Issue/8071 store i18n dictionary

:id:
Fixes #8071
:pencil2: A description of the changes proposed in the pull request
All of the work required to create, read, update and delete i18n dictionaries and their translations:
Backend
REST resource, service and mongo/jdbc repository implementations, testcontainer test, Jest integration testing.
All the files under gravitee-am-test/api/management have been generated by the OpenApi generator tool and can be ignored for review purposes.
Frontend
New form added to Domain settings for CRUDing dictionaries and adding/removing translations.
:computer:

Few comments on the UI:
We can add two languages with the same code, this will probably lead to unexpected behaviour as the underlying i18n mechanism will probably take care of the first one (or last one). Also we may provide a dropdown list of supported code filtered based on the user input like proposed in figma.
The screen doesn't match the one provided in figma:

there is a "SAVE CHANGES" button in the language section that is missing in your version
the "SAVE CHANGES" button in the Translation section use the wrong background color and when there are no new entries, it should be deisabled.
the "Edit in a File" tab visible in figma is missing, so the user can't upload a properties files with all the translation at once.

About the default language, I wondering if we should enable the defaultLocale option by default for the first language created and when a language with the default flag is deleted, maybe we should enable this flag on the first language of the list to be sure that there will be a default language? wdyt ?

Yes I think that's a good idea. What about Audrey's suggestion that a sole language can't be deleted?
If we're going to provide a list of codes, don't you agree that we should provide a list of display names as well? There are libraries that can provide this, I believe. The only snag is that the lists will need to be language specific (e.g. "Deutsch" for ger when the user's browser settings are in German).

When a domain is deleted, we do not clean the related dictionaries. We should clean all of them to avoid orphan data https://github.com/gravitee-io/gravitee-access-management/blob/master/gravitee-am-service/src/main/java/io/gravitee/am/service/impl/DomainServiceImpl.java#L371

Done.

UI comments :

Default locale checkbox is useless in the table list
Do not push the package-lock.json file

I'm working against the figma screens designed by Audrey and agreed by John and Eric which feature a toggle for default_locale. I thought the plan was to move default_locale to the Domain but that still needs the toggle in order to set it, surely?


Gitpod dev environment

Set up a click-to-start https://gitpod.io/ workspace to create a low barrier of entry for contributors or others who want to tinker with our solution.
The first time it should run "docker-compose up -d", run "make schema-newest", etc.
https://www.gitpod.io/docs/configure

Lots of things can be packaged well (for example I am using a PubSub and an S3 emulator) but some don't really have anything like that available (AWS media packager) so not everything will be possible in an automated way with no "real" credentials involved.
Mocks could be considered in this case as that would also to some extent enable offline development.


Added ability to localize based on user's location

Instead of listing position options as elsewhere, it might be possible to localize to the user's own location, using the user's IP to detect where he or she is, and render in the site copy.
This would help make possible remote workers feel encouraged to apply.

 Thank you for your submission, we really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.:x: azilnik sign nowYou have signed the CLA already but the status is still pending? Let us recheck it.

This is nice!
Did you forget to remove the API Key ?

@leovarmak good call out! I removed the API Key. @prichodko, I added a comment in location.js about including an API key if this were to be merged. Here is what it looks like with the API key all set up properly.

Hey @azilnik, thanks for you contribution! Although it's a neat feature I am afraid it could confuse people into thinking there is a Microsoft office hiring in their city, which probably is not true. What do you think

It's a good call-out @prichodko! I think it would work if there are remote opportunities. Hmm I wonder if there's a way to get the user's location data and match it to open roles, and indicate whether you're hiring in that particular location. Thoughts?


Make tablex.deepcopy and tablex.deepcompare cycle-aware.

Make these functions support tables featuring cycles.

Coverage decreased (-0.05%) to 83.787% when pulling 7fc5c234ff85580931350656d08d5429a4e2af11 on hishamhm:cycle-aware into e644b725c57062956d338c0fced6985d851b8fd7 on stevedonovan:master.

Coverage increased (+0.02%) to 83.856% when pulling d81221ecf37b7bcf68d05e5ac3d0e2010fb6d001 on hishamhm:cycle-aware into e644b725c57062956d338c0fced6985d851b8fd7 on stevedonovan:master.

Coverage increased (+0.02%) to 83.856% when pulling d81221ecf37b7bcf68d05e5ac3d0e2010fb6d001 on hishamhm:cycle-aware into e644b725c57062956d338c0fced6985d851b8fd7 on stevedonovan:master.

Coverage increased (+0.02%) to 83.856% when pulling d81221ecf37b7bcf68d05e5ac3d0e2010fb6d001 on hishamhm:cycle-aware into e644b725c57062956d338c0fced6985d851b8fd7 on stevedonovan:master.

Coverage increased (+0.02%) to 83.856% when pulling d81221ecf37b7bcf68d05e5ac3d0e2010fb6d001 on hishamhm:cycle-aware into e644b725c57062956d338c0fced6985d851b8fd7 on stevedonovan:master.

Coverage increased (+0.02%) to 83.856% when pulling d81221ecf37b7bcf68d05e5ac3d0e2010fb6d001 on hishamhm:cycle-aware into e644b725c57062956d338c0fced6985d851b8fd7 on stevedonovan:master.

Coverage increased (+0.02%) to 83.856% when pulling d81221ecf37b7bcf68d05e5ac3d0e2010fb6d001 on hishamhm:cycle-aware into e644b725c57062956d338c0fced6985d851b8fd7 on stevedonovan:master.

lgtm

@mpeterv @stevedonovan can we merge this and cut a release?


Error message instead of object

Fixes https://github.com/snapshot-labs/snapshot-hub/issues/413

I think this can be closed, as most of the files does not exist anymore


Detach Delete performance questions

I'm finding DETACH DELETE of a filtered list of nodes to be very slow in comparison with the equivalent match or create. I understand there's work to do but its taking 30 seconds to delete 1000 vertices.
Given a schema where we have Observations(100000s), Features (1000s) and Properties( 100s) and Datasets (10s)
That each observation has three outgoing edges ( example values )

(o:Observation) -[observedProperty]-> (p:Property { id: 'water_temperature_celsius'})
(o:Observation) -[featureOfInterest]-> (f:Feature { id: 'tank:A01'})
(o:Observation) -[in]-> (d:Dataset { id: 'site_temperatures'})

The Observation has properties such as date, result etc.
Creating and Matching observations performance is very good - I can upload 1000s of observations a second and retrieving a set of observations filtered on particular properties and belonging to a given dataset takes only a few seconds to get MB of results.
However, Deleting observations is really really slow in comparison.
For example to remove all the obs in a dataset.
MATCH (o:Observation)-[in]->(d:Dataset { id: 'site_temperatures'} )
DETACH DELETE o
RETURN o

Takes so long it times out.  I have seen examples where the database process receives a kill 9 from the supervisor.
Adding LIMIT 1000 does complete but still takes several seconds.
Questions:
1 - am I doing this with the correct query?
2 - why might this take so long? - Although there are 1 vertex and 3 edges to remove per observation this is not much more work to find than the equivalent match.
I wonder whether:

is this an indexing thing?
Is this a lock / deadlock thing? - some suggestion that any other asynch requests to the db to get observations ( which is quite likely) results in some obs being 'in use'. blocking the delete.   This might just be a side effect of it taking so long.

This screen shot from PGAdmin taken at 14:06 shows a detach delete of all observations that started at 13:26.

[edit - this did not complete after 20 hours.]
This is running on a MacBook Pro 2023. Apple M2 Max 64GB.  MacOS Ventura.  PostgreSQL 15.
I see the same problem on an Ubuntu Linux server.
My app is running in docker - but I can reproduce the issue by putting the same SQL request into PgAdmin.

Hi @avowkind
Thank you very much for sharing this issue. Our team is already looking into it. In the meantime, please do not hesitate to reach out if you have any questions.

Some tools for diagnosis.
observations_generator.py.txt
The attached python script will generate a test graph with mock data to illustrate the above schema. it outputs two sql files
- create_graph.sql: creates a graph with 1000 features, 100 properties, and 10 datasets
- create_observations.sql: creates 1000 batches of 100 observations each
create observations take about 3 minutes to create 1M observations.
These queries list and count observations
LOAD 'age';

-- list some observations in a dataset
SET search_path = ag_catalog, "$user", public;
SELECT * FROM cypher('perf_test_graph', $$
  MATCH (d:Dataset {id: 'dataset:1'})<-[:in]-(o:Observation)
  RETURN o
$$) as (o agtype);

This is fast - 100ms to return >10000 results.

-- count obs in each dataset.
SELECT * FROM cypher('perf_test_graph', $$
  MATCH (d:Dataset)<-[:in]-(o:Observation)
  RETURN d.id, count(o) as observation_count
$$) as (d_id text, observation_count bigint);

This is also fast:  but noting that here if I omit the arrow on the edge <-  then the query takes forever.
  Taking 1:46 mins.

Assign me!

Hi @avowkind I don't see why your query would be incorrect.
Also, I believe there might be area of improvement for DETACH DELETE code. I am currently working on it.

@avowkind A patch for detach delete was merged into master recently. Could you let us know if that improves the performance issue?

Closing due to inactivity.


chore: enforce npm and node requirements

Require relatively modern node>=12 and npm>7.11.2 in order to avoid bugs and different behaviors during build and testing.
npm 7.11.2 is the version currently shipping with fedora 34.
That is in sync with requirements that we already use for
vscode-ansible extension. These requirements are build/test specific
and do not affect the runtime.
Prevents bug where older npm would mess the format of package-lock.json file. As CI is not setup yet, it is recommended to test it locally first.
Originally included in #17

Hey! I think this new npm version requirement might be a bit too harsh? I believe it's quite common for people to use the npm version that came bundled (using nvm) with their Node version, so for Node 12.0.0 this seems to be<EMAIL_ADDRESS>The current Node LTS version (14.17.6) is bundled with<EMAIL_ADDRESS>The reason I'm commenting here is that I found that ansiblels started failing to install on my Windows machine using https://github.com/williamboman/nvim-lsp-installer:


Adding multiple RM3 abilities using the mac address of each device.

The only conflicts i can see are related to the receiving of temperatures.   You'll see I've added a getdevices (as opposed to getdevice) which returns an array.  And this array is used by on_message to select mutliple devices based on a : stripped mac address.

Thanks for your pull request!
Unfortunately, it has a lot of changes related to your custom configuration so I cannot apply it as is
But I definitely will rely on it during implementation of the same functionality

Yeah I wondered about that.  Also I don't think I'd done it  in a particularly good way.

From: Eugene Schava<EMAIL_ADDRESS>Sent: Tuesday, August 22, 2017 2:27:38 AM
To: eschava/broadlink-mqtt
Cc: psyciknz; Author
Subject: Re: [eschava/broadlink-mqtt] Adding multiple RM3 abilities using the mac address of each device. (#19)
Thanks for your pull request!
Unfortunately, it has a lot of changes related to your custom configuration so I cannot apply it as is
But I definitely will rely on it during implementation of the same functionality
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHubhttps://github.com/eschava/broadlink-mqtt/pull/19#issuecomment-323756580, or mute the threadhttps://github.com/notifications/unsubscribe-auth/AFGkczZdiO2zUYjUGNafBqF5dHFf2hDlks5saZPZgaJpZM4O3ZjT.


