Getting "Unable to save settings: Failed to save settings. Please restart IntelliJ IDEA" while editing a xlf file

What steps will reproduce the issue?

Open attached xlf file
try to add some text like Test
Idea will give an error about not being able to save

What is the expected result?
Editing an xlf file should be possible
What happens instead?
I need to restart Idea.
idea.log
messages.zip

+1

Still not fixed :/

+1 very this is happening automatically on any .xlf file
After I activated the plugin it works for a (very) short time.
Then got the 'Unable to save settings' error.
From then it's imposible to do anything, got to desactivate the plugin and relauch.

PLease re-assign the xlf file type to xml.

@cedricziel can you please tell me how to do ?
Nothing is showing up in PHPStorm option when I look for XLF except the plugin.

Sure, you can do that under the file types section in the settings. Unassign the xlf file type from the XLIFF type and re-assign it to XML

Same here, it's breaking PHPStorm.

@EliuTimana
The fix provided by cedricziel just above worked for me.

If I am not missing something, the plugin is obsolete? Maybe mark it as such?

The plugin is currently not in a healthy state and i dont have the resources to actively work on it. Sorry.

Not to be rude, then pull it from the plugins repo. Breaking installations is quite annoying in my opinion.

Same here. Once you edit an xlf file the entire IntelliJ application is not able to open any file anymore. My sistem is Ubuntu 17.10

Lol, just not going to use it. No matter what I do, same kak - it's now of my waste of time. I will use a more simpler IDE.


More reliable jumppack

Old method is inconsistent and easily exploited (using cl_cmdrate).

Fixed jumppack:
https://dl.dropboxusercontent.com/u/8081284/ShareX/2016/03/2016-03-27_16-39-21.mp4
Old jumppack:
https://dl.dropboxusercontent.com/u/8081284/ShareX/2016/03/2016-03-27_16-52-32.mp4


GUVNOR-2364: Invalid enumeration is validated without error

See https://issues.jboss.org/browse/GUVNOR-2364
This PR changes instantiation of ViewDRLSourceWidget to use GWT.create(..) to support Unit Testing.

See related PR: https://github.com/droolsjbpm/drools-wb/pull/121

+1

master: f15cad5a3ac00202edf2cc1c8cd96cec9ce835a8


[docs] Polymer serve Typescript Lit Element - non-JavaScript MIME type

Description
Going off of this SO post, I followed the docs guide exactly for setting up a Lit Element locally. Using what they had written in their stackblitz examples.
Ignoring the fact they have no script tag to include the index.ts I get the following error after running polymer serve:
Failed to load module script:
The server responded with a non-JavaScript MIME type of "video/mp2t".
Strict MIME type checking is enforced for module scripts per HTML spec.

I understand this is because I'm giving it a typescript file and it can only naturally handle JS. But I was hoping the documentation could provide a note or something that points to how to get it to work locally.
Live Demo
Stackblitz seems to handle it for you which is why their examples work.
Steps to Reproduce
Copy the exact files they have in their stackblitz locally and try and serve it. You may need to add the following to the html head
<script type="module" src="./index.ts"></script>

Expected Results
No error is thrown and the lit element appears
Actual Results
Blank page and the following error in the console
Failed to load module script:
The server responded with a non-JavaScript MIME type of "video/mp2t".
Strict MIME type checking is enforced for module scripts per HTML spec.

Browsers Affected

[x ] Chrome
[ x] Firefox
[x ] Edge
[x ] Safari 11
[x ] Safari 10
[ x] IE 11

Versions

<EMAIL_ADDRESS><EMAIL_ADDRESS>

Related to #420, among others.

Related to #420.

Is there any update on this issue?
I've done the same thing: followed the same steps in the documentation, and it doesn't work (as described in this issue).
What has to be done to the sample code to make it work?

Apologies, I'm in the middle of rewriting the getting started section, but it's not ready yet.
You can't copy the stackblitz example directly for a local project, because stackblitz handles TypeScript in an unusual fashion. In particular: for normal development, you never include a TypeScript file, you include the compiled version:
<script type="module" src="./index.js"></script>

StackBlitz uses the ".ts" as a cue that it needs to transpile that file... But a real project needs to reference the compiled JavaScript. If you already have the TypeScript compiler set up, this may be the only thing you need to change.
If you don't have TypeScript set up, you need to install the typescript compiler and set up a compilation step.
Here's a (work-in-progress) starter repo that includes everything you need to compile TypeScript (and then some): https://github.com/PolymerLabs/lit-element-starter-ts
If you want to get started and try out some of the TypeScript decorators, you can start with cloning that repo. (Note that its README points back to the getting started guide. This is somewhat misleading, as the updated getting started guide isn't ready and the existing getting started guide doesn't discuss this repo.)
Please let me know if you run into any problems.

Thanks for the helpful reply @arthurevans .
I've cloned that repo, and will attempt to pick out the basics of the minimum that is needed for me to get just a decorator working... plan on creating a simple repo to show this, so will ping you when that's done.

Great. Actually if you roll back to the initial commit in that repo (https://github.com/PolymerLabs/lit-element-starter-ts/commit/387a753d1f3ad652f8c3957702fbd4f2d674fc5b) you can find a version without testing, doc site, and all that.
I think the TypeScript config in the new version is simpler, though.

@arthurevans Ok, I've really quickly put something together:
https://github.com/mcalthrop/wc-lit-element-ts
Would be grateful for your opinion – and hope it's useful!
Signing off for the week... have a good weekend :-)

Thanks @mcalthrop ... I think your issue with @types/form-data is related to polymer-cli; when I remove polymer-cli and replace it with es-dev-server I don't see any references to @types/form-data.

@arthurevans Ah, nice... I just updated the repo to reflect this change. Thanks!

This one's obsolete as we don't use the Polymer CLI anymore.


x/term: The handle is invalid on windows

Go version
go version go1.22.3 windows/amd64
Output of go env in your module/workspace:
set GO111MODULE=
set GOARCH=amd64
set GOBIN=
set GOCACHE=C:\Users\magic\AppData\Local\go-build
set GOENV=C:\Users\magic\AppData\Roaming\go\env
set GOEXE=.exe
set GOEXPERIMENT=
set GOFLAGS=
set GOHOSTARCH=amd64
set GOHOSTOS=windows
set GOINSECURE=
set GOMODCACHE=C:\Users\magic\go\pkg\mod
set GONOPROXY=
set GONOSUMDB=
set GOOS=windows
set GOPATH=C:\Users\magic\go
set GOPRIVATE=
set GOPROXY=https://proxy.golang.org,direct
set GOROOT=C:\Program Files\Go
set GOSUMDB=sum.golang.org
set GOTMPDIR=
set GOTOOLCHAIN=auto
set GOTOOLDIR=C:\Program Files\Go\pkg\tool\windows_amd64
set GOVCS=
set GOVERSION=go1.22.3
set GCCGO=gccgo
set GOAMD64=v1
set AR=ar
set CC=gcc
set CXX=g++
set CGO_ENABLED=0
set GOMOD=D:\goterpix\go.mod
set GOWORK=
set CGO_CFLAGS=-O2 -g
set CGO_CPPFLAGS=
set CGO_CXXFLAGS=-O2 -g
set CGO_FFLAGS=-O2 -g
set CGO_LDFLAGS=-O2 -g
set PKG_CONFIG=pkg-config
set GOGCCFLAGS=-m64 -fno-caret-diagnostics -Qunused-arguments -Wl,--no-gc-sections -fmessage-length=0 -ffile-prefix-map=C:\Users\magic\AppData\Local\Temp\go-build3875495501=/tmp/go-build -gno-record-gcc-switches

What did you do?
go get  golang.org/x/term
        terY, terX, err := term.GetSize(0)
	if err != nil {
		panic(err)
	}

run on powershell
What did you see happen?
panic: The handle is invalid.
goroutine 1 [running]:
main.main()
D:/goterpix/goterpix.go:54 +0xd8e
exit status 2
What did you expect to see?
Value given

Similar Issues

x/sys/windows: go test ./... failed on windows #35246
x/term: operation not supported by device #65095
x/term: "Access is denied." error with ReadPassword on Windows #46164
x/term: git-bash.exe reports stdout is not a terminal.  #46681
x/term: Fails to build with golang < 1.12 #42665
go command #62170
Exmaple #53998
im going to go #53597
x/sys: golang.org/x/crypto/ssh/terminal fail for windows #34461
this is a test #64928

(Emoji vote if this was helpful or unhelpful; more detailed feedback welcome in this discussion.)

I believe 0 is the incorrect file descriptor on windows.
Unlike many projects, the Go project does not use GitHub Issues for general discussion or asking questions. GitHub Issues are used for tracking bugs and proposals only.
For questions please refer to https://github.com/golang/go/wiki/Questions


Enhance force-chatter node

Dear moriuchi,
I have confirmed my new "load more group" button in "force-chatter" also added some enhance for the node too. In my case, to check 2 button I have a mention list with 400 persons, 2 groups and each time it load will add more 50 persons. So if the user have lower than 50 the button will be disabled. Can you take a look by, thank you!

Dear OrisVN,
I checked with 444 users, 177 groups of organizations.
Did you hide the "load more group" button in the case of "Get Group Feed"?
Also, in the case of "Post Feed", why did you add one group each with the "load more group" button?
I think the following is a glitch, can you please confirm it?

When I clicked "load more user" button → deploy → restarted node-red, only the first 50 users were retrieved.
Click "load more group" button → Done the node edit → Open the node edit, the first group is displayed as a duplicate (the number of "load more group" is also one more)
When I click "load more group" button → deploy → restart the node-red, only the first one group were retrieved.

Dear moriuchi,
I have confirmed some of the glitch and fix it. With the "Load more groups" button at tab "Get Group Feed" issue, after reconsider it, I think it's not really necessary to put the button there when it load same groups list data as "Post feed".
In case of "load more group" only add 1 group each click, I have fix that and set it load 50 groups/ time.
With the glitch after clicked "Load more user/ group" button -> deploy -> restart node-red and only first 50 users and first group load out. Actually this depend on the source code and limit API call data per time of Salesforce. According to the Salesforce docs, I find it limit is 100 data per call, you can see it here https://developer.salesforce.com/docs/atlas.en-us.api_rest.meta/api_rest/resources_knowledge_support_artlist.htm?search_text=pageSize so to get the stability in the performance, I set it 50.
The "load more group" load out a duplicate glitch, I have check it and fix the issue. will make a new Pull Request for you soon. Thanks !

With the "Load more groups" button at tab "Get Group Feed" issue, after reconsider it, I think it's not really necessary to put the button there when it load same groups list data as "Post feed".

