[ROCKETMQ-161] Update runbroker.sh and runserver.sh to support user defined jvm mem flag

https://issues.apache.org/jira/browse/ROCKETMQ-161?filter=-1

Coverage decreased (-0.1%) to 31.776% when pulling 23e14efd07f0e68b52d139053f0c94043164efda on dongeforever:ROCKETMQ-161 into 45a64fd6a8ab66a8b0eb30cbe2dffd59b19274f9 on apache:develop.

Coverage decreased (-0.1%) to 31.776% when pulling 23e14efd07f0e68b52d139053f0c94043164efda on dongeforever:ROCKETMQ-161 into 45a64fd6a8ab66a8b0eb30cbe2dffd59b19274f9 on apache:develop.

Coverage decreased (-0.1%) to 31.776% when pulling 23e14efd07f0e68b52d139053f0c94043164efda on dongeforever:ROCKETMQ-161 into 45a64fd6a8ab66a8b0eb30cbe2dffd59b19274f9 on apache:develop.

@shroman please help review and check it.

@shroman @lizhanhui Could you help us to review this long-time delayed PR

LGTM +1

@dongeforever Sorry, I don't think this modification is needed. A user will modify this file anyway in order to match his/her system requirements.
Also, there are even more flags, and if you take this approach, you may have to add more variables for each in future, which will make the script tricky.

When running in docker,  this would be useful.  Users just want to run a docker demo, but the computer could not allocate 8g memory, and there is no way to define the JVM flags in docker's script. OMG!

Ok, but let's set it through JVM_OPTS instead of introducing a variable for that specific setting.

+1 JVM_OPTS, Do not try to introducing new variable.

Or just check JAVA_OPTS have already defined Xmx

http://stackoverflow.com/questions/229551/string-contains-in-bash

+1, maybe it's better to merge JAVA_OPTS

The intention is to make user-defined JVM flags to replace the initial ones.
So just put JAVA_OPT_EXT after JAVA_OPT is enough.
The later defined JVM parameters will replace the previous ones. I have already tested it.
@vsair @netroby @shroman  how do you think

Coverage decreased (-0.04%) to 34.591% when pulling 77e657f1addccedae4c21bc287d04fc2c9db71fd on dongeforever:ROCKETMQ-161 into 42f78c281cbeb5072b04eaf03b1a8059b8d281a7 on apache:develop.

Coverage decreased (-0.04%) to 34.591% when pulling 77e657f1addccedae4c21bc287d04fc2c9db71fd on dongeforever:ROCKETMQ-161 into 42f78c281cbeb5072b04eaf03b1a8059b8d281a7 on apache:develop.

Coverage decreased (-0.04%) to 34.591% when pulling 77e657f1addccedae4c21bc287d04fc2c9db71fd on dongeforever:ROCKETMQ-161 into 42f78c281cbeb5072b04eaf03b1a8059b8d281a7 on apache:develop.

@dongeforever Hmm, sorry I don't understand yet why JAVA_OPTS won't work. Can you please explain how/when it happens? :)

@shroman In runbroker.sh and runserver.sh, some default options, such as -Xmx8g, are placed after the JVM_OPTS, so user-defined -Xmx will not take effect.
And if we put JAVA_OPT_EXT after all default options, it will replace the default ones.

@dongeforever I see, thank you!
How about just changing the code to
if [ -z "$JVM_OPTS" ] ; then
  #default_options
  JAVA_OPT="${JAVA_OPT} -server -Xms8g -Xmx8g -Xmn4g"
fi

?
But if you guys think we need JAVA_OPT_EXT, please go ahead ;)

@shroman I insist on using JAVA_OPT_EXT, for that we may not only want to override -Xms -Xmx -Xmn, but also other jvm flags.
We could use JAVA_OPT_EXT once and for all.

It's OK to introduce an extra variable to override default Java VM options.
+1


Disable should_process_waiting_queue_as_fifo test

COUCHDB-3140
This PR disables the problematic queue-as-fifo test. As written, any
call in a test to spawn_client/1 returns immediately, and does not
guarantee that the call to couch_query_servers:get_ddoc_process/2
returns before control flow proceeds to the next line in the eunit test.
As it turns out, on Windows, the call to spawn_client for ddoc5 succeeds
prior to the ddoc4 call in this test, thus always failing.
Insertion of a timer:sleep/1 call between the spawn_client/1 calls seems
to solve the problem, but even this is "lucky" behaviour. Semantically
the way this test is written, with spawn_client/1 using spawn/1 to spin
off the actual get_ddoc_process/2 call, there is no guarantee that the
couch_proc_manager FIFO queue is being populated correctly.
Further, if the get_ddoc_process/2 call takes longer than the defined
timeout (5000 ms) this test will always fail, as no provision is made to
keep trying for an os_process after that time. Again we are "lucky" that
the test runs fast enough that this is not a problem, but relying on a
performant BEAM VM for test success in any regard is equally
problematic.
For this reason I am completely commenting out this test until the
harness can be fixed. I believe the impact to couchdb is minimal.
(It also suggests we may want to rethink how requests for os processes
are queued and issued at some point in the future; this approach seems
sub-optimal, especially if strict FIFO ordering is an expectation of the
system.)
/cc @eiri @rnewson @janl

For reference, disabling this one test allows the subsequent test in the suite (should_reduce_pool_on_idle_os_procs) to pass on Windows, so it's just this one test that is a problem.

nice find and way better than disabling the whole file. +1


DeprecationWarning from lspopt

YASA relies on lspopt, which imports pkg_resources here and causes a DeprecationWarning when using Python >=3.12. This got observed during #187, see comments there for more details.
This is not urgent by any means, and should be addressable with a PR on lspopt.

Just opened a PR on lspopt to address this: hbldh/lspopt#8


SSR: Restrict to current selection if any

The selection is also used to avoid unnecessary work, but only to the file level. Further restricting unnecessary work is left for later.

It's possible that this needs more work in the case of there being no selection...

If nothing was selected, I was restricting SSR to the empty range. Fixed now.

#3186

bors r+


Fix WKNavigationDelegate methods in ExampleApp-iOS

fix WKNavigationDelegate method name
set ExampleWKWebViewController as WKNavigationDelegate
set ExampleUIWebViewController as UIWebViewDelegate in example

change the PR branch, update at https://github.com/marcuswestin/WebViewJavascriptBridge/pull/206


Implemented callback for individual tokens

This PR adds the functionality to set a callback for the predicted tokens. The callback will be called after a token has been predicted. The callback must return true if the model should predict more tokens or false if it should stop.
You can call l.SetTokenCallback(callback) to register the callback and l.SetTokenCallback(nil) to deregister it. Only one callback can be registered per *LLama instance but different instances can use different callbacks. The callbacks are also thread-safe, you can (de-)register them freely while the model is predicting.
Solves #4

Seven minutes from opening the PR to the merge. Now that was fast :grin:

That was a great contribution! Kudos!
My only dilemma now is - is going this to penalize the execution time? swinging context between C to go has def. some impacts - but maybe we can get away with branching? only benchmarking will tell I guess.

CGo got a lot faster in the last few Go versions. It's not like we are predicting at thousands of tokens per second anyway.

As someone who has taken CGo pretty far, it has an execution cost for sure. However, from very briefly looking over the code in llama.cpp probably the bulk of time will still be spent executing the C code, and not dealing with the runtime stack switching.
Also, see https://pkg.go.dev/runtime/cgo#Handle for a slightly updated way to pass function pointer around.


Use flagutil package across most Go binaries [phab:D317]

Created by schroederc at 2015-06-04 19:49:58:

shahms accepted this revision at 2015-06-04 20:16:22

schroederc closed via commit 91a26e6db021c0522879f5ae312e663f0f19fe57 at 2015-06-04 20:26:08


Seasons Pause Progression Inoperative

Describe the bug
The pause season progression mechanic does not work.
Turning the setting to True in the calendar config and reloading AND restarting the server does nothing. In the previous version I had, setting it to paused would generate exceptions multiple times a second in the server console, since updating to latest it no longer generates exceptions, but still does not function as intended.
I paid for this plugin some time ago and it is supposed to be an integral part of the server that opened last week, seeing 30-35 concurrent players at any given time, but has been disabled now for days. Discord support was not helpful.
How to reproduce

Set season progression to paused in config
Wait for the correct amount of days to progress, the season will change.
Reinstall, reconfig, and reload, the seasons still change.

Screenshots / Videos
No response
Server Log
No response

Are there any known workarounds to this?

Are there any known workarounds to this?

Yes, fixed. Wait for the next release!


Return correct collection instance when calling all

Fixes #452
Calling User::all(); returned a Eloquent/Collection. This PR makes sure a Support/Collection is returned so that User::all()->first() returns a User|null.

Thank you for you PR!
https://www.php.net/manual/en/function.in-array.php
in_array return a boolean. Could you please correct the code?

@szepeviktor Done!

Thanks.
Could you add a 3rd parameter true to get in_array work in a strict mode?


Support request for https://www.blutv.com.tr

Please follow the guide below

You will be asked some questions and requested to provide some information, please read them carefully and answer honestly
Put an x into all the boxes [ ] relevant to your issue (like this: [x])
Use the Preview tab to see what your issue will actually look like

Make sure you are using the latest version: run youtube-dl --version and ensure your version is 2018.03.20. If it's not, read this FAQ entry and update. Issues with outdated version will be rejected.

[x] I've verified and I assure that I'm running youtube-dl 2018.03.20

Before submitting an issue make sure you have:

[x] At least skimmed through the README, most notably the FAQ and BUGS sections
[x] Searched the bugtracker for similar issues including closed ones
[x] Checked that provided video/audio/playlist URLs (if any) are alive and playable in a browser

What is the purpose of your issue?

