Support TS moduleResolution: node16

Describe the bug
In TS, import {...} from tinybase is broken under moduleResolution: nodenext (currently equivalent to moduleResolution: node16). See<EMAIL_ADDRESS>By taking a quick look, I think the reason is imports missing file extensions (eg. export * from './store.d' instead of export * from './store.d.ts').
We use moduleResolution: nodenext because currently it is the strictest option, ensuring wide compatibility.
Your Example Website or App
No response
Steps to Reproduce the Bug or Issue
No response
Expected behavior
No response
Screenshots or Videos
No response
Platform

OS: [e.g. macOS, Windows, Linux]
Browser: [e.g. Chrome, Safari, Firefox]
Version: [e.g. 91.1]

Additional context
No response

On it!

OK take a look at v4.7.2 and see if that works better.

Hey, sorry for the late reply.
I confirm that import {...} from tinybase works correctly.
However, import {...} from tinybase/persisters/persister-browser does not work, the problem likely affects other import paths.
By inspecting the node_modules/tinybase/lib/types folder, I noticed that top-level files now include import file extensions (eg. import {Store} from './store.d.ts'), while files in sub-folders do not (eg. import {Store} from '../store').

I think I got them all in v4.8.5 - please check!

It's working, thank you so much!


testID for DatePickerIOS

DatePickerIOS  should have a testID properties for end-to-end tests

It is passed to native Component (iOS only atm) https://github.com/react-native-community/react-native-datetimepicker/blob/review/src/datetimepicker.ios.js#L82, would you like to have it demonstrated as part of the example?

I will take another look but I test it on Appium and I wasn't able to use the testID, I will try it on Detox to see if I have better luck.
BTW: @Swaagie how can I run the Detox test locally for this repo, do we have any guidance? do you need help with the setup to run it locally? I think is not ready, yet. https://github.com/react-native-community/react-native-datetimepicker/blob/review/.circleci/config.yml

There are no detox tests yet, was just wondering how you were consuming the component. I'll double check with Appium as well during the weekend.

I found this Detox test https://github.com/facebook/react-native/blob/8270de9c2cfad721b554201ab97d645ffbfdc84b/RNTester/e2e/tests/DatePickerIOS-test.js#L55 so is possible to do it at least with Detox

Nice find on the detox tests, I hand't seen those while going through core to get all related code. I will port these over to module.


V2 Updates

Bring up to v2 verification standards, most significantly, adding authenticity checks to verify the issuer address from the transaction checks out with those on the issuer id page. We want to ensure that the tx was issued when the issuing key was valid.
Exceptional cases handled:

tx signing key not on issuer id page
tx signing key was revoked, expired, or not yet created

Added more test cases to: cert-walletTests/CertificateValidationRequestTests.swift

tampered v2 certificate: changed existing field should break hash and fail
authenticity failure: certificate issued after issuer revoked key should fail
valid v2 certificate with legacy (v1) issuer format should pass

There is a lot of code duplication in that test class, but I'm having issues getting the test expectations cleanly refactored. I did some cleanup to make this easier in the future.
Opened issue #32 to track detection of unmapped JSON-LD fields. This will be doable; just need to find the right way to pass the fallback context to swift ld libraries during normalization.
Note I changed assertion id (uid) to extract just the guid to allow for the following cases:

it's a url, like we had in v1
it has a urn:uuid prefix, which v2 allows (but also allows urls). The prefix is used for unhosted assertions.

pushed fixes for PR feedback. Confirmed tests pass locally. Waiting for travis build, and will merge if everything looks good


Keyboard navigation fixes

Removed textarea element from Viewer DOM. Viewer.canvas now handles keyboard navigation.

Hooray for simplification!

Word :)


Refactor events

add noop events for unused powerups

Conflicts with the changes I have just merged in, needs to be resolved

@sigu: conflicts resolved. I still haven't gotten the hang of when to base a branch off another branch to minimize conflicts.

The current release candidate branch should be the base branch for new features since we are ultimately going to merge into it

I will wait for a review from @TraceyOnim and/ or @WanjikuMac before merging this in

I'm jumping the gun and merging in so can have in the demo .5 coming out


Consumption: Using existing Sentinel API connection with User Assigned MI causing LA save failure

Describe the Bug with repro steps

Create a user assigned MI and assign to Logic App
Create 2 Sentinel API connections with user assigned MI in Logic App, use one of the 2 Sentinel connections for the Sentinel action and then save the Logic App
Open designer again then switch to the other Sentinel API connection, after click save button, we can see the exception

Note: The issue does not repro with the preview designer.
What type of Logic App Is this happening in?
Consumption (Portal)
Are you using new designer or old designer
Old Designer
Did you refer to the TSG before filing this issue? https://aka.ms/lauxtsg
Yes
Workflow JSON
No response
Screenshots or Videos
No response
Browser
Chrome
Additional context
No response

If anyone runs into this, the suggestion for now is to use preview designer.


Switch to Python 3.10

Aethel requires python >= 3.10, while our server currently runs on 3.9
~Either we have to upgrade the server, or run parseport inside docker like spindle-server~
We'll solve this by moving parseport to run inside the docker compose setup we already have

solved with docker


Get same Adafruit GPIO ribbon cable from DigiKey & save shipping

The SAME 6" 40 connector GPIO ribbon listed in the parts spreadsheet from Adafruit:
https://www.adafruit.com/product/1988
can be purchased from DigiKey along with the other parts & save separate shipping:
https://www.digikey.com/product-detail/en/adafruit-industries-llc/1988/1528-2235-ND/7241480
Jim Phelan
Mars Rover project lead
USAi Labs (formerly Houston Robotics)

Sure thing good find. Would you mind opening a pull request with that changed in the parts list and I'll merge it in

All Adafruit items can be ordered from Digi-Key, which is generally the most convenient and cheapest way if you're ordering from Digi-Key anyway.

Since we order parts from both DigiKey and Adafruit for the whole rover, I'll leave this as it is for now.  You only save shipping if you are only ordering upgraded parts for the electronics-pcb-rework branch.


Clarify GitHub Actions webhooks limit

Why:
Closes: https://github.com/github/docs/issues/35447

What's being changed (if available, include any code snippets, screenshots, or gifs):

Check off the following:

[ ] A subject matter expert (SME) has reviewed the technical accuracy of the content in this PR. In most cases, the author can be the SME. Open source contributions may require a SME review from GitHub staff.
[X] The changes in this PR meet the docs fundamentals that are required for all content.
[ ] All CI checks are passing.

@alxch- Thanks so much for opening a PR! I'll get this triaged for review ✨

Hjj

Thanks for opening a pull request! We've triaged this issue for technical review by a subject matter expert 👀


Prevent parseForESLint() behavior from changing after parse() is called

(fixes https://github.com/babel/babel-eslint/issues/558, fixes https://github.com/eslint/eslint/issues/9767)
This updates the parseForESLint implementation to still provide custom visitorKeys/scopeManager objects even after parse() has been called before (and eslint-scope has been monkeypatched).
The custom scopeManager should not be affected by the legacy monkeypatching to eslintScope.analyze and estraverse.VisitorKeys, because it does not use either of them.

Actually, this is probably not correct (see https://github.com/babel/babel-eslint/issues/558#issuecomment-353821396). Closing.

I think I fixed the issue. I also updated the regression tests to check both old and new versions of ESLint.
I realized that it was necessary for babel-eslint to use a global when monkeypatching eslint-scope, because it can't modify parserOptions (since ESLint clones them here), and ESLint would always default to sourceType: script and ecmaVersion: 5 here.
Unfortunately, this makes eslint-scope effectively useless for all other modules after babelEslint.parse is called, because it doesn't use the provided options. (Actually, this was already a problem in previous versions of ESLint if another parser was being used at the same time as babel-eslint.) Separately from this change, maybe it would be a good idea to release a major version of babel-eslint that removes all of the monkeypatching, so that it doesn't break other parsers when eslint-plugin-import causes it to monkeypatch things.

I have a concern about tests. Most test cases look to be run after monkey-patched. I'm writing improvement...

I updated this PR about two things:

I separated monkey-patching to lib/patch-eslint-scope.js then made it applies the patch of escope.analyze for each parserOptions. Then eslintOptions global state was removed.
I modified npm test script to test three cases properly:

<EMAIL_ADDRESS>normally. (mocha)
<EMAIL_ADDRESS>after patched. (mocha --require test/fixtures/preprocess-to-patch.js)
<EMAIL_ADDRESS>(mocha --require test/fixtures/use-eslint-old.js)

@not-an-aardvark Please check it.

LGTM

Thank you for all your work!


Broker InstanceName Problem

if I set
./pinot-admin.sh StartBroker -brokerPort 8099 -zkAddress "localhost:2181" -brokerInstName "MyNameIsBroker"

Then I received Exception below:
ZKExceptionHandler - Exception while invoking init callback for listener:com.linkedin.pinot.broker.broker.helix.LiveInstancesChangeListenerImpl@50b7114a
java.lang.ArrayIndexOutOfBoundsException: 1
	at com.linkedin.pinot.broker.broker.helix.LiveInstancesChangeListenerImpl.onLiveInstanceChange(LiveInstancesChangeListenerImpl.java:75)
	at org.apache.helix.manager.zk.CallbackHandler.invoke(CallbackHandler.java:173)
	at org.apache.helix.manager.zk.CallbackHandler.init(CallbackHandler.java:324)
	at org.apache.helix.manager.zk.CallbackHandler.<init>(CallbackHandler.java:114)
	at org.apache.helix.manager.zk.ZKHelixManager.addListener(ZKHelixManager.java:299)
	at org.apache.helix.manager.zk.ZKHelixManager.addLiveInstanceChangeListener(ZKHelixManager.java:318)
	at com.linkedin.pinot.broker.broker.helix.HelixBrokerStarter.<init>(HelixBrokerStarter.java:120)
	at com.linkedin.pinot.tools.admin.command.StartBrokerCommand.execute(StartBrokerCommand.java:98)
	at com.linkedin.pinot.tools.admin.PinotAdministrator.execute(PinotAdministrator.java:85)
	at com.linkedin.pinot.tools.admin.PinotAdministrator.main(PinotAdministrator.java:94)

So is this an issue?

We assume that the instance names always start with "Broker_" or "Server_" and contain the instance's address and port; we'll come up with a resolution for this.

Tracked internally as PINOT-1658.
The workaround is to use a broker instance name of the form "Broker_address_port" and the default should be fine. Can you check if this issue happens if your broker instance name is something like "Broker_<IP_ADDRESS>_8099"?

