train_demo.sh throws ValueError exception

pip3 freeze:

appdirs==1.4.3
image==1.5.5
Keras==2.0.4
numpy==1.12.1
olefile==0.44
packaging==16.8
Pillow==4.1.1
protobuf==3.3.0
pyparsing==2.2.0
pytz==2017.2
PyYAML==3.12
scipy==0.19.0
six==1.10.0
tensorflow-gpu==1.1.0
Theano==0.9.0
tqdm==4.11.2
Werkzeug==0.12.2

(Maybe I don't have the right version of Keras?)
The error thrown:
2017-05-23 10:03:59,609 root  INFO     loading data
2017-05-23 10:03:59,611 root  INFO     phase: train
2017-05-23 10:03:59,611 root  INFO     model_dir: model_01_16
2017-05-23 10:03:59,611 root  INFO     load_model: False
2017-05-23 10:03:59,611 root  INFO     output_dir: results
2017-05-23 10:03:59,612 root  INFO     steps_per_checkpoint: 2000
2017-05-23 10:03:59,612 root  INFO     batch_size: 64
2017-05-23 10:03:59,612 root  INFO     num_epoch: 3
2017-05-23 10:03:59,612 root  INFO     learning_rate: 1
2017-05-23 10:03:59,612 root  INFO     reg_val: 0
2017-05-23 10:03:59,612 root  INFO     max_gradient_norm: 5.000000
2017-05-23 10:03:59,613 root  INFO     clip_gradients: True
2017-05-23 10:03:59,613 root  INFO     valid_target_length inf
2017-05-23 10:03:59,613 root  INFO     target_vocab_size: 39
2017-05-23 10:03:59,613 root  INFO     target_embedding_size: 10.000000
2017-05-23 10:03:59,613 root  INFO     attn_num_hidden: 256
2017-05-23 10:03:59,614 root  INFO     attn_num_layers: 2
2017-05-23 10:03:59,614 root  INFO     visualize: True
2017-05-23 10:03:59,614 root  INFO     buckets
2017-05-23 10:03:59,614 root  INFO     [(16, 11), (27, 17), (35, 19), (64, 22), (80, 32)]
2017-05-23 10:03:59,614 root  INFO     ues GRU in the decoder.
input_tensor dim: (?, 1, 32, ?)
CNN outdim before squeeze: (?, 1, ?, 512)
CNN outdim: (?, ?, 512)
using GRU CELL in decoder
Traceback (most recent call last):
File "src/launcher.py", line 146, in
main(sys.argv[1:], exp_config.ExpConfig)
File "src/launcher.py", line 142, in main
session = sess)
File "/home/kankroc/AttentionOCR/Attention-OCR/src/model/model.py", line 151, in init
use_gru = use_gru)
File "/home/kankroc/AttentionOCR/Attention-OCR/src/model/seq2seq_model.py", line 141, in init
softmax_loss_function=softmax_loss_function)
File "/home/kankroc/AttentionOCR/Attention-OCR/src/model/seq2seq.py", line 993, in model_with_buckets
decoder_inputs[:int(bucket[1])], int(bucket[0]))
File "/home/kankroc/AttentionOCR/Attention-OCR/src/model/seq2seq_model.py", line 140, in
self.target_weights, buckets, lambda x, y, z: seq2seq_f(x, y, z, False),
File "/home/kankroc/AttentionOCR/Attention-OCR/src/model/seq2seq_model.py", line 122, in seq2seq_f
attn_num_hidden = attn_num_hidden)
File "/home/kankroc/AttentionOCR/Attention-OCR/src/model/seq2seq.py", line 675, in embedding_attention_decoder
initial_state_attention=initial_state_attention, attn_num_hidden=attn_num_hidden)
File "/home/kankroc/AttentionOCR/Attention-OCR/src/model/seq2seq.py", line 577, in attention_decoder
cell_output, state = cell(x, state)
File "/home/kankroc/AttentionOCR/env/lib/python3.5/site-packages/tensorflow/contrib/rnn/python/ops/core_rnn_cell_impl.py", line 953, in call
cur_inp, new_state = cell(cur_inp, cur_state)
File "/home/kankroc/AttentionOCR/env/lib/python3.5/site-packages/tensorflow/contrib/rnn/python/ops/core_rnn_cell_impl.py", line 146, in call
with _checked_scope(self, scope or "gru_cell", reuse=self._reuse):
File "/usr/lib/python3.5/contextlib.py", line 59, in enter
return next(self.gen)
File "/home/kankroc/AttentionOCR/env/lib/python3.5/site-packages/tensorflow/contrib/rnn/python/ops/core_rnn_cell_impl.py", line 77, in _checked_scope
type(cell).name))
ValueError: Attempt to reuse RNNCell <tensorflow.contrib.rnn.python.ops.core_rnn_cell_impl.GRUCell object at 0x7f9a3c88cf98> with a different variable scope than its first use.  First use of cell was with scope 'embedding_attention_decoder/attention_decoder/multi_rnn_cell/cell_0/gru_cell', this attempt is with scope 'embedding_attention_decoder/attention_decoder/multi_rnn_cell/cell_1/gru_cell'.  Please create a new instance of the cell if you would like it to use a different set of weights.  If before you were using: MultiRNNCell([GRUCell(...)] * num_layers), change to: MultiRNNCell([GRUCell(...) for _ in range(num_layers)]).  If before you were using the same cell instance as both the forward and reverse cell of a bidirectional RNN, simply create two instances (one for forward, one for reverse).  In May 2017, we will start transitioning this cell's behavior to use existing stored weights, if any, when it is called with scope=None (which can lead to silent model degradation, so this error will remain until then.)
The error seems to indicate a version mismatch, what is the recommanded combo (TF + Keras) version?

TensorFlow 1.0 with Keras 1.* did the trick.


Playground execution failed with AKMicrophone examples

Using Xcode 10.1, macOS Mojave 10.14.2, AudioKit
I'm a complete noob to AudioKit so do excuse me if this a known issue with using Microphones in Playground environments! I did a Quick Search on related Issues and found a fix whereby the Info.plist needed the NSMicrophoneUsageDescription key set (https://github.com/AudioKit/AudioKit/issues/1557), but this appears to have been fixed in 4.5.5 so must be another issue.
I've had success with other Playground files, but Tracking Microphone Input fails to run in Xcode Playgrounds.
Steps I took to repro:
-Downloaded AudioKitPlaygrounds-4.5.5.zip
-Open AudioKitPlaygrounds.xcodeproj
-Cmd+B to build.
-Open Analysis.playground > Tracking Microphone Input
-Click on play icon.
Result: Debug console reports the following:
Playground execution failed:

error: Execution was interrupted, reason: EXC_BAD_INSTRUCTION (code=EXC_I386_INVOP, subcode=0x0).
The process has been left at the point where it was interrupted, use "thread return -x" to return to the state before expression evaluation.

* thread #1, queue = 'com.apple.main-thread', stop reason = EXC_BAD_INSTRUCTION (code=EXC_I386_INVOP, subcode=0x0)
  * frame #0: 0x00007fff361a1a9b AppKit`-[NSApplication _crashOnException:] + 109
    frame #1: 0x00007fff361a197e AppKit`-[NSApplication reportException:] + 939
    frame #2: 0x00007fff36263813 AppKit`uncaughtErrorProc + 157
    frame #3: 0x00007fff38972301 CoreFoundation`__handleUncaughtException + 775
    frame #4: 0x00007fff649b8c81 libobjc.A.dylib`_objc_terminate() + 91
    frame #5: 0x00007fff631b9dfe libc++abi.dylib`std::__terminate(void (*)()) + 8
    frame #6: 0x00007fff631b9be2 libc++abi.dylib`__cxxabiv1::failed_throw(__cxxabiv1::__cxa_exception*) + 27
    frame #7: 0x00007fff631acbb9 libc++abi.dylib`__cxa_throw + 113
    frame #8: 0x00007fff649b685a libobjc.A.dylib`objc_exception_throw + 362
    frame #9: 0x00007fff38915b2a CoreFoundation`+[NSException raise:format:arguments:] + 98
    frame #10: 0x00007fff3497e2bc AVFAudio`AVAE_RaiseException(NSString*, ...) + 156
    frame #11: 0x00007fff349842cb AVFAudio`_AVAE_Check(char const*, int, char const*, char const*, bool) + 323
    frame #12: 0x00007fff349d1c13 AVFAudio`AVAudioIONodeImpl::SetOutputFormat(unsigned long, AVAudioFormat*) + 349
    frame #13: 0x00007fff349b2213 AVFAudio`AVAudioEngineGraph::_Connect(AVAudioNodeImplBase*, AVAudioNodeImplBase*, unsigned int, unsigned int, AVAudioFormat*) + 1653
    frame #14: 0x00007fff349b5d3e AVFAudio`AVAudioEngineGraph::ConnectMultipleOutputs(AVAudioNode*, NSArray*, unsigned long, AVAudioFormat*) + 3370
    frame #15: 0x00007fff349da197 AVFAudio`AVAudioEngineImpl::ConnectMultipleOutputs(AVAudioNode*, NSArray*, unsigned long, AVAudioFormat*) + 673
    frame #16: 0x00007fff349d9eae AVFAudio`-[AVAudioEngine connect:toConnectionPoints:fromBus:format:] + 94
    frame #17: 0x00000001133d7a56 AudioKitPlaygrounds`function signature specialization <Arg[4] = Dead> of static AudioKit.AudioKit.connect(_: __C.AVAudioNode, to: Swift.Array<__C.AVAudioConnectionPoint>, fromBus: Swift.Int, format: Swift.Optional<__C.AVAudioFormat>) -> () + 1990
    frame #18: 0x00000001132fcdd8 AudioKitPlaygrounds`function signature specialization <Arg[18446744073709551615] = Owned To Guaranteed> of generic specialization <AudioKit.AKPeriodicFunction> of (extension in AudioKit):AudioKit.AKOutput.connect(to: AudioKit.AKInput, bus: Swift.Int) -> AudioKit.AKInput + 616
    frame #19: 0x00000001132ff0a9 AudioKitPlaygrounds`function signature specialization <Arg[18446744073709551615] = Owned To Guaranteed> of generic specialization <__C.AVAudioInputNode> of (extension in AudioKit):AudioKit.AKOutput.connect(to: AudioKit.AKInput, bus: Swift.Int) -> AudioKit.AKInput + 9
    frame #20: 0x000000011325588c AudioKitPlaygrounds`AudioKit.AKMicrophone.init() -> AudioKit.AKMicrophone + 588
    frame #21: 0x00000001132558bf AudioKitPlaygrounds`@objc AudioKit.AKMicrophone.init() -> AudioKit.AKMicrophone + 15
    frame #22: 0x00000001138d9057 $__lldb_expr6`main at Tracking Microphone Input.xcplaygroundpage:6
    frame #23: 0x000000010ef0f1a0 com.apple.dt.Xcode.PlaygroundStub-macosx
    frame #24: 0x00007fff38852ffc CoreFoundation`__invoking___ + 140
    frame #25: 0x00007fff38852ecb CoreFoundation`-[NSInvocation invoke] + 311
    frame #26: 0x00007fff388b3959 CoreFoundation`-[NSInvocation invokeWithTarget:] + 56
    frame #27: 0x00007fff61aef6c5 ViewBridge`__68-[NSVB_ViewServiceImplicitAnimationDecodingProxy forwardInvocation:]_block_invoke_2 + 46
    frame #28: 0x00007fff61ab4995 ViewBridge`-[NSViewServiceMarshal withHostWindowFrameAnimationInProgress:perform:] + 53
    frame #29: 0x00007fff61aef68e ViewBridge`__68-[NSVB_ViewServiceImplicitAnimationDecodingProxy forwardInvocation:]_block_invoke + 113
    frame #30: 0x00007fff35e2b11f AppKit`+[NSAnimationContext runAnimationGroup:] + 55
    frame #31: 0x00007fff35e2b0d5 AppKit`+[NSAnimationContext runAnimationGroup:completionHandler:] + 82
    frame #32: 0x00007fff61b11c24 ViewBridge`runAnimationGroup + 295
    frame #33: 0x00007fff61aef165 ViewBridge`+[NSVB_View _animateWithAttributes:animations:completion:] + 490
    frame #34: 0x00007fff61aef5f8 ViewBridge`-[NSVB_ViewServiceImplicitAnimationDecodingProxy forwardInvocation:] + 206
    frame #35: 0x00007fff3889c87e CoreFoundation`___forwarding___ + 780
    frame #36: 0x00007fff3889c4e8 CoreFoundation`__forwarding_prep_0___ + 120
    frame #37: 0x00007fff38852ffc CoreFoundation`__invoking___ + 140
    frame #38: 0x00007fff38852ecb CoreFoundation`-[NSInvocation invoke] + 311
    frame #39: 0x00007fff388b3959 CoreFoundation`-[NSInvocation invokeWithTarget:] + 56
    frame #40: 0x00007fff61ab7442 ViewBridge`-[NSVB_QueueingProxy forwardInvocation:] + 324
    frame #41: 0x00007fff3889c87e CoreFoundation`___forwarding___ + 780
    frame #42: 0x00007fff3889c4e8 CoreFoundation`__forwarding_prep_0___ + 120
    frame #43: 0x00007fff38852ffc CoreFoundation`__invoking___ + 140
    frame #44: 0x00007fff38852ecb CoreFoundation`-[NSInvocation invoke] + 311
    frame #45: 0x00007fff388b3959 CoreFoundation`-[NSInvocation invokeWithTarget:] + 56
    frame #46: 0x00007fff3889c87e CoreFoundation`___forwarding___ + 780
    frame #47: 0x00007fff3889c4e8 CoreFoundation`__forwarding_prep_0___ + 120
    frame #48: 0x00007fff38852ffc CoreFoundation`__invoking___ + 140
    frame #49: 0x00007fff38852ecb CoreFoundation`-[NSInvocation invoke] + 311
    frame #50: 0x00007fff61a83f4d ViewBridge`__deferNSXPCInvocationOntoMainThread_block_invoke + 237
    frame #51: 0x00007fff61a795aa ViewBridge`__wrapBlockWithVoucher_block_invoke + 37
    frame #52: 0x00007fff61a7935c ViewBridge`__deferBlockOntoMainThread_block_invoke_2 + 553
    frame #53: 0x00007fff38880d17 CoreFoundation`__CFRUNLOOP_IS_CALLING_OUT_TO_A_BLOCK__ + 12
    frame #54: 0x00007fff38843d51 CoreFoundation`__CFRunLoopDoBlocks + 395
    frame #55: 0x00007fff3884344f CoreFoundation`__CFRunLoopRun + 1204
    frame #56: 0x00007fff38842d48 CoreFoundation`CFRunLoopRunSpecific + 463
    frame #57: 0x00007fff37ad9ab5 HIToolbox`RunCurrentEventLoopInMode + 293
    frame #58: 0x00007fff37ad97eb HIToolbox`ReceiveNextEventCommon + 618
    frame #59: 0x00007fff37ad9568 HIToolbox`_BlockUntilNextEventMatchingListInModeWithFilter + 64
    frame #60: 0x00007fff35d94363 AppKit`_DPSNextEvent + 997
    frame #61: 0x00007fff35d93102 AppKit`-[NSApplication(NSEvent) _nextEventMatchingEventMask:untilDate:inMode:dequeue:] + 1362
    frame #62: 0x00007fff61a81aa6 ViewBridge`-[NSViewServiceApplication nextEventMatchingMask:untilDate:inMode:dequeue:] + 92
    frame #63: 0x00007fff35d8d165 AppKit`-[NSApplication run] + 699
    frame #64: 0x00007fff35d7c8a3 AppKit`NSApplicationMain + 780
    frame #65: 0x00007fff65cbcef7 libxpc.dylib`_xpc_objc_main + 612
    frame #66: 0x00007fff65cbc9bd libxpc.dylib`xpc_main + 433
    frame #67: 0x00007fff61a735e6 ViewBridge`-[NSXPCSharedListener resume] + 16
    frame #68: 0x00007fff61a7c373 ViewBridge`NSViewServiceApplicationMain + 2877
    frame #69: 0x000000010ef0f1ca com.apple.dt.Xcode.PlaygroundStub-macosx`main + 42
    frame #70: 0x00007fff65a84ed9 libdyld.dylib`start + 1

