Regions - "500 Internal Server Error" when trying to create a external service link with no alias name. Not able to load stack/user UI anymore.

Rancher versions: Build from https://github.com/alena1108/cattle - "region" branch
network policy manager - leodotcloud/network-policy-manager:regions
Steps to reproduce the problem:Had following setup:
Region1 with environments - "test1","test2"
There were 2 hosts in both the environments.
"network policy manager"  was deployed with "allow within linked services" and deny for all other policies.
From test1 environment:
Create a service test1 with service link pointing to "region1/test2/stack1/service1" with no alias name provided.
NullPointerException exception seen in logs:
2017-12-02 00:43:01,944 DEBUG [:] [] [] [] [ecutorService-7] [i.c.p.c.v.impl.ConfigUpdatePublisher] 		Finished work item agent:133 [180190889]
2017-12-02 00:43:02,132 ERROR [:] [] [] [] [cutorService-15] [o.a.c.m.context.NoExceptionRunnable ] Uncaught exception java.lang.NullPointerException: null
	at io.cattle.platform.iaas.api.filter.service.ServiceOutputFilter.filter(ServiceOutputFilter.java:78)
	at io.github.ibuildthecloud.gdapi.response.impl.ResourceOutputFilterChain.filter(ResourceOutputFilterChain.java:20)
	at io.github.ibuildthecloud.gdapi.request.resource.impl.AbstractBaseResourceManager.convertResponse(AbstractBaseResourceManager.java:200)
	at io.github.ibuildthecloud.gdapi.request.resource.impl.FilteredResourceManager.convertResponse(FilteredResourceManager.java:76)
	at io.github.ibuildthecloud.gdapi.request.resource.impl.FilteredResourceManager.convertResponse(FilteredResourceManager.java:76)
	at io.github.ibuildthecloud.gdapi.request.resource.impl.FilteredResourceManager.convertResponse(FilteredResourceManager.java:76)
	at io.github.ibuildthecloud.gdapi.request.resource.impl.FilteredResourceManager.convertResponse(FilteredResourceManager.java:76)
	at io.github.ibuildthecloud.gdapi.request.resource.impl.FilteredResourceManager.convertResponse(FilteredResourceManager.java:76)
	at io.github.ibuildthecloud.gdapi.request.resource.impl.FilteredResourceManager.convertResponse(FilteredResourceManager.java:76)
	at io.github.ibuildthecloud.gdapi.request.resource.impl.FilteredResourceManager.convertResponse(FilteredResourceManager.java:76)
	at io.github.ibuildthecloud.gdapi.request.resource.impl.FilteredResourceManager.convertResponse(FilteredResourceManager.java:76)
	at io.github.ibuildthecloud.gdapi.request.resource.impl.FilteredResourceManager.convertResponse(FilteredResourceManager.java:76)
	at io.cattle.platform.iaas.api.change.impl.ResourceChangeEventProcessor.processEvent(ResourceChangeEventProcessor.java:57)
	at io.cattle.platform.api.pubsub.subscribe.NonBlockingSubscriptionHandler.postProcess(NonBlockingSubscriptionHandler.java:106)
	at io.cattle.platform.api.pubsub.subscribe.NonBlockingSubscriptionHandler$1.onEvent(NonBlockingSubscriptionHandler.java:82)
	at io.cattle.platform.eventing.impl.AbstractThreadPoolingEventService$2.doRun(AbstractThreadPoolingEventService.java:141)
	at org.apache.cloudstack.managed.context.NoExceptionRunnable.runInContext(NoExceptionRunnable.java:15)
	at org.apache.cloudstack.managed.context.ManagedContextRunnable$1.run(ManagedContextRunnable.java:49)
	at org.apache.cloudstack.managed.context.impl.DefaultManagedContext$1.call(DefaultManagedContext.java:55)
	at org.apache.cloudstack.managed.context.impl.DefaultManagedContext.callWithContext(DefaultManagedContext.java:108)
	at org.apache.cloudstack.managed.context.impl.DefaultManagedContext.runWithContext(DefaultManagedContext.java:52)
	at org.apache.cloudstack.managed.context.ManagedContextRunnable.run(ManagedContextRunnable.java:46)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)

After this error is seen , I tried deleting the service which was stuck in "registering" state which also fails.
Now I am not able to load UI to display user stacks . "500 Internal Server Error" encountered when UI is trying to list all services.

