Exception InvalidFieldNameException thrown upon first run

Running on docker/windows
Installed fine, no errors following instructions.
Upon first access it throws the following exception:
[PDOException](http://<IP_ADDRESS>:8001/login#trace-box-3)  [Exception](http://<IP_ADDRESS>:8001/login#trace-box-2)  [InvalidFieldNameException](http://<IP_ADDRESS>:8001/login#trace-box-1)
An exception occurred while executing 'SELECT t0.id AS id_1, t0.password AS password_2, t0.avatar AS avatar_3, t0.nickname AS nickname_4, t0.lock_password AS lock_password_5, t0.roles AS roles_6, t0.email AS email_7, t0.email_canonical AS email_canonical_8, t0.username AS username_9, t0.username_canonical AS username_canonical_10, t0.enabled AS enabled_11, t0.salt AS salt_12, t0.last_login AS last_login_13 FROM app_user t0':
SQLSTATE[42S22]: Column not found: 1054 Unknown column 't0.lock_password' in 'field list'
I assume something is wrong with user register?
Help is appreciated.
Thanks in advance.

another exception but same issue for me. Installation run smooth, no errors. First attempt to navigate to http://mydomain:8001 results in this:
An exception occurred while executing 'SELECT t0.id AS id_1, t0.name AS name_2, t0.value AS value_3 FROM setting t0 WHERE t0.name = ?' with params ["modules"]:
SQLSTATE[42S02]: Base table or view not found: 1146 Table 'pms.setting' doesn't exist
someone?

Can't really help here because everything works for me, just spawned the fresh instance from container, went in, called first run setup and worked out. sh docker-first-run.sh


Fix: Literal parentheses not outputting with regexify

Should solve #1523
This improves the grouped regex matching for regexify.
There is now the possibility for the input regex to contain escaped
parentheses which will stay in the final result.

Thanks for the patch.
I'm honestly not very enthusiastic about complexifying the regex as you did. The code will be harder to read and maintain, for a short benefit - the regexify formatter will always be very limited. Also, I'm concerned about the performance impact, because regexify is already one of the slowest Faker formatters.
So I'd rather keep the regexify formatter with its limitations (already documented), and encourage you to publish your own regex formatter with a much larger coverage of the regular expression grammar - which, I think, is a project by itself.

@localheinz there are also numerous other open PR concerning regexify.
#1453, #1624, and #1515
The all focus around the same changes I did.
How to we solve this?

Thanks for clarification. Should we then close the linked PRs as well including their issues?
I would create a new issue, with the information provided, to link to those issues for keeping a small feature list. So we can then easily plan the new regex feature.
What do you think?

@icanhazstring you're right, I closed the 3 PRs you linked.
As for creating an issue with the remaining issues with regexify, let me reiterate: Faker won't implement a more complex regexify formatter, it's up to the community to publish it as a third party package (not in the Faker code).

it's up to the community to publish it as a third party package
Alright, got it. Then I put it on my TODO ;)


fix a bug in the ReleaseDevirtualizer pass

The release-devirtualizer must not run on the same alloc_ref twice.
This is a very rare case, but if it happens it's a very bad thing, because it results in a double-free crash.
The fix is to detect that a dealloc_ref instruction (although it isn't "releasing"), does a memory deallocation.
Found by doing some unrelated experiments.

@swift-ci smoke test

@swift-ci smoke test

@swift-ci smoke test macos


max limit on number of stores/instances?

Is there a known, max limit on number of stores created on any of the browser stores (websql, indexeddb etc)?
I may need to create hundreds or thousands of them.
Another question:
Does .createInstance() properly separates/partitions data into separate databases and stores for all of the following data stores?
localforage.INDEXEDDB, localforage.WEBSQL, localforage.LOCALSTORAGE

For localforage, it simply creates keys that namesplace the days, but they
aren't really different stores technically speaking. They aren't visible to
each other in localForage though, if that's what you mean.
Regarding max number of stores... I don't know, but I would love to!
Browser vendors might specify such things in their docs but I don't think
anyone has run into a problem before.
If you do find any, please feel free to reopen this issue; we will either
find a workaround or document the limits, and see about increasing them as
well. Thanks!

tofumatt


Is it better to use yaml than json in config files?

I think yaml format is more readable than json format, and it's easy to handle with yaml module. So is it more proper to replace the json files (as well as related code) in the template with yaml?

just change the configuration system as you want no problem but make sure that everything is like a class variable


Updating sphinx version

Description
Update the version of sphinx to 5.3.0 to allow doc to create correctly.
Fixes issue #465.
Please remove options that are irrelevant.

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

Checklist

[x] I have read the contributing guidelines
[ ] I have updated the HISTORY.rst and AUTHORS.rst files
[x] Linting passes successfully : make lint
[x] Typing passes successfully : make type-check
[x] Unit tests pass successfully : make tests
[x] Coverage is 100% : make coverage
[ ] Documentation builds successfully : make doc

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 100.00%. Comparing base (614293e) to head (5bd2456).
Report is 461 commits behind head on master.

Additional details and impacted files
@@            Coverage Diff             @@
##            master      #466    +/-   ##
==========================================
  Coverage   100.00%   100.00%
==========================================
  Files           39        41     +2
  Lines         4616      4954   +338
  Branches       487       812   +325
==========================================
+ Hits          4616      4954   +338

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.


Fixed bug that show undefined where country flag is not unavailable.

Fixed #1603
Just Add Small if Else Condition to check whether the flag is available or not. if available then display it otherwise do nothing only show country name.

That's pretty the same fix than the one proposed on https://github.com/llaske/sugarizer/pull/1604


Update intro.md

some proofreading

Thank you! I did not think that it had so many typos and errors


Remove validation  dynamically

I have an issue with a form witch shows fields from 2 models,  a checkbox enables the fields of the second model; so I want, when the checkbox is checked it adds a validation rule for the field of the second model, and when it is unchecked the rules have to be removed. To add the rules is working fine with $('#myform').yiiActiveForm('add', attributes), but to remove the validation it is not working or maybe I am doing wrong, I trying with $('#myform').yiiActiveForm('remove', 'field-id'); but no success.
Can you help me with this please?
Thank you.

Are you using the same ID as was used when you were adding it?

After checking my code and looking the ID of the input $('#tour-form').yiiActiveForm('add', {  'id': 'slideritem-sid', 'name': 'sid', 'container': '.field-slider_id', 'input':  '#slider_id',...}) and the to remove    $('#tour-form').yiiActiveForm('remove', 'slideritem-sid'); I tried changing the ID for id for both in the add and remove to the id set in the "input" attribute and now it works.
$('#tour-form').yiiActiveForm('add', { ..., 'id': 'slider_id', ... }), $('#tour-form').yiiActiveForm('remove','slider_id');
Thank you.


PCR-323 Issue in success page notice creat

PCR-323 Issue in success page notice create

Fixing acknowledgemnt

Updated PR


Regression: yt-dlp clobbers mp4 output file when I select multiple formats.

Checklist

[X] I'm reporting a bug unrelated to a specific site
[X] I've verified that I'm running yt-dlp version 2022.07.18 (update instructions) or later (specify commit)
[X] I've checked that all provided URLs are playable in a browser with the same IP and same login details
[X] I've checked that all URLs and arguments with special characters are properly quoted or escaped
[X] I've searched the bugtracker for similar issues including closed ones. DO NOT post duplicates
[X] I've read the guidelines for opening an issue

Provide a description that is worded well enough to be understood
Observed behavior:
As you might notice, yt-dlp says "Invoking http downloader on..." twice and downloads a video twice; ending with the smaller of the two on disk.
Expected behavior:
yt-dlp refuses to overwrite a video file with another video file.
This is a regression compared to youtube-dl, which, when passed multiple formats to be requested (because not every format is available), it simply will not download the next format as the file size is smaller than the initial mp4 file that was downloaded.
I tried using the --no-overwrites , which works, but breaks the possibility of continuing a partially downloaded file.
Thanks!
Provide verbose output that clearly demonstrates the problem

[X] Run your yt-dlp command with -vU flag added (yt-dlp -vU <your command line>)
[X] Copy the WHOLE output (starting with [debug] Command-line config) and insert it below

