Edit DB.clone(), DB.Dialect(), and Scope.Dialect() preserve transactions

What did this pull request do?
The problem I'm trying to solve
When running a migration in a transaction, the DB.AutoMigrate() function queries the database for the existence of tables outside of the context of the transaction. This can result in the attempt to create a table which already exists in the transaction. For instance, the following migration results in a failure.
package models

import (
	"time"

	"github.com/jinzhu/gorm"
	gormigrate "gopkg.in/gormigrate.v1"
)

func Migrate() error {
	db, openErr := gorm.Open("postgres", "host=<IP_ADDRESS> port=5432 user=ingress dbname=ingress password=password sslmode=disable")

	if openErr != nil {
		return openErr
	}

	options := &gormigrate.Options{
		TableName:      "migrations",
		IDColumnName:   "id",
		UseTransaction: true,
	}

	if db.Error != nil {
		return db.Error
	}

	m := gormigrate.New(db, options, []*gormigrate.Migration{
		{
			ID: "initial",
			Migrate: func(tx *gorm.DB) error {
				type JsonifiedModel struct {
					ID        uint       `json:"id" gorm:"primary_key"`
					CreatedAt time.Time  `json:"created_at"`
					UpdatedAt time.Time  `json:"updated_at"`
					DeletedAt *time.Time `json:"deleted_at" sql:"index"`
				}

				type First struct {
					JsonifiedModel
					Name string `json:"name" gorm:"not null"`
				}

				err := tx.CreateTable(&First{}).Error
				if err != nil {
					return err
				}

				return nil
			},
		},
		{
			ID: "add_ttl",
			Migrate: func(tx *gorm.DB) error {
				// when table already exists, it just adds fields as columns
				type First struct {
					TTL int `gorm:"not null"`
				}

				return tx.AutoMigrate(&First{}).Error
			},
			Rollback: func(tx *gorm.DB) error {
				err := tx.Table("firsts").DropColumn("ttl").Error
				if err != nil {
					return err
				}

				return nil
			},
		},
	})

	err := m.Migrate()

	if err != nil {
		return err
	}

	return nil
}

The migration above results in an error: Could not perform database migrations: pq: relation "firsts" already exists.
Proposed Fix
When a DB connection is cloned, I propose that it stores a Dialect based off the parent's dialect, but using the db SQLCommon of the connection it was cloned from. This will make the current transaction available to a newly created scope so that when it interrogates the DB for the existence of a table, it has the context of the current running transaction.
Additionally, when a transaction is begun, I think it should update the DB connection of the dialect stored in the newly cloned connection.
Feedback is very welcome.

Have you had a chance to look at this PR and if so, do you have any feedback or needs from me on this PR?


json.readArray() causes panic when reading empty arrays

Component
Forge
Have you ensured that all of these are up to date?

[X] Foundry
[X] Foundryup

What version of Foundry are you on?
forge 0.2.0 (624797e 2023-02-20T00:07:44.723592254Z)
What command(s) is the bug in?
forge script
Operating System
Linux
Describe the bug
Empty arrays in JSON files cause a panic, when a corresponding json.readTypeArray() is called. Attaching a minimal example:
{
  "tokens": ["0xC02aaA39b223FE8D0A0e5C4F27eAD9083C756Cc2"],
  "empty": []
}

// SPDX-License-Identifier: MIT
pragma solidity 0.8.17;

import {console, stdJson, Script} from "forge-std/Script.sol";

contract TestScript is Script {
    using stdJson for string;

    function run() external {
        string memory json = vm.readFile("test.json");
        // This succeeds
        address[] memory tokens = json.readAddressArray(".tokens");
        console.log("Tokens Length: %s", tokens.length);
        // Every one of these causes panic
        json.readAddressArray(".empty");
        json.readBoolArray(".empty");
        json.readBytesArray(".empty");
        json.readBytes32Array(".empty");
        json.readStringArray(".empty");
        json.readIntArray(".empty");
        json.readUintArray(".empty");
    }
}

The application panicked (crashed).
Message:  index out of bounds: the len is 0 but the index is 0
Location: evm/src/executor/inspector/cheatcodes/util.rs:133

This is a bug. Consider reporting it at https://github.com/foundry-rs/foundry

  ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ BACKTRACE ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
   1: __libc_start_call_main<unknown>
      at ./csu/../sysdeps/nptl/libc_start_call_main.h:58
   2: __libc_start_main_impl<unknown>
      at ./csu/../csu/libc-start.c:392

Run with COLORBT_SHOW_HIDDEN=1 environment variable to disable frame filtering.
Aborted (core dumped)

Also worth noting that my local .env file contains  the line COLORBT_SHOW_HIDDEN=1

cc @odyslam

@mattsse can you assign pls

Will try to tackle this in the week @ChiTimesChi


Timerfd fix 32bits

Fix bug #1350

ugh, this PR includes another fix... will send another version

updated with a single commit to fix your issue.

merged.


conformance-k8s-kind: Use Helm mode cilium-cli

Ref: https://github.com/cilium/cilium-cli#experimental-helm-installation-mode
Ref: #25156

/test


nginx: forceSSL breaks enableACME

Describe the bug
I am experiencing that when these two options are enabled at the same time, the certificate fails to be generated as when Let's encrypt tries to request the authorization token, it gets a "connection refused" from the machine. This does not happen when forceSSL is not enabled.
Once the ceritificate is generated properly without forceSSL, then one can enable the option and successive deployments do work.
Steps To Reproduce
Enable both forceSSL end enableACME on a new virtualHost in an nginix configuration.
Expected behavior
The new configuration is applied without errors.
Screenshots
If applicable, add screenshots to help explain your problem.
Metadata
Please run nix-shell -p nix-info --run "nix-info -m" and paste the result.
[user@system:~]$ nix-shell -p nix-info --run "nix-info -m"
 - system: `"x86_64-linux"`
 - host os: `Linux 5.15.59, NixOS, 22.11 (Raccoon), 22.11pre-git`
 - multi-user?: `yes`
 - sandbox: `yes`
 - version: `nix-env (Nix) 2.11.1`
 - channels(root): `"nixos-21.11, nixpkgs"`
 - nixpkgs: `/root/.nix-defexpr/channels/nixpkgs`

I'm actually not sure anymore this was the root cause, as some investigation seems to imply that it was some of the other options at play...

Yeah I had something similar happen to me. I definitely was doing double-deploys, first without the virtualhost and only with the catchall for the challenge, and a second deploy with the virtualhost after the cert was generated.

Can this be re-opened? there should be an update on the docs at least?

Same issue here, I always have to do double-deploys.

@ChrisDeadman
I am no longer using forceSSL, now I use onlySSL and it works better.
First you add a catchall for the challenge:
      "acmechallenge.domain.tld" = {
        # Catchall vhost, will redirect users to HTTPS for all vhosts
        serverAliases = [ "*.domain.tld" ];
        locations."/.well-known/acme-challenge" = {
          root = acme.webroot;
        };
        locations."/" = {
          return = "301 https://$host$request_uri";
        };

Then you add your vhosts with onlySSL
      "subdomain.domain.tld " = {
        onlySSL = true;
        useACMEHost = "domain.tld";
      };

This requires
  security.acme.certs."domain.tld" = {
    webroot = acme.webroot;
    extraDomainNames = [ "subdomain.domain.tld" ];
  };

The problem with forceSSL is that it creates a vhost for the http route which redirects to the https version, this obscures the catch-all for the challenge.


TH-11: Themes > Can’t modify/hide "add comment button" in product review

JIRA Ticket
Ticket: TH-11.
Prerequisites

[ ] Check this branch locally and run pnpm run release
[ ] 3 new files will be generated in this format theme name + date + .zip
[ ] Upload generated file locally or in seller-area test env

QA Steps

[ ] Go to /something
[ ] Verify said thing

Note
Leave empty when you have nothing to say.

The PR looks good. I left u some suggestions (applied to all themes). Also, please avoid making changes to .css files and keep .scss files only.

The SCSS is getting converted to CSS, browser only understands CSS


Message Count Rewards

Simple rewards checker for each count goal that is reached, starting at 50. Everything is commented and readily editable.

Seems perfect but it should be put under the already made message count cmd (in the code, at the bottom) cus it uses .* regex already so two .* regex is a waste

damn looks lit, can i use it now xd


[Backport release-24.05] veilid: 0.3.3 -> 0.3.4

backport of #331817
Description of changes

Things done

Built on platform(s)

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

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

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

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

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

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

[ ] Fits CONTRIBUTING.md.

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

Result of nixpkgs-review pr 332327 run on x86_64-linux 1

3 packages built:

veilid
veilid.dev
veilid.lib


Add attachment support for mailgun

This PR adds attachment support to the mailgun adapter.
After #306 is merged this PR needs to be adjusted.

I haven't found a way to test the attachments for the mailgun adapter. Can anyone help me with it?
It uses multipart as content type and I can't get the attachment by calling assert_receive {:fake_mailgun, struct} in the test.

@schurig Now that https://github.com/thoughtbot/bamboo/pull/306 has been merged, it is a simple matter to resolve the merge conflicts for this PR?  We'd really like to be able to start sending attachments via Mailgun.

@schurig Hi, what is the status of this PR? Is any help needed to get it merged?