[ ] Bug report (encountered problems with youtube-dl)
[x] Site support request (request for adding support for a new site)
[ ] Feature request (request for a new functionality)
[ ] Question
[ ] Other

The following sections concretize particular purposed issues, you can erase any section (the contents between triple ---) not applicable to your issue

If the purpose of this issue is a bug report, site support request or you are not completely sure provide the full verbose output as follows:
Add the -v flag to your command line you run youtube-dl with (youtube-dl -v <your command line>), copy the whole output and insert it here. It should look similar to one below (replace it with your log inserted between triple ```):
youtube-dl --verbose https://www.blutv.com.tr/ar-en/series/turkish/7faces/season-1/7faces-episode-1-watch
[debug] System config: []
[debug] User config: []
[debug] Custom config: []
[debug] Command-line args: [u'--verbose', u'https://www.blutv.com.tr/ar-en/series/turkish/7faces/season-1/7faces-episode-1-watch']
[debug] Encodings: locale UTF-8, fs UTF-8, out UTF-8, pref UTF-8
[debug] youtube-dl version 2018.03.20
[debug] Python version 2.7.12 (CPython) - Linux-4.4.0-45-generic-x86_64-with-Ubuntu-16.04-xenial
[debug] exe versions: none
[debug] Proxy map: {}
[generic] 7faces-episode-1-watch: Requesting header
WARNING: Falling back on generic information extractor.
[generic] 7faces-episode-1-watch: Downloading webpage
[generic] 7faces-episode-1-watch: Extracting information
ERROR: Unsupported URL: https://www.blutv.com.tr/ar-en/series/turkish/7faces/season-1/7faces-episode-1-watch
Traceback (most recent call last):
  File "/usr/local/bin/youtube-dl/youtube_dl/extractor/generic.py", line 2223, in _real_extract
    doc = compat_etree_fromstring(webpage.encode('utf-8'))
  File "/usr/local/bin/youtube-dl/youtube_dl/compat.py", line 2542, in compat_etree_fromstring
    doc = _XML(text, parser=etree.XMLParser(target=_TreeBuilder(element_factory=_element_factory)))
  File "/usr/local/bin/youtube-dl/youtube_dl/compat.py", line 2531, in _XML
    parser.feed(text)
  File "/usr/lib/python2.7/xml/etree/ElementTree.py", line 1653, in feed
    self._raiseerror(v)
  File "/usr/lib/python2.7/xml/etree/ElementTree.py", line 1517, in _raiseerror
    raise err
ParseError: mismatched tag: line 94, column 3
Traceback (most recent call last):
  File "/usr/local/bin/youtube-dl/youtube_dl/YoutubeDL.py", line 785, in extract_info
    ie_result = ie.extract(url)
  File "/usr/local/bin/youtube-dl/youtube_dl/extractor/common.py", line 440, in extract
    ie_result = self._real_extract(url)
  File "/usr/local/bin/youtube-dl/youtube_dl/extractor/generic.py", line 3161, in _real_extract
    raise UnsupportedError(url)
UnsupportedError: Unsupported URL: https://www.blutv.com.tr/ar-en/series/turkish/7faces/season-1/7faces-episode-1-watch
...
<end of log>

If the purpose of this issue is a site support request please provide all kinds of example URLs support for which should be included (replace following example URLs by yours):

Single video: https://www.blutv.com.tr/ar-en/series/turkish/7faces/season-1/7faces-episode-1-watch
Single video: https://www.blutv.com.tr/ar-en
Playlist: https://blutv.akamaized.net/D3/fb18201b2365799cb07da14c290cadf7/output.mpd

site support request
free registration shows videos.
It is mpeg-dash with widevine DRM. is it downloadable?

yes please add support for this site if possible

Support this site please.

Issue should be closed, URL is dead


Ground and model with same name (csv).

Hi all,
There is a bug in surfplots if ground stations and model have the same variable named. The bug is caused because monet changes the name by adding "new", whereas the pairing tool in melodies-monet tool.py utility (mobile_and_ground_pair) uses directly pandas merge_asof, which in that case changes the name by adding _x, _y, etc.
Then, the plotting tool looks for the variable "_new", which does not exist.
Probably the easiest fix is adding _new to repeated variables, and sticking to the MONET method, although I tend to think that the pandas way of dealing with it is probably better.
What do you think, @zmoon ?
Cheers
Pablo

@blychs this could likely be done in your pandas merge with suffixes=(None, '_new') (which is how monet combinetool does it too). Depending on context of course, I do like the approach of only adding a suffix to the "new" column.


Contribution to "Improper Input Validation and Uncontrolled Recursion in Apache Log4j2"

Updates

Affected products
Description

This GH advisory GHSA-p6xc-xr62-6r2g includes Affected Versions > 2.12.3
Proposed edit to affected versions so that this GH advisory matches the details of https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-45105 and https://logging.apache.org/log4j/2.x/security.html
-Affected Versions > 2.12.3
+Affected Versions < 2.12.3


Instructions for setting up a caja server

I'm currently looking to see if it might be possible to integrate the services provided by Caja into a project that I am working on that will allow instructors and course authors (who are not professional, trusted developers) to provide client-side code that will be used as part of an online learning experience. I'm using the XBlock API in a client-side-authoring XBlock into which I am hoping to integrate Caja.
Unfortunately, the API that Caja currently provides does not integrate well with this particular XBlock because Caja currently assumes that the client-side code of interest is being hosted on an external website (like an iframe) rather than being served as an untrusted component of a webpage as it is being rendered. I would like to see if I can harvest the guts of Caja in a way that will allow this XBlock to continue to receive updates as Caja matures, but I can only do that if I know how to mess with Caja code and run it locally. Halp?
(As an aside, another feature of interest would be to cache cajoled versions of client-provided client-side code, but I'm mentioning it only as a point of interest rather than the main question.)

When creating the Caja guest "frame", you can specify the HTML or JS content to load directly (as a string) rather than fetching it from any URL.
Please use https://groups.google.com/forum/#!forum/google-caja-discuss for further questions rather than this issue tracker.

Thanks.


Unwanted notification on Mailreading (Message is not end to end encrypted)

Expected behavior
Click on a mail at the Mainscreen, enter my passpharse and view mail
Actual behavior
After entering a mail i get this Message displayed every time... Is the a chance to disable that?
Steps to reproduce

Use OpenKeyChain, german mail Provider with Inline PGP Mail enceyption
Get a mail :-)
Here is a screenshot: https://cloud.teyro.tech/index.php/s/ZntXAqB3VrICdtn

Environment
K-9 Mail version: lastest stable 5.207 i think
Android version:
LinaeageOS on OnePlus2 and Stock Android 6.0 on a Samsung Galaxy Tab A 2016

Duplicate of #2286


Issue #SC-1061 feat: System update API changes - Add Test Cases

Codecov Report

Merging #513 into release-2.2.0 will decrease coverage by 0.03%.
The diff coverage is n/a.

@@                 Coverage Diff                 @@
##             release-2.2.0     #513      +/-   ##
===================================================
- Coverage            32.33%   32.29%   -0.04%
+ Complexity            1242     1236       -6
===================================================
  Files                  172      170       -2
  Lines                15187    15072     -115
  Branches              2403     2390      -13
===================================================
- Hits                  4910     4868      -42
+ Misses                9539     9467      -72
+ Partials               738      737       -1

Impacted Files
Coverage Δ
Complexity Δ

...dex/transformer/AggregationsResultTransformer.java
0% <0%> (-100%)
0% <0%> (-4%)

...p/searchindex/elasticsearch/ElasticSearchUtil.java
43.56% <0%> (-4.39%)
49% <0%> (-3%)

.../ekstep/searchindex/processor/SearchProcessor.java
65.45% <0%> (-0.91%)
99% <0%> (ø)

.../mgr/impl/operation/event/RejectFlagOperation.java

...ontent/mgr/impl/operation/event/FlagOperation.java

...g/ekstep/taxonomy/mgr/impl/BaseContentManager.java
59.47% <0%> (+1.67%)
87% <0%> (+5%)
:arrow_up:

...kstep/taxonomy/controller/ContentV3Controller.java
53.48% <0%> (+4.55%)
18% <0%> (ø)
:arrow_down:

...g/ekstep/taxonomy/mgr/impl/ContentManagerImpl.java
75% <0%> (+12.14%)
15% <0%> (-1%)
:arrow_down:

...g/ekstep/content/mgr/impl/ContentEventManager.java
85.71% <0%> (+14.28%)
3% <0%> (-1%)
:arrow_down:

Continue to review full report at Codecov.

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Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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Test and Build Hooks for release (4-2-stable)

Yet to do:

test on Ubuntu 18
potentially exercise more code paths by changing time of AVU collection annotation
create new test overlapping indexing types on a collection [ #19 ]

tested and passing on all Ub18, Ub16, Cen7.

excellent - please rebase and squash to single commit.


Textures uses linear filtering in previews, regardless of node or default settings

Godot version
4.0.dev (042e81f663)
System information
Windows 10
Issue description
Seems like this should be open because it's been around forever, but I can't find an open ticket associated with this. Feel free to close if otherwise.
When using a texture, while the node renders correctly, the preview uses linear filtering, even when used for a node with filtering set to nearest and nearest set as the project default import setting.

Steps to reproduce
Use a small pixel image as a texture.
Minimal reproduction project
No response

Duplicate of #60150


Could it show you how many points a move is worth before finalizing it?

This would help my friend get the scoring system.  They're a little confused by it still.

Done in b9c3ab9cb1a24d1680febe27e14cf26c61fc2f49 !


Is this project abandoned?

Hi Ralf, Are there any plans to add support for pdfbox 3 (and beyond)?

@ralfstuckert I would also like to know if this project is still supported

is there any alternative for this library?, we also upgraded the pdfbox to version 3 and looking to fix some issues

Maybe you can have a look at https://github.com/phax/ph-pdf-layout/ which does something very similar. Except for the "in text formatting" I assume it can do most of it (and supports PDFBox 3.x)
The respective in text formatting may be taken over from this library with limited effort I assume...

thank you @phax


Adding a Unified web console.

This PR implements the https://github.com/apache/incubator-druid/issues/6832 proposal.

From a technical point of view this creates a single unified console that leverages system tables via SQL. This console queries both the overlord and the coordinator meaning that is has to run on a node that can route requests to both. In this PR it is expected to run on the router node (part 1) of the proposal. In part (2) this console will also be placed on the coordinator.
This console utilises TypeScript and React and is built in such a way as to be maximally simple and maintainable by non web developers while still being slick and powerful.
In an effort to consolidate this PR also pulls into itself the legacy consoles. Their functionality is still fully available for anyone to use.

There is also a handy tab for running SQL (and native) queries without using curl:

I am looking forward to unified web console :+1:
Is there a possibility to set credentials, eg. login and pwd? At the moment, everybody how knows the url ist able to stop/suspend even kill eg. kafka supervisors which is a little bit painful.

@aleksi75 The underlying APIs the console uses can be protected, and if you do so, then valid credentials will be needed in order to do anything useful with the console.

@vogievetsky do you plan to work on part (2) - allowing to access the unified console on Coordinator?

Opened #8150 to track this.


No warning or error when package name contains underscore

Hi, this might be my relative inexperience with bitbake speaking but I was quite surprised when my package, foo_bar encountered a bunch of (nothing provides foo_bar) errors when using the recipe generated by this crate.
Turns out the problem was that bb doesn't allow underscores in package names and changing it to foo-bar fixed everything.
I feel like cargo-bitbake could at least produce a warning in this case, since the file it is producing is not a valid bitbake file.
I'm not sure I'd advocate for a hard error or an implicit transformation of the name, since it's always possible to change the generated file by hand.

Agreed here. This should get fixed up.

Fixed with v0.3.14


fix: release asset file name change

Starting with sops v3.8.0, the sops-v3.8.0.linux is no longer being built and is replaced by sops-v3.8.0.linux.amd64, for which it was an alias.
This breaks the existing workflow, so this PR fixes it.
See https://github.com/getsops/sops/issues/1296#issuecomment-1723280303

Resolves #1296


Reorder table

Some ideas:

Add a "country" column, for people who want EU servers
Re-order table : open source services first, commercial companies last... or random order.

Done


Spot existing redirects and respond with caution

A typical complex case would be something like this:
http://redant.com.au/ruby-on-rails-devops/manage-ssl-redirection-in-nginx-using-maps-and-save-the-universe/
In that case we should probably be able to spot a directive like this:
return 301 http://... and refuse to try to enable a redirect in such a configuration (or warn/ask the user before trying)

Oops, sorry wrong repo!


Add mousedown / mouseup events to relevant bits.

