[1.18.2] Minceraft crashed after ineract with "table cut" item

Describe the bug: A clear and concise description of what the bug is.
The "table cut" makes ppl and sometime server crashed.
To Reproduce: Steps to reproduce the behavior
I put a "table cut" to put a quartz block to obtein 4 quartz pieces, after put the "table cut" and righ clicked, mi minecraft crashed, and everyone in X radious of that item, crashed too
Expected behavior: A clear and concise description of what you expected to happen.
The quartz block should be convert in 4 quartz pieces
Screenshots: If applicable, add screenshots to help explain your problem.
crash-2023-08-30_15.54.25-client.txt

Versions: Delightful, Farmer's Delight, and Forge versions.
Delightful version: 1.18.2-3.2.1
Forge version: 40.2.10
Minecraft: 1.18.2

Closing due to unsupported version


Memory leak? [Node 0.6.6]

Hi, we have upgraded our real-time chat application from node 0.4.8 to 0.6.6 and this is what happened...
The application is built using socket.io 0.8.7 with node-mysql (latest) and runs on a stable UNIX system.
The first graph is irrelevant.
We've been running at ~75MB RSS for months, now we instantly see a sharp increase in RSS usage.
The second graph corresponds to the RSS size in MB and it has been quite stable for months.

The update was at ~14:30 and i only updated node.
Socket.io and node-mysql were already at their latest, node 0.6.x compatible versions.
What could be the cause of this?

I noticed that our server was also leaking memory slowly. At peak times it had about 4000 connected sockets on it. Eventually the server would run out of RAM and then "forever" would restart it. I did all kinds of things to figure out if I was causing the memory leak or socket.io was causing it. I used node-inspector, v8-profiler, assertvanish and couldn't figure it out. I thought maybe it was my understanding of closures and garbage collection in node.
However, here's what happens to my RAM usage. The first part of the graph is using different version of node 0.6... Meaning I tried 0.6.4, 0.6.6, 0.6.7, etc. Any of the .6 that I tried would have the slow memory leak.
Then look what happens when I run THE SAME CODE on node 0.4.12.

Does that mean the leak is in NODE??

Seems like a pretty big issue, I wonder how many people are just not on node 0.6.* and not aware of this. Is anyone else investigating this?

I've run my chat app on 0.6.6 for a week and now it seems like it's not really leaking but has a higher and more variable base memory consumption.
But it's definitely a setback. 0.4.12 is just SO MUCH better, it cant be just the V8 engine modifications. Must be a bug.

Closing the issue as a 2-week long testing period proved that it's just a higher base memory consumption and there are no leaks in My Case.


Source::chars() iter is lossy but not documented as so

I recently switched my parsing from going over a stream of characters produced by str::chars() to parsing over a stream of characters from ariadne::Source::chars(). This makes it a lot easier to load all of my source files through a cache which can be directly used by ariadne for printing reports.
Unfortunately it isn't well documented that str::char() and ariadne::Source::chars() don't produce the same, or even roughly equivalent, output.
I spent some time debugging why none of my line-ending parsers were succeeding before I realized that ariadne::Source::chars() doesn't produce any line-endings (or even whitespace).
fn main() {
    let raw_src = "a \nb";
    let src = ariadne::Source::from(raw_src);

    let raw_char_vec = raw_src.chars().collect::<Vec<_>>();
    let src_char_vec = src.chars().collect::<Vec<_>>();

    println!("{:#?}", raw_char_vec);
    println!("{:#?}", src_char_vec);

    assert_eq!(raw_src.len(), src.len());
    assert_eq!(raw_src.len(), src.chars().count());
}

It would be nice if ariadne::Source::chars() were documented as not producing any white-space.
It would also be nice if ariadne::Source provided another method which could get a stream of characters including line-endings with appropriate spans.
I mocked up an adapter which can re-engineer a character stream which is mostly equivalent to str::chars() as long as your parser doesn't care about white-space.  It returns all the characters in the file with their correct indices, and then also injects newline characters using the index at the end of the line span. This works as a replacement for str::chars().enumerate() in my parsing code.
struct Renumerate<'a> {
    produced: usize,
    line_info: Option<(usize, usize, Vec<char>)>,
    lines: Box<dyn Iterator<Item = &'a ariadne::Line> + 'a>,
}

impl<'a> Renumerate<'a> {
    pub fn new(src: &'a ariadne::Source) -> Renumerate<'a> {
        let mut lines = src.lines();

        Renumerate {
            produced: 0,
            line_info: lines
                .next()
                .map(|line| (line.span().start, line.span().end, line.chars().collect())),
            lines: Box::new(lines),
        }
    }
}

impl<'a> Iterator for Renumerate<'a> {
    type Item = (usize, char);

    fn next(&mut self) -> Option<Self::Item> {
        if let Some((start, end, ref line_chars)) = self.line_info {
            if self.produced < line_chars.len() {
                self.produced += 1;
                Some((start + self.produced - 1, line_chars[self.produced - 1]))
            } else {
                self.line_info = self
                    .lines
                    .next()
                    .map(|line| (line.span().start, line.span().end, line.chars().collect()));
                self.produced = 0;
                Some((end - 1, '\n'))
            }
        } else {
            None
        }
    }
}

Hi, thanks for opening this issue. I definitely agree that this should be documented better and I'll be adding this to my TODO list (including moving to byte offsets instead of character positions) for my planned refactor of the library.
From my end, I wonder whether it would be better for me to keep Source's internal view of things as an implementation detail: it's set up to make it as easy as possible for Ariadne's diagnostic generator to work with and isn't really intended as a way for library users to directly interact with a file's contents.

Thanks for taking a look.
It would be fine if Source wasn't intended for use as an input type.
Having percolated on it over night, I would change the flow of my code to: Parse on a str, convert str to Source and place in Cache, Print diagnostics from the Cache.
This may already be what you intended it just wasn't the first thing that came to my mind because I was looking at the ariadne::Cache which directly returns Source objects.
I ended up writing my own cache so I didn't have to load the files from the filesystem at both parsing and diagnostics.

I ran into the same issue just now. I do agree that it doesn't have to be Sources job to act as input to a parser but given the state of documentation it's not unreasonable to try to use it that way.
For me, my main motivation to use Source as input to Chumsky was that it looked like the safest bet to avoid getting bitten by changes to the newline handling, ie.:
len: line.chars().count() + 1, // TODO: Don't assume all newlines are a single character!

Now, if you can promise not to work on this TODO until switching to byte offsets (at which point this is probably moot, anyway), I'd just switch to iterate the source string directly, filtering out any '\r' characters.

This is handled slightly better in master, fwiw. I've not had time to sit down and do the rework of the crate I've been meaning to in order to properly address this though.


Is the COCOA-cls result trained from scratch or COCO pretrained?

Hi @trqminh
Really nice work done~
Just want to confirm that is the COCOA-cls result trained from scratch using resnet50 pretrain only?
Or use the Mask-RCNN weights trained on COCO dataset then finetune on COCOA-cls?
Thank you very much

Hi @zbwxp ,
Thank you for your interest in our work and sorry for the late response.
We used Mask-RCNN weights trained on COCO dataset then finetuned on COCOA-cls.


Revert and reimplement the --ignore-xss switch while keeping logind IdleHint support

Using --ignore-xss broke logind IdleHint support (was not set/unset any more).
This version allows to disable locker-starts on xss-events while still having
logind IdleHint managed and also allows notifier starts if such given.
Note about systemd logind:
logind expects graphical sessions to set IdleHint=yes on their own
(auto-detection only works for plain text sessions of Type=tty)
Machine won't be suspended by logind in spite of IdleAction was set
in logind.conf if one or more sessions stay on IdleHint=no.
edit/update: no need to disable notifier
2nd update: fix indentation and commit message

When started from i3 using exec --no-startup-id, --ignore-xss causes xss-lock to keep running even after i3 exits. This PR fixes that.

Thanks for the heads up. This just went past and forgot about it.


litgpt cannot be imported with PyTorch build without distributed support

Bug description
In [1]: import litgpt
---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
Cell In[1], line 1
----> 1 import litgpt

File ~\mambaforge\envs\pytorch-cuda-dev\lib\site-packages\litgpt\__init__.py:6
      3 import logging
      4 import re
----> 6 from litgpt.api import LLM
      7 from litgpt.model import GPT  # needs to be imported before config
      8 from litgpt.config import Config

File ~\mambaforge\envs\pytorch-cuda-dev\lib\site-packages\litgpt\api.py:20
     18 from litgpt.tokenizer import Tokenizer
     19 from litgpt.generate.sequentially import sequential
---> 20 from litgpt.generate.tp import tensor_parallel
     21 from litgpt.generate.base import generate as generate_fn
     22 from litgpt.chat.base import generate as stream_generate_fn

File ~\mambaforge\envs\pytorch-cuda-dev\lib\site-packages\litgpt\generate\tp.py:19
     17 from lightning.fabric.plugins import BitsandbytesPrecision
     18 from lightning.fabric.utilities import rank_zero_only
---> 19 from torch.distributed._functional_collectives import all_reduce
     21 import litgpt.generate.base as generate_base
     22 from litgpt.model import GPT

File c:\users\ivan\dev\pytorch\torch\distributed\_functional_collectives.py:7
      5 import torch
      6 import torch.distributed as dist
----> 7 import torch.distributed.distributed_c10d as c10d
      8 from torch._custom_ops import impl_abstract
      9 from torch.distributed.device_mesh import DeviceMesh

File c:\users\ivan\dev\pytorch\torch\distributed\distributed_c10d.py:19
     16 from typing import Any, Callable, Dict, Optional, Tuple, Union, List, TYPE_CHECKING
     18 import torch
---> 19 from torch._C._distributed_c10d import (
     20     AllgatherOptions,
     21     AllreduceCoalescedOptions,
     22     AllreduceOptions,
     23     AllToAllOptions,
     24     _DistributedBackendOptions,
     25     BarrierOptions,
     26     BroadcastOptions,
     27     GatherOptions,
     28     PrefixStore,
     29     ProcessGroup,
     30     ReduceOp,
     31     ReduceOptions,
     32     ReduceScatterOptions,
     33     ScatterOptions,
     34     Store,
     35     DebugLevel,
     36     get_debug_level,
     37     Work,
     38     _register_process_group,
     39     _resolve_process_group,
     40     _unregister_all_process_groups,
     41     _unregister_process_group,
     42 )
     43 from torch._utils_internal import set_pytorch_distributed_envs_from_justknobs
     44 from .constants import default_pg_timeout, default_pg_nccl_timeout

ModuleNotFoundError: No module named 'torch._C._distributed_c10d'; 'torch._C' is not a package

What operating system are you using?
Windows
LitGPT Version
litgpt-0.5.2.dev1

Seems like a litgpt bug, we could fix it there? Note that we pin litgpt for the CI.

Thanks for reporting. That's a weird error and looks more like a PyTorch bug. I wonder why you get the error when this line is executed
from torch.distributed._functional_collectives import all_reduce

It looks almost like your PyTorch installation is missing something or the PyTorch C++ extensions are not installed correctly. Which PyTorch version are you using?

It's a PyTorch version that was compiled with the USE_DISTRIBUTED=0 flag. It can be imitated with two changes:

Modify is_available() function to return False in torch/distributed/__init__.py
Modify is_available() function to return False in torch/distributed/rpc/__init__.py

Oh I see now, thanks for the info!


