text:
2.0.0-beta4 - ViewPager2 inside constraint layout

ContraintLayout: 2.0.0-beta4
ViewPager2: 1.0.0
When a constraint layout contains a viewpager2, it's children doesn't have focus (not clickable).
`
<androidx.constraintlayout.widget.ConstraintLayout
android:layout_width="match_parent"
android:layout_height="match_parent">
    <androidx.viewpager2.widget.ViewPager2
        android:id="@+id/pager_bridge"
        android:layout_width="match_parent"
        android:layout_height="0dp"
        app:layout_constraintBottom_toTopOf="@+id/navigation_bridge"
        app:layout_constraintTop_toTopOf="parent" />

...
`
In my case, the view pager contains recycler views. The view holders are not clickable.
When I use a frame layout or a linear layout, the view holders are clickable

We have same problem.
Another problem which we have, then we use ViewPager2 with RecyclerView, after scrolling RecycleView sometimes items are empty. We use data binding.

I have the very similar problem.
I have a viewpager2 which links two fragments. Inside the fragment A there is a expandablelistview. When I first come into the the first page, where the fragment A is located and initialized first time, the expandablelistview works well. While when I come into the seconde page, and return back to the first page, the expandablelistview can't be even clicked. Then I set a button with OnClick event, where it tell the expandablelistview to request focus. So when I come to page 2 and return back to page 1, and click the button, then the expandablelistview can react to click event, i.e., it can expand and collapse as normal. So I guess the viewpager2 may lead to a problem of lossing focus.
I search on stackoverflow, and I see this answer:
https://stackoverflow.com/questions/56590340/fragments-in-viewpager2-does-not-respond-to-clicks-if-scroll-position-is-0
The answer tells clearly that, he met the same issue and after changing the parent layout of viewpager2 from constraintlayout to linearlayout, the bug disappeared. I guess that's the point, but I can't do that like him, because my project has used constraintlayout everywhere and includes a lot of items, which will be hard to make a replacement.
I hope the post will be seen by more people and developers.

source: gharchive/issue

authors: Nikochaix rmazajev vainquit

repo: googlecodelabs/constraint-layout

license_type: permissive

license_source: bigquery


text:
Connection to 'Colaboratory' issues

Followed instructions as described here. Jupyter works on localhost without issues. I open the firewall to allow TCP over port 9090 and issued this
jupyter notebook --NotebookApp.allow_origin='https://colab.research.google.com' --port=9090

and tried to reconnect in codelab, it fails and this is what is seen on the jupyter terminal.
[C 16:36:43.917 NotebookApp]

    Copy/paste this URL into your browser when you connect for the first time,
    to login with a token:
        http://localhost:9090/?token=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
[I 16:36:44.072 NotebookApp] Accepting one-time-token-authenticated connection from ::1
[W 16:38:04.056 NotebookApp] Forbidden
[W 16:38:12.181 NotebookApp] 403 GET /api/kernelspecs (::1) 8124.95ms referer=None

Any help appreciated!

I completely disabled my firewall/antivirus. It is the same browser (chrome), that https://colab.research.google.com was open. Just for testing I did issue the command suggested above with --no-browser option, I get the same errors. I closed everything and used firefox as well (enabling network.websocket.allowInsecureFromHTTPS) and the same result.
jupyter notebook --NotebookApp.allow_origin='https://colab.research.google.com' --port=9090
 --no-browser
jupyter_http_over_ws extension initialized. Listening on /http_over_websocket
[I 17:57:49.410 NotebookApp] JupyterLab beta preview extension loaded from C:\ProgramData\Anaconda3\lib\site-packages\jupyterlab
[I 17:57:49.410 NotebookApp] JupyterLab application directory is C:\ProgramData\Anaconda3\share\jupyter\lab
[W 17:57:49.434 NotebookApp] Error loading server extension jupyterlab
    Traceback (most recent call last):
      File "C:\ProgramData\Anaconda3\lib\site-packages\jupyterlab\commands.py", line 321, in __init__
        self._run(['node', 'node-version-check.js'], cwd=HERE, quiet=True)
      File "C:\ProgramData\Anaconda3\lib\site-packages\jupyterlab\commands.py", line 1165, in _run
        proc = Process(cmd, **kwargs)
      File "C:\ProgramData\Anaconda3\lib\site-packages\jupyterlab\process.py", line 73, in __init__
        self.proc = self._create_process(cwd=cwd, env=env)
      File "C:\ProgramData\Anaconda3\lib\site-packages\jupyterlab\process.py", line 131, in _create_process
        cmd[0] = which(cmd[0], kwargs.get('env'))
      File "C:\ProgramData\Anaconda3\lib\site-packages\jupyterlab\jlpmapp.py", line 59, in which
        raise ValueError(msg)
    ValueError: Please install nodejs 5+ and npm before continuing installation. nodejs may be installed using conda or directly from the nodejs website.

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
      File "C:\ProgramData\Anaconda3\lib\site-packages\notebook\notebookapp.py", line 1454, in init_server_extensions
        func(self)
      File "C:\ProgramData\Anaconda3\lib\site-packages\jupyterlab\extension.py", line 111, in load_jupyter_server_extension
        info = get_app_info(app_dir)
      File "C:\ProgramData\Anaconda3\lib\site-packages\jupyterlab\commands.py", line 244, in get_app_info
        handler = _AppHandler(app_dir, logger)
      File "C:\ProgramData\Anaconda3\lib\site-packages\jupyterlab\commands.py", line 324, in __init__
        raise ValueError(msg)
    ValueError: Please install nodejs 5+ and npm before continuing installation. nodejs may be installed using conda or directly from the nodejs website.
[I 17:57:49.648 NotebookApp] Serving notebooks from local directory: C:\programdata\Anaconda3
[I 17:57:49.649 NotebookApp] 0 active kernels
[I 17:57:49.650 NotebookApp] The Jupyter Notebook is running at:
[I 17:57:49.650 NotebookApp] http://localhost:9090/?token=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
[I 17:57:49.651 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[C 17:57:49.654 NotebookApp]

    Copy/paste this URL into your browser when you connect for the first time,
    to login with a token:
        http://localhost:9090/?token=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
[W 18:00:21.655 NotebookApp] Forbidden
[W 18:00:21.657 NotebookApp] 403 GET /api/kernelspecs (::1) 3.00ms referer=None

I used simple websocket client and connected to ws://localhost:9090/http_over_websocket?token=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx and it connects, even though the origin was localhost and not https://colab.research.google.com! So either way, the websocket component is working from Jupyter's perspective.

Do you think my network provider is blocking certain ports from colab? I will retry on a private network.

Ok got it working! It was the ad blockers. Had to disable them to get this working, add that info to the README?

I get a similar issue where even adding --no-browser cannot fix that problem.
A potential (but not safe at all) solution is by adding --NotebookApp.token=''  --NotebookApp.disable_check_xsrf=True.
My final running command looks like:
jupyter notebook --no-browser --allow-root --NotebookApp.allow_origin='https://colab.research.google.com' --NotebookApp.token=''  --NotebookApp.disable_check_xsrf=True

I'm getting  below error,need help to trobleshoot

I'm also getting this it keep saying connecting but at the end this dialog shows up!

I've followed the steps in here and checked on the issues on this page, but still can't connect to local.
By using:
jupyter notebook --NotebookApp.allow_origin='https://colab.research.google.com' \
>   --port=9090 --no-browser

response is:
jupyter_http_over_ws extension initialized. Listening on /http_over_websocket
JupyterLab beta preview extension loaded from /Users/myUser/anaconda3/lib/python3.6/site-packages/jupyterlab
JupyterLab application directory is /Users/myUser/anaconda3/share/jupyter/lab
Serving notebooks from local directory: /Users/myUser
0 active kernels
The Jupyter Notebook is running at:
http://localhost:9090/?token=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).

    Copy/paste this URL into your browser when you connect for the first time,
    to login with a token:
        http://localhost:9090/?token= xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx&token= xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

So I copy and paste
http://localhost:9090/?token= xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx&token= xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
in my browser (Safari) and get the page response:
302 GET /?token= xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx&token= xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx (::1) 1.56ms
But when I go on Colab and try to connect to local runtime (with the right port 9090 in this case) it says: Unable to connect to the runtime. Troubleshoot.
And it asks me to check:

Ensure the jupyter_http_over_ws Jupyter extension is enabled and up to date on your machine.
pip install --upgrade jupyter_http_over_ws>=0.0.1a3 && \ jupyter serverextension enable --py jupyter_http_over_ws

Ensure the notebook server on your machine is running on port 9090 and accepting requests from https://colab.research.google.com.
jupyter notebook \ --NotebookApp.allow_origin='https://colab.research.google.com' \ --port=9090 \ --NotebookApp.port_retries=0
which I tried but have the same results.

About jupyter_http_over_ws in my system, it shows:
pip show jupyter_http_over_ws

Name: jupyter-http-over-ws
Version: 0.0.6
Summary: Jupyter support for HTTP-over-ws
Home-page: https://github.com/googlecolab/jupyter_http_over_ws
Author: Google Colaboratory team
Author-email: colaboratory-team@google.com
License: Apache 2.0
Location: /Users/myUser/anaconda3/lib/python3.6/site-packages
Requires: six, notebook, tornado, enum34
Required-by:

Hi, has anyone found an alternative solution to disable_check_xsrf? Disabling the ad blockers does not solve the problem for me.

This is super frustrating I have even attempted to use the disable_check_xsrf, disabled my Norton software and disabled my MacOS firewall and still nothing.  BTW the firewall is not the problem because this works just fine in Chrome with the normal suggested jupiter notebook command.
jupyter notebook   --NotebookApp.allow_origin='https://colab.research.google.com'   --port=9090   --NotebookApp.port_retries=0   --no-browser --NotebookApp.disable_check_xsrf=True --NotebookApp.token=''
Does not work on Safari
jupyter notebook   --NotebookApp.allow_origin='https://colab.research.google.com'   --port=9090   --NotebookApp.port_retries=0   --no-browser
Does not work on Safari
Does work in Chrome
When attempting with Safari, the terminal window where I executed jupyter notebook does not show any STDERR or STDOUT, the browser window simply and immediately returns a could not connect... troubleshoot message with NO details.

Colaboratory attempts to make a connection to your local kernel using a WebSocket (ws://). Safari disallows connections from HTTPS domains using insecure WebSockets. Due to this, you won't be able to connect to your local kernel using Safari.
We'll work to update our documentation and error handling to try and make this more clear. An additional place to look when encountering issues like this is in the console of your browser's developer tools.

I had this issue because I had disabled 3rd party cookies. Fixed by enabling them.

My colab notebook has suddenly stopped connecting to jupyter runtime - does anyone know how to fix this? I get the same connection output as below

I'm getting below error,need help to trobleshoot

jupyter notebook --NotebookApp.allow_origin='https://colab.research.google.com' --NotebookApp.port_retries=0 --notebook-dir="" --no-browser --allow-root  --NotebookApp.token=''  --NotebookApp.disable_check_xsrf=True --port=8888
worked for me chrome : 78.0.3904.108 win 10 : 1909 update

Thank you talk2sunil83. It also worked for me.

@colaboratory-team I still could not connect (Windows 10, Chrome 81 beta, Anaconda3) after following troubleshooting steps, updating jupyter config, spending an hour on it. The command from @talk2sunil83 worked like a charm.

