Unable to build Linux kernel module for v4.15

I managed to build sofa on Ubuntu Linux 18.04-LTS which is based on Linux kernel version 4.15. However, I failed to build Linux kernel module. Here are the instructions to reproduce:
cd src
sh build_sofa.sh

The build system complained as following:
sofa/src/storage_core/lfsm/common/mem_manager.c: In function 'init_memory_manager':
sofa/src/storage_core/lfsm/common/mem_manager.c:42:10: error: implicit declaration of function 'bioset_init'; did you mean 'bio_init'? [-Werror=implicit-function-declaration]
          bioset_init(&memMgr.bioset, bio_pool_size, 0,
          ^~~~~~~~~~~
          bio_init
sofa/src/storage_core/lfsm/common/mem_manager.c: In function 'rel_memory_manager':
sofa/src/storage_core/lfsm/common/mem_manager.c:115:5: error: implicit declaration of function 'bioset_exit'; did you mean 'bioset_free'? [-Werror=implicit-function-declaration]
     bioset_exit(&memMgr.bioset);
     ^~~~~~~~~~~
     bioset_free
cc1: some warnings being treated as errors

ITRI-SOFA is developed and compiled on Centos 8 which is based on kernel 4.18. We did not run SOFA on Ubuntu. In the future we will support fedora and ubuntu platforms. On Fedora 29, we have verified that it is executable.

Linux 4.18 replaced bioset_{create,free} with bioset_{init,exit}.
Check this patch for details: https://github.com/crawfxrd/dattobd/commit/c9e1e0117e8c1bd51a3cfe88701cb86573f30df9

Thanks for your suggestion, we will fix this problem in the next version


[Bug]: Listener Device ID Unassigned

What happened?
Hey all,
After flashing my M5Atom with the pre-built listener image (v3.0.1) and configuring it, it connects to both the wifi network and Tally Arbiter, but it does not get a Device ID, doesn't show up as a listener in TallyArbiter and doesn't respond to input changes on my ATEM. An M5StickC-plus that runs some older build-it-yourself Arduino code works without any problems (don't know the version, downloaded on november 6th I think).
Any help would be greatly appreciated.
Version
2.0.16
Distribution
Desktop
OS
MacOS
What browsers are you seeing the problem on?
No response
If applicable, What Listener Clients are You Using?
No response
TallyArbiter configuration
No response
Relevant log output
[22:15:12]*wm:[1] STA IP Address: <IP_ADDRESS>
[22:15:12]connected...yay :)
[22:15:14]Setting TallyArbiter host as <IP_ADDRESS>
[22:15:14]Setting TallyArbiter port as 4455
[22:15:14]---------------------------------
[22:15:14]Connecting to Tally Arbiter host: <IP_ADDRESS>
[22:15:14]---------------------------------
[22:15:30]---------------------------------
[22:15:30]Connected to Tally Arbiter host: <IP_ADDRESS>
[22:15:30]deviceObj = {"deviceId": "unassigned", "listenerType": "m5Atom-153742843654548", "canBeReassigned": true, "canBeFlashed": true, "supportsChat": false }
[22:15:30]DeviceId = unassigned
[22:15:30]["listenerclient_connect",{"deviceId": "unassigned", "listenerType": "m5Atom-153742843654548", "canBeReassigned": true, "canBeFlashed": true, "supportsChat": false }]
[22:15:30]charDeviceObj = {"deviceId": "unassigned", "listenerType": "m5Atom-153742843654548", "canBeReassigned": true, "canBeFlashed": true, "supportsChat": false }
[22:15:30]---------------------------------
[22:15:51]
[22:15:51]---------------------------------
[22:15:51]Button Pressed.
[22:15:51]M5Atom IP Address:<PHONE_NUMBER>
[22:15:51]Tally Arbiter Server: <IP_ADDRESS>
[22:15:51]Device ID: unassigned
[22:15:51]Device Name: unassigned
[22:15:51]Cam Number: 2
[22:15:51]---------------------------------

Error stacktrace (if applicable)
No response

Which Tally Arbiter server version are you using?

I'm running 2.0.16

New listener client firmware version is incompatible with new version. Please update your server to the latest beta (download it from releases) or downgrade your listener until we release v3.0.0 stable.

That... Makes an awful lot of sense. Thank you for your quick response!

@MatteoGheza I'm having the same problem, using the m5stickc-listener listener provided as part of the 2.0.16 version.
As the 3.0.0 and 3.0.1 server does not work on my Windows Laptop, I will try a listener downgrade. Can you be more specific on which commit for the listener you expect to work for the 2.0.16 server?

I tried upgrading to the beta version of the server 3.0.1 on Windows 10. Unfortunately the application has an error and doesn't work...
How can i find out which version of the client runs with the server 2.0.16?

I tried upgrading to the beta version of the server 3.0.1 on Windows 10. Unfortunately the application has an error and doesn't work... How can i find out which version of the client runs with the server 2.0.16?

@edbneutron The problem raised in this thread has been addressed and the thread closed. Please create a new thread with your problem.


feat: adding failure comment to PR when name not valid

:tada: This PR is included in version 1.0.0-dev.3 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


With Confluent Cloud, when selecting a topic, the corresponding schema registry should be selected.

Sign into Confluent Cloud.
Observe "Schemas" section shows "Select a schema registry"
Navigate to an environment, and select a topic.
Observe "Schemas" section.

Actual: Schema registry remains unselected.
Expected: The corresponding schema registry in the same environment of the selected topic should be selected. (Basically SR selection should be coupled to topic selection)

@derek1ee this is currently intended behavior to not explicitly link the two views to provide flexibility across connections/environments, but I'm interested in your thoughts here: if you're working with a schema listing in one (CCloud) environment and want to look at messages in another environment, what is the expected behavior? Switch away from the currently-focused Schema Registry in the Schemas view? Or is this only when there is no currently selected Schema Registry in the Schemas view?

if you're working with a schema listing in one (CCloud) environment and want to look at messages in another environment, what is the expected behavior?

I can see that allowing users to "override / change" the SR after we automatically select one based on topic selection. But I'm also curious what's the use case / whether this is something people actually need to do (e.g. why wouldn't you just upload the schema to that other environment?)

I'm also curious what's the use case / whether this is something people actually need to do (e.g. why wouldn't you just upload the schema to that other environment?)
My main concern is disrupting the state a user may have been in after initially selecting a Schema Registry and pulling them into another Schema Registry that they may not have wanted focused because they clicked on a Kafka cluster. I think we could offer a dedicated "focus Kafka cluster and associated Schema Registry" / "focus environment" type action, or maybe offer a setting that users can enable to sync the focused Kafka cluster with the focused Schema Registry (if there is one), but doing it automatically may be a bit too aggressive.

I find myself "double selecting" almost every single time: select the cluster, then select the SR right under it. So I feel defaulting to "couple schema registry to topic selection" should be the default behavior, and allow user to opt out (e.g. configurable via the overflow menu for SR/in settings.


chore: add JinaReaderConnector to README

Related Issues

part of #663

Proposed Changes:
We added this new component in #1150, but I forgot to add it to README, so I'm adding it.
Checklist

I have read the contributors guidelines and the code of conduct
I have updated the related issue with new insights and changes
I added unit tests and updated the docstrings
I've used one of the conventional commit types for my PR title: fix:, feat:, build:, chore:, ci:, docs:, style:, refactor:, perf:, test:.

It is a whole new type of component in integrations, do we need to add it somewhere else as well @dfokina ?

Thanks, I will create an issue for documenting the new component.
The API reference is already published: https://docs.haystack.deepset.ai/reference/integrations-jina#module-haystack_integrationscomponentsconnectorsjinareader


Bar Graph: Hide/Show Labels automatically if enough space when zooming

What problem does this feature solve?
I have a bar graph (screenshots below) with few big entries an many small entries. It is not possible to display a label for every entry. There would be too many labels overlapping.
My current solution is to use label: formatter: p => p.value[1] > minLabelValue ? p.value[1] : '' in order to hide labels for values smaller than my defined minLabelValue.
However, when zooming in, those entries will of course not get displayed.
Users should only see relevant labels (without beeing distracted from man overlapping tiny ones). But when zooming in, these labels (as there is enough room) should appear.
What does the proposed API look like?
an option like:
barMinHeightLabel: 10
could only show the label if there is enough room (at least 10 pixel) for it.
or even better
label: {
hideIfNotEnoughSpace: true
}

When not zoomed, it looks like intended.

But on zoom, label values should appear as they fit into the graph.

Thanks for the advice @zevero . We are planning to add automatic label layout to solve issues like this.

#11497


chore: remove some dead code

Types

[x] 💄 Code Style Changes

Background or solution
Changelog

remove deprecated monacoLoaded logic

Codecov Report

Merging #659 (631e117) into main (6e57e9d) will decrease coverage by 0.00%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##             main     #659      +/-   ##
==========================================
- Coverage   58.98%   58.98%   -0.01%
==========================================
  Files        1209     1209
  Lines       74645    74637       -8
  Branches    15464    15465       +1
==========================================
- Hits        44028    44022       -6
+ Misses      27915    27913       -2
  Partials     2702     2702

Impacted Files
Coverage Δ

...owser/monaco-contrib/tokenizer/textmate.service.ts
43.16% <ø> (-0.16%)
:arrow_down:

...ion/src/browser/vscode/api/main.thread.language.ts
63.14% <ø> (ø)

packages/monaco/src/browser/monaco.service.ts
80.00% <ø> (-2.76%)
:arrow_down:

packages/core-browser/src/monaco/index.ts
100.00% <100.00%> (ø)

packages/core-common/src/localize.ts
98.55% <0.00%> (+0.11%)
:arrow_up:

packages/core-common/src/node/port.ts
46.96% <0.00%> (+3.03%)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 6e57e9d...631e117. Read the comment docs.


Fixed example in README

👍

Coverage remained the same at 81.352% when pulling 5fe863f12a65c9db14ebf961a4d5fbe2c8c12705 on hotfix/readme into d28a327300e706472e211bb7ad9838eb16072649 on master.


BUG: Validating When Editing Admins

Describe the bug
Error message appears under the Username field stating that the "Name + Username must contain letters and numbers only"  after I added letters only to the Last Name field
To Reproduce
Steps to reproduce the behavior:

Go to 'Admins'
Click on 'the pencil to edit an admin'
Click on 'the Last Name field to edit an admins name and add some letters'
See error

Expected behavior
Admin's last name to be changed
Screenshots

Desktop (please complete the following information):

OS: [Manjaro]
Browser [Chromium]
Version [Version 129.0.6668.70 (Official Build) Arch Linux (64-bit)]

I wasn't able to reproduce this exact issue but when I picked the task the update user handler wasn't working correctly.


Adding attributes conditionally

For a checkbox input, you provide an empty attribute, checked, if the checkbox is selected. I could do this with javascript, but it would be great if it worked with Ractive.
<input type="checkbox" value="checked" {{#truestatement}}checked{{/trustatement}} id="full" name="full"/>
This might be one of the only cases where this functionality is necessary, but it would be useful nonetheless.

I want to render element ID only if an ID was supplied in the data model (copied from the supplied props object), and I go like this (can be executed in the mentioned tutorial):
template:

Hello world!

code:
function create(props) {
  return new Ractive({
    template: template,
    data: {
      id: props.id
    }
  });
}
var props = {}; // the caller decides whether to supply an id or not
create(props).render(output);

The following is rendered:
Hello world!
, but I would like to have:
Hello world!

@xorcus You can accomplish that by wrapping the attribute with an if statement:

Hello world!

PS: You posted in a very, very old thread. It's better for organization and clarity for everyone if you create a new issue for your questions/concerns.


Feature Request: Support hardware tokens

Adding support for hardware tokens would make MFA less intrusive.