@alena I dont see service stuck in "registering" state anymore. But in this case , do we expect the API to error out ? How will the user be able to use this external service link in this case .

@sangeethah for now, we just ignore the error. But I can add an extra API validation to error out when alias is absent while region is present in the link

Tested with Rancher server version-v1.6.13-rc6 .
When attempting to create services with external service link with no alias name following error is presented to the user -  Setservicelinks Error:Validation failed in API: name is required


Easyfax missing important monster causing abort

VuvuzelaFeb6FailedFax.txt
This is the second time I've encountered this issue, and it seems to be due to Easyfax missing some monsters now. When Loopsmol starts trying to Fax a Camel Toe, it goes through the process of realizing that the fax has still not been delivered 6 times, then exits out with an error.
Looking in-game when this happens, I find that I have messages in in-game chat messages with EasyFax saying

[16:35] vuvuzela virtuoso: Camel's Toe
[21:58] Easyfax: I couldn't find that monster. Please look here [link] http:// sourceforge.net/p/ easyfax/code/HEAD/ tree/list for a list of monster names.

I am able to manually intervene once things error out, and request a fax from OnlyFax instead, then rerun and all works fine.
I know that there is already a boolean option to utilize Faxbots or not, but obviously it would be ideal to be able to still make use of a fax, so it would be nice if either Onlyfax could be given request priority, and/or if after a couple failures, that the loop script would try an alternate faxbot instead.

#15

Thank you! I am no longer experiencing the issue.


Bug | int a = true;

[19:04:35] [Server thread/WARN]: java.lang.IllegalArgumentException: Can not set boolean field net.minecraft.server.v1_9_R2.EntityArmorStand.bz to java.lang.Integer
version spigot 1.9.4
magic version: 6.2

This was fixed a while back, sorry for not letting you know!


DTLS: Receiving data when after triggering a renegotiation

Hi all,
I'm facing a problem and I'm not 100% if the problem is within my code or OpenSSL.
I have a DTLS/UDP connection between a DTLS/UDP character generator and a echo server.
https://github.com/nplab/DTLS-Examples/blob/master/src/dtls_udp_chargen.c
https://github.com/nplab/DTLS-Examples/blob/master/src/dtls_sctp_echo.c
The chargen client connects to the echo server and transmits data.
The echo server replies.
The chargen clients randomly triggers renegotiations from time to time, see here.
But, this fails.
SSL write error: error:141020F5:SSL routines:dtls1_read_bytes:unexpected record (5)

It seems that if the client throws an error when receiving data from the server after triggering the renegotiation process.
How to reproduce:

Download and the Repo and modify the Makefile if necessary.
Generate certificates by calling the cert .sh
Start the server ./dtls_udp_chargen -v
Start the client ./dtls_udp_chargen -v <IP_ADDRESS>

Client output
$ ./dtls_udp_chargen -v <IP_ADDRESS>

Using OpenSSL 1.1.1i  8 Dec 2020

Connected to <IP_ADDRESS>
wrote num 0 with 100 bytes
read num 0 with 100 bytes
Now renegotiate...
SSL write error: error:141020F5:SSL routines:dtls1_read_bytes:unexpected record (5)

Server output
$ ./dtls_udp_chargen -v

Using OpenSSL 1.1.1i  8 Dec 2020

Thread 70000061c000: accepted connection from ::ffff:<IP_ADDRESS>:53965
Thread 70000061c000: wrote num 0 with 100 bytes
Thread 70000061c000: wrote num 1 with 100 bytes
Thread 70000061c000: wrote num 2 with 100 bytes
Thread 70000061c000: wrote num 3 with 100 bytes
Thread 70000061c000: wrote num 4 with 100 bytes
Thread 70000061c000: wrote num 5 with 100 bytes
Thread 70000061c000: read num 0 with 100 bytes
Thread 70000061c000: wrote num 6 with 100 bytes
Thread 70000061c000: wrote num 7 with 100 bytes
Thread 70000061c000: wrote num 8 with 100 bytes
Thread 70000061c000: wrote num 9 with 100 bytes
Socket read error: Unexpected error! (errno = 61)
Thread 70000061c000: done, connection closed.