Fixed it. The only option for me was to remove the password from the jupyter config file (the one you set when you first open jupyter notebooks) and simply copy and paste the generated token into the backend url when connecting to colab.

The password in the jupyter config file was my problem too.  Removing the password fixed it.  Thanks @cmp1 !

jupyter notebook --NotebookApp.allow_origin='https://colab.research.google.com' --NotebookApp.port_retries=0 --notebook-dir="" --no-browser --allow-root --NotebookApp.token='' --NotebookApp.disable_check_xsrf=True --port=8888
worked for me chrome : 78.0.3904.108 win 10 : 1909 update

I tried this but still can't connect
[I 13:09:14.093 NotebookApp] 302 GET / (::1) 0.00ms [I 13:09:14.096 NotebookApp] Refusing to serve hidden directory, via 404 Error [W 13:09:14.098 NotebookApp] 404 GET /tree (::1) 2.00ms referer=None [E 13:09:14.098 NotebookApp] Uncaught error when proxying request     Traceback (most recent call last):       File "c:\python\python37\lib\site-packages\jupyter_http_over_ws\handlers.py", line 180, in _attach_auth_cookies         parsed_auth_url, self.ca_certs, self._get_http_client())       File "c:\python\python37\lib\site-packages\tornado\gen.py", line 1055, in run         value = future.result()       File "c:\python\python37\lib\site-packages\tornado\concurrent.py", line 238, in result         raise_exc_info(self._exc_info)       File "<string>", line 4, in raise_exc_info       File "c:\python\python37\lib\site-packages\tornado\gen.py", line 1069, in run         yielded = self.gen.send(value)       File "c:\python\python37\lib\site-packages\jupyter_http_over_ws\handlers.py", line 535, in _perform_request_and_extract_cookies         raise response.error     tornado.httpclient.HTTPError: HTTP 404: Not Found [E 13:09:14.099 NotebookApp] Couldn't attach auth cookies

Is Safari one of the supported browsers at all? I've been trying all the mentioned solutions above, but all my attempts were in vain. Any help is appreciated, thank you!

authors: AIWithShrey R-N SilvioJin XericZephyr aarvignesh acarl005 beerpulse cmp1 colaboratory-team debsahu eanxgeek hisoffshoot loukad siddu541 talk2sunil83 tamaradanceva


text:
Create an empty shell Angular template for the front end

this is the template for an angular project generated with "ng new"
I also included the google charts module in the components

Please update the name of the change to use "what does this commit do" as a convention as opposed to "what happened here", i.e. -> "Create an empty shell Angular template for the front end"

there is a README in the frontend folder which has the "ng serve" command that you need

LGTM

source: gharchive/pull-request

authors: netkuba peterborocz sophiebpeneva

repo: googleinterns/inventory-visualizer


text:
Clustering: Breaks marker anchoring for markers not of the "pin" style.

The new Clustering() implementation appears to have a preset marker image anchor offset.  Or, to be more precise, the composable passed into the clusterItemContent parameter appears to be wrapped in an offset composable when placed on the screen.  I see no way to configure that anchor offset, which appears to be Offset(0.5f, 1.0f), the default assigned to markers.  This does not break "pin" style markers, but breaks all other marker image types as they are not able to be centered on the point.  Adding anchor configurability may be the most robust fix.

If you would like to upvote the priority of this issue, please comment below or react with :+1: so we can see what is popular when we triage.
@mpfulc Thank you for opening this issue. 🙏
Please check out these other resources that might help you get to a resolution in the meantime:

Check the issue tracker - bugs and feature requests for Google Maps Platform APIs and SDKs
Open a support case - Get 1:1 support in Cloud Console.
Discord - chat with other developers
StackOverflow - use the google-maps tag

This is an automated message, feel free to ignore.

any update on this?
seems quite crucial to have that configurability - otherwise clustering cannot be used with custom pins. :(

+1 to getting this fixed. Being able to change the content of the marker but not the anchor point really limits the usefulness of it.

any update? this would be a highly appreciated - this is blocker for our product launch.

Thanks for the workaround - will try to implement that.
Still I would see the ability of "setting anchor" as essential - having a Map SDK that does not support custom marker content (and as content varies the anchor needs to be adjusted) seems too limited.

authors: cwsiteplan mpfulc noelb wangela

repo: googlemaps/android-maps-compose


text:
perf: Make CameraPositionState stable

CameraPositionState has a few unstable properties. Rather than verify all usages of these are safe for stability, I'm opting to back them with mutable states, so the compiler can mark the class stable for us.
Verified stability via compiler report.

Superseded by #254


text:
Unable to instantiate activity ComponentInfo MainActivity

Attempting to run the program results in the following error:
com.example.google.playservices.placepicker E/AndroidRuntime: Process: com.example.google.playservices.placepicker, PID: 9635
com.example.google.playservices.placepicker E/AndroidRuntime: java.lang.RuntimeException: Unable to instantiate activity
ComponentInfo{com.example.google.playservices.placepicker/com.example.google.playservices.placepicker.MainActivity}: java.lang.ClassNotFoundException:
Didn't find class "com.example.google.playservices.placepicker.MainActivity" on path: DexPathList[[zip file "/data/app/com.example.google.playservices.placepicker-2/base.apk"],nativeLibraryDirectories=[/vendor/lib, /system/lib]]
Device Used is running 5.1.1 API 22 - Xperia SP

This sample has been deprecated/archived (check README for more information on newer samples related to this technology).
As recommended by GitHub, we are closing all issues and pull requests.

repo: googlesamples/android-play-places


text:
sample outdated

com.google.android.gms.location.places.Places no longer exists in play-services-location:9.4.0

quick fix is to add com.google.android.gms:play-services-places:9.4.0

This sample has been deprecated/archived (check README for more information on newer samples related to this technology).
As recommended by GitHub, we are closing all issues and pull requests.

authors: SjoerdvGestel codingjeremy


text:
Infinite loop if i have a method that need runtime permission in onResume().

when requesting permission in onResume(), i deny the permission with the "Never Ask Again" option,then show AppSettingsDialog. However it seems the onResume() is always running,and the AppSettingsDialog splash all the time.

@mrldroid can you provide some code that demonstrates the problem?

@mrldroid it's been over two weeks since the last update so I am going to close this issue.  Please re-open if you want to discuss further.

authors: mrldroid samtstern

repo: googlesamples/easypermissions


text:
New helper class QueueToDeviceMap.

Shared between the frame_time and runtime layers, without growing the
LayerData class. Intend to use also for the memory_usage layer. Also
fix runtime layer to use separate type-safe maps for VkCommandBuffer
and VkQueue, rather than a map keyed by void*.

Hi @nisse-work,
I opened a PR for what I suggested in the previous comment: https://github.com/googlestadia/performance-layers/pull/41. Could you see if it makes sense from the perspective of the memory usage layer?

The changes in pr #41 makes this a lot simpler. Nice!

authors: kuhar nisse-work

repo: googlestadia/performance-layers

license_source: github-api


text:
Unlisted dependency on plenary

Installing this on NixOS and attempting to use the theta theme blows up the neovim config with unhelpful error messages until I also installed telescope. This dependency should be mentioned in these docs.

ah yeah I didn't originally author that file so i totally glazed over its dependency on plenary. i'll see about removing it or at least documenting it

theta's dependency on plenary is listed in the readme now https://github.com/goolord/alpha-nvim/commit/1356b9ef31b985d541d94314f2cf73c61124bf1d

authors: NickHackford goolord

repo: goolord/alpha-nvim

license: MIT


text:
Command jsonapi configure not working

Summary
I tried to run the command 'gopass jsonapi configure' on my fresh installed gopass version 1.9.2 but it seems that the command isn't present anymore. Instead of creating native messaging scripts it tries to find a password entry. So I've installed gopass 1.8.6 where that command works as expected.
Steps To Reproduce

Install newest gopass version 1.9.2 with go get github.com/gopasspw/gopass
run wizard, mount store
run gopass jsonapi configure

gopass now tries to find a password entry
Expected behavior
gopass should run the Native Messaging Setup Wizard
Environment

OS: Ubuntu 20.04 LTS
gopass Version: 1.9.2
Installation method: go get github.com/gopasspw/gopass

This command has been removed from the main gopass binary.
Workaround: Use cmd/gopass-jsonapi.

This is how I tried to run the gopass jsonapi. Unfortunatelly, I also ran into this bug. I solved it by editing the gopass_wrapper.sh.
Steps to reproduce
The new version (1.9.2-git+HEAD go1.14.3 linux amd64) comes without the jsonapi command. It is now provided by gopass-jsonapi which has to be created first
$ cd ~/gopasspw/gopass/cmd/gopass-jsonapi/
$ make

Now, configure the gopass-jsonapi in that folder:
$ ./gopass-jsonapi configure

which will also display the gopass_wrapper.sh:
Wrapper Script (/home/user/.config/gopass/gopass_wrapper.sh):
#!/bin/sh

if [ -f ~/.gpg-agent-info ] && [ -n "$(pgrep gpg-agent)" ]; then
   source ~/.gpg-agent-info
   export GPG_AGENT_INFO
else
   eval $(gpg-agent --daemon)
fi

export PATH="$PATH:/usr/local/bin" # required on MacOS/brew
export GPG_TTY="$(tty)"

/home/user/go/src/github.com/gopasspw/gopass/cmd/gopass-jsonapi/gopass-jsonapi jsonapi listen

exit $?

Manifest File (/home/user/.mozilla/native-messaging-hosts/com.justwatch.gopass.json):
{
   "name": "com.justwatch.gopass",
   "description": "Gopass wrapper to search and return passwords",
   "path": "/home/user/.config/gopass/gopass_wrapper.sh",
   "type": "stdio",
   "allowed_extensions": [
       "{0815-0815-0815-0815}"
   ]
}

The line ending with gopass-jsonapi jsonapi listen contains a bug, as the jsonapi is redundant. Removing it solved the problem (resulting in: ... gopass-jsonapi listen)

Thank you for pointing out this issue.
The wrapper output will be fixed soon.

This command has been removed from the main gopass binary.
Workaround: Use cmd/gopass-jsonapi.

how can this be used?

This command has been removed from the main gopass binary.
Workaround: Use cmd/gopass-jsonapi.

I wondered how i can use this.
Then I realized that you mean this directory in the sources you get from https://github.com/gopasspw/gopass.
There going to cmd/gopass-jsonapi
But a normal make does not work there; it need root privileges

You don't need root privileges for any part of gopass.
And you shouldn't use it as root - at least not build it as root.

of course build as root is not good, but it does not work else:
$ make
go: finding github.com/urfave/cli v1.22.4
go: finding golang.org/x/net latest
go: finding github.com/blang/semver v3.5.1+incompatible
go: writing stat cache: mkdir /usr/go/pkg/mod/cache/download/github.com/urfave/cli/@v: permission denied
...

That seems like an issue with your Go installation.
Running as root is not the proper solution.
Of course you can do what you like, but I discourage building as root.

I dont know, I am not a go developer. I just installed go to install gopass and just used the normal apt package of golang on my ubuntu.
it seems like solving dependencies, but the installer tries to install it globally, not for the actual user.

I'm afraid I can't help you debug this, but I strongly suggest getting some advice to fix your go installation.
Or you could just use our binary packages.

It is hard to get an advice, if I don't know enough about go language to describe the problem. I do not even know, what i can google for.
I already tried the binary packages, but they don't contain the jsonapi command.

