all. Can we keep this feature request for a while so that more people can see? If five person can donate $200 each, we will be able to easily reach the target. Since I just started developing my business, I can't donate the full amount alone at this stage. This will be the first feature I am going to invest once I start getting revenue if there is still not enough donation.
btw, many thanks again for the confirmation about the cost of the Geocoding service. I didn't know this plugin also does geocoding & reverse geocoding as well.  If I understand it correctly, with the new google pricing model, google maps(dynamic maps) has also become free on mobile platforms when using cordova-plugin-googlemaps? I remember there was some limitation before.
I just donated a very small amount to buy you a coffee for thanking you for the great cordova-plugin-googlemaps. It's not the donation for the new feature yet:-).

Auto complete donation

Can we keep this feature request for a while so that more people can see?
If five person can donate $200 each, we will be able to easily reach the target.

Yes, you can spread the amount. But if the number of people more than three people, I might be limit the number of people for private support.
Because private support during the development is kind of another hard work.
So I would spread donors to primary and beta testers depends on their donation amounts.

Maps price

If I understand it correctly, with the new google pricing model, google maps(dynamic maps) has also become free on mobile platforms when using cordova-plugin-googlemaps?

Yes, correct.

Android, iOS -> still free
Browser -> Free up to 28,000 loads, then $7.00/1,000 times

Your donation
Thank you for your donation. I really appreciate for your help ;)

@wf9a5m75 Thanks again!

@wf9a5m75
I might be wrong about the cost calculation.
If we want to get a selected place from the drop down menu and do our own geocoding, it's not possible because place is an object and the autocomplete results we are seeing are derived from the properties of Place object. That means, we have to pay for the place details api call as well. That make it $17 per 1k requests:
Autocomplete (included with Places Details) - Per Session

Places Details
Basic Data

Anyway, my feature request stays valid and  so does my calling for more people for sharing the amount.

It seems nobody is interested in this project.

ping

Since there is no update for a while, I close this thread.

I'm waiting for that too.

I am still interested in this @lolaswift . Did this project ever take off? Or did you find an alternative?

hi, I do not use cordova anymore. switched to flutter.

hi, I do not use cordova anymore. switched to flutter.

That's what I was afraid of. :P

authors: lolaswift orchoban spinninghamster wf9a5m75


text:
Unclear how to prove ownership vs existence.

Demonstrating data ownership without revealing actual data.
You can publicly reveal the digest and if conflict arises you can prove you had the data that generates the digest. Useful for copyrighted material, patents, etc.

Doesn't say how. I can see at least two ways:

Submitting signed or watermarked documents that can be used as proof to the ownership of both that and the unwatermarked version, by virtue of being dated earlier than yourself or anyone else submitting the unwatermarked version.
Submitting a snapshot of your public web page where you list the (submitted) hashes you own every time you update the page.

Neither method is really optimal (both require extra submissions) and neither is presented on the page.
Perhaps there should be one of the following:

A field for an email address or other public identifier to be hashed and appended (so that the existence of the unique document can be verified without inputting the author).
A field for an email address or other public identifier to salt the hash with (which doesn't create extra data, so will not require weaker hashes). This method is identical to manual solution 1 above.
Encrypting the file with the author's private key to verify that not only did they possess the file at the date, but were in fact the person responsible for registering it. (So that a third party can not use the feature for defamation.)

Thank you for your well thought out feedback.
I've seen both A1 and A2 being used by https://proofofexistence.com/ users, and as you say, they're not optimal.
As an attempt at a better solution, we are now testing something similar to your suggestion B3. The difference is instead of encrypting the file, we're using PGP signatures.
You can try it here: https://proofofexistence.com/sign (it's far from ideal).
Feedback welcome :)

That's pretty cool, thanks.
My only suggestion is that you could allow people to copy down a blob of text, sign it, and stick it back in, in case they are uncomfortable exposing their private key to their browser environment. (Or your webapp for that matter, that could have been compromised.)
After the feature is finalized anyone using it regularly would still just have it as an automated part of their publishing process (they would probably still want to sign it locally for the API, just like they SHA it locally), but I am asking for a middle ground (which seems trivial to implement)
Also, the pricing is provisionary, correct?
I tried different numbers of signatures and it's always 0.02 BTC there.

source: gharchive/issue

repo: maraoz/proofofexistence

license: mit

license_type: permissive

license_source: bigquery


text:
Allow using variables from context processor inside form templates

Currently if you try to override the crispy_forms templates and use something like {{ request }} it can't really find the request.

This sounds like it would be solved by #579 - The problem is that the crispy form tag processing builds up an individual context based (mostly) on attributes received from the helper in addition to a couple of selection ones, such as csrf_token.  The PR adds implicit context passing, so {{ request }} would work if that was already present on the context.

authors: cool-RR lskillen

repo: maraujop/django-crispy-forms


text:
Add userConfig settings addressBook.savePath

As per https://gluwa.atlassian.net/browse/SMC-347

added to #61

repo: marc-aurele-besner/hardhat-awesome-cli

license: MIT

license_source: github-api


text:
"Actual OS:   win32" reported on Windows x64

I don't know if this is related to nodist.
I'm trying to install node-syslog and I get the following error.
npm ERR! notsup Not compatible with your operating system or architecture: node-syslog@1.2.0
npm ERR! notsup Valid OS:    !win32
npm ERR! notsup Valid Arch:  any
npm ERR! notsup Actual OS:   win32
npm ERR! notsup Actual Arch: x64

nodist reports
  (x64)
> nodev0.12.7  (env) (global)

I'm on Windows 10 x64. How do I correct "Actual OS"?

!win32 means not windows, afaict. Also, the README says: "This is a node module (add-on) to work with syslog (system log) daemon on unix systems."

Thanks marcelklehr.
Node-syslog should work on Windows according to their own readme and changelogs.
Node-syslog does not officially support Darwin OS and MS Windows but should work fine.
I'll try ask them.

+1

Unfortunately, libuv reports to Node that the OS is win32 any time it notices it's "not *nix", irrespective of the processor architecture or 64-bit-ness.  One can think of it as a boolean flag like "is it linux?"  "nope."
What this error says to me is the Node-syslog installer specifically blocks Windows installation.  That's pretty bold of them.

authors: archenroot jakobrosenberg marcelklehr robrich

repo: marcelklehr/nodist


text:
🛑 kljb-lauben.de is down

In ff07d46, kljb-lauben.de (https://kljb-lauben.de) was down:

HTTP code: 0
Response time: 0 ms

Resolved: kljb-lauben.de is back up in 28e453f.


text:
🛑 Grafana is down

In 383f305, Grafana (https://grafana.bojko.eu) was down:

HTTP code: 503
Response time: 541 ms

Resolved: Grafana is back up in b9fa7fb after 9 minutes.

repo: marcinbojko/upptime


text:
No dnd off if manually activated

If a user already has DND activated before a screen share or recording starts, do not turn it off when the session ends.
Note that this trivially conflicts with PR #3.

Hmm, interesting, I actually thought about adding that behavior originally, but I must have forgotten :slightly_smiling_face:

source: gharchive/pull-request

authors: F-i-f marcinjahn


text:
Fix subpixel sizes support

When you are using of non-integer values for the sizes, offsetWidth can be differ per each element in a list

// What was used
$$('.item').map(i => i.offsetWidth)
(8) [199, 200, 199, 199, 199, 200, 199, 199]
// Computed css styles
$$('.item').map(i => i.style.width)
(8) ["199.5px", "199.5px", "199.5px", "199.5px", "199.5px", "199.5px", "199.5px", "199.5px"]
// BoundingClientRect
$$('.item').map(i => i.getBoundingClientRect().width)
(8) [199.5, 199.5, 199.5, 199.5, 199.5, 199.5, 199.5, 199.5]
Compatibility: https://developer.mozilla.org/en-US/docs/Web/API/Element/getBoundingClientRect

Do you know why the browser engine sometimes returns 199 and sometimes 200 for a value of 199.5?

Probably, a bug or trying of use the same summ result as the container offsetWidth

Ok cool, thanks!

authors: el-fuego marcj

repo: marcj/css-element-queries


text:
🛑 Web Patient is down

In 69afa10, Web Patient (https://www.sanna.pe/citas/) was down:

HTTP code: 403
Response time: 11 ms

Resolved: Web Patient is back up in fe9f40f after 5 minutes.

repo: marcoadasilvaa/health


text:
🛑 Web Patient is down

In 43e38ab, Web Patient (https://www.sanna.pe/citas/) was down:

HTTP code: 403
Response time: 25 ms

Resolved: Web Patient is back up in a8a85d5 after 4 minutes.


text:
date_locale returning incorrect data

If date_locale is set to "au" then the date returned is mm/dd/yy, which is incorrect for au. Australia uses day month year in every format.
For example, if I use "nl" then for Bahrain (at the time of writing) then I correctly see 06/03/23. If I set it to "au" then it returns "03/06/23" which is incorrect for Australia.
If "au" is not a valid option, then please provide a list of valid options.
PS thank you very much for the project - it's excellent.

If you don't pass the locale to the card it takes your locale of home assistant. The options you have are listed here https://www.w3.org/International/O-charset-lang.html


text:
SELECT component: displaying selected text (rather than value)

Hey Marcos,
This is more of a question than an issue. I am using the SELECT component, but unlike the example you have in your docs (https://marcosmoura.github.io/vue-material/#/components/select) my value attribute for the items is different from the item text. However, the control seems to display the selected value rather than the text once an item is selected. Is there a way to display the text instead?
Attached is the screenshot of some sample code.

And here is what my screen looks like after I selected an item with Name "One"

I would prefer if it displayed the Name ("One") rather than the Value ("1"), as it does now.
Once again, thank you for the awesome library!

Hey @cheresier.
I'm sorry about that. This is a bug. The <select> from HTML have this behaviour that you described and the <md-select> will have it too.
Right now you can't do this, unfortunately. I will fix and report on this on the issue #24
Thank you! and sorry to make you wait a little longer to use this component properly.

Sorry for the duplicate. One other thing I noticed (just FYI) is this. In my example, if you select the item with value 0 this is how it displays:

Probably because it evaluates as boolean false. I am guessing it will be fixed in the next iteration as well, but I thought I'd let you know.