I didn't set broker name that starts with "Broker_" , I just set randomly . I know the reason, thanks


Issue with two way data binding not syncing

I'm using your solution in a simple form with 2-way data binding. I have several select drop-downs each containing the same choices. When a user selects an option within SelectA I need to check and deselect the same option from the other drop-downs. To try and achieve this goal I hooked into the (selected) event and altered the properties that are bound to. Unfortunately the changes are not reflected in the DOM. My DOM elements are defined in a loop as follows:
<ng-select name="{{ chosenAssets[asset.id] }}" id="{{ chosenAssets[asset.id] }}"
    [options]="options"
placeholder="Select one"
multiple="true"
(selected)="selected($event, asset.id)"
[(ngModel)]="chosenAssets[asset.id]"
[ngModelOptions]="{standalone: true}"
>
</ng-select>

Any advice?

Sorry, from this little piece of code I cannot tell if this is an issue in the select component or in your code, nor can I help in solving your issue. Either prepare a concrete example showing an issue in the select component, or expand the question (show more code) and ask a question on for example stackoverflow.
Instead of using the selected event, you can use ngModelChange when using two-way data binding.

It's possible to dynamically change values of other drop-downs based on events from one.  I suggest not using ngModel and doing it imperatively.

Maintain class level references to your drop-down options:

private dropdown1Options;
private dropdown2Options;

Initialise these in ngInit()

Setup a selected event: (selected)="selected($event)"

In your selected() function you can get the value of the event and then filter out from the options:

selected(item: any) {
    this.dropdown2Options = this.dropdown2Options.filter( each => {
        return each.id !== item.value
   }
}


Chromakey Filter

Hi @mat-sz ,
I am trying to add the chromaKey filter, which requires two Channel, (iTexture is already defined in fxGlue library and works with the current layer).
How do I add the other channel which is on another layer?
ShadartoyEffect: https://www.shadertoy.com/view/XsfGzn
Steps:

Made changed toabove shaderToy by replacing the channel0 with iTexture, fragColor -> gl_FragColor and other changes as mentioned in fxGlue
No GlueProgramError when adding the shadar.
The only issue is with how to pass the two-channel, I have replaced both channel(0 and 1) with iTexture.

Thanks for your help.

@mustafamasvi This might be useful if the replaced color would just become transparent instead of selecting another texture. I'll look into this.


Closing a websocket that is never in a stable connected state

If websocket is never in a stable connected state and user wants to disconnect websocket, then reconnecting websocket would never stop reconnecting.
Example:
Back end sends disconneting message and closes websocket.
ws.onclose is called before this.close is called then forcedClose was never set true.

also fixed the grunt task


Article of cryptocurrency is added

I have created the article on the topic Cryptocurrencies and blockchain, do check it out @ swoyam2609 n allow my Pull-Request.

Keep Contributing...


Mention with HTML tags aren't escaping

When you start typing something such as <a href="#">hello, the rendered text starts to generate the anchor tag.

This should only be escaping our @mention use cases, and not for raw HTML such as anchors.  This also seems to happen on other tags as <em>, <strong>, and a few others that may be going into $element.next().html(html); in render (https://github.com/angular-ui/ui-mention/blob/master/src/mentionController.es6.js#L75)
You can see the text being italicized/bolded if you remove this rule from the highlight div: color: transparent

Could this possibly work?
 this.render = function () {
    var html = arguments.length <= 0 || arguments[0] === undefined ? ngModel.$modelValue : arguments[0];

    html = (html || '').toString();

+    var entityMap = {
+      "&": "&",
+      "<": "<",
+      ">": ">",
+      '"': '"',
+      "'": ''',
+      "/": '/'
+    };
+
+    // escape these html characters into entities
+    html = String(html).replace(/[&<>"'\/]/g, function (s) {
+        return entityMap[s];
+    });
+
+    // transform the mentions and wrap them into unescaped `<span>` tags
    _this2.mentions.forEach(function (mention) {
      html = html.replace(_this2.encode(mention), _this2.highlight(mention));
    });
    $element.next().html(html);
    return html;
  };

the escaping function was pulled out of mustache.js (https://github.com/janl/mustache.js/blob/master/mustache.js#L82) as I was reading this (http://stackoverflow.com/questions/14462612/escape-html-text-in-an-angularjs-directive/28537958#28537958)

Have you tried hotpatching the render function in your wrapper directive?

Like this:
var render = uiMention.render.bind(uiMention);
uiMention.render = function(html) {
  html = html || ngModel.$modelValue;
  if (typeof html == 'string')
    html = replace(html);
  render(html);
}

hm... so I tried this:
        var render = uiMention.render.bind(uiMention);
        uiMention.render = function(html)
        {
          html = html || uiMention.$modelValue;

          var entityMap = {
            "&": "&",
            "<": "<",
            ">": ">",
            '"': '"',
            "'": ''',
            "/": '/'
          };

          html = String(html).replace(/[&<>"'\/]/g, function(s)
          {
            return entityMap[s];
          });

          render(html);
        }

however, it won't render the mentions until i type another character.  This leads me to believe that the hotpatching occurs AFTER the base render method.

Hmm yeah since anyone could type in HTML this should probably be fixed in core.

I can make a PR for this, it would be the first codeblock I mentioned above.

yeah

Just noticed this issue, I just submitted a PR with a fix for this. See #26

Fixed by #26


New version of the bot errors out on old working config

$ python lendingbot.py
Welcome to Lending Bot on POLONIEX
2018-02-11 12:15:20 Error frrasmin
Traceback (most recent call last):
File "lendingbot.py", line 94, in
Lending.lend_all()
File "/home/skosoy/Desktop/poloniexlendingbot/modules/Lending.py", line 252, in lend_all
usable_currencies += lend_cur(cur, total_lent, lending_balances, ticker)
File "/home/skosoy/Desktop/poloniexlendingbot/modules/Lending.py", line 433, in lend_cur
cur_min_daily_rate = get_min_daily_rate(active_cur)
File "/home/skosoy/Desktop/poloniexlendingbot/modules/Lending.py", line 285, in get_min_daily_rate
cur_min_daily_rate = get_frr_or_min_daily_rate(cur)
File "/home/skosoy/Desktop/poloniexlendingbot/modules/Lending.py", line 268, in get_frr_or_min_daily_rate
frrasmin = coin_cfg[cur]['frrasmin']
KeyError: 'frrasmin'
v316
Unhandled error, please open a Github issue so we can fix it!
2018-02-11 12:15:22 bye
bye

'Error frrasmin' - I have same error.

Same error coming up here.

Similar here:
I have #frrasmin commented
Welcome to Lending Bot on POLONIEX
2018-02-14 16:37:10 Error 'bool' object is not iterable
Traceback (most recent call last):
File "lendingbot.py", line 94, in
Lending.lend_all()
File "/home/leo/python/poloniexlendingbot/modules/Lending.py", line 252, in lend_all
usable_currencies += lend_cur(cur, total_lent, lending_balances, ticker)
File "/home/leo/python/poloniexlendingbot/modules/Lending.py", line 449, in lend_cur
orders = construct_orders(active_cur, active_bal, active_cur_total_balance, ticker)  # Build all potential orders
File "/home/leo/python/poloniexlendingbot/modules/Lending.py", line 350, in construct_orders
top_rate, bottom_rate = get_gap_mode_rates(cur, cur_active_bal, cur_total_balance, ticker)
File "/home/leo/python/poloniexlendingbot/modules/Lending.py", line 397, in get_gap_mode_rates
for coin in ticker:
TypeError: 'bool' object is not iterable
v317
Unhandled error, please open a Github issue so we can fix it!

Issue is related to coin config and latest frr as min change, specific line:
https://github.com/BitBotFactory/poloniexlendingbot/blob/fcd3fbb83797cb636a55b9059d8273b071c2beaa/modules/Lending.py#L268
Assumes that frrasmin is present.

Are you using "old" coinconfig line configuration?

remove and re-install again. and use new default.cfg.
But It has same bug.

@Nitro888  are you using coinconfig line configuration?

you mean this line?
'coinconfig = ["BTC:0.18:1:0:0:0","CLAM:0.6:1:0:0:0"]'
yes i'm using it.  is this old?

"oldish", anyway the implementation of frrmin didn't take this into consideration, use the segment coin config.
We will remove the coincfg one line in the future anyway.

Thanks. It works.

That's great, I made a PR and coinconfig will be removed from the configuration options.


Invalid value when you point the mouse at a variable

Does this issue occur when all extensions are disabled?: No, but the problem occurs in various extensions (Go, C/C++)

VS Code Version:

Version: 1.75.0 (Universal)
Commit: e2816fe719a4026ffa1ee0189dc89bdfdbafb164
Date: 2023-02-01T15:24:42.903Z
Electron: 19.1.9
Chromium: 102.0.5005.194
Node.js: 16.14.2
V8: <IP_ADDRESS>-electron.0
OS: Darwin x64 22.2.0
Sandboxed: No

OS Version: macOS Ventura 13.1

Steps to Reproduce:

Define a variable or constant and comment it out
Redefine the same variable with different value line below
Use variable in your app
When you point the mouse at a variable, you will see an invalid value

Please file this on the go extension repo, thanks


SLING-6851 - Add Healthcheck Api to healthcheck karaf feature.

With the upcoming migration to git this repository will be deleted. If the pull request contains data that should be re-submitted I suggest that you save the changes locally and resubmit them after the migration, which will likely happen on Monday the 9th of October.


WIP: [htlcswitch] fwdpkg/resolution cleanup

STILL IN PROGRESS, NEEDS TESTING
should get rid of:
2018-07-27 20:23:25.255 [ERR] HSWC: ChannelLink(528615:1949:1) Failing link: unable to settle incoming HTLC: No HTLC with ID

2018-07-27 20:23:25.255 [ERR] HSWC: ChannelLink(528615:1949:1) unable to fail incoming HTLC: No HTLC with ID

Depends on:

[ ] #1747
[x] #1748

Split out two portions of this PR, #1747 and #1748, into their own PRs to ease review.

Rebased now that #1748 is in master


Add command to show status of copy

Suggestion to include the following command to see the status of the copy.
Get-AzStorageBlobCopyState -Container $storageContainerName -Blob $destinationVHDFileName -Context $destinationContext

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 07bf8ea7-91db-de43-acf1-af16543971fd
Version Independent ID: 22c2d984-0d21-b8f8-905a-dd173c171f86
Content: Export/Copy snapshot as VHD to a storage account in different region - PowerShell Sample
Content Source: articles/virtual-machines/scripts/virtual-machines-windows-powershell-sample-copy-snapshot-to-storage-account.md
Service: virtual-machines-windows
GitHub Login: @ramankumarlive
Microsoft Alias: ramankum

@rphoon
Thanks for the feedback! I have assigned the issue to content author to check and update the document as appropriate.