Latest Android updates causing problems?

I'm not entirely sure of the cause, but I'm quietly confident recent changes in Android have caused a conflict with your library:
~PathToMyProject\app\build\intermediates\exploded-aar\de.madcyph3r\materialDrawer\1.1.3\res\values\values.xml
Error:(2) Attribute "rippleColor" has already been defined

I'm pretty sure it's adding this new dependency which is causing the problem since it seems to compile without it:
compile 'com.android.support:design:22.2.0'

just need use the new prefix.

normally it's renamed to sectionRippleColor. I will check this.

Use the latest version and make a cleanup, Now all should be okay.


Editable vehicle image

It get nicely sourced from dbpedia but then impossible to change

Add https://commons.wikimedia.org/wiki/File:Tiger_Line.jpg to Myllenium Hyline


Remove godot form global scope, make it as an esmodule.

import { Vector2, Node, clamp } from 'godot';

related #187


Spine anchoring

Can we add spine anchoring?
Currently if I rotate my spine animation it rotates around the center, it would be great to be able to set anchor points.

Typically in a Spine runtime the position at which you draw the skeleton maps to 0,0 in world coordinates in Spine. This is the only reference point that makes sense for positioning. Since a skeleton is nearly always animated, it's AABB is constantly changing position, so performing operations on the center of the AABB isn't very helpful.
Depending on your needs, it might be best if you adjust the rotation of a particular bone in your skeleton so you can exactly control the rotation origin.

Tracking this at pixijs/pixi-spine#13.


Bump snippets tool to 0.3.0

@HansMuller chances are good that this will fix the super parameter issue you were recently running into in your doc sample.


make_changelog script is unable to completely generate the DETAILED_CHANGELOG file

Issue checklist
Note: these are not necessarily requirements

[x] I have checked existing OPL issues for duplicates and found none @ http://psx-scene.com/forums/official-open-ps2-loader-forum/ & https://github.com/ifcaro/Open-PS2-Loader/issues

Open PS2 loader version
Open PS2 loader mode (USB, SMB, HDD)
Open PS2 type (Normal, Childproof, VMC, GSM, PS2RD)
Issue description - Describe the problem you are having
Expected result
A new DETAILED_CHANGELOG file is generated, which lists all commits and their commit messages.
Actual result
Only commits up to r1007 are listed.
How to reproduce the issue
./make_changelog.sh

Does this solve the problem: cd48fb7d ?
It's already waiting in a pull request.

I have faith in your work. If you've fixed the bug, then it should be okay. I'll close this issue when your commits are merged. Thanks.

Is it merged now? Can this issue be closed, or is the pull-request still 'open'?

Fixed in cd48fb7.


feature: Df-daemon support multi-registries

Provide df-daemon rest_api for --registry parameter,this can change the registry_address online.
sample:
curl -i http://df-daemon_ip:65001/args?registry=registry.example.com

 Thank you for your submission, we really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

Could you explain how would this help #142, what would be the new user experience?

@zhouhaibing089 My PR need I to do something else？

There are pull requests to support multi-registries: #389 #410


DrivesWidget -> DrivesWidgetMoreOptionsButton isn't accessible / is hidden

Description
When the grid is stretched from side to side, the "additional options" button cannot be clicked.

Steps To Reproduce

Go to Home.
Resize the window so that the grid is stretched from side to side.

Steps to fix
Option 1: Set max width of the grid.
Option 2: Move the button to the "Group Header" (before the arrow)
Files Version
Version: <IP_ADDRESS> OS Version: 10.0.19044.2006
Windows Version
Windows 10 Pro 21H2 19044.2006
Relevant Assets/Logs
debug.log

I can reproduce this

@yaira2 Can you approve this?

We need to make some changes to widgets before this can be fixed.

This has been fixed in <IP_ADDRESS>


Turn ArgumentGroup into an interface extended by ArgumentParser and MutuallyExclusiveGroup

I want to write general helpers that can add arguments to groups and parsers.

ArgumentParser, ArgumentGroup and MutuallyExclusiveGroup share the same interface for add arguments:
public interface ArgumentHolder {
    Argument addArgument(String... nameOrFlags);
}

Having this interface will be good, for example, in case of dynamic parser building in runtime.

Fixed by #90. Introduced new interface ArgumentContainer implemented by ArgumentParser, ArgumentGroup and MutuallyExclusiveGroup.


gha: bump post-upgrade timeout in clustermesh upgrade/downgrade tests

The KPR matrix entry recently started failing quite frequently due to cilium status --wait failing to complete within the timeout after the upgrading Cilium to the tip of main. Part of the cause seems to be cilium/test-connection-disruption@619be5ab79a6, which made the connection disruption test more aggressive. In turn, causing more CPU contention during endpoint regeneration, which now requires longer. Hence, let's bump the timeout, to avoid failing too early due to the endpoint regeneration not having terminated yet.

/test


GraphiQL broken in production. Duplicate "graphql" modules.

As @lufutu suggested is not possible to use GraphiQL in production. See this comment.
Bug
Accessing GraphiQL page I see only the loading... message and get this error:
Uncaught Error: Cannot use t "__Schema" from another module or realm.

Ensure that there is only one instance of "graphql" in the node_modules
directory. If different versions of "graphql" are the dependencies of other
relied on modules, use "resolutions" to ensure only one version is installed.

https://yarnpkg.com/en/docs/selective-version-resolutions

Duplicate "graphql" modules cannot be used at the same time since different
versions may have different capabilities and behavior. The data from one
version used in the function from another could produce confusing and
spurious results.

Which then create a second obvious error:
Uncaught ReferenceError: GraphiQL is not defined

How to reproduce it

create a new Rails 5.2 application
install Binda 0.1.10 and Binda API master
deploy to production (on Heroku or anywhere with Capistrano)
go to http://your.domain.com/admin_panel/graphiql
check your browser console logs

Hint
The issue is probably due to GraphiQL Rails or GraphQL as they are the only responsible for injecting graphql as a dependency.
Versions
Rails 5.2
Binda 0.1.10
Binda API master (https://github.com/BindaCMS/binda-api/commit/c0c688494566e6689976cd38faff1aceb1314f70)

I can confirm that the issue isn't present when using graphql-rails 1.4.11.

It's possible to temporarily fix this issue using version v0.1.4.alpha.1
gem "binda-api", github: "BindaCMS/binda-api", tag: "v0.1.4.alpha.1"

Just remember to change config/environments/production.rb from config.assets.js_compressor = :uglifier to config.assets.js_compressor = Uglifier.new(harmony: true)


Bump prismic-dom from 2.2.5 to 2.6

Is your feature request related to a problem? Please describe.
A bugfix has been released in prismic-dom  2.6
Describe the solution you'd like
Bump current dependency from 2.2.5 to 2.6

Hey, as explained, just running yarn upgrade or npm update should bump prismic-dom for you ☺ (and if not, try removing your node_modules and lock file to force an update)
This package uses the caret (^) semver version range for prismic-dom. This means that upon installation (or update) it will install the most recent version from the said range (^2.2.5), here the latest version we published today: ^2.2.6.
I will perform dependency maintenance later this month, in the meantime the above already get you covered ☺
Let us know if anything!


issue about sidebar.md not found

problem 1
The scroll will be in the wrong position when you save the markdown file if the current markdown file can't be found in the sidebar. I find the reason is that Docsify won't execute the function hook.ready if the Markdown file is not in the sidebar. So you'd better add the markdown file to the sidebar first before writing the Markdown file with joy.
problem 2
docsify-plugin-runkit doesn't work if sidebar.md doesn't exist in the same directory.

the problem is that I don't respond to 404 if the file is not found.


[BUG] Generating webapi does not seem to work in new nx workspace

Current Behavior
Running the base generator for an application fails with error: Cannot find configuration for '[app-name]-[app-name]' (app name is repeated when parameter --directory is specified)
Expected Behavior
Generator should generate webapi as expected.
Github Repo
No response
Steps to Reproduce

Create new nx-repo

pnpm create create-nx-workspace@latest dotnet-test --workspaceType=integrated --nxCloud=skip --preset=apps --defaultBase=main

Install @nx-dotnet/core and initialize

pnpm add -D @nx-dotnet/core
pnpm exec nx g @nx-dotnet/core:init

Run generator to create a webapi in c#

pnpm exec nx generate @nx-dotnet/core:application --name=admin-api --language=C# --directory=admin/api --template=webapi --testTemplate=xunit --pathScheme=nx --verbose=true
# or without --directory
pnpm exec nx generate @nx-dotnet/core:application --name=admin-api --language=C# --template=webapi --testTemplate=xunit --pathScheme=nx --verbose=true

Generator fails with  Cannot find configuration for [app-name]:
 NX  Generating @nx-dotnet/core:application

Executing Command: dotnet "new" "webapi" "--language" "C#" "--name" "DotnetTest.Admin.Api.AdminApi" "--output" "admin/api/admin-api"
The template "ASP.NET Core Web API" was created successfully.

Processing post-creation actions...
Restoring C:\projects\temp\dotnet-test\admin\api\admin-api\DotnetTest.Admin.Api.AdminApi.csproj:
  Determining projects to restore...
  All projects are up-to-date for restore.
Restore succeeded.

Executing Command: dotnet "new" "xunit" "--language" "C#" "--name" "DotnetTest.Admin.Api.AdminApi.Test" "--output" "admin/api/admin-api-test"
The template "xUnit Test Project" was created successfully.

Processing post-creation actions...
Restoring C:\projects\temp\dotnet-test\admin\api\admin-api-test\DotnetTest.Admin.Api.AdminApi.Test.csproj:
  Determining projects to restore...
  All projects are up-to-date for restore.
Restore succeeded.

Executing Command: dotnet "add" "admin/api/admin-api-test/DotnetTest.Admin.Api.AdminApi.Test.csproj" "reference" "admin/api/admin-api/DotnetTest.Admin.Api.AdminApi.csproj"
Reference `..\admin-api\DotnetTest.Admin.Api.AdminApi.csproj` added to the project.