Oh. Don't worry about the duplicate. And yes. You're right about that. It's evaluating as a Boolean in a silly and wrong way. This will be fixed on the next release. :D

Sorry to bother again. Quick question (although I have a feeling that the answer to it may be obvious): is there a way to set the selected item programmatically? Something similar to the "selected" attribute on one of the options in the HTML select?

authors: cheresier marcosmoura

repo: marcosmoura/vue-material


text:
Example needed for md-list-item using router-link

Hello.
When using vue-router router-link custom element and md-list-item from md-list component inside a sidenav component, how can achieve the best result?
http://codepen.io/fergardi/pen/rjZYYZ

hi, @fergardi
md-sidenav.md-left
    md-toolbar
      div.md-toolbar-container
        h3.md-title Navigation
    md-list
      md-list-item
        router-link(exact to="/iwant") I want
      md-list-item
        router-link(exact to="/to") To
      md-list-item
        router-link(exact to="/go") Go
      md-list-item
        router-link(exact to="/home") Home

Is that you looking for?

Perfect, thank you. Integration with vue-router should definitely be in the docs.

It will. I will fix that on the website. :)

authors: VicarEscaped fergardi marcosmoura


text:
Ink ripple only works once on Firefox 51

Steps to reproduce
Which browser?
Firefox 51 on macOS 10.12
What is expected?
Ink ripples should work more than once
What is actually happening?
After the first ink ripple, the element just flashes dark with no ripple.
Reproduction Link

I see the same effect on IE11 in vue-material v0.6.3 also.

Samue issue. Firefox 51.0.1 Windows

Now Ink-Ripple effect is not working anymore at all with Firefox 51.0.1 (Windows) on demo site  https://vuematerial.github.io/#/components/ink-ripple (v7.0.1)
It does however work on Chrome 56.0 as expected.

@thomasd for me is working

@Samuell1 I cleared the cache several times, still the same.
I also tried it via this http://codepen.io/vue-material/pen/WGavBE
But still not working.

You can see that vue-material is indeed v0.7.1 (loaded via unpkg.com)
Very strange, but it seems it's only happening to me???

for me is fine

In my Firefox 53.0.2 it doesn't work either. Cache is clean.

Do we have an issue here guys? I'm confused.

Ripple doesn't work for me Firefox 53.0.3 (64-bit) OSX

works on macOS 10.12.3 Firefox 53.03 (64-bit)

authors: Pixelrise Samuell1 alexstacey pablohpsilva thomasd waspinator


text:
Version checking should support wildcards

In order to require labview version to be 2020 it requires two comparisons to be used together:
-gt 20 -lt 21
I was assuming that -eq 20 or -eq 20.* might work, but that didn’t do the trick. The output complained that it wasn’t exactly 20.0.0f2 (or similar).
Is there a trick to requiring a major version and ignoring minor, fix, and patch?

Great suggestion. The current version checking is very much aligned with the implementation details. We really should make it much more semantic version checking, especially in the -eq case.

authors: jimkring marcpage

repo: marcpage/pylavi

license: Unlicense


text:
online editor not opening files

The website loads, but when I browse to a garden_plus.dat file and choose to open, the browse window closes and goes back to the website home (rather than opening the file to show the town map).  Encountered this problem on Saturday 4/27, worked properly again on 4/28, encountering problem again today 4/29

I cannot replicate this bug.
Please post the garden_plus.dat file here so I can take a look.
Which website are you visiting?
http://www.marcrobledo.com/acnl-editor/
or
https://www.marcrobledo.com/acnl-editor/ ?
Which version is shown in site footer?

Well, everything is opening now.  I had last tried a little over an hour ago (at about 6am EST), and I've enclosed the file I was using.  I tried several different files though.
The issue occurred using the https site, but I don't see a footer even when printing the home screen.  I'm using Safari, and the home screen says that the editor is the 4/28 version.  Here is the first file that wouldn't open.
Thank you!

From: Marc Robledo notifications@github.com
Sent: Monday, April 29, 2019 6:43 AM
To: marcrobledo/acnl-editor
Cc: gardnerk; Author
Subject: Re: [marcrobledo/acnl-editor] online editor not opening files (#62)
I cannot replicate this bug.
Please post the garden_plus.dat file here so I can take a look.
Which website are you visiting?
http://www.marcrobledo.com/acnl-editor/
or
https://www.marcrobledo.com/acnl-editor/ ?
Which version is shown in site footer?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHubhttps://github.com/marcrobledo/acnl-editor/issues/62#issuecomment-487533863, or mute the threadhttps://github.com/notifications/unsubscribe-auth/AL6IBBXSBHO2YNBOGYOFPBTPS3GO7ANCNFSM4HJB5QLA.

Here - just a couple of minutes later, and now this file isn't opening.  The "browse to" dialog box opens, then when I choose the file, the dialog box closes and stays on the editor https home page.

From: GardnerK@live.com gardnerk@live.com
Sent: Monday, April 29, 2019 7:06 AM
To: marcrobledo/acnl-editor
Subject: Re: [marcrobledo/acnl-editor] online editor not opening files (#62)
Well, everything is opening now.  I had last tried a little over an hour ago (at about 6am EST), and I've enclosed the file I was using.  I tried several different files though.
The issue occurred using the https site, but I don't see a footer even when printing the home screen.  I'm using Safari, and the home screen says that the editor is the 4/28 version.  Here is the first file that wouldn't open.
Thank you!

From: Marc Robledo notifications@github.com
Sent: Monday, April 29, 2019 6:43 AM
To: marcrobledo/acnl-editor
Cc: gardnerk; Author
Subject: Re: [marcrobledo/acnl-editor] online editor not opening files (#62)
I cannot replicate this bug.
Please post the garden_plus.dat file here so I can take a look.
Which website are you visiting?
http://www.marcrobledo.com/acnl-editor/
or
https://www.marcrobledo.com/acnl-editor/ ?
Which version is shown in site footer?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHubhttps://github.com/marcrobledo/acnl-editor/issues/62#issuecomment-487533863, or mute the threadhttps://github.com/notifications/unsubscribe-auth/AL6IBBXSBHO2YNBOGYOFPBTPS3GO7ANCNFSM4HJB5QLA.

You didn't post the file :-(

Sorry about that!  I had not used GitHub before, so I didn't upload the file properly.  Here is one of the files.  It won't open in the online editor on 3 different computers (one Mac, a PC with Windows 8, and a PC with Windows 10) using Safari, Chrome, or Internet Explorer.
Most of my files won't open online, but they open fine in the downloaded version of your editor.  And, if I make a new garden_plus.dat file for the same town, it opens fine.
I don't know enough about software to make any educated guesses, but my older files aren't opening online, and my newer ones are.  If no one else is having this issue, then perhaps I've edited these older towns in some way that just isn't compatible? I'm curious, but it may not be worth investigating on your end.  Thank you again!
garden_plus.dat.zip

Thank you :-)
Found the bug, gonna fix it asap!

Fixed!
Will upload the changes tomorrow.
If you really need to use the editor, use the old v1.4 for now.

No rush on my account - the offline version is working fine for me.  I really appreciate this though. :)

Should be fixed in 916f432292400bb55b35d985e4eaa0c305bbe31e :-)
You might to force a cache refresh in order to get the latest editor version (make sure it's the 1st May version).

authors: gardnerk marcrobledo

repo: marcrobledo/acnl-editor


text:
Target GUIDs for PoC?

In reviewing some headers regarding function introspection, I noticed what I guessed are RVAs for a specific build of ntdll, etc.
Could you share the PDB GUID(s) used for building/testing this proof of concept?
Many thanks!

The referred version is Windows 8 x64 and its corresponding DLLs. I'll provide more information ASAP.

Thank you - much appreciated!

Take a look if the newly added information helps you.

authors: marcusbotacin smaresca

repo: marcusbotacin/BranchMonitoringProject


text:
Test run on GitHub Actions

CI
This doesn't test correctness, but does test the program can run without erros, and does so on matrix of Windows, macOS and Ubuntu and on Python versions 3.7-3.10.
I added the GPX files from https://github.com/marcusvolz/strava/tree/master/inst/gpx/cycling to tests/gpx here as input.
Here's a sample run: https://github.com/hugovk/strava_py/actions/runs/1808323998
After running, it also uploads the output files as an artifact, you click "images" to download a zip and check how they look.
(Note: there's a single file even though there's 12 jobs in the matrix. I think each one overwrites previous ones. We could probably set it to upload images from each job, but I think this is fine for now.)

Also

Rename src package directory to stravavis

Review comments from https://github.com/marcusvolz/strava_py/pull/2

Amazing, thanks again!

authors: hugovk marcusvolz


text:
Add qe-tools to registry with support for QE PW and QE CP input files

Adding qe-tools to the registry. For now, it will support QE's PW and CP input files. Others may follow depending on how this goes.
A few notes:

Had to add an extract function as a middle layer between MaRDA and qe-tools classes. Open PR pending review. For now, the extractor schema added to the registry points to my qe-tools fork. Let's see how that goes.

The command for my extractor is qe_tools.extractors.extract({{ input_path }}, {{ input_type }}), where input_path is expected to be the path to the file, and input_type is PW or CP. I defined input_type under each supported_filetypes entry in the schema. Not sure if this is the way.

I force pushed a correction - installation now points to aiidateam/qe-tools. Will update pointer to pypi once officially released, at which point, I'll tag minimal version in reqs.

@ml-evs okay, fixed. Had to add the extractors module to the root __init__.py. For now, I reverted the redirect back to my repo. Let's make sure it works before I push any further changes to qe-tools.

I'm going to merge this now because I want to test some other stuff based on it; we can always revise in a future PR.

Sorry @ml-evs, busy bee 🐝 Thanks for the merge 🙏 I'll open a follow-up PR once qe-tools side is settled 👍

authors: edan-bainglass ml-evs


text:
Mod: Add a battery power in Volts

This could be used to compute a coil performance.

Done.

repo: marek-hanzal/puff-smith


text:
Add N7QNM to the Adopters list

Please add N7QNM to the adopters list - I have an LLC, Jackson Holdings, but prefer to just use my Amateur Radio Callsign, N7QNM.
I have over 10 years of weather data stored in MariaDB (and MySQL before the Sun/Oracle acquisition) that's used by several farmers in the Columbia River basin in Washington State.
I contribute my weather data to NOAA/Citizen's Weather Observer Program and Washington State University's AgWeatherNet.
I also have over 25 years of Amateur Radio logs and several years of Home Automation (Home Assistant) data stored in MariaDB.
I'm consolidating 3 different databases, one on Windows, 2 on Linux into one Galera Database running in a 3-node kubernetes cluster running inside a 4 Node Proxmox virtual environment.
In my "day job" I'm a Solutions Architect for Quest Software, specializing in database-adjacent products, including SharePlex (Data Movement), Foglight (Database Monitoring) and the TOAD family (database management and SQL Development).