Automatically activate testfield in macOS when receives accessibility…

… focus
This matches native behavior
fixes https://github.com/flutter/flutter/issues/77835
Pre-launch Checklist

[ ] I read the Contributor Guide and followed the process outlined there for submitting PRs.
[ ] I read the Tree Hygiene wiki page, which explains my responsibilities.
[ ] I read and followed the Flutter Style Guide, including Features we expect every widget to implement.
[ ] I signed the CLA.
[ ] I listed at least one issue that this PR fixes in the description above.
[ ] I updated/added relevant documentation (doc comments with ///).
[ ] I added new tests to check the change I am making or feature I am adding, or Hixie said the PR is test-exempt.
[ ] All existing and new tests are passing.

If you need help, consider asking for advice on the #hackers-new channel on Discord.

LGTM 👍
Are you sure this doesn't happen on Windows or Linux as well?
Also there are some test failures about the semantics tree.

I am not sure since I haven't tested on those devices, but we can add that fairly easy. cc @cbracken  who is working on windows accessibility


Replaced i18n.t w/ tpl helper in scheduler-intergation

refs: #13380
The i18n package is deprecated. It is being replaced with the tpl package.
Got some code for us? Awesome 🎊!
Please include a description of your change & check your PR against this list, thanks!

[X] There's a clear use-case for this code change
[X] Commit message has a short title & references relevant issues
[X] The build will pass (run yarn test and yarn lint)

More info can be found by clicking the "guidelines for contributing" link above.

This is my first contribution to an open source project, let me know if there's anything I should be doing differently! I'd be happy to take on more of these refactors, just wanted to make sure I have the process right first.

Absolutely nailed it in one! Thank you 🙏


Simplify and/or define a premise.

As of now (judging from design docs), player can be an agent of one of SCPverse organizations, but goals and win/lose conditions are defined only for "Containment breach" game mode. We should focus on that mode and implement a simple, straightforward dungeon-dive game (get in, find the authorization key, arm the nuke, get out). This mode can be folded into the mission system later, when said system is implemented.

Personally, I think this premise should also be the definition for our first project milestone.

Alright, I propose the following. Let's make a simple little roguelike.

The game shouldn't be long; probably 2 or 3 floors long.
The game shouldn't be overwhelmed by content. Let's make some basic enemies, the dungeon generator, a bossfight, and that's it.
We don't need to be too specific about the story for now.
The list of weapons shouldn't be too long. Let's add some basic stuff for now (pistol, shotgun, some special sci-fi gun) and that's it.
I want the augmentation system to be included in the game, but probably it shouldn't be included in the first milestone. Let's just keep it in mind.
We currently have no useful draft of ability/magic systems, so I'd probably keep them out of the first milestone, too.

What will you say, guys? Capn?

LGTM. Except that it looks more like GOC: The roguelike... We need to flesh out the story a bit. Oh, wait, that's kinda sorta my responsibility. In that case, I'm perfectly fine with the concept.

We never called our game "SCP: The roguelike"; GOC is an integral part of the concept. I think that's okay if the first playable faction will be GOC.

@ForNeVeR nevermind, i've misinterpreted your proposal a bit. There is no real constraint on the faction there.

FYI i've created separate issues for designing items, scips and other generic/reusable content. All that's left is to write plot blurb (brief recount of containment breach, intel on the scips involved, other flavor text).


Update AutoMM presets

Add presets: default, medium_quality_faster_train, high_quality, and best_quality in AutoMM.
add the preset argument in .fit() and use it in get_config().
Use registry for presets.
Add a function to return AutoMM's basic config.
Update some function names to be specific for AutoMM.

Need to add unittest about registry. You may copy the file in https://github.com/dmlc/gluon-nlp/blob/master/tests/test_utils_registry.py

Job PR-1843-9 is done.
Docs are uploaded to http://autogluon-staging.s3-website-us-west-2.amazonaws.com/PR-1843/9/index.html

Job PR-1843-10 is done.
Docs are uploaded to http://autogluon-staging.s3-website-us-west-2.amazonaws.com/PR-1843/10/index.html

Job PR-1843-11 is done.
Docs are uploaded to http://autogluon-staging.s3-website-us-west-2.amazonaws.com/PR-1843/11/index.html

Job PR-1843-12 is done.
Docs are uploaded to http://autogluon-staging.s3-website-us-west-2.amazonaws.com/PR-1843/12/index.html


add a new fact

Is your feature request related to a problem? Please describe.
NA
Describe the solution you'd like
Fact - The first computer virus was created in 1963.
Describe alternatives you've considered
NA
Additional context
NA

Can I be assigned this task?

sure @AayushMehta169 go ahead 😄


[BEAM-12197] TPC-DS: Fix SQL-queries syntax

Fix SQL queries to make them execute
Added missed queries
Make possible to run additional queries

R: @iemejia
R: @boyuanzz

Thank you for your contribution! Follow this checklist to help us incorporate your contribution quickly and easily:

[x] Choose reviewer(s) and mention them in a comment (R: @username).
[x] Format the pull request title like [BEAM-XXX] Fixes bug in ApproximateQuantiles, where you replace BEAM-XXX with the appropriate JIRA issue, if applicable. This will automatically link the pull request to the issue.
[ ] Update CHANGES.md with noteworthy changes.
[ ] If this contribution is large, please file an Apache Individual Contributor License Agreement.

See the Contributor Guide for more tips on how to make review process smoother.

GitHub Actions Tests Status (on master branch)

See CI.md for more information about GitHub Actions CI.

Hi Alexey, I'm not familiar with the functionality of this module, so I'm going to drop myself from reviewers.
cc: @kennknowles in case you are interested in changes here.

@iemejia Thanks for quick review! For the moment, only 23 queries from 103 are passed (~22%). Many fails are related to either non-supporting syntax/feature or some query planner exceptions. We will need to investigate it more deeply.


Fixes for issue 2. Also requires a generated test change outside of t…

Description

This PR fixes DOTNET-7357 issue 2. Issue number 2 Rest-Json Protocol: Unmarshalling nested Documents

(Review manual changes) commit cfd0d44ddbef718e0b562845d311b20ceefbe4d2 - Fixes for issue 2. Also requires a generated test change outside of this commit.

IMPORTANT: this issue requires that a generated test is changed in https://github.com/aws/aws-sdk-net/pull/3230
MERGE into protocol-tests feature branch only
Merge order: 12
Ticket: DOTNET-7357
Motivation and Context

Testing

N/A - the test cases are the protocol tests. A final dry-run will be done on the protocol-tests feature branch once everything is merged into the feature branch.
Screenshots (if appropriate)
Types of changes

[x] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to change)

Checklist

[x] My code follows the code style of this project
[ ] My change requires a change to the documentation
[ ] I have updated the documentation accordingly
[ ] I have read the README document
[ ] I have added tests to cover my changes
[ ] All new and existing tests passed

License

[x] I confirm that this pull request can be released under the Apache 2 license

I see there's a generated protocol test, but should we add a unit test in https://github.com/aws/aws-sdk-net/tree/main/sdk/test/UnitTests/Custom/Runtime/Documents as well?

Added two more extra unit tests on this which pass as expected.


panic when sketching

Dear Will,
With the newest go version 1.16, I have the following error:
(base) [jianshu@c391 fasta]$ hulk sketch --fasta -f S_Baltica_OS675.fna -o ./S_Baltica_OS675.hulk.sketch
2021/12/26 18:24:00 this is hulk (version 1.0.0)
2021/12/26 18:24:00 please cite Rowe et al. 2019, doi: https://doi.org/10.1186/s40168-019-0653-2
2021/12/26 18:24:00 starting the sketch subcommand
2021/12/26 18:24:00 checking parameters...
2021/12/26 18:24:00 	mode: FASTA
2021/12/26 18:24:00 	no. processors: 1
2021/12/26 18:24:00 	minimizer k-mer size: 21
2021/12/26 18:24:00 	minimizer window size: 9
2021/12/26 18:24:00 	sketch size: 50
2021/12/26 18:24:00 	streaming: disabled
2021/12/26 18:24:00 	concept drift: disabled
2021/12/26 18:24:00 	number of bins in k-mer spectrum: 194481
2021/12/26 18:24:00 	adding KHF sketch: false
2021/12/26 18:24:00 	adding KMV sketch: false
2021/12/26 18:24:00 initialising sketching pipeline...
2021/12/26 18:24:00 	initialising the processes
2021/12/26 18:24:00 	connecting data streams
2021/12/26 18:24:00 	number of processes added to the sketching pipeline: 4
2021/12/26 18:24:00 	number of minions in the sketching pool: 1
2021/12/26 18:24:00 finding minimizers...
2021/12/26 18:24:00 generating final histosketch of k-mer spectra...
panic: send on closed channel
goroutine 8 [running]:
github.com/will-rowe/hulk/src/pipeline.(*Minion).Start.func1(0xc00010c0f0)
/opt/conda/conda-bld/hulk_1563274818218/work/src/github.com/will-rowe/hulk/src/pipeline/minion.go:56 +0x5e
created by github.com/will-rowe/hulk/src/pipeline.(*Minion).Start
/opt/conda/conda-bld/hulk_1563274818218/work/src/github.com/will-rowe/hulk/src/pipeline/minion.go:35 +0x3f
Is that because the new version of go?
Thanks,
Jianshu

S_Baltica_OS675.fna.zip


ZEVA: Fix Credit Transactions Page Issues for Organization 17

Describe the task
Address and correct two key issues on the credit transactions page for organization 17 in the ZEVA System:

Align the Detailed Credit Balance values with the assessed balance for MY 2021 Credits, resolving any rounding discrepancies.
Update the credit reduction transaction line to accurately reflect the latest re-assessment reduction amount.

Purpose
This task is necessary for maintaining the accuracy of credits displayed on the credit transactions page for organization 17. Correcting these issues will ensure users have precise and up-to-date credit information, which is vital for compliance with the ZEVA Act and Regulations.
Acceptance Criteria

[ ] The Detailed Credit Balance values for MY 2021 Credits display accurately, with no discrepancies when compared to the assessed balance.
[ ] The credit reduction transaction line correctly reflects the latest reduction amount from the most recent re-assessment report.
[ ] All rounding issues related to the Detailed Credit Balance are resolved.
[ ] The credit balance table correctly accounts for supplementary and reassessment reports by using the most recent supplementary/reassessment report, rather than only the most recent MYR.

Additional context

The current issue with the credit balance table is that it only considers the final balances from the most recent MYR and adds subsequent credit transactions (e.g., assessed credit applications, transfers), without accounting for supplementary/reassessment reports.
The table should incorporate data from the most recent MYR or the most recent supplementary/reassessment report to provide accurate balance calculations.

Please reach out to the PO for organization name if you have issues finding it.

Notes from the business area:
Incorrect Detailed Credit Balance - Organization 17's Credit Transaction Page
-Issue occurs on credit transaction page under the header: detailed credit balance.
i. 2021 Model Year Credits are incorrect.
ii. Should reflect the 2022 MYR reassessment’s 2021 MY Credit balance: 35,728.05.
iii. Currently reflects the original 2022 MYR notice of assessment’s 2021 MYR Credit balance: 35,727.32


Add plugin icon

This PR belongs with refinerycms changes to the backend interface (glass)
Use classes to add icons to actions
Expand versions of refinery accepted
Add a plugin icon

@bricesanchez has been removing the glass stuff as it's incomplete. Thanks!


Transfer with auditors precompile

Describe your changes and provide context
Transfer with auditors precompile
Testing performed to validate your change

unit tests
cli testing against local node

One tradeoff we seem to be making: In our EVM precompile, we expect all the addresses passed in to be EVM addresses - this makes sense for cleanliness since it is technically an 'EVM side' thing.
However, this puts an artificial limitation on the precompile, since all parties involved need to be associated before they can use the precompile (even though there's no functional reason why this should be the case)
Wonder if it would make sense or be possible to enable users to pass in Sei addresses (especially for auditors, recipients). Doing that might enable better usability but might be more confusing to maintain.

