docker compose fails to build due to jupyter nbextension

Describe the bug
When I ran docker compose up -d --build, 'jupyter-nbextension' seems to break it.
To Reproduce
Steps to reproduce the behavior:

clone & cd repo
run:
comp@usr:~/repos/graphein$ docker compose up -d --build
[+] Building 1842.7s (26/26) FINISHED                                                                                docker:default
=> [graphein-gpu internal] load build definition from Dockerfile                                                                                0.0s
=> => transferring dockerfile: 2.68kB                                                                                0.0s
=> [graphein-gpu internal] load metadata for docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-runtime                                                                                1.2s
=> [graphein-gpu internal] load .dockerignore                                                                                0.0s
=> => transferring context: 2B                                                                                0.0s
=> [graphein-gpu  1/22] FROM docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-runtime@sha256:8711d55e2b5c42f3c070e1f2bacc2d1988c9b3b5b99694abc6691a852536efbe                                                                                168.4s
=> => resolve docker.io/pytorch/pytorch:1.13.0-cuda11.6-cudnn8-runtime@sha256:8711d55e2b5c42f3c070e1f2bacc2d1988c9b3b5b99694abc6691a852536efbe                                                                                0.0s
=> => sha256:a404e54162968593b8d92b571f3cdd673e4c9eab5d9be28d7c494595c0aa6682 26.71MB / 26.71MB                                                                                0.6s
=> => sha256:d70bbcbd9fa5ac5613648594bc56c2c1c74c0dfcbe4ff22f0f20b79b2a49b591 9.92MB / 9.92MB                                                                                0.9s
=> => sha256:2f8d87f6e9b576cc8aafb6a58c866a9516611d549be360361c2126d91ab6a3e6 5.64GB / 5.64GB                                                                                86.4s
=> => sha256:8711d55e2b5c42f3c070e1f2bacc2d1988c9b3b5b99694abc6691a852536efbe 1.16kB / 1.16kB                                                                                0.0s
=> => sha256:1c9fb6f6f844dd852801691b87755ec1ee1693c6c28c70fc93106b2f49c97971 2.83kB / 2.83kB                                                                                0.0s
=> => extracting sha256:a404e54162968593b8d92b571f3cdd673e4c9eab5d9be28d7c494595c0aa6682                                                                                0.8s
=> => sha256:f0869fc5825082f7a44b0c9973d3d977f89a1589fe12881e53900346ba3e4863 98B / 98B                                                                                0.8s
=> => extracting sha256:d70bbcbd9fa5ac5613648594bc56c2c1c74c0dfcbe4ff22f0f20b79b2a49b591                                                                                0.7s
=> => extracting sha256:2f8d87f6e9b576cc8aafb6a58c866a9516611d549be360361c2126d91ab6a3e6                                                                                80.8s
=> => extracting sha256:f0869fc5825082f7a44b0c9973d3d977f89a1589fe12881e53900346ba3e4863                                                                                0.0s
=> [graphein-gpu internal] load build context                                                                                0.0s
=> => transferring context: 1.08kB                                                                                0.0s
=> [graphein-gpu  2/22] RUN apt-get update     && apt-get -y install build-essential ffmpeg libsm6 libxext6 wget git     && rm -rf /var/lib/apt/lists/*                                                                                66.0s
=> [graphein-gpu  3/22] RUN apt-get update && apt-get install -y iputils-ping && apt-get clean     && rm -rf /var/lib/apt/lists/*                                                                                6.5s
=> [graphein-gpu  4/22] RUN apt-get update && apt-get install -y ncbi-blast+ && apt-get clean     && rm -rf /var/lib/apt/lists/*                                                                                11.9s
=> [graphein-gpu  5/22] RUN apt-get update && apt-get install -y dssp && apt-get clean     && rm -rf /var/lib/apt/lists/*                                                                                5.6s
=> [graphein-gpu  6/22] RUN mkdir -p graphein/requirements                                                                                0.6s
=> [graphein-gpu  7/22] WORKDIR /graphein                                                                                0.0s
=> [graphein-gpu  8/22] COPY .requirements /graphein/requirements                                                                                0.0s
=> [graphein-gpu  9/22] RUN echo "$(cat requirements/base.in)" >> requirements.txt     && echo "$(cat requirements/dev.in)" >> requirements.txt     && echo "$(cat requirements/extras.in)" >> requirements.txt                                                           0.7s
=> [graphein-gpu 10/22] RUN pip install -r requirements.txt --no-cache-dir                                                                                63.6s
=> [graphein-gpu 11/22] RUN conda install -c conda-forge libgcc-ng                                                                                22.2s
=> [graphein-gpu 12/22] RUN conda install scipy scikit-learn matplotlib pandas cython ipykernel                                                                                74.4s
=> [graphein-gpu 13/22] RUN pip install ticc==0.1.4 --no-cache-dir                                                                                1.6s
=> [graphein-gpu 14/22] RUN conda install -c conda-forge vmd-python                                                                                633.1s
=> [graphein-gpu 15/22] RUN git clone https://github.com/getcontacts/getcontacts.git                                                                                3.6s
=> [graphein-gpu 16/22] RUN conda install -c fvcore -c iopath -c conda-forge fvcore iopath                                                                                50.4s
=> [graphein-gpu 17/22] RUN conda install -c pytorch3d pytorch3d                                                                                14.6s
=> [graphein-gpu 18/22] RUN conda install -c dglteam dgl                                                                                15.1s
=> [graphein-gpu 19/22] RUN conda install -c conda-forge ipywidgets                                                                                49.5s
=> [graphein-gpu 20/22] RUN export CUDA=$(python -c "import torch; print('cu'+torch.version.cuda.replace('.',''))")     && export TORCH=$(python -c "import torch; print(torch.version)")     && pip install torch-scatter -f https://pytorch-geometric.com/whl/to  640.4s
=> [graphein-gpu 21/22] RUN pip install jupyter_contrib_nbextensions                                                                                12.9s
=> ERROR [graphein-gpu 22/22] RUN jupyter nbextension enable --py widgetsnbextension                                                                                0.5s

[graphein-gpu 22/22] RUN jupyter nbextension enable --py widgetsnbextension:
0.433 usage: jupyter [-h] [--version] [--config-dir] [--data-dir] [--runtime-dir]
0.433                [--paths] [--json] [--debug]
0.433                [subcommand]
0.433
0.433 Jupyter: Interactive Computing
0.433
0.433 positional arguments:
0.433   subcommand     the subcommand to launch
0.433
0.433 optional arguments:
0.433   -h, --help     show this help message and exit
0.433   --version      show the versions of core jupyter packages and exit
0.433   --config-dir   show Jupyter config dir
0.433   --data-dir     show Jupyter data dir
0.433   --runtime-dir  show Jupyter runtime dir
0.433   --paths        show all Jupyter paths. Add --json for machine-readable
0.433                  format.
0.433   --json         output paths as machine-readable json
0.433   --debug        output debug information about paths
0.433
0.433 Available subcommands: contrib dejavu events execute kernel kernelspec lab
0.433 labextension labhub migrate nbconvert nbextensions_configurator notebook run
0.433 server troubleshoot trust
0.433
0.433 Jupyter command jupyter-nbextension not found.

failed to solve: process "/bin/sh -c jupyter nbextension enable --py widgetsnbextension" did not complete successfully: exit code: 1
Desktop (please complete the following information):

OS: Ubuntu 22.04.4 LTS (GNU/Linux 6.5.0-18-generic x86_64)
Docker version 25.0.3, build 4debf41
Python Version: as specified in Dockerfile (3.8 I think)
Graphein Version [e.g. 22] & how it was installed: freshly cloned (master)

Additional context
It also looks like you should be able to upgrade torch to 2.2.0 now and set python=3.10  (#290 ), so in case you make a new Dockerfile to fix this bug, it might be a good time to include this too.

Thanks for flagging @avivko!
Looks like Jupyter Notebook 7+ doesn't support jupyter-nbextension. Any preferences on how to resolve? I suppose pinning the notebook version to <7 seems simplest.

@a-r-j Yeah, looks like it is the easiest solution. Another solution could be using nbclassic with a newer server-backend. But I think you can go with setting Jupyter Notebook < 6.5 and revisit this in case there are incompatibilities with this in future releases of Graphein

Have merged the PR as tests pass. Feel free to re-open if it doesn't work :)


Docker Container Created

Just wanted to let you know that I turned this into a docker container. Here is the GitHub link https://github.com/KristianFJones/smartthingXBox-docker
Docker Store link: https://store.docker.com/community/images/kristianfjones/smartthingxboxon

Sweet!


Fix flow interface imports giving false-negative with named rule

This fixes #708 without ignoring all type imports.

Coverage remained the same at 95.963% when pulling 9a064263867a7d266402de9ffccab3094d21bb12 on futpib:named-flow-import-interface into 8101d39ea7fe94c1611b7183e5b171428f86f042 on benmosher:master.

No idea on that travis-ci error, seems unrelated to the changes in this PR.

It just needs a merge now, right ? ;)

published with 2.6.1 👍🏻 thanks!

Looks like I'm still experiencing this issue in 2.7.0.

@athomann we are seeing it also, but it may be a different issue (possibly https://github.com/benmosher/eslint-plugin-import/issues/616 ?) since redux-form >= 7 exports flow defs from the module itself.
To expound on that - for us, this works with flow but results in named error from eslint-plugin-import
import type {FormProps} from 'redux-form'

but this works and results in no eslint error
import type {FormProps} from 'redux-form/es/index.js.flow'


Object.defineProperty with a property descriptor without "value" causes an error

When I try to use Object.defineProperty with an accessor property descriptor, flow check shows an error.
It seems that using Object.defineProperty with a property descriptor without value property fails to typecheck.
/* @flow */
var x = { foo: 1 };

// this typechecks
Object.defineProperty(x, "foo", {
    value: 1,
    writable: false
});

// this does not
Object.defineProperty(x, "foo", {
    writable: false
});
// error message:
// Object.defineProperty
// Property not found in
// (position of the property descriptor argument): object literal

// this neither
Object.defineProperty(x, "foo", {
    get: function() { return 1; }
});
// error message is the same as the above

Is this behavior intentional?

Indeed it looks like Flow currently special-cases value properties in the descriptor:
https://github.com/facebook/flow/blob/master/src/typing/type_inference_js.ml#L3651
It's definitely worth looking into support for more of the descriptor features than just value.

+1 for a fix. I'm hitting the problem with get descriptors.

I'm running into it when trying to type this call inside of React
https://github.com/facebook/react/blob/master/src/shared/utils/canDefineProperty.js#L17

Please fix :(

Wanna workaround?
Object.defineProperty(x, "foo", ({
    get: function() { return 1; }
} : Object ));

I'm suffering with it 😢

A real use case here:
https://github.com/vuejs/vue/pull/5132/files

A related discussion here: https://github.com/facebook/flow/issues/1336
IMO if unsafe.enable_getters_and_setters works with object literal syntax for getter/setters, it should work for defineProperty() too.
@gaperton thanks for mentioning the workaround, but does this accomplish anything other than suppressing the error (as can be done using suppress_comment)? It doesn't seem to actually type-check, e.g. if you add (x.foo: number) afterwards, it says "No errors" instead of "This type is incompatible with...".