Describe the feature in detail (code, mocks, or screenshots encouraged)
The current bits button is only exposing the following events...
on:click
on:change
on:keydown
on:keyup
on:mouseenter
on:mouseleave

Would it be possible to also add
on:mousedown
on:mouseup

What type of pull request would this be?
None
Provide relevant links or additional information.
No response

Works for me! Can't wait until Svelte 5 so that we don't have to manually expose all of these listeners 😃

Closing as fixed in bits-ui@next


Take ownership in IsReady, to avoid capacity exhaustion

Motivation
The new IsReady API in PR #3241 is easy to use in ways that create test bugs, or hide production bugs.
Solution

take ownership of the service when calling IsReady methods
document the constraints on the methods

Review
@jvff asked me to open a ticket for these changes in https://github.com/ZcashFoundation/zebra/pull/3241#discussion_r771871194
This PR contains the parts we can do immediately, it is based on PR #3241, and it is ok to merge into that PR.
Reviewer Checklist

[ ] Code implements Specs and Designs
[ ] Tests for Expected Behaviour
[ ] Tests for Errors

Follow Up Work

#3261

I'm not sure about this. The potential bug that's been mentioned in a comment on #3241 was already present before, so it's not related to #3241. IMO it would probably be best to be merged separately, to improve change management (i.e., we have one PR for a refactor, and a second PR for the bug fix).
That said, the solution here has something that bothers me. It drops the Client during the call, which could alter the assertions done afterwards. Doing the assertion last is also not ideal, since some assertions require the client instance to be polled first. You probably realized this in the implementation, but the workaround implemented in some of the tests seems needlessly complicated.
This seems to be more of a tower issue than anything else. tower::Service has the design where it can be checked for readiness multiple times (see the last paragraph of Service::poll_ready's documentation). Trying to work around this is possible, but I don't think this should be done immediately, and I also don't think IsReady is the place for it.
I still think it would be best to have a separate issue for us to do this later, with more time and thought. This is also low priority, since there currently isn't any bugs, and this is mitigation for potential future bugs if we change things specifically in the Client. If such changes are made, we'd have to rethink Client anyway, because we wouldn't actually be trying to fix a bug, but actually workaround an intentional tower design.

I'm not sure about this. The potential bug that's been mentioned in a comment on #3241 was already present before, so it's not related to #3241. IMO it would probably be best to be merged separately, to improve change management (i.e., we have one PR for a refactor, and a second PR for the bug fix).

I'll open a separate PR to improve the test coverage.

That said, the solution here has something that bothers me. It drops the Client during the call, which could alter the assertions done afterwards. Doing the assertion last is also not ideal, since some assertions require the client instance to be polled first. You probably realized this in the implementation, but the workaround implemented in some of the tests seems needlessly complicated.

I don't like the workaround either, so I think I might just close this PR.

This seems to be more of a tower issue than anything else. tower::Service has the design where it can be checked for readiness multiple times (see the last paragraph of Service::poll_ready's documentation). Trying to work around this is possible, but I don't think this should be done immediately, and I also don't think IsReady is the place for it.

I think you're right.

I still think it would be best to have a separate issue for us to do this later, with more time and thought. This is also low priority, since there currently isn't any bugs, and this is mitigation for potential future bugs if we change things specifically in the Client. If such changes are made, we'd have to rethink Client anyway, because we wouldn't actually be trying to fix a bug, but actually workaround an intentional tower design.

There could be some genuine issues here, particularly with services that hold reservations. But it's also possible that the tower::Buffer documentation is outdated, and the undocumented behaviour of mpsc channels is actually ok.
I've tried to fix similar issues before using general workarounds, but it hasn't been particularly successful. So I think we'd be better to open tickets for any specific issues that actually happen.


LCFS - BUG when reporting HDRD supply in the fuel supply grid

Describe the Bug
In the Fuel Supply section, when attempting to save an entry for the fuel type HDRD, an error warning appears. After inputting the Fuel Type and Fuel Category and then selecting the Determining Carbon Intensity, an error message displays as "Error updating row." The Fuel Type, Fuel Category, and Determining Carbon Intensity columns are outlined in red, and the entry does not save.
Expected Behaviour

Users should be able to enter values for Fuel Type, Fuel Category, and Determining Carbon Intensity for HDRD without errors.
The row should save successfully after completing these inputs.

Actual Behaviour

Upon selecting the Determining Carbon Intensity for HDRD, an error warning appears as "Error updating row."
The Fuel Type, Fuel Category, and Determining Carbon Intensity columns are outlined in red.
The entry does not save, preventing users from successfully adding HDRD as a fuel type.

Implications

Users are unable to record HDRD fuel supply data, which impacts accurate reporting in the fuel supply table.
This error prevents users from completing and saving necessary entries for compliance reporting.

Steps To Reproduce
Steps to reproduce the behaviour:
User/Role: BCeID

Select HDRD as the Fuel Type and input the Fuel Category.
Select a Determining Carbon Intensity.
Attempt to save the row and observe the "Error updating row" message.
Note that the Fuel Type, Fuel Category, and Determining Carbon Intensity fields are outlined in red, and the entry does not save.

@Grulin can we check on dev the scenario?

Hi @areyeslo. This bug does not seem to be occurring anymore. Thank you for catching this. I will close this ticket out.


Enhancement: default handleRequest method

Hi, I'm building tool to create resources with fake data and I've came across one error due to no actual database rows for that resource when executing action (nova checks that by default). And I noticed that this package already has overridden DispatchAction::forModels() (and removed check there) but it's not actually overriding handleRequest method on DetachedAction which is also doing that check and causing the error message "Sorry!
My proposition is to create trait for overriding handleRequest (for backwards compatibility with default nova action behaviour)

Thanks @Lai0n Can you submit a PR with the changes you've outlined above so I can review.

Done some digging around. Turns out it was half way implemented. As I mentioned there was overridden DispatchAction::class but there was also forgotten member variable DetachedAction::standalone So instead of creating trait I just implemented it right into DetachedAction::handleRequest.

Find out that it was not package issue but it was Nova's. Standalone actions are not implemented until version 3.10.0, I was using older version. Please change minimum required laravel/nova package version in composer.json


Add Bitbucket cloud support to SCM generator

Would be great to have BitBucket cloud as a provide in SCM generator:
https://argocd-applicationset.readthedocs.io/en/stable/Generators-SCM-Provider/#scm-provider-generator

Would access be by using a personal access token?  That can be passed as a bearer token, from the docs here: https://confluence.atlassian.com/bitbucketserver072/personal-access-tokens-1005335924.html

The cloud based version of bitbucket also doesn't have labels.  There is the idea of a workspace, so if you need to group respositories together, I guess they could be put in the same workspace.  That's not really the intent of a workspace though.  At least I don't see the ability to put labels on repositories in the cloud version of bitbucket.

@mmerrill3 is the labels something required? I could imagine that scanning whole workspace is fine.
Access would be via App Password https://support.atlassian.com/bitbucket-cloud/docs/app-passwords/ with option to reuse credentials defined for argocd - I've already have a password to bitbucket there, would be nice to reuse it instead of adding new one.

@jdomag , labels are not required.  They just would be empty in the scm_provider.Repository structure.
The other two scm providers, gitlab and github.com, use static access tokens for authenticating with the cloud provider.  I see that bitbucket does as well, if you pass in the static access token as a bearer token, and the go client library for bitbucket supports that method as well.
If we use an app password, we would also need to pass in a username as well, which is an extra configuration parameter.  On the other hand, using the static token approach would be just one configuration setting.

@mmerrill3 I think Personal Access Tokens are not available on BitBucket cloud:
https://community.atlassian.com/t5/Bitbucket-questions/Personal-Access-Token-for-Bitbucket-Cloud/qaq-p/677663

It would be awesome to have bitbucket added :)

I know it's in the title, but is this issue strictly limited to Bitbucket Cloud (i.e. API 2.0)?
For those interested in Bitbucket Server (i.e. API 1.0), I have an implementation for SCM and PR generators on this branch

Thanks @mlosicki , the bitbucket server supports labels now if you'd like to use it.  That's great work.  I do get the sense that this is for Bitbucket Cloud.

This is related to #472, since there's a change in the interface in that PR if it gets merged.  I was holding off on looking deeper into this ask until that PR had movement.

Hey @mlosicki,
Loved what you did with Bitbucket Server (as my organization uses it currently). Would love if you open a PR to the main repository, and that your feature will be in the next version so everyone could use it!

@jdomag the PR is merged, this issue can be closed.

@mmerrill3  that's great news! I will give it a try in the next release of applicationSet controller!
thanks!

Hello!
Does it mean bitbucket will be included as a Generator Pull Request https://argocd-applicationset.readthedocs.io/en/stable/Generators-Pull-Request/ ?

Does this mean path generator annotation should work @mmerrill3 because on my current test with Bitbucket on webhooks it is being ignored?


[VSCode] Binary file sharing support

I have been using the Live Share extension to collaboratively edit LaTeX, but have always had trouble viewing image and PDF files.
https://github.com/microsoft/live-share/issues/1895
What I would like to request is similar to this issue. If this is resolved, it would be an advantage that Live Share does not have!
Thank you.

I'm not sure what kind of architecture Microsoft is using internally for their live share feature (it's closed source after all), but I'm a bit confused why they haven't fixed it after 5 (!) years. Anyway, see PR https://github.com/TypeFox/open-collaboration-tools/pull/51 for a fix for that.


Enabled header_saveload feature

Closes #86
I enabled header_saveload feature

The cloud save and load feature works, but displays many other layouts

Where do they come from?

When I save a chart I see this additional selector

But when I then reload the website, that additional selector is gone. Where does it come from?

Where do they come from?

They come from other users those use public user id
https://github.com/blockchainprojects/bitshares-ui/pull/89/files#diff-2e5f570765c5384009838dde2aa05e2eR89
We can create own or add to the settings store possibility to add own exist account for each user
https://github.com/mmmy/css3demos/wiki/Saving-and-Loading-Charts#managing-saved-charts-access

that additional selector is gone. Where does it come from?

It caused because we initialize tradeview widget each time when we mount component

Where do they come from?

They come from other users those use public user id
https://github.com/blockchainprojects/bitshares-ui/pull/89/files#diff-2e5f570765c5384009838dde2aa05e2eR89
We can create own or add to the settings store possibility to add own exist account for each user
https://github.com/mmmy/css3demos/wiki/Saving-and-Loading-Charts#managing-saved-charts-access

First step I would like to a user to only see templates saved by himself

Where do they come from?

They come from other users those use public user id
https://github.com/blockchainprojects/bitshares-ui/pull/89/files#diff-2e5f570765c5384009838dde2aa05e2eR89
We can create own or add to the settings store possibility to add own exist account for each user
https://github.com/mmmy/css3demos/wiki/Saving-and-Loading-Charts#managing-saved-charts-access

First step I would like to a user to only see templates saved by himself

Is this implemented?

Not yet

there are three ways to implement it:

save data to Local storage
save data to own data storage https://github.com/mmmy/css3demos/wiki/Saving-and-Loading-Charts#using-high-level-saveload
save data to tiny storage provided by http://saveload.tradingview.com (unsafe) https://github.com/mmmy/css3demos/wiki/Saving-and-Loading-Charts#using-demo-charts-and-study-templates-storage

Which way should I choose?