Supporting both sei and EVM addresses is possible, and I think it we have done this for other precompiles, although use cases were not clear. As you mentioned, if you are working on EVM side, what would be the use case you need to work with Sei native address?

I think the main thing is being able to send to users or listed auditors who have not associated their accounts


ZAP tooling support for custom access quality definitions in cluster XML

This task is adding support for clusters to be able to define custom (non-default) access qualities in their cluster XML.

clusters can define their access qualities (VOMA, FS, etc.)
tools (ZAP etc.) need to be able to handle these definitions
error checking (missing required access quality definitions, bad access qualities, etc.)

These custom definitions would have been handled by ZAP (this issue) and provided by Ember (#10247). In the meantime, we have a simple (not ZAP or Ember) class (#14283) to provide that functionality until ZAP and Ember can do so.

Is the remaining work required for v1?


how to run model and use it

Hello,
I need to know how to load the model and run it?
even though, by searching online, I could not find any useful resource.
I am new with NEMO.
thanks,

I  have tried the provided .pt file, but failed, if the authors can give an example of how to use their provided file, that is better.

Thank you for taking the time to consider my message. I am eager to apply the model based on my research, but I am currently awaiting a response from the authors.

We are preparing a demo codes and will release the demo codes as soon as possible.

GatorTron models are available from Hugging Face: https://huggingface.co/UFNLP
'How to use' codes was added to this repository as well as the Hugging Face repository.

How to use code was provided.


Interestingness score

Hey,
you were roughly explaining the interestingness score in your paper and in the supplementaries. Are you planning to share more details about the process of selecting interesting scenarios or is this confidential functionality?
I am looking forward to your answer.
Best regards

Hi @odunkel, thanks for your interest in the motion forecasting dataset!
At a high level, the interestingness score is a sum of four different types of score types, which are intended to encourage the selection of scenarios which exhibit:

Kinematic complexity
Map complexity
Social complexity
AV relevance

The kinematic score associated with each scenario is made up of the following components:

Non-straight score (promotes scenarios with focal tracks that exhibit curvature)
Blind turn score (promotes scenarios with straight line trajectories in the observed segment, but contain turns in the prediction horizon)
Velocity change score (promotes scenarios with significant changes in speed)
Includes stop score (promotes scenarios which start or end at a stop)

Social score components include:

Agent type score (encourages a diverse distribution of focal agent types)
Actor density score (promotes interaction density within scenarios)

Please let me know if this helps! Happy to discuss any of the scoring components in additional detail if it's useful for the community.


Add / modify fields for New License Request

Followup from #1108, filing here at @goneall's request:
From @vmbrasseur:

The current 'new license request' issue template (by way of tools.spdx.org, I believe) has these fields:
License Name:
Short identifier:
License Author or steward:
Comments:
Standard License Header:
URL:
OSI Status:
It may make sense to evolve this template a bit to include more of the information needed for the inclusion principles. For instance, maybe add a field for listing example projects using the license.
What do folks think of reconsidering the fields on this template?

I'm +1 on adding a field to list URLs to example projects using the license, this is info we almost always want.
I'll take another look through the inclusion principles to see if there's more we want to ask.

resolved with PR #248


Crash after calling purchase with "android.test.canceled" or an invalid SKU as the argument

"android.test.canceled" is supposed to simulate a canceled purchase, I can use "android.test.purchased" to test purchases just fine, maybe "android.test.canceled" only works with the old billing API but It would be nice if the game didn't crash or at least an error message was printed to make the reason why the game crashed more clear.

This looks very similar https://github.com/dooboolab/react-native-iap/issues/386

"android.test.canceled" works, the crash was my fault, but I'll keep this open because there aren't any error messages when you call purchase with an SKU that doesn't exist or if you call it before querySkuDetails succeeds.

@MightyPrinny The error is broken in the current release. It's already fixed on master through. I'll make a new release soon.


Notifications may be logged without trace ID due to lacking request context

Prerequisites: https://github.com/turms-im/turms/issues/803 should be done first so that we can ensure the trace ID will be logged in related processes after this ticket done.


Conflicting overloads, redeclarations, overload resolution ambiguity since version 1.5.0

When running the gradle command ./gradlew testReleaseUnitTest testDebugUnitTest (or running multiple tests of different modules in 1 command), I get compile issues (Redeclarations, overload resolution ambiguity)
My test class is just a very simple basic UnitTest with mocks, and I am trying to execute the tests of multiple flavors/configurations at once. Running this at versions 1.1.0 to 1.4.0 of MocKMP gives no issues. When using version 1.5.0 or 1.6.0 i get the issues.
In the build folders i see duplicate generated code:
build
  \ generated
    \ ksp
      \ android
        \ androidDebugUnitTest
          \ <kotlin/package structure and generated code. IDE says the kotlin folder is part of [commonTest]>
        \ androidReleaseUnitTest
          \ <kotlin/package structure and generated code. IDE says the kotlin folder is part of [commonTest]>

These are the issues i am seeing

> Task :compileDebugUnitTestKotlinAndroid FAILED
Execution optimizations have been disabled for task ':compileDebugUnitTestKotlinAndroid' to ensure correctness due to the following reasons:
  - Gradle detected a problem with the following location: '/<my_project_location>/build/generated/ksp/android/androidReleaseUnitTest/kotlin'. Reason: Task ':compileDebugUnitTestKotlinAndroid' uses this output of task ':kspReleaseUnitTestKotlinAndroid' without declaring an explicit or implicit dependency. This can lead to incorrect results being produced, depending on what order the tasks are executed. Please refer to https://docs.gradle.org/7.4.2/userguide/validation_problems.html#implicit_dependency for more details about this problem.
e: /<my_project_location>/build/generated/ksp/android/androidDebugUnitTest/kotlin/com/example/HelloCoreTest_injectMocks.kt: (6, 1): Conflicting overloads: internal fun HelloCoreTest.injectMocks(mocker: Mocker): Unit defined in com.example in file HelloCoreTest_injectMocks.kt, internal fun HelloCoreTest.injectMocks(mocker: Mocker): Unit defined in com.example in file HelloCoreTest_injectMocks.kt
e: /<my_project_location>/build/generated/ksp/android/androidDebugUnitTest/kotlin/com/example/MockHelloBrowser.kt: (6, 16): Redeclaration: MockHelloBrowser
e: /<my_project_location>/build/generated/ksp/android/androidDebugUnitTest/kotlin/com/example/MockHelloNetworking.kt: (6, 16): Redeclaration: MockHelloNetworking
e: /<my_project_location>/build/generated/ksp/android/androidReleaseUnitTest/kotlin/com/example/HelloCoreTest_injectMocks.kt: (6, 1): Conflicting overloads: internal fun HelloCoreTest.injectMocks(mocker: Mocker): Unit defined in com.example in file HelloCoreTest_injectMocks.kt, internal fun HelloCoreTest.injectMocks(mocker: Mocker): Unit defined in com.example in file HelloCoreTest_injectMocks.kt
e: /<my_project_location>/build/generated/ksp/android/androidReleaseUnitTest/kotlin/com/example/MockHelloBrowser.kt: (6, 16): Redeclaration: MockHelloBrowser
e: /<my_project_location>/build/generated/ksp/android/androidReleaseUnitTest/kotlin/com/example/MockHelloNetworking.kt: (6, 16): Redeclaration: MockHelloNetworking
e: /<my_project_location>/src/commonTest/kotlin/com/example/HelloCoreTest.kt: (9, 33): Overload resolution ambiguity:
internal fun HelloCoreTest.injectMocks(mocker: Mocker): Unit defined in com.example in file HelloCoreTest_injectMocks.kt
internal fun HelloCoreTest.injectMocks(mocker: Mocker): Unit defined in com.example in file HelloCoreTest_injectMocks.kt

Do you have a reproducer project ?

multiplatform-project.zip
I extracted the issue in this reproducer project.
In the build.gradle.kts file of the root project on line 20, you can change the version of the MocKMP dependency. version 1.4.0 works, but 1.5.0 and 1.6.0 do not.
To see that it malfunctions either run ./gradlew runUnitTests (thats a convenience task that adds multiple unit test tasks together) or run them all in 1 command like so: ./gradlew :core:testReleaseUnitTest :core:iosX64Test :lib1:testReleaseUnitTest :lib1:iosX64Test :lib2:testReleaseUnitTest :lib2:iosX64Test

Fixed in 1.7.0

It does not work with my reproducer project in version 1.7.0 (when running ./gradlew runUnitTests)


Validation suggestion: Need to validate clear regions passed to vkCmdClearAttachments()

It seems like these are not verified at the moment.

Please check to see if still needed.

This work has been completed.


use largest child and adjust main view and secondary view size

If the main view and the secondary view have different measurement sizes, but they both have the layout_height set to match_parent, they should both expand to match the parents size.
This should fix #29 .
BR,
geo

Thank you for fix. I will accept this and test it latter. Currently I'm still a bit busy to actually work on this project.


Proposed edits to PR #68

Proposed edits to PR #68
1 - Use mattermost.example.com as the host/domain, consistent with TE Helm Chart configuration doc https://github.com/helm/charts/tree/master/stable/mattermost-team-edition#example-configuration
2 - Due to the Markdown heading formatting, it was hard to read through and understand if one was still part of "Configuration" or was already a new section within the guide. Propose we numbers for the sections to help guide through the set up.
This also helps with linking to specific sections of the doc, given "Ingress" is a section heading twice (once for a prerequisite, once for a configuration)
I'm 3/5 on making the sections and linking more clear, 1/5 on proposed approach.
3 - Other minor suggestions to grammar and wording.

Questions:
4 - Is there value adding mattermost-enterprise-edition helm chart to https://github.com/helm/charts/tree/master/stable?
5 - Are there are any minimum version requirements for Kubernetes or Helm?
In TE Helm Chart guide, we require Kubernetes 1.8+ with Beta APIs enabled: https://github.com/helm/charts/tree/master/stable/mattermost-team-edition#prerequisites

Not right now as they're deprecating including the full charts in that repository. They're going to move to just having links out to the maintainer's repo (e.g. this one)
@cpanato will know better but I think we have the same min reqs here

Helm no but lets set to the latest v2.13.1 and k8s 1.8+


Add synctex to the delegation spec document

based on #373

@mgudemann Rebase this on master now that #373 is merged?

@nc6 done


fix(bolt): update rust test package_id parsing

Pulled from downstream

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#622  👈
#621
main

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IIS as reverse proxy?

Hi,
I want to use this great library as MQTT broker in ASP.NET Core project. The same app host a http site, and the MQTT broker.
.UseKestrel(o => {     o.ListenAnyIP(1883, l => l.UseMqtt());      o.ListenAnyIP(80); }).UseIISIntegration()
I wondering is it possible to use in this situation the IIS as a reverse proxy?
Microsoft recommends to use in production Kestrel behind IIS.
Now I access the site on port 80, but I can't access the broker.
Thanks
Adam

i dont use .UseKestrel(o => { o.ListenAnyIP(1883, l => l.UseMqtt()); o.ListenAnyIP(80); }).UseIISIntegration()
use this :
first delete the UseKestrel
than under Startup.cs -> public void ConfigureServices(IServiceCollection services)
add this :
            var mqttServerOptions = new MqttServerOptionsBuilder()                 .WithDefaultEndpointPort(1883)                 .Build();             services                 .AddHostedMqttServer(mqttServerOptions)                 .AddMqttConnectionHandler()                 .AddConnections()                 .AddMqttTcpServerAdapter();

Please feel free to re-open this if needed.


Add Botania metals (aka. terrasteel/elementium)

@Mrthomas20121 this could be a good addition

i could

do it

but won't do it. sorry


add Partners section

Hi, I've checked from developer side and as per me code seems clean and correct 👍

@met Dobře, díky, referer se tady hodí.


