example not working from source

Hi,
I tried to run the example from source and I got a lot of errors when running it localy:
➜  example git:(master) yarn
[yan install logs]

➜  example git:(master) yarn start
yarn run v1.22.15
$ react-scripts start
(node:42454) [DEP_WEBPACK_DEV_SERVER_ON_AFTER_SETUP_MIDDLEWARE] DeprecationWarning: 'onAfterSetupMiddleware' option is deprecated. Please use the 'setupMiddlewares' option.
(Use `node --trace-deprecation ...` to show where the warning was created)
(node:42454) [DEP_WEBPACK_DEV_SERVER_ON_BEFORE_SETUP_MIDDLEWARE] DeprecationWarning: 'onBeforeSetupMiddleware' option is deprecated. Please use the 'setupMiddlewares' option.
Starting the development server...
Failed to compile.

Module not found: Error: Can't resolve<EMAIL_ADDRESS>in '/Users/valentin/Mee6/Projects/livekit-react/example/src'
ERROR in ./src/App.tsx 6:0-50
Module not found: Error: Can't resolve<EMAIL_ADDRESS>in '/Users/valentin/Mee6/Projects/livekit-react/example/src'

ERROR in ./src/PreJoinPage.tsx 13:0-96
Module not found: Error: Can't resolve '@livekit/react-components' in '/Users/valentin/Mee6/Projects/livekit-react/example/src'

ERROR in ./src/PreJoinPage.tsx 14:0-52
Module not found: Error: Can't resolve '@livekit/react-core' in '/Users/valentin/Mee6/Projects/livekit-react/example/src'

ERROR in ./src/RoomPage.tsx 15:0-72
Module not found: Error: Can't resolve '@livekit/react-components' in '/Users/valentin/Mee6/Projects/livekit-react/example/src'

webpack compiled with 4 errors
Files successfully emitted, waiting for typecheck results...
Issues checking in progress...
ERROR in src/PreJoinPage.tsx:3:69
TS2307: Cannot find module '@livekit/react-components' or its corresponding type declarations.
    1 | import { faBolt } from '@fortawesome/free-solid-svg-icons';
    2 | import { createLocalVideoTrack, LocalVideoTrack } from 'livekit-client';
  > 3 | import { AudioSelectButton, ControlButton, VideoSelectButton } from '@livekit/react-components';
      |                                                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^
    4 | import { VideoRenderer } from '@livekit/react-core';
    5 | import { ReactElement, useEffect, useState } from 'react';
    6 | import { AspectRatio } from 'react-aspect-ratio';

ERROR in src/PreJoinPage.tsx:4:31
TS2307: Cannot find module '@livekit/react-core' or its corresponding type declarations.
    2 | import { createLocalVideoTrack, LocalVideoTrack } from 'livekit-client';
    3 | import { AudioSelectButton, ControlButton, VideoSelectButton } from '@livekit/react-components';
  > 4 | import { VideoRenderer } from '@livekit/react-core';
      |                               ^^^^^^^^^^^^^^^^^^^^^
    5 | import { ReactElement, useEffect, useState } from 'react';
    6 | import { AspectRatio } from 'react-aspect-ratio';
    7 | import { useNavigate } from 'react-router-dom';

ERROR in src/RoomPage.tsx:4:61
TS2307: Cannot find module '@livekit/react-components' or its corresponding type declarations.
    2 | import { FontAwesomeIcon } from '@fortawesome/react-fontawesome';
    3 | import { Room, RoomEvent, setLogLevel, VideoPresets } from 'livekit-client';
  > 4 | import { DisplayContext, DisplayOptions, LiveKitRoom } from '@livekit/react-components';
      |                                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^
    5 | import { useState } from 'react';
    6 | import 'react-aspect-ratio/aspect-ratio.css';
    7 | import { useNavigate, useLocation } from 'react-router-dom';

ERROR in src/RoomPage.tsx:92:25
TS7006: Parameter 'room' implicitly has an 'any' type.
    90 |           url={url}
    91 |           token={token}
  > 92 |           onConnected={(room) => {
       |                         ^^^^
    93 |             setLogLevel('debug');
    94 |             onConnected(room, query);
    95 |             room.on(RoomEvent.ParticipantConnected, () => updateParticipantSize(room));

can you try running it from the repo root folder, instead of the example folder?
just run yarn start there.

It does pretty much te same thing but with lot of other logs.
In facts, it apears examble have been updated with new packages names, but all @livekit/* packages are missing from dependencies. Which probably explain why it doesn't work ?

did you runn 'yarn install' in the root folder as well?
I'm surprised it doesn't work for you as 'yarn start' on the root level works for me just fine. which OS are you using?

Yes, I ran it.
I'm using macOS.
I found out that it is missing @livekit/core dependency. After adding it, the app is startable, but we have lots of TypeScript errors because it doesn't seems to find type definitions for @livekit/components.
Try to create a fresh git clone, you probably be able to reproduce this. I think you probably have some local setup that makes it work for you, like a yarn link or something.

Yeah, the problem seems to be that the build step was not required to run before the start command for @livekit/react-core, this PR should address this: https://github.com/livekit/livekit-react/pull/63
Does that fix the problem for you?


Provide Placeholder for Profile page during loading

Description
It would be better to have a placeholder for the images and text button , rather than a progress bar for loading the profile page content
Screenshots
No response
Additional information
No response

I like to work on this

imho Skeletons would be better...

this issue has been resolved by fbac8f7


Search broken in combination with Memex extension

With https://addons.mozilla.org/en-US/firefox/addon/worldbrain/ enabled the search does not work, keypress in search, and starting the search errors with:
 Uncaught TypeError: can't access property "childNodes", n is undefined
    r https://search.nixos.org/main-b2904e74a1dc556b64d0.js:1
    r https://search.nixos.org/main-b2904e74a1dc556b64d0.js:1
    r https://search.nixos.org/main-b2904e74a1dc556b64d0.js:1
    Cn https://search.nixos.org/main-b2904e74a1dc556b64d0.js:1
    Rn https://search.nixos.org/main-b2904e74a1dc556b64d0.js:1
    In https://search.nixos.org/main-b2904e74a1dc556b64d0.js:1
    Vn https://search.nixos.org/main-b2904e74a1dc556b64d0.js:1
    b https://search.nixos.org/main-b2904e74a1dc556b64d0.js:1
    t https://search.nixos.org/main-b2904e74a1dc556b64d0.js:1

Firefox Developer 95.0b12 (64-bit) on Arch

Same issue with only the WOT plugin active.

https://github.com/WorldBrain/Memex/issues/835

So it seems this issue is more common than previously thought. Basically its because elm replaces the entire body element by its vdom which confuses/gets confused with plugins that inject their own elements into the html DOM.
Its a shame initializing an elm app under a different node does not work with applications, and if done takes the ability to handle url changes.
There is partial workarounds as shown above but I'm not sure if these are (still) valid.
@garbas what do you think about this?


get_node_version() not working with custom vim.opt.shell

get_node_version() was not working for me with a custom vim.opt.shell.
Using a table instead of a concatenation solved the issue.

What's the value of your custom vim.opt.shell?

Thanks!


[WIP] Add Dask example

This PR adds an example for Optuna's upcoming native Dask integration (xref https://github.com/optuna/optuna/pull/2023). This shouldn't be merged until after https://github.com/optuna/optuna/pull/2023 has been merged

Similar to https://github.com/optuna/optuna/pull/2023, I'd like to pick this PR back up but don't see the "Reopen pull request" button in the GitHub UI. Could someone reopen this PR for me? (maybe @nzw0301 can since they were the one who reopened https://github.com/optuna/optuna/pull/2023?)

@jrbourbeau I've reopened this PR. Thank you for your huge effort. I'll review https://github.com/optuna/optuna/pull/2023 within a week :bow:

Thanks @c-bata!


CreditCard verification methods missing/broken

When processing credit card payments, the tokenizeCard method always returns a nonce, no matter what data is passed to it. If you send a malformed cc-number, no number at all, or invalid expiration dates - the braintree server always returns a nonce.
Only at the point where you try to process a payment with the received nonce, you will get an error from braintree.
There really needs to be a validateCardNumber method in the SDK that can pre-check the entered CC-data before sending it somewhere (for example using the Luhn algorithm) - or maybe even the braintree server itself returning an error when you call the tokenizeCard method and try to tokenize malformed cc-data.
It would be great if there would be live-errors for:

Malformed card numbers (too short, too long, checksum error, card-type not supported)
Invalid expiration date
Missing/malformed CVC

To give users some live feedback before trying to finish the whole process with invalid cc information.

@Paratron the tokenizeCard method provided by our raw api client is designed in such a way to allow developers the ability to use any validation mechanism they so choose. In our products such as Drop-in and Hosted Fields this validation is handled for you. If you would like to handle your own validation and card type detection, we have a couple libraries to help you do that:
https://github.com/braintree/card-validator
https://github.com/braintree/credit-card-type
Also, these blog posts may be of some interest as well:
https://www.braintreepayments.com/blog/building-an-open-source-payments-toolkit-for-the-web/
https://www.braintreepayments.com/blog/your-checkout-our-iframes/

Thats a nice information, thank you. Sadly, your documentation lacks this information completely. There is no notice about tokenizeCard not doing any verification (I would have assumed that it does at least refuse nonsense input) in the docs and also no links about that there are other libraries for validations available.

@Paratron we have made some updates to our documentation to clear up these points and that should be released soon. Thanks for your feedback, it was very helpful!


Add docs comparing EKS Anywhere to EKS on Outposts

Issue #, if available: Issue #1479
Description of changes: Update the Compare EKS Anywhere and EKS page in the EKS Anywhere docs to describe differences between EKS Anywhere and Outposts.

I would also make a comment about the interface differences.
Customers can use Amazon EKS on Outposts with the same console, APIs, and tools they use to run Amazon EKS clusters in AWS Cloud. With EKS Anywhere, customers can use the eksctl CLI to manage their clusters, optionally connect their clusters to the EKS console for observability, and optionally use infrastructure as code tools such as Terraform and GitOps to manage their clusters. However, the primary interface for EKS Anywhere are the EKS Anywhere Custom Resources. Amazon EKS does not have a CRD-based interface today.

@chrisnegus one minor comment, other than that looks good

/lgtm

/cherry-pick release-0.14


mnnpy: error building wheel

I have successfully been able to install Celligner in both Python and R, however, when attempting to run it, the package mnnpy gives many errors building the wheel. I have tried using brew, cloning the mnnpy repository, I tried using gcc, llvm, lomp, and libomp, all unsuccessful on two different macs and a PC, all with no success at installing mnnpy. Is anyone able to help with this issue?