@mbrowne @gaperton The workaround doesn't catch all problems. In this example:
const o = {};

Object.defineProperty(o, 'foo', ({
    enumerable: true,
    get: () => this.foo || 1,
    set: n => {
        this.foo = n;
    }
}: Object));

You still get an error that foo does not exist on this.

@lll000111 the problem with your example is that you're using arrow functions, so this is lexically scoped. (If you run it inside a function in strict mode, it won't even work, since this would be undefined in that case.) This works:
const o = {};

Object.defineProperty(o, 'foo', ({
    enumerable: true,
    get: function() {
        return this.foo;
    },
    set: function(n) {
        this.foo = n;
    }
}: Object));

To be clear, I still don't like the workaround of casting to Object, which only suppresses the error (which you could alternatively do with $FlowFixMe comments).

But I ran this code (from a file):
// @flow
'use strict';

const o = {};

Object.defineProperty(o, 'foo', {
    enumerable: true,
    get: () => this.foo,
    set: n => {
        this.foo = n;
    }
});

console.log(JSON.stringify(o, null, 4));
o.foo = 42;
console.log(JSON.stringify(o, null, 4));

and got
$ flow-node src/main.js
{}
{
    "foo": 42
}

@mbrowne That is correct, I updated my issue (https://github.com/facebook/flow/issues/4742).

I wonder why this hasn't been fixed yet

Current error in v0.70 is: Property value is missing in object literal.
testcase

My workaround is:
const defineProperty = Object.defineProperty;
defineProperty(obj, 'key', {
  enumerable: true,
  get() {
    return "something;
  },
});

It looks like this is enough to avoid the special case, but still profiting from the typing in lib/core.js.

For anyone following here, my workaround above switches off any special handling of Object.property, such as the code from this try. It's fine for my usage but maybe not for yours.

value is no longer special cased


Null input fix

First commit prevents errors / false-positives on length and RegExp checks if input value is null or false.
2nd commit updates package.json to prevent build error/conflict with<EMAIL_ADDRESS>

Thanks @jmorganmartin for your fantastic work! I will review soon 👍

@xxxtonixxx Updated with your suggestion. Let me know if I can help get this released. It's causing a lot of errors in one of my projects.

Thanks @jmorganmartin for your work! I just have uploaded a new version 0.2.0-alpha.12 ! I hope it helps in your projects :+1:


Input/output using external programs

Currently input and output of osm.gz and osm.bz2 use the external programs gzip and bzip2. When we didn't have multithreading this wasn't such a bad idea, because at least the compressing and umcompressing was done in a separate process speeding things up. But it makes everything a little more brittle (what happens if it can't find that executable?) and, more importantly, it doesn't work on Windows, where we can't just fork the process.
Now that we have multithreading in Osmium, compressing and uncompressing should be done in extra threads using the respective libraries.
A similiar issue is the use of the "curl" executable for downloading OSM files from a URL. This should also be done in a thread using the curl or some other http library.

I am thinking about using http://cpp-netlib.org/ for integrating the read-via-HTTP part. Looks like it is easier to use then libcurl which has a horrible API. Any opinions?

easier to use then libcurl which has a horrible API. Any opinions?

Since GDAL is already a dependency, a viable alternative might be to use its libcurl wrapper: CPLHTTPFetch.

@mloskot GDAL is only a dependency for very few things that osmium does. Dragging this into something basic like I/O is not an option.

@joto Right, since it's not a hard dep. Although API/quality-wise cpp-netlib is a very good piece, there are lighter-simpler alternatives. So, whatever is your policy regarding deps and deps of deps, etc.

It doesn't look like this will be happening anytime soon. Closing here.


Fix/tanstack v9 feature test fixes

updated table-core/tsconfig to include /tests directory
fixes lint and type errors in core/tests/
fixes test cases so all pass in core/tests/

@KevinVandy Ran into a couple things I had questions on but wasn't sure the best place to ask them. figured we could just have a thread here.

Is it expected to need to pass coreFeatures to constructTable? - without it lots of core methods I was expecting to work did not exist
tried to keep these mostly the same and just update them to work with v9. let me know if there was anything you wanted changed or added to these files and I'm happy to update.

This is great. We should discuss your questions maybe in the discord table-v9 channel. Your questions address some decisions that I have not totally decided on, actually.


running docker on ubuntu windows 10 app

This bug-tracker is monitored by developers and other technical types.  We like detail!  So please use this form and tell us, concisely but precisely, what's up.  Please fill out ALL THE FIELDS!
If you have a feature request, please post to the UserVoice.  If you're reporting a BSOD, don't post here!  Instead, e-mail<EMAIL_ADDRESS>and if possible attach the minidump from "C:\Windows\minidump".

Your Windows build number:  (Type ver at a Windows Command Prompt)
Microsoft Windows [Version 10.0.16241.100
What you're doing and what's happening:  (Copy&paste specific commands and their output, or include screen shots)
docker daemon is not running because of cgroup mount
What's wrong / what should be happening instead:
docker requires to use cgroup and kernel has to support, Is there any plan for docker running in ubuntu app?
Strace of the failing command, if applicable:  (If <cmd> is failing, then run strace -o strace.txt -ff <cmd>, and post the strace.txt output here)

See our contributing instructions for assistance.

duplicate. Docker engine is not yet supported.  Based on some research and testing by @therealkenc , it looks like a bunch of necessary kernel namespace surface has been covered for systemd-nspawn, and therefore rkt, which uses nspawn as the base engine.
Docker engine is weird and requires a lot more syscall surface.  Right now, WSL appears to implement all of the additional syscall surface to get nspawn working once the base systemd is working.
Compare
https://wiki.gentoo.org/wiki/Docker
https://wiki.gentoo.org/wiki/systemd
In the meantime, you can run Docker for Windows with Hyper-v, and control it with the Ubuntu Docker client.

Thanks a lot. I can communicate with docker daemon using your recommendation.


PLAT-132841: Navigating with left and right keys in PopupTabLayout and FixedPopupPanels

Enact-DCO-1.0-Signed-off-by: Mikyung Kim<EMAIL_ADDRESS>Checklist

[x] I have read and understand the contribution guide
[ ] A CHANGELOG entry is included
[ ] At least one test case is included for this feature or bug fix
[x] Documentation was added or is not needed
[ ] This is an API breaking change

Issue Resolved / Feature Added
Added new UX that navigating with left and right keys in PopupTablayout and FixedPopupPanels.
Resolution
For right key navigation, the framework cannot support this feature so I added some example to the sampler
For left key navigation, added handles for the left key to the component and if it's the left-most spottable then it calls onBack.
Additional Considerations
Links
PLAT-132841
Comments

UI test verified in # 1569 on jenkins.


Added datacommons-bar 'subscribe' event listener to handle date change events from datacommons-slider.

Added datacommons-bar 'subscribe' event listener to handle date change events from datacommons-slider.
Updated error display for all components.

Bar chart slider integration
Example usage:
  <datacommons-bar
    apiRoot="http://localhost:8080"
    places="geoId/06 geoId/11 geoId/12"
    date="HIGHEST_COVERAGE"
    title="Life expectancy vs Median age in California, the District of Columbia, and Florida (${date})"
    subscribe="dc-bar"
    variables="LifeExpectancy_Person Median_Age_Person"
  >
    <div slot="footer">
      <datacommons-slider
        apiRoot="http://localhost:8080"
        places="geoId/06 geoId/11 geoId/12"
        publish="dc-bar"
        variables="LifeExpectancy_Person Median_Age_Person"
      ></datacommons-slider>
    </div>
  </datacommons-bar>

Error display update:

Very nice! Let's add some examples to the docsite as well of using a slider with a bar chart.

Will do


If i use chinese input methods, the editor will lose the focus,when the style is changed

If Using chinese  input methods,the editor will lose the focus at the second Chinese characters,when i change style(font color,font size and so on).
But English input method is ok. I want to know how to deal with the proplem,thx!

已测 是搜狗输入法的问题，切换微软自带输入法没问题，但是会出现删除不掉的bug

已测 是搜狗输入法的问题，换成微软自带输入法可以，但是会出现 删除不掉的bug


[WIP] Adding basic integration cases

Hey, @eschaefer I've added the basic states that we need to handle for the integration.
Right now it's just showing/hiding links on the top of the homepage, but it'll show you where to start.

covered in https://github.com/edenspiekermann/espi-dni/pull/14


Fix the issue with primary expression in JSX attribute

Fixes #1526

Current coverage is 100% (diff: 100%)

Merging #1529 into master will not change coverage

@@           master   #1529   diff @@
=====================================
  Files           1       1
  Lines        3735    3735
  Methods         0       0
  Messages        0       0
  Branches      629     629
=====================================
  Hits         3735    3735
  Misses          0       0
  Partials        0       0

Powered by Codecov. Last update d27d440...9fb40cb

:+1:

Thanks @mikesherov! We are soon back to zero JSX problem, yay 😸


Pulumi latest (3.18.1) image has older version of CLI

Hello!

Vote on this issue by adding a 👍 reaction
To contribute a fix for this issue, leave a comment (and link to your pull request, if you've opened one already)

Issue details
The latest (at time of writing) tag on the pulumi-go docker image is reporting an older version via pulumi version on the command line.
> docker run -it --rm pulumi/pulumi-go:3.18.1 pulumi version

Unable to find image 'pulumi/pulumi-go:3.18.1' locally
3.18.1: Pulling from pulumi/pulumi-go
Digest: sha256:93aa1a8c33d73b073b50b20aec1b8f3ebcf3fc06c8fcef803139f74a9e16be63
Status: Downloaded newer image for pulumi/pulumi-go:3.18.1
v3.18.0

warning: A new version of Pulumi is available. To upgrade from version '3.18.0' to '3.18.1', visit https://pulumi.com/docs/reference/install/ for manual instructions and release notes.

Expected: The version to be 3.18.1
Actual: The version was 3.18.0

@pyoio Just to confirm, you pulled this from Docker Hub (as opposed to the AWS ECR public gallery)?

Isolated this issue specifically to the pulumi-go image.

@pyoio Just to confirm, you pulled this from Docker Hub (as opposed to the AWS ECR public gallery)?

that's correct


Unit test for failing Arbitrum eth_call

Fixes: https://github.com/runtimeverification/firefly/issues/664

Reopening because the test passes now.


Feature Suggestion: add SelectedValuePath and SelectedValue to DropDown

These are implemented in wpf ComboBox and are quite hard to work around without changing view models when converting from wpf.  I've so far failed to work around it with converters, the ConverterParameter does not appear to support binding so it is hard to pass the value and items collection, the multivalue converter is oneway only.

This is supported by other WPF and WinUI/UWP controls such as ListView as well.

Since a newer issue received more feedback, I will close this one as a duplicate - https://github.com/AvaloniaUI/Avalonia/issues/4718


Add domains on the fly

Hi,
I am implemententing an auto-whitelabel fature on my service based on the host. For this i use wildcard dns resolution, and allow clients to register custom domains on the same service that will change based on host, at least one subdomain is provided.
Is this crate capable of adding new domains on the fly ?