Hey @n7qnm! What an impressive career, thanks for adopting mariadb-operator 🦭
Could you please open a PR and add you/your project/your company to be ADOPTERS list?
Thanks 🙏🏻

repo: mariadb-operator/mariadb-operator


text:
Update README.md

I changed the code description from python to bash so that there is the "play button" (on click execution of the command) in the PyCharm IDE.  Technically, this is rather bash code than Python code and only calling the python CLI.  I hope you think so too and approve it as an improvement.

I've fixed this in #14 along with a few other typos you've covered in other PRs, please do feel free to review #14 if it's got any other useful things that would be of benefit to the repo.

Refer to #14

authors: MG-ng TAJD marinlauber

repo: marinlauber/Python-VPP


text:
Improve test harness: soldeerignore/githubignore

The ignore of files while pushing to central repo needs tests

https://github.com/mario-eth/soldeer/pull/75 did that here

repo: mario-eth/soldeer


text:
--cwd not working

from directory without commitlint config files, lets suppose home (~)
 ~  echo "foo" | commitlint --cwd /home/bjorn/.config/dotfiles/commitlint/
⧗   input: foo
✔   found 0 problems, 0 warnings

expected some error
 ~/.config/dotfiles/commitlint   master ●  tree -a.
├── .commintlint.json
├── node_modules
│   ├── conventional-changelog-lint-config-canonical
│   │   ├── conventional-changelog-lintrc.json
│   │   ├── index.js
│   │   ├── LICENSE
│   │   ├── .npmignore
│   │   ├── package.json
│   │   └── README.md
│   └── .yarn-integrity
├── package.json
└── yarn.lock

2 directories, 10 files

.commitlint.json
{
  "extends": ["canonical"]
}

P.S. what I want is to fallback on my personal .commintlint.json  if current direcory has no .commintlint.json

made some script, to lint and commit if all is fine (I don't like cz-cli)
#!/usr/bin/env ruby
# Author - Sergey Homa <melgaardbjorn@gmail.com>
# License - none

# lint commit message using commitlint, commit if valid
# usage:
# - in bash
#   alias lc="linted-git-commit -m"
#   alias lc!="linted-git-commit --amend -m"
# - in console
#   gaa && lc "feat: added linted-git-commit"

# options
dir_with_commitlint_config = '/home/bjorn/.config/dotfiles/commitlint/'

# run
options = ARGV
message_pointer_index = options.index('-m')

unless message_pointer_index
  puts 'Message is required'
  exit false
end

message = options.delete_at(message_pointer_index + 1)
options.delete_at(message_pointer_index)

lint = "commitlint --cwd #{dir_with_commitlint_config}"
cmd = "echo \"#{message}\" | #{lint}"

return unless system(cmd)

`git commit #{options.join(' ')} -m \"#{message}\"`

linted-git-commit in dotfiles
commitlint.config.js in dotfiles
P.S. it would be very helpful to allow some sort of  commitlint.config.js in home directory

Hey @BjornMelgaard, have you tried  @commitlint/prompt-cli for your usecase?
--cwd is intended to tell commitlint where to read commit history and or edit files from if applicable (if the -e, --from or --to flags are set).
If you want to have a global fallback for commit configuration you could install the configuration you need globally:
npm install -g commitlint-config-angular

commitlint.config.js is read from every directory that is above your current cwd, e.g.:
// in ~/projects
echo "foobar" | npx commitlint

will pick up
// ~/commitlint.config.js
module.exports = {
  extends: ['angular']
}

have you tried @commitlint/prompt-cli for your usecase?
same as cz-cli, its not saving my commit message if something goes wrong (zsh history does), but thanks))

ok, I have updated my dotfiles here and here
and what I found is that commitlint not working in directories with git :astonished:
example
 ~  ls -lAFh | grep commit
lrwxrwxrwx   1 bjorn users   45 Oct 18 20:41 .commitlintrc.yml -> /home/bjorn/.config/dotfiles/commitlintrc.yml
 ~  echo "foo" | commitlint
⧗   input: foo
✖   scope may not be empty [scope-empty]
✖   message may not be empty [subject-empty]
✖   type may not be empty [type-empty]
⚠   header must not be shorter than 30 characters [header-min-length]
✖   found 3 problems, 1 warnings
 ✘  ~  cd Documents
 ~/Documents  echo "foo" | commitlint
⧗   input: foo
✖   scope may not be empty [scope-empty]
✖   message may not be empty [subject-empty]
✖   type may not be empty [type-empty]
⚠   header must not be shorter than 30 characters [header-min-length]
✖   found 3 problems, 1 warnings
 ✘  ~/Documents  pjdot
 ~/.config/dotfiles   master  echo "foo" | commitlint
⧗   input: foo
✔   found 0 problems, 0 warnings

 ~/.config/dotfiles   master  ls -lAFh | grep commit
-rw-r--r-- 1 bjorn users 1.1K Oct 18 20:42 commitlintrc.yml
 ~/.config/dotfiles   master  pj psc-ide-vim
 ~/projects/psc-ide-vim   fix ●  echo "foo" | commitlint
⧗   input: foo
✔   found 0 problems, 0 warnings

 ~/projects/psc-ide-vim   fix ●  echo "foo" | npx commitlint
⧗   input: foo
✔   found 0 problems, 0 warnings

 ~/projects/psc-ide-vim   fix ●  ..
 ~/projects  echo "foo" | npx commitlint
⧗   input: foo
✖   scope may not be empty [scope-empty]
✖   message may not be empty [subject-empty]
✖   type may not be empty [type-empty]
⚠   header must not be shorter than 30 characters [header-min-length]
✖   found 3 problems, 1 warnings

Ok my bad - commitlint currently stops searching upwards for config files on the git root (if any) we probably should change that to stops at the git root if there is a a file found there.

Wow, looking forward to fix)

Concerning @commitlint/prompt-cli: Would you consider using a commit prompt if it injected the equivalent git commit into history?

@marionebl , first of all, thanks for fix

Would you consider using a commit prompt if it injected the equivalent git commit into history?

not sure how it will work
basically what I want is:

to reapply commit if it failed in midway. Consider project with tests running on precommit hook. I've made message, I press enter, test failed, I have to reenter message
make new commit with slightly modified message of previous commit. (so I just searching command in zsh history starting with a gaa && lc in this case)

authors: BjornMelgaard marionebl

repo: marionebl/commitlint


text:
🤡😡

https://blog.bangwu.top/environment/CDN日记.html
一个小白友好的教程网站

解决此方案源站之间的同步可以使用Rclone：https://blog.bangwu.top/software/Rclone.html


text:
False positives: version numbers

Version numbers like 0.5.0.0 are considered as IP addresses without a schema.

I can add more strict condition for heading zeros, but it will not help with 1.5.0.0 and so on. I see only one possibility - more options to tune fuzzy links.

I agree. #14 would also fix this issue for diaspora* but I think for other projects it might help to disable IP adresses without schemas. (at least add a setting to enable/disable it)

authors: puzrin svbergerem

repo: markdown-it/linkify-it


text:
autoscaling enhancement

The demo would be smoother if it were easier to show more incremental scaling up and down

scale up from 0-1, then wait for cold-start and offset to start moving, then scale 1-N if necessary
scale down from n-1 incrementally instead of all at once, the pause scaling down at 1, before going to 0.

I experimented a bit with tapered downscale delays. For example, scaling 1->0 should be the full idleTimeout value, but scaling max->(max-1) should be 1/2 of the idleTimeout (with the rest of the range adjusted linearly. That's just one idea; implementation could vary and will likely continue to evolve.

this needs to be reported as a function-controller issue (those changes would be internal based on the current state)

authors: jldec markfisher


text:
RawCombinedQueryDefinition in QueryBatcher throws NPE

Version of MarkLogic Java Client API
develop (post 5.2.0 tag release)
Version of MarkLogic Server
10.0 night (post 10.0-4 server release)
Java version
Java 9
OS and version
Linux and Windows
Input: Some code to illustrate the problem, preferably in a state that can be independently reproduced on our end
Given a combined query such as one here https://github.com/marklogic/java-client-api/blob/develop/marklogic-client-api-functionaltests/src/test/java/com/marklogic/client/functionaltest/combined/combinedQueryOptionJSON.json
{"search":{"query":{"value-constraint-query":{"constraint-name":"id", "text":"0026"}}, "options":{"return-metrics":false, "return-qtext":false, "debug":true, "transform-results":{"apply":"raw"}, "constraint":{"name":"id", "value":{"element":{"ns":"", "name":"id"}}}}}}

and data files
constraint1.xml
<root>
  <title>Vannevar Bush</title>
  <popularity>5</popularity>
  <id>0011</id>
  <date xmlns="http://purl.org/dc/elements/1.1/">2005-01-01</date>
  <price xmlns="http://cloudbank.com" amt="0.1"/>

Vannevar Bush wrote an article for The Atlantic Monthly

</root>

constraint2.xml
<root>
  <title>The Bush article</title>
  <popularity>4</popularity>
  <id>0012</id>
  <date xmlns="http://purl.org/dc/elements/1.1/">2006-02-02</date>
  <price xmlns="http://cloudbank.com" amt="0.12"/>

The Bush article described a device called a Memex.

</root>

constraint3.xml
<root>
  <title>For 1945</title>
  <popularity>3</popularity>
  <id>0113</id>
  <date xmlns="http://purl.org/dc/elements/1.1/">2007-03-03</date>
  <price xmlns="http://cloudbank.com" amt="1.23"/>

For 1945, the thoughts expressed in The Atlantic Monthly were groundbreaking.

</root>

constraint4.xml
<root>
  <title>Vannevar served</title>
  <popularity>5</popularity>
  <id>0024</id>
  <date xmlns="http://purl.org/dc/elements/1.1/">2008-04-04</date>
  <price xmlns="http://cloudbank.com" amt="12.34"/>

Vannevar served as a prominent policymaker and public intellectual.

</root>

constraint5.xml
<root>
  <title>The memex</title>
<popularity>5</popularity>
<id>0026</id>
<date xmlns="http://purl.org/dc/elements/1.1/">2009-05-05</date>
<price xmlns="http://cloudbank.com" amt="123.45"/>

The Memex, unfortunately, had no automated search feature.