Did you find a solution to this? I am running into the same issue. I have tried mac, pc, and linux and also tried fresh python virtual environments within these systems and am unable to successfully install/run Celligner. I get hung up at various points in the installation process, but the farthest I have been able to get is on a Mac where I have gotten to the same point as you, unable to install mnnpy


Is it supported to generate Cosign key pair without input password

Question
Now when use "cosign generate-key-pair" to generate Cosign Key pair,  must input a password, is it possible to disable encrypt the private key?

export COSIGN_PASSWORD="your password"
then generate key pair

You can also hit enter to set an empty password.
Does that or the $COSIGN_PASSWORD approach work for you?


Add ADOT Ruby Documentation

Description
Adds ADOT Ruby documentation for how to instrument OpenTelemetry Ruby for compatibility with the AWS X-Ray Service.
Follow the templates for ADOT documentation here: https://github.com/willarmiros/aws-otel-docs/tree/main/templates

@willarmiros Addressed your comments! Hopefully you can look at the latest commit to see just what changed? Thanks for your helpful feedback! 🙂

@NathanielRN can you check and fix this PR check is failing for one of the tests.

@alolita Looks like it was an intermittent connection issue 😞
error UNHANDLED EXCEPTION read ECONNRESET

Can you try re-running workflows?

@NathanielRN you may need to push a commit to re-trigger the workflow.


Allow only alphabetical characters as input (remove digits, punctuation, spaces etc)

You can use HTML5's form validation, you just need to wrap inputs into a <form /> and add the attribute pattern to the first <input> element with some regex (maybe pattern="[a-zA-Z]+").
Reference: http://www.w3schools.com/tags/att_input_pattern.asp


About args n_view,max_samples

Hello! Your work is outstanding!
I did a detailed research on both the paper and the code.
There are a lot of questions that I don’t understand:

I want to ask first about the loss_contrast.py
Can you explain the meaning of max_samples and n_views in the hard_anchor_sampling function?
If you apply this method to small samples, can the hard_anchor_sampling step be omitted?
I hope you can explain in more detail，many thanks！

Hi，Thanks for your interest.

As given in the following line, max_samples is the maximum number of samples for all classes, and n_views is the average number for each class.
https://github.com/tfzhou/ContrastiveSeg/blob/7be326ae9127a847558584eac489d4858adf7cb1/lib/loss/loss_contrast.py#L47
You can also try to find some hard anchors (which are misclassified), no matter how many samples you have.

Thank you for your prompt reply!
Then I have corresponding questions and look forward to your help to explain:
classes = []
total_classes = 0
for ii in range(batch_size):
this_y = y_hat[ii]
this_classes = torch.unique(this_y)
this_classes = [x for x in this_classes if x != self.ignore_label]
this_classes = [x for x in this_classes if (this_y == x).nonzero().shape[0] > self.max_views]
        classes.append(this_classes)
        total_classes += len(this_classes)

In your code, if there are the same categories in different batches, will there be duplicate statistics in the result of total_classes? Hope you can solve my confusion.

What do you mean for "duplicate statistics"? p.s. If you have many questions, please also feel free to compile them together here at one time.

Hello! Your work is outstanding!
I did a detailed research on both the paper and the code.
There are a lot of questions that I don’t understand:

Can you explain the meaning of self.max_views in the hard_anchor_sampling function？ And why need (this_y == x).nonzero().shape[0] > self.max_views ？
In my project, some labels only have a little targat pixels, specially resized to the size of embedding, so the total_classes==0 situation may be happened, so that feats_ is None and self._contrast function can not run.
I want to ask about the class HRNet_W48_MEM of hrnet.py:
 def _momentum_update_key_encoder(self):      for param_q, param_k in zip(self.encoder_q.parameters(), self.encoder_k.parameters()):          param_k.data = param_k.data * self.m + param_q.data * (1. - self.m)
Can you explain the meaning of self.encoder_k？I am sorry that I did not find its definition.
I hope you can explain in more detail，many thanks！


tools: add opm to third_party go.mod

What this PR does / why we need it:
Adds opm tool from https://github.com/operator-framework/operator-registry to third_party/ go.mod and makes it so that go toolchain is used to manage its version and installation.
This makes it inline with other tools already using this mechanism in Makefile: https://github.com/Kong/gateway-operator/blob/20014217269daa7cfb540df4683f60c6b3862f57/Makefile#L56-L91
This PR retains the original version of opm, i.e. v1.19.1.

 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.


Add: Estrella TV News [MX]

Channel Name
Estrella TV News
Alternative Names (optional)
No response
Network (optional)
No response
Owners (optional)
Estrella Media
Country
MX
Subdivision (optional)
No response
City (optional)
No response
Broadcast Area
c/MX
Languages
Spa
Categories (optional)
News
NSFW
FALSE
Launched (optional)
No response
Closed (optional)
No response
Replaced By (optional)
No response
Website (optional)
https://estrellatv.com/live/estrella-news/
Logo
https://upload.wikimedia.org/wikipedia/commons/2/22/Estrella_TV_Logo_2020.png
Notes
No response

Already in the database: https://iptv-org.github.io/?q=Estrella News


chore: upload coverage reports to codecov

Issue #, if available:
Description of changes:
Why is this change necessary:
How was this change tested:
Any additional information or context required to review the change:
Checklist:

[ ] Updated the README if applicable
[ ] Updated or added new unit tests
[ ] Updated or added new integration tests
[ ] Updated or added new end-to-end tests

By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

Codecov Report

:exclamation: No coverage uploaded for pull request base (main@0802078). Click here to learn what that means.
Patch has no changes to coverable lines.

Additional details and impacted files
@@           Coverage Diff           @@
##             main     #196   +/-   ##
=======================================
  Coverage        ?   86.75%
=======================================
  Files           ?       12
  Lines           ?      951
  Branches        ?       97
=======================================
  Hits            ?      825
  Misses          ?       79
  Partials        ?       47

Flag
Coverage Δ

integration
68.98% <0.00%> (?)

unit
86.75% <0.00%> (?)

Flags with carried forward coverage won't be shown. Click here to find out more.
Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Do you have feedback about the report comment? Let us know in this issue.


no reflection fallout

Seeing this in CoreDNS tests:
PASS
ok  	github.com/miekg/coredns/middleware/errors	1.015s
2016/06/14 12:05:57 [WARNING] Forwarding cycle detected, refusing msg: example.org.
--- FAIL: TestStubLookup (0.01s)
panic: interface conversion: dns.RR is *dns.RR_Header, not *dns.OPT [recovered]
	panic: interface conversion: dns.RR is *dns.RR_Header, not *dns.OPT
goroutine 512 [running]:
testing.tRunner.func1(0xc8203d46c0)
	/tmp/workdir/go/src/testing/testing.go:450 +0x1f5
github.com/miekg/dns.(*Msg).IsEdns0(0xc8203d4900, 0xc8200fc340)
	/home/travis/gopath/src/github.com/miekg/dns/defaults.go:151 +0x1f8
github.com/miekg/coredns/middleware.(*State).SizeAndDo(0xc8202196c0, 0xc8203d4900, 0xc8203f09c0)
	/home/travis/gopath/src/github.com/miekg/coredns/middleware/state.go:137 +0x114
github.com/miekg/coredns/middleware/etcd.Stub.ServeDNS(0x0, 0x0, 0xc820137260, 0x3, 0x3, 0xe36210, 0x6, 0x0, 0x0, 0xc820177860, ...)
	/home/travis/gopath/src/github.com/miekg/coredns/middleware/etcd/stub_handler.go:36 +0x5d3
github.com/miekg/coredns/middleware/etcd.Etcd.ServeDNS(0x0, 0x0, 0xc820137260, 0x3, 0x3, 0xe36210, 0x6, 0x0, 0x0, 0xc820177860, ...)
	/home/travis/gopath/src/github.com/miekg/coredns/middleware/etcd/handler.go:34 +0x5f0
github.com/miekg/coredns/middleware/etcd.TestStubLookup(0xc8203d46c0)
	/home/travis/gopath/src/github.com/miekg/coredns/middleware/etcd/stub_test.go:26 +0x426
testing.tRunner(0xc8203d46c0, 0x122a4a0)
	/tmp/workdir/go/src/testing/testing.go:456 +0xdd
created by testing.RunTests
	/tmp/workdir/go/src/testing/testing.go:561 +0xaa4
goroutine 1 [chan receive]:
testing.RunTests(0xfa7830, 0x122a3e0, 0x9, 0x9, 0x1)
	/tmp/workdir/go/src/testing/testing.go:562 +0xafa
testing.(*M).Run(0xc82009fef0, 0x1)
	/tmp/workdir/go/src/testing/testing.go:494 +0xe5
main.main()
	github.com/miekg/coredns/middleware/etcd/_test/_testmain.go:70 +0x210

This diff fixes this for OPT:
+       rr := new(OPT)
+       rr.Hdr = h
+
        if noRdata(h) {
-               return &h, off,
+               return rr, off,
        }
        var err error
        rdStart := off
        _ = rdStart

-       rr := new(OPT)
-       rr.Hdr = h
-

In short, don't return just the header, return the empty RR with the header.


Question: Is there a conan package for threadx

Hi,
Is there a conan package for threadx?
could not find one on https://conan.io/center/search/threadx
Regards Stefan

@stefaneicher no conan package today, but we are always open to suggestions. Today we use github and the Microsoft DevOps CI/CD pipelines.


set client origin after socket open

changed the line 211

you cannot use origin header. It's optional header and it may be missed at all (undefined value) or just set to some user defined value


attachEvent event handler missing from CanIUse

attachEvent is an old IE-ism. addEventListener is the standard equivalent.
Cursory testing suggests that none of the current modern browsers (including IE11) support attachEvent.

Search result now available: https://caniuse.com/?search=attachevent


Gulp command fails

Hi,
I have a problem with the gulp command after installing with npm install.
Does anyone have an idea or a solution.

device        desktop:
OS            ubuntu 16.04:
node version  v4.2.6:
npm version   3.5.2:
error message
confItems = [...current]
^^^
SyntaxError: Unexpected token ...

ok, I updated to 7.X ... that seems to fix it.


WSL --unmount syntax?

I don't see anything in the docs or in the --help page as to how to use WSL --unmount.
on a related note with WSL1, ever since I've installed the latest google drive, which mounts it to a disk letter on windows, i get
An error occurred mounting one of your file systems. Please run 'dmesg' for more details.

I know I can work around this by creating an fstab for all of my drives... but I would like to automatically mount every drive except this one, and I'd rather not use an fstab so if I ever plug/unplug a drive there aren't issues.
I've tried wsl --unmount X:\ wsl --unmount X, wsl --unmount /mnt/x/ etc but it always says
The system cannot find the file specified.

Hi @AskAlice,
wsl --mount is designed to attach a physical disk to WSL2 (and so this is a completely separated feature from the fstab).
To mount all drives except a specific one, the fstab is indeed the way to go (along with disabling automount)
For reference, wsl --umount takes a physical disk as argument, so it would be of the form wsl --umount \\.\\PhysicalDrive1.
Documentation


Thread dump on test timeout

Additional information may potentially help when investigating transient timeout failures in tests.