With the glitch after clicked "Load more user/ group" button -> deploy -> restart node-red and only first 50 users and first group load out. Actually this depend on the source code and limit API call data per time of Salesforce. According to the Salesforce docs, I find it limit is 100 data per call,

==> I understand.

In case of "load more group" only add 1 group each click, I have fix that and set it load 50 groups/ time.

The "load more group" load out a duplicate glitch, I have check it and fix the issue. will make a new Pull Request for you soon.

==> We have confirmed that there is no problem.

Hi moriuchi,
As I see you have merged my pull request in, thank you! But seem like you haven't update the source in https://flows.nodered.org/node/node-red-contrib-force yet. Can you confirm it ?

Dear OrisVN,
After publishing the updated node to npm, it didn't seem to be reflected in the Flow Library.
I added this to the Flow Library and confirmed that the updated version can be installed on node-red.

Dear OrisVN,
After publishing the updated node to npm, it didn't seem to be reflected in the Flow Library.
I added this to the Flow Library and confirmed that the updated version can be installed on node-red.

Thank you, I have confirmed that. The flow version work well now !


Inconsistencies between 2 ways methods

I don't know where to open this since this is more of something about the API itself and not specifically the nodejs wrapper.
However it seems that the methods do_deposit_funds_from_wallet & do_withdrawal_funds_to_wallet do differ in the answer about 1 parameter:

do_withdrawal_funds_to_wallet takes an optional accountId as a parameter & gives an optional accountId in the answer
do_deposit_funds_from_wallet takes an optional accountId as a parameter and doesn't return any

Shouldn't both have the same signature: either return the original accountId or don't return it in the answer ?
referring to

https://docs.plus.cex.io/#rest-private-api-calls-funds-deposit-from-wallet
https://docs.plus.cex.io/#rest-private-api-calls-funds-withdrawal-to-wallet

@codlab nice catch! Absolutely agree with some sort of dissimilarity with these two calls. We've already add this issue to our backlog, so stay tuned for API & documentation updates. And thanks for raising this issue, we appreciate that!


FIX: Corrected padding on non-sortable columns.

span.non-sortable in the GridField header relies on there being other, sortable columns in the list to get the padding right. If there are no such columns (e.g. in a simple header), then the header is shown without padding, which is ugly.
This small change fixes that. Tested on Chrome and Firefox. 1px smaller than a sortable header on Firefox but still looks fine.

Looks like this needs rebasing. Also, any chance of before/after shots?

Rebasing? You mean to 3.2? I figured it's a bugfix so 3.1 is okay, but could do 3.2 if you think that's best.
Before: https://www.evernote.com/shard/s11/sh/78e917b0-b0a9-4a78-a3bf-6a4f60af5903/16cc8a11834d4e97115f81e2eb73a410
After: https://www.evernote.com/shard/s11/sh/7e3913ad-28bc-46dc-9d07-67f0250959a0/f6c8b25cfe37223581b46a10742ea518

No, sorry, against 3.1, We can't merge cleanly at the moment:

Doh, I missed that. Fixed now.

thanks :)


Support TCP

When working with TCP, the OSC spec mentions:

In a stream-based protocol such as TCP, the stream should begin with an int32 giving the size of the first packet, followed by the contents of the first packet, followed by the size of the second packet, etc.

I've had much trouble with rosc to use TCP, reading this little line in the spec I finally understand. Is it true that rosc doesn't implement this right now, and if so, would this be a good idea to have?

Given the signature of decode and encode rosc is actually transport agnostic since it consumes and produces slices of bytes. I guess the spec proposes to send the size of each packet when using TCP in case you want to send more than one OSC package/message in one TCP connection.  It would likely be beneficial if rosc would provide some higher level networking abstractions but I lost track of how one is now doing proper networking with Rust when the whole asyncio thing happenend.

Thanks for your response!
I understand you've left out the networking part from rosc, I think that's fine. Someone else could provide a crate integrating rosc with a certain approach to networking. The existing examples here are helpful already for people wanting to use this.
Perhaps something like fn decode_tcp(msgs: &[u8]) -> Result<Vec<OscPacket>> and fn encode_tcp(packets: &Vec<OscPacket>) -> Result<Vec<u8>> would still be useful. (Though I'm not sure if it should be &Vec<OscPacket> or Vec<&OscPacket>.)

Perhaps something like fn decode_tcp(msgs: &[u8]) -> Result<Vec> and fn encode_tcp(packets: &Vec) -> Result<Vec> would still be useful. (Though I'm not sure if it should be &Vec or Vec<&OscPacket>.)

Yes, this would be helpful when interacting with other OSC implementations over TCP which follow the spec closely.  Would you mind to contribute an implementation of those two functions?  I can implement this as well but cannot guarantee when I will find the time to do that.

This got finally resolved with #21 , but there is no release yet.  A proper release will follow  as soon as we removed the dependency on the regex crate.


[text] Support SDF spritefont generation

This new functionality has been added to stb_truetype library, already used by raylib.
More info on SDF fonts:
https://github.com/libgdx/libgdx/wiki/Distance-field-fonts
https://blog.mapbox.com/drawing-text-with-signed-distance-fields-in-mapbox-gl-b0933af6f817
https://lambdacube3d.wordpress.com/2014/11/12/playing-around-with-font-rendering/
https://www.youtube.com/watch?v=CGZRHJvJYIg
Supporting SDF fonts it's a great addition for raylib.

Someway related discussion in issue https://github.com/raysan5/raylib/issues/549

Commented on related issue: https://github.com/raysan5/raylib/issues/375
SDF support is implemented along TTF loading improvement. Closing this one.


Increase file save hash size

Issue #8249 runs into a problem where the max hash size is low, resulting in files being potentially overwritten.
The behavior of this functionality is as such:
As batch size increases, the probability that any given file will have a conflict in the hash reduces. However, when the author wants to save images with a batch size of one, the probability of a conflict increases since {index} is always 1. This seems to just be an unforeseen bug because a batch size of one is uncommon.

The reason why the random integer range is small is because this functionality is really meant for debugging. It is not efficient and you should typically not be using it at scale.

100% agree, but it's still odd behavior that a function used for debugging would be overwriting files that are being written to test your own sanity 😄


refactor: move confirm dialog functions to utils package

Why?
Simplify the cmd package and trim it down to the CLI interface only

Codecov Report

Merging #352 (bad85be) into main (6849b6c) will not change coverage.
The diff coverage is 0.00%.

:exclamation: Current head bad85be differs from pull request most recent head be430ca. Consider uploading reports for the commit be430ca to get more accurate results

@@           Coverage Diff           @@
##             main     #352   +/-   ##
=======================================
  Coverage   53.66%   53.66%
=======================================
  Files          60       59    -1
  Lines        4877     4877
=======================================
  Hits         2617     2617
  Misses       1962     1962
  Partials      298      298

Impacted Files
Coverage Δ

cmd/dump.go
24.48% <0.00%> (ø)

cmd/konnect_dump.go
27.08% <0.00%> (ø)

cmd/reset.go
28.33% <0.00%> (ø)

utils/utils.go
54.34% <0.00%> (-38.25%)
:arrow_down:

Continue to review full report at Codecov.

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Powered by Codecov. Last update 6849b6c...be430ca. Read the comment docs.


Roll Engine from 3f05b521b939 to d368b8763a49 (6 revisions)

https://github.com/flutter/engine/compare/3f05b521b939...d368b8763a49
2020-09-03<EMAIL_ADDRESS>Log the results when ShellTest.Screenshot fails (flutter/engine#20932)
2020-09-03<EMAIL_ADDRESS>Started printing out error messages when the observatory won't be reachable because of permissions problems. (flutter/engine#20960)
2020-09-03<EMAIL_ADDRESS>Fix iOS text field input keyboard flickering & crash (flutter/engine#20805)
2020-09-03<EMAIL_ADDRESS>Roll Skia from 5951e8fc3369 to 1ee21cdfb6fe (4 revisions) (flutter/engine#20979)
2020-09-03<EMAIL_ADDRESS>Roll Fuchsia Linux SDK from odFvFQV9Z... to 81O8Kg_Rw... (flutter/engine#20978)
2020-09-03<EMAIL_ADDRESS>Roll Skia from f8823b572600 to 5951e8fc3369 (5 revisions) (flutter/engine#20977)
Also rolling transitive DEPS:
fuchsia/sdk/core/linux-amd64 from odFvFQV9Ze6Q to 81O8Kg_RwUtu
If this roll has caused a breakage, revert this CL and stop the roller
using the controls here:
https://autoroll.skia.org/r/flutter-engine-flutter-autoroll
Please CC<EMAIL_ADDRESS>on the revert to ensure that a human
is aware of the problem.
To report a problem with the AutoRoller itself, please file a bug:
https://bugs.chromium.org/p/skia/issues/entry?template=Autoroller+Bug
Documentation for the AutoRoller is here:
https://skia.googlesource.com/buildbot/+doc/master/autoroll/README.md

Commit queue failed; closing this roll.


OpenAI ChatClient tools support

Add support for ChatClient function calling.

Add generic (model) ToolFunctionCallback and AbstractToolFunctionCallback  abstractions for defining and registering function callbacks with the ChatClient.
OpenAiChatClient Function calling implementation.
Unit/IT tests for OpenAiApi and OpenAiChatClient function calling.
Add function calling docs.

removed the default methods in the chat option interface to make tests pass.
Merged as ffd8222c209967552ea32a265837a48e72076b13
Can review the small comments in this PR afterwards


Block Trend seems reversed when a state flips

With Georgia having just flipped, it looks like the Block Trend is now saying Trump, but is still using the Biden number

Sorry - this looks like the same thing as #210
I'll close this issue


401 with "new-style" credential provider plugin

We switched to explicitly use new method, nuget is no more in same location as the plugin and plugin is pointed by NUGET_PLUGIN_PATHS env variable.
Nuget <IP_ADDRESS>90
Command-line v0.1.19
This time we can get:
..\..\Build\NuGet\NuGet.exe install MyPackage -NonInteractive -ConfigFile ..\..\Build\NuGet\NuGet.Config -Prerelease -Framework net472 -ExcludeVersion -DependencyVersion Lowest -OutputDirectory ..\..\Build\NuGet\Tools -Version <IP_ADDRESS>
Feeds used:
  https://pkgs.dev.azure.com/Company/_packaging/CompanyFeed/nuget/v3/index.json

Attempting to gather dependency information for package 'MyPackage.<IP_ADDRESS>' with respect to project '..\..\Build\NuGet\Tools', targeting '.NETFramework,Version=v4.7.2'
Problem starting the plugin 'M:\Repo\Build\NuGet\CredentialProvider\CredentialProvider.Microsoft.exe'. Plugin 'CredentialProvider.Microsoft' failed within 6.279 seconds with exit code -1.
Problem starting the plugin 'M:\Repo\Build\NuGet\CredentialProvider\CredentialProvider.Microsoft.exe'. Plugin 'CredentialProvider.Microsoft' failed within 6.279 seconds with exit code -1.
  Plugin 'CredentialProvider.Microsoft' failed within 6.279 seconds with exit code -1.
  A task was canceled.
An error occurred while retrieving package metadata for 'MyPackage.<IP_ADDRESS>' from source 'CompanyFeed'.
  Response status code does not indicate success: 401 (Unauthorized).

