text:
Back #2, I just need 1 piece of information

I read the javadocs, but one issue I didn't find out was how I can draw the TiledTile on my canvas, since canvas can only draw Images not TiledImages, and I can't cast it.
P.S, sorry, It was Alex who referred me to you!

Not sure why Alex refered you to me, I don't know anything about what you are asking. Anyway...
There is a lib included with Tiled that does rendering for you iirc https://github.com/mapeditor/tiled/tree/master/util/java/libtiled-java. Maybe use that instead.
You could also just export the map to PNG and use that.
With TiledReader it seems pretty strait forward to me. Looking at the classes, probably use TiledTile.getTilesetX/Y and TiledTile.getImage to get to the source image.
For the actual rendering I suggest you check stackoverflow or some basic Java tutorial.
For question about the Tiled editor check their forum of discord.
But most importantly: Use your favorite search engine, pretty sure it has answers to your questions ;).
I'm sure you can figure this out!
Please don't open any more issues on this repo, except if it's about the actual software in the repo.


text:
Feature Request - Use web GUI to modify local nfo without scraping

Sometimes after watching a movie, I want to go back and update the nfo genres. I don't want to have to rescrape everything when I already have the covers. I'd rather be able to edit nfo in the web GUI rather than in a notepad. GUI has advantage of simple clicking to remove genre or add from favorites.

I've dabbled with this one in the past, but I wasn't able to get it in a state I was satisfied with. I would recommend either using an external nfo/xml editor or to use JAVMovieScraper's desktop editor.
The issue with the current javinizer gui is that the data model and the editor gui don't really match up to be able to transform back and forth 1 <-> 1. This is because there are transformations that happen in the backend as the metadata gets transformed into the nfo file. Unfortunately development on the GUI is at a standstill as well due to the difficulty of the technology used.

source: gharchive/issue

authors: fumbleone jvlflame

repo: jvlflame/Javinizer

license: MIT

license_type: permissive

license_source: github-api


text:
Percentage of sampling traces are low in async-profiler

Hi Panjin,
Appreciate your contribution to async-profiler. Its commendable effort.
Since we are planning to integrate async-profiler as an one stop APM solution for all our apps we have been asked to evaluate async-profiler against JMC.
During evaluation we noticed few deviations in samples been collected while comparing the performance data between async-profiler against Java Mission Control(JMC).
Total samples count was huge for async-profiler compared against JMC . We are cleat that its due to asyncgetcalltrace.
Top methods were highlighted properly.
But samples percentage for few non critical packages was shown less in async-profiler compared against JMC. Since the samples are collected from the same app the samples percentage should be same for all packages right. We would like to know how samples collection been performed in async-profiler. Any inputs or assumptions behind the deviations. Even though we dont see it as an issue we would like to understand. Could you please clarify
We enabled -XX:+DebugNonSafepoints.
Command executed inside docker:
./profiler.sh -e itimer -s 30 -f /tmp/sample.svg $PID we used itimer since we couldn't inside perf inside the container and due to restricted access to host.
Are we missing something from our side . Please guide us
Sattish.

Hi Panjin,
Is it possible to record only Java stacks in async-profiler. We tried with the flag  --all-user but still we could see events related GC and Native code in the dump. Since we want to compare with JFR dump do we have an option in async-profiler to dump only Java stacks. Please confirm
Sattish.

async-profiler and JMC (or, more precisely, Flight Recorder) work differently.
In itimer mode async-profiler wakes up every period of cpu time and gets a stack trace from one of the threads currently scheduled on cpu.
Flight Recorder wakes up every period of wall-clock time and gets stack traces from a subset of all threads. So, it's more like async-profiler's -e wall mode, except that it skips non-runnable (blocked / waiting / sleeping) threads.
The problem is - JVM does not distinguish idle and busy threads executing a native method. E.g. when there are two threads both executing SocketInputStream.read, if one of the threads is actively receiving data, and the other thread is just waiting for incoming data, JVM will not make a difference - from its point of view both threads will be in RUNNABLE state. However, only one of these threads will consume CPU time.
In the above example async-profiler will sample only one thread receiving data, while Flight Recorder will sample both, because JVM thinks both are RUNNABLE. This is my guess where the difference comes from, though I can't be absolutely sure without seeing the profiles or the code.

Is it possible to record only Java stacks in async-profiler. We tried with the flag --all-user but still we could see events related GC and Native code in the dump. Since we want to compare with JFR dump do we have an option in async-profiler to dump only Java stacks.

Well, the ability of profiling JVM and native code is one of the main advantages of async-profiler. This part of the profile is the essential difference between AP and JFR. Since you are comparing the tools, you want to know what the difference is, right? So why make the output intentionally worse, just to make it look more like JFR?
But it is still possible to get a profile without JVM part: create a dump in a collapsed text format, filter out all lines starting with start_thread (a simple grep command), and then use FlameGraph script to convert text output to SVG.
I plan to add general purpose filtering to async-profiler (#187) to avoid such kind of manipulations with grep etc.

Hi ,
Thanks for clarifying our queries. This was really useful to us for comparing the performance data between JFR and async-profoler. Will get back to you incase we need few more details.
Thanks
Sattish.

Hi ,
Sorry for continuing with the same topic. Today we executed series tests with different number of concurrent users(5,10,15)  same requests rate on the same code base. When analyzed we found the samples count increased relatively with the number of users. But the package percentage % match for ex. org.apache. reduced with the number of users increased. The percentage match calculated for each packages got reduced with the test having 15 users. For 5 users test percentage was high. We are curious to know how the samples are collected and how the cpu time is calculated from each samples. Could you please clarify
Thanks

Hi ,
Sorry i missed your statement which you mentioned before on stack trace collection.
"itimer mode async-profiler wakes up every period of cpu time and gets a stack trace from one of the threads currently scheduled on cpu."

How are we calculating the cpu time spent from the static stack trace.
why are we seeing the difference in percentage per package in search option for different user test.

Thanks in advance

This article by Brendan Gregg should explain how to interpret Flame Graphs (including those collected by async-profiler).
This is a sampling profiler. It does not tell exactly how much time was spent in a specific method, or how many times the method was executed. Though it may give an estimate as discussed in #107.
It's absolutely possible that some methods have higher or lower percentage of samples depending on the load. This behavior is purely application-specific. So far I don't see a contradiction. If you suspect that data collected by async-profiler is somehow wrong, please open an new issue, attach the suspicious profile and, if possible, provide a test case that demonstrates the problem.

Hi,
Thanks once again for clarifying us.

It's absolutely possible that some methods have higher or lower percentage of samples depending on the load. This behavior is purely application-specific. So far I don't see a contradiction.

I agree Yes you are right . But our question is different . To make it clear
Let me list our test parameters
5 user test recorded 30,000 samples
10 user recorded 50,000 samples
15 user recorded 70.000 samples
But the match percentage for few packages e.g (org.springframework) varies with the workload. For 5 user test it was high compared to 15 user test.
Our question is with the high samples count been recorded in 15 user how come package percentage went low compared to 5 user test where samples count is less. Does the samples resides within other packages.
If you suspect that data collected by async-profiler is somehow wrong, please open an new issue, attach the suspicious profile and, if possible, provide a test case that demonstrates the problem.
We arent suspecting the data we would like to understand why we see match percentage for certain packages is low as the load increases. Thought understanding the collection behavior of async will help us to understand the behavior.
Let me collect the samples with output format as flat and see what we incur from it.
Thanks

Hi ,
while searching we came across this blog where they have cleared explained how sampling technique works and how the metrics like total self time been calculated . Can you let us know are we following this similar approach in collecting samples.
https://devblogs.microsoft.com/devops/how-cpu-sampling-works/
Thanks

Yes, that's how sampling profilers (including async-profiler) typically work.

Thanks. In flat file format we could see data been measured as
      ns  percent  samples  top

13420000000    4.34%     1342  ObjArrayKlass::allocate(int, Thread*)
want to confirm what does ns denotes is it nano seconds or something else. Please confirm

Yes, that's the estimated CPU time in nanoseconds spent in the function.
The key word is estimated, because the exact time cannot be known with a sampling profiler.
In this case the estimation is pretty straightforward: if the sampling interval is 10 ms (the default), and the function receives 1342 samples, then the total time is computed as 1342 * 10 ms = 13.42 s.

Thanks for the immediate response. Appreciate your commitment

authors: apangin sattishv

repo: jvm-profiling-tools/async-profiler

license_source: bigquery


text:
Patch 4

For the moment I only applied changes keeping original functionality, but looking forward, the token analysis also gives us a head start building a more robust way to get e.g. the data providers, maybe combined w/ 3rd party annotation parsing (doctrine/annotations).
Cheers

Can you test [jwage/phpchunkit-demo] against this branch? https://github.com/jwage/phpchunkit-demo

This will fix #9.

:+1:

[wiese@localhost phpchunkit-demo]$ composer.phar info jwage/phpchunkit
name     : jwage/phpchunkit
descrip. : PHPUnit Test Runner
keywords : phpunit, tests
versions : * dev-patch-4
...
[wiese@localhost phpchunkit-demo]$ docker run -v $(pwd):/app -w "/app" --rm php ./vendor/bin/phpchunkit all
PHPUnit 5.5.7 by Sebastian Bergmann and contributors.

.....                                                               5 / 5 (100%)

Time: 71 ms, Memory: 4.00MB

OK (5 tests, 5 assertions)
Total Tests: 8
Number of Chunks Configured: 14
Number of Chunks Produced: 2
Tests Per Chunk: ~1
-----------

Running chunk #1

 1/4 [🌭]  25%
 4/4 [=] 100%
Running chunk #2

 1/4 [🌭]  25%
 4/4 [=] 100%

Time: 0.12 seconds, Memory: 4MB

OK (14 chunks, 8 tests)

Seems to work

:+1: anything else you want to take care of here or are you ready to merge?

No amendments in this matter. If you feel it's good, please do the honours.

source: gharchive/pull-request

authors: jwage wiese

repo: jwage/phpchunkit

license: mit


text:
Generalize where* functions

This PR generalized the where* functions to allow an array or slice of any map or struct type.
This should make it possible to fix https://github.com/jwilder/nginx-proxy/issues/115 since the updated where function can be used like this: {{where (where $container.Addresses "Proto" "tcp") "Port" "80" | len}} to detect the case where there are multiple ports exposed but not port 80.
I also introduced a templateTestList type with a run function to simplify writing tests that actually execute a template and check its output. Let me know if you'd like that split into a separate PR.

Looks like os.Unsetenv is only in Go 1.4+, causing the Travis failure. I've changed it to os.Setenv("DOCKER_HOST","")

Are there blockers for Go 1.4 in docker-gen, or are people importing it in other projects? Perhaps 1.4 isn't a bad thing to use (Docker, for example, very recently dropped 1.3 support)

Good point @thaJeztah.

I don't see any reason to keep 1.3 around.  docker-gen isn't really intended to be used as a library right now so it should not matter if the code is dependent on 1.4 features.

@jwilder I've dropped commit 844fa876c2f65a79ed5e05dfe06f2c256e345b07, so the Travis build now fails again on 1.3.

@md5 I removed 1.3 from travis.  If you rebase, it should pass now.

Rebased. Travis is green :+1:

Thanks @md5!

You're welcome! 👍

authors: jwilder md5 thaJeztah

repo: jwilder/docker-gen


text:
Just updated to latest versions of nginx and docker-gen.

No fundamental changes, only updated versions. Maybe you like to update too?

@wfrank2509 0.5.0 got released around the time this PR was created :)

@wfrank2509 Also see #311 for nginx

Current image uses nginx:1.9.12 and DOCKER_GEN_VERSION 0.7.0, this PR can be closed.

authors: michaellopez sdurrheimer wfrank2509

repo: jwilder/nginx-proxy


text:
C-SPC causes hang

Using origin/master, latest commit is 4fb7801ba3515922e3dbb8b27c1c28ec2efaf22b.
In an emacs buffer, setting a mark (C-@ or C-SPC) causes alacritty to hang. The emacs child process is healthy but doesn't receive any other signals and the screen doesn't update.
Subsequent to the hang, alacritty begins using all of one core.  MacOS "samples" attached of both emacs and alacritty.
Sample of alacritty.txt
Sample of emacs-25.1.txt

I had filed an issue about the cocoa event loop in glutin going to 100% CPU and blocking Alacritty. Need to reopen that on winit.
Does your description reliably reproduce the problem?