I've tried analyzing a thread dump associated to one of the failures: https://github.com/enso-org/enso/actions/runs/7558161910/job/20579030654?pr=8790#step:10:14579
But the dump itself is HUUGE:
logs-timeout-dump.txt
In particular, it contains lots of (mostly zio?) threads that just sit on Unsafe.park.
@hubertp do you think it could make sense to filter such threads out?
I'm not sure if that is right, since I guess if we have e.g. a deadlock and threads are waiting on some resources, they will be parked. OTOH without it, the dump is just so big it's hard to find anything. Maybe we can at least somehow distinguish threads that are not parked? So that one could easier search for those.


Improve frontend lint settings

Description

closes frontend part of #469
Frontend:

Use ~/... instead of relative path
Use return as needed (get rid of the return statement when there is only the return in the function body)
Require to use curly for all the statements (if, while, etc...)
Encourage to name variables in camelCase
Prevent else return and absolute import from the src folder like services/**, pages/**, etc...
Require to read all the methods in the ~/api folder not to use the specific file path
Add no-console rule
Add order rules for imports

How Has This Been Tested?

Merge criteria:

[ ] The commits are squashed in a cohesive manner and have meaningful messages.
[ ] Testing instructions have been added in the PR body (for PRs involving changes that are not immediately obvious).
[ ] The developer has manually tested the changes and verified that the changes work

@andrewballantyne I thought of that, and at first, I tried to create a glob pattern matching like */**, but it will filter the imported from packages like react-dom/client. There are actually two ways, and I don't know which one is better.

block all the path like */** and create an allowlist for the paths like ~/**, ./** and node packages we are using
create a blocklist for the paths like services/**, types, pages/**, and don't block any other paths

Which option do you think is better?

@andrewballantyne I thought of that, and at first, I tried to create a glob pattern matching like */**, but it will filter the imported from packages like react-dom/client. There are actually two ways, and I don't know which one is better.

block all the path like */** and create an allowlist for the paths like ~/**, ./** and node packages we are using
create a blocklist for the paths like services/**, types, pages/**, and don't block any other paths

Which option do you think is better?

Hmmmm -- are you sure there is no way to just block non npm dependencies? Surely there is a webpack setting or something; I swear I recall this being a thing 🤔 I'd be shocked if there was no way to stop root-level imports like from 'directory' because it should say "that's not an npm import", just thinking about it.

Is there a reason to use the tilde ~/....  We can get the same effect of accessing root level folders by just omitting ~/
Example - these have the same outcome:
import { ... } from "folder"

import { ... } from "~/folder"

Is there a reason to use the tilde ~/.... We can get the same effect of accessing root level folders by just omitting ~/
Example - these have the same outcome assuming folder structure has folder at the root level.
import { ... } from "folder"

import { ... } from "~/folder"

Yuppers -- because import { ... } from 'thing' is an npm import. Overloading that has no value. Putting ~ prefix indicates that it is not an npm package.
Will we conflict with a folder and a npm package? Probably not... but it is the same as "why use ; at the end of every line". There are things we do for ease of use, common acceptance for new comers, and in general just a style we choose. I don't see any value in compounding concepts for ease of use.
Is there a reason you're against it @Gkrumbach07 ?

Is there a reason you're against it @Gkrumbach07 ?

Nope, it just seemed like extra chars at first glance. But the reasons to use it make sense


Please add beautifulhugo theme as a submodule

Please add the beautifulhugo theme as a submodule. Located here: https://github.com/halogenica/beautifulhugo
Tested and verified working with inlcuded exampleSite.

Very nice, merged in ef4dedd


Guest Wi-Fi network

Good morning,
Congratulations for this project.
I would like to know if for future revisions it would be possible to add the guest Wi-Fi network (to activate and deactivate it)
, many thanks.

Good afternoon! I think it's possible. I will write to you when it will be possible to test. Most likely it will be a beta version.

Good afternoon! I think it's possible. I will write to you when it will be possible to test. Most likely it will be a beta version.

Perfect, many thanks again.

https://github.com/dmamontov/hass-miwifi/releases/tag/v2.5.0
@fcoval enjoy)


LVOGL (Velocity v<IP_ADDRESS>): LVOGL cannot start on Linux.

LVOGL start fails due to missing libraries (cannot find liblwjgl.so on org.lwjgl.librarypath).
Likely caused by a broken path collection implementation within LVOGL.

See #8


Gogs Private Repository with Drone 0.5.0 not working

Drone 0.5.0 fails to login over self-hosted Gogs repository. Drone responded, "Unable to login. Registration is closed." with Gogs running on HTTP port 10080 and SSH port 10022, and /etc/dronerc configured as such:
DRONE_DEBUG=true
DRONE_GOGS=true
DRONE_GOGS_URL=http://gogs.company.com:10080
DRONE_AGENT_SECRET=secret
I_UNDERSTAND_I_AM_USING_AN_UNSTABLE_VERSION=true
I_AGREE_TO_FIX_BUGS_AND_NOT_FILE_BUGS=true

Got it working with instructions in http://readme.drone.io/0.5/manage/proxy_reverse/

@joelchen you understand I_AGREE_TO_FIX_BUGS_AND_NOT_FILE_BUGS  not really, right?

@joelchen please read the documentation regarding user configuration:
http://readme.drone.io/0.5/manage/users/
also if you are going to use 0.5 please note that it is unstable and you should be digging through code and attempting to resolve issues yourself.  If you are unwilling to do so we would appreciate you using 0.4 stable instead.
I_AGREE_TO_FIX_BUGS_AND_NOT_FILE_BUGS=true

Thanks for your reminders, @tboerger and @bradrydzewski. I'm not sure if this is best practice, but I wonder how do contributors and early adopters know about statuses of bugs without issue tracking.

@joelchen if people just open a bunch of bugs on 0.5 then it just overwhelms the issue tracker. This is why the environment variable is in place. If you want to try out 0.5 that's great it'll help get it in shape that much sooner, but we would like it if you actively chased down the issue rather than saying it didn't work.
Either the problem is user error, where the configuration you are using is wrong, in which case there might be issue with the documentation and that should be addressed by a pull request on the docs. If its something wrong with the code then actually debugging the issue and determining where it fails and providing a patch or a detailed description of your debugging would be the way to go. This particular issue does neither and that's why you got the response you have here.


Add  Railway deployment process.

Description
This PR fixes #93

I really appreciate any feedback. I have to write the code in main.py instead app.py. Every time I deployed with app.py the building process on Railway failed. But that is a thing with Railway, you have to have a main.py to start any app. Should I mention that issue explicitly?

No problem. Thank you for the suggestions. Let me know if I can add anything else.

Thank you for the quick revert. 😄

I have to write the code in main.py instead app.py. Every time I deployed with app.py the building process on Railway failed. But that is a thing with Railway, you have to have a main.py to start any app.

Can you please mention this in the docs too?

I changed it a little bit.

Which one?

We have to write the code in main.py instead app.py. If there is no main.py file the building process will fail. But that is a thing with Railway, you have to have a main.py to start any app.

I think I added the text above in the wrong place. I think it makes more sense if I add it after the main.py. What do you think?


Copyright is missing from licence

Copyright statement should be added to the licence to be MIT compliant.

Fixed in 1.0.1. Thanks!


Aligner trying to make overlapping intervals

Hi Kyle! My friend @mariannehuijsmans is using the aligner for data from Ayajuthem (a Coast Salish language), and we've got it working up to a certain point. We've succeeded in creating aya-mod.zip and have ourselves a big directory of data to be aligned. However, when we go to align this data, we consistently get the following (verbose) output:
Reading aligner from '/Users/mhuijs/Dropbox/QP2/Prosodylab-Aligner/aya-mod.zip'.
Preparing corpus '/Users/mhuijs/Dropbox/QP2/audiofiles'.
Aligning corpus '/Users/mhuijs/Dropbox/QP2/audiofiles'.
Writing TextGrids.
Traceback (most recent call last):
  File "/usr/local/Cellar/python3/3.6.1/Frameworks/Python.framework/Versions/3.6/lib/python3.6/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/usr/local/Cellar/python3/3.6.1/Frameworks/Python.framework/Versions/3.6/lib/python3.6/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/Users/mhuijs/Dropbox/QP2/Prosodylab-Aligner/aligner/__main__.py", line 134, in <module>
    size = MLF(aligned).write(args.align)
  File "/usr/local/lib/python3.6/site-packages/textgrid/textgrid.py", line 722, in __init__
    self.read(f, samplerate)
  File "/usr/local/lib/python3.6/site-packages/textgrid/textgrid.py", line 763, in read
    phon.add(pmin, pmax, line[2])
  File "/usr/local/lib/python3.6/site-packages/textgrid/textgrid.py", line 408, in add
    self.addInterval(Interval(minTime, maxTime, mark))
  File "/usr/local/lib/python3.6/site-packages/textgrid/textgrid.py", line 416, in addInterval
    i = bisect_left(self.intervals, interval)
  File "/usr/local/lib/python3.6/site-packages/textgrid/textgrid.py", line 193, in __lt__
    raise(ValueError(self, other))
ValueError: (Interval(5.8300001, 5.9000001, N), Interval(5.9, 5.97, T))

It looks like it's mad about trying to make overlapping intervals, so we tried adjusting the DEFAULT_PRECISION variable in textgrid.py, but that didn't help at all. Any advice? (It's not just one or two problem wav files causing this error, it seems to be all of them.)

Oh right, this bug again, really annoying. I assume it doesn't work if you
set DEFAULT_PRECISION to be, like, 4?
If this is still happening, I suppose we took the wrong approach the last
time. Instead, we either want to use exact decimals or make the overlap
checker weaker; the latter is simpler.
Here is a quick hack that should work in the meantime. Find wherever
textgrid.py lives (It'll be in one of the directories in import sys; print sys.path). Replace lines 256-257 with:
return True

(I.e, make it so the overlap test always passes.)
On Tue, Apr 11, 2017 at 1:21 AM, Kedersha<EMAIL_ADDRESS>wrote:

Hi Kyle! My friend @mariannehuijsmans
https://github.com/mariannehuijsmans is using the aligner for data from
Ayajuthem (a Coast Salish language), and we've got it working up to a
certain point. We've succeeded in creating aya-mod.zip and have ourselves a
big directory of data to be aligned. However, when we go to align this
data, we consistently get the following (verbose) output:
Reading aligner from '/Users/mhuijs/Dropbox/QP2/Prosodylab-Aligner/aya-mod.zip'.
Preparing corpus '/Users/mhuijs/Dropbox/QP2/audiofiles'.
Aligning corpus '/Users/mhuijs/Dropbox/QP2/audiofiles'.
Writing TextGrids.
Traceback (most recent call last):
File "/usr/local/Cellar/python3/3.6.1/Frameworks/Python.framework/Versions/3.6/lib/python3.6/runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "/usr/local/Cellar/python3/3.6.1/Frameworks/Python.framework/Versions/3.6/lib/python3.6/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/Users/mhuijs/Dropbox/QP2/Prosodylab-Aligner/aligner/main.py", line 134, in
size = MLF(aligned).write(args.align)
File "/usr/local/lib/python3.6/site-packages/textgrid/textgrid.py", line 722, in init
self.read(f, samplerate)
File "/usr/local/lib/python3.6/site-packages/textgrid/textgrid.py", line 763, in read
phon.add(pmin, pmax, line[2])
File "/usr/local/lib/python3.6/site-packages/textgrid/textgrid.py", line 408, in add
self.addInterval(Interval(minTime, maxTime, mark))
File "/usr/local/lib/python3.6/site-packages/textgrid/textgrid.py", line 416, in addInterval
i = bisect_left(self.intervals, interval)
File "/usr/local/lib/python3.6/site-packages/textgrid/textgrid.py", line 193, in lt
raise(ValueError(self, other))
ValueError: (Interval(5.8300001, 5.9000001, N), Interval(5.9, 5.97, T))
It looks like it's mad about trying to make overlapping intervals, so we
tried adjusting the DEFAULT_PRECISION variable in textgrid.py, but that
didn't help at all. Any advice? (It's not just one or two problem wav files
causing this error, it seems to be all of them.)
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Yeah, DEFAULT_PRECISION didn't help us anywhere in the range between 5-50.
Thanks so much for the quick response! @mariannehuijsmans what happens when you try this?