 NX   Cannot find configuration for 'admin-api-admin-api'

Error: Cannot find configuration for 'admin-api-admin-api'
    at readProjectConfiguration (C:\projects\temp\dotnet-test\node_modules\.pnpm\nx@18.0.7\node_modules\nx\src\generators\utils\project-configuration.js:99:15)
    at C:\projects\temp\dotnet-test\node_modules\.pnpm\@nx-dotnet+core@2.2.0_@nx+js@18.0.7_nx@18.0.7\node_modules\@nx-dotnet\core\src\generators\add-swagger-target\add-swagger-target.js:11:63
    at Generator.next (<anonymous>)
    at C:\projects\temp\dotnet-test\node_modules\.pnpm\tslib@2.6.2\node_modules\tslib\tslib.js:169:75
    at new Promise (<anonymous>)
    at Object.__awaiter (C:\projects\temp\dotnet-test\node_modules\.pnpm\tslib@2.6.2\node_modules\tslib\tslib.js:165:16)
    at generateSwaggerSetup (C:\projects\temp\dotnet-test\node_modules\.pnpm\@nx-dotnet+core@2.2.0_@nx+js@18.0.7_nx@18.0.7\node_modules\@nx-dotnet\core\src\generators\add-swagger-target\add-swagger-target.js:9:20)
    at C:\projects\temp\dotnet-test\node_modules\.pnpm\@nx-dotnet+core@2.2.0_@nx+js@18.0.7_nx@18.0.7\node_modules\@nx-dotnet\core\src\generators\utils\generate-project.js:129:63
    at Generator.next (<anonymous>)
    at fulfilled (C:\projects\temp\dotnet-test\node_modules\.pnpm\tslib@2.6.2\node_modules\tslib\tslib.js:166:62)

Nx Report
NX   Report complete - copy this into the issue template

Node   : 20.9.0
OS     : win32-x64
pnpm   : 8.15.4

nx             : 18.0.7
@nx/js         : 18.0.7
@nx/workspace  : 18.0.7
@nx/devkit     : 17.0.2
@nrwl/tao      : 18.0.7
typescript     : 5.4.2
---------------------------------------
Community plugins:
@nx-dotnet/core : 2.2.0
---------------------------------------
The following packages should match the installed version of nx
  -<EMAIL_ADDRESS>  -<EMAIL_ADDRESS>
To fix this, run `nx migrate<EMAIL_ADDRESS>
nx.json
{
  "$schema": "./node_modules/nx/schemas/nx-schema.json",
  "namedInputs": {
    "default": [
      "{projectRoot}/**/*",
      "sharedGlobals"
    ],
    "production": [
      "default"
    ],
    "sharedGlobals": []
  },
  "plugins": [
    "@nx-dotnet/core"
  ]
}

Failure Logs
No response
Additional Information
dotnet --version
8.0.102

pnpm -v
8.15.4

node -v
v20.9.0

Current workaround.

Run the generator once until it fails.
Create project.json files for the app and test projects.

{
	"name": "admin-api",
	"$schema": "../../node_modules/nx/schemas/project-schema.json",
	"sourceRoot": "apps/admin-api",
	"projectType": "application",
	"targets": {},
	"tags": []
}

Delete all files and folders except the project.json files from each folder.
Re-run the generator. It succeeds since the project now exists in the nx graph.

I'm also having the same issue, but I can't replicate the solution from @rudfoss.

This is a duplicate of https://github.com/nx-dotnet/nx-dotnet/issues/828

Hi, yea this should be fixed. I'll try to make some time this week to get something put together.

Thanks for the updates and the quick fix guys! It is greatly appreciated.

I'm getting Cannot find configuration when generating webapi, so it is still relevant.
> nx g @nx-dotnet/core:application --name=foo-webapi --language=C# --template=webapi --testTemplate=nunit --pathScheme=nx --verbose

 NX  Generating @nx-dotnet/core:application

Executing Command: dotnet "new" "webapi" "--language" "C#" "--name" "NxDotnet7Example.FooWebapi" "--output" "foo-webapi"
The template "ASP.NET Core Web API" was created successfully.

Processing post-creation actions...
Restoring C:\tmp\nx-dotnet7-example\foo-webapi\NxDotnet7Example.FooWebapi.csproj:
  Determining projects to restore...
  All projects are up-to-date for restore.
Restore succeeded.

Executing Command: dotnet "new" "nunit" "--language" "C#" "--name" "NxDotnet7Example.FooWebapi.Test" "--output" "foo-webapi-test"
The template "NUnit 3 Test Project" was created successfully.

Processing post-creation actions...
Restoring C:\tmp\nx-dotnet7-example\foo-webapi-test\NxDotnet7Example.FooWebapi.Test.csproj:
  Determining projects to restore...
  All projects are up-to-date for restore.
Restore succeeded.

Executing Command: dotnet "add" "foo-webapi-test/NxDotnet7Example.FooWebapi.Test.csproj" "reference" "foo-webapi/NxDotnet7Example.FooWebapi.csproj"
Reference `..\foo-webapi\NxDotnet7Example.FooWebapi.csproj` added to the project.

 NX   Cannot find configuration for 'foo-webapi'

Error: Cannot find configuration for 'foo-webapi'
    at readProjectConfiguration (C:\tmp\nx-dotnet7-example\node_modules\@nx-dotnet\core\node_modules\nx\src\generators\utils\project-configuration.js:101:15)
    at C:\tmp\nx-dotnet7-example\node_modules\@nx-dotnet\core\src\generators\add-swagger-target\add-swagger-target.js:11:63
    at Generator.next (<anonymous>)
    at C:\tmp\nx-dotnet7-example\node_modules\tslib\tslib.js:169:75
    at new Promise (<anonymous>)
    at Object.__awaiter (C:\tmp\nx-dotnet7-example\node_modules\tslib\tslib.js:165:16)
    at generateSwaggerSetup (C:\tmp\nx-dotnet7-example\node_modules\@nx-dotnet\core\src\generators\add-swagger-target\add-swagger-target.js:9:20)
    at C:\tmp\nx-dotnet7-example\node_modules\@nx-dotnet\core\src\generators\utils\generate-project.js:129:63
    at Generator.next (<anonymous>)
    at fulfilled (C:\tmp\nx-dotnet7-example\node_modules\tslib\tslib.js:166:62)

Hey, yeah - this has taken way too long but the fix is included in the Nx 19 PR
I'm going to merge it now and release, so update whenever you get a minute and we can verify.

@AgentEnder just checked with the latest nx-dotnet and nx and can confirm that it is fixed!

This one is minor, but I found a blinking terminal on Windows while generating webapi types.
Haven't tried it yet but it looks like windowsHide: true here might fix the issue:
https://github.com/nx-dotnet/nx-dotnet/blob/629e6d89ed7df98d37c88f7b6d1ab871b3078cfb/packages/core/src/executors/openapi-codegen/executor.ts#L69-L78


Implement the Detect interface to generate the /bin/detect program.

assign to me @wangeguo

This issue will be write by go, it can close.


feat: add Minuit2.setup() method

This makes it possible to access iminuit.Minuit's methods and attributes before calling optimize().

@Leongrim, have a look if this helps.
@spflueger, I don't like the way setup() modifies the behaviour of optimize(), but this is the best I could come up with for now given this Optimizer interfaces.

Why does the minuit instance have to be tweaked before optimize? Cant that be done at construction?
A more general question. As far as I remember the operator interface is solely connected to the user. So a user can swap optimizers and does not have to adjust the optimize call. But the optimizer interface is not used in tensorwaves internally right?
Hence the interface is not really needed per se. Just some consistency thing for the user. But if this is too restrictive. Then I think it can be abandoned.

Why does the minuit instance have to be tweaked before optimize? Cant that be done at construction?

I would have preferred that too, but one needs an estimator and the free parameters in order to construct an iminuit.Minuit instance. That would mean these become tied to the constructor, so each TensorWaves Minuit2 instance is specific to each set of free parameters. (At the same time though, this setup() method just obscures that fact and one can mess up things by for instance inserting a different estimator in setup() than in optimize()...)

A more general question. As far as I remember the operator interface is solely connected to the user. So a user can swap optimizers and does not have to adjust the optimize call. But the optimizer interface is not used in tensorwaves internally right? Hence the interface is not really needed per se. Just some consistency thing for the user. But if this is too restrictive. Then I think it can be abandoned.

[optimizer interface?] Yes, the Optimizer interface class is only used as an ABC to optimizer implementations and optimizer instances are not (currently) used elsewhere in the source code.

@redeboer Ok maybe we can do a quick call to discuss this.

@redeboer Ok maybe we can do a quick call to discuss this.

@spflueger Done :heavy_check_mark: Usage can be previewed here. Not the most pretty, but less error prone than this setup() method.

@redeboer Ok maybe we can do a quick call to discuss this.

@spflueger Done heavy_check_mark Usage can be previewed here. Not the most pretty, but less error prone than this setup() method.

LGTM


Fix Class "Str" not found error on fresh install

Hello,
On a fresh install, going to /pulse results in the following error: https://flareapp.io/share/87nK4ry5
Adding missing use for Illuminate\Support\Str in 3 blade views fixed the issue.

Doesn't this mean just you don't have the aliases set up in your config/app.php?

After a fresh install, I get the following error :
Call to undefined method Illuminate\Support\Benchmark::value()


fix: previously tuple, now dict

dictionary return and processing may be more elegant, as well as explicit

Good job!


RuntimeError: Unsloth: unsloth/llama-3-8b-bnb-4bit is not a full model or a PEFT model.

RuntimeError: Unsloth: unsloth/llama-3-8b-bnb-4bit is not a full model or a PEFT model.

Are you connected to the internet?

RuntimeError: Unsloth：unsloth/llama-3-8b-bnb-4bit不是完整模型或 PEFT 模型。

I have encountered the same problem. Have you resolved it?

Are you connected to the internet?

sure

Normally if Colab works, then it should be fine - did you all clone the colab notebook exactly?

It maybe something wrong with your network or proxy
The following is my solution, it works for me.
Download this model mannually:
git lfs clone https://huggingface.co/unsloth/llama-3-8b-bnb-4bit
Change model_name to your local path
model_name = "unsloth/llama-3-8b-bnb-4bit"  ==> model_name = "./llama-3-8b-bnb-4bit"
Let me know if it works :)

It maybe something wrong with your network or proxy
The following is my solution, it works for me.
Download this model mannually: git lfs clone https://huggingface.co/unsloth/llama-3-8b-bnb-4bit
Change model_name to your local path model_name = "unsloth/llama-3-8b-bnb-4bit" ==> model_name = "./llama-3-8b-bnb-4bit"
Let me know if it works :)
大佬能不能具体一点，我的llama模型的位置是："F:\unsloth-win11\model\llama-3-8b-bnb-4bit"我该如何设置model_name

@zhuangkun5 Sorry on the delay - if this is a local folder, it should function hopefully


AutoDyamoLens: Support set types

The Dynamo SS and NS types aren't supported by the autoDynamoLens.
From Object to Item: Java Set<*> is converted to Dynamo L
From Item to Object: Dynamo NS and SS are omitted when mapping to the Object
Currently I'm unsure if this can properly be supported.  When converting to a Dynamo Item, I believe the Object is converted to JSON, which erases the concrete type of the java Collection.

Item to Object is now supported.  Object to Item may not be possible.


部门活动打开后闪退

When not logged in and not in guest mode, accessing the schedule page will make the app crash.


[release] Set up version; set up testing

This tests our dummy functorch package.

Looks like torchvision RC binaries have not been cut yet


I'm coming from Entity Framework and I can't understand some concepts

First off, this seems to be the best ORM for Node. Thanks for your work, but I'm having a hard time understanding some concepts. Please do not take me wrong, the critics are constructive :+1:
My biggest problem is with what represents 1 object vs. what represents the repository of objects.
Entity Framework
I'm coming from Entity Framework, so, if I do this:
var me = new Contact();

... Now me represents 1 contact. If I want to get a Contact from the database, I do:
var me = dbContext.Contacts.First(c => c.name = "Andre");

So, Contact represents 1 contact and dbContext.Contacts represents the repository of contacts.
Bookshelf
Bookshelf doesn't seem to have a clear distinction between 1 Contact and the repository of Contacts.
I've read the documentation and I found that some methods are in model and others are the Model (the static ones). The first thing that came to my mind was: Hey! So, the Model. methods are  the methods that operate on the repository, and the model. methods are the ones that operate on a single instance**.
Then, to my surprise, the where method was on the model, not on the Model, so I was like this:

I mean... I have to instantiate 1 Contact in order to do a where, like this:
new Contact().where('id', '>', 1).fetchAll().then(m => {
    console.log(m);
    knex.destroy();
});

The above code wouldn't be that hard to understand if you thought of Contact as being the repository, but it's not. You can actually do var me = Contact.forge({ name: 'Andre' }).
It would be much easier to understand if where was a static method. You could do this:
Contact.where(...).then(...); // you can get instances of Contact this way

Can you please explain the difference between the Model.* and model.* and what represents 1 Contact and what represents the Contacts repository?
Thank you.