Yes, I made sure it was repeatable before I filed the bug.

Can confirm. In nvim, I have a binding on Ctrl+Space to clear hlsearch which also causes Alacritty to hang:
if maparg('<C-Space>', 'n') ==# ''
  nnoremap <silent> <C-Space> :nohlsearch<CR><C-L>
endif

In a new terminal running just bash, invoking C-SPC causes the hang.  No emacs or nvim required. Thanks for the confirmation!

I think this may be related to https://github.com/jwilm/alacritty/issues/264

Duplicate of #99.

authors: eugene jwilm okuuva zoratu

repo: jwilm/alacritty


text:
Update glutin to version 0.20

Fixes https://github.com/jwilm/alacritty/issues/458.
Fixes https://github.com/jwilm/alacritty/issues/1681.

I think cargo.lock needs to be re-updated. The image crate no longer matches what's in Cargo.toml.

@atouchet The lockfile has been updated. We're now actually depending on both image files, one likely being the dependency for a different crate.

authors: atouchet chrisduerr


text:
Fix typo in README

allow_nil_kid option was introduced in #543, but the option name was wrong in README.
This change fixes the typo.

Super, thanks for the quick reaction.

Thank you for reviewing!

authors: anakinj tatsuyafw

repo: jwt/ruby-jwt


text:
Pillow multiple version requirements in Pytorch-1.0?

Torchvision, used here, requires Pillow>=4.1.1.
However, demo.py uses scipy.misc.imread, which relies on Pillow functionality that only appears seemingly if you go as far back as Pillow version 2.
I've been unable to satisfy both requirements at the same time. Is there a workaround? Or maybe this code should be re-written to use cv2 instead of scipy.misc.imread, to avoid the dependency on an old Pillow.

If this is the error that is in minibatch.py, the code is already using cv2.imread. Just remove the deprecated import statement ;)

+1

Hi,
I encountered the similar error with you guys, and I modified the code of "demo.py" and "minibatch.py"(under the directory /faster-rcnn.pytorch/lib/roi_data_layer/).
I replaced "scipy.misc" with "imageio", and this solved my problem.
Hope this will help you too.

@ensenginbaieer feel free to submit a PR

Hi,
I encountered the similar error with you guys, and I modified the code of "demo.py" and "minibatch.py"(under the directory /faster-rcnn.pytorch/lib/roi_data_layer/).
I replaced "scipy.misc" with "imageio" since imread is deprecated in SciPy 1.0.0 and removed in SciPy 1.2.0
This solved my problem. Hope it will help you too.

you can also pip install scipy==1.1.0 and the imread function still is there

authors: CJMenart EMCP ensenginbaieer marcunzueta rparundekar rsl18


text:
🛑 le Zata is down

In 6909f51, le Zata (http://zata.free.fr) was down:

HTTP code: 0
Response time: 0 ms

Resolved: le Zata is back up in 8790831 after 11 minutes.

repo: jyhem/upptime-jyhem


text:
Allow 'inline' keyword in declarations

For now, it should just be a no-op.
static inline void f();
<stdin>:1:8: error: expected variable name or '(', got 'inline'

Steps to get started:

Parse inline as a Qualifier in declaration_specifier
Optionally, give an error for inline int a in declarator
Write some test cases in tests/decl.rs

Current behavior:
$ RUST_BACKTRACE=1 cargo run
    Finished dev [unoptimized] target(s) in 0.54s
     Running `target/debug/rcc`
int main(restrict int *p);
thread 'main' panicked at 'unrecognized declaration specifier restrict', src/parse/decl.rs:1486:25
stack backtrace:
  13: rcc::parse::decl::<impl rcc::parse::Parser<I>>::declaration_specifier::{{closure}}
  14: core::result::Result<T,E>::unwrap_or_else
  15: rcc::parse::decl::<impl rcc::parse::Parser<I>>::declaration_specifier
  16: rcc::parse::decl::<impl rcc::parse::Parser<I>>::declaration_specifiers
  17: rcc::parse::decl::<impl rcc::parse::Parser<I>>::parameter_type_list
  18: rcc::parse::decl::<impl rcc::parse::Parser<I>>::postfix_type
  19: rcc::parse::decl::<impl rcc::parse::Parser<I>>::direct_declarator
  20: rcc::parse::decl::<impl rcc::parse::Parser<I>>::declarator
  21: rcc::parse::decl::<impl rcc::parse::Parser<I>>::declaration
  22: <rcc::parse::Parser<I> as core::iter::traits::iterator::Iterator>::next::{{closure}}
  23: core::option::Option<T>::or_else
  24: <rcc::parse::Parser<I> as core::iter::traits::iterator::Iterator>::next
  25: rcc::compile
  26: rcc::real_main
  27: rcc::main

https://stackoverflow.com/questions/3430315/what-is-the-purpose-of-static-keyword-in-array-parameter-of-function-like-char


text:
Update README

Noticed after publishing that it still says the preprocessor is unimplemented :(

Codecov Report

Merging #297 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master     #297   +/-   ##
=======================================
  Coverage   78.66%   78.66%
=======================================
  Files          25       25
  Lines        6725     6725
=======================================
  Hits         5290     5290
  Misses       1435     1435

Impacted Files
Coverage Δ

src/lex/cpp.rs
80.94% <ø> (ø)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
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text:
Front-End - saving books

[ ]  need to add button for users to save books to their user book listing
[ ] button will save books

done

repo: k-pineda/ShelfSwap


text:
actions: bump node 20.14.0

Applied mkpr on .github/workflows/*.yml
sed s/20.13.1/20.14.0/

Pull Request Test Coverage Report for Build 9273851922
Details

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 100.0%

Totals

Change from base Build 9266655579:
0.0%

Covered Lines:
96

Relevant Lines:
96

💛  - Coveralls


text:
Error in training conformer_ctc2 for librispeech WSASR

Hello.
I want to train a ASR model for Librispeech dataset. I use recipes for training conformer_ctc2 in this link:
https://github.com/k2-fsa/icefall/blob/master/egs/librispeech/WSASR/README.md
After preparation and making error making synthetic errors to the transcript, I use this command for training:
otc_lang_dir=data/lang_bpe_200
otc_token="<star>"
manifest_dir="data/manifests"
sub_er=0.17
ins_er=0.17
del_er=0.17
synthetic_train_manifest="librispeech_cuts_train-clean-100_${sub_er}_${ins_er}_${del_er}.jsonl.gz"
train_manifest="librispeech_cuts_train-clean-100.jsonl.gz"
exp_dir="conformer_ctc2/librispeech_training/exp"
allow_bypass_arc=true
allow_self_loop_arc=true
initial_bypass_weight=-19
initial_self_loop_weight=3.75
bypass_weight_decay=0.975
self_loop_weight_decay=0.999

show_alignment=true

export CUDA_VISIBLE_DEVICES="0"
./conformer_ctc2/train.py \
  --world-size 1 \
  --manifest-dir "${manifest_dir}" \
  --train-manifest "${synthetic_train_manifest}" \
  --exp-dir "${exp_dir}" \
  --lang-dir "${otc_lang_dir}" \
  --otc-token "${otc_token}" \
  --allow-bypass-arc "${allow_bypass_arc}" \
  --allow-self-loop-arc "${allow_self_loop_arc}" \
  --initial-bypass-weight "${initial_bypass_weight}" \
  --initial-self-loop-weight "${initial_self_loop_weight}" \
  --bypass-weight-decay "${bypass_weight_decay}" \
  --self-loop-weight-decay "${self_loop_weight_decay}" \
  --show-alignment "${show_alignment}"

output log:
fatal: not a git repository (or any parent up to mount point /home)
Stopping at filesystem boundary (GIT_DISCOVERY_ACROSS_FILESYSTEM not set).
fatal: not a git repository (or any parent up to mount point /home)
Stopping at filesystem boundary (GIT_DISCOVERY_ACROSS_FILESYSTEM not set).
fatal: not a git repository (or any parent up to mount point /home)
Stopping at filesystem boundary (GIT_DISCOVERY_ACROSS_FILESYSTEM not set).
2024-02-19 18:04:42,665 INFO [train.py:881] Training started
2024-02-19 18:04:42,665 INFO [train.py:882] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 1, 'reset_interval': 200, 'valid_interval': 1600, 'alignment_interval': 25, 'feature_dim': 768, 'subsampling_factor': 2, 'encoder_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'beam_size': 10, 'reduction': 'sum', 'use_double_scores': True, 'model_warm_step': 3000, 'env_info': {'k2-version': '1.24.4', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f6919c0ddb311bea7b53a50f3afdcb3c18b8ccc8', 'k2-git-date': 'Sat Feb 10 09:23:09 2024', 'lhotse-version': '1.21.0', 'torch-version': '2.1.0+cu121', 'torch-cuda-available': True, 'torch-cuda-version': '12.1', 'python-version': '3.8', 'icefall-git-branch': None, 'icefall-git-sha1': None, 'icefall-git-date': None, 'icefall-path': '/home/reza.khodadadi/icefall', 'k2-path': '/usr/local/lib/python3.8/dist-packages/k2/__init__.py', 'lhotse-path': '/usr/local/lib/python3.8/dist-packages/lhotse/__init__.py', 'hostname': '038a368561ec', 'IP address': '172.17.0.3'}, 'world_size': 1, 'master_port': 12354, 'tensorboard': True, 'num_epochs': 20, 'start_epoch': 1, 'start_batch': 0, 'exp_dir': PosixPath('conformer_ctc2/librispeech_training/exp'), 'lang_dir': 'data/lang_bpe_200', 'initial_lr': 0.003, 'lr_batches': 5000, 'lr_epochs': 6, 'att_rate': 0.0, 'num_decoder_layers': 0, 'seed': 42, 'print_diagnostics': False, 'save_every_n': 8000, 'keep_last_k': 10, 'average_period': 100, 'use_fp16': False, 'otc_token': '▁<star>', 'allow_bypass_arc': True, 'allow_self_loop_arc': True, 'initial_bypass_weight': -19.0, 'initial_self_loop_weight': 3.75, 'bypass_weight_decay': 0.975, 'self_loop_weight_decay': 0.999, 'show_alignment': True, 'full_libri': False, 'mini_libri': False, 'manifest_dir': PosixPath('data/manifests'), 'max_duration': 200.0, 'bucketing_sampler': True, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'input_strategy': 'PrecomputedFeatures', 'train_manifest': 'librispeech_cuts_train-clean-100_0.17_0.17_0.17.jsonl.gz'}
2024-02-19 18:04:42,825 INFO [train.py:908] About to create model
Conformer(
  (encoder_embed): Conv2dSubsampling2(
    (conv): Sequential(
      (0): ScaledConv2d(1, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
      (1): ActivationBalancer()
      (2): DoubleSwish()
      (3): ScaledConv2d(8, 32, kernel_size=(3, 3), stride=(2, 2))
      (4): ActivationBalancer()
      (5): DoubleSwish()
      (6): ScaledConv2d(32, 128, kernel_size=(3, 3), stride=(1, 1))
      (7): ActivationBalancer()
      (8): DoubleSwish()
    )
    (out): ScaledLinear(in_features=48768, out_features=512, bias=True)
    (out_norm): BasicNorm()
    (out_balancer): ActivationBalancer()
  )
  (encoder_pos): RelPositionalEncoding(
    (dropout): Dropout(p=0.2, inplace=False)
  )
  (encoder): ConformerEncoder(
    (layers): ModuleList(
      (0-11): 12 x ConformerEncoderLayer(
        (self_attn): RelPositionMultiheadAttention(
          (in_proj): ScaledLinear(in_features=512, out_features=1536, bias=True)
          (out_proj): ScaledLinear(in_features=512, out_features=512, bias=True)
          (linear_pos): ScaledLinear(in_features=512, out_features=512, bias=False)
        )
        (feed_forward): Sequential(
          (0): ScaledLinear(in_features=512, out_features=2048, bias=True)
          (1): ActivationBalancer()
          (2): DoubleSwish()
          (3): Dropout(p=0.2, inplace=False)
          (4): ScaledLinear(in_features=2048, out_features=512, bias=True)
        )
        (feed_forward_macaron): Sequential(
          (0): ScaledLinear(in_features=512, out_features=2048, bias=True)
          (1): ActivationBalancer()
          (2): DoubleSwish()
          (3): Dropout(p=0.2, inplace=False)
          (4): ScaledLinear(in_features=2048, out_features=512, bias=True)
        )
        (conv_module): ConvolutionModule(
          (pointwise_conv1): ScaledConv1d(512, 1024, kernel_size=(1,), stride=(1,))
          (deriv_balancer1): ActivationBalancer()
          (depthwise_conv): ScaledConv1d(512, 512, kernel_size=(31,), stride=(1,), padding=(15,), groups=512)
          (deriv_balancer2): ActivationBalancer()
          (activation): DoubleSwish()
          (pointwise_conv2): ScaledConv1d(512, 512, kernel_size=(1,), stride=(1,))
        )
        (norm_final): BasicNorm()
        (balancer): ActivationBalancer()
        (dropout): Dropout(p=0.2, inplace=False)
      )
    )
  )
  (encoder_output_layer): Sequential(
    (0): Dropout(p=0.2, inplace=False)
    (1): ScaledLinear(in_features=512, out_features=200, bias=True)
  )
)
2024-02-19 18:04:43,798 INFO [train.py:922] Number of model parameters: 100922826
2024-02-19 18:04:44,793 INFO [asr_datamodule.py:323] About to get train-clean-100 cuts
2024-02-19 18:04:44,801 INFO [asr_datamodule.py:216] About to create train dataset
2024-02-19 18:04:44,801 INFO [asr_datamodule.py:224] Using DynamicBucketingSampler.
2024-02-19 18:04:45,264 INFO [asr_datamodule.py:239] About to create train dataloader
2024-02-19 18:04:45,265 INFO [asr_datamodule.py:345] About to get dev-clean cuts
2024-02-19 18:04:45,266 INFO [asr_datamodule.py:270] About to create dev dataset
2024-02-19 18:04:45,369 INFO [asr_datamodule.py:283] About to create dev dataloader
Traceback (most recent call last):
  File "./conformer_ctc2/train.py", line 1115, in <module>
    main()
  File "./conformer_ctc2/train.py", line 1108, in main
    run(rank=0, world_size=1, args=args)
  File "./conformer_ctc2/train.py", line 1015, in run
    train_one_epoch(
  File "./conformer_ctc2/train.py", line 753, in train_one_epoch
    loss, loss_info = compute_loss(
  File "./conformer_ctc2/train.py", line 563, in compute_loss
    nnet_output, encoder_memory, memory_mask = model(
  File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/reza.khodadadi/icefall/egs/librispeech/WSASR/conformer_ctc2/transformer.py", line 174, in forward
    encoder_memory, memory_key_padding_mask = self.run_encoder(
  File "/home/reza.khodadadi/icefall/egs/librispeech/WSASR/conformer_ctc2/conformer.py", line 135, in run_encoder
    x = self.encoder_embed(x)
  File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/reza.khodadadi/icefall/egs/librispeech/WSASR/conformer_ctc2/subsampling.py", line 181, in forward
    x = self.out(x.transpose(1, 2).contiguous().view(b, t, c * f))
  File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/reza.khodadadi/icefall/egs/librispeech/WSASR/conformer_ctc2/scaling.py", line 301, in forward
    return torch.nn.functional.linear(input, self.get_weight(), self.get_bias())
RuntimeError: mat1 and mat2 shapes cannot be multiplied (9612x4736 and 48768x512)