This command has been removed from the main gopass binary.
Workaround: Use cmd/gopass-jsonapi.

Can you please document this in the release notes, because I can't find any mentioning of the api deprecation for 1.9.2 (https://github.com/gopasspw/gopass/releases). Thanks !

authors: Chrisx0385 dominikschulz ferdizmn teezett varac

repo: gopasspw/gopass

license: mit


text:
[WIP] Add env command

Fixes #1227
Signed-off-by: Dominik Schulz dominik.schulz@gauner.org

Hello @dominikschulz, I am the proposer of #1227, thanks for picking this up :-)
I looked at the code, first thing that I see missing are the tests :-), is this because of the WIP tag? (I am not familiar with the gopass project conventions).
Thanks!

authors: dominikschulz marco-m


text:
Fixed gnocchi metrics and resources list pager

In the current implementation, pager type of gnocchi metrics and resources list
is SinglePageBase, which is wrong. In Gnocchi, query results in one page
are limited to max_limit value set in the configuration file (default 1000).
With the current implementation, AllPages() method can only show the first
page of query result (the first 1000 metrics, for example).
The pager type should be MarkerPageBase and LastMarker() method needs to
be implemented.

@tzmtl thank you for submitting this. Are you able to show some kind of failure with the original code and success with the new code? Or API JSON responses that have paging enabled?

I tested in a openstack test environment, with code below:
package main

import (
	"fmt"
	"github.com/gophercloud/gophercloud/pagination"
	"github.com/gophercloud/utils/openstack/clientconfig"
	"github.com/gophercloud/utils/gnocchi/metric/v1/metrics"
	"github.com/gophercloud/utils/gnocchi/metric/v1/resources"
)

func main() {
	//Create endpoints
	opts := &clientconfig.ClientOpts{
		Cloud: "oi-admin",
	}

	gnocchiClient, err := clientconfig.NewServiceClient("gnocchi", opts)
	if err != nil {
		panic(err)
	}

	fmt.Printf("Testing metrics list: \n")
	listOpts := metrics.ListOpts{
		Limit: 500,
	}

	fmt.Printf("Each page: \n")
	err = metrics.List(gnocchiClient, listOpts).EachPage(func(page pagination.Page) (bool, error) {
		s, err := metrics.ExtractMetrics(page)
		if err != nil {
			return false, err
		}

		fmt.Printf("Metric number in this page: %d\n", len(s))
		return true, nil
	})

	fmt.Printf("All page: \n")
	allPages, err := metrics.List(gnocchiClient, listOpts).AllPages()
	if err != nil {
		panic(err)
	}

	allMetrics, err := metrics.ExtractMetrics(allPages)
	if err != nil {
		panic(err)
	}

	fmt.Printf("Metric number in all pages: %d\n", len(allMetrics))

	fmt.Printf("Testing resources list: \n")
	rListOpts := resources.ListOpts{
		Details: true,
		Limit:   200,
	}

	fmt.Printf("Each page: \n")
	err = resources.List(gnocchiClient, rListOpts, "generic").EachPage(func(page pagination.Page) (bool, error) {
		s, err := resources.ExtractResources(page)
		if err != nil {
			return false, err
		}

		fmt.Printf("Resource number in this page: %d\n", len(s))
		return true, nil
	})

	if err != nil {
		panic(err)
	}

	fmt.Printf("All page: \n")
	allPages, err = resources.List(gnocchiClient, rListOpts, "generic").AllPages()
	if err != nil {
		panic(err)
	}

	allResources, err := resources.ExtractResources(allPages)
	if err != nil {
		panic(err)
	}

	fmt.Printf("Resource number in all pages: %d\n", len(allResources))
}

With original implementation, it returns only the first page:
test ./gnocchi-pager-test
Testing metrics list:
Each page:
Metric number in this page: 500
All page:
Metric number in all pages: 500
Testing resources list:
Each page:
Resource number in this page: 200
All page:
Resource number in all pages: 200

With my fix, now it can return every page properly:
  test ./gnocchi-pager-test
Testing metrics list:
Each page:
Metric number in this page: 500
Metric number in this page: 500
Metric number in this page: 500
Metric number in this page: 500
Metric number in this page: 500
Metric number in this page: 499
All page:
Metric number in all pages: 2999
Testing resources list:
Each page:
Resource number in this page: 200
Resource number in this page: 200
Resource number in this page: 179
All page:
Resource number in all pages: 579

result from openstack cli:
~ openstack metric list -f value | wc -l
    2999
~ openstack metric resource list -f value | wc -l
     579

Thank you for confirming 🙂

authors: jtopjian tzmtl

repo: gophercloud/utils


text:
svg: consider adding new subpackage for working with SVG documents

SVG manipulation could work in the same exact way as the elem subpackage and could be auto-generated. This is something I'm very interested in adding.

I notice @jgennis has a fork with some SVG work in it earlier in 2016: https://github.com/jgennis/vecty/tree/svg

I am working with svg and golang front end.
This being integrated would be useful.

repo: gopherjs/vecty


text:
VCPKG integration

Hi,
is there any plan to integrate your SDK into vckpg install manager?

I created a custom repository with Cineform here : https://github.com/LWKS-Software/vcpkg-registry
if that's any use to you.

Thanks you
Envoyé à partir de Outlook pour Androidhttps://aka.ms/AAb9ysg

From: Nick Walsh @.>
Sent: Sunday, October 15, 2023 10:55:27 AM
To: gopro/cineform-sdk @.>
Cc: Yannick Kohn @.>; Author @.>
Subject: Re: [gopro/cineform-sdk] VCPKG integration (Issue #56)
I created a custom repository with Cineform here : https://github.com/LWKS-Software/vcpkg-registry
if that's any use to you.
—
Reply to this email directly, view it on GitHubhttps://github.com/gopro/cineform-sdk/issues/56#issuecomment-1763325810, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AEISZRHCPFVK56FSTUX6J63X7OQH7AVCNFSM6AAAAAA54UCGASVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTONRTGMZDKOBRGA.
You are receiving this because you authored the thread.Message ID: @.***>

repo: gopro/cineform-sdk


text:
UID

Hi!
Do you really need uid package?

Hi @ayozebarrera,
We can certainly do without it.
Thanks for reporting

@ayozebarrera released as 1.1.2

Great!
El 19 may 2016 15:07 +0100, Goran Udosicnotifications@github.com, escribió:

Closed#1(https://github.com/gor181/react-chartjs-2/issues/1)viab2878bd(https://github.com/gor181/react-chartjs-2/commit/b2878bdfb14c9a21025cf610df876514fe15ac0b).
—
You are receiving this because you were mentioned.
Reply to this email directly orview it on GitHub(https://github.com/gor181/react-chartjs-2/issues/1#event-665846171)


text:
feat(libreoffice): preserve filenames for zipped files

Fixes #771.

@chrishughes20 I've added some commits so that it's always "document.docx" -> "document.docx.pdf".

(It also simplifies the code 👍 )

Nice! Thanks for the help, @gulien !

Thanks @chrishughes20 for your time!

repo: gotenberg/gotenberg


text:
Fix current_user method & add custom header option

Hi
I fixed current_user method after migrate to knock 2.x and added specs.
Also I added option for header name. It can be useful

Looks good! Thx :)

authors: gottfrois max-konin

repo: gottfrois/grape-knock


text:
🛑 Editor CMS is down

In b5c9b76, Editor CMS (https://editor.ritamdigital.org/services/ritam/api/posts/top-headlines/tag/top-stories/editor) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Editor CMS is back up in 00b351a after 5 minutes.

repo: govindbhardwaj/monitor-ritam


text:
Something wrong with 64-bit compilation.

Great FGTranslator, but doesn't compile with 64-bit architecture. Is it possible to fix it?

@sarslander what kind of error are you seeing? The demo supports arm64, armv7, and armv7s architectures. Can you run it?

if I set 'Build for active architecture' to NO
Undefined symbols for architecture arm64:
"OBJC_CLASS$_TMCache", referenced from:
objc-class-ref in FGTranslator.o
"OBJC_CLASS$_AFXMLParserResponseSerializer", referenced from:
objc-class-ref in FGTranslateRequest.o
"OBJC_CLASS$_AFJSONResponseSerializer", referenced from:
objc-class-ref in FGTranslateRequest.o
"OBJC_CLASS$_AFHTTPRequestOperation", referenced from:
objc-class-ref in FGTranslateRequest.o
"OBJC_CLASS$_SVProgressHUD", referenced from:
objc-class-ref in ViewController.o
ld: symbol(s) not found for architecture arm64
clang: error: linker command failed with exit code 1 (use -v to see invocation)

If I set 'Build Active architecture Only' to YES, the demo works fine

'Build Active architecture Only' is set to YES for Debug and NO for Release. Release builds should work fine. Is there a reason why you're changing the YES setting for Debug?

reinstall pod and the problem gone. Thanks for the great library!

Thanks @sarslander , glad it works. :)
Looks like Cocoapods changes the active architecture when installing pods: http://guides.cocoapods.org/using/troubleshooting.html#running-into-build-failures-after-migrating-to-xcode-5-and-cocoapods-0.25.0. Search for "ONLY_ACTIVE_ARCH" in the link above if you're curious.

authors: gpolak sarslander

repo: gpolak/FGTranslator


text:
Read MODEL_NAME from env if it is set there.

Small change that allows to read value of MODEL_NAME from environment. Value taken from env has lower priority than one from command line and higher than default "gpt-4-0125-preview".

We would be interested in a broader PR which adds environment variable configuration of all models, broadly.  If you're interested in picking that up, please expand the PR.  Otherwise, this PR is not substantial enough to merge, per our Contributing Guidelines.

Hey, @TheoMcCabe, can you please take a look into this, rebase if needed and fix the tests?

Heya @danielrosly!
This is not a substantive enough PR to be merged, per our Contributing Guidelines. We are always eager for new developers to contribute, so please have a peek at open issues and see if you feel comfortable tackling any of them. New opportunities to contribute also emerge almost daily in our Discord server as users report issues or feature requests.
We hope to see you contributing to GPT-Engineer soon!

authors: captivus danielrosly viborc

repo: gpt-engineer-org/gpt-engineer


text:
chore: add tool that allows sending dm via slack

Signed-off-by: Taylor Price tayworm@gmail.com
This needs some additional permissions configured - who has access to change the slack app?

@drpebcak I'm enhancing the Slack tools here: https://github.com/gptscript-ai/tools/pull/33

authors: drpebcak g-linville

repo: gptscript-ai/tools


text:
Initial REST api for heartbeat.

Closes #14
This need a bit more work before being usefull, but I want to land/get your review now, because groundstation<->satellite comunication is important.
Core Ideas:

uplink package defines data format for this communication

Any types that need to cross the network here should be defined here.
IE we should move GPUStatsPacket into here.

fempto contains abstractions for HTTP.