Ive added save /load charts functionality please look.  Ive temporarily used  in memory charts saving

LocalStorage would be preferable

Accidently closed

I`ve implemented in local storage saving and charts deleting. Please review it

I think what it will be cool if users have the possibility to share their charts layout. What do you think about it?

I think what it will be cool if users have the possibility to share their charts layout. What do you think about it?

I agree, in what way would you propose this to be done?

We can add export via JSON file uploading also it can be coded in base64 format. I wonder UI like 2 buttons (expor and import) on the Load charts layout modal

Please rebase

Accepted and forwarded

Rebased to newest develop
Plz review it

fixed issues https://github.com/bitshares/bitshares-ui/pull/2804#issuecomment-506967445

?

?

I`ve updated develop and looks like it merged automatically because it has been merged to the origin develop


[JS] Sticky + off-canvas

Take a look at the docs page for off-canvas. Click the Toggle off-canvas button and scroll the page. The right sticky sidebar get a strange position when it starts to stick; and it keep this position when you close the off-canvas untill you scroll to the top again to 'unstick' it.

mine sticky bar is having class "sticky is-stuck is-at-top" for about 600px scroll and then suddenly class changes to "sticky is-anchored is-at-bottom". Sticky bar isn't anymore at the top..


Not handling NotImplementedError leads to difficult to understand issues

https://github.com/ApeWorX/ape/blob/30c90195190d7915decc97f17bf4ef427337d24c/src/ape/managers/accounts.py#L56
When this issue is raised, it looks like it can't find the address, when the real issue is that the provider does not allow impersonation. The error message should reflect that, or we can see about just not handling this NotImplementedError and letting it propagate upwards.

Let's say I think I have a keyfile with address "0xd8dA6BF26964aF9D7eEd9e03E53415D37aA96045" so I go to grab it:
If we are to raise NotImplemented, it would error with that when I do this:
my_account = accounts["0xd8dA6BF26964aF9D7eEd9e03E53415D37aA96045"]

which seems like a funny error for trying to access an account I thought was mine.

I think adjusting the error message to indicate it could be from either situations is the best way for now

I personally think it is odd to secretly unlock the account from using address-index access and would rather have the user explicitly call unlock_account()

I am okay with this, yes


Docker isnt working?

Only dockerPluginType of mesos currently works.

Is this true? I see that some code was added here: https://github.com/yp-engineering/rundeck-docker-plugin/commit/4fa1cca7bec3abbfca85b285be491a4cbab6b2bd .
Thanks for building this! We've been looking for something like it. Possibly would like to contribute Kubernetes functionality in the future.

Nope, that is completely incorrect! Thanks for taking notice and feel free to submit PR's whenever.


Feature Request: Add Edit Distance metric_fn to tf.metrics or Make a way to Pass Custom metric_fn outside tf.metrics

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
Yes
OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
Windows 8.1
TensorFlow installed from (source or binary):
Binary
TensorFlow version (use command below):
1.4 CPU
Python version:
3.6
CUDA/cuDNN version:
N/A
GPU model and memory:
N/A

Describe the problem
I would like another metric (edit_distance) to be added into tf.metrics for label_error_rate calculation. I'm having trouble passing metric dicts for eval_metric_ops to be used by ModelFnOps that are not part of  tf.metrics.
If that isn't possible, would it be possible for us we can pass our own metric_fns that are outside tf.metrics?
Source code / logs
This is the metric dict I would like to pass as the eval_metric_ops for ModelFnOps:
metric = {"label_error_rate": tf.reduce_mean(tf.edit_distance(tf.cast(y_pred, tf.int32), y_true), name="label_error_rate")}
Where y_pred and y_true are sparse.

We will consider it if we heard more demands for this request.

Alright

I needed this today too.

One workaround I made is wrapped the edit_distance metric with tf.metrics.mean like so edit_distance = tf.metrics.mean(tf.reduce_mean(tf.edit_distance(tf.cast(y_pred, tf.int32), y_true), name=name)) and passed that as the dict value for eval_metric_ops {"edit_distance": edit_distance}. It works but I'm not sure if this is the proper way of doing it.


Limited test size while rendering

When I trying to run the rendering procedure with test_size parameter being -1, the output shows that only 728 frames are being rendered, instead of 8000 frames according to the original video. I checked the code and found that it may be caused by the parameter poses.shape[0], which is 728. But according to the original vedio which is 25 fps and 5:20 long, there should be 8000 frames where the poses.shape[0] should also be 8000 to render all the frames. I don't know how to fix this problem, could anybody help?

What if you change test_pose_file = transforms_val.json to test_pose_file = transforms_train.json in the TorsoNeRFTest_config.txt?


Tauri not support <input type='file'> element ?

Hi,there.
I found html element <input type='file'> can't open select file dialog
Now time, i must use @tauri-apps/api dialog api manual open file dialog
Tauri can support this element ? or i must write Javascript code manual open ?
Thanks !
This is my env information:
Operating System - Mac OS, version 10.15.7 X64
Node.js environment
Node.js - 17.0.1
@tauri-apps/cli - 1.0.0-beta.10
@tauri-apps/api - 1.0.0-beta.8
Global packages
npm - 8.1.0
yarn - 1.22.17
Rust environment
rustc - 1.56.1
cargo - 1.56.0

refer to https://github.com/tauri-apps/wry/issues/305 once it is solved , it will be automatically available to tauri, hopefully


update to use new Graphics package

Ref https://github.com/JuliaLang/julia/pull/10150

Coverage decreased (-3.93%) to 60.65% when pulling 8714c658ca426dfadd3accf409aea174dce1ced4 on jakebolewski:jcb/graphics into e40e11c3569d5ca0de623a076e856cb5953a4cab on timholy:master.


Unexpected lack of images in html report and incomplete output

I have been trying to run fmriprep using fmriprep-docker and I am encountering trouble. I have attached a tree of my bids compliant data set.
tree_sub-test01_2.txt
Given these inputs I expect the html report to look similar to the example reports in the documentation but it contains no images and no confounds information at all:
sub-test01.html.pdf
Second, the output seems incomplete as there is no confounds information at all, and none of the func/_spaces- outputs (eg func/sub-<subject_label>_[specifiers]_space-<space_label>_desc-preproc_bold.nii.gz) that are described in the documentation. See attached derivatives tree.
tree_derivatives.txt
I do get an early error (crash) while fmriprep is running. It is attached, but I have no idea what it means.
crash-20191029-223737-root-fsdir_run_20191029_223642_cc6ba41c_9515_4378_af4b_6028846d074f-f9306052-4f67-44a7-908c-01f4826cbf24.txt
Any help or suggestions would be deeply appreciated.

Command.
fmriprep-docker /net/rc-fs-nfs/ifs/data/NoSync/FNNDSC-NR/neuro/labs/grantlab/research/SCD /net/rc-fs-nfs/ifs/data/NoSync/FNNDSC-NR/neuro/labs/grantlab/research/SCD/derivatives_2 participant --participant-label test01 --fs-license-file ~/license.txt --output-spaces T1w fsnative func > /net/rc-fs-nfs/ifs/data/NoSync/FNNDSC-NR/neuro/labs/grantlab/research/SCD/fmripreprun_2.txt
Log.
fmripreprun_2.txt
The error looked vaguely permissions like, so I made certain the output directory ".../derivatives_2" had complete permissions:
drwxrwxrwx   4 jeff   grantlab_local     54 Oct 29 18:37 derivatives_2

There may be strange interactions with NFS policies here. It runs as root by default, so that it's being recast to nobody makes me think Docker or your filesystem is doing something too clever for its own good. If you add -u $UID to your fmriprep-docker command, it should write all outputs as as your user.
As an aside, I would generally not recommend nesting your derivatives inside your source dataset at runtime. If you're going to nest derivatives inside the raw dataset, then I would do it after everything is done, when it's time to publish or archive, but that's a bit beside the point here... While derivatives/ is ignored and thus should not affect execution, any other name will almost always be picked up, so you're seeing things like:
                ./fmripreprun_2.txt
			Evidence: fmripreprun_2.txt
		./tree_derivatives.txt
			Evidence: tree_derivatives.txt
		./tree_sub-test01.txt
			Evidence: tree_sub-test01.txt

I don't think that's your problem here, but it's generally best to keep things separate, as that gives the opportunity for one error to turn into another when you try to rerun.

Thank you for your help! You were exactly correct about the file system doing something too clever for its own good. I wrote the outputs to my very own home directory and everything is beautiful. I will mark closed, but a slightly more descriptive error message, or a final warning in the report itself, if there is some catastrophic failure in write permissions would be a really great addition.

I add just for someone's future reference, that the -u $UID threw an error that allowed me to diagnose the problem, but did not fix it. Interpreting the error, anything docker writes initially (folder for mount points) are created as root, and if that ownership is subsequently transfer to UID. If ownership gets altered by some file system cleverness (root is squashed), then the permissions transfer doesn't work for the orphaned files. In my case if the initial folders and files were owned by UID to start I don't think I would have had an issue.

Thanks for that feedback. I'm glad you were able to resolve the issue. I opened #1846 to track improvements to this reporting. If you have reproducible conditions you can set up on a local system, that would help a lot. Feel free to comment on that issue with any suggestions you may have.


Require padding lines between statements

https://eslint.org/docs/rules/padding-line-between-statements

Closed in favor of #68.


EEPROM version register documentation mismatch with library ?

We're using both Medical/Extended-grade and standard versions of the sensor.
In the library during initialization, the following check is performed in the EEPROM version register 0x240b
https://github.com/melexis/mlx90632-library/blob/0b1be08be1191f7244b3b65eac74a1614edaf3b8/src/mlx90632.c#L467
with
https://github.com/melexis/mlx90632-library/blob/0b1be08be1191f7244b3b65eac74a1614edaf3b8/inc/mlx90632.h#L192
Yet the latest datasheet from your website does not document this register. It however documents the product code like this:

Questions:
Is the magic 0x0500 always reflecting a medical-grade device or which meaning does it have ? Why not use in the library the product code as a way to identify a medical-grade device ?

0x0500 does not mention anything about medical-grade device, so I am not sure why you would think this is connected?
The extended range is read at initialization (https://github.com/melexis/mlx90632-library/blob/0b1be08be1191f7244b3b65eac74a1614edaf3b8/src/mlx90632.c#L446) from EE_VERSION (https://github.com/melexis/mlx90632-library/blob/master/inc/mlx90632.h#L87) which is on address 0x240B and it defines the eeprom content variation which enables us to keep some backwards compatibility with older versions as well as with newer extended range versions. The product code you are referencing is not present in older devices.

I am cleaning up the open issues and this seems to be resolved.


Stackable Splash Potions in config

Could we get the ability to config being able to stack splash potions? The default stack could still be 1, but as a player you'd be able to config this if wanted.

I didn't change this on purporse because splash potions stackable would have been too broken to my mind.
However, I thought of something that may make it more balanced: stackable splash potions but it has a cooldown like ender pearls for example. What do you think about it?

a cooldown on stackable potions sounds like a great solution to the issue of balancing it, even if the cooldown is very long


 The Test bench is trying to introduce delay to each channels, but no delay.