@a12e @rickclare hi both of you. I would be happy to get help with this PR. I currently don't have time to work on it. Also I'm still stuck with the tests for the attachments https://github.com/thoughtbot/bamboo/pull/307#issuecomment-315197367

After digging a little, here is what I found about the test issue.
This is the raw HTTP body that we send to Mailgun, which seems right:
-----------------------------mhcillixvhiobfhg
content-length: 12
content-type: application/octet-stream
content-disposition: form-data; name="from"

<EMAIL_ADDRESS>-----------------------------mhcillixvhiobfhg
content-length: 15
content-type: application/octet-stream
content-disposition: form-data; name="h:X-My-Header"

my_header_value
-----------------------------mhcillixvhiobfhg
content-length: 9
content-type: application/octet-stream
content-disposition: form-data; name="html"

HTML BODY
-----------------------------mhcillixvhiobfhg
content-length: 10
content-type: application/octet-stream
content-disposition: form-data; name="subject"

My Subject
-----------------------------mhcillixvhiobfhg
content-length: 9
content-type: application/octet-stream
content-disposition: form-data; name="text"

TEXT BODY
-----------------------------mhcillixvhiobfhg
content-length: 0
content-type: application/octet-stream
content-disposition: form-data; name="to"

-----------------------------mhcillixvhiobfhg
content-length: 16
content-type: application/octet-stream
content-disposition: form-data; "name"="attachment"; "filename"="attachment.txt"

Test Attachment

-----------------------------mhcillixvhiobfhg--

This request is parsed by the Plug.Parsers.MULTIPART as configured in the fake server:
    plug Plug.Parsers,
      parsers: [:urlencoded, :multipart, :json],
      pass: ["*/*"],
      json_decoder: Poison

This Parser should create a :body_params array in the Conn with all MIME fields. This is what we actually get in the Conn:
%Plug.Conn{...,
body_params: %{"bcc" => "BCC<EMAIL_ADDRESS>"cc" => "CC<EMAIL_ADDRESS>  "from" =><EMAIL_ADDRESS>"subject" => "",
  "to" => "To <to<EMAIL_ADDRESS>}

The attachment field has not been parsed. It does not appear in the Conn params.
The solution is to use Plug.Upload. I'll try to work on this. (I found it after writing this message)

@a12e awesome thank you so much! Let me know how it goes. Also, feel free to open a new PR and use my changes if that works better for you!

New PR: #341


make ruby tests pass

change handler to conform to test expectation
change bootstrap.rb server address to use AWS_LAMBDA_RUNTIME_API from ENV
change bootstrap.rb to load lambda handler properly from LAMBDA_TASK_ROOT
add ruby2.5 and ruby2.7 runtimes
add install-ruby script
use rvm to install rubies
add ruby-version test for ruby2.7 and ruby2.7

hey @styfle - what's the best way to ask for a review / discuss this with you? I'm a little new to contributing so however you'd prefer I format my pull request, I'd be happy to do so.
Additionally, I noticed that this is probably not going to work correctly end-to-end unless:

https://github.com/zeit/now/blob/master/packages/now-cli/src/util/dev/builder.ts#L362 is cast as a RuntimeLiteral (or something else needs to happen? Right now it complains about that when I try to build, I've changed that line to Runtime: asset.runtime as RuntimeLiteral locally)
https://github.com/zeit/now/blob/master/packages/now-ruby/install-ruby.ts#L53-L61 is modified to look for the correct gemHome if meta.isDev === true
https://github.com/zeit/now/blob/master/packages/now-ruby/install-ruby.ts#L21-L24 needs to be removed of course :)

Please let me know your thoughts on the code!

Ah, I see now about https://github.com/zeit/now/pull/3667 - Would make sense to modify that PR a bit more to take my suggestions above into account?

hey @styfle - thanks for the suggestions! I made the updates you recommended :)


jupytercalpoly logo

It has come to my attention that our current organization logo is a little too robotic/lacking the necessary flair. I propose an amateur's alternative to this problem.
Any thoughts/input from an actual designer is appreciated

Or this ¯_(ツ)_/¯

Love this idea, maybe we could spice it up a bit? Here's a simple, yet still more extravagant design idea..

I think this belongs on some T-shirts :)

On Jun 17, 2016, at 5:07 PM, matt-bowers<EMAIL_ADDRESS>wrote:
Love this idea, maybe we could spice it up a bit? Here's a simple, yet still more extravagant design idea..
https://cloud.githubusercontent.com/assets/9501647/16167756/fc73886a-34ad-11e6-8d37-eec49a924938.png
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ping 🔔

ping @willingc

@Ruv7 @ellisonbg The interns have put together a pretty cool logo for the summer teams. Would it be possible to get shirts made for the CP folks that uses the latest logo? If so, what would be the best way to do that? Thanks!

@ellisonbg - whatever happened to the Jupyter branding guidelines? Were those published somewhere we can view?

@Ruv7 This was something that was more of a team building idea than anything that is a rush. It could be as simple as buying t-shirt transfer paper from Staples and use that for putting on the shirts. Branding guidelines are probably in the jupyter/design repo.

Link to the jupyter/design repo

@willingc I have clicked about in good faith in that repo but can't seem to find branding guidelines. I would like anything promoting Project Jupyter to follow the established protocol. Assuming one exists :)  I will follow up to should make those guidelines more available and known among the team and community...

@willingc tbh I just wanted that logo to be the new jupytercalpoly logo instead of the default alien lol ¯\_(ツ)_/¯

@Ruv7 Sounds good to me. Your wish is our mission.
Okay, team. Marshmallow challenge of the week: Design a non-Jupyter logo for the Cal Poly summer intern t-shirt logo. Extra points for incorporating salsa (music, dancing, or food).
Branding guidelines for the marketing guru. 👕 👚 👟 👒 👽 🌔 Logos for all the things ;-)

More than willing to purchase the students special team t-shirts :-)
We can use Custom Ink for that too...
Cheers,
Brian
On Fri, Jul 1, 2016 at 2:34 PM, Carol Willing<EMAIL_ADDRESS>wrote:

@Ruv7 https://github.com/Ruv7 Sounds good to me. Your wish is our
mission.
Okay, team. Marshmallow challenge of the week: Design a non-Jupyter logo
for the Cal Poly summer intern t-shirt logo. Extra points for incorporating
salsa (music, dancing, or food).
Branding guidelines for the marketing guru. 👕 👚 👟 👒 👽 🌔 Logos for
all the things ;-)
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Brian E. Granger
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Cal Poly State University, San Luis Obispo
@ellisonbg on Twitter and GitHub
<EMAIL_ADDRESS>and<EMAIL_ADDRESS>

Awesome! Any guidance on where to find the branding guidelines or is that project still in progress?

The closest was some work that Cameron did - Matt, could you contact him
about that stuff?
On Fri, Jul 1, 2016 at 2:41 PM, Ana Ruvalcaba<EMAIL_ADDRESS>wrote:

Awesome! Any guidance on where to find the branding guidelines or is that
project still in progress?
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<EMAIL_ADDRESS>and<EMAIL_ADDRESS>

@willingc
Before:

After:
after.pdf
Plz for my sanity

Good to keep this conversation alive, I think the hold up was whether or not we could get status update on branding parameters. If we are going to publish these to the community we shouldn't be the first to break them! @matt-bowers - are you open to leading that discussion?

I do like the after version. I will leave this in @Ruv7's capable hands to guide you :sunny:

+1 on the JupyterCalPoly Github Organization logo redesign!

I am somewhat amused that the after version looks as if Chompy has chomped some bites out of the logo.

Would a simplified avatar be good to replace the default avatar for now, until we can figure out if there are guidelines to follow or not?

We need to figure out branding before using a variation of the logo.
On Jul 27, 2016 5:28 PM, "Matt Bowers"<EMAIL_ADDRESS>wrote:

Would a simplified avatar be good to replace the default avatar for now,
until we can figure out if there are guidelines to follow or not?
[image: screen shot 2016-07-27 at 5 27 06 pm]
https://cloud.githubusercontent.com/assets/9501647/17197203/87c776a2-541f-11e6-8bfb-762ad33248ea.png
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I yield. I don't care about the logo anymore.

Bummer. Not trying to be an idea squasher, but this is a gap in our design processes and without a design lead on filling the need we can't move forward.

@eskirk :cry: We want you to have a logo. We also want to protect Jupyter's intellectual property. For context, this is the short version of the Python Software Foundation's trademark guidance https://www.python.org/psf/trademarks/ and there is a Working Group to work with folks that wish to use/modify the logo.
If you scan down to the derived works section, that specifies what the PSF feels is acceptable or not. I'm wondering if the summer logo was changed enough perhaps using a "sun" instead of "Jupyter" and planets instead of moons that the logo would be different enough to move forward with.
As an example, we spent quite a bit of time making sure that legally the new Python packaging logo https://pypi.io/ protected the IP of the PSF logo https://www.python.org/community/logos/

So I was in the process of creating a branding guidelines page right before leaving for the summer, I am pretty sure in the guidelines we stated that there should not be any variation to the logo or any components of the logo (aka anything within the three planets in the jupyter logo). The logo that @matt-bowers posted, with the "cp" next to the Jupyter logo, should comply with our guidelines though @Ruv7. However, I am not sure about the one with the text within the planets and under the jupyter wording. When I get home tonight, I will check to see where these guidelines are stored. Regardless, I should be able to have the page or documentation to you guys by tomorrow!

Hey @cameronoelsen! Were you able to find those guidelines?

No worries if not btw, we just don't want to recreate the wheel if you've already started. Any guidance or thoughts today or tomorrow would be great otherwise we'll get started on creating them. Thanks!

Hey everyone, so I mocked up another temporary "Jupyter Cal Poly" avatar that we can use in place of the branding guidelines being finished. This one will indeed comply with the branding guidelines the design team is working on, as it is simply a photo overlay of the inverted single color main logo.

This is what it would look like as an avatar:

Yes but how would it look on a t-shirt?

Might look good on a shirt if the overlay was on a watercolor of the photo. :art:


In vscode 1.10.1, the .vue file extension is no longer associated with HTML by default

Congratulations on your plugin as an official recommendation.

This is encouraging news -- thanks for letting me know :-)


Build failures: unknown property 'nexusUsername' & no configured signatory

gradlew clean build

FAILURE: Build failed with an exception.

* Where:
Build file '~/bravo/build.gradle' line: 93

* What went wrong:
A problem occurred evaluating root project 'bravo'.
> Could not get unknown property 'nexusUsername' for object of type org.gradle.api.publication.maven.internal.deployer.DefaultGroovyMavenDeployer.

I know this is trivial to fix locally by removing these lines:
https://github.com/king/bravo/blob/4311dc2ccfe3066c136f9d1bf08d218f2d0c7b43/build.gradle#L92-L98
After that I get:
> Task :bravo:signArchives FAILED

FAILURE: Build failed with an exception.

* What went wrong:
Execution failed for task ':bravo:signArchives'.
> Cannot perform signing task ':bravo:signArchives' because it has no configured signatory

which can be fixed by removing:
https://github.com/king/bravo/blob/4311dc2ccfe3066c136f9d1bf08d218f2d0c7b43/build.gradle#L54-L56
It would be nice to have some official way to avoid these errors so that there's no need to work on a dirty repo locally. What would you suggest?