Hi @andrerpena, thanks for the issue.

Can you please explain the difference between the Model.* and model.* and what represents 1 Contact and what represents the Contacts repository?

The two concepts are conflated in Bookshelf.

Then, to my surprise, the where method was on the model, not on the Model...

Actually where is aliased on the constructor too.
// the following:
Model.where(condition).fetch()
// is equivalent to:
Model.forge().where(condition).fetch()

Basically any model instance can be used to chain new queries. Allowing you to create such nonsense statements as:
// user model with name 'John' is created and discarded.
new User({ name: 'John' }).where({ name: 'Jane' }).fetchAll().then(janes =>

I agree that this is a confusing design choice, but that's how it's been since before I started using the project. When using Bookshelf I just stick to using the static aliases for where fetch etc. to keep these concepts separate.
I've brought this issue up before in discussions for "bookshelf next", but I don't believe @tgriesser feels that this is a significant problem. Either way I imagine a change here would break dependant projects in such a way that it would not be viable. It would also require re-architecting a lot of Bookshelf. Currently there are no collaborators working on large scale changes here, so it would be up to somebody from the community to take the project and do the work. I'd be happy to help guide the project, but I would not guarantee any major personal involvement.

@rhys-vdw Thank you for your reply. It's clarifying. I didn't know where was aliased on Model.
Good to know I'm not the only one that's not kin of this design. I'd love to see this changed in the next version.
Again, I don't mean to disregard the work you going put into this.
Thanks again.


New numbers: dozen, gross, pair, ream, mol

New numbers:
dozen = 12
gross = 144
pair = 2
ream = 500
mol = 6.02214179 × 10^23

hey thanks!
firstly, wanna add the nlp_compromise typescript typings to the main repo somehow?
that's really neat!
i like this idea too. 'Gross' may be too ambiguous though

@spencermountain typings are not finished yet. Once they are I will submit a PR.


Model_Average_optimizer Use Problems in got multiple values for keyword argument 'dtype'

I use tensorflow_gpu version:1.8.0
I use Model_Average_optimizer and occurs some problems:
the code is used more likely as model_average_optimizer_test.py.
I find this error is occured in init ModelAverageOptimizer to create local_step. And this problem is more likely some problems with device_setter.
But I don't know why. Could someone help me?
Traceback (most recent call last):
File "/data00/home/wupeihao/ma_test/src/rnnlm.py", line 112, in
tf.app.run()
File "/data00/home/wupeihao/anaconda2/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 126, in run
_sys.exit(main(argv))
File "/data00/home/wupeihao/ma_test/src/rnnlm.py", line 109, in main
test()
File "/data00/home/wupeihao/ma_test/src/rnnlm.py", line 84, in test
interval_steps=3)
File "/data00/home/wupeihao/anaconda2/lib/python2.7/site-packages/tensorflow/contrib/opt/python/training/model_average_optimizer.py", line 139, in init
name="local_step")
File "/data00/home/wupeihao/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 1317, in get_variable
constraint=constraint)
File "/data00/home/wupeihao/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 1079, in get_variable
constraint=constraint)
File "/data00/home/wupeihao/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 417, in get_variable
return custom_getter(**custom_getter_kwargs)
File "/data00/home/wupeihao/anaconda2/lib/python2.7/site-packages/tensorflow/contrib/opt/python/training/model_average_optimizer.py", line 92, in call
return getter(name, trainable, collections, *args, **kwargs)
TypeError: _true_getter() got multiple values for keyword argument 'dtype'
if FLAGS.job_name == "ps":
    server.join()
elif FLAGS.job_name == "worker":
    is_chief = (FLAGS.task_id == 0)
    #Between-graph replication
    worker_device = "/job:worker/task:%d" % (FLAGS.task_id)
    ma_custom = model_average_optimizer.ModelAverageCustomGetter(worker_device=worker_device)
    from tensorflow.python.training import device_setter
    with tf.device(
            device_setter.replica_device_setter(
                cluster=cluster,
                worker_device=worker_device,
                ps_device="/job:ps")), \
         tf.variable_scope("", custom_getter=ma_custom):
        #create model
        opt, lr = optimizer.get_optimizer("sgd")
        sync_opt = model_average_optimizer.ModelAverageOptimizer(
                    opt=opt,
                    num_worker=num_workers,
                    ma_custom_getter=ma_custom,
                    is_chief=is_chief,
                    interval_steps=3)
        tf.logging.info('model start')
        train_model = Model(sync_opt)
        tf.logging.info('model end')
        ma_hook = sync_opt.make_session_run_hook()
    sess_config = tf.ConfigProto(gpu_options=gpu_options)
    sess_config.log_device_placement = False
    sess_config.allow_soft_placement = True

    all_hooks = [ma_hook]

    tf.logging.info('Start Sess')
    with tf.train.MonitoredTrainingSession(master=server.target,
                is_chief=is_chief,
                hooks=all_hooks) as sess:
        tf.logging.info("is chief: %s, len: %s", is_chief, num_workers)
        for i in range(4):
            sess.run(train_op)
            pp1 = sess.run(tf.get_default_graph().get_tensor_by_name('v0:0'))
            pp2 = sess.run(tf.get_default_graph().get_tensor_by_name('v1:0'))
            tf.logging.info("%d %.2f %.2f" % (FLAGS.task_id, pp1, pp2))
    sv.stop()
    tf.logging.info("done")

Thank you for your post. We noticed you have not filled out the following field in the issue template. Could you update them if they are relevant in your case, or leave them as N/A? Thanks.
Have I written custom code
OS Platform and Distribution
TensorFlow installed from
TensorFlow version
Bazel version
CUDA/cuDNN version
GPU model and memory
Exact command to reproduce

Sorry for delay, details are updated.

Thank you for your post. We noticed you have not filled out the following field in the issue template. Could you update them if they are relevant in your case, or leave them as N/A? Thanks.
Have I written custom code
OS Platform and Distribution
TensorFlow installed from
TensorFlow version
Bazel version
CUDA/cuDNN version
GPU model and memory
Exact command to reproduce

I've updated this questions yesterday.
I've no idea if there are any problems for solving this problem.

Hi @yunyin, I am the author of ModelAverageOptimizer. Sorry for the bug. Did you solve the problem? There are two ways to solve it:

place opt out of the ma_custom scope
modify model_average_optimizer.py line 91 like this:

    else:
      kwargs['trainable'] = trainable
      kwargs['collections'] = collections
      return getter(name, *args, **kwargs)

I will make a pull request to fix this. Thanks for trying this opt!

Thanks for responding @jinxin0924 - marking as "Contributions welcome" since it seems you have PR out for this.

@jinxin0924 Thank you for your reply. I solve this problems with your second suggestion.
It's a nice work. But I still have some problems about local_step in model_average_optimizer.py.
I found that it seems different workers share the same local_step.
detail logs are shown below,
It seems that model average is triggered in (0,0),(4,2),(6,4),(9,9), it doesn't make any sense.
worker0 log:
INFO:tensorflow:is chief: True, len: 2
INFO:tensorflow:0 0 8.00 9.00
INFO:tensorflow:0 1 9.00 10.00
INFO:tensorflow:0 2 10.00 11.00
INFO:tensorflow:0 3 11.00 12.00
INFO:tensorflow:0 4 18.00 19.00
INFO:tensorflow:0 5 19.00 20.00
INFO:tensorflow:0 6 27.00 28.00
INFO:tensorflow:0 7 28.00 29.00
INFO:tensorflow:0 8 29.00 30.00
INFO:tensorflow:0 9 48.50 49.50

worker1 log:
INFO:tensorflow:is chief: False, len: 2
INFO:tensorflow:1 0 8.00 9.00
INFO:tensorflow:1 1 16.00 17.00
INFO:tensorflow:1 2 18.00 19.00
INFO:tensorflow:1 3 26.00 27.00
INFO:tensorflow:1 4 27.00 28.00
INFO:tensorflow:1 5 35.00 36.00
INFO:tensorflow:1 6 43.00 44.00
INFO:tensorflow:1 7 51.00 52.00
INFO:tensorflow:1 8 59.00 60.00
INFO:tensorflow:1 9 48.50 49.50

@yunyin, yes, different workers share the same local_step. It is a bug. You can modify model_average_optimizer.py line 91 like this:
    else:
      kwargs['trainable'] = trainable
      kwargs['collections'] = collections
      if ops.GraphKeys.LOCAL_VARIABLES in collections:
        with ops.device(self._worker_device):
          return getter(name, *args, **kwargs)
      else:
        return getter(name, *args, **kwargs)

In my experiments, I always create model average optimizer out of the ma_custom scope, so I did not find these bugs. Again, thanks a lot!

@jinxin0924 Thank you for reply soon.

@yunyin , clould you debug at model_average_optimizer.py line 94 if ops.GraphKeys.LOCAL_VARIABLES in collections: and take a look what will happen when the name is local_step?

@jinxin0924 I've solved this problem.
You should put opt in ma_custom scope, so that local_step could be LOCAL_VARIABLES.
Thanks again for your work and support.


Move protocol negotiation and discovery to service

Now that the October event has completed, move the protocol negotiation and endpoint / function block discovery from the API to the service.

Developer Preview 4 will have this functionality built in, for USB MIDI 2.0 devices. It will not be turned on for the loopback endpoints.


Please expose more depth reconstruction settings

Is your feature request related to a problem? Please describe.
3D object features well below the resolution of the sensor get filtered away.
Describe the solution you'd like
Please provide more API (and viewer) control over how heavy the filtering is. The SDK currently only seems to provide one setting related to 3d reconstruction (the Depth Mode). By comparison, Intel's Realsense L515 drivers provide much more control over the emitter, sensor, and post-processing functions.
I can't make concrete suggestions since I don't know what is actually performed in the sensor, but I am particularly interested in reducing the amount of spatial and temporal filtering that seems to be performed within the sensor. Also reducing emitter power can help with artifacts related to saturation.

Fully agree!
The current default settings for generating the depth data are generally excellent (and better than competing sensors) but for advanced users it could definitely help being able to tune things for specific scenarios.
For example scenarios where subjects are close vs far away from the sensor may benefit from different settings.
Some scenarios may benefit from disabling filtering/post processing or making it less aggressive.
When latency is most important could benefit from disabling some things maybe even if it increases noise.
The same holds true for body tracking, the fact that the team implemented a setting for joint smoothing (and the ability to disable it) made a huge difference for my applications at least.
The more settings the better, and if things changes for future SDKs or sensor models that is generally not an issue for advanced users anyway.