@ramankumarlive
Can you please check and add your comments on this doc update request as applicable.

@roygara to get the doc updated.

We are currently cleaning up old issues and closing out items that are greater than 90 days old. If an issue is still present, please open a new feedback item on the document so we can prioritize correctly.
#please-close


import importlib.util needed on 3.11

I went ahead and added an if statement which opens support for 3.10, 3.11, and 3.12. I'll go ahead and close this out.


fix: #6465

Description of change
The main problem in #6271 is currentFrame.
currentFrame is 0 when _currentTime > _textures.length.
So I put some restrictions on it.
Pre-Merge Checklist

[ ] Tests and/or benchmarks are included
[ ] Documentation is changed or added
[x] Lint process passed (npm run lint)
[x] Tests passed (npm run test)

Codecov Report

Merging #6487 into dev will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##              dev    #6487   +/-   ##
=======================================
  Coverage   80.14%   80.14%
=======================================
  Files          57       57
  Lines        2825     2825
=======================================
  Hits         2264     2264
  Misses        561      561

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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lgtm - but is there a unit test that can cover why this fix works, and the current code doesn't? https://github.com/pixijs/pixi.js/pull/6274 may have introduced this issue whilst fixing another, but it did also include lots of nice unit tests to narrow down expected behaviour

I agree with @themoonrat. Can you make a test please @JetLua?

@bigtimebuddy @ivanpopelyshev @themoonrat Updated PR and description.

I like the test!

I like the test!
Wait, I saw 2 and 1 somehow, in fixed version. Do you have pixijs build somewhere that we can reference from that playground? Also, even if you specify settings in playground - modify code, and press "save" or it wont be really saved. Its buggy.

Yes, the custom url did not take effect.
https://static.lufei.so/tmp/pixi.js

Checks out https://jsfiddle.net/bigtimebuddy/qwo32ph9/5/


Fix slug generation for uppercase branch names

There is another issue with slugs that was raised in #1176. The current implementation turns uppercase letters into dashes so that SomeChar-charclass as branch name results in -ome-har-charclass as slug. However our regex in the URLs don't allow leading dashes.
This PR changes the algorithm to strip punctuation from the generated slug. It includes a migration to fix the currently broken slugs. I tested locally that pypy's version page works after applying it.

Excellent, looks good


switch to msgpack (or something similar)

msgpack, capnproto, whatevah

This is msg pack library looks really nice and has a good example.
https://github.com/3Hren/msgpack-rust

What part of the protocol did want switched over the msgpack? The (nonce, payload) part?

@zmanian I'm thinking more the file descriptor/metadata message that's sent before the data blocks start coming in. This is kind of in anticipation of having more complex data structures when recursive folder downloading is implemented.
Keeping the (nonce, payload) structure for the crypto layer is probably fine as-is for now, I agree.


return in call + call &self test

The original call implementation suppose the called method gets atoms and returns atoms, so no additional wrapping/unwrapping is required. If it is not convenient for a specific scenario then we need specific call version which unwraps arguments and wraps the result.

The original call implementation didn't return any result at all. So, this is an extension of its functionality - not replacement. And while we don't have other use cases, I prefer the extension, which is needed right now.


Optimize JLS file responsiveness for small files

Version: 0.8.3 and earlier
Platforms: all
The JLS file format is capable of storing and accessing long data captures with reasonable performance.  However, it is not too much faster with small files than it is with big files.  For files that can fit entirely in RAM, the UI should just load them into RAM.  The UI could have a preference for the maximum amount of data to load into RAM.

Fixed in 1.0.0 with JLS v2 for save/load.


style shown in document

This is a...

[ ] Feature Request
[x] Bug Report

Problem:
{: style="max-width: 50%" } is shown in pods-overview and pods page below the image
Proposed Solution:
Page to Update:
https://kubernetes.io/docs/concepts/workloads/pods/pod-overview/
https://kubernetes.io/docs/concepts/workloads/pods/pod/

1.10v

/cc @chenopis, @mistyhacks


Revert "nixos/systemd: Handle template overrides"

This reverts commit e3b90b6ccc4cf4147fd01df1ed8779b1c85744bd.
That commit broke nixos-container start and thus breaks tests which depend on that command, in particular the test containers-ip.nix which prevents channels nixos-unstable and nixos-unstable-small from advancing.

Motivation for this change
Unblock nixos-unstable and nixos-unstable-small.
Things done

[x] Tested using sandboxing (nix.useSandbox on NixOS, or option sandbox in nix.conf on non-NixOS linux)
Built on platform(s)

[x] NixOS
[ ] macOS
[ ] other Linux distributions

[x] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[x] Tested compilation of all pkgs that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review wip"
[ ] Tested execution of all binary files (usually in ./result/bin/)
[ ] Determined the impact on package closure size (by running nix path-info -S before and after)
[ ] Ensured that relevant documentation is up to date
[x] Fits CONTRIBUTING.md.

CC @adrianparvino @flokli @vcunat

Thanks for this. I'm also investigating this myself. The container module doesn't seem to handle having template overrides well.

I merged this in - we can bring it back once we figured out how we don't break the container module. Too bad actually testing channels is somewhere buried deep in hydra, and not easily exposed as an attribut.

The set for nixos-unstable is probably too large to run in most of local configurations.

For reference, individual (matching-platform) tests are fairly easy now, I believe:
nix build -f. nixosTests.containers-ip


Reports (management APIs)

@jgrim is still up to date? As all the management is already done.

@Pdzly I don't think so. I think some of the issue statuses got messed up with the migration.


Peer review (vertaisarviointi)

This peer review is made based of this commit: 80ab6650a3124400513e1ee4c4e4b4893ca1f9ce. (pulled on 16.10.2022 02:15)

I have to start by saying that I have never used rust in any way before (I have been programming in c++ before). I will comment more on the general project structure as in some cases I have no idea on what some parts of the code does.
Interesting project! I haven't really before thought about how to actually implement a parsing system for math notation, but It has come into my mind a few times out of curiosity.
Generic things I noticed
I started by reading through the readme and the linked user guide. The user guide was easy to follow and I got the application running really quickly even without any previous rust experience. I would suggest adding the other documents like the definition document too in the readme as they contain useful information about the project and it would be easier to know that they exists if there are direct links to them.
I would suggest adding equation history as I noticed very many times me trying to press the up arrow to get the latest command and fix a typo or similliar. Also maybe considering making for example .21 valid syntax as it is quite common to allow removing the leading zero on values between 0 and 1.
Also defining of functions doesn't work in the version I cloned because it complains that it is invalid syntax.
f(x)=x^2
'(' not allowed in function declaration!

Code review
I don't really have anything extra to say about the code itself. It looks like rust and the code structure looks sensible and somewhat easy to understand.
The code would probably be a bit easier to read if there were newlines between individual whatever these blocks are called
https://github.com/kbjakex/tiralab-calculator/blob/80ab6650a3124400513e1ee4c4e4b4893ca1f9ce/src/parser.rs#L57-L77
Because currently when scrolling through the code it looks like one big blob of code rather than individual code blocks for different situations.
Tests
The tests seem to be comprehensive and test vary many different situations. Also the automatic codecov action for tests is a good to have. When running the cargo test all tests passed quickly.
I didn't actually know or I never have thought about having tests inside the same file as the source code as I have done testing exclusively on javascript projects where there is usually a separate filename.test.js file for every file to be tested.

Thanks!
I just pushed a huge commit before you downloaded the project (I changed from 64-bit floats to multiple arbitrary-precision value representations, which introduced quite some complexity), so unfortunately you had to go through a bit of a mess. Glad to hear it was still a-okay. I was meaning to add a prebuilt release for you, but forgot, sorry - also glad you were able to run it fine anyways.

I would suggest adding the other documents like the definition document too in the readme

Noted, thanks

I would suggest adding equation history as I noticed very many times me trying to press the up arrow to get the latest command and fix a typo or similar.

This is tricky because it requires platform-specifics, as every console behaves differently. 100% agree this would be a big ergonomics improvement though. On the list of "if I find the time".

considering making for example .21 valid syntax

Fair, I'll add that

Also defining of functions doesn't work in the version I cloned because it complains that it is invalid syntax.

Waaaaaah! The previous reviewer had the same issue, yet it works for me on all the machines I test on.
What is this blasphemy
It's as if everybody else got a slightly different version of the project somehow but I'm sure that's not what's going on. Incredibly weird. Thanks for pointing this out again

The code would probably be a bit easier to read if there were newlines between individual whatever these blocks are called

Noted, I'll add those.
I'm really bummed functions are consistently broken for everybody else and I have no way to test this. Which OS are you on?

Feel free to ask more questions on what versions of what I am running to get the functions working. I can also run the code occasionally if I notice you asking for testing. Weird thing is that when running tests the function tests seem to run without any problems.

Thanks both! (was contacted thru Discord). Functions finally work in release mode as well.
Also integrated all of your suggestions: .<number> is now accepted, you can use up/down arrows to scroll history, and the link is now in the README.


haskell-packages: bring hoogle and haddock to the masses

With this, using ghcWithHoogle instead of ghcWithPackages does everything you'd expect it to do, and generates documentation indexes for all the packages.
When combined with the first patch from #9326 directing a browser of your choice to /run/current-system/sw/share/doc/hoogle/index.html brings up a module index (like https://downloads.haskell.org/~ghc/latest/docs/html/libraries/index.html) for all installed packages.
Also try adding this to ~/.ghc/ghci.conf:
:def hoogle \s -> return $ ":! hoogle search -cl --count=15 \"" ++ s ++ "\""
:def doc \s -> return $ ":! hoogle search -cl --info \"" ++ s ++ "\""

and then in ghci:
:hoogle a -> a
:doc a -> a

or maybe run
hoogle server -p 8080

and then navigate to http://localhost:8080/

The name ghcWithHoogle sounds strange. I'd prefer ghcWithPackagesAndHoogle. I see that it's a bit longish, though.

Yep, that was my concern too. But the absolutely correct name would be
ghcWithPackagesAndDocumentationIndexesAndHoogle, so I gave in to this,
since WithHoogle kinda sorta suggests a set of packages to be hoogled.

Maybe it's possible to find a name that's shorter than ghcWithPackagesAndDocumentationIndexesAndHoogle, but still more expressive than ghcWithHoogle? Those are not the only two choices, right? How about ghcWithPackagesAndHoogle?

If going in for a long name I'd suggest ghcWithPackagesAndIndexes
since both haddock indexes and hoogle databases are kinds of indexes.

Yeah, that sounds pretty nice -- it's fine with me.

Will you rename it, or should I?

I'll do it. I'll wait a day or two, though, so that I have some time to think about even better options.

I like ghcWithHoogle. It’s short, pregnant, and with good documentation should be clear.