Yes, thanks you so much for the quick response! When I went to edit textgrid.py this afternoon, I realized that I have textgrid.py saved in more than one location on my computer. I think we must have been editing one that was saved in a different location last night (not the one that the aligner was using), I tried changing DEFAULT_PRECISION to 4 in the textgrid.py file that the aligner was using (/usr/local/lib/python3.6/site-packages/textgrid/textgrid.py) and the aligner ran! Then I tried it with DEFAULT_PRECISION set at 8 and I got the same error mesage. At 6, the aligner still ran.
Marianne

On Apr 11, 2017, at 10:37 AM, Kedersha<EMAIL_ADDRESS>wrote:
Yeah, DEFAULT_PRECISION didn't help us anywhere in the range between 5-50.
Thanks so much for the quick response! @mariannehuijsmans https://github.com/mariannehuijsmans what happens when you try this?
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Alright: trying something here. I just updated the TextGrid library on
GitHub so that MLF precision is, by default, just 5 digits---MLFs are what
the aligner spits out and TextGrids are then constructed from them.
TextGrid precision itself remains higher by default---15---so this ought
not to affect any users not using Prosodylab-Aligner or HTK features.
If you could, please destroy every other copy of textgrid.py, grab the
module from GitHub, and confirm that takes care of your issue.
Then, if it does, I'll upload the revised textgrid to PyPi so everyone can
benefit.
If it doesn't work, let's start a new issue over at the TextGrid GitHub
repo (github.com/kylebgorman/textgrid) and I'll take it from there.
On Tue, Apr 11, 2017 at 6:57 PM, Marianne Huijsmans <
<EMAIL_ADDRESS>wrote:

Yes, thanks you so much for the quick response! When I went to edit
textgrid.py this afternoon, I realized that I have textgrid.py saved in
more than one location on my computer. I think we must have been editing
one that was saved in a different location last night (not the one that the
aligner was using), I tried changing DEFAULT_PRECISION to 4 in the
textgrid.py file that the aligner was using (/usr/local/lib/python3.6/
site-packages/textgrid/textgrid.py) and the aligner ran! Then I tried it
with DEFAULT_PRECISION set at 8 and I got the same error mesage. At 6, the
aligner still ran.
Marianne

On Apr 11, 2017, at 10:37 AM, Kedersha<EMAIL_ADDRESS>wrote:
Yeah, DEFAULT_PRECISION didn't help us anywhere in the range between
5-50.
Thanks so much for the quick response! @mariannehuijsmans <
https://github.com/mariannehuijsmans> what happens when you try this?
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Thanks Kyle! Yes, I ran it with a freshly installed version of textgrid and it worked!
Marianne

On Apr 11, 2017, at 4:10 PM, Kyle Gorman<EMAIL_ADDRESS>wrote:
Alright: trying something here. I just updated the TextGrid library on
GitHub so that MLF precision is, by default, just 5 digits---MLFs are what
the aligner spits out and TextGrids are then constructed from them.
TextGrid precision itself remains higher by default---15---so this ought
not to affect any users not using Prosodylab-Aligner or HTK features.
If you could, please destroy every other copy of textgrid.py, grab the
module from GitHub, and confirm that takes care of your issue.
Then, if it does, I'll upload the revised textgrid to PyPi so everyone can
benefit.
If it doesn't work, let's start a new issue over at the TextGrid GitHub
repo (github.com/kylebgorman/textgrid) and I'll take it from there.
On Tue, Apr 11, 2017 at 6:57 PM, Marianne Huijsmans <
<EMAIL_ADDRESS>wrote:

Yes, thanks you so much for the quick response! When I went to edit
textgrid.py this afternoon, I realized that I have textgrid.py saved in
more than one location on my computer. I think we must have been editing
one that was saved in a different location last night (not the one that the
aligner was using), I tried changing DEFAULT_PRECISION to 4 in the
textgrid.py file that the aligner was using (/usr/local/lib/python3.6/
site-packages/textgrid/textgrid.py) and the aligner ran! Then I tried it
with DEFAULT_PRECISION set at 8 and I got the same error mesage. At 6, the
aligner still ran.
Marianne

On Apr 11, 2017, at 10:37 AM, Kedersha<EMAIL_ADDRESS>wrote:
Yeah, DEFAULT_PRECISION didn't help us anywhere in the range between
5-50.
Thanks so much for the quick response! @mariannehuijsmans <
https://github.com/mariannehuijsmans> what happens when you try this?
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Hi Michael, any chance you could update the textgrid.py in on PyPi to match
HEAD at GitHub? It looks like you were the last person to upload this---it
looks like you're the editor of that repo on PyPi?
On Tue, Apr 11, 2017 at 7:34 PM, Marianne Huijsmans <
<EMAIL_ADDRESS>wrote:

Thanks Kyle! Yes, I ran it with a freshly installed version of textgrid
and it worked!
Marianne

On Apr 11, 2017, at 4:10 PM, Kyle Gorman<EMAIL_ADDRESS>wrote:
Alright: trying something here. I just updated the TextGrid library on
GitHub so that MLF precision is, by default, just 5 digits---MLFs are
what
the aligner spits out and TextGrids are then constructed from them.
TextGrid precision itself remains higher by default---15---so this ought
not to affect any users not using Prosodylab-Aligner or HTK features.
If you could, please destroy every other copy of textgrid.py, grab the
module from GitHub, and confirm that takes care of your issue.
Then, if it does, I'll upload the revised textgrid to PyPi so everyone
can
benefit.
If it doesn't work, let's start a new issue over at the TextGrid GitHub
repo (github.com/kylebgorman/textgrid) and I'll take it from there.
On Tue, Apr 11, 2017 at 6:57 PM, Marianne Huijsmans <
<EMAIL_ADDRESS>wrote:

Yes, thanks you so much for the quick response! When I went to edit
textgrid.py this afternoon, I realized that I have textgrid.py saved in
more than one location on my computer. I think we must have been
editing
one that was saved in a different location last night (not the one
that the
aligner was using), I tried changing DEFAULT_PRECISION to 4 in the
textgrid.py file that the aligner was using (/usr/local/lib/python3.6/
site-packages/textgrid/textgrid.py) and the aligner ran! Then I tried
it
with DEFAULT_PRECISION set at 8 and I got the same error mesage. At 6,
the
aligner still ran.
Marianne

On Apr 11, 2017, at 10:37 AM, Kedersha<EMAIL_ADDRESS>wrote:
Yeah, DEFAULT_PRECISION didn't help us anywhere in the range between
5-50.
Thanks so much for the quick response! @mariannehuijsmans <
https://github.com/mariannehuijsmans> what happens when you try this?
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Sure, I can do that! Version number is based off that in setup.py, so I can do a PR for that, or you can update it more easily.  Maybe also we can update the README to specify the easier installation of pip install textgrid with the pip+git for installing the development version?  Also, I can add you as an owner to the pypi repo for the future (and you should be on there just for principle's sake regardless).  Do you have a pypi account?

On Wed, Apr 12, 2017 at 3:27 PM, Michael McAuliffe<EMAIL_ADDRESS>
wrote:

Sure, I can do that! Version number is based off that in setup.py, so I
can do a PR for that, or you can update it more easily.

Just push a commit that bumps the version number.

Maybe also we can update the README to specify the easier installation of pip
install textgrid with the pip+git for installing the development version?

Suppose we could, but this really is pretty stable---first major change in
2 years.

Also, I can add you as an owner to the pypi repo for the future (and you
should be on there just for principle's sake regardless). Do you have a
pypi account?

Sure, feel free to add me to. I'm kylebgorman on pypi.

Ok, updated on pypi and added you as owner!

And uploaded.
On Wed, Apr 12, 2017 at 3:57 PM, Michael McAuliffe<EMAIL_ADDRESS>
wrote:

Ok, updated on pypi and added you as owner!
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Introduce dedicated DSL to customize the POM of a MavenPublication

Resolves #3348. Documentation in the User Guide will be done as part of #5094.

As a side note it would be nice to have more complete commit messages, following these guidelines.

After chatting with @melix I've added explanatory text to those commits where it made sense.

We should make sure the new DSL is reasonably usable from Kotlin build scripts.
Note that without getters simple assignement won't work, you'll have to spell the setters name.

That's a shame, so we're stuck between "sucks with Kotlin now" and "no good Property migration path"?

MavenPom.getPackaging() was already there.
@oehme Do you think we should remove that, too? MavenPom is incubating, after all.

@marcphilipp Yes, I think adding write-only support to the DSL reference makes sense . As for packaging, I'd probably do a deprecation instead. But let's do that in another PR.

I added two more commits: One that adds support for write-only properties to the DSL reference generator and one that deprecates MavenPom.getPackaging().
@oehme Please take another look! 🙂

On the Kotlin topic, I was wondering whether we could mitigate the write-only property problem by adding "set" methods (e.g. packaging(String)) to the bytecode (similar to what Lombok does) instead of doing it dynamically at runtime, i.e. move some of the things AsmBackedClassGenerator does from runtime to Gradle compile time. I'm not familiar with how the Kotlin DSL is implemented, so maybe that's complete nonsense. In any case, I wanted to throw in the idea.
@eskatos @oehme @bamboo Thoughts?

After talking to @oehme this morning, we decided to use the Provider API for the new DSL. I've updated this PR with another commit. MavenPom.getPackaging() is no longer deprecated but left in place for now. The commit that completes support for write-only properties to the DSL Reference is still part of this PR because it fixes a scenario that was already partially supported. Please let me know if you'd rather see it gone.
@oehme This PR is now ready for another review.