Hi @aure - thanks for getting back to me. I've tried setting the Mic to 48kHz, 44.1kHz, 16/24-bit, it seems to make no difference to the crash I'm seeing unfortunately! Your offer to screen share would be much appreciated!

Send me an email with your Apple ID associated email address and I'll message you so share (if you have Mojave), otherwise, if you can sign up for zoom.us, we can do it with that too.

Hello all, getting this same crash with the FFT playground. My microphone sample rate set to 44.1. Xcode 10.2.1, Mohave 10.14.4, downloaded the playgrounds last week, don't know what version that would be.

@mklybor I just verified it works here with the latest develop branch. I can do a screen share with you too if you like.

thanks I will check out the dev branch and give it a go.


is_colliding does not works

I'm following your awesome tutorials about up and running godot engine. in part 10, you wrote a code to avoid character jumping to sky with holding ui_up key with adding RayCast2D. but for me. if i hold arrow up key first time it well be fine but after landing on the ground and jumping again(i'm still holding up key) the character goes to sky! even if write set_process_input(true)!
the code:
      extends KinematicBody2D
      onready var ground_ray = get_node("gr")

const ACCEL = 1500
const MAX_SPEED = 400
const FRICTION = -400
const GRAVITY = 2000
const JUMP_SPEED = -300

var acc = Vector2()
var vel = Vector2()

func _ready():
	set_fixed_process(true)
	set_process_input(true)

func _input(event):
	if Input.is_action_pressed("ui_up") and ground_ray.is_colliding():
		vel.y = JUMP_SPEED

func _fixed_process(delta):
	acc.y = GRAVITY
	acc.x = Input.is_action_pressed("ui_right") - Input.is_action_pressed("ui_left")
	acc.x *= ACCEL
	if acc.x == 0:
		acc.x = vel.x * FRICTION * delta

	vel += acc * delta
	vel.x = clamp(vel.x, -MAX_SPEED,MAX_SPEED)

	var motion = move(vel * delta)
	if is_colliding():
		var n = get_collision_normal()
		motion = n.slide(motion)
		vel = n.slide(vel)
		move(motion) `

oops, i forget to change Input to event in new added function, the jumping issue with holding up key solved. but when the jump starts, if i press up key in repeating sequence, the character goes up and up again.

You need to check your ground ray. That's the thing that's checking if a jump should be allowed. If it's sticking out too far (cast_to property) then it will still be hitting the ground even when you're up in the air.  Also, if it's touching the player's CollisionShape, then it counts as colliding all the time. You can either adjust its position, or add the player as an exception by adding this to _ready():
ground_ray.add_exception(self)

there was a connection between the collisionShape and the rayCast.
Thanks


v2.12.0 introduces out of memory (OOM) error when included in libarary built with svelte-package

[x] Before posting an issue, read the FAQ and search the previous issues.

Description
As of v2.12.0, running svelte-package in a package containing the use of FormPathLeaves with a generic T param results in a memory leak and OOM error.
If applicable, a MRE
Run npm run package in the console here

Woo! I'm issue #404!

Will hopefully be fixed in the next release.

See if it's working now with 2.12.4.

@ciscoheat works perfectly now! Thank you so much for such a quick fix :)


desktop-managers: do not leak feh to PATH

Motivation for this change
feh is used to set background image for desktop managers that do not support it directly, however there is no need to include it in PATH.
Fixes #17450.
Things done

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

[x] NixOS
[ ] macOS
[ ] other Linux distributions

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

I’ve reverted the change, it’s not possible to assign something not called config or options to a module.
Please test changes before you PR.

My bad for merging without a local test on my side. It looked innocent enough (famous last words I guess).

Sorry, I too thought there should be no problem with doing that... I'll open a new pull request after I test the change.

My bad for merging without a local test on my side. It looked innocent enough

Yeah, no problem.

@peterhoeg, reopen #17450?…


Resinos in container

This adds support for running resinOS as a docker container. See https://github.com/resin-os/resinos-in-container for how to do it.

@resin-jenkins retest this please

Force pushed to fix a typo in the last commit log:
"ina" -> "in a"

Rebased on current HEAD.


Backstage version update

Thanks @swnia will have a look at this on saturday.

Please provide a changeset, see https://github.com/dweber019/backstage-plugins/blob/main/CONTRIBUTING.md#creating-changesets
The rest looks good.

Sorry about that. Changeset is now in


How to GPU profiling with BeginEvent in DX11 ?

Hello,
I would like to do very lightweight GPU profiling for DX11 in real-time, and therefore I would like to know an easy way to get the time it takes to perform a given GPU command.
Thanks in advance.
Mat.

This is not a good place to ask question about Direct3D API.  Specifically to your question, google gives you this http://reedbeta.com/blog/gpu-profiling-101/ and otherwise you should ask this question to www.gamedev.net/forum/10-directx-and-xna/

Yeah you are right I thought that because of C# there would be a special sauce to do the DX11 queries... But even without examples I eventually managed to do the queries following the C++ doc.


Create pull_request_labels.yml

https://werkbotstudios.teamwork.com/#/tasks/29402677
Summary
Required release-related labels on PRs. Requires exactly one semvar label.
Testing

[ ] confirm the action check fails for this PR
[ ] add a "patch" label here, confirm the check passes now

Concern

Not sure if we want to enforce "category" labels like these here https://github.com/werkbot/silverstripe-module-search/blob/master/.github/release-drafter.yml#L5. You could have a mixture of labels like that, so we would need to figure out how the rules should work for those.

Not sure if we want to enforce "category" labels like these here https://github.com/werkbot/silverstripe-module-search/blob/master/.github/release-drafter.yml#L5. You could have a mixture of labels like that, so we would need to figure out how the rules should work for those.

Hmm I think for now just enforcing the semvar labels is good, but I think thats something we can enforce later after working with the process a bit.


Many nested paths

On the installation I e.g. have the following path: linter-alex\node_modules\alex\node_modules\update-notifier\node_modules\latest-version\node_modules\package-json\node_modules\got\node_modules\duplexify\node_modules\end-of-stream\node_modules\once\node_modules\wrappy\test
(that's only the part after the package dir)
On Windows 7 in certain circumstances this even gave me a message that the path is too long (and it was an NTFS file system), so please try too use paths which are a bit shorter and don't contain thousand empty subfolders named node_modules.

This is out of my control; not something I am able to change. It’s good practice to depend on packages, and it’s a problem with npm’s design. Read this on how to “fix” it: http://engineroom.teamwork.com/dealing-with-long-paths/

Okay, nice link.

:+1:


cpu: Handle interrupt nesting correctly

This restores the logic to enable interrupts while handling exceptions, and also ensures that user mode runs with interrupts disabled when required.

There was a small race-condition on my side, I already merged a fix for the user-if problem prior to seeing this PR. Sorry for that, but I cherry-picked the commit fixing the irq-state tracking into the user-mode PR and merged it via that path. I am closing this PR now.


Interactive code snippet

Hello 😁
This PR makes the code snippet widget in the example project more interactive.
Added functionalities:

user can highlight and copy  the code snippet:

click on the "Copy" button to copy the code snippet to the clipboard:

@bdlukaa thank you for accepting this PR, happy to contribute to this cool and important project.


Flesh out viewer beta

Can be enabled via --vis viewer_beta.

@kerrj Hi, what's the difference between the viewer and view_beta?


[Suggestion] Red Power-Style cables?

what do you think of the idea of adding cables like the ones from red power which can be placed on walls and insulated in all 16 colors so they don't connect? and maybe also bundled cables?