</root>

A QueryBatcher with RawCombinedQueryDefinition created with help of a Handle, when run, produces NPE
The same RawCombinedQueryDefinition  when run with a QueryManager, produces the desired result.
Sample code:
     WriteBatcher wbatcher = dmManagerTmp.newWriteBatcher();

      wbatcher.withBatchSize(2);
      InputStreamHandle contentHandle1 = new InputStreamHandle();
      contentHandle1.set(new FileInputStream(dataFileDir + filenames[0]));
      InputStreamHandle contentHandle2 = new InputStreamHandle();
      contentHandle2.set(new FileInputStream(dataFileDir + filenames[1]));
      InputStreamHandle contentHandle3 = new InputStreamHandle();
      contentHandle3.set(new FileInputStream(dataFileDir + filenames[2]));
      InputStreamHandle contentHandle4 = new InputStreamHandle();
      contentHandle4.set(new FileInputStream(dataFileDir + filenames[3]));
      InputStreamHandle contentHandle5 = new InputStreamHandle();
      contentHandle5.set(new FileInputStream(dataFileDir + filenames[4]));

      wbatcher.add(filenames[0], contentHandle1);
      wbatcher.add(filenames[1], contentHandle2);
      wbatcher.add(filenames[2], contentHandle3);
      wbatcher.add(filenames[3], contentHandle4);
      wbatcher.add(filenames[4], contentHandle5);

      wbatcher.flushAndWait();
      // get the combined query
      File file = new File(combQueryFileDir + combinedQueryFileName);

      String combinedQuery = convertFileToString(file);

      // create a handle for the search criteria
      StringHandle rawHandle = new StringHandle(combinedQuery);
      rawHandle.setFormat(Format.JSON);

      // create a handle for the search criteria
      //FileHandle rawHandle = (new FileHandle(file)).withFormat(Format.JSON);
      // create a search definition based on the handle
      RawCombinedQueryDefinition querydef = queryMgr.newRawCombinedQueryDefinition(rawHandle);

      /*String wordQuery = "<cts:word-query xmlns:cts=\"http://marklogic.com/cts\">" +
              "<cts:text>unfortunately</cts:text></cts:word-query>";
      StringHandle handle = new StringHandle().with(wordQuery);
      RawCtsQueryDefinition querydef = queryMgr.newRawCtsQueryDefinition(handle);*/

      StringBuilder batchResults = new StringBuilder();
      StringBuilder batchFailResults = new StringBuilder();

      // Run a QueryBatcher on the new URIs.
      QueryBatcher queryBatcher1 = dmManagerTmp.newQueryBatcher(querydef);

      queryBatcher1.onUrisReady(batch -> {
        for (String str : batch.getItems()) {
          batchResults.append(str)
              .append('|');
        }
      });
      queryBatcher1.onQueryFailure(throwable -> {
        System.out.println("Exceptions thrown from callback onQueryFailure");
        batchFailResults.append(throwable.getMessage());
        batchFailResults.append("Test has Exceptions");
      });

      dmManagerTmp.startJob(queryBatcher1);
      boolean bJobFinished = queryBatcher1.awaitCompletion(3, TimeUnit.MINUTES);
...
...

Actual output: What did you observe? What errors did you see? Can you attach the logs? (Java logs, MarkLogic logs)
Listener QueryFailure StringBuilder variable has java.lang.NullPointerException
Expected output: What specifically did you expect to happen?
URI returned in StringBuilder should be constraint5.xml.
Alternatives: What else have you tried, actual/expected?
Used a simple word-query as QueryDefinition, the results returned are as expected.

@georgeajit , do you happen to have the stack trace?

@georgeajit , is this issue for the com.marklogic.client.functionaltest.TestRawCombinedQuery#test5RawCombinedQueryJSON test?  That's running without exception in my local environment.
I also notice that the Java-client-api-develop-10.0-nightly_OPENJDK9 Jenkins job is green.

We need to ran it in DMSDK. With QueryManager it works, but on QueryBatcher it fails.  com.marklogic.client.functionaltest.TestRawCombinedQuery#test5RawCombinedQueryJSON is a non DMSDK test and that works fine.

The checkin above should fix the null pointer exception. However, once past the null pointer exception, a search problem that's the root cause for the null pointer would still manifest.
The search issue -- at least for the recurrence of #1163 -- was that the enode refactoring mistakenly removed support for one query case.  Support for that query case has been restored under internal bug 55120.
So, the search issue should go away with the next nightly build of b10 / trunk for the server.

The issue is fixed.

authors: ehennum georgeajit

repo: marklogic/java-client-api


text:
wb.awaitCompletion() and wb.awaitTermination() getting called after stopping wb instance

Currently, wb.awaitCompletion() and wb.awaitTermination() are not throwing any exception when they are called after the 'wb' instance has been stopped.

I don't see any risk in calling those methods after stopping wb instance.  They should just return immediately.  I think current behavior is acceptable.  By the way, I just logged #586 - remove awaitTermination since I don't see any significant difference between awaitCompletion and awaitTermination

authors: sammefford srinathgit


text:
[BUG] Banner aren't responsive

Describe the bug
Scale as expected on large screen. Scale like large screen on mobile, letting a huge blank below
To Reproduce
Steps to reproduce the behavior:
1.Setup tailwindcss 3.4.1
2.Make standard html file with head and body and link to the tailwindcss output file
3.copy and paste Centered with Actions and Gradient
4.Open chrome (or firefox) developer tool to switch from normal layout to responsive (Iphone 14 Pro Max in my case)
Expected behavior
Should have scaled exactly like the mobile button preview on the website
Screenshots

Desktop (please complete the following information):

OS: Linux
Browser: Brave or Firefox
Version: latest

Smartphone (please complete the following information):

Device: Iphone 14 Pro Max (emulated)

You're right. I'm kinda dumb. Thx for pointing me out

repo: markmead/hyperui


text:
feat: default to python3-openssl in Ubuntu and Debian

Add support for Ubuntu 22.04 LTS release.
This should work as the new default since Python 2 is EOL.
Fix #54

Excellent :) Thanks!

authors: bartdorsey markosamuli

repo: markosamuli/ansible-pyenv


text:
curious error when reading fastq.gz files (maybe not an issue)

Hi,
Many thanks for developing and sharing seq_io!
I recently got a curious case when trying to parse a gziped fastq files sent by one of my collaborators. When using seq_io directly on these files, I get for all them the following error message:

Err value: UnexpectedEnd { pos: ErrorPosition { line: 713, id: None } }

However, if I gunzip these fastq files and re-gzip them, they get parsed as expected.
Would you know what could cause this error? Could it be an incompatibility Windows/Unix (I'm using a Unix system but I don't know how these files have been generated)?
My apologies if this is a trivial question/issue.

Without details about the implementation, I cannot precisely know what is going on.
However, in case you are using GzDecoder from the flate2 crate, the described error can in fact occur. Many 'fastq.gz' files are in fact multi-member files which makes it necessary to use MultiGzDecoder instead. I've hit this problem earlier as well, since I didn't know about this. Could this be the problem in your case?

Hi,
Thanks a lot for your reply and my apologies for not giving you more details!
You have indeed identified my mistake: I was using GzDecoder instead of GzDecoder. Now all files are correctly parsed.
best,
Romain

authors: markschl rderelle


text:
More on File uploads => Multipart

Am in a situation where i'd like all files uploaded to be sent as multi-part, there are forms where i have many file inputs but i can't figure out a way to loop through all the file fields without repeating my code for each and every file input field.
To my observation, admin-on-rest is ideal for text-content only. I mean managing content that doesn't need file uploads e.t.c
Due to the fact that your library lacks in-depth documentation on files handling, for example i only found ImageInput for handling image files, what about other types of files?  these are critical aspects of a modern admin-dashboard.
Regards i do appreciate this lib, Awesome lib man!

Admin-on-rest lacks documentation on submitting multipart data with AJAX because it's not in its scope. Admin-on-rest provides a resource created or edited via a web interface as à JSON object, it's your job to pass it to your backend. The reason is that since REST isn't standardized, there is no way we can adapt to your own API with a library.
Google for "Multipart AJAX" to find answers to your question.

authors: ceddyb fzaninotto

repo: marmelab/admin-on-rest


text:
Update PeekPop.swift

Remove unused variable.

Hi @TheDarkCode, thanks for the contribution. previewingContexts is used though to keep a reference to registered previewing contexts and shouldn't be removed. Closing this PR.

To have it remain is just a waste of reference count operations as-is because you never do anything with the reference. Hence, the removal. I don't see the need for ever having more than one previewing context registered, especially if you're going to keep the reference private within PeekPop which disallows its utility unless as included in an extension to PeekPop.
However, this still comes down to the fact that you're maintaining multiple previewing contexts loaded in memory without handling disposing of stale references. A previewing context can already load so fast, why would you waste the memory on keeping multiple contexts in an array?

authors: TheDarkCode marmelroy

repo: marmelroy/PeekPop


text:
potential model name collision of models on slurm cluster: afterall: domainlab/compos/exp/exp_utils.py", line 99, in load

currently, the code is like this:
   def after_all(self):
        """
        After training is done
        """
        model_ld = None
        try:
            model_ld = self.exp.visitor.load()
        except FileNotFoundError:
            # this can happen if loss is increasing, model never get selected
            return

        model_ld = model_ld.to(self.device)
        model_ld.eval()
        print("persisted model performance metric: \n")
        metric_te = model_ld.cal_perf_metric(self.loader_te, self.device)
        self.dump_prediction(model_ld, metric_te)
        self.exp.visitor(metric_te)
        # prediction dump of test domain is essential to verify the prediction results

The error to report here is that in afterall, the model loaded does not match the model in memory in size for diva and hduva, see below
in slurm log file:
run_experiment-index=13-11936875.out
the output file displays no error but with early stop finished.
processing dataset for  hduva
b'ed330e4'
model name: pathlist_te_sketch_hduva_bed330e4_2023md_06md_06_14_55_52_seed_0

with

epoch: 321  now:  2023-06-06 21:31:53.171784 epoch time:  0:01:13.399267 used:  6:35:56.573210 model:  pathlist_te_sketch_hduva_bed330e4_2023md_06md_06_14_55_52_seed_0
epoch: 322
pooled train domains performance:
{
    'acc': 1.0,
    'precision': 1.0,
    'recall': 1.0,
    'specificity': 1.0,
    'f1': 1.0,
    'auroc': 1.0
}
confusion matrix:
     0    1    2    3    4    5     6
0  860    0    0    0    0    0     0
1    0  821    0    0    0    0     0
2    0    0  730    0    0    0     0
3    0    0    0  453    0    0     0
4    0    0    0    0  649    0     0
5    0    0    0    0    0  773     0
6    0    0    0    0    0    0  1154
out of domain test performance:
{
    'acc': 0.5907675,
    'precision': 0.576159,
    'recall': 0.53352654,
    'specificity': 0.92936075,
    'f1': 0.523332,
    'auroc': 0.8630302
}
confusion matrix:
     0    1    2    3    4   5    6
0  180  231   17    1  197   2   66
1   30  585    2    0   22   0   26
2   45   75  237   15  188  13  104
3    2   22   14  501    1   3    4
4   20  123   28    2  532  10   19
5    0   35    1    0    0  35    0
6    0  101   26    0    0   0   16
early stop counter:  6
loss:3847192432.0, best loss: 3846092536.0
epoch: 322  now:  2023-06-06 21:33:05.517891 epoch time:  0:01:12.346107 used:  6:37:08.919317 model:  pathlist_te_sketch_hduva_bed330e4_2023md_06md_06_14_55_52_seed_0
early stop trigger
Experiment finished at epoch: 322 with time: 6:37:08.919317 at 2023-06-06 21:33:05.517891

but in the error file: run_experiment-index=13-11936875.err
Building DAG of jobs...
Using shell: /usr/bin/bash
Provided cores: 2
Rules claiming more threads will be scaled down.
Provided resources: mem_mb=100000, mem_mib=95368, disk_mb=1000, disk_mib=954, nvidia_gpu=1
Select jobs to execute...