Adding domains on the fly isn't supported yet, but could probably be added. Could you describe your usecase a little more?
If I understood your use case correctly you would like to add (and presumably remove) additional domains, which may not share the same TLD, on the fly. Not sure I understood the parts about wildcard dns and the subdomain, so I'm not sure if that is relevant here.
I think there is one key consideration. Do you want one or a few certs for all domains (iirc Let's Encrypt allows about a hundred), or many certs for many sets of domains. Different rate limits may apply to each case. I suspect the latter is more robust and scalable, so I'll focus on that in the following.
I can think of three ways to go about this:

Allow the low level API to construct AcmeAccept from futures_rustls::StartHandshake instead of the TCP stream. This would allow you to inspect the host before handing the connection over to the respective AcmeAcceptor instance for the domain.
Generalize all components to handle multiple independently maintained certs with different domain sets (this affects mostly resolver and state structs).
Do (1) and add a new high level type specifically to provide a high-level API to do manage the state collection, inspection and matching.

(1) seems like a low-hanging fruit and generally useful. (3) is a nice composition of existing features (after (1) is implemented).
However (2) is quite appealing in terms of resource sharing and while composing atomic features is nice, it may be too easy to generalize here to pass that up for introducing something more complex like (3), which may be something better done by the users of this crate if desired.
Do you think (some/all of) these options would match your requirements?
Also, this sound like you may be working on a commercial service. If that is the case, feel free to contact me at<EMAIL_ADDRESS>if professional support or accelerated development could be valuable to you.

Thank you for the description, i'm not too familiar with rustls and how certificates work but i indeed envisioned the latter where i store lots of certs in the database and choose one as needed (with a local cache of course).
I'll try the different options, but my ideal high level api would be to just have an arc dashmap that maps the domains to certificates and you can just add a new certificate manually, or request a new one be generated for a domain (that does a dns check if it has the right IP before challenging acme). I suppose that would imply solution 2.

To prevent misunderstandings: You can't do this at the moment with rustls-acme (well, you might, but it's not obvious how). I'm trying to understand your use case better to come up with a solution that makes sense. The 3 options above were ideas for implementations.
I'm a bit confused what exactly you want to accomplish, so here are a few questions/notes:

Your last comment, sounds like you may want to use a mix of certs from other sources and let's encrypt. If that is the case, that would be good to know.
You mention a certificate container (dashmap). I think that may be based on a misunderstanding of how rustls-acme works. rustls-acme  is not primarily a library to execute acme orders and get a certificate in return to use as you please. You can do that with the stuff in the rustls_acme::acme module. I'll happily support changes that make the stuff in that module useful to more people, but high-level helpers for manual order workflows would have to live in another crate.
Instead rustls-acme focuses on a convenient implementation of the tls-alpn-01 validation, which implies, that it has access to all incoming TLS handshakes. The benefit is that you can set up a TLS listener with Let's Encrypt support in about 5 lines of code (see high-level example in the docs), with certificate acquisition and renewal taken care of under the hood. This means:
a. If you need more control than adding/removing which domains you need certs for, this is not the crate to use. DNS checks are of course something you may do on your own before adding/removing domains (which isn't implemented yet).
b. If you want to keep rustls-acme separate from your regular TLS handshaking code, that's not an option either, because that isn't compatible with how the tls-alpn-01 validation procedure works.
c. If you want manual control when/how certificate acquisition/renewal is done, this isn't the right crate either, because taking that pain away is the point of the crate. Use another crate or build your own solution using the rustls_acme::acme module.
Persistent caching is done by user provided Cache trait implementations, so that is likely already solved in a way that works for you. It only assumes you can store some bytes keyed by domain and directory string in some key-value-store like a DB or a folder. Does that work for your use case?
Do you want one certificate with all domains or multiple certificates with one or a few domains each?

If you don't want to deal with certificate and rustls details, the high-level API is probably what you want. Please have a look at it and let me know if that sufficient for you if a way to add/remove domains is added.

If possible yes, some clients may want to provide their own certificates for https, bit it's clearly a nice to have and not absolutely necessary. i suppose if you inject a cert from the cache it should work ?
i'm not familiar with  tls-alpn-01 so i might be mistaken on how this works. the dashmap would simply be the cache that allows adding certificates on the fly, either by the challenge system or user provided (like a DB to store them long term)
that solves 2 for me :) i just need to know that it checks the cache every time
anything that works, i don't know all the nuances it entails.

I know it's not yet possible, but i was thinking of forking it to make it work, sounds like it should be feasible.
From what you are saying a method to add/remove a domain on the fly should be all i need.

If possible yes, some clients may want to provide their own certificates for https, bit it's clearly a nice to have and not absolutely necessary. i suppose if you inject a cert from the cache it should work ?
It's ugly, but should work. Only if you inject before starting the state management though. I'm considering implementing a pinning compatible mechanism where you can specify a cert instead of a new one being generated. That would have the side effect of covering this usecase.

i'm not familiar with  tls-alpn-01 so i might be mistaken on how this works. the dashmap would simply be the cache that allows adding certificates on the fly, either by the challenge system or user provided (like a DB to store them long term)
I don't see any overlap between how this crate works and the dashmap idea. I think there may still be some fundamental misconceptions about how this crate is used. I would recommend that you start using the crate with a fixed set of domains to figure out how the existing interface could be extended to add more domains in a convenient way.

that solves 2 for me :) i just need to know that it checks the cache every time
Currently it does when a certifcate is missing (so currently at startup), but not for renewals.

anything that works, i don't know all the nuances it entails.

I know it's not yet possible, but i was thinking of forking it to make it work, sounds like it should be feasible. From what you are saying a method to add/remove a domain on the fly should be all i need.
Not quite. You would have to touch multiple places. Most importantly the underlying state machine has to be generalized to mutliple sets of certificates if you want to be able to scale beyond 100 domains.

I suspect that this will become possible quite soon by using the lower level API and simply running multiple instances of rustls_acme::AcmeState as issue #46 is resolved. Then you would simply receive the "client hello" yourself, and fetch the certificate from the respective resolver yourself.

I started reworking the crate pretty fundamentally based around a new ResolvesServerCert implementation.
I already added multi certificate support and x509 based domain verification (so there is no need to save anything but the certificates)
I also did a few refactors, do you want me to keep them in my PR or should i just keep to the new implementation ?

with the latest push it is now pretty much ready, StreamlinedResolver::new_with_updater can be given directly as the certificate provider for rustls, and existing pems can be added to it. The updater can be driven from anywhere.


feat(linter) add fixer to no-redundant-roles

#5146  👈
main

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Re-order Build Tasks to Publish to the Ballerina Central

Purpose
$subject.

LGTM

Also, shall put the else clause for if (ballerinaCentralAccessToken != null) { in ballerinaPublish? @Bhashinee


Perform Helm logout after pulling and pushing

The Helm credentials of the source are still present at the time of logging into the destination registry. This causes 403 errors when pushing to the destination. Hence we perform logout from the appropriate registry after pull/push.
By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

/lgtm
/approve

/override eks-anywhere-attribution-files-presubmit
/override eks-anywhere-e2e-presubmit
/override eks-anywhere-mocks-presubmits
/override eks-anywhere-presubmit

/cherrypick release-0.12


Reinitiate workflow

A rejected approval workflow allows the owner to modify it and reinitiate approval

@gzusgw there is comments to collaborate around that discussion. They don't need to reject? why we need this option

@harshach  In my understanding, the mention that collaboration brings to each other is less direct than bringing each other a task. For a user, seeing a task to be processed may be prioritized.


added new site for explore country data in charts

name: feat: Globe Graph
about: Globe Graph is a web app that visualizes the countries data like GDP, GDP per capita, and population in different years using many charts.
labels: feature

Describe the awesome thing you want to add
What is it?
Globe Graph is a web app that visualizes the countries data like GDP, GDP per capita, and population in different years using many charts.
What category does it belong to? (Libs and Components, Apps, Ports, Design System, Boilerplates/Templates)
Apps
Anything else? (optional) (e.g. screenshots, additional information, etc.)
Checklist

[✔] I checked that it is in alphabetical order.
[✔] I have checked that the awesome thing is not already listed.
[✔] I have provided a clear and concise description of the awesome thing.
[✔] I have provided a link to the awesome thing.
[✔] I have assigned the correct category to the awesome thing.

Please note: If you are adding a new category, you will need to create a new section in the README.md file. Please make sure to update the table of contents as well.
Important: The idea of this repository is to bring together free projects for open-source contributions. If the proposed addition is an entirely paid project, the PR will be closed.

ngl recommend u to keep the name in small-case i.e country-data-in-charts

ngl recommend u to keep the name in small-case i.e country-data-in-charts

Do you mean the name of site or here for docs?

ngl recommend u to keep the name in small-case i.e country-data-in-charts

Do you mean the name of site or here for docs?

i mean over here..

country-data-in-charts - Globe graph is a web app that visualizes the countries data like GDP, GDP per capita, and population in different years using many charts.
keep this..

and @Virous77 your graph is starting from 2023 and going to the start date.. shouldn't it start from the start date and go till 2023?

@avalynndev I have added default from 2010- to 2024. You can select years and country as per your need. Also It should always show the latest data first thats why when we show data it like TO-FROM.

@avalynndev I have added default from 2010- to 2024. You can select years and country as per your need. Also It should always show the latest data first thats why when we show data it like TO-FROM.

great work.. im still studying and this website is loved by my teacher.. thx for this project

country-data-in-charts - Globe graph is a web app that visualizes the countries data like GDP, GDP per capita, and population in different years using many charts.

keep this in the readme..

@birobirobiro  it's done.


Mem (GB) difference between pascal_voc and coco for the same model?

why Mem (GB) needed of the same model for different datasets(eg: pascal_voc and coco) are so different?

coco use larger batch size

For SSD, the main difference is the batch size and num of gt bboxes. And for two-stage detectors, the default image scale is not the same for two datasets, and the number of gt bboxes also leads to different memory.


Existing classes are removed when v-animate is applied

Fix: Append .animate instead of replace.

b07ab33


Automatically bootstrap ginkgo as a part of generate target

Ginkgo tests require each tested package to be bootstrapped to run.
This patch makes the bootstrapping available in makefile's generate
target (which is safe automatically in commit hook).
The nature of this approach causes multiple new files - these indicate
packages that were not really tested by ginkgo. On the other hand,
when adding tests for those packages, we are not required to bootstrap
them anymore.
Signed-off-by: Martin Polednik<EMAIL_ADDRESS>

The objective is not really improving the current suite, but making sure if/when new packages are added or current packages are split, we don't forget to bootstrap ginkgo within them (otherwise, they'll be left out of testing). Ran into the issue myself in previous PR, would prefer to have it done automatically.

@rmohr this is probably something you should weigh in on.

Pushed the arg removal, the decision is up to you all. Also note that the generation isn't perfect - it would be nice to have some kind of go package introspection to really only call it in directories where it's needed.

While I would prefer, that the suits are only added, if there is a tests file which needs it, or there would be some kind of check which makes travis fail, I like that it eliminates the mentioned errors. I also found some disabled tests a few days ago, because accidentally such a suit file was removed.

ok to test

OK to test

testing this again.