My container specifications:
python 3.8
torch==2.1.0+cu121
torchaudio==2.1.0+cu121
k2 version: 1.24.4
lhotse==1.21.0
icefall: clone from git(master branch) and install requierments

Thanks.

@DongjiGao
Could you have a look at this issue?

@csukuangfj
@DongjiGao
I appreciate your attention, could you please consider my issue?

Problem solved by this pull request

Sorry for the slow response. The notification email was incorrectly tagged as trash and stored away.
Yes, the problem is due to the different dimensions of acoustic features (I just set it to be 768). Thanks for the PR!

authors: DongjiGao Rezakh20 csukuangfj


text:
Getting error in prepare (compute fbank) stage.

RuntimeError: setStorage: sizes [1, 1, 400], strides [366, 160, 1], storage offset 0, and itemsize 4 requiring a storage size of 1600 are out of bounds for storage of size 1464

You should figure out how to paste as text, and include more output, including any backtrace.

concurrent.futures.process._RemoteTraceback:
"""
Traceback (most recent call last):
File "/usr/lib/python3.9/concurrent/futures/process.py", line 246, in _process_worker
r = call_item.fn(*call_item.args, **call_item.kwargs)
File "/workspace/lhotse/lhotse/cut/set.py", line 2057, in compute_and_store_features
return CutSet.from_cuts(
File "/workspace/lhotse/lhotse/cut/set.py", line 305, in from_cuts
return CutSet(cuts=index_by_id_and_check(cuts))
File "/workspace/lhotse/lhotse/utils.py", line 681, in index_by_id_and_check
for m in manifests:
File "/workspace/lhotse/lhotse/cut/set.py", line 2057, in
return CutSet.from_cuts(
File "/workspace/lhotse/lhotse/cut/set.py", line 2060, in
null_result_on_audio_loading_error(
File "/workspace/lhotse/lhotse/audio.py", line 2524, in wrapper
return func(*args, **kwargs)
File "/workspace/lhotse/lhotse/cut/data.py", line 467, in compute_and_store_features
features_info = extractor.extract_from_samples_and_store(
File "/workspace/lhotse/lhotse/features/base.py", line 245, in extract_from_samples_and_store
feats = self.extract(samples=samples, sampling_rate=sampling_rate)
File "/workspace/lhotse/lhotse/features/kaldi/extractors.py", line 109, in extract
feats = self.extractor(samples.to(self.device))[0]
File "/usr/local/lib/python3.9/dist-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/workspace/lhotse/lhotse/features/kaldi/layers.py", line 323, in forward
x_strided, log_e = self.wav2win(x)
File "/usr/local/lib/python3.9/dist-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/workspace/lhotse/lhotse/features/kaldi/layers.py", line 195, in forward
x_strided = _get_strided_batch(x, self._length, self._shift, self.snip_edges)
File "/workspace/lhotse/lhotse/features/kaldi/layers.py", line 788, in _get_strided_batch
return waveform.as_strided(sizes, strides)
RuntimeError: setStorage: sizes [1, 1, 400], strides [366, 160, 1], storage offset 0, and itemsize 4 requiring a storage size of 1600 are out of bounds for storage of size 1464
"""
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/builds/mihup/asr/zipformer/icefall/egs/librispeech/ASR/./local/compute_fbank_mihup.py", line 174, in
compute_fbank_mihup(
File "/builds/mihup/asr/zipformer/icefall/egs/librispeech/ASR/./local/compute_fbank_mihup.py", line 157, in compute_fbank_mihup
cut_set = cut_set.compute_and_store_features(
File "/workspace/lhotse/lhotse/cut/set.py", line 2125, in compute_and_store_features
cuts_with_feats = combine(progress(f.result() for f in futures))
File "/workspace/lhotse/lhotse/manipulation.py", line 30, in combine
return reduce(add, manifests)
File "/usr/local/lib/python3.9/dist-packages/tqdm/std.py", line 1182, in iter
for obj in iterable:
File "/workspace/lhotse/lhotse/cut/set.py", line 2125, in
cuts_with_feats = combine(progress(f.result() for f in futures))
File "/usr/lib/python3.9/concurrent/futures/_base.py", line 439, in result
return self.__get_result()
File "/usr/lib/pytho
n3.9/concurrent/futures/_base.py", line 391, in __get_result
raise self._exception
RuntimeError: setStorage: sizes [1, 1, 400], strides [366, 160, 1], storage offset 0, and itemsize 4 requiring a storage size of 1600 are out of bounds for storage of size 1464

Which feature extractor are you using?
Do you think it fixes the issue when switching to another extractor?
File "/workspace/lhotse/lhotse/features/kaldi/layers.py", line 788, in _get_strided_batch
return waveform.as_strided(sizes, strides)

Could you place a breakpoint at line 788 and show the following output:
print(waveform.shape)
print(waveform.is_contiguous())
print(sizes)
print(strides)

@csukuangfj thanks for the solution.

authors: csukuangfj danpovey sanjuktasr


text:
Can't  understand some output has oov?

Hi,
I see my output of decode has some case like this:
ground truth transcript: "mở bài hát florentino" . The word: "florentino" is the word not in vietnamese (we call it's rareword, or something like foreign word). And we have cover this word in lexicon: "florentino": "phờ lo ren ti nô" (spell in vietnamese).
And output of my model (conformer + transducer stateless) decode with LG is:
"mở bài hát phờ lo ren ti nô".
You can see, the spell: "'phờ lo ren ti nô" has covered by lexicon, and in Language model also have this sent in training. But Decode with LG can't group spell to my ground truth. In some another case, I try to increase weighted LM, and it's can be group but some case still not. I'm not sure why it's not word as it should be. I am thinking about the silent weight or threshold or something like this need tuning for spell can group.
Can give me some idea  for tuning?
Tks

What modeling units are you using?

What modeling units are you using?

Hi, I work with him. Do you mean what type of token we use?

What modeling units are you using?

Hi, I work with him. Do you mean what type of token we use?

Yes, BPE, phonemes, or something else?

We use phonemes.
It is weird that, for example, "phờ lo ren ti nô" and "florentino" have the same phonemes in our lexicon, and our LM designs that "florentino" has higher LM score than "phờ lo ren ti nô", which is completely meaningless, but the decoding stills choose "phờ lo ren ti nô".

authors: csukuangfj ncakhoa trangtv57


text:
How to create LM for nemo offlne model

How to create LM to use for Nemo offline model in nodejs or python version and how to create those HCG graphs for nemo model.

There is nothing special for NeMo models.
All models trained by the CTC loss, including but not limited to those from NeMo and icefall and other frameworks, can follow what we have done in icefall to build HLG.fst.
Please see
https://github.com/k2-fsa/icefall/blob/master/egs/librispeech/ASR/prepare_lm.sh#L97
    if [ ! -f $lang_dir/HL.fst ]; then
      ./local/prepare_lang_fst.py  \
        --lang-dir $lang_dir \
        --ngram-G ./data/lm/G_3_gram.fst.txt
    fi

You need to prepare

tokens.txt
lexicon.txt
words.txt
an n-gram arpa file

tokens.txt is already contained in the NeMo model, I think. You can reuse words.txt and the 3-gram arpa file from librispeech if you want.

authors: csukuangfj rohithkodali


text:
[Release-1.25] - no nodes have reconciled ETCDSnapshotFile resources, requeuing error on clusters with no etcd snapshots

Backport fix for no nodes have reconciled ETCDSnapshotFile resources, requeuing error on clusters with no etcd snapshots

#8665

Validated with RC version 1.25.15-rc1+k3s1, Replicated on release-1.25 commit b02a874d
Environment Details

Infrastructure

[x] Cloud
[ ] Hosted

Node(s) CPU architecture, OS, and Version:

Ubuntu 22.04.2 LTS (GNU/Linux 5.15.0-1031-aws x86_64)

Cluster Configuration:

Split servers: 1 etcd only, 1 cp only, 1 agent

Config.yaml:

# server1                                    |# server2                                               | # agent1                             |
---------------------------------------------|--------------------------------------------------------|--------------------------------------|
write-kubeconfig-mode: 644                   | write-kubeconfig-mode: 644                             | server: "https://<etcdonly-ip>:6443" |
cluster-init: true                           | token: <TOKEN>                                         | token: <TOKEN>                       |
token: <TOKEN>                               | node-external-ip: "<cponly-ip>"                        | node-external-ip: "<agent-ip>"       |
node-external-ip: "<etcdonly-ip>"            | node-name: cponly                                      | node-name: agent                     |
node-name: etcdonly                          | server: "https://<etcdonly-ip>6443"                    |
disable-apiserver: true                      | disable-etcd: true                                     |
disable-controller-manager: true             | node-taint:                                            |
disable-scheduler: true                      |   - node-role.kubernetes.io/control-plane:NoSchedule   |
node-taint:                                  |
  - node-role.kubernetes.io/etcd:NoExecute   |

Testing Steps

Copy config.yaml

$ sudo mkdir -p /etc/rancher/k3s && sudo cp config.yaml /etc/rancher/k3s

Install k3s
Check cp-only server log does not have the error

level=error msg="error syncing '_reconcile_': handler managed-etcd-snapshots-controller: no nodes have reconciled ETCDSnapshotFile resources, requeuing"

Ensure the cluster is up and running

Replication Results:

k3s version used for replication:

k3s version v1.25.14+k3s-b02a874d (b02a874d)
go version go1.20.8

Observed the error in cp-only server log

$ sudo journalctl -u k3s | grep 'ETCDSnapshotFile'
Oct 24 00:37:14 ip-xxx-xx-xx-11 k3s[18291]: time="2023-10-24T00:37:14Z" level=info msg="Starting k3s.cattle.io/v1, Kind=ETCDSnapshotFile controller"
Oct 24 00:37:15 ip-xxx-xx-xx-11 k3s[18291]: time="2023-10-24T00:37:15Z" level=error msg="error syncing '_reconcile_': handler managed-etcd-snapshots-controller: no nodes have reconciled ETCDSnapshotFile resources, requeuing"
...