Complete Verbose Output
% yt-dlp --no-abort-on-error --throttled-rate 100K --socket-timeout 60 --extractor-retries 3 --no-hls-use-mpegts --restrict-filenames --no-part --write-description --cookies ../cookies2.txt --write-thumbnail -f 22,20,18 --write-auto-subs --sub-langs "en.*" --embed-chapters -o '%(title)s-%(id)s.%(ext)s' -vU https://youtu.be/qngCzfqi_LM
[debug] Command-line config: ['--no-abort-on-error', '--throttled-rate', '100K', '--socket-timeout', '60', '--extractor-retries', '3', '--no-hls-use-mpegts', '--restrict-filenames', '--no-part', '--write-description', '--cookies', '../cookies2.txt', '--write-thumbnail', '-f', '22,20,18', '--write-auto-subs', '--sub-langs', 'en.*', '--embed-chapters', '-o', '%(title)s-%(id)s.%(ext)s', '-vU', 'https://youtu.be/qngCzfqi_LM']
[debug] Encodings: locale UTF-8, fs utf-8, pref UTF-8, out utf-8, error utf-8, screen utf-8
[debug] yt-dlp version 2022.07.18 [135f05ef6]
[debug] Lazy loading extractors is disabled
[debug] Python 3.9.2 (CPython 64bit) - Linux-5.18.0-0.bpo.1-amd64-x86_64-with-glibc2.31 (glibc 2.31)
[debug] Checking exe version: ffmpeg -bsfs
[debug] Checking exe version: ffprobe -bsfs
[debug] exe versions: ffmpeg 4.3.4-0, ffprobe 4.3.4-0, rtmpdump 2.4
[debug] Optional libraries: Cryptodome-3.9.7, brotli-1.0.9, certifi-2020.06.20, mutagen-1.45.1, secretstorage-3.3.1, sqlite3-2.6.0, websockets-8.1, xattr-0.9.7
[debug] Proxy map: {}
[debug] Fetching release info: https://api.github.com/repos/yt-dlp/yt-dlp/releases/latest
Latest version: 2022.07.18, Current version: 2022.07.18
yt-dlp is up to date (2022.07.18)
[debug] [youtube] Extracting URL: https://youtu.be/qngCzfqi_LM
[youtube] qngCzfqi_LM: Downloading webpage
[youtube] qngCzfqi_LM: Downloading android player API JSON
[debug] Sort order given by extractor: quality, res, fps, hdr:12, source, codec:vp9.2, lang, proto
[debug] Formats sorted by: hasvid, ie_pref, quality, res, fps, hdr:12(7), source, vcodec:vp9.2(10), acodec, lang, proto, filesize, fs_approx, tbr, vbr, abr, asr, vext, aext, hasaud, id
[debug] Downloading subtitles: en
[info] qngCzfqi_LM: Downloading 2 format(s): 22, 18
[info] Writing video description to: _-qngCzfqi_LM.description
[info] Writing video subtitles to: _-qngCzfqi_LM.en.vtt
[debug] Invoking http downloader on "https://www.youtube.com/api/timedtext?v=qngCzfqi_LM&caps=asr&xoaf=5&xosf=1&hl=en&ip=<IP_ADDRESS>&ipbits=0&expire=1659336278&sparams=ip%2Cipbits%2Cexpire%2Cv%2Ccaps%2Cxoaf&signature=D462D0B082395AA6C25A387E252807F5F3E9668F.5C53B1FFD0A2D4F4DD9B389083E6D7EBBA9C2D62&key=yt8&kind=asr&lang=ru&tlang=en&fmt=vtt"
[download] Destination: _-qngCzfqi_LM.en.vtt
[download] 100% of 12.10KiB in 00:00
[info] Downloading video thumbnail 41 ...
[info] Writing video thumbnail 41 to: _-qngCzfqi_LM.webp
[debug] Invoking http downloader on "https://rr5---sn-hp57ynly.googlevideo.com/videoplayback?expire=1659332679&ei=5xPnYvKvDYmB8gSjkrxg&ip=<IP_ADDRESS>&id=o-AGJsQPXBG1wFxNP1YtYscBFBipSibdzgUfz0fYC1MSWp&itag=22&source=youtube&requiressl=yes&mh=Mh&mm=31%2C29&mn=sn-hp57ynly%2Csn-hp57kn6r&ms=au%2Crdu&mv=m&mvi=5&pl=17&initcwndbps=846250&vprv=1&mime=video%2Fmp4&cnr=14&ratebypass=yes&dur=123.274&lmt=1470945835201045&mt=1659310853&fvip=2&fexp=24001373%2C24007246&c=ANDROID&sparams=expire%2Cei%2Cip%2Cid%2Citag%2Csource%2Crequiressl%2Cvprv%2Cmime%2Ccnr%2Cratebypass%2Cdur%2Clmt&sig=AOq0QJ8wRQIhAMEvaCeKwdx9BkowYjTv583wsgn-FK-TfzPovetjdGJSAiBWfdW0Vr9Kf25r1aIIyXKl9exg0LmRaLgyLjIq4K4yew%3D%3D&lsparams=mh%2Cmm%2Cmn%2Cms%2Cmv%2Cmvi%2Cpl%2Cinitcwndbps&lsig=AG3C_xAwRQIhAILZZH-K2Kg7Brio5Zu2J5zl_bbRxZsluhYzhZkdJRIkAiAKwnFwRS6b6-pmWqFA1FABWb8_tt3zP1rtXRb_H_JP-w%3D%3D"
[download] Destination: _-qngCzfqi_LM.mp4
[download] 100% of 16.21MiB in 00:39
[Metadata] There isn't any metadata to add
[info] Writing video description to: _-qngCzfqi_LM.description
Deleting existing file _-qngCzfqi_LM.en.vtt
[info] Writing video subtitles to: _-qngCzfqi_LM.en.vtt
[debug] Invoking http downloader on "https://www.youtube.com/api/timedtext?v=qngCzfqi_LM&caps=asr&xoaf=5&xosf=1&hl=en&ip=<IP_ADDRESS>&ipbits=0&expire=1659336278&sparams=ip%2Cipbits%2Cexpire%2Cv%2Ccaps%2Cxoaf&signature=D462D0B082395AA6C25A387E252807F5F3E9668F.5C53B1FFD0A2D4F4DD9B389083E6D7EBBA9C2D62&key=yt8&kind=asr&lang=ru&tlang=en&fmt=vtt"
[download] Destination: _-qngCzfqi_LM.en.vtt
[download] 100% of 12.10KiB in 00:00
Deleting existing file _-qngCzfqi_LM.webp
[info] Downloading video thumbnail 41 ...
[info] Writing video thumbnail 41 to: _-qngCzfqi_LM.webp
[debug] Invoking http downloader on "https://rr5---sn-hp57ynly.googlevideo.com/videoplayback?expire=1659332679&ei=5xPnYvKvDYmB8gSjkrxg&ip=<IP_ADDRESS>&id=o-AGJsQPXBG1wFxNP1YtYscBFBipSibdzgUfz0fYC1MSWp&itag=18&source=youtube&requiressl=yes&mh=Mh&mm=31%2C29&mn=sn-hp57ynly%2Csn-hp57kn6r&ms=au%2Crdu&mv=m&mvi=5&pl=17&initcwndbps=846250&vprv=1&mime=video%2Fmp4&gir=yes&clen=7769049&ratebypass=yes&dur=123.274&lmt=1419519955747726&mt=1659310853&fvip=2&fexp=24001373%2C24007246&c=ANDROID&sparams=expire%2Cei%2Cip%2Cid%2Citag%2Csource%2Crequiressl%2Cvprv%2Cmime%2Cgir%2Cclen%2Cratebypass%2Cdur%2Clmt&sig=AOq0QJ8wRQIhAPguCeHC55_bEY-X7Jm6TFhgmMtTMiyc66_a87vbmUURAiBQolX63YSRLwxXOHKUkjLIGt28xDs0ZCCPUjgcNjHAYA%3D%3D&lsparams=mh%2Cmm%2Cmn%2Cms%2Cmv%2Cmvi%2Cpl%2Cinitcwndbps&lsig=AG3C_xAwRQIhAILZZH-K2Kg7Brio5Zu2J5zl_bbRxZsluhYzhZkdJRIkAiAKwnFwRS6b6-pmWqFA1FABWb8_tt3zP1rtXRb_H_JP-w%3D%3D"
[download] Resuming download at byte 16999594
[download] Unable to resume
[download] Destination: _-qngCzfqi_LM.mp4
[download] 100% of 7.41MiB in 00:14
[Metadata] There isn't any metadata to add

Please also show the relevant youtube-dl log

I'm curious though, why are you running this command? What are yo trying to accomplish over just downloading a single format?

I'm curious though, why are you running this command? What are yo trying to accomplish over just downloading a single format?
I wrote above, "(because not every format is available)". As in, some videos have format 22, some have only 20 or 18. Hence the need. This also applies to other sites. I just used youtube because it was easiest to get a small video to work with.

I wrote above, "(because not every format is available)". As in, some videos have format 22, some have only 20 or 18. Hence the need. This also applies to other sites. I just used youtube because it was easiest to get a small video to work with.

That is what / is for. Eg: -f 22/20/18

% youtube-dl -f 22,20,18 --socket-timeout 60 -i --no-call-home --restrict-filenames --yes-playlist --hls-prefer-native --write-auto-sub --write-description --cookies ../cookies2.txt --verbose https://www.youtube.com/watch?v=qngCzfqi_LM
[debug] System config: []
[debug] User config: []
[debug] Custom config: []
[debug] Command-line args: [u'-f', u'22,20,18', u'--socket-timeout', u'60', u'-i', u'--no-call-home', u'--restrict-filenames', u'--yes-playlist', u'--hls-prefer-native', u'--write-auto-sub', u'--write-description', u'--cookies', u'../cookies2.txt', u'--verbose', u'https://www.youtube.com/watch?v=qngCzfqi_LM']
[debug] Encodings: locale ANSI_X3.4-1968, fs ANSI_X3.4-1968, out ANSI_X3.4-1968, pref ANSI_X3.4-1968
[debug] youtube-dl version 2021.12.17
[debug] Python version 2.7.18 (CPython) - Linux-5.18.0-0.bpo.1-amd64-x86_64-with-debian-11.1
[debug] exe versions: ffmpeg 4.3.4-0, ffprobe 4.3.4-0, rtmpdump 2.4
[debug] Proxy map: {}
[youtube] qngCzfqi_LM: Downloading webpage
[info] qngCzfqi_LM: downloading video in 2 formats
[info] Writing video description to: _-qngCzfqi_LM.description
[info] Writing video subtitles to: _-qngCzfqi_LM.en.vtt
[debug] Invoking downloader on u'https://rr5---sn-hp57ynly.googlevideo.com/videoplayback?expire=1659333402&ei=uRbnYrSSM4mvhgbXwJfwCA&ip=<IP_ADDRESS>&id=o-AK6hXbzSGS786XsaLCse21cKjifaq1vYoRAjnv6lSHXz&itag=22&source=youtube&requiressl=yes&mh=Mh&mm=31%2C26&mn=sn-hp57ynly%2Csn-q4flrne6&ms=au%2Conr&mv=m&mvi=5&pl=17&initcwndbps=855000&spc=lT-KhuUXoJQ9L-WVYAEjJ8adEPWyHUE&vprv=1&mime=video%2Fmp4&ns=R_JBEhAI5571EstMQP3ziTQH&cnr=14&ratebypass=yes&dur=123.274&lmt=1470945835201045&mt=1659311335&fvip=4&fexp=24001373%2C24007246&beids=24239134&c=WEB&rbqsm=fr&n=wq2g4sEFWiANm8Le&sparams=expire%2Cei%2Cip%2Cid%2Citag%2Csource%2Crequiressl%2Cspc%2Cvprv%2Cmime%2Cns%2Ccnr%2Cratebypass%2Cdur%2Clmt&sig=AOq0QJ8wRAIgWrpUuht6x3QPCHTdXVDsrMmJ8v5AvNvKePemGSS48yACIB4VOOukJPQDqcSXieL3PDkYMnQYj1B0eMPT2lYGiVSQ&lsparams=mh%2Cmm%2Cmn%2Cms%2Cmv%2Cmvi%2Cpl%2Cinitcwndbps&lsig=AG3C_xAwRAIgWpiM7ALTj3XBtzOpAx0GC95YNCiNY4c07PhwD3HyrNACICrQYt3IvLMg9uc4kx04qf808vxBULKHEOuTZ46otVgN'
[download] Destination: _-qngCzfqi_LM.mp4
[download] 100% of 16.21MiB in 04:23
[info] Writing video description to: _-qngCzfqi_LM.description
[info] Writing video subtitles to: _-qngCzfqi_LM.en.vtt
[debug] Invoking downloader on u'https://rr5---sn-hp57ynly.googlevideo.com/videoplayback?expire=1659333402&ei=uRbnYrSSM4mvhgbXwJfwCA&ip=<IP_ADDRESS>&id=o-AK6hXbzSGS786XsaLCse21cKjifaq1vYoRAjnv6lSHXz&itag=18&source=youtube&requiressl=yes&mh=Mh&mm=31%2C26&mn=sn-hp57ynly%2Csn-q4flrne6&ms=au%2Conr&mv=m&mvi=5&pl=17&initcwndbps=855000&spc=lT-KhuUXoJQ9L-WVYAEjJ8adEPWyHUE&vprv=1&mime=video%2Fmp4&ns=R_JBEhAI5571EstMQP3ziTQH&gir=yes&clen=7769049&ratebypass=yes&dur=123.274&lmt=1419519955747726&mt=1659311335&fvip=4&fexp=24001373%2C24007246&beids=24239134&c=WEB&rbqsm=fr&n=wq2g4sEFWiANm8Le&sparams=expire%2Cei%2Cip%2Cid%2Citag%2Csource%2Crequiressl%2Cspc%2Cvprv%2Cmime%2Cns%2Cgir%2Cclen%2Cratebypass%2Cdur%2Clmt&sig=AOq0QJ8wRQIhALhaVJLIYaJf4eaMQWEl1AeA7QI7n6qp2gU_-egeEbkwAiBkV2JRLzM9Y0dwoulVhIj8MBREwRo2PvrKqwBq0z9F2A%3D%3D&lsparams=mh%2Cmm%2Cmn%2Cms%2Cmv%2Cmvi%2Cpl%2Cinitcwndbps&lsig=AG3C_xAwRAIgWpiM7ALTj3XBtzOpAx0GC95YNCiNY4c07PhwD3HyrNACICrQYt3IvLMg9uc4kx04qf808vxBULKHEOuTZ46otVgN'
[download] _-qngCzfqi_LM.mp4 has already been downloaded
[download] 100% of 16.21MiB

That is what / is for. Eg: -f 22/20/18

Thanks! I checked that and it works. I had no idea that you could use backwards slashes and it would work like that for me.