These are long-term goals, yes. (closing this because it's not a bug report)

ah ok, id suggest stating that this isnt for bugs somewhere :D


Memory hogs using the booru browser

The tags listed a little over 700 images, I scrolled down to the bottom and used the save images option. It plowed through all 8GB of RAM and the 8GB of extra swap space. This is with a relatively small amount of images, I can't imagine what would happen with very popular tags.  I guess this isn't a common scenario, but I bet others save most images and then delete the ones they dislike.
This is also probably on my end, but browsing a directory with lots of images takes some time to startup, other viewers have no problem opening up an individual image in the unsorted mess.

The issue when saving a large number of images should be easily fixable.
The load times when opening a directory with a large number of images I'll have to look into.
Around how many images or files are in the directory?

The directory in question has over 18k files. I tried one with around half of it and the issue is still there albeit not as severe.


Thread-1 WARN Unable to register Log4j shutdown hook because JVM is shutting down. Using SimpleLogger

Hello @Rbillon59,
Thanks for this starterkit, it's very helpfull.
I have an issue when launching the test, I keep getting the same error :

Sadly I can't get the report from the master node because it stopped and grafana has no data.
I tried with this command : ./start_test.sh -j my-scenario.jmx -n default -c -m -i 5 -r
I am using the demo test since I haven't developed mine for now.
Thanks

Hi @Davmira
Thanks you for your feedback, I'll take a look asap.

Just checked,
The WARN log you are seeing is linked to the PluginsManagerCMD.sh script used by JMeter to install the plugins with the command line (by analysing the JMX needs). If your terminal is hangging on this message, hitting CTRL +C will not stop the test and you'll be able to recover your terminal. So don't worry, your test is executing well behind the scene !
But you are right. In the default scenario I did not add the BackendListener with the default influxdb connection, thus, you've not your result uploaded in it. I added it in the PR linked to this comment.
Also, I made a mistake in the result location in the README, the result location are not : :/opt/jmeter/apache-jmeter/bin/
But it's stored in :/report
Would you take the time to checkout the fix branch I created to test it again please ?
The PR branch is : #10
Thanks you,
Romain

Thank you for the quick reply.
I have checkout your new branch add-influxdb-listener-to-default-jmx, and I still have the same issue :

As you can see I am on your branch (I have checked the two files you have changed) and the master pod stopped. CTRL+C or not the test have stopped, I think so I can't go inside the master pod and get the report at the path : /report.

Ok I guess I've understand what I've missed here.
Do you confirm that the test is executing correctly and the master pod is in completed state after the rest execution ? Or it just get completed directly after the end of the script ?
Effectively when the master is done, the pod is deleted by the cleaner job. So to recover, a new master needs to be deployed (by default, the master command is to wait indefinitely). So I need to update the readme or create a script.. I'll think about a solution quickly and update the PR.
Thanks again

I pushed a commit to explain how to get the report if the master pod have been cleaned by the cronjob. Let me know if it's understandable and it cover your use case please.
Thanks you

No, I don't think the execution finish well, I still have the WARN Unable to register Log4j error. At the end now, the master pod is in state NotReady and no more completed :

Also, the grafana graph is empty and if I restart a master pod there is nothing at the path /result :

Since today I also have those warnings at the start :

Thanks for the update anyway and let's keep in touch.

Hi,
It seems I'm missing somethings because I tested everything locally on docker-desktop on windows and on minikube on Linux. Everything was working well.
To be able to go deeper on your problem, could you provide me the following infos :

Kubernetes version
Kubernetes provider
JMeter logs (should be on stdout of the slaves and master pods)

About the Kubernetes warning, it happen when you try to make a kubectl apply on resources created with the kubectl create command. I've used the create command and not apply because the Grafana config maps of the dashboard are too heavy to be created with kubectl apply.
Thanks you

Hello,
My kubernetes version :
kubectl version
Client Version: version.Info{Major:"1", Minor:"22", GitVersion:"v1.22.2", GitCommit:"8b5a19147530eaac9476b0ab82980b4088bbc1b2", GitTreeState:"clean", BuildDate:"2021-09-15T21:38:50Z", GoVersion:"go1.16.8", Compiler:"gc", Platform:"linux/amd64"}
Server Version: version.Info{Major:"1", Minor:"20", GitVersion:"v1.20.6", GitCommit:"8a62859e515889f07e3e3be6a1080413f17cf2c3", GitTreeState:"clean", BuildDate:"2021-04-15T03:19:55Z", GoVersion:"go1.15.10", Compiler:"gc", Platform:"linux/amd64"}
WARNING: version difference between client (1.22) and server (1.20) exceeds the supported minor version skew of +/-1

I am using rancher to manage my cluster and my provider is open stack.
I have :

2 control nodes : 4 Cores / 14.6 GiB
3 etcd nodes : 4 Cores / 14.6 GiB
6 workers nodes : 4 Cores / 14.6 GiB

I am using CentOS Linux 7 images on my workers because I needed it for another project.
My output of my master and slave pod (I guess it was you mean by stdout) :
`09:03:12 airflow@paqctdm:[~]: kubectl describe pod jmeter-master-qqzxg
Name:         jmeter-master-qqzxg
Namespace:    default
Priority:     0
Node:         worker2/<IP_ADDRESS>
Start Time:   Mon, 13 Dec 2021 09:05:57 -0500
Labels:       controller-uid=6f314e1a-6836-445b-ba39-9681b391bad6
jmeter_mode=master
job-name=jmeter-master
Annotations:  cni.projectcalico.org/podIP: <IP_ADDRESS>/32
cni.projectcalico.org/podIPs: <IP_ADDRESS>/32
telegraf.influxdata.com/class: app
telegraf.influxdata.com/inputs:
[[inputs.jolokia2_agent]]
urls = ["http://localhost:8778/jolokia"]
              [[inputs.jolokia2_agent.metric]]
                name  = "java_runtime"
                mbean = "java.lang:type=Runtime"
                paths = ["Uptime"]

              [[inputs.jolokia2_agent.metric]]
                name  = "java_memory"
                mbean = "java.lang:type=Memory"
                paths = ["HeapMemoryUsage", "NonHeapMemoryUsage", "ObjectPendingFinalizationCount"]

              [[inputs.jolokia2_agent.metric]]
                name     = "java_garbage_collector"
                mbean    = "java.lang:name=*,type=GarbageCollector"
                paths    = ["CollectionTime", "CollectionCount"]
                tag_keys = ["name"]

              [[inputs.jolokia2_agent.metric]]
                name  = "java_last_garbage_collection"
                mbean = "java.lang:name=G1 Young Generation,type=GarbageCollector"
                paths = ["LastGcInfo/duration", "LastGcInfo/GcThreadCount", "LastGcInfo/memoryUsageAfterGc"]

              [[inputs.jolokia2_agent.metric]]
                name  = "java_threading"
                mbean = "java.lang:type=Threading"
                paths = ["TotalStartedThreadCount", "ThreadCount", "DaemonThreadCount", "PeakThreadCount"]

              [[inputs.jolokia2_agent.metric]]
                name  = "java_class_loading"
                mbean = "java.lang:type=ClassLoading"
                paths = ["LoadedClassCount", "UnloadedClassCount", "TotalLoadedClassCount"]

              [[inputs.jolokia2_agent.metric]]
                name     = "java_memory_pool"
                mbean    = "java.lang:name=*,type=MemoryPool"
                paths    = ["Usage", "PeakUsage", "CollectionUsage"]
                tag_keys = ["name"]

            [[inputs.jolokia]]
              context = "/jolokia/"
            [[inputs.jolokia.servers]]
              host = "<IP_ADDRESS>"
              port = "8778"
            [[inputs.jolokia.metrics]]
              name = "heap_memory_usage"
              mbean  = "java.lang:type=Memory"
              attribute = "HeapMemoryUsage"
            [[inputs.jolokia.metrics]]
              name = "thread_count"
              mbean  = "java.lang:type=Threading"
              attribute = "TotalStartedThreadCount,ThreadCount,DaemonThreadCount,PeakThreadCount"

Status:       Running
IP:           <IP_ADDRESS>
IPs:
IP:           <IP_ADDRESS>
Controlled By:  Job/jmeter-master
Containers:
jmmaster:
Container ID:  docker://5a31f5e92c03f6778493b37ba914a534f24e29ff1d0b5cf762127f7fc99051a6
Image:         rbillon59/jmeter-k8s-base:5.4.1
Image ID:      docker-pullable://rbillon59/jmeter-k8s-base@sha256:dd74e89bbc1f3ccdffb28b8c115fce73891a3ee365ce833f291b565a217f3503
Port:          60000/TCP
Host Port:     0/TCP
Command:
/bin/bash
Args:
-c
trap 'exit 0' SIGUSR1 && while true; do sleep 30;done
State:          Terminated
Reason:       Completed
Exit Code:    0
Started:      Mon, 13 Dec 2021 09:07:03 -0500
Finished:     Mon, 13 Dec 2021 09:08:03 -0500
Ready:          False
Restart Count:  0
Limits:
cpu:     1024m
memory:  2Gi
Requests:
cpu:     1024m
memory:  1Gi
Liveness:  exec [cat /opt/jmeter/apache-jmeter/bin/jmeter] delay=5s timeout=1s period=5s #success=1 #failure=3
Environment:
MODE:       MASTER
NODE_NAME:   (v1:spec.nodeName)
POD_NAME:   jmeter-master-qqzxg (v1:metadata.name)
NAMESPACE:  default (v1:metadata.namespace)
Mounts:
/report from jmeter-data-dir (rw)
/var/run/secrets/kubernetes.io/serviceaccount from default-token-l65cf (ro)
telegraf:
Container ID:   docker://57309edf15874f2ddd6f1f53f04c10ed428db3bc91bffee88e54743af964d308
Image:          docker.io/library/telegraf:1.14
Image ID:       docker-pullable://telegraf@sha256:32fd7cc8528ec27f94a83da19c2dba48fa01d7120a98845ecd28fd0313f2adf0
Port:
Host Port:
State:          Running
Started:      Mon, 13 Dec 2021 09:07:03 -0500
Ready:          True
Restart Count:  0
Limits:
cpu:     200m
memory:  200Mi
Requests:
cpu:     10m
memory:  10Mi
Environment:
NODENAME:   (v1:spec.nodeName)
Mounts:
/etc/telegraf from telegraf-config (rw)
/var/run/secrets/kubernetes.io/serviceaccount from default-token-l65cf (ro)
Conditions:
Type              Status
Initialized       True
Ready             False
ContainersReady   False
PodScheduled      True
Volumes:
jmeter-data-dir:
Type:       PersistentVolumeClaim (a reference to a PersistentVolumeClaim in the same namespace)
ClaimName:  jmeter-data-dir-pvc
ReadOnly:   false
default-token-l65cf:
Type:        Secret (a volume populated by a Secret)
SecretName:  default-token-l65cf
Optional:    false
telegraf-config:
Type:        Secret (a volume populated by a Secret)
SecretName:  telegraf-config-jmeter-master-qqzxg
Optional:    false
QoS Class:       Burstable
Node-Selectors:
Tolerations:     node.kubernetes.io/not-ready:NoExecute op=Exists for 300s
node.kubernetes.io/unreachable:NoExecute op=Exists for 300s
Events:
Type     Reason                  Age    From                     Message