Agreed, can you add one @marcphilipp ?

@bamboo @oehme Here is the missing test for the Kotlin DSL: #5257. Please review! 🙂


Unable to Install

Bug report
Describe the bug
Syntax bug on install:
Traceback (most recent call last):
  File "/Users/wolf/test/supabase-py/test.py", line 2, in <module>
    from supabase_py import create_client, Client
  File "/Users/wolf/test/supabase-py/supabase_py/__init__.py", line 2, in <module>
    from . import lib
  File "/Users/wolf/test/supabase-py/supabase_py/lib/__init__.py", line 2, in <module>
    from . import query_builder
  File "/Users/wolf/test/supabase-py/supabase_py/lib/query_builder.py", line 8, in <module>
    from .realtime_client import SupabaseRealtimeClient
  File "/Users/wolf/test/supabase-py/supabase_py/lib/realtime_client.py", line 21
    if (payload.type === 'UPDATE' or payload.type === 'DELETE'):                  ^

To Reproduce
clone python3 -m venv env source env/bin/activate clone pip install -e . and run example code in README
import os
from supabase_py import create_client, Client

url: str = "URL"
key: str = "KEY"
supabase: Client = create_client(url, key)

Expected behavior
A successful import and set up of client
Screenshots
If applicable, add screenshots to help explain your problem.
System information
Additional context
These repo is awesome and would definitely streamline part of the application i'm building on Supabase - a python API would like to read from the database and perform some calcs - but I can't seem to stand it up. Tried all of the branches.

Fixing the syntax leads to this error ModuleNotFoundError: No module named 'realtime_py'. That's also the error you get if you try to install from master.

Hi @Jacobsolawetz thanks for the issue. We are actively developing on this and hope to have the client in a basic working order within a week or so - but don't hold me to that haha!
We have a few PRs that are getting merged soon so please keep an eye on things.

@fedden - epic, looking forward to it! Thank you for your work

Hey @Jacobsolawetz I've pushed the fix to my working branch - feature/update-to-latest-gotrue-py.
Heads up - to use this branch there are a couple of dependancies you'd need to install manually to get things working, and we'll hopefully get things more streamlined soon after we get a few PRs merged but until then you'll need to install the following:

https://github.com/supabase/realtime-py (not sure which branch - @J0 ?)
my fork of https://github.com/fedden/gotrue-py

Awesome! sounds good, sounds good, I'll check it out - thanks again

Hey @fedden and @Jacobsolawetz,
Thanks for your patience. The version of realtime-py listed is not up to date -- I have just updated it. Alternatively, as @fedden has mentioned you can install the master branch of the repository manually.
I'm attempting to integrate the realtime-py library now and will let you know once it's ready.
Thanks for your understanding on this!
Joel

Update: I've pushed the latest gotrue to pypi - that should be working fine now, will hopefully get my branch merged to develop asap

merged!

Closing this, lmk if there is any issue.


sdk: python: Don’t timeout by default

Fixes #4111
Dagger pipelines can take a long time to run. There’s no good default here so it’s better not to timeout unless the user says so.
Signed-off-by: Helder Correia

Not sure why added tests are failing only on CI. I'll return to this shortly. Still good to review in the meantime though.

Status update: As I said it, works locally but haven't dug into debugging through CI yet. It has more to do with the tests than the implementation.
Reason for pausing this is that I'm re-prioritizing a sizeable refactor:

https://github.com/dagger/dagger/issues/4210

Will rebase this PR on top of that one with it's published.

Rebased on top of https://github.com/dagger/dagger/pull/4255, so we need to merge that first.

@helderco For the python test failures, on a re-run in CI I got a failure again but more output (think there might be a race condition with log output getting cut off from dagger-in-dagger tests?).
Not totally sure but seems like the test might just be hitting an different exception type than httpx.TimeoutException: https://github.com/dagger/dagger/actions/runs/3767484500/jobs/6406839678#step:4:2396 ?

Yeah, that's the async timeout. I thought I removed that but it got lost in the refactor. It was failing before that though. I'm going to change that real quick.

Ok, I recovered something that got lost after rebasing with the refactor PR. Now I'm back to where I was before all that. CI's log doesn't show much:
#38 74.73 tests/api/test_integration_sync.py Error: input:1: container.from.withEnvVariable.withExec.withExec.withExec.withEnvVariable.withEnvVariable.withEnvVariable.withWorkdir.withRootfs.withExec.withRootfs.withExec.withUnixSocket.withMountedFile.withMountedFile.withEnvVariable.withEnvVariable.withMountedDirectory.withExec.exitCode process "poe test --exitfirst" did not complete successfully: exit code: 1

@helderco does this line mean that the exception being raised is httpx.ReadTimeout https://github.com/dagger/dagger/actions/runs/3768773562/jobs/6407516372#step:4:2139 ?
Is that just not getting caught by our code for some reason?

I've been tinkering locally and I believe I got it.
httpx.ReadTimeout is a subclass of httpx.TimeoutException, so that's not the problem.
The test is capturing the exception on execute, basically when requesting any scalar which triggers a GraphQL request. The problem is that during establishing a connection, a first request is made to fetch the schema (introspection query), because of the dynamic query builder. The really short timeout (0.01) then is also being applied during with dagger.Connection(), which is too short.
I guess it's just that my computer is fast enough for that, but not CI. Anyway, it was intended for the test to fail fast, thus the short value, but I didn't intend that to apply to getting the schema.

Just increased the timeout to cover fetching schema. with_exec ensures it takes longer than that.


Fix Era Certificate for the case where era does not cross into Conway…

… or back
Changelog
- description: |
    <insert-changelog-description-here>
  # no-api-changes: the API has not changed
  # compatible: the API has changed but is non-breaking
  # breaking: the API has changed in a breaking way
  compatibility: <no-api-changes|compatible|breaking>
  # feature: the change implements a new feature in the API
  # bugfix: the change fixes a bug in the API
  # test: the change fixes modifies tests
  # maintenance: the change involves something other than the API
  # If more than one is applicable, it may be put into a list.
  type: <feature|bugfix|test|maintenance>

Context
Addititional context for the PR goes here.
If the PR fixes a particular issue please provide a
link
to the issue.
Checklist

[ ] Commit sequence broadly makes sense and commits have useful messages
[ ] The change log section in the PR description has been filled in
[ ] New tests are added if needed and existing tests are updated.  These may include:

golden tests
property tests
roundtrip tests

[ ] The version bounds in .cabal files are updated
[ ] CI passes. See note on CI.  The following CI checks are required:

[ ] Code is linted with hlint.  See .github/workflows/check-hlint.yml to get the hlint version
[ ] Code is formatted with stylish-haskell.  See .github/workflows/stylish-haskell.yml to get the stylish-haskell version
[ ] Code builds on Linux, MacOS and Windows for ghc-8.10.7 and ghc-9.2.7

[ ] The changelog section in the PR is updated to describe the change
[ ] Self-reviewed the diff

Note on CI
If your PR is from a fork, the necessary CI jobs won't trigger automatically for security reasons.
You will need to get someone with write privileges.  Please contact IOG node developers to do this
for you.

This should fix https://github.com/input-output-hk/cardano-api/pull/170


Handle errors in pkg/downwardmetrics

What this PR does / why we need it:
Ignore error when closing a read-only file.
Release note:
None

/sig code-quality

@akrejcir please don't mass-create individual trivial tiny PRs which are closely related. Just separate them by commit and bundle the changes at least until a reasonable PR since. As the project is set up, this creates a lot of email, review and CI overhead without benefit.
In the past we still merged such mass PRs, despite being discouraged, but I want to ask you to not continue doing that.
The changes as such are very welcome.

Closing, and will merge with #8635
/close


Fix @kie-tools/form-generation-tool: Problems generating forms for schemas that have # in the filename.

The form-generation-tool fails when generating forms for schemas that contain the # character in the name.
Generating form "demo#orderItems"
Cannot generate form "demo#orderItems":  ',' expected. (3:17)
  1 | import React, { useCallback, useEffect, useState }  from "react";
  2 |     import { TextInput, FormGroup, Card, CardBody, Checkbox } from "@patternfly/react-core";
> 3 | const Form__demo#orderItems: React.FC<any> = ( props:any ) => {
    |                 ^
  4 |   const [formApi, setFormApi] = useState<any>();
  5 |   const [ item, set__item ] = useState<string>("");
  6 | const [ order__orderNumber, set__order__orderNumber ] = useState<string>("");

Kogito codegen creates the file using the BPMN processId as the schema name. If the processId contains the .  character It is replaced by the # (eg: if the processId is demo.orderItems the generated schema is demo#orderItems.json).
We must make the form-generation-tool shouldn't fail when dealing with # in the schema name and should generate clean id's to be used inside of the generated Forms.
For simplicity, I think the generated form should use the . in the file name, since the form-matching mechanism is done by comparing the form name with the id provided by the runtime, and the runtime will always use the ..
Steps to reproduce:

Generate Patternfly forms using form-generation-tool for any BPM Quarkus project in kogito-examples (for example process-usertasks-quarkus-with-console)

Related to https://github.com/kiegroup/kie-issues/issues/556

Closed by https://github.com/kiegroup/kie-tools/pull/1978


[WIP] enable datetime ops to work if mask is NULL

I put this on top of #83, so we should not merge this before that one is in

Can one of the admins verify this patch?

ok to test

This looks good to me!

@mike-wendt what is the comment to leave to verify the patch?

i haven't injected the null testing into the other testing code paths yet - not sure if tha'ts necessary though, it's a fiarly simple change

add to whitelist

Any chance we can get this in, please, since it is blocking #186

@mt-jones Can you review and merge?


Add support to check children bounds for visibility before selecting a tile

Todo:

[ ] Testing and profiling for performance. Initial tests show about 0ms slowdown, with a few MB less downloaded data, and a big reduction in draw calls.
[ ] Unit tests

Part of #3241

In addition to testing terrain, cities, and design models, @lilleyse can you provide a massive point cloud dataset for testing?

Some test results: these represent the deltas between original and optimized versions of the code. i.e (original - optimized)

Requests
MB
Tiles Selected
Draw Commands
MS

Philly 3/4 View
2
0.1
1
1
0

Philly Top-Down
30
1.2
6
6
0

Philly Street
34
0.9
5
5
-0.1

Rio 3/4 View
22
0.5
6
13
0.2

Rio Mountains
33
1.5
2
6
0.2

Rio Downhill
4
0.1
2
4
0

Philly 3/4 View

2 fewer requests
0.1 fewer MB
1 fewer draw commands
0 ms slower per frame

Philly Top-Down

30 fewer requests
1.2 fewer MB
6 fewer draw commands
0 ms slower per frame

This optimization seems to be most effective for culling large tiles mostly behind the camera

Philly Street

34 fewer requests
0.9 fewer MB
5 fewer draw commands
0.1 ms slower per frame

Rio 3/4 View

22 fewer requests
0.5 fewer MB
13 fewer draw commands
0.2 ms faster per frame

Rio Mountains

33 fewer requests
1.5 fewer MB
6 fewer draw commands
0.2 ms faster per frame

Rio Downhill

4 fewer requests
0.1 fewer MB
4 fewer draw commands
0 ms slower per frame

Please unit test this carefully including cases with request volumes.