That would be great. We are researching depth completion and estimation and it will help us a lot to get the raw data from the sensor and hopefully get more control over other aspects of the emitter and sensor.

raw depth data was adjusted for optimazing, but we want raw depth and pointcloud like kinect 2.0 to scan object's details.

I'd echo this request. Having more control over depth data (preprocessing) would be great. What's the status of this?

I'd echo this request. Having more control over depth data (preprocessing) would be great. What's the status of this?


Auto release fails for credentials

Bug Description
CI fails to publish the charm for
No keyring found to store or retrieve credentials from.
To Reproduce
Merge a PR to main.
https://github.com/canonical/avalanche-k8s-operator/runs/6391106788?check_suite_focus=true
Environment
GH CI
Relevant log output
https://github.com/canonical/avalanche-k8s-operator/runs/6391106788?check_suite_focus=true

Additional context
No response

Fixed.


Non-HD is poor quality on HTML5 player

I'm not sure whether this is a new issue, or if it's been around for a while, but I have noticed that, whenever a video is loaded @ 480p, the quality is degraded much more than it should be.
This happens on a custom preset to force a video player size of 1280x720 and it's meant that every video I watch has to be @ 720p, even though my connection is a little slower than normal to buffer that without delays.
Is this possibly a side effect of the higher frame rate options? Would appreciate opinions from @YePpHa or @Yonezpt if possible, but anyone can jump in here.
EDIT: The quality variation seems to be random. Some videos have fairly good quality @ 480p, so it might just be an issue with bitrate of uploaded videos.

I'm pretty sure this has to do with upscale algorithms. In the end the player will have to upscale the 480P video to 720P and the upscale quality just depends on the source. I wouldn't be surprised if YTC, Youtube or your browser is very limited when it comes to upscale algo's so I don't think there will be an easy solution for your problem (outside just going for 720P video quality and make the video buffer)

I doubt it's my browser. I can just set to 720p to get around it anyway, not a big deal. Just thought I'd post it here as a reference in case others are getting the issue too. :)


No TSM files are being created

System info:
InfluxDB: 1.6
System: Ubuntu 18.04
Steps to reproduce:
Install InfluxDB, create Database and write to the measurements  every 30 seconds
Expected behavior:
The write-ahead-log is being compressed into TSM files.
Actual behavior:
The write-ahead-log is not being compressed to TSM files and just keeps growing. Currently there are 2 .wal files. one with the size of 24 MB and a newer one that is actively being written to, currently 4MB.
Additional info:
I have a number of measurements for which I create new series every 30 seconds. I want to keep the data on a long term basis and therefore need to make sure that it is being compressed.
My config
### Welcome to the InfluxDB configuration file.

# The values in this file override the default values used by the system if
# a config option is not specified. The commented out lines are the configuration
# field and the default value used. Uncommenting a line and changing the value
# will change the value used at runtime when the process is restarted.

# Once every 24 hours InfluxDB will report usage data to usage.influxdata.com
# The data includes a random ID, os, arch, version, the number of series and other
# usage data. No data from user databases is ever transmitted.
# Change this option to true to disable reporting.
reporting-disabled = true

# Bind address to use for the RPC service for backup and restore.
# bind-address = "<IP_ADDRESS>:8088"

###
### [meta]
###
### Controls the parameters for the Raft consensus group that stores metadata
### about the InfluxDB cluster.
###

[meta]
  # Where the metadata/raft database is stored
  dir = "/var/lib/influxdb/meta"

  # Automatically create a default retention policy when creating a database.
  # retention-autocreate = true

  # If log messages are printed for the meta service
  # logging-enabled = true

###
### [data]
###
### Controls where the actual shard data for InfluxDB lives and how it is
### flushed from the WAL. "dir" may need to be changed to a suitable place
### for your system, but the WAL settings are an advanced configuration. The
### defaults should work for most systems.
###

[data]
  # The directory where the TSM storage engine stores TSM files.
  dir = "/var/lib/influxdb/data"

  # The directory where the TSM storage engine stores WAL files.
  wal-dir = "/var/lib/influxdb/wal"

  # The amount of time that a write will wait before fsyncing.  A duration
  # greater than 0 can be used to batch up multiple fsync calls.  This is useful for slower
  # disks or when WAL write contention is seen.  A value of 0s fsyncs every write to the WAL.
  # Values in the range of 0-100ms are recommended for non-SSD disks.
  # wal-fsync-delay = "0s"

  # The type of shard index to use for new shards.  The default is an in-memory index that is
  # recreated at startup.  A value of "tsi1" will use a disk based index that supports higher
  # cardinality datasets.
  # index-version = "inmem"

  # Trace logging provides more verbose output around the tsm engine. Turning
  # this on can provide more useful output for debugging tsm engine issues.
  # trace-logging-enabled = false

  # Whether queries should be logged before execution. Very useful for troubleshooting, but will
  # log any sensitive data contained within a query.
  # query-log-enabled = true

  # Settings for the TSM engine

  # CacheMaxMemorySize is the maximum size a shard's cache can
  # reach before it starts rejecting writes.
  # Valid size suffixes are k, m, or g (case insensitive, 1024 = 1k).
  # Values without a size suffix are in bytes.
  # cache-max-memory-size = "1g"

  # CacheSnapshotMemorySize is the size at which the engine will
  # snapshot the cache and write it to a TSM file, freeing up memory
  # Valid size suffixes are k, m, or g (case insensitive, 1024 = 1k).
  # Values without a size suffix are in bytes.
 cache-snapshot-memory-size = "7m"

  # CacheSnapshotWriteColdDuration is the length of time at
  # which the engine will snapshot the cache and write it to
  # a new TSM file if the shard hasn't received writes or deletes
 cache-snapshot-write-cold-duration = "10m"

  # CompactFullWriteColdDuration is the duration at which the engine
  # will compact all TSM files in a shard if it hasn't received a
  # write or delete
 compact-full-write-cold-duration = "4h"

  # The maximum number of concurrent full and level compactions that can run at one time.  A
  # value of 0 results in 50% of runtime.GOMAXPROCS(0) used at runtime.  Any number greater
  # than 0 limits compactions to that value.  This setting does not apply
  # to cache snapshotting.
  # max-concurrent-compactions = 0

  # The threshold, in bytes, when an index write-ahead log file will compact
  # into an index file. Lower sizes will cause log files to be compacted more
  # quickly and result in lower heap usage at the expense of write throughput.
  # Higher sizes will be compacted less frequently, store more series in-memory,
  # and provide higher write throughput.
  # Valid size suffixes are k, m, or g (case insensitive, 1024 = 1k).
  # Values without a size suffix are in bytes.
  # max-index-log-file-size = "1m"

  # The maximum series allowed per database before writes are dropped.  This limit can prevent
  # high cardinality issues at the database level.  This limit can be disabled by setting it to
  # 0.
  # max-series-per-database = 1000000

  # The maximum number of tag values per tag that are allowed before writes are dropped.  This limit
  # can prevent high cardinality tag values from being written to a measurement.  This limit can be
  # disabled by setting it to 0.
  # max-values-per-tag = 100000

###
### [coordinator]
###
### Controls the clustering service configuration.
###

[coordinator]
  # The default time a write request will wait until a "timeout" error is returned to the caller.
  # write-timeout = "10s"

  # The maximum number of concurrent queries allowed to be executing at one time.  If a query is
  # executed and exceeds this limit, an error is returned to the caller.  This limit can be disabled
  # by setting it to 0.
  # max-concurrent-queries = 0

  # The maximum time a query will is allowed to execute before being killed by the system.  This limit
  # can help prevent run away queries.  Setting the value to 0 disables the limit.
  # query-timeout = "0s"

  # The time threshold when a query will be logged as a slow query.  This limit can be set to help
  # discover slow or resource intensive queries.  Setting the value to 0 disables the slow query logging.
  # log-queries-after = "0s"

  # The maximum number of points a SELECT can process.  A value of 0 will make
  # the maximum point count unlimited.  This will only be checked every second so queries will not
  # be aborted immediately when hitting the limit.
  # max-select-point = 0

  # The maximum number of series a SELECT can run.  A value of 0 will make the maximum series
  # count unlimited.
  # max-select-series = 0

  # The maxium number of group by time bucket a SELECT can create.  A value of zero will max the maximum
  # number of buckets unlimited.
  # max-select-buckets = 0

###
### [retention]
###
### Controls the enforcement of retention policies for evicting old data.
###

[retention]
  # Determines whether retention policy enforcement enabled.
  # enabled = true

  # The interval of time when retention policy enforcement checks run.
  # check-interval = "30m"

###
### [shard-precreation]
###
### Controls the precreation of shards, so they are available before data arrives.
### Only shards that, after creation, will have both a start- and end-time in the
### future, will ever be created. Shards are never precreated that would be wholly
### or partially in the past.

[shard-precreation]
  # Determines whether shard pre-creation service is enabled.
  # enabled = true

  # The interval of time when the check to pre-create new shards runs.
  # check-interval = "10m"

  # The default period ahead of the endtime of a shard group that its successor
  # group is created.
  # advance-period = "30m"

###
### Controls the system self-monitoring, statistics and diagnostics.
###
### The internal database for monitoring data is created automatically if
### if it does not already exist. The target retention within this database
### is called 'monitor' and is also created with a retention period of 7 days
### and a replication factor of 1, if it does not exist. In all cases the
### this retention policy is configured as the default for the database.

[monitor]
  # Whether to record statistics internally.
  # store-enabled = true

  # The destination database for recorded statistics
  # store-database = "_internal"

  # The interval at which to record statistics
  # store-interval = "10s"

###
### [http]
###
### Controls how the HTTP endpoints are configured. These are the primary
### mechanism for getting data into and out of InfluxDB.
###

[http]
  # Determines whether HTTP endpoint is enabled.
  enabled = true

  # The bind address used by the HTTP service.
  # bind-address = ":8086"

  # Determines whether user authentication is enabled over HTTP/HTTPS.
  auth-enabled = true

  # The default realm sent back when issuing a basic auth challenge.
  # realm = "InfluxDB"

  # Determines whether HTTP request logging is enabled.
  # log-enabled = true

  # Determines whether the HTTP write request logs should be suppressed when the log is enabled.
  # suppress-write-log = false

  # When HTTP request logging is enabled, this option specifies the path where
  # log entries should be written. If unspecified, the default is to write to stderr, which
  # intermingles HTTP logs with internal InfluxDB logging.
  #
  # If influxd is unable to access the specified path, it will log an error and fall back to writing
  # the request log to stderr.
  # access-log-path = ""

  # Determines whether detailed write logging is enabled.
  # write-tracing = false

  # Determines whether the pprof endpoint is enabled.  This endpoint is used for
  # troubleshooting and monitoring.
  # pprof-enabled = true

  # Enables a pprof endpoint that binds to localhost:6060 immediately on startup.
  # This is only needed to debug startup issues.
  # debug-pprof-enabled = false