You are passing --no-part for yt-dlp, but not for youtube-dl. With it, the behavior is same for upstream
❯ youtube-dl -f 22,20,18 --no-part -v https://www.youtube.com/watch?v=qngCzfqi_LM
[debug] System config: []
[debug] User config: []
[debug] Custom config: []
[debug] Command-line args: ['-f', '22,20,18', '--no-part', '-v', 'https://www.youtube.com/watch?v=qngCzfqi_LM']
[debug] Encodings: locale cp65001, fs mbcs, out cp65001, pref cp65001
[debug] youtube-dl version 2021.12.17
[debug] Python version 3.4.4 (CPython) - Windows-10-10.0.22000
[debug] exe versions: ffmpeg N-106550-g072101bd52-20220410, ffprobe N-106624-g391ce570c8-20220415, phantomjs 2.1.1
[debug] Proxy map: {}
[youtube] qngCzfqi_LM: Downloading webpage
[info] qngCzfqi_LM: downloading video in 2 formats
[debug] Invoking downloader on 'https://rr3---sn-gwpa-jv36.googlevideo.com/videoplayback?expire=1659333802&ei=ShjnYtv8EeLQz7sPm4GYoAE&ip=<IP_ADDRESS>&id=o-AMgxMyDaAUAu2YlRLoFZEcXgmg-rLa_XWt5Nz6JhXC3p&itag=22&source=youtube&requiressl=yes&mh=Mh&mm=31%2C29&mn=sn-gwpa-jv36%2Csn-gwpa-h55e7&ms=au%2Crdu&mv=m&mvi=3&pl=20&initcwndbps=396250&spc=lT-KhiARV87x2h-wFvcD9mO1z0aB3QE&vprv=1&mime=video%2Fmp4&ns=3MxtWYM9S0fQ1-0IaERrFqMH&cnr=14&ratebypass=yes&dur=123.274&lmt=1470945835201045&mt=1659311815&fvip=7&fexp=24001373%2C24007246&c=WEB&rbqsm=fr&n=ZPr5YyBs1shGMiD2&sparams=expire%2Cei%2Cip%2Cid%2Citag%2Csource%2Crequiressl%2Cspc%2Cvprv%2Cmime%2Cns%2Ccnr%2Cratebypass%2Cdur%2Clmt&sig=AOq0QJ8wRQIhAOd8WuB6OtmUmbE7SYcz7Dvx2x4RrXKnyce2EM155EUPAiAYtZPLYDyCzS6cRRi72LRbU-f08HUzvIuFQ85iqTboUg%3D%3D&lsparams=mh%2Cmm%2Cmn%2Cms%2Cmv%2Cmvi%2Cpl%2Cinitcwndbps&lsig=AG3C_xAwRgIhAOrFvcnBTrbN6yskAB6VAtE5ICS7kmdzjt-aacuVPASbAiEA3GZzMNU61VMP92hAYvGZUFGCF6zTKfni7yzfJaFzOe8%3D'
[download] Destination: Шуля и Дядя Эник - от этикетки к этикету (фрагмент)-qngCzfqi_LM.mp4
[download] 100% of 16.21MiB in 04:52
[debug] Invoking downloader on 'https://rr3---sn-gwpa-jv36.googlevideo.com/videoplayback?expire=1659333802&ei=ShjnYtv8EeLQz7sPm4GYoAE&ip=<IP_ADDRESS>&id=o-AMgxMyDaAUAu2YlRLoFZEcXgmg-rLa_XWt5Nz6JhXC3p&itag=18&source=youtube&requiressl=yes&mh=Mh&mm=31%2C29&mn=sn-gwpa-jv36%2Csn-gwpa-h55e7&ms=au%2Crdu&mv=m&mvi=3&pl=20&initcwndbps=396250&spc=lT-KhiARV87x2h-wFvcD9mO1z0aB3QE&vprv=1&mime=video%2Fmp4&ns=3MxtWYM9S0fQ1-0IaERrFqMH&gir=yes&clen=7769049&ratebypass=yes&dur=123.274&lmt=1419519955747726&mt=1659311815&fvip=7&fexp=24001373%2C24007246&c=WEB&rbqsm=fr&n=ZPr5YyBs1shGMiD2&sparams=expire%2Cei%2Cip%2Cid%2Citag%2Csource%2Crequiressl%2Cspc%2Cvprv%2Cmime%2Cns%2Cgir%2Cclen%2Cratebypass%2Cdur%2Clmt&sig=AOq0QJ8wRgIhAP75EpCZUxyGtSgn_IAiY21tlAeY6rnAL5qGDS69d45jAiEAuDFr4XxpUFNRtaf6TXkvLmL0gdgb06WQWu7rJx0W38I%3D&lsparams=mh%2Cmm%2Cmn%2Cms%2Cmv%2Cmvi%2Cpl%2Cinitcwndbps&lsig=AG3C_xAwRgIhAOrFvcnBTrbN6yskAB6VAtE5ICS7kmdzjt-aacuVPASbAiEA3GZzMNU61VMP92hAYvGZUFGCF6zTKfni7yzfJaFzOe8%3D'
[download] Resuming download at byte 16999594
[download] Unable to resume
[download] Destination: Шуля и Дядя Эник - от этикетки к этикету (фрагмент)-qngCzfqi_LM.mp4
[download] 100% of 7.41MiB in 02:14


Fix incorrect continue statement

The continue statements in the case / esac block are vestigial from
refactoring a code block inside a loop [1]. This patch replaces continue
with return.
[1] 8064efb0e51415ef47ee4d670d67b21825e3c62d

+1

+1

still +1

THANKS
:+1:  but it should be +10000


update whatsnew.rst, add contributors, v0.7.0 release date, address #809

[x] Closes #809
[x] I am familiar with the contributing guidelines
[x] Tests added

N/A

[x] Updates entries to docs/sphinx/source/api.rst for API changes.

N/A

[x] Adds description and name entries in the appropriate "what's new" file in docs/sphinx/source/whatsnew for all changes. Includes link to the GitHub Issue with :issue:`num` or this Pull Request with :pull:`num`. Includes contributor name and/or GitHub username (link with :ghuser:`user`).
[x] New code is fully documented. Includes numpydoc compliant docstrings, examples, and comments where necessary.

N/A

[x] Pull request is nearly complete and ready for detailed review.
[x] Maintainer: Appropriate GitHub Labels and Milestone are assigned to the Pull Request and linked Issue.

This updates whatsnew.rst with the proposed release date (2019-12-18), contributors to PRs and issues and includes the v0.7.0 tag.
The method I used to catch all the contributors from PRs is to use the Contributors section and select the dates on the graph since the previous release until now. The url api "from" and "to" fields can be used to make this exact. E.g. https://github.com/pvlib/pvlib-python/graphs/contributors?from=2019-05-17&to=2019-12-17&type=c . To get all the contributors to issues I performed a search in issues with the parameters "sort:created-asc closed:2019-05-16..2019-12-31 " and scanned for people who weren't on the list. I have found a utility that we can implement that could make this process more thorough and I will create an issue for us to discuss its use.

thanks, release time!


webhooks/freshdesk/doc.md: Remove unescape_rendered_html kludge

This reverts commit f476ec7fac7a68920fdf5e5f98f8034ff5a57c4c (#10312) and replaces it with a proper fix using Jinja2 raw blocks.
Cc: @eeshangarg
Testing Plan: Verified http://localhost:9991/integrations/doc/freshdesk with run-dev.

Merged, thanks @andersk!


The parameter start for sev::launch::sev::Launcher::start should be passed by reference

Since Start is a data structure that reaches up to 2KB in size (typically), I think it should be passed by reference.
i.e.
    pub fn start(mut self, start: Start) -> Result<Launcher<Started, U, V>> {

to
    pub fn start(mut self, start: &Start) -> Result<Launcher<Started, U, V>> {

@FuuuOverclocking Thanks for pointing this out. I think our initial motivation for passing by value is that we wanted the function to consume the value instead of allowing it to be re-used. I suppose there is no issue in letting it be re-used. However, I've never run into any issue with this API as is.
@larrydewey what do you think here? Obviously we'd like to avoid a situation in which a stack overflow could result.

Closing this for now, but will re-consider on 2.0.0 release, as this change breaks API.


Define a new Amount Constraint for Note values w/ [0..2^64) as valid_range()

Motivation

Orchard defines the valid range of note values to be not [0..MAX_MONEY] as defined in several places in the spec for Sapling and Sprout, but [0..2^64), which is the range of values for Orchard, Sapling, and Sprout that are actually checked in the circuit. The value balance, at the transaction level, is still checked to be {−MAX_MONEY .. MAX_MONEY} for Orchard/Sapling. There are already Orchard test vectors that define note values (not value balances) MAX_MONEY < v < 2^64, which is out of range of the Amount Constraints we have defined so far.
Specifications

https://zips.z.cash/protocol/protocol.pdf#notes

Designs

Change the underlying type for Amount

The current underlying type is i64.
We could change the type based on the constraint, or use i128, or use u64 and a sign bit.

Implement a Constraint that has a value_range of [0..u64::MAX):

pub struct NonNegativeMaxU64;

impl Constraint for NonNegativeMaxU64 {
    fn valid_range() -> RangeInclusive<u64> {
        0..=u64::MAX
    }
}

Change Amount additions and subtractions to use checked arithmetic, to prevent silent overflows. (Currently, only multiplications, divisions, and sums have to use checked arithmetic, because the existing constraints restrict values to less than 2^51.)

Related Work

https://github.com/zcash/zips/issues/533

We might want to re-think this design, because some coins like ethereum use 128-bit amounts.
We could end up with a new Amount128 type, which always comes with an asset ID, and then Amount would just be used for ZEC/TAZ.


[BUGFIX] Account contacts position

tasks:

[ ] test coverage
[ ] submit changes to the documentation

informations:

q
a

Fixed tickets
none

Related PRs
none

BC breaks
none

Documentation PR
none

how can i test this feature?

go to contacts tab in accounts
click on add an existing contact to the organization
select a position
when clicking 'ok' a new record with the correct position should be added to the datagrid.


Add Openshift setup and test

This commit adds scripts to setup the environment for running OpenShift on top of Clear Containers, initialize the nodes and run a simple Connectivity test.
Fixes #465.
Signed-off-by: Salvador Fuentes<EMAIL_ADDRESS>

@egernst thanks for your comments.
I added a verification on the scripts to state that currently these scripts only work on Fedora.
Also added a README.md with that information and how to execute the scripts.

@iphutch can you take a look at the README created here? thanks

@iphutch thanks for your comments, they are now fixed.


Image dosen't run flask

I had build my image and i'm trying run my flask app with:
$ docker run  -p 8080:8080 -e DEBUG="True" -e APP_MODULE="server:application" myimage
Nothing happened. Only the prestart.sh has be processed.
Any idea?

What is the structure of your project?
As given, if you are copying your path into the /app did, it will be expecting there to be a file named server.py in the project root which contains a WSGI variable called application.
Here's an example that hopefully will clear things up for you.
Suppose you have a server.py file as such:
from flask import Flask

app = Flask(__name__)

@app.route("/")
def hello_world():
    return "
Hello, World!
"

If you have server.py in the root, it would look like this:
/
- server.py

Then
APP_MODULE="server:app"
If you have server.py within a package you would need to specify the package as well.
/
+ my_app
- - __init__.py
- - server.py

Then:
APP_MODULE="my_app.server:app"
You can also specify this in the Docker file itself so you don't want to pass this in on the command line.
For example:
FROM tecktron/python-bjoern:latest

ENV APP_MODULE=my_app.server:app

COPY . /app
WORKDIR /app/

RUN python -m pip install flask

yes, my server file is in root. Im run like you have showed, but it still not working.
it just works if a put   api.run(HOST, PORT, threaded=True) at the end of my server.py file.. but i think this is wrong way to run flask in production envirioments.
Thank you so much for your help!!!

I've tested this out and I have found 2 things.
The first is a bug on my end that is preventing the output to the console. I have identified the issue and will have the fix out very shortly on all versions.
The second I see is your docker call, specifically the port.
Bjoern is setup to run on port 80 inside the container so you need to adjust your call:
$ docker run -p 8080:80 -it -e DEBUG="True" -e APP_MODULE="server:application" myimage
To run on localhost:8080
If you want to change the port within the container (for whatever reason) you would need to pass in the BJOERN_PORT variable to have it run on whatever port you want.
$ docker run -p 8080:8080 -it -e DEBUG="True" -e APP_MODULE="server:application" -e BJOERN_PORT=8080 myimage

Thank you angain for your quick response. I'll be waiting for  this bug fix. see you.

@Rafael-Sampaio-Pereira The output issue has been resolved and updated on docker hub.
Please be sure to pull the image before you build to make sure you get the update.
I also pushed the very simple demo project I used in case it has value for you:
https://github.com/Tecktron/docker-bjoern-flask-demo

Now its working fine. Thanks one more time.


Open Banking Demo - update IG version for autodiscovery of ssoTokenHeader

IG has to be configured with a static ssoTokenHeader value to talk to AM. In Identity Cloud, this header is randomised per tenant. This means that the header value needs to be manually updated in the kustomize configmap.yaml before deployment (or scripted as part of deployment).
We should use the discovery feature in IG 7.0.1 where ssoTokenHeader is discovered automatically from AM. This requires

Update Dockerfile to use IG 7.0.1 image
Remove ssoTokenHeader from AmService config in IG config.json
Remove AM_COOKIE_NAME from configmap.yaml

As well as updating the IG image version and removing cookie name from the config, I had to fix a couple of ingress issues with the paths /rcs and /rcs-api that came up during testing.


how to train with one GPU?