@mpolednik could you rebase? Sorry for letting that hang so long in approved state.

retest this please


Update huawei.rst - Examples - Draft v0.1

Description

This is the initial (draft) version of the Huawei examples.  As per comments at the top of the file, additional derived sensors are required to be created, for which these yaml files are being verified and will either need to be pasted in here (or a repository with them created and a link provided)

Related issues

Motivation and Context

Add examples to support Huawei users
How has this been tested

Testing on dual M1 instance and dual L1 with Battery instance

Type of change
Please delete options that are not relevant.

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

Checklist

[X] My code follows the style guidelines of this project
[X] I have performed a self-review of my code
[X] I have commented my code, particularly in hard-to-understand areas
[X] I have made corresponding changes to the documentation
[X] My changes generate no new warnings
[x] Any dependent changes have been merged and published in downstream modules
[x] I have updated the version in package.json following semver

@slipx06 Could you please review / approve. Thanks.


Roll down beta to main

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you all sign our Contributor License Agreement before we can accept your contribution.8 out of 9 committers have signed the CLA.:white_check_mark: greens:white_check_mark: ctowns:white_check_mark: NoahCornell:white_check_mark: tandres:white_check_mark: linus2017:white_check_mark: cjswedes:white_check_mark: dljsjr:white_check_mark: heoyslscomm:x: varzacYou have signed the CLA already but the status is still pending? Let us recheck it.


getAccessToken always rejects with "NO_ACTIVITY" since 0.6.0

Since 0.6.0, getAccessToken stopped working reliably.
getAccessToken is dependent on the current Activity. getCurrentActivity seems to always return null on app start. When the app has been resumed (after being paused), getCurrentActivity seems to return an Activity. Am I doing something wrong?
I tried passing a WeakReference of this from MainActivity to RNGoogleSigninModule (via RNGoogleSigninPackage) to use as a fallback when getCurrentActivity returns null, and everything seems to work fine. This was how it was done (without using WeakReference) prior to 0.6.0.

It should be noted that I don't use getAccessToken explicitly, but implictly within signIn().
If I call NativeModules.RNGoogleSignin.getAccessToken() after I have gotten the response from signIn(), the accessToken is returned.
This works:
GoogleSignin.signIn()
        .then(async (response) => {
          return await NativeModules.RNGoogleSignin.getAccessToken(response);
        })

This doesn't:
GoogleSignin.signIn()
        .then((response) => {
          return response.accessToken;
        })

There seems to be a race condition here. I guess we're not back to the react-native activity when getAccessToken is called.

yes this is correct the activity seems not to be active when we come back from the authentification flow.
thanks for catching this. I push the fix right away.

Great, thanks!
My working example (with nested promises) doesn't seem to work consistently either, so it was a bad example.

v0.6.1 is the fix ; )

This works!
Thanks a lot! This is the quickest fix I've ever seen. Great work!


New version: Microsoft.PowerShell version 7.4.5

Pull request has been created with komac v2.3.0 :rocket:
Microsoft Reviewers: Open in CodeFlow

Hi @anamnavi,
Do you approve of these changes?
(Automated response - build 887.)

@stephengillie no, could we take this PR for <IP_ADDRESS> instead: https://github.com/microsoft/winget-pkgs/pull/168424
In addition to the reason you mention, this PR adds x86 msi for arm which is not correct for us.

Close with reason: Duplicate of #168424;


DM groups?

I cannot seem to find support for sending a direct message into a group via conversation id. Would appreciate an implementation of this or solution if possible.
Thanks

Thanks for the question, from what I remember groups were just defined as the concatenation of each user ID in the group, separated by -, so you would call account.dm('hello', receivers=[123,456,789]). I'll check back and see if this is still the case next time I run my tests.


[FLINK-2675] [streaming] Integrate Timer Service with StreamTask

This integrates the timer as a service in StreamTask that
StreamOperators can use by calling a method on the
StreamingRuntimeContext.
This also ensures that the timer callbacks can not be called
concurrently with other methods on the StreamOperator. This behaviour is
ensured by an ITCase.

@StephanEwen, I removed the special handling of exceptions in the ProcessingTimeWindows operator since this is now handled in a generic way by the stream tasks.

Not the expert on this, but the changes look good. Had some minor comments. The tests look very good. :)

I addressed your comments. I also ran five travis builds overnight and none of them failed so this should be good to merge.
@StephanEwen Could you please have a look at how I moved the exception handling from your WindowingOperators to the StreamTasks. We should be damn sure this is correct. :smile:
Other than that, I would merge this later today.

I think this is good.
In the long run, I would like to change that all functionality is currently pushed into the StreamRuntimeContext (it gets overloaded and exposes concepts to user functions that we may not want to expose), but that is a separate issue not blocking this pull request.

Merging this...


Update README.md

can you write readme.md and give me some information about this

updating @Another-A-Boo


Native Kafka ProducerConfig (like: client.id) support has been added

Now key-value pairs under spring.cloud.stream.kafka.bindings.< channelName >.producer.config key are set as native Kafka producer configuration.
This is useful because this way we can configure all Kafka specific producer configuration values through application properties.

Hi @urgelacko,
Did you sign the contributor agreement (https://support.springsource.com/spring_committer_signup) ? Thank you.

Planning to address this as part of 1.1.0.M1 as we will have more flexibility with the Spring Integration Kafka 2.0 support.

I have signed the agreement now. Sorry for missing it first time.
As I see the merge request is in conflict state now. Should I resolve the conflicts or if these kind of missing parts are in the next version it is useless and we should just wait for the official solution?

Hi Laszlo - no problem! Thanks for the contribution! I would advise waiting for the next version, and I've created https://github.com/spring-cloud/spring-cloud-stream/issues/531 to track this.

Thanks a lot we are waiting for it :)

You're welcome - I will close this then in favour of the issue.


Tasks 535-564 naming

I noticed tasks 535-564 are from ALT dataset but they have been named task*_spl_*. They should be renamed to task*_alt_*.

Addressed in https://github.com/allenai/natural-instructions-expansion/pull/587


Allow rules to be bound to specific phase(s)

Please make other rules configurable in the same way the RequireFilesExist rule can be configured to be triggered by specific phases.

Related to #10


No crosshair / current position

I got the map added to my dashboard running with Grafana v4.3.2 (commit: ed4d170)
The map displays the values from the geohash as a track, and when I restrict the time beeing displayed, I see that the map shows the correct location(s).
However when I move the synchronized cross-hairs around, I see them in all panels, except the map.
Any advice?

Not really. That works for me - maybe something has changed in Grafana?
The relevant code is at https://github.com/tkurki/grafana-track-map/blob/master/src/clock_ctrl.js#L24


README: update links to PHPUnit docs

As PHPUnit 11.0 has been released, the main branch of the PHPUnit docs now points to the PHPUnit 11.0 documentation, while the last 2.x release of the Polyfills supports PHPUnit 5.x - 10.x.
This commit updates the links in the README to point explicitly to the PHPUnit 10.5 documentation.
PHPUnit 11.0 support will be handled in a new major of the Polyfills and the links should be updated (again) to point to the PHPUnit 11.0 documentation in the branch containing that major.

coverage: 95.846%. remained the same
when pulling 199bd093c3fb47360aac977663ca0036e2c52445 on feature/2.x/readme-updates
into eb2db842dbf61f74f074a513201d5c574cc90db7 on 2.x.


Scene should be renamed to MetaData

Scene is an ambiguous word, so it's better to clarify.
In addition, I propose two changes

Blend and Observation have metadata members instead of being derived from Scene
Blend.match() happens during initialization to avoid ambiguity of who's responsible for calling it.

This makes sense to me, except I'm not sure what you mean by Blend.match. Blend doesn't have a match method but calls observation.match for each observation it is passed.

Sorry, I misspoke. However, the match function should be called at init time given the metadata of Blend. This makes for a more logical way of specifying stuff for the users

Isn't that what it does? https://github.com/fred3m/scarlet/blob/master/scarlet/blend.py#L25-L42

sure, this is merely to clarify the terminology. once done we need to update the docs, too.


Resource collect

Robots are now able to collect resources if they have the collectable property / added blocks for main and event (only log the code inside their context right now)

Thanks, should have noticed that...


rkt api service: Still seeing  "already locked" errors

Trying kube-up with rkt (v0.15.0 release) as container runtime on gce. Still see errors:
kube-system   6m          1m         28        fluentd-cloud-logging-kubernetes-minion-sc9u                  Pod                     spec.containers{fluentd-cloud-logging}     InspectFailed           {kubelet kubernetes-minion-sc9u}      Failed to inspect image "gcr.io/google_containers/fluentd-gcp:1.14": couldn't list images: rpc error: code = 2 desc = "file \"/var/lib/rkt/cas/db/.f630cc97640448d8f823924a7df3ca00e4d9e53b\" already locked"