Can you help us with this issue?
Best regards
Felix

Probably the "easiest" thing to do in terms of tracking down what's happening, would be to get a packet capture of the exchange while using a NULL-encryption cipher, so the message payloads are visible.
(I'm not in a good position to attempt to do so myself locally at the moment, though.)
Also, to clarify, when you say "this fails" and quote SSL write error: error:141020F5:SSL routines:dtls1_read_bytes:unexpected record (5), is that logged on the DTLS client or server?

Sure!
dtls.pcapng.zip
CCing @tuexen

The SSL write error: error occurs on the client which triggers the renegotiation.

Marking as inactive, to be closed at the end of 3.4 dev barring further input


Error during execution docker-compose

Hello ,
docker-compose does not want to run any solution please ?

<EMAIL_ADDRESS>start /usr/src/app
plugin_1  | > node ./plugin/index.js
plugin_1  |
plugin_1  | Plugin is starting
plugin_1  | /usr/src/app/node_modules/devicehive-plugin-core/src/PluginCore.js:21
plugin_1  |             request(options, (err, response, body) => err || body.error ? reject(err || body.message) : resolve(body));
plugin_1  |                                                                   ^
plugin_1  |
plugin_1  | TypeError: Cannot read property 'error' of undefined

Closing as duplicate (see https://docs.devicehive.com/discuss/5af9a21c74f9be000347573d)


can't access sonarqube

unable to load sonar webpage

Is the port 8082,8081 opened?
From: Sumanth-lsvs<EMAIL_ADDRESS>Sent: Tuesday, October 6, 2020 5:35 AM
To: QT-DevOps/DevOpsIssues<EMAIL_ADDRESS>Cc: Subscribed<EMAIL_ADDRESS>Subject: [QT-DevOps/DevOpsIssues] can't access sonarqube (#967)
unable to load sonar webpage
[Screenshot (140)]https://user-images.githubusercontent.com/68912089/95144181-05b84680-0746-11eb-9900-6ae6869768d0.png
[Screenshot (141)]https://user-images.githubusercontent.com/68912089/95144182-05b84680-0746-11eb-8511-ccf0f41736a5.png
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Are the ports opened can you share the security group inbound rules
From: Sumanth-lsvs<EMAIL_ADDRESS>Sent: Tuesday, October 6, 2020 5:35 AM
To: QT-DevOps/DevOpsIssues<EMAIL_ADDRESS>Cc: Subscribed<EMAIL_ADDRESS>Subject: [QT-DevOps/DevOpsIssues] can't access sonarqube (#967)
unable to load sonar webpage
[Screenshot (140)]https://user-images.githubusercontent.com/68912089/95144181-05b84680-0746-11eb-9900-6ae6869768d0.png
[Screenshot (141)]https://user-images.githubusercontent.com/68912089/95144182-05b84680-0746-11eb-8511-ccf0f41736a5.png
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the underlined part from the above pic is the one line that I got different from the youtube video sir
I didn't understand what went wrong and I tried multiple times, I got that line differently all the times sir.
,

Sir is it a t2.micro?
From: Sumanth-lsvs<EMAIL_ADDRESS>Sent: Thursday, October 8, 2020 8:08 AM
To: QT-DevOps/DevOpsIssues<EMAIL_ADDRESS>Cc: shaikkhajaibrahim<EMAIL_ADDRESS>Comment<EMAIL_ADDRESS>Subject: Re: [QT-DevOps/DevOpsIssues] can't access sonarqube (#967)
[Screenshot (140)_LI]https://user-images.githubusercontent.com/68912089/95408347-40a8ae80-08ed-11eb-8a0f-2534c4f3e728.jpg
the underlined part from the above pic is the one line that I got different from the youtube video sir
I didn't understand what went wrong and I tried multiple times, I got that line differently all the times sir.
,
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yes sir it is t2.micro
should i do it in t2.medium