And internal log
[18:38:05.441 11584 Verbose] Running in plug-in mode
[18:38:05.448 11584 Verbose] Command-line v0.1.19: "M:\Repo\Build\NuGet\CredentialProvider\CredentialProvider.Microsoft.exe" -Plugin
[18:38:05.519 11584 Verbose] Handling 'Request' 'Initialize'. Time elapsed in ms: 22 - Payload: {"ClientVersion":"5.2.0","Culture":"en-GB","RequestTimeout":"00:00:05"}
[18:38:05.520 11584 Verbose] Sending response: 'Request' 'Initialize'. Time elapsed in ms: 24
[18:38:05.522 11584 Verbose] Time elapsed in milliseconds after sending response 'Request' 'Initialize': 25
[18:38:05.531 11584 Verbose] Handling 'Request' 'GetOperationClaims'. Time elapsed in ms: 1 - Payload: {}
[18:38:05.532 11584 Verbose] Sending response: 'Request' 'GetOperationClaims'. Time elapsed in ms: 2
[18:38:05.556 11584 Verbose] Time elapsed in milliseconds after sending response 'Request' 'GetOperationClaims': 26
[18:38:05.617 11584 Verbose] Handling 'Request' 'SetLogLevel'. Time elapsed in ms: 2 - Payload: {"LogLevel":"Information"}
[18:38:05.619 11584 Verbose] Sending response: 'Request' 'SetLogLevel'. Time elapsed in ms: 3
[18:38:05.620 11584 Verbose] Time elapsed in milliseconds after sending response 'Request' 'SetLogLevel': 5
[18:38:05.640 11584 Verbose] Handling 'Request' 'GetAuthenticationCredentials'. Time elapsed in ms: 5 - Payload: {"Uri":"https://pkgs.dev.azure.com/Company/_packaging/CompanyFeed/nuget/v3/index.json","IsRetry":false,"IsNonInteractive":true,"CanShowDialog":true}
[18:38:05.641 11584 Verbose] Creating a progress reporter with interval: 00:00:02
[18:38:05.647 11584 Verbose] Handling auth request, Uri: https://pkgs.dev.azure.com/Company/_packaging/CompanyFeed/nuget/v3/index.json, IsRetry: False, IsNonInteractive: True, CanShowDialog: True
[18:38:05.647 11584 Verbose] URI: https://pkgs.dev.azure.com/Company/_packaging/CompanyFeed/nuget/v3/index.json
[18:38:05.649 11584 Verbose] VstsBuildTaskServiceEndpointCredentialProvider - This credential provider must be run under the Team Build tasks for NuGet with external endpoint credentials. Appropriate environment variable needs to be set.
[18:38:05.649 11584 Verbose] Skipping NuGetCredentialProvider.CredentialProviders.VstsBuildTaskServiceEndpoint.VstsBuildTaskServiceEndpointCredentialProvider, cannot provide credentials for https://pkgs.dev.azure.com/Company/_packaging/CompanyFeed/nuget/v3/index.json
[18:38:05.650 11584 Verbose] VstsBuildTaskCredentialProvider - This credential provider must be run under the Team Build tasks for NuGet. Appropriate environment variables must be set.
[18:38:05.651 11584 Verbose] Skipping NuGetCredentialProvider.CredentialProviders.VstsBuildTask.VstsBuildTaskCredentialProvider, cannot provide credentials for https://pkgs.dev.azure.com/Company/_packaging/CompanyFeed/nuget/v3/index.json
[18:38:06.436 11584 Verbose] GET https://pkgs.dev.azure.com/Company/_packaging/CompanyFeed/nuget/v3/index.json
[18:38:06.746 11584 Verbose] IsRetry: False
[18:38:06.775 11584 Verbose] Found cached SessionToken for https://pkgs.dev.azure.com/Company/_packaging/CompanyFeed/nuget/v3/index.json
[18:38:06.776 11584 Verbose] Sending response: 'Request' 'GetAuthenticationCredentials'. Time elapsed in ms: 1142
[18:38:06.782 11584 Verbose] Time elapsed in milliseconds after sending response 'Request' 'GetAuthenticationCredentials': 1147

this looks like the cancellation issue that we are working with the nuget team on. link. can you try some of those steps? I see startup is taking longer than 5 seconds so it is probably that case. thanks.

For what it's worth, I'm seeing the same issue with NuGet <IP_ADDRESS>68.  On some of my (self-hosted) build agents, it's picking up the V1 credential manager and succeeds.    I'm not entirely sure what the difference is between the agents, but it's very consistent.

Ok, I think I have a fix for my specific situation.  My pipeline specified the NugetCommand task with a externalFeedCredentials parameter which pointed to a valid service connection with a valid PAT.  As noted above, some of my agents were using the V1 credential manager and some were using V2.  At least, I assume V1 was being invoked because there wasn't any logging output about the credential manager at all.  I still don't know why this difference in behavior existed, but the V1 credential manager was able to access the service connection correctly but the V2 credential manager failed to access the service connection.  Specifically, V2 failed here:
[CredentialProvider]Sending response: 'Request' 'GetAuthenticationCredentials'. Time elapsed in ms: 0
[CredentialProvider]Time elapsed in milliseconds after sending response 'Request' 'GetAuthenticationCredentials': 0
NuGet.Protocol.Core.Types.FatalProtocolException: Unable to load the service index for source https://redacted.pkgs.visualstudio.com/_packaging/redacted/nuget/v3/index.json. ---> System.Net.Http.HttpRequestException: Response status code does not indicate success: 401 (Unauthorized).

I modified the NugetCommand task and removed the externalFeedCredentials parameter entirely.  Now the pipeline invokes the V2 credential manager on all agents and successfully authenticates to the feed.

This is NuGet/Home#8528

Should be fixed with NuGet 5.5.x and cred provider 0.1.20


Linux problem with 2-Step Verification

After typing password, windows freezes

Does an app password work?

Same issue here. Haven't tried app password, but I'm pretty sure it won't work as it's basically a browser and they won't allow using an app password for a device that should support 2FA codes.

Running on Linux and no such issue. However, I didn't use the .deb, but rather run from git clone.

Same issue here, using an app password doesn't work as GPMDP explicitly requests the account's password.

This is the expected behaviour.  Imagine the login process for the player is the same as in any browser (Chrome, Firefox, Etc.)
Google's login process doesn't accept app passwords :)
If you want more security enable 2FA as that is supported during this login flow.

The issue is actually that the player freeze after inserting password when 2FA is enabled.

OK, I misread the issue.  Can you tell me exactly when the player freezes?
I.e. First keydown, first keyup, after submitting Etc.

Immediately after pressing "Sign in" under the password field in the login screen (in the second stage, the first one is where you enter your email)

Can you run the development environment and start the app with the flags --enable-logging to see what chromium is failing with in the background :+1:
Also I'm going to close here and ask to move to the atom/electron repo when you find out what chromium is crashing at.

Couldn't find exactly why Chromium is crashing but running Google Play Music Desktop Player with --disable-gpu flag workarounds the issue.


Run time error for main_fed.py (without gpu)

When I was running this code, using the command as you suggested,

python main_fed.py --dataset mnist --model cnn --epochs 50 --gpu  -1 --num_channels 1

It raised the following error:
CNNMnist(
(conv1): Conv2d(1, 10, kernel_size=(5, 5), stride=(1, 1))
(conv2): Conv2d(10, 20, kernel_size=(5, 5), stride=(1, 1))
(conv2_drop): Dropout2d(p=0.5)
(fc1): Linear(in_features=320, out_features=50, bias=True)
(fc2): Linear(in_features=50, out_features=10, bias=True)
)
0%|                                      | 0/50 [00:00<?, ?it/s]
Traceback (most recent call last):
File "main_fed.py", line 122, in
w, loss = local.update_weights(net=copy.deepcopy(net_glob))
File "C:\Users\lliubb\PycharmProjects\DistributedLearning_LLM\Fed
Avg\Update.py", line 50, in update_weights
for batch_idx, (images, labels) in enumerate(self.ldr_train):
File "C:\Users\lliubb\PycharmProjects\Federated-Learning\venv\lib
\site-packages\torch\utils\data\dataloader.py", line 314, in __next
__
batch = self.collate_fn([self.dataset[i] for i in indices])
File "C:\Users\lliubb\PycharmProjects\Federated-Learning\venv\lib
\site-packages\torch\utils\data\dataloader.py", line 314, in
batch = self.collate_fn([self.dataset[i] for i in indices])
File "C:\Users\lliubb\PycharmProjects\DistributedLearning_LLM\Fed
Avg\Update.py", line 21, in getitem
image, label = self.dataset[self.idxs[item]]
File "C:\Users\lliubb\PycharmProjects\Federated-Learning\venv\lib
\site-packages\torchvision\datasets\mnist.py", line 68, in getite
m
img, target = self.train_data[index], self.train_labels[index]
IndexError: only integers, slices (:), ellipsis (...), None and
long or byte Variables are valid indices (got numpy.float64)
Can you give me some hints on how to solve this?
I do not have a gpu and I am using python 3.6 on a windows system.

I think I found the problem, not quite sure whether it is a problem caused by using cpu.
The type index in local update step is float.64, after converting the type to np.int, this code can run well


Uxplatform 9611

Summary

What was changed:
Why it was changed:
Testing

This change was tested using:

[ ] WDIO
[ ] Jest
[ ] Visual testing (please attach a screenshot or recording)
[ ] Other (please describe below)
[ ] No tests are needed

Reviews
In addition to engineering reviews, this PR needs:

[ ] UX review
[ ] Accessibility review
[ ] Functional review

Additional Details

This PR resolves:
UXPLATFORM-XXXX

Thank you for contributing to Terra.
@cerner/terra

Test PR, no longer needed.