More logs
-- Logs begin at Sat 2016-01-16 01:45:18 UTC, end at Sat 2016-01-16 02:07:18 UTC. --
Jan 16 01:45:41 kubernetes-minion-sc9u systemd[1]: Started Start rkt API service as Daemon.
Jan 16 01:45:41 kubernetes-minion-sc9u rkt[1159]: 2016/01/16 01:45:41 API service starting...
Jan 16 01:45:41 kubernetes-minion-sc9u systemd[1]: Started Start rkt API service as Daemon.
Jan 16 01:45:41 kubernetes-minion-sc9u rkt[1159]: 2016/01/16 01:45:41 API service running on localhost:15441...
Jan 16 01:50:46 kubernetes-minion-sc9u rkt[1159]: 2016/01/16 01:50:46 Failed to get ACI info for image ID "sha512-9abe60da0597010d5e003cfff11a51c4e57daf563c38077cb21b117fee31e650": ACI info not found with blob key "sha512-9abe60da0597010d5e003cfff11a51c4e57daf563c38077cb21b117fee31e650"
Jan 16 01:50:46 kubernetes-minion-sc9u rkt[1159]: 2016/01/16 01:50:46 Failed to get ACI info for image ID "sha512-c6ccc225f4ecf74d228512072582c8a619452b03fd9966f74a95d5e8f3f1953b": ACI info not found with blob key "sha512-c6ccc225f4ecf74d228512072582c8a619452b03fd9966f74a95d5e8f3f1953b"
Jan 16 01:50:46 kubernetes-minion-sc9u rkt[1159]: 2016/01/16 01:50:46 Failed to get ACI info for image ID "sha512-f199f46b8269404ac1eaddf3bc54dd84720aad6a67a655d96f6aef1c69b9fe7e": ACI info not found with blob key "sha512-f199f46b8269404ac1eaddf3bc54dd84720aad6a67a655d96f6aef1c69b9fe7e"
Jan 16 01:50:46 kubernetes-minion-sc9u rkt[1159]: 2016/01/16 01:50:46 Failed to get ACI info for image ID "sha512-c6ccc225f4ecf74d228512072582c8a619452b03fd9966f74a95d5e8f3f1953b": ACI info not found with blob key "sha512-c6ccc225f4ecf74d228512072582c8a619452b03fd9966f74a95d5e8f3f1953b"
Jan 16 01:50:46 kubernetes-minion-sc9u rkt[1159]: 2016/01/16 01:50:46 Failed to get ACI info for image ID "sha512-7af32f9fe0105cb5d4ebaaba437a5da471bc973646db0601e75c60e32cad97ac": ACI info not found with blob key "sha512-7af32f9fe0105cb5d4ebaaba437a5da471bc973646db0601e75c60e32cad97ac"
Jan 16 01:50:46 kubernetes-minion-sc9u rkt[1159]: 2016/01/16 01:50:46 Failed to get ACI info for image ID "sha512-f199f46b8269404ac1eaddf3bc54dd84720aad6a67a655d96f6aef1c69b9fe7e": ACI info not found with blob key "sha512-f199f46b8269404ac1eaddf3bc54dd84720aad6a67a655d96f6aef1c69b9fe7e"
Jan 16 01:50:46 kubernetes-minion-sc9u rkt[1159]: 2016/01/16 01:50:46 Failed to get ACI info for image ID "sha512-7af32f9fe0105cb5d4ebaaba437a5da471bc973646db0601e75c60e32cad97ac": ACI info not found with blob key "sha512-7af32f9fe0105cb5d4ebaaba437a5da471bc973646db0601e75c60e32cad97ac"
Jan 16 01:50:46 kubernetes-minion-sc9u rkt[1159]: 2016/01/16 01:50:46 Failed to get ACI info for image ID "sha512-9abe60da0597010d5e003cfff11a51c4e57daf563c38077cb21b117fee31e650": ACI info not found with blob key "sha512-9abe60da0597010d5e003cfff11a51c4e57daf563c38077cb21b117fee31e650"
Jan 16 01:50:46 kubernetes-minion-sc9u rkt[1159]: 2016/01/16 01:50:46 Failed to get ACI info for image ID "sha512-c6ccc225f4ecf74d228512072582c8a619452b03fd9966f74a95d5e8f3f1953b": ACI info not found with blob key "sha512-c6ccc225f4ecf74d228512072582c8a619452b03fd9966f74a95d5e8f3f1953b"
Jan 16 01:50:46 kubernetes-minion-sc9u rkt[1159]: 2016/01/16 01:50:46 Failed to get ACI info for image ID "sha512-f199f46b8269404ac1eaddf3bc54dd84720aad6a67a655d96f6aef1c69b9fe7e": ACI info not found with blob key "sha512-f199f46b8269404ac1eaddf3bc54dd84720aad6a67a655d96f6aef1c69b9fe7e"
Jan 16 01:50:46 kubernetes-minion-sc9u rkt[1159]: 2016/01/16 01:50:46 Failed to get ACI info for image ID "sha512-7af32f9fe0105cb5d4ebaaba437a5da471bc973646db0601e75c60e32cad97ac": ACI info not found with blob key "sha512-7af32f9fe0105cb5d4ebaaba437a5da471bc973646db0601e75c60e32cad97ac"
Jan 16 01:50:46 kubernetes-minion-sc9u rkt[1159]: 2016/01/16 01:50:46 Failed to get all ACI infos: file "/var/lib/rkt/cas/db/.f630cc97640448d8f823924a7df3ca00e4d9e53b" already locked
Jan 16 01:50:48 kubernetes-minion-sc9u rkt[1159]: 2016/01/16 01:50:48 Failed to get ACI info for image ID "sha512-9abe60da0597010d5e003cfff11a51c4e57daf563c38077cb21b117fee31e650": ACI info not found with blob key "sha512-9abe60da0597010d5e003cfff11a51c4e57daf563c38077cb21b117fee31e650"

Debugging this. Not sure the reason. Currently rktnetes only uses rkt release binary. I need to make it to use some binary compiled from master for debugging purpose.

I remember getting that error (file "/var/lib/rkt/cas/db/.f630cc97640448d8f823924a7df3ca00e4d9e53b" already locked)  occasionally. When it happened, running rkt again fixed the issue...
cc @sgotti

Getting more details by adding a few logs. The errors comes from db.Begin()[1]:
-- Logs begin at Fri 2016-01-22 17:44:34 UTC, end at Fri 2016-01-22 17:50:16 UTC. --
Jan 22 17:44:57 yifan-rkt-minion-armf systemd[1]: Started Start rkt API service as Daemon.
Jan 22 17:44:57 yifan-rkt-minion-armf rkt[1157]: 2016/01/22 17:44:57 API service starting...
Jan 22 17:44:57 yifan-rkt-minion-armf systemd[1]: Started Start rkt API service as Daemon.
Jan 22 17:44:57 yifan-rkt-minion-armf rkt[1157]: 2016/01/22 17:44:57 API service running on localhost:15441...
Jan 22 17:48:05 yifan-rkt-minion-armf rkt[1157]: 2016/01/22 17:48:05 Failed to resolve the image ID "sha512-4028ff6849a22b674e49608d1cfdc110055fe184577c691e41e5e412c83e297d": error retrieving ACI Infos: db dotx error: db begin error: resource temporarily unavailable
Jan 22 17:48:05 yifan-rkt-minion-armf rkt[1157]: 2016/01/22 17:48:05 Failed to resolve the image ID "sha512-4028ff6849a22b674e49608d1cfdc110055fe184577c691e41e5e412c83e297d": error retrieving ACI Infos: db dotx error: db begin error: file "/var/lib/rkt/cas/db/.f630cc97640448d8f823924a7df3ca00e4d9e53b" already locked

[1] https://github.com/coreos/rkt/blob/v0.16.0/store/db.go#L137

Ref https://github.com/cznic/ql/issues/69

Got more information:
The error comes from
https://github.com/cznic/ql/blob/master/file.go#L391
Which invokes https://github.com/camlistore/lock/blob/master/lock_linux_amd64.go#L35
I read the function above, it seems when there is an error in acquiring the lock(https://github.com/camlistore/lock/blob/master/lock_linux_amd64.go#L74) the in-memory lock. Besides, as the function returns nil, error, there is no way for the caller to close the lock to release the in-memory lock, thus cause the deadlock we met here.

Filed an issue https://github.com/camlistore/lock/issues/12

Also https://github.com/camlistore/go4/pull/7 and https://github.com/camlistore/go4/pull/8

the lock package in camlistore is fixed, waiting https://github.com/cznic/ql/pull/117 to be merged and then we need to update the godep to close this.


Add 'Create a Log Analytics workspace' example

This issue is stale because it has been open 170 days with no activity. Remove stale label or comment or this will be closed in 10 days

See #209


WSL2 Issues with VPNs (Viscosity)

Your Windows build number:  2004 (BUILD 19033.1)

What you're doing and what's happening:  Using Ubuntu with VSCode, everything works as intended. Connect to a work VPN via Viscosity, everything in Windows works as expected (can access sites both on work network and off), Ubuntu cannot reach any internet locations. Checking Network Connections shows that the vEthernet adapter is unplugged. Cannot resolve this without restarting the machine.

What's wrong / what should be happening instead: Expect WSL2 instance to be able to reach VPN network resources as before (builds 19030 worked, as did 19025)

Not a lot of information to post, as there isn't really an error, the network connection just thinks it isn't connected anymore. Submitted to feedback hub as well, but figured I'd post here in-case others had seen problems with this.

Of note- if you connect to the VPN before starting Ubuntu- everything works as intended. It's only an issue if you connect WHILE Ubuntu is running (or has been run, I haven't seemed to have luck trying to trick it by running wsl -t ubuntu before connecting the VPN).


Sense mapping (twsi_evaluation)

I've noticed that the sense mapping between a custom inventory and TWSI inventory is saved to a file with unique name bound to file name of custom inventory.
The script could check for existence of such a file and load mapping instead of computing them anew. It would be a great improvement for multiple evaluations with the same inventory, cause mapping often takes more time then predictions evaluation itself.
Possible drawbacks are:

Mapping files pile up, get forgotten and take too much space
By chance two different custom inventories with the same name are used at different times -> old mapping taken instead of a new one
Alternative solution:
optional parameter for a path to a mapping file?

I would be happy to learn your opinion about it.

Personally, I didn't see this as a top priority, but indeed as a nice feature to have. Therefore, I cannot implement it myself in the following time, but if you eager to contribute please go for it. As to the solution, I think you can just save the mapping file next to the input sense inventory and during start of the program just check its existence.


Operations on signal tracks

As a reminder, once Anton's PR is merged we should see how/whether to implement operations with signal tracks, such as average profiles, at least as an example notebook at first.

Do you intend to represent signal tracks as run length encodings?


What software to use to simulate workloads

I read your paper PBScaler: A Bottleneck-aware Autoscaling Framework for Microservice-based Applications. I was impressed by your innovation and I am very interested. I would like to ask you what software you are using to simulate workflow loads.
I've acquired the Wikipedia workload from the Wiki-Pageviews, a GZ file. But I don't know how to use it.
Thank you for your help.

I read your paper PBScaler: A Bottleneck-aware Autoscaling Framework for Microservice-based Applications. I was impressed by your innovation and I am very interested. I would like to ask you what software you are using to simulate workflow loads. I've acquired the Wikipedia workload from the Wiki-Pageviews, a GZ file. But I don't know how to use it. Thank you for your help.

Sorry, I just saw this issue. I use locust to simulate workflow loads.

I read your paper PBScaler: A Bottleneck-aware Autoscaling Framework for Microservice-based Applications. I was impressed by your innovation and I am very interested. I would like to ask you what software you are using to simulate workflow loads. I've acquired the Wikipedia workload from the Wiki-Pageviews, a GZ file. But I don't know how to use it. Thank you for your help.

Sorry, I just saw this issue. I use locust to simulate workflow loads.


npm updates

Coverage remained the same at 100.0% when pulling 69e50dee84f064cebb80c199bd4bf399a2e22ae1 on proto into 8ad5cd1542b162481a6f29cc5d5fd93ffc3dda11 on main.


A creation-time is mandatory for datasets, and this is not made clear to people

Summary generation throws an exception if datasets are missing a creation time (by default: 'creation_dt' in the yaml)
This has confused a few people, as some datacube guides don't include the field in metadata.
We need to either make it clear why it's failing (a firendly error message?), or else make the field optional in cubedash.

Should be fixed in #196. It now falls back to the indexed time of the dataset.


Doesn't work with phpunit installed from composer

If you use composer and composer's autoloader, then soft-mocks can't rewrite composer auto loader.
It happens, because command phpunit requre's composer auto loader, see https://github.com/sebastianbergmann/phpunit/blob/5.6/phpunit.
For fix it, you can add custom phpunit command, for example:
#!/usr/bin/env php
<?php
if (version_compare('5.6.0', PHP_VERSION, '>')) {
    fwrite(
        STDERR,
        'This version of PHPUnit requires PHP 5.6; using the latest version of PHP is highly recommended.' . PHP_EOL
    );
    die(1);
}

if (!ini_get('date.timezone')) {
    ini_set('date.timezone', 'UTC');
}

// soft-mocks bootstrap
require_once dirname(__DIR__) .'/src/bootstrap.php';
\QA\SoftMocks::setPhpunitPath('/vendor/phpunit/');

// require composer autoloader
define('PHPUNIT_COMPOSER_INSTALL', \QA\SoftMocks::rewrite(dirname(dirname(__DIR__)) . '/autoload.php'));
require_once \QA\SoftMocks::rewrite(dirname(dirname(__DIR__)) . '/autoload.php');

PHPUnit_TextUI_Command::main();

Please, add this command and/or update documentation.

Also https://github.com/sebastianbergmann/phpunit/pull/2116

@mougrim maybe close this?

Yes, it's fixed now.