[Tue Jun  6 14:52:26 2023]
rule run_experiment:
    input: zoutput/benchmarks/pacs_benchmark/hyperparameters.csv
    output: zoutput/benchmarks/pacs_benchmark/rule_results/13.csv
    jobid: 0
    reason: Missing output files: zoutput/benchmarks/pacs_benchmark/rule_results/13.csv
    wildcards: index=13
    resources: mem_mb=100000, mem_mib=95368, disk_mb=1000, disk_mib=954, tmpdir=/tmp, partition=gpu_p, qos=gpu, nvidia_gpu=1

/home/aih/xudong.sun/anaconda3/lib/python3.9/site-packages/torch/nn/_reduction.py:42: UserWarning: size_average and reduce args will be deprecated, please use reduction='sum' instead.
  warnings.warn(warning.format(ret))
/home/aih/xudong.sun/anaconda3/lib/python3.9/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
  warnings.warn(
/home/aih/xudong.sun/anaconda3/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=AlexNet_Weights.IMAGENET1K_V1`. You can also use `weights=AlexNet_Weights.DEFAULT` to get the most up-to-date weights.
  warnings.warn(msg)
/home/aih/xudong.sun/anaconda3/lib/python3.9/site-packages/torchmetrics/utilities/prints.py:36: UserWarning: Metric `AUROC` will save all targets and predictions in buffer. For large datasets this may lead to large memory footprint.
  warnings.warn(*args, **kwargs)
/home/aih/xudong.sun/domainlab4matchdg/domainlab/algos/trainers/train_visitor.py:31: UserWarning: hyper-parameter scheduler not set,                           going to use default Warmpup and epoch update
  warnings.warn("hyper-parameter scheduler not set, \
[Tue Jun  6 21:33:06 2023]
Error in rule run_experiment:
    jobid: 0
    input: zoutput/benchmarks/pacs_benchmark/hyperparameters.csv
    output: zoutput/benchmarks/pacs_benchmark/rule_results/13.csv

RuleException:
RuntimeError in file /home/aih/xudong.sun/domainlab4matchdg/domainlab/exp_protocol/benchmark.smk, line 121:
Error(s) in loading state_dict for ModelHDUVA:
	size mismatch for encoder.net_infer_zd_topic.imgtopic2zd.encoder_cat_topic_img_h2zd.fc_loc.0.weight: copying a param with shape torch.Size([32, 4096]) from checkpoint, the shape in current model is torch.Size([64, 4096]).
	size mismatch for encoder.net_infer_zd_topic.imgtopic2zd.encoder_cat_topic_img_h2zd.fc_loc.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
	size mismatch for encoder.net_infer_zd_topic.imgtopic2zd.encoder_cat_topic_img_h2zd.fc_scale.0.weight: copying a param with shape torch.Size([32, 4096]) from checkpoint, the shape in current model is torch.Size([64, 4096]).
	size mismatch for encoder.net_infer_zd_topic.imgtopic2zd.encoder_cat_topic_img_h2zd.fc_scale.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
	size mismatch for encoder.net_infer_zx.fc_loc.0.weight: copying a param with shape torch.Size([64, 179776]) from checkpoint, the shape in current model is torch.Size([32, 179776]).
	size mismatch for encoder.net_infer_zx.fc_loc.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for encoder.net_infer_zx.fc_scale.0.weight: copying a param with shape torch.Size([64, 179776]) from checkpoint, the shape in current model is torch.Size([32, 179776]).
	size mismatch for encoder.net_infer_zx.fc_scale.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for encoder.net_infer_zy.net_fc_mean.0.weight: copying a param with shape torch.Size([32, 4096]) from checkpoint, the shape in current model is torch.Size([64, 4096]).
	size mismatch for encoder.net_infer_zy.net_fc_mean.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
	size mismatch for encoder.net_infer_zy.net_fc_scale.0.weight: copying a param with shape torch.Size([32, 4096]) from checkpoint, the shape in current model is torch.Size([64, 4096]).
	size mismatch for encoder.net_infer_zy.net_fc_scale.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
	size mismatch for decoder.net_fc_z2flat_img.0.h.weight: copying a param with shape torch.Size([150528, 131]) from checkpoint, the shape in current model is torch.Size([150528, 163]).
	size mismatch for decoder.net_fc_z2flat_img.0.g.weight: copying a param with shape torch.Size([150528, 131]) from checkpoint, the shape in current model is torch.Size([150528, 163]).
	size mismatch for net_p_zy.net_linear_bn_relu.0.weight: copying a param with shape torch.Size([32, 7]) from checkpoint, the shape in current model is torch.Size([64, 7]).
	size mismatch for net_p_zy.net_linear_bn_relu.1.weight: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
	size mismatch for net_p_zy.net_linear_bn_relu.1.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
	size mismatch for net_p_zy.net_linear_bn_relu.1.running_mean: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
	size mismatch for net_p_zy.net_linear_bn_relu.1.running_var: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
	size mismatch for net_p_zy.fc_loc.0.weight: copying a param with shape torch.Size([32, 32]) from checkpoint, the shape in current model is torch.Size([64, 64]).
	size mismatch for net_p_zy.fc_loc.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
	size mismatch for net_p_zy.fc_scale.0.weight: copying a param with shape torch.Size([32, 32]) from checkpoint, the shape in current model is torch.Size([64, 64]).
	size mismatch for net_p_zy.fc_scale.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
	size mismatch for net_classif_y.op_linear.weight: copying a param with shape torch.Size([7, 32]) from checkpoint, the shape in current model is torch.Size([7, 64]).
	size mismatch for net_p_zd.net_linear_bn_relu.0.weight: copying a param with shape torch.Size([32, 3]) from checkpoint, the shape in current model is torch.Size([64, 3]).
	size mismatch for net_p_zd.net_linear_bn_relu.1.weight: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
	size mismatch for net_p_zd.net_linear_bn_relu.1.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
	size mismatch for net_p_zd.net_linear_bn_relu.1.running_mean: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
	size mismatch for net_p_zd.net_linear_bn_relu.1.running_var: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
	size mismatch for net_p_zd.fc_loc.0.weight: copying a param with shape torch.Size([32, 32]) from checkpoint, the shape in current model is torch.Size([64, 64]).
	size mismatch for net_p_zd.fc_loc.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
	size mismatch for net_p_zd.fc_scale.0.weight: copying a param with shape torch.Size([32, 32]) from checkpoint, the shape in current model is torch.Size([64, 64]).
	size mismatch for net_p_zd.fc_scale.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
  File "/home/aih/xudong.sun/domainlab4matchdg/domainlab/exp_protocol/benchmark.smk", line 121, in __rule_run_experiment
  File "/home/aih/xudong.sun/domainlab4matchdg/domainlab/exp_protocol/run_experiment.py", line 109, in run_experiment
  File "/home/aih/xudong.sun/domainlab4matchdg/domainlab/compos/exp/exp_main.py", line 70, in execute
  File "/home/aih/xudong.sun/domainlab4matchdg/domainlab/algos/trainers/a_trainer.py", line 106, in post_tr
  File "/home/aih/xudong.sun/domainlab4matchdg/domainlab/algos/observers/c_obvisitor_cleanup.py", line 12, in after_all
  File "/home/aih/xudong.sun/domainlab4matchdg/domainlab/algos/observers/b_obvisitor.py", line 61, in after_all
  File "/home/aih/xudong.sun/domainlab4matchdg/domainlab/compos/exp/exp_utils.py", line 99, in load
  File "/home/aih/xudong.sun/anaconda3/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1671, in load_state_dict
  File "/home/aih/xudong.sun/anaconda3/lib/python3.9/concurrent/futures/thread.py", line 52, in run
Shutting down, this might take some time.
Exiting because a job execution failed. Look above for error message

while in snakemake console,  the snakemake stops making further submissions.
Select jobs to execute...

10, Task2, hduva, 333, sketch, 2, "{'gamma_y': 192400, 'zx_dim': 64, 'zy_dim': 64, 'zd_dim': 64}", 0.59274995, 0.60296017, 0.52567023, 0.929962, 0.52843946, 0.8426663
Building DAG of jobs...
Using shell: /usr/bin/bash
Provided cores: 2
Rules claiming more threads will be scaled down.
Provided resources: mem_mb=100000, mem_mib=95368, disk_mb=1000, disk_mib=954, nvidia_gpu=1
Select jobs to execute...

    reason: Missing output files: zoutput/benchmarks/pacs_benchmark/rule_results/10.csv; Input files updated by another job: zoutput/benchmarks/pacs_benchmark/hyperparameters.csv
    wildcards: index=10
    resources: mem_mb=100000, mem_mib=95368, disk_mb=1000, disk_mib=954, tmpdir=<TBD>, partition=gpu_p, qos=gpu, nvidia_gpu=1

Submitted job 14 with external jobid 'Submitted batch job 11947037'.
[Tue Jun  6 21:33:15 2023]
Error in rule run_experiment:
    jobid: 17
    input: zoutput/benchmarks/pacs_benchmark/hyperparameters.csv
    output: zoutput/benchmarks/pacs_benchmark/rule_results/13.csv
    cluster_jobid: Submitted batch job 11936875

Error executing rule run_experiment on cluster (jobid: 17, external: Submitted batch job 11936875, jobscript: /home/aih/xudong.sun/domainlab4matchdg/.snakemake/tmp.q1xxt1ea/snakejob.run_experiment.17.sh). For error details see the cluster log and the log files of the involved rule(s).
Trying to restart job 17.
Select jobs to execute...