Cluster does not come up properly

Validation Results:

k3s version used for validation:

k3s version v1.25.15-rc1+k3s1 (d2b3219c)
go version go1.20.10

Observed that the error msg is NOT visible

Oct 24 00:48:31 ip-xxx-xx-xx-11 k3s[20113]: time="2023-10-24T00:48:31Z" level=info msg="Starting k3s.cattle.io/v1, Kind=ETCDSnapshotFile controller"
ubuntu@ip-xxx-xx-xx-11:~$

Cluster is up and running

$ kubectl get nodes,pods -A -o wide
NAME            STATUS   ROLES                  AGE     VERSION             INTERNAL-IP     EXTERNAL-IP    OS-IMAGE             KERNEL-VERSION    CONTAINER-RUNTIME
node/agent      Ready    <none>                 6m26s   v1.25.15-rc1+k3s1   xxx.xx.24.224   x.xx.xxx.147   Ubuntu 22.04.2 LTS   5.15.0-1031-aws   containerd://1.7.7-k3s1
node/cponly     Ready    control-plane,master   6m38s   v1.25.15-rc1+k3s1   xxx.xx.21.11    x.xxx.xx.128   Ubuntu 22.04.2 LTS   5.15.0-1031-aws   containerd://1.7.7-k3s1
node/etcdonly   Ready    etcd                   6m42s   v1.25.15-rc1+k3s1   xxx.xx.24.146   x.xx.xxx.77    Ubuntu 22.04.2 LTS   5.15.0-1031-aws   containerd://1.7.7-k3s1

NAMESPACE     NAME                                          READY   STATUS      RESTARTS   AGE     IP          NODE     NOMINATED NODE   READINESS GATES
kube-system   pod/coredns-8b9777675-lptbq                   1/1     Running     0          6m30s   xx.xx.1.3   cponly   <none>           <none>
kube-system   pod/helm-install-traefik-bkdrs                0/1     Completed   1          6m30s   xx.xx.2.2   agent    <none>           <none>
kube-system   pod/helm-install-traefik-crd-t4bsb            0/1     Completed   0          6m30s   xx.xx.2.3   agent    <none>           <none>
kube-system   pod/local-path-provisioner-69dff9496c-wwkvx   1/1     Running     0          6m30s   xx.xx.1.2   cponly   <none>           <none>
kube-system   pod/metrics-server-854c559bd-v7rfz            1/1     Running     0          6m30s   xx.xx.1.4   cponly   <none>           <none>
kube-system   pod/svclb-traefik-919d2cc3-287gk              2/2     Running     0          6m12s   xx.xx.2.4   agent    <none>           <none>
kube-system   pod/svclb-traefik-919d2cc3-9m54g              2/2     Running     0          6m12s   xx.xx.1.5   cponly   <none>           <none>
kube-system   pod/traefik-7c48d7b8b4-cdlbn                  1/1     Running     0          6m12s   xx.xx.2.5   agent    <none>           <none>

NOTE: The issue was not observed on all roles cluster setup

authors: brandond mdrahman-suse


text:
Kubectl in rancher/k3s Docker image doesn't work

Environmental Info:
K3s Version:
$ docker run --rm rancher/k3s@sha256:5f7b660e6f2a6dd712350a8f1fd5ad6beafd62a06df5e2f46e432e6f151652fc -v
k3s version v1.25.14+k3s1 (3624e6c4)
go version go1.20.8

Node(s) CPU architecture, OS, and Version:
$ uname -a
Linux angus-laptop 6.5.7-arch1-1 #1 SMP PREEMPT_DYNAMIC Tue, 10 Oct 2023 21:10:21 +0000 x86_64 GNU/Linux

Cluster Configuration: N/A
Describe the bug:
When I try to run kubectl as the command of the rancher/k3s docker image, I get this error message:
$ docker run --rm rancher/k3s@sha256:5f7b660e6f2a6dd712350a8f1fd5ad6beafd62a06df5e2f46e432e6f151652fc kubectl
error: unknown command "kubectl" for "kubectl"

Steps To Reproduce:
See above.
Expected behavior:
It should run kubectl. With no further arguments it should output something like this:
$ docker run --rm rancher/k3s@sha256:5f7b660e6f2a6dd712350a8f1fd5ad6beafd62a06df5e2f46e432e6f151652fc kubectl
kubectl controls the Kubernetes cluster manager.

 Find more information at: https://kubernetes.io/docs/reference/kubectl/

Basic Commands (Beginner):
  create          Create a resource from a file or from stdin
  expose          Take a replication controller, service, deployment or pod and expose it as a new Kubernetes service
[etc]

Actual behavior:
See above.
Additional context / logs:
As a workaround, setting entrypoint works, i.e.
docker run --rm --entrypoint /bin/kubectl rancher/k3s@sha256:5f7b660e6f2a6dd712350a8f1fd5ad6beafd62a06df5e2f46e432e6f151652fc

Did this work previously? If so, I'm curious when it broke. The main k3s binary for the docker image is different than the k3s artifact in GitHub, it does not have the same self-extracting behavior but the multi-call binary behavior should work when executed properly.

Yeah I don't think this ever worked. As far as I look back its always done the same:
brandond@dev01:~$ docker run --rm -it rancher/k3s:v1.19.15-k3s1 kubectl --help
Error: unknown command "kubectl" for "kubectl"
Run 'kubectl --help' for usage.
unknown command "kubectl" for "kubectl"

authors: amcinnes brandond


text:
Handling error code for defer functions

related to #124
because of the metrics we have to run the deferred function even if an error occurred during main processing. Until now, we used to call os.Exit(1) in main if any error occurred. Unfortunately, os.exit skips the deferred function call.
The solution is implementation. In case of an error we call return instead of os.Exit, and os.Exit itself is a deferred function.

@ytsarev , thx. Yes it's inherited from generated code which doesn't contain any deferred functions. But yes, we can try to push upstream as template.


text:
[common] version 2.2.0

Description of the change

Bump common to v2.2.0

Applicable issues

fixes #436

Checklist

[x] Chart version bumped in Chart.yaml according to semver.
[x] Title of the PR starts with chart name (e.g. [home-assistant])
[x] Chart is using our common library as a dependency.
[ ] (optional) Variables are documented in the README.md

I'll update the changelog later and then mark it ready for review

I'll update the changelog later and then mark it ready for review

I'm wondering if we should set service.targetPort as the default value for port name in the container, that could also help with #458

I'm wondering if we should set service.targetPort as the default value for port name in the container, that could also help with #458


text:
operator netobserv-operator (0.2.1)

Signed-off-by: Joel Takvorian jtakvori@redhat.com
Thanks submitting your Operator. Please check below list before you create your Pull Request.
New Submissions

[ ] Are you familiar with our contribution guidelines?
[ ] Have you packaged and deployed your Operator for Operator Framework?
[ ] Have you tested your Operator with all Custom Resource Definitions?
[ ] Have you tested your Operator in all supported installation modes?
[ ] Have you considered whether you want use semantic versioning order?
[ ] Is your submission signed?
[ ] Is operator icon set?

Updates to existing Operators

[ ] Did you create a ci.yaml file according to the update instructions?
[ ] Is your new CSV pointing to the previous version with the replaces property if you chose replaces-mode via the updateGraph property in ci.yaml?
[ ] Is your new CSV referenced in the appropriate channel defined in the package.yaml or annotations.yaml ?
[ ] Have you tested an update to your Operator when deployed via OLM?
[ ] Is your submission signed?

Your submission should not

[ ] Modify more than one operator
[ ] Modify an Operator you don't own
[ ] Rename an operator - please remove and add with a different name instead
[ ] Modify any files outside the above mentioned folders
[ ] Contain more than one commit. Please squash your commits.

Operator Description must contain (in order)

[ ] Description about the managed Application and where to find more information
[ ] Features and capabilities of your Operator and how to use it
[ ] Any manual steps about potential pre-requisites for using your Operator

Operator Metadata should contain

[ ] Human readable name and 1-liner description about your Operator
[ ] Valid category name1
[ ] One of the pre-defined capability levels2
[ ] Links to the maintainer, source code and documentation
[ ] Example templates for all Custom Resource Definitions intended to be used
[ ] A quadratic logo

Remember that you can preview your CSV here.
--
1 If you feel your Operator does not fit any of the pre-defined categories, file an issue against this repo and explain your need
2 For more information see here

/merge possible

/merge possible

authors: framework-automation jotak


text:
operator [CI] susql-operator (0.0.2)

Thanks submitting your Operator. Please check below list before you create your Pull Request.
New Submissions

[ ] Are you familiar with our contribution guidelines?
[ ] Have you packaged and deployed your Operator for Operator Framework?
[ ] Have you tested your Operator with all Custom Resource Definitions?
[ ] Have you tested your Operator in all supported installation modes?
[ ] Have you considered whether you want use semantic versioning order?
[ ] Is your submission signed?
[ ] Is operator icon set?

Updates to existing Operators

[x] Did you create a ci.yaml file according to the update instructions?
[ ] Is your new CSV pointing to the previous version with the replaces property if you chose replaces-mode via the updateGraph property in ci.yaml?
[x] Is your new CSV referenced in the appropriate channel defined in the package.yaml or annotations.yaml ?
[x] Have you tested an update to your Operator when deployed via OLM?
[x] Is your submission signed?

Your submission should not

[x] Modify more than one operator
[x] Modify an Operator you don't own
[x] Rename an operator - please remove and add with a different name instead
[x] Modify any files outside the above mentioned folders
[x] Contain more than one commit. Please squash your commits.

Operator Description must contain (in order)

[x] Description about the managed Application and where to find more information
[x] Features and capabilities of your Operator and how to use it
[x] Any manual steps about potential pre-requisites for using your Operator

Operator Metadata should contain

[x] Human readable name and 1-liner description about your Operator
[x] Valid category name1
[x] One of the pre-defined capability levels2
[x] Links to the maintainer, source code and documentation
[x] Example templates for all Custom Resource Definitions intended to be used
[x] A quadratic logo

Remember that you can preview your CSV here.
--
1 If you feel your Operator does not fit any of the pre-defined categories, file an issue against this repo and explain your need
2 For more information see here

/merge possible

/merge possible

/merge possible

/merge possible

/merge possible

/merge possible

/merge possible

/merge possible

authors: framework-automation mamy-CS


text:
operators aqua (6.2.0)

Signed-off-by: J0zi jbreza@redhat.com

ignore this, just a final test. Thanks for understanding

/merge possible


text:
MedusaBackup may have status.finishTime set to "1970-01-01T00:00:00Z" while backup is in progress

What happened?
A MedusaBackup CR may have the field status.finishedTime set to  "1970-01-01T00:00:00Z"  while the backup is still in progress.