Yes sir
Get Outlook for Androidhttps://aka.ms/ghei36

From: Sumanth-lsvs<EMAIL_ADDRESS>Sent: Thursday, October 8, 2020 9:07:29 PM
To: QT-DevOps/DevOpsIssues<EMAIL_ADDRESS>Cc: shaikkhajaibrahim<EMAIL_ADDRESS>Comment<EMAIL_ADDRESS>Subject: Re: [QT-DevOps/DevOpsIssues] can't access sonarqube (#967)
yes sir it is t2.micro
should i do it in t2.medium
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Thank you sir


add decorator

Issue #, if available:
Description of changes:
By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

This allows following:

cid-cmd status --region_name us-east-2
cid-cmd --region_name eu-west-2 status


ofac: call 'GET /search?q=..' to also check SDN alt names

Codecov Report

Merging #109 into master will not change coverage.
The diff coverage is 0%.


Add the metrics for trainer.

Signed-off-by: wxywb<EMAIL_ADDRESS>

Codecov Report

Merging #509 (c3f38da) into training (05f261c) will increase coverage by 0.82%.
The diff coverage is 96.80%.

@@             Coverage Diff              @@
##           training     #509      +/-   ##
============================================
+ Coverage     57.66%   58.49%   +0.82%
============================================
  Files           150      151       +1
  Lines          5783     5908     +125
  Branches        846      848       +2
============================================
+ Hits           3335     3456     +121
- Misses         2230     2234       +4
  Partials        218      218

Impacted Files
Coverage Δ

towhee/trainer/metrics.py
96.80% <96.80%> (ø)

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

/lgtm

/approve


Help wanted: Catalog performance testing

Hi,
We are looking for help measuring the performance of the software catalog to potentially find room for improvements. There have been improvements for large catalogs in recent months but we hope to improve the situation even further but we would like to back it up with data. We therefore added experimental prometheus metrics to help out measuring. If run a large software catalog, we're interested in hearing from you!
Currently these metrics and other are emitted when enabled:
catalog_registered_locations_count
catalog_relations_count
catalog_entities_count
catalog_processing_queue_delay_seconds - The amount of delay between being scheduled for processing, and the start of actually being processed
catalog_processors_duration_seconds - Time spent executing catalog processors
catalog_processing_duration_seconds - Time spent executing the full processing flow

Information we would like to receive in your reply:

Catalog version
Amounts of entities in the catalog, output from catalog_entities_count metric
Relations, output from catalog_relations_count metric
Queue delay, output from catalog_processing_queue_delay_seconds, it’s best to leave the catalog running for a while as this number will be high for a newly started catalog with a backlog of work.
Processing duration catalog_processing_duration_seconds{quantile=~'0.99|0.5'}
CPU & memory pressure of the catalog/database instance together with available cores/memory.

How do I instrument?
The process for adding them is currently manual as we do not make any guarantees about the future format. Of course we want instrumentations to all parts of the backend but agnostic tools like OpenTelemetry are still not far enough in its development yet. We have for now settled on prom-client to get Prometheus metrics but this WILL change in the future.
Add dependencies
"express-prom-bundle": "^6.3.6",
"prom-client": "^13.2.0",

Create metrics.ts next to your catalog with this content
https://github.com/backstage/backstage/blob/6277060d72748ebd4edcf6dae4fd8eac1d23d470/packages/backend/src/metrics.ts
Initialise the metric:
https://github.com/backstage/backstage/blob/6277060d72748ebd4edcf6dae4fd8eac1d23d470/packages/backend/src/index.ts#L76
Add the metrics endpoint:
https://github.com/backstage/backstage/blob/6277060d72748ebd4edcf6dae4fd8eac1d23d470/packages/backend/src/index.ts#L129
Configure your prometheus instance to scrape the metrics.
Thanks!