A PR is working its way through the pipeline for improved support for hardware tokens storing private keys and certs. Once that is merged, we can look at adding support to this ZDE as an alternative to storing in the OS Keychain.  We don't have support in ziti-sdk-c for MFA via hardware token.  cc: @ekoby


Document resolver = "2" effective requirement for rust-gpu

Add official documentation that one should have either
[workspace.package]
edition = "2021"

or
[workspace]
resolver = "2"

in their root cargo.toml to make sure dependencies are resolved correctly and that crates compiled with different features on native and spirv don't get merged into one feature set.
An example can be num-traits which compiles with features default,std on native and libm on spirv target.
For a practical example see the issue below:
https://github.com/EmbarkStudios/rust-gpu/issues/986

Official documentation: https://doc.rust-lang.org/cargo/reference/resolver.html#resolver-versions
I'll also add that if you have both [workspace] and [package] in your root Cargo.tool (i.e. the workspace root is not a "virtual manifest"), then edition = "2021" inside [package] should "just work".
So there's 3 avenues to getting the resolver changes, but sadly Cargo doesn't warn users when they have e.g. virtual manifests with edition = "2021" everywhere but still Rust 2015 behavior.

I've previously mentioned that
[workspace.package]
edition = "2021"

is enough, but that is sadly wrong. In this documentation it is stated that resolver="2" is the only way to specify it in a virtual workspace:

The resolver is a global setting for a workspace, and the setting is ignored in dependencies. The setting is only honored for the top-level package of the workspace. If you are using a virtual workspace, you will still need to explicitly set the resolver field in the [workspace] definition if you want to opt-in to the new resolver.

https://doc.rust-lang.org/edition-guide/rust-2021/default-cargo-resolver.html#details


⚠ Bofrost.at has degraded performance

In a439b24, Bofrost.at (https://www.bofrost.at) experienced degraded performance:

HTTP code: 200
Response time: 1424 ms

Resolved: Bofrost.at performance has improved in 192c42c.


Add ssh keys endpoint support

[Resolves phadej/github#362]

Implements an interface for GitHub's SSH public key API
Adds tests for the read-only interface
Does not add tests for SSH key creation/deletion to avoid polluting anyone's GH account
Adds relevant samples

I'm not sure why tests fail?

Rebased in https://github.com/phadej/github/pull/375, tests probably fail because past state of master, not due this PR.
Thanks for your contribution!


Improvement: set the namespace from the request on the object, if none is set

…e is present

Codecov Report

Merging #9 (f06754c) into master (5788d88) will decrease coverage by 0.10%.
The diff coverage is 81.81%.

@@            Coverage Diff             @@
##           master       #9      +/-   ##
==========================================
- Coverage   87.67%   87.56%   -0.11%
==========================================
  Files          30       30
  Lines         576      587      +11
==========================================
+ Hits          505      514       +9
- Misses         44       45       +1
- Partials       27       28       +1

Impacted Files
Coverage Δ

pkg/webhook/handler/unmarshal_req_obj.go
83.33% <81.81%> (-0.88%)
:arrow_down:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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skip instruction

References

https://github.com/udem-dlteam/ribbit/blob/0c2b5f2a35f0ce13fd678285760ce698e5e65912/src/rsc.scm#L2219

Closed by #155 and #152.


[viewster] accept https links and fix api_token extraction and extract mp4 video link(fixes #6787)

the problem happen in this issue #6787 because viewster return 404 errors happen for some types of urls(urls without slug) but the extractor actually can handle these types.
so i change the head request to extract the api_auth to get it from the homepage of the site instead of getting it from the url provided by the user so it wont get 404 in the request for api_auth.

Same error for me:
[debug] System config: []
[debug] User config: []
[debug] Command-line args: [u'http://www.viewster.com/serie/1280-18794-000/', u'-F', u'-v']
[debug] Encodings: locale cp1251, fs mbcs, out cp866, pref cp1251
[debug] youtube-dl version 2015.09.09
[debug] Git HEAD: 59234f0
[debug] Python version 2.6.6 - Windows-2003Server-5.2.3790-SP2
[debug] exe versions: avconv 10.6, avprobe 10.6, ffmpeg N-74386-g542562e, ffprobe N-74386-g542562e, rtmpdump 2.4
[debug] Proxy map: {}
[Viewster] 1280-18794-000: Downloading webpage
[Viewster] 1280-18794-000: Downloading entry JSON
[Viewster] 1280-18794-000: Downloading series JSON
ERROR: Unable to download JSON metadata: HTTP Error 404: Not Found (caused by HTTPError()); please report this issue on https://yt-dl.org/bug . Make sure you are using the latest version; see  https://yt-dl.org/update  on how to update. Be sure to call youtube-dl with the --verbose flag and include its complete output.

  File "C:\Dev\git\youtube-dl\master\youtube_dl\extractor\common.py", line 326, in _request_webpage
    return self._downloader.urlopen(url_or_request)
  File "C:\Dev\git\youtube-dl\master\youtube_dl\YoutubeDL.py", line 1865, in urlopen
    return self._opener.open(req, timeout=self._socket_timeout)
  File "C:\python\python266\lib\urllib2.py", line 397, in open
    response = meth(req, response)
  File "C:\python\python266\lib\urllib2.py", line 510, in http_response
    'http', request, response, code, msg, hdrs)
  File "C:\python\python266\lib\urllib2.py", line 435, in error
    return self._call_chain(*args)
  File "C:\python\python266\lib\urllib2.py", line 369, in _call_chain
    result = func(*args)
  File "C:\python\python266\lib\urllib2.py", line 518, in http_error_default
    raise HTTPError(req.get_full_url(), code, msg, hdrs, fp)

i get the same result in the browser it doesn't show 404 error but it doesn't show any episode and it fails in the episodes api request.

the code fix the problem for example for this case:
before:
youtube-dl -F http://www.viewster.com/serie/1152-12103-000/house-of-venus-show-season-2/
[Viewster] 1152-12103-000: Downloading webpage
[Viewster] 1152-12103-000: Downloading entry JSON
[Viewster] 1152-12103-000: Downloading series JSON
[download] Downloading playlist: House of Venus Show - Season 2
[Viewster] playlist House of Venus Show - Season 2: Collected 6 video ids (downloading 6 of them)
[download] Downloading video 1 of 6
[Viewster] 1152-12103-001: Downloading webpage
ERROR: Unable to download webpage: HTTP Error 404: Not Found (caused by HTTPError()); please report this issue on https://yt-dl.org/bug . Make sure you are using the latest version; see  https://yt-dl.org/update  on how to update. Be sure to call youtube-dl with the --verbose flag and include its complete output.

after:
youtube-dl -F http://www.viewster.com/serie/1152-12103-000/house-of-venus-show-season-2/
[Viewster] 1152-12103-000: Downloading webpage
[Viewster] 1152-12103-000: Downloading entry JSON
[Viewster] 1152-12103-000: Downloading series JSON
[download] Downloading playlist: House of Venus Show - Season 2
[Viewster] playlist House of Venus Show - Season 2: Collected 6 video ids (downloading 6 of them)
[download] Downloading video 1 of 6
[Viewster] 1152-12103-001: Downloading webpage
[Viewster] 1152-12103-001: Downloading entry JSON
[Viewster] 1152-12103-001: Downloading application/f4m+xml JSON
[Viewster] 1152-12103-001: Downloading f4m manifest

Then add a test that it fixes and remove fixes #6787 from title.

i still think that this pull request fixes the error in the issue (which happen because youtube-dl get 404 error from the from the head request).
this the part where the error happen for @daphee

[Viewster] 1280-18794-001: Downloading webpage
ERROR: Unable to download webpage: HTTP Error 404: Not Found (caused by HTTPError()); please report this issue on https://yt-dl.org/bug . Make sure you are using the latest version; type  youtube-dl -U  to update. Be sure to call youtube-dl with the --verbose flag and include its complete output.

Cherry-picked in 92085e7099d3607ff512f241454d6f6f4535b05a, thanks.
http://www.viewster.com/serie/1280-18794-000/ fails due to geo restriction.


Tag Jenkins images with ODS version

Right now, Jenkins master and slave images are only tagged with latest, and all Jenkinsfile references point to latest. I think this is fragile, and propose to use a similar approach as we do for the Jenkins shared library: tag with the ODS version.
To be precise:
For a given ODS branch, e.g. 2.0.x, I would set all BuildConfig items to emit tags 2.0.x, and all quickstarter Jenkinsfiles point to that tag, e.g. image: "${dockerRegistry}/cd/jenkins-slave-maven:2.0.x". Also, the Jenkins master should point to that image.
That would allow us to make breaking changes if needed. Also, it allows users to pin a version if a change that ODS deems "non-breaking" actually turns out to be breaking for that user.
If OpenShift supports building multiple tags, I would support to continue tagging with latest additionally, to offer that for users who want to be bleeding edge.
Finally, if we are concerned regarding upgrading, we could offer at least "major version tags", e.g. sth like 2.x.
@rattermeyer @tjaeschke @clemensutschig @stitakis Please comment if that is a direction we want to go in. I propose to introduce it together with ODS 2.0.

I am always in favor for a strict version. Otherwise something miracally stops working, see also #357.
So, clear thumbs up from me.

Cool. Settings this to 2.0.

Adopting patches or even minor versions automatically can break existing consumers.
I strongly agree that this should not be the default way of how things work.
So +1 here.


A first draft of an about page.

@jasongrout A few wording suggestions... Overall, looks good.

@willingc - thanks! I think applied all your fixes.

@jasongrout Looks good to me. I'll let one of the JS folks or you merge. :+1:

Merging, thanks!  I'll cut a release and make the necessary PR against jupyter/notebook tomorrow morning.


refine torchvision examples

Signed-off-by: Xin He<EMAIL_ADDRESS>Type of Change
refine examples with new API

/AzurePipelines run

extension test

retest after fix

retest after bug fix

retest after bug fix


[google_sign_in_web] Ensure not-signed-in users are returned as null.

Description
This change ensures that not signed-in users are returned as null, not as an object with all its properties set to null!
The core plugin assumes that a not-authenticated user is being returned as null from the platform code, but the web implementation is currently returning a null-object (as in the pattern).
WHY did the above prevented creating sign-in popups?
Because of this. The call to signIn is marked as canSkipCall, assuming that there's a non-null user known by the plugin, returning that directly.
In some cases, the user would never be properly cleared (or a null-User-object would be returned from the init/silentSignIn), making the proper signIn call to NOT happen!!
(This PR should fix most of the current open issues with the Google Sign In for web plugin.)
Testing
I have deployed a version of Flutter's Google Sign In example app that uses this version of the plugin here:
https://dit-sign-in-debug.web.app
Related Issues
Fixes:

https://github.com/flutter/flutter/issues/49500
https://github.com/flutter/flutter/issues/52338
https://github.com/flutter/flutter/issues/54106
flutter/flutter#54768
(Maybe others)

Checklist
Before you create this PR confirm that it meets all requirements listed below by checking the relevant checkboxes ([x]). This will ensure a smooth and quick review process.

[x] I read the Contributor Guide and followed the process outlined there for submitting PRs.
[x] My PR includes unit or integration tests for all changed/updated/fixed behaviors (See Contributor Guide).
[x] All existing and new tests are passing.
[x] I updated/added relevant documentation (doc comments with ///).
[x] The analyzer (flutter analyze) does not report any problems on my PR.
[x] I read and followed the Flutter Style Guide.
[x] The title of the PR starts with the name of the plugin surrounded by square brackets, e.g. [shared_preferences]
[x] I updated pubspec.yaml with an appropriate new version according to the pub versioning philosophy.
[x] I updated CHANGELOG.md to add a description of the change.
[x] I signed the CLA.
[x] I am willing to follow-up on review comments in a timely manner.

Breaking Change
Does your PR require plugin users to manually update their apps to accommodate your change?