  # Determines whether HTTPS is enabled.
  https-enabled = true

  # The SSL certificate to use when HTTPS is enabled.
  https-certificate = "/etc/ssl/influxdb.cert.pem"

  # Use a separate private key location.
  https-private-key = "/etc/ssl/influxdb.key.unencrypted.pem"

  # The JWT auth shared secret to validate requests using JSON web tokens.
  # shared-secret = ""

  # The default chunk size for result sets that should be chunked.
  # max-row-limit = 0

  # The maximum number of HTTP connections that may be open at once.  New connections that
  # would exceed this limit are dropped.  Setting this value to 0 disables the limit.
  # max-connection-limit = 0

  # Enable http service over unix domain socket
  # unix-socket-enabled = false

  # The path of the unix domain socket.
  # bind-socket = "/var/run/influxdb.sock"

  # The maximum size of a client request body, in bytes. Setting this value to 0 disables the limit.
  # max-body-size = 25000000

  # The maximum number of writes processed concurrently.
  # Setting this to 0 disables the limit.
  # max-concurrent-write-limit = 0

  # The maximum number of writes queued for processing.
  # Setting this to 0 disables the limit.
  # max-enqueued-write-limit = 0

  # The maximum duration for a write to wait in the queue to be processed.
  # Setting this to 0 or setting max-concurrent-write-limit to 0 disables the limit.
  # enqueued-write-timeout = 0

###
### [ifql]
###
### Configures the ifql RPC API.
###

[ifql]
  # Determines whether the RPC service is enabled.
  # enabled = true

  # Determines whether additional logging is enabled.
  # log-enabled = true

  # The bind address used by the ifql RPC service.
  # bind-address = ":8082"

###
### [logging]
###
### Controls how the logger emits logs to the output.
###

[logging]
  # Determines which log encoder to use for logs. Available options
  # are auto, logfmt, and json. auto will use a more a more user-friendly
  # output format if the output terminal is a TTY, but the format is not as
  # easily machine-readable. When the output is a non-TTY, auto will use
  # logfmt.
  # format = "auto"

  # Determines which level of logs will be emitted. The available levels
  # are error, warn, info, and debug. Logs that are equal to or above the
  # specified level will be emitted.
  # level = "info"

  # Suppresses the logo output that is printed when the program is started.
  # The logo is always suppressed if STDOUT is not a TTY.
  # suppress-logo = false

###
### [subscriber]
###
### Controls the subscriptions, which can be used to fork a copy of all data
### received by the InfluxDB host.
###

[subscriber]
  # Determines whether the subscriber service is enabled.
  # enabled = true

  # The default timeout for HTTP writes to subscribers.
  # http-timeout = "30s"

  # Allows insecure HTTPS connections to subscribers.  This is useful when testing with self-
  # signed certificates.
  # insecure-skip-verify = false

  # The path to the PEM encoded CA certs file. If the empty string, the default system certs will be used
  # ca-certs = ""

  # The number of writer goroutines processing the write channel.
  # write-concurrency = 40

  # The number of in-flight writes buffered in the write channel.
  # write-buffer-size = 1000

###
### [[graphite]]
###
### Controls one or many listeners for Graphite data.
###

[[graphite]]
  # Determines whether the graphite endpoint is enabled.
  # enabled = false
  # database = "graphite"
  # retention-policy = ""
  # bind-address = ":2003"
  # protocol = "tcp"
  # consistency-level = "one"

  # These next lines control how batching works. You should have this enabled
  # otherwise you could get dropped metrics or poor performance. Batching
  # will buffer points in memory if you have many coming in.

  # Flush if this many points get buffered
  # batch-size = 5000

  # number of batches that may be pending in memory
  # batch-pending = 10

  # Flush at least this often even if we haven't hit buffer limit
  # batch-timeout = "1s"

  # UDP Read buffer size, 0 means OS default. UDP listener will fail if set above OS max.
  # udp-read-buffer = 0

  ### This string joins multiple matching 'measurement' values providing more control over the final measurement name.
  # separator = "."

  ### Default tags that will be added to all metrics.  These can be overridden at the template level
  ### or by tags extracted from metric
  # tags = ["region=us-east", "zone=1c"]

  ### Each template line requires a template pattern.  It can have an optional
  ### filter before the template and separated by spaces.  It can also have optional extra
  ### tags following the template.  Multiple tags should be separated by commas and no spaces
  ### similar to the line protocol format.  There can be only one default template.
  # templates = [
  #   "*.app env.service.resource.measurement",
  #   # Default template
  #   "server.*",
  # ]

###
### [collectd]
###
### Controls one or many listeners for collectd data.
###

[[collectd]]
  # enabled = false
  # bind-address = ":25826"
  # database = "collectd"
  # retention-policy = ""
  #
  # The collectd service supports either scanning a directory for multiple types
  # db files, or specifying a single db file.
  # typesdb = "/usr/local/share/collectd"
  #
  # security-level = "none"
  # auth-file = "/etc/collectd/auth_file"

  # These next lines control how batching works. You should have this enabled
  # otherwise you could get dropped metrics or poor performance. Batching
  # will buffer points in memory if you have many coming in.

  # Flush if this many points get buffered
  # batch-size = 5000

  # Number of batches that may be pending in memory
  # batch-pending = 10

  # Flush at least this often even if we haven't hit buffer limit
  # batch-timeout = "10s"

  # UDP Read buffer size, 0 means OS default. UDP listener will fail if set above OS max.
  # read-buffer = 0

  # Multi-value plugins can be handled two ways.
  # "split" will parse and store the multi-value plugin data into separate measurements
  # "join" will parse and store the multi-value plugin as a single multi-value measurement.
  # "split" is the default behavior for backward compatability with previous versions of influxdb.
  # parse-multivalue-plugin = "split"
###
### [opentsdb]
###
### Controls one or many listeners for OpenTSDB data.
###

[[opentsdb]]
  # enabled = false
  # bind-address = ":4242"
  # database = "opentsdb"
  # retention-policy = ""
  # consistency-level = "one"
  # tls-enabled = false
  # certificate= "/etc/ssl/influxdb.pem"

  # Log an error for every malformed point.
  # log-point-errors = true

  # These next lines control how batching works. You should have this enabled
  # otherwise you could get dropped metrics or poor performance. Only points
  # metrics received over the telnet protocol undergo batching.

  # Flush if this many points get buffered
  # batch-size = 1000

  # Number of batches that may be pending in memory
  # batch-pending = 5

  # Flush at least this often even if we haven't hit buffer limit
  # batch-timeout = "1s"

###
### [[udp]]
###
### Controls the listeners for InfluxDB line protocol data via UDP.
###

[[udp]]
  # enabled = false
  # bind-address = ":8089"
  # database = "udp"
  # retention-policy = ""

  # These next lines control how batching works. You should have this enabled
  # otherwise you could get dropped metrics or poor performance. Batching
  # will buffer points in memory if you have many coming in.

  # Flush if this many points get buffered
  # batch-size = 5000

  # Number of batches that may be pending in memory
  # batch-pending = 10

  # Will flush at least this often even if we haven't hit buffer limit
  # batch-timeout = "1s"

  # UDP Read buffer size, 0 means OS default. UDP listener will fail if set above OS max.
  # read-buffer = 0

###
### [continuous_queries]
###
### Controls how continuous queries are run within InfluxDB.
###

[continuous_queries]
  # Determines whether the continuous query service is enabled.
  # enabled = true

  # Controls whether queries are logged when executed by the CQ service.
  # log-enabled = true

  # Controls whether queries are logged to the self-monitoring data store.
  # query-stats-enabled = false

  # interval for how often continuous queries will be checked if they need to run
  # run-interval = "1s"

Thanks!

@TheTechnoMan it's likely that the cache is not yet 7m. The WAL stores data in an append only format that will likely be bigger than the size of the in-memory cache.
Try reducing your cache size further, and see if that helps. Aside from that, the cache will snapshot to a TSM file with it hits the cache-snapshot-memory-size. The WAL should then be truncated.


Incorrect behaviour of __isNumeric

The check within __isNumeric behaves not in the intended way.
Tested the following stuff in Firefox:

[ ] Provide unit-tests for __is* methods
[ ] Fix __isNumeric
[ ] Ensure all __is* methods work as intended


[ENH] Improve deep learning networks test coverage for parameters which can be list

Reference Issues/PRs
Improves part of #1233
What does this implement/fix? Explain your changes.
Improve the test_all_networks_functionality tests, adding cases when some parameters can be a list.

Before
After

Does your contribution introduce a new dependency? If yes, which one?
No.
Any other comments?
Some tests won't work and are disabled as 'continue exceptions'. I don't know if this is the right way to do it.
In any case, these problems will need to be fixed, and are related to the implementations themselves.
Anyway, we are adding new tests, and these cases are just like before, without the improvement.
# Exceptions to fix
if (
    attrname in ["kernel_size", "padding"]
    and network.__name__ == "TapNetNetwork"
):
    continue
if attrname in ["activation"] and network.__name__ == "AEBiGRUNetwork":
    continue
# LITENetwork does not seem to work with list args
if network.__name__ == "LITENetwork":
    continue

PR checklist
For all contributions

[x] I've added myself to the list of contributors. Alternatively, you can use the @all-contributors bot to do this for you.
[x] The PR title starts with either [ENH], [MNT], [DOC], [BUG], [REF], [DEP] or [GOV] indicating whether the PR topic is related to enhancement, maintenance, documentation, bugs, refactoring, deprecation or governance.

Thanks for taking care of this, coverage seems great now !
We should open an issue after this getting merged for cases like LITE (still not parametrized as it should with list inputs)

This should be a separate test IMO i.e. test_all_networks_functionality.
Will these parameters be in every network (even future ones)? May be missing something, but would this fail if a network does not have one from the list?

hmm good point @MatthewMiddlehurst , maybe we can have a test per network ? test_inception_parameters, test_lite_parameters etc.

This should be a separate test IMO i.e. test_all_networks_params.

Not sure about this as it's exactly the same test as before but with different types for some parameters.
But yeah, it's easy to change as you asked :)

hmm good point @MatthewMiddlehurst , maybe we can have a test per network ? test_inception_parameters, test_lite_parameters etc.

This is also a valid choice, but which requires a new test to be created for each new network.
For now, I was mimicking the actual tests that do not require that.

Will these parameters be in every network (even future ones)? May be missing something, but would this fail if a network does not have one from the list?

The networks do not share the parameters, that's why we check that the network have the parameters or not. So no, this would not fail if a network does not have the parameter.
The only reason to have a fail is if a new network use the same parameters name but do not allow the usage of both types (e.g. like LITE for now).

I do not mind it being a singular test for now instead of going through each file and adding a bunch of tests. Ideally the parameters would be used in more than one network though.

Not sure about this as it's exactly the same test as before but with different types for some parameters.
But yeah, it's easy to change as you asked :)

I think it's acceptable to lose a bit of testing efficiency here for readability. You don't have to assert the output etc like the current test. I would like to avoid forming the "omni-test" for all networks which just covers everything in a single function, it was kinda like that before 🙂.