According to https://docs.k8ssandra.io/tasks/backup-restore/#checking-backup-completion , a backup is considered completed when status.finishedTime is set.
Did you expect to see something different?
I expected the field status.finishedTime to not be set while backup is in progress, as stated by documentation.
How to reproduce it (as minimally and precisely as possible):

Deploy k8ssandra cluster
Create a MedusaBackupJob
Create a MedusaTask in sync mode while the backup job is in pogress

If the backup sync is completed before the backup job is completed, the issue will happen.
Environment

K8ssandra Operator version:
1.14

Kubernetes version information:
1.27 and 1.29

Kubernetes cluster kind:
EKS, AKS and GKE

K8ssandra Operator Logs:

insert K8ssandra Operator logs relevant to the issue here

Anything else we need to know?:
I'm pretty sure the issue is caused by this line
https://github.com/k8ssandra/k8ssandra-operator/blob/main/controllers/medusa/medusatask_controller.go#L328
It will set finishTime to the zero unix timestamp (1970-01-01)
however, the zero metav1.Time timestamp is not 1970-01-01 but 0001-01-01 (January 1, year 1, 00:00:00 UTC)

Manifests:

apiVersion: v1
items:
- apiVersion: medusa.k8ssandra.io/v1alpha1
  kind: MedusaBackup
  metadata:
    creationTimestamp: "2024-04-26T17:00:04Z"
    generation: 1
    name: k8scass-cs-001-k8scass-001-k9sbq
    namespace: eksdoucy
    resourceVersion: "5686257"
    uid: b793f159-5cf0-48b9-9dd5-23f63e49e93f
  spec:
    backupType: differential
    cassandraDatacenter: k8scass-001
  status:
    finishTime: "1970-01-01T00:00:00Z"
    finishedNodes: 1
    nodes:
    - datacenter: k8scass-001
      host: k8scass-cs-001-k8scass-001-default-sts-1
      rack: default
      tokens:
      - -2589360646730023400
      - -3653701636503086600
      - -4912122227646739000
      - -7033817127648975000
      - -769356345750076800
      - -8091193644577933000
      - 1107707983762909200
      - 2276662906941923600
      - 3325786707271115000
      - 4261699880062630000
      - 4677337539634270000
      - 5889017886306251000
      - 6286340738654964000
      - 7544761454600407000
      - 8579062101275812000
      - 9005348602556940000
    - datacenter: k8scass-001
      host: k8scass-cs-001-k8scass-001-default-sts-0
      rack: default
      tokens:
      - -1364658714710476000
      - -2182330647322826800
      - -288902833484896500
      - -3200182052065254000
      - -4271682668405287000
      - -5711950898307870000
      - -6556327545799032000
      - -7647624656491244000
      - -8743666556726182000
      - 1526385666673598700
      - 2769905672354191000
      - 3737269915432726000
      - 447012859225997100
      - 5327274467946625000
      - 6946297763643668000
      - 7924443216159782000
    - datacenter: k8scass-001
      host: k8scass-cs-001-k8scass-001-default-sts-2
      rack: default
      tokens:
      - -1689492637652962000
      - -2827619177042857000
      - -3889971576713209000
      - -4552103083015450000
      - -5216611785192708000
      - -6043458241930822000
      - -7285896556610953000
      - -8343453241301002000
      - -9010383990221943000
      - 142423091302120580
      - 1973957006571479000
      - 5045680731261046000
      - 6678161695265310000
      - 7311145518738443000
      - 8289036375131932000
      - 856718555699781500
    startTime: "2024-04-26T16:59:13Z"
    status: IN_PROGRESS
    totalNodes: 3
kind: List
metadata:
  resourceVersion: ""

apiVersion: v1
items:
- apiVersion: medusa.k8ssandra.io/v1alpha1
  kind: MedusaRestoreJob
  metadata:
    creationTimestamp: "2024-04-26T17:10:41Z"
    generateName: k8scass-cs-001-k8scass-001-k9sbq-
    generation: 1
    labels:
      app: c3aiops
      ops.c3.ai/parent-resource: eksdoucy-c3cassandrarestore-k8scass-cs-001-6pr92
      role: c3aiops-C3CassandraRestore
    name: k8scass-cs-001-k8scass-001-k9sbq-rh4hx
    namespace: eksdoucy
    ownerReferences:
    - apiVersion: cassandra.datastax.com/v1beta1
      blockOwnerDeletion: true
      controller: true
      kind: CassandraDatacenter
      name: k8scass-001
      uid: 2ad0341f-cb57-425e-9a3f-533a31a83152
    resourceVersion: "5691659"
    uid: 596f85ce-01da-464a-a666-482f330090ae
  spec:
    backup: k8scass-cs-001-k8scass-001-k9sbq
    cassandraDatacenter: k8scass-001
  status:
    finishTime: "2024-04-26T17:10:56Z"
    message: target backup has not completed successfully
    restoreKey: 6dca1918-1fdf-47dd-86b1-3f29f0b14c9b
    restoreMapping: {}
    startTime: "2024-04-26T17:10:56Z"
kind: List
metadata:
  resourceVersion: ""

Here are some logs to help debug the issue.
In the k8ssandra-operator logs, it says that the still "IN_PROGRESS" (but with finished time set to 1970-01-01T00:00:00Z ) MedusaBackupJob is blocking the next backup schedule:
2024-05-02T07:46:58.393Z	DEBUG	Postponing backup schedule due to existing active backups	{"controller": "medusabackupschedule", "controllerGroup": "medusa.k8ssandra.io", "controllerKind": "MedusaBackupSchedule", "MedusaBackupSchedule": {"name":"medusa-backup-schedule-dc1","namespace":"cassandra"}, "namespace": "cassandra", "name": "medusa-backup-schedule-dc1", "reconcileID": "7e23a08a-864f-40dd-bb88-47195370663e", "medusabackupscheduler": "cassandra/medusa-backup-schedule-dc1", "MedusaBackupSchedule": {"namespace": "cassandra", "name": "medusa-backup-schedule-dc1"}}

In my case there is only one node which did not finished the backup, and here are the logs of the medusa container which are repeating:
[2024-05-02 07:58:46,167] INFO: Using service file: /etc/medusa-secrets/credentials
[2024-05-02 07:58:46,167] DEBUG: Connecting to Google Storage
[2024-05-02 07:58:46,168] DEBUG: Blob main-cluster/main-cluster-dc1-rack1-sts-2/medusa-backup-schedule-dc1-1712368800/meta/schema.cql was not found in cache.
[2024-05-02 07:58:46,168] DEBUG: [Storage] Getting object main-cluster/main-cluster-dc1-rack1-sts-2/medusa-backup-schedule-dc1-1712368800/meta/schema.cql
[2024-05-02 07:58:46,325] DEBUG: Blob main-cluster/main-cluster-dc1-rack1-sts-2/medusa-backup-schedule-dc1-1712368800/meta/schema.cql last modification time is 2024-04-06 02:00:16.517000
[2024-05-02 07:58:46,326] DEBUG: Blob main-cluster/main-cluster-dc1-rack1-sts-2/medusa-backup-schedule-dc1-1712368800/meta/manifest.json was not found in cache.
[2024-05-02 07:58:46,326] DEBUG: [Storage] Getting object main-cluster/main-cluster-dc1-rack1-sts-2/medusa-backup-schedule-dc1-1712368800/meta/manifest.json
[2024-05-02 07:58:46,348] DEBUG: No manifest blob for backup medusa-backup-schedule-dc1-1712368800 of fqdn main-cluster-dc1-rack1-sts-2
[2024-05-02 07:58:46,348] DEBUG: Registered backup name medusa-backup-schedule-dc1-1712368800 found existing, replacing with new
[2024-05-02 07:58:46,348] DEBUG: Cancelling backup` id: medusa-backup-schedule-dc1-1712368800
[2024-05-02 07:58:46,348] INFO: Registered backup id medusa-backup-schedule-dc1-1712368800
[2024-05-02 07:58:46,348] DEBUG: Blob main-cluster/main-cluster-dc1-rack1-sts-2/medusa-backup-schedule-dc1-1712368800/meta/manifest.json was not found in cache.
[2024-05-02 07:58:46,349] DEBUG: [Storage] Getting object main-cluster/main-cluster-dc1-rack1-sts-2/medusa-backup-schedule-dc1-1712368800/meta/manifest.json
[2024-05-02 07:58:46,372] DEBUG: No manifest blob for backup medusa-backup-schedule-dc1-1712368800 of fqdn main-cluster-dc1-rack1-sts-2
[2024-05-02 07:58:46,373] DEBUG: Updated from existing status: -1 to new status: 0 for backup id: medusa-backup-schedule-dc1-1712368800
[2024-05-02 07:58:46,373] DEBUG: Disconnecting from Google Storage

@rzvoncek, did we change something recently that would set the finishTime where it wasn't the case before?

For information, deleting the MedusaBackupJob stucked with IN_PROGRESS status triggers a new MedusaBackupJob from the MedusaBackupSchedule.

Hi. I tried to reproduce this, but I could not.
On a fresh deployment, I tried starting the sync task always after creating the MedusaBackupJob, but sometimes before that started (got the start timestamp) and sometimes after. I did this on the current main, and 1.14 k8ssandra operator.
What I saw, in both cases, was that doing the sync before the start timestamp appeared broke the eventual MedusaBackup, which did not correctly show file count and size.
It might be that I'd need a MedusaBackupJob stuck in IN_PROGRESS, which currently happens a lot because of a bug we fixed here. I think I'll go ahead and try to reproduce this as well.

I've got the same issue on 6 node cluster. trying to fix it by cleaning all medusa tasks, backup jobs and schedules, snapshots etc. no luck atm

Hi folks, the only place where this could happen in the code is here.
If we have a 0 value for the finishTime, it's going to convert to 1970-01-01T00:00:00Z.
Nonetheless, this means the sync is running concurrently with a backup which isn't finished yet, and creating that MedusaBackup object.
It's most probable that the sync should only locally persist completed backups, since there's nothing to do anyway with incomplete ones.
I'll prepare a PR for this, so that if we don't have a finish time we don't sync the MedusaBackup object.

authors: Pylypp adejanovski c3-clement mlallaouret rzvoncek


text:
Helm chart: Adding cleanup.enabled and cleanup.imagePullSecrets

Summary
This PR introduces two new settings to the k8up helm chart:

cleanup.enabled:  Allows users to enable/disable the cleanup of leftover role bindings and roles from older K8up versions.
cleanup.imagePullSecrets: This allows the cleanup job to pull images from private repositories.

Checklist
For Helm Chart changes

[x] Categorize the PR by setting a good title and adding one of the labels:
bug, enhancement, documentation, change, breaking, dependency
as they show up in the changelog
[x] PR contains the label area:chart
[x] PR contains the chart label, e.g. chart:k8up
[x] Variables are documented in the values.yaml using the format required by Helm-Docs.
[ ] Chart Version bumped if immediate release after merging is planned
[ ] I have run make chart-docs
[ ] Link this PR to related code release or other issues.

@enrique-ayala
Thanks for this PR.
Please run make chart-docs and commit the change.
Furthermore ensure that the commits are all signed to ensure the DCO check passes.
Cheers Nicolas

authors: TheBigLee enrique-ayala


text:
Add app shortcut for composing email

Expected behavior
Be able to long-press on the K-9 app for a short-cut to compose an e-mail.
Actual behavior
Nothing. We don't have any shortcuts
Steps to reproduce

Long-press on the K-9 app

Environment
K-9 Mail version: 5.203
Android version: 7.1.1
Account type (IMAP, POP3, WebDAV/Exchange): IMAP
Developer Notes
Requires API version 25

Wouldn't it also be useful if the user could define a few favourite contacts that are directly used as recipient?
Or we provide shortcuts to either the most used or the last recently used addresses. The problem with this would be that they need to be updated to be in sync with the database.

Depends on #2110
Note: You can get most of this functionality today by using one of the numerous "email shortcut" apps.