Sorry this is a side effect of my last attempt to publish this to the central repo.
I will fix it so it doesn’t affect you after lunch

this should be fixed with the latest commit on master ^^


create a centralized firebase auth error handler

Issue reference: :  #46
Proposed changes:
create a centralized firebase error handler that handles firebase auth errors.
Type of change: : Bug fix
Please delete options that are not relevant.

[x] Bug fix (non-breaking change which fixes an issue)

Checklist:

[x] My code follows the style guidelines of this project
[x] I have performed a self-review of my own code
[x] I have commented my code, particularly in hard-to-understand areas
[x] I have made corresponding changes to the documentation
[x] My changes generate no new warnings

Additional info (if any):

@Devika-Sahu
You deleted the env.sample 🙂
You had to create a .env file and copy the contents of .env.sample to it, you just renamed it to .env 😅
Anyways fix that and I'll review it 👍

@Devika-Sahu
First of all, really sorry for being late, I had some urgent work 😞
I have reviewed your pull request. You have to make some more changes:

You have not provided a default case in the error handler. There are more types of errors apart from the ones you made cases for. For example:

For this kind of error, you can use the default case with the default error message:

default:
  toast.error(`Error: {errorCode}`);
  break;

Make the firebaseAuthErrorHandler as a default export:

export default firebaseAuthErrorHandler;

Use prettier to format all the files you have modified. If you are using VS Code you can install the prettier extension and from VS Code settings, enable format on save. Also, for future pull requests, make sure you do this step 👍

Make these changes and I'll review it without any delay now 👍

@varunKT001 Could you please merge my PR as it's the time of evaluation.

@Devika-Sahu Make the required changes I mentioned. Once you make the changes  I'll merge your PR.


Add or remove data in octree.bin

Hi,
Is it planned to be able to add or remove parts of the point cloud in the octree.bin afterwards?
In short, edit the octree.bin
Thanks in advance,

Not planned since it's a rather large effort. CPotree will soon be able to apply filter operations on Potree 2.0 point clouds, and store the result in las files.


App Works Launched from Command Line But Not When Double-Clicked

I'm just dipping my toes in the water with Platypus and trying to put together an app which edits the /etc/hosts file. Code is given below.
My problem is that, when I run the app bundle directly from the command line:
/Users/madra/claraithe/python/Prevvo/Prevvo.app/Contents/MacOS/Prevvo
it works perfectly; backs up the existing etc/hosts file, writes the new one and shows the appropriate notifications.
However, if I launch the app the conventional way, by double-clicking it in the Finder, nothing seems to happen. Well, I get the dialogue to enter my admin password [obviously, the app requires root privileges] but after that no further output. I don't get any error messages, but the existing /etc/hosts file isn't backed up and nothing is written to it either.
Ironically, it was for this reason that I launched the app via the command line in the first place:
/Users/madra/claraithe/python/Prevvo/Prevvo.app/Contents/MacOS/Prevvo
as I was hoping to get some useful debugging info in my terminal. But, the app runs perfectly when launched that way. So I'm a bit stuck as to how I go about troubleshooting this.
Here's the code I've got so far. As it's very initial stages, please forgive the clunkiness!
#!/usr/bin/env python3

#import modules
import sys
import logging
from logging.handlers import SysLogHandler
from shutil import copyfile

#setup logging
logger = logging.getLogger("Prevvo")
logger.setLevel(logging.DEBUG)
syslog = SysLogHandler(address ="/var/run/syslog")
formatter = logging.Formatter("%(name)s: %(levelname)s %(message)s")
syslog.setFormatter(formatter)
logger.addHandler(syslog)

#test log messages
#logger.debug('this is debug')
#logger.critical('this is critical')

#source and destination hosts file & backup
source = "/etc/hosts"
destination = "/etc/hosts-prevvo-backup"

#banlist file [hard-wired for now]
banlist = open("/Users/madra/claraithe/python/Prevvo/banlist.txt")

#backup existing hosts file
try:
	if copyfile(source, destination):
            logger.info("hosts file backed up")
            print("NOTIFICATION:Hosts file backed up\n")

#permissions error
except PermissionError:
    logger.critical("Permissions error backing up existing hosts file. Are you admin?")
    print("Permissions error backing up existing hosts file. Are you admin?\n")

#misc. error
except:
    logger.critical("Unknown error")
    print("Unknown error")

#open hosts file
try:
	with open(source, "a") as hostfile:
            #append start of prevvo block
            hostfile.write("\n### PREVVO BLOCKLIST ###\n")
            #append normal and www version for each line in banlist
            for line in banlist.readlines():
                hostfile.write("<IP_ADDRESS>\t{0}".format(line))
                hostfile.write("<IP_ADDRESS>\twww.{0}".format(line))
            #append end of prevvo block
            hostfile.write("### END PREVVO BLOCKLIST ###\n")
            logger.info("New hosts file written")
            print("NOTIFICATION:Wrote new hosts file\n")

#permissions error
except PermissionError:
    logger.critical("Permissions error writing hosts file. Are you admin?")
    print("Permissions error writing hosts file.  You could try to wrap the invocation of the python script in a bash script. Try to run it through Platypus via /bin/bash -l and see if it works.

The only environment related thing I can think of is that I've got a shebang at the top of the Python script, to use Python3 instead of the default system Python [2,7] #!/usr/bin/env python3.  Other than that, it's a pretty straightforward script. It writes to /etct/hosts which requires sudo, but that should be covered by Platypus's 'require Root prveleges', shouldn't it?

Ah, so you're running it through /usr/bin/env ... try setting the interpreter as your python3 path see whether that changes anything.

Ah. I've solved the mystery.
I tried various options for the shebang, including #!/usr/bin/env python3 #!/usr/bin/python3, #!/usr/local/bin/python3 and no shebang --none of which made any difference.  Then, I wondered if the Python script should be made executable.  So I did a chmod +x on it and tried again and it worked perfectly.

Apologies if this was mentioned in the docs, but [as ever] I decided to tinker first and RTFM afterwards.
Cheers for your help!.

Just to [sort of] close this:
I reconfigured my Platypus settings to use the default system Python, rather than trying to induce it to use Python3 and it worked fine. So obviously the problem lies in not using the system Python.
No biggie. I'll just rejigger the script a bit if needs be to use Python, rather than Python3 syntax.


CIP-0053? | Multi-Script Hashes

This is a proposal to generalize the script hashing functionality, so that multiple mutually-depended scripts can be assigned fixed addresses at the same time.

see rendered Markdown

#321 is IMO a better solution, albeit not perfect

I feel that this proposal is not "general" enough; it currently works from the plutus-tx API which is one of the possible interfaces to deal with Plutus -- which leads, I believe, to some confusion as to what the proposal is trying to achieve.
I'd suggest to re-formulate this from a more general point of view, taking Plutus core concepts irrespective of the framework used to represent those concepts. In essence, I understand that you are proposing a way for inter-dependent scripts to have ways to reference one another. How is that already not possible when providing configuration-as-datums to the respective script (would love to see this argued somewhere)?

Storing the dependent script hashes in datums is an alternative solution, but it's not trivial to get right because datum on its own can't be trusted. If dApp is not properly designed, attackers can perform a two-step attack:

send a UTxO to a script's address with a datum containing other scripts hashes of their own choosing, and then
submit a transaction that consumes the UTxO from step 1, other outputs from their own scripts, and performs other effects that escalate their access.

The "other effects" part may or may not exist for any particular dApp, but the point is that this may not be easy to prove. In contrast, the txInfoValidators would carry a static, compiled list of script hashes that can't be manipulated by any attacker. The only check that any validator would need to perform is
all (all (`elem` txInfoValidators info) . scriptHashAddress) . txOutAddress . txInInfoResolved) (txInfoInputs info)

Storing the dependent script hashes in datums is an alternative solution, but it's not trivial to get right because datum on its own can't be trusted. If dApp is not properly designed, attackers can perform a two-step attack:

send a UTxO to a script's address with a datum containing other scripts hashes of their own choosing, and then
submit a transaction that consumes the UTxO from step 1, other outputs from their own scripts, and performs other effects that escalate their access.

The "other effects" part may or may not exist for any particular dApp, but the point is that this may not be easy to prove. In contrast, the txInfoValidators would carry a static, compiled list of script hashes that can't be manipulated by any attacker. The only check that any validator would need to perform is
all (all (`elem` txInfoValidators info) . scriptHashAddress) . txOutAddress . txInInfoResolved) (txInfoInputs info)

[EDIT] ... besides, obviously, the checks specific to their own input.

Can't the use of Native Assets serve as guards against this sort of attack? Where the only appropriate UTXOs + Datums the script/dApp should ever interact with will be ones explicitly marked with specific Native Assets, provided by dApp provider/author.

The major problem with this proposal is the transaction size. Every transaction that needs to invoke any validator script that's interconnected with others would need to supply all interconnected scripts, otherwise the hash won't match.
CIP-33 could help with this problem. Unfortunately I wrote up the proposal before reference scripts were available, so that part is lacking.

I've decided I have no further interest in this proposal, and it doesn't look like anybody else does.


Add support for static HTML page generation with input from Handlebars template

Is your feature request related to a problem? Please describe.
I am able to generate the Swagger specification file in JSON and YAML, but I need to generate a static HTML document from the specification that can be hosted separately.
Describe the solution you'd like
It would be comfortable to have a configuration that would let us enable the generation of a static HTML while using a handlebars template. Also, a nested config that will have a default name for the generated html file, but can also be customized as per requirement.
Describe alternatives you've considered
I'm not aware of alternative that I can use. Any suggestion is welcome that can solve the problem.
Additional context
The feature is provided by Swagger plugin from Yukai Kong but it doesn't seem to be working with Swagger v3 annotations. It takes a Handlebars template to generate the static html document.