@Profpatsch Would this #9946 be enough?

Verily.


fix Insert.on_conflict_do_nothing return type

Bump issue #212
Fix typing for dialects.postgresql.dml.Insert.on_conflict_do_nothing.

released as https://github.com/sqlalchemy/sqlalchemy2-stubs/releases/tag/v0.0.2a31


Add resnext29 to the model zoo

推荐使用英语模板 General question，以便你的问题帮助更多人。
首先确认以下内容

我已经查询了相关的 issue，但没有找到需要的帮助。
我已经阅读了相关文档，但仍不知道如何解决。

描述你遇到的问题
I tried to use resnext29 to classify Cifar100 dataset. I have added the following code in mmcls/models/backbones/resnet.py & resnext.py . And I met this bug in training.
Traceback (most recent call last):
File "tools/train.py", line 188, in
main()
File "tools/train.py", line 176, in main
train_model(
File "/home/user/mmclassification/mmcls/apis/train.py", line 192, in train_model
runner.run(data_loaders, cfg.workflow)
File "/home/user/anaconda3/envs/pytorch/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 127, in run
epoch_runner(data_loaders[i], **kwargs)
File "/home/user/anaconda3/envs/pytorch/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 50, in train
self.run_iter(data_batch, train_mode=True, **kwargs)
File "/home/user/anaconda3/envs/pytorch/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 29, in run_iter
outputs = self.model.train_step(data_batch, self.optimizer,
File "/home/user/anaconda3/envs/pytorch/lib/python3.8/site-packages/mmcv/parallel/data_parallel.py", line 75, in train_step
return self.module.train_step(*inputs[0], **kwargs[0])
File "/home/user/mmclassification/mmcls/models/classifiers/base.py", line 139, in train_step
losses = self(**data)
File "/home/user/anaconda3/envs/pytorch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/user/anaconda3/envs/pytorch/lib/python3.8/site-packages/mmcv/runner/fp16_utils.py", line 98, in new_func
return old_func(*args, **kwargs)
File "/home/user/mmclassification/mmcls/models/classifiers/base.py", line 83, in forward
return self.forward_train(img, **kwargs)
File "/home/user/mmclassification/mmcls/models/classifiers/image.py", line 137, in forward_train
loss = self.head.forward_train(x, gt_label)
File "/home/user/mmclassification/mmcls/models/heads/linear_head.py", line 78, in forward_train
x = self.pre_logits(x)
File "/home/user/mmclassification/mmcls/models/heads/linear_head.py", line 40, in pre_logits
x = x[-1]
IndexError: tuple index out of range
相关信息

pip list | grep "mmcv\|mmcls\|^torch" 命令的输出
mmcls                 0.21.0        /home/user/mmclassification
mmcv                  1.3.14
mmcv-full             1.4.2
torch                 1.9.1+cu111
torchaudio            0.9.1
torchvision           0.10.1+cu111

如果你修改了，或者使用了新的配置文件，请在这里写明

_base_ = [
    '../_base_/datasets/cifar100_bs16.py',
     '../_base_/default_runtime.py'
]

model = dict(
	type='ImageClassifier',
	backbone=dict(
	        type='ResNeXt',
	        depth=29,
	        num_stages=4,
	        out_indices=(3, ),
	        groups=8,
	        width_per_group=64,
	        style='pytorch'),
	neck=dict(type='GlobalAveragePooling'),
	head=dict(
	        type='LinearClsHead',
	        num_classes=100,
	        in_channels=2048,
	        loss=dict(type='CrossEntropyLoss', loss_weight=1.0),
	        topk=(1, 5),
	    ))

img_norm_cfg = dict(
    mean=[129.304, 124.070, 112.434],
    std=[68.170, 65.392, 70.418],
    to_rgb=False)

train_pipeline = [
    #dict(type='Resize', size=256, interpolation='bicubic'),
    dict(type='RandomFlip', flip_prob=0.5, direction='horizontal'),
    dict(type='RandomResizedCrop', interpolation='bicubic'),
    dict(type='Normalize', **img_norm_cfg),
    dict(type='ImageToTensor', keys=['img']),
    dict(type='ToTensor', keys=['gt_label']),
    dict(type='Collect', keys=['img', 'gt_label']),
]

test_pipeline = [
    #dict(type='Resize', size=224, interpolation='bicubic'),
    dict(type='Normalize', **img_norm_cfg),
    dict(type='ImageToTensor', keys=['img']),
    dict(type='Collect', keys=['img']),
]

data = dict(
    samples_per_gpu=128,
    # workers_per_gpu=2,
    train=dict(
        data_prefix='data/cifar/cifar-100-python'),
    val=dict(
        data_prefix='data/cifar/cifar-100-python'),
    test=dict(
        data_prefix='data/cifar/cifar-100-python')
)
#optimizer = dict(type='AdamW', lr=0.1, betas=(0.9, 0.999), eps=1e-08, weight_decay=0.0005, amsgrad=False)
optimizer = dict(type='SGD',lr=0.1,momentum=0.9, weight_decay=5e-4)
optimizer_config = dict(grad_clip=None)
lr_config = dict(policy='step', step=[150,225], gamma=0.1)
runner = dict(type='EpochBasedRunner', max_epochs=300)
checkpoint_config = dict(interval=5)

如果你是在训练过程中遇到的问题，请填写完整的训练日志和报错信息
2022-04-20 20:18:44,089 - mmcls - INFO - Environment info:

sys.platform: linux
Python: 3.8.11 (default, Aug  3 2021, 15:09:35) [GCC 7.5.0]
CUDA available: True
GPU 0: NVIDIA GeForce MX250
CUDA_HOME: /usr/local/cuda
NVCC: Build cuda_11.4.r11.4/compiler.30300941_0
GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
PyTorch: 1.9.1+cu111
PyTorch compiling details: PyTorch built with:

GCC 7.3
C++ Version: 201402
Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications
Intel(R) MKL-DNN v2.1.2 (Git Hash 98be7e8afa711dc9b66c8ff3504129cb82013cdb)
OpenMP 201511 (a.k.a. OpenMP 4.5)
NNPACK is enabled
CPU capability usage: AVX2
CUDA Runtime 11.1
NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86
CuDNN 8.0.5
Magma 2.5.2
Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.9.1, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON,