Change CSS to fix long text in MudSelectList

Edit CSS to solve issue #2477
It should be checked if other components would benefit from this too.

Is this ready to be merged? Can you post a screenshot, before and after?

Before and after are posted in the issue.
This can be merged, yes.

Looks good, question does autocomplete suffer from this as well?

Thanks!


Manual linking for RN 0.59

Hi Andrej, thanks for this!
Are you planning to add instructions for manual linking? Would love to help out but unfortunately wouldn't even know where to start 😅

Hey @mezod
Sorry for the delay, was busy with ... everything else.
Since iOS 13 is out, I am back to this.
Will def add instructions on manual linking but I am working on even more seamless integration with latest React Native!
If you have any question, issue them here so that we can resolve them and those answers could become the instructions you are looking for!


AltGr not working on linux terminal ubuntu18.04

Environment
Windows build number: Microsoft Windows [Version 10.0.18362.175]
Windows Terminal version (if applicable): windows terminal (Preview) 0.2.1715.0

Any other software?

Steps to reproduce
Create a Ubuntu 18 tab
type $ or any sign that can be created with AltGr

Expected behavior
we must see $ sign with AltGr+4
Actual behavior
nothing happens

The same happens in PowerShell tabs

Same behavior in all tabs (Pwsh, Powershell, Cmd and Ubuntu) with Swedish keyboard layout.
Valid for all characters that need "Alt Gr"

Seems to me like duplicate of #521


Hide default date selected in first time

Please, is there any way to hide date in input datetimepicker before opening it the first time.
Thank you

http://eonasdan.github.io/bootstrap-datetimepicker/Options/#usecurrent
set useCurrent: false
This is a how to question, so will be closed


Support laravel 8

https://github.com/phpsa/filament-password-reveal/blob/a1617d164bc947d49581578c59aa581f10082da1/src/Password.php#L62
Maybe we can have a condition like this
if(app()->version() == 8.0.0){
        return Str::of($this->getId())->replace(".", "_")->prepend('input_')->studly()->snake()->toHtmlString();
}
        return Str::of($this->getId())->replace(".", "_")->prepend('input_')->studly()->snake()->toString();

Would accept a PR for this

Actually fixed in 1.1.3


Shared services limited to TRE admin in API and UI

Resolves issue #2236

API GET for shared-services is secured to TRE admins only
Link in left nav of UI is limited to TRE Admins
Shared services page and shared service item page both secured by role to TRE admins to prevent the user following a saved link and seeing a page full of errors.

@damoodamoo does this still allow researchers to see summary info around the shared service?

Are you able to share how this API will be used in conjunction with the new API?
e.g. how will the UI (or a user of the API) decide which API endpoint to call?

/test-force-approve
all Api stuff removed from PR


Feature/upload example

🤔 这个 PR 的性质是？

[ ] 日常 bug 修复
[ ] 新特性提交
[ ] 文档改进
[x] 演示代码改进
[ ] 组件样式/交互改进
[ ] CI/CD 改进
[ ] 重构
[ ] 代码风格优化
[ ] 测试用例
[ ] 分支合并
[ ] 其他

🔗 相关 Issue

💡 需求背景和解决方案

📝 更新日志

根据UI稿完善 upload 组件示例。

fix(组件名称): upload

[ ] 本条 PR 不需要纳入 Changelog

☑ 请求合并前的自查清单
⚠ 请自检并全部勾选全部选项。⚠

[ ] 文档已补充或无须补充
[ ] 代码演示已提供或无须提供
[ ] TypeScript 定义已补充或无须补充
[ ] Changelog 已提供或无须提供

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make it even more asynchronous

This change makes afatfs_poll() an internal static function, and everything else works (almost) as before.
The one difference is that callbacks may be called directly from the routine where it was provided, even before the routine returns. E.g. the callback for "unlink complete" may be called before afatfs_funlink() returns.

My concern with this approach is that if the sdcard read/write primitives are implemented synchronously (i.e. they call the completion callback before returning), this will cause asyncfatfs to re-enter afatfs_poll(). This will lead to it performing an unbounded amount of work (particularly at card init when writing the freefile) and using an unbounded amount of stacksize, neither of which can be tolerated.
Synchronous read/write SD card primitives are a common choice when DMA is not available.

My concern with this approach is that if the sdcard read/write primitives are implemented synchronously (i.e. they call the completion callback before returning), this will cause asyncfatfs to re-enter afatfs_poll(). This will lead to it performing an unbounded amount of work (particularly at card init when writing the freefile) and using an unbounded amount of stacksize, neither of which can be tolerated.
Synchronous read/write SD card primitives are a common choice when DMA is not available.

Yes, I understand your concern. I had some thoughts about putting ifdefs around these changes since they are rather experimental, and some major disclaimers

I reworked the changes so the feature can be enabled at compile time, and also updated the readme file :smiley_cat:
@thenickdude, do you think this feature is useful for AsyncFS?


Support @NotNull annotation in form binding

Describe your motivation
Suppose i have a entity class that has some child object associated with JPA annotations (@OneToOne, @ManyToOne) like this:
public class Pet extends IdEntity {
    @NotEmpty(message = "Cannot be empty")
    private String name;

    @ManyToOne
    private Fence fence;

   ...
}

And in a page to create i have a simple control to associate Pets to a Fence (for example a PickList or something similar)
At the moment i have not found a way to impose that to register a new Pet it must be associated to a Fence and make the association required so that if fence is null the form is invalid. For a @OneToMany association that is on a collection field i can use the @NotEmpty association and even customize the message if the collection is empty but the reverse seems impossible.
If i use the @NotNull annotation from jakarta.validation.constraints package the typescript interface for Pet requires that the fence is not null:
interface Pet {
    name: string;
    fence: Fence_1;
}

But the generated model for form bindings is missing the information that the fence is required
class PetModel<T extends Pet_1 = Pet_1> extends ObjectModel_1<T> {
    static override createEmptyValue = makeObjectEmptyValueCreator_1(PetModel);
    get name(): StringModel_1 {
        return this[_getPropertyModel_1]("name", (parent, key) => new StringModel_1(parent, key, true, { validators: [new NotEmpty_1({ message: "Cannot be empty" })], meta: { javaType: "java.lang.String" } }));
    }
    get fence(): FenceModel_1 {
        return this[_getPropertyModel_1]("fence", (parent, key) => new FenceModel_1(parent, key, true, { meta: { annotations: [{ name: "jakarta.persistence.ManyToOne" }] } }));
    }

If i add a @Nonnull annotation (for example the jakarta or spring ones that do not have a "message" field) in the generated model the 'optional' parameter is false but still there are no validators like the NotEmpty one in the name field.
Is this a bug or is it the intended behaviour (or am i doing something really wrong without realizing it)?
Describe the solution you'd like
I would like that when i write the "fence" field in the class like this:
    @NotNull(message = "Specify a fence for the pet")
    @ManyToOne
    private Fence fence;

In the generated model the field is generated like this:
    get fence(): FenceModel_1 {
        return this[_getPropertyModel_1]("fence", (parent, key) => new FenceModel_1(parent, key, true, { validators: [new NotEmpty_1({ message: "Specify a fence for the pet" })], meta: { annotations: [{ name: "jakarta.persistence.ManyToOne" }, {}] } }));
    }

Describe alternatives you've considered
As i've said in the motivation section i've tried adding some `@Nonnull' annotation, in particular i've tried:

jakarta.validation.constraints.NotNull
jakarta.annotation.Nonnull
org.springframework.lang.NonNull

Additional context
Maybe there could be hope that to define a field nullability, instead of any 'nonnull' (case insensitive) annotation, to define a field that cannot be null hilla could switch to using jakarta.validation.constraints.NotNull (maybe adding a commodity one like dev.hilla.NotNull for generic types) to conform more to the Jakarta Bean Validation specification?

Let's investigate if we have a bug in this case.

What I observe is that having a @NotNull on a relation property (e.g. marked with @ManyToOne) doesn't generate a validation in the TS model for that property.
As an example, I have a City entity with a name property, and a Country property (a @ManyToOne relation). The generated TS model for City is:
class CityModel<T extends City_1 = City_1> extends AbstractEntityModel_1<T> {
    static override createEmptyValue = makeObjectEmptyValueCreator_1(CityModel);
    get name(): StringModel_1 {
        return this[_getPropertyModel_1]("name", (parent, key) => new StringModel_1(parent, key, true, { validators: [new NotEmpty_1()], meta: { javaType: "java.lang.String" } }));
    }
    get country(): CountryModel_1 {
        return this[_getPropertyModel_1]("country", (parent, key) => new CountryModel_1(parent, key, true, { meta: { annotations: [{ name: "jakarta.persistence.ManyToOne" }] } }));
    }
}

Which is clearly missing a validator for the Country being not null.
I believe this is a bug (maybe a regression), rather than an enhancement.


TensorFlow upgrade to 1.0.0 breaking import

On the Mac OS X El Capitan V 10.11.6 using python 2.7.11 with anaconda
when I run this code:
pip install https://storage.googleapis.com/tensorflow/mac/tensorflow-0.9.0-py2-none-any.whl
I get a working version of tensorflow 0.9.0. import tensorflow in python throws no errors.
I type in the command:
pip install --upgrade tensorflow
I get a successful install
Collecting tensorflow
  Using cached tensorflow-1.0.0-cp27-cp27m-macosx_10_11_x86_64.whl
Requirement already up-to-date: mock>=2.0.0 in ./anaconda/lib/python2.7/site-packages (from tensorflow)
Requirement already up-to-date: six>=1.10.0 in ./anaconda/lib/python2.7/site-packages (from tensorflow)
Requirement already up-to-date: numpy>=1.11.0 in ./anaconda/lib/python2.7/site-packages (from tensorflow)
Collecting protobuf>=3.1.0 (from tensorflow)
  Using cached protobuf-3.2.0-py2.py3-none-any.whl
Requirement already up-to-date: wheel in ./anaconda/lib/python2.7/site-packages (from tensorflow)
Requirement already up-to-date: funcsigs>=1; python_version < "3.3" in ./anaconda/lib/python2.7/site-packages (from mock>=2.0.0->tensorflow)
Requirement already up-to-date: pbr>=0.11 in ./anaconda/lib/python2.7/site-packages (from mock>=2.0.0->tensorflow)
Requirement already up-to-date: setuptools in ./anaconda/lib/python2.7/site-packages (from protobuf>=3.1.0->tensorflow)
Requirement already up-to-date: appdirs>=1.4.0 in ./anaconda/lib/python2.7/site-packages (from setuptools->protobuf>=3.1.0->tensorflow)
Requirement already up-to-date: packaging>=16.8 in ./anaconda/lib/python2.7/site-packages (from setuptools->protobuf>=3.1.0->tensorflow)
Requirement already up-to-date: pyparsing in ./anaconda/lib/python2.7/site-packages (from packaging>=16.8->setuptools->protobuf>=3.1.0->tensorflow)
Installing collected packages: protobuf, tensorflow
  Found existing installation: protobuf 3.0.0b2
    Uninstalling protobuf-3.0.0b2:
      Successfully uninstalled protobuf-3.0.0b2
  Found existing installation: tensorflow 0.9.0
    Uninstalling tensorflow-0.9.0:
      Successfully uninstalled tensorflow-0.9.0
Successfully installed protobuf-3.2.0 tensorflow-1.0.0

and I get a broken import statement in python (.. modify dir names)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "../anaconda/lib/python2.7/site-packages/tensorflow/__init__.py", line 24, in <module>
    from tensorflow.python import *
  File "../anaconda/lib/python2.7/site-packages/tensorflow/python/__init__.py", line 124, in <module>
    from tensorflow.python.platform import test
  File "../anaconda/lib/python2.7/site-packages/tensorflow/python/platform/test.py", line 83, in <module>
    import mock                # pylint: disable=g-import-not-at-top,unused-import
  File "../anaconda/lib/python2.7/site-packages/mock/__init__.py", line 2, in <module>
    import mock.mock as _mock
  File "../anaconda/lib/python2.7/site-packages/mock/mock.py", line 71, in <module>
    _v = VersionInfo('mock').semantic_version()
  File "../anaconda/lib/python2.7/site-packages/pbr/version.py", line 460, in semantic_version
    self._semantic = self._get_version_from_pkg_resources()
  File "../anaconda/lib/python2.7/site-packages/pbr/version.py", line 447, in _get_version_from_pkg_resources
    result_string = packaging.get_version(self.package)
  File "../anaconda/lib/python2.7/site-packages/pbr/packaging.py", line 750, in get_version
    name=package_name))
Exception: Versioning for this project requires either an sdist tarball, or access to an upstream git repository. It's also possible that there is a mismatch between the package name in setup.cfg and the argument given to pbr.version.VersionInfo. Project name mock was given, but was not able to be found.