Would like to hand in data, but we are still on the old backend 😞 We are still hanging on not being able to force a reimport #6775

@Fox32 I expected you guys to be running the latest and greatest! 😅
It hurts to hear that you are still on the old catalog because of lack of ability to trigger a refresh. It does not sound like a hard thing to implement so let's continue the discussion on that in the other thread.

catalog_entities_count{kind="component"} 384
catalog_entities_count{kind="system"} 381
catalog_entities_count{kind="location"} 760
catalog_entities_count{kind="api"} 29
catalog_relations_count 2258
catalog_processing_queue_delay_seconds{quantile="0.5"} 0.577625
catalog_processing_queue_delay_seconds{quantile="0.999"} 0.9949953333333333
catalog_processing_duration_seconds{quantile="0.5",result="changed"} 0.304637286
catalog_processing_duration_seconds{quantile="0.99",result="changed"} 0.559695679

Really appreciate the instrumentation. We have been able to set some alerts based on the catalog numbers, looking forward to other parts (techdocs, scaffolder, etc) being monitored too. Potentially providing a hook for plugin-authors to also include their own metrics, certainly that would be useful for our closed source plugins.

@julioz Thank you for sharing!
A realization I had when looking at the numbers is that our queue poll interval is 1s, so a healthy p999 queue delay is gonna be right around 1s, and p5 at 0.5s

Sharing metrics from our org:
catalog_entities_count{kind="component"} 623 catalog_entities_count{kind="resource"} 1.95k catalog_entities_count{kind="location"} 2.79k catalog_entities_count{kind="api"} 1.45k catalog_relations_count 546.88k catalog_processing_queue_delay_seconds{quantile="0.5"}<PHONE_NUMBER> catalog_processing_queue_delay_seconds{quantile="0.999"} 512576.773 catalog_processors_duration_seconds{quantile="0.5",result="ok"} 0.21001975 catalog_processors_duration_seconds{quantile="0.99",result="ok"} 0.4275464

@sonali-mishra-94 Thank you for sharing!
This looks like something every interesting to look into further, because the queue delay is definitely not where we would want it! 3 days? O_O
I'm wondering if you're seen issue with entities being updated very slowly or other things misbehaving? It could also be a bug in our metrics but we should definitely figure out what's up either way!
I'm also curious about the number of relations, are you able to share a bit more about your ingestion setup and if you generate any additional relations and so on?
And then finally are you running a plain deployment in docker with a single instance or something else?

@Rugvip I just edited the comment with correct data. Sorry about earlier, I copied the wrong data

@sonali-mishra-94 aha, that looks much more reasonable x)

@Fox32 are running the latest catalog now? 😉

@Fox32 are running the latest catalog now? 😉

Have to handover to @dhenneke for that

But I can share some first values from our test instance:

Catalog version: https://github.com/backstage/backstage/commit/ab2e915c6ce4d7cf35e67e277a9fdc0be78bedca (should be ^0.14.0)

Metrics:
catalog_entities_count{kind="location"} 102
catalog_entities_count{kind="component"} 170
catalog_entities_count{kind="system"} 39
catalog_entities_count{kind="api"} 70
catalog_entities_count{kind="domain"} 10
catalog_entities_count{kind="template"} 3
catalog_entities_count{kind="solution"} 14
catalog_entities_count{kind="user"} 143
catalog_entities_count{kind="group"} 37

catalog_relations_count 1852

catalog_processing_queue_delay_seconds{quantile="0.5"} 0.6284156517963746
catalog_processing_queue_delay_seconds{quantile="0.95"} 1.278494934086629
catalog_processing_queue_delay_seconds_sum 10626.415999999996
catalog_processing_queue_delay_seconds_count 13737

catalog_processing_duration_seconds{quantile="0.5",result="changed"} 0.20223802145185185
catalog_processing_duration_seconds{quantile="0.95",result="changed"} 1.4494809654958325
catalog_processing_duration_seconds_sum{result="changed"}<PHONE_NUMBER>269991
catalog_processing_duration_seconds_count{result="changed"} 1153
catalog_processing_duration_seconds{quantile="0.5",result="unchanged"} 0.014919155300449544
catalog_processing_duration_seconds_sum{result="unchanged"} 2818.016394247009
catalog_processing_duration_seconds_count{result="unchanged"} 12584