I added the new test as a new function, test_all_networks_params as proposed. I also changed the AE skip using tag instead of the network name and added a skip info.
Also, is tensorflow-addons requirement still needed ? ref

thanks for the changes @Cyril-Meyer ! the check for config existence is good solution for now, we should keep in mind removing it once we add the config to all other networks
great catch on tensorflow-addons, we dont need it no, we removed its usage before and project  no longer depends on it, probably forgot to remove it here

thanks for the changes @Cyril-Meyer ! the check for config existence is good solution for now, we should keep in mind removing it once we add the config to all other networks

The check was not necessary, as the base class has it :
    _config = {
        "python_dependencies": ["tensorflow"],
        "python_version": "<3.12",
        "structure": "encoder",
    }

I just didn't see this before, but it's cool.

great catch on tensorflow-addons, we dont need it no, we removed its usage before and project no longer depends on it, probably forgot to remove it here

Yeah, I think it will be more clear if we create a new issue and solve it with a new PR (I can handle that).

Looks good to me @MatthewMiddlehurst how about you ? (btw for some reason readthedocs says "pending" for 12 hours now)

Can ignore the docs, says it has built fine when you click on details.


Connect Error with Docker Installation

Hello,
i have a Problem with the Login.
I have an Home Assistant OS to test, there the login is ok.
But on my Dockers Installation with an Rasperry there i become this error when i want to login:

Can anyone help?
Thanks a lot

if you need hep, you need to follow the bug template and put all the required information there

Oh, ok sorry, here the template:
Please check Services, Known Bug / Issues and Troubleshooting over here first: https://github.com/fuatakgun/kia_uvo/blob/master/README.md
Region and Brand of car
Europe Germany Kia EV6 GT 2023
Version of the integration
current v2.10.2
Describe the bug
A clear and concise description of what the bug is.
When i want to login, i become immediately an error: "Unbekannter Fehler" (englisch: "unknown error")
Debug logs if an error occurred
`Logger: custom_components.kia_uvo.config_flow
Source: custom_components/kia_uvo/config_flow.py:63
Integration: Hyundai / Kia Connect (documentation, issues)
First occurred: 29. Juni 2023 um 08:53:04 (8 occurrences)
Last logged: 12:45:58
Unexpected exception
Traceback (most recent call last):
File "/config/custom_components/kia_uvo/config_flow.py", line 159, in async_step_user
await validate_input(self.hass, user_input)
File "/config/custom_components/kia_uvo/config_flow.py", line 63, in validate_input
token: Token = await hass.async_add_executor_job(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/concurrent/futures/thread.py", line 58, in run
result = self.fn(*self.args, **self.kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/hyundai_kia_connect_api/KiaUvoApiEU.py", line 198, in login
device_id = self._get_device_id(stamp)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/hyundai_kia_connect_api/KiaUvoApiEU.py", line 1104, in _get_device_id
_check_response_for_errors(response)
File "/usr/local/lib/python3.11/site-packages/hyundai_kia_connect_api/KiaUvoApiEU.py", line 110, in _check_response_for_errors
raise APIError(f"Server returned: '{response['resMsg']}'")
hyundai_kia_connect_api.exceptions.APIError: Server returned: 'Invalid request body - Invalid parameter.'`
Outlined here: https://github.com/fuatakgun/kia_uvo/blob/master/README.md
To Reproduce
yes
Expected behavior
?
Screenshots
If applicable, add screenshots to help explain your problem.

Additional context
I have an Home Assistant OS to test, there the login is ok.
But on my Dockers Installation with an Rasperry there i become this error

should be related to this: https://github.com/Hyundai-Kia-Connect/kia_uvo/issues/660
not specific to your setup but an overall issue impacting EU

Oh, thank you

Same issue here wit my Kia eNero. Worked perfect in the recent past


New hand_landmark.tflite model worse than previous

The new hand_landmark.tflite model is considerably worse than the previous one.
On my PC, i3-8100K, the old hand_landmark.tflite gives 8-9 FPS, whereas the current one only gives 6 FPS.

Hi, thank you for testing the model performance! I wonder for previous model, are you comparing with the hand_landmark_3d or hand_landmark?
We expect the new model (3D) to be faster than previous 3D version, but slightly slower than the 2D version.

Hi,
I was comparing 3D to 2D. Is there an updated 2D version, or it now only 2D?

We don't have a standalone 2D version anymore since the 3D has comparable quality on x,y. Sorry that it's slower than the previous 2D version and causes trouble. We have speed up the model internally (2.5x faster on GPU, 3x faster on CPU) with minimum quality change, but haven't determined the plan to release it yet. We'll consider prioritize releasing the light model.

OK. Is the speed up in the 2D model or the 3D model?

Hi, have you tried our latest model? the 3D model should be ~2.5x faster than before.


CI may have created a flawed image

The file /usr/local/share/acme/deploy/haproxy.sh contains 404: Not Found, causing haproxy to not start.
Tested with ghcr.io/flobernd/haproxy-acme-dns01:latest

Tried 2.9 as well, same issue

Seems like the deploy script got merged to the upstream acme.sh repository. It was previously only available from the haproxy repo and downloaded in the Dockerfile (and I forgot to pass --fail to curl which allowed the build process to continue even tho a 404 was returned).
Removing the download step should fix this problem. I'll take a look.

Should be fixed for 3.0 now. 2.9 is currently being deployed as well.

Confirmed that it works now. Thanks for being so quick to fix this!


Bump min support Python to 3.10

Hi @gerrymanoim
The latest numpy minor release (2.10) now requires Python >= 3.10. This PR bumps the minimum Python version for exchange_calendars to 3.10 and amends the requirements file to the latest numpy version.
Bumping the min allows us to lose most of the from __future__ import annotations lines. This has the benefit that the interpreter now actually looks at the typing syntax (raising errors if the syntax is not correct).
There's also the release of Python 3.13 around the corner - seems like a reasonable time to bump the min.
Cheers
Marcus

Thanks! LGTM - merge whenever you're ready.


Feedback on topic detection

@m1ci  wrote
@koidl the topics and associated weights and labels are already provided as part of the output. See
http://api-dev.freme-project.eu/current/e-entity/freme-ner/documents/?informat=text&input=Berlin+is+in+Germany.&outformat=turtle&language=en&dataset=dbpedia&enrichement=dbpedia-categories
The categories information are not included by default. You need to add the enrichement=dbpedia-categories parameter to include also the topics as part of the output.
Any feedback is more than welcome.

... waiting for feedback from @koidl and/or @xFran

@koidl and/or @xFran, if you have feedback on this could you please provide it in this issue? Thanks.

I'm busy right now. I have to write an app for Trinity College Dublin/FALCON Project. Soon as I have some time to implement topic detection in Wripl's application or Kevin has time to test it we will provide feedback.
Sorry about this guys.

Ok. My other project is going well so, I may be able to take a look at this Monday.
Is there anything where I have to focus more my attention? Or just use some random text and check if the topics makes sense. Topic detection is working only for English? Maybe the last question it's a silly one. But hey! Is mine! :-)
Any suggestions please?
Thanks in advance.

I would suggest that you take text that is actually used by WRIPL and comes from one of the WRIPL domains, e.g. finance. It should be text where you have clear expectations what the topics are. I suggest you start with English text. I think it should work for all languages that FREME NER supports. So you can test other languages also as long as you understand them so you can judge if the topic detection is right.

Ok @jnehring. I will try to do may best following your recommendations.
Regarding languages I can test in English, Spanish and Romanian but is not supported by NER engine I believe (it will be nice to have it in the future) and Kevin in German. Those are the languages we manage here.
Thank you.

Currently, entities can be enriched with categories only for entities spotted in English texts.
Note that the categories are retrieved from DBpedia. You can check all available categories for an entity by 1) visiting the DBpedia page for the entity and looking at dcterms:subject, or 2) query them via our Freme LDF endpoint at rv2622.1blu.de:5000/dbpedia-types

Thank you for the note @m1ci.

Hi all
I'm running some tests here. Please see the attached text file.
test.txt
First cUrl command on FREME's production server
curl -v -d @test.txt "http://api.freme-project.eu/current/e-entity/freme-ner/documents/?informat=text&input=&outformat=json-ld&language=en&dataset=dbpedia"

Response:
{
  "timestamp":<PHONE_NUMBER>139,
  "error": "Bad Gateway",
  "status": 502,
  "exception": "eu.freme.broker.exception.ExternalServiceFailedException",
  "path": "//e-entity/freme-ner/documents/"
* Closing connection 0
}

Second cUrl command on FREME's dev server
curl -v -d @test.txt "http://api-dev.freme-project.eu/current/e-entity/freme-ner/documents/?informat=text&input=&outformat=json-ld&language=en&dataset=dbpedia"

Response:
HTTP/1.1 200 OK

But the strange part here is that even the response is 200 OK I don't have any entity spotted.
I really hope I did something wrong because if not this can affect Wripl a lot.

@xFran
You discovered a bug in FREME NER and i created a bug report for this: https://github.com/freme-project/freme-ner/issues/47
But the problem lies within the &input=&outformat=... part of your request. The input parameter overwrites the post body. So you submit an empty string to enrichment. I could reproduce the bug and when i remove the bit &input= then it works.

Second test
I'm using the same boxing articles as @jnehring used before.
FREME's production server
I get the same error. No changes here.
In FREME's development server
curl -v -d @test.txt "http://api-dev.freme-project.eu/current/e-entity/freme-ner/documents/?informat=text&input=&outformat=json-ld&language=en&dataset=dbpedia&enrichement=dbpedia-categories"

I get 3 entities and 11 categories not all related to boxing or sports but seems to make sense.

The category system is not deployed on production. Please use dev for testing.

For the categories I used dev. I just wanted to see if any differences sporting entities between dev and prod.

@xFran
Your cURL is not OK. cURL by default sets the Content-Type header to application/x-www-form-urlencoded which is then incorrectly interpreted by the API. When calling the service set also the Content-Type header to an empty value using -H "Content-Type:"
curl -v -d @test-2.txt "http://api-dev.freme-project.eu/current/e-entity/freme-ner/documents/?informat=text&input=&outformat=json-ld&language=en&dataset=dbpedia&enrichement=dbpedia-categories" -H "Content-Type:"

@m1ci
Still no entities.
}(13:36:00) ○ [fran@xps] ~/Downloads
→ curl -v -d @test.txt "http://api-dev.freme-project.eu/current/e-entity/freme-ner/documents/?informat=text&outformat=json-ld&language=en&dataset=dbpedia&enrichement=dbpedia-categories" -H "Content-Type:"

cUrl fixed.

Removing the first paragraph I get:
One entity
 {
    "@id" : "http://freme-project.eu/#char=10,17",
    "@type" : [ "nif:Phrase", "nif:Word", "nif:RFC5147String", "nif:String" ],
    "nif:anchorOf" : "Germany",
    "beginIndex" : "10",
    "endIndex" : "17",
    "referenceContext" : "http://freme-project.eu/#char=0,2889",
    "taClassRef" : "http://nerd.eurecom.fr/ontology#Location",
    "itsrdf:taConfidence" : 0.5323128034518319,
    "taIdentRef" : "dbpedia:Germany"
  }

and 11 categories.

The categories are not really relevant for this article.

Germany/German  is mentioned 13 times in the article so this entity is OK. China/China’s is mentioned 4 times and was not spotted as a entity.

@m1ci Still no entities.

I believe this is related to the https://github.com/freme-project/freme-ner/issues/41 issue

Can you please move the discussion about getting no entities to a new GitHub issue? We should not mix up different topics in the same discussion.