Normal   Scheduled               8m25s  default-scheduler        Successfully assigned default/jmeter-master-qqzxg to worker2
Warning  FailedAttachVolume      8m25s  attachdetach-controller  Multi-Attach error for volume "pvc-332a608c-25c4-4d50-8769-1d86d13ca658" Volume is already used by pod(s) jmeter-master-j2kkj
Normal   SuccessfulAttachVolume  7m38s  attachdetach-controller  AttachVolume.Attach succeeded for volume "pvc-332a608c-25c4-4d50-8769-1d86d13ca658"
Normal   Pulling                 7m20s  kubelet                  Pulling image "rbillon59/jmeter-k8s-base:5.4.1"
Normal   Pulled                  7m19s  kubelet                  Successfully pulled image "rbillon59/jmeter-k8s-base:5.4.1" in 291.832393ms
Normal   Created                 7m19s  kubelet                  Created container jmmaster
Normal   Started                 7m19s  kubelet                  Started container jmmaster
Normal   Pulled                  7m19s  kubelet                  Container image "docker.io/library/telegraf:1.14" already present on machine
Normal   Created                 7m19s  kubelet                  Created container telegraf
Normal   Started                 7m19s  kubelet                  Started container telegraf
Warning  Unhealthy               6m19s  kubelet                  Liveness probe failed: cannot exec in a stopped state: unknown
`
`09:14:22 airflow@paqctdm:[~]: kubectl describe pod jmeter-slaves-4ss74
Name:         jmeter-slaves-4ss74
Namespace:    default
Priority:     0
Node:         worker3/<IP_ADDRESS>
Start Time:   Mon, 13 Dec 2021 09:06:00 -0500
Labels:       controller-uid=3935be65-fa25-43b2-bdc7-ea2dc318d815
jmeter_mode=slave
job-name=jmeter-slaves
Annotations:  cni.projectcalico.org/podIP: <IP_ADDRESS>/32
cni.projectcalico.org/podIPs: <IP_ADDRESS>/32
telegraf.influxdata.com/class: app
telegraf.influxdata.com/inputs:
[[inputs.jolokia2_agent]]
urls = ["http://localhost:8778/jolokia"]
              [[inputs.jolokia2_agent.metric]]
                name  = "java_runtime"
                mbean = "java.lang:type=Runtime"
                paths = ["Uptime"]

              [[inputs.jolokia2_agent.metric]]
                name  = "java_memory"
                mbean = "java.lang:type=Memory"
                paths = ["HeapMemoryUsage", "NonHeapMemoryUsage", "ObjectPendingFinalizationCount"]

              [[inputs.jolokia2_agent.metric]]
                name     = "java_garbage_collector"
                mbean    = "java.lang:name=*,type=GarbageCollector"
                paths    = ["CollectionTime", "CollectionCount"]
                tag_keys = ["name"]

              [[inputs.jolokia2_agent.metric]]
                name  = "java_last_garbage_collection"
                mbean = "java.lang:name=G1 Young Generation,type=GarbageCollector"
                paths = ["LastGcInfo/duration", "LastGcInfo/GcThreadCount", "LastGcInfo/memoryUsageAfterGc"]

              [[inputs.jolokia2_agent.metric]]
                name  = "java_threading"
                mbean = "java.lang:type=Threading"
                paths = ["TotalStartedThreadCount", "ThreadCount", "DaemonThreadCount", "PeakThreadCount"]

              [[inputs.jolokia2_agent.metric]]
                name  = "java_class_loading"
                mbean = "java.lang:type=ClassLoading"
                paths = ["LoadedClassCount", "UnloadedClassCount", "TotalLoadedClassCount"]

              [[inputs.jolokia2_agent.metric]]
                name     = "java_memory_pool"
                mbean    = "java.lang:name=*,type=MemoryPool"
                paths    = ["Usage", "PeakUsage", "CollectionUsage"]
                tag_keys = ["name"]

            [[inputs.jolokia]]
              context = "/jolokia/"
            [[inputs.jolokia.servers]]
              host = "<IP_ADDRESS>"
              port = "8778"
            [[inputs.jolokia.metrics]]
              name = "heap_memory_usage"
              mbean  = "java.lang:type=Memory"
              attribute = "HeapMemoryUsage"
            [[inputs.jolokia.metrics]]
              name = "thread_count"
              mbean  = "java.lang:type=Threading"
              attribute = "TotalStartedThreadCount,ThreadCount,DaemonThreadCount,PeakThreadCount"

Status:       Running
IP:           <IP_ADDRESS>
IPs:
IP:           <IP_ADDRESS>
Controlled By:  Job/jmeter-slaves
Containers:
jmslave:
Container ID:  docker://f4f848d90c1c00fd307147b64e13b233e4064f2296ab22721113b0e0e9622dbd
Image:         rbillon59/jmeter-k8s-base:5.4.1
Image ID:      docker-pullable://rbillon59/jmeter-k8s-base@sha256:dd74e89bbc1f3ccdffb28b8c115fce73891a3ee365ce833f291b565a217f3503
Ports:         1099/TCP, 50000/TCP, 4445/TCP
Host Ports:    0/TCP, 0/TCP, 0/TCP
Command:
/bin/bash
Args:
-c
trap 'exit 0' SIGUSR1 && while true; do sleep 30;done
State:          Running
Started:      Mon, 13 Dec 2021 09:06:01 -0500
Ready:          True
Restart Count:  0
Limits:
cpu:     1024m
memory:  1Gi
Requests:
cpu:     1024m
memory:  1Gi
Liveness:  exec [cat /opt/jmeter/apache-jmeter/bin/jmeter] delay=0s timeout=1s period=10s #success=1 #failure=3
Environment:
MODE:  SLAVE
Mounts:
/var/run/secrets/kubernetes.io/serviceaccount from default-token-l65cf (ro)
telegraf:
Container ID:   docker://e86f5bfc827f5f3d91ce2bb8348a9090378cbaac091c72a6c35ec107a417bb0c
Image:          docker.io/library/telegraf:1.14
Image ID:       docker-pullable://telegraf@sha256:32fd7cc8528ec27f94a83da19c2dba48fa01d7120a98845ecd28fd0313f2adf0
Port:
Host Port:
State:          Running
Started:      Mon, 13 Dec 2021 09:06:01 -0500
Ready:          True
Restart Count:  0
Limits:
cpu:     200m
memory:  200Mi
Requests:
cpu:     10m
memory:  10Mi
Environment:
NODENAME:   (v1:spec.nodeName)
Mounts:
/etc/telegraf from telegraf-config (rw)
/var/run/secrets/kubernetes.io/serviceaccount from default-token-l65cf (ro)
Conditions:
Type              Status
Initialized       True
Ready             True
ContainersReady   True
PodScheduled      True
Volumes:
default-token-l65cf:
Type:        Secret (a volume populated by a Secret)
SecretName:  default-token-l65cf
Optional:    false
telegraf-config:
Type:        Secret (a volume populated by a Secret)
SecretName:  telegraf-config-jmeter-slaves-4ss74
Optional:    false
QoS Class:       Burstable
Node-Selectors:
Tolerations:     node.kubernetes.io/not-ready:NoExecute op=Exists for 300s
node.kubernetes.io/unreachable:NoExecute op=Exists for 300s
Events:
Type    Reason     Age    From               Message

Normal  Scheduled  9m12s  default-scheduler  Successfully assigned default/jmeter-slaves-4ss74 to worker3
Normal  Pulling    9m12s  kubelet            Pulling image "rbillon59/jmeter-k8s-base:5.4.1"
Normal  Pulled     9m12s  kubelet            Successfully pulled image "rbillon59/jmeter-k8s-base:5.4.1" in 259.707985ms
Normal  Created    9m12s  kubelet            Created container jmslave
Normal  Started    9m12s  kubelet            Started container jmslave
Normal  Pulled     9m12s  kubelet            Container image "docker.io/library/telegraf:1.14" already present on machine
Normal  Created    9m12s  kubelet            Created container telegraf
Normal  Started    9m12s  kubelet            Started container telegraf`
I have retry tests this morning and I have the same behaviour.
Thank you for your time. As you might have understood I am not a kubernetes expert yet.

I have tested with minikube and it's working well :

I still have the warning but the start command don't stop after the warning, I just have to, like you said before, to cancel the command using CTRL + C and I am able to get the result.
But, when I am doing this using my cluster the start command stopped and the master pod crash ...

Ok, I'm not totally crazy.
Yeah, the warning is really not something to care about. It is only linked to plugin install and not test start.
I will try to reproduce that on a rancher 2 farm locally

I tried locally deploying rancher. And I needed to manually create persistantVolumes because there was no default storage class. But apart from this, I was able to run the demo project witnout any problem :
As the master pod is deploying without any problem I support you haven't problems with your storage configuration ? I saw in the describe of the master pod that you the scheduler had problem with the volume claim for a minute :
Warning  FailedAttachVolume      8m25s  attachdetach-controller  Multi-Attach error for volume "pvc-332a608c-25c4-4d50-8769-1d86d13ca658" Volume is already used by pod(s) jmeter-master-j2kkj

Hi again,
You are right about the warning. But I have tested without the job which recreate the master pod (kubectl delete job jmeter-master) and without a master pod at start. I get the same result, tests are stopped for some reason :

I have retested on minikube it still woking well. The only difference I can see between rancher and minikube is that I have a telegraf container inside the master pod which I don't have inside the master pod for minikube :

It getting me crazy even if I learn lot's of stuffs. The project is running on minikube and it fit perfectly with what I need. I have also checked, everything seems right on openstack for the volumes.
On rancher I can get more details when the master pod has finished :

Since I don't have any errors inside my pods stdout it is possible to have some logs about the jmeter execution ?
Thanks

For the telegraf stuff, it's maybe because I pushed a fix this noon about the telegraf operator that did not deployed sidecar correctly. Would you retry ?
I continue to dig on my side to understand what could go wrong on your setup. But in the dedicaced JMeter image I made, every jmeter logs are redirected to stdout.

Does the container finish in completed state ? Because in your first screenshot, it appears to be in "Running" state.
Openstack is a bit tricky to deploy locally to test with Rancher so it's pretty hard to reproduce on my side.
Maybe, you could try to play with the liveness timeout or something related ?
Also, maybe you could try to find some logs related to the Kubernetes scheduler. I work a lot with Lens which is an IDE for the Kubernetes cluster and helped me a lot debugging my resources.
Thanks you

Hi @Rbillon59
I am working in Montreal and I have pulled each day your last commit from master so I was up to date.
I still have the same issue today.
I have tried to lower the number of worker from 6 to 2.
I have changed the image from the workers from centos7 to ubuntu.
At the end of the performance test, the master pod has the status 'Running' for like 10 secondes. After those 10 secondes it changes to 'NotReady' :

I have checked the yml of the pod at the end of the execution, if it can help :
status:
  conditions:
  - lastProbeTime: null
    lastTransitionTime: "2021-12-15T15:54:11Z"
    status: "True"
    type: Initialized
  - lastProbeTime: null
    lastTransitionTime: "2021-12-15T15:55:44Z"
    message: 'containers with unready status: [jmmaster]'
    reason: ContainersNotReady
    status: "False"
    type: Ready
  - lastProbeTime: null
    lastTransitionTime: "2021-12-15T15:55:44Z"
    message: 'containers with unready status: [jmmaster]'
    reason: ContainersNotReady
    status: "False"
    type: ContainersReady
  - lastProbeTime: null
    lastTransitionTime: "2021-12-15T15:54:11Z"
    status: "True"
    type: PodScheduled
  containerStatuses:
  - containerID: docker://a889cf5e7554f02d06fecf2413a0639ea9939a002aeb75f21ca159f36ebbd125
    image: rbillon59/jmeter-k8s-base:5.4.1
    imageID: docker-pullable://rbillon59/jmeter-k8s-base@sha256:d405117e1ec055a9d3a22e648b4b1770956f983fb546200f6f220a3feada9602
    lastState: {}
    name: jmmaster
    ready: false
    restartCount: 0
    started: false
    state:
      terminated:
        containerID: docker://a889cf5e7554f02d06fecf2413a0639ea9939a002aeb75f21ca159f36ebbd125
        exitCode: 0
        finishedAt: "2021-12-15T15:55:44Z"
        reason: Completed
        startedAt: "2021-12-15T15:54:14Z"
  - containerID: docker://dec311e39113669347d6093c7757d13ce886e1c1f87782df019c02101a001e6d
    image: telegraf:1.14
    imageID: docker-pullable://telegraf@sha256:32fd7cc8528ec27f94a83da19c2dba48fa01d7120a98845ecd28fd0313f2adf0
    lastState: {}
    name: telegraf
    ready: true
    restartCount: 0
    started: true
    state:
      running:
        startedAt: "2021-12-15T15:54:19Z"
  hostIP: <IP_ADDRESS>
  phase: Running
  podIP: <IP_ADDRESS>
  podIPs:
  - ip: <IP_ADDRESS>
  qosClass: Burstable
  startTime: "2021-12-15T15:54:11Z"

In fact, the master pod has the status 'NotReady', inside the telegraf container is working well with a 'Ready' status but the container jmmaster has the status 'NotReady' :

When I go inside the conditions status I don't get usefull informations :

But I think I made good progress this morning. I might have found my issue which is link to the volume. I think jmmeter container can't write the report output file which made the performance test crashed :

In case it can helps, I get this result running this command : kubectl logs jmeter-master-rlxg8 jmmaster (kubectl logs
Can you confirm my problem is linked to this error message :
java.lang.IllegalArgumentException: Cannot write to '/report/report-my-scenario.jmx-2021-12-15_105501' as folder does not exist and parent folder is not writable

Hi thanks for the details !
I'll try tomorrow to run a test asking the master to write the report to a folder where it has no permissions and see if the test continue to be executed or it crash immediately.
But obviously, you need to fix this, even to recover your jtl.
I'm curious about what could cause this permissions problem or mounting errors.