Release Google.Cloud.RecaptchaEnterprise.V1 version 2.17.0

Changes in this release:
New features

A new enum Challenge is added (commit 3080dfc)
A new field challenge is added to message .google.cloud.recaptchaenterprise.v1.RiskAnalysis (commit 3080dfc)

Created release for Google.Cloud.RecaptchaEnterprise.V1-2.17.0


[en] Clarify secret encryption in the glossary

Changes

Add a sentence to the glossary entry for Secret clarifying that by default secrets are not encrypted, but only encoded in base64 strings.

/lgtm
/approve


kubelet not woking.

Rancher versions:
rancher/server:
rancher/agent:v1.2.9
Infrastructure Stack versions:
kubernetes (if applicable):rancher/k8s:v1.8.5-rancher4
Docker version: (docker version,docker info preferred)
Docker version 17.12.1-ce, build 7390fc6
Operating system and kernel: (cat /etc/os-release, uname -r preferred)
ubuntu 16.04 amd64 kernel 4.4.0-87-generic
Type/provider of hosts: (VirtualBox/Bare-metal/AWS/GCE/DO)
VMWare
Setup details: (single node rancher vs. HA rancher, internal DB vs. external DB)
Single Node
Environment Template: (Cattle/Kubernetes/Swarm/Mesos)
Kubernetes custom template follow https://www.cnrancher.com/kubernetes-installation/
Results:
kubelet (Expected state running but got error: Error response from daemon: invalid mount config: must use either propagation mode "rslave" or "rshared" when mount source is within the daemon root, daemon root: "/var/lib/docker", bind mount source: "/var/lib/docker", propagation: "rprivate")

I am facing same issue on oracle enterprise linux with 3 nodes - 1 master and two slaves. Both slaves installation failing on error above

I don't know what's wrong.I follow document on VM Ware and Aliyun, VMware and Aliyun use same Linux system ubuntu 16.04 but Aliyun is normal, VM Ware installation has the error

Same. CentOS 7 for me.
Client:
 Version:	17.12.1-ce
 API version:	1.35
 Go version:	go1.9.4
 Git commit:	7390fc6
 Built:	Tue Feb 27 22:15:20 2018
 OS/Arch:	linux/amd64

Server:
 Engine:
  Version:	17.12.1-ce
  API version:	1.35 (minimum version 1.12)
  Go version:	go1.9.4
  Git commit:	7390fc6
  Built:	Tue Feb 27 22:17:54 2018
  OS/Arch:	linux/amd64
  Experimental:	false

Hi,
Although Rancher supports Docker CE/EE version 17.12.x (Rancher Docs, Kubernetes does not Kubernetes CHANGELOG, not even in 1.9 (which still mentions that validated Docker versions are the same as for 1.8.
I ran into the same issue on CentOS 7. The highest version I got it to work without issues is 17.09.1-ce.
I'd suggest you downgrade to that version and give it another try.
Kind regards,
Eric V.

This (breaking) change went into 17.12.1, 17.12.0 should work fine but as stated by @EricVS the currently supported Docker versions for Kubernetes are 1.12,1.13 and 17.03. (http://rancher.com/docs/rancher/v1.6/en/hosts/#supported-docker-versions)

Docker 17.12.1 is now the default for CoreOS Stable channel, and I couldn't find anyway to downgrade it, so I'm not able to bring new nodes up in my cluster, is this being worked on?

There is a way to downgrade Docker on CoreOS, but you will get a old version (1.12).
See: https://coreos.com/blog/toward-docker-17-in-container-linux


Upgrade to julia 1.9

This PR upgrade to julia 1.9

Done via https://github.com/CliMA/ClimaAtmos.jl/pull/2050


Cannot convert a video that has been outputted from a numpy array back to a numpy array.

I have video test.mkv that I have converted a NumPy array video and then back to a video text_2.mkv. Not I can't convert this new video back to a NumPy array. The code is below.
import hashlib
import ffmpeg
import numpy as np

file_name = 'test.mkv'

probe = ffmpeg.probe(file_name)
video_stream = next((stream for stream in probe['streams'] if stream['codec_type'] == 'video'), None)
width = int(video_stream['width'])
height = int(video_stream['height'])

out, error = (
    ffmpeg
        .input(file_name, threads=120)
        .output("pipe:", format='rawvideo')
        .run(capture_stdout=True)
)

video = (
    np
        .frombuffer(out, np.uint8)
        .reshape([-1, height, width, 3])
)

video_buffer = (
    np.ndarray
        .flatten(video)
        .tobytes()
)

# Convert NumPy array to video
process = (
    ffmpeg
        .input('pipe:', format='rawvideo', s='{}x{}'.format(width, height))
        .output("test_2.mkv", r=30)
        .overwrite_output()
        .run_async(pipe_stdin=True)
)
process.communicate(input=video_buffer)

out_2, error = (
    ffmpeg
        .input("test_2.mkv", threads=40)
        .output("pipe:", format='rawvideo')
        .run(capture_stdout=True)
)

video_2 = (
    np
        .frombuffer(out_2, np.uint8)
        .reshape([-1, height, width, 3])
)

print(out==out_2) # False. Why don't they match?

print(np.array_equal(video, video_2)) # This must equal to True

print(hashlib.sha256(bytes(video_2)).digest()) # These hashes must be the same
print(hashlib.sha256(bytes(video)).digest())

Terminal Output:
Traceback (most recent call last):
  File "...\.venv\lib\site-packages\IPython\core\interactiveshell.py", line 3437, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-2-dd88ca422995>", line 1, in <module>
    runfile('.../main2.py', args=['pypy'], wdir='...')
  File "...\JetBrains\PyCharm 2020.2.3\plugins\python\helpers\pydev\_pydev_bundle\pydev_umd.py", line 197, in runfile
    pydev_imports.execfile(filename, global_vars, local_vars)  # execute the script
  File "...\JetBrains\PyCharm 2020.2.3\plugins\python\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile
    exec(compile(contents+"\n", file, 'exec'), glob, loc)
  File ".../main2.py", line 113, in <module>
    .reshape([-1, height, width, 3])
ValueError: cannot reshape array of size 997764480 into shape (1080,608,3)

I would like to be able to convert it to a NumPy array and have both the output be the same.

Hello!
Did you solve this problem?
I encounterd same problem.


Windows io buffer sample

This change is to ensure that samples are valid for both dGPU and iGPU in a multi gpu system

@jywu-msft Please review

I think it would be nice to provide some more details in the README to explain the differences between the two squeezenet samples. The user may not be familiar with "iobuffer optimization" and what it means. Would it be better to say one example is for cpu and the other one is for running on gpu's (and the optimization is there for memory copy avoidance?)

We have made the change


where-is-my-sddm-theme: refactoring

Description of changes
Move to pkgs/by-name. Add qt5 variant.
Things done

Built on platform(s)

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

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

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

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

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
24.05 Release Notes (or backporting 23.05 and 23.11 Release notes)

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

[ ] Fits CONTRIBUTING.md.

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

Result of nixpkgs-review pr 302661 run on x86_64-linux 1

1 package built:

where-is-my-sddm-theme


feat/gather-prometheus: collecting metrics from Prometheus API

WIP:
Collecting metrics from Prometheus API running on OCP cluster.
Those data could be read by an Prometheus backfill data. One importer was build here: https://github.com/mtulio/omg-metrics/pull/1
setup

Creating config map

cat << EOF >>  /tmp/env-metrics
export GATHER_METRICS_NAME="up
etcd_disk_backend_commit_duration_seconds_bucket
etcd_disk_wal_fsync_duration_seconds_bucket
etcd_disk_wal_fsync_duration_seconds_bucket
apiserver_flowcontrol_current_executing_requests
apiserver_flowcontrol_request_concurrency_limit"
EOF

oc create configmap must-gather-env \
    -n openshift-monitoring \
    --from-file=env=/tmp/env-metrics

Tests w/ w/o config map:
$ /must-gather/gather_metrics
Error from server (NotFound): configmaps "must-gather-env" not found
> Unable to find env GATHER_METRICS_NAME, loading default...
#> Metrics will be collected from [Wed Feb  3 11:48:50 EST 2021] to [Wed Feb 10 11:48:50 EST 2021] <#
INFO: Getting metric range: up
INFO: Getting metric range: etcd_disk_backend_commit_duration_seconds_bucket
INFO: Getting metric range: etcd_disk_wal_fsync_duration_seconds_bucket
INFO: Getting metric range: etcd_disk_wal_fsync_duration_seconds_bucket
INFO: Getting metric range: apiserver_flowcontrol_current_executing_requests
INFO: Getting metric range: apiserver_flowcontrol_request_concurrency_limit

$ oc create configmap must-gather-env     -n openshift-monitoring     --from-file=env=.env

$ /must-gather/gather_metrics
#> Metrics will be collected from [Wed Feb  3 11:49:09 EST 2021] to [Wed Feb 10 11:49:09 EST 2021] <#
INFO: Getting metric range: up
INFO: Getting metric range: etcd_disk_backend_commit_duration_seconds_bucket
INFO: Getting metric range: etcd_disk_wal_fsync_duration_seconds_bucket
INFO: Getting metric range: etcd_disk_wal_fsync_duration_seconds_bucket
INFO: Getting metric range: apiserver_flowcontrol_current_executing_requests
INFO: Getting metric range: apiserver_flowcontrol_request_concurrency_limit

Latest version we collect metrics from all Grafana dashboards to be able to playback data points from some period on analysis.


update for current Rust nightly

Thanks for the pull request, and welcome! You should hear from @huonw (or someone else) soon.


Seemingly Duplicate convos due to lens resolution

Glad to know these are seemingly duplicate and not actually-duplicate

Glad to know these are seemingly duplicate and not actually-duplicate

this is my best guess but let me know if anyone thinks otherwise!


Randomly stopped working

Had to give it a good restart. Maybe it's the same thing that happens to the Mattermost one.

/shrug it's been running

Hmm may also need a kdestroy to properly receive messages.


Error building with gradle wrapper from commandline

After adding sqldelight to a project and working for some time I decided to build from the commandline and got this error:
FAILURE: Build failed with an exception.

* What went wrong:
A problem occurred configuring project ':app'.
> Could not resolve all dependencies for configuration ':app:classpath'.
   > Could not find com.android.tools.build:gradle:2.2.1.
     Searched in the following locations:
         https://maven.fabric.io/public/com/android/tools/build/gradle/2.2.1/gradle-2.2.1.pom
         https://maven.fabric.io/public/com/android/tools/build/gradle/2.2.1/gradle-2.2.1.jar
         https://repo1.maven.org/maven2/com/android/tools/build/gradle/2.2.1/gradle-2.2.1.pom
         https://repo1.maven.org/maven2/com/android/tools/build/gradle/2.2.1/gradle-2.2.1.jar
     Required by:
         hi!You:app:unspecified > com.squareup.sqldelight:gradle-plugin:0.5.1

Using git-bisect I reached to the initial commit which just adds sqldelight without any other code. Everything works fine in Android Studio, what has to be changed for the gradle wrapper?

The Android Gradle plugin 2.2.0 and newer is only available through JCenter. If that doesn't suit you file an issue on the Android bug tracker.

The fix is to add jcenter() to your repositories.


国际化问题，怎么实现呢

I'm submitting a

Current behavior

Expected behavior

Minimal reproduction of the problem with instructions

What is the motivation / use case for changing the behavior

Environment

请看 master 分支 已经有了这个功能


update dependencies for this component even though its internal

Signed-off-by: Gus Parvin<EMAIL_ADDRESS>Fix for issue https://github.com/open-cluster-management/backlog/issues/15959

@gparvin Travis can't accept PRs from forks. The Framework right now is the one exception to our "develop in your own fork" rule.


iOS9 Ready

Is SwfitWebSocket ready for iOS9 and App Transport Security?