[x] No, this is not a breaking change.

Just to chime in, flutter/cocoon used to have checks for this specific behavior like user?.id. When some of the race conditions relating to networking were fixed that code was removed. Good to see that behavior was unintentional as the Cocoon project ran into issues because of this too.

@CaseyHillers yep, I came up with this fix after littering the core plugin code with user?.id == null checks :/

This pull request does not fix my problem. The first time opened a pop-up and i clicked my account and it closed. It did not log me in.
Other times doesn't open the pop up at all.

@SwissCheese5 are you seeing a cached version of the site, maybe?

@ditman I cleared cookies and hit ctrl + f5 and shift + f5 for good measure (on chrome). Same results. Pop up appears once, I click my account and it closes. No sign in. And trying again doesn't reveal the pop up.

@mklim added unit tests for the new logic that returns null (the happy-case paths are already covered)

Still can't sign in on ur site, fyi

@SwissCheese5, I am aware. Let me do some issue cleanup by notifying other people of the fix that was pushed, and then I'll get back to your issue. I'll probably start a new one :)

Hello all,
I'm basically experiencing exactly what was reported in https://github.com/flutter/flutter/issues/54106, which this pull is meant to fix. I'd have reopened the issue only it's locked so, thought I'd try commenting on this pull instead of opening another issue.
I'm using:
google_sign_in-4.5.9
google_sign_in_web-0.9.2
I verified that the code in google_sign_in_web-0.9.2/lib/src/utils.dart contains the code changes made as part of this pull. The issue is specific to Safari but happens on both Macs and iPhones. It works very well with all other browsers and OS combos I tried.
I get no exceptions apart from the very same JS error noted on the original issue.
The iOS version also works correctly. It's only Flutter web with Safari.
[✓] Flutter (Channel beta, 1.24.0-10.2.pre, on Linux, locale en_GB.UTF-8)
    • Flutter version 1.24.0-10.2.pre at /opt/flutter
    • Framework revision 022b333a08 (4 months ago), 2020-11-18 11:35:09 -0800
    • Engine revision 07c1eed46b
    • Dart version 2.12.0 (build 2.12.0-29.10.beta)

[✓] Android toolchain - develop for Android devices (Android SDK version 30.0.0)
    • Android SDK at /home/james/Android/Sdk
    • Platform android-30, build-tools 30.0.0
    • Java binary at: /opt/android-studio/jre/bin/java
    • Java version OpenJDK Runtime Environment (build 1.8.0_242-release-1644-b3-6222593)
    • All Android licenses accepted.

[✓] Chrome - develop for the web
    • Chrome at google-chrome

[✓] Android Studio
    • Android Studio at /opt/android-studio
    • 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 1.8.0_242-release-1644-b3-6222593)

[✓] Connected device (3 available)
    • sdk gphone x86 arm (mobile) • emulator-5554 • android-x86    • Android 11 (API 30) (emulator)
    • Web Server (web)            • web-server    • web-javascript • Flutter Tools
    • Chrome (web)                • chrome        • web-javascript • Google Chrome 89.0.4389.90

• No issues found!

Appreciate any help you can provide.
Cheers,


[7.11] [meta] bump helm support to 3.5.2 (#1065)

Backports the following commits to 7.11:

[meta] bump helm support to 3.5.2 (#1065)

jenkins test this please

x


Improve CI/CD experience

This PR ...

fixes branch references for deployments
improves release pull request description

Checklist

Checklist for Contributors

nothing

Codecov Report

Merging #36 (59a884d) into main (02cba51) will not change coverage.
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  Files          72       72
  Lines        1153     1153
=======================================
  Hits         1042     1042
  Misses        111      111

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[ci] speed up CI (hopefully)

Fixes https://github.com/headwaymaps/headway/issues/147
And secondarily:

removed default args
exercised the "guessed country" path
no reason to log in to docker

After a few samples, I landed on Bogotá. Some not very scientific measurements show the build to be a wee bit quicker, which is nice, but the bigger advantage I'm hoping for is to avoid the intermittent timeouts during the WOF import.


refactor: Bot.load_extensions rework

Summary
This PR refactors Bot.load_extensions, improving several aspects and hopefully making common patterns easier to use.
Module discovery now works similar to pkgutil.walk_packages.
Initially I removed utils.search_directory entirely, but then opted to keep it for now and only deprecate it. While the transition to Bot.find_extensions (or even just Bot.load_extensions) should be trivial, having a deprecation period still won't hurt.

TODO:

[ ] make sure to clear up confusions between cwd and sys.path relative to main module

Checklist

[x] If code changes were made, then they have been tested

[x] I have updated the documentation to reflect the changes
[x] I have formatted the code properly by running task lint
[x] I have type-checked the code by running task pyright

[ ] This PR fixes an issue
[x] This PR adds something new (e.g. new method or parameters)
[ ] This PR is a breaking change (e.g. methods or parameters removed/renamed)
[ ] This PR is not a code change (e.g. documentation, README, ...)

Recently I've realized there are few ways of passing stuff around that doesn't involve slapping said stuff as bot attribute.
I could see a system where apart from accepting the client/bot instance in extensions' setup function, users could define extra arguments for the function of arbitrary type, which would be passed the relevant objects from the call to .load_extensions (probably as *args). Thoughts?

Recently I've realized there are few ways of passing stuff around that doesn't involve slapping said stuff as bot attribute. I could see a system where apart from accepting the client/bot instance in extensions' setup function, users could define extra arguments for the function of arbitrary type, which would be passed the relevant objects from the call to .load_extensions (probably as *args). I reckon this would go into a separate PR but I am mentioning this here as it'd likely depend on this PR.

That would be useful, yeah.
I'm sure people have different ideas for this, so it would warrant some more discussion about the specific design and to make sure common use cases are supported:

pass arguments as dict or **kwargs to setup?

perhaps even parse the signature to only pass the declared subset of kwargs?

how would it work with load_extensions, where the modules are not necessarily known ahead of time, and one may want to pass different arguments to different extensions?
...


Reduce graph size through writing indexes directly into graph for map_blocks

[x] Closes #8409
[x] Tests added

When looking at then map_blocks variant of the benchmark here, I noticed that we had a 30 MiB graph for the medium variant. 10MiB of those were just the repeated adding of the PandasIndexes as an argument for map_blocks. Writing them directly to the graph will de-duplicate the value, and thus only have this object once instead of many many times. We can then reference the key for the function arguments.
The tokenise adds some overhead, so there is a drawback of this.
Happy to open an issue if required
Is this something that you all would consider merging?
cc @dcherian

Is this something that you all would consider merging?

Yes. This would extend what was done in https://github.com/pydata/xarray/pull/8412.
I think I initially chose this approach to make the graph absolutely embarrassingly parallel.
Can you add a test or confirm that dask has a test that makes sure the ordering scheduling is "nice" for this kind of case (widely duplicated dependency)?

Can you add a test to dask or confirm that dask has a test that makes sure the ordering/scheduling is "nice" for this kind of case (widely duplicated dependency)?

This is the same pattern as we have with the open_dataset tasks and in the new dask array take implementation, we have existing tests covering these 2 patterns already

Ya this pattern used to suck, so I avoided it. But good to know it's fixed. Thanks for the PR!

TLDR is: If your task does not have a callable, it will be ignored during ordering


Put options for bulk_save into a hash

please code review and feedback.

5 years later, this is now in master, ready for 2.0.0!


Making new scripts should not require Golden membership

I have checked the following:

[X] I use the newest version of bruno.
[X] I've searched existing issues and found nothing related to my issue.

Describe the bug
When right clicking a folder and selecting New script, a payment pop-up shows up. But the documentation does not claim for scripts to be a payed feature.

.bru file to reproduce the bug
No response
Screenshots/Live demo link
https://github.com/usebruno/bruno/assets/3716335/68a2269a-4f21-47ef-b3a5-8065d1892f82

The paid feature here is the ability to edit the .js script in Bruno. But you can edit it in your own IDE, and require this script in pre/post script or tests without a golden license

This isn't mentioned in the docs you're right.
You can require a script placed at the root of your collection and require it this way :
const testScript = require('./script.js')

You could also require a script that is nested inside folders in your collection but you would have to specify, require assumes you start at your collection's root.


Add new SessionMgmt test verifying error thrown when attempting two consecutive reservations

[x] This contribution adheres to CONTRIBUTING.md.

What does this Pull Request accomplish?
Adds new SessionMgmt test verifying error thrown when attempting two consecutive reservations.
Why should this Pull Request be merged?
Reservation is a pivotal aspect of the Session Management API, and users are reasonably prone to exercise the API in the same way as is exercised in this new test.  Presence of the test should help ensure that this reservation behavior of the Session Management Service (and its usage from LV clients) is as expected and does not undergo regression.
What testing has been done?

Ran test by-hand; passes.
Ran test by-hand without having started the discovery service.  Test fails as expected with helpful output.
Ran test by-hand in the context of the full set of Tests.lst.  Test succeeds along with the rest.
Test runs as part of the action invoked by this PR.

Test VI's diagram:

Unseen cases all report false for pass along with an explanation for the failure into result:


Bootstrap + AngualarJS form validation +  angular-recaptcha

the Bootstrap + AngualarJS form validation +  angular-recaptcha is failing and its very unclear what is the cause, would be extremely helpful with some examples

the form validation fails somehow and does not seem to be able to ignore

You can move the recaptcha element outside of your form if you don't want the form to be marked as invalid when the recaptcha is not "checked".  Right now there is not an easy way to opt out of the form validation. Perhaps a change should be made to utilize the required attribute to opt in or something else to opt out.

it would look very awkard to have a form with this design, have not even checked what other dependencies there are...  especially with backend validation and formatting

If recaptcha is inside your form will raise a error if it is not checked therefore your form will have error

And if is checked and the rest of your form is valid, you can submit the form

That is correct. As stated before, there is no easy way to opt out of that feature; which I believe is what @Webinator2129 is needing/wanting.

I see Failed validation but why i don't know.

Posting your code would help track it down, but it looks like you are not sending the captcha response to the server correctly and the server is returning an error.

When i try usage.html i see too same failed validation.you can look usage.html file.

So.. the part that say:
 /**
                     * SERVER SIDE VALIDATION
                     *
                     * You need to implement your server side validation here.
                     * Send the reCaptcha response to the server and use some of the server side APIs to validate it
                     * See https://developers.google.com/recaptcha/docs/verify
                     */

Working as intended.

Thank you i will try .

Actually, the form "$error.required" still there, it will block the form validate when we set "requred='false'" to the recaptcha:
<div vc-recaptcha key="xxxx" requred="false"></div>

Who can help me figure out how to fix it? thanks so much.


mkdir if it does not exist

Coverage remained the same at 51.196% when pulling e4bf4af9baf893b7da26bcac6230f90372ec584b on ywk253100:161117_prepare into c221ce7b49096c671b9d468f5970d1520526dacf on vmware:dev.

LGTM!


Credential helpers

Previous PR seems to be stalled, here is the same code with the if condition fix to invoke credentials helper if no credentials were found, plus merged with current master.
This functionality is tested on Docker-for-Mac and works fine. Unfortunately I am not able to test it on Windows, but it would be awesome if this was included in next release (as per "release early, release often") and maybe the Windows fix will arrive later when someone will have a chance to test/fix it?
See https://github.com/testcontainers/testcontainers-java/pull/647 for previous discussions.

Ok, didn't expect it to fail the build, sorry. Working on it.

@TheIndifferent thanks - work isn't stalled per se, but I'm very busy 😄.
I'm very grateful for your input on this, and will close my original PR.

Ok, so quick update: the assumption about incorrect logic there is completely wrong. I am testing with gcr.io at the moment, it behaves little differently than expected, so I will try to add one more unit test and make everything work.