when I import again in the same interface, I get a different error which repeats if I do it anymore
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "../anaconda/lib/python2.7/site-packages/tensorflow/__init__.py", line 24, in <module>
    from tensorflow.python import *
  File "../anaconda/lib/python2.7/site-packages/tensorflow/python/__init__.py", line 72, in <module>
    raise ImportError(msg)
ImportError: Traceback (most recent call last):
  File "../anaconda/lib/python2.7/site-packages/tensorflow/python/__init__.py", line 61, in <module>
    from tensorflow.python import pywrap_tensorflow
ImportError: cannot import name pywrap_tensorflow

Failed to load the native TensorFlow runtime.

See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/g3doc/get_started/os_setup.md#import_error

for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

Same issue here.
Tried to reinstall several time using virtualenv with different settings (--no-site-packages, --system-site-packages, update packages, etc.), no difference made.
List of package versions:
adium-theme-ubuntu==0.3.4
appdirs==1.4.2
attrs==15.2.0
backports-abc==0.4
beautifulsoup4==4.4.1
blinker==1.3
certifi==2016.8.31
characteristic==14.3.0
chardet==2.3.0
command-not-found==0.3
cryptography==1.2.3
cycler==0.10.0
Cython==0.23.4
debtags==2.0
decorator==4.0.6
defer==1.0.6
dirspec==13.10
duplicity==0.7.6
enum34==1.1.2
funcsigs==1.0.2
functools32==3.2.3.post2
gevent==1.1.0
greenlet==0.4.9
h5py==2.5.0
html5lib==0.999
httplib2==0.9.1
idna==2.0
ipaddress==1.0.16
ipdb==0.10.1
ipykernel==4.2.2
ipython==4.0.3
ipython-genutils==0.1.0
ipywidgets==5.2.2
Jinja2==2.8
jsonschema==2.5.1
jupyter==1.0.0
jupyter-client==4.1.1
jupyter-console==5.0.0
jupyter-core==4.0.6
leveldb==0.193
lockfile==0.12.2
lxml==3.7.3
M2Crypto==0.22.6rc4
MarkupSafe==0.23
matplotlib==2.0.0
mistune==0.7.1
mock==2.0.0
nbconvert==4.1.0
nbformat==4.0.1
ndg-httpsclient==0.4.0
networkx==1.11
nose==1.3.7
notebook==4.1.0
numpy==1.12.0
oauthlib==1.0.3
olefile==0.44
oneconf==0.3.9
packaging==16.8
PAM==0.4.2
pandas==0.17.1
path.py==8.1.2
pbr==2.0.0
pexpect==4.2.1
pickleshare==0.6
Pillow==4.0.0
piston-mini-client==0.7.5
pkg-resources==0.0.0
prompt-toolkit==1.0.7
protobuf==3.2.0
psutil==3.4.2
ptyprocess==0.5
pyasn1==0.1.9
pyasn1-modules==0.0.7
pycrypto==2.6.1
pycups==1.9.73
Pygments==2.1
pygobject==3.20.0
PyJWT==1.3.0
pyOpenSSL==0.15.1
pyparsing==2.1.10
pyserial==3.0.1
pysqlite==2.7.0
Pyste==0.9.10
python-apt==1.1.0b1
python-dateutil==1.5
python-debian==0.1.27
python-gflags==2.0
pytz==2014.10
pyxdg==0.25
PyYAML==3.11
pyzmq==15.4.0
qtconsole==4.2.1
scikit-image==0.11.3
scikit-learn==0.18.1
scipy==0.18.1
scour==0.32
service-identity==16.0.0
simplegeneric==0.8.1
singledispatch==<IP_ADDRESS>
six==1.10.0
software-center-aptd-plugins==0.0.0
subprocess32==3.2.7
tensorflow==1.0.0
terminado==0.6
tornado==4.4.1
traitlets==4.1.0
Twisted==16.0.0
ubuntuone-client-data==14.4
unity-lens-photos==1.0
update==0.4.4
urllib3==1.13.1
virtualenv==15.0.1
wcwidth==0.1.7
widgetsnbextension==1.2.6
wxPython==<IP_ADDRESS>
wxPython-common==<IP_ADDRESS>
xlrd==1.0.0
zope.interface==4.1.3

Yeah, I wouldn't expect it to break like that if 0.9.0 works fine. Any necessary updates of packages should be handled at installation.

We test our upgrade script from 0.12 to 1.0
0.9 to 1.0 is a substantial upgrade, I don't think we did test for that.
@aselle any ideas?

Gunan,
I tried all the upgrades in between 0.10.0, 0.11.0, and 0.12.0 and they all have the same problem. 0.9.0 still works when I pip install it though.

Ah, wait now I see.
The issue is you are missing the mock library. Sorry for the confusion.
Could you try running sudo pip install mock and see if that resolves the issue for you?

I'm in macOS 10.12.3 and I have the same error. When I try to install mock it says it is already installed.

Sergio could you copy paste your full error message?
The last error can look similar, but the real error may be hidden in the
big stack trace preceeding the last import error.
On Mar 3, 2017 12:38 AM, "Sergio Díaz"<EMAIL_ADDRESS>wrote:

I'm in macOS 10.12.3 and I have the same error. When I try to install mock
it says it is already installed.
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub
https://github.com/tensorflow/tensorflow/issues/7980#issuecomment-283897212,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AHlCOWQP1VOrSCHHBsuyAl_CsXe9Zrogks5rh9GhgaJpZM4MQC1z
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No gunan, I have mock. I have used mock before in my own projects. That is not the issue. This appears to be a tensorflow issue and it seems to have appeared when tensorflow went from one version to two versions - one for the CPU and one for the GPU.

The first stack trace you have in the report is tied to mock.
The 2nd one however, is not.
Tensorflow also had one CPU and one GPU version in 0.9.0, too.
We just renamed the GPU package after 0.9 to help distinguish the pip packages for users.
And the two version thing has been working for thousands of people for months.
I am suspecting pip tool itself may be struggling to update everything correctly. Could you try first uninstalling then reinstalling tensorflow?
Also, with anaconda we see various issues. Can you try the following?
pip uninstall tensorflow
pip install --upgrade --ignore_installed tensorflow

pip install --upgrade --ignore_installed tensorflow
"--ignore_installed" solved the issue in my case. Otherwise some of the packages are using system installed ones instead of in virtual environment.
Thanks!

pip install --upgrade --ignore_installed tensorflow
should be:
pip install --upgrade --ignore-installed tensorflow
and it did not solve my issue... same error as before. But I am not using a virtual environment.

@xiaoliangbai I'm glad the issue is resolved for you.
@MikeTam1021 This is interesting. What is your Anaconda installation located?
Is it possible we need to add "sudo" to all pip commands we have?

My anaconda installation is in my home directory.. I use pip without sudo all the time, so I would imagine we do not need to use sudo. I think I am going to try to start developing in a container. I would really like to get this working though as it would speed my development time.

Sorry for all the inconvenience @MikeTam1021
We are seeing similar issues on Anaconda, I will try to find a macos machine and reproduce your setup.
Have you been using the GPU version, or the CPU version with 0.9?

I believe it is the CPU version

Got it!!!
So, I tried the virtual environment conda install. It worked (but was buggy, as noted). Then I thought "maybe this will work on my native system". It did. Now I can access tensorflow 1.0.0 from my system. Many thanks!
conda install -c conda-forge tensorflow

I encountered the same problem. I tried all the method mentioned but they did not work. How about you? @MikeTam1021

I did a conda install ningyuma. That solved it for me.

@MikeTam1021 the problem is that such solution don't install the GPU version (as it is documented here: https://www.tensorflow.org/install/install_linux

I was not installing the GPU version hfranco. Conda installed worked for me. pip install was breaking on the import statement in the REPL.

@MikeTam1021 Good approach if you are not using CUDA. The other side has the nightmare of installing tensorflow and anaconda alongside

Still facing the same problem..
i did try the all the above mentioned solution. Nothing worked for me..
tried all in "MacOS 10.12.1" and using virtual environment ...
i am installing CPU version of tensorflow.

I am also facing the issue. Tensorflow was working fine in my system, but suddenly this problem appears. I am using ubuntu 16.04 and installation is running on virtualenv. My tensorflow verson is tensorflow==1.1.0

try this
pip install -U protobuf==3.0.0b2
and in my case it solve the problem

@imanabbasnejad Thanks, it solved my problem.

export PBR_VERSION='your pbr version', it's will be worked, but i don't know why VersionInfo('mock') is wrong, maybe setup.cfg in mock has some problem.


No documentation on how to specify policies in a config file

Rasa Core version: 0.13.1
Python version: 3.6.6
Operating system (windows, osx, ...): OS X 10.14.2
Issue: There is no documentation on how to provide policies via a configuration file or how to feed this file to an Agent.
I can't figure a way to achieve this code with a configuration file:
agent = Agent('chat_domain.yml', policies = [MemoizationPolicy(), KerasPolicy()])

When I run this I get:
Exception: Passing policy configuration parameters to `agent.train(...)` is not supported anymore.