@pjcozzi Updated. I believe the failing tests should be fixed after this

@lilleyse can you review this?

In addition to testing terrain, cities, and design models, @lilleyse can you provide a massive point cloud dataset for testing?

I don't actually have a massive point cloud that does replacement refinement...

I don't actually have a massive point cloud that does replacement refinement...

OK, we should be fine here.
@austinEng can you merge in 3d-tiles and fix the conflicts?
@lilleyse please merge when ready and check this off the roadmap, #3241

@lilleyse updated

@lilleyse updated

Alright, everything looks good here now.


UUID

Added Identifier for faker.
Usage:
faker:"uuid_digit" xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
faker:"uuid_hyphenated" xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx

Looks like a feature more than one is looking for, i think it would be fair to close issue #39 after merging.


error training svdf_resnet on custom data

Hi @rybakov ,
I am trying to follow the steps for svdf_resnet here for quantization with the below command on custom data.

Instructions for updating:
Colocations handled automatically by placer.
W0903 18:00:45.072718<PHONE_NUMBER>89632 deprecation.py:347] From /srewai-venv/lib/python3.6/site-packages/keras/layers/normalization/batch_normalization.py:532: _colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
Model: "model"
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to
==================================================================================================
input_1 (InputLayer)            [(100, 16000)]       0           []
__________________________________________________________________________________________________
speech_features (SpeechFeature  (100, 49, 40)        0           ['input_1[0][0]']
s)
__________________________________________________________________________________________________
dense_1 (Dense)                 (100, 49, 32)        1280        ['speech_features[0][0]']
__________________________________________________________________________________________________
svdf_1_0 (Svdf)                 (100, 49, 32)        1632        ['speech_features[0][0]']
__________________________________________________________________________________________________
batch_normalization_1 (BatchNo  (100, 49, 32)        128         ['dense_1[0][0]']
rmalization)
__________________________________________________________________________________________________
add (Add)                       (100, 49, 32)        0           ['svdf_1_0[0][0]',
                                                                  'batch_normalization_1[0][0]']
__________________________________________________________________________________________________
activation (Activation)         (100, 49, 32)        0           ['add[0][0]']
__________________________________________________________________________________________________
max_pooling1d (MaxPooling1D)    (100, 24, 32)        0           ['activation[0][0]']
__________________________________________________________________________________________________
dense_3 (Dense)                 (100, 24, 50)        1600        ['max_pooling1d[0][0]']
__________________________________________________________________________________________________
svdf_2_0 (Svdf)                 (100, 24, 50)        2150        ['max_pooling1d[0][0]']
__________________________________________________________________________________________________
batch_normalization_3 (BatchNo  (100, 24, 50)        200         ['dense_3[0][0]']
rmalization)
__________________________________________________________________________________________________
add_1 (Add)                     (100, 24, 50)        0           ['svdf_2_0[0][0]',
                                                                  'batch_normalization_3[0][0]']
__________________________________________________________________________________________________
activation_1 (Activation)       (100, 24, 50)        0           ['add_1[0][0]']
__________________________________________________________________________________________________
max_pooling1d_1 (MaxPooling1D)  (100, 11, 50)        0           ['activation_1[0][0]']
__________________________________________________________________________________________________
svdf_3_0 (Svdf)                 (100, 11, 50)        3250        ['max_pooling1d_1[0][0]']
__________________________________________________________________________________________________
dense_6 (Dense)                 (100, 11, 128)       6400        ['max_pooling1d_1[0][0]']
__________________________________________________________________________________________________
svdf_3_1 (Svdf)                 (100, 11, 128)       8320        ['svdf_3_0[0][0]']
__________________________________________________________________________________________________
batch_normalization_6 (BatchNo  (100, 11, 128)       512         ['dense_6[0][0]']
rmalization)
__________________________________________________________________________________________________
add_2 (Add)                     (100, 11, 128)       0           ['svdf_3_1[0][0]',
                                                                  'batch_normalization_6[0][0]']
__________________________________________________________________________________________________
activation_2 (Activation)       (100, 11, 128)       0           ['add_2[0][0]']
__________________________________________________________________________________________________
max_pooling1d_2 (MaxPooling1D)  (100, 9, 128)        0           ['activation_2[0][0]']
__________________________________________________________________________________________________
global_average_pooling1d (Glob  (100, 128)           0           ['max_pooling1d_2[0][0]']
alAveragePooling1D)
__________________________________________________________________________________________________
dropout (Dropout)               (100, 128)           0           ['global_average_pooling1d[0][0]'
                                                                 ]
__________________________________________________________________________________________________
dense_7 (Dense)                 (100, 64)            8256        ['dropout[0][0]']
__________________________________________________________________________________________________
dense_8 (Dense)                 (100, 3)             195         ['dense_7[0][0]']
==================================================================================================
Total params: 33,923
Trainable params: 32,983
Non-trainable params: 940
__________________________________________________________________________________________________
I0903 18:00:45.455425<PHONE_NUMBER>89632 train.py:71] None

But it fails at the time of converting into tflite stream. Here is the error:
2021-09-03 18:22:54.631382: I tensorflow/core/grappler/clusters/single_machine.cc:357] Starting new session
2021-09-03 18:22:54.634525: E tensorflow/core/grappler/grappler_item_builder.cc:669] Init node svdf_1_0/dense/kernel/Assign doesn't exist in graph
I0903 18:22:54.659212<PHONE_NUMBER>90304 lite.py:1723] Using experimental converter: If you encountered a problem please file a bug. You can opt-out by setting experimental_new_converter=False
2021-09-03 18:22:54.663914: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:351] Ignored output_format.
2021-09-03 18:22:54.663933: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:354] Ignored drop_control_dependency.
2021-09-03 18:22:54.698313: W tensorflow/compiler/mlir/lite/flatbuffer_export.cc:1855] TFLite interpreter needs to link Flex delegate in order to run the model since it contains the following flex op(s):
Flex ops: FlexAudioSpectrogram, FlexMfcc
Details:
	tf.AudioSpectrogram(tensor<16000x1xf32>) -> (tensor<1x49x513xf32>) : {device = "", magnitude_squared = true, stride = 320 : i64, window_size = 640 : i64}
	tf.Mfcc(tensor<1x49x513xf32>, tensor<i32>) -> (tensor<1x49x40xf32>) : {dct_coefficient_count = 40 : i64, device = "", filterbank_channel_count = 80 : i64, lower_frequency_limit = 2.000000e+01 : f32, upper_frequency_limit = 7.600000e+03 : f32}

******snipped****

I0903 18:01:06.509099<PHONE_NUMBER>89632 test.py:510] tflite test accuracy, non stream model = 74.63% 200 out of 221
I0903 18:01:06.552580<PHONE_NUMBER>89632 test.py:514] tflite Final test accuracy, non stream model = 75.11% (N=221)
I0903 18:01:06.553761<PHONE_NUMBER>89632 model_train_eval.py:257] run TFlite streaming model accuracy evaluation
W0903 18:01:07.091468<PHONE_NUMBER>89632 test.py:560] FAILED to convert to mode STREAM_EXTERNAL_STATE_INFERENCE, tflite: Negative dimension size caused by subtracting 3 from 1 for '{{node streaming/max_pooling1d/MaxPool}} = MaxPool[T=DT_FLOAT, data_format="NHWC", explicit_paddings=[], ksize=[1, 3, 1, 1], padding="VALID", strides=[1, 2, 1, 1]](streaming/max_pooling1d/ExpandDims)' with input shapes: [1,1,1,32].
I0903 18:01:07.091856<PHONE_NUMBER>89632 test.py:364] tflite stream model state external with reset_state 1
I0903 18:01:07.342433<PHONE_NUMBER>89632 model_train_eval.py:282] FAILED to run TFLite streaming: Mmap of '7' at offset '0' failed with error '22'.

It is a known issue stackoverflow, there are are two options to solve it: 1 rebuild tf with bazel with enabled flex delegate; 2 use tf as it is but do not use flex ops in your model and replace
--feature_type 'mfcc_op' \

by
--feature_type 'mfcc_tf' \

The last one will use standard tf ops (this is what we used in the paper). 'mfcc_op' is a good option if you plan to quantize you model.

Thanks @rybakov , when I replace the suggested , I still get the error the second error:
2021-09-04 18:41:59.625944: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:351] Ignored output_format.
2021-09-04 18:41:59.625969: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:354] Ignored drop_control_dependency.
2021-09-04 18:41:59.636301: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:210] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.
2021-09-04 18:41:59.698157: I tensorflow/compiler/mlir/lite/flatbuffer_export.cc:1922] Estimated count of arithmetic ops: 66.155 M  ops, equivalently 33.077 M  MACs

Estimated count of arithmetic ops: 66.155 M  ops, equivalently 33.077 M  MACs
I0904 18:42:00.552432<PHONE_NUMBER>17472 test.py:510] tflite test accuracy, non stream model = 32.34% 200 out of 221
I0904 18:42:00.605312<PHONE_NUMBER>17472 test.py:514] tflite Final test accuracy, non stream model = 32.13% (N=221)
I0904 18:42:00.606071<PHONE_NUMBER>17472 model_train_eval.py:236] run TF evalution only without optimization/quantization
I0904 18:42:01.808442<PHONE_NUMBER>17472 model_train_eval.py:255] FAILED to run TF streaming: Negative dimension size caused by subtracting 3 from 1 for '{{node streaming/max_pooling1d/MaxPool}} = MaxPool[T=DT_FLOAT, data_format="NHWC", explicit_paddings=[], ksize=[1, 3, 1, 1], padding="VALID", strides=[1, 2, 1, 1]](streaming/max_pooling1d/ExpandDims)' with input shapes: [1,1,1,32].
I0904 18:42:01.809512<PHONE_NUMBER>17472 model_train_eval.py:257] run TFlite streaming model accuracy evaluation
W0904 18:42:02.433501<PHONE_NUMBER>17472 test.py:560] FAILED to convert to mode STREAM_EXTERNAL_STATE_INFERENCE, tflite: Negative dimension size caused by subtracting 3 from 1 for '{{node streaming/max_pooling1d/MaxPool}} = MaxPool[T=DT_FLOAT, data_format="NHWC", explicit_paddings=[], ksize=[1, 3, 1, 1], padding="VALID", strides=[1, 2, 1, 1]](streaming/max_pooling1d/ExpandDims)' with input shapes: [1,1,1,32].
I0904 18:42:02.433842<PHONE_NUMBER>17472 test.py:364] tflite stream model state external with reset_state 1
I0904 18:42:02.692718<PHONE_NUMBER>17472 model_train_eval.py:282] FAILED to run TFLite streaming: Mmap of '7' at offset '0' failed with error '22'.
I0904 18:42:02.693176<PHONE_NUMBER>17472 model_train_eval.py:194] feature type mfcc_tf needs quantization aware training for quantization - it is not implemented

With option "mfcc_tf" you should follow kws_experiments_paper_12_labels: these are not quantized models.
If you need quantized models then it has to be kws_experiments_quantized_12_labels in this case you will need tflite flex, as descried in stackoverflow.
It was designed this way because TFLite did not support some tf ops and I had to use custom TFLite ops with "mfcc_op" (for quantized models) or their direct tf re-implementation with "mfcc_tf" (for non quantized models). In the last case if you enable quantization it will also quantize DFT weights which will degrade model accuracy. Now TFLite supports all ops in this lib, so I can try to enable quantization of "mfcc_tf" too.