I used pods_train --num-gpus 1 , but I got error:
Traceback (most recent call last):
File "/home//anaconda3/envs/torch1.8/lib/python3.7/runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "/home//anaconda3/envs/torch1.8/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home//.vscode/extensions/ms-python.python-2021.5.926500501/pythonFiles/lib/python/debugpy/main.py", line 45, in
cli.main()
File "/home//.vscode/extensions/ms-python.python-2021.5.926500501/pythonFiles/lib/python/debugpy/../debugpy/server/cli.py", line 444, in main
run()
File "/home//.vscode/extensions/ms-python.python-2021.5.926500501/pythonFiles/lib/python/debugpy/../debugpy/server/cli.py", line 285, in run_file
runpy.run_path(target_as_str, run_name=compat.force_str("main"))
File "/home//anaconda3/envs/torch1.8/lib/python3.7/runpy.py", line 263, in run_path
pkg_name=pkg_name, script_name=fname)
File "/home//anaconda3/envs/torch1.8/lib/python3.7/runpy.py", line 96, in _run_module_code
mod_name, mod_spec, pkg_name, script_name)
File "/home//anaconda3/envs/torch1.8/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/media//D/05_source_code/01_torch/detection/cvpods/tools/train_net.py", line 124, in
args=(args,),
File "/media//D/05_source_code/01_torch/detection/cvpods/cvpods/engine/launch.py", line 56, in launch
main_func(args)
File "/media//D/05_source_code/01_torch/detection/cvpods/tools/train_net.py", line 110, in main
runner.train()
File "/media//D/05_source_code/01_torch/detection/cvpods/cvpods/engine/runner.py", line 271, in train
super().train(self.start_iter, self.start_epoch, self.max_iter)
File "/media//D/05_source_code/01_torch/detection/cvpods/cvpods/engine/base_runner.py", line 84, in train
self.run_step()
File "/media//D/05_source_code/01_torch/detection/cvpods/cvpods/engine/base_runner.py", line 185, in run_step
loss_dict = self.model(data)
File "/home//anaconda3/envs/torch1.8/lib/python3.7/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(input, kwargs)
File "/media//D/05_source_code/01_torch/detection/cvpods/playground/detection/coco/ota.res50.fpn.coco.800size.1x/fcos.py", line 218, in forward
gt_ious, box_cls, box_delta, box_iou)
File "/media//D/05_source_code/01_torch/detection/cvpods/playground/detection/coco/ota.res50.fpn.coco.800size.1x/fcos.py", line 383, in losses
dist.all_reduce(num_foreground)
File "/home//anaconda3/envs/torch1.8/lib/python3.7/site-packages/torch/distributed/distributed_c10d.py", line 1168, in all_reduce
default_pg = _get_default_group()
File "/home/*/anaconda3/envs/torch1.8/lib/python3.7/site-packages/torch/distributed/distributed_c10d.py", line 347, in _get_default_group
raise RuntimeError("Default process group has not been initialized, "
RuntimeError: Default process group has not been initialized, please make sure to call init_process_group.
how to train with one GPU?
Thank you

one GPU don't need norm_sync...


Upgrade MSAL library version

Also removed Asserts that compared error messages not owned by SqlClient.

Can I ask why did you just remove these five expected messages among all tests?

As mentioned above, these error messages are "not owned by SqlClient", so they are subject to change from MSAL. It's reasonable to validate that an exception occurred but comparing error message texts to be of match didn't seems a very good idea for our library tests.


Can not set times before 1970

FileTime uses u64 for the seconds field, rendering it unable to represent timestamps before 1970.
I believe time_t is signed on most systems, so using an i64 would be a better match.

Thanks for the report! Definitely sounds like a bug.
I'd like to keep backwards compatibility for now so we can likely just add a suite of mirroring APIs that work with i64 instead of u64, and then we could also add notes to the documentation of other APIs and such about this.

I think this has since been fixed, so closing.


Waveshare 1.27" RGB OLED Module 128x96

Thank you for making your work available.
I'm trying to use the new Waveshare 1.27" RGB OLED Module 128x96 ssd1351 with a Pi Pico and have got the display working. I've set the height = 96 in your driver and this allows be to draw things on the screen. The problem is that the origin appears to be 32 pixels above the top of the screen display and the bottom 32 pixels are always blank. I need to offset 32 pixels downwards.
I wonder if you can suggest how I can get the physical screen origin and the coding origin to coincide?
I am using the following GPIO pins on my Pi Pico:
spi = SPI(1, baudrate=13000000, sck=Pin(10), mosi=Pin(11))
display = Display(spi, dc=Pin(14), cs=Pin(9), rst=Pin(8))

I think I have fixed it. I changed this line (100)
self.write_cmd(self.START_LINE, 0x60)  # Set Display start line it was 0x00


[feat] Make the "Enter" key work on a modal to advance it to the next step.

For all of the keyboard warriors out there – make it so that hitting "Enter" on a modal will submit the modal. #753 partially seeks to solve this problem and could be a reference.
Bonus:

Make the "Delete" key work on the "delete element" modal as well as the enter key

Let the user "tab" between the button options and then hit "Enter" to advance.

Hey @Kitenite Could you assign me this issue

For sure go for it! @kartik-raj7


Test: Update all tests to use testing library

Good job, just missing the changeset (patch) to reference the changes in the changelog.

Good job, just missing the changeset (patch) to reference the changes in the changelog.

Oops, thanks, I just added one :)


🧪 get-transaction-count.test.ts

@dawsbot here is another mocking pr.
I removed this comment you had above the helper to stay consistent with the other test helpers that don't have a comment like this, but lmk if you want me to go through an add a comment like this above all the helpers used in tests.
/**
 *
 * @param rpcUrl
 * @param blockTag
 */
async function testGetTC(rpcUrl: string, blockTag?: BlockTag) {

I removed the comment above your hot wallet address because now that we are mocking the address we use is arbitrary


[swift-inspect] Make sure to initialize backtrace flags.

This eliminates a compilation error with Swift 5.5 and the latest
argument parser library.

@swift-ci please smoke test and merge

@swift-ci please smoke test Linux


How to open the pdf blob in the same window

My app implements a PDF view by clicking on a print button on a form page. When the button is clicked a new tab is opened a the component where the PDF content resides is loaded. I purposely do not load/import the component which has the PDF component inside the same form due to complexity of the overall form component. So the page to print is actually another page. If i set download and preview to false to get the blob how can i open the blob within the same window? What is currently happening is that another page opens to show the PDF even though I have this code in the beforeDownload method:
async beforeDownload({ html2pdf, options, pdfContent }){                 await html2pdf().set(options).from(pdfContent).toPdf().get('pdf').then((pdf) => {                       window.open(pdf.output('bloburl'));                 }) },

how can i open the blob within the same window
hmm one solution is just create an iframe that covers the whole page, and insert the blob file in the iframe,
let me know if that works

Thanks for this idea. It does work.


Align ResultMessage#getPayload implementations

Currently, in certain places, we throw an IllegalPayloadAccessException and in some other places we return null when accessing the payload of exceptional Result Message.
In all places, we should throw an IllegalPayloadAccessException.

Closing this issue as it has been resolved in pull request #1514.


Update README.md : Fix installation instructions

Description of changes:
This pull request fixes an issue in the installation instructions on the README.
It instructs the user to directly install the mlm package through pip install git+git://github.com/awslabs/mlm-scoring.git@master#egg=mlm.
The current instruction to clone the repository and then run pip install -e . won't work on several environments, including Google Colab.
By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

Thank you


chore: Minor logging fix for untested version workflow

@therightstuff the CircleCI check doesn't appear to have happened. Is there an issue?

@therightstuff the CircleCI check doesn't appear to have happened. Is there an issue?

hey @kenfinnigan - apparently PRs from forked repos don't trigger builds, i'm going to see what i can do about that


Twilio flex webchat not working

yarn start
yarn run v1.22.22
$ react-app-rewired start
node:internal/modules/cjs/loader:599
throw e;
^
Error [ERR_PACKAGE_PATH_NOT_EXPORTED]: Package subpath './lib/tokenize' is not defined by "exports" in /workspaces/chat-integrations/twilio-flex-webchat/node_modules/postcss-safe-parser/node_modules/postcss/package.json
at exportsNotFound (node:internal/modules/esm/resolve:304:10)
at packageExportsResolve (node:internal/modules/esm/resolve:651:9)
at resolveExports (node:internal/modules/cjs/loader:592:36)
at Module._findPath (node:internal/modules/cjs/loader:669:31)
at Module._resolveFilename (node:internal/modules/cjs/loader:1131:27)
at Module._load (node:internal/modules/cjs/loader:986:27)
at Module.require (node:internal/modules/cjs/loader:1233:19)
at require (node:internal/modules/helpers:179:18)
at Object. (/workspaces/chat-integrations/twilio-flex-webchat/node_modules/postcss-safe-parser/lib/safe-parser.js:1:17)
at Module._compile (node:internal/modules/cjs/loader:1358:14) {
code: 'ERR_PACKAGE_PATH_NOT_EXPORTED'
}
Node.js v20.14.0
error Command failed with exit code 1.
info Visit https://yarnpkg.com/en/docs/cli/run for documentation about this command.

Hi @jessmitch42, Flex flow sid is considered obsolete and it is only available for the accounts with older UI versions 1.x.. Could you update this repo? that would be helpful!

Hey @nitishymtpl! Feel free to open a PR with the changes you're recommending and someone from Daily can review. This isn't a codebase I'm personally maintaining.


ARM64 support

Fix bad code generation issues and build hangs so that we can produce official ARM64 builds. This would unblock using Swift on Windows on Apple hardware via Parallels, which would be useful to macOS-based engineers at Apple and The Browser Company.

Some fixes thus far (in reverse chronological order):

https://reviews.llvm.org/D155001
https://github.com/apple/swift/pull/68174
https://github.com/apple/swift/pull/67993
https://github.com/apple/llvm-project/pull/7276
https://github.com/apple/llvm-project/pull/7107
https://github.com/apple/llvm-project/pull/7081

One more fix: https://github.com/llvm/llvm-project/commit/0ecd8846aedac1039448a32f87d299ce244dda68

https://github.com/llvm/llvm-project/commit/f776e0b6df611d973db1778256dfcd1dc37128c5

https://github.com/apple/swift/pull/69836

https://github.com/apple/swift/pull/69929

https://github.com/apple/swift/pull/70050

https://github.com/apple/swift/pull/69935

https://github.com/apple/swift/pull/69368

https://github.com/apple/swift/pull/69375

https://github.com/apple/swift/pull/68780

@hjyamauchi , with your work we are able to build and run arm64 now. Should we complete this and file more granular follow-ups like fixing tests?

Sure

@hjyamauchi  Ok, I'm completing this task because we do have arm64 support now. I don't know if the breakdown in the description is still valid but please file follow-up tasks as necessary.


Merge recent changes from release-1.0

Syncing up to avoid them getting out of sync.

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[APPROVALNOTIFIER] This PR is NOT APPROVED
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To fully approve this pull request, please assign additional approvers.
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we need to retain individual commits.. please don't lgtm these PRs. I can do a merge commit once all tests pass.