This is a DV only comment, so please do not change the subject to indicate anything other than a DV issue.
This has been fixed and should be working in 0.8.5 release.

My mistake. This was done in a local area, but did not make it into my pull. Should be in next drop.

I can see there are many changes in the CA DV.  There is no instruction as how to make delay happen (When we say delay, I mean delay skew between two lanes).  If I just follow the README in ca/dv directory:
cmd to run test:

Go to directory '/design/ca/dv'
Use command :   xrun -f ca_tb.args
This will help run the preset test 'ca_basic_test_c' from the script file 'ca_tb.args'

I did not see delay skew from simulation right at beginning. If you have any instruction how to make that happen, I can try again.

Updated 0.8.7 with updated README and changed default simulation to add delay.

CA test bench has the updated delay skew for 8 channel. This has been verified. Issue closed.


Uncaught ReferenceError: path is not defined

[Enter steps to reproduce below:]

Install Atom V0.199.0
Open Atom
"Toggle Projects List"

Per Atom release notes:
"Fixed an issue where fs and path would be accidentally available as global variables"
Atom Version: 0.199.0
System: linux 3.13.0-52-generic
Thrown From: git-projects package, v1.13.0
Stack Trace
Uncaught ReferenceError: path is not defined
At /home/chris/.atom/packages/git-projects/lib/models/project.coffee:22

ReferenceError: path is not defined
  at Project.module.exports.Project.readConfigFile (/home/chris/.atom/packages/git-projects/lib/models/project.coffee:22:24)
  at new Project (/home/chris/.atom/packages/git-projects/lib/models/project.coffee:11:6)
  at /home/chris/.atom/packages/git-projects/lib/git-projects.coffee:113:29
  at Set.forEach (native)
  at Object.module.exports.findGitRepos (/home/chris/.atom/packages/git-projects/lib/git-projects.coffee:108:15)
  at /home/chris/.atom/packages/git-projects/lib/views/projects-list-view.coffee:54:29

Commands
     -0:02.8.0 git-projects:toggle (ul.list-inline.tab-bar.inset-panel)

Config
{
  "core": {
    "disabledPackages": [
      "autocomplete-plus-async",
      "emmet",
      "vim-mode",
      "linter-csslint",
      "todo-list",
      "package-sync",
      "autocomplete-plus",
      "auto-indent",
      "jsonlint"
    ],
    "autoHideMenuBar": true,
    "projectHome": "/var/www/html",
    "followSymlinks": false
  },
  "git-projects": {
    "rootPath": "/var/www/html"
  }
}

Installed Packages
# User
autoclose-html, v0.16.0
color-picker, v1.7.0
docblockr, v0.7.1
file-icons, v1.5.5
git-projects, v1.13.0
language-apache, v1.3.0
language-gitignore, v0.2.0
language-ini, v1.10.0
linter, v0.12.2
linter-php, v0.0.12
travis-ci-status, v0.14.1

# Dev
No dev packages

Thank you for reporting the issue.
I have just merged a PR that should fix this –  https://github.com/prrrnd/atom-git-projects/commit/667d49d12f0aa34336f436c34ec6c62e065e7a03


ddl: Fix sync empty schema diff

What problem does this PR solve?
Issue Number: close https://github.com/pingcap/tiflash/issues/8578
Problem Summary: When there is conflict in concurrency DDL, it will skip some schema version, which generate an empty SchemaDiff.
What is changed and how it works?
Skip when meets an empty SchemaDiff in the non-latest schema version
As that in the relese-7.1 branch https://github.com/pingcap/tiflash/issues/8578#issuecomment-1869402064
Refine the readme of running integration tests in local
Check List
Tests

[ ] Unit test
[x] Integration test
[ ] Manual test (add detailed scripts or steps below)
[ ] No code

Side effects

[ ] Performance regression: Consumes more CPU
[ ] Performance regression: Consumes more Memory
[ ] Breaking backward compatibility

Documentation

[ ] Affects user behaviors
[ ] Contains syntax changes
[ ] Contains variable changes
[ ] Contains experimental features
[ ] Changes MySQL compatibility

Release note

Fix the crash issue after TiDB's concurrent DDL meets a conflict

/run-all-tests

/run-unit-test


Need a link so that users can go to the Create new account screen in case having no account to connect to dApp (improve #798)

Description the issue
Need a link so that users can go to the Create new account screen in case having no account to connect to dApp (improve #798 )

Resolved in new UI version


Enable flag developmentDependency

Hi
Please add the developmentDependency to nuget package.
This will automatically add it in the packages.config file so it will not be referenced in the nuget package build form this project.

Fixed in https://github.com/loresoft/msbuildtasks/pull/158

if this is fixed...can it be closed please?


sound created by Tacotron-2 is much more longer

Hi, everyone.
Firstly, I'd like to thank you for your excellent Tacotron-2 code! @Rayhane-mamah
I'm a rookie in TTS, and I'm trying to run this Tacotron-2 model on my server. But I came up with a problem.
I was training the end-to-end TTS with LJSpeech. When I listen to the wavs in eval-dir/wavs after 60k wavenet training step, I found it was good. So I tried to synthesis wav from TTS.
In the first time, I tried 'Hello.' But wavenet told me that it need generate about 80000 samples. The sample rate was 22050, which means that 'Hello' takes about 4 seconds! When it finished, I found that the wav is horrible..... I can hear something like hello, but other part of this audio is completely mess.
In the second time, I tried 'Scientists at the CERN laboratory say they have discovered a new particle.' And Wavenet told me that it need 2560000 samples! WOW! So, I checked the npy file created by Tacotron2, and I found that it is right. The npy file contains a 10000×80 array.I'm not sure whether the output is right.
So the question is: why did Wavenet try to generate so many samples?
Would you please be so kind to help me on this problem? @Rayhane-mamah
I'd like to provide my hparams here. I have changed some of them because I'd like to comparte Tacotron2 with other mel-spectrogram generator...
tacotron_num_gpus = 1, #Determines the number of gpus in use for Tacotron training.
wavenet_num_gpus = 1, #Determines the number of gpus in use for WaveNet training.
split_on_cpu = True, #Determines whether to split data on CPU or on first GPU. This is automatically True when more than 1 GPU is used.
#(Recommend: False on slow CPUs/Disks, True otherwise for small speed boost)
###########################################################################################################################################
#Audio

num_mels = 80, #Number of mel-spectrogram channels and local conditioning dimensionality
num_freq = 513, # (= n_fft / 2 + 1) only used when adding linear spectrograms post processing network
rescale = True, #Whether to rescale audio prior to preprocessing
rescaling_max = 0.999, #Rescaling value

clip_mels_length = True, #For cases of OOM (Not really recommended, only use if facing unsolvable OOM errors, also consider clipping your samples to smaller chunks)
max_mel_frames = 1000,  #Only relevant when clip_mels_length = True, please only use after trying output_per_steps=3 and still getting OOM errors.

use_lws=True, #Only used to set as True if using WaveNet, no difference in performance is observed in either cases.
silence_threshold=2, #silence threshold used for sound trimming for wavenet preprocessing

#Mel spectrogram
n_fft = 1024, #Extra window size is filled with 0 paddings to match this parameter
hop_size = 256, #For 22050Hz, 275 ~= 12.5 ms (0.0125 * sample_rate)
win_size = 1024, #For 22050Hz, 1100 ~= 50 ms (If None, win_size = n_fft) (0.05 * sample_rate)
sample_rate = 22050, #22050 Hz (corresponding to ljspeech dataset) (sox --i <filename>)
frame_shift_ms = None, #Can replace hop_size parameter. (Recommended: 12.5)
magnitude_power = 2., #The power of the spectrogram magnitude (1. for energy, 2. for power)

#M-AILABS (and other datasets) trim params (there parameters are usually correct for any data, but definitely must be tuned for specific speakers)
trim_silence = True, #Whether to clip silence in Audio (at beginning and end of audio only, not the middle)
trim_fft_size = 1024, #Trimming window size
trim_hop_size = 256, #Trimmin hop length
trim_top_db = 23, #Trimming db difference from reference db (smaller==harder trim.)

#Mel and Linear spectrograms normalization/scaling and clipping
signal_normalization = True, #Whether to normalize mel spectrograms to some predefined range (following below parameters)
allow_clipping_in_normalization = True, #Only relevant if mel_normalization = True
symmetric_mels = True, #Whether to scale the data to be symmetric around 0. (Also multiplies the output range by 2, faster and cleaner convergence)
max_abs_value = 4., #max absolute value of data. If symmetric, data will be [-max, max] else [0, max] (Must not be too big to avoid gradient explosion,
																									  #not too small for fast convergence)
normalize_for_wavenet = True, #whether to rescale to [0, 1] for wavenet. (better audio quality)
clip_for_wavenet = True, #whether to clip [-max, max] before training/synthesizing with wavenet (better audio quality)
wavenet_pad_sides = 1, #Can be 1 or 2. 1 for pad right only, 2 for both sides padding.

#Contribution by @begeekmyfriend
#Spectrogram Pre-Emphasis (Lfilter: Reduce spectrogram noise and helps model certitude levels. Also allows for better G&L phase reconstruction)
preemphasize = True, #whether to apply filter
preemphasis = 0.97, #filter coefficient.

#Limits
min_level_db = -100,
ref_level_db = 20,
fmin = 125, #Set this to 55 if your speaker is male! if female, 95 should help taking off noise. (To test depending on dataset. Pitch info: male~[65, 260], female~[100, 525])
fmax = 7600, #To be increased/reduced depending on data.

#Griffin Lim
power = 1.4, #Only used in G&L inversion, usually values between 1.2 and 1.5 are a good choice.
griffin_lim_iters = 60, #Number of G&L iterations, typically 30 is enough but we use 60 to ensure convergence.
###########################################################################################################################################

#Tacotron
#Model general type
outputs_per_step = 1, #number of frames to generate at each decoding step (increase to speed up computation and allows for higher batch size, decreases G&L audio quality)
stop_at_any = True, #Determines whether the decoder should stop when predicting <stop> to any frame or to all of them (True works pretty well)
batch_norm_position = 'after', #Can be in ('before', 'after'). Determines whether we use batch norm before or after the activation function (relu). Matter for debate.

#Input parameters
embedding_dim = 512, #dimension of embedding space

#Encoder parameters
enc_conv_num_layers = 3, #number of encoder convolutional layers
enc_conv_kernel_size = (5, ), #size of encoder convolution filters for each layer
enc_conv_channels = 512, #number of encoder convolutions filters for each layer
encoder_lstm_units = 256, #number of lstm units for each direction (forward and backward)

#Attention mechanism
smoothing = False, #Whether to smooth the attention normalization function
attention_dim = 128, #dimension of attention space
attention_filters = 32, #number of attention convolution filters
attention_kernel = (31, ), #kernel size of attention convolution
cumulative_weights = True, #Whether to cumulate (sum) all previous attention weights or simply feed previous weights (Recommended: True)

#Attention synthesis constraints
#"Monotonic" constraint forces the model to only look at the forwards attention_win_size steps.
#"Window" allows the model to look at attention_win_size neighbors, both forward and backward steps.
synthesis_constraint = False,  #Whether to use attention windows constraints in synthesis only (Useful for long utterances synthesis)
synthesis_constraint_type = 'window', #can be in ('window', 'monotonic').
attention_win_size = 7, #Side of the window. Current step does not count. If mode is window and attention_win_size is not pair, the 1 extra is provided to backward part of the window.