Yes for iOS9, and as long as the socket connection starts with "wss://" ATS should work out of the box. What issue are you seeing with ATS?

I have a simple test trying to connect to wss://sandbox-realtime.ably.io:443/?accessToken=Xyer8g.EbFHJcHX214Bs79S4JGrPPgbYV49AtxwOPpp5W1sN7Qq_HMrCLyuPyYN8HuE-k0OG7rSwxYsW684H83qZPukMi3ToF5Y2IHlqpi56nNUqgM-LBElfJyepNAemSPQoIuTWIJA8viR2qYblZROgLOUWAg&client_id=client_string&echo=true&format=json
I'm always getting error Network(The operation couldn’t be completed. Connection reset by peer).
I tested it with https://chrome.google.com/webstore/detail/simple-websocket-client and it works.
Can you help me to figure it out, please?

This is a bug. It looks like the issue may be with having both wss:// and :443 in the url.
SwiftWebSocket wasn't negotiating an SSL connection when a port is specified. I pushed a change to the dev branch which should allow for both wss and 443 in the url.
Please let me know if this fixes the problem on your side.

Yes, with dev branch it is working.

Why don't you have support for Objective-C?
I noticed and SwiftWebSocket does not use delegate, right?
One delegate with @objc attribute is enough.

Glad the fixed worked for you.
Regarding ObjC. I personally stopped working with ObjC earlier this year, and I'm a bit rusty with the interop rules. But I'm not totally opposed to adding support if there's a demand for it. Feel free to send a pull request my way.
Thanks a bunch for your help.

Well, didn't know that WebSocket is a Hashable 😶
Hashable is a protocol and is invalid for Objective-C.
Need to think about it.

I'm not sure that Hashable is required for the WebSocket class. There's an InnerWebSocket that must be Hashable because the Manager stores them in a Set, but the outer WebSocket is just a wrapper. Perhaps the Hashable can be removed.


Revision of Modelica.Icons

Reported by christiankral on 17 Mar 2010 07:45 UTC
The Modelica.Icons look a bit outdated and old fashioned and shall be updated and revised. Attached you find a proposal for Modelica.Icons and a sample package (FundamentalWave) which appears in the new look. Johan Andreasson and Christian Kral have been working on this issue and propose to include the revised Icons package in the 3.2 version of the MSL.
One additional intention of the revision of Modelica.Icons is to clearly indicate how the icons shall be used. So the user shall not have any unclear guidelines which icon he has to pick. Therefore, each icon has a short descriptions which indicates the application.
The Modelica.Icons now only contain general icons which may applicable to any library. Domain specific icons are excluded and are thus already indicated as obsolete in the package.
The names are now more structured. In this context the package specific icons are indicated by the prefix "Package" and models specific icons do not have a postfix, e.g. "Example" and "ExamplesPackage". Additional icons according to #305 and #307 are also included in the proposal. Please have a look at the attached files.

Migrated-From: https://trac.modelica.org/Modelica/ticket/317

Comment by dietmarw on 17 Mar 2010 08:42 UTC
One thing I noticed is that the Modelica32_Icons.mo provides the Information icon. This means we can finally remove yet another tool vendor annotation (i.e., __xxx_DocumentClass) from the library. Which is great!

Comment by dietmarw on 17 Mar 2010 08:44 UTC
I meant actually __xxx_DocumentationClass

Comment by dietmarw on 14 Apr 2010 09:10 UTC
I just noticed that the description string of
Modelica.Icons.MotorIcon and Modelica.Icons.GearIcon states that:
This icon will be removed in future Modelica versions, use the one in Modelon.Mechanics.Rotational instead
Now simply changing this to "Modelica.Mechanics.Rotational" does not help as those don't exist. So they should be added to the respective sub-library.

Comment by otter on 16 Jul 2010 09:23 UTC
Issues seemed to be fixed (Christian has introduced the redesigned icons in MSL3.2)

Comment by dietmarw on 16 Jul 2010 09:28 UTC
Reopening since the error mentioned in comment:4 is still not corrected. We should leave it to Johan as library officer to finalise this and finally close this issue.

Comment by otter on 16 Jul 2010 09:39 UTC
Comment 4 is handled in #340 (when conversion scripts are provided, this can be fixed. This cannot be fixed in MSL3.2).

Comment by dietmarw on 16 Jul 2010 09:44 UTC
No, comment:4 is about the missleading comment. Going to fix that myself now. What was again the tasks of the library officers? Just wondering.

Comment by otter on 16 Jul 2010 09:47 UTC
The comment is still correct. Once conversion scripts are available, these icons are moved to "Rotational", so please keep the comment.
The comment in #340:
The following icons shall be indicated as deprecated

    * Icons.MotorIcon
    * Icons.GearIcon

is not correct. It should be to move the icons to Rotational (the icons are useful and are used in user models, it is therefore impossible to remove them and it does not make sense to mark it as deprecated). I will change this in #340.

Comment by dietmarw on 16 Jul 2010 09:53 UTC
Martin you missread the essence of comment:4. It was about a wrong component link in the description link. I removed that in 0001d2b69f9e288fabae58d53c7e65ddc281182c.


Username is different in Auth.currentAuthenticatedUser and signInUserSession.accessToken.payload - Why?

Amplify CLI Version
10.5.2
Question
Username is different in Auth.currentAuthenticatedUser and signInUserSession.accessToken.payload - Why?
In Auth.currentAuthenticatedUser the Username is the Mail Adress.
In signInUserSession.accessToken.payload the username is the sub.

Hey @biller-aivy :wave: thanks for raising this! I'm going to transfer this over to the JS repo for better assistance.


(🎁) only use tomli in python<3.11

Hi @KotlinIsland,
Thanks for the contribution and sorry for the slow response. I intend to deal with this properly but don't have a lot of time lately. Having one less dependency for python 3.11 is a nice outcome.
However it looks like the change to the conftest is causing problems. Maybe we should still use tomli as a dev dependency to avoid that issue?

@nat-n I'm not sure what's happening in the CI, but it looks like the @pytest.mark.skipif(version_info < (3, 7) is running on python 3.7

@KotlinIsland It looks like something is fishy the the CI environment. Rerunning the action on main:HEAD fails :(
There's no reason to block this PR, so I've disable that test env for now, and will merge.

For some reason this 'regressed' without comment in #102 and tomli is again a required dependency.

Thanks for highlighting this @bluss. It's been fixed in 0.29.0 🚀

Oh, nice, thanks


Please use cm³ instead of cm^3

The TUI is pretty, but cm^3 looks just wrong. Fortunately, it's easy to correct:
sed -i 's/cm^3/cm³/g' data.json

Thanks for the suggestion!  This change has been added to version 2.1.1.  Let me know if you see any issues.

Looks perfect to me. :+1:


Default sort on load?

Hi Stupid-Table-Plugin people,
Amazing tool - light weight and easy to use (even for a jQuery/js noob like myself).
Anyone know how to sort by a particular column as default when the page loads?
Any help much appreciated!

This solution sets the column sort but not the direction (ASC / DESC)


Building Omni Core <IP_ADDRESS> release

Just for the reference and completness, so we're on the same level.
The previous steps are based on:

https://github.com/OmniLayer/omnicore/blob/omnicore-0.0.10/doc/gitian-building.md

If needed, refresh the inputs (from ~/gitian-builder):
make -C ../omnicore/depends download SOURCES_PATH=`pwd`/cache/common

If needed, download the SDK for OS X (stored in ~/gitian-builder/inputs):
wget https://s3.amazonaws.com/ci.omnicore.private/depends-sources/sdks/MacOSX10.7.sdk.tar.gz

Update the local copy of Omni Core:
git clone https://github.com/OmniLayer/omnicore.git

Then set the environment:
SIGNER=dexX7
COMMIT=v<IP_ADDRESS>
RELEASE=<IP_ADDRESS>

Note: the release is tagged with v<IP_ADDRESS> instead of v<IP_ADDRESS>-rel, even though the version suffix in Omni Core itself is -rel.
Build for Windows:
./bin/gbuild --commit omnicore=${COMMIT} ../omnicore/contrib/gitian-descriptors/gitian-win.yml
./bin/gsign --signer ${SIGNER} --release ${RELEASE}-win --destination ../gitian.sigs/ ../omnicore/contrib/gitian-descriptors/gitian-win.yml
mv build/out/omnicore-*.zip build/out/omnicore-*.exe ../

Build Linux:
./bin/gbuild --commit omnicore=${COMMIT} ../omnicore/contrib/gitian-descriptors/gitian-linux.yml
./bin/gsign --signer $SIGNER --release ${RELEASE}-linux --destination ../gitian.sigs/ ../omnicore/contrib/gitian-descriptors/gitian-linux.yml
mv build/out/omnicore-*.tar.gz build/out/src/omnicore-*.tar.gz ../

Build for OS X:
./bin/gbuild --commit omnicore=${COMMIT} ../omnicore/contrib/gitian-descriptors/gitian-osx.yml
./bin/gsign --signer $SIGNER --release ${RELEASE}-osx-unsigned --destination ../gitian.sigs/ ../omnicore/contrib/gitian-descriptors/gitian-osx.yml
mv build/out/omnicore-*.tar.gz build/out/omnicore-*.dmg ../

Finally continue with signing the results, as described in the gitian.sigs guide:

https://github.com/OmniLayer/gitian.sigs/blob/master/CONTRIBUTING.md

For discussion about building 0.0.11, see #406.

I've run the builds, sigs published in https://github.com/OmniLayer/gitian.sigs/pull/33 and results below:
WINDOWS:
69d3cdbdcaca7734b56dc5f8555abc58fc2a961f89f8ffaea7f148523869bafb  omnicore-<IP_ADDRESS>-rel-win32-setup.exe
a249300de2ddfb6f527bf2c8e0b703dad9bb3612c06c13fa84ab1ef240b4fb41  omnicore-<IP_ADDRESS>-rel-win32.zip
dcf25639e48f0e6d632a74dcae8913697df6ed5a8368cc9f64a742f7ec6b62e6  omnicore-<IP_ADDRESS>-rel-win64-setup.exe
e58be9381609043cec31a4202f127ba461f5c2d3b7c61bc33009daa86e3a71ec  omnicore-<IP_ADDRESS>-rel-win64.zip
d58e02c9d322c76103a600b589d7e15af9c933c60f03c7baafa60fb48fc55716  src/omnicore-<IP_ADDRESS>-rel.tar.gz

LINUX:
9daa43a667a42882aae09a04d61c7648c0f425fbe4d798d9e946b131d8e9d543  omnicore-<IP_ADDRESS>-rel-linux32.tar.gz
eeda7385bf6540ea4043adb2b924a99418ae2e67e8f0f069c48146fac82fe562  omnicore-<IP_ADDRESS>-rel-linux64.tar.gz
d58e02c9d322c76103a600b589d7e15af9c933c60f03c7baafa60fb48fc55716  src/omnicore-<IP_ADDRESS>-rel.tar.gz

OSX:
66467867cee7ec23f3d9db9fe441ac2f22f8b5415a4ddf36a74dc7bb25b5fe7d  omnicore-<IP_ADDRESS>-rel-osx-unsigned.dmg
d6b90352aaf16245ec0e74c5b6e1db5cc30e9537a5da4a972150e4d83f2ba9e8  omnicore-<IP_ADDRESS>-rel-osx-unsigned.tar.gz
734093b3409f269b959c89f197ce1c7bcd6a9d29570557e81c0b1447e3e1005a  omnicore-<IP_ADDRESS>-rel-osx64.tar.gz
d58e02c9d322c76103a600b589d7e15af9c933c60f03c7baafa60fb48fc55716  src/omnicore-<IP_ADDRESS>-rel.tar.gz