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[BUG] Deepspeed Zero 3 Inference InFlight Params with new HuggingFace Mixtral Model

Describe the bug
I tried running deepspeed zero 3 on a new huggingface model and got the following error:
      [2023-12-13 04:12:18,837] [WARNING] [parameter_offload.py:86:_apply_to_tensors_only] A module has unknown inputs or outputs type (<class 'transformers.cache_utils.DynamicCache'>) and the tensors embedded in it cannot be detected. The ZeRO-3 hooks designed to trigger before or after backward pass of the module relies on knowing the input and output tensors and therefore may not get triggered properly.
      Invalidate trace cache @ step 14: expected module 19, but got module 34
      Traceback (most recent call last):
        File "/home/ubuntu/mixtral_hf/deepspeed_zero.py", line 36, in <module>
          outputs = model.generate(inputs, max_new_tokens=20)
        File "/home/ubuntu/anaconda3/envs/mixtral/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
          return func(*args, **kwargs)
        File "/home/ubuntu/mixtral_hf/transformers/src/transformers/generation/utils.py", line 1731, in generate
          return self.greedy_search(
        File "/home/ubuntu/mixtral_hf/transformers/src/transformers/generation/utils.py", line 2592, in greedy_search
          outputs = self(
        File "/home/ubuntu/anaconda3/envs/mixtral/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
          return self._call_impl(*args, **kwargs)
        File "/home/ubuntu/anaconda3/envs/mixtral/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1581, in _call_impl
          hook_result = hook(self, args, result)
        File "/home/ubuntu/anaconda3/envs/mixtral/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
          ret_val = func(*args, **kwargs)
        File "/home/ubuntu/anaconda3/envs/mixtral/lib/python3.10/site-packages/deepspeed/runtime/zero/parameter_offload.py", line 350, in _end_of_forward_hook
          self.get_param_coordinator(training=False).reset_step()
        File "/home/ubuntu/anaconda3/envs/mixtral/lib/python3.10/site-packages/deepspeed/runtime/zero/partitioned_param_coordinator.py", line 203, in reset_step
          raise RuntimeError(f"still have inflight params "
          RuntimeError: still have inflight params [{'id': 9, 'status': 'AVAILABLE', 'numel': 58720256, 'ds_numel': 58720256, 'shape': (14336, 4096), 'ds_shape': (14336, 4096), 'requires_grad': True, 'grad_shape': None, 'persist': False, 'active_sub_modules': set(), 'ds_tensor.shape': torch.Size([58720256])}, {'id': 11, 'status': 'INFLIGHT', 'numel': 58720256, 'ds_numel': 58720256, 'shape': (14336, 4096), 'ds_shape': (14336, 4096), 'requires_grad': True, 'grad_shape': None, 'persist': False, 'active_sub_modules': set(), 'ds_tensor.shape': torch.Size([58720256])}, {'id': 10, 'status': 'INFLIGHT', 'numel': 58720256, 'ds_numel': 58720256, 'shape': (4096, 14336), 'ds_shape': (4096, 14336), 'requires_grad': True, 'grad_shape': None, 'persist': False, 'active_sub_modules': set(), 'ds_tensor.shape': torch.Size([58720256])}, {'id': 15, 'status': 'INFLIGHT', 'numel': 58720256, 'ds_numel': 58720256, 'shape': (14336, 4096), 'ds_shape': (14336, 4096), 'requires_grad': True, 'grad_shape': None, 'persist': False, 'active_sub_modules': set(), 'ds_tensor.shape': torch.Size([58720256])}, {'id': 17, 'status': 'INFLIGHT', 'numel': 58720256, 'ds_numel': 58720256, 'shape': (14336, 4096), 'ds_shape': (14336, 4096), 'requires_grad': True, 'grad_shape': None, 'persist': False, 'active_sub_modules': set(), 'ds_tensor.shape': torch.Size([58720256])}, {'id': 16, 'status': 'INFLIGHT', 'numel': 58720256, 'ds_numel': 58720256, 'shape': (4096, 14336), 'ds_shape': (4096, 14336), 'requires_grad': True, 'grad_shape': None, 'persist': False, 'active_sub_modules': set(), 'ds_tensor.shape': torch.Size([58720256])}, {'id': 21, 'status': 'INFLIGHT', 'numel': 58720256, 'ds_numel': 58720256, 'shape': (14336, 4096), 'ds_shape': (14336, 4096), 'requires_grad': True, 'grad_shape': None, 'persist': False, 'active_sub_modules': set(), 'ds_tensor.shape': torch.Size([58720256])}, {'id': 23, 'status': 'INFLIGHT', 'numel': 58720256, 'ds_numel': 58720256, 'shape': (14336, 4096), 'ds_shape': (14336, 4096), 'requires_grad': True, 'grad_shape': None, 'persist': False, 'active_sub_modules': set(), 'ds_tensor.shape': torch.Size([58720256])}, {'id': 22, 'status': 'INFLIGHT', 'numel': 58720256, 'ds_numel': 58720256, 'shape': (4096, 14336), 'ds_shape': (4096, 14336), 'requires_grad': True, 'grad_shape': None, 'persist': False, 'active_sub_modules': set(), 'ds_tensor.shape': torch.Size([58720256])}, {'id': 27, 'status': 'INFLIGHT', 'numel': 58720256, 'ds_numel': 58720256, 'shape': (14336, 4096), 'ds_shape': (14336, 4096), 'requires_grad': True, 'grad_shape': None, 'persist': False, 'active_sub_modules': set(), 'ds_tensor.shape': torch.Size([58720256])}]

To Reproduce
Steps to reproduce the behavior:
Simple inference script to reproduce:
  model_id = "mistralai/Mixtral-8x7B-v0.1"
  ds_config = {
      "bf16": {
          "enabled": True,
      },
      "zero_optimization": {
          "stage": 3,
          "offload_param": {
              "device": "cpu",
          }
      },
      "train_micro_batch_size_per_gpu": 1,
  }

  hfdsc = HfDeepSpeedConfig(ds_config)

  tokenizer = AutoTokenizer.from_pretrained(model_id)
  model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16)
  model.eval()

  ds_engine = deepspeed.initialize(model=model, config_params=ds_config)[0]
  ds_engine.module.eval()
  model = ds_engine.module

  inputs = tokenizer.encode("DeepSpeed is", return_tensors="pt").to("cuda")
  outputs = model.generate(inputs, max_new_tokens=20)
  output_str = tokenizer.decode(outputs[0])

What packages are required and their versions

HuggingFace 4.65
Deepspeed 0.12.4
Torch 2.1
Cuda 12.1

ds_report output
Please run ds_report to give us details about your setup.
    DeepSpeed C++/CUDA extension op report
    --------------------------------------------------
    NOTE: Ops not installed will be just-in-time (JIT) compiled at
          runtime if needed. Op compatibility means that your system
          meet the required dependencies to JIT install the op.
    --------------------------------------------------
    JIT compiled ops requires ninja
    ninja .................. [OKAY]
    --------------------------------------------------
    op name ................ installed .. compatible
    --------------------------------------------------
    async_io ............... [NO] ....... [OKAY]
    fused_adam ............. [NO] ....... [OKAY]
    cpu_adam ............... [NO] ....... [OKAY]
    cpu_adagrad ............ [NO] ....... [OKAY]
    cpu_lion ............... [NO] ....... [OKAY]
     [WARNING]  Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH
    evoformer_attn ......... [NO] ....... [NO]
    fused_lamb ............. [NO] ....... [OKAY]
    fused_lion ............. [NO] ....... [OKAY]
    inference_core_ops ..... [NO] ....... [OKAY]
    cutlass_ops ............ [NO] ....... [OKAY]
    quantizer .............. [NO] ....... [OKAY]
    ragged_device_ops ...... [NO] ....... [OKAY]
    ragged_ops ............. [NO] ....... [OKAY]
    random_ltd ............. [NO] ....... [OKAY]
     [WARNING]  sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.1
     [WARNING]  using untested triton version (2.1.0), only 1.0.0 is known to be compatible
    sparse_attn ............ [NO] ....... [NO]
    spatial_inference ...... [NO] ....... [OKAY]
    transformer ............ [NO] ....... [OKAY]
    stochastic_transformer . [NO] ....... [OKAY]
    transformer_inference .. [NO] ....... [OKAY]
    --------------------------------------------------
    DeepSpeed general environment info:
    torch install path ............... ['/home/ubuntu/anaconda3/envs/mixtral/lib/python3.10/site-packages/torch']
    torch version .................... 2.1.1
    deepspeed install path ........... ['/home/ubuntu/anaconda3/envs/mixtral/lib/python3.10/site-packages/deepspeed']
    deepspeed info ................... 0.12.4, unknown, unknown
    torch cuda version ............... 12.1
    torch hip version ................ None
    nvcc version ..................... 12.1
    deepspeed wheel compiled w. ...... torch 2.1, cuda 12.1
    shared memory (/dev/shm) size .... 124.52 GB

Screenshots
If applicable, add screenshots to help explain your problem.
System info (please complete the following information):

AWS g5.16x large instance
OS: Ubuntu 22.04
GPU: Nvidia A10G
OS: [e.g. Ubuntu 18.04]
GPU count: 1
Python version: 3.10.13

same question

Same problem

same problem

same problem
It's similar to https://github.com/microsoft/DeepSpeed/issues/4094

Changing that parameter fundamentally changes the model

same problem It's similar to #4094

I modify the num_experts_per_tok to 8 in config.json of mixtral-8x7b and everything works well. So I think the problem is caused by the offload for unused parameters.
I try to use "stage3_prefetch_bucket_size": 0 as described in [BUG] Unused params lead to "still have inflight params" error #4094. After that, it does not report any error, but reports some warnings

[2023-12-19 19:41:54,820] [WARNING] [parameter_offload.py:86:_apply_to_tensors_only] A module has unknown inputs or outputs type (<class 'transformers.cache_utils.DynamicCache'>) and the tensors embedded in it cannot be detected. The ZeRO-3 hooks designed to trigger before or after backward pass of the module relies on knowing the input and output tensors and therefore may not get triggered properly.
Invalidate trace cache @ step 14: expected module 19, but got module 34
Invalidate trace cache @ step 19: expected module 44, but got module 34
Invalidate trace cache @ step 56: expected module 133, but got module 123
Invalidate trace cache @ step 14: expected module 14, but got module 24
Invalidate trace cache @ step 14: expected module 34, but got module 14
Invalidate trace cache @ step 14: expected module 29, but got module 14
Invalidate trace cache @ step 14: expected module 14, but got module 29
Invalidate trace cache @ step 14: expected module 14, but got module 29
Invalidate trace cache @ step 14: expected module 29, but got module 19
Invalidate trace cache @ step 61: expected module 148, but got module 133
<s> DeepSpeed is a deep learning optimization library that makes distributed deep learning fast and efficient. DeepSpeed is designed to be

Changing that parameter fundamentally changes the model right? By default, it should only route to 2 experts per token.

Changing that parameter fundamentally changes the model

same problem It's similar to #4094

I modify the num_experts_per_tok to 8 in config.json of mixtral-8x7b and everything works well. So I think the problem is caused by the offload for unused parameters.
I try to use "stage3_prefetch_bucket_size": 0 as described in [BUG] Unused params lead to "still have inflight params" error #4094. After that, it does not report any error, but reports some warnings

[2023-12-19 19:41:54,820] [WARNING] [parameter_offload.py:86:_apply_to_tensors_only] A module has unknown inputs or outputs type (<class 'transformers.cache_utils.DynamicCache'>) and the tensors embedded in it cannot be detected. The ZeRO-3 hooks designed to trigger before or after backward pass of the module relies on knowing the input and output tensors and therefore may not get triggered properly.
Invalidate trace cache @ step 14: expected module 19, but got module 34
Invalidate trace cache @ step 19: expected module 44, but got module 34
Invalidate trace cache @ step 56: expected module 133, but got module 123
Invalidate trace cache @ step 14: expected module 14, but got module 24
Invalidate trace cache @ step 14: expected module 34, but got module 14
Invalidate trace cache @ step 14: expected module 29, but got module 14
Invalidate trace cache @ step 14: expected module 14, but got module 29
Invalidate trace cache @ step 14: expected module 14, but got module 29
Invalidate trace cache @ step 14: expected module 29, but got module 19
Invalidate trace cache @ step 61: expected module 148, but got module 133
<s> DeepSpeed is a deep learning optimization library that makes distributed deep learning fast and efficient. DeepSpeed is designed to be

Changing that parameter fundamentally changes the model right? By default, it should only route to 2 experts per token.