catalog_processors_duration_seconds{quantile="0.5",result="ok"} 0.0033221048373567354
catalog_processors_duration_seconds{quantile="0.95",result="ok"} 1.117828550139825
catalog_processors_duration_seconds_sum{result="ok"} 3166.562075741002
catalog_processors_duration_seconds_count{result="ok"} 13737

I am not seeing catalog related data on the metrics @jhaals, I can see node and system metrics on /metrics,  what could be the issue.


No JSON object could be decoded

I've tried using both, Python 2 and 3 for running this package, however, I'm getting a similar error for both.
ValueError: No JSON object could be decoded
Kindly let me know what changes I should make to run the same. So far, I'm running the package in an empty python environment with just the basic functionality.
Thank you!

The server is live from today. Please try again and it should be working. Please post any issues you find. New functionality will be added going forward and existing models will be updated constantly to increase accuracy.


Add registration test

This is currently throwing the error:

RuntimeError: Exception thrown in SimpleITK ImageRegistrationMethod_Execute: /tmp/SimpleITK-build/ITK-prefix/include/ITK-5.3/itkMattesMutualInformationImageToImageMetricv4.hxx:307:
E       ITK ERROR: MattesMutualInformationImageToImageMetricv4(0x55bba3d302b0): All samples map outside moving image buffer. The images do not sufficiently overlap. They need to be initialized to have more overlap before this metric will work. For instance, you can align the image centers by translation.

The first two rotational registrations seem to be working fine, and this comes from the final similarity registration. As far as I can tell the initial transformation parmaters are all fine. @JosephBrunet wondering if you've seen this error before and have any ideas?

If I set the metric sampling strategy to R.NONE (ie use all the pixels in the image), this works. And if I keep it as R.RANDOM, but increase the sampling percentage to 0.1 the registration runs a bit but then crashes. So I think this is a combination of having a low sampling percentage and a very small moving image size (in the test I've currently added). Will have a think of a good way to work around this.


tmux-git: No error, blank screen

Hi. I am having issues with tmux-git. After execution of tmux command nothing happens, and terminal hangs. It does not respond to any keys (nor ctrl+C). The same happens on a fresh install of msys.
My tmux version:
local/tmux-git 2.1.61.gc975de2-1
Logs from tmux -vvvv
http://www.speedyshare.com/XM3Da/tmux-logs.zip
Any ideas, what could be the source of this problem?

we found same issue on https://github.com/Alexpux/MSYS2-packages/issues/376.

Can someone try bringing these issues up with t-mux upstream?

Looks like its still there? No fix till now?

That's not occurred on current version. (at least on my environment...)


docs: Rendering Error for GRPCRoute page

What type of PR is this?

/kind documentation
What this PR does / why we need it:
The page does not render at https://gateway-api.sigs.k8s.io/api-types/grpcroute/

It's referencing a file that is missing from the path.

Which issue(s) this PR fixes:

Fixes #
Does this PR introduce a user-facing change?:

NONE

ah, great catch, thanks @robertwenquan! I missed this when removing GRPCRoute experimental examples.
/approve
/lgtm


Please release 0.12

Mostly interested in a tagged release because of the recent change of the deployment target to 8.0. Using 7.0 breaks integration builds for TestFlight.

@st3fan not sure I follow? There is no v0.12.0?

@st3fan I see you're after a version that works for iOS 7.0? Are you using it on an enterprise iOS 7.0 app where you can deploy frameworks?