There is also issue with striding parameter in the model. I will submit a fix on Monday.
After that you should also add:
--data_stride 4 \

@rybakov, thanks so much for your help.  kws_experiments_paper_12_labels do not have svdf_resnet training example and svdf works fine for me. So, once you have time to implement the changes, please add a comment here for the heads up! :)
Thanks again!

svdf_resnet was added after paper was published. It was not streamable, so in the last CL I made it streamable.  Thank you so much for your help! It works :)
I really appreciate it. Very quick response!

If you don't mind I have few questions as below, just for confirmation:
Consider the below data folder :
data folder:
_background_noise_  bed  bird  cat  dog  happy  srewai  house  marvin   sheila  tree  wow

Q.1 if we train a model with --wanted-word 'srewai', it will consider everything else in the data folder (bed,bird,dog,house,marvin,sheila,tree,wow) as unknown words but still use these words for training the model, right?
Q.2 How do I add additonal background noise for the training? Do I just add the noise .wav files into the background_noise folder?  Is there limitaion on number of files and *audio file length in background_noise folder?

@rybakov , got my answers, simply great! Thanks again!

Following the inference notebook
I see that the model is converted into streaming mode as below, (Run streaming inference with TFLite):
tflite_streaming_model = utils.model_to_tflite(sess, model_non_stream_batch, flags, Modes.STREAM_EXTERNAL_STATE_INFERENCE)
tflite_stream_fname = 'tflite_stream.tflite'

with open(os.path.join(MODEL_PATH, tflite_stream_fname), 'wb') as fd:
  fd.write(tflite_streaming_model)

But after training a model, we already have the tflite_stream.tflite file, so not sure why not use that directly?
The notebook loads use model_content, for tf.lite.Interpreter as an argument,
example 1:interpreter = tf.lite.Interpreter(**model_content**=tflite_non_streaming_model)

Isn't it ok to just load the streaming .tflite file from the models folder like below and run it for inference?
example 2: interpreter = tf.lite.Interpreter(**model_path**='path_to_/tflite_stream.tflite')

I tried example 1 and example 2 and both of them predict different labels for the same input by the same .tflite model.
I want to implement .tflite model on embedded platform in C++.
Do you have some recommendations to directly implement the available .tflite  in C++ and skip converting functions likeutils.model_to_tflite  and others from python to C++ that have been used in the inference notebook.

If you trained your model, then all conversion to streaming is already done (you can use it as it is) so there is no need to convert the model again. Your example 1 and example 2 should be numerically the same, I guess there is a difference in flags parameters, which are used for converting a model in colab (I would suggest to use model generated by training script, utils.model_to_tflite is part of it any way).
I do not have open sourced c++ demo. But there are a lot of examples of running tflite module in c++. TFLite c++ api is similar to python, you will need to re-implement py in c++.

@rybakov , you are an amazing person! Thanks again! You have always helped me extra mile :)
Yes, the difference is in the flag parameter that might have caused the varying results. I am going to use the models generated post model training and will re-implement part of inference.py in c++ as suggested.

Hi @rybakov,
I am trying to train sdvf model with custom data split with the below directory structure and training parameters.
(venv) srewai@las:~/path/final_dataset$ ls -l
_background_noise_
       < doing_the_dishes.wav
          dude_miaowing.wav
         ...
testing
      < down
               gen-12.wav
                ..
         eight
              gen-1.wav
               ...
         five
              xyz.wav
              ...
         four
             ...
         hey_babuni
         nine
         no
         on
         one
         seven
         six
         three
         two
         up
         zero
             abc.wav
training
          < down
               gen-3.wav
                ..
         eight
              gen-2.wav
               ...
         five
              xyzr.wav
              ...
         four
             ...
         hey_babuni
         nine
         no
         on
         one
         seven
         six
         three
         two
         up
         zero
             abcx.wav
validation
           < down
               gen-3.wav
                ..
         eight
              gen-12.wav
               ...
         five
              xeyz.wav
              ...
         four
             ...
         hey_babuni
         nine
         no
         on
         one
         seven
         six
         three
         two
         up
         zero
              #abcd.wav

$CMD_TRAIN \
--data_url '' \
--wanted_words hey_babuni \
--split_data 0 \
--data_dir $DATA_PATH/ \
--train_dir $MODELS_PATH/svdf/ \
--mel_upper_edge_hertz 7600 \
--how_many_training_steps 20000,20000,20000,20000 \
--learning_rate 0.001,0.0005,0.0001,0.00002 \
--window_size_ms 40.0 \
--window_stride_ms 20.0 \
--mel_num_bins 80 \
--dct_num_features 30 \
--resample 0.15 \
--alsologtostderr \
--time_shift_ms 100 \
--train 1 \
svdf \
--svdf_memory_size 4,10,10,10,10,10 \
--svdf_units1 256,256,256,256,256,256 \
--svdf_act "'relu','relu','relu','relu','relu','relu'" \
--svdf_units2 128,128,128,128,128,-1 \
--svdf_dropout 0.0,0.0,0.0,0.0,0.0,0.0 \
--svdf_pad 0 \
--dropout1 0.0 \
--units2 '' \
--act2 ''

But I am getting the exception error as:
Traceback (most recent call last):
  File "/usr/lib/python3.6/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/usr/lib/python3.6/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/lhome/srauniy/test2/kws_streaming/train/model_train_eval.py", line 367, in <module>
    tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
  File "/lhome/srauniy/test2/sonu-venv/lib/python3.6/site-packages/tensorflow/python/platform/app.py", line 40, in run
    _run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
  File "/lhome/srauniy/test2/sonu-venv/lib/python3.6/site-packages/absl/app.py", line 312, in run
    _run_main(main, args)
  File "/lhome/srauniy/test2/sonu-venv/lib/python3.6/site-packages/absl/app.py", line 258, in _run_main
    sys.exit(main(argv))
  File "/lhome/srauniy/test2/kws_streaming/train/model_train_eval.py", line 147, in main
    train.train(flags)
  File "/lhome/srauniy/test2/kws_streaming/train/train.py", line 51, in train
    audio_processor = input_data.AudioProcessor(flags)
  File "/lhome/srauniy/test2/kws_streaming/data/input_data.py", line 124, in __init__
    self.prepare_split_data_index(wanted_words, flags.split_data, file_ext)
  File "/lhome/srauniy/test2/kws_streaming/data/input_data.py", line 324, in prepare_split_data_index
    raise Exception('Unknown word ' + word)
Exception: Unknown word six

All the folders one two three.. in the training, testing, and validation are phonetic segmentation of --wanted_word hey_babuni.
I am considering these as contrasting examples of the wanted word. Would you please help me with what is missing here and causing the error? Also, do you think creating contrasting examples using phonetic segmentation would help for a robust model by reducing the number of false positives?
Thank you!

My previous answer was for a case when lib will split data for you with option
--split_data 1 \

But here you are using custom data split with
--split_data 0 \

so you have to control all data on your own: data split and labels. As it is shown here SILENCE_LABEL and UNKNOWN_WORD_LABEL will not be added to your wanted_words as it was with split_data=1.
In this case (split_data=0) folders "testing"/"training"/"validation" should have only wanted.
For example if you have wanted_words: "hey_babuni", "other" then testing folders will contain
testing
      < other     "you can copy here all wav files from other folders 'down', 'eight', 'five' etc..."
               gen-12.wav
               gen-1.wav
               xeyz.wav
                ..
         hey_babuni

Sub-folders names (in "testing" folder) have to be the same with wanted_words. Number of wanted_words is the number of categories in the classifier.
"training" and "validation" folders should have the same structure as "testing" above.

@rybakov . Thank you so much for the clarification. Here, I want to use the phonetic segmentation of the --ẁanted_word hey babuni to be treated as  UNKNOWN_WORD_LABEL so that the model is more robust to avoid false positives. So all the contents of the folder other are individual sounds (phonetic segmentation) of ẁanted word hey babuni which means these are not the list of my wanted words but I want the model to learn them as  UNKNOWN_WORD_LABEL.
Q.1. Is this a good approach for a robust model to avoid false positives, please suggest?
Q.2  I still want to have 3 output labels, or there is a better approach:
'hey babuni'
“silence”
“unknown” (all individual sounds, phonetic segmentation).
Thank you for your understanding!

It sounds reasonable to add segments to the “unknown” bucket for reducing false positives. You could also use them as separate labels.
Another standard approach for controlling false positive is thresholding neural net output score (positive rate also will be impacted), in addition you could check that the score is passing a threshold several times before making a final decision.

For example you can collect many hours of speech which does not have any key command. Then compute the distributions of output scores and set a threshold to satisfy your conditions for example probability of false alarm.

Thank you so much! But how does this work in the case of --split 1 ?

@rybakov , while performing quantization there is talk about calibration dataset for full quantization. How do I achieve this, are there steps mentioned anywhere?

@srewai please have a look at issues/836 it discusses post training quantization with calibration data. I am also working on quantization aware training which will not requre calibration data, but I do not have ETA yet.

@rybakov, I wish you a happy new year :)
I quickly wanted to ask you, is there anywhere you've also calculated the precision and recall of the models in the code? if not could you please give me any hints on the same.:)

Thank you, happy new year!
It is a multiclass precision recall, so I would suggest to look at link, link

@rybakov, thank you.


Bug: API keys only able to be set by environment variables

The latest update to<EMAIL_ADDRESS>introduced a bug where you're only able to set the API keys for both current gen and next gen through environment variables.

No change with 0.1.11 - same error.
This is the provider config (working with previous versions)
provider "harness" {
endpoint   = var.api_endpoint
account_id = data.vault_generic_secret.harness.data.account_id
api_key    = data.vault_generic_secret.harness.data.api_key
}
variable for the api endpoint has been updated in line with changes.

@mattcharlton strange. Let me take a look.