Ok so I have checked the difference between minikube and rancher for the permission at the root of the master pod. In minikube the report folder has full rights for each user when in rancher only the root user has full right, otherwise all others user only have execution permission :
Minikube :

Rancher :

Now I need to learn how to fix this 😄

Well done !
I think it's because Rancher as a safer default approach in terms of security.
In the pod specifications, you can force the mount path to be writable for a specific Gid by setting a security context. I did not remember the jmeter group gid. I'll check it tomorrow. But if you can before, you just have to run the Id command in a slave pod to get it.
Adding the below lines with the right gid in the master pod specification would do the trick.
spec:
      securityContext:
        fsGroup: 1000

Thanks you for the quick reply.
I am so glad it's working now !
If I am not wrong the jmeter group gid is like in your example, 1000 :

I have added the code inside the master pod yml and it's working. It's not perfect because I have to cancel the test when I have the 'WARN Unable to register Log4j shutdown '. And now my master and slave pods change to 'NotReady' after 10 secondes :

But I am able to get the results !

It's seems to be the "normal" behaviour in some way, because the master and the slaves are working as Kubernetes jobs. So when completed, the JMeter container shutdown.
Also there is a cleaner running every minutes as cronjob that should delete the JMeter jobs to free the resources. But because the telegraf operator put a sidecar container, when the JMeter job is completed and the jmeter container  deleted, it remains only the telegraf container inside the pod.
As far I've tested, the complete pod should be destroyed when the job is completed. But maybe there was a change in the telegraf operator. I'll dig that tomorrow.
Don't worry pressing ctrl+c while launching the test, it's really linked to the plugin management.
Anyway, the weirdest thing is you haven't any data back in Grafana. But hey, you struggled to write in /report with the JMeter master. As I provisioned a persistent volume to mount for the influxdb data. I bet you've the very same problem for Influxdb to write on the mounted volume. Could you try to find the Influx logs please ?
Thanks you

Ok I get it for the cleaner not doing its job because of one of the container still running healthy.
Because 24h later, my pods are still there with 'NotReady' and 'CrashLoopBackOff' status for influxdb :

Here the logs of influx container running : kubectl logs influxdb-d6f8b6c89-rvc8t influxdb :
ts=2021-12-16T20:36:04.560514Z lvl=info msg="InfluxDB starting" log_id=0YTFBeK0000 version=1.8.10 branch=1.8 commit=688e697c51fd
ts=2021-12-16T20:36:04.560537Z lvl=info msg="Go runtime" log_id=0YTFBeK0000 version=go1.13.8 maxprocs=4
ts=2021-12-16T20:36:04.662368Z lvl=info msg="Using data dir" log_id=0YTFBeK0000 service=store path=/var/lib/influxdb/data
ts=2021-12-16T20:36:04.662403Z lvl=info msg="Compaction settings" log_id=0YTFBeK0000 service=store max_concurrent_compactions=2 throughput_bytes_per_second=50331648 throughput_bytes_per_second_burst=50331648
ts=2021-12-16T20:36:04.662413Z lvl=info msg="Open store (start)" log_id=0YTFBeK0000 service=store trace_id=0YTFBeiW000 op_name=tsdb_open op_event=start
ts=2021-12-16T20:36:04.675704Z lvl=info msg="Reading file" log_id=0YTFBeK0000 engine=tsm1 service=cacheloader path=/var/lib/influxdb/wal/_internal/monitor/3/_00001.wal size=10489156
ts=2021-12-16T20:36:04.685486Z lvl=info msg="Opened file" log_id=0YTFBeK0000 engine=tsm1 service=filestore path=/var/lib/influxdb/data/_internal/monitor/2/000000001-000000001.tsm id=0 duration=9.314ms
ts=2021-12-16T20:36:04.769633Z lvl=info msg="Opened shard" log_id=0YTFBeK0000 service=store trace_id=0YTFBeiW000 op_name=tsdb_open index_version=inmem path=/var/lib/influxdb/data/_internal/monitor/2 duration=96.091ms
ts=2021-12-16T20:36:04.887026Z lvl=info msg="Opened file" log_id=0YTFBeK0000 engine=tsm1 service=filestore path=/var/lib/influxdb/data/telegraf/autogen/1/000000052-000000001.tsm id=2 duration=105.827ms
ts=2021-12-16T20:36:04.887512Z lvl=info msg="Opened file" log_id=0YTFBeK0000 engine=tsm1 service=filestore path=/var/lib/influxdb/data/telegraf/autogen/1/000000051-000000002.tsm id=1 duration=111.819ms
ts=2021-12-16T20:36:04.969395Z lvl=info msg="Opened file" log_id=0YTFBeK0000 engine=tsm1 service=filestore path=/var/lib/influxdb/data/telegraf/autogen/1/000000037-000000003.tsm id=0 duration=193.752ms
ts=2021-12-16T20:36:04.973061Z lvl=info msg="Opened file" log_id=0YTFBeK0000 engine=tsm1 service=filestore path=/var/lib/influxdb/data/telegraf/autogen/1/000000056-000000001.tsm id=4 duration=85.468ms
ts=2021-12-16T20:36:04.983021Z lvl=info msg="Opened file" log_id=0YTFBeK0000 engine=tsm1 service=filestore path=/var/lib/influxdb/data/telegraf/autogen/1/000000054-000000001.tsm id=3 duration=94.738ms
ts=2021-12-16T20:36:04.999058Z lvl=info msg="Opened file" log_id=0YTFBeK0000 engine=tsm1 service=filestore path=/var/lib/influxdb/data/telegraf/autogen/1/000000064-000000001.tsm id=8 duration=223.368ms
ts=2021-12-16T20:36:05.003621Z lvl=info msg="Opened file" log_id=0YTFBeK0000 engine=tsm1 service=filestore path=/var/lib/influxdb/data/telegraf/autogen/1/000000058-000000001.tsm id=5 duration=34.148ms
ts=2021-12-16T20:36:05.070370Z lvl=info msg="Opened file" log_id=0YTFBeK0000 engine=tsm1 service=filestore path=/var/lib/influxdb/data/telegraf/autogen/1/000000062-000000001.tsm id=7 duration=87.298ms
ts=2021-12-16T20:36:05.076085Z lvl=info msg="Opened file" log_id=0YTFBeK0000 engine=tsm1 service=filestore path=/var/lib/influxdb/data/telegraf/autogen/1/000000060-000000001.tsm id=6 duration=102.969ms
ts=2021-12-16T20:36:05.076250Z lvl=info msg="Reading file" log_id=0YTFBeK0000 engine=tsm1 service=cacheloader path=/var/lib/influxdb/wal/telegraf/autogen/1/_00494.wal size=10556965
ts=2021-12-16T20:36:07.372134Z lvl=info msg="Reading file" log_id=0YTFBeK0000 engine=tsm1 service=cacheloader path=/var/lib/influxdb/wal/telegraf/autogen/1/_00495.wal size=4623757
ts=2021-12-16T20:36:08.176478Z lvl=info msg="Reading file" log_id=0YTFBeK0000 engine=tsm1 service=cacheloader path=/var/lib/influxdb/wal/_internal/monitor/3/_00002.wal size=10489288
ts=2021-12-16T20:36:09.265196Z lvl=info msg="Opened shard" log_id=0YTFBeK0000 service=store trace_id=0YTFBeiW000 op_name=tsdb_open index_version=inmem path=/var/lib/influxdb/data/telegraf/autogen/1 duration=4495.509ms
ts=2021-12-16T20:36:10.466474Z lvl=info msg="Reading file" log_id=0YTFBeK0000 engine=tsm1 service=cacheloader path=/var/lib/influxdb/wal/_internal/monitor/3/_00003.wal size=2858560
ts=2021-12-16T20:36:10.903401Z lvl=info msg="Opened shard" log_id=0YTFBeK0000 service=store trace_id=0YTFBeiW000 op_name=tsdb_open index_version=inmem path=/var/lib/influxdb/data/_internal/monitor/3 duration=6229.830ms
ts=2021-12-16T20:36:10.903537Z lvl=info msg="Open store (end)" log_id=0YTFBeK0000 service=store trace_id=0YTFBeiW000 op_name=tsdb_open op_event=end op_elapsed=6241.124ms
ts=2021-12-16T20:36:10.903584Z lvl=info msg="Opened service" log_id=0YTFBeK0000 service=subscriber
ts=2021-12-16T20:36:10.903603Z lvl=info msg="Starting monitor service" log_id=0YTFBeK0000 service=monitor
ts=2021-12-16T20:36:10.903612Z lvl=info msg="Registered diagnostics client" log_id=0YTFBeK0000 service=monitor name=build
ts=2021-12-16T20:36:10.903623Z lvl=info msg="Registered diagnostics client" log_id=0YTFBeK0000 service=monitor name=runtime
ts=2021-12-16T20:36:10.903628Z lvl=info msg="Registered diagnostics client" log_id=0YTFBeK0000 service=monitor name=network
ts=2021-12-16T20:36:10.903681Z lvl=info msg="Registered diagnostics client" log_id=0YTFBeK0000 service=monitor name=system
ts=2021-12-16T20:36:10.903708Z lvl=info msg="Starting precreation service" log_id=0YTFBeK0000 service=shard-precreation check_interval=10m advance_period=30m
ts=2021-12-16T20:36:10.903719Z lvl=info msg="Starting snapshot service" log_id=0YTFBeK0000 service=snapshot
ts=2021-12-16T20:36:10.903728Z lvl=info msg="Starting continuous query service" log_id=0YTFBeK0000 service=continuous_querier
ts=2021-12-16T20:36:10.903745Z lvl=info msg="Starting HTTP service" log_id=0YTFBeK0000 service=httpd authentication=false
ts=2021-12-16T20:36:10.903750Z lvl=info msg="opened HTTP access log" log_id=0YTFBeK0000 service=httpd path=stderr
ts=2021-12-16T20:36:10.903791Z lvl=info msg="Storing statistics" log_id=0YTFBeK0000 service=monitor db_instance=_internal db_rp=monitor interval=10s
ts=2021-12-16T20:36:10.904029Z lvl=info msg="Listening on HTTP" log_id=0YTFBeK0000 service=httpd addr=[::]:8086 https=false
ts=2021-12-16T20:36:10.904054Z lvl=info msg="Starting retention policy enforcement service" log_id=0YTFBeK0000 service=retention check_interval=30m
ts=2021-12-16T20:36:10.904185Z lvl=info msg="Listening for signals" log_id=0YTFBeK0000
ts=2021-12-16T20:36:10.904637Z lvl=info msg="Sending usage statistics to usage.influxdata.com" log_id=0YTFBeK0000
[httpd] <IP_ADDRESS> - user [16/Dec/2021:20:36:20 +0000] "POST /write?db=telegraf HTTP/1.1 " 204 0 "-" "-" d38ae914-5eaf-11ec-8001-26b188b37fee 667852
[httpd] <IP_ADDRESS> - user [16/Dec/2021:20:36:20 +0000] "POST /write?db=telegraf HTTP/1.1 " 400 190902 "-" "-" d38afa02-5eaf-11ec-8003-26b188b37fee 671709
[httpd] <IP_ADDRESS> - user [16/Dec/2021:20:36:20 +0000] "POST /write?db=telegraf HTTP/1.1 " 400 382482 "-" "-" d38b42dd-5eaf-11ec-8005-26b188b37fee 761836
[httpd] <IP_ADDRESS> - user [16/Dec/2021:20:36:20 +0000] "POST /write?db=telegraf HTTP/1.1 " 400 164819 "-" "-" d38af892-5eaf-11ec-8002-26b188b37fee 772765
[httpd] <IP_ADDRESS> - user [16/Dec/2021:20:36:20 +0000] "POST /write?db=telegraf HTTP/1.1 " 400 190932 "-" "-" d38d6412-5eaf-11ec-8006-26b188b37fee 849683
[httpd] <IP_ADDRESS> - user [16/Dec/2021:20:36:20 +0000] "POST /write?db=telegraf HTTP/1.1 " 400 380244 "-" "-" d38afbc0-5eaf-11ec-8004-26b188b37fee 1075949
[httpd] <IP_ADDRESS> - user [16/Dec/2021:20:36:21 +0000] "POST /write?db=telegraf HTTP/1.1 " 204 0 "-" "-" d3fe8df7-5eaf-11ec-8007-26b188b37fee 518142
[httpd] <IP_ADDRESS> - user [16/Dec/2021:20:36:21 +0000] "POST /write?db=telegraf HTTP/1.1 " 400 222713 "-" "-" d3fe8df7-5eaf-11ec-8008-26b188b37fee 929475
[httpd] <IP_ADDRESS> - user [16/Dec/2021:20:36:21 +0000] "POST /write?db=telegraf HTTP/1.1 " 400 185163 "-" "-" d40dd1a3-5eaf-11ec-800a-26b188b37fee 900042
[httpd] <IP_ADDRESS> - user [16/Dec/2021:20:36:21 +0000] "POST /write?db=telegraf HTTP/1.1 " 400 414406 "-" "-" d400fb46-5eaf-11ec-8009-26b188b37fee 1086628
[httpd] <IP_ADDRESS> - user [16/Dec/2021:20:36:21 +0000] "POST /write?db=telegraf HTTP/1.1 " 400 348686 "-" "-" d43b9d8b-5eaf-11ec-800c-26b188b37fee 703394
[httpd] <IP_ADDRESS> - user [16/Dec/2021:20:36:21 +0000] "POST /write?db=telegraf HTTP/1.1 " 400 222748 "-" "-" d41d14f6-5eaf-11ec-800b-26b188b37fee 909378
[httpd] <IP_ADDRESS> - user [16/Dec/2021:20:36:21 +0000] "POST /write?db=telegraf HTTP/1.1 " 204 0 "-" "-" d45ba049-5eaf-11ec-800d-26b188b37fee 499996
[httpd] <IP_ADDRESS> - user [16/Dec/2021:20:36:22 +0000] "POST /write?db=telegraf HTTP/1.1 " 400 222713 "-" "-" d49727bb-5eaf-11ec-800e-26b188b37fee 405440
[httpd] <IP_ADDRESS> - user [16/Dec/2021:20:36:22 +0000] "POST /write?db=telegraf HTTP/1.1 " 400 159086 "-" "-" d4a6d1f2-5eaf-11ec-800f-26b188b37fee 312104