Please see the latest commit, had to reorganize the code a little bit, but now tested it with gcloud docker --authorize-only and with empty auth section but with helper present.

Cannot really understand why Travis build is failing, does not seem to be related. Could someone please take a look and either rebuild or point me to the actual error to fix?

@TheIndifferent could be related to #731

@TheIndifferent err, no, it's actually javadoc task (you can also run it locally)

@bsideup thank you for the pointer, fixed it, it passes now. Could you please take a look at current version of RegistryAuthLocator if it looks sane?

@rnorth got it, I will address the comment this weekend, sorry for the delay.

I have a moment now - I'll update this.

@rnorth thank you for picking this up and merging! Can't wait for next release to try it out for real :)

Released in 1.8.1! 🎉
Thanks for your work on this, @TheIndifferent!


feat(i18n): handle new v8 permissions

While we don't support Discord v8 yet, it's worth it to support the new permissions ahead of time, so when we upgrade, we have one less thing to take care of.

I don't see the permissions for stage channels? There's 2 new ones for that.

I don't see the permissions for stage channels? There's 2 new ones for that.

The new permissions are REQUEST_TO_SPEAK and USE_APPLICATION_COMMANDS, both of which are new from Discord v8, this PR implements both of them.

I don't see the permissions for stage channels? There's 2 new ones for that.

The new permissions are REQUEST_TO_SPEAK (exclusive to stage channels) and USE_APPLICATION_COMMANDS (slash commands).

so chop chop and add those too

I don't see the permissions for stage channels? There's 2 new ones for that.

The new permissions are REQUEST_TO_SPEAK (exclusive to stage channels) and USE_APPLICATION_COMMANDS (slash commands).

so chop chop and add those too

Those were added with this PR, that's why there are 4 new lines.


More graceful ErrOffsetOutOfRange handling

Go version: 1.14.2
Burrow version: github.com/linkedin/Burrow v1.3.4-0.20200506150011-4ce194fea01a
We have lately been seeing (seemingly random) ErrOffsetOutOfRange errors for two specific partitions of the __consumer_offsets topic and the internal Burrow consumer. This has started happening after upgrading our cluster to Kafka version 2.4.
We have not found the reason for this, and it may be related to our cluster setup. But the error, ErrOffsetOutOfRange, causes a nil-pointer in Burrow after the error is logged.
{"level":"ERROR","@timestamp":"2020-05-27T08:14:04.090Z","caller":"runtime/asm_amd64.s:1373","message":"consume error","@version":"1","type":"module","coordinator":"consumer","class":"kafka","name":"prod","topic":"__consumer_offsets","partition":9,"error":"kafka server: The requested offset is outside the range of offsets maintained by the server for the given topic/partition.","stacktrace":"github.com/linkedin/Burrow/core/internal/consumer.(*KafkaClient).partitionConsumer\n\t/go/pkg/mod/github.com/linkedin/!burrow@v1.3.4-0.20200506150011-4ce194fea01a/core/internal/consumer/kafka_client.go:261"}
panic: runtime error: invalid memory address or nil pointer dereference
[signal SIGSEGV: segmentation violation code=0x1 addr=0x8 pc=0x9ca109]

goroutine 393 [running]:
github.com/linkedin/Burrow/core/internal/consumer.(*KafkaClient).partitionConsumer(0xc00042edc0, 0xdf2b40, 0xc000ddb4a0, 0x0)
        /go/pkg/mod/github.com/linkedin/!burrow@v1.3.4-0.20200506150011-4ce194fea01a/core/internal/consumer/kafka_client.go:262 +0x5e9
created by github.com/linkedin/Burrow/core/internal/consumer.(*KafkaClient).startKafkaConsumer
        /go/pkg/mod/github.com/linkedin/!burrow@v1.3.4-0.20200506150011-4ce194fea01a/core/internal/consumer/kafka_client.go:314 +0x968

The underlying Sarama partition consumer considers the error fatal, and require user action:
https://github.com/Shopify/sarama/blob/b5764af1c47d0f6718dba3be6a3d75e8c97b351a/consumer.go#L826-L828
I would be nice if Burrow could handle the error more gracefully, and possibly restart the partition consumer at OffsetNewest.

It looks like we're hitting
https://issues.apache.org/jira/browse/KAFKA-9543,
which is causing the ErrOffsetOutOfRange errors.
The question still remains if Burrow should handle the error more gracefully than crashing.


buildbot: 4.0.3 -> 4.1.0

Changelog: https://github.com/buildbot/buildbot/releases/tag/v4.1.0

Things done

Built on platform(s)

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

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] 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
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
24.11 Release Notes (or backporting 23.11 and 24.05 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

[ ] Fits CONTRIBUTING.md.

Add a :+1: reaction to pull requests you find important.

I fixed all mypy errors in buildbot. Could do a "touch py.typed" in the buildbot main module. This allows us to check types in buildbot-nix, which should make upgrades less scary.
I will try to get this file created next buildbot release. I would have already done though, if I had new that the release was due to happen.

Could do a "touch py.typed" in the buildbot main module?

Do you want one in the worker as well?

Could do a "touch py.typed" in the buildbot main module?

Do you want one in the worker as well?

Yes, we that should also now fully type check.


[#167804765] Update to UAA v74.0.0

What
Update our fork of UAA to contain upstream's v74.0.0 changes, including a security fix: https://www.cloudfoundry.org/blog/cve-2019-11274/.
How to review
@AP-Hunt came up with a nice testing regime in https://github.com/alphagov/paas-uaa/pull/6#issuecomment-518290300:

[ ] Google SSO users managed correctly
[x] Able to invite users and accept invites
[x] Able to sign in with Google
[x] MS SSO uplift journey works
[ ] Able to sign in with MS

Who can review
Not @46bit

Testing this was going really well in my miki dev env until I tried to sign-in with Microsoft:
org.springframework.security.oauth2.common.exceptions.InvalidTokenException: Invalid issuer (https://login.microsoftonline.com/8fb610dd-de5e-4b38-9f55-d4752ccb1bde/v2.0) for token did not match expected: https://login.microsoftonline.com/a9ef326d-12c9-4877-84ee-4c293e364a8b/v2.0

😬 This somehow didn't include our changes.

OK, I've retested successfully. It's ready for final review.


service update needs option to delete old image

When you use service update --image, it would be nice if there were an option for docker to delete the old image once the service has updated.

Thanks, sounds like a good idea we should think about!

/cc @mlaventure @aluzzardi

I like the idea, we should take "rollback" into account when doing so (i.e. at what point do we consider the old image no longer needed); https://github.com/docker/docker/pull/26421

I guess swarm could call the prune endpoint of the nodes after a given grace period (in order to allow for easy rollbacks) to achieve this.

/cc @aaronlehmann


add: Agglomerative Hierarchy clustering algorithm

Describe the algorithm/code
This is the most common type of hierarchical clustering algorithm. It's used to group objects in clusters based on how similar they are to each other. This is a form of bottom-up clustering, where each data point is assigned to its own cluster. Then those clusters get joined together. At each iteration, similar clusters are merged until all of the data points are part of one big root cluster.Please assign me this issue under hacktoberfest tag
Do you want to work on this feature?

[X] I am willing to implement this feature.

Hi @adi271001! 👋🏻
You can start working on this issue! Do let me know if you need any help. ✨

created pull request and added codes


[cloud_infra_center] Fix some typos in README.md

@ddimatos @itsBryantP After your reviews in https://github.com/IBM/z_ansible_collections_samples/pull/54, I've fixed typos in REAMED.md. Pls have a look, thanks.

Thank you. You can also have your teammates review as well.

Thank you. You can also have your teammates review as well.

Thanks, got it.


Pull upstream and update the explorer

The current fork is a bit old and not having the latest upstream changes.
We should pull those changes for the testnet deployment.

done

Can you please  open a PR to this repo containing this change ?


python: ../nptl/pthread_mutex_lock.c:349: __pthread_mutex_lock_full: Assertion `INTERNAL_SYSCALL_ERRNO (e, __err) != EDEADLK || (kind != PTHREAD_MUTEX_ERRORCHECK_NP && kind != PTHREAD_MUTEX_RECURSIVE_NP)' failed.

Tensorflow is crashing when run using multiple GPUs (2,3,and 4) on cifar10_multi_gpu .py example in a Power8 computer.
What related GitHub issues or StackOverflow threads have you found by searching the web for your problem?
We have found some suggestions regarding updating glibc (https://bugs.launchpad.net/ubuntu/+source/glibc/+bug/1642390?cm_mc_uid=49967414488814888059863&cm_mc_sid_50200000=1489663906), but our system is already updated to the latest version and the problem remains.
We have also used ppc64_pc to reduce SMT (to 2)  and also turned off. Still the problem remains.
Environment info
Operating System:
Distributor ID:	Ubuntu
Description:	Ubuntu 16.04.2 LTS
Release:	16.04
Codename:	xenial
Linux minsky31 4.4.0-64-generic #85-Ubuntu SMP Mon Feb 20 17:05:51 UTC 2017 ppc64le ppc64le ppc64le GNU/Linux
Installed version of CUDA and cuDNN:
(please attach the output of ls -l /path/to/cuda/lib/libcud*):
CUDA
-rw-r--r-- 1 root root 559800 gen 27 00:10 /usr/local/cuda/lib64/libcudadevrt.a
lrwxrwxrwx 1 root root     16 gen 27 00:13 /usr/local/cuda/lib64/libcudart.so -> libcudart.so.8.0
lrwxrwxrwx 1 root root     19 gen 27 00:13 /usr/local/cuda/lib64/libcudart.so.8.0 -> libcudart.so.8.0.61
-rw-r--r-- 1 root root 476024 gen 27 00:10 /usr/local/cuda/lib64/libcudart.so.8.0.61
-rw-r--r-- 1 root root 966166 gen 27 00:10 /usr/local/cuda/lib64/libcudart_static.a
cuDNN
/usr/lib/powerpc64le-linux-gnu/libcudnn_static.a
/usr/lib/powerpc64le-linux-gnu/libcudnn.so.5.1.10
/usr/lib/powerpc64le-linux-gnu/libcudnn.so
/usr/lib/powerpc64le-linux-gnu/libcudnn_static_v5.a
/usr/lib/powerpc64le-linux-gnu/libcudnn.so.5
If installed from source, provide
1. The commit hash (git rev-parse HEAD):
012f9c10dcc27a838ed4b170b9036483bc2c5869

The output of bazel version:
Build label: 0.4.3-2017-01-24 (@6fc5c53)
Build target: bazel-out/local-opt/bin/src/main/java/com/google/devtools/build/lib/bazel/BazelServer_deploy.jar
Build time: Tue Jan 24 20:34:16 2017<PHONE_NUMBER>)
Build timestamp:<PHONE_NUMBER>
Build timestamp as int:<PHONE_NUMBER>