Omni Core <IP_ADDRESS> was verified and created successfully. :)
Downloads
You can download Omni Core <IP_ADDRESS> here:
Windows
https://bintray.com/artifact/download/omni/OmniBinaries/omnicore-<IP_ADDRESS>-rel-win64-setup.exe
https://bintray.com/artifact/download/omni/OmniBinaries/omnicore-<IP_ADDRESS>-rel-win64.zip
https://bintray.com/artifact/download/omni/OmniBinaries/omnicore-<IP_ADDRESS>-rel-win32-setup.exe
https://bintray.com/artifact/download/omni/OmniBinaries/omnicore-<IP_ADDRESS>-rel-win32.zip
OS X
https://bintray.com/artifact/download/omni/OmniBinaries/omnicore-<IP_ADDRESS>-rel-osx64.tar.gz
https://bintray.com/artifact/download/omni/OmniBinaries/omnicore-<IP_ADDRESS>-rel-osx-unsigned.dmg
https://bintray.com/artifact/download/omni/OmniBinaries/omnicore-<IP_ADDRESS>-rel-osx-unsigned.tar.gz
Linux
https://bintray.com/artifact/download/omni/OmniBinaries/omnicore-<IP_ADDRESS>-rel-linux64.tar.gz
https://bintray.com/artifact/download/omni/OmniBinaries/omnicore-<IP_ADDRESS>-rel-linux32.tar.gz


'EBLinearRegression' object has no attribute '_center_data'

Hello,
I'm trying to use skbayes with the latest scikit-learn (0.18.x). It looks like self._center_data is no longer being used in sklearn:
from skbayes.linear_models import EBLinearRegression
EB = EBLinearRegression()

EB.fit(X,y)
Traceback (most recent call last):

  File "<ipython-input-30-cd5ea38985d5>", line 1, in <module>
    EB.fit(X,y)

  File "C:\Anaconda2\lib\site-packages\skbayes\linear_models\bayesian_regression.py", line 102, in fit
    X, y, X_mean, y_mean, X_std = self._center_data(X, y, self.fit_intercept,

AttributeError: 'EBLinearRegression' object has no attribute '_center_data'

Hmm,
You are right.  I will look into this if you have any suggestions you are welcome to contribute.
Thanks.

I renamed self._center_data to self._preprocess_data in a bunch of place and it seems to have worked, but I can't test because tester.py seems to be out of date.

I just think a lot of people still use old versions of scikit-learn, where there is no _preprocess_data
method ( I was one of those people ). I think it will be easier to write simple _center_data method.
As for testing, I am working on my test suite , but you can use check_estimator method from scikit-learn for testing any Linear Regression Model in skbayes.

Hi, Sergey=)
I added  _center_method to linear models issue should be resolved.

Thank you very much, that fixed it!


Show age distribution graph only if there is data to show

Especially for rare variants, the age distribution graph is frequently empty (for example: https://gnomad.broadinstitute.org/variant/1-55505483-C-G). In these cases, a message should be shown "Age data is not available for this variant" instead of a blank graph.

Currently, the histogram on the SV page is shown if there is no age data at all, for heterozygotes or homozygotes. Thus, a blank histogram may still be shown for one of those if the other has some age data. It would probably be better to show a message for the specific group selected. For gnomAD variants, those are heterozygotes/homozygotes in exome/genome samples.

Would be better to return null instead of an empty histogram.

Would be better to return null instead of an empty histogram.


release

Add aarch64/arm64 binary release please..... :package: :package:

Will have a look to get this compiled for you

thanks, i'am waiting for the releases file.


Ranger3 Sick (3d Machine Vision Camera) not being able to fetch buffer through harvester

Describe the Bug
I am using Ranger3 Sick (3d machine vision camera) with Ubuntu 18.04. I have *.cti file from their Linux SDK. I am able to load cti file through harvester and get Camer info.
but when I try to fetch_buffer I am gettig the following error.
_genapi.RuntimeException: Invalid layout of buffer attached to chunk parser! : RuntimeException thrown (file 'ChunkAdapterGEV.cpp', line 99)
I have used following code
from harvesters.core import Harvester   import numpy as np   h = Harvester()   h.add_file("sickGenTLProducer.cti")   h.update()   print(len(h.device_info_list))   print(h.device_info_list[0])   ia = h.create_image_acquirer(0)   ia.start_acquisition()   with ia.fetch_buffer() as buffer:       print(buffer)
To Reproduce
Steps to reproduce the behavior:

Connect Ranger3 sick camera with Ubuntu system.
Build Linux sdk from sicksupportportal
Install genicam and harvester
Use the code from harvester for image aquisition
See error

Expected Behavior
Needed buffer data from camera through code
Screenshots
If applicable, add screenshots to help explain your problem; Note that it is not necessary to put everything as a screenshot! If the source is a text just paste the text because that is much helpful for us.
Configuration

OS: Ubuntu 18.04
Python: 3.8
Harvester: 1.3.2
GenTL Producer: SICK_AG
Camera: Ranger3-40

Reproducibility
This phenomenon can be reproduced by other versions:

[ ] Yes

If so, please list up the reproducible versions you have confirmed:

a.b.c

Actions You Have Taken

[X] I've read the Harvester FAQ page.

Additional context
Add any other context about the problem here.

@pratiksparwatwar Hi,
Thank you for the report and for trying out Harvester. Here's a quick question: Does the issue happen every fetch_buffer call?
As a typical scenario, there is a case where a frame turns corrupted due to an unexpected trouble such as insufficiently small size buffers; once an image buffer consisted of corrupted part then it cannot be parsed as long as the chunk parser is enabled. This case can be resolved with a large enough buffer that's about 9 kB enabling jumbo frame on the NIC. There is also a case where the corruption is introduced by a poor quality cable but it should be enough if you remind there's such a case.
Best regards,
Kazunari

Hi
I have exactly the same problem as reported above by @pratiksparwatwar.  My setup is also the same as his.
With device setting DeviceScanType = "Linescan3D" the following happens:
The first 17 calls to 'fetch_buffer' raises an exception with:
Invalid layout of buffer attached to chunk parser! : RuntimeException thrown (file 'ChunkAdapterGEV.cpp', line 99)
Calls to 'fetch_buffer" after the first 17 calls raise a TimeoutException.
With  device setting DeviceScanType = "Areascan" I do get 2D frames from the device when calling 'fetch_buffer'.
I.e. Areascan works whereas Linescan3D does not work.
Regards
Francois

@pratiksparwatwar Hi,
Thank you for the report and for trying out Harvester. Here's a quick question: Does the issue happen every fetch_buffer call?
As a typical scenario, there is a case where a frame turns corrupted due to an unexpected trouble such as insufficiently small size buffers; once an image buffer consisted of corrupted part then it cannot be parsed as long as the chunk parser is enabled. This case can be resolved with a large enough buffer that's about 9 kB enabling jumbo frame on the NIC. There is also a case where the corruption is introduced by a poor quality cable but it should be enough if you remind there's such a case.
Best regards, Kazunari

Issue Happens every fetch buffer call

Hi
I have exactly the same problem as reported above by @pratiksparwatwar. My setup is also the same as his.
With device setting DeviceScanType = "Linescan3D" the following happens:
The first 17 calls to 'fetch_buffer' raises an exception with: Invalid layout of buffer attached to chunk parser! : RuntimeException thrown (file 'ChunkAdapterGEV.cpp', line 99)
Calls to 'fetch_buffer" after the first 17 calls raise a TimeoutException.
With device setting DeviceScanType = "Areascan" I do get 2D frames from the device when calling 'fetch_buffer'.
I.e. Areascan works whereas Linescan3D does not work.
Regards Francois

Can you please share how to apply device settings through code.

Device settings are applied programatically using:
self.ia = self.harvester.create_image_acquirer(dev_idx)

# Iterate over all settings and apply.
nm = self.ia.remote_device.node_map
for m in my_camera_config:
    for (k, v) in m.items():
        if nm.has_node(k):
            nm.get_node(k).value = v

In this code my_camera_config is a list of dictionaries with key/value pairs being the name of the setting and the required valued.
For the Ranger3, these are two of the settings supported by the device:
my_camera_config = [{"DeviceScanType": "Linescan3D"}, {"RegionSelector": "Region1"}]
I have these in a TOML configuration file which the application loads and applies.
I tested the behaviour of harvesters_gui (from https://github.com/genicam/harvesters_gui) and see the same problem that the 3D data cannot be acquired from the Ranger3 due to:

Invalid layout of buffer attached to chunk parser! : RuntimeException thrown (file 'ChunkAdapterGEV.cpp', line 99)

Hi, I'd appreciate it if you could give it a try with the GenTL producer from MATRIX VISION to check if the phenomenon can be reproduced with that. Here's the link to their installer:

Linux (x64): http://static.matrix-vision.com/mvIMPACT_Acquire/2.45.0/install_mvGenTL_Acquire.sh
Windows: http://static.matrix-vision.com/mvIMPACT_Acquire/2.45.0/mvGenTL_Acquire-x86_64-2.45.0.exe

Once you installed that on your machine, please grep their CTI file (i.e., a GenTL producer). And then, please run your program again with their CTI file. Thanks! Regards, Kazunari.

Hi @kazunarikudo
Thanks for the idea to use the Matrix Vision CTI file.  Using this file
/opt/mvIMPACT_Acquire/lib/x86_64/mvGenTLProducer.cti
I am able to acquire buffers from the SICK Ranger3 device!
I will see whether I can extract 3D profiles as needed using this.
Does this mean there is a bug in the CTI file provided by SICK?
Regards
Francois

Hi  @pratiksparwatwar
I finally got feedback from Sick support.  It seems there is an issue where chunk data provided by the Ranger3 is not dealt with well in Harvester.  Their recommendation is to disable Chunk Data on the device.
I tried this and it seems to have fixed the problem.
Regards
Francois

@fswane and @pratiksparwatwar I would recommend that you test the fix provided by #281 and see if that solves your problems with chunks together with the Ranger3-camera.
Please report back if you still experience troubles.
Best regards
Jonas

@olofsjo Hi Jonas, thank you for taking care of this issue. I appreciate that. I have added some lines based on the suggested fix presented by Alfred to take care of some more practical situations. Hence, it's ready to be tested on the field! Thank you again for your support. Regards, Kazunari.

Hi Everybody, Could you ping me when any of you could confirm the issue has been resolved. We have resolved the first issue but I do not know if there are some more defects that block us to get the SICK Ranger 3 working. Thanks!

We have started testing on the release candidate for GenApi v3.4. Alfred found a smaller problem and made a pull request https://github.com/genicam/harvesters/pull/295, we will continue testing this week.