[Tue Jun  6 21:33:15 2023]
rule run_experiment:
    input: zoutput/benchmarks/pacs_benchmark/hyperparameters.csv
    output: zoutput/benchmarks/pacs_benchmark/rule_results/13.csv
    jobid: 17
    reason: Missing output files: zoutput/benchmarks/pacs_benchmark/rule_results/13.csv; Input files updated by another job: zoutput/benchmarks/pacs_benchmark/hyperparameters.csv
    wildcards: index=13
    resources: mem_mb=100000, mem_mib=95368, disk_mb=1000, disk_mib=954, tmpdir=<TBD>, partition=gpu_p, qos=gpu, nvidia_gpu=1

Submitted job 17 with external jobid 'Submitted batch job 11949921'.
Submitted job 17 with external jobid 'Submitted batch job 11949921'.
[Wed Jun  7 14:24:10 2023]
Finished job 7.
2 of 20 steps (10%) done
[Wed Jun  7 19:21:47 2023]
Finished job 6.
3 of 20 steps (15%) done
[Wed Jun  7 23:53:59 2023]
Finished job 5.
4 of 20 steps (20%) done
[Thu Jun  8 00:31:29 2023]
Finished job 12.
5 of 20 steps (25%) done
[Thu Jun  8 00:55:59 2023]
Finished job 15.
6 of 20 steps (30%) done
[Thu Jun  8 01:22:02 2023]
Finished job 19.
7 of 20 steps (35%) done
[Thu Jun  8 02:01:41 2023]
Finished job 10.
8 of 20 steps (40%) done
[Thu Jun  8 04:01:49 2023]
Finished job 11.
9 of 20 steps (45%) done
[Thu Jun  8 05:08:29 2023]
Finished job 9.
10 of 20 steps (50%) done
[Thu Jun  8 08:49:49 2023]
Finished job 8.
11 of 20 steps (55%) done
[Thu Jun  8 08:55:07 2023]
Finished job 18.
12 of 20 steps (60%) done
[Thu Jun  8 09:55:37 2023]
Finished job 13.
13 of 20 steps (65%) done
[Thu Jun  8 12:23:34 2023]
Finished job 3.
14 of 20 steps (70%) done
[Thu Jun  8 13:16:02 2023]
Finished job 14.
15 of 20 steps (75%) done
[Thu Jun  8 18:39:06 2023]
Finished job 17.
16 of 20 steps (80%) done

From another run, similar error occurs while in the out file the last line read early stop encountered

Building DAG of jobs...
Using shell: /usr/bin/bash
Provided cores: 2
Rules claiming more threads will be scaled down.
Provided resources: mem_mb=100000, mem_mib=95368, disk_mb=1000, disk_mib=954, nvidia_gpu=1
Select jobs to execute...

[Mon Jun  5 14:17:56 2023]
rule run_experiment:
    input: zoutput/benchmarks/pacs_benchmark_big_gamma/hyperparameters.csv
    output: zoutput/benchmarks/pacs_benchmark_big_gamma/rule_results/15.csv
    jobid: 0
    reason: Missing output files: zoutput/benchmarks/pacs_benchmark_big_gamma/rule_results/15.csv
    wildcards: index=15
    resources: mem_mb=100000, mem_mib=95368, disk_mb=1000, disk_mib=954, tmpdir=/tmp, partition=gpu_p, qos=gpu, nvidia_gpu=1

/home/aih/xudong.sun/anaconda3/lib/python3.9/site-packages/torch/nn/_reduction.py:42: UserWarning: size_average and reduce args will be deprecated, please use reduction='sum' instead.
  warnings.warn(warning.format(ret))
/home/aih/xudong.sun/anaconda3/lib/python3.9/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
  warnings.warn(
/home/aih/xudong.sun/anaconda3/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=AlexNet_Weights.IMAGENET1K_V1`. You can also use `weights=AlexNet_Weights.DEFAULT` to get the most up-to-date weights.
  warnings.warn(msg)
/home/aih/xudong.sun/anaconda3/lib/python3.9/site-packages/torchmetrics/utilities/prints.py:36: UserWarning: Metric `AUROC` will save all targets and predictions in buffer. For large datasets this may lead to large memory footprint.
  warnings.warn(*args, **kwargs)
/home/aih/xudong.sun/DomainLab/domainlab/algos/trainers/train_visitor.py:31: UserWarning: hyper-parameter scheduler not set,                           going to use default Warmpup and epoch update
  warnings.warn("hyper-parameter scheduler not set, \
[Mon Jun  5 21:42:32 2023]
Error in rule run_experiment:
    jobid: 0
    input: zoutput/benchmarks/pacs_benchmark_big_gamma/hyperparameters.csv
    output: zoutput/benchmarks/pacs_benchmark_big_gamma/rule_results/15.csv

RuleException:
RuntimeError in file /home/aih/xudong.sun/DomainLab/domainlab/exp_protocol/benchmark.smk, line 121:
Error(s) in loading state_dict for ModelHDUVA:
	size mismatch for encoder.net_infer_zd_topic.imgtopic2zd.encoder_cat_topic_img_h2zd.fc_loc.0.weight: copying a param with shape torch.Size([64, 4096]) from checkpoint, the shape in current model is torch.Size([32, 4096]).
	size mismatch for encoder.net_infer_zd_topic.imgtopic2zd.encoder_cat_topic_img_h2zd.fc_loc.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for encoder.net_infer_zd_topic.imgtopic2zd.encoder_cat_topic_img_h2zd.fc_scale.0.weight: copying a param with shape torch.Size([64, 4096]) from checkpoint, the shape in current model is torch.Size([32, 4096]).
	size mismatch for encoder.net_infer_zd_topic.imgtopic2zd.encoder_cat_topic_img_h2zd.fc_scale.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for encoder.net_infer_zy.net_fc_mean.0.weight: copying a param with shape torch.Size([64, 4096]) from checkpoint, the shape in current model is torch.Size([32, 4096]).
	size mismatch for encoder.net_infer_zy.net_fc_mean.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for encoder.net_infer_zy.net_fc_scale.0.weight: copying a param with shape torch.Size([64, 4096]) from checkpoint, the shape in current model is torch.Size([32, 4096]).
	size mismatch for encoder.net_infer_zy.net_fc_scale.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for decoder.net_fc_z2flat_img.0.h.weight: copying a param with shape torch.Size([150528, 163]) from checkpoint, the shape in current model is torch.Size([150528, 99]).
	size mismatch for decoder.net_fc_z2flat_img.0.g.weight: copying a param with shape torch.Size([150528, 163]) from checkpoint, the shape in current model is torch.Size([150528, 99]).
	size mismatch for net_p_zy.net_linear_bn_relu.0.weight: copying a param with shape torch.Size([64, 7]) from checkpoint, the shape in current model is torch.Size([32, 7]).
	size mismatch for net_p_zy.net_linear_bn_relu.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for net_p_zy.net_linear_bn_relu.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for net_p_zy.net_linear_bn_relu.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for net_p_zy.net_linear_bn_relu.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for net_p_zy.fc_loc.0.weight: copying a param with shape torch.Size([64, 64]) from checkpoint, the shape in current model is torch.Size([32, 32]).
	size mismatch for net_p_zy.fc_loc.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for net_p_zy.fc_scale.0.weight: copying a param with shape torch.Size([64, 64]) from checkpoint, the shape in current model is torch.Size([32, 32]).
	size mismatch for net_p_zy.fc_scale.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for net_classif_y.op_linear.weight: copying a param with shape torch.Size([7, 64]) from checkpoint, the shape in current model is torch.Size([7, 32]).
	size mismatch for net_p_zd.net_linear_bn_relu.0.weight: copying a param with shape torch.Size([64, 3]) from checkpoint, the shape in current model is torch.Size([32, 3]).
	size mismatch for net_p_zd.net_linear_bn_relu.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for net_p_zd.net_linear_bn_relu.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for net_p_zd.net_linear_bn_relu.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for net_p_zd.net_linear_bn_relu.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for net_p_zd.fc_loc.0.weight: copying a param with shape torch.Size([64, 64]) from checkpoint, the shape in current model is torch.Size([32, 32]).
	size mismatch for net_p_zd.fc_loc.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
	size mismatch for net_p_zd.fc_scale.0.weight: copying a param with shape torch.Size([64, 64]) from checkpoint, the shape in current model is torch.Size([32, 32]).
	size mismatch for net_p_zd.fc_scale.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
  File "/home/aih/xudong.sun/DomainLab/domainlab/exp_protocol/benchmark.smk", line 121, in __rule_run_experiment
  File "/home/aih/xudong.sun/DomainLab/domainlab/exp_protocol/run_experiment.py", line 109, in run_experiment
  File "/home/aih/xudong.sun/DomainLab/domainlab/compos/exp/exp_main.py", line 70, in execute
  File "/home/aih/xudong.sun/DomainLab/domainlab/algos/trainers/a_trainer.py", line 106, in post_tr
  File "/home/aih/xudong.sun/DomainLab/domainlab/algos/observers/c_obvisitor_cleanup.py", line 12, in after_all
  File "/home/aih/xudong.sun/DomainLab/domainlab/algos/observers/b_obvisitor.py", line 61, in after_all
  File "/home/aih/xudong.sun/DomainLab/domainlab/compos/exp/exp_utils.py", line 99, in load
  File "/home/aih/xudong.sun/anaconda3/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1671, in load_state_dict
  File "/home/aih/xudong.sun/anaconda3/lib/python3.9/concurrent/futures/thread.py", line 52, in run
Shutting down, this might take some time.
Exiting because a job execution failed. Look above for error message