If possible, provide a minimal reproducible example (We usually don't have time to read hundreds of lines of your code)
We downloaded the files from https://github.com/tensorflow/models/tree/master/tutorials/image/cifar10
and tried to run the cifar10_multi_gpu example using four P100 gpus.
What other attempted solutions have you tried?
We tried removing the calls from measuring time, logging etc, but the problem remains.
Logs or other output that would be helpful
(If logs are large, please upload as attachment or provide link).
When it blocks, it simply hangs
2017-03-16 12:09:56.391752: step 800, loss = 3.33 (2982.8 examples/sec; 0.011 sec/batch)
2017-03-16 12:09:57.002419: step 810, loss = 3.49 (3998.9 examples/sec; 0.008 sec/batch)
2017-03-16 12:09:57.476172: step 820, loss = 3.24 (3003.8 examples/sec; 0.011 sec/batch)
and the result from strace when it blocks:
strace: Process 111228 attached
futex(0x3fffd5d49744, FUTEX_WAIT_PRIVATE, 1, NULL
Otherwise, when it gives the error :
futex(0x10013f8cf10, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, ffffffff) = 0
futex(0x10013f8cf10, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, ffffffff) = 0
futex(0x10013f8cf10, FUTEX_WAKE_PRIVATE, 1) = 1
futex(0x10013f8cf10, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, ffffffff) = 0
futex(0x10013f8cf10, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, ffffffff) = 0
futex(0x10013f8cf10, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, ffffffff) = -1 EAGAIN (Resource temporarily unavailable)
futex(0x10013f8cf10, FUTEX_WAKE_PRIVATE, 1) = 1
futex(0x3fffd1afc324, FUTEX_WAIT_PRIVATE, 1, NULL) = 0
futex(0x3fffd1afc2f8, FUTEX_WAKE_PRIVATE, 1) = 0
futex(0x3fffd1afc324, FUTEX_WAIT_PRIVATE, 1, NULL <unfinished ...>
+++ killed by SIGABRT (core dumped) +++
strace gives as last lines:
futex(0x1001efacf10, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, ffffffff) = 0
futex(0x1001efacf10, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, ffffffff) = 0
futex(0x1001efacf10, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, ffffffff) = -1 EAGAIN (Resource temporarily unavailable)
futex(0x3ffff8dbd184, FUTEX_WAIT_PRIVATE, 1, NULL) = 0
futex(0x3ffff8dbd158, FUTEX_WAKE_PRIVATE, 1) = 0
futex(0x3ffff8dbd184, FUTEX_WAIT_PRIVATE, 1, NULL) = 0
futex(0x3ffff8dbd158, FUTEX_WAKE_PRIVATE, 1) = 0
futex(0x3ffff8dbd184, FUTEX_WAIT_PRIVATE, 1, NULL) = 0
futex(0x3ffff8dbd158, FUTEX_WAKE_PRIVATE, 1) = 0
futex(0x3ffff8dbd184, FUTEX_WAIT_PRIVATE, 1, NULL) = 0
futex(0x3ffff8dbd158, FUTEX_WAKE_PRIVATE, 1) = 0
futex(0x3ffff8dbd184, FUTEX_WAIT_PRIVATE, 1, NULL) = 0
futex(0x3ffff8dbd158, FUTEX_WAKE_PRIVATE, 1) = 0
futex(0x1001efacf10, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, ffffffff) = 0
futex(0x3ffff8dbd184, FUTEX_WAIT_PRIVATE, 1, NULL) = 0
futex(0x3ffff8dbd158, FUTEX_WAKE_PRIVATE, 1) = 0
futex(0x3bff90000020, FUTEX_WAKE_PRIVATE, 1) = 1
futex(0x3ffff8dbd184, FUTEX_WAIT_PRIVATE, 1, NULL) = 0
futex(0x3ffff8dbd158, FUTEX_WAKE_PRIVATE, 1) = 0
stat("/etc/localtime", {st_mode=S_IFREG|0644, st_size=2692, ...}) = 0
write(1, "2017-03-16 12:22:38.084717: step"..., 90) = 90
futex(0x1001efacf10, FUTEX_WAKE_PRIVATE, 1) = 1
futex(0x1001efacf10, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, ffffffff) = 0
futex(0x1001efacf10, FUTEX_WAIT_BITSET_PRIVATE|FUTEX_CLOCK_REALTIME, 0, NULL, ffffffff) = -1 EAGAIN (Resource temporarily unavailable)
futex(0x3ffff8dbd184, FUTEX_WAIT_PRIVATE, 1, NULL

Also, increasing the batch_size for a single GPU (from 128 to 512) gives the same error, i.e. the process starts but then after a few iterations it halts again.
_2017-03-16 13:56:24.380589: step 390, loss = 3.90 (918.7 examples/sec; 0.557 sec/batch)
2017-03-16 13:56:30.259091: step 400, loss = 3.89 (831.1 examples/sec; 0.616 sec/batch)
2017-03-16 13:56:36.581468: step 410, loss = 3.87 (909.2 examples/sec; 0.563 sec/batch)
python: ../nptl/pthread_mutex_lock.c:349: __pthread_mutex_lock_full: Assertion `INTERNAL_SYSCALL_ERRNO (e, _err) != EDEADLK || (kind != PTHREAD_MUTEX_ERRORCHECK_NP && kind != PTHREAD_MUTEX_RECURSIVE_NP)' failed.
Aborted (core dumped)

Exactly same issue I am getting.

I am using Power8 box.. and dont see this issue.
python ./cifar10_multi_gpu_train.py --data_dir=/mldl/NVME/scratch/inception_output_data/ --train_dir=/tmp/ --num_gpus 4 --batch_size 512 --max_steps 200
I tried it with TensorFlow 1.0.1 and using libc6_2.23-0ubuntu5_ppc64el.deb
Kernel : 4.4.0-59-generic

@pedropgusmao would it be possible to try version 1.0.1? That will help narrow down the problem.
Similarly, @abdasgupta which TensorFlow version are you running?

Hi @skye  and  @antoajayraj ,
First let me describe my setup - I am running tensorflow training on inception v3 model to fine tune for Flowers data set(see https://github.com/tensorflow/models/tree/master/inception), through docker in a small kubernetes cluster made of power 8 machines. I have 4GPUs at my disposal.
My container and host OS are Ubuntu 16.04.
Host kernel is : 4.4.0-64-generic
GLibc version: Ubuntu GLIBC 2.23-0ubuntu7
I was hitting the above mentioned issue with tensorflow version 1.0.0 only when I ran 1000 iterations of training or above. The above error was appearing approx after 600-900 iterations.
After I upgraded to version 1.0.1, I am seeing no such error within 10000 iterations.
But if I run 100000 iterations, the training is getting stuck at around 50k and stack trace is showing that it is executing some waitpid(-1..) and stuck there.
Command to run the training in docker container:
docker run -it --privileged -v /usr/local/cuda-8.0/:/usr/local/cuda-8.0/ -v /usr/lib/powerpc64le-linux-gnu/:/usr/lib/powerpc64le-linux-gnu/ -v /usr/lib/nvidia-375/:/usr/lib/nvidia-375/  tf-inception-trainer-flowers-v101 /bin/bash -c "./run-trainer.sh 100000"
Image name : tf-inception-trainer-flowers-v101
This is the same image I am using for Kubernetes. This is a locally built image with tensorflow 1.0.1 installed.
Content of run-trainer.sh:
#!/bin/bash

if [ $1 ];  then
  ITERATIONS=$1
else
  echo $0": usage: ./run-traner.sh [iterations]"
  exit 1
fi

curl -O http://download.tensorflow.org/models/image/imagenet/inception-v3-2016-03-01.tar.gz && \
tar xzf inception-v3-2016-03-01.tar.gz && \
ls inception-v3

mkdir /flowers-data

cd /models/inception && \
export LD_LIBRARY_PATH=/usr/lib/powerpc64le-linux-gnu/ && \
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-8.0/lib64/ && \
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib/nvidia-375/ && \
bazel build inception/download_and_preprocess_flowers && \
bazel-bin/inception/download_and_preprocess_flowers /flowers-data && \

# Build the model. Note that we need to make sure the TensorFlow is ready to
# use before this as this command will not build TensorFlow.
bazel build inception/flowers_train

# Path to the downloaded Inception-v3 model.
MODEL_PATH="/inception-v3/model.ckpt-157585"

# Directory where the flowers data resides.
FLOWERS_DATA_DIR=/flowers-data/

# Directory where to save the checkpoint and events files.
TRAIN_DIR=/flowers_train/

# Run the fine-tuning on the flowers data set starting from the pre-trained
# Imagenet-v3 model.
bazel-bin/inception/flowers_train \
  --train_dir="${TRAIN_DIR}" \
  --data_dir="${FLOWERS_DATA_DIR}" \
  --pretrained_model_checkpoint_path="${MODEL_PATH}" \
  --fine_tune=True \
  --initial_learning_rate=0.001 \
  --max_steps="${ITERATIONS}" \
  --input_queue_memory_factor=1

Is the behaviour expected? Am I doing something wrong? Please, guide me. Though my current purpose is served as I can run the training now till 5000 iterations through docker. It gives me about 99.8% of accuracy. And accuracy is same while the iterations go up to 50k. But the accuracy is hurt while I lower the iterations to , say 2000 (Only 93.4%)
I will update my findings after I run the training on P8 bare-metal till 100000 iterations.
Thank you.

So it sounds like the crash was resolved in 1.0.1. That's good. @pedropgusmao please let us know if you still see this after upgrading to 1.0.1.
@abdasgupta you mention a stacktrace with waitpid(-1), could you post the full stacktrace? Also how are you collecting it?

Hi everyone. I was also using a Power8 with IBM's packages (https://www-01.ibm.com/common/ssi/cgi-bin/ssialias?htmlfid=POO03514WWEN&) which included Tensorflow 1.0.0 . I solved the problem by using CUDA8 for Power8, which is NOT(!!!!) the same for the general pc64_el architecture. You must use the cuda-repo-ubuntu1604-8-0-local-ga2_8.0.54-1_ppc64el-deb from https://developer.nvidia.com/cuda-downloads-power8 .

@skye  I ran the tensorflow training on bare-metal. The error is sporadic; though after using Tensorflow 1.0.1, the error is seldom coming within 50000 iterations.  I am collecting stacktrace with "strace -p " and during the error , it only shows waitpid(-1), nothing more.
@pedropgusmao Yes, I am using CUDA8 from cuda-repo-ubuntu1604-8-0-local-ga2_8.0.54-1_ppc64el-deb from https://developer.nvidia.com/cuda-downloads-power8 .

@abdasgupta , I am also using  Nvidia  Driver Version: 361.10. From line export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib/nvidia-375/ && \ and docker run it seems that you are using the new 375 driver. Could you try and downgrade to 361.10?

I've also experienced this error using TensorFlow on POWER8, and have now also
just hit it on a source installation of caffe2 on POWER8. So this may not be
an issue with TensorFlow. My environment:
System:        Power8 Minsky, 4xP100
OS:            Ubuntu 16.04.2
CUDA:          cuda-repo-ubuntu1604-8-0-local-ga2v2_8.0.61-1_ppc64el.deb
cuDNN:         5.1.10
Python:        2.7
NVIDIA Driver: 375.51
I'm curious, what kinds of GPUs is everyone running? @pedrogusmao and I are on
P100 and having this issue. How about @abdasgupta and @antoajayraj?

@bcbrock I have the same issue on a Minsky machine:
System: Power8 Minsky, 4xP100
OS: Ubuntu 16.04.2
CUDA: 8.0.61
cuDNN: 5.1.10/6.0.20
Python: 2.7.12
NVIDIA Driver: 375.51
TensorFlow: 1.0.1
Any more ideas on this issue?

@dahlem What is the command or recreate steps ? and is it consistent ?