Needs a better icon and there's an package issue regarding the debug suffix but this isn't so complex (once #2110 is fixed). See https://github.com/philipwhiuk/k-9/commit/a712d9e34f267052e47ba924121965d4e550efc3 for the changes needed.

As I said in my dup #3919 I'd like to see new letter shortcut in that list.

authors: 532910 GoneUp cketti philipwhiuk


text:
Edit Folderlist

Is there a way to edit the folder list and show only the folders you need the user to see?

There's an option in Incoming server settings to only show subscribed folders.
There's display options to re-order the list.


text:
Add feature to deselect all selected mail

Expected behavior
Add features to deselect all selected mail in the inbox (add to the action bar)
Actual behavior
The current feature is only 'select all'
Steps to reproduce

Move the inbox
Select some mails

Environment
K-9 Mail version: 5.600
Android version: 8.0.0
Account type (IMAP, POP3, ##WebDAV/Exchange):

You can leave selection mode by pressing the check mark button in the upper left corner.


text:
Can no longer filter messages

Sorting ISN'T the same thing as filtering! We can no longer filter by unread, read, starred, attachments, and/or date ranges.

Duplicate of #4330

authors: DasWookie cketti


text:
Design message list

Implements some of the changes suggested in #1859.
In particular it:

Rounds corners on contact badges
Changes placeholder contact badges colours
Increases font size of subject line
Removes different background colours for read and unread messages in the themes
Adds a "half" bottom border

Hastily redacted screenshot:

Awesome! Looks really great. I just created a screenshot with placeholder text instead of white boxes, so everyone can see it in its full beauty.

Any update on fixing these conflicts to be able to merge?

Oh my, this is beautiful, I really hope it'll get merged soon, great job!

Sorry for sitting on this for so long. I certainly looks much nicer than what we currently have :+1:
However, there are a couple of things I'd like to do differently, especially the colors.
This PR changes too many things at once. I think a good first step would be to start with the rounded contact images. Are you up for extracting that to a separate pull request?

That's fair.  I understand it isn't perfect: was aiming for "done".  Perhaps you'd care to share some of the things you'd like to do differently?
I'll start with one thing: I'd prefer to round the images differently.  What I have is cheap, and works, but doesn't extend to things like the AlternateRecipientAdapter.  I'd propose ContactBadge to extend some sort of rounded image class instead of the ImageView.  I'd also like it to work with the recipients in message composition.

I wrote down my thoughts on the message list appearance: See issue #4110.

authors: ByteHamster cketti immanuelfodor realmain rspencer01


text:
KAA-1655: Fix unescaped binary data in resulting string of GenericData.toString().

KAA-1655: Fix unescaped binary data in resulting string of org.apache.avro.generic.GenericData.toString() method.

@kaa-leeroy test this please

@kaa-leeroy add to whitelist

@kaa-leeroy add to whitelist

@kaa-leeroy test this please

Closed due to Jenkins job rework.

authors: Oldnickus Rib47 vtkhir

repo: kaaproject/avro


text:
Discuss the scope of the Appsody operator deployed by the Kabanero operator

I'd like to continue the discussion started in #94 about the scoping of the Appsody operator deployed by the Kabanero operator.  Currently for each Kabanero object instance, an Appsody operator is deployed in that namespace, which only watches that namespace.  There can only be one Kabanero instance per namespace.
@arthurdm @navidsh @kyleschlosser
Going forward, there is a desire to have the Appsody operator watch multiple namespaces.  I've had conversations with several different people with different opinions so this is really going to be a brain dump which can hopefully evolve into a discussion about how this should look going forward.

There is a desire to only deploy the Appsody operator if there are collections in the Kabanero instance that require it.  So for example if there were a Kabanero instance which only contained collections that promote code from dev to test, there would be no need for Appsody in that instance, and therefore the Appsody operator would not be installed there.  I think this was with the understanding that Appsody only watches a single namespace, which is no longer a restriction.
There is a desire to have the Appsody operator watch more than one namespace.  My understanding of the next rev of Kabanero is that there will be a Kabanero Instance which contains a new concept called a Workspace, where a workspace is a pair (or more) of Namespaces.  Under this arrangement the Appsody operator would need to watch all of the namespaces contained in all of the Workspaces.  It seems at this point that Appsody should be a cluster scoped operator.  At that point it becomes difficult for the Kabanero operator to manage, since it would need to keep track of whether it installed an Appsody operator to this cluster or not (any Kabanero instance on the cluster might have done it) and coordinate when it's safe to remove the Appsody operator.  It would become a pre-req dependency like Knative and Tekton Pipelines, that is pre-installed on the cluster and is not managed by the Kabanero operator.
It was mentioned in #94 that it might be nice to give the user the choice as to what to watch.  I just worry about the operator managing that in an intelligent way, such that we don't deploy two operators that are both watching the same namespace and both trying to react to what is happening there.  Maybe there is no concern here but it seems like a bad idea to me.

The Appsody operator managed by Kabanero is owned by the Kabanero operator.  If the consumer wants to expand the scope of the operator to multiple namespaces, they are free to deploy it themselves.   We aren't deploying general use components.  That said, you are dead on with the current design thinking around multi-namespace Workspaces.

The appsody operator should be deploy once by kabanero on the kabanero namespace but the defect I found is that when customer deploys using kabanero piepeline and configures the appsody application CR on a different namespace appsody operator is not listening on their namespace.
Appsody operator needs to be configure with the env variable to listen to all namespace this way customer can create appsody application on their namespace
This is how Tekton and Knative operators work they listen on all namespace for custom resources of type Knative and Tekton

Also istio controller is configured this way to listen to custom resource such as virtualservice and gateway

hi guys - the Appsody Operator can be configured in different ways, depending on the outcome wanted.  It can watch its own namespace, another namespace, or all namespaces.  The mechanism to control that is outlined here.
It depends on how Champ wants to slice things:  he may want to configure different defaults/overrides for different lines of business - in which case you would want different instances of the operator watching different namespaces - or maybe they just want something consistent across the enterprise - in which case a single instance watching all namespaces would be suitable.

hi guys - it seems like we've settled (for now) on having the kabanero operator (v0.2.0) take in a list of target namespaces, and then deploying the appsody operator to watch the namespace where kabanero is installed, as well as the target namespaces.  The new version of the appsody operator (0.2.0) includes a cluster role which allows these target namespaces to deploy appsody applications.
Are we comfortable with ending the discussion here for now, or is there still more work to be done?  We've not addressed deploying appsody at the cluster scope, I'll need you to tell me if that's still a requirement.

Targeting a set of namespace I think it solves the problem.
My other concern how would this work for adding and removing namespaces being watched?
Meaning when I install kabanero the some target namespaces don’t exist, as new projects come onboard or test namespaces how does the user add namespaces? Is there a config map or CR that I had the list of namespaces being watched the operations person can list, add, remove namespaces ?

Thanks @kaczyns - it's great that Kabanero will leverage the multi-namespace support.
I agree with @csantanapr's point about updating the namespaces afterwards.  Is there an existing CR that holds the Kabanero install configuration?   That could be the perfect place to edit the list of namespace and then simply oc apply it.

apiVersion: kabanero.io/v1alpha1
kind: Kabanero
metadata:
  name: kabanero
spec:
  targetNamespaces:
  - ns1
  - ns2

When you change this list (oc apply or whatever) we'll re-deploy the Appsody operator deployment with a new watch namespace list.

that's great @kaczyns, thanks.   I am good with closing this issue.

Perfect +1
I’m ok if you want to close

Thanks for the dialog guys.  Please open a new issue if we need to make another enhancement.

authors: arthurdm csantanapr kaczyns stephenkinder

repo: kabanero-io/kabanero-operator


text:
added dark and white theme and remove the json files

Fixes Issue Number

Changes proposed

Screenshots

Note to reviewers

Check List (Check all the applicable boxes)

[ ] My code follows the code style of this project.
[ ] My change requires changes to the documentation.
[ ] I have updated the documentation accordingly.
[ ] All new and existing tests passed.
[ ] This PR does not contain plagiarized content.
[ ] The title of my pull request is a short description of the requested changes.

Code of Conduct

[ ] By submitting this pull request, I confirm I've read and complied with the CoC 🖖

If you would like to continue contributing to open source and would like to do it with an awesome inclusive community.
Feel free to check out other cool open-source repositories and communities:
Kabir0x23 • Cryptoverse Web3 • Thecyberworld

hope this will work sir , thank you

You just removed those files again.

let me help you,

You just removed those files again.
let me help you,

you can join discord and i will help you there.

i am already in your discord server

this is my discord user name - rdx-coder#9906 please text me or call me thank you

sir , this is my phone number you can call when me your free { 9398300727 }

if i am not wrong then you only told  me to don't include this two files

if i am not wrong then you only told  me to don't include this two files

leave it sir , i am happy that my first contribution start from your project . if you have more issue / task then i am happy to work on it thank you

leave it sir , i am happy that my first contribution start from your project . if you have more issue / task then i am happy to work on it thank you

hello i have a solution
just upload the code that you have shared before
then i will help you
Will take 5 minutes of work

sir , if you don't mind can you share your twitter handle or LinkedIn or discord username please , i am so confuse

sir , i send you LinkedIn request please when your FREE then accept it

done.

sir , i send you LinkedIn request please when your FREE then accept it

done.

please chek your dm sir (LinkedIn )


text:
Expose Meta in typechecked AST

pact-analyze currently gets this meta information from the upstream Term

/cc @joelburget

repo: kadena-io/pact


text:
Style bug (paddingLeft)

I just upgraded Storybook to 2.20.1, and now I'm getting the following warning:
Warning: Unsupported style property padding-left. Did you mean paddingLeft? Check the render method of `Stories`

Fixed with https://github.com/kadirahq/storybook-ui/pull/52

This should be fixed by now.
Delete storybook-ui and install it again.
rm -rf node_modules/@kadira/storybook-ui
npm i

I think we could close this now.

authors: PEM-- arunoda ffxsam

repo: kadirahq/react-storybook


text:
latex不能正常显示

使用markdown写的公式有部分无法正常显示
这是本地的效果

这是浏览器显示效果：

找不到什么原因

这是公式原码
$x_t=W_eq_t$ ，$t \in \left \{ 1, 2, \cdots, T  \right \}$
$h_t=LSTM(x_t)$ ，$t \in \left \{ 1, 2, \cdots, T \right \}$


text:
Random bogus part numbers

I see errors of the form:
2015/10/08 21:29:23.665162 code=Part number must be an integer between 1 and 10000, inclusive msg=400 request=

randomly when writing small files to AWS S3.