My initial thought would be to do this as a separate step instead of including it in this plugin. The initial idea was to create a wrapper as thin as possible around the functionality provided by the Swagger project itself. I would use the yaml or json together with a templating framework of choice to render a html version (possibly including the Swagger UI library)

That's true.
Just for reference, the task can be achieved with the swagger-codegen-maven-plugin.
But the problem is, this the openapitools/swagger-maven-plugin works in the prepare-package phase while the codegen plugin works in the compile phase. It would be helpful if the openapitools/swagger-maven-plugin can also be used it the compile phase as sometimes it's not possible/feasible to build a project just for the documentation.

Yeah, now it has been some years since I did the first parts of this. As far as I recall the reason for doing it in prepare-package is because Swagger works on the compiled classes, not the source code. Hence, we need to be sure the project is built before running Swagger. You might be able to attach to the process-classes lifecycle instead, that would allow for skipping at least test - I think you would be able to test this by means of the plugin configuration in the pom.xml overriding the default lifecycle binding.

@langecode
That sounds good, and it does make sense to work on the compiled classes.
That apart, would it be possible to run the swagger-codegen-plugin as part of this plugin? At least that can help to generate static documentation, even if not template-based.


🐛 fix: boolean fields in kafka producer monitor

⚠⚠⚠ Since we do not accept all types of pull requests and do not want to waste your time. Please be sure that you have read pull request rules:
https://github.com/louislam/uptime-kuma/blob/master/CONTRIBUTING.md#can-i-create-a-pull-request-for-uptime-kuma
Tick the checkbox if you understand [x]:

[x] I have read and understand the pull request rules.

Description
Fix field types in database and converting it to boolean just like other boolean fields
newly added migrations should be okay since we where storing data in 0 and 1
Fixes #3760
Type of change
Please delete any options that are not relevant.

Bug fix (non-breaking change which fixes an issue)

Checklist

[x] My code follows the style guidelines of this project
[x] I ran ESLint and other linters for modified files
[x] I have performed a self-review of my own code and tested it
[x] I have commented my code, particularly in hard-to-understand areas
(including JSDoc for methods)
[x] My changes generate no new warnings
[ ] My code needed automated testing. I have added them (this is optional task)

Screenshots (if any)

@louislam
IDK if I had to add migrations in knex or old ones since it's a patch for an older bug and I don't know if it will get released before v2 release or not

Please remove formatting changes unrelated to this PR in monitor.js.

Bug fix can be in 1.23.X.
But since this pr is touching 2.0.0's code, I am afraid that it cannot be simply rebased into the 1.23.X branch automatically.
If you want this bug fix in 1.23.X, feel free to create a new pr which is based on this branch:
https://github.com/louislam/uptime-kuma/tree/1.23.X

Closing this in flavor of #3949


Face detection

Thank you for your hard work，
before run infer.py,it need us modify some configuration accordingly in the config file like configs/infer/retinanet/retinanet.py,What are these parameters？just change the num_classes ande classes_names?Looking forward to your reply。

Hi,
Actually, you only need to change the "weights", the "filepath" where you save your trained model. And others like num_classes and class_names are based on your dataset. Besides, some post process parameters like "score_thr", "max_per_img" and "iou_thr" in "infer_engine" are based on your needs.

Hi,
Actually, you only need to change the "weights", the "filepath" where you save your trained model. And others like num_classes and class_names are based on your dataset. Besides, some post process parameters like "score_thr", "max_per_img" and "iou_thr" in "infer_engine" are based on your needs.

Hi,
Actually, you only need to change the "weights", the "filepath" where you save your trained model. And others like "num_classes" and "class_names" are based on your dataset. Besides, some post process parameters like "score_thr", "max_per_img" and "iou_thr" in "infer_engine" are based on your needs.

thank you for your reply,
however，When I change ‘configs/infer/retinanet/retinanet.py’ to ‘configs/infer/tinaface/tinaface.py’, I can run infer.py successfully. Does this command need to be adjusted？【CUDA_VISIBLE_DEVICES="0" python tools/infer.py configs/infer/retinanet/retinanet.py image_path】 thank  you

Hi,
Actually, you only need to change the "weights", the "filepath" where you save your trained model. And others like "num_classes" and "class_names" are based on your dataset. Besides, some post process parameters like "score_thr", "max_per_img" and "iou_thr" in "infer_engine" are based on your needs.

thank you for your reply,
however，When I change ‘configs/infer/retinanet/retinanet.py’ to ‘configs/infer/tinaface/tinaface.py’, I can run infer.py successfully. Does this command need to be adjusted？【CUDA_VISIBLE_DEVICES="0" python tools/infer.py configs/infer/retinanet/retinanet.py image_path】 thank  you

You mean that you will get error when running "CUDA_VISIBLE_DEVICES="0" python tools/infer.py configs/infer/retinanet/retinanet.py image_path". Please provide the error info.

You mean that you will get error when running "CUDA_VISIBLE_DEVICES="0" python tools/infer.py configs/infer/retinanet/retinanet.py image_path". Please provide the error info.

You mean that you will get error when running "CUDA_VISIBLE_DEVICES="0" python tools/infer.py configs/infer/retinanet/retinanet.py image_path". Please provide the error info.

Some of them are as follows：
The model and loaded state dict do not match exactly
size mismatch for bbox_head.retina_cls.weight: copying a param with shape torch.Size([3, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([9, 256, 3, 3]).
size mismatch for bbox_head.retina_cls.bias: copying a param with shape torch.Size([3]) from checkpoint, the shape in current model is torch.Size([9]).
size mismatch for bbox_head.retina_reg.weight: copying a param with shape torch.Size([12, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([36, 256, 3, 3]).
size mismatch for bbox_head.retina_reg.bias: copying a param with shape torch.Size([12]) from checkpoint, the shape in current model is torch.Size([36]).
unexpected key in source state_dict: backbone.gn1.weight, backbone.gn1.bias, backbone.layer1.0.gn1.weight, backbone.layer1.0.gn1.bias, backbone.layer1.0.gn2.weight, backbone.layer1.0.gn2.bias, backbone.layer1.0.gn3.weight, backbone.layer1.0.gn3.bias, backbone.layer1.1.gn1.weight, backbone.layer1.1.gn1.bias, backbone.layer1.1.gn2.weight, backbone.layer1.1.gn2.bias, backbone.layer1.1.gn3.weight, backbone.layer1.1.gn3.bias, backbone.layer1.2.gn1.weight, backbone.layer1.2.gn1.bias, backbone.layer1.2.gn2.weight, backbone.layer1.2.gn2.bias, backbone.layer1.2.gn3.weight, backbone.layer1.2.gn3.bias, backbone.layer2.0.gn1.weight, backbone.layer2.0.gn1.bias, backbone.layer2.0.gn2.weight, backbone.layer2.0.gn2.bias, backbone.layer2.0.gn3.weight, backbone.layer2.0.gn3.bias, backbone.layer2.1.gn1.weight, backbone.layer2.1.gn1.bias, backbone.layer2.1.gn2.weight, backbone.layer2.1.gn2.bias, backbone.layer2.1.gn3.weight, backbone.layer2.1.gn3.bias, backbone.layer2.2.gn1.weight, backbone.layer2.2.gn1.bias, backbone.layer2.2.gn2.weight, backbone.layer2.2.gn2.bias, backbone.layer2.2.gn3.weight, backbone.layer2.2.gn3.bias, backbone.layer2.3.gn1.weight, backbone.layer2.3.gn1.bias, backbone.layer2.3.gn2.weight, backbone.layer2.3.gn2.bias, backbone.layer2.3.gn3.weight, backbone.layer2.3.gn3.bias, backbone.layer3.0.gn1.weight, backbone.layer3.0.gn1.bias, backbone.layer3.0.gn2.weight, backbone.layer3.0.gn2.bias, backbone.layer3.0.gn3.weight, backbone.layer3.0.gn3.bias, backbone.layer3.0.conv2.conv_offset.weight, backbone.layer3.0.conv2.conv_offset.bias, backbone.layer3.1.gn1.weight, backbone.layer3.1.gn1.bias, backbone.layer3.1.gn2.weight, backbone.layer3.1.gn2.bias, backbone.layer3.1.gn3.weight, backbone.layer3.1.gn3.bias, backbone.layer3.1.conv2.conv_offset.weight, backbone.layer3.1.conv2.conv_offset.bias, backbone.layer3.2.gn1.weight, backbone.layer3.2.gn1.bias, backbone.layer3.2.gn2.weight, backbone.layer3.2.gn2.bias, backbone.layer3.2.gn3.weight, backbone.layer3.2.gn3.bias, backbone.layer3.2.conv2.conv_offset.weight, backbone.layer3.2.conv2.conv_offset.bias, backbone.layer3.3.gn1.weight, backbone.layer3.3.gn1.bias, backbone.layer3.3.gn2.weight, backbone.layer3.3.gn2.bias, backbone.layer3.3.gn3.weight, backbone.layer3.3.gn3.bias, backbone.layer3.3.conv2.conv_offset.weight, backbone.layer3.3.conv2.conv_offset.bias, backbone.layer3.4.gn1.weight, backbone.layer3.4.gn1.bias, backbone.layer3.4.gn2.weight, backbone.layer3.4.gn2.bias, backbone.layer3.4.gn3.weight, backbone.layer3.4.gn3.bias, backbone.layer3.4.conv2.conv_offset.weight, backbone.layer3.4.conv2.conv_offset.bias, backbone.layer3.5.gn1.weight, backbone.layer3.5.gn1.bias, backbone.layer3.5.gn2.weight, backbone.layer3.5.gn2.bias, backbone.layer3.5.gn3.weight, backbone.layer3.5.gn3.bias, backbone.layer3.5.conv2.conv_offset.weight, backbone.layer3.5.conv2.conv_offset.bias, backbone.layer4.0.gn1.weight, backbone.layer4.0.gn1.bias, backbone.layer4.0.gn2.weight, backbone.layer4.0.gn2.bias, backbone.layer4.0.gn3.weight, backbone.layer4.0.gn3.bias, backbone.layer4.0.conv2.conv_offset.weight, backbone.layer4.0.conv2.conv_offset.bias, backbone.layer4.1.gn1.weight, backbone.layer4.1.gn1.bias, backbone.layer4.1.gn2.weight, backbone.layer4.1.gn2.bias, backbone.layer4.1.gn3.weight, backbone.layer4.1.gn3.bias, backbone.layer4.1.conv2.conv_offset.weight, backbone.layer4.1.conv2.conv_offset.bias, backbone.layer4.2.gn1.weight, backbone.layer4.2.gn1.bias, backbone.layer4.2.gn2.weight, backbone.layer4.2.gn2.bias, backbone.layer4.2.gn3.weight, backbone.layer4.2.gn3.bias, backbone.layer4.2.conv2.conv_offset.weight, backbone.layer4.2.conv2.conv_offset.bias, neck.0.lateral_convs.0.conv.weight, neck.0.lateral_convs.0.gn.weight, neck.0.lateral_convs.0.gn.bias, neck.0.lateral_convs.1.conv.weight, neck.0.lateral_convs.1.gn.weight, neck.0.lateral_convs.1.gn.bias, neck.0.lateral_convs.2.conv.weight, neck.0.lateral_convs.2.gn.weight, neck.0.lateral_convs.2.gn.bias, neck.0.lateral_convs.3.conv.weight, neck.0.lateral_convs.3.gn.weight, neck.0.lateral_convs.3.gn.bias, neck.0.fpn_convs.0.conv.weight, neck.0.fpn_convs.0.gn.weight, neck.0.fpn_convs.0.gn.bias, neck.0.fpn_convs.1.conv.weight, neck.0.fpn_convs.1.gn.weight, neck.0.fpn_convs.1.gn.bias, neck.0.fpn_convs.2.conv.weight, neck.0.fpn_convs.2.gn.weight, neck.0.fpn_convs.2.gn.bias, neck.0.fpn_convs.3.conv.weight, neck.0.fpn_convs.3.gn.weight, neck.0.fpn_convs.3.gn.bias, neck.0.fpn_convs.4.conv.weight, neck.0.fpn_convs.4.gn.weight, neck.0.fpn_convs.4.gn.bias, neck.0.fpn_convs.5.conv.weight, neck.0.fpn_convs.5.gn.weight, neck.0.fpn_convs.5.gn.bias, neck.1.level_convs.0.0.conv.weight, neck.1.level_convs.0.0.gn.weight, neck.1.level_convs.0.0.gn.bias, neck.1.level_convs.0.1.conv.weight, neck.1.level_convs.0.1.gn.weight, neck.1.level_convs.0.1.gn.bias, neck.1.level_convs.0.2.conv.weight, neck.1.level_convs.0.2.gn.weight, neck.1.level_convs.0.2.gn.bias, neck.1.level_convs.0.3.conv.weight, neck.1.level_convs.0.3.gn.weight, neck.1.level_convs.0.3.gn.bias, neck.1.level_convs.0.4.conv.weight, neck.1.level_convs.0.4.gn.weight, neck.1.level_convs.0.4.gn.bias, bbox_head.retina_iou.weight, bbox_head.retina_iou.bias, bbox_head.cls_convs.0.gn.weight, bbox_head.cls_convs.0.gn.bias, bbox_head.cls_convs.1.gn.weight, bbox_head.cls_convs.1.gn.bias, bbox_head.cls_convs.2.gn.weight, bbox_head.cls_convs.2.gn.bias, bbox_head.cls_convs.3.gn.weight, bbox_head.cls_convs.3.gn.bias, bbox_head.reg_convs.0.gn.weight, bbox_head.reg_convs.0.gn.bias, bbox_head.reg_convs.1.gn.weight, bbox_head.reg_convs.1.gn.bias, bbox_head.reg_convs.2.gn.weight, bbox_head.reg_convs.2.gn.bias, bbox_head.reg_convs.3.gn.weight, bbox_head.reg_convs.3.gn.bias