@mattcharlton Can you give this build a try?
terraform {
  required_providers {
    harness = {
      source = "harness-io/harness"
      version = "0.1.12-beta1"
    }
  }
}

Ran into this issue as well. Was seeing
Error: invalid config: ApiKey must be set %!s()
on provider.tf line 1, in provider "harness":
1: provider "harness" {
downgrading or upgrading to version 0.1.12-beta1 works!

Thanks for confirming @stan-yago . Just published the new version 0.1.12.


TLS 1.2 support

Please add TLS 1.2 support. Currently the library only uses TLS v1.

You can add this to the top of your application to support TLS 1.2:
using System.Net;
// snip
ServicePointManager.SecurityProtocol = SecurityProtocolType.Tls | SecurityProtocolType.Tls11 | SecurityProtocolType.Tls12;


Add mobile support for demo project and menu links to display documentation

Add mobile support for demo project and menu links to display documentation #2

done


Honor .eslintignore ?

I guess its not guaranteed that standard is eslint under the hood, but since it is, does it make sense to also read ignore paths from the local .eslintignore?

I think you answered your own question.

I guess its not guaranteed

We want standard to work exactly the same way for everyone, with as little unpredictable behavior as possible. You can configure which files to ignore in package.json with the ignore property.


Update app.js

Fixed Error: "value" required in setHeader("Content-Type", value)
I am testing the cartridge with an Angular2 app.

Ok, accepting the PR won't hurt, but... what's the deal with the Angular2 app?

@icflorescu It might be linked with a certain version of NodeJS see here
I mentioned the Angular2 app, as no one else seems to have the issue.


Intellisense disabled

Hi,
I just installed the extension and I noticed that the intellisense is disabled (for CSS, JS and HTML). Is this a problem related to the extension or to visual studio code itself?

see #12


SuperSu/KingoRoot

When I try to run SuperSu or KingoRoot on my device, the screen becomes unusable. Is there any way to allow this to enable root access on my device that does not have a screen?

Additional Information: when I press SuperSu or KingoRoot it says this:
INFO: Initial texture: 1920x1080
INFO: New texture: 1080x1920
So it seems it is inverting the resolution and breaking your program.

INFO: Initial texture: 1920x1080
INFO: New texture: 1080x1920

This is just a device rotation.
Does it work with screenrecord:
adb shell screenrecord /sdcard/file.mp4
adb pull /sdcard/file.mp4

?

Same issue

OK, so if it does not work even with screenrecord, it won't work.


defcustom mbsync-auto-accepts-certs nil

Only auto-accept certs if this is non-nil. Probably a slightly safer
default.

Thanks! I'm not using mbsync at all anymore. Do you want me to add you as a contributor to the project here on github so that you can take care of it?

Sure :-)


Split @include('googletagmanager::script') into two parts

According to GTM docs (https://developers.google.com/tag-manager/quickstart) <script> should be placed "as close to the opening <head> tag as possible" and <noscript> part "immediately after the opening <body> tag".
Simo Ahava explains reasoning behind this: https://www.simoahava.com/gtm-tips/gtm-container-snippet-in-the-head/

This is a breaking change. I'll revisit this when creating the next major version. Might take a while though.


Add search functionality

Codecov Report

Merging #13 into master will decrease coverage by 7.35%.
The diff coverage is 35.48%.

Impacted Files
Coverage Δ

lib/src/libgen.dart
43.75% <20.00%> (-13.83%)
:arrow_down:

lib/src/models/book.dart
100.00% <100.00%> (ø)

lib/src/pagination/pagination.dart
100.00% <100.00%> (ø)

lib/src/pagination/pagination_options.dart
47.36% <0.00%> (ø)

lib/src/pagination/compute_pagination.dart
100.00% <0.00%> (ø)


ARROW-4535: [C++] Fix MakeBuilder to preserve ListType's field name

MakeBuilder doesn't preserve the field name in the given ListType.
I think this is a bug.

The test failure on Travis CI is related to a garrow_list_array_new() bug.
It must be passed GArrowFiled * instead of using arrow::list() internally.
We need to fix this bug. The fix of this breaks backward compatibility but this is acceptable. Because normal users don't use garrow_list_array_new() directly.

@kou I'll make another pull-request to modify garrow_list_array_new().

Thanks!


Changed name of environment variable for TOKEN_SENDER_AMOUNT

TOKEN_SENDER_AMOUNT -> PROTOCOL_API_TOKEN_SENDER_AMOUNT

Tested that this change (and the new configuration on the production API) is working. Test transaction: https://testnet.game7.io/tx/0x6939941ce8e5dcfcd325ed55e0a134f9ba2a68c25c5e09c7c978eca4e9b321ce?tab=index


Exporting of object detection & segmentation code

Hello
How are you?
Thanks for contributing to this project.
When can we expect to get the object detection & segmentation code?

Really looking forward to the code for classification, object detection and segmentation!

Really looking forward to the code for classification! Thanks!

Thank you for this awesome work!
Could you kindly let me know a probable time when the object detection code might be released?

I have been working on polishing the codes, and am about to commit them in a few weeks.

Hi there! Has there been an update regarding this? :D

Hello @tdchua @Filipwansen @Sairam13001 @stayhungry1 @yuanbianGit,
Sorry for being so late. The code repos of detection and segmentation are updated along with the newer extended version of DAT. Please check them out and feel free to raise issues if you encounter any problems.


The New Boston Ad Network

How would you describe your project?
Develop an ad network that accepts TheNewBostonCoins (TNBC) along with other mainstream cryptocurrencies like bitcoin etc.
What problem does it solve?
enable advertisers to ad campaigns and pay with Cryptocurrency.
enable Publishers to add websites, monetise and get paid in cryptocurrency as well.
Who is the target market?
Cryptocurrency advertisers and publishers.
What do you think is the opportunity of this project?
Increase the TNBC market and enhance the possibility of establishing new crypto-currency globally.
How does it integrate with thenewboston digital currency work?
Thenewboston ad network would provide a platform to the advertisers and Publishers to use TNBC to deposit funds and receive payments.
Are there any competitors?
Google, Hilltopads and AdEx.
What are your goals and objectives?
Advertiser:
As a user advertiser can create ad campaigns, set the limits, filters, and deposit funds in cryptocurrency using coinbase payment gateway.
Publisher:
Enable users to add new sites, verify, and monetize it as soon as possible.
Admin:
enable admins to manage the advertisers, publisher accounts & payment as well as assign the contact managers to the advertisers and publishers.
How will you evaluate project success?
This platform should play a role to build trust of the users (advertisers/publishers) whoever visited this ad Network and it should have a high conversion rate.
If this ad network would help establish TNBC as a digital currency in the market that would be a success.
By posting this issue, I (Pitchapa Nickonpol) allow my project idea to be used by other people for any commercial as well as non-commercial purposes and I'll not be liable for misuse of my idea.

Here are some UX research docs as well.
https://www.figma.com/proto/tN7v8eggv8WaN2jrPlgqel/UX-Research-TheNewBoston-Ads?node-id=4%3A2&viewport=-1906%2C-7206%2C0.44441649317741394&scaling=min-zoom
TheNewBoston Ads Network-UX-Research.pdf

Hey, @pitchapa-n I really liked your project idea and I liked it so much that I want to take this one if you allow me to. 🙂

Anyone working on this project idea yet if no one is working on it, I will like to take on the project. @manishram @buckyroberts

Hey @Sulaiman001, nobody is working on this yet. Please feel to take over it. Make a new proposal with MVP details.

Alright, thank you @manishram I will do that.

The New Proposal please review https://github.com/thenewboston-developers/Projects/issues/408 and these https://github.com/thenewboston-developers/Projects/issues/404


Speed up time?

Is there a way to speed up the simulation? Nothing happens when I press the "Full Speed" button in the Time control box.

the speed up simply removes de framerate cap so there are two possibilities:

your pc is at max capacity already
the button is not working
what happens if you use Full Speed with just a few ants? does it works in this case?

I´m using the AntSimulator-Editor. I reduced the ants to 1000 in conf-file, which seems to be the lowest possible. My CPU is about 40% and no real change when I press the button. I also tryed 4.1 version, and same/similar result there.
I don´t know if I can do any other change then that.

You are not the only one mentionning this issue, maybe there is something else. Do you have multiple monitors connected at the same time?

Ok. No other monitor. I am using a (gaming) laptop.

same issue here using a laptop and the program only taking 40% of CPU and button doesn't work

Do you know how to compile it? Since I cannot reproduce the issue (neither on my Windows or Mac machines) I would like to create a branch to push potentiel fixes and let you give me feedback.

Do you mean the source code? Because I´m just opening the AntSim program. For that I would have to install c++ first i guess. Which i could  possibly do in june when I have time.

I have the AntSimulator 4.1 source installed, compiled under VS2K19. The Full Speed button only works for me in Release build.

Thanks for your feedback. That's probably because without release optimizations the program is already at max speed even when the toggle is disabled.

My full speed button is not working either. Which file is the time sped up in?


Alerts for alarm states

Is it possible to add ST alerts or messaging when panel is in alarm state?

removed ST support


DatePicker validations for minDate/maxDate not working in repeating groups

Description
While developing , I found that custom form validations for the DatePicker component seems to only iterate through components on the top level, failing to validate minDate/maxDate for DatePicker components in repeating groups.
Affected code (at the time of writing this issue, in the feature branch):
https://github.com/Altinn/app-frontend-react/blob/7c1e45b6b1fef97d73620ecf744cebd0a87808f5/src/altinn-app-frontend/src/utils/validation.ts#L518-L544
The code above fixes this for FileUpload and FileUploadWithTag, so it shouldn't take much to fix this for DatePicker as well.
To Reproduce
(I haven't reproduced this myself, but I assume:)

Create an app with at least one repeating group
Add a DatePicker component to that group
Set minDate/maxDate restrictions (in FormLayout, I believe)
Input an invalid date

Expected behavior
You should see a validation error
Actual behaviour
Most likely no validation error :crossed_fingers: (assuming your javascript engine is somewhat compatible with the one in my mind)

I'm grabbing this one from the improvements in repeating groups project - sorry! Because of changes in the validation code to support layout validations, I have to make changes to the code causing this, and I think I might have fixed the issue as a consequence of those changes. I'm adding it to the layout expressions project so the fix will get tested there.

This seems to work in repeating groups after all, but mostly because the code in validation.ts does not seem to be in use at all.. I created #600 for cleaning up the validation duplication in DatepickerComponent.tsx, as this seems to be a bigger task than I anticipated.


Feature/67 render mural marker

Summary
implemented render the mural markers to the map, added cors in backend to run backend and frontend at the same time locally (not sure if this is the way to do that....)

Test Plan
manually
Related Issues
#67

for reference:

feel free to merge!

for reference:

feel free to merge!


GHA: Create Release Task

Task/Issue URL:
Description
Steps to test this PR
Feature 1

[ ]
[ ]

UI changes

Before
After

!(Upload before screenshot)
(Upload after screenshot)

#4988  👈
develop

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