To test:
go run ./cmd/groundstation/
# in another tab:
go run ./cmd/satellite/

Which will output something like:
2024/01/18 01:51:05 INFO Starting groundstation
2024/01/18 01:51:08 INFO New Request req_no=3 method=POST url=/gs-api/heartbeat/ from=127.0.0.1:60420
2024/01/18 01:51:08 INFO New Request req_no=1 method=POST url=/gs-api/heartbeat/ from=127.0.0.1:60404
2024/01/18 01:51:08 INFO New Request req_no=2 method=POST url=/gs-api/heartbeat/ from=127.0.0.1:60374
2024/01/18 01:51:08 INFO Received a heartbeat req_no=2 prev_time=0001-01-01T00:00:00.000Z cur_time=2024-01-18T01:51:08.362Z
2024/01/18 01:51:08 INFO New Request req_no=5 method=POST url=/gs-api/heartbeat/ from=127.0.0.1:60394
2024/01/18 01:51:08 INFO Received a heartbeat req_no=1 prev_time=0001-01-01T00:00:00.000Z cur_time=2024-01-18T01:51:08.362Z
2024/01/18 01:51:08 INFO New Request req_no=4 method=POST url=/gs-api/heartbeat/ from=127.0.0.1:60436
2024/01/18 01:51:08 INFO Received a heartbeat req_no=3 prev_time=0001-01-01T00:00:00.000Z cur_time=2024-01-18T01:51:08.362Z
2024/01/18 01:51:08 INFO Received a heartbeat req_no=4 prev_time=0001-01-01T00:00:00.000Z cur_time=2024-01-18T01:51:08.362Z
2024/01/18 01:51:08 INFO Received a heartbeat req_no=5 prev_time=0001-01-01T00:00:00.000Z cur_time=2024-01-18T01:51:08.362Z
2024/01/18 01:51:08 INFO New Request req_no=6 method=POST url=/gs-api/heartbeat/ from=127.0.0.1:60380
2024/01/18 01:51:08 INFO Received a heartbeat req_no=6 prev_time=0001-01-01T00:00:00.000Z cur_time=2024-01-18T01:51:08.362Z
2024/01/18 01:51:08 INFO New Request req_no=7 method=POST url=/gs-api/heartbeat/ from=127.0.0.1:60432
2024/01/18 01:51:08 INFO Received a heartbeat req_no=7 prev_time=0001-01-01T00:00:00.000Z cur_time=2024-01-18T01:51:08.362Z
2024/01/18 01:51:08 INFO New Request req_no=8 method=POST url=/gs-api/heartbeat/ from=127.0.0.1:60454
2024/01/18 01:51:08 INFO Received a heartbeat req_no=8 prev_time=0001-01-01T00:00:00.000Z cur_time=2024-01-18T01:51:08.362Z
2024/01/18 01:51:08 INFO New Request req_no=9 method=POST url=/gs-api/heartbeat/ from=127.0.0.1:60396
2024/01/18 01:51:08 INFO Received a heartbeat req_no=9 prev_time=0001-01-01T00:00:00.000Z cur_time=2024-01-18T01:51:08.362Z
2024/01/18 01:51:08 INFO New Request req_no=10 method=POST url=/gs-api/heartbeat/ from=127.0.0.1:60442
2024/01/18 01:51:08 INFO Received a heartbeat req_no=10 prev_time=0001-01-01T00:00:00.000Z cur_time=2024-01-18T01:51:08.362Z

(This probably needs to be automated)

Other than comments made above, this all looks good to me

repo: gpuctl/gpuctl


text:
Expand building instructions

Like a recipe explaining step by step explaining the use of CMake and so forth.

still no update on this

CMake 'howto' added

The volume of documentation has grown. A proper test would probably be if non-project people can build it.

authors: bjoernthiel jkfindeisen superchromix

repo: gpufit/GPUfit


text:
After updating to 0.0.95, the SD model can no longer be loaded, it was working before.

Integrated model：
PS C:\Users\shibingli> llama-box.exe --host 127.0.0.1 --port 61633 --threads 62 --parallel 4 -m F:\\llm_models\\stabilityai\\stable-diffusion-3.5-large-GGUF\\sd3.5_large-q4_1.gguf --alias sd3.5-large --images
0.00.125.936 I ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
0.00.125.943 I ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
0.00.125.943 I ggml_cuda_init: found 4 CUDA devices:
0.00.125.955 I   Device 0: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes
0.00.125.956 I   Device 1: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes
0.00.125.957 I   Device 2: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes
0.00.125.957 I   Device 3: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes
C:\Users\shibingli\qdi\bin\llama-box.exe --host 127.0.0.1 --port 61633 --threads 62 --parallel 4 -m F:\\llm_models\\stabilityai\\stable-diffusion-3.5-large-GGUF\\sd3.5_large-q4_1.gguf --alias sd3.5-large --images
0.00.440.501 I
0.00.440.511 I version: v0.0.95 (529c2ab)
0.00.440.511 I compiler: unknown
0.00.440.511 I target: unknown
0.00.440.512 I vendor:
0.00.440.512 I   - llama.cpp 0e70ba68 (4354)
0.00.440.513 I   - stable-diffusion.cpp c8837bd (208)
0.00.440.587 I system_info: n_threads = 62 (n_threads_batch = 62) / 128 | CUDA : ARCHS = 600,610,700,750,800,860,890,900 | F16 = 1 | USE_GRAPHS = 1 | PEER_MAX_BATCH_SIZE = 128 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | AVX2 = 1 | F16C = 1 | FMA = 1 | LLAMAFILE = 1 | AARCH64_REPACK = 1 |
0.00.440.587 I
0.00.441.615 I srv                      main: listening, hostname = 127.0.0.1, port = 61633, n_threads = 6 + 2
0.00.443.296 I srv                      main: loading model
0.00.443.320 I srv                load_model: loading model ''
0.00.443.356 I load_from_file: loading model from 'F:\\llm_models\\stabilityai\\stable-diffusion-3.5-large-GGUF\\sd3.5_large-q4_1.gguf'
0.00.443.565 I init_from_file: load F:\\llm_models\\stabilityai\\stable-diffusion-3.5-large-GGUF\\sd3.5_large-q4_1.gguf using gguf format
0.00.464.323 I load_from_file: Version: SD3.x
0.00.474.521 I load_from_file: Weight type:                 q4_1
0.00.474.525 I load_from_file: CLIP_L weight type:          NONE
0.00.474.525 I load_from_file: CLIP_G weight type:          NONE
0.00.474.526 I load_from_file: T5XXL weight type:           NONE
0.00.474.526 I load_from_file: Diffusion model weight type: q4_1
0.00.474.527 I load_from_file: VAE weight type:             q4_1
0.00.762.423 I MMDiT: MMDiT layers: 38 (including 0 MMDiT-x layers)
0.01.723.901 E ggml_backend_cuda_buffer_type_alloc_buffer: allocating 5257.49 MiB on device 0: cudaMalloc failed: out of memory
0.01.723.908 E alloc_params_buffer: mmdit alloc params backend buffer failed, num_tensors = 923

Original model：
PS C:\Users\shibingli> llama-box-windows-amd64-cuda.exe --host 127.0.0.1 --port 61633 --threads 62 --parallel 4 --device CUDA0,CUDA1,CUDA2,CUDA3 -m F:\\llm_models\\stabilityai\\stable-diffusion-3.5-large-GGUF\\sd3.5_large-q4_1.gguf --alias sd3.5-large --images --image-max-batch 4 --image-t5xxl-model F:\\llm_models\\Comfy-Org\\stable-diffusion-3.5-fp8\\text_encoders\\t5xxl_fp16.safetensors --image-no-text-encoder-model-offload --image-clip-l-model F:\\llm_models\\Comfy-Org\\stable-diffusion-3.5-fp8\\text_encoders\\clip_l.safetensors --image-clip-g-model F:\\llm_models\\Comfy-Org\\stable-diffusion-3.5-fp8\\text_encoders\\clip_g.safetensors
0.00.134.892 I ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
0.00.134.899 I ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
0.00.134.900 I ggml_cuda_init: found 4 CUDA devices:
0.00.134.913 I   Device 0: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes
0.00.134.914 I   Device 1: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes
0.00.134.915 I   Device 2: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes
0.00.134.915 I   Device 3: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes
C:\Users\shibingli\qdi\bin\llama-box-windows-amd64-cuda.exe --host 127.0.0.1 --port 61633 --threads 62 --parallel 4 --device CUDA0,CUDA1,CUDA2,CUDA3 -m F:\\llm_models\\stabilityai\\stable-diffusion-3.5-large-GGUF\\sd3.5_large-q4_1.gguf --alias sd3.5-large --images --image-max-batch 4 --image-t5xxl-model F:\\llm_models\\Comfy-Org\\stable-diffusion-3.5-fp8\\text_encoders\\t5xxl_fp16.safetensors --image-no-text-encoder-model-offload --image-clip-l-model F:\\llm_models\\Comfy-Org\\stable-diffusion-3.5-fp8\\text_encoders\\clip_l.safetensors --image-clip-g-model F:\\llm_models\\Comfy-Org\\stable-diffusion-3.5-fp8\\text_encoders\\clip_g.safetensors
0.00.510.037 I
0.00.510.046 I version: v0.0.95 (529c2ab)
0.00.510.047 I compiler: unknown
0.00.510.047 I target: unknown
0.00.510.047 I vendor:
0.00.510.048 I   - llama.cpp 0e70ba68 (4354)
0.00.510.049 I   - stable-diffusion.cpp c8837bd (208)
0.00.510.128 I system_info: n_threads = 62 (n_threads_batch = 62) / 128 | CUDA : ARCHS = 600,610,700,750,800,860,890,900 | F16 = 1 | USE_GRAPHS = 1 | PEER_MAX_BATCH_SIZE = 128 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | AVX2 = 1 | F16C = 1 | FMA = 1 | LLAMAFILE = 1 | AARCH64_REPACK = 1 |
0.00.510.129 I
0.00.511.212 I srv                      main: listening, hostname = 127.0.0.1, port = 61633, n_threads = 6 + 2
0.00.512.972 I srv                      main: loading model
0.00.512.981 I srv                load_model: loading model ''
0.00.513.027 I load_from_file: loading model from 'F:\\llm_models\\stabilityai\\stable-diffusion-3.5-large-GGUF\\sd3.5_large-q4_1.gguf'
0.00.513.260 I init_from_file: load F:\\llm_models\\stabilityai\\stable-diffusion-3.5-large-GGUF\\sd3.5_large-q4_1.gguf using gguf format
0.00.534.299 I load_from_file: loading clip_l from 'F:\\llm_models\\Comfy-Org\\stable-diffusion-3.5-fp8\\text_encoders\\clip_l.safetensors'
0.00.535.037 I init_from_file: load F:\\llm_models\\Comfy-Org\\stable-diffusion-3.5-fp8\\text_encoders\\clip_l.safetensors using safetensors format
0.00.536.341 I load_from_file: loading clip_g from 'F:\\llm_models\\Comfy-Org\\stable-diffusion-3.5-fp8\\text_encoders\\clip_g.safetensors'
0.00.537.804 I init_from_file: load F:\\llm_models\\Comfy-Org\\stable-diffusion-3.5-fp8\\text_encoders\\clip_g.safetensors using safetensors format
0.00.541.012 I load_from_file: loading t5xxl from 'F:\\llm_models\\Comfy-Org\\stable-diffusion-3.5-fp8\\text_encoders\\t5xxl_fp16.safetensors'
0.00.541.743 I init_from_file: load F:\\llm_models\\Comfy-Org\\stable-diffusion-3.5-fp8\\text_encoders\\t5xxl_fp16.safetensors using safetensors format
0.00.543.179 I load_from_file: Version: SD3.x
0.00.557.553 I load_from_file: Weight type:                 q4_1
0.00.557.559 I load_from_file: CLIP_L weight type:          f16
0.00.557.559 I load_from_file: CLIP_G weight type:          f16
0.00.557.560 I load_from_file: T5XXL weight type:           f16
0.00.557.560 I load_from_file: Diffusion model weight type: q4_1
0.00.557.561 I load_from_file: VAE weight type:             q4_1
0.00.557.800 I load_from_file: CLIP: Using CPU backend
0.00.850.970 I MMDiT: MMDiT layers: 38 (including 0 MMDiT-x layers)
0.17.039.812 I operator (): unknown tensor 'text_encoders.t5xxl.transformer.encoder.embed_tokens.weight | f16 | 2 [4096, 32128, 1, 1, 1]' in model file
0.17.480.071 I load_from_file: total params memory size = 16065.61MB (VRAM 5417.49MB, RAM 10648.12MB): clip 10648.12MB(RAM), unet 5257.49MB(VRAM), vae 160.00MB(VRAM), controlnet 0.00MB(VRAM), pmid 0.00MB(RAM)
0.17.480.082 I load_from_file: loading model from 'F:\\llm_models\\stabilityai\\stable-diffusion-3.5-large-GGUF\\sd3.5_large-q4_1.gguf' completed, taking 16.49s
0.17.480.083 I load_from_file: running in FLOW mode
0.17.480.547 W common_sd_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
0.21.915.789 I get_sampling_stream: get_learned_condition completed, taking 4435 ms
0.22.233.710