[Tue Jun 13 20:31:15 2023]
Error in rule run_experiment:
jobid: 0
input: zoutput/benchmarks/pacs_benchmark/hyperparameters.csv
output: zoutput/benchmarks/pacs_benchmark/rule_results/12.csv
RuleException:
RuntimeError in file /home/aih/xudong.sun/domainlab_correct_pacs_split/domainlab/exp_protocol/benchmark.smk, line 121:
Error(s) in loading state_dict for ModelHDUVA:
size mismatch for encoder.net_infer_zd_topic.imgtopic2zd.encoder_cat_topic_img_h2zd.fc_loc.0.weight: copying a param with shape torch.Size([64, 4096]) from checkpoint, the shape in current model is torch.Size([32, 4096]).
size mismatch for encoder.net_infer_zd_topic.imgtopic2zd.encoder_cat_topic_img_h2zd.fc_loc.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for encoder.net_infer_zd_topic.imgtopic2zd.encoder_cat_topic_img_h2zd.fc_scale.0.weight: copying a param with shape torch.Size([64, 4096]) from checkpoint, the shape in current model is torch.Size([32, 4096]).
size mismatch for encoder.net_infer_zd_topic.imgtopic2zd.encoder_cat_topic_img_h2zd.fc_scale.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for encoder.net_infer_zx.fc_loc.0.weight: copying a param with shape torch.Size([32, 179776]) from checkpoint, the shape in current model is torch.Size([64, 179776]).
size mismatch for encoder.net_infer_zx.fc_loc.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for encoder.net_infer_zx.fc_scale.0.weight: copying a param with shape torch.Size([32, 179776]) from checkpoint, the shape in current model is torch.Size([64, 179776]).
size mismatch for encoder.net_infer_zx.fc_scale.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for encoder.net_infer_zy.net_fc_mean.0.weight: copying a param with shape torch.Size([64, 2048]) from checkpoint, the shape in current model is torch.Size([32, 2048]).
size mismatch for encoder.net_infer_zy.net_fc_mean.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for encoder.net_infer_zy.net_fc_scale.0.weight: copying a param with shape torch.Size([64, 2048]) from checkpoint, the shape in current model is torch.Size([32, 2048]).
size mismatch for encoder.net_infer_zy.net_fc_scale.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for decoder.net_fc_z2flat_img.0.h.weight: copying a param with shape torch.Size([150528, 163]) from checkpoint, the shape in current model is torch.Size([150528, 131]).
size mismatch for decoder.net_fc_z2flat_img.0.g.weight: copying a param with shape torch.Size([150528, 163]) from checkpoint, the shape in current model is torch.Size([150528, 131]).
size mismatch for net_p_zy.net_linear_bn_relu.0.weight: copying a param with shape torch.Size([64, 7]) from checkpoint, the shape in current model is torch.Size([32, 7]).
size mismatch for net_p_zy.net_linear_bn_relu.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for net_p_zy.net_linear_bn_relu.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for net_p_zy.net_linear_bn_relu.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for net_p_zy.net_linear_bn_relu.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for net_p_zy.fc_loc.0.weight: copying a param with shape torch.Size([64, 64]) from checkpoint, the shape in current model is torch.Size([32, 32]).
size mismatch for net_p_zy.fc_loc.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for net_p_zy.fc_scale.0.weight: copying a param with shape torch.Size([64, 64]) from checkpoint, the shape in current model is torch.Size([32, 32]).
size mismatch for net_p_zy.fc_scale.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for net_classif_y.op_linear.weight: copying a param with shape torch.Size([7, 64]) from checkpoint, the shape in current model is torch.Size([7, 32]).
size mismatch for net_p_zd.net_linear_bn_relu.0.weight: copying a param with shape torch.Size([64, 3]) from checkpoint, the shape in current model is torch.Size([32, 3]).
size mismatch for net_p_zd.net_linear_bn_relu.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for net_p_zd.net_linear_bn_relu.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for net_p_zd.net_linear_bn_relu.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for net_p_zd.net_linear_bn_relu.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for net_p_zd.fc_loc.0.weight: copying a param with shape torch.Size([64, 64]) from checkpoint, the shape in current model is torch.Size([32, 32]).
size mismatch for net_p_zd.fc_loc.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for net_p_zd.fc_scale.0.weight: copying a param with shape torch.Size([64, 64]) from checkpoint, the shape in current model is torch.Size([32, 32]).
size mismatch for net_p_zd.fc_scale.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
File "/home/aih/xudong.sun/domainlab_correct_pacs_split/domainlab/exp_protocol/benchmark.smk", line 121, in __rule_run_experiment
File "/home/aih/xudong.sun/domainlab_correct_pacs_split/domainlab/exp_protocol/run_experiment.py", line 109, in run_experiment
File "/home/aih/xudong.sun/domainlab_correct_pacs_split/domainlab/compos/exp/exp_main.py", line 70, in execute
File "/home/aih/xudong.sun/domainlab_correct_pacs_split/domainlab/algos/trainers/a_trainer.py", line 106, in post_tr
File "/home/aih/xudong.sun/domainlab_correct_pacs_split/domainlab/algos/observers/c_obvisitor_cleanup.py", line 12, in after_all
File "/home/aih/xudong.sun/domainlab_correct_pacs_split/domainlab/algos/observers/b_obvisitor.py", line 71, in after_all
File "/home/aih/xudong.sun/domainlab_correct_pacs_split/domainlab/compos/exp/exp_utils.py", line 99, in load
File "/home/aih/xudong.sun/anaconda3/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1671, in load_state_dict
File "/home/aih/xudong.sun/anaconda3/lib/python3.9/concurrent/futures/thread.py", line 52, in run
Shutting down, this might take some time.
Exiting because a job execution failed. Look above for error message

maybe this will fix it
https://github.com/marrlab/DomainLab/pull/468

merged into master
Merge pull request https://github.com/marrlab/DomainLab/pull/468 from marrlab/xd_benchmark_fix_model_name
…
3479847
@Car-la-F , could you test if it still occurs?

fixed

repo: marrlab/DomainLab


text:
No gpu found error

(rapids) root@ctpai-node1:~# python
Python 3.6.10 | packaged by conda-forge | (default, Apr 24 2020, 16:44:11)
[GCC 7.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.

import mars
import mars.tensor as mt
a=mt.random.rand(10,10,gpu=True)
a.sum().execute()
Traceback (most recent call last):
File "", line 1, in
File "/opt/conda/envs/rapids/lib/python3.6/site-packages/mars/core.py", line 580, in execute
self._data.execute(session, **kw)
File "/opt/conda/envs/rapids/lib/python3.6/site-packages/mars/core.py", line 370, in execute
session.run(self, **kw)
File "/opt/conda/envs/rapids/lib/python3.6/site-packages/mars/session.py", line 461, in run
result = self._sess.run(*tileables, **kw)
File "/opt/conda/envs/rapids/lib/python3.6/site-packages/mars/session.py", line 99, in run
raise RuntimeError('No GPU found for execution')
RuntimeError: No GPU found for execution

i can see there is a same issue before but i didn't understand how to resolve it, anyone have a more specific solution? thanks a loooot !!!

Check #1370 if it's duplicated issue.
For LInux, you can set LD_LIBRARY_PATH manually to see if you can resolve the issue.

This issue must have been resolved in v0.4.6 as well as v0.5.0rc1.
pip install pymars>=0.4.6 to verify.

repo: mars-project/mars


text:
Bootlint & small fixes

Fixed bootlint issues, Bootstrap updated to latest version, removed unused Font Awesome

dik

authors: freezy-sk scholtz

repo: marsher/volby-zo-zahranicia


text:
2213332_2213996_2213851

Brief Description of the Policy: The policy focuses on optimizing the cutting process of materials into specified product sizes. It includes two approaches:

Near Optimal Cutting Action: Aims to minimize leftover material by finding the best placement for products based on their sizes.
Two Dimensional Cutting Action: Prioritizes products by height and accommodates both orientations to maximize material usage.

Implementation of the Policy:

near_optimal_cutting_action(observation): Evaluates possible cutting positions in a stock roll for products, selecting the position that minimizes leftover space.

two_dimensional_cutting_action(observation): Iterates through products sorted by height, checking for valid cutting positions with and without rotation.

Results from 200 actions
Average trim lost:

Near Optimal Cutting Action: 0,2019%
Two Dimensional Cutting Action: 0,3103%

Please read the submission instructions carefully. Otherwise I could not merge your PR (0 grade for code).


text:
set noisev to Volatile to freeze netG when updating netD.

when training netD, we won't need the gradient and buffer of netG. set noisev to volatile would acclerate training step and reduce memory usage which is even better than detach.

thanks!

authors: chenyuntc soumith

repo: martinarjovsky/WassersteinGAN


text:
Add a documentation section about integrating with third-party software

It would be nice to include info about how to use distcc or ElectricCloud's eMake.
This would serve both as documentation of those tools and also provide links to them for people who use ninja and don't know about them.

Accelerating Ninja with Electric Cloud's ElectricAccelerator®
ElectricAccelerator (http://electric-cloud.com/products/electricaccelerator/) is an acceleration platform that optimally parallelizes software tasks across clusters of physical or cloud CPUs. This gives software-driven organizations the ability to speed up any number of concurrent activities so they can deliver better software faster.
ElectricAccelerator offers the following unique capabilities:

Safe and deterministic object file caching
Optimized dependency management
Reliable blazing incremental builds
Fault-tolerant workload distribution
Enterprise scalablity
Flexibility and manageability
Rich analytics and monitoring

ElectricAccelerator works on the basis of an agent model. Agents are daemons that run on agent boxes, usually 1.5 x #_of_cores. These agents are managed by a Cluster Manager, which represents the gateway to the machines running the agents, or what is referred to as a cluster. eMake and tools are installed on build machines owned by developers or build managers, and that is how builds are initiated. In a very simplistic explanation, eMake talks to the Cluster Manager and asks for agents for a task. Once it receives a list of the agents and their IP's, it then orchestrates the parallelization of the build.
However, in the case of builds that use Ninja, eMake is not an option because it does not know how to read Ninja build files. Ninja does support parallelization in a manner similar to GMake, with both automatic parallelization based on the number of cores, and a -j option that can be used to override the default value, forcing Ninja to produce N number of processes as necessary to parallelize a build.
That means that if you want to parallelize using just Ninja, and you want blazing fast speed, you have to be prepared to spend blazing big money for large servers with high numbers of cores.
ElectricAccelerator, however, can give you the ability to pile up large numbers of inexpensive boxes with i7 processors, for example, to build a cluster of unlimited size. What it also provides is an alternate way to access the parallelization infrastructure of the cluster without having to use the eMake tool.
The key to this feature is a tool called Electrify which is included at no extra charge. This tool can run an executable and monitor it as it spawns processes. These processes can then be intercepted and "sent" to the build cluster for parallel execution.
Now, this sounds simple on its face, but the requirements for successful parallelization are strict and can present challenges. The processes themselves must be just that, processes that are distinct and can run on their own without having to operate under some underlying runtime. This requirement excludes Java threads, because they cannot be separated from their underlying JRE without breaking the thread.
The processes also must not have dependencies between each other that would cause them to step over each other during execution, such as sharing files in read/write mode.
In addition. parallelization itself benefits from tasks that can be broken up into small pieces that can run simultaneously. Some large tasks, such as linking libraries or executables, creating .tar or .deb packages or other similar tasks cannot be broken up, so they do not contribute to the performance of the build as a whole if they are parallelized. All they do is add the overhead of sending the task to the agent, creating network traffic, etc. and as such are better off running on the machine from which the build was initiated. Those are referred to as local tasks, and in ElectricMake they are designated as such with a #pragma runlocal statement in a Makefile. More on how Electrify can keep those running on the build machine in a minute.
Because ElectricCloud has customers who like Ninja and don't want to switch to Makefiles, but who would also like to take advantage of our parallelization tool, I decided to see if I could parallelize Ninja builds with Electrify. The short answer is that it works, and it works very, very well.
The longer answer is that it takes some prep to be able to do this. This is a rough list of what needs to be done and it assumes you already have a cluster of agents and a Cluster Manager installed. If you are using the peer-to-peer ElectricAccelerator Huddle (http://electric-cloud.com/products/electricaccelerator/huddle)