Like you are saying, I am not sure if everything is working well for grafana here some screenshots :

Hi !
As far I can say, data are written to influxdb because you was able to graph it.
By default, the demo is reaching google.com. Is there anything that would block the traffic from your rancher farm to the external network ?
Because here I'm just seeing that things works.
In fact, the master and slaves being in not ready stats is obviously because they have completed their jobs. If you want to test something else, you can just update the variables in the .env file in the scenario/my-scenario folder with a longer duration.
Just, you should take a look at the cleaner cronjob. I suspect it do not work well in your configuration and I don't really understand why. Because, every minutes, it should clean master and slaves jobs completely if they are done.
Could you provide me some logs about the cleaner cronjob please ?
I'm happy things are getting closer to work for you !

Hey,
I think that data are written too to influxdb because I am able to see some graphs.
I don't have any cronjobs :

I have pull the code to be sure before ...

If you've created the resources with kubectl create -R -f k8s/ the cleaner job should have been created.
But anyway, it's not a problem because every time you start a test, JMeter job are deleted and created again. You just waste few resources with the sidecar containers that are still up and running.
I'll push the permission fix for the master soon. Thanks you for helping me to improve this project.

Thank you for your time helping me :+1:


word missing

"When content is missing for a software update in a deployment created at a parent site, the software update needs to [BE ??] replicated or redistributed to the child site."

Document Details
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ID: 524deab5-2856-c816-c1be-c93ee71910a6
Version Independent ID: eb9d7d68-a321-c33f-41b7-fe370d15d806
Content: Icons used for software updates - Configuration Manager
Content Source: sccm/sum/understand/software-updates-icons.md
Product: configuration-manager
Technology: configmgr-sum
GitHub Login: @mestew
Microsoft Alias: mstewart

Thanks @ISSC-Workplace for catching that. If you'd like to submit the change yourself, see How to contribute. 😉
I suggest changing it to a more active voice:

When content is missing for a software update in a deployment created at a parent site, you need to replicate or redistribute the software update to the child site.

I made this change while I happened to be in the article.


[Bug]: Traefik SSL certificate is not automatically renewed.

Error Message and Logs
Visiting my website that is hosted with coolify yields:
net::ERR_CERT_DATE_INVALID

Subject: ********

Issuer: R10

Expires on: Oct 23, 2024

Current date: Nov 14, 2024

I redeployed the application several times but no changes. I do not use any custom ssl certificates but the default traefik one that should be updated before expiry according to coolify documentation. I also tried updating the domains as mentioned in this issue but to no success.
Steps to Reproduce

Redeploy with coolify default traefik settings
After successful deployment, visit URL but get "Not Secure" warning due to expired certificate

Example Repository URL
https://github.com/stefanwezel/fisch_oder_finte
Coolify Version
v4.0.0.-beta.367
Are you using Coolify Cloud?
No (self-hosted)
Operating System and Version (self-hosted)
Debian 12 (bookworm)
Additional Information
No response

@stefanwezel  is port 80 accessible?
can you check proxy logs

@djsisson port 80 is accessible.
Here is an excerpt from the proxy logs:
`
Coolify
v4.0.0-beta.367
2024-11-14T02:04:48.960263884Z time="2024-11-14T02:04:48Z" level=error msg="Unable to get token: missing token." providerName=acme
2024-11-14T13:46:49.772993674Z time="2024-11-14T13:46:49Z" level=error msg="Error while Peeking first byte: read tcp <IP_ADDRESS>:80-><IP_ADDRESS>:19861: read: connection reset by peer"
2024-11-14T17:31:45.172913659Z time="2024-11-14T17:31:45Z" level=error msg="Error while Peeking first byte: read tcp <IP_ADDRESS>:80-><IP_ADDRESS>:49466: read: connection reset by peer"
2024-11-14T17:38:43.763285900Z time="2024-11-14T17:38:43Z" level=error msg="Error renewing certificate from LE: {fischoderfinte.de []}" providerName=letsencrypt.acme ACME CA="https://acme-v02.api.letsencrypt.org/directory" error="error: one or more domains had a problem:\n[fischoderfinte.de] acme: error: 403 :: urn:ietf:params:acme:error:unauthorized :: 2a01:4a0:2002:4:1da9:a99f:5423:3cf1: Invalid response from http://standby.checkdomain.de/: "\n    \n    \n        \n            <meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />"\n"
`

@stefanwezel 403 is forbidden have u put auth on endpoint?

@stefanwezel ok its a redirect, can u explain your setup
what url u want ssl on, u cant redirect a http challenge to a different domain

@stefanwezel if you run  curl -v http://fischoderfinte.de you wil lsee you are returning a redirect to http://standby.checkdomain.de/ hence the http challenge fails, you can't return a redirect

This redirect has been up for a while already. Since it is only HTTP I didn't bother too much. If you do curl -v https://fischoderfinte.de instead, you will get the response SSL certificate problem: certificate has expired.

@stefanwezel yes but httpo challenge doesnt work on redirects which is why you arent getting it renewed, you will have to a different method to generate a cert
either install manually, use dns challenge or tls challenge

@djsisson thanks for your hint. I think it was indeed due to my dns provider setting up a redirect automatically since the http version of my domain was not pointing to anything. @mihneawalker maybe it is due to a firewall setting on your VPS?


segment.GNN_seg error

Hello,
I am trying to replicate your results running the example.ipynb file, but the code shows following error, I have not made any changes to the code still getting this error;
1 stride = 8
2 device = 'cuda' if torch.cuda.is_available() else 'cpu'
----> 4 segment.GNN_seg(mode, epochs, K, pretrained_weights, in_dir, out_dir, save, cc, bs, log_bin, res, facet, layer, stride,
5         device)
TypeError: GNN_seg() missing 2 required positional arguments: 'stride' and 'device'

I found solution to this this,
in gnn_pool.py replacing
x = self.convs(x, edge_index, edge_atrr)  # applying con5v
x = self.convs(x, edge_index)  # applying con5v

resolves the error as in pyg_nn.GCN, does not need edge_attr.
Doing this changes, the code runs and gives the output as mentioned in the paper.
Please let me if thats correct way to rectify the changes.

I found solution to this this,
in gnn_pool.py replacing
x = self.convs(x, edge_index, edge_atrr) # applying con5v
x = self.convs(x, edge_index)  # applying con5v

resolves the error as in pyg_nn.GCN, does not need edge_attr.
Doing this changes, the code runs and gives the output as mentioned in the paper. Please let me if thats correct way to rectify the changes.

I use your solution, but it doesn't work, and still the same error

I also use your solution, but it doesn't work, and still the same error


Prefer constraint type for object literal completion

Fixes #9900
Fixes #12968
Store constraint type when inferring and prefer it when resolving contextual type for completion.
I'm not sure what i'm doing it by correct way, anyway i just want to move these issues forward 😃

Hi @asvetliakov, I'm your friendly neighborhood Microsoft Pull Request Bot (You can call me MSBOT). Thanks for your contribution!
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I feel like a better fix would be to use the apparent type of the contextual type when it comes to completions. It used to be the case that the language service's concept of getContextualType was intermingled with the apparent type (and was made explicit with https://github.com/Microsoft/TypeScript/pull/5185/commits/d8d72aabae439e17d18e35887981165413b71556).

The completion flow is already calling getApparentType in few places, but they don't return constraint type because object literal is being created as totally new anonymous type object. Not sure how to get correct type by this case.

@DanielRosenwasser
I tried to use getApparentType approach, but object literals in function arguments are being created with new anonymous object type and don't contain necessary flag TypeVariable with resolvedBaseConstraint property. I tried to fill this information in createObjectLiteralType() or in getInferredType() but this broke checker completely - looks like it doesn't expect constraint type inferring for these object literals. (it even was not able to compile)
Let me know if you have any ideas

This is stale by now. @andy-ms was looking into something similar recently.


add cfn stackset execution role name support

Please check if the PR fulfills these requirements

[x] The commit message describes your change
[x] Tests for the changes have been added if possible (for bug fixes / features)
[x] Docs have been added / updated (for bug fixes / features)
[x] Changes are mentioned in the changelog (for bug fixes / features)

What kind of change does this PR introduce? (Bug fix, feature, docs update, ...)
Adds support for execution role name in stacksets

What is the current behavior? (You can also link to an open issue here)
Unable to set this in the stackset

What is the new behavior (if this is a feature change)?
The field can be set

Does this PR introduce a breaking change? (What changes might users need to make in their setup due to this PR?)
no

Other information:

Can you please add this to the docs too?


Rating sizes are not correct

The rating sizes are not correct.

Still looks different.