PS C:\Users\shibingli> nvidia-smi.exe
Fri Dec 20 17:27:21 2024
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 566.36                 Driver Version: 566.36         CUDA Version: 12.7     |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                  Driver-Model | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA GeForce RTX 3090      WDDM  |   00000000:31:00.0 Off |                  N/A |
| 31%   32C    P8             13W /  350W |       0MiB /  24576MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
|   1  NVIDIA GeForce RTX 3090      WDDM  |   00000000:4B:00.0 Off |                  N/A |
| 31%   28C    P8             15W /  350W |       0MiB /  24576MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
|   2  NVIDIA GeForce RTX 3090      WDDM  |   00000000:B1:00.0  On |                  N/A |
| 31%   36C    P8             37W /  350W |    1428MiB /  24576MiB |     10%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
|   3  NVIDIA GeForce RTX 3090      WDDM  |   00000000:CA:00.0 Off |                  N/A |
| 31%   33C    P8             16W /  350W |      41MiB /  24576MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

My previous version was 0.0.90, and there was confirmed free VRAM, which was available before.

You can try the following options to adapt to memory usage.

use --no-warmup to disable the first-time calculation for occupying the VRAM.
use --image-free-compute-memory-immediately to free compute memory as soon as possible.
use --image-vae-tiling to reduce the memory usage during encoding/decoding, but raise the computing usage.

The problem persists. I don't know where it went wrong, with the same software and hardware environment and parameters, the model was working fine before.
llama-box.exe --host 127.0.0.1 --port 61633 --threads 8 --parallel 1 -m F:\\llm_models\\stabilityai\\stable-diffusion-3.5-large-GGUF\\sd3.5_large-q4_1.gguf --alias sd3.5-large --images --no-warmup --image-free-compute-memory-immediately --image-vae-tiling
PS C:\Users\shibingli> llama-box.exe --host 127.0.0.1 --port 61633 --threads 8 --parallel 1 -m F:\\llm_models\\stabilityai\\stable-diffusion-3.5-large-GGUF\\sd3.5_large-q4_1.gguf --alias sd3.5-large --images --no-warmup --image-free-compute-memory-immediately --image-vae-tiling
0.00.164.104 I ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
0.00.164.113 I ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
0.00.164.113 I ggml_cuda_init: found 4 CUDA devices:
0.00.164.137 I   Device 0: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes
0.00.164.138 I   Device 1: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes
0.00.164.139 I   Device 2: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes
0.00.164.140 I   Device 3: NVIDIA GeForce RTX 3090, compute capability 8.6, VMM: yes
PS C:\Users\shibingli\llama-box-bin\0.0.95\llama-box.exe --host 127.0.0.1 --port 61633 --threads 8 --parallel 1 -m F:\\llm_models\\stabilityai\\stable-diffusion-3.5-large-GGUF\\sd3.5_large-q4_1.gguf --alias sd3.5-large --images --no-warmup --image-free-compute-memory-immediately --image-vae-tiling
0.01.047.128 I
0.01.047.145 I version: v0.0.95 (529c2ab)
0.01.047.145 I compiler: unknown
0.01.047.146 I target: unknown
0.01.047.146 I vendor:
0.01.047.146 I   - llama.cpp 0e70ba68 (4354)
0.01.047.147 I   - stable-diffusion.cpp c8837bd (208)
0.01.047.248 I system_info: n_threads = 8 (n_threads_batch = 8) / 128 | CUDA : ARCHS = 600,610,700,750,800,860,890,900 | F16 = 1 | USE_GRAPHS = 1 | PEER_MAX_BATCH_SIZE = 128 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | AVX2 = 1 | F16C = 1 | FMA = 1 | LLAMAFILE = 1 | AARCH64_REPACK = 1 |
0.01.047.249 I
0.01.048.409 I srv                      main: listening, hostname = 127.0.0.1, port = 61633, n_threads = 3 + 2
0.01.050.412 I srv                      main: loading model
0.01.050.425 I srv                load_model: loading model ''
0.01.050.492 I load_from_file: loading model from 'F:\\llm_models\\stabilityai\\stable-diffusion-3.5-large-GGUF\\sd3.5_large-q4_1.gguf'
0.01.050.781 I init_from_file: load F:\\llm_models\\stabilityai\\stable-diffusion-3.5-large-GGUF\\sd3.5_large-q4_1.gguf using gguf format
0.01.071.435 I load_from_file: Version: SD3.x
0.01.082.262 I load_from_file: Weight type:                 q4_1
0.01.082.266 I load_from_file: CLIP_L weight type:          NONE
0.01.082.267 I load_from_file: CLIP_G weight type:          NONE
0.01.082.267 I load_from_file: T5XXL weight type:           NONE
0.01.082.268 I load_from_file: Diffusion model weight type: q4_1
0.01.082.268 I load_from_file: VAE weight type:             q4_1
0.01.376.210 I MMDiT: MMDiT layers: 38 (including 0 MMDiT-x layers)
0.02.496.618 E ggml_backend_cuda_buffer_type_alloc_buffer: allocating 5257.49 MiB on device 0: cudaMalloc failed: out of memory
0.02.496.626 E alloc_params_buffer: mmdit alloc params backend buffer failed, num_tensors = 923
PS C:\Users\shibingli>

PS C:\Users\shibingli> nvidia-smi.exe
Fri Dec 20 19:12:16 2024
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 566.36                 Driver Version: 566.36         CUDA Version: 12.7     |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                  Driver-Model | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA GeForce RTX 3090      WDDM  |   00000000:31:00.0 Off |                  N/A |
| 31%   31C    P8             13W /  350W |       0MiB /  24576MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
|   1  NVIDIA GeForce RTX 3090      WDDM  |   00000000:4B:00.0 Off |                  N/A |
| 31%   28C    P8             14W /  350W |       0MiB /  24576MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
|   2  NVIDIA GeForce RTX 3090      WDDM  |   00000000:B1:00.0  On |                  N/A |
| 31%   35C    P8             36W /  350W |    1629MiB /  24576MiB |      6%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
|   3  NVIDIA GeForce RTX 3090      WDDM  |   00000000:CA:00.0 Off |                  N/A |
| 31%   32C    P8             15W /  350W |      41MiB /  24576MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

版本	Windows 11 专业工作站版
版本号	23H2
安装日期	2024/3/13
操作系统版本	22631.4602
体验	Windows 功能体验包 1000.22700.1055.0

For some reason, I tried to verify the MD5 of the model and found that the local model's MD5 did not match the MD5 of the model on the HF website. After updating, it works normally.

Thank you,  @thxCode

authors: shibingli thxCode

repo: gpustack/llama-box


text:
Question regarding reproduction of results

Hello,
Thanks for sharing the code and congratulations on your publication. I have been trying to reproduce your results on CIFAR-100 and I am not getting the average accuracy of 89.96. Here is the config file: https://pastebin.com/FzdDxBD7
Here is the log file: https://pastebin.com/qFMv3kW4
Looking forward to hearing from you :)

Hi @gulzainali98,
Thank you for your interest in our work.
After reviewing the config file and log file you've provided, it seems that you have set module.num_emas=0 in your config file (https://pastebin.com/FzdDxBD7), please setmodule.num_emas=1 (line 65) to reproduce the experiment.
If you encounter any further issues or have additional questions, please don't hesitate to reach out.
Best regards,
Qiankun Gao

Here are the new logs on class order 1 with num_emas set to 1. I downloaded your git and ran the repository without any changes.
https://pastebin.com/mSY6s5Vs
my question is what would \hat{A} in the logs be. We get following final accuracies:
Acc: 85.43
Global Per Task Accs: 85.70, 82.30, 87.10, 84.40, 87.00, 78.60, 85.30, 85.00, 89.80, 89.10
Global Task Accs Avg: 85.43
Local Per Task Accs: 99.40, 98.00, 97.20, 97.80, 97.80, 96.40, 96.60, 98.80, 98.90, 99.10

It seems that from the formula given in the paper, \hat{A} is the average global task accuracy. However, last task 9 accuracy seems to be closer to the \hat{A} reported in the paper. Looking forward to your answer.
Thanks :)

Hi, @gulzainali98，
I'm happy to provide some clarification on the terms you've encountered.

Acc: This refers to $A_{10}$ as mentioned in the paper, indicating the accuracy measured across all 10 tasks. This accuracy is calculated over the entire set of 100 classes.

Global Per Task Accs: These are the accuracies for each of the 10 tasks when tested individually. Here, classification is performed across all 100 classes too.

Global Task Accs Avg: This is the average of the 10 values listed in Global Per Task Accs.

Local Per Task Accs: These accuracies are also calculated for each of the 10 tasks individually. However, unlike Global Per Task Accs, the classification here is limited to the 10 classes relevant to each specific task.

To calculate $\bar{A}$, you would use the command grep 'Acc:' /path/to/log.txt to extract the Acc values for each of the 10 learning stages. The average of these 10 Acc values will give you the $\bar{A}$
I hope this helps clarify your doubts. If you have any more questions or need further assistance, feel free to reach out.
Best regards,
Qiankun Gao

repo: gqk/LAE


text:
Incorrect Date Conversion in nodered, moment.js in javascript works fine.

I posted this on the node-red-contrib-moment github issue board. A awesome contributor pointed me it seems to be an issue with this library.  Here is the issue.
https://github.com/TotallyInformation/node-red-contrib-moment/issues/20
Thanks!

The input value 2018-06-01T18:13:03.909192+00:00  as too many decimal points, I’ve never seen that format before. I think this lib can handle up to 3. In your case, I think that would be precise enough? Maybe remove all decimal points after that?

I went ahead and did a regex in my node-red flow to capture only the first three, so I would say there is nothing more to do here. Odd that Home Assistant does a second with so much precision.
Thanks anyways!


text:
MasterHash?

https://pool.masterhash.us/

Added via 6d42aba806ff344bd4f11776aa84e61d32c8ec70

repo: gradinkov/rudehash


text:
Depending on a Git repository with a git submodule throws an NPE

I reproduce the issue with 2 simple repositories: a library and an application that depends on that library.