#Decoder
prenet_layers = [256, 256], #number of layers and number of units of prenet
decoder_layers = 2, #number of decoder lstm layers
decoder_lstm_units = 1024, #number of decoder lstm units on each layer
max_iters = 10000, #Max decoder steps during inference (Just for safety from infinite loop cases)

#Residual postnet
postnet_num_layers = 5, #number of postnet convolutional layers
postnet_kernel_size = (5, ), #size of postnet convolution filters for each layer
postnet_channels = 512, #number of postnet convolution filters for each layer

#CBHG mel->linear postnet
cbhg_kernels = 8, #All kernel sizes from 1 to cbhg_kernels will be used in the convolution bank of CBHG to act as "K-grams"
cbhg_conv_channels = 128, #Channels of the convolution bank
cbhg_pool_size = 2, #pooling size of the CBHG
cbhg_projection = 256, #projection channels of the CBHG (1st projection, 2nd is automatically set to num_mels)
cbhg_projection_kernel_size = 3, #kernel_size of the CBHG projections
cbhg_highwaynet_layers = 4, #Number of HighwayNet layers
cbhg_highway_units = 128, #Number of units used in HighwayNet fully connected layers
cbhg_rnn_units = 128, #Number of GRU units used in bidirectional RNN of CBHG block. CBHG output is 2x rnn_units in shape

#Loss params
mask_encoder = True, #whether to mask encoder padding while computing attention. Set to True for better prosody but slower convergence.
mask_decoder = False, #Whether to use loss mask for padded sequences (if False, <stop_token> loss function will not be weighted, else recommended pos_weight = 20)
cross_entropy_pos_weight = 1, #Use class weights to reduce the stop token classes imbalance (by adding more penalty on False Negatives (FN)) (1 = disabled)
predict_linear = True, #Whether to add a post-processing network to the Tacotron to predict linear spectrograms (True mode Not tested!!)
###########################################################################################################################################

#Wavenet
# Input type:
# 1. raw [-1, 1]
# 2. mulaw [-1, 1]
# 3. mulaw-quantize [0, mu]
# If input_type is raw or mulaw, network assumes scalar input and
# discretized mixture of logistic distributions output, otherwise one-hot
# input and softmax output are assumed.
#Model general type
input_type="raw", #Raw has better quality but harder to train. mulaw-quantize is easier to train but has lower quality.
quantize_channels=2**16,  # 65536 (16-bit) (raw) or 256 (8-bit) (mulaw or mulaw-quantize) // number of classes = 256 <=> mu = 255
use_bias = True, #Whether to use bias in convolutional layers of the Wavenet
legacy = True, #Whether to use legacy mode: Multiply all skip outputs but the first one with sqrt(0.5) (True for more early training stability, especially for large models)
residual_legacy = True, #Whether to scale residual blocks outputs by a factor of sqrt(0.5) (True for input variance preservation early in training and better overall stability)

#Model Losses parmeters
#Minimal scales ranges for MoL and Gaussian modeling
log_scale_min=float(np.log(1e-14)), #Mixture of logistic distributions minimal log scale
log_scale_min_gauss = float(np.log(9.1188196 * 1e-4)), #Gaussian distribution minimal allowed log scale
#Loss type
cdf_loss = True, #Whether to use CDF loss in Gaussian modeling. Advantages: non-negative loss term and more training stability. (Automatically True for MoL)

#model parameters
#To use Gaussian distribution as output distribution instead of mixture of logistics, set "out_channels = 2" instead of "out_channels = 10 * 3". (UNDER TEST)
out_channels = 2, #This should be equal to quantize channels when input type is 'mulaw-quantize' else: num_distributions * 3 (prob, mean, log_scale).
layers = 20, #Number of dilated convolutions (Default: Simplified Wavenet of Tacotron-2 paper)
stacks = 2, #Number of dilated convolution stacks (Default: Simplified Wavenet of Tacotron-2 paper)
residual_channels = 128, #Number of residual block input/output channels.
gate_channels = 256, #split in 2 in gated convolutions
skip_out_channels = 128, #Number of residual block skip convolution channels.
kernel_size = 3, #The number of inputs to consider in dilated convolutions.

#Upsampling parameters (local conditioning)
cin_channels = 80, #Set this to -1 to disable local conditioning, else it must be equal to num_mels!!
upsample_conditional_features = True, #Whether to repeat conditional features or upsample them (The latter is recommended)
#Upsample types: ('1D', '2D', 'Resize', 'SubPixel')
#All upsampling initialization/kernel_size are chosen to omit checkerboard artifacts as much as possible. (Resize is designed to omit that by nature).
#To be specific, all initial upsample weights/biases (when NN_init=True) ensure that the upsampling layers act as a "Nearest neighbor upsample" of size "hop_size" (checkerboard free).
#1D spans all frequency bands for each frame (channel-wise) while 2D spans "freq_axis_kernel_size" bands at a time. Both are vanilla transpose convolutions.
#Resize is a 2D convolution that follows a Nearest Neighbor (NN) resize. For reference, this is: "NN resize->convolution".
#Finally, SubPixel (2D) is the ICNR version (initialized to be equivalent to "convolution->NN resize") of Sub-Pixel convolutions. also called "checkered artifact free sub-pixel conv".
upsample_type = 'SubPixel', #Type of the upsampling deconvolution. Can be ('1D' or '2D', 'Resize', 'SubPixel').
upsample_activation = 'Relu', #Activation function used during upsampling. Can be ('LeakyRelu', 'Relu' or None)
upsample_scales = [8, 8, 4], #prod(upsample_scales) should be equal to hop_size
freq_axis_kernel_size = 5, #Only used for 2D upsampling types. This is the number of requency bands that are spanned at a time for each frame.
leaky_alpha = 0.4, #slope of the negative portion of LeakyRelu (LeakyRelu: y=x if x>0 else y=alpha * x)
NN_init = True, #Determines whether we want to initialize upsampling kernels/biases in a way to ensure upsample is initialize to Nearest neighbor upsampling. (Mostly for debug)
NN_scaler = 0.1, #Determines the initial Nearest Neighbor upsample values scale. i.e: upscaled_input_values = input_values * NN_scaler (1. to disable)

#global conditioning
gin_channels = -1, #Set this to -1 to disable global conditioning, Only used for multi speaker dataset. It defines the depth of the embeddings (Recommended: 16)
use_speaker_embedding = True, #whether to make a speaker embedding
n_speakers = 5, #number of speakers (rows of the embedding)
speakers_path = None, #Defines path to speakers metadata. Can be either in "speaker\tglobal_id" (with header) tsv format, or a single column tsv with speaker names. If None, use "speakers".
speakers = ['speaker0', 'speaker1', #List of speakers used for embeddings visualization. (Consult "wavenet_vocoder/train.py" if you want to modify the speaker names source).
			'speaker2', 'speaker3', 'speaker4'], #Must be consistent with speaker ids specified for global conditioning for correct visualization.
###########################################################################################################################################

#Tacotron Training
#Reproduction seeds
tacotron_random_seed = 5339, #Determines initial graph and operations (i.e: model) random state for reproducibility
tacotron_data_random_state = 1234, #random state for train test split repeatability

#performance parameters
tacotron_swap_with_cpu = False, #Whether to use cpu as support to gpu for decoder computation (Not recommended: may cause major slowdowns! Only use when critical!)

#train/test split ratios, mini-batches sizes
tacotron_batch_size = 32, #number of training samples on each training steps
#Tacotron Batch synthesis supports ~16x the training batch size (no gradients during testing).
#Training Tacotron with unmasked paddings makes it aware of them, which makes synthesis times different from training. We thus recommend masking the encoder.
tacotron_synthesis_batch_size = 1, #DO NOT MAKE THIS BIGGER THAN 1 IF YOU DIDN'T TRAIN TACOTRON WITH "mask_encoder=True"!!
tacotron_test_size = 0.05, #% of data to keep as test data, if None, tacotron_test_batches must be not None. (5% is enough to have a good idea about overfit)
tacotron_test_batches = None, #number of test batches.

#Learning rate schedule
tacotron_decay_learning_rate = True, #boolean, determines if the learning rate will follow an exponential decay
tacotron_start_decay = 40000, #Step at which learning decay starts
tacotron_decay_steps = 24500, #Determines the learning rate decay slope (UNDER TEST)
tacotron_decay_rate = 0.5, #learning rate decay rate (UNDER TEST)
tacotron_initial_learning_rate = 1e-3, #starting learning rate
tacotron_final_learning_rate = 1e-5, #minimal learning rate

#Optimization parameters
tacotron_adam_beta1 = 0.9, #AdamOptimizer beta1 parameter
tacotron_adam_beta2 = 0.999, #AdamOptimizer beta2 parameter
tacotron_adam_epsilon = 1e-6, #AdamOptimizer Epsilon parameter

#Regularization parameters
tacotron_reg_weight = 1e-7, #regularization weight (for L2 regularization)
tacotron_scale_regularization = False, #Whether to rescale regularization weight to adapt for outputs range (used when reg_weight is high and biasing the model)
tacotron_zoneout_rate = 0.1, #zoneout rate for all LSTM cells in the network
tacotron_dropout_rate = 0.5, #dropout rate for all convolutional layers + prenet
tacotron_clip_gradients = True, #whether to clip gradients

#Evaluation parameters
tacotron_natural_eval = False, #Whether to use 100% natural eval (to evaluate Curriculum Learning performance) or with same teacher-forcing ratio as in training (just for overfit)

#Decoder RNN learning can take be done in one of two ways:
#	Teacher Forcing: vanilla teacher forcing (usually with ratio = 1). mode='constant'
#	Scheduled Sampling Scheme: From Teacher-Forcing to sampling from previous outputs is function of global step. (teacher forcing ratio decay) mode='scheduled'
#The second approach is inspired by:
#Bengio et al. 2015: Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks.
#Can be found under: https://arxiv.org/pdf/1506.03099.pdf
tacotron_teacher_forcing_mode = 'constant', #Can be ('constant' or 'scheduled'). 'scheduled' mode applies a cosine teacher forcing ratio decay. (Preference: scheduled)
tacotron_teacher_forcing_ratio = 1., #Value from [0., 1.], 0.=0%, 1.=100%, determines the % of times we force next decoder inputs, Only relevant if mode='constant'
tacotron_teacher_forcing_init_ratio = 1., #initial teacher forcing ratio. Relevant if mode='scheduled'
tacotron_teacher_forcing_final_ratio = 0., #final teacher forcing ratio. (Set None to use alpha instead) Relevant if mode='scheduled'
tacotron_teacher_forcing_start_decay = 10000, #starting point of teacher forcing ratio decay. Relevant if mode='scheduled'
tacotron_teacher_forcing_decay_steps = 40000, #Determines the teacher forcing ratio decay slope. Relevant if mode='scheduled'
tacotron_teacher_forcing_decay_alpha = None, #teacher forcing ratio decay rate. Defines the final tfr as a ratio of initial tfr. Relevant if mode='scheduled'

#Speaker adaptation parameters
tacotron_fine_tuning = False, #Set to True to freeze encoder and only keep training pretrained decoder. Used for speaker adaptation with small data.
###########################################################################################################################################

#Wavenet Training
wavenet_random_seed = 5339, # S=5, E=3, D=9 :)
wavenet_data_random_state = 1234, #random state for train test split repeatability

#performance parameters
wavenet_swap_with_cpu = False, #Whether to use cpu as support to gpu for synthesis computation (while loop).(Not recommended: may cause major slowdowns! Only use when critical!)