You mean that you will get error when running "CUDA_VISIBLE_DEVICES="0" python tools/infer.py configs/infer/retinanet/retinanet.py image_path". Please provide the error info.

Some of them are as follows：
The model and loaded state dict do not match exactly
size mismatch for bbox_head.retina_cls.weight: copying a param with shape torch.Size([3, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([9, 256, 3, 3]).
size mismatch for bbox_head.retina_cls.bias: copying a param with shape torch.Size([3]) from checkpoint, the shape in current model is torch.Size([9]).
size mismatch for bbox_head.retina_reg.weight: copying a param with shape torch.Size([12, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([36, 256, 3, 3]).
size mismatch for bbox_head.retina_reg.bias: copying a param with shape torch.Size([12]) from checkpoint, the shape in current model is torch.Size([36]).
unexpected key in source state_dict: backbone.gn1.weight, backbone.gn1.bias, backbone.layer1.0.gn1.weight, backbone.layer1.0.gn1.bias, backbone.layer1.0.gn2.weight, backbone.layer1.0.gn2.bias, backbone.layer1.0.gn3.weight, backbone.layer1.0.gn3.bias, backbone.layer1.1.gn1.weight, backbone.layer1.1.gn1.bias, backbone.layer1.1.gn2.weight, backbone.layer1.1.gn2.bias, backbone.layer1.1.gn3.weight, backbone.layer1.1.gn3.bias, backbone.layer1.2.gn1.weight, backbone.layer1.2.gn1.bias, backbone.layer1.2.gn2.weight, backbone.layer1.2.gn2.bias, backbone.layer1.2.gn3.weight, backbone.layer1.2.gn3.bias, backbone.layer2.0.gn1.weight, backbone.layer2.0.gn1.bias, backbone.layer2.0.gn2.weight, backbone.layer2.0.gn2.bias, backbone.layer2.0.gn3.weight, backbone.layer2.0.gn3.bias, backbone.layer2.1.gn1.weight, backbone.layer2.1.gn1.bias, backbone.layer2.1.gn2.weight, backbone.layer2.1.gn2.bias, backbone.layer2.1.gn3.weight, backbone.layer2.1.gn3.bias, backbone.layer2.2.gn1.weight, backbone.layer2.2.gn1.bias, backbone.layer2.2.gn2.weight, backbone.layer2.2.gn2.bias, backbone.layer2.2.gn3.weight, backbone.layer2.2.gn3.bias, backbone.layer2.3.gn1.weight, backbone.layer2.3.gn1.bias, backbone.layer2.3.gn2.weight, backbone.layer2.3.gn2.bias, backbone.layer2.3.gn3.weight, backbone.layer2.3.gn3.bias, backbone.layer3.0.gn1.weight, backbone.layer3.0.gn1.bias, backbone.layer3.0.gn2.weight, backbone.layer3.0.gn2.bias, backbone.layer3.0.gn3.weight, backbone.layer3.0.gn3.bias, backbone.layer3.0.conv2.conv_offset.weight, backbone.layer3.0.conv2.conv_offset.bias, backbone.layer3.1.gn1.weight, backbone.layer3.1.gn1.bias, backbone.layer3.1.gn2.weight, backbone.layer3.1.gn2.bias, backbone.layer3.1.gn3.weight, backbone.layer3.1.gn3.bias, backbone.layer3.1.conv2.conv_offset.weight, backbone.layer3.1.conv2.conv_offset.bias, backbone.layer3.2.gn1.weight, backbone.layer3.2.gn1.bias, backbone.layer3.2.gn2.weight, backbone.layer3.2.gn2.bias, backbone.layer3.2.gn3.weight, backbone.layer3.2.gn3.bias, backbone.layer3.2.conv2.conv_offset.weight, backbone.layer3.2.conv2.conv_offset.bias, backbone.layer3.3.gn1.weight, backbone.layer3.3.gn1.bias, backbone.layer3.3.gn2.weight, backbone.layer3.3.gn2.bias, backbone.layer3.3.gn3.weight, backbone.layer3.3.gn3.bias, backbone.layer3.3.conv2.conv_offset.weight, backbone.layer3.3.conv2.conv_offset.bias, backbone.layer3.4.gn1.weight, backbone.layer3.4.gn1.bias, backbone.layer3.4.gn2.weight, backbone.layer3.4.gn2.bias, backbone.layer3.4.gn3.weight, backbone.layer3.4.gn3.bias, backbone.layer3.4.conv2.conv_offset.weight, backbone.layer3.4.conv2.conv_offset.bias, backbone.layer3.5.gn1.weight, backbone.layer3.5.gn1.bias, backbone.layer3.5.gn2.weight, backbone.layer3.5.gn2.bias, backbone.layer3.5.gn3.weight, backbone.layer3.5.gn3.bias, backbone.layer3.5.conv2.conv_offset.weight, backbone.layer3.5.conv2.conv_offset.bias, backbone.layer4.0.gn1.weight, backbone.layer4.0.gn1.bias, backbone.layer4.0.gn2.weight, backbone.layer4.0.gn2.bias, backbone.layer4.0.gn3.weight, backbone.layer4.0.gn3.bias, backbone.layer4.0.conv2.conv_offset.weight, backbone.layer4.0.conv2.conv_offset.bias, backbone.layer4.1.gn1.weight, backbone.layer4.1.gn1.bias, backbone.layer4.1.gn2.weight, backbone.layer4.1.gn2.bias, backbone.layer4.1.gn3.weight, backbone.layer4.1.gn3.bias, backbone.layer4.1.conv2.conv_offset.weight, backbone.layer4.1.conv2.conv_offset.bias, backbone.layer4.2.gn1.weight, backbone.layer4.2.gn1.bias, backbone.layer4.2.gn2.weight, backbone.layer4.2.gn2.bias, backbone.layer4.2.gn3.weight, backbone.layer4.2.gn3.bias, backbone.layer4.2.conv2.conv_offset.weight, backbone.layer4.2.conv2.conv_offset.bias, neck.0.lateral_convs.0.conv.weight, neck.0.lateral_convs.0.gn.weight, neck.0.lateral_convs.0.gn.bias, neck.0.lateral_convs.1.conv.weight, neck.0.lateral_convs.1.gn.weight, neck.0.lateral_convs.1.gn.bias, neck.0.lateral_convs.2.conv.weight, neck.0.lateral_convs.2.gn.weight, neck.0.lateral_convs.2.gn.bias, neck.0.lateral_convs.3.conv.weight, neck.0.lateral_convs.3.gn.weight, neck.0.lateral_convs.3.gn.bias, neck.0.fpn_convs.0.conv.weight, neck.0.fpn_convs.0.gn.weight, neck.0.fpn_convs.0.gn.bias, neck.0.fpn_convs.1.conv.weight, neck.0.fpn_convs.1.gn.weight, neck.0.fpn_convs.1.gn.bias, neck.0.fpn_convs.2.conv.weight, neck.0.fpn_convs.2.gn.weight, neck.0.fpn_convs.2.gn.bias, neck.0.fpn_convs.3.conv.weight, neck.0.fpn_convs.3.gn.weight, neck.0.fpn_convs.3.gn.bias, neck.0.fpn_convs.4.conv.weight, neck.0.fpn_convs.4.gn.weight, neck.0.fpn_convs.4.gn.bias, neck.0.fpn_convs.5.conv.weight, neck.0.fpn_convs.5.gn.weight, neck.0.fpn_convs.5.gn.bias, neck.1.level_convs.0.0.conv.weight, neck.1.level_convs.0.0.gn.weight, neck.1.level_convs.0.0.gn.bias, neck.1.level_convs.0.1.conv.weight, neck.1.level_convs.0.1.gn.weight, neck.1.level_convs.0.1.gn.bias, neck.1.level_convs.0.2.conv.weight, neck.1.level_convs.0.2.gn.weight, neck.1.level_convs.0.2.gn.bias, neck.1.level_convs.0.3.conv.weight, neck.1.level_convs.0.3.gn.weight, neck.1.level_convs.0.3.gn.bias, neck.1.level_convs.0.4.conv.weight, neck.1.level_convs.0.4.gn.weight, neck.1.level_convs.0.4.gn.bias, bbox_head.retina_iou.weight, bbox_head.retina_iou.bias, bbox_head.cls_convs.0.gn.weight, bbox_head.cls_convs.0.gn.bias, bbox_head.cls_convs.1.gn.weight, bbox_head.cls_convs.1.gn.bias, bbox_head.cls_convs.2.gn.weight, bbox_head.cls_convs.2.gn.bias, bbox_head.cls_convs.3.gn.weight, bbox_head.cls_convs.3.gn.bias, bbox_head.reg_convs.0.gn.weight, bbox_head.reg_convs.0.gn.bias, bbox_head.reg_convs.1.gn.weight, bbox_head.reg_convs.1.gn.bias, bbox_head.reg_convs.2.gn.weight, bbox_head.reg_convs.2.gn.bias, bbox_head.reg_convs.3.gn.weight, bbox_head.reg_convs.3.gn.bias