TorchVision: 0.10.1+cu111
OpenCV: 4.5.4
MMCV: 1.4.2
MMCV Compiler: GCC 7.3
MMCV CUDA Compiler: 11.1
MMClassification: 0.21.0+2037260
2022-04-20 20:18:44,089 - mmcls - INFO - Distributed training: False
2022-04-20 20:18:44,182 - mmcls - INFO - Config:
dataset_type = 'CIFAR100'
img_norm_cfg = dict(
mean=[129.304, 124.07, 112.434], std=[68.17, 65.392, 70.418], to_rgb=False)
train_pipeline = [
dict(type='RandomFlip', flip_prob=0.5, direction='horizontal'),
dict(type='RandomResizedCrop', interpolation='bicubic'),
dict(
type='Normalize',
mean=[129.304, 124.07, 112.434],
std=[68.17, 65.392, 70.418],
to_rgb=False),
dict(type='ImageToTensor', keys=['img']),
dict(type='ToTensor', keys=['gt_label']),
dict(type='Collect', keys=['img', 'gt_label'])
]
test_pipeline = [
dict(
type='Normalize',
mean=[129.304, 124.07, 112.434],
std=[68.17, 65.392, 70.418],
to_rgb=False),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
]
data = dict(
samples_per_gpu=128,
workers_per_gpu=2,
train=dict(
type='CIFAR100',
data_prefix='data/cifar/cifar-100-python',
pipeline=[
dict(type='RandomCrop', size=32, padding=4),
dict(type='RandomFlip', flip_prob=0.5, direction='horizontal'),
dict(
type='Normalize',
mean=[129.304, 124.07, 112.434],
std=[68.17, 65.392, 70.418],
to_rgb=False),
dict(type='ImageToTensor', keys=['img']),
dict(type='ToTensor', keys=['gt_label']),
dict(type='Collect', keys=['img', 'gt_label'])
]),
val=dict(
type='CIFAR100',
data_prefix='data/cifar/cifar-100-python',
pipeline=[
dict(
type='Normalize',
mean=[129.304, 124.07, 112.434],
std=[68.17, 65.392, 70.418],
to_rgb=False),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
],
test_mode=True),
test=dict(
type='CIFAR100',
data_prefix='data/cifar/cifar-100-python',
pipeline=[
dict(
type='Normalize',
mean=[129.304, 124.07, 112.434],
std=[68.17, 65.392, 70.418],
to_rgb=False),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
],
test_mode=True))
checkpoint_config = dict(interval=5)
log_config = dict(interval=100, hooks=[dict(type='TextLoggerHook')])
dist_params = dict(backend='nccl')
log_level = 'INFO'
load_from = None
resume_from = None
workflow = [('train', 1)]
model = dict(
type='ImageClassifier',
backbone=dict(
type='ResNeXt',
depth=29,
num_stages=4,
out_indices=(3, ),
groups=8,
width_per_group=64,
style='pytorch'),
neck=dict(type='GlobalAveragePooling'),
head=dict(
type='LinearClsHead',
num_classes=100,
in_channels=2048,
loss=dict(type='CrossEntropyLoss', loss_weight=1.0),
topk=(1, 5)))
optimizer = dict(type='SGD', lr=0.1, momentum=0.9, weight_decay=0.0005)
optimizer_config = dict(grad_clip=None)
lr_config = dict(policy='step', step=[150, 225], gamma=0.1)
runner = dict(type='EpochBasedRunner', max_epochs=50)
work_dir = './work_dirs/my_resnext29'
gpu_ids = [0]
2022-04-20 20:18:44,185 - mmcls - INFO - Set random seed to<PHONE_NUMBER>, deterministic: False
2022-04-20 20:18:44,443 - mmcls - INFO - initialize ResNeXt with init_cfg [{'type': 'Kaiming', 'layer': ['Conv2d']}, {'type': 'Constant', 'val': 1, 'layer': ['_BatchNorm', 'GroupNorm']}]
2022-04-20 20:18:44,638 - mmcls - INFO - initialize LinearClsHead with init_cfg {'type': 'Normal', 'layer': 'Linear', 'std': 0.01}
Name of parameter - Initialization information
backbone.conv1.weight - torch.Size([64, 3, 7, 7]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.bn1.weight - torch.Size([64]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.bn1.bias - torch.Size([64]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.0.conv1.weight - torch.Size([512, 64, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer1.0.bn1.weight - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.0.bn1.bias - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.0.conv2.weight - torch.Size([512, 64, 3, 3]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer1.0.bn2.weight - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.0.bn2.bias - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.0.conv3.weight - torch.Size([256, 512, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer1.0.bn3.weight - torch.Size([256]):
Initialized by user-defined init_weights in ResNeXt
backbone.layer1.0.bn3.bias - torch.Size([256]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.0.downsample.0.weight - torch.Size([256, 64, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer1.0.downsample.1.weight - torch.Size([256]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.0.downsample.1.bias - torch.Size([256]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.1.conv1.weight - torch.Size([512, 256, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer1.1.bn1.weight - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.1.bn1.bias - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.1.conv2.weight - torch.Size([512, 64, 3, 3]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer1.1.bn2.weight - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.1.bn2.bias - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.1.conv3.weight - torch.Size([256, 512, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer1.1.bn3.weight - torch.Size([256]):
Initialized by user-defined init_weights in ResNeXt
backbone.layer1.1.bn3.bias - torch.Size([256]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.2.conv1.weight - torch.Size([512, 256, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer1.2.bn1.weight - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.2.bn1.bias - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.2.conv2.weight - torch.Size([512, 64, 3, 3]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer1.2.bn2.weight - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.2.bn2.bias - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer1.2.conv3.weight - torch.Size([256, 512, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer1.2.bn3.weight - torch.Size([256]):
Initialized by user-defined init_weights in ResNeXt
backbone.layer1.2.bn3.bias - torch.Size([256]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.0.conv1.weight - torch.Size([1024, 256, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer2.0.bn1.weight - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.0.bn1.bias - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.0.conv2.weight - torch.Size([1024, 128, 3, 3]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer2.0.bn2.weight - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.0.bn2.bias - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.0.conv3.weight - torch.Size([512, 1024, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer2.0.bn3.weight - torch.Size([512]):
Initialized by user-defined init_weights in ResNeXt
backbone.layer2.0.bn3.bias - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.0.downsample.0.weight - torch.Size([512, 256, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer2.0.downsample.1.weight - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.0.downsample.1.bias - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.1.conv1.weight - torch.Size([1024, 512, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer2.1.bn1.weight - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.1.bn1.bias - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.1.conv2.weight - torch.Size([1024, 128, 3, 3]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer2.1.bn2.weight - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.1.bn2.bias - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.1.conv3.weight - torch.Size([512, 1024, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer2.1.bn3.weight - torch.Size([512]):
Initialized by user-defined init_weights in ResNeXt
backbone.layer2.1.bn3.bias - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.2.conv1.weight - torch.Size([1024, 512, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer2.2.bn1.weight - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.2.bn1.bias - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.2.conv2.weight - torch.Size([1024, 128, 3, 3]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer2.2.bn2.weight - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.2.bn2.bias - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer2.2.conv3.weight - torch.Size([512, 1024, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer2.2.bn3.weight - torch.Size([512]):
Initialized by user-defined init_weights in ResNeXt
backbone.layer2.2.bn3.bias - torch.Size([512]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.0.conv1.weight - torch.Size([2048, 512, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer3.0.bn1.weight - torch.Size([2048]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.0.bn1.bias - torch.Size([2048]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.0.conv2.weight - torch.Size([2048, 256, 3, 3]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer3.0.bn2.weight - torch.Size([2048]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.0.bn2.bias - torch.Size([2048]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.0.conv3.weight - torch.Size([1024, 2048, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer3.0.bn3.weight - torch.Size([1024]):
Initialized by user-defined init_weights in ResNeXt
backbone.layer3.0.bn3.bias - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.0.downsample.0.weight - torch.Size([1024, 512, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer3.0.downsample.1.weight - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.0.downsample.1.bias - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.1.conv1.weight - torch.Size([2048, 1024, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer3.1.bn1.weight - torch.Size([2048]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.1.bn1.bias - torch.Size([2048]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.1.conv2.weight - torch.Size([2048, 256, 3, 3]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer3.1.bn2.weight - torch.Size([2048]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.1.bn2.bias - torch.Size([2048]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.1.conv3.weight - torch.Size([1024, 2048, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer3.1.bn3.weight - torch.Size([1024]):
Initialized by user-defined init_weights in ResNeXt
backbone.layer3.1.bn3.bias - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.2.conv1.weight - torch.Size([2048, 1024, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer3.2.bn1.weight - torch.Size([2048]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.2.bn1.bias - torch.Size([2048]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.2.conv2.weight - torch.Size([2048, 256, 3, 3]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer3.2.bn2.weight - torch.Size([2048]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.2.bn2.bias - torch.Size([2048]):
The value is the same before and after calling init_weights of ImageClassifier
backbone.layer3.2.conv3.weight - torch.Size([1024, 2048, 1, 1]):
KaimingInit: a=0, mode=fan_out, nonlinearity=relu, distribution =normal, bias=0
backbone.layer3.2.bn3.weight - torch.Size([1024]):
Initialized by user-defined init_weights in ResNeXt
backbone.layer3.2.bn3.bias - torch.Size([1024]):
The value is the same before and after calling init_weights of ImageClassifier
head.fc.weight - torch.Size([100, 2048]):
NormalInit: mean=0, std=0.01, bias=0
head.fc.bias - torch.Size([100]):
NormalInit: mean=0, std=0.01, bias=0
2022-04-20 20:18:49,041 - mmcls - INFO - Start running, host: user@user-KLV-WX9, work_dir: /home/user/mmclassification/work_dirs/my_resnext29
2022-04-20 20:18:49,042 - mmcls - INFO - Hooks will be executed in the following order:
before_run:
(VERY_HIGH   ) StepLrUpdaterHook
(NORMAL      ) CheckpointHook
(LOW         ) EvalHook
(VERY_LOW    ) TextLoggerHook
before_train_epoch:
(VERY_HIGH   ) StepLrUpdaterHook
(LOW         ) IterTimerHook
(LOW         ) EvalHook
(VERY_LOW    ) TextLoggerHook
before_train_iter:
(VERY_HIGH   ) StepLrUpdaterHook
(LOW         ) IterTimerHook
(LOW         ) EvalHook
after_train_iter:
(ABOVE_NORMAL) OptimizerHook
(NORMAL      ) CheckpointHook
(LOW         ) IterTimerHook
(LOW         ) EvalHook
(VERY_LOW    ) TextLoggerHook
after_train_epoch:
(NORMAL      ) CheckpointHook
(LOW         ) EvalHook
(VERY_LOW    ) TextLoggerHook
before_val_epoch:
(LOW         ) IterTimerHook
(VERY_LOW    ) TextLoggerHook
before_val_iter:
(LOW         ) IterTimerHook
after_val_iter:
(LOW         ) IterTimerHook
after_val_epoch:
(VERY_LOW    ) TextLoggerHook
after_run:
(VERY_LOW    ) TextLoggerHook
2022-04-20 20:18:49,042 - mmcls - INFO - workflow: [('train', 1)], max: 50 epochs
2022-04-20 20:18:49,042 - mmcls - INFO - Checkpoints will be saved to /home/user/mmclassification/work_dirs/my_resnext29 by HardDiskBackend.

如果你对 mmcls 文件夹下的代码做了其他相关的修改，请在这里写明
【in mmcls/models/backbones/resnet.py】
arch_settings = {
29: (Bottleneck, (3, 3, 3)),
……}
【in mmcls/models/backbones/resnext.py】
arch_settings = {
……
29: (Bottleneck, (3, 3, 3)),
……}

29: (Bottleneck, (3, 3, 3))

need a 4-values tuple for ResNeXt.

But resnext29 has no conv_5 stage. Will  29: (Bottleneck, (3, 3, 3, 0))  make sence?

There're still something wrong with the model when using the code above. The model still has 4 layer and the accuracy is not good.


ref: some minor style fixes

Pull request checklist:

[X] CHANGELOG.md was updated, if applicable (n/a)

Description
xD

Replaced by later changes.


fix: Add 'live' argument to liquidityProvisionsConnection query

This will return only live LPs, which is the number we want (it should match the value in supplied stake).
This PR gets the correct number from the API - but does not resolve the decimal place issues for either the Total Staked or Fee - both of which will need a change on the healthbar component in the monorepo, which I'll follow this with.

https://deploy-preview-677--vega.netlify.app/liquidity-provision/ @JonRay15


workbench.action.quickOpenNavigatePreviousInFilePicker doesn't work on Shift+Tab

Does this issue occur when all extensions are disabled?: Yes

VS Code Version: 1.73.0
OS Version: Windows 10

Steps to Reproduce:

Enable Tab and Shift+Tab hotkeys in keybindings.json:

  {
    "key": "tab",
    "command": "workbench.action.quickOpenNavigateNextInFilePicker",
    "when": "inFilesPicker && inQuickOpen"
  },
  {
    "key": "shift+tab",
    "command": "workbench.action.quickOpenNavigatePreviousInFilePicker",
    "when": "inFilesPicker && inQuickOpen"
  },

Disable default hotkeys, to ensure no conflicts:

  {
    "key": "shift+tab",
    "command": "-acceptAlternativeSelectedSuggestion",
    "when": "suggestWidgetHasFocusedSuggestion && suggestWidgetVisible && textInputFocus"
  },
  {
    "key": "shift+tab",
    "command": "-acceptAlternativeSelectedSuggestion",
    "when": "suggestWidgetHasFocusedSuggestion && suggestWidgetVisible && textInputFocus"
  },
  {
    "key": "shift+tab",
    "command": "-insertPrevSuggestion",
    "when": "hasOtherSuggestions && textInputFocus && !inSnippetMode && !suggestWidgetVisible && config.editor.tabCompletion == 'on'"
  },
  {
    "key": "shift+tab",
    "command": "-jumpToPrevSnippetPlaceholder",
    "when": "editorTextFocus && hasPrevTabstop && inSnippetMode"
  },
  {
    "key": "shift+tab",
    "command": "-outdent",
    "when": "editorTextFocus && !editorReadonly && !editorTabMovesFocus"
  },

Then open quickOpen menu, also known as "Go to File..." (default shortcut Ctrl+P)
Try Tab and it works! Great.
Try Shift+Tab and it doesn't work...

Any other shortcuts do work for this action. For example if I rebind to Ctrl+Shift+Tab then it works. It's just by some reason Shift+Tab doesn't work, in particular.
As you can see, I don't have any other custom or default shortcuts for this, so there should be no conflicts:

Thanks for creating this issue! It looks like you may be using an old version of VS Code, the latest stable release is 1.88.0. Please try upgrading to the latest version and checking whether this issue remains.
Happy Coding!

Just updated VSCode to the latest, 1.88.0 – the issue preserves.