Format of returned dates

i am guessing the below is a date of some sort?
created          :<PHONE_NUMBER>,761
lastContact      :<PHONE_NUMBER>,339
lastUpdate       :<PHONE_NUMBER>
How is it structured? like ddmmyyyy or what? it does not make sense to me lol
Originally posted by @duffman36 in https://github.com/homotechsual/NinjaRMM/issues/3#issuecomment-915280628

These are dates in a UNIX Epoch format (number of seconds and milliseconds since January 1st 1970).
You can turn these into a UNIX Epoch like so:
([DateTime]::UnixEpoch).AddMilliseconds($Created)


remove callbacks from more methods

closed in favour of https://github.com/ethereum/remix-project/pull/62


[Question]: 调用Trainer时传入lr_scheduler_type cosine 后lr不变化

请提出你的问题
在使用UIE的Finetune.py脚本时，传入lr_scheduler_type cosine 后监控lr 并无变化 ，请问是或正常？

你好，请升级 paddlenlp 到最新版本试一试看看？pip install paddlenlp==2.4.3

升级后依然不生效

升级后依然不生效 @ZHUI

[2022-11-23 11:11:17,169] [    INFO] - max_steps is given, it will override any value given in num_train_epochs
[2022-11-23 11:11:17,170] [    INFO] - ============================================================
[2022-11-23 11:11:17,171] [    INFO] -     Training Configuration Arguments
[2022-11-23 11:11:17,171] [    INFO] - paddle commit id              :2ea3700a336ea844389298a7520b386d4ec5fc3b
[2022-11-23 11:11:17,171] [    INFO] - _no_sync_in_gradient_accumulation:True
[2022-11-23 11:11:17,172] [    INFO] - adam_beta1                    :0.9
[2022-11-23 11:11:17,172] [    INFO] - adam_beta2                    :0.999
[2022-11-23 11:11:17,172] [    INFO] - adam_epsilon                  :1e-08
[2022-11-23 11:11:17,172] [    INFO] - bf16                          :False
[2022-11-23 11:11:17,173] [    INFO] - bf16_full_eval                :False
[2022-11-23 11:11:17,173] [    INFO] - current_device                :gpu:4
[2022-11-23 11:11:17,173] [    INFO] - dataloader_drop_last          :False
[2022-11-23 11:11:17,174] [    INFO] - dataloader_num_workers        :0
[2022-11-23 11:11:17,174] [    INFO] - device                        :gpu
[2022-11-23 11:11:17,174] [    INFO] - disable_tqdm                  :True
[2022-11-23 11:11:17,174] [    INFO] - do_eval                       :True
[2022-11-23 11:11:17,175] [    INFO] - do_export                     :True
[2022-11-23 11:11:17,175] [    INFO] - do_predict                    :True
[2022-11-23 11:11:17,175] [    INFO] - do_train                      :True
[2022-11-23 11:11:17,176] [    INFO] - eval_batch_size               :32
[2022-11-23 11:11:17,176] [    INFO] - eval_steps                    :200
[2022-11-23 11:11:17,176] [    INFO] - evaluation_strategy           :IntervalStrategy.STEPS
[2022-11-23 11:11:17,176] [    INFO] - fp16                          :False
[2022-11-23 11:11:17,177] [    INFO] - fp16_full_eval                :False
[2022-11-23 11:11:17,177] [    INFO] - fp16_opt_level                :O2
[2022-11-23 11:11:17,177] [    INFO] - gradient_accumulation_steps   :2
[2022-11-23 11:11:17,177] [    INFO] - greater_is_better             :True
[2022-11-23 11:11:17,178] [    INFO] - ignore_data_skip              :False
[2022-11-23 11:11:17,178] [    INFO] - label_names                   :None
[2022-11-23 11:11:17,178] [    INFO] - learning_rate                 :0.0001
[2022-11-23 11:11:17,179] [    INFO] - load_best_model_at_end        :True
[2022-11-23 11:11:17,179] [    INFO] - local_process_index           :0
[2022-11-23 11:11:17,179] [    INFO] - local_rank                    :0
[2022-11-23 11:11:17,180] [    INFO] - log_level                     :-1
[2022-11-23 11:11:17,180] [    INFO] - log_level_replica             :-1
[2022-11-23 11:11:17,180] [    INFO] - log_on_each_node              :True
[2022-11-23 11:11:17,180] [    INFO] - logging_dir                   :./tmp/xnli_cn/runs/Nov23_11-11-07_yq01-qianmo-com-255-129-12.yq01
[2022-11-23 11:11:17,181] [    INFO] - logging_first_step            :False
[2022-11-23 11:11:17,181] [    INFO] - logging_steps                 :10
[2022-11-23 11:11:17,181] [    INFO] - logging_strategy              :IntervalStrategy.STEPS
[2022-11-23 11:11:17,182] [    INFO] - lr_scheduler_type             :SchedulerType.COSINE
[2022-11-23 11:11:17,182] [    INFO] - max_grad_norm                 :1.0
[2022-11-23 11:11:17,182] [    INFO] - max_steps                     :10000
[2022-11-23 11:11:17,183] [    INFO] - metric_for_best_model         :eval_accuracy
[2022-11-23 11:11:17,183] [    INFO] - minimum_eval_times            :-1
[2022-11-23 11:11:17,183] [    INFO] - no_cuda                       :False
[2022-11-23 11:11:17,184] [    INFO] - num_train_epochs              :3
[2022-11-23 11:11:17,184] [    INFO] - optim                         :OptimizerNames.ADAMW
[2022-11-23 11:11:17,184] [    INFO] - output_dir                    :./tmp/xnli_cn
[2022-11-23 11:11:17,184] [    INFO] - overwrite_output_dir          :False
[2022-11-23 11:11:17,185] [    INFO] - past_index                    :-1
[2022-11-23 11:11:17,185] [    INFO] - per_device_eval_batch_size    :32
[2022-11-23 11:11:17,185] [    INFO] - per_device_train_batch_size   :32
[2022-11-23 11:11:17,185] [    INFO] - prediction_loss_only          :False
[2022-11-23 11:11:17,186] [    INFO] - process_index                 :0
[2022-11-23 11:11:17,186] [    INFO] - recompute                     :True
[2022-11-23 11:11:17,186] [    INFO] - remove_unused_columns         :True
[2022-11-23 11:11:17,187] [    INFO] - report_to                     :['visualdl']
[2022-11-23 11:11:17,187] [    INFO] - resume_from_checkpoint        :None
[2022-11-23 11:11:17,187] [    INFO] - run_name                      :./tmp/xnli_cn
[2022-11-23 11:11:17,187] [    INFO] - save_on_each_node             :False
[2022-11-23 11:11:17,188] [    INFO] - save_steps                    :200
[2022-11-23 11:11:17,188] [    INFO] - save_strategy                 :IntervalStrategy.STEPS
[2022-11-23 11:11:17,188] [    INFO] - save_total_limit              :3
[2022-11-23 11:11:17,189] [    INFO] - scale_loss                    :32768
[2022-11-23 11:11:17,189] [    INFO] - seed                          :42
[2022-11-23 11:11:17,189] [    INFO] - sharding                      :[]
[2022-11-23 11:11:17,189] [    INFO] - sharding_degree               :2
[2022-11-23 11:11:17,190] [    INFO] - should_log                    :True
[2022-11-23 11:11:17,190] [    INFO] - should_save                   :True
[2022-11-23 11:11:17,190] [    INFO] - train_batch_size              :32
[2022-11-23 11:11:17,190] [    INFO] - warmup_ratio                  :0.0
[2022-11-23 11:11:17,191] [    INFO] - warmup_steps                  :0
[2022-11-23 11:11:17,191] [    INFO] - weight_decay                  :0.01
[2022-11-23 11:11:17,191] [    INFO] - world_size                    :4
[2022-11-23 11:11:17,191] [    INFO] -
[2022-11-23 11:11:17,254] [    INFO] - ***** Running training *****
[2022-11-23 11:11:17,254] [    INFO] -   Num examples = 392701
[2022-11-23 11:11:17,254] [    INFO] -   Num Epochs = 7
[2022-11-23 11:11:17,255] [    INFO] -   Instantaneous batch size per device = 32
[2022-11-23 11:11:17,255] [    INFO] -   Total train batch size (w. parallel, distributed & accumulation) = 256
[2022-11-23 11:11:17,255] [    INFO] -   Gradient Accumulation steps = 2
[2022-11-23 11:11:17,255] [    INFO] -   Total optimization steps = 10000
[2022-11-23 11:11:17,255] [    INFO] -   Total num train samples = 2560000
[2022-11-23 11:11:18,787] [    INFO] -   Number of trainable parameters = 99868419
[2022-11-23 11:11:27,064] [    INFO] - loss: 1.0899848, learning_rate: 9.999975326009292e-05, global_step: 10, interval_runtime: 8.2708, interval_samples_per_second: 309.523, interval_steps_per_second: 1.209, epoch: 0.0065
[2022-11-23 11:11:32,768] [    INFO] - loss: 0.94208021, learning_rate: 9.999901304280685e-05, global_step: 20, interval_runtime: 5.7045, interval_samples_per_second: 448.768, interval_steps_per_second: 1.753, epoch: 0.013
[2022-11-23 11:11:38,476] [    INFO] - loss: 0.86334038, learning_rate: 9.99977793554475e-05, global_step: 30, interval_runtime: 5.7078, interval_samples_per_second: 448.509, interval_steps_per_second: 1.752, epoch: 0.0196
[2022-11-23 11:11:44,074] [    INFO] - loss: 0.80716286, learning_rate: 9.999605221019081e-05, global_step: 40, interval_runtime: 5.5982, interval_samples_per_second: 457.29, interval_steps_per_second: 1.786, epoch: 0.0261
[2022-11-23 11:11:49,725] [    INFO] - loss: 0.7661695, learning_rate: 9.999383162408304e-05, global_step: 50, interval_runtime: 5.6511, interval_samples_per_second: 453.009, interval_steps_per_second: 1.77, epoch: 0.0326
[2022-11-23 11:11:55,454] [    INFO] - loss: 0.73705273, learning_rate: 9.999111761904046e-05, global_step: 60, interval_runtime: 5.7298, interval_samples_per_second: 446.789, interval_steps_per_second: 1.745, epoch: 0.0391
[2022-11-23 11:12:01,294] [    INFO] - loss: 0.7377521, learning_rate: 9.998791022184922e-05, global_step: 70, interval_runtime: 5.8394, interval_samples_per_second: 438.401, interval_steps_per_second: 1.713, epoch: 0.0456
[2022-11-23 11:12:06,893] [    INFO] - loss: 0.71224113, learning_rate: 9.9984209464165e-05, global_step: 80, interval_runtime: 5.5986, interval_samples_per_second: 457.256, interval_steps_per_second: 1.786, epoch: 0.0522