Hi
Thanks we'll have a look later this week and provide feedback.
Regards
Francois
On 2022/03/07 08:12, Kazunari Kudo wrote:

Hi Everybody, Could you ping me when any of you could confirm the
issue has been resolved. We have resolved the first issue but I do not
know if there are some more defects that block us to get the SICK
Ranger 3 working. Thanks!
—
Reply to this email directly, view it on GitHub
https://github.com/genicam/harvesters/issues/269#issuecomment-1060228222,
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You are receiving this because you were mentioned.Message ID:
@.***>

Hi everyone, please help me down sdk 2.8 or 2.9 sick ranger3 from website sicksupportportal. Thanks

@manhsp I recommend that you pick 2.9 or a later version.
2.9 can be found here: https://supportportal.sick.com/release/3d-stream-sdk-version-29/
and 3.1 (currently the latest) here: https://supportportal.sick.com/release/3d-stream-sdk-version-31/

I don't have account this website. Can you help me?
Vào Th 2, 29 thg 8, 2022 vào lúc 13:33 Jonas Olofsson <
@.***> đã viết:

@manhsp https://github.com/manhsp I recommend that you pick 2.9 or a
later version.
2.9 can be found here:
https://supportportal.sick.com/release/3d-stream-sdk-version-29/
and 3.1 (currently the latest) here:
https://supportportal.sick.com/release/3d-stream-sdk-version-31/
—
Reply to this email directly, view it on GitHub
https://github.com/genicam/harvesters/issues/269#issuecomment-1229839286,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/ASAXPHZUQDG7PXHHCROEVALV3RKVBANCNFSM5JJPRZWA
.
You are receiving this because you were mentioned.Message ID:
@.***>

@manhsp I recommend that you register for an account at https://supportportal.sick.com/

Hello everyone, I have a question regarding the scaling factors of the ranger3 3D camera, I have the datacube with the following bands: 'ZRange', 'Reflectance', 'XRange'. I also have the scaling factors: 'scale_factors_x_y_z': ['0.0130191', '1', '0.00870004'].
I used this code in python to convert pixel values into real distances:
z_range = data_cube[:,:,0]
x_range = data_cube[:,:,2]
ref = data_cube[:,:,1]
converted_data = np.empty_like(data_cube)
converted_data[:,:,0] = z_range * scale[2]
converted_data[:,:,1] = ref * scale[1]
converted_data[:,:,2] = x_range * scale[0]
but the resulted values do not represent the real distances. I would very much appreciate any help on this matter.
Note: the camera is well calibrated and the aspect ratio is also well calibrated.
Thank you


Kill artisan-serve command when environment file has been modified

artisan serve command is constantly watching if .env file has changed or not. Downside is that even if change is detected, not all php get's reloaded, only php server is reloaded, and some of environment variables are not updated on reload.
For example changing APP_ENV value, change is detected by artisan serve command and it restarts php server, but APP_ENV value does not change. Change only takes affect after docker container is restarted (or whole artisan command is killed and restarted).
Change that I've made starts 'artisan serve' command without active watch on .env, but started second supervisor command, to watch if .env has changed outside, and if it detects change it kills artisan serve and lets supervisor to restart it. This change always loads new environment values after change, without need of restarting docker container.
This might be not the best solution, but it works and saves some time, because it's faster to restart only serve command, rather than all docker container. Also it fixes for new developers, when they update their environment, it looks like that server has restarted, but some values are cached...
If you are interested in this change, I can apply it to other php versions.

Changing the environment would still require artisan cache:clear which accomplishes the same thing, right?

Just running artisan cache:clear does not pick up updated APP_ENV.
It might be worth adding this, just to be safe that everything is fresh after restart.

What's the status here? Please remember draft pr's aren't reviewed.

@driesvints sorry, I didn't that drafts aren't reviewed. I'm up to implementing this changes to other php versions if maintainers are interested in these changes.

Taylor will need to review. Please mark as ready if you need a review.

I don't really want to take on all this extra weight just to auto-restart if APP_ENV changes (which should very rarely happen anyways).


Prevent mobile menu from blocking header elements during animation

Account: e5c2ff3c4f6886fd7cd87002d83c6aabe48e585ce38026c0df6ea7c517e0f7a4

@SirDaev the linting seems to be failing, I suspect it is due to the CSS linter violations. Can you run npm run stylelint locally and push again?

@jamessspanggg Thanks, I missed that. Should be all set!


Broken Link Found and Updated

I found a broken link and identified the correct, updated one.
Hope this helps streamline the project!
Best regards,
Bilogweb3

Thanks!


Check focusable elements have a correct tabindex

Proposal
Check the tabIndex of commonly tabbed to elements to ensure that they remain accessible.
## Problem
Sometimes, elements which should be able to be tabbed to have their tabIndex incorrectly set, meaning they are skipped over when navigating using the keyboard
<button type="submit" tabIndex="-1">Submit</button>

The above button would be skipped past when navigating using the keyboard, making its associated form un-submittable.
Solution
For a specified list of elements, if a tabIndex is present and equal to "-1" an error should be shown.
Elements:

[ ] a[href]
[ ] area[href]
[ ] input:not([disabled])
[ ] select:not([disabled])
[ ] textarea:not([disabled])
[ ] button:not([disabled])
[ ] iframe
[ ] [contentEditable=true]

Any others which I've missed?

I like this feature! If I'm correct, using tabIndex="-1" means you can only focus on that element programmatically?

So just to confirm

[ ] Error for the above elements if tabIndex="-1"
[ ] Warn on any other element if tabindex is set at all?

Maybe the second one could be a different feature? But yes, I think that would be good.

Hey Jack! I'd like to work on the negative tabIndex issue. Could you please assign me to it?


Initialization of Embedding/NormalizedEmbedding

I noticed something that might be a problem.
You are using NormalizedEmbedding which multiplies the embedding output by sqrt(dim).  This is good, because if you don't do this, the elements of the embedding parameter matrix will stay with a standard deviation around 1.0, which is way larger than other parameters and makes the embedding parameters train (relatively) much slower.  With the NormalizedEmbedding, the elements of that parameter matrix should approach very roughly 1.0/sqrt(dim) as training proceeds.  However, you seem to be using the default initialization of torch.nn.Embedding() which initializes the parameters to stddev=1.0.  This probably makes the job of initially training the parameters harder than it needs to be.
I just discovered a related problem in our own codebase, which is different, closer to ESPNet -- that the decoder Embedding parameters were training much slower than others.  E.g. from epoch 2->3 of full Librispeech, most parameters (norm of difference) / (norm of epoch-3 parameter) was in the range [0.5,1], but the decoder embedding was something like 0.08.     @sw005320 you might want to look at this issue as well.

Interesting observation. What do you think @popcornell? @johntremblay is refactoring the transformer part these days. He might wanna try an experiment to evaluate the difference.

Sorry for the super late response.
Thanks @danpovey for spotting this. I think it makes sense to change the initialization.
I have run two experiments actually to see if in practice a difference is observed.
I added after https://github.com/speechbrain/speechbrain/blob/b408b0c1062277370bc4efa2f2b2c9a79aebcc50/speechbrain/nnet/embedding.py#L101
torch.nn.init.normal_(self.Embedding.weight, 0.0, (1/self.num_embeddings**0.5))
Here are the results:
Standard: best-valid-wer:  3.05 |  test-clean: 2.25 | test-other 5.32
Normalized:  best-valid-wer:  3.12 | test-clean: 2.23 |test-other 5.26
standard init seems more prone to overfitting.

OK-- I'd put those differences down to noise myself.
For us also, fixing this did not make much difference (although it did allow the embedding to train more meaningfully).
I suspect the reason is that they are only used as an input, so the random initialization works OK (the network can
work around it, whatever it is).

Hello,
Sorry to bring this issue out of the abyss, but is there anything we should be doing about this issue?
I don't see any reason to keep it alive.
Feel free to let me know what you think. 🙂

Hello,
It seems there has been no activity for a long time, so I am closing this issue.
Feel free to reopen it if you still encounter the problem. Thank you. 🙂


build package on Mac OS shows stat usage error

I build the package on Mac OS and below error will throw:
hchenxa@hchen-mac:~/Documents/hchenxa/src/hchenxa_github/service-catalog$ make build
stat: cannot read file system information for '%c %N': No such file or directory
stat: cannot read file system information for '%c %N': No such file or directory
stat: cannot read file system information for '%c %N': No such file or directory
stat: cannot read file system information for '%c %N': No such file or directory
stat: cannot read file system information for '%c %N': No such file or directory
hchenxa@hchen-mac:~ uname  -a
Darwin hchen-mac.cn.ibm.com 16.5.0 Darwin Kernel Version 16.5.0: Fri Mar  3 16:52:33 PST 2017; root:xnu-3789.51.2~3/RELEASE_X86_64 x86_64 i386 MacBookPro11,5 Darwin

Root causing this, in my opinion it would be better to entirely get rid of the stat call and let the go compiler do it's job of checking if packages are up to date.


Translate section title in Japanese

This is a...

[x]  Feature Request
[ ]  Bug Report

Problem:
Some section titles aren't Japanese.
Proposed Solution:
Translate section title in Japanese.
Copy from en contents and update the files listed below.

[x] content/ja/docs/_index.md (#11422)
[ ] content/ja/docs/home/_index.md
[ ] content/ja/docs/setup/custom-cloud/_index.md
[ ] content/ja/docs/setup/independent/_index.md
[ ] content/ja/docs/setup/on-premises-vm/_index.md
[ ] content/ja/docs/setup/release/_index.md
[ ] content/ja/docs/setup/turnkey/_index.md
[ ] content/ja/docs/tutorials/kubernetes-basics/create-cluster/_index.md
[ ] content/ja/docs/tutorials/kubernetes-basics/deploy-app/_index.md
[ ] content/ja/docs/tutorials/kubernetes-basics/explore/_index.md
[ ] content/ja/docs/tutorials/kubernetes-basics/expose/_index.md
[ ] content/ja/docs/tutorials/kubernetes-basics/scale/_index.md
[ ] content/ja/docs/tutorials/kubernetes-basics/update/_index.md

Page to Update:
Several pages including TOC.

content/ja/docs/home/_index.md
こちらやります

content/ja/docs/setup/custom-cloud/_index.md
こちらやります

content/ja/docs/tutorials/kubernetes-basics/create-cluster/_index.md
こちらやりまっす。

content/ja/docs/setup/independent/_index.md
これやります！

content/ja/docs/setup/on-premises-vm/_index.md
こちらやります

content/ja/docs/setup/release/_index.md
こちらやります

content/ja/docs/setup/turnkey/_index.md
こちらやります！

content/ja/docs/tutorials/kubernetes-basics/deploy-app/_index.md
こちらやります！

コレやります。
content/ja/docs/tutorials/kubernetes-basics/explore/_index.md

content/ja/docs/tutorials/kubernetes-basics/scale/_index.md
こちらやります

content/ja/docs/tutorials/kubernetes-basics/expose/_index.md
こちらやります

/assign

/close


Add FANUC M-710iC description

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

7 of 7 (100.0%)  changed or added relevant lines in 1 file are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+0.01%) to 98.472%

Totals

Change from base Build<PHONE_NUMBER>:
0.01%

Covered Lines:
838

Relevant Lines:
851

💛  - Coveralls

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Warning: This coverage report may be inaccurate.
This pull request's base commit is no longer the HEAD commit of its target branch. This means it includes changes from outside the original pull request, including, potentially, unrelated coverage changes.

For more information on this, see Tracking coverage changes with pull request builds.
To avoid this issue with future PRs, see these Recommended CI Configurations.
For a quick fix, rebase this PR at GitHub. Your next report should be accurate.

Details

7 of 7 (100.0%)  changed or added relevant lines in 1 file are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+0.01%) to 98.472%

Totals

Change from base Build<PHONE_NUMBER>:
0.01%

Covered Lines:
838

Relevant Lines:
851

💛  - Coveralls

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Warning: This coverage report may be inaccurate.
This pull request's base commit is no longer the HEAD commit of its target branch. This means it includes changes from outside the original pull request, including, potentially, unrelated coverage changes.

For more information on this, see Tracking coverage changes with pull request builds.
To avoid this issue with future PRs, see these Recommended CI Configurations.
For a quick fix, rebase this PR at GitHub. Your next report should be accurate.