Trained TinaFace model can not be loaded into RetinaNet, cause they are different models. If you want to use some models to infer, you should first train a corresponding model.

Trained TinaFace model can not be loaded into RetinaNet, cause they are different models. If you want to use some models to infer, you should first train a corresponding model.

Trained TinaFace model can not be loaded into RetinaNet, cause they are different models. If you want to use some models to infer, you should first train a corresponding model.

ok , i get it, Is there any solution to the false face detection？

Trained TinaFace model can not be loaded into RetinaNet, cause they are different models. If you want to use some models to infer, you should first train a corresponding model.

ok , i get it, Is there any solution to the false face detection？


Request to create semconv-cloud-native-approvers

I'd like to request creating a new approvers group semconv-cloud-native-approvers that would be responsible for reviewing and maintaining semantic conventions related to the cloud-native domain (e.g. containers, kubernetes).
Folks proposed for that group / interested:

@frzifus
@dmitryax
@ChrsMark
@mx-psi
@TylerHelmuth
@jinja2
TBA

Related PRs and issues:

https://github.com/open-telemetry/semantic-conventions/pull/159
https://github.com/open-telemetry/semantic-conventions/pull/282
https://github.com/open-telemetry/semantic-conventions/pull/125
https://github.com/open-telemetry/semantic-conventions/issues/48
https://github.com/open-telemetry/semantic-conventions/issues/58

@dmitryax could you also ping people from the Collector's side that would be interested to join?
@mlunadia would you be interested into joining as well?

I am interested in joining.  I would also like to nominate @jinja2 who has been a tremendous source of Kubernetes knowledge for the Collector components.

Awesome @TylerHelmuth , I have added you both :)!

Thank you, @ChrsMark!

Additional releated issue: https://github.com/open-telemetry/semantic-conventions/issues/430

I think this is a little to broad of a scope.  E.g. are you going to be owning every semconv for technology coming from CNCF, including otel itself?
Let's alter the name to denote some limits, e.g.

semconv-container-approvers: All things container related (not just docker)
semconv-k8s-approvers: All things kubernetes related (but not nomad, e.g.)

I think it makes sense for us to keep the two lists separate even if it's the same set of folks initially.

Thank's @jsuereth , that makes sense! I can split the group into 2 different groups then.

I'd like to nominate myself for the k8s-approvers group.

@ChrsMark yes, please add me in

I created @open-telemetry/semconv-container-approvers and added the following members:
@frzifus
@dmitryax
@ChrsMark
@mx-psi
@TylerHelmuth
@jinja2
@mlunadia I was not able to add you as you are not a member of the OpenTelemetry organization yet.
Please review the requirements and application steps described here: https://github.com/open-telemetry/community/blob/main/community-membership.md#member

I created @open-telemetry/semconv-k8s-approvers and added the following members:

@frzifus
@dmitryax
@ChrsMark
@mx-psi
@TylerHelmuth
@jinja2
@dashpole

@mlunadia please see my comment above.

@open-telemetry/semconv-container-approvers and @open-telemetry/semconv-k8s-approvers you can go ahead and update https://github.com/open-telemetry/semantic-conventions/blob/main/.github/CODEOWNERS to add OWNERS for the relevant subdirectories.

Thank's @arminru. I have filed https://github.com/open-telemetry/semantic-conventions/pull/510 to add the CODEOWNERS.

@arminru I have now my membership and have requested to join. Thanks!

@arminru just checking if you can add me to the approvers for both of these groups.
TIA

Hi @mlunadia!
After the initial bootstrapping of a newly founded group, approvers are expected to satisfy the approver requirements laid out here: https://github.com/open-telemetry/community/blob/main/community-membership.md#approver
Please open an issue if all of these apply so we can add you to the group.
Thanks!


ansible osdsdb container installation fails because of missing docker-py

Describe the bug
ansible-playbook failes at the osdsdb installation step when 'etcd_container_enabled' is true.
This is because 'ansible/roles/osdsdb/scenarios/container.yml' does not have 'pip install docker-py' task.
To Reproduce
Steps to reproduce the behavior:

Follow the ansible based installation doc. https://github.com/opensds/opensds/wiki/OpenSDS-Cluster-Installation-through-Ansible
set 'etcd_container_enabled: true' in ansible/group_vars/osdsdb.yml
Run ansible-playbook

Expected behavior
No failure when 'etcd_container_enabled' is true
Screenshots
ubuntu@ubuntu203:~/opensds-installer/ansible$ ansible-playbook -i local.hosts site.yml

(snip)

TASK [osdsdb : run etcd containerized service] *********************************
fatal: [localhost]: FAILED! => {"changed": false, "failed": true, "msg": "Failed
 to import docker-py - No module named docker. Try `pip install docker-py`"}
        to retry, use: --limit @/home/ubuntu/opensds-installer/ansible/site.retry

PLAY RECAP *********************************************************************
localhost                  : ok=22   changed=12   unreachable=0    failed=1

ubuntu@ubuntu203:~/opensds-installer/ansible$

Desktop (please complete the following information):

OS: Ubuntu 16.04.6 LTS (canonical cloud image)

Additional context
This behavior is the same for master and development branches.

This is a kind of trivial bug, and I have a fix. Please feel free assigning this to me.

As the fix was already merged, I'm closing this issue.


filter2 API performance regression

The new filter API seems to be much slower (or perhaps I'm using it wrong :)
Code using an UnboundRecordFilter:
ColumnRecordFilter.column(column,
    ColumnPredicates.applyFunctionToBinary(
    input -> Binary.fromString(value).equals(input)));

vs. code using FilterPredicate:
eq(binaryColumn(column), Binary.fromString(value));

The latter performs twice as slow on the same Parquet file (built using 1.6.0rc2).
Note: the reader is constructed using
ParquetReader.builder(new ProtoReadSupport().withFilter(filter).build()

The new filter API based approach seems to create a whole lot more garbage (perhaps due to reconstructing all the rows?).
Reporter: Viktor Szathmáry / @phraktle
Related issues:

FilteredRecordReader skips rows it shouldn't for schema with optional columns (is related to)

Note: This issue was originally created as PARQUET-98. Please see the migration documentation for further details.

Viktor Szathmáry / @phraktle:
Any thoughts on this? No change with 1.6.0rc3.

Viktor Szathmáry / @phraktle:
My initial impression based on a quick profiling run is that it was creating a whole lot more garbage, seemingly instantiating all the protobufs (or just reading all columns of every row?), rather than just the ones matching the expression.

Ryan Blue / @rdblue:
Could you try out the problem data with VisualVM or another profiling tool to see if there's anything funny going on? It doesn't look like your code is the problem. If anything, I would have guessed the first version runs more slowly because it converts a String to Binary each time it runs.

Viktor Szathmáry / @phraktle:
anyone out there? :)

Ryan Blue / @rdblue:
PARQUET-128 does look like it might be related. Sorry I haven't had time to track this down lately. Maybe @isnotinvain can take a look.

Viktor Szathmáry / @phraktle:
While I'm not familiar with the internals of the implementation, the main difference seems to be that with filter2, all columns are deserialized for all rows. Wheres the classic approach, only the selector column is involved.

Viktor Szathmáry / @phraktle:
possibly related to https://issues.apache.org/jira/browse/PARQUET-128 ?

Alex Levenson / @isnotinvain:
I don't think anything has changed yet that would effect this, so no surprises there.
I've not had a chance to look into the performance difference yet, from your testing is there anything specific you suspect is causing the issue? Or still more investigation needed?
Thanks,
Alex

Ryan Blue / @rdblue:

for parquet to skip a value, it essentially has to deserialize it

Maybe the problem is a defensive copy? Converting a byte array to a String would do it, too, which probably happens when the value is set in the object model.

Viktor Szathmáry / @phraktle:
Tested with 1.6.0rc6, the problem still exists: filter2 API is more than 2x slower...