@antoajayraj I'm using Mozilla's deepspeech [1] to build a speech transcription model using the LibriSpeech dataset. It does not happen consistently.
[1] https://github.com/mozilla/DeepSpeech

I'm able to reproduce this on a POWER system with:

TensorFlow        1.1.0
Ubuntu            16.04.2 (kernel 4.4.0-77-generic)
libc6:ppc64el     2.23-0ubuntu7
cuda-cudart-8-0   8.0.61-1
GPU driver        375.51

In a crash I caught, it looks like there are 2 mutexes and 2 or 3 threads involved.
First mutex is wanted by thread 1 (110471 / 0x1af87), and seems to be owned by thead 17 (110465 / 0x1af81). Thread 1 detects a deadlock while trying to acquire and asserts.
(In the core file, this mutex appears locked by thread 113 (110449 / 0x1af71) which conflicts with the ownership recorded in the mutex. But it also appears to be marked as if the owner has died, so maybe thread 113 had been waiting and made a bit of progress after thread 1 hit the assert().)
(gdb) x/20x 0x100056c7e40
0x100056c7e40:  0xc001af71      0x00000001      0x0001af81      0x00000001
                __lock          __count         __owner         __nusers
0x100056c7e50:  0x00000021      0x00000000      0x00000000      0x00000000
                __kind

Second mutex is wanted by thead 17 (110465 / 0x1af81) and is locked by thread 1 (110471 / 0x1af87).
(gdb) x/8x 0x3fff57d39e78
0x3fff57d39e78: 0x8001af87      0x00000001      0x00000000      0x00000000
                __lock          __count         __owner         __nusers
0x3fff57d39e88: 0x00000021      0x00000000      0x00000000      0x00000000
                __kind

All three of the involved threads had come through cudaLaunch() and are somewhere in libcuda:
Thread 1 (Thread 0x3bffad57f1a0 (LWP 110471)):
#0  0x00003fffa027edb0 in __GI_raise (sig=<optimized out>) at ../sysdeps/unix/sysv/linux/raise.c:54
#1  0x00003fffa0281270 in __GI_abort () at abort.c:89
#2  0x00003fffa0274290 in __assert_fail_base (fmt=<optimized out>,
    assertion=0x3fffa04296e8 "INTERNAL_SYSCALL_ERRNO (e, __err) != EDEADLK || (kind != PTHREAD_MUTEX_ERRORCHECK_NP && kind != PTHREAD_MUTEX_RECURSIVE_NP)",
    file=0x3fffa04296c8 "../nptl/pthread_mutex_lock.c", line=<optimized out>, function=<optimized out>) at assert.c:92
#3  0x00003fffa0274384 in __GI___assert_fail (
    assertion=0x3fffa04296e8 "INTERNAL_SYSCALL_ERRNO (e, __err) != EDEADLK || (kind != PTHREAD_MUTEX_ERRORCHECK_NP && kind != PTHREAD_MUTEX_RECURSIVE_NP)",
    file=0x3fffa04296c8 "../nptl/pthread_mutex_lock.c", line=<optimized out>, function=0x3fffa0429830 <__PRETTY_FUNCTION__.9294> "__pthread_mutex_lock_full") at assert.c:101
#4  0x00003fffa041b400 in __pthread_mutex_lock_full (mutex=0x100056c7e40) at ../nptl/pthread_mutex_lock.c:347
#5  0x00003fff8b94e268 in ?? () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#6  0x00003fff8b9202d8 in ?? () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#7  0x00003fff8b806ef4 in ?? () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#8  0x00003fff8b9a46f8 in cuLaunchKernel () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#9  0x00003fff7596f0b8 in ?? () from /usr/local/cuda-8.0/lib64/libcudart.so.8.0
#10 0x00003fff759bda88 in cudaLaunch () from /usr/local/cuda-8.0/lib64/libcudart.so.8.0
#11 0x00003fff909d4678 in ?? () from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#12 0x00003fff909e95e0 in tensorflow::functor::CastFunctor<Eigen::GpuDevice, float, unsigned char>::operator()(Eigen::GpuDevice const&, Eigen::TensorMap<Eigen::Tensor<float, 1, 1, long>, 16,
 Eigen::MakePointer>, Eigen::TensorMap<Eigen::Tensor<unsigned char const, 1, 1, long>, 16, Eigen::MakePointer>) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#13 0x00003fff909d0c6c in ?? () from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#14 0x00003fff9096c03c in tensorflow::CastOpBase::Compute(tensorflow::OpKernelContext*) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#15 0x00003fff91a8332c in tensorflow::BaseGPUDevice::ComputeHelper(tensorflow::OpKernel*, tensorflow::OpKernelContext*) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#16 0x00003fff91a83778 in tensorflow::BaseGPUDevice::Compute(tensorflow::OpKernel*, tensorflow::OpKernelContext*) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#17 0x00003fff91ac6e20 in ?? () from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#18 0x00003fff91ee0d30 in Eigen::NonBlockingThreadPoolTempl<tensorflow::thread::EigenEnvironment>::WorkerLoop(int) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#19 0x00003fff91ee1688 in std::_Function_handler<void (), Eigen::NonBlockingThreadPoolTempl<tensorflow::thread::EigenEnvironment>::NonBlockingThreadPoolTempl(int, bool, tensorflow::thread::E
igenEnvironment)::{lambda()#1}>::_M_invoke(std::_Any_data const&) () from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#20 0x00003fff91eddf74 in std::_Function_handler<void (), tensorflow::thread::EigenEnvironment::CreateThread(std::function<void ()>)::{lambda()#1}>::_M_invoke(std::_Any_data const&) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#21 0x00003fff91f12f90 in ?? () from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#22 0x00003fff758049a4 in ?? () from /usr/lib/powerpc64le-linux-gnu/libstdc++.so.6
#23 0x00003fffa0418070 in start_thread (arg=0x3bffad57f1a0) at pthread_create.c:335
#24 0x00003fffa0363230 in clone () at ../sysdeps/unix/sysv/linux/powerpc/powerpc64/clone.S:96

Thread 17 (Thread 0x3bffb057f1a0 (LWP 110465)):
#0  0x00003fffa041adc4 in __pthread_mutex_lock_full (mutex=0x3fff57d39e78) at ../nptl/pthread_mutex_lock.c:339
#1  0x00003fff8b94e268 in ?? () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#2  0x00003fff8b9202d8 in ?? () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#3  0x00003fff8b929e28 in ?? () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#4  0x00003fff8b8f95ac in ?? () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#5  0x00003fff8b90cab0 in ?? () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#6  0x00003fff8ba9a454 in ?? () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#7  0x00003fff8b806cec in ?? () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#8  0x00003fff8b806f38 in ?? () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#9  0x00003fff8b9a46f8 in cuLaunchKernel () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#10 0x00003fff7596f0b8 in ?? () from /usr/local/cuda-8.0/lib64/libcudart.so.8.0
#11 0x00003fff759bda88 in cudaLaunch () from /usr/local/cuda-8.0/lib64/libcudart.so.8.0
#12 0x00003fff90bc9e08 in ?? () from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#13 0x00003fff90be4a50 in void tensorflow::functor::ReduceFunctor<Eigen::GpuDevice, Eigen::internal::ProdReducer<int> >::Reduce<Eigen::TensorMap<Eigen::Tensor<int, 0, 1, long>, 16, Eigen::Ma
kePointer>, Eigen::TensorMap<Eigen::Tensor<int const, 1, 1, long>, 16, Eigen::MakePointer>, Eigen::array<long, 1ul> >(Eigen::GpuDevice const&, Eigen::TensorMap<Eigen::Tensor<int, 0, 1, long>
, 16, Eigen::MakePointer>, Eigen::TensorMap<Eigen::Tensor<int const, 1, 1, long>, 16, Eigen::MakePointer>, Eigen::array<long, 1ul> const&, Eigen::internal::ProdReducer<int> const&) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#14 0x00003fff90b919c4 in tensorflow::ReductionOp<Eigen::GpuDevice, int, Eigen::internal::ProdReducer<int> >::Compute(tensorflow::OpKernelContext*) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#15 0x00003fff91a8332c in tensorflow::BaseGPUDevice::ComputeHelper(tensorflow::OpKernel*, tensorflow::OpKernelContext*) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#16 0x00003fff91a83778 in tensorflow::BaseGPUDevice::Compute(tensorflow::OpKernel*, tensorflow::OpKernelContext*) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#17 0x00003fff91ac6e20 in ?? () from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#18 0x00003fff91ee0d30 in Eigen::NonBlockingThreadPoolTempl<tensorflow::thread::EigenEnvironment>::WorkerLoop(int) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#19 0x00003fff91ee1688 in std::_Function_handler<void (), Eigen::NonBlockingThreadPoolTempl<tensorflow::thread::EigenEnvironment>::NonBlockingThreadPoolTempl(int, bool, tensorflow::thread::E
igenEnvironment)::{lambda()#1}>::_M_invoke(std::_Any_data const&) () from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#20 0x00003fff91eddf74 in std::_Function_handler<void (), tensorflow::thread::EigenEnvironment::CreateThread(std::function<void ()>)::{lambda()#1}>::_M_invoke(std::_Any_data const&) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#21 0x00003fff91f12f90 in ?? () from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#22 0x00003fff758049a4 in ?? () from /usr/lib/powerpc64le-linux-gnu/libstdc++.so.6
#23 0x00003fffa0418070 in start_thread (arg=0x3bffb057f1a0) at pthread_create.c:335
#24 0x00003fffa0363230 in clone () at ../sysdeps/unix/sysv/linux/powerpc/powerpc64/clone.S:96

Thread 113 (Thread 0x3bffb857f1a0 (LWP 110449)):
#0  0x00003fffa041adc4 in __pthread_mutex_lock_full (mutex=0x100056c7e40) at ../nptl/pthread_mutex_lock.c:339
#1  0x00003fff8b94e268 in ?? () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#2  0x00003fff8b9202d8 in ?? () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#3  0x00003fff8b806ef4 in ?? () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#4  0x00003fff8b9a46f8 in cuLaunchKernel () from /usr/lib/powerpc64le-linux-gnu/libcuda.so.1
#5  0x00003fff7596f0b8 in ?? () from /usr/local/cuda-8.0/lib64/libcudart.so.8.0
#6  0x00003fff759bda88 in cudaLaunch () from /usr/local/cuda-8.0/lib64/libcudart.so.8.0
#7  0x00003fff909d3238 in ?? () from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#8  0x00003fff909e38e0 in tensorflow::functor::CastFunctor<Eigen::GpuDevice, int, unsigned char>::operator()(Eigen::GpuDevice const&, Eigen::TensorMap<Eigen::Tensor<int, 1, 1, long>, 16, Eig
en::MakePointer>, Eigen::TensorMap<Eigen::Tensor<unsigned char const, 1, 1, long>, 16, Eigen::MakePointer>) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#9  0x00003fff909d099c in ?? () from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#10 0x00003fff9096c03c in tensorflow::CastOpBase::Compute(tensorflow::OpKernelContext*) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#11 0x00003fff91a8332c in tensorflow::BaseGPUDevice::ComputeHelper(tensorflow::OpKernel*, tensorflow::OpKernelContext*) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#12 0x00003fff91a83778 in tensorflow::BaseGPUDevice::Compute(tensorflow::OpKernel*, tensorflow::OpKernelContext*) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#13 0x00003fff91ac6e20 in ?? () from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#14 0x00003fff91ee0d30 in Eigen::NonBlockingThreadPoolTempl<tensorflow::thread::EigenEnvironment>::WorkerLoop(int) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#15 0x00003fff91ee1688 in std::_Function_handler<void (), Eigen::NonBlockingThreadPoolTempl<tensorflow::thread::EigenEnvironment>::NonBlockingThreadPoolTempl(int, bool, tensorflow::thread::E
igenEnvironment)::{lambda()#1}>::_M_invoke(std::_Any_data const&) () from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#16 0x00003fff91eddf74 in std::_Function_handler<void (), tensorflow::thread::EigenEnvironment::CreateThread(std::function<void ()>)::{lambda()#1}>::_M_invoke(std::_Any_data const&) ()
   from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#17 0x00003fff91f12f90 in ?? () from /opt/DL/tensorflow/lib/python2.7/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so
#18 0x00003fff758049a4 in ?? () from /usr/lib/powerpc64le-linux-gnu/libstdc++.so.6
---Type <return> to continue, or q <return> to quit---
#19 0x00003fffa0418070 in start_thread (arg=0x3bffb857f1a0) at pthread_create.c:335
#20 0x00003fffa0363230 in clone () at ../sysdeps/unix/sysv/linux/powerpc/powerpc64/clone.S:96

Confirmed that I also see this with NVIDIA driver 375.66.  I've asked NVIDIA to take a look as well.