#train/test split ratios, mini-batches sizes
wavenet_batch_size = 8, #batch size used to train wavenet.
#During synthesis, there is no max_time_steps limitation so the model can sample much longer audio than 8k(or 13k) steps. (Audio can go up to 500k steps, equivalent to ~21sec on 24kHz)
#Usually your GPU can handle ~2x wavenet_batch_size during synthesis for the same memory amount during training (because no gradients to keep and ops to register for backprop)
wavenet_synthesis_batch_size = 10 * 2, #This ensure that wavenet synthesis goes up to 4x~8x faster when synthesizing multiple sentences. Watch out for OOM with long audios.
wavenet_test_size = None, #% of data to keep as test data, if None, wavenet_test_batches must be not None
wavenet_test_batches = 1, #number of test batches.

#Learning rate schedule
wavenet_lr_schedule = 'exponential', #learning rate schedule. Can be ('exponential', 'noam')
wavenet_learning_rate = 1e-4, #wavenet initial learning rate
wavenet_warmup = float(4000), #Only used with 'noam' scheme. Defines the number of ascending learning rate steps.
wavenet_decay_rate = 0.5, #Only used with 'exponential' scheme. Defines the decay rate.
wavenet_decay_steps = 200000, #Only used with 'exponential' scheme. Defines the decay steps.

#Optimization parameters
wavenet_adam_beta1 = 0.9, #Adam beta1
wavenet_adam_beta2 = 0.999, #Adam beta2
wavenet_adam_epsilon = 1e-6, #Adam Epsilon

#Regularization parameters
wavenet_clip_gradients = True, #Whether the clip the gradients during wavenet training.
wavenet_ema_decay = 0.9999, #decay rate of exponential moving average
wavenet_weight_normalization = False, #Whether to Apply Saliman & Kingma Weight Normalization (reparametrization) technique. (Used in DeepVoice3, not critical here)
wavenet_init_scale = 1., #Only relevent if weight_normalization=True. Defines the initial scale in data dependent initialization of parameters.
wavenet_dropout = 0.05, #drop rate of wavenet layers
wavenet_gradient_max_norm = 100.0, #Norm used to clip wavenet gradients
wavenet_gradient_max_value = 5.0, #Value used to clip wavenet gradients

#training samples length
max_time_sec = None, #Max time of audio for training. If None, we use max_time_steps.
max_time_steps = 11000, #Max time steps in audio used to train wavenet (decrease to save memory) (Recommend: 8000 on modest GPUs, 13000 on stronger ones)

#Evaluation parameters
wavenet_natural_eval = False, #Whether to use 100% natural eval (to evaluate autoregressivity performance) or with teacher forcing to evaluate overfit and model consistency.

#Tacotron-2 integration parameters
train_with_GTA = True, #Whether to use GTA mels to train WaveNet instead of ground truth mels.
###########################################################################################################################################

#Eval/Debug parameters
#Eval sentences (if no eval text file was specified during synthesis, these sentences are used for eval)
sentences = [
# From July 8, 2017 New York Times:
'Scientists at the CERN laboratory say they have discovered a new particle.',
'There\'s a way to measure the acute emotional intelligence that has never gone out of style.',
'President Trump met with other leaders at the Group of 20 conference.',
'The Senate\'s bill to repeal and replace the Affordable Care Act is now imperiled.',
# From Google's Tacotron example page:
'Generative adversarial network or variational auto-encoder.',
'Basilar membrane and otolaryngology are not auto-correlations.',
'He has read the whole thing.',
'He reads books.',
'He thought it was time to present the present.',
'Thisss isrealy awhsome.',
'Punctuation sensitivity, is working.',
'Punctuation sensitivity is working.',
"Peter Piper picked a peck of pickled peppers. How many pickled peppers did Peter Piper pick?",
"She sells sea-shells on the sea-shore. The shells she sells are sea-shells I'm sure.",
"Tajima Airport serves Toyooka.",
#From The web (random long utterance)
# 'On offering to help the blind man, the man who then stole his car, had not, at that precise moment, had any evil intention, quite the contrary, \
# what he did was nothing more than obey those feelings of generosity and altruism which, as everyone knows, \
# are the two best traits of human nature and to be found in much more hardened criminals than this one, a simple car-thief without any hope of advancing in his profession, \
# exploited by the real owners of this enterprise, for it is they who take advantage of the needs of the poor.',
# A final Thank you note!
'Thank you so much for your support!',
],

#Wavenet Debug
wavenet_synth_debug = False, #Set True to use target as debug in WaveNet synthesis.
wavenet_debug_wavs = ['training_data/audio/audio-LJ001-0008.npy'], #Path to debug audios. Must be multiple of wavenet_num_gpus.
wavenet_debug_mels = ['training_data/mels/mel-LJ001-0008.npy'],

Hello,
I'm facing the same issue, did you get any way around that?
thank you


[BUG] UI goes into error state after no name error with multiple VM creation

Describe the bug

When you try to create multiple VMs with no name you can't then add a name and save.
To Reproduce
Steps to reproduce the behavior:

Start to create a new VM
Don't put in a name
Select multiple instances and leave it at 2
Add the volume and network
Click Create

After error put in a name and click create

Expected behavior

You should be able to add a name and click save
Support bundle

supportbundle_3f342501-1f22-48b0-bc6f-3bb4393f3977_2023-03-15T18-10-35Z.zip
Environment

Harvester ISO version: v1.1.2-rc3 and v1.1.1
Underlying Infrastructure (e.g. Baremetal with Dell PowerEdge R630): I tested this on a single node libvirt 1.1.1 VM, and on a 4 node physical cluster (DL160) with v1.1.2-rc3

Additional context
Add any other context about the problem here.
The error messages are different if you are creating a single VM, and it doesn't go into the error state. After the error in the single VM creation you can just add a name and it will create afterwards.

Tested in v1.1.2-rc3 with external ui-source to pull new dashboard code.
Verification steps
Steps to reproduce the behavior:

Start to create a new VM
Don't put in a name
Select multiple instances and leave it at 2
Add the volume and network
Click Create

After error put in a name and click create

Expected results

After first error you should be able to put in name and create VMs.


http://www.asiandate.com/login/mailsystem/inbox/message828231441.html?token=7eb8a82b8f074a490ac819b4bf17c24f

ℹ Please fill out this template when filing an issue.
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Per our *CONTRIBUTING guidelines, we use GitHub for
bugs and feature requests, not general support. Other issues should be opened on Stack Overflow with the tag alamofire.
Please remove this line and everything above it before submitting.

[ ] I've read, understood, and done my best to follow the *CONTRIBUTING guidelines.

What did you do?
ℹ Please replace this with what you did.
What did you expect to happen?
ℹ Please replace this with what you expected to happen.
What happened instead?
ℹ Please replace this with of what happened instead.
Alamofire Environment
Alamofire version:
Xcode version:
Swift version:
Platform(s) running Alamofire:
macOS version running Xcode:
Demo Project
ℹ Please link to or upload a project we can download that reproduces the issue.

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COVID-19 GridWorkers are now at risk to get coronavirus.

it's not fair that humans are susceptible to coronavirus disease while databases are not.
Now GridWorkers have a chance to get coronavirus infection and even die of it.

workers from common pool should infects each other

Should a node drop messages is gotten from infected remote node?

Guys, don't panic!

Guys, don't panic!

Unless it is not infected itself.

It doesn't matter.


@MridulS Is this essentially covered by our linter and formatter pre-commit routine?

Yeah, it should. We can always add more ruff things.


Add seccompProfile field in pod's security context

This change has been implemented for the following control-plane
components:

Pod checkpointer.
Kube apiserver.
Kube controller manager.
Kube scheduler.

Fixes #1107

Add an explanation also the PR desc links to the relevant issues.

If the PSP is not accurate then pod won't be mirrored, that's the reason we have dedicated PSP for podcheckpointer.

Hm, can we change commit title to something better representing changed done by this commit? We do not "add" anything, but we replace old annotation with dedicated field in pod spec.
Also, we do not "implement it for control-plane components". Control-plane components are self-hosted deployments/deamonsets. This commit changes it only for bootstrap controlplane, which is currently NOT checkpointed (as it has no checkpointer.alpha.coreos.com/checkpoint: "true" annotation).

If the PSP is not accurate then pod won't be mirrored, that's the reason we have dedicated PSP for podcheckpointer.

I still don't understand. What has PSP for podcheckpointer to do with mirrored pods? Mirrored pods should use their own PSPs if I understand correctly.

Hm, can we change commit title to something better representing changed done by this commit? We do not "add" anything, but we replace old annotation with dedicated field in pod spec.

We are not replacing with the same thing. So added a line in the commit.

Also, we do not "implement it for control-plane components". Control-plane components are self-hosted deployments/deamonsets. This commit changes it only for bootstrap controlplane, which is currently NOT checkpointed (as it has no checkpointer.alpha.coreos.com/checkpoint: "true" annotation).

IMHO anything that does control plane activity bootstrap or not is control plane component.

I still don't understand. What has PSP for podcheckpointer to do with mirrored pods? Mirrored pods should use their own PSPs if I understand correctly.

It is not necessary for a mirrored pod to use their own PSP. Any PSP that admits the pod spec should work.

Hm, can we change commit title to something better representing changed done by this commit? We do not "add" anything, but we replace old annotation with dedicated field in pod spec.

We are not replacing with the same thing. So added a line in the commit.

If that's the case, then maybe we should remove in separate commit? But then it will produce broken revision.

IMHO anything that does control plane activity bootstrap or not is control plane component.

Okay, then still, this only affects bootstrap manifests, so saying "implement it for control-plane components" means implement for all variants of control-plane components, including bootstrap AND self-hosted ones.

I still don't understand. What has PSP for podcheckpointer to do with mirrored pods? Mirrored pods should use their own PSPs if I understand correctly.

It is not necessary for a mirrored pod to use their own PSP. Any PSP that admits the pod spec should work.

"Any PSP that admits" doesn't sound like the best solution for me. Anyway, still, this PR changes PSP used for running pod-checkpointer pod, which should have nothing to do with actually mirroring the pod if I understand correctly, hence my question.