I'm trying to add the library that is a Git repository as a dependency to my application with

// settings.gradle.kts

val myRepo = "https://github.com/Furetur/simplelib.git"
val myRepoProjectName = "me.user"
sourceControl {
    gitRepository(java.net.URI.create(myRepo)) {
        producesModule("$myRepoProjectName:simplelib")
    }
}

// build.gradle.kts

dependencies {
    testImplementation(kotlin("test"))

    val myRepoProjectName = "me.user"
    implementation("$myRepoProjectName:simplelib") {
        version {
            branch = "master-with-submodule"
        }
    }
}

The library has 1 git submodule. The submodule does not contain any code, only a README.
Gradle fails to build the application. However, if I remove the submodule from the library, the build passes.

Expected Behavior

Gradle should build the application if it depends on a library that has a Git submodule.
Current Behavior

Gradle throws a NullPointerException: stacktrace.txt
Context

I have a library that has tests itself on mock data. That mock data is located in another Git repo and is attached to the library as a git submodule. When I'm trying to depend on that library Gradle fails to build the application.
Steps to Reproduce

Library and application.

Clone the application and run ./gradlew build.
It should fail with that NPE
If you change the branch of the library in build.gradle.kts to master the gradle build will pass. The only difference between branches master and master-with-submodule is that the latter has a Git submodule that contains a README.

Your Environment

Build scan URL: https://scans.gradle.com/s/jmavmepum35is

One interesting thing is that the first invocation of ./gradlew build after checking out works, only consecutive ones fail.
Unfortunately, source dependencies are not in the focus so the issue is unlikely to be addressed in the short or medium term.

Should be fixed by #20090

authors: Furetur jbartok mlopatkin

repo: gradle/gradle


text:
Dependency not resolved because Gradle didn't expand profile property in version number inside POM

If a dependency uses Maven profiles to set properties of the POM, the profiles are not activated by Gradle's POM-handling logic. Thus, the properties are not set, don't get substituted, and adding the dependency fails.
Steps to Reproduce
Try to add this dependency to your build:
dependencies {
    implementation("org.jfree:org.jfree.skijagraphics2d:1.0.4")
}

Expected Behavior
The dependency is resolved.
Current Behavior
Dependency resolution fails, and you can see the unsubstituted variable still in the version string:
compose-math:jvmMain: Could not find io.github.humbleui:skija-${skija.platform}:0.98.1.
Required by:
    project : > org.jfree:org.jfree.skijagraphics2d:1.0.4

Context
I was just trying to add an implementation dependency.
But the library in question seems to be using some feature of Maven where it loads different dependencies depending on what platform you're on. I guess it's a reasonable feature, but I had no idea that was possible. (It certainly wasn't possible back when I was using Maven.)
In any case, it seems that in this instance I would have to use a ClientModule or similar in order to use that library.

Your Environment

Windows 10
Java 11
Gradle 7.1.1

Build scan URL:

Support for Maven Profiles in Gradle is limited.
See #19225
There are no plans at this point to improve the situation.

authors: hakanai ljacomet


text:
Tests are skipped when maxParallelForks number is low

Expected Behavior
Should run all tests in tests folder
Current Behavior
I have a Spring Boot app with Gradle and a few dozens of tests. The tests are divided into packages and all packages are located under the standard tests folder. Some of the tests run test containers. The build.gradle file contains a setting for maxParallelFork:
 useJUnitPlatform {         maxParallelForks = 1 }
I noticed that when maxParallelForks = 1, about half of the tests are simply skipped. When I open the Gradle test report, the tests are not marked as skipped, but simply don't appear in the report at all. When maxParallelForks is equal to half of the number of available processors, most of the tests are executed, but still some are skipped. Only when maxParallelForks is equal to the number of available processors, all tests are run and pass:
 useJUnitPlatform {         maxParallelForks = Runtime.runtime.availableProcessors() }
That makes me wonder though, what will happen when more and more tests will be added, and the number of available processors won't be enough so tests again will get skipped.
My machine:
MacOS Apple M1 Pro, Ventura 13.4
Gradle 7.5.1
Spring Boot 2.7.12
Junit 5
Context (optional)
No response
Steps to Reproduce
Create a few dozens of integration tests with test containers and run them with different values of maxParallelForks, preferably on Apple M1 Pro.
Gradle version
7.5.1
Build scan URL (optional)
No response
Your Environment (optional)
No response

Sorry that you're having trouble with Gradle!
We appreciate the effort that went into filing this issue, but we must ask for more information.
As stated in our issue template, a minimal reproducible example is a must for us to be able to track down and fix your problem efficiently. Our available resources are severely limited, and we must be sure we are looking at the exact problem you are facing.
If we have a reproducer, we may be able also to suggest workarounds or ways to avoid the problem.
The ideal way to provide a reproducer is to leverage our reproducer template. You can also use Gradle Project Replicator to reproduce the structure of your project.
This issue will be closed after 7 days unless you provide more information.


text:
Do not add enforced-platform variant to published components

Instead, implement enforcedPlatform() with strict versions for external modules:

For external dependencies, we use stricty and no additional variant. This avoids "leaking" an enforced-platform variant everywhere causing potential disambiguety issues and in general make matching issues/errors harder to understand.
In particular, there is no more variant derivation for Gradle Module Metadata directly in the parser (!).
It also means cleaner semantics and error messages as we do not use "force" anymore.
For platform projects, we still use the enforced platform variant. But that's only an internal usage of the attribute/variant can be improved in the future. Also, the java-platform plugin comes with additional disambiguation rules to deal with the variant.
declaring enforcedPlatform for dependency constraints is deprecated. It won't work this way and I fail to see the use case for it. There is also not test coverage. (This could maybe be removed directly - it was still incubating.)

I'm wondering because using strictly is not strictly (no pun intended) the same. If you're lucky, it is. However there's the possibility that consumers break because they would use a non compatible version.

This is solved by #11118 instead

authors: jjohannes melix


text:
Allow included builds to contribute settings plugins

https://github.com/gradle/gradle/issues/14562
This change allows builds that contribute build logic to be included via a new (private for now) API in settings:
pluginManagement {
    includeBuild('included-build')
}

Behavior of builds included using this API:

If a settings plugin is applied in a project and if it is not found in a binary repository, then included builds (included using the new API) will be configured and searched for settings plugins.

If a plugin is applied in a project without a version specified or a plugin with a given version is not found in binary repositories, then included builds (included via the new API) will be configured (possibly early for settings plugins) and searched for plugins.

Can contribute project plugins. If the above conditions that would trigger early configuration of those builds are not satisfied, the builds will be configured at the time the regular included builds (included outside of pluginManagement {}) are configured. If the build happens to be configured early because of the above conditions, it can still contribute project plugins.

Can not contribute library components to the build. Regular included builds, included outside of pluginManagement {} should be used for this. If a build contributes both build logic and libraries, then such build should be included twice - once in pluginManagement {} and once outside it. This works similarly to repositories - they are separate for plugins and production components and if the same repository is used for both, it is specified once for each use case.

This PR is gold, thank you so much for doing it!

authors: TWiStErRob rieske


text:
Fix failed tests after upgrading to JDK 17

Cherrypick the fix from master.

@bot-gradle test and merge

Your PR is queued. See the queue page for details.

OK, I've already triggered a build for you.

authors: blindpirate bot-gradle


text:
Fixing for better understanding

Fix #28078
Context

Contributor Checklist

[x] Review Contribution Guidelines
[x] Make sure that all commits are signed off to indicate that you agree to the terms of Developer Certificate of Origin.
[x] Make sure all contributed code can be distributed under the terms of the Apache License 2.0, e.g. the code was written by yourself or the original code is licensed under a license compatible to Apache License 2.0.
[x] Check "Allow edit from maintainers" option in pull request so that additional changes can be pushed by Gradle team
[ ] Provide integration tests (under <subproject>/src/integTest) to verify changes from a user perspective
[ ] Provide unit tests (under <subproject>/src/test) to verify logic
[ ] Update User Guide, DSL Reference, and Javadoc for public-facing changes
[ ] Ensure that tests pass sanity check: ./gradlew sanityCheck
[ ] Ensure that tests pass locally: ./gradlew <changed-subproject>:quickTest

Reviewing cheatsheet
Before merging the PR, comments starting with

❌ ❓must be fixed
🤔 💅 should be fixed
💭 may be fixed
🎉 celebrate happy things

Thank you for your contribution!

@bot-gradle merge

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@bot-gradle merge

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authors: bot-gradle helfese ov7a


text:
Pyroscope Java profiling not working after following documentation

What's wrong?
After following the documentation here, profiling of Java processes results in the following errors for all processes:
{"ts":"2024-09-04T20:14:23.991554124Z","level":"error","msg":"failed to get process info","component_path":"/","component_id":"discovery.process.all","err":"readlink /proc/1/exe: permission denied","pid":1}
{"ts":"2024-09-04T20:14:23.991644175Z","level":"error","msg":"failed to get process info","component_path":"/","component_id":"discovery.process.all","err":"readlink /proc/2/exe: permission denied","pid":2}
{"ts":"2024-09-04T20:14:23.991677615Z","level":"error","msg":"failed to get process info","component_path":"/","component_id":"discovery.process.all","err":"readlink /proc/3/exe: permission denied","pid":3}
{"ts":"2024-09-04T20:14:23.991708775Z","level":"error","msg":"failed to get process info","component_path":"/","component_id":"discovery.process.all","err":"readlink /proc/4/exe: permission denied","pid":4}
{"ts":"2024-09-04T20:14:23.991749485Z","level":"error","msg":"failed to get process info","component_path":"/","component_id":"discovery.process.all","err":"readlink /proc/6/exe: permission denied","pid":6}
{"ts":"2024-09-04T20:14:23.991779286Z","level":"error","msg":"failed to get process info","component_path":"/","component_id":"discovery.process.all","err":"readlink /proc/8/exe: permission denied","pid":8}
{"ts":"2024-09-04T20:14:23.991807106Z","level":"error","msg":"failed to get process info","component_path":"/","component_id":"discovery.process.all","err":"readlink /proc/9/exe: permission denied","pid":9}
...