/duplicate https://github.com/microsoft/vscode/issues/98479

Thanks for creating this issue! We figured it's covering the same as another one we already have. Thus, we closed this one as a duplicate. You can search for similar existing issues. See also our issue reporting guidelines.
Happy Coding!


xff: add support for configuring a list of trusted CIDRs

Commit Message: xff: add support for configuring a list of trusted CIDRs
The original client IP address can be determined from the x-forwarded-for header either by a fixed number of trusted hops, or by evaluating the client IP address against a list of trusted addresses.
This adds support for configuring a list of CIDRs in the xff original IP detection extension. The remote IP address is evaluated against these, and optionally recurses through XFF to find the last non-trusted address.
Additional Description:
This feature is generally used by people with a CDN in front of their edge proxy to ensure that XFF is only parsed when the remote connection comes from a CDN server.
The behaviour of the new functionality should be the same as Nginx's realip module.
Disclaimer: This is my first time writing C++ so I'm not certain my changes are completely idiomatic, but I've tried to stick with existing style in the codebase. Feedback very welcome!
Risk Level: Medium
Testing: Unit tests, manual tests
Docs Changes: Updates to HTTP Connection Manager header manipulation docs, and proto docs.
Release Notes: Added to changelogs/current.yaml
Platform Specific Features: None
Fixes #21639
Relates to #31296

/lgtm api

Apologies for the delay in pushing updates. I got caught in the weeds a bit trying to understand some of the internals.
I think I've addressed all of Alyssa's feedback, and I added more documentation and examples to headers.rst.
The one change I'm not sure about is a587a23d55ca8d042250c87b33d1d7db3af4f138 - I've tried to understand what "internal" means to Envoy and I still can't say I'm 100% sure. PR #2232 added some comments about it needing to be a single IP in XFF, so I've made a similar change here but I don't feel quite right about it.

Can you merge main?
/wait

Can you merge main?

Done.

/retest

Argh sorry I think the CI issue is real since some of this code goes in the mobile build which doesn't use exceptions. Can you take a look? Hopefully it will be an easy fix.
/wait

Argh sorry I think the CI issue is real since some of this code goes in the mobile build which doesn't use exceptions. Can you take a look? Hopefully it will be an easy fix.

Ah, I meant to follow up on this one, I noticed that failure too. I could use some advice here actually. In an earlier change I had the constructor for the xff extension forcibly setting xff_num_trusted_hops to 0 when xff_trusted_cidrs was set, but Alyssa recommended logging an exception instead.
What's the best way to fix this to work for mobile, do you think? Should I set it back to overwriting the value and logging it, or is there another way to make it fail that works for Mobile?

What's the best way to fix this to work for mobile, do you think? Should I set it back to overwriting the value and logging it, or is there another way to make it fail that works for Mobile?

Probably the best way would be to somehow make this code return an error and then somehow fail with an exception outside in the server (non mobile code) but we probably will need to ask @alyssawilk about this tomorrow when she is around.

Digging through the codebase a bit, I think I could either:

ENVOY_LOG(warn, "setting both xff_num_trusted_hops and xff_trusted_cidrs is not recommended"); or
Revert some of d976354a8906b186d4b01f2ab995594b2cca5933 and:

Force set xff_num_trusted_hops_ to 0 when has_xff_trusted_cidrs()
ENVOY_LOG(error, "cannot set both xff_num_trusted_hops and xff_trusted_cidrs; xff_num_trusted_hops is ignored")

Hey folks, any feedback to which approach I should take here? Thanks!

Not stale, waiting for feedback! But I'm also trying to find other examples in the codebase that do similar things, but there's a lot of code to examine...

Can we keep this open and get it reviewed? @alyssawilk @mattklein123

I put it back into draft because I need to make some more changes but I haven't had the time. I'm hoping to get back to it soon.

Please keep this open, also Happy 4th of July! 🇺🇸

Sorry for the long delay here. Life kind of got in the way and it took me some time to trawl through existing code to see if there was an existing pattern for handling the case on mobile to remove the throw. All tests are passing now, hopefully this covers the last of the feedback.

hm, CI looks wedged.  can you do a main merge - maybe sorting current.yaml will fix?

/retest

Maybe a maintainer needs to run that? :-) Seems like CI got wedged.

/retest

/wait

/retest

Sorry for the delay. Some times I may ignore the notification from tools. It's OK to ping me directly on slack.

/wait


Update CommandBars to NuGet package

Update the Microsoft.VisualStudio.CommandBars reference to be a
NuGet package reference.

Thank you


MicroProfile Metrics 3.0 Specification Review

Specification issue template
When creating a specification project release review, create an issue in the MicroProfile-WG repository repo with the content defined as follows.

[x] Specification name and version: MicroProfile Metrics V3.0
[x] Add the label Release Review
[x] Naming conventions for artifacts:

[x] Specification PDF in the form of microprofile-project-spec-version.pdf
[x] Specification HTML in the form of microprofile-project-spec-version.html
project is the microprofile specification short project name (config, health, ...)
version is the two digit x.y version of the specification

[x] The Nexus Staging links (orgeclipsemicroprofile-NNNN where NNNN is the staging repository id) (eg, https://oss.sonatype.org/content/repositories/orgeclipsemicroprofile-NNNN/org/eclipse/microprofile/config/) which contain all the binaries and relevant documentation:

[x] Staging Repo
[x] Spec PDF
[x] Spec HTML
[x] Javadoc
[x] API Jar
[x] API TCK Jar
[x] REST TCK Jar
[x] Optional TCK Jar

[x] A link in the Eclipse downloads sections is still available for specs and apidocs:

[x] https://download.eclipse.org/microprofile/staging/microprofile-metrics-3.0/
[x] An apidocs directory containing the javadoc associated with the API jar.

[x] Summary that a Compatible Implementation is complete, passes the TCK, and that the TCK includes sufficient coverage of the specification.

[x] [Compatible Certification Request] (https://github.com/eclipse/microprofile-metrics/issues/623)

[x] Release Review

[x] Follow governance process and create/update release record

Component Release Record

[x] Email to PMC (more info here)
[x] Start release review by emailing EMO (more info here)(Track the bug issue created by EMO after the email)
[x] A member of Steering/Spec Committee initiates the ballot by sending an email to [microprofile-wg]<EMAIL_ADDRESS>(more info here
[x] Result ballot notification - https://docs.google.com/document/d/1wISp-yRzQZNOHULNekxxg1U18be3v-3CRUswklcpmr8/edit

hola Don,  @donbourne,
we forgot to include the final step, the Result Ballot notification after the initiated ballot is sent.
can you you add the step to Metrics?  https://docs.google.com/document/d/1wISp-yRzQZNOHULNekxxg1U18be3v-3CRUswklcpmr8/edit
:) thank YOU! the general template needs to be adjusted as well. :)

hey Amelia @aeiras , I've added that to the end per your comment.

Amazing Don, thank you!

+1

@donbourne I just commented on the CCR that the CI used for the testing needs to be a "permanent" artifact and not just a nightly driver that would be difficult to reproduce in the future.

@kwsutter , we intended for the nightly driver to be stored as a permanent artifact, but messed that up and the driver was deleted.  We've rerun the TCK on a newer driver which we're copying for permanent storage and will update the CCR with that URL once it's in place.

@kwsutter , the problem with the CCR pointing to a non-permanent driver has been resolved.  It now points to a downloadable driver that should be there "permanently".

MP Metrics 3.0 has been released


Update en.toml

change time

Hello @sonjaisw, can you explain the purpose of your PR? Your change doesn't make a complete sentence.


Fix device login link

@noelbundick,
Thanks for your contribution as a Microsoft full-time employee or intern. You do not need to sign a CLA.
Thanks,
Microsoft Pull Request Bot

@noelbundick : Thanks for your contribution to the Azure documentation! The author, @v-chenyh, has been notified to review your proposed change.

#sign-off


new: added kmod example source file.

No CI for now. @alexellis i can add a small ci job that eg: runs weekly to test that we can still build the small kmod example on an actuated node.

I've just merged the PR, so you should be able to see the action now?

Ah, you didn't include a GitHub Action. Could you do so please?

Ah, you didn't include a GitHub Action. Could you do so please?

Yes, on push to master, right?


Jonas picture

@coroa could you send me a picture of you? or add one to your section?

Just stumbling over this again:

great thanks!


Do not crash on unnamed double splat argument

Description
Handle double splats in more safe manner, and do not crash on unnamed double splat arguments like this:
def example(**)
end

Describe your pull request and problem statement here.
Completed Tasks

[x] I have read the Contributing Guide.
[x] The pull request is complete (implemented / written).
[x] Git commits have been cleaned up (squash WIP / revert commits).
[x] I wrote tests and ran bundle exec rake locally (if code is attached to PR).

I'm not sure why rubocop raises so much offenses, but I haven't add any new.


Don't fail DiscoveryClient when curator throws NoNodeException.

https://github.com/spring-cloud/spring-cloud-netflix/issues/2269#issuecomment-374262975

Closed via dab8f973a577d9293e8c6620f0046aa90c1df9fa

Is there any estimate, when new 2.0 milestone with this fix will be released?

https://github.com/spring-cloud/spring-cloud-release/milestones?direction=asc&sort=due_date

it appears that when the topic does not exists this exception is thrown.


Updates to cancel dataset upload

Intermittently worked
No loading or progress bar, just hangs until it happens.
@javisantana

Could you please provide some steps to reproduce or a description of what what happened for "intermittently worked?"
Regarding not having a loading or progress bar: cancelling stops the UI polling immediately, so from the user standpoint it should appear to cancel instantly. What hangs, and what is the desired UI?

@mbforr @javisantana can one of you address the above comment?

All I had was that it sort of hung there sometimes and sometimes it worked.
The main thing was that when cancel was hit is that the cancel dialogue
held there for a while sometimes. We weren't able to directly replicate
that though.
On Thu, Jun 16, 2016 at 9:20 AM, Andrew Fink<EMAIL_ADDRESS>wrote:

@mbforr https://github.com/mbforr @javisantana
https://github.com/javisantana can one of you address the above
comment?
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/cartodb-org/cartodb/issues/26#issuecomment-226482563,
or mute the thread
https://github.com/notifications/unsubscribe/AEmtLI_kVPjtVceJsPfNRjVNI5qA0orLks5qMU2RgaJpZM4Iasf9
.

--
Matt Forrest
Client Success Manager
CartoDB
201 Moore St, Brooklyn, NY, 11206, USA
T:<PHONE_NUMBER> Skype: mbforr
W: www.cartodb.com
Live sessions to learn CartoDB http://cartodb.com/webinars/

After a discussion with Matt, this maybe related to delay in the PUT request to cancel the job. We're going to close this for now, future improvements could include a spinner until the UI receives a 200 back on the request to cancel.


fix json syntax error in error api spec

Codecov Report

Merging #3658 (8628eab) into main (0eca211) will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##             main    #3658   +/-   ##
=======================================
  Coverage   56.58%   56.58%
=======================================
  Files         103      103
  Lines        7520     7520
=======================================
  Hits         4255     4255
  Misses       2596     2596
  Partials      669      669

Continue to review full report at Codecov.