Web: Uploading a file

How would I upload a file from my browser via compose for web?
I have tried using the FileInput control but I am unable to grab the actual file?
I am using Ktor on the backend.
Are there any examples for uploading a file from compose for web?
Thanks

Not related to Compose, but simple JS file api:
@Composable
fun Upload(title: String, onDone: (ByteArray) -> Unit) {
    Column {
        var uploadButton: HTMLInputElement? = null
        Input(type = InputType.File) {
            hidden() // Hidden, because I dislike the HTML file button
            accept(".xlsx") // optional

            ref {
                uploadButton = it
                onDispose {
                    uploadButton = null
                }
            }

            onChange {
                val file: File = it.target.files!!.asList().single()
                scope.launch {
                   file.buffer() // do something with its content, eg
                }
            }
        }
        Button(title) {
            uploadButton?.value = "" // reset the previous file to upload a new file again
            uploadButton?.click()
        }
    }
}

suspend fun Blob.buffer(): ArrayBuffer = suspendCoroutine {
    FileReader().apply {
        onload = { _ ->
            it.resume(result as ArrayBuffer)
        }
        onerror = { _ ->
            it.resumeWithException(Error("reading file: $this"))
        }
    }.readAsArrayBuffer(this)
}

fun ArrayBuffer.toByteArray(): ByteArray = Int8Array(this).unsafeCast<ByteArray>()

Please check the following ticket on YouTrack for follow-ups to this issue. GitHub issues will be closed in the coming weeks.


Change LinkLabel back to Label in error status bar

This PR changed LinkLabel(which I changed in https://github.com/godotengine/godot/pull/23875) back to Label - I found it better than current version, because I found that cutting off the long error message is both confusing and annoying - now it will wrap-off as before

The error jumping is preserved untouched.

Thanks!


Readds deferred log statements.

I noticed you added metrics to GetFile - we should have them on PutFile too. But we can make that a separate issue.


Incorrect results on Travis CI

Locally I get ~83% coverage, but I only get ~52% on Travis CI. Perhaps it's not a SimpleCov bug, but hoping someone might have some ideas. Using SimpleCov 0.9.1. Ruby version is identical in both environments (ruby 2.1.5p273 (2014-11-13 revision 48405) [x86_64-linux]). Tests are run with RSpec 3.1.0. Any suggestions appreciated :)

Strangely, I'd like to add that using the Code Climate gem seems to work directly despite the fact that it's using the same version of SimpleCov under the hood.

I can't really diagnose your problem without any code or more information, but it may be related to running parallel specs, the command you run the tests with locally vs. on ci, or your merge timeout, if any.
Please see https://github.com/colszowka/simplecov/issues/340 and report back.

Sorry for the lack of details. Hopefully the points below help

This is not a Rails app
My command locally is the same as on Travis CI bundle exec rspec --tag ~disabled
I have no .simplecov file (however, I added one and this didn't change anything)
My tests are not run in parallel

Without more code there's really nothing I can do.

@michaelmior I had a similar problem with Circle CI. I think the problem might be that the gems are being installed in your apps directory and they're being added to simple cov report. I was able to resolve this using an add_filter "/vendor/" but if your directory is different, you might have the same problem.

@whatasunnyday  Thanks! That did the trick. I forgot that by default Travis configures bundler to install dependencies in vendor. Given how common the usage of Travis CI is these days, perhaps that's worth mentioning in the documentation somewhere.

@bf4 Would you be interested in a PR? I had the same problem today and spent 10 mins figuring it out.

Sure.  I've had this problem in other situations as well when I forget that I've bundled gems in the current dir, like when I use bundle standalone (  add_filter 'bundle' ).
It looks like only the Rails profile excludes vendor/bundle by default  I'm not sure why that would be.
@colszowka @sferik @xaviershay Any reason not to put these in the test_frameworks config? The commit that added it only to the Rails profile doesn't make me think otherwise.
Per travis docs

If you have custom Bundler arguments, and these include the --path option, Travis CI will use that path. If --path is missing but --deployment is present, it will use vendor/bundle.

Otherwise it will automatically add the --path option. In this case it will either use the value of the environment variable BUNDLE_PATH or, if it is missing, vendor/bundle.

(via the bash-fu --path=${BUNDLE_PATH:-vendor/bundle} that falls back to vendor/bundle if BUNDLE_PATH isn't set)

Sorry I missed your question when you first asked it. I was just bitten by this today. I'd support adding add_filter '/vendor/bundle/' to the appropriate default config.

For completeness:

Failing build: https://travis-ci.org/square/ruby-tree_filter/jobs/54964333
Fix: https://github.com/square/ruby-tree_filter/pull/1
Was able to repro locally by bundle install --deployment

Going to re-open this ticket.

I'd support adding add_filter '/vendor/bundle/' to the appropriate default config.

This has been added and released in version 0.10.0. Please reopen this issue if that doesn’t solve it for you.


Run tests across a range of JDKs

This will probably fail because of Android SDK tools requiring Java 17.
Therefore to make this work I will take the same approach as in Masetro:

use latest Java and Gradle
set -release for javac and -Xjdk-target for kotlinc
test on lowest supported Java (8), like we do in Maestro


Ignore comments while searching in file/s.

Three state button in current search feature to look outside or in comments (depending on filetype, for example in:
 /* */, //, /** */, #, <!-- -->
).

/duplicate of #11688 (which looks more like search in editor) and #140294 (for search in files, see https://github.com/microsoft/vscode/issues/140294#issuecomment-1007796325 for details)


Replace iphone splash photo and copy placement

file asset: https://cl.ly/473C1G1y023d

The end of an era 😢

Long Live Eigen!

@alloy wha?????

The splash screen was such a fixed point in Eigen’s existence since forever, I’m just saying my goodbyes 🎩👌

wha? we changed it in 3.0 lol...

lol this is funny ^_^.
Also, FYI, I've created new assets for the logos in black.
blacklogos.zip
I'm assuming these are fine @katarinabatina :)?

When you’re as young as I am, time feels like it takes longer! 😛

Current state:

Closed by #2161


perf: Improve validation for usernameAvailable

Resolves #365

Adds "lnbc1" to the hasNoRestictedStartCharacters function to reduce calls to the server.
Adds some clarity to the forbiddenStart message letting the user know the username cannot be a bitcoin address or lightning invoice
Adds test for "lnbc1"

*Note - I did my best to translate the forbidden start error message which may benefit from being proofed by a native Spanish speaker. The added language may not be even be necessary and can be removed also.

Hi @danwebb1. Thanks for the contribution. If you have the time it would be good to make the improvements I mentioned in my comments. If you don't have time just let me know and I can take over the PR.

I will make the updates/improvements this evening!

https://user-images.githubusercontent.com/17483038/150078703-6331477e-4c6e-4af2-978a-cb5027c23df7.mov


Starting a project with --at does not stop the currently running project at that time (stop_on_start is true)

I have set stop_on_start to true.
When I start a project using --at when another project is running, it stops the currently running project at current time, thus it fails to start the new project because it cannot start before the previous project ends.

[Current time: 11:00] watson start project_1 --at 11:00
[Current time: 12:00] watson start project_2 --at 11:30

// Expected output
Stopping project project_1
Starting project project_2

// Actual output (duration and ID trimmed)
Stopping project project_1
Error: Task cannot start before the previous task ends.

Yup, I've already experienced this issue, but didn't took time to investigate. Did you?

Experienced the same and think that is a quite common use-case, as one has forgotten to switch project and want to make the switch in the past.
Thx for the helpful tool, like it a lot so far.


link getting started repo in getting started guide

Description
The Getting Started guide on the ocm website uses the getting started ocm repository but does not mention it.
The corresponding link should be added.

Technically, it's just using a helmChart resource. It's not using anything from the Getting Started repository. I think mentioning that just adds to the confusion because the getting started repository is quite large. How would the user know which step we are on at that moment? The guide is only stating that you have a helm chart locally.

First, we want to add a Helm Chart stored in a local folder named helmchart.

Granted, it could be elaborated some more that there should be a helm chart locally. What that chart is, is irrelevant.

Granted, it could be elaborated some more that there should be a helm chart locally. What that chart is, is irrelevant.

True - but to expect that somebody has a helm chart locally, if the user just wants to "get started" with OCM, is unreasonable.
In https://github.com/open-component-model/ocm-website/pull/295 I added a subsection to the "Prerequisites" - I agree that this can be confusing, if the "getting started" repository is not used any further in the "First Steps with OCM" section. There should rather just be a hint where to find such resources if they are needed, e.g. here.
For the future, however, we should consider what we do with the “getting-started” repository. Is it still used anywhere?

I'm unaware if it is used anywhere.

True - but to expect that somebody has a helm chart locally, if the user just wants to "get started" with OCM, is unreasonable.

I've seen more being requested from a user during Getting Started than having a plain helm chart locally... :)

I updated the issue description because I saw some other things in the "First Steps with OCM" section that need a rework. If one sees anything else please let me know in the issue.


Reset my goal

Delete my goal and set it on the why part. :smile

Why are you doing this changes ?

This is a good change. Bye!

Thank.

hadazda


WIP: Adds a case study landing page

Waiting on a few fixes to the core theme and it to be upgraded on npm but should enable us to render a layout close to the following:

Currently getting the logos from the different projects in the right format...


JSGrid Plugin

I was going to suggest this then saw there is already a plugin repo.... however, unless I'm missing something, it doesn't seem to be in the plugin store.

Doh
Of course its already there!


Missing implementation for "MPIConstantFill"

$ test/mpi_test
...
C++ exception with description "[enforce fail at operator.cc:110] op. Cannot create operator of type 'MPIConstantFill' on the device 'CPU'. Verify that implementation for the corresponding device exist. It might also happen if the binary is not linked with the operator implementation code. If Python frontend is used it might happen if dyndep.InitOpsLibrary call is missing. Operator def: output: "X" type: "MPIConstantFill" arg { name: "shape" ints: 10 } arg { name: "value" f: 0 } " thrown in the test body.
...
[==========] 5 tests from 1 test case ran. (4 ms total)
[  PASSED  ] 0 tests.
[  FAILED  ] 5 tests, listed below:
[  FAILED  ] MPITest.TestMPIBroadcast
[  FAILED  ] MPITest.TestMPIReduce
[  FAILED  ] MPITest.TestMPIAllgather
[  FAILED  ] MPITest.TestMPIAllreduce
[  FAILED  ] MPITest.TestInPlaceMPIAllreduce

$ test/mpi_gpu_test
...
C++ exception with description "[enforce fail at operator.cc:110] op. Cannot create operator of type 'MPIConstantFill' on the device 'CUDA'. Verify that implementation for the corresponding device exist. It might also happen if the binary is not linked with the operator implementation code. If Python frontend is used it might happen if dyndep.InitOpsLibrary call is missing. Operator def: output: "X" type: "MPIConstantFill" arg { name: "shape" ints: 10 } arg { name: "value" f: 0 } device_option { device_type: 1 } " thrown in the test body.
...
[==========] 5 tests from 1 test case ran. (214 ms total)
[  PASSED  ] 0 tests.
[  FAILED  ] 5 tests, listed below:
[  FAILED  ] MPITest.TestMPIBroadcast
[  FAILED  ] MPITest.TestMPIReduce
[  FAILED  ] MPITest.TestMPIAllgather
[  FAILED  ] MPITest.TestMPIAllreduce
[  FAILED  ] MPITest.TestInPlaceMPIAllreduce

/cc @Yangqing because https://github.com/caffe2/caffe2/commit/3eeb18a6a168ec74ad287001ee9fe399ad90cb6d

That is my fault. Will fix.