@briup1 上面是我的运行日志，可以看到可以生效，你贴一下你的日志吧。

[2022-11-23 01:26:08,092] [    INFO] - We are using <class 'paddlenlp.transformers.ernie.tokenizer.ErnieTokenizer'> to load 'uie-base-en'.
[2022-11-23 01:26:15,034] [    INFO] - ============================================================
[2022-11-23 01:26:15,034] [    INFO] -     Training Configuration Arguments
[2022-11-23 01:26:15,034] [    INFO] - paddle commit id              :590b4dbcdd989324089ce43c22ef151c746c92a3
[2022-11-23 01:26:15,035] [    INFO] - _no_sync_in_gradient_accumulation:True
[2022-11-23 01:26:15,035] [    INFO] - activation_quantize_type      :None
[2022-11-23 01:26:15,035] [    INFO] - adam_beta1                    :0.9
[2022-11-23 01:26:15,036] [    INFO] - adam_beta2                    :0.999
[2022-11-23 01:26:15,036] [    INFO] - adam_epsilon                  :1e-08
[2022-11-23 01:26:15,036] [    INFO] - algo_list                     :None
[2022-11-23 01:26:15,036] [    INFO] - batch_num_list                :None
[2022-11-23 01:26:15,037] [    INFO] - batch_size_list               :None
[2022-11-23 01:26:15,037] [    INFO] - bf16                          :False
[2022-11-23 01:26:15,037] [    INFO] - bf16_full_eval                :False
[2022-11-23 01:26:15,038] [    INFO] - bias_correction               :False
[2022-11-23 01:26:15,039] [    INFO] - current_device                :gpu:0
[2022-11-23 01:26:15,039] [    INFO] - dataloader_drop_last          :False
[2022-11-23 01:26:15,040] [    INFO] - dataloader_num_workers        :0
[2022-11-23 01:26:15,040] [    INFO] - device                        :gpu
[2022-11-23 01:26:15,041] [    INFO] - disable_tqdm                  :True
[2022-11-23 01:26:15,041] [    INFO] - do_compress                   :False
[2022-11-23 01:26:15,042] [    INFO] - do_eval                       :True
[2022-11-23 01:26:15,042] [    INFO] - do_export                     :True
[2022-11-23 01:26:15,042] [    INFO] - do_predict                    :False
[2022-11-23 01:26:15,043] [    INFO] - do_train                      :True
[2022-11-23 01:26:15,043] [    INFO] - eval_batch_size               :32
[2022-11-23 01:26:15,044] [    INFO] - eval_steps                    :100
[2022-11-23 01:26:15,044] [    INFO] - evaluation_strategy           :IntervalStrategy.STEPS
[2022-11-23 01:26:15,044] [    INFO] - fp16                          :False
[2022-11-23 01:26:15,045] [    INFO] - fp16_full_eval                :False
[2022-11-23 01:26:15,045] [    INFO] - fp16_opt_level                :O1
[2022-11-23 01:26:15,046] [    INFO] - gradient_accumulation_steps   :1
[2022-11-23 01:26:15,046] [    INFO] - greater_is_better             :True
[2022-11-23 01:26:15,047] [    INFO] - ignore_data_skip              :True
[2022-11-23 01:26:15,047] [    INFO] - input_infer_model_path        :None
[2022-11-23 01:26:15,047] [    INFO] - label_names                   :['start_positions', 'end_positions']
[2022-11-23 01:26:15,047] [    INFO] - learning_rate                 :2e-05
[2022-11-23 01:26:15,048] [    INFO] - load_best_model_at_end        :True
[2022-11-23 01:26:15,048] [    INFO] - local_process_index           :0
[2022-11-23 01:26:15,049] [    INFO] - local_rank                    :0
[2022-11-23 01:26:15,049] [    INFO] - log_level                     :-1
[2022-11-23 01:26:15,049] [    INFO] - log_level_replica             :-1
[2022-11-23 01:26:15,050] [    INFO] - log_on_each_node              :True
[2022-11-23 01:26:15,050] [    INFO] - logging_dir                   :./finetuned_model_qq/runs/Nov23_01-24-57_6bf6d99aotq62-0
[2022-11-23 01:26:15,050] [    INFO] - logging_first_step            :False
[2022-11-23 01:26:15,051] [    INFO] - logging_steps                 :20
[2022-11-23 01:26:15,051] [    INFO] - logging_strategy              :IntervalStrategy.STEPS
[2022-11-23 01:26:15,052] [    INFO] - lr_scheduler_type             :SchedulerType.CONSTANT
[2022-11-23 01:26:15,052] [    INFO] - max_grad_norm                 :1.0
[2022-11-23 01:26:15,053] [    INFO] - max_steps                     :-1
[2022-11-23 01:26:15,053] [    INFO] - metric_for_best_model         :eval_f1
[2022-11-23 01:26:15,054] [    INFO] - minimum_eval_times            :None
[2022-11-23 01:26:15,054] [    INFO] - moving_rate                   :0.9
[2022-11-23 01:26:15,054] [    INFO] - no_cuda                       :False
[2022-11-23 01:26:15,055] [    INFO] - num_train_epochs              :50.0
[2022-11-23 01:26:15,055] [    INFO] - onnx_format                   :True
[2022-11-23 01:26:15,055] [    INFO] - optim                         :OptimizerNames.ADAMW
[2022-11-23 01:26:15,056] [    INFO] - output_dir                    :./finetuned_model_qq
[2022-11-23 01:26:15,056] [    INFO] - overwrite_output_dir          :True
[2022-11-23 01:26:15,057] [    INFO] - past_index                    :-1
[2022-11-23 01:26:15,057] [    INFO] - per_device_eval_batch_size    :32
[2022-11-23 01:26:15,057] [    INFO] - per_device_train_batch_size   :32
[2022-11-23 01:26:15,058] [    INFO] - prediction_loss_only          :False
[2022-11-23 01:26:15,058] [    INFO] - process_index                 :0
[2022-11-23 01:26:15,058] [    INFO] - recompute                     :False
[2022-11-23 01:26:15,059] [    INFO] - remove_unused_columns         :True
[2022-11-23 01:26:15,059] [    INFO] - report_to                     :['visualdl']
[2022-11-23 01:26:15,059] [    INFO] - resume_from_checkpoint        :None
[2022-11-23 01:26:15,060] [    INFO] - round_type                    :round
[2022-11-23 01:26:15,060] [    INFO] - run_name                      :./finetuned_model_qq
[2022-11-23 01:26:15,061] [    INFO] - save_on_each_node             :False
[2022-11-23 01:26:15,061] [    INFO] - save_steps                    :100
[2022-11-23 01:26:15,061] [    INFO] - save_strategy                 :IntervalStrategy.STEPS
[2022-11-23 01:26:15,062] [    INFO] - save_total_limit              :1
[2022-11-23 01:26:15,062] [    INFO] - scale_loss                    :32768
[2022-11-23 01:26:15,062] [    INFO] - seed                          :42
[2022-11-23 01:26:15,062] [    INFO] - sharding                      :[]
[2022-11-23 01:26:15,063] [    INFO] - sharding_degree               :-1
[2022-11-23 01:26:15,063] [    INFO] - should_log                    :True
[2022-11-23 01:26:15,064] [    INFO] - should_save                   :True
[2022-11-23 01:26:15,064] [    INFO] - strategy                      :dynabert+ptq
[2022-11-23 01:26:15,064] [    INFO] - train_batch_size              :32
[2022-11-23 01:26:15,065] [    INFO] - use_pact                      :True
[2022-11-23 01:26:15,065] [    INFO] - warmup_ratio                  :0.1
[2022-11-23 01:26:15,066] [    INFO] - warmup_steps                  :0
[2022-11-23 01:26:15,066] [    INFO] - weight_decay                  :0.0
[2022-11-23 01:26:15,066] [    INFO] - weight_quantize_type          :channel_wise_abs_max
[2022-11-23 01:26:15,067] [    INFO] - width_mult_list               :None
[2022-11-23 01:26:15,067] [    INFO] - world_size                    :4
[2022-11-23 01:26:15,067] [    INFO] -
[2022-11-23 01:26:15,155] [    INFO] - ***** Running training *****
[2022-11-23 01:26:15,155] [    INFO] -   Num examples = 10631
[2022-11-23 01:26:15,156] [    INFO] -   Num Epochs = 50
[2022-11-23 01:26:15,156] [    INFO] -   Instantaneous batch size per device = 32
[2022-11-23 01:26:15,156] [    INFO] -   Total train batch size (w. parallel, distributed & accumulation) = 128
[2022-11-23 01:26:15,157] [    INFO] -   Gradient Accumulation steps = 1
[2022-11-23 01:26:15,157] [    INFO] -   Total optimization steps = 4200.0
[2022-11-23 01:26:15,158] [    INFO] -   Total num train samples = 531550.0
[2022-11-23 01:26:15,429] [    INFO] -   Number of trainable parameters = 109485314
[2022-11-23 01:26:37,530] [    INFO] - loss: 0.00170259, learning_rate: 2e-05, global_step: 20, interval_runtime: 22.0947, interval_samples_per_second: 115.865, interval_steps_per_second: 0.905, epoch: 0.2381
[2022-11-23 01:26:58,366] [    INFO] - loss: 0.00105053, learning_rate: 2e-05, global_step: 40, interval_runtime: 20.8368, interval_samples_per_second: 122.86, interval_steps_per_second: 0.96, epoch: 0.4762
[2022-11-23 01:27:13,205] [    INFO] - loss: 0.00058154, learning_rate: 2e-05, global_step: 60, interval_runtime: 14.8386, interval_samples_per_second: 172.522, interval_steps_per_second: 1.348, epoch: 0.7143
[2022-11-23 01:27:34,129] [    INFO] - loss: 0.00063376, learning_rate: 2e-05, global_step: 80, interval_runtime: 20.924, interval_samples_per_second: 122.347, interval_steps_per_second: 0.956, epoch: 0.9524
[2022-11-23 01:27:54,536] [    INFO] - loss: 0.00043808, learning_rate: 2e-05, global_step: 100, interval_runtime: 20.4046, interval_samples_per_second: 125.462, interval_steps_per_second: 0.98, epoch: 1.1905
@ZHUI 在这里我设置的是constant，但用cosine也是一样的。
Name: paddlenlp
Version: 2.4.3
Summary: Easy-to-use and powerful NLP library with Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including Neural Search, Question Answering, Information Extraction and Sentiment Analysis end-to-end system.
Home-page: https://github.com/PaddlePaddle/PaddleNLP
Author: PaddleNLP Team
Author-email<EMAIL_ADDRESS>License: Apache 2.0
Location: /zhangxuejie373/anaconda3/envs/p38_paddle/lib/python3.8/site-packages
Requires: colorama, colorlog, datasets, dill, jieba, multiprocess, paddle2onnx, paddlefsl, protobuf, sentencepiece, seqeval, tqdm, visualdl
Required-by:

你日志里面的，是constant类型的lr_scheduler_type。请检查一下你的启动命令，参数的传入？
lr_scheduler_type             :SchedulerType.CONSTANT

[2022-11-23 05:35:27,615] [    INFO] - ============================================================
[2022-11-23 05:35:27,615] [    INFO] -     Training Configuration Arguments
[2022-11-23 05:35:27,615] [    INFO] - paddle commit id              :590b4dbcdd989324089ce43c22ef151c746c92a3
[2022-11-23 05:35:27,616] [    INFO] - _no_sync_in_gradient_accumulation:True
[2022-11-23 05:35:27,616] [    INFO] - activation_quantize_type      :None
[2022-11-23 05:35:27,617] [    INFO] - adam_beta1                    :0.9
[2022-11-23 05:35:27,617] [    INFO] - adam_beta2                    :0.999
[2022-11-23 05:35:27,617] [    INFO] - adam_epsilon                  :1e-08
[2022-11-23 05:35:27,618] [    INFO] - algo_list                     :None
[2022-11-23 05:35:27,618] [    INFO] - batch_num_list                :None
[2022-11-23 05:35:27,618] [    INFO] - batch_size_list               :None
[2022-11-23 05:35:27,619] [    INFO] - bf16                          :False
[2022-11-23 05:35:27,619] [    INFO] - bf16_full_eval                :False
[2022-11-23 05:35:27,619] [    INFO] - bias_correction               :False
[2022-11-23 05:35:27,620] [    INFO] - current_device                :gpu:3
[2022-11-23 05:35:27,620] [    INFO] - dataloader_drop_last          :False
[2022-11-23 05:35:27,620] [    INFO] - dataloader_num_workers        :0
[2022-11-23 05:35:27,621] [    INFO] - device                        :gpu
[2022-11-23 05:35:27,621] [    INFO] - disable_tqdm                  :True
[2022-11-23 05:35:27,621] [    INFO] - do_compress                   :False
[2022-11-23 05:35:27,622] [    INFO] - do_eval                       :True
[2022-11-23 05:35:27,622] [    INFO] - do_export                     :True
[2022-11-23 05:35:27,622] [    INFO] - do_predict                    :False
[2022-11-23 05:35:27,623] [    INFO] - do_train                      :True
[2022-11-23 05:35:27,623] [    INFO] - eval_batch_size               :32
[2022-11-23 05:35:27,623] [    INFO] - eval_steps                    :100
[2022-11-23 05:35:27,624] [    INFO] - evaluation_strategy           :IntervalStrategy.STEPS
[2022-11-23 05:35:27,624] [    INFO] - fp16                          :False
[2022-11-23 05:35:27,624] [    INFO] - fp16_full_eval                :False
[2022-11-23 05:35:27,625] [    INFO] - fp16_opt_level                :O1
[2022-11-23 05:35:27,625] [    INFO] - gradient_accumulation_steps   :1
[2022-11-23 05:35:27,625] [    INFO] - greater_is_better             :True
[2022-11-23 05:35:27,626] [    INFO] - ignore_data_skip              :True
[2022-11-23 05:35:27,626] [    INFO] - input_infer_model_path        :None
[2022-11-23 05:35:27,626] [    INFO] - label_names                   :['start_positions', 'end_positions']
[2022-11-23 05:35:27,627] [    INFO] - learning_rate                 :2e-05
[2022-11-23 05:35:27,627] [    INFO] - load_best_model_at_end        :True
[2022-11-23 05:35:27,627] [    INFO] - local_process_index           :0
[2022-11-23 05:35:27,628] [    INFO] - local_rank                    :-1
[2022-11-23 05:35:27,628] [    INFO] - log_level                     :-1
[2022-11-23 05:35:27,628] [    INFO] - log_level_replica             :-1
[2022-11-23 05:35:27,629] [    INFO] - log_on_each_node              :True
[2022-11-23 05:35:27,629] [    INFO] - logging_dir                   :./finetuned_model_qq/runs/Nov23_05-35-18_6bf6d99aotq62-0
[2022-11-23 05:35:27,630] [    INFO] - logging_first_step            :False
[2022-11-23 05:35:27,630] [    INFO] - logging_steps                 :10
[2022-11-23 05:35:27,630] [    INFO] - logging_strategy              :IntervalStrategy.STEPS
[2022-11-23 05:35:27,631] [    INFO] - lr_scheduler_type             :SchedulerType.COSINE
[2022-11-23 05:35:27,631] [    INFO] - max_grad_norm                 :1.0
[2022-11-23 05:35:27,631] [    INFO] - max_steps                     :-1
[2022-11-23 05:35:27,631] [    INFO] - metric_for_best_model         :eval_f1
[2022-11-23 05:35:27,632] [    INFO] - minimum_eval_times            :None
[2022-11-23 05:35:27,632] [    INFO] - moving_rate                   :0.9
[2022-11-23 05:35:27,633] [    INFO] - no_cuda                       :False
[2022-11-23 05:35:27,633] [    INFO] - num_train_epochs              :5.0
[2022-11-23 05:35:27,633] [    INFO] - onnx_format                   :True
[2022-11-23 05:35:27,634] [    INFO] - optim                         :OptimizerNames.ADAMW
[2022-11-23 05:35:27,634] [    INFO] - output_dir                    :./finetuned_model_qq
[2022-11-23 05:35:27,634] [    INFO] - overwrite_output_dir          :True
[2022-11-23 05:35:27,635] [    INFO] - past_index                    :-1
[2022-11-23 05:35:27,635] [    INFO] - per_device_eval_batch_size    :32
[2022-11-23 05:35:27,635] [    INFO] - per_device_train_batch_size   :32
[2022-11-23 05:35:27,635] [    INFO] - prediction_loss_only          :False
[2022-11-23 05:35:27,636] [    INFO] - process_index                 :0
[2022-11-23 05:35:27,636] [    INFO] - recompute                     :False
[2022-11-23 05:35:27,636] [    INFO] - remove_unused_columns         :True
[2022-11-23 05:35:27,637] [    INFO] - report_to                     :['visualdl']
[2022-11-23 05:35:27,637] [    INFO] - resume_from_checkpoint        :None
[2022-11-23 05:35:27,637] [    INFO] - round_type                    :round
[2022-11-23 05:35:27,638] [    INFO] - run_name                      :./finetuned_model_qq
[2022-11-23 05:35:27,638] [    INFO] - save_on_each_node             :False
[2022-11-23 05:35:27,638] [    INFO] - save_steps                    :100
[2022-11-23 05:35:27,639] [    INFO] - save_strategy                 :IntervalStrategy.STEPS
[2022-11-23 05:35:27,639] [    INFO] - save_total_limit              :1
[2022-11-23 05:35:27,639] [    INFO] - scale_loss                    :32768
[2022-11-23 05:35:27,640] [    INFO] - seed                          :42
[2022-11-23 05:35:27,640] [    INFO] - sharding                      :[]
[2022-11-23 05:35:27,640] [    INFO] - sharding_degree               :-1
[2022-11-23 05:35:27,641] [    INFO] - should_log                    :True
[2022-11-23 05:35:27,641] [    INFO] - should_save                   :True
[2022-11-23 05:35:27,641] [    INFO] - strategy                      :dynabert+ptq
[2022-11-23 05:35:27,642] [    INFO] - train_batch_size              :32
[2022-11-23 05:35:27,642] [    INFO] - use_pact                      :True
[2022-11-23 05:35:27,642] [    INFO] - warmup_ratio                  :0.1
[2022-11-23 05:35:27,643] [    INFO] - warmup_steps                  :0
[2022-11-23 05:35:27,643] [    INFO] - weight_decay                  :0.0
[2022-11-23 05:35:27,643] [    INFO] - weight_quantize_type          :channel_wise_abs_max
[2022-11-23 05:35:27,644] [    INFO] - width_mult_list               :None
[2022-11-23 05:35:27,644] [    INFO] - world_size                    :1
[2022-11-23 05:35:27,644] [    INFO] -
[2022-11-23 05:35:27,646] [    INFO] - ***** Running training *****
[2022-11-23 05:35:27,646] [    INFO] -   Num examples = 10631
[2022-11-23 05:35:27,647] [    INFO] -   Num Epochs = 5
[2022-11-23 05:35:27,647] [    INFO] -   Instantaneous batch size per device = 32
[2022-11-23 05:35:27,647] [    INFO] -   Total train batch size (w. parallel, distributed & accumulation) = 32
[2022-11-23 05:35:27,648] [    INFO] -   Gradient Accumulation steps = 1
[2022-11-23 05:35:27,648] [    INFO] -   Total optimization steps = 1665.0
[2022-11-23 05:35:27,648] [    INFO] -   Total num train samples = 53155.0
[2022-11-23 05:35:27,846] [    INFO] -   Number of trainable parameters = 109485314
[2022-11-23 05:35:38,718] [    INFO] - loss: 0.00220406, learning_rate: 2e-05, global_step: 10, interval_runtime: 10.8645, interval_samples_per_second: 29.454, interval_steps_per_second: 0.92, epoch: 0.03
[2022-11-23 05:35:48,959] [    INFO] - loss: 0.00207934, learning_rate: 2e-05, global_step: 20, interval_runtime: 10.2417, interval_samples_per_second: 31.245, interval_steps_per_second: 0.976, epoch: 0.0601
[2022-11-23 05:35:59,216] [    INFO] - loss: 0.00126031, learning_rate: 2e-05, global_step: 30, interval_runtime: 10.2564, interval_samples_per_second: 31.2, interval_steps_per_second: 0.975, epoch: 0.0901
[2022-11-23 05:36:03,783] [    INFO] - loss: 0.0013646, learning_rate: 2e-05, global_step: 40, interval_runtime: 4.5671, interval_samples_per_second: 70.066, interval_steps_per_second: 2.19, epoch: 0.1201
[2022-11-23 05:36:14,029] [    INFO] - loss: 0.00103009, learning_rate: 2e-05, global_step: 50, interval_runtime: 10.2461, interval_samples_per_second: 31.231, interval_steps_per_second: 0.976, epoch: 0.1502
[2022-11-23 05:36:24,288] [    INFO] - loss: 0.00078573, learning_rate: 2e-05, global_step: 60, interval_runtime: 10.2587, interval_samples_per_second: 31.193, interval_steps_per_second: 0.975, epoch: 0.1802
[2022-11-23 05:36:34,552] [    INFO] - loss: 0.00088691, learning_rate: 2e-05, global_step: 70, interval_runtime: 10.2639, interval_samples_per_second: 31.177, interval_steps_per_second: 0.974, epoch: 0.2102
lr_scheduler_type             :SchedulerType.COSINE 当前COSINE 依旧保持了learning_rate不变 T-T @ZHUI

你这个是模型压缩的api吗？我看用了 dynabert+ptq

@LiuChiachi 辛苦看看

如果是 UIE finetune的代码的话，可以删除这一行：
https://github.com/PaddlePaddle/PaddleNLP/blob/fc7cdc025f70f5236420a56487dd3a983665b4fd/model_zoo/uie/finetune.py#L198-L200

可以了。感谢！！！
这行代码后续也会删除吗？
之所以能够直接删除是因为Trainer默认了一个优化器的吗？

对的，后续会删除的。Trainer 需要自己控制 optimizer，不然很多功能无法生效。
@LiuChiachi 辛苦后续删除一下。


electron spin-rotation coupling, effective charges including transition-metals

New code for electron spin-rotation coupling in /pyscf/prop/esr
Effective charge for two-electron spin-orbit coupling in /pyscf/prop/zfs/uhf.py

merged in dev branch (commit id 3eb25961783b2b08f46a8ec4c53c39b2f2200552)


UITableVieCel->UITableViewCell in comment

fix "UITableVieCel->UITableViewCell": a tiny issue in code comment (in header) copy-pasted into README.md

Hi,
Thanks for the pull request. Won't merge because you have a lot of changes not related to the pull request, even including private headers "MOVOpaqueView.h"


Annotation definition syntax highlighting not working

Description:
Refer the following screen capture

Affected Versions:
v1.2.0-SNAPSHOT at least

Fixed with SL Alpha3 release.