Debug logs:
---[ REQUEST POST-SIGN ]-----------------------------
PUT http://XXX.s3.amazonaws.com/baz?partNumber=0&uploadId=_2HC8M.YigKHxHwgYm0kvK96spr1wTAEBCoZDF6dPgpI_zyTCAq9s6htkDJhRHsrERf5FPAkZUHnZPE4c8VpMQ-- HTTP/1.1
Host: XXX.s3.amazonaws.com
User-Agent: aws-sdk-go/0.9.5
Content-Length: 0
Authorization: AWS4-HMAC-SHA256 Credential=XXX/20151009/us-east-1/s3/aws4_request, SignedHeaders=host;x-amz-date, Signature=XXX
X-Amz-Content-Sha256: e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855
X-Amz-Date: 20151009T042923Z
Accept-Encoding: gzip

-----------------------------------------------------
2015/10/08 21:29:23 DEBUG: Response s3/UploadPart Details:
---[ RESPONSE ]--------------------------------------
HTTP/1.1 400 Bad Request
Connection: close
Transfer-Encoding: chunked
Content-Type: application/xml
Date: Fri, 09 Oct 2015 04:29:23 GMT
Server: AmazonS3
X-Amz-Id-2: XXX
X-Amz-Request-Id: XXX

Works for me with latest master.

repo: kahing/goofys


text:
webui doesn't render properly

Using a latest build from kairos master the webui doesn't render fully and there is no validation (reported on Slack:
 ...the WebUI which does not render properly, although you can still paste the cloud-init-config (no validation) and it stops working during the install...

patch linked fixed this and adds the missing docs. Validation not checked yet.

validation seems to work as expected

authors: Itxaka jimmykarily

repo: kairos-io/kairos


text:
[CI] Bundles test failing

+run-qemu-datasource-tests *failed* |   os-release:
+run-qemu-datasource-tests *failed* |   NAME="openSUSE Leap"
+run-qemu-datasource-tests *failed* |   VERSION="15.5"
+run-qemu-datasource-tests *failed* |   ID="opensuse-leap"
+run-qemu-datasource-tests *failed* |   ID_LIKE="suse opensuse"
+run-qemu-datasource-tests *failed* |   VERSION_ID="15.5"
+run-qemu-datasource-tests *failed* |   PRETTY_NAME="openSUSE Leap 15.5"
+run-qemu-datasource-tests *failed* |   ANSI_COLOR="0;32"
+run-qemu-datasource-tests *failed* |   CPE_NAME="cpe:/o:opensuse:leap:15.5"
+run-qemu-datasource-tests *failed* |   BUG_REPORT_URL="https://bugs.opensuse.org/"
+run-qemu-datasource-tests *failed* |   HOME_URL="https://www.opensuse.org/"
+run-qemu-datasource-tests *failed* |   DOCUMENTATION_URL="https://en.opensuse.org/Portal:Leap"
+run-qemu-datasource-tests *failed* |   LOGO="distributor-logo-Leap"
+run-qemu-datasource-tests *failed* |   KAIROS_NAME="leap-15.5-core-amd64-generic-v2.4.1-30-g1ad015a"
+run-qemu-datasource-tests *failed* |   KAIROS_VERSION="v2.4.1-30-g1ad015a"
+run-qemu-datasource-tests *failed* |   KAIROS_ID="kairos"
+run-qemu-datasource-tests *failed* |   KAIROS_ID_LIKE="leap-15.5-core-amd64-generic-v2.4.1-30-g1ad015a"
+run-qemu-datasource-tests *failed* |   KAIROS_VERSION_ID="v2.4.1-30-g1ad015a"
+run-qemu-datasource-tests *failed* |   KAIROS_PRETTY_NAME="leap-15.5-core-amd64-generic-v2.4.1-30-g1ad015a v2.4.1-30-g1ad015a"
+run-qemu-datasource-tests *failed* |   KAIROS_BUG_REPORT_URL="[https://github.com/kairos-io/kairos/issues](https://github.com/kairos-io/kairos/issues?q=is%3Aissue+is%3Aopen+sort%3Aupdated-desc)"
+run-qemu-datasource-tests *failed* |   KAIROS_HOME_URL="https://github.com/kairos-io/kairos"
+run-qemu-datasource-tests *failed* |   KAIROS_IMAGE_REPO="quay.io/kairos/opensuse:leap-15.5-core-amd64-generic-v2.4.1-30-g1ad015a"
+run-qemu-datasource-tests *failed* |   KAIROS_IMAGE_LABEL="v2.4.1-30-g1ad015a"
+run-qemu-datasource-tests *failed* |   KAIROS_GITHUB_REPO="kairos-io/kairos"
+run-qemu-datasource-tests *failed* |   KAIROS_VARIANT="core"
+run-qemu-datasource-tests *failed* |   KAIROS_FLAVOR="opensuse"
+run-qemu-datasource-tests *failed* |   90_custom.yaml:
+run-qemu-datasource-tests *failed* |   #cloud-config

+run-qemu-datasource-tests *failed* |   install:
+run-qemu-datasource-tests *failed* |       auto: true
+run-qemu-datasource-tests *failed* |       bundles:
+run-qemu-datasource-tests *failed* |           - rootfs_path: /var/lib/extensions/kubo
+run-qemu-datasource-tests *failed* |             targets:
+run-qemu-datasource-tests *failed* |               - container://ttl.sh/f254ffa9-bc82-435a-8d26-1e34642723e6:24h
+run-qemu-datasource-tests *failed* |           - rootfs_path: /var/lib/extensions/kubo
+run-qemu-datasource-tests *failed* |             targets:
+run-qemu-datasource-tests *failed* |               - container://ttl.sh/f254ffa9-bc82-435a-8d26-1e34642723e6:24h
+run-qemu-datasource-tests *failed* |       device: auto
+run-qemu-datasource-tests *failed* |       grub_options:
+run-qemu-datasource-tests *failed* |           extra_cmdline: foobarzz
+run-qemu-datasource-tests *failed* |       reboot: true
+run-qemu-datasource-tests *failed* |   stages:
+run-qemu-datasource-tests *failed* |       initramfs:
+run-qemu-datasource-tests *failed* |           - hostname: kairos-{{ trunc 4 .Random }}
+run-qemu-datasource-tests *failed* |             name: Set user and password
+run-qemu-datasource-tests *failed* |             users:
+run-qemu-datasource-tests *failed* |               kairos:
+run-qemu-datasource-tests *failed* |                   passwd: kairos
+run-qemu-datasource-tests *failed* |           - hostname: kairos-{{ trunc 4 .Random }}
+run-qemu-datasource-tests *failed* |             name: Set user and password
+run-qemu-datasource-tests *failed* |             users:
+run-qemu-datasource-tests *failed* |               kairos:
+run-qemu-datasource-tests *failed* |                   passwd: kairos

+run-qemu-datasource-tests *failed* |   extension-release.kubo:
+run-qemu-datasource-tests *failed* |   ID=_any

+run-qemu-datasource-tests *failed* |   systemd-sysext status:
+run-qemu-datasource-tests *failed* |   HIERARCHY EXTENSIONS SINCE
+run-qemu-datasource-tests *failed* |   /opt      none       -
+run-qemu-datasource-tests *failed* |   /usr      none       -

+run-qemu-datasource-tests *failed* |   Expected
+run-qemu-datasource-tests *failed* |       <string>: HIERARCHY EXTENSIONS SINCE
+run-qemu-datasource-tests *failed* |       /opt      none       -
+run-qemu-datasource-tests *failed* |       /usr      none       -
+run-qemu-datasource-tests *failed* |
+run-qemu-datasource-tests *failed* |   to contain substring
+run-qemu-datasource-tests *failed* |       <string>: kubo

flavor was wrong, using leap which has a systemd version not compatible (needs 252+)


text:
설치중에 아래와 같은 에러가 발생합니다.

Environment
OS :  Window 10
Python Version : 3.7.7

Collecting pororo
  Using cached pororo-0.3.1-py3-none-any.whl (211 kB)
Collecting marisa-trie
  Using cached marisa-trie-0.7.5.tar.gz (270 kB)
Collecting whoosh
  Using cached Whoosh-2.7.4-py2.py3-none-any.whl (468 kB)
Collecting sentence-transformers==0.4.1.2
  Using cached sentence-transformers-0.4.1.2.tar.gz (64 kB)
Collecting kss
  Using cached kss-2.4.0.1-py3-none-any.whl (66 kB)
Collecting nltk==3.5
  Using cached nltk-3.5.zip (1.4 MB)
Collecting wget
  Using cached wget-3.2.zip (10 kB)
Collecting transformers>=4.0.0
  Using cached transformers-4.2.2-py3-none-any.whl (1.8 MB)
Collecting g2p-en
  Using cached g2p_en-2.1.0-py3-none-any.whl (3.1 MB)
Collecting fairseq==0.10.2
  Using cached fairseq-0.10.2.tar.gz (938 kB)
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'error'
  ERROR: Command errored out with exit status 1:
   command: 'c:\programdata\anaconda3\python.exe' 'c:\programdata\anaconda3\lib\site-packages\pip\_vendor\pep517\_in_process.py' get_requires_for_build_wheel 'C:\Users\Y_BANG~1\AppData\Local\Temp\tmp6_ujjzw6'
       cwd: C:\Users\Y_BANG~1\AppData\Local\Temp\pip-install-g1p7bpee\fairseq_7bcacca07705475f8c7fc3346d13a310
  Complete output (31 lines):
  Traceback (most recent call last):
    File "setup.py", line 214, in <module>
      do_setup(package_data)
    File "setup.py", line 191, in do_setup
      zip_safe=False,
    File "C:\Users\Y_BANG~1\AppData\Local\Temp\pip-build-env-030fno3d\overlay\Lib\site-packages\setuptools\__init__.py", line 152, in setup
      _install_setup_requires(attrs)
    File "C:\Users\Y_BANG~1\AppData\Local\Temp\pip-build-env-030fno3d\overlay\Lib\site-packages\setuptools\__init__.py", line 147, in _install_setup_requires
      dist.fetch_build_eggs(dist.setup_requires)
    File "C:\Users\Y_BANG~1\AppData\Local\Temp\pip-build-env-030fno3d\overlay\Lib\site-packages\setuptools\build_meta.py", line 60, in fetch_build_eggs
      raise SetupRequirementsError(specifier_list)
  setuptools.build_meta.SetupRequirementsError: ['cython', 'numpy', 'setuptools>=18.0']

  During handling of the above exception, another exception occurred:

  Traceback (most recent call last):
    File "c:\programdata\anaconda3\lib\site-packages\pip\_vendor\pep517\_in_process.py", line 280, in <module>
      main()
    File "c:\programdata\anaconda3\lib\site-packages\pip\_vendor\pep517\_in_process.py", line 263, in main
      json_out['return_val'] = hook(**hook_input['kwargs'])
    File "c:\programdata\anaconda3\lib\site-packages\pip\_vendor\pep517\_in_process.py", line 114, in get_requires_for_build_wheel
      return hook(config_settings)
    File "C:\Users\Y_BANG~1\AppData\Local\Temp\pip-build-env-030fno3d\overlay\Lib\site-packages\setuptools\build_meta.py", line 150, in get_requires_for_build_wheel
      config_settings, requirements=['wheel'])
    File "C:\Users\Y_BANG~1\AppData\Local\Temp\pip-build-env-030fno3d\overlay\Lib\site-packages\setuptools\build_meta.py", line 130, in _get_build_requires
      self.run_setup()
    File "C:\Users\Y_BANG~1\AppData\Local\Temp\pip-build-env-030fno3d\overlay\Lib\site-packages\setuptools\build_meta.py", line 145, in run_setup
      exec(compile(code, __file__, 'exec'), locals())
    File "setup.py", line 217, in <module>
      os.unlink(fairseq_examples)
  PermissionError: [WinError 5] 액세스가 거부되었습니다: 'fairseq\\examples'
  ----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/02/59/1f466d82d64482e2809a167e0067979c23057b3752e668537d5ff24453c9/fairseq-0.10.2.tar.gz#sha256=45b90d8ccc3f5a4623a523fe2d0465f54413d03fd1ec9a9d7af0461148ca1a68 (from https://pypi.org/simple/fairseq/). Command errored out with exit status 1: 'c:\programdata\anaconda3\python.exe' 'c:\programdata\anaconda3\lib\site-packages\pip\_vendor\pep517\_in_process.py' get_requires_for_build_wheel 'C:\Users\Y_BANG~1\AppData\Local\Temp\tmp6_ujjzw6' Check the logs for full command output.
ERROR: Could not find a version that satisfies the requirement fairseq==0.10.2 (from pororo)
ERROR: No matching distribution found for fairseq==0.10.2

관리자 권한으로 cmd를 실행하시고 다시 시도해보실 수 있으실까요?