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Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 0eca211...8628eab. Read the comment docs.


About Smart Indent

Hi.
I'm a student using wandbox.
I just write this to ask something about 'Smart Indent' in editor.
There are lots of tabs on next line that 'Smart Indent' is checked, but I don't remember when the error occured and why. It works fine it is not checked.
I think Something wrong with stack counting '{' and '}'.
Thank you.
smidt.txt

Sorry I'm confused


is uv bug?

code at line 176,
float2 decalSpaceUV = decalSpaceScenePos.xy + 0.5;
if the cube has no roation, should decalSpaceScenePos.xy as decalSpaceScenePos.xz?

use .xy will make decal projection projects towards cube's forward direction

you can change to .xz if you like it

ok, thanks


Unable to get the docker container using MacOS

Hi, I'm trying to build hassos using MacOS. I have Docker installed, but when I run enter.sh file I get the following error:
$ sudo scripts/enter.sh
Password:
scripts/enter.sh: line 2: modprobe: command not found
Sending build context to Docker daemon  30.39MB
Step 1/6 : FROM ubuntu:18.04
Get https://registry-1.docker.io/v2/: net/http: request canceled while waiting for connection (Client.Timeout exceeded while awaiting headers)
Unable to find image 'hassbuildroot:latest' locally
docker: Error response from daemon: Get https://registry-1.docker.io/v2/library/hassbuildroot/manifests/latest: unauthorized: incorrect username or password.
See 'docker run --help'.

Do I need to move the enter.sh script to the root directory?

Just a quick follow up, I managed to get a build working in VirtualBox in the end, going to close this as I'm sure the devs have more important things to worry about!


Added Swift Package Manager support.

To get it work, I had to flatten the source files structure and conditionally alter getting paths to test resources when in the package.

I would want a way to prevent flattening of the source files first, especially for some of our more complex libraries.

Hey @bosborn, do you plan merging this to master branch?


merge package from arlac77/npm-package-template

package.json

chore(package<EMAIL_ADDRESS>chore(package<EMAIL_ADDRESS>chore(scripts): cover@#overwrite c8 --temp-directory build/coverage ava && c8 report -r lcov --temp-directory build/coverage
chore(package): add nyc from template
docs(package): remove keyword null
chore(package): set $.ava.require='esm' as in template
chore(package): set $.ava.files='tests/-test.js,tests/-test.mjs' as in template
chore(package): set $.ava.extensions='js,mjs' as in template

Codecov Report

Merging #661 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master     #661   +/-   ##
=======================================
  Coverage   92.91%   92.91%
=======================================
  Files           7        7
  Lines        1073     1073
=======================================
  Hits          997      997
  Misses         76       76

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Coverage remained the same at 89.74% when pulling 107f8eb2ce0e82bb3942cbf5fad5c6edd654d5d2 on template-sync-1 into 397a061be6977fc5b80a06ec2d075ad65f00fe14 on master.

:tada: This PR is included in version 5.0.0 :tada:
The release is available on:

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GitHub release

Your semantic-release bot :package::rocket:


Web ant93.2 2021 01 15

MSFT employees can try out our new experience at OpenAPI Hub  - one location for using our validation tools and finding your workflow.

Changelog
Please ensure to add changelog with this PR by answering the following questions.

What's the purpose of the update?

[ ] new service onboarding
[x] new API version
[ ] update existing version for new feature
[ ] update existing version to fix swagger quality issue in s360
[ ] Other, please clarify

When you are targeting to deploy new service/feature to public regions? Please provide date, or month to public if date is not available yet.
When you expect to publish swagger? Please provide date, or month to public if date is not available yet.
If it's an update to existing version,  please select SDKs of specific language and CLIs that require refresh after swagger is published.

[ ] SDK of .NET (need service team to ensure code readiness)
[ ] SDK of Python
[ ] SDK of Java
[ ] SDK of Js
[ ] SDK of Go
[ ] PowerShell
[ ] CLI
[ ] Terraform
[ ] No, no need to refresh for updates in this PR

Contribution checklist:

[ ] I commit to follow the Breaking Change Policy of "no breaking changes"
[ ] I have reviewed the documentation for the workflow.
[ ] Validation tools were run on swagger spec(s) and errors have all been fixed in this PR. How to fix?

If any further question about AME onboarding or validation tools, please view the FAQ.
ARM API Review Checklist

[ ] Ensure to check this box if one of the following scenarios meet updates in the PR, so that label “WaitForARMFeedback” will be added automatically to involve ARM API Review. Failure to comply may result in delays for manifest application. Note this does not apply to data plane APIs, all “removals” and “adding a new property” no more require ARM API review.

Adding new API(s)
Adding a new API version
[ ] Ensure to copy the existing version into new directory structure for first commit (including refactoring) and then push new changes including version updates in separate commits. This is required to review the changes efficiently.
Adding a new service

[ ] Please ensure you've reviewed following guidelines including ARM resource provider contract and REST guidelines. Estimated time (4 hours). This is required before you can request review from ARM API Review board.

[ ] If you are blocked on ARM review and want to get the PR merged with urgency, please get the ARM oncall for reviews (RP Manifest Approvers team under Azure Resource Manager service) from IcM and reach out to them.

Breaking Change Review Checklist
If there are following updates in the PR, ensure to request an approval from Breaking Change Review Board as defined in the Breaking Change Policy.

[ ] Removing API(s) in stable version
[ ] Removing properties in stable version
[ ] Removing API version(s) in stable version
[ ] Updating API in stable or public preview version with Breaking Change Validation errors
[ ] Updating API(s) in public preview over 1 year (refer to Retirement of Previews)

Action: to initiate an evaluation of the breaking change, create a new intake using the template for breaking changes. Addition details on the process and office hours are on the Breaking change Wiki.
Please follow the link to find more details on PR review process.

@weidongxu-microsoft Please review but not merge yet

@naveedaz
Please check "ModifiedOperationId" error in "Cross-Version Breaking Changes" (maybe more). This will be marked a breaking changes and would require board review.

If you have new API, please add ARM for review.

@naveedaz
Please check "ModifiedOperationId" error in "Cross-Version Breaking Changes" (maybe more). This will be marked a breaking changes and would require board review.

The change in the operation ID is fix an existing issue where the collection was incorrect named with prefix Get instead of List

@naveedaz
As long as it changes (and there is SDK released on the previous version), it will be a breaking changes, and you will need approval from Jeffrey.

@naveedaz
As long as it changes (and there is SDK released on the previous version), it will be a breaking changes, and you will need approval from Jeffrey.

@JeffreyRichter Can you please review and approve?

Complete list on breaking changes reported by CI https://dev.azure.com/azure-sdk/internal/_build/results?buildId=946994&view=logs&j=8f628bfe-7d8d-5bf3-e141-37106862c4f5&t=e8cd626d-0ee4-5bf1-69f3-fe7732da313d
"TypeChanged" can be ignored.

@ArcturusZhang and @msyyc for awareness on "CrossVersionBreakingChange"

Please go through the contribution checklist and ARM API Review Checklist added as part of the review and mark them completed. It will help you fix most of the issues and improve the quality of swagger and help close the PR faster. This is a requirement before review can be continued.

"/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Web/sites/{name}/slots/{slot}/basicPublishingCredentialsPolicies": {

The response for this API has nextLink defined in it, so I am guessing you have a pagable API. In that case, this definition requires below annotation:
  `  "x-ms-pageable": {
      "nextLinkName": "nextLink"
    }`

Same goes for "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Web/sites/{name}/basicPublishingCredentialsPolicies" API as well.

Refers to: specification/web/resource-manager/Microsoft.Web/stable/2021-01-15/WebApps.json:9189 in d1361d0. [](commit_id = d1361d07f3f49e2fe647e5d318bb20480a681d51, deletion_comment = False)

  "put": {

Could you add an example for this new operation? Or point me to it, if it's already created. There are many example files.

Refers to: specification/web/resource-manager/Microsoft.Web/stable/2021-01-15/WebApps.json:14959 in d1361d0. [](commit_id = d1361d07f3f49e2fe647e5d318bb20480a681d51, deletion_comment = False)

/azp run

@naveedaz Let me know when you need it merged (after ARM approval).


Problem with empty non-null values and UTF8

Hi,
I have a table with some fields filled with '' (it's not null) values in Oracle DB, and I can't change that. Your connector perfectly handles the update operations, but when I flush the SQL_REDO from the topic to my Postgres DB (also in UTF8), it fails with "PSQLException: ERROR: invalid byte sequence for encoding "UTF8": 0x00" because in topic, the values of those fields become '\u0000' instead of '' in Oracle. Is there any way to replace it with something like ' ', without modifying the source tables.
Thank you!

Hi,
After capturing data from Oracle , before populating this data to Postgres you can change captured data.Replace or rewrite is possible for SQL_REDO if you write some code .
But I think you mention , without writing code you would like to create topic messages as you like ?
Thanks

Thank you for clarification.
I could get rid of those '\u0000' by adding
sqlRedo = sqlRedo.replaceAll("[^\u0009\u000a\u000d\u0020-\uD7FF\uE000-\uFFFD]", " ");

The problem is solved, it was a data issue.
Thank you for robust, clear and fast connector.

Thank you very much.


Interested in my changes?

Hey @MarinX,
I've recently forked this repo and added a CI pipeline.
Exposed encryption and decryption using Scrypt Identities for a project I'm involved with.
Added tests for the new methods.
Added renovatebot.
Would you be interested in a PR for these changes?
Fork can be found at github.com/shift/agemobile :smile:

Cool raised as #3 :smile:


FLUME-3339: Remove xerces and xalan dependencies

Xerces and Xalan dependencies reference old versions, but actually aren't used and furthermore are only "provided" scope. Removed these dependencies.

Done in trunk.


chore: only reset previous segment on looping rundowns

What kind of change does this PR introduce? (Bug fix, feature, docs update, ...)

This is a bugfix.

What is the current behavior? (You can also link to an open issue here)

After playback of a segment ends, PartInstances inside are reset. This causes problems for timing in the GUI as reset PartInstances are not sent to the GUI and are not taken under consideration for timing purposes.

What is the new behavior (if this is a feature change)?

PartInstances inside segments that stop playing are only reset if the playlist is looping.