Yes

Changing that parameter fundamentally changes the model

same problem It's similar to #4094

I modify the num_experts_per_tok to 8 in config.json of mixtral-8x7b and everything works well. So I think the problem is caused by the offload for unused parameters.
I try to use "stage3_prefetch_bucket_size": 0 as described in [BUG] Unused params lead to "still have inflight params" error #4094. After that, it does not report any error, but reports some warnings

[2023-12-19 19:41:54,820] [WARNING] [parameter_offload.py:86:_apply_to_tensors_only] A module has unknown inputs or outputs type (<class 'transformers.cache_utils.DynamicCache'>) and the tensors embedded in it cannot be detected. The ZeRO-3 hooks designed to trigger before or after backward pass of the module relies on knowing the input and output tensors and therefore may not get triggered properly.
Invalidate trace cache @ step 14: expected module 19, but got module 34
Invalidate trace cache @ step 19: expected module 44, but got module 34
Invalidate trace cache @ step 56: expected module 133, but got module 123
Invalidate trace cache @ step 14: expected module 14, but got module 24
Invalidate trace cache @ step 14: expected module 34, but got module 14
Invalidate trace cache @ step 14: expected module 29, but got module 14
Invalidate trace cache @ step 14: expected module 14, but got module 29
Invalidate trace cache @ step 14: expected module 14, but got module 29
Invalidate trace cache @ step 14: expected module 29, but got module 19
Invalidate trace cache @ step 61: expected module 148, but got module 133
<s> DeepSpeed is a deep learning optimization library that makes distributed deep learning fast and efficient. DeepSpeed is designed to be

Changing that parameter fundamentally changes the model right? By default, it should only route to 2 experts per token.

Yes

Will that impact the performance?

Changing that parameter fundamentally changes the model

same problem It's similar to #4094

I modify the num_experts_per_tok to 8 in config.json of mixtral-8x7b and everything works well. So I think the problem is caused by the offload for unused parameters.
I try to use "stage3_prefetch_bucket_size": 0 as described in [BUG] Unused params lead to "still have inflight params" error #4094. After that, it does not report any error, but reports some warnings

[2023-12-19 19:41:54,820] [WARNING] [parameter_offload.py:86:_apply_to_tensors_only] A module has unknown inputs or outputs type (<class 'transformers.cache_utils.DynamicCache'>) and the tensors embedded in it cannot be detected. The ZeRO-3 hooks designed to trigger before or after backward pass of the module relies on knowing the input and output tensors and therefore may not get triggered properly.
Invalidate trace cache @ step 14: expected module 19, but got module 34
Invalidate trace cache @ step 19: expected module 44, but got module 34
Invalidate trace cache @ step 56: expected module 133, but got module 123
Invalidate trace cache @ step 14: expected module 14, but got module 24
Invalidate trace cache @ step 14: expected module 34, but got module 14
Invalidate trace cache @ step 14: expected module 29, but got module 14
Invalidate trace cache @ step 14: expected module 14, but got module 29
Invalidate trace cache @ step 14: expected module 14, but got module 29
Invalidate trace cache @ step 14: expected module 29, but got module 19
Invalidate trace cache @ step 61: expected module 148, but got module 133
<s> DeepSpeed is a deep learning optimization library that makes distributed deep learning fast and efficient. DeepSpeed is designed to be

Changing that parameter fundamentally changes the model right? By default, it should only route to 2 experts per token.

Yes

Will that impact the performance?

Of course :)

Will the inference speed slow down if I understand correctly, and will the model's performance deteriorate?

Changing that parameter fundamentally changes the model

same problem It's similar to #4094

I modify the num_experts_per_tok to 8 in config.json of mixtral-8x7b and everything works well. So I think the problem is caused by the offload for unused parameters.
I try to use "stage3_prefetch_bucket_size": 0 as described in [BUG] Unused params lead to "still have inflight params" error #4094. After that, it does not report any error, but reports some warnings

[2023-12-19 19:41:54,820] [WARNING] [parameter_offload.py:86:_apply_to_tensors_only] A module has unknown inputs or outputs type (<class 'transformers.cache_utils.DynamicCache'>) and the tensors embedded in it cannot be detected. The ZeRO-3 hooks designed to trigger before or after backward pass of the module relies on knowing the input and output tensors and therefore may not get triggered properly.
Invalidate trace cache @ step 14: expected module 19, but got module 34
Invalidate trace cache @ step 19: expected module 44, but got module 34
Invalidate trace cache @ step 56: expected module 133, but got module 123
Invalidate trace cache @ step 14: expected module 14, but got module 24
Invalidate trace cache @ step 14: expected module 34, but got module 14
Invalidate trace cache @ step 14: expected module 29, but got module 14
Invalidate trace cache @ step 14: expected module 14, but got module 29
Invalidate trace cache @ step 14: expected module 14, but got module 29
Invalidate trace cache @ step 14: expected module 29, but got module 19
Invalidate trace cache @ step 61: expected module 148, but got module 133
<s> DeepSpeed is a deep learning optimization library that makes distributed deep learning fast and efficient. DeepSpeed is designed to be

Changing that parameter fundamentally changes the model right? By default, it should only route to 2 experts per token.

Yes

Will that impact the performance?

Of course :)

Will the inference speed slow down if I understand correctly, and will the model's performance deteriorate?

same question

Guys, thanks for the great debugging and collaboration here to understand this problem. The fundamental issue is that zero3 caches the parameter trace to enable parameter prefetching to reduce all-gather latency. Unfortunately, since MoE layers can activate different experts across iterations, the parameter trace cache is invalidated when the expert changes. The warning messages are for the trace cache invalidations. In this case, the warning is avoidable since prefetching is disabled by setting  "stage3_prefetch_bucket_size": 0, so a minor fix is required in this case. However, in general inference speed will be very slow as observed.
We have not previously tested zero3 and MoE, but we will prioritize this investigation now given the interest.

I got the error  with "stage_prefetch_bucket_size": 0
Invalidate trace cache @ step 1323: expected module 2476, but got module 2510                                    | 20/2466 [02:15<4:12:07,  6.18s/it, gpt_loss=1.28, loss_mean=1.22, balancing_loss=8]

[rank0]:[E ProcessGroupNCCL.cpp:754] [Rank 0] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=151178, OpType=_ALLGATHER_BASE, NumelIn=65536, NumelOut=262144, Timeout(ms)=1800000) ran for 1800326 milliseconds before timing out.
[rank0]:[E ProcessGroupNCCL.cpp:768] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank0]:[E ProcessGroupNCCL.cpp:774] To avoid data inconsistency, we are taking the entire process down.
[rank0]:[E ProcessGroupNCCL.cpp:1282] [Rank 0] NCCL watchdog thread terminated with exception: [Rank 0] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=151178, OpType=_ALLGATHER_BASE, NumelIn=65536, NumelOut=262144, Timeout(ms)=1800000) ran for 1800326 milliseconds before timing out.
Exception raised from checkTimeout at /opt/pytorch/pytorch/torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:756 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >) + 0x99 (0x7f9ddd19c8f9 in /usr/local/lib/python3.10/dist-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(c10::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1f2 (0x7f9d7ef58142 in /usr/local/lib/python3.10/dist-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::workCleanupLoop() + 0x178 (0x7f9d7ef5e538 in /usr/local/lib/python3.10/dist-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x8e (0x7f9d7ef5eb2e in /usr/local/lib/python3.10/dist-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0xdc253 (0x7f9ddccb0253 in /usr/lib/x86_64-linux-gnu/libstdc++.so.6)
frame #5: <unknown function> + 0x94ac3 (0x7f9e8ad78ac3 in /usr/lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126660 (0x7f9e8ae0a660 in /usr/lib/x86_64-linux-gnu/libc.so.6)

I am also observing the same issue even with "stage_prefetch_bucket_size": 0. The runtime error about inflight parameters does not occur but the process just hangs indefinitely and crashes at the end with timeout.
Did someone manage to fine-tune Mixtral with zero3 and huggingface? Could you share your deepspeed config? @K-Nick @LZHgrla @ryandeng1

@BBerabi
You can try it with https://github.com/InternLM/xtuner/tree/main/xtuner/configs/mixtral
But remember that, using deepspeed_zero3 instead of deepspeed_zero3_offload

I can fully fine-tune Mistral7b*8 instruct with deepspeed zero3 on 2 A100-80GB instances, the code won't hook and run smoothly. I didn't change anything except disabling the evaluation part to calculate ppl for val data set. The fine-tuned model looks normal but I still don't know why it can happen. I just provide my training environment for your inference.
Transformer version: 4.36.2, deepspeed 0.12.5, deepspeed zero_3 config:
  "gradient_accumulation_steps": 8,
  "train_micro_batch_size_per_gpu": 4,
  "prescale_gradients": false,
  "zero_allow_untested_optimizer": true,
  "zero_optimization": {
    "stage": 3,
    "offload_param": {
        "device": "none"
    },
    "offload_optimizer": {
        "device": "none"
    },
    "stage3_param_persistence_threshold": 1.000000e+04,
    "stage3_max_live_parameters": 3.000000e+07,
    "stage3_prefetch_bucket_size": 3.000000e+07,
    "memory_efficient_linear": false
  },
  "steps_per_print": 1,
  "gradient_clipping": 1.0,
  "wall_clock_breakdown": true,
  "bf16": {
    "enabled": true
  }
}```

I have same question...how resolve it ?

Hi all,
If you want to generate text with Mixtral, DeepSpeed-FastGen (DeepSpeed-MII) will be the first choice. The example is available here. I verified that Mixtral works just by modifying the model name.
It is easier to use "non-persistent" mode for testing purpose, but "persistent" mode will give you the best performance. Please refer to DeepSpeed-MII for more details.

Is there any progress ?

Hi @hijkzzz and all,
#4966 should have fixed this issue. You can find working example there.
The PR was already merged into master. Please feel free to try, but I still recommend using DeepSpeed-FastGen for text generation. It is much faster and supports Mixtral.

@mynewstart Hey, would u mind to share your complete deepspeed config?

Thank you for sharing the issue, @ftgreat. The same issue is reported at #4966. Let me take a look.

I wrote a monkey patch using dense moe impl instead of mixtral sparse moe. Tested ok for my cases, no hangs happend.
https://github.com/ftgreat/llmkit/blob/main/huggingface/mixtral/mixtral_dense_moe_monkey_patch.py

@ftgreat The root cause of this issue is that DeepSpeed tries to run reduce-scatter for only a part of experts.
ZeRO3 sets hooks on parameters to run reduce-scatter. However, the hook is not fired unless the expert is activated at a forward pass. Our data parallel processes may activate different sets of experts. We need all processes to join such a communication collective, but the reduce-scatter is called only on some processes in this case.
Since we already implemented the API to set a leaf module for ZeRO3, the solution will be to delay reduce-scatter until the backward pass of the leaf module finishes. I will work on this direction.

@ftgreat
Hello,
I would like to know if your monkey patch can achieve the same results as the original mixtral forward.
Is this method currently the best approach right?

https://github.com/ftgreat/llmkit/blob/main/huggingface/mixtral/mixtral_dense_moe_monkey_patch.py

Add some unittest cases.
https://github.com/ftgreat/llmkit/blob/main/huggingface/mixtral/mixtral_dense_moe_monkey_patch.py#L69

I've opened a PR to fix the issue causing hangs during backward passes. Please feel free to test it with your model.

https://github.com/ftgreat/llmkit/blob/main/huggingface/mixtral/mixtral_dense_moe_monkey_patch.py

Add some unittest cases. https://github.com/ftgreat/llmkit/blob/main/huggingface/mixtral/mixtral_dense_moe_monkey_patch.py#L69

I tried the code  and run without error, but the loss is all 0. and grad is 1?

Hey @tohtana
Deepspeed FastGen would only be for inference right? Does it support full standard finetuning of Mixtral / MoE models?

We have an example to run training for Mixtral here:
https://github.com/microsoft/DeepSpeed/pull/5008#issuecomment-1910607845
@Sniper970119 @nilsec @hchoi-moveworks
Can you try this solution?

Thanks @tohtana !!
Would deepspeed also support also using CPU offloading for Mixtral model ?
If not, https://github.com/microsoft/DeepSpeed/pull/5008#issuecomment-1910607845 assumes that we need 2 A100 nodes right?

@hchoi-moveworks The CPU offloading should work, but I haven't tried.
I think I needed four A100s to run the example.

We have an example to run training for Mixtral here: #5008 (comment)
@Sniper970119 @nilsec @hchoi-moveworks Can you try this solution?