Details

7 of 7 (100.0%)  changed or added relevant lines in 1 file are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+0.01%) to 98.472%

Totals

Change from base Build<PHONE_NUMBER>:
0.01%

Covered Lines:
838

Relevant Lines:
851

💛  - Coveralls


Export a BandwidthEstimate histogram via Prometheus

This is stage 1 of the BBR quic changes, this helps us to
understand how much of a difference the BBR changes are going
to make, since it the current state of my BBR stack, it's
far more aggressive than questionably it should be. That means
that it will send more data than will be rx'd on the other side.
This means that directly metering the bandwidth from the other
side is no longer a 100% valid strategy for measuring success.
Ideally in the future we will find a way to export the acknowledged
bytes metric and use that as a goodput number for clients. And monitor
that closely. On CUBIC the output rate is very close to acked_bytes,
but in BBR that might not be true anymore. Even worse in very
throttled or high random loss situations.

WARNING - This template is public, do not include any sensitive information

[X] Do the tests pass? Consistently?
[ ] Did this change improve test coverage?
[ ] Has it been reviewed/approved by relevant teammates?
[X] Can it be QA’d in staging or something like staging?
[ ] Is the code in question being linted? If not, consider adding a linter step to CI. If yes, make sure the linter is happy.
[X] Do we know how we’re going to deploy this?
[X] Are we clear on what the support and maintenance impact is?
[X] Did you create new documentation? Is it accessible and in the right place?
[ ] Has existing documentation been updated?
[ ] Have you logged tickets for related technical debt with the label “techdebt”?

It's not exactly what you want since it's not acknowledged, but just to point it out, there is also this measurement of what is sent which doesn't include retransmissions and other overhead https://github.com/getlantern/http-proxy-lantern/blob/master/instrument/instrument.go#L140


docker run error

docker run --volume /data/keepalived.conf:/container/service/keepalived/assets/keepalived.conf osixia/keepalived:1.3.9
*** CONTAINER_LOG_LEVEL = 3 (info)
*** Search service in CONTAINER_SERVICE_DIR = /container/service :
*** link /container/service/keepalived/startup.sh to /container/run/startup/keepalived
*** link /container/service/keepalived/process.sh to /container/run/process/keepalived/run
*** link /container/service/keepalived/finish.sh to /container/run/process/keepalived/finish
*** Set environment for startup files
*** Environment files will be proccessed in this order :
Caution: previously defined variables will not be overriden.
/container/environment/99-default/default.yaml
To see how this files are processed and environment variables values,
run this container with '--loglevel debug'
*** Running /container/run/startup/keepalived...
sed: can't move '/container/service/keepalived/assets/keepalived.confALkEhK' to '/container/service/keepalived/assets/keepalived.conf': Resource busy
*** /container/run/startup/keepalived failed with status 1
*** Running /container/run/process/keepalived/finish...
*** Killing all processes...

Hello,
try to run the container with --copy-service argument
please refer to the README.md for more information


Edits view steals ctrl+L from chat view

Focus chat view
ctrl+L, for "new chat"
It clears the edits view, not the chat view

Not sure of the history of why this has to be a separate command from the typical "new chat". If it needs to be separate, then probably we need a context key to identify the edits view vs chat view?


How to convert scalar types like JSONB and numeric

I'm getting errors on a few fields that are not one of the standard types when I use them in queries. Is there a recommended best way to handle the translation of extended types to types that Houdini can deal with?
Error: Could not convert scalar type: jsonb
Error: Could not convert scalar type: numeric

Hey @thormuller! Thanks again for opening an issue.
Unfortunately, houdini doesn't have any support for custom scalars. If you have any ideas for what supporting them could look like, please add them to #56.
I'm going to close this issue to keep things tidy. If you are interested / have the time to add support for them, please let me know. I'd love to provide any guidance you need


[Feature Request] llama-cpp-python Web Server api support

I set up Vicuna on a local server, but when calling the API, an error occurred.
{
	"detail": [{
		"loc": ["body", "max_tokens"],
		"msg": "none is not an allowed value",
		"type": "type_error.none.not_allowed"
	}]
}

It was set up according to this project: llama-cpp-python Web Server

FROM continuumio/miniconda3:latest
RUN /bin/bash -c "\
    conda create -n llama -c conda-forge python=3.8 -y\
    && conda install -n llama compilers make -c conda-forge -y\
    && conda run -n llama pip install llama-cpp-python[server] -i https://pypi.tuna.tsinghua.edu.cn/simple"
ENV MODEL=/llama/model.bin
ENV HOST=<IP_ADDRESS>
ENV PORT=1234
CMD ["/opt/conda/envs/llama/bin/python3.8", "-m", "llama_cpp.server"]

version: '3.3'
services:
    llama:
        ports:
            - '1234:1234'
        restart: always
        volumes:
            - './ggml-vicuna-13b-1.1-q4_3.bin:/llama/model.bin'
        image: limour/llama
        command: ["/opt/conda/envs/llama/bin/python3.8", "-m", "llama_cpp.server"]

mkdir -p ~/app/llama && cd ~/app/llama && nano Dockerfile && nano docker-compose.yml
docker build -t limour/llama .
wget https://huggingface.co/eachadea/ggml-vicuna-13b-1.1/resolve/main/ggml-vicuna-13b-1.1-q4_3.bin
sudo docker-compose up -d

Using curl is correct.
curl http://localhost:1234/v1/chat/completions \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "gpt-3.5-turbo",
  "messages": [{"role": "user", "content": "Hello!"}]
}'

The result obtained is as follows.
{
	"id": "chatcmpl-1ee5c0e3-3890-4ba2-b5d3-f8a391b90b67",
	"object": "chat.completion",
	"created":<PHONE_NUMBER>,
	"model": "/llama/model.bin",
	"choices": [{
		"index": 0,
		"message": {
			"role": "assistant",
			"content": " Hello! How can I help you today?"
		},
		"finish_reason": "stop"
	}],
	"usage": {
		"prompt_tokens": 11,
		"completion_tokens": 9,
		"total_tokens": 20
	}
}

I believe that the reason for this error is because Better ChatGPT streams the results by default, which has a different results format compared to non-streaming. We will add an option to toggle streaming to support this.

I believe that the reason for this error is because Better ChatGPT streams the results by default, which has a different results format compared to non-streaming. We will add an option to toggle streaming to support this.

Based on the error message 'loc': ['body', 'max_tokens'] and 'msg': 'none is not an allowed value', it seems to be an issue with "max_tokens: null"?

I believe that the reason for this error is because Better ChatGPT streams the results by default, which has a different results format compared to non-streaming. We will add an option to toggle streaming to support this.

 Based on the error message 'loc': ['body', 'max_tokens'] and 'msg': 'none is not an allowed value', it seems to be an issue with "max_tokens: null"?
 Based on the source code of the project, it should support streams. https://github.com/abetlen/llama-cpp-python/blob/main/llama_cpp/server/main.py

I used an old version of FreeGPT, which does not have 'max_tokens: null'. It seems to be compatible.

I see, so the error is with the null max_tokens

Another error is that the first generated token is lost, but based on the response, it seems that the server returned the first token correctly.

Personally, I think setting max_tokens to null is useful, and that the implementations should fix it if they're aiming for OpenAI compatibility, with all of the quirks, and default or interpret null to -1 for llama.cpp. One small fix I found with another implementation is just to change the regex from:
/^data: / to /.*data: /
See https://github.com/keldenl/gpt-llama.cpp/pull/25

Decent output with -1 for n_predict, Vicuna 13B:
https://user-images.githubusercontent.com/2163230/234132874-d94da365-a7f0-4206-a14d-1622a6f2471e.mp4

Ref https://github.com/abetlen/llama-cpp-python/pull/111 and https://github.com/ztjhz/BetterChatGPT/pull/249


Intellisense taking minutes to be available

Issue Description
I have several projects that now take several minutes for the intellisense information to appear, and for the functionality to be available. This seems to be a recent change.
During most of this time a process named Code Helper (Renderer) is using pretty much 100% of the CPU.
A colleague was on an older version of Code and didn't have this issue until updating to 1.43.0. I have tried 1.42.1 and 1.41.1 but I still get the issue.
Steps to Reproduce
Expected Behavior
Actual Behavior
Logs
OmniSharp log
Post the output from Output-->OmniSharp log here
C# log
Post the output from Output-->C# here
Environment information
VSCode version: 1.43.0
C# Extension: 1.21.14
Mono Information
        OmniSharp using global mono :6.6.0
Dotnet Information
.NET Core SDK (reflecting any global.json):
 Version:   3.1.101
 Commit:    b377529961
Runtime Environment:
OS Name:     Mac OS X
OS Version:  10.14
OS Platform: Darwin
RID:         osx.10.14-x64
Base Path:   /usr/local/share/dotnet/sdk/3.1.101/
Host (useful for support):
Version: 3.1.1
Commit:  a1388f194c
.NET Core SDKs installed:
2.1.302 [/usr/local/share/dotnet/sdk]
2.2.104 [/usr/local/share/dotnet/sdk]
3.1.101 [/usr/local/share/dotnet/sdk]
.NET Core runtimes installed:
Microsoft.AspNetCore.All 2.1.2 [/usr/local/share/dotnet/shared/Microsoft.AspNetCore.All]
Microsoft.AspNetCore.All 2.2.2 [/usr/local/share/dotnet/shared/Microsoft.AspNetCore.All]
Microsoft.AspNetCore.App 2.1.2 [/usr/local/share/dotnet/shared/Microsoft.AspNetCore.App]
Microsoft.AspNetCore.App 2.2.2 [/usr/local/share/dotnet/shared/Microsoft.AspNetCore.App]
Microsoft.AspNetCore.App 3.1.1 [/usr/local/share/dotnet/shared/Microsoft.AspNetCore.App]
Microsoft.NETCore.App 2.1.2 [/usr/local/share/dotnet/shared/Microsoft.NETCore.App]
Microsoft.NETCore.App 2.2.2 [/usr/local/share/dotnet/shared/Microsoft.NETCore.App]
Microsoft.NETCore.App 3.1.1 [/usr/local/share/dotnet/shared/Microsoft.NETCore.App]
To install additional .NET Core runtimes or SDKs:
https://aka.ms/dotnet-download

Visual Studio Code Extensions

Extension
Author
Version

azure-account
ms-vscode
0.8.8

csharp
ms-dotnettools
1.21.14

playfab-explorer
Playfab
0.1.7

unity-debug
Unity
2.7.2

vscode-azurefunctions
ms-azuretools
0.21.0

@zvinless Can you provide a complete OmniSharp log? And is the code that this reproduces on available for us to test against?

Please try the v1.21.15 prerelease and let us know if it resolves your performance issue.

Thanks.
Yes, that's better. Probably takes 20 seconds for intellisense to be ready
now. Is that the expected wait?
On Thu, 19 Mar 2020 at 03:22, Joey Robichaud<EMAIL_ADDRESS>wrote:

Please try the v1.21.15
https://github.com/OmniSharp/omnisharp-vscode/releases/tag/v1.21.15
prerelease and let us know if it resolves your performance issue.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/OmniSharp/omnisharp-vscode/issues/3661#issuecomment-600967078,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/ADUCPAM2AEWCCQ7CSY3CSH3RIGFXRANCNFSM4LHBW7YQ
.

@andymads It all depends on the size of your workspace (Number of projects, number of references, etc...). 20 seconds is actually pretty good compared to larger solutions like the Rolsyn repo. =)

@JoeRobich the code is not available, but the v1.21.15 prerelease is a huge improvement over the previous version. I haven't done a precise comparison but I think the delay before intellisense is in the same ballpark as v1.21.12. Let me know if a log would still be helpful.

@zvinless We made an additional improvement in the release build of 1.21.15 where we remove any file searching. I would hope it matches performance with 1.21.12 at this point. If you have any issue with the new release please open an issue and we will look into it.