![Screenshot 2021-10-09 at 15 22 44](https://user-images.githubusercontent.com/37311649/136661938-e98126b5-8a95-4796-8c10-c6ddabc628cd.png)


doc changes for 2.1.4 patch

Just FYI, fixing some typos in https://github.com/pachyderm/pachyderm/pull/7410


"Intelligent Cloud Sync as a Data Migration Mechanism" link not working

"Intelligent Cloud Sync as a Data Migration Mechanism" link not working

Document Details
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ID: 71aa4400-739a-6867-a2f5-2917a72d7620
Version Independent ID: e0153a2f-2b2f-919a-33b1-43b0e9113413
Content: The “Ready to Go” Online learning for developers, architects, and engineers - Business Central
Content Source: dev-itpro/developer/readiness/readiness-learning-dev-archs-engineers.md
Service: dynamics365-business-central
GitHub Login: @SusanneWindfeldPedersen
Microsoft Alias: solsen

Hello, thanks for your feedback. We're hoping to have the video ready within the next week, and then the link will be updated. Thanks.


fix git clone github url

Changes

Point git clone url to NOAA-OWP instead of fork

@Nels Frazier - NOAA Affiliate<EMAIL_ADDRESS>Squash and merge or rebase for a small change like this?
(your prior comment seems to indicate "always rebase"...)
James Halgren
NOAA National Water Center
+1<PHONE_NUMBER>
Lynker https://www.lynker.com/
On Fri, Apr 10, 2020 at 3:16 PM Nels<EMAIL_ADDRESS>wrote:

@hellkite500 https://github.com/hellkite500 requested your review on: #2
https://github.com/NOAA-OWP/t-route/pull/2 fix git clone github url.
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In this case they are one and the same.  Rebase just keeps all commits in the PR and applies them to the head of the destination branch.  Since this is only one commit, it will do the same.  Only difference is squash and merge will generate a new commit id and a new commit message to associate with it.  If there are multiple commits, squashing creates a new single commit with all changes.  Sometimes this is required to prevent merge conflicts, though typically you do this locally and update the PR with whatever commit you want in the upstream history.  If you don't want certain commits to show up in the upstream history, they should be rebased in the fork/local dev clone then the "final" ones pushed to the PR branch.

Thanks -- that make sense. Since it's the same, I squashed for this time.
James Halgren
NOAA National Water Center
+1<PHONE_NUMBER>
Lynker https://www.lynker.com/
On Fri, Apr 10, 2020 at 4:39 PM Nels<EMAIL_ADDRESS>wrote:

In this case they are one and the same. Rebase just keeps all commits in
the PR and applies them to the head of the destination branch. Since this
is only one commit, it will do the same. Only difference is squash and
merge will generate a new commit id and a new commit message to associate
with it. If there are multiple commits, squashing creates a new single
commit with all changes. Sometimes this is required to prevent merge
conflicts, though typically you do this locally and update the PR with
whatever commit you want in the upstream history. If you don't want certain
commits to show up in the upstream history, they should be rebased in the
fork/local dev clone then the "final" ones pushed to the PR branch.
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Idea: Support init from connection string & map

Allow user to init a service like:
Open("s3://bucket_name?access_key=xxxx&secret_key=xxxx")

Or
Open(map[string]interface{
    "name": "xxxxx"
})

Take https://github.com/xo/dburl a look

@xxchan will implement this idea.
Please create an RFC which refers to this issue.


no support Django==4.2

i start django server and get answer:
Watching for file changes with StatReloader Exception in thread django-main-thread: Traceback (most recent call last):   File "/Users/vladimir/.pyenv/versions/3.11.2/lib/python3.11/threading.py", line 1038, in _bootstrap_inner     self.run()   File "/Users/vladimir/.pyenv/versions/3.11.2/lib/python3.11/threading.py", line 975, in run     self._target(*self._args, **self._kwargs)   File "/Users/vladimir/.pyenv/versions/project_name/lib/python3.11/site-packages/django/utils/autoreload.py", line 64, in wrapper     fn(*args, **kwargs)   File "/Users/vladimir/.pyenv/versions/project_name/lib/python3.11/site-packages/django/core/management/commands/runserver.py", line 125, in inner_run     autoreload.raise_last_exception()   File "/Users/vladimir/.pyenv/versions/project_name/lib/python3.11/site-packages/django/utils/autoreload.py", line 87, in raise_last_exception     raise _exception[1]   File "/Users/vladimir/.pyenv/versions/project_name/lib/python3.11/site-packages/django/core/management/__init__.py", line 394, in execute     autoreload.check_errors(django.setup)()   File "/Users/vladimir/.pyenv/versions/project_name/lib/python3.11/site-packages/django/utils/autoreload.py", line 64, in wrapper     fn(*args, **kwargs)   File "/Users/vladimir/.pyenv/versions/project_name/lib/python3.11/site-packages/django/__init__.py", line 24, in setup     apps.populate(settings.INSTALLED_APPS)   File "/Users/vladimir/.pyenv/versions/project_name/lib/python3.11/site-packages/django/apps/registry.py", line 116, in populate     app_config.import_models()   File "/Users/vladimir/.pyenv/versions/project_name/lib/python3.11/site-packages/django/apps/config.py", line 269, in import_models     self.models_module = import_module(models_module_name)                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^   File "/Users/vladimir/.pyenv/versions/3.11.2/lib/python3.11/importlib/__init__.py", line 126, in import_module     return _bootstrap._gcd_import(name[level:], package, level)            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^   File "<frozen importlib._bootstrap>", line 1206, in _gcd_import   File "<frozen importlib._bootstrap>", line 1178, in _find_and_load   File "<frozen importlib._bootstrap>", line 1149, in _find_and_load_unlocked   File "<frozen importlib._bootstrap>", line 690, in _load_unlocked   File "<frozen importlib._bootstrap_external>", line 940, in exec_module   File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed   File "/Users/vladimir/.pyenv/versions/project_name/lib/python3.11/site-packages/chunked_upload/models.py", line 10, in <module>     from .constants import CHUNKED_UPLOAD_CHOICES, UPLOADING   File "/Users/vladimir/.pyenv/versions/project_name/lib/python3.11/site-packages/chunked_upload/constants.py", line 1, in <module>     from django.utils.translation import ugettext as _ ImportError: cannot import name 'ugettext' from 'django.utils.translation' (/Users/vladimir/.pyenv/versions/project_name/lib/python3.11/site-packages/django/utils/translation/__init__.py)

With the same error in Django>4, I just added these lines on the top of settings.py, and worked.
import django
from django.utils.translation import gettext
django.utils.translation.ugettext = gettext


Replace JSON null with undefined when parsing response

closing as we haven't gotten a request for this


remove icp code

remove ICP code

clang format successful! https://ci.trafficserver.apache.org/job/clang-format-github/402/

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[approve ci]

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Resolved Bug 628 : Label Is CICD Instead Of Ci/CD

Description

Change label name Ci/Cd to CICD

Screenshots:

Checklist:

[x] My code follows the style guidelines of this project
[x] I have performed a self-review of my own code
[x] I have commented my code, particularly in hard-to-understand areas
[x] I have made corresponding changes to the documentation
[x] My changes generate no new warnings
[x] I have added tests that prove my fix is effective or that my feature works
[x] New and existing unit tests pass locally with my changes

Changes Reviewed and PR Approved


does http://scholars.sciencecommons.org/ have a heartbeat?

on twitter, someone asking about the Scholar's Copyright Addendum Engine; used to be located at this page

It was up, and it needs to get back up before the Summit. It's part of the Open Access session.
@Mattl, can you find it and restore it please?
@tvol, what's the note on twitter? I'm interested, because we're updating the engine and agreements with SPARC and Authors Alliance.

@diane it's public on our Twitter feed. just someone wondering why it doesn't work anymore.

understood. I've been working on that with sparc and authors alliance, and it was up not that long ago. agree we need it back up, and i was wondering if you had more info about the tweet behind the scenes.
look forward to having that back online.

Just updated the DNS, should be back very soon. @tvol let's have a meeting/email soon to discuss what we need to keep on that domain and where we're going to put it on CC.org so we can retire the Science Commons websites

@mattl @tvol We need it live for awhile, somewhere. I think there should at most be a redirect, so the link stays good for those who use or reference it as we discuss the Arcadia revamp of SCAE and the addenda.
Regarding science commons site, we should do an inventory. there is a lot of stuff on there I still link to that we need to preserve live somewhere in an orderly fashion. can we discuss post summit?

:+1:

why can't we just leave the sciencecommons pages as is with the notice at the top?

We'd like to switch the server off, and we should do something with all the
various things on that site.

IMO the important pieces of content to harvest would be:

project pages
reading room papers written by Science Commons staff
the video

@peterspdx what do you think?

for @peterspdx to review

got it, will look later this week and provide a recommendation.

cool. thanks.
On Tuesday, January 26, 2016, Diane Peters<EMAIL_ADDRESS>wrote:

got it, will look later this week and provide a recommendation.
—
Reply to this email directly or view it on GitHub
https://github.com/creativecommons/creativecommons.org/issues/137#issuecomment-175315341
.

--
Invest in a free and open internet. Donate to Creative Commons:
https://donate.creativecommons.org/

by way of update @tvol, I am looking at these still in light of Arcadia deliverables, and should have an update with some thoughts on your recommendations next week. Happy to have this assigned to me for next steps.

@tvol recommended:

project pages
reading room papers written by Science Commons staff
the video

I think almost all of the content on the site is valuable. There are only so many having just clicked around bunches. The challenge in reviewing is that the main page at sciencecommons.org redirects to the CC website with a note it has been reintegrated. And I can't find a site map for all of the pages, which I assume can be found off the main page (which redirects) and pages those pages link to.
Can we get a site map produced?
Based on what I've seen, all of the patent license-related pages should be retained, all of the project pages, I believe there was a separate weblog -- would be great to see those posts merged with our weblog so they're not lost, all of the database and data information. Again, I see almost nothing there that isn't useful especially as we work with Arcadia and others on scholarly works including those in the science arena.
@mattl and @robmyers, suggestions for how we can inventory? Thanks.

I can get a site map created. https://github.com/creativecommons/creativecommons.org/issues/245


Higher Hartree Fock energy in the latest version

Hello,
HF calculation behavior is different up to ver 2.1.1 and after 2.2.0, where we checked ver 2.0.1, 2.1.0, 2.1.1, 2.2.0, and 2.2.1, and pyscf is installed with pip.
HF calculations were performed on a planar model with four hydrogens.
from pyscf import gto, scf
import numpy as np
mol = gto.M(atom = '"H 0.0 0.0 0.0 ;H 1.34 0.0 0.0 ;H 0.0 1.34 0.0 ;H 1.34 1.34 0.0 "', basis = 'sto-3g', spin=0)
mf = scf.RHF(mol).run()
print("mo coeff\n", np.round(mf.mo_coeff,3))

Here are the results.
ver 2.1.0
converged SCF energy = -1.75914707282045
mo coeff
 [[ 0.374 -0.54   0.54  -0.708]
 [ 0.374 -0.54  -0.54   0.708]
 [ 0.374  0.54   0.54   0.708]
 [ 0.374  0.54  -0.54  -0.708]]

ver 2.2.0
converged SCF energy = -1.67708182393442
mo coeff
 [[ 0.409  0.    -0.763 -0.689]
 [ 0.339 -0.763 -0.     0.725]
 [ 0.339  0.763  0.     0.725]
 [ 0.409 -0.     0.763 -0.689]]

Compared to the ver. 2.1.0 results, the ver. 2.2.0 results show a localized MO and higher HF energy. GAMESS-US also produced results corresponding to those of ver. 2.1.0. Therefore, ver 2.1 appears to be more consistent with our chemical intuition.
We expect that the way to determine the axis of symmetry in the xy-plane has changed between ver 2.1.1 and 2.2.0. One of the reasons is that the behavior was reproduced in GAMESS-US when the symmetry axis was rotated by 45 degrees. Also, in pyscf ver 2.1.0, when HF calculation was run 10 times with the atomic coordinates rotated by 45 degrees, MO localization occurred 3 times (this kind of randomness also sometimes occurs in other systems, is this a feature?)
I am currently pending an update of pyscf due to this behavior, but I am wondering if there is a way to manage it.
Thanks,
Shu

I have just tested with the latest pyscf version on here (git hash 485098119e4879acebfedc3f17d956a0c0377124 ) and I get -1.75914707282022. This could of course be system dependent.