Install ElectricAccelerator tools on the machine where you are currently running builds.
Install whatever dependencies your builds needs (such as shared libraries) in the machines where the agents reside. For the Google Chrome build, for example, this is done with the build/install-build-deps.sh script. If you don't do this, Electrify will still send those to the agent when it needs them, but it will be more work for you and more work for the network and agents.
You will need to identify what ElectricAccelerator refers to as the "eMake root" of the build. If you are using eMake already you know what this is -- one or more directories from which eMake will identify files that the agents need to complete an assigned task. In the case of the Google Chrome build, it's the ./chromium directory.
My recommendation is to build a script with the command line you will use to launch the parallelized build. The command line I use to launch the Google Chrome build is this:

electrify   --emake-annofile=build-@ECLOUD_BUILD_ID@.anno
--emake-annodetail=basic
--emake-annoupload=1
--emake-root=<home_dir_where_chrome_build_lives>
--emake-cm=<ip_of_your_huddle_main_server>
--electrify-allow-regexp=".*"
-- ninja-linux64 -j 300 -C out/Release chrome
In order, the arguments mean:

Write the annotation file to a file named build_(build-number).anno.
Include the only annotation detail possible with Electrify, basic annotation.
Upload the annotation to the cluster manager at the end of the build.
Set the emake-root to a specified folder from which Electrify will serve files to the agents.
Intercept all spawned processes and send them to the cluster.
-- indicates the end of the Electrify command line and the beginning of the command line for Ninja
Launch the 64-bit build of Ninja directly (because ninja is usually just a script
Launch up to 300 processes at at time.
Go to the out/Release directory where you will find the build.ninja file.
Build the Chrome target.

Adjust as necessary. The documentation for all our products is located at http://docs.electric-cloud.com. The documentation for Electrify is in the ElectricAccelerator Electric Make User Guide.
Couple more details. I said Electrify can be told to keep selected processes from being sent to the cluster. You do that with the --electrify-not-remote=<x;y;> or --electrify-deny-regexp=
 command line options, explained in the User Guide.
Also, if you are familiar with Electric Insight and its fantastic visualization capabilities into your builds (see below), you will be disappointed to know that Electrify does not produce the annotations necessary for Insight more advanced features, such as ElectricSimulator.
Note that all of this can be done with the peer-to-peer ElectricAccelerator Huddle product that is currently in open beta.
Finally, if you do have Electric Insight, this is what you want to see as a result of a Ninja build parallelized with Electrify. It's a thing of parallelized beauty, the brick wall. :smile: This is the full clean Google Chrome build, shrunk to a mere 9 minutes and a handful of seconds.

Any questions? http://ask.electric-cloud.com is your friend. Have fun with your new warp speed engine!

repo: martine/ninja


text:
Doubt regarding deeplab for new dataset

If we want to use deeplab for new dataset that is substantially different from the trained datasets,how do we go about the training this network?
My understanding: deeplab=DCNN(trainable) + CRF(not trainable-but can cross validate parameters)
So we train deeplab for the new dataset,ie training DCNN and then cross-validate the CRF parameters.Is this correct or is it possible to train deeplab end-to-end ,meaning training CRF also?

Have you ever solved your problem?
I try to train Deeplab on SUNRGBD dataset but it has 38 classes and looks quite different from VOC12, finally result I got looks terrible.
Have I need to do something with the labels, or change some parameters in the code?
If you have any hint it will be very pleasure.

repo: martinkersner/train-DeepLab


text:
Add monadic operations for std::optional, p0798

See p0798Rx
See also optional-fun-lite.

See also PR 60 and PR 61 of expected-lite for C++11 implementation ideas.

repo: martinmoene/optional-lite


text:
Do not check if "_actions" exists in object

This fixes deprecation warning: https://github.com/emberjs/ember.js/pull/12028 and leaves backward compatibility for some ancient versions of Ember
Fixes issue: https://github.com/martndemus/ember-invoke-action/issues/6

Ping @martndemus

Can we merge this please ?

@martndemus ??

authors: kliput msalahz

repo: martndemus/ember-invoke-action


text:
Now playing/queue swipe

The distance of a swipe up on the song title bar required to open up the queue should be smaller. Also, users should be able to swipe up on the cover with the same effect.

I see what you mean. I'm not actually sure how to change this since I'm just using an implementation that comes with Android, but I'll look into it. I believe this will involve overriding some of the behavior in the CoordinatorLayout behavior responsible for snapping that view.

authors: SzymonSporysz marverenic

repo: marverenic/Jockey


text:
Dashboard, Edit Echarts component, right Settings option expanded, UI style adjustment

仪表盘，编辑Echarts组件，右侧设置选项展开后，页面出现滚动条，穿透顶部栏，且左侧区域空白。需调整样式

@xie1wei2 顶部栏是否需要穿透

可以修改为中间部分固定左侧部分滚动

顶部固定，不需要穿透。这个感觉相当奇怪。


text:
🛑 POH events bot from render hosting is down

In 0ce0880, POH events bot from render hosting (https://poh-events-bot.onrender.com/ping) was down:

HTTP code: 0
Response time: 0 ms

Resolved: POH events bot from render hosting is back up in 9eaf6ad.

repo: masch/poh-events-uptime


text:
🛑 POH events bot from render hosting is down

In 4a9d191, POH events bot from render hosting (https://poh-events-bot.onrender.com/ping) was down:

HTTP code: 0
Response time: 0 ms

Resolved: POH events bot from render hosting is back up in ad9a5d0 after 11 minutes.


text:
🛑 POH events bot from render hosting is down

In 4c88031, POH events bot from render hosting (https://poh-events-bot.onrender.com/ping) was down:

HTTP code: 0
Response time: 0 ms

Resolved: POH events bot from render hosting is back up in a71eb57 after 9 minutes.


text:
Light/Dark Mode

Default: Uses user settings
Should have the option to change it in the app if they choose.

Added a toggle in settings page.

done

repo: masongaller/IndependentStudy


text:
Feature: added import transformer for massaExport functions

This transformer allows to use massa exported function in other files in the same contract.
For the moment only the build is tested, I still need to test on sample contracts that the feature works.
I would like other people to test it as well to avoid the 'it works on my amchine' syndrome.

Broken, on hold.

In testing, but can start reviewing and testing on your side to avoid "it works on my machine" syndrome.
To do so, checkout this branch, create a smart contract, and in asconfig.json add a transformer locally : e.g.:
        "release": {
            "outFile": "build/main.wasm",
            "sourceMap": true,
            "optimizeLevel": 3,
            "shrinkLevel": 0,
            "converge": false,
            "noAssert": false,
            "transform": [
                "../../../as/packages/as-transformer"
            ]

repo: massalabs/as


text:
Fix dependencies and imports

Signed-off-by: Jean-François Morcillo jfm@massa.net

@Ben-Rey can U merge please

repo: massalabs/massa-sc-toolkit


text:
🛑 RESTREAM-IR-12-ZirSakht-3 is down

In aa090db, RESTREAM-IR-12-ZirSakht-3 ($IR_12) was down:

HTTP code: 0
Response time: 0 ms

Resolved: RESTREAM-IR-12-ZirSakht-3 is back up in b119fe9.


text:
🛑 RESTREAM-IR-10-ParsOnline-4 is down

In 833ce9f, RESTREAM-IR-10-ParsOnline-4 ($IR_10) was down:

HTTP code: 0
Response time: 0 ms

Resolved: RESTREAM-IR-10-ParsOnline-4 is back up in 7948590.


text:
🛑 RESTREAM-IR-11-ZirSakht-2 is down

In 20667ec, RESTREAM-IR-11-ZirSakht-2 ($IR_11) was down:

HTTP code: 0
Response time: 0 ms

Resolved: RESTREAM-IR-11-ZirSakht-2 is back up in b8ad682.


text:
🛑 Iran 12 - ParsOnline 5 is down

In 45a8084, Iran 12 - ParsOnline 5 ($IR_12) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Iran 12 - ParsOnline 5 is back up in 141d3a2.


text:
🛑 Iran 10 - Zirsakht 3 is down

In 6480745, Iran 10 - Zirsakht 3 ($IR_10) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Iran 10 - Zirsakht 3 is back up in 6c6ccd4.


text:
🛑 Iran 10 - Zirsakht 3 is down

In 76fcc51, Iran 10 - Zirsakht 3 ($IR_10) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Iran 10 - Zirsakht 3 is back up in f43a4b0.


text:
ActionButton without Items.

Hi,
What do you think about to add onPress on ActionButton?

Hi,
You mean just a callback on pressEvent . ?

Yes,
I want to start work with the simple one button on the first screen of my app and 3 action buttons on the second screen.
First screen:
  <ActionButton buttonColor="rgba(231,76,60,1)"  onPress={ () => console.log("Yep!")}>
    <Icon ... />
  </ActionButton />

Second:
 <ActionButton buttonColor="rgba(231,76,60,1)">
   <ActionButton.Item buttonColor='#9b59b6' title="New Task" onPress={() => console.log("notes tapped!")}>
     <Icon name="android-create" style={styles.actionButtonIcon} />
   </ActionButton.Item>
...
...

With v1.1.0, it's possible!
The code would simply look like that:
<ActionButton
   buttonColor="rgba(231,76,60,1)"
   icon={<Icon ... />}
   onPress={ () => console.log("Yep!")}
/>

authors: Partysun gs-akhan mastermoo

repo: mastermoo/react-native-action-button


text:
How to increase body font size?

Hello,
Greetings!!
I have been trying to increase the body font size, and checking as a trail and error basis by changing where ever I see font-size in theme.css, but I don't see any change in the website. Could you please assist me in increasing the font size of my website a bit.
Thank you.

https://stackoverflow.com/questions/16460990/change-text-font-size-of-whole-page-content
https://css-tricks.com/confused-rem-em/
maybe these two posts will help you. i have not needed that before.

So, is there no option in the theme itself? I doubt this is a solution.

Nope there's no option built into the theme config. The theme allows you to provide your own css file to override whichever style you like.
Follow the docs at https://learn.netlify.com/en/basics/style-customization/#yours-variant to create a "yours" style.

Okay, I got it. Thanks for the help! I appreciate it.

authors: Nightshadelink kpatnayakuni matalo33

repo: matcornic/hugo-theme-learn