네 그렇게 했는데도 똑같은 에러가 발생합니다.

pip install --upgrade pip
pip install fairseq

진행하면 어떠실까요?

pip 최신으로 업그레이드 하고
fairseq 인스톨을 진행해 봤는데 10.2, 10.1 버전은 마찬가지 에러가 나서
10.0 버전이 설치되서 pororo 설치는 안되네요.
fairseq 이슈로 가봤는데 저랑 비슷한 문제가 있는 사람이 있지만 명확한 해결 답은 안준 것 같습니다.
pororo 이슈라기 보다는 fairseq 이슈인 것 같네요.

fairseq>=0.10.0 버전에서 정상 동작하는지 확인 후, 의존성 정보를 업데이트하겠습니다 :)

fairseq==0.10.0 버전에서 라이브러리가 정상 동작하는지 확인한 결과,
torch 버전 호환이 되지 않는 관계로 정상 동작하지 않는 것으로 파악되었습니다.
Windows 운영체제에서 최소 기능이라도 제공을 할 수 있으면 좋겠지만,
현재 fairseq의 Windows 지원 문제가 해결되기 이전까지 활용이 어려울 것 같습니다.
Ubuntu 등의 Linux 계열 머신을 활용하는 것을 추천드립니다.
감사합니다.

authors: Huffon fspanda hyunwoongko

repo: kakaobrain/pororo


text:
wc-edostavka woocommerce 3.0.7

Максим, здравствуйте.
Установил плагин на тестовом сайте с woo 2.6.4, все отлично, плагин просто супер. Но на основном сайте стоит уже woo 3.0.7 и откатываться назад страшновато, т.к. обязательно что-нибудь перестанет работать. В СДЭК при запросе плагина перенаправляют на вас. Вопрос я смотрю актуальный для многих, аналогов этого плагина я нигде не нашел.  Планируется ли обновление плагина для работы с woo 3 (если да, то когда?) и будет ли дальнейшая поддержка плагина?
Спасибо!

Здравствуйте. Дальнейшая бесплатная поддержка плагина больше не будет осуществляться. На данный момент адаптирую плагин под 3+ версию вуккомерца только по запросу пользователей на платной основе.

Сколько будет стоить адаптация?
29 мая 2017 г., 14:27 пользователь Максим Мартиросов <
notifications@github.com> написал:

Здравствуйте. Дальнейшая бесплатная поддержка плагина больше не будет
осуществляться. На данный момент адаптирую плагин под 3+ версию вуккомерца
только по запросу пользователей на платной основе.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/kalbac/wc-edostavka/issues/41#issuecomment-304638763,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AbsboblXICXEkhG1Oy7cJF_29OUOtnqpks5r-qukgaJpZM4NpLJH
.

И как с вами связаться?

maksim@martirosoff.ru

а нельзя ли просто выпустить коммерческую версию с фиксированной
ценой...чтобы было всем понятна совместимость, требования, возможности. А
то как-то не по -программистки, честное слово:)) Один раз поработать,
пофиксить баги, протестировать на совместимость, обкатать функционал,
благо, не с нуля все и не на пустом месте. А потом просто ждать, пока
денежки капают и оказывать support, ну там на 6 мес включенный в
стоимость...
На codecanyon.net выложить и нормально...
2017-05-29 14:59 GMT+03:00 Максим Мартиросов notifications@github.com:

maksim@martirosoff.ru
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
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or mute the thread
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.

Да, это идея есть в планах. Но я всё никак не найду свободного времени что бы сделать всё это поуму. Когда делаешь плагин под широкую аудиторию, нужно учитывать много нюансов. А когда делаешь под конкретного пользователя на конкретном сервере, то и отталкиваешься только от нужд клиента.

почему select2 не работает в новом вукомерце?

authors: kalbac mel139 miraserver vguns

repo: kalbac/wc-edostavka


text:
Multiple files as entry point

Update: after #102 have added multiple entry points to the checker. However it is not fully wired up to Ezno's CLI with:
https://github.com/kaleidawave/ezno/blob/1aa77e2aabb9533fb4fe90fa1ac9aaa24136256b/src/cli.rs#L170-L172
The next part (that you can contribute to):

Get a Vec<PathBuf> from a input path.

This could be a glob pattern or just a comma separated list
Should consider whether this method will work with the notify crate. While check --watch isn't currently implemented, it would be good if this addition can work with a watch mode in the future

Note I have not checked side-effect edge cases in #102

Currently there is only one entry path. OP wants to check all files in the directory. Note each entry point also type checks its imports, so this isn't necessary for checking imports and exports.

Rather than running entry_points.for_each(|path| check_project(path, ...)) this needs to be built into the internal ModuleData. So it should be callable as check_project(vec![...]).
Things to think about

Side effects in modules (want to reuse some existing data, but make it distinct)
How to get a Vec<PathBuf> from the glob passed to the CLI

How this works in the CLI watch mode

Discussed in https://github.com/kaleidawave/ezno/discussions/80

Originally posted by o-az November 11, 2023
How can I run oxidation-compiler to typecheck multiple files by passing a glob string / directory path?
Works:
npx oxidation-compiler@latest check src/file.tsx

None of these commands check all files:
npx oxidation-compiler@latest check src/*.tsx

npx oxidation-compiler@latest check src/

npx oxidation-compiler@latest check src/*

Implemented in #155

repo: kaleidawave/ezno


text:
Composer 2 support

I see this error message:
kalessil/production-dependencies-guard dev-master requires composer-plugin-api ^1.1 -> found composer-plugin-api[2.0.0] but it does not match the constraint.

You are using Composer 2, which some of your plugins seem to be incompatible with. Make sure you update your plugins or report a plugin-issue to ask them to support Composer 2.

Your requirements could not be resolved to an installable set of packages.
Problem 1
- Root composer.json requires zendframework/zend-skeleton-installer ^0.1.7 || ^1.0 -> satisfiable by zendframework/zend-skeleton-installer[0.1.7].
- zendframework/zend-skeleton-installer 0.1.7 requires composer-plugin-api ^1.0 -> found composer-plugin-api[2.0.0] but it does not match the constraint.
Problem 2
- zendframework/zend-component-installer[1.0.0, ..., 1.1.1, 2.1.0, ..., 2.1.2] require composer-plugin-api ^1.0 -> found composer-plugin-api[2.0.0] but it does not match the constraint.
- Root composer.json requires zendframework/zend-component-installer ^1.0 || ^2.1 -> satisfiable by zendframework/zend-component-installer[1.0.0, 1.1.0, 1.1.1, 2.1.0, 2.1.1, 2.1.2].
You are using Composer 2, which some of your plugins seem to be incompatible with. Make sure you update your plugins or report a plugin-issue to ask them to support Composer 2.

I have same issue:
Your requirements could not be resolved to an installable set of packages.
Problem 1
- Root composer.json requires zendframework/zend-skeleton-installer ^0.1.7 || ^1.0 -> satisfiable by zendframework/zend-skeleton-installer[0.1.7].
- zendframework/zend-skeleton-installer 0.1.7 requires composer-plugin-api ^1.0 -> found composer-plugin-api[2.0.0] but it does not match the constraint.
Problem 2
- zendframework/zend-component-installer[1.0.0, ..., 1.1.1, 2.1.0, ..., 2.1.2] require composer-plugin-api ^1.0 -> found composer-plugin-api[2.0.0] but it does not match the constraint.
- Root composer.json requires zendframework/zend-component-installer ^1.0 || ^2.1 -> satisfiable by zendframework/zend-component-installer[1.0.0, 1.1.0, 1.1.1, 2.1.0, 2.1.1, 2.1.2].
You are using Composer 2, which some of your plugins seem to be incompatible with. Make sure you update your plugins or report a plugin-issue to ask them to support Composer 2.

Foxed!

I'm afraid not foxed nor fixed yet :-(
I get such error:
php composer.phar create-project -sdev zendframework/skeleton-application helloworld
Creating a "zendframework/skeleton-application" project at "./helloworld"
Installing zendframework/skeleton-application (3.1.3)

Installing zendframework/skeleton-application (3.1.3): Extracting archive
Created project in /home/roman/helloworld
Loading composer repositories with package information
Updating dependencies
Your requirements could not be resolved to an installable set of packages.

Problem 1
- Root composer.json requires zendframework/zend-skeleton-installer ^0.1.7 || ^1.0 -> satisfiable by zendframework/zend-skeleton-installer[0.1.7].
- zendframework/zend-skeleton-installer 0.1.7 requires composer-plugin-api ^1.0 -> found composer-plugin-api[2.1.0] but it does not match the constraint.
Problem 2
- zendframework/zend-component-installer[1.0.0, ..., 1.1.1, 2.1.0, ..., 2.1.2] require composer-plugin-api ^1.0 -> found composer-plugin-api[2.1.0] but it does not match the constraint.
- Root composer.json requires zendframework/zend-component-installer ^1.0 || ^2.1 -> satisfiable by zendframework/zend-component-installer[1.0.0, 1.1.0, 1.1.1, 2.1.0, 2.1.1, 2.1.2].

authors: jammyproject kalessil promko voku

repo: kalessil/production-dependencies-guard


text:
Form element components

@srvance Have a look at this. One could still add some more component tests for the new (private) components (e.g. controls), but all essential things should be covered by the existing FormElement test, so should hopefully be ok to merge. There will probably be some merge conflicts with the bs4 branch, I can resolve them once merged to master...

Btw, the failed build comes from FastBoot tests not able to run with node 4, because of https://github.com/ember-fastboot/fastboot/pull/125. So not related to any code changes here...

A fair amount of internal complexity but it preserves the external simplicity. I think this is probably the most complex part of the addon. From a quick inspection, it looks like a nice set of abstractions for the problem. I'm going to make a couple of minor code review comments, but otherwise, let's go forward with it. I think it also provides all the control points we'll need for the bs4 adaptations. We're due for a merge to the bs4 branch anyway.

@srvance I merged this. But another thing: right now al these new component are declared as private, as they are only used by bs-form/element internally. However I was asking myself if it would make sense to make the controls (input, textarea, checkbox) public, like bs-input (which was existing before, but was just extending the two-way only {{input}} of Ember itself). This way one could use these as standalone (one-way) components where the functionality of a form-element might not be needed. Your thoughts?
On the other hand I would not want to g as gar as one day duplication the functionality of ember-one-way-controls.
We can still go that route any day though, when the need arises.

authors: simonihmig srvance


text:
[Request] Record achievement points when querying lodestone

aside from just being a generally nice addition, it'd also be personally helpful to query the api for so I do not have to reinvent playertrack and have a duplicate db just to utilise that bit of data

PlayerTrack no longer does any lodestone querying now that content ids are possible. The lodestone is a bit of a mess so I'd like to avoid future integrations with it.

authors: Jaksuhn kalilistic

repo: kalilistic/PlayerTrack


text:
Support Implicit Auth Flow

⚠ This brings breaking code changes
Added support for Implicit auth flow, that directly contains the access token in the redirect.
Could not test as it's impossible to build on anything other than macOS but should work as before except removed/renamed models.
This does not come with a new auth flow implementation as it's not 100% possible to determine the actual auth result and may depend on the same configuration.
This also makes it possible to support implicit grant and code auth flow for the same website while only registering one auth flow in the application.

@DatL4g Hey, any update on this?

Hi, i think i'd rather have this defined in a separate class ("ImplicitAuthFlow"), because it is another flow after all.
If you like, you may send a new PR, or @DatL4g you could change this in your PR.

authors: DatL4g Jimaloo kalinjul

repo: kalinjul/kotlin-multiplatform-oidc


text:
Allow to get the area/perimeter of a feature

Existing or user-defined feature.
Related to https://github.com/kalisio/kano/issues/191.

Maybe a simple first version could be to display the perimeter/area in the information box when selecting a feature (e.g. in the title or in an additional property).

authors: claustres cnouguier

repo: kalisio/kano


text:
git shake with custom main branch

In Go projects, I have branches with v2+ rule, and git shake didn't work properly.
Changes:
$ git shake v5 # use v5 as a base branch
$ git shake all v5 # use v5 as a base branch for local and remotes

it has to prevent delete version branches, e.g.
$ git branch --merged v5 | cat
  issue-158
  issue-169
  master
  v3
  v4
* v5

$ git branches
  master - 939feaf -
  v3 - f47577f -
  v4 - f45915f -
  issue-158 - 074ffd8 - <- THIS
  issue-169 - 9169027 - <- THIS
  issue-163 - edec5d8 -
* v5 - 0f199af -

repo: kamilsk/dotfiles


text:
[FEATURE] Extra explanation on AM fix and differences

Not so much a feature request for the firmware, but I don't fully understand how the AM fix works, nor how it differs from the AM fix on other authors' firmware. It would be great if there was an additional paragraph in there, please. I do enjoy this build. Thank you.

Feel free to submit such paragraph here.

Ah! You caught me! I'm afraid I have no idea how either works! If you give me a hint, I could go looking and write it up.