When I add a line to my chat domain, it has no effect. What is the correct thing here? I will add it to the docs if only someone will tell me. A google search hits nothing and fifteen minutes with the code yields nothing either.
Content of domain file (if used & relevant):
intents:
    - order_pizza
    - greet

entities:
    - size
    - toppings

slots:
    size:
         type: text
    toppings:
        type: text

templates:
    utter_greet:
        - 'Hello, how can I help you?'
        - 'Hi, I am here to help.'
    utter_get_pizza_size:
        - 'What pizza size?'
    utter_get_pizza_toppings:
        - 'What toppings would you like on your pizza?'
actions:
    - utter_greet
    - utter_get_pizza_size
    - utter_get_pizza_toppings
    - actions.ActionOrderPizza

policies:
    - 'KerasPolicy'
    - 'MemoizationPolicy'

@rjurney please take a look at our docs here: https://rasa.com/docs/core/policies/#configuring-polices-using-a-configuration-file

@akelad I have. That is how I know this is missing: how to actually feed policies into an Agent is not in the documentation and I can't figure it out.
First I tried this, and it throws an error that specifying policies like this is no longer supported:
agent = Agent('config/chat_domain.yml', policies = [MemoizationPolicy(), KerasPolicy()])

Note that now my domain file config/chat_domain.yaml includes:
policies:
    - 'KerasPolicy'
    - 'MemoizationPolicy'

The file has no effect and it still says:
Exception: Passing policy configuration parameters to `agent.train(...)` is not supported anymore.

@akelad What am I missing in the documentation that addresses this problem?

If you really want to pass your yaml file to the polices, you have to use the config.load function first, like it's done here https://github.com/RasaHQ/rasa_core/blob/master/rasa_core/train.py#L172


| 4Sum | C++

Title - 4Sum
What will change - Adding a solution code in C++ for the mentioned problem.
Type of Issue -
Please add/delete options that are not relevant.

[x] Adding New Code

Programming Language
Please add/delete options that are not relevant.

[x] C++

Self Check

Ask for issue assignment and wait to get assigned to it before making Pull Request.
Add your file in the proper folder
Clean Code and Documentation for better readability
Add Title and Description of the program in the file

:star2: Star it :fork_and_knife:Fork it :handshake: Contribute to it!
Discord server ✉ - https://discord.gg/CXksGdn
Happy Coding,

Would you please assign this issue to me?

Hello I'm Interested to work on this. Pls assign this to me


[Core] [Frontend] Make detokenization optional

FIX #3635
This PR makes detokenization optional during generation. The changes here are the minimal ones required to enable this: We add an optional detokenize argument to SamplingParams which defaults to True. In LLMEngine we then skip detokenization if detokenize is set to False for the current request. In that case, CompletionOutput.text is returned empty, but CompletionOutput.token_ids contains the generated token IDs.
One thing I don't know is how (if at all) we could make this work with th OpenAI API server, at least in combination with the openai python client library. If anyone has ideas on that, or of course any other feedback, I'd be happy to make changes!

Quick code snippet to test this:
from vllm import LLM, SamplingParams

llm = LLM(
    model=f"gpt2",
)

prompt = "Today is a good day to"

print("Now with detokenize=False")
sampling_params = SamplingParams(max_tokens=10, temperature=0.0, detokenize=False)
outputs = llm.generate(prompt, sampling_params)
print(outputs[0].outputs[0])

print("Now with detokenize=True")
sampling_params = SamplingParams(max_tokens=10, temperature=0.0, detokenize=True)
outputs = llm.generate(prompt, sampling_params)
print(outputs[0].outputs[0])

yields (skipping the tqdm bar):
Now with detokenize=False
CompletionOutput(index=0, text='', token_ids=[307, 257, 636, 286, 262, 995, 13, 198, 198, 40], cumulative_logprob=-16.733878153841943, logprobs=None, finish_reason=length, stop_reason=None)
Now with detokenize=True
CompletionOutput(index=0, text=' be a part of the world.\n\nI', token_ids=[307, 257, 636, 286, 262, 995, 13, 198, 198, 40], cumulative_logprob=-16.733878153841943, logprobs=None, finish_reason=length, stop_reason=None)

With a larger list of prompts and larger max_tokens I see a roughly 20% speedup on an A100 when disabling detokenization.

+1 on this feature - in practice this feature can benefit a lot of use cases when the detokenization is not necessary and only the token ids themselves are needed for downstream tasks.
We also observe roughly 10-15% speedup on ShareGPT when simply commenting out
https://github.com/vllm-project/vllm/blob/9c82a1bec3a177ff2d611c092c19d25cabd90bb0/vllm/engine/llm_engine.py#L419-L421
There's also https://github.com/vllm-project/vllm/pull/3748, so I think we should consolidate the efforts for this feature.

After digging some more, I don't see an easy way to support this through the OpenAI server, at least while maintaining close compatibility wih their API. Instead, I propose adding token input and output to the (non-OpenAI) API server. I've added a proposed implementation to this PR. The API server now takes either prompt or prompt_token_ids as input. If detokenize is set to True it will return text, otherwise it will return token_ids.

+1 on this feature - in practice this feature can benefit a lot of use cases when the detokenization is not necessary and only the token ids themselves are needed for downstream tasks.
We also observe roughly 10-15% speedup on ShareGPT by simply commenting out
https://github.com/vllm-project/vllm/blob/9c82a1bec3a177ff2d611c092c19d25cabd90bb0/vllm/engine/llm_engine.py#L419-L421
~There's also #3748, so I think we should consolidate the efforts for this feature~ Edit: the other PR simply disables the use of tokenizer completely, so these two features should technically be able to co-exist.

Thank you! And yeah, the other PR was opened almost the same minute as mine, otherwise we could have coordinated. They are indeed somewhat orthogonal though. I don't know if removing the tokenizer altogether gives an additional performance benefit, but there may be other considerations.

After digging some more, I don't see an easy way to support this through the OpenAI server, at least while maintaining close compatibility wih their API. Instead, I propose adding token input and output to the (non-OpenAI) API server.

@mgerstgrasser The non-OpenAI API server is actually deprecated already and no longer accepting changes. IMO if OpenAI API does not support token ids only as output, then we should keep it as a feature on the engine level instead of server level (at least for this PR).
I believe the goal of the OpenAI API server is the ability to serve an OSS model as a drop-in placement for OpenAI endpoints, so I think we should try to include as little vLLM custom logic there as possible. Plus, there's no restriction for users to build their own API servers with just AsyncLLMEngine. WDYT?

After digging some more, I don't see an easy way to support this through the OpenAI server, at least while maintaining close compatibility wih their API. Instead, I propose adding token input and output to the (non-OpenAI) API server.

@mgerstgrasser The non-OpenAI API server is actually deprecated already and no longer accepting changes. IMO if OpenAI API does not support token ids only as output, then we should keep it as a feature on the engine level instead of server level (at least for this PR).
I believe the goal of the OpenAI API server is the ability to serve an OSS model as a drop-in placement for OpenAI endpoints, so I think we should try to include as little vLLM custom logic there as possible. Plus, there's no restriction for users to build their own API servers with just AsyncLLMEngine. WDYT?

Yes, absolutely! I kind of did the API server changes for my own project primarily (so exactly as you suggest, easy to build your own API server if needed). I figured I'd be happy to share that, but also don't mind removing it from the PR!

@mgerstgrasser Hello! Thanks for making this PR - IMO overall the logic looks good to me, but do you mind adding some tests just as a sanity check?
The other thing I'm not sure about is whether we should enforce detokenize=True if the request is coming from a call to the OAI server in serving_chat.py and serving_completion.py, since the OpenAI API itself does not support token ids only as output.

Yes, absolutely! Is there anywhere existing where these could fit in well? I don't see any end-to-end tests where I could easily add something.

Perhaps a new file under tests/engine?

Since CompletionRequest and ChatCompletionRequest don't include any logic to override it

Oh Yes that's right - could you leave a # NOTE like the following to indicate that this parameter is only exposed at the engine level for now? Thanks!https://github.com/vllm-project/vllm/blob/b95047f2dad3cc4d64e6f4d76974e3c55917c5ee/vllm/utils.py#L141-L143

Yes, absolutely! Is there anywhere existing where these could fit in well? I don't see any end-to-end tests where I could easily add something.

Perhaps a new file under tests/engine?

Since CompletionRequest and ChatCompletionRequest don't include any logic to override it

Oh yes that's right - could you leave a # NOTE like the following to indicate that this parameter is only exposed at the engine level for now? Thanks!
https://github.com/vllm-project/vllm/blob/b95047f2dad3cc4d64e6f4d76974e3c55917c5ee/vllm/utils.py#L141-L143

Done, and done! I see a few checks failed now, but as far as I can tell due to internal errors?

@mgerstgrasser looks like you need to run format.sh too

@mgerstgrasser looks like you need to run format.sh too

@njhill I did, not sure why it failed earlier, but the simplification commit triggered a re-run and seems to be good now.

@mgerstgrasser Thank you again for working on this PR!

Of course! Thank you both @ywang96 @njhill for being so quick and responsive with reviewing, and for all your work on this fantastic project in general!


Move the ansi implementation to a separate module.

This cuts down deps on the main module.

Nevermind, just realized term_windows is using these anyway...


docs: flipt grpc example

This PR

This fixes open-feature/go-sdk-contrib#397. As seen in the service implementation, the scheme is used for http/https or if GRPC then unix:// is used. But plain GRPC should not provide the scheme.
Related Issues

Fixes #397
Notes

Follow-up Tasks

How to test
A demo app can be seen here.

Hey @boyvinall, thanks for the PR.

I've updated the PR title so that the change is more accurately reflected in the release notes.

Thank you @boyvinall !!!


RTL

is it RTL ready ? and if yes from where ?
I've added the  "rtl"  attribute to the html dir as this ```

@ahmgeek Take a Look at PR #489


GO SAM sample logging errors

[NOTE]: # /var/task/bootstrap: /lib64/libc.so.6: version `GLIBC_2.34' not found
Description
Seeing /var/task/bootstrap: /lib64/libc.so.6: version `GLIBC_2.34' not found (required by /var/task/bootstrap)  in aws cloudwatch logs.
Steps to Reproduce

build the example.
send it a test message.

Expected Behavior
No errors.
Relevant Logs / Console output
[NR_EXT] New Relic Lambda Extension starting up
/var/task/bootstrap: /lib64/libc.so.6: version GLIBC_2.32' not found (required by /var/task/bootstrap) /var/task/bootstrap: /lib64/libc.so.6: version GLIBC_2.34' not found (required by /var/task/bootstrap)
EXTENSION	Name: newrelic-lambda-extension	State: Registered	Events: [INVOKE, SHUTDOWN]
INIT_REPORT Init Duration: 86.89 ms	Phase: init	Status: error	Error Type: Runtime.ExitError
Your Environment
aws

ex: Browser name and version:
ex: Operating System and version:

Additional context

Hi!  +1 this issue is taking down our whole app.
/opt/extensions/newrelic-lambda-extension: /lib64/libc.so.6: versionGLIBC_2.34' not found (required by /opt/extensions/newrelic-lambda-extension)`

The GLIBC_2.34 error was result of migration of CI pipeline. Any of the production layers don't have such issue. Please use latest layer for the lambda runtime.


Remove office links for worldwide organisations

In https://github.com/alphagov/whitehall/pull/8857, we emptied the office links from Worldwide Organisations, as offices are now being included in the main details of the content item, to allow us to use the same content item to render all pages.
After these have been republished, we no longer need the office links to be present in the presenter, so can remove them.
Depends on: https://github.com/alphagov/whitehall/pull/8857
Trello card

Closing, as we are no longer proceeding with multi-part content for worldwide organisations.


vars(x)['y'] is better written as x.y

I started work in #149 but decided to clean this up first
By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

quick review if this looks good to me.  I'll try get this in shortly.  Thanks!