Helm values:
alloy:
  configMap:
    create: false
    name: alloy-config
    key: config.alloy
  stabilityLevel: "generally-available"
  enableReporting: false
  securityContext:
    runAsUser: 0

controller:
  type: daemonset
  hostPID: true

Alloy config:
logging {
	level  = "info"
	format = "json"
}

discovery.kubernetes "local_pods" {
  selectors {
    field = "spec.nodeName=" + env("HOSTNAME")
    role = "pod"
  }
  role = "pod"
}

discovery.relabel "java_pods" {
  targets = discovery.kubernetes.local_pods.targets
  // Filter only java processes
  rule {
    source_labels = ["__meta_process_exe"]
    action = "keep"
    regex = ".*/java$"
  }
  rule {
    action = "drop"
    regex = "Succeeded|Failed|Completed"
    source_labels = ["__meta_kubernetes_pod_phase"]
  }
  rule {
    action = "replace"
    source_labels = ["__meta_kubernetes_namespace"]
    target_label = "namespace"
  }
  rule {
    action = "replace"
    source_labels = ["__meta_kubernetes_pod_name"]
    target_label = "pod"
  }
  rule {
    action = "replace"
    source_labels = ["__meta_kubernetes_pod_node_name"]
    target_label = "node"
  }
  rule {
    action = "replace"
    source_labels = ["__meta_kubernetes_pod_container_name"]
    target_label = "container"
  }
  // Provide arbitrary service_name label, otherwise it will be inferred from discovery labels automatically
  rule {
    action = "replace"
    regex = "(.*)@(.*)"
    replacement = "java/${1}/${2}"
    separator = "@"
    source_labels = ["__meta_kubernetes_namespace", "__meta_kubernetes_pod_container_name"]
    target_label = "service_name"
  }
}

pyroscope.java "java" {
  forward_to = [pyroscope.write.pyroscope_write.receiver]
  targets = discovery.relabel.java_pods.output
}

pyroscope.write "pyroscope_write" {
	endpoint {
		url = "http://pyroscope.pyroscope.svc.cluster.local:4040"
	}
}

Steps to reproduce
Install Alloy in a Kubernetes cluster using the above values and configuration
System information
Linux version 5.10.223-212.873.amzn2.x86_64
Software version
Grafana Alloy v1.3.1
Configuration
logging {
	level  = "info"
	format = "json"
}

discovery.kubernetes "local_pods" {
  selectors {
    field = "spec.nodeName=" + env("HOSTNAME")
    role = "pod"
  }
  role = "pod"
}

discovery.relabel "java_pods" {
  targets = discovery.kubernetes.local_pods.targets
  // Filter only java processes
  rule {
    source_labels = ["__meta_process_exe"]
    action = "keep"
    regex = ".*/java$"
  }
  rule {
    action = "drop"
    regex = "Succeeded|Failed|Completed"
    source_labels = ["__meta_kubernetes_pod_phase"]
  }
  rule {
    action = "replace"
    source_labels = ["__meta_kubernetes_namespace"]
    target_label = "namespace"
  }
  rule {
    action = "replace"
    source_labels = ["__meta_kubernetes_pod_name"]
    target_label = "pod"
  }
  rule {
    action = "replace"
    source_labels = ["__meta_kubernetes_pod_node_name"]
    target_label = "node"
  }
  rule {
    action = "replace"
    source_labels = ["__meta_kubernetes_pod_container_name"]
    target_label = "container"
  }
  // Provide arbitrary service_name label, otherwise it will be inferred from discovery labels automatically
  rule {
    action = "replace"
    regex = "(.*)@(.*)"
    replacement = "java/${1}/${2}"
    separator = "@"
    source_labels = ["__meta_kubernetes_namespace", "__meta_kubernetes_pod_container_name"]
    target_label = "service_name"
  }
}

pyroscope.java "java" {
  forward_to = [pyroscope.write.pyroscope_write.receiver]
  targets = discovery.relabel.java_pods.output
}

pyroscope.write "pyroscope_write" {
	endpoint {
		url = "http://pyroscope.pyroscope.svc.cluster.local:4040"
	}
}

Logs
{"ts":"2024-09-04T20:14:23.783384097Z","level":"info","boringcrypto enabled":false}
{"ts":"2024-09-04T20:14:23.783438837Z","level":"info","msg":"starting complete graph evaluation","controller_path":"/","controller_id":"","trace_id":"c1709a86c9849a4bc42d9586b31a673f"}
{"ts":"2024-09-04T20:14:23.783469298Z","level":"info","msg":"finished node evaluation","controller_path":"/","controller_id":"","trace_id":"c1709a86c9849a4bc42d9586b31a673f","node_id":"logging","duration":119411}
{"ts":"2024-09-04T20:14:23.783507508Z","level":"info","msg":"finished node evaluation","controller_path":"/","controller_id":"","trace_id":"c1709a86c9849a4bc42d9586b31a673f","node_id":"labelstore","duration":9270}
{"ts":"2024-09-04T20:14:23.783551438Z","level":"info","msg":"finished node evaluation","controller_path":"/","controller_id":"","trace_id":"c1709a86c9849a4bc42d9586b31a673f","node_id":"tracing","duration":8990}
{"ts":"2024-09-04T20:14:23.783574438Z","level":"info","msg":"finished node evaluation","controller_path":"/","controller_id":"","trace_id":"c1709a86c9849a4bc42d9586b31a673f","node_id":"otel","duration":1810}
{"ts":"2024-09-04T20:14:23.78361252Z","level":"info","msg":"applying non-TLS config to HTTP server","service":"http"}
{"ts":"2024-09-04T20:14:23.78362498Z","level":"info","msg":"finished node evaluation","controller_path":"/","controller_id":"","trace_id":"c1709a86c9849a4bc42d9586b31a673f","node_id":"http","duration":32892}
{"ts":"2024-09-04T20:14:23.783952992Z","level":"info","msg":"finished node evaluation","controller_path":"/","controller_id":"","trace_id":"c1709a86c9849a4bc42d9586b31a673f","node_id":"cluster","duration":2580}
{"ts":"2024-09-04T20:14:23.784420467Z","level":"info","msg":"Using pod service account via in-cluster config","component_path":"/","component_id":"discovery.kubernetes.local_pods"}
{"ts":"2024-09-04T20:14:23.784886451Z","level":"info","msg":"finished node evaluation","controller_path":"/","controller_id":"","trace_id":"c1709a86c9849a4bc42d9586b31a673f","node_id":"discovery.kubernetes.local_pods","duration":877908}
{"ts":"2024-09-04T20:14:23.785026342Z","level":"info","msg":"finished node evaluation","controller_path":"/","controller_id":"","trace_id":"c1709a86c9849a4bc42d9586b31a673f","node_id":"discovery.process.all","duration":90800}
{"ts":"2024-09-04T20:14:23.785502667Z","level":"info","msg":"finished node evaluation","controller_path":"/","controller_id":"","trace_id":"c1709a86c9849a4bc42d9586b31a673f","node_id":"discovery.relabel.java_pods","duration":403204}
{"ts":"2024-09-04T20:14:23.786070292Z","level":"info","msg":"finished node evaluation","controller_path":"/","controller_id":"","trace_id":"c1709a86c9849a4bc42d9586b31a673f","node_id":"pyroscope.write.pyroscope_write","duration":518875}
{"ts":"2024-09-04T20:14:23.929998101Z","level":"info","msg":"finished node evaluation","controller_path":"/","controller_id":"","trace_id":"c1709a86c9849a4bc42d9586b31a673f","node_id":"pyroscope.java.java","duration":143866429}
{"ts":"2024-09-04T20:14:23.930232423Z","level":"info","msg":"finished node evaluation","controller_path":"/","controller_id":"","trace_id":"c1709a86c9849a4bc42d9586b31a673f","node_id":"remotecfg","duration":132201}
{"ts":"2024-09-04T20:14:23.930302133Z","level":"info","msg":"finished node evaluation","controller_path":"/","controller_id":"","trace_id":"c1709a86c9849a4bc42d9586b31a673f","node_id":"livedebugging","duration":25870}
{"ts":"2024-09-04T20:14:23.930370644Z","level":"info","msg":"finished node evaluation","controller_path":"/","controller_id":"","trace_id":"c1709a86c9849a4bc42d9586b31a673f","node_id":"ui","duration":14340}
{"ts":"2024-09-04T20:14:23.930394904Z","level":"info","msg":"finished complete graph evaluation","controller_path":"/","controller_id":"","trace_id":"c1709a86c9849a4bc42d9586b31a673f","duration":147237459}
{"ts":"2024-09-04T20:14:23.931033431Z","level":"info","msg":"scheduling loaded components and services"}
{"ts":"2024-09-04T20:14:23.931588126Z","level":"info","msg":"starting cluster node","service":"cluster","peers_count":0,"peers":"","advertise_addr":"127.0.0.1:12345"}
{"ts":"2024-09-04T20:14:23.932640515Z","level":"info","msg":"peers changed","service":"cluster","peers_count":1,"peers":"grafana-alloy-4pt7h"}
{"ts":"2024-09-04T20:14:23.933006819Z","level":"info","msg":"now listening for http traffic","service":"http","addr":"0.0.0.0:12345"}
{"ts":"2024-09-04T20:14:23.991554124Z","level":"error","msg":"failed to get process info","component_path":"/","component_id":"discovery.process.all","err":"readlink /proc/1/exe: permission denied","pid":1}
{"ts":"2024-09-04T20:14:23.991644175Z","level":"error","msg":"failed to get process info","component_path":"/","component_id":"discovery.process.all","err":"readlink /proc/2/exe: permission denied","pid":2}
{"ts":"2024-09-04T20:14:23.991677615Z","level":"error","msg":"failed to get process info","component_path":"/","component_id":"discovery.process.all","err":"readlink /proc/3/exe: permission denied","pid":3}
{"ts":"2024-09-04T20:14:23.991708775Z","level":"error","msg":"failed to get process info","component_path":"/","component_id":"discovery.process.all","err":"readlink /proc/4/exe: permission denied","pid":4}
{"ts":"2024-09-04T20:14:23.991749485Z","level":"error","msg":"failed to get process info","component_path":"/","component_id":"discovery.process.all","err":"readlink /proc/6/exe: permission denied","pid":6}
{"ts":"2024-09-04T20:14:23.991779286Z","level":"error","msg":"failed to get process info","component_path":"/","component_id":"discovery.process.all","err":"readlink /proc/8/exe: permission denied","pid":8}
{"ts":"2024-09-04T20:14:23.991807106Z","level":"error","msg":"failed to get process info","component_path":"/","component_id":"discovery.process.all","err":"readlink /proc/9/exe: permission denied","pid":9}

Adding the following allows the container to read what it needs:
alloy:
  # ...
  securityContext:
    runAsUser: 0
    runAsNonRoot: false
    capabilities:
      add:
        - all

Is it documented anywhere which capabilities are required for Alloy to function?
Thanks

Yes, it is documented https://grafana.com/docs/alloy/latest/reference/components/pyroscope/pyroscope.java/#pyroscopejava

Yes, it is documented https://grafana.com/docs/alloy/latest/reference/components/pyroscope/pyroscope.java/#pyroscopejava

Hi @korniltsev! The only thing I can see in that documentation is a note about requiring root and running inside the host pid namespace, but that is not necessarily sufficient for things to work if linux capabilities are enabled (of which they will usually be in any well-configured production environment).
Took a little trial and error, but we found that the following was sufficient for our use case (using Grafana Alloy only to scrape data for Pyroscope):
alloy:
  # ...
  securityContext:
    runAsUser: 0
    runAsNonRoot: false
    capabilities:
      add:
        - PERFMON
        - SYS_PTRACE
        - SYS_RESOURCE
        - SYS_ADMIN

We run it as "privileged" root.
I agree we need to update docs

authors: caspar-ds korniltsev

repo: grafana/alloy


text:
Fix Async go call handling

When we have async calls within server request handlers, it might be the child goroutine that finishes the response to the request. This PR handles this scenario.

Codecov Report
All modified lines are covered by tests :white_check_mark:

Comparison is base (1ab5942) 74.25% compared to head (3988958) 49.12%.

Additional details and impacted files
@@             Coverage Diff             @@
##             main     #320       +/-   ##
===========================================
- Coverage   74.25%   49.12%   -25.13%
===========================================
  Files          39       34        -5
  Lines        3376     2701      -675
===========================================
- Hits         2507     1327     -1180
- Misses        665     1290      +625
+ Partials      204       84      -120

Flag
Coverage Δ

integration-test
?

unittests
49.12% <ø> (?)

Flags with carried forward coverage won't be shown. Click here to find out more.
see 36 files with indirect coverage changes

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

Thanks Matt!

authors: codecov-commenter grcevski

repo: grafana/beyla


text:
Support Microsoft SQL Server Source

Currently, there are no query target helpers/functions for Microsoft SQL Server.
It would be great to support Microsoft SQL Server as this data source is quite popular.