Fix project dirs path

ProjectDirs::from("miri", "miri", "miri")

would get you miri\miri on Windows and miri.miri.miri on macOS.
I'm assuming here that your intention was to have only a miri directory on every OS.

So on Linux, this remains at ~/.cache/miri?
To fix Windows CI, you'll have to adjust the path here.

@RalfJung Yes. The arguments for ProjectDirs::from are qualifier: &str, organization: &str, application: &str, not e. g. linux: &str, macos: &str, windows: &str.

I see. Would it make sense for us to use "rust" or "rust-lang" as "organization"?
I don't know what "qualifier" is supposed to mean.

Nobody seemed to care much when I asked on Zulip. So I'd say let's go with org.rust-lang.miri on macOS, unless @oli-obk objects.

unless @oli-obk objects.

quite the opposite, let's do this

@soc okay so can you make this "org", "rust-lang", "miri"? That will have the effect of using org.rust-lang.miri on macOS and rust-lang\miri on Windows, right?

@RalfJung Sorry for the delay, your commit looks good to me. Thanks!

No trouble, and thanks for pointing out that we were using this API the wrong way. :)

It's been a pleasure! No I just need to fix cargo and the rest of the ecosystem. :-)


Create Tao-Framework.md

Grant Application Form for Tao-Framework project
Project Abstract

Please provide a brief description of your project here summarising key points (1-2 paragraphs).
If your application is a follow-up to a previous grant, please mention which one in the first line of the abstract and include a link to previous pull requests if applicable.

For which grant level are you applying?

[ ] Level 1:  Up to $10,000, 2 approvals
[x] Level 2:  Up to $50,000, 3 approvals
[ ] Level 3:  Unlimited, 5 approvals (for > $100k Web3 Foundation Council approval)

Application Checklist

[x] The application template has been copied, renamed ( project_name.md) and updated.
[x] A BTC or Ethereum (DAI/USDT) address for the payment of the milestones is provided inside the application.
[x] I have read and acknowledged the terms and conditions.
[x] The software delivered for this grant will be released under an open-source license specified in the application.
[x] The initial PR contains only one commit (squash and force-push if needed).
[x] The grant will only be announced once the first milestone has been accepted.

Grant application form for Tao-Framework project

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

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

We have updated the grant application as requested, please check

We have made the change accordingly and committed the file. Please review. Again we appreciate the general questions raised by David, and we think those are excellent questions. Since we are taking a new approach to resolving the scalability issue, we understand that many new concepts need to be introduced and explained. We have added much more detail in the development section to explain how our incentive mechanism works and security analysis. The data footprinting process is detailed in the data model section. The auditing process has been elaborated in the auditors component section. The payment model we mean here refers to the payment structure to the nodes that act as a cloud provider, not the payment related to the smart contract. We are more than happy to discuss more on these issues as the review process goes further.

Thx very much for your feedback and questions. We really appreciate it since this makes us think and re-think our approaches and sometimes it helps the innovative idea to emerge. We think our Tao Node is not a standard network node of a blockchain network. Instead, it is based on a MoonBeam dev node, and used as a smart contract execution engine to execute our customer Smart contract (Tcontract). Please refer to this image: https://docs.google.com/document/d/10eGrW6_UvUTn-kYeup2zFUQLPDvJsMLgP53pTB6WN-I/edit?usp=sharing
So we will leverage MoonBeam network to handle the transaction validation and storage. And use MoonBeam Unified Account to deploy a smart contract in the Ethereum network just for the footprinting validation and synchronize the Tao Nodes. Since we are going to cooperate with the MoonBeam Development team on the implementation, so hopefully these technical difficulties can be resolved.
In our opinion, the Tao Framework itself is not a Blockchain network, it is more a cloud service cluster network, that web3 client can use the RPC to connect and execute the smart contract in the MoonBeam network, since MoonBeam is a Polkadot parachain, the security can be handled there.
please check out this link : https://docs.google.com/document/d/10eGrW6_UvUTn-kYeup2zFUQLPDvJsMLgP53pTB6WN-I/edit?usp=sharing

Thanks for your question, the file should have open access and be shared with everyone, let me know if you have an issue accessing the link. Again we really appreciate your open-mindedness and patience during this review process. We understand since we are taking a new approach, there are a few new concepts that need to be introduced :

We can use a centralized service for running scalable decentralized smart contracts.

Like in a DNS system, we have to trust the network of centralized routers and Internet Service Providers(ISP) to correctly take the URL we enter and route into one or multiple IP addresses. In the web3 world is similar, right now in order to run a smart contract in MoonBeam, users can set up the MetaMask and point it to the MoonBeam network, then Moonbeam network will decide to rout the RPC to a particular MoonBeam node to run the smart contract user submit. Our idea is to build a cloud network as an underlying communication, storage, and computation. The client first needs to get subscription access to the cloud, and they can route RPC calls to the cloud node that is close to them to improve the performance. The node then passes the smart contract to MoonBeam network for execution. Or we can use the MoonBeam standard node as the execution engine to execute the smart contract. We will work closely with MoonBeam development team during the implementation.

Public blockchain network has a high cost due to its unstructured permission less P2P network. So our Proof of Correctness (POC) is designed to provide a centralized cloud environment instead of the random P2P network node to run decentralized smart contracts. The cloud node knows nothing about the smart contract is going to run, and has no control over the execution nor interface with the data stored by these contracts. We use a smart contract deployed on Ethereum to provide periodic proofs on the decentralization of the cloud network and ensure any attempt of the bad behavior will generate a public-verifiable proof.

Regarding the question on how are we going to leverage the MoonBeam network, let me clarify as the following:
We will develop our Tao Node based on the MoonBeam development node and use that as the smart contract execution engine to run our custom Tcontract and system Tcontract. Then we have two solutions to choose from to run our POC(Proof of Correctness) consensus protocol to synchronize our Tao Node inside the Cloud network :

Deploy the Smart Contract which executes the POC algorithm into Ethereum Public blockchain network.
Deploy the Smart Contract which executes the POC algorithm into the MoonBeam network which is the Polkadot ParaChain

We only need to implement one of the above solutions, not both.
Hopefully, that can clarify a little bit, thx

Thx very much for your feedback and suggestion. We strongly believe blockchain is a revolutionary technology and the web3 is the future Internet. But before it can make a real impact on modern society, we have to make the efforts to put it into real use, run it on a large scale and provide the economic incentive to those who are willing to provide resources and adapt to this amazing technology, otherwise, it will just remain as a high tech toy played by the tech people in the lab. It is true that today, anyone who takes two hours tutorial can create a sample smart contract and deploy it into a MoonBeam test net, create a few fake accounts and tokens and move those tokens around. But we don't want to stop there, our ultimate goal is to provide the general public with the tools to not only use but also create their own token for their own business propose and financial incentive that currently resides only in the hands of technologies. And that required a scalable cloud environment to run the smart contracts in a secure and low-cost way. It is easy said than done.
We have already applied for the Moonbean grant and have been in contact with the MoonBeam development team. We are hoping to get more resources to help us to put this amazing technology into real practical use.  Thx very much!

I have double-checked, now everyone should have access to this link: https://docs.google.com/document/d/10eGrW6_UvUTn-kYeup2zFUQLPDvJsMLgP53pTB6WN-I/edit?usp=sharing
It is just a picture to show how a web3 app works, we are using this to demonstrate that just like CDN (content delivery network) with the Internet, we can build many consortium clouds based on geolocation, then the user can route their RPC calls to the closest cloud consortium to run their smart contracts thus increase the performance and scalability.
Thx

Thx again for your open-mindedness and willingness to give us an opportunity to show more people our idea and get more resources to help us find out the solution. As you said the key point is how are we going to achieve it. We understand without a use case and a prototype for proof of the concept, it is hard to conceive people to support this project. We have already started with our implementation of a prototype for our first use case which is to provide local communities, commons, associations with instruments to help finance themselves with tokens representing prepaid cards, crowdfunding, complementary currencies, to share tools and infrastructures with tokens representing access rights. We will keep updating you on the progress since we believe the only way to prove a solution will work is through detailed implementation. Thx


[feature request] multiple user/pass or custom authentication handler

Could you please provide an example of how to implement a custom user/pass authentication handler function so that people can run a socks5 server with multiple username / password combinations?

Just use small API to build your own server.
more about socks5:
https://www.txthinking.com/talks/articles/socks5-and-http-proxy-en.article
https://www.youtube.com/watch?v=sBCB-X7BoP8

what is small api and where do i find it?
i want to make this support multiple outgoing and username/password, and able to configure it without restarting the server


Updated official release

I created a Conan package (https://conan.io/center/yojimbo) for Yojimbo a while ago. As there's been quite a few new commits/merged PRs since the last official release (1.2.1), is it possible to get another official versioned release so I can update the package?

Hello, any update on this ? The current version in conan.io  has a few issues:

https://github.com/conan-io/conan/issues/3573 says that msvc is planned to replace Visual Studio for settings.compiler
Visual studio 2022 is not supported (but fixing the conanfile.py is not enough, premake5 version in Conan is stale too, I had to also replace it manually in my .conan/data folder locally)
yaml.load(...) seems to be yaml.full_load(...) in recent versions.