I can move it into another GitHub issue no probs.
This is about "Feedback on topic detection" I don't know if this is a bug and/or if is there any relations between the issues or just my fault because I mess up  things. We have nothing clear yet and I don't know the code and the workflow of your application either.
If you don't mind, can you or @m1ci open the GitHub issue please if needed?
You guys know better than me what is going on.

Hi @xFran , I think this issue is about whether this type of output
1   dbc:British_Islands 15.94680660984782
2   dbc:Slavic_countries_and_territories    15.821275727763961
(see top of the issue) is relevant for you, and if not what could be changed. Above type of output is not the entity identification itself but about the topic, I assume this is why @jnehring proposed to have here only topic detection related discussion and in a different issue discussion about entity detection itself.

Actually I think this issue is too long. We should close it. I created #53 to collect information about the quality of topic detection. @xFran please start new issues for the bugs you discovered. The issue looks very similar to https://github.com/freme-project/freme-ner/issues/46 maybe you can link in your new issue to https://github.com/freme-project/freme-ner/issues/46


STB001.002 fails with The device has been reset during the test! when it's not

Device
VP2410
RTE version
1.1.0
Affected component(s) or functionality
No response
Brief summary
STB001.002 fails with The device has been reset during the test! when it's not
How reproducible
No response
How to reproduce
robot -b command_log.txt -v snipeit:no -L TRACE -v rte_ip:<IP_ADDRESS> -v device_ip:<IP_ADDRESS> -v config:protectli-vp2410 -v fw_file:protectli_vp2410_v1.1.0.rom -t STB001.002* dasharo-performance/platform-stability.robot
Expected behavior
Test should run.
Actual behavior
STB001.002 Verify if no reboot occurs in the OS (Ubuntu 22.04) :: ... | FAIL |
The device has been reset during the test!

Link to screenshots or logs
logs.tar.gz
Additional context
No response
Solutions you've tried
No response

Sounds like needs reproduction and analysis/fix.

@pkubaj please check for duplicates before opening new issue: https://github.com/Dasharo/open-source-firmware-validation/issues/233
It is enough to report with new conditions (like a device) in the old ticket.


Hematite Encyclopedia Typo

Tinkers' Construct version: 1.19.2-<IP_ADDRESS>
Tinkers' Things version: 1.19.2-<IP_ADDRESS>

Typo in Hematite's Armor Material Encyclopedia Entry; the word "slots" is repeated

Fixed in 1.2.1


Fix bump-formula-pr on a file with no tap

fixes #6821

[x] Have you followed the guidelines in our Contributing document?
[x] Have you checked to ensure there aren't other open Pull Requests for the same change?
[x] Have you added an explanation of what your changes do and why you'd like us to include them? on issue, and title really.
[ ] Have you written new tests for your changes? Here's an example.

[x] Have you successfully run brew tests with your changes locally?

Have you written new tests for your changes?

Any more detailed pointers for how to do this? The command appears to have no tests at present except for argument parsing

Thanks @fredemmott, much appreciated (and hope you're well)!


feature(laconia-config): Parse integers and floats from LACONIA_CONFIG_ env variables

This adds an integer converter and float converter when parking LACONIA_CONFIG_ environment variables (#542).

[x] Add LACONIA_CONFIG_PORT: integer:8080 to env to be interpreted by laconia-config as parseInt(8080);
[x] Add LACONIA_CONFIG_TAX: float:80.80 to env to be interpreted by laconia-config as parseFloat(80.08);
[ ] Update documentation and examples with new features laconiajs/website/issues/8

Note: There was a .forEach with an async callback in the acceptance test that I changed to a for..of loop in order to properly await the promises.

Yeah I was thinking how we handle that. Should we throw an error if either is NaN, or just return NaN?

Yeah I was thinking how we handle that. Should we throw an error if either is NaN, or just return NaN?

NaN is good enough :wink:

I kind of prefer throwing, over returning NaN. As a user, I'll discover my configuration error faster if Laconia is throwing that error for me, instead of me discovering that I'm passing NaN into our app code. I take the error as a configuration issue as, if I configure float:not-float-string, that's my fault as a user, and I'd like to know that. Throwing error is also the behaviour that we currently have under SsmConfigConverter.js, so consistency is a plus.
Thoughts?

Ah yeah if we're throwing in another one with an unexpected value, I'd say we throw here too, or at the very least return null or something so you could do something like const dbPort = env.dbPort || 3306.
@hugosenari What do you think about throwing an error if the value is NaN?

Some days ago I was thinking that if null invention was billion dollar.
JavaScript has trillion dollars mistake (null, undefined and NaN) :-)
NaN: user could write defensive code;
Exception: fail fast.
Both ok, stay with exception for consistency.

Sounds good. One more case I thought of, what should happen if I pass ‘integer:1.23’?

parseInt ignores:

parseInt('<IP_ADDRESS>000.222,2222', 10) === 1
parseInt('1avocado', 10) === 1

I updated the tests for NaN to throw an error if the value is not a valid integer or float.
We could probably combine validateAndParseInt and validateAndParseFloat to a more generic function, but I figured it'd be best to be explicit that the value is not a float or not a integer depending on the config key.

Ha yeah I was thinking about that too when mixing numbers and letters/other chars. We could do something like:
if (inputVal !== inputVal.replace(/\D/g,"")) {
  throw Error("passed string contains invalid characters");
}

Otherwise I'd say just call it out in the docs. Any preference?

source

@geoffdutton It seems like @hugosenari is genuinely waiting for this one, haha. I prefer to throw an error as you have made it look super simple to implement, but I'm happy to merge and release to make it available with this one! Let me know!

I implemented those checks as well, but I'll still call it out int he docs. Should be good to go.

Current regex fail for negative inputs?
Any reason to not use match instead of replace?

if (isNaN(parsedVal) || val.macth(floatRegex))

Good call on the negative numbers and using .match, I've updated to address those.
I think for now we ignore the _ as a Numeric Separator since:
parseInt("99_99", 10 ) === 99;
parseFloat("80_8") === 80;

I will update the documentation to reflect when errors are thrown now. Do one of you want to merge the PR per the "don't merge your own PRs" guideline?


Timeout if MQTT connect to GCP does not respond

Added a timeout handler because initial connect attempt never returns or generates a handle-able event.

I self-certify!


Integrate go-etcd-harness

See https://github.com/mwitkow/go-etcd-harness
Still needs a etcd binary, but hides the hassle of starting the damn thing.

First I will copy the SkyDNS .travis file that already starts etcd so we can run tests.


How to serve GroundingDINO

Thanks for the great work and releasing your model.
My laptop GPU doesn't have enough memory to run GroundingDINO and another model. But I have a local workstation with multiple GPUs that I can infer on. But how can I infer GroundingDINO on another machine. I looked around and TorchServe seems to be the default serving library but it requires a MAR file. If I understand this correct, I don't think I can get that for GroundingDINO. What is the recommended way to serve in this case?

This is not serving through pytorch library, but I was able to setup a Docker image with a simple HTTP path on /inference that accepts a base64 image, a prompt, a text_threshold, and a box_threshold, which in turn calls groundingdino.util.inference.predict - it works fine with marginal latency overhead.

for anyone who want to serve it, can refer to: https://github.com/HaoLiuHust/GroundingDINO-Service


I can´t use commando help

I tried of many ways to give me the permission for the command help, I can use any other commands with the permission minecraft.command. ... but with minecraft.command.help it does´nt work, what could it be?

It's probably checking for a different permission.
Use the verbose command to diagnose further.
https://github.com/lucko/LuckPerms/wiki/Verbose


[pattgen,SiVal] Silicon validation testplan for pattern generator

This PR is based on previous silicon validation test plans. It really only contains one test, but it is simple enough that I don't think it is necessary to split it into separate tests. Happy to make adjustments based on feedback though.

CHANGE AUTHORIZED: hw/ip/pattgen/data/pattgen.hjson

Created issue to track implementing test for silicon validation: https://github.com/lowRISC/opentitan/issues/19832


attempt to update golangci-lint

Signed-off-by: Kuat Yessenov<EMAIL_ADDRESS>

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/assign @geeknoid

@geeknoid Setting CPU_NUM to 1 seems to resolve OOM problem.

/approve
/lgtm

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@kyessenov: The following test failed, say /retest to rerun them all:

Test name
Commit
Details
Rerun command

prow/istio-integ-k8s-tests.sh
c30f70859994332a21f9fb7becc73a7cccf2e20c
link
/test istio-integ-k8s-tests

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@kyessenov lint seems to flake after this change
https://circleci.com/gh/istio/istio/396902?utm_campaign=vcs-integration-link&utm_medium=referral&utm_source=github-build-link
https://circleci.com/gh/istio/istio/396236?utm_campaign=vcs-integration-link&utm_medium=referral&utm_source=github-build-link

Ugh, so I guess it's OOMing again on circle. Should we roll it back? WDYT?

We could try this https://github.com/golangci/golangci-lint#memory-usage-of-golangci-lint maybe?
Its crazy it OOMs when we give it 16gb... I can't repro locally though as it segfaults for me

my PR (#13586) is blocked by this ... can we fix quickly or rollback?

fix hopefully in #13587

@kyessenov I'm still seeing it happen: https://circleci.com/gh/istio/istio/397680?utm_campaign=vcs-integration-link&utm_medium=referral&utm_source=github-build-link

@nmittler rebase or merge manually. Circle doesn't do that for you automatically.


Non-fake fake VRF should incorporate key.

When using the FakeVRF in a non-fake mode (e.g. not using WithResult),
use the signing key as part of the output and verified values.

@nfrisby , could you verify if this resolves the problem we were having? If so, we can close https://github.com/input-output-hk/ouroboros-network/issues/2332 right?

Yep, looks good. For example, I see one of the actual leader schedules during RealTPraos was the following.
[(0,[c0]),(1,[c0,c1,c3]),(2,[]),(3,[]),(4,[c3]),(5,[]),(6,[c2]),(7,[c0,c4]),(8,[c2,c3]),...]

Note that there are active slots consisting of various subsets of the nodes instead of only either one node or all nodes -- that is what we want to see and weren't seeing before. ✔

Awesome! Thanks for the quick turnout @nc6 :)


Data update

Github search for "star"

@jaffee Doesn't pilosa import already sort the data ?

@jaffee Isn't 2MB a very low limit? I was thinking there's not enough data in the sample dataset, and maybe using the 30MB one was a better idea :)

@jaffee Repository 0 appears more than others, since the repos was sorted by stars.

$ cat stargazer.csv | cut -f2 -d',' | grep 0 | wc -l
48026

Of the 275k repo 0 appears in 48k rows.

Sorry, that's wrong, just 19k:
$ cat stargazer.csv | grep ',0,' | wc -l
19705

I think it would be fine to keep both a small and large data set on hand, but IMO we shouldn't require users to download a 30 meg file just to complete our getting started section.

I agree about having small and large versions of the dataset. But even our compressed pilosa binary is 5MB in size.

i haven't reviewed the new data file, but does it significantly improve the sample queries in the getting started? i tend to agree with @jaffee that requiring a large data download just for a getting started doesn't make sense.
also, pilosa will do the sorting internally if it needs to, but it's going to be a lot faster if the data is already sorted.

New data files probably don't improve the queries much. Not sure whether publicly discussing the dataset size is a good idea. Closing this PR.