Alex Levenson / @isnotinvain:
Yes, I think that is the main difference. However, I'm a bit surprised it has much performance impact – for parquet to skip a value, it essentially has to deserialize it, so even when we aren't reading some values, we do have to skip them.

Alex Levenson / @isnotinvain:
I will try to take a look but it might take be a while before I get a chance.
The filter2 API still skips assembly for records that are filtered out (eg does not instantiate a protobuf), and it only visits the columns you have asked for via the column projection API. But it doesn't look at the columns in the filter and project to only those columns, (neither does the unbound record filter approach I think) and it also still visits every one of the columns that you want in the final output record (it does not short circuit – the unbound record filter might short circuit here, but the importance of that depends on the order columns are visited in).

Viktor Szathmáry / @phraktle:
Not sure how the "classic" filter implementation gets by, but it seems to be doing a much better job (2-3x faster).

Viktor Szathmáry / @phraktle:
Tested with 1.6.0 release, still has this issue.

Ryan Blue / @rdblue:
@phraktle, to save you some time, the 1.7.0 release will also have this problem. I'll find some time to look into it further.

Alex Levenson / @isnotinvain:
@phraktle well that's my point, even though you don't need to read A and B, you've got to skip their current values so you can move on to the next record. That often involves essentially reading the value (think delta encoding for example). But as @rdblue said, we might be doing more work than needed to do the skip. Definitely worth investigating, and definitely room for improvement.

Viktor Szathmáry / @phraktle:
Not knowing much about the implementation, this is just conjecture – but based on the performance results and the extra amount of garbage during profiling, it seems to also read columns that are not needed for the query (e.g. if you have column A, B, C and you try to find rows where C='x', there's no need to read A and B – just when you have a match on C).
But in any case, this slowness is easy to reproduce based on the example I have provided above, I'm sure someone familiar with the internals can figure this out without my guesses ;)


Get basic blocks of a given function (Python scripting)

Is it possible to get a given function's BB's without having to iterate over the entire program using BasicBlockModel or similar objects?

Try this:
CodeBlockModel blockModel = new BasicBlockModel(controller.getProgram());
AddressSetView addresses = function.getBody();
CodeBlockIterator iterator = blockModel.getCodeBlocksContaining(addresses, monitor);


Error while reading precomp directory contents

Thank you for your work on racoco! I've been waiting for a tool like this one for a while now. :dagger:
I tried recently to run it as part of my CI setup, but I ran into a strange error that I cannot actually reproduce locally. You can see the error in question on the logs for that job here: https://gitlab.com/jjatria/raku-game-entities/-/jobs/1735233677, but the relevant part is
$ racoco --exec='prove6 -Ilib' --html --fix-compunit
Failed to get the directory contents of '/builds/jjatria/raku-game-entities/lib/.precomp': Failed to open dir: No such file or directory
  in sub MAIN at /usr/share/perl6/site/sources/44A4D1B35D8BDF9C08695E7730B9BD23D1D0C3D6 (App::Racoco::Cli) line 122
  in block <unit> at /usr/share/perl6/site/resources/1737D3959927C9BF0C4E4A1C2EA9DB935C657379 line 2
  in sub MAIN at /usr/share/perl6/site/bin/racoco line 3
  in block <unit> at /usr/share/perl6/site/bin/racoco line 1

Any idea what might be the reason?

@jjatria Thank you for the report. Yes, I've faced such behavior. It happens when we run racoco on a library without .precomp directory at all. I've fixed it in v.1.4.5 (released a minute ago). Please try it now.


[jvm-packages] Replace JNI with Java Native Access

Problem
Currently, XGBoost4J uses Java Native Interface (JNI) to call the native code in libxgboost4j.so. JNI has served our needs so far, but its use causes a tight coupling with the particular JDK that XGBoost4J was built with.
For example, when building XGBoost4J on Mac mini M1, I used Azul JDK 8 (*):
$ export JAVA_HOME=/Library/Java/JavaVirtualMachines/zulu-8.jdk/Contents/Home/
$ mkdir build
$ cd build
$ cmake .. -GNinja -DJVM_BINDINGS=ON -DUSE_OPENMP=OFF

This leads to a binary that has a hard dependency on libjvm.dylib:
$ otool -L libxgboost4j.dylib

libxgboost4j.dylib:
        @rpath/libxgboost4j.dylib (compatibility version 0.0.0, current version 0.0.0)
        @rpath/libjvm.dylib (compatibility version 1.0.0, current version 1.0.0)
        /usr/lib/libc++.1.dylib (compatibility version 1.0.0, current version 1500.65.0)
        /usr/lib/libSystem.B.dylib (compatibility version 1.0.0, current version 1319.100.3)

As a result, when I try to load the binary on another MacOS machine without Azul JDK 8, the import fails with an error:
$ java -version   # This machine has OpenJDK 21
openjdk version "21" 2023-09-19
OpenJDK Runtime Environment Homebrew (build 21)
$ python -c "import ctypes; ctypes.cdll.LoadLibrary('./libxgboost4j.dylib')"
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "/Users/phcho/mambaforge/lib/python3.10/ctypes/__init__.py", line 452, in LoadLibrary
    return self._dlltype(name)
  File "/Users/phcho/mambaforge/lib/python3.10/ctypes/__init__.py", line 374, in __init__
    self._handle = _dlopen(self._name, mode)
OSError: dlopen(./libxgboost4j.dylib, 0x0006): Library not loaded: @rpath/libjvm.dylib
Reason: tried: '/Library/Java/JavaVirtualMachines/zulu-8.jdk/Contents/Home/jre/lib/server/libjvm.dylib' (no such file)  ...

The error message suggests a tight coupling of XGBoost4J with a particular JDK. The coupling makes it difficult for us to distribute pre-built binaries targeting the MacOS Apple Silicon platform. Users may have installed Azul JDK 8 (whose support is due to end in 2026), OpenJDK 11, or OpenJDK 21 (the latest version).
Proposal. Replace JNI with Java Native Access (JNA). JNA works like ctypes in Python, so we would be able to call functions directly from libxgboost.so. JNA is used by many java software such as IntelliJ IDEA, and it is tested with multiple versions of JDK and platforms. The removal of JNI stub code will also reduce the boilerplate in the code base.
Alternatives. We can tell users to install a particular JDK as we have done so far. So for example, users of MacOS Apple Silicon will be asked to install Azul JDK 8.
@trivialfis  @wbo4958 @WeichenXu123 @Craigacp @drnguyen @terrytangyuan Your feedback will be highly appreciated.
(*) OpenJDK 8 supports Intel only and is not available for Apple Silicon.

I think that error is something we could fix by changing how it's compiled. There are plenty of other native libraries which don't have that issue (e.g. ONNX Runtime's Java API), so it's definitely fixable.
From the benchmarks I've seen (e.g. https://github.com/zakgof/java-native-benchmark) JNA is substantially slower than JNI as it's more dynamic. Java 22 introduces a new FFI which is comparable in speed to JNI and much easier to use, that's going to be the future of these things so moving an existing JNI binding to something else that isn't the new FFI seems suboptimal.

@Craigacp I am currently trying to set up a CI/CD pipeline for M1-native XGBoost4J binaries. Can you give me any points for building native libs without such tight coupling with a particular JDK?

Java 22 introduces a new FFI which is comparable in speed to JNI and much easier to use

That's great to hear!

Interesting, there is no need for linking libjvm.so or libawt.dylib, according to https://github.com/microsoft/onnxruntime/pull/2873

If other projects can use JNI without issues, we should stick with it.

@Craigacp Just filed https://github.com/dmlc/xgboost/pull/9698 to remove the dependency on libjvm.

It's been fine in ONNX Runtime for years so I would expect it to cause trouble here unless there's something very odd in how xgboost4j works it'll be good. As you can see from the other issue cmake and jni have a rather complicated interaction at times and it can be pretty system specific.

@Craigacp Thanks to your input, we were able to release XGBoost 2.0.1 with native support for Apple Silicon. Thank you!

@hcho3 Happy to help. I hit the same issue with it tightly linking to the JDK a few weeks ago when onboarding someone new with an Apple Silicon laptop, but I didn't have time to run it down. I'm glad you got it all working, the new release will be very helpful.


Use microbadger bage for displaying image size.

ImageLayers.io is not working anymore. So use microbadger instead.

I know about microbadger and I would love to use it, but their badge seems to be useless at the moment: https://github.com/microscaling/microbadger/issues/1


Private repositories

Does Stryker support private repositories? I can't seem to grant access to those when using the app?

We do not, since there is no authentication on the reports itself. We would not want users to accidentally reveal their source code without realising.


Create contact-us.php

wait. i will try to fix issues #386

Done, Maybe its correct for fix issues no 386

@ykris45 did you try running this locally? You'd need to clone the repo, make your changes and then run the website locally. You can do this on Linux or possible Bash for Windows (See instructions on how to install).

@ykris45 going to close this until you can get a local test environment running to see your changes.


Add async test

Simple test to check if async functionality is working or not.
We are not running the test since it is currently failing.
@nordlander please have a look if you agree that this test actually tests async, like should these method calls be async or not?
Part of #361

Spoke to @nordlander on the phone about this, who agrees this should work. I'll merge.


eat quotation marks?

My vimrc is here: https://github.com/Martinits/dotfiles/blob/master/.vim/vimrc
When I edit some json files, the quotation marks disappear (just on the screen, not in the file).
Then the quotation marks come back when I comment out this plugin in vimrc.
I'm not sure whether it's this plugin's fault, but commenting out other plugins have no such effect.

let g:vim_json_conceal=0

Oh thanks a lot.
Need to learn more about vim.


Update webapp.flow example to fix syntax errors

Hi,
I noticed this when I was trying out the README example.  Without the proposed change, the command to convert this flow document to dfd fails:
$ dataflow dfd webapp.flow
"webapp.flow" (line 7, column 12):
unexpected "{"
expecting space, "->", "--" or "<-"

Thanks for the great tool!