I have created a short workaround by adding some file in the code deployed by the jb install:

vendor\custom\query\sql.libsonnet

local d = import 'github.com/jsonnet-libs/docsonnet/doc-util/main.libsonnet';

{
  '#new':: d.func.new(
    'Creates a new Microsoft SQL Server query target for panels.',
    args=[
      d.arg('datasource', d.T.string),
	  d.arg('rawSql', d.T.string),
	  d.arg('format', d.T.string),
	  d.arg('rawEditor', d.T.bolean),
	  d.arg('rawQuery', d.T.bolean),
      d.arg('queryText', d.T.string),
    ]
  ),
  new(datasource, rawSql, format='time_series', rawEditor=true, rawQuery=true, queryText=rawSql):
    self.withDatasource(datasource)
    + {
		format: format,
		rawSql: rawSql,
		rawEditor: rawEditor,
		rawQuery: rawQuery,
		queryText: queryText,
	  },

  '#withDatasource':: d.func.new(
    'Set the datasource for this query.',
    args=[
      d.arg('value', d.T.string),
    ]
  ),
  withDatasource(value): {
    datasource+: {
      type: 'Microsoft SQL Server',
      uid: value,
    },
  },
  '#withDatasourceMixin':: { ignore: true },
}

vendor/query.libsonnet

 // This file is generated, do not manually edit.
{
  '#': { help: 'grafonnet.query', name: 'query' },
  azureMonitor: import 'query/azureMonitor.libsonnet',
  cloudWatch: import 'query/cloudWatch.libsonnet',
  elasticsearch: import 'query/elasticsearch.libsonnet',
  expr: import 'query/expr.libsonnet',
  googleCloudMonitoring: import 'query/googleCloudMonitoring.libsonnet',
  grafanaPyroscope: import 'query/grafanaPyroscope.libsonnet',
  loki: import 'query/loki.libsonnet',
  parca: import 'query/parca.libsonnet',
  prometheus: import 'query/prometheus.libsonnet',
  tempo: import 'query/tempo.libsonnet',
  testData: import 'query/testData.libsonnet',
  sql: import 'query/sql.libsonnet'
}

\vendor\query\sql.libsonnet

// This file is generated, do not manually edit.
{
  '#': { help: 'grafonnet.query.sql', name: 'sql' },
  '#withDatasource': { 'function': { args: [{ default: null, enums: null, name: 'value', type: ['object'] }], help: "For mixed data sources the selected datasource is on the query level.\nFor non mixed scenarios this is undefined.\nTODO find a better way to do this ^ that's friendly to schema\nTODO this shouldn't be unknown but DataSourceRef | null" } },
  withDatasource(value): {
    datasource: value,
  },
  '#withDatasourceMixin': { 'function': { args: [{ default: null, enums: null, name: 'value', type: ['object'] }], help: "For mixed data sources the selected datasource is on the query level.\nFor non mixed scenarios this is undefined.\nTODO find a better way to do this ^ that's friendly to schema\nTODO this shouldn't be unknown but DataSourceRef | null" } },
  withDatasourceMixin(value): {
    datasource+: value,
  },
}
+ (import '../custom/query/sql.libsonnet')

repo: grafana/grafonnet


text:
Deprecate "ANY" data quality

Is your feature request related to a problem? Please describe.
I recently spent time debugging an issue where I set up a GetInterpolatedPropertyValues query and did not receive any data back when I should have. After a lot of digging I realized that I was using the "ANY" quality and the data I expected back was all "BAD". We recently updated "ANY" to default to "GOOD" which should not be the assumption.
"ANY" is not a valid API prompt, so we should not support this in our datasource query.
Describe the solution you'd like
We should remove "ANY" as a quality option for all Get* APIs, and instead just have "GOOD"/"BAD"/"UNCERTAIN". We should default to "GOOD".
Describe alternatives you've considered
The only alternative is to actually implement "ANY" by querying the Get APIs with each possible quality and combining the values into a single response.
Additional context
None

@hwandersman In the description it says

"ANY" to default to "GOOD" which should not be the assumption.

But in the solution section it says

We should default to "GOOD".

Can you clarify a bit better what you expect the end behavior to be?
In the linked PR, we already removed the "ANY" dropdown option from the query editor and if there's no quality selected, it defaults to GOOD here. This sounds to me like the solution proposed, lmk if I misunderstand!

Ah I see it was fully removed for the Interpolated query. We just need to do the same for the "Get property value aggregates" and "Get property value history" queries.

authors: hwandersman idastambuk

repo: grafana/iot-sitewise-datasource


text:
Support complex MQTT Payloads

Hello!
Nice plugin. Can you please update the documentation with information on how to format the payload?
No matter what I try, all I get is "Data does not have a time field"
Can I have complex objects with multiple values? Can I instruct it to parse the json?
E.g
{
  foo: {
   bar: 1337
  }
  baz: 555
}

Thanks!

Currently the plugin supports simple values ie "555" or a simple map[string]number -- we should be able to support a more complex shape

Thanks!
The no-data was solved by setting a low timerange, like 5 mins. I used it in an existing dashboard which defaulted to 30d.

I'm new to grafana. Could you give more specific examples of the what the data should look like (i.e. what does map[string]number mean?) . I can generate data points with mosquitto_pub -t grafana -m 555 but want to attach a time to the data.

currently we support very basic JSON structures like:
{
    'value1': 1.0,
    'value2': 2,
    'value3': 3.33,
    ...
}

notice how the key is string and the value is number in the JSON, that is what map[string]number (golang lingo) means in this context.
we do plan to bring support for more complex JSON structures soon (contributions are always welcome too 🙂)
as far as the timestamp is concerned currently we just naively use time.Now() for every message coming in, see: https://github.com/grafana/mqtt-datasource/blob/46b617808aab084804a89dd5b7ad31462e106d7f/pkg/mqtt/client.go#L98
however i do agree we should have a way to set that based on the incoming message in cases where the data is delayed and needs a timestamp on the publisher side to be propagated. any suggestions on this?

Thanks for the detailed reply. I'm currently sending just raw data. Once I understand more about Grafana I'll try out your more complex json payload and recommend how time might be encoded.
Re: contributions your typescript and go code (and how they interact) is beyond me at this point (I'm a C++/Java/Python guy).

support for more data types with the JSON payload would be super handy as part of this enhancement, see: https://github.com/grafana/mqtt-datasource/issues/19

Hi @atifali,
How do you plan to support more complex json? will that be arbitrary json?
This has caught my attention, I think it is awesome: https://grafana.com/blog/2021/08/12/streaming-real-time-sensor-data-to-grafana-using-mqtt-and-grafana-live/
But we can currently not use it, because our json is more complex and also subject to change.

Hi @rafaelschlatter really appreciate your enthusiasm and patience with this. We are currently in the midst of incorporating a very versatile and flexible automatic JSON processor within Live "pipelines" in Grafana core (see: https://github.com/grafana/grafana/tree/main/pkg/services/live/pipeline), which will eventually be used here. This means that virtually any message that has a valid JSON format would work. Stay tuned!

Sounds awesome, thanks for the update, @atifali !

@rafaelschlatter that sounds awesome, nice work!

Hello, what is the status for the integration of the Live "pipelines" JSON processor in mqtt-datasource? Do you have any news? thanks and have a good day.

One idea about complex mqtt payloads would be to implement something like what Amazon did for the rules processing feature of IoT Core.  Essentially, it allows you to use a language very close to SQL to "select" data out of a JSON object of arbitrary structure and depth, pull out the data you want, rename the fields, and do some basic math on them.  Some of what they do probably wouldn't be necessary here (I don't think you really need WHERE clauses, for example).

Sorry, which the state of this integration? I tried to understand it by clicking on the various links: closed, enahuced, open ....
It's Like a stuck loop

Hello, What is the status of this?

Any progress on this?

authors: Appelg DonatoD OlivierGre atifali grabouillon06 pkkrusty rafaelschlatter ryantxu whbruce wz2b

repo: grafana/mqtt-datasource


text:
Update OG image

OG share image still says "one new recipe every day" and we're switching to a more flexible schedule (prob twice a week).

Could fork https://github.com/styfle/og-image to generate custom images for each post with hook name in the image.

repo: gragland/usehooks

license: Unlicense


text:
Test the CTCast and Python script to make sure they have identical outputs

Maybe also change how the fake server works to accept both the Python script and CTCast at once

This could not work as a unit test because it requires multiple applications (scripts) to work together.

Updated fake server. Now it takes input from ports 10002 and 10003. we select 10003 as the "comparison group"  which runs the python script. The python script is updated as well.

Seems that they are providing same outputs now.

authors: HanBoyou romerorisa

repo: grainger-illinois/CTCast


text:
How to deal with Viewpager?

I use a viewpager
a) to show data in RecyclerViews
b) to create a new object
and I'm interested how to use it with your lib.

ThirtyInch doesn't define how you structure your UI implementation. ViewPager works as well but your Activity (the TiView implementation) is responsible to forward the data to the corresponding pages inside the ViewPager. The presenter doesn't know about the ViewPager, it only knowns the TiView has multiple lists which have to be filled with data.
It's hard to guess how you are using the ViewPager right now. Here some suggestions:
You can use a ViewPager with fragments inside. Each Fragment can have it's own presenter. This is useful when one tab is totally independent from the others.
We recently had a UI with two tabs showing different lists. We used a ViewPager to switch between them. Instead of a ViewPager with fragments we used plain views (RecyclerView) and filled the data in those adapters from the presenter.

I'm using the ViewPager with fragments.

I have ViewPagers with fragments inside which have ReceyclerViews. Data is loaded from database. User could interact with RecyclerView-items (mark favorite, open items,...).
The RecyclerView-items (items look nearly same and also the functionality is nearly the same (items have state "running"/"finished", therefore different interactions)).

And I also have ViewPager to create an item. This means every fragment is completely different - but at the sum all data of the fragments is ONE object which will be created. I have to validate the input data (not only for one fragment but for all fragments together).

@passsy Should I provide more information? What do you need? I'm very interested in using this lib.

There is no "right" way to implement MVP with ThirtyInch when your UI has a ViewPager. It's totally up to you.
You can put presenters in the fragments of the ViewPager, you can put a single presenter in the Activity. I've seen and implemented all of those scenarios. All have pros and cons and you have to decide what fits best into your app architecture and personal preference.
First of all you should ask yourself what kind of problem you are trying to solve with the introduction of MVP. That's why I can't answer your questions. I have no idea what stops you from using Ti.
If you don't have a problem you should not use Ti.

One last question in this thread (thanks for your time):

You can put presenters in the fragments of the ViewPager, you can put a single presenter in the Activity. I've seen and implemented all of those scenarios. All have pros and cons and you have to decide what fits best into your app architecture and personal preference.

And all scenarios are working with Ti?

yes, there is TiActivity and TiFragment

authors: Rainer-Lang passsy

repo: grandcentrix/ThirtyInch


text:
failed to find error!

i get this error when when want add it to android studio:
Error:Failed to find: me.grantland:autofittextview:0.2.+

You need to add mavenCentral() to your main build.gradle script like the following:
buildscript {
    repositories {
        mavenCentral()
    }
    ...
}

authors: grantland miladsalehi

repo: grantland/android-autofittextview