Other information:

Status

[ ] Code documentation for the relevant parts in the code have been added/updated by the PR author
[ ] The functionality has been tested by the PR author
[ ] The functionality has been tested by NRK

Codecov Report

Merging #507 (c346232) into release32 (fb9f9e4) will increase coverage by 33.28%.
The diff coverage is n/a.

:exclamation: Current head c346232 differs from pull request most recent head eb4e3dd. Consider uploading reports for the commit eb4e3dd to get more accurate results

@@               Coverage Diff               @@
##           release32      #507       +/-   ##
===============================================
+ Coverage      66.71%   100.00%   +33.28%
===============================================
  Files            245         2      -243
  Lines          14776        32    -14744
  Branches        3244         9     -3235
===============================================
- Hits            9858        32     -9826
+ Misses          4753         0     -4753
+ Partials         165         0      -165

Impacted Files
Coverage Δ

meteor/server/api/ingest/generation.ts

...server-core-integration/src/lib/corePeripherals.ts

meteor/server/api/translationsBundles.ts

...kages/server-core-integration/src/lib/ddpClient.ts

meteor/client/lib/data/mos/plugin-support.ts

meteor/server/api/playout/pieces.ts

meteor/lib/database.ts

meteor/server/codeControl.ts

meteor/server/security/system.ts

meteor/server/api/blueprints/context/context.ts

... and 232 more

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I have no problem with this short-term, but we should revisit it in future release.
I know that it has been discussed a few times to reset previous segments to minimise the amount of data the ui has to keep loaded, as well as to show the user the planned parts to aid in re-playing segments

Yes, let's revisit it fully at some point. With the current data structure, the PartInstances are the only source of timing information the GUI can use to calculate stuff. If we want to drop them, we need to replace them with something else.


java: cal+tz pickle results in wrong tz offset in python after unpickling

pickling a  Calendar with a TimeZone results in a pickle that contains an embedded pytz._p constructor call. Unfortunately it seems that the tz offsets encoded in it are incorrect, the resulting datetime object on the Python side (after unpickling) has a wrong tz offset.
I think this is because the pickle code encodes tz.getRawOffset() which is wrong when DST is in effect.
Because tz's are pickled without context, I don't see how we can fix this :-(   Because we'll need access to the calendar's date and time to know when DST is in effect
Example code:
		cal = Calendar.getInstance();
		cal.set(Calendar.YEAR, 2015);
		cal.set(Calendar.MONTH, 4);
		cal.set(Calendar.DAY_OF_MONTH, 18);
		cal.set(Calendar.HOUR_OF_DAY, 23);
		cal.set(Calendar.MINUTE, 59);
		cal.set(Calendar.SECOND, 59);
		cal.set(Calendar.MILLISECOND, 0);
		cal.setTimeZone(TimeZone.getTimeZone("Europe/Amsterdam"));

after pickling that cal, unpickling it with Python (2.7) results in a datetime like this;
2015-05-18T23:59:59+01:00
datetime.datetime(2015, 5, 18, 23, 59, 59, tzinfo=<DstTzInfo 'Europe/Amsterdam' CEST+1:00:00
DST>)

whose tz offset is wrong by 1 hour (should be +02:00)
(btw for UTC timezones, the offset is 0, and there is no problem)

Maybe we can build a special pickle that conforms to how pytz expects you to create a datetime with correct tz; it requires you to call tz.localize(dt) instead of passing the tz as constructor arg to the dt.
So perhaps we can construct a pickle that invokes this:
pytz.tzfile.DstTzInfo.localize(tz, dt)       # .... is it always DstTzInfo???

instead of relying on
datetime.datetime(........, tz)

Wow, that would be a hack :fearful:

Well, it's possible to create a pickle that invokes pytz.tzfile.DstTzInfo.localize(tz, dt),  but this requires access to builtins.getattr to retrieve the localize member.  This is problematic because on Python 3 it is "builtins", while on Python 2 it is "builtins".
So we need a way in the java code to decide between Python 2 or Python 3 pickle targets....

It will be a challenge to be able to unpicke such a pickle with the Java code itself. Or the .net code. We will have to emulate the attrgetter call somehow.

I'm actually proud of abusing pickle's arbitrary code execution vulnerability to our advantage here. :grin:

@airhorns again I had to replace some of your code with an alternative, to be able to fix this issue. Can you please check that my modifications work on your end?


Rename GraphService?

I would like to have a GraphService class that inherits from the Vstack Graph class. I could name it AppGraphService, but since there will only be one we typically prefer to not prefix files or classes with the name of the app. This will also help when comparing code from one project to the next. I'm not sure what we'd rename it to. Maybe BaseGraphService?
For now I'm using this: import {GraphService as BaseGraphService} from 'vstack-graph'; so maybe we don't need to rename it.

Rename sounds reasonable. I'd like to document some recommended naming conventions as well. Tackle this first thing in the morning.


Icons not shown in web version

All the NeumorphicIcon elements are not rendered properly in the web version both from Mobile and Desktop, even in the same link you share to showcase the features (on firebase), see the picture.
https://flutter-neumorphic.firebaseapp.com/#/

Hi, is this still an issue?


.outerHTML breaks

require('jsdom').jsdom('<select><option value="foo"></option></select>').body.firstChild.outerHTML

TypeError: Cannot read property 'nodeType' of undefined
    at exports.domToHtml (/Users/munter/src/frontend-rails/node_modules/jsdom/lib/jsdom/browser/domtohtml.js:14:20)
    at outerHTML (/Users/munter/src/frontend-rails/node_modules/jsdom/lib/jsdom/level1/core.js:1390:12)
    at repl:1:90
    at REPLServer.self.eval (repl.js:110:21)
    at Interface.<anonymous> (repl.js:239:12)
    at Interface.EventEmitter.emit (events.js:95:17)
    at Interface._onLine (readline.js:202:10)
    at Interface._line (readline.js:531:8)
    at Interface._ttyWrite (readline.js:760:14)
    at ReadStream.onkeypress (readline.js:99:10)

Haha man I am literally writing the changelog for this now... fixed in master, release going out in like 5 minutes. https://github.com/tmpvar/jsdom/commit/a702d102984560ed379e365747bf7b668464ac71

Awesome :dancer:
Will this be in the 3.x branch as well?

Nope, 3.x does not receive fixes.

Well, I need this and can't  do the switch. I guess you're loosing my further input then. Forking for now and evaluating alternatives then

Sounds good, that was always the intent of the io.js requirement.

Here's the specific patch you will need to fix it: https://github.com/tmpvar/jsdom/commit/a702d102984560ed379e365747bf7b668464ac71
Basically the issue was that  has a length property, which causes domToHtml to assume it is a list instead of a node

I gave up on the idea of running a fork of jsdom. I have other projects that I want to move on without having the overhead of maintaining legacy projects. I figured out a way to work with old jsdom versions in the assertion library where it failed for me.


Custom Inventory issue

I created a custom Inventory with archetype MENU_GRID, I filled the inventory with random items, every time I click on an item, all items disappear except the clicked one.
I remember having seen a similar issue in past but I can't find it anymore.
The server is a recent clone of SpongeForge/bleeding and there is no error in the log. Also, I'm cancelling any ClickInventoryEvent.Primary of the specified inventory.

Could you provide your code (Inventory creation + Listener) please?

http://pastebin.com/G867HwNq
http://pastebin.com/RVNgjNZS
http://pastebin.com/2qjHwW3H
http://pastebin.com/w3a9entG
These sources are part of a pretty big plugin, if you need some details just ask

ok... so the ClickInventoryEvent has around 300-400 Transactions in it.
It seems the inventory changes made in the repeating task are attributed to the player.
When canceling the event all of those transactions get reset.
@bloodmc @gabizou

This large number of transactions is only related to the item being clicked, or to the fact that the inventory is filled with many items randomly?

Its the random items. But imo they should not be part of the Event.
On ClickInventoryPrimary there should be a single SlotTransaction.

Would calling detectAndSendChanges() (without capturing transactions) before the CPacketClickWindow and detectAndSendChanges() (capturing transactions) after the CPacketClickWindow fix the issue? It would separate plugins's transactions and players's transactions

@Yeregorix One thing you can do until the issue is fixed is filter out the transactions from the event yourself. If you remove them from the event.getTransactions() list I found that I was able to prevent items from reappearing when I cancelled the event.

The idea is good but I don't see how to differentiate plugins's transactions and player's transactions.

@Yeregorix The pastebin links you provided are no longer valid. Is it possible to get new links?

I think @bloodmc already had fixed this a little while ago, not sure as to when but I do remember that the commit did involve calling the necessary methods to end capturing.

I can try to generate new pastebins if it's really needed but it seems that the issue was fixed in my case. Should I close this issue ?


Typo

It's a web app :)

:(

:(

Actually, my intuition was correct here. Its an because web is pronounced with vowel first. Its the same with an hour.

Yes, but hour begins with a vowel sound, while web begins with a consonant sound(I think it's considered smth like consonant glide, look at what you made me research :D) And according to google books it's used quite a bit more

Yup, that's true. Did the same research after the revert when 364b2d8844e58b5951ee519c6e40b30cdded332a popped out :sweat_smile:
Work arounds instead of problem solving, ftw!

Sound better that way :D


✨ Add torchfx feature extractor

Description
This PR only introduces torchfx. For other refactor see #717

Add torchfx feature extractor
Rename existing one to timm
Add custom backbone support in TorchFX feature extractor

Changes

[x] New feature (non-breaking change which adds functionality)

Checklist

[x] My code follows the pre-commit style and check guidelines of this project.
[x] I have performed a self-review of my code
[ ] I have commented my code, particularly in hard-to-understand areas
[ ] I have made corresponding changes to the documentation
[ ] My changes generate no new warnings
[x] I have added tests that prove my fix is effective or that my feature works
[x] New and existing tests pass locally with my changes

Another comment would be that this PR would break the backward compatibility due to the removal of FeatureExtractor. It would be good to still support it such that when the user tries to import from anomalib.models.components import FeatureExtractor it would inherit TimmFeatureExtractor but throws a deprecation warning.

Good point

sorry @ashwinvaidya17 i couldn't find the time to review this one


--nth skips included fields

[x] I have read through the manual page (man fzf)
[x] I have the latest version of fzf
[x] I have searched through the existing issues

Info

OS

[ ] Linux
[x] Mac OS X
[ ] Windows
[ ] Etc.

Shell

[ ] bash
[x] zsh
[ ] fish

Problem / Steps to reproduce
echo '123:456:789' | command fzf --delimiter : --with-nth 1,3 --nth 1,3
Searching for 789 doesn't match. I have tested this with a clean env -i zsh -f, too.
fzf --version                                                                                0|130
0.21.1 (brew)

After reading https://github.com/junegunn/fzf/issues/1440 , it seems this is the intended behavior. I think clarifying the manpage will help people.