Let me know if I should put the above in a separate issue.

Working on this now

Hello, the version on https://github.com/conan-io/conan-center-index/tree/master/recipes/yojimbo still seems to be 1.2.1 ?

Hi, I don't control Conan-io repo?

Hi, @pixsperdavid the current release should be appropriate for your Conan package. Do you have any time to update it?

I'll try and take a look at it at some point but pretty busy with other projects right now and I'm not using yojimbo in any code at present.


Burst photos are exported multiple times

Burst photos are exported multiple times -- e.g. each burst photo in the burst set is exported every time a burst photo is evaluated.  This results in duplicate copies being exported.

Fixed in https://github.com/RhetTbull/osxphotos/releases/tag/v0.41.5


[tooling] Fix GitHub Pages generation

#616 changed the folder structure of the artifacts generated during CI, putting them two extra folders (/uss_qualifier/output) deep, which broke all the report links at https://interuss.github.io/monitoring/  I believe this PR will fix the issue though I am not totally sure (e.g., does $d necessarily have a trailing /?)

(e.g., does $d necessarily have a trailing /?)

I tried on the default OS X shell and the default Ubuntu one: if the pattern has a trailing slash (as currently in the script) then the variable has the trailing slash too (and dropping the trailing slash causes it to be removed from the variable too).
So this seems reasonable to try out.


[Feature request] Add injection of assets at specific position

This pull request adds the feature to inject assets at a specific position within the head or body element
ref #389

The inject feature is only a shortcut for the underlieing template system. If inject does not fulfill your needs please use the template variables.. they allow to solve every use case and can be used with any webpack supported template language even with pure JavaScript or react


Silent pull?

Is there any way to have a silent pull (without any output) and without any questions?
E.g.:
Proceed with the changes? [Y/n]:Y

I think you are looking for -quiet and -no-prompt.  Not sure if quiet implied no-prompt or not.

@IS-smcleod gave the right answer. Closing this.


Cloud Formation error on setup

Describe the bug
I encounter consistent error on cloud formation with error below
"
Embedded stack arn:aws:cloudformation:us-east-2:734928534788:stack/samstack1-BBBECSStack-WIAQ4K0V9OXO/9b389510-716e-11eb-82c3-024874579a58 was not successfully created: The following resource(s) failed to create: [BBBECSCapacityProvider].
"
To Reproduce
Steps to reproduce the behavior:
./setup.sh -p user1 -e<EMAIL_ADDRESS>-h Z05115161FM7Y5SVAYMDR -s samstack1 -d example.ng
I have tried granting all permissions I know it might required.
Kindly help me out on this issue.

Got into the same issue and could not apply the solutions provided in [#1]
My configuration:
hosted zone : myDomain.com
BBBDomainName :meeting.myDomain.com
Both are available at route53. What am I missing here?
+ grep -m 1 'has address <IP_ADDRESS>'
+ sleep 5
+ host tu-5l26l4.meeting.myDomain.com
+ grep -m 1 'has address <IP_ADDRESS>'
+ sleep 5
+ host tu-5l26l4.meeting.myDomain.com
+ grep -m 1 'has address <IP_ADDRESS>'
+ sleep 5

are you using an AWS registered or "external" Domain?
if 2nd. please check if the AWS DNS Servers (ref: Documentation) are properly registered and the name resolution is working from you or test devices (or internet test suites)
Cheers!

The main domain myDomain.com is registered from namecheap and we have ns from aws there.
And the sub domain meeting.myDomain.com is configured from route53 and name resolution is also working.

can you see tu-5l26l4.meeting.myDomain.com added to the route53 domain and is it resolvable for you while the setup runs?

yes there is tu-5l26l4.meeting.myDomain.com being added to route53 and it was only resolvable once out of few tries that too was at the beginning when  tu-5l26l4.meeting.myDomain.com was added to route53 but after few minutes it was not resolvable even though it was still in route53.

if you deploy again, can you check if the hostname gets resolvable while the turn server is deploying?
the only reason i can think about is, that it takes too long until it can be resolved and then the deployment is cancelled.

can you also check the nested stacks events for the error causing the rollback and post it here, jic

Hostname do get resolved when turn server is deploying

And this is screenshot of /var/log/cloud-init-output.log

Stack Events

can you please check on the turn server itself if the hostname is resolving.
you can use the Systems Manager Session Manager to log into the Instance (Console -> EC2 -> Turn instance -> Connect -> Session Manager)

closing due inactivity


Add CI build status & dependency badge in readme

Hope you'll like it.

The build and dependency badges are already in the readme

Oops, my fault.


v1.1.5 release is broken

I am getting the following exception after upgrading to v1.1.5
Unable to import module 'index': Error
at Function.Module._resolveFilename (module.js:469:15)
at Function.Module._load (module.js:417:25)
at Module.require (module.js:497:17)
at require (internal/module.js:20:19)
at Object.<anonymous> (/var/task/node_modules/aws-xray-sdk-core/lib/context_utils.js:5:11)
at Module._compile (module.js:570:32)
at Object.Module._extensions..js (module.js:579:10)
at Module.load (module.js:487:32)
at tryModuleLoad (module.js:446:12)
at Function.Module._load (module.js:438:3)

Seriously. you have to unpublish this version
i'm not even sure you guys understood the impact of change dependency to peerDependency
missing continuation-local-storage causing a lot of problems all over the place.
most of npm install (especially node 6.X.X, which lambda support) doesn't have any simple way to check peerDependency has been fulfilled or not.

Also, even npm <~ 3 doesn't install peerDependency automatically. idk why did you thought only npm3 has this problem
and even with knowing that, this should be at least "Major" release, not "patch" this gonna break all the clients that using "'aws-xray-sdk-core': '^1.1.x'"

this could become a production problem for anyone using xray who deploys an app right now, Support is going to be overwhelmed with this one if its not fixed soon

@kazimanzurrashid @breath103 the X-Ray team is actively investigating this issue

@kazimanzurrashid @breath103 @camwes can you confirm where this is occurring (e.g. EC2, ECS, Lambda, etc.) and with which version of NPM?

It it's occurring in elastic beanstalk for me

Let me clear out this

from npm >= 3 npm install doesn't install peerDependencies.
So if you made artifact such as

 dst.zip
   -- app.js
   -- node_modules
       -- ext..
   -- package.json

node_modules won't include "continuation-local-storage" even if you do npm install. it shows warnings on npm install, but it doesn't fail (npm ls would raise error, but which most of people doesn't do obviously)

So if there is any code const xray = require("aws-xray-sdk") in app.js, it failed like @kazimanzurrashid mentioned,

and if you do this locally,

show proper error. i guess this is also problem (that if lambda fails to import, it doesn't raw error at all)
And most of case you won't even know this on test environment since aws-xray-sdk raise error if you execute any of methods in the local eviroment where there is no XRAY_AGENT is available
shortly. just quickly upload new version(1.1.6) with removing peer dependencies, otherwise there is no way to fix this unless you force every single clients to change there CI / CD scripts.

The install has a peer dependency warning on the missing module but npm assumes the install went well.

@breath103 thanks for the details. We are working on pushing out a new version (1.1.6) with the fix.

An updated version (1.1.6) hs been published to NPM. This should resolve the issue. We will close this issue if we don’t receive any further updates in the next 24 hours.

@abhiksingh Checked the new version. thanks
for anyone having problems with this, i recommend to do npm ls before make deployment package from now on. which will raise error if there is any unmet peer dependencies.

Closing as 1.1.6 released and no further issues reported.


Structured validation framework

In addition to the currently implemented simple chainable validation framework, a more structured version modeled after ow is desired. This will allow more use-cases with vahvista such as function argument and object schema validation.
This will require exposing the two frameworks as different namespaces in a breaking change:
import { simple: v } from "vahvista"; or
import { structured: v } from "vahvista";

vahvista will be deprecated in favor of zod


Fix rustdocs in Units crate

The rustdocs in the Units crate has been reviewed and improved.
Some of the links were missing backticks, these have been added.
Some grammatical changes have been made to improve the documentation.
The use of links was inconsistent and has been changed to have links everywhere that seemed appropriate.
A couple of error headings were added and a description as to why a capital M is not accepted in the denomination for MegaSatoshi or MegaBitcoin.

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Details

0 of 0   changed or added relevant lines in 0 files are covered.
2 unchanged lines in 1 file lost coverage.
Overall coverage remained the same at 83.014%

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2 unchanged lines in 1 file lost coverage.
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2 unchanged lines in 1 file lost coverage.
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2
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Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Details

0 of 0   changed or added relevant lines in 0 files are covered.
2 unchanged lines in 1 file lost coverage.
Overall coverage remained the same at 83.014%

Files with Coverage Reduction
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%

units/src/amount.rs
2
88.09%

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Addressed review comments, split out "Add missing links" into its own commit which was accidentally combined with another commit previously.

Its not super important but we tend to not treat crate names as propper nouns, so we tend to write units instead of Units - at least I believe that is not just me.

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Details

0 of 0   changed or added relevant lines in 0 files are covered.
2 unchanged lines in 1 file lost coverage.
Overall coverage remained the same at 83.014%

Files with Coverage Reduction
New Missed Lines
%

units/src/amount.rs
2
88.09%

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Its not super important but we tend to not treat crate names as propper nouns, so we tend to write units instead of Units - at least I believe that is not just me.

Thanks, I changed the PR heading.  And I think I have addressed all of your comments.

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Details

0 of 0   changed or added relevant lines in 0 files are covered.
2 unchanged lines in 1 file lost coverage.
Overall coverage remained the same at 82.943%

Files with Coverage Reduction
New Missed Lines
%

units/src/amount.rs
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This change shouldn't be in here now :)

Thanks I missed this when removing the backticks.  I have removed the changed.

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Details

0 of 0   changed or added relevant lines in 0 files are covered.
2 unchanged lines in 1 file lost coverage.
Overall coverage remained the same at 82.936%

Files with Coverage Reduction
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units/src/amount.rs
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Removed merge conflict with #2964

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Details

0 of 0   changed or added relevant lines in 0 files are covered.
2 unchanged lines in 1 file lost coverage.
Overall coverage remained the same at 82.933%

Files with Coverage Reduction
New Missed Lines
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units/src/amount.rs
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BOOM! Thanks for sticking with this one @jamillambert


Bazel support: implement extra_action to extract Java CompilationUnits as kindex files [phab:D190]

Created by schroederc at 2015-04-15 22:31:59:

schroederc wrote at 2015-04-15 22:33:02:
Revert BUILD file

zarko accepted this revision at 2015-04-15 22:54:09

schroederc closed via commit aa80110f19ed6981143aa7f9367c57f17ae7bf16 at 2015-04-15 22:54:59