The results of my testing so far as as follows. All tests with Ubuntu 16.04.2 (kernel 4.4.0-72 or -78) and CUDA 8.0.61:
TF      Driver    cuDNN     Comment
1.0.1   361.119   5.0.10    OK
1.0.1   375.51    5.1.10    Hang/Assert
1.0.1   375.51    6.0.20    Hang/Assert
1.1.0   361.119   5.0.10    OK
1.1.0   375.51    6.0.20    Assert
1.1.0   375.66    6.0.20    Assert/Hang

The problem seems not to occur with the 361 series driver, but does with the 375 series driver.
Generally, I see much higher throughput (images / sec) with TF 1.1.0 and with the system more aggressively tuned (with adjustments to performance governor, SMT mode, and GPU clock settings).

In the lower-throughput configs the symptom is more likely a process hang.
In the higher-throughput configs the symptom is more likely the assert.

Will share these results with NVIDIA.
For now, I'd suggest using the 361-series driver, and would be interested in any reports of hangs or asserts with that driver.

Just got recheck from our IBM PowerAI experts: this is a known bug in the current Nvidia 375 GPU driver: back-leveling the driver to the 361 level will fix the issue.


Dalle3模型是否支持一次性返回四张图片      ？[Feature Request]

🥰 需求描述
Does the Dalle3 model support returning 4 images at once?
🧐 解决方案
Does the Dalle3 model support returning 4 images at once?
📝 补充信息
No response

不行，api不支持


I'm not using mouse and it still promote.

Like this.

When I only use keyboard, it will pop up.
As I think, if I don't use mouse, it will not give me any promotion.
Is there something wrong?

Hi, which OS you use?

Hi, which OS you use?

I have tried in MacOS and Windows10.

I have the same issue running Windows 11. Example of shortcuts that I use the trigger warnings are ctrl+pgup, f5, shift+f5

I have also the same issue with Linux on a gnome environment under wayland

I am getting such ridiculous hints as "use delete" or "home". Obviously those are exactly keys I am using already. (No, I am really not using mouse context menu.)

I have the same issue.
Version: 1.85.2 (system setup)
Commit: 8b3775030ed1a69b13e4f4c628c612102e30a681
Date: 2024-01-18T06:40:10.514Z
Electron: 25.9.7
ElectronBuildId: 26354273
Chromium: 114.0.5735.289
Node.js: 18.15.0
V8: <IP_ADDRESS>-electron.0
OS: Windows_NT x64 10.0.22631

i have the same issue on arch linux

same issue on arch linux

I'm also having the same problem with any shortcut that I run with my keyboard.
As an example, opening a new empty window and pressing command+N a few times (I'm on macos) shows the following dialog:

My version:
Version: 1.91.1 (Universal)
Commit: f1e16e1e6214d7c44d078b1f0607b2388f29d729
Date: 2024-07-09T22:07:54.982Z (3 wks ago)
Electron: 29.4.0
ElectronBuildId: 9728852
Chromium: 122.0.6261.156
Node.js: 20.9.0
V8: 12.2.281.27-electron.0
OS: Darwin arm64 23.5.0


ctrl+c not always effective

I think that I saw ctrl+C not working if it is called before the last point of a scan like this
|        20 | 02:56:37.3 |    714.428 |             714.500 |                      0 |      37260 |
|        21 | 02:56:47.3 |    714.886 |             715.000 |                      0 |      36664 |
+-----------+------------+------------+---------------------+------------------------+------------+
generator ascan ['8a2bc2'] (scan num: 74169)
Transient Scan ID: 74170 @ 2017/02/13 02:56:48
Persistent Unique Scan ID: '0be04ae5-5465-4525-a3a3-012fd2f664bc'
+-----------+------------+------------+---------------------+------------------------+------------+
|   seq_num |       time |     energy | pgm_energy_setpoint | pgm_energy_stop_signal |   sclr_ch2 |
+-----------+------------+------------+---------------------+------------------------+------------+
|         1 | 02:57:03.8 |    704.953 |             705.000 |                      0 |      27512 |
|         2 | 02:57:14.6 |    705.498 |             705.500 |                      0 |      31062 |
|         3 | 02:57:25.2 |    706.016 |             706.000 |                      0 |      48252 |
|         4 | 02:57:35.0 |    706.552 |             706.500 |                      0 |      79285 |
|         5 | 02:57:45.2 |    706.900 |             707.000 |                      0 |      74643 |
|         6 | 02:57:55.3 |    707.338 |             707.500 |                      0 |      70215 |
|         7 | 02:58:05.0 |    707.945 |             708.000 |                      0 |     134201 |
|         8 | 02:58:15.8 |    708.947 |             708.500 |                      0 |     116444 |
|         9 | 02:58:25.7 |    708.884 |             709.000 |                      0 |      90134 |
|        10 | 02:58:35.8 |    709.549 |             709.500 |                      0 |      70281 |
|        11 | 02:58:45.6 |    709.954 |             710.000 |                      0 |      60523 |
|        12 | 02:58:56.8 |    710.546 |             710.500 |                      0 |      56438 |
|        13 | 02:59:07.0 |    710.978 |             711.000 |                      0 |      54218 |
|        14 | 02:59:16.7 |    711.462 |             711.500 |                      0 |      48565 |
|        15 | 02:59:26.7 |    712.008 |             712.000 |                      0 |      44180 |
|        16 | 02:59:36.6 |    712.542 |             712.500 |                      0 |      40166 |
|        17 | 02:59:46.8 |    713.118 |             713.000 |                      0 |      38786 |
|        18 | 02:59:56.7 |    713.422 |             713.500 |                      0 |      38883 |
|        19 | 03:00:07.2 |    713.865 |             714.000 |                      0 |      38396 |
|        20 | 03:00:17.0 |    714.522 |             714.500 |                      0 |      35274 |
^CA 'deferred pause' has been requested. The RunEngine will pause at the next checkpoint. To pause immediately, hit Ctrl+C again in the next 10 seconds.
Deferred pause acknowledged. Continuing to checkpoint.
|        21 | 03:00:26.7 |    715.095 |             715.000 |                      0 |      35893 |
+-----------+------------+------------+---------------------+------------------------+------------+
generator ascan ['0be04a'] (scan num: 74170)
Transient Scan ID: 74171 @ 2017/02/13 03:00:27
Persistent Unique Scan ID: 'f3b1654f-d6ee-4a9f-95b4-c529a90ea137'
+-----------+------------+------------+---------------------+------------------------+------------+
|   seq_num |       time |     energy | pgm_energy_setpoint | pgm_energy_stop_signal |   sclr_ch2 |
+-----------+------------+------------+---------------------+------------------------+------------+
|         1 | 03:00:40.4 |    705.009 |             705.000 |                      0 |      26266 |
^CA 'deferred pause' has been requested. The RunEngine will pause at the next checkpoint. To pause immediately, hit Ctrl+C again in the next 10 seconds.
Deferred pause acknowledged. Continuing to checkpoint.
|         2 | 03:00:50.7 |    705.476 |             705.500 |                      0 |      31268 |
Pausing...
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
/home/xf23id1/Beamline/Commissioning/2017_02/20170212_night.py in <module>()
----> 1 while(True):RE(ascan(pgm_en,705,715,20))

/opt/conda_envs/collection-17Q1.0/lib/python3.5/site-packages/bluesky/run_engine.py in __call__(self, plan, subs, raise_if_interrupted, **metadata_kw)
    541         # If we are in the wrong state, raise.
    542         if not self.state.is_idle:
--> 543             raise RuntimeError("The RunEngine is in a %s state" % self.state)
    544
    545         futs = []

RuntimeError: The RunEngine is in a paused state

In [176]: RE.stop()
Stopping: running cleanup and marking exit_status as 'success'...

Useless to say, it was not in a plan but in a stupid loop as I was quickly checking for stability while at the keyboard
while(True):
RE(ascan(pgm_en,705,715,20))
however normally it stops no problem at the next iteration, thing that this was not happening...


speech_recognition does not implemented the vosk wrapper

I'm trying to use speech_regognition with vosk. But when I try to call the vosk method I receive the following message:
  Traceback (most recent call last):
   File "C:\Users\user\projects\\studies\speechreco.py", line 27, in <module>
   text = recognizer.recognize_vosk(audio)
   AttributeError: 'Recognizer' object has no attribute 'recognize_vosk'. Did you mean: 'recognize_api'?

The method is:
import speech_recognition as speechreco
import vosk

while True:

    try:
        print("begin loop")
        with speechreco.Microphone() as mic:
            recognizer.adjust_for_ambient_noise(mic)
            print("begin listening")
            audio = recognizer.listen(mic)

            text = recognizer.recognize_vosk(audio)
            ...

It looks like the vosk wrapper is not implemented at the version:
vosk       -   0.3.42
python   -  3.10.4
Need I use a downgrade version?
I follow the sample:

version 3.8.1 doesn't include vosk:
https://github.com/Uberi/speech_recognition/blob/3.8.1/speech_recognition/__init__.py
I'm also interested in using Vosk as it seems to be the only offline option that actually works.

Yeah same problem, any fix?

As @Enhex mentioned (Thanks! ❤),

version 3.8.1 was released in 2017
version 3.8.1 does not include recognize_vosk method

This method was added at https://github.com/Uberi/speech_recognition/pull/513 on 2020

For example if you install from PyPI, recognize_vosk was not implemented
$ pip install SpeechRecognition

>>> import speech_recognition as speechreco
>>> recognizer = speechreco.Recognizer()
>>> "recognize_vosk" in dir(recognizer)
False

Temporary workaround
Clone this repository and install from source
$ # I recommend to prepare another virtual environment for source installation
$ git clone https://github.com/Uberi/speech_recognition.git
$ cd speech_recognition/
$ pip install -e .

>>> import speech_recognition as speechreco
>>> recognizer = speechreco.Recognizer()
>>> "recognize_vosk" in dir(recognizer)
True

Thanks for reporting this issue. ❤
Can you try this workaround, @ramleda @mattiasu96 ?
I will prepare for PyPI release.
It is preferable as solution.

Clone this repository and install from source

You can do it with a single pip command actually:
pip3 install git+https://github.com/Uberi/speech_recognition

@nshmyrev Thanks!
Actually, I misunderstood the project's metadata and was not able to install like pip install SomeProject<EMAIL_ADDRESS>https://pip.pypa.io/en/stable/cli/pip_install/#examples (example 5)
Your comment gave me suggestions and helped me realize the misunderstanding.
pip install speech-recognition@git+https://github.com/Uberi/speech_recognition.git


Terminal window not working correctly for Resources Show Logs

Bug description

When showing the logs for terminal, there are UI/UX issues for showing the terminal even if it errors out.
The sidebar is positioned incorrectly, terminal window is broken, etc.
Operating system
mac M1
Installation Method
None
Version
1.11.1
Steps to reproduce

Install Minikube
Try to do create
Press show logs
See incorrect UI/UX.

Relevant log output
No response
Additional context
No response

Looks OK on Windows

Or maybe this is a just "small" error? :D


Wildcard DNS-Records

Why
I use Headscale to securely selfhost my Applications. Currently i just route the Local IPs to my Server and force all my Tailscale Devices to use the Local DNS-Server. however, if i could define the Domains in the Headscale DNS-Config (Via a Wildcard in the best Case) i could stop advertising local routes and instead resolve those Domains to the Tailscale Domain.
I would prefer Wildcards, as i sometimes add / remove Services with unique subdomains and I'm a bit scared of a indent-mistake in the config when adding the new record bringing the Server down, locking me out.

Description
currently the DNS of Headscale (this one: https://github.com/juanfont/headscale/blob/main/docs/dns-records.md#Limitations) can only resolve specific Domains. I would like to be able to put a wildcard in there and all subdomains getting redirected off of that Wildcard

hey, can I get a quick feedback instead of just a stale? even if it's a wontfix, just so we know what's up.