Hi，I tried the script and get an error at L132.
 File "test_moe_train.py", line 132, in training_function
    accelerator.backward(loss)
  File ".../lib/python3.8/site-packages/accelerate/accelerator.py", line 1899, in backward

and
deepspeed                     0.13.4
sentence-transformers         2.2.2
transformers                  4.38.1
transformers-stream-generator 0.0.4

What should I do? Or need more error information？

We have an example to run training for Mixtral here: #5008 (comment)
@Sniper970119 @nilsec @hchoi-moveworks Can you try this solution?

Hi，I tried the script and get an error at L132.
 File "test_moe_train.py", line 132, in training_function
    accelerator.backward(loss)
  File ".../lib/python3.8/site-packages/accelerate/accelerator.py", line 1899, in backward
             self.deepspeed_engine_wrapped.backward(loss, **kwargs)self.deepspeed_engine_wrapped.backward(loss, **kwargs)self.deepspeed_engine_wrapped.backward(loss, **kwargs)
 File ".../lib/python3.8/site-packages/accelerate/utils/deepspeed.py", line 167, in backward
            self.deepspeed_engine_wrapped.backward(loss, **kwargs)
 File "/.../lib/python3.8/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
      self.engine.backward(loss, **kwargs)
  File ".../lib/python3.8/site-packages/deepspeed/runtime/zero/stage3.py", line 2213, in backward
        self.loss_scaler.backward(loss.float(), retain_graph=retain_graph)        self.loss_scaler.backward(loss.float(), retain_graph=retain_graph)
self.loss_scaler.backward(loss.float(), retain_graph=retain_graph)self.loss_scaler.backward(loss.float(), retain_graph=retain_graph)

RuntimeError: The size of tensor a (0) must match the size of tensor b (14336) at non-singleton dimension 1
RuntimeErrorRuntimeError: : The size of tensor a (0) must match the size of tensor b (14336) at non-singleton dimension 1The size of tensor a (0) must match the size of tensor b (14336) at non-singleton dimension 1

and
deepspeed                     0.13.4
sentence-transformers         2.2.2
transformers                  4.38.1
transformers-stream-generator 0.0.4

What should I do? Or need more information？

@tohtana  Could you help me?

I'm trying Mixtral inference with multiple process, however, when each rank take different input, it hangs on some rank. Anyone encountered same problem? Thanks


neomutt: 20230407 -> 20230512

Description of changes
ChangeLog: https://github.com/neomutt/neomutt/releases/tag/20230512

Things done

Built on platform(s)

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

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

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

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
23.05 Release Notes (or backporting 22.11 Release notes)

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

[x] Fits CONTRIBUTING.md.

Result of nixpkgs-review pr 231638 run on x86_64-linux 1

1 package built:

neomutt

This pull request has been mentioned on NixOS Discourse. There might be relevant details there:
https://discourse.nixos.org/t/can-we-make-ofborg-show-broken-tests-as-red/10717/2


Use git subtree to manage third party libraries

This uses a git subtree to manage lib/gbenchmark and in lib/README.md are some instructions for using git subtree. If possible I'd like to get a version of this into the next pony release. For the up coming pony release I'd like to incoporate the next google/benchmark release, which with luck will be sometime this week, see issue 549 on google/benchmark.

@winksaville - is this still something you want to pursue? How does it fit into what you discovered in the vendoring of LLVM PR you did recently?

Closing as we believe this is no longer the approach that @winksaville was advocating and was used for allowing vendoring of LLVM.

Correct, git submodules are used.


Segmentation contour boundaries off by 1 pixel on two edges

For segmentation, if you zoom the model output layer close enough, you can see that between segmentation masks for different classes, there is a one-pixel gap, see screenshot:

It happens because after stitching the model outputs, the contour is found by the OpenCV (findContours), which finds top-left corner of the contour pixel. Afterwards, it is converted to a polygon layer, which goes through all the contour points, therefore, on the opposite edges, we lose one pixel.
It should be fixed, but I do not have a good idea now on how to do it.

I'm implementing raw result raster output for MapProcessorSegmentation so I can use thresholding, argmax and gdal_polygonize  on the raw result instead of the default argmax + cv2.findContours. This is something I would have done anyway as some models use probability masks as input.
But the edge effects are present in the argmaxed output (just full result img as a raster in QGIS, which I have already implemented in a quick and dirty way. Now I'm moving couple of raster functions from MapProcessorSuperresolution to processing_utlis and use those to save the rasters in MapProcessorSegmentation.


Error when running watchman

npm start

><EMAIL_ADDRESS>start /home/oren/projects/react-native/ReactNative-PropertyFinder
> node_modules/react-native/packager/packager.sh

 ┌────────────────────────────────────────────────────────────────────────────┐
 │  Running packager on port 8081.                                            │
 │                                                                            │
 │  Keep this packager running while developing on any JS projects. Feel      │
 │  free to close this tab and run your own packager instance if you          │
 │  prefer.                                                                   │
 │                                                                            │
 │  https://github.com/facebook/react-native                                  │
 │                                                                            │
 └────────────────────────────────────────────────────────────────────────────┘
Looking for JS files in
   /home/oren/projects/react-native/ReactNative-PropertyFinder

React packager ready.

[12:00:54] <START> Building Dependency Graph
[12:00:54] <START> Crawling File System
 ERROR  A non-recoverable condition has triggered.  Watchman needs your help!
The triggering condition was at timestamp=1443812455: inotify-add-watch(/home/oren/projects/react-native/ReactNative-PropertyFinder/node_modules/react-native/node_modules/module-deps/node_modules/detective/node_modules/escodegen/node_modules/.bin) -> The user limit on the total number of inotify watches was reached; increase the fs.inotify.max_user_watches sysctl
All requests will continue to fail with this message until you resolve
the underlying problem.  You will find more information on fixing this at
https://facebook.github.io/watchman/docs/troubleshooting.html#poison-inotify-add-watch

{"watchmanResponse":{"version":"3.7.0","error":"A non-recoverable condition has triggered.  Watchman needs your help!\nThe triggering condition was at timestamp=1443812455: inotify-add-watch(/home/oren/projects/react-native/ReactNative-PropertyFinder/node_modules/react-native/node_modules/module-deps/node_modules/detective/node_modules/escodegen/node_modules/.bin) -> The user limit on the total number of inotify watches was reached; increase the fs.inotify.max_user_watches sysctl\nAll requests will continue to fail with this message until you resolve\nthe underlying problem.  You will find more information on fixing this at\nhttps://facebook.github.io/watchman/docs/troubleshooting.html#poison-inotify-add-watch\n"}}
Error: A non-recoverable condition has triggered.  Watchman needs your help!
The triggering condition was at timestamp=1443812455: inotify-add-watch(/home/oren/projects/react-native/ReactNative-PropertyFinder/node_modules/react-native/node_modules/module-deps/node_modules/detective/node_modules/escodegen/node_modules/.bin) -> The user limit on the total number of inotify watches was reached; increase the fs.inotify.max_user_watches sysctl
All requests will continue to fail with this message until you resolve
the underlying problem.  You will find more information on fixing this at
https://facebook.github.io/watchman/docs/troubleshooting.html#poison-inotify-add-watch

    at ChildProcess.<anonymous> (/home/oren/projects/react-native/ReactNative-PropertyFinder/node_modules/react-native/node_modules/sane/node_modules/fb-watchman/index.js:202:17)
    at emitTwo (events.js:87:13)
    at ChildProcess.emit (events.js:172:7)
    at maybeClose (internal/child_process.js:817:16)
    at Process.ChildProcess._handle.onexit (internal/child_process.js:211:5)

I tried echo 524288 | sudo tee -a /proc/sys/fs/inotify/max_user_watches but it didn't help.
i guess i'll have to spend the time here - https://facebook.github.io/watchman/docs/troubleshooting.html#poison-inotify-add-watch
btw, I am on ubuntu, not mac.
if anyone got a quick solution, please comment here.

posted it on watchman's repo - https://github.com/facebook/watchman/issues/163

echo 256 | sudo tee -a /proc/sys/fs/inotify/max_user_instances
echo 32768 | sudo tee -a /proc/sys/fs/inotify/max_queued_events
echo 65536 | sudo tee -a /proc/sys/fs/inotify/max_user_watches
watchman shutdown-server

the last command solved it.

The same problem.Thanks for your sharing oren!

+1. Thanks for your sharing.

@oren It is work for me ,Thanks!

@oren Thanks!

Many Thanks! @oren

Thanks!! work for me :+1:

For Info: I Reboot my Mashine at now it works

Thanks...!!

Thanks @oren !

@oren dude I dont know how to thank you, but you are a genius!

Thank you @oren.

many thanks @oren

I tried orens way, got rid of the error, but then when i tried runnin the app, i got a scary red screen with  "Could not get BatchedBridge, make sure your bundle is packaged correctly" written on it. Help

@dennisobel use "react-native start" in the root of your project and then (in other terminal) "react-native run-android" or "run-ios"

Thanks for reply,
I've made 3 new tests and I got this result:

Thanks @oren

Thanks @oren

Does anyone have a permanent solution for this?,
I did use the following command and it works fine, but every time i restart my pc it resets the values.
I have tried editing the maximum queued file itself but i again it always resets.
I am running a Ubuntu 16.10.

Thanks @oren

@AndreiCalazans a hack I use is to add echo 256 | sudo tee -a /proc/sys/fs/inotify/max_user_instances echo 32768 | sudo tee -a /proc/sys/fs/inotify/max_queued_events echo 65536 | sudo tee -a /proc/sys/fs/inotify/max_user_watches  to /etc/rc.local prior to exit 0. /etc/rc.local is executed at startup.

Thank you @oren and @viviannysdiaz

Thanks @oren

@AndreiCalazans on Ubuntu 16.04 (not sure about 16.10) fs.inotify.max_user_watches in /etc/sysctl.conf needs to be changed and then run watchman shutdown-server && sudo sysctl -p for a permanent fix.


[google_maps_flutter] arm64 EXCLUDED_ARCHS causes issues on iOS 16 emulator with M1

Details

The google_maps_flutter plugin defines 'EXCLUDED_ARCHS[sdk=iphonesimulator*]' => 'arm64' in its podspec file.
The latest iOS 16 emulator option can't run with Rosetta

the above two are causing performance issues (input is slow to respond, lags, glitches, jank) and cause a funky scroll effect, where scrollviews immediately jump to the bottom when scrolling.
Target Platform: iOS
Target OS version/browser: 16
Devices: any iOS 16 emulator
Related issues
A similar problem is described:

here https://github.com/flutter/flutter/issues/112325
and here https://github.com/flutter/flutter/issues/79641

Hello @mbtodorov. Thanks for raising this issue. I can indeed reproduce this issue, but I do not think this is just related to google maps. This might be a regression of https://github.com/flutter/flutter/issues/79641 since I can reproduce the "scroll jump" behavior with a simple ListView.builder.
cc: @jmagman for insights

Code Sample including google maps implementation and ListView (both are buggy)
import 'package:flutter/material.dart';
import 'package:google_maps_flutter/google_maps_flutter.dart';

void main() {
  runApp(const MyApp());
}

class MyApp extends StatelessWidget {
  const MyApp({super.key});

  @override
  Widget build(BuildContext context) {
    return const MaterialApp(
      // home: HomePage(),
      home: SimpleListView(),
    );
  }
}

class SimpleListView extends StatelessWidget {
  const SimpleListView({super.key});

  @override
  Widget build(BuildContext context) {
    return Scaffold(
      body: ListView.builder(
        itemCount: 100,
        itemBuilder: (context, index) {
          return ListTile(
            title: Text('Item ${index + 1}'),
          );
        },
      ),
    );
  }
}

class HomePage extends StatelessWidget {
  const HomePage({super.key});

  @override
  Widget build(BuildContext context) {
    return Scaffold(
      appBar: AppBar(title: const Text('Google Maps demo')),
      body: const Center(
        child: GoogleMap(
          initialCameraPosition: CameraPosition(
            target: LatLng(37.3967317, -122.1000127),
            zoom: 15,
          ),
        ),
      ),
    );
  }
}

Google Maps video
https://user-images.githubusercontent.com/50555895/215983376-70836f65-367a-44b8-a247-71b239858fbf.mov

ListView video
https://user-images.githubusercontent.com/50555895/215983527-7337dd01-8f57-4d17-b233-f981911ee0e8.mov

flutter doctor -v (Master)
[!] Flutter (Channel master, 3.8.0-1.0.pre.4, on macOS 13.1 22C65 darwin-arm64, locale en-US)
    • Flutter version 3.8.0-1.0.pre.4 on channel master at /Users/nabeelparkar/fvm/versions/master
    ! Warning: `dart` on your path resolves to /opt/homebrew/Cellar/dart/2.18.6/libexec/bin/dart, which is not inside your current Flutter SDK checkout at /Users/nabeelparkar/fvm/versions/master. Consider adding /Users/nabeelparkar/fvm/versions/master/bin to the front of your path.
    • Upstream repository https://github.com/flutter/flutter.git
    • Framework revision a752c2f154 (35 minutes ago), 2023-02-01 00:41:16 -0500
    • Engine revision 1703a39662
    • Dart version 3.0.0 (build 3.0.0-187.0.dev)
    • DevTools version 2.20.1
    • If those were intentional, you can disregard the above warnings; however it is recommended to use "git" directly to perform update checks and upgrades.