Thank you for your response. As you've suggested, there seems to be a system-dependent variability in the output. Specifically, I've observed different results just by translating or rotating the atomic coordinates of input. Moreover, I noticed different behaviors when installing via pip and conda. Furthermore, other members running the same code have reported different outcomes as well.
In my current environment (WSL2, Ubuntu 20.04.5, Python 3.9.13, PySCF 2.1.0), the output is stable for specific inputs, but I cannot guarantee that this will remain the case if the software is updated. In my research, I frequently call this software from external software, specifically OpenFermion, and Qiskit. If the output is sensitively dependent on the system and changes with every call, it becomes difficult to benchmark my experiments.
Do you have any suggestions for handling this issue? Currently, I'm considering using pickle to save the Hamiltonian data when lower HF energy is produced, but this approach may not work well for more complex systems.

Yes this behaviour with the differing HF solutions is not ideal. Can you try running stability analysis after the HF calculation and then restart if not stable to find a more stable solution, see e.g. examples/scf/17-stability.py ? To save the molecular coefficients etc from the SCF calculation, you can save them to a chkfile if you like, see scf/14-restart.py .

You are running HF in square planar H4 at a bond length of 1.34 Å. This system is strongly correlated, and HF has a plethora of local solutions; the solution you land on may depend even on numerical roundoff errors.

Thank you for the information.

Yes this behaviour with the differing HF solutions is not ideal. Can you try running stability analysis after the HF calculation and then restart if not stable to find a more stable solution, see e.g. examples/scf/17-stability.py ?

I got better a result by using stability analysis.
"""
from pyscf import gto, scf
import numpy as np
mol = gto.M(atom = '"H 0.0 0.0 0.0 ;H 1.34 0.0 0.0 ;H 0.0 1.34 0.0 ;H 1.34 1.34 0.0 "', basis = 'sto-3g', spin=0)
mf = scf.RHF(mol).run()
print("mo coeff\n", np.round(mf.mo_coeff,3))
from pyscf.lib import logger
def stable_opt_internal(mf):
log = logger.new_logger(mf)
mo1, _, stable, _ = mf.stability(return_status=True)
cyc = 0
while (not stable and cyc < 1000):
log.note('Try to optimize orbitals until stable, attempt %d' % cyc)
dm1 = mf.make_rdm1(mo1, mf.mo_occ)
mf = mf.run(dm1)
mo1, _, stable, _ = mf.stability(return_status=True)
cyc += 1
if not stable:
log.note('Stability Opt failed after %d attempts' % cyc)
return mf
print('loop example')
mf2 = stable_opt_internal(mf)
print("mo coeff\n", np.round(mf2.mo_coeff,3))
"""
Here is a result in pyscf ver 2.2.1.
"""
converged SCF energy = -1.67708182393441
mo coeff
[[ 0.409 -0.    -0.763 -0.689]
[ 0.339  0.763 -0.     0.725]
[ 0.339 -0.763  0.     0.725]
[ 0.409  0.     0.763 -0.689]]
loop example
<class 'pyscf.scf.hf.RHF'> wavefunction has an internal instability
Try to optimize orbitals until stable, attempt 0
converged SCF energy = -1.75914707280783
<class 'pyscf.scf.hf.RHF'> wavefunction is stable in the internal stability analysis
mo coeff
[[ 0.374 -0.54  -0.54   0.708]
[ 0.374  0.54  -0.54  -0.708]
[ 0.374 -0.54   0.54  -0.708]
[ 0.374  0.54   0.54   0.708]]
"""
I will also try restart mode.

You are running HF in square planar H4 at a bond length of 1.34 Å. This system is strongly correlated, and HF has a plethora of local solutions; the solution you land on may depend even on numerical roundoff errors.

While electron correlation would affect the result as you said, the MO localization happens even when the bond length is 0.7 angstrom. From the reproduction of this issue by GAMESS in the first comment, I think that this higher energy comes from the rotation of the symmetry axis. Specifically, when the atoms are arranged in the square $\square$ like the input, low energy is obtained, but due to the symmetry axis search, when the arrangement is rotated by 45 degrees and becomes rhombic $\diamond$, the hydrogen atoms are placed on the symmetry axis, which affects the symmetry operation, and high energy is obtained.

The conclusion is that we should include a stability analysis in each Hartree-Fock calculation, right?
Thanks for the suggestions. I will close the issue if there are no other suggestions or comments.

I think especially in systems with many HF solutions being close together, like this one as @susilehtola mentioned, it is not a bad idea. Good luck!


What's the point of Ingress Controller?

The nginx pod can land on any node and get one of many possible IPs, but its supposed to be my access to the internet, what do you expect me to use in my domain A record? Why would I not just use a separate machine, outside of the cluster, for proxying traffic to my pods. Maybe a better idea would be to allow me to find the IPs of the pods when I'm outside the cluster as well.

Why would I not just use a separate machine, outside of the cluster, for proxying traffic to my pods.

The machine outside your network cannot see the pod ips. You probably want a loadbalancer at the edge, both exposed to the outside and capable of seeing the podips.

Maybe a better idea would be to allow me to find the IPs of the pods when I'm outside the cluster as well.
Pod ips are typically cluster private (https://github.com/kubernetes/kubernetes/blob/release-1.1/docs/user-guide/ingress.md#what-is-ingress), you can give each pod a hostport, but that is not advisable.

what do you expect me to use in my domain A record?

If you're using a cloudprovider, you would put the loadbalancer ip assigned to the ingress. If you're using baremetal with something like haproxy, you would setup corosync and/or pacemaker to setup public vips. See https://groups.google.com/forum/#!topic/kubernetes-sig-network/B-A_RuqpFWk for a more detailed discussion.

Feel free to post on stack overflow or get on slack for further clarification


GPU Symmetric Fake Quantization

Extension of PR #48580 which adds GPU unit tests for symmetric fake quantization.
Attn: @Xhark.

Looks like this has been rolled back again in e4f883065966d41ce6e04061100c3c5d8e0eec7a.

@Xhark do you have any information on why this has been rolled back in e4f883065966d41ce6e04061100c3c5d8e0eec7a?

@philipphack Do you mind reopening the PR as it looks like it has been rolled back in e4f883065966d41ce6e04061100c3c5d8e0eec7a?

Hi @lgeiger, It was rollbacked because it broken some internal tests. sorry for the late notice. I'm trying to find a way to handle that. Thanks.

It was rollbacked because it broken some internal tests. sorry for the late notice. I'm trying to find a way to handle that.

Thanks for looking into it 👍


Shows deleted tags

Apparently, go-git is able to discover tags that have been deleted.
Steps to reproduce:
Considering this snippet:
package main

import (
	"fmt"

	git "gopkg.in/src-d/go-git.v4"
	"gopkg.in/src-d/go-git.v4/plumbing/object"
)

func main() {
	repo, err := git.PlainOpen(".")
	if err != nil {
		panic(err)
	}
	tags, err := repo.TagObjects()
	if err != nil {
		panic(err)
	}

	tags.ForEach(func(t *object.Tag) error {
		fmt.Println(t)
		return nil
	})
}

Do the following steps:

Create a new git repo
$ git init
Run the snippet. As expected, there is no output.
Create a tag:

$ touch test
$ git add test
$ git commit -m "test"
$ git tag -am "test" 1.0.0

Run again, the tag is shown:

$ go run main.go
tag 1.0.0
Tagger: shorez<EMAIL_ADDRESS>Date:   Fri Oct 12 14:51:13 2018 +0200

test

commit 284da2eb4c87c0467c87ce131156d75c74d84736
Author: shorez<EMAIL_ADDRESS>Date:   Fri Oct 12 14:50:52 2018 +0200

    test

Delete the tag:
git tag -d 1.0.0
Run the snippet again:

 go run main.go
tag 1.0.0
Tagger: shorez<EMAIL_ADDRESS>Date:   Fri Oct 12 14:51:13 2018 +0200

test

commit 284da2eb4c87c0467c87ce131156d75c74d84736
Author: shorez<EMAIL_ADDRESS>Date:   Fri Oct 12 14:50:52 2018 +0200

    test

Unlike expectations, the tag is still shown, but the git cli does not seem to know about it:
$ git tag
# nothing here

And there is no ref in the folder:
$ find .git/refs
.git/refs
.git/refs/heads
.git/refs/heads/master
.git/refs/tags

I really have no idea why this is even possible, so maybe somebody can help?
Thanks,
sh0rez

For the record, deleting the tag using repo.DeleteObject make it disappear for good.

The problem is that repo.TagObjects calls repo.Storer.IterEncodedObjects. Storer is an interface, and the Filesystem implementation (the one that reads from the .git directory), just loops over all the objects inside .git/objects, and only filters out the ones that are of type Tag.
Git by design always performs non-destructive operations, so when you delete a tag, you are only deleting the reference (.git/refs/tags) to the commit, not the particular "tag" object, that will stay forever in the repository (unless you run git fsck, I guess).
I'm not acquainted with the codebase, so I'm not sure how to fix this, but I'd be happy to help if someone points me in the right direction.

I'm not acquainted with the codebase, so I'm not sure how to fix this, but I'd be happy to help if someone points me in the right direction.

I'm not in the code either, but I believe go-git should behave like the real git and use the refs instead discovering them from the objects. So probably just change the implementation of repo.TagObjects to return the objects the refs of type tag point to? From my point of view this should be the desired behaviour ...

Yeah. I mean, I know what to do (exactly what you proposed), but not how for this codebase from the design point of view :)
The problem I see is that various functionalities related with "fetching objects" are generalized, and the code passes around the type of object to filter by, and now that I think about it, this should be the way to go IMHO. For all type of objects only fetch from whatever tip is in refs/ instead accessing the objects directory directly as it can contain spureous/dangling objects.
I'll try to give it a shot the following days.

TagObjects will only return annotated tags. And any which appear in the object store (whether they are referenced or not).
If you are trying to replicate git tag you should iterate over tag references instead (this is necessary to support both lightweight and annotated tags). Iterating over references would also allow you to skip tags that have been deleted (aka unreferenced).
See https://godoc.org/gopkg.in/src-d/go-git.v4#Repository.References , filter out references that don't start with refs/tags/

@orirawlings just got the response faster :wink:, so what he said, and some more details:
@sh0rez You will achieve your desired behavior by using the Tags function, instead of TagObjects.

Tags returns tag references. The behaviour is analogous to git tag.
TagObjects returns all tag objects, no matter if they are reachable from a reference or not. Which is analogous to something like git cat-file --batch-check --batch-all-objects | grep ' tag '.

Most of our iterators (TagObjects, Commits, etc) return all objects whether they are reachable or not. This is more performant (computing reachability is expensive), but sometimes unexpected depending on the use case. Reachability can be checked with the revlist package, the Walk* functions, etc.
This behavior cannot really change in v4, since it would be not backwards compatible.

Closing as invalid, since current behavior works as designed in go-git v4.


Dynamic GSSOC banner

Description
Changed the current image to images which will load based on device theme
Screenshots -

Fixes #325
Have you read the Contributing Guidelines on Pull Requests?

[x] Yes
[ ] No

Type of change
Please delete options that are not relevant.

[ ] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[x] Breaking change (fix or feature that would cause existing functionality to not work as expected)

Checklist:

[x] My code follows the style guidelines(Clean Code) of this project
[x] I have performed a self-review of my own code
[x] My changes generate no new warnings
[x] I have added tests/screenshots(if any) that prove my fix is effective or that my feature works.

Hey there @suman-somu, this issue is assigned to me.
So you can't work on this issue to make a PR.
Kindly close this PR otherwise this Project's PA will Close this.
Hope you understood.