Thank you very much for the pull request! I'm glad you like DataFlow. :smiley:


Fix/validation Custom Header causes problem with Cloudflare

Pull Request
Is you/your team sponsoring this project

[ ] Yes
[ x ] No

If your team sponsoring this project, please attach here your team lead or who purchased license GitHub login
What you changed

[ x ] Code changes
[ ] Tests changed
[ ] Typo fixes

If you change code, tests should be passed
Note

Your every change to feature/code should be documented
📝 Documentation fixes should be filled here
🔗 Middlewares fixes should be filled here

As no response within such of period of time


Add build package.json to blacklist

@tbergq Closes #297?

Yes, closes #297, it is getting too late for me 😖


Ignores fail when used in a subdirectory

First of all, thanks for all your hard work on this! I really appreciate it.
I'm having a problem where gulp-xo seems to fail when dealing with ignores that have a subfolder.
Example:
//Doesn't work.
"ignores": [
  "src/vendor/**"
]
//Works.
"ignores": [
  "vendor/**"
]

The regular xo tool works fine, ignoring the files and continuing on.
On the other hand, the gulp-xo tool will still check these files.
Those pictures were both taken, one after the other, in the same development enviroment.
Gulpfile:
const gulp = require('gulp');
const xo = require('gulp-xo');

gulp.task('xo', function () {
    return gulp.src('src/**/*.js')
    .pipe(xo())
    .pipe(gulp.dest('.tmp'));
});

package.json:
"xo": {
    "envs": [
      "browser"
    ],
    "globals": [
      "angular",
      "_"
    ],
    "ignores": [
      "gulp_tasks/**",
      "conf/**",
      "src/vendor/**"
    ]
  }

I'm sorry if I missed something obvious about gulp-xo and the difference from xo.
Thanks for your work on this project and other projects.

return gulp.src('src/**/*.js', {
    base: process.cwd(),
})
  .pipe(xo())
  .pipe(gulp.dest('.tmp'));

you can have a try.


Can't download big files by using quiche integrated with curl

I have file-server (caddy) running on localhost using http/3 protocol serving one file of 2319MiB.
When I try to download that file using curl with http3 support, the download stops at 129MiB (see attached screenshot).
Same file can be downloaded successfully by using http/2 protocol or by using web browser (Firefox in my case).
Can anyone give me insights what exactly is happening here and how to resolve this issue.

Might be related to https://github.com/cloudflare/quiche/issues/1115

@LPardue thanks, will do tomorrow. #1115 could be, I think with debug logging I saw quiche dropping invalid packets at around the stall time.

Update on this: the fix of #1115 fixed this problem.
Now, could you make a v0.17 version jump and tag? Then I will update the curl configure to check for that. Thanks!

We're at v0.18 now, and in the meantime curl has continued other :bug:  squashing. @icing I think we can close this one?

@LPardue yes, thanks for fixing this.


Using firebase-php without a composer

Hi,
I have really old native PHP website, and I'm trying to use the firebase-php library without a composer.
I tried to include it directly:
error_reporting(-1);
	require 'includes/firebase/Firebase.php';
use Kreait\Firebase\Factory;
use Kreait\Firebase\ServiceAccount;
$serviceAccount = ServiceAccount::fromJsonFile('realtime-chat-efadc-firebase-adminsdk.json');

but adding the $serviceAccount line throws error 500.
Any ideas?

Hey @theunreal! I would suggest registering an autoloader for this, see http://php.net/manual/en/function.spl-autoload-register.php
You can find an adaptable implementation example here: http://www.php-fig.org/psr/psr-4/examples/
As PHP class autoloading is not in the scope of this library, I'm closing this issue, but feel free to add further comments if you habe additional questions.


Selection of a specific BERT pretrained model

Hi Amaiya,
it's a great project! Congrats!
However, I'd like to specify which specific BERT pretrained model to use.
For example, I'd like to try the last Multilingual Cased, but I don't see in the documentation how to do that.
I guess It might be an option in this call:
txt.text_classifier('bert', (x_train, y_train))
Thank you in advance.
Cheers,
Emanuele

Hello:  Several people have requested this.  This can be added to future release, and I agree that it should be an option in text_classifier.
If I push an experimental branch to GitHub with this feature, would you be willing to install and test it with your language of interest?

Yes, with pleasure. :)
thanks

I am using ktrain in portuguese. But I`m facing some issues like in the load_predictor asking for some gelu tensorflow but I don't find anything about that on google.

@Krids The issue with load_predictor complaining about gelu_tensorflow was fixed a while ago.  This should work with the latest version of ktrain, so please upgrade to the latest version.  If you still have trouble, then please open a new issue with more details including code.  On a side note, the next version of ktrain (to be released soon) provides better support for non-English languages for all text classification models including BERT.

@emanueledirosa
ktrain v0.4.0, which was just released, attempts to provide support for multilingual text classification for all models including BERT.  In the case of BERT, if a non-English language is detected, then the multilingual-cased BERT model will be downloaded (instead of the English-only model).    See this example notebook for an example of building a sentiment analysis model for Chinese:
ChineseHotelReviews-BERT.ipynb
As you'll see in the notebook, an attempt has been made to make this completely automated.   ktrain will attempt to detect the language and character encoding and prepare the data and configure the model appropriately.  However, it was only tested on a single non-English corpus (i.e., the Chinese corpus above).
If you find a problem/bug when testing this on your language of interest, please open an issue about it with details. Thanks.

@emanueledirosa
There was a bug in 0.4.0 with multilingual BERT.  Please be sure to use ktrain v0.4.1+ if using BERT on non-English corpus.


fix #227 : replace deprecated gallery by recycler view

Fix #227
Please make sure these boxes are checked before submitting your pull request - thanks!

[x] Run the unit tests with gradlew app:connectedGmsDebugAndroidTest to make sure you didn't break anything (with an emulator running or phone connected)

[x] If you have multiple commits please combine them into one commit by squashing them.

Replaces deprecated Gallery by RecyclerVIew .

Improved performance
Better UI
Less empty screen

@jaydeetay I think this would be another good addition for the project. Gallery was deprecated in API 16 and is no longer supported.
@shiv07tiwari Would you be able to rebase this on the latest commit?


[Q] /Ac/Energy/Forward total or session?

Does the value refer to the total charging energy or to the current charging session?

Total

thxs for your quick answer.. but I find a litte mistake.
/Ac/Energy/Forward         --> Write: Charged Energy (Wh)
The value must be set in kWh, not in Wh

Thanks, I corrected it.

PR with some more minors #3


OCM-13193 | fix: Filter DNS domains when create/cluster if hosted CP

When making a hosted control plane cluster, filter DNS domains in interactive mode and return only hostedCP dns domains (using the new ClusterArch field)

/lgtm


Implement specified version selfupdate subcommand feature

I added the functionality that updates specified Embulk version into selfupdate subcommand.
Related to #270.

Good! merged.

Thanks! Can I close this PR?

I close this PR because already merged into master.


spirv-reduce: Invalidate DefUse analysis

Fixes #4252.
Also, I've noticed that if you add CheckValid to unit tests to all the places it's missing from (e.g. when the initial binary is constructed, after every TryToApply etc), a bunch of tests fail. I also have doubts about whether CheckValid ensures that the module is well-formed (i.e. all analyses are correct) - maybe fuzzerutil::IsValidAndWellFormed can help with that?
Either way, I think refactoring tests (if at all) is better left for a separate PR.

@afd ping.

@Vasniktel Thanks for this! I think it would be good to improve the tests (or the reducer code, if needed) so that everything is valid and well-formed. Let me open an issue for that so we can discuss it.


Where should we take ClusterTasks next?

Feature request
We've discussed the possible future of ClusterTasks in our API Working Group but haven't created an issue for it yet as far as I can see. The intention for this issue is to act as the focal point for discussion around the feature, its future, and where we see it going within the context of Tekton Pipelines' other features.
Background
ClusterTask is a CRD that Tekton Pipelines provides that is the cluster-scoped equivalent of a Task. It shares all of the same fields as a Task but can be referenced regardless of the namespace that a TaskRun is executing in. By contrast a Task can only be referred to by a TaskRun in the same namespace.
While ClusterTask has been part of the codebase for a long time it's unclear precisely how much use it actually sees in practice. In our own dogfooding of Tekton Pipelines we don't currently leverage the resource but it does get exercised by unit and integration testing.
There have been some requests for a cluster-scoped Pipeline (https://github.com/tektoncd/pipeline/issues/1876, https://github.com/tektoncd/pipeline/issues/4432) and as part of those discussions there have definitely been a number of messages in support of ClusterTasks too. At the same time Tekton has introduced support for Bundles (an OCI image with Tasks and Pipelines, stored in a registry) that seems to provide a lot of the same benefit as cluster-scoped Task / Pipeline resources (accessible regardless of the namespace that a TaskRun or PipelineRun is executing in). More recently we've also been making moves to expand the number of places that Tekton Pipelines can access Tasks and Pipelines from, such as git repositories.
Next Steps

[ ] Solicit feedback from the community on usage of ClusterTask
[ ] Present the results from this feedback to the API WG
[ ] Assess overlap of ClusterTasks with other features Tekton Pipelines is pursuing
[ ] ... figure out the next next steps ...

One quick note there, OpenShift Pipelines ships with several ClusterTask by default, so any user of OpenShift Pipelines might be using them — and we know some of them use it a lot. That said, one of our goal is to migrate from ClusterTask to oci bundle once those are considered stable.

Using Remote Resolution it's possible to emulate ClusterTasks and ClusterPipelines. Here's a resolver that does exactly this: https://github.com/sbwsg/clusterresolver
This works by keeping all the "Cluster-Scoped" Tasks and Pipelines in one private namespace.  The Resolver has exclusive access to those resources and returns them to anyone who asks from any namespace.  So an operator/admin can add or remove "ClusterTask" and "ClusterPipeline" by applying or deleteing the Tasks and Pipelines from that private namespace.

we still need to figure this out
/remove-lifecycle stale

/lifecycle frozen
I'd like to propose deprecating ClusterTasks, now that remote resolution (+ the cluster resolver) will be moving into Pipelines. @abayer WDYT?

@abayer have clusterTasks been officially deprecated? I'm happy to open a PR deprecating them now that the cluster resolver is in pipelines

Not officially, I don't believe, so yeah, that'd be great!


[#2063][Hotfix] Spatial reference - string wrap fix

Fix for text overflow in Spatial Reference table of File Metadata

+1. Merge after Jenkins checks are successful.