[✓] Android toolchain - develop for Android devices (Android SDK version 33.0.0)
    • Android SDK at /Users/nabeelparkar/Library/Android/sdk/
    • Platform android-33, build-tools 33.0.0
    • ANDROID_SDK_ROOT = /Users/nabeelparkar/Library/Android/sdk/
    • Java binary at: /Users/nabeelparkar/Library/Application Support/JetBrains/Toolbox/apps/AndroidStudio/ch-0/213.7172.25.2113.9123335/Android Studio.app/Contents/jre/Contents/Home/bin/java
    • Java version OpenJDK Runtime Environment (build 11.0.13+0-b1751.21-8125866)
    • All Android licenses accepted.

[✓] Xcode - develop for iOS and macOS (Xcode 14.2)
    • Xcode at /Applications/Xcode.app/Contents/Developer
    • Build 14C18
    • CocoaPods version 1.11.3

[✓] Chrome - develop for the web
    • CHROME_EXECUTABLE = /Applications/Brave Browser.app/Contents/MacOS/Brave Browser

[✓] Android Studio (version 2021.3)
    • Android Studio at /Users/nabeelparkar/Library/Application Support/JetBrains/Toolbox/apps/AndroidStudio/ch-0/213.7172.25.2113.9123335/Android Studio.app/Contents
    • Flutter plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/9212-flutter
    • Dart plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/6351-dart
    • Java version OpenJDK Runtime Environment (build 11.0.13+0-b1751.21-8125866)

[!] Android Studio (version 2022.1)
    • Android Studio at /Users/nabeelparkar/Library/Application Support/JetBrains/Toolbox/apps/AndroidStudio/ch-0/221.6008.13.2211.9477386/Android Studio.app/Contents
    • Flutter plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/9212-flutter
    • Dart plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/6351-dart
    ✗ Unable to find bundled Java version.
    • Try updating or re-installing Android Studio.

[✓] VS Code (version 1.74.3)
    • VS Code at /Applications/Visual Studio Code.app/Contents
    • Flutter extension version 3.58.0

[✓] Connected device (2 available)
    • macOS (desktop) • macos  • darwin-arm64   • macOS 13.1 22C65 darwin-arm64
    • Chrome (web)    • chrome • web-javascript • Brave Browser <IP_ADDRESS>

[✓] HTTP Host Availability
    • All required HTTP hosts are available

! Doctor found issues in 2 categories.

Upon further investigation, this seems like a duplicate of https://github.com/flutter/flutter/issues/112244. This would be fixed by https://github.com/flutter/flutter/issues/94491. Thank you


DeepSleep power consumption

Can we have detailed infos on the power consumption of the product? (working / deepsleep)

Working current: refer to https://github.com/lyusupov/SoftRF/wiki/Badge-Edition#battery-life
Sleep current: about 0.25mA

Thanks for your answer. I was expecting a few microA, according to datasheets of components. Do you have plan to reduce the consumption in deep-sleep?

Hi, There are no plans, and its sleep power consumption is already very low

Thanks for your answer. I was expecting a few microA, according to datasheets of components. Do you have plan to reduce the consumption in deep-sleep?

@FabTangi
Hello, the latest low-power example has been updated. You can try using the example Sleep_Display to reduce the power consumption of your onboard board.


Permission denied

Hi guys
I'm using java lambda layer (https://github.com/shelfio/java-lambda-layer) that uses tika to extract text (Python runtime 3.9, tika server standard 2.6) and got this error

os.environ['TIKA_JAVA'] = '/opt/lib/jvm/java-1.8.0-openjdk-<IP_ADDRESS>.b10-0.lambda2.0.1.x86_64/jre/bin'

"errorMessage": "[Errno 13] Permission denied: '/opt/lib/jvm/java-1.8.0-openjdk-<IP_ADDRESS>.b10-0.lambda2.0.1.x86_64/jre/bin'",
"errorType": "PermissionError",

How can I resolve this?
Thank

I think you need to ensure that you run the command java from your computer or reinstall it? Thanks.


feat(icons): [STLX-12690] Add logos for non-native tokens

Add logos for non-native tokens BOX, IQ, and CHEX.
Jira ticket:
https://bitgoinc.atlassian.net/browse/STLX-12690

I've changed the base repository, I've created this new PR with this changes https://github.com/BitGo/cryptocurrency-icons/pull/5


classic instead of confined

The snap is currently set to confinement: devmode which later will probably be promoted to strict. This will prevent executing other programs from inside sway. I would propose to set the confinement to classic to allow running as a full desktop and executing other programs.

Hi Christian,
my plan was to create a classic and a strict snap.
I'm just cleaning up the git-tree and will publish it soon.
In futher version of snapd, the classic confinment will be disabled. They are working on that.
But it will than be possible to allow access to other application.

In futher version of snapd, the classic confinment will be disabled.

Uh, do you mean that it will be disabled in your snap or the feature will be removed from the snap package format? Do you have a reference to this?

I heard it in a conversation on irc. Until then I will support both, classic and strict.
I think classic mode will be still there for the next years.

@christianrauch
What are you doing with sway ?
Would it be okay, if sway is strict, but able to launch other applications in classic-mode ?
What features are you using in "swaybar" ? Should it be "classic" or is it enougt to read network, battery, cpu, and so on ?
I asked, because on snapstore it is now difficult to publish classic snaps.

I initially wanted to use a sway snap to test Wayland clients, but I am also interested to use it as a desktop to replace GNOME etc. For the first case, a confined environment is fine, but for full desktop usage, I don't see how confinement is going to work.
The confined egmde snap  adds client apps (neverball, stellarium, kodi) to the snap to demonstrate the use, but I don't think this is a longterm solution to be able to provide a desktop environment inside a snap.

interesting.
Just launched a request for "sway-classic"


Selectables remove

Required for uktrade/data-hub-leeloo#214

We should try and remember to rebase changes on top of develop to avoid multiple merge commits


Fixed logger name

file as a logger name doesn't allow to configure envparse logging externally.

I hit the issue of not being able to override the logger level due to __file__ being used for the logger name. @rconradharris is this something that is going to get merged soon?


An error occurred when creating and mounting a 3T disk. The device 0 is invalid

ISSUE TYPE

Bug Report
Improvement Request
Enhancement Request
Feature Idea
Documentation Report
Other

COMPONENT NAME

api

CLOUDSTACK VERSION

4.17

CONFIGURATION

OS / ENVIRONMENT

SUMMARY

STEPS TO REPRODUCE

EXPECTED RESULTS

An error occurred when creating and mounting a 3T disk. The device 0 is invalid

ACTUAL RESULTS

@itgyn can you please share more details such as hypervisor, error from management and agent (if applicable) logs, etc

@itgyn can you please share more details such as hypervisor, error from management and agent (if applicable) logs, etc
Mount disks larger than 3T on cloudstack. Vmware6.7 error message for Virtualization: failed to create volume: Java lang.runtimeexception: invalid configuration for device '0'.

Hi @itgyn, I've tried to create and attach a 3TB disk to a VM and is successful. Can you please try it again with a new VM and check if the issue is consistent across all VMs and disks.
Can you also check if this is something related to this article https://kb.vmware.com/s/article/77134. I've tried both with 6.7u3 and 7.0 versions, it worked fine.

Thank you very much. My version of wmware is a little low. Mine is 6.5

Is this reproducible with other VMs?

Yes, it's OK to expand the data disk by 3T, but as long as the disk is attached to the virtual machine for the first time, it will report that device 0 is invalid

I've tried with 6.5 version too and it worked fine. Can you try with some other setup or upgrade your Vmware version and check once.
I'm assuming you have already checked what I've asked,

You could reproduce the issue with any VM.
You are observing only with 3TB disks, lower size disks are attaching fine.

Please check various combinations of tests please provide some pinpointers to the issue, since I could not reproduce the issue.

Do you operate through cloudstack?

Yes, creating VM, disks, attach, detach operations I'm trying from CloudStack.
Aren't you trying these from CloudStack ?

Hi @itgyn yes, we're the contributors (committers and PMCs) of the project. Could you check if this relates to your issue https://github.com/apache/cloudstack/issues/6492
We're assuming this is a data disk that you've created and attached, @harikrishna-patnala did you try the same (i.e. create 3T datadisk and attach to a VM?).

Thank you very much. Let me verify it here

@itgyn I'm closing this issue as I could not reproduce it. Please feel free to reopen if you still face the issue with CloudStack.


make:view fails with error "File does not exists", view.stub seems to be missing

After quite some work to get AdminLTE to work on windows (llum not working as it should) i discovered an issue with the php artisan make:view command. Whatever view i try to create, i get the error "File does not exists". Tracing back in the code it requires a file "/stubs/view.stub", but it appears to be missing form the package.

Hi @Fluxlicious
About llum not working as it should please could you give me more info or please open and issue:
https://github.com/acacha/llum/issues/
About the issue I don't have any problems with a fresh installation of this package. The file you mention already exists in package:
https://github.com/acacha/adminlte-laravel/tree/master/src/Console/stubs
Please could you try with a fresh package? If you are using and old installation please manually update your project.

Oh i was looking in the wrong stubs dir. The view file is actually there, but i traced down the problem to the Filesystem class.
I'm not sure if this is a windows only issue, but the Filesystem->getPath() method does not make sense.
    public function get($file)
    {
        echo $file . "\n"; // result: D:\Www\laravel\fluxticket\vendor\acacha\admin-lte-template-laravel\src\Console/stubs/view.stub
        $path = $this->getPath($file);
        echo $path;        // result: //D:\Www\laravel\fluxticket\vendor\acacha\admin-lte-template-laravel\src\Console/stubs/view.stub

        if (! file_exists($path)) {
            throw new FileDoesNotExists;
        }

        return file_get_contents($path);
    }

Notice the // that are added because of the getPath() function. I can't seem to figure out why the getPath is even needed, just use the $file as it's passed in the parameters.

Ok I see the problem I don't know Windows does not support // and I don't have any windows to use to test it. As soon as I can (or maybe someone could propose a PR) I will try to do a multiplatform version.

Then someone already has a truly proven answer to this problem
$ php artisan make: view about
File does not exist
I just do not want to alter the code without knowing, I've been a week with this problem and I have not been able to solve it

I am working with
-Windowa 10 Pro
-Xamp v3.2.2
-PHP Version 7.0.5
-laravel 5.4
Adminlte (github)
-composer 1.4.2
Your answer would be very helpful to me, thank you

Found the solution for windows users!
Open Filesystem.php and replace the getpath() function with the following:
protected function getPath($file)
{
if(strtoupper(substr(PHP_OS, 0,3)) == "WIN")
return $file;
else
return $this->root . '/' . $file;
}

The function now checks whether the OS is windows or something else and provides with appropriate path information. In case of windows it just forwards the file which contains the full path, in case of linux, the function will add "//" as prefix to the file path.

Thanks Nircode (y)

Thanks @nircode if you wish you could propose a Pull Request!

Close this issue and open a new one to add possible PR to source code.