Ping :)

Hello perhaps the same subject, i like to have nice local dns names,
-in the LAN i use AdGuard to rewrite all local DNS names to traefik with one rule using wildcard : see picture
-headscale there is " dns: > extra_records: " section for this, but unfortunatly you must add all your local dns names one by one : see picture

Would be very nice to have record like this (to replace all the individual lines) :

Best regards :)

I think this is a duplicate of #2159, I've replied there that it needs investigation, but I think it is a client limitation we cant do anything about. If it does currently not work, it probably wont as we just pass the option straight too the client.

wait, but this Issue is older?
Shouldn't you mark 2159 as a duplicate of 1840, the older one?
oh well, whatever, I'll check it out over there.


[ado] Pierce ADO NPM feed cache for published packages

Still need to add the PAT to the secrets group, looking into ADO CLI now.

@kenotron I'd also like to make sure this step does not in any way fail the pipeline, as it needs some testing and isn't a required step. Do you know how I can ensure that?

At least in a test with no publishing it doesn’t fail and if it were to fail after the next publish, it would at least fail after the publish.


Only repeat the site's name once in the header

Remove the underlines on the arrow links.

Looks good to me, pending circle


Potential security issues reported by Snyk.io

Snyk reports quite alerting issues with this repo:
https://snyk.io/test/github/alanshaw/david-www
Let's patch up everything that's possible to patch!

Nice! That's indeed a sneaky way to do your advertising...

Well I have no affiliation with Snyk and it's free for OS, so no money's involved anyway 😃
But this doesn't change the subject, Snyk gives instructions what's problematic, so let's fix them if possible

That's exactly what an advertiser would say :)

I think the reason why it looks like ad is that you make it click bait, instead of importing the issues as a todo list. I've tried to do so but failed to extract useful information from the linked site.

Snyk gives instructions what's problematic,

Its advice for each listed problem is "run our tool to fix it", and the claims of what that tool would do seem to all be about making a modified version of the couchwatch module, because its dependencies are insecure and npm currently has no update for couchwatch.

so let's fix them if possible

I don't think any of those fixes are possible in this module and repo, as they are, to my understanding, all about couchwatch, so that would have to be fixed first. I hope I'm mistaken, because otherwise the OP seems like outright spam really.

ok


llvm-stdenv: fix default stdlib

Motivation for this change
Fixes #28223
Things done

[x] Tested using sandboxing
(nix.useSandbox on NixOS,
or option build-use-sandbox in nix.conf
on non-NixOS)
Built on platform(s)

[x] NixOS
[ ] macOS
[ ] Linux

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[ ] Tested compilation of all pkgs that depend on this change using nix-shell -p nox --run "nox-review wip"
[x] Tested execution of all binary files (usually in ./result/bin/)
[x] Fits CONTRIBUTING.md.

@Ericson2314 It works fine, NIX_CXXSTDLIB_COMPILE will be either empty or the default at that point.
$ nix-shell -E 'with import ./. {}; llvmPackages.stdenv.mkDerivation { name = "foo"; }' --run 'NIX_DEBUG=1 $CXX'
HARDENING: disabled flags: IGNORED_KEY
HARDENING: Is active (not completely disabled with "all" flag)
HARDENING: enabling fortify
HARDENING: enabling stackprotector
HARDENING: enabling pic
HARDENING: enabling strictoverflow
HARDENING: enabling format
HARDENING: enabling relro
HARDENING: enabling bindnow
extra flags before to /nix/store/gmb9n24q2brhd3x2z1c5zv3psy1yv4jk-clang-4.0.1/bin/clang++:
  ''
original flags to /nix/store/gmb9n24q2brhd3x2z1c5zv3psy1yv4jk-clang-4.0.1/bin/clang++:
  ''
extra flags after to /nix/store/gmb9n24q2brhd3x2z1c5zv3psy1yv4jk-clang-4.0.1/bin/clang++:
  -B/nix/store/gmb9n24q2brhd3x2z1c5zv3psy1yv4jk-clang-4.0.1/lib
  -B/nix/store/yz5vwqycca5jrgcdigxyj5776jalbvsh-glibc-2.25/lib/
  -idirafter
  /nix/store/6jyqh11wgbam661h9sqfpydan6jhsh30-glibc-2.25-dev/include
  -idirafter
  -B/nix/store/i3knpsfj710dxmpx73vbh16mhfpv4jnh-clang-wrapper-4.0.1/bin/
  -isystem
  /nix/store/dj2w6h9vyma0bvrchb8npwk6s1m62j10-gcc-6.4.0/include/c++/6.4.0
  -isystem
  /nix/store/dj2w6h9vyma0bvrchb8npwk6s1m62j10-gcc-6.4.0/include/c++/6.4.0/x86_64-unknown-linux-gnu
  -O2
  -D_FORTIFY_SOURCE=2
  -fstack-protector-strong
  --param
  ssp-buffer-size=4
  -fPIC
  -fno-strict-overflow
  -Wformat
  -Wformat-security
  -Werror=format-security
clang-4.0: error: no input files

@Ericson2314 just finished both afl and python27Packages.vowpalwabbit, they are both ok.

Oh my bad, I thought the export line used the salted variable. I see how it works now, but unfortunately I don't think this will work in the cross case, where that variable won't be inspected if the "host role" is not in use. For that reason we do need to stuff it directly into the salted var, but only if none of the activities input roll-based ones are defined.

Yeah, I thought so. Would doing the same for the build/target variants work?

@LnL7 I suppose, though the flags will be repeated when more the cc-wrapper takes on multiple roles. I think going straight to defining the salted var like I described is cleanest for now---I'll just look forward to the day when we can remove all CXXSTDLIB_*.


Testing loadable-components with enzyme, Mocha, chai, sinon snapshots

💬 Questions and Help
Hey Team,
Recently I have done migration to @loadable component from universal component, but  I am trying to solve the test coverage issue with enzyme Mocha chai  snapshots for my existing project. Earlier all test cases were working fine with Universal component, but now Its lagging coverage percentage due to following

any help would be highly appreciated.
thanks in advance.

@gregberge - please provide help on it.


newlines in processes name (cmdline) aren't escaped

Bug description
Newlines in process' cmdline aren't escaped and break Prometheus output format.
To Reproduce

start a process containing a newline in its command line:# bash -c 'sleep infinity;
> echo plop'

query metrics endpoint. The response looks like this:[…]
# HELP scaph_process_power_consumption_microwatts Power consumption due to the process, measured on at the topology level, in microwatts
# TYPE scaph_process_power_consumption_microwatts gauge
scaph_process_power_consumption_microwatts{cmdline="bash-csleep infinity;
echo plop",exe="bash",pid="2786006"} 0
[…]

Prometheus fails to parse scaphandre's output and ignore all metrics from scaphandre job.

Expected behavior
newlines should be either escaped or replaced by spaces like in ps.
Environment

Debian buster
Kernel version: 5.10.0-9-amd64

Thanks!

@uggla did you open a PR on this ? I see the commit but I cannot find the related PR, did I miss something ?

@bpetit yes I wrote a PR to fix this bug.

https://github.com/hubblo-org/scaphandre/pull/195

Thanks a lot ! I lost it for a moment.

Applied changes from @uggla in aa15ae288a91184041c4dce19debb869b6a1b385
It is fixed, thanks a lot @billux for raising the issue and @uggla for fixing it !


valueChanges() loses type information

Using<EMAIL_ADDRESS>Calling .valueChanges() on an AngularFireObject<T> should return an Observable<T | null>, but instead returns Observable<{} | null>.
Similarly, calling .valueChanges() on an AngularFireList<T> should return an Observable<T[]>, but instead returns  Observable<{}[]>.
This results in error messages for code that should be correct.   For example, the following code:
interface FooBar {
	foo: string;
	bar: number;
}

afDb.object<FooBar>("/foo-bar/1")
	.valueChanges()
	.subscribe(fooBarItem => {
		if (fooBarItem !== null) {
			console.log(`Foo: ${fooBarItem.foo}, Bar:${fooBarItem.bar}`);
		}
	});

afDb.list<FooBar>("/foo-bar")
	.valueChanges()
	.subscribe(fooBarArray => {
		fooBarArray.forEach(fooBarItem => {
			console.log(`Foo: ${fooBarItem.foo}, Bar:${fooBarItem.bar}`);
		});
	});

yields the following TypeScript  errors on the console.log() statements:
Property 'foo' does not exist on type '{}'.
Property 'bar' does not exist on type '{}'.
Property 'foo' does not exist on type '{}'.
Property 'bar' does not exist on type '{}'.

I think fixing this problem is simply a matter of setting the return type explicitly for the .valueChanges() function.

Could this be related to why I'm getting this error on building?
`            Property 'valueChanges' does not exist on type 'FirebaseListObservable<any[]>'.
  L24:    constructor(public navCtrl: NavController, public navParams: NavParams, public viewCtrl: ViewController, afDB: AngularFireDatabase) {
  L25:      this.items = afDB.list('snippets'+this.title).valueChanges();

Error: Failed to transpile program
at new BuildError (/Users/sr/Ionic/http/node_modules/@ionic/app-scripts/dist/util/errors.js:16:28)
at /Users/sr/Ionic/http/node_modules/@ionic/app-scripts/dist/transpile.js:137:20
at transpileWorker (/Users/sr/Ionic/http/node_modules/@ionic/app-scripts/dist/transpile.js:103:12)
at Object.transpile (/Users/sr/Ionic/http/node_modules/@ionic/app-scripts/dist/transpile.js:61:12)
at buildProject (/Users/sr/Ionic/http/node_modules/@ionic/app-scripts/dist/build.js:97:78)
at /Users/sr/Ionic/http/node_modules/@ionic/app-scripts/dist/build.js:47:16`

@TheShashank, your error is due to versioning issues and unrelated to my issue.  In previous versions afdb.list() returns a FirebaseListObservable, but with version 5 the new API returns an AngularFireList.  .valueChanges() is a method of AngularFireList.  You seem to  be attempting to use the version 5 API but running version 4.  Check you package.json and update to the latest version and your error should go away.

the latest version of firebase or AngularFire?

No, please post that as a separate issue.

I'm having this issue as well. Right now it doesn't disrupt anything in the application, but it triggers a tslint error in my console.

just encountered this, any workarounds?

had to set the return type to any to get it to stop complaining -_-

Despite creating a complete interface that reflected my database... I had to add [propName: string]: any; to my interface to get it to stop complaining.. pretty ugly stuff.

i think a more elegant workaround until this gets fixed would be to explicitly cast the output of .valueChanges() to your desired type
(afDb.object<FooBar>("/foo-bar/1")
	.valueChanges() as Observable<FooBar>)
	.subscribe(fooBarItem => {
		if (fooBarItem !== null) {
			console.log(`Foo: ${fooBarItem.foo}, Bar:${fooBarItem.bar}`);
		}
	});

(afDb.list<FooBar>("/foo-bar")
	.valueChanges() as Observable<FooBar[]>)
	.subscribe(fooBarArray => {
		fooBarArray.forEach(fooBarItem => {
			console.log(`Foo: ${fooBarItem.foo}, Bar:${fooBarItem.bar}`);
		});
	});


Can't run, Garbage Collector grayed out.

OS: Windows 10 x65.
Version of IPFS Desktop 0.30.1

Describe the bug
Garbage Collector option is grayed out.
To Reproduce
Steps to reproduce the behavior:

Go to '...'
Click on '....'
Scroll down to '....'
See error

Expected behavior
Be allowed to run it.
Screenshots

@ZeroCool22 @whizzzkid Can you two provide your log files and also confirm whether you have automatic garbage collection enabled or not?

nvm, i don't need it.. we're good. fix coming shortly.