Hey Robert, let me explain. We are using SnapKit in Firefox for iOS. Wonderful library, thank you very much.
Firefox is for iOS 8 and up only so we include SnapKit as a framework. Now, when I include 0.11, everything builds and runs fine. But when I submit to the App Store, the application validation process fails horribly with errors like in this screenshot:
https://bug1158895.bugzilla.mozilla.org/attachment.cgi?id=8598096
This all looks pretty scary but the simple fix to make all of these go away is to change the deployment target of SnapKit to 8.0.
You already changed the deployment target to 8.0, but it happened after 0.11 and no release has been tagged yet. My request to tag a v0.12 release is just because we like to clearly pin our dependencies instead of using master.

@st3fan Ahh! I see it was a minor change I didn't catch as queued for release sorry about that.
I'll get this out over the weekend.

@st3fan now in trunk, let me know if this doesn't resolve your issues!


Add Support for Mac Catalyst

The SDK contains a bunch of binary frameworks which are not compiled for the x86_64-maccatalyst architecture which is necessary to support Mac Catalyst (formerly UIKit for Mac).
Is resolving this in the pipeline?

Hi @diederich no plans for mac. I will check how big effort it is and I will talk with product management. thanks for the idea.

Thanks @stefan-sedlak. I looked through the repo and the SDK looks pretty neat. If there are no other binary dependencies, it might be just flipping a switch / delivering XCFrameworks.
We're currently using Braintree, but there's no support planned (https://github.com/braintree/braintree_ios/issues/479), so we're actively looking for alternatives.
🙏🙏🙏

@diederich We use no 3rd party binaries in core/card frameworks. Maybe we can enable it just for core/card frameworks. I guess you do not need card scanner on desktop 😄

Sounds fantastic! And yes, that would be a big step forward, thank you for considering!


Should we / can we calculate some kind of coverage metric?

For each release, we have a bunch of tests, but there's no easy way of getting an overview of how much of the schema is covered by tests. Should we try to add something like that, or do we think that just the "key-complete" CITATION.cff is enough?

If there is a relatively easy way (e.g., a GH Action) for this, I'd be for introducing a coverage test.


List/Tree: Screenreader does not read the role of the buttons properly

Environment Details:
VSCode Version : 1.24.0
OS Version : Win10
Additional Details:
MAS Violated : MAS 1.3.1
ScreenReader Versions : NVDA2018.1.1
Repro Steps:

Navigate to Status Bar at the bottom and move to notifications.
Move to any notification that appears at the screen.
Navigate to any button inside the notification.

Actual:
ScreenReader does not read the role as buttons for all the notification buttons.
Also does not read the name as well as role for close, settings buttons within the notification window.
Expected:
The screenreader should read all the buttons along with role as buttons and also should read the name and role for close and settings buttons. Screenreader should read the content info along with first button only.
Recommendations:
Refer below link which is repository of bug fixes code snippets:
https://microsoft.sharepoint.com/teams/msenable/mas/Pages/browse-fixes.aspx
User Impact:
The screenreader users will not be able to know all the controls present on the screen along with their purpose.
MAS Reference:
MAS 1.3.1 - https://microsoft.sharepoint.com/teams/msenable/_layouts/15/WopiFrame.aspx?sourcedoc={54f28d1f-a2d1-4dcd-84e1-5c9b87e8aba4}
Attachment For Reference:
A11y_VSCode_StatusBar_ScreenReader_Notification.pptx
Does this issue occur when all extensions are disabled?: Yes

This seems to be true for anything I focus within a list item.

This seems to be an Electron issue. When I copy-paste our HTML to vanilla Chrome, NVDA correctly reads the button roles.

Nice investigation skillz.


Triage the miette breaking updates

Updating to the latest version of miette pulls in a crate, sys, which is not available in all of our targets. This issue tracks the work of investigating if we can update without sys, and if we want to update to the latest version in general. Deciding we are okay sticking with the current version would be a valid solution to this issue, but we need to do some research to make that decision.

Looks like https://github.com/zkat/miette/pull/349 should fix this.


Box lines around every element and some sort (may have be caused by color inversion on mac)

Issue Type: Bug
My VSCode has changed to look like this, solid lines are showing up around elements and also in the indentation level of code.

A couple of weeks ago, I attempted to disable command+q on the mac because I kept accidentally closing the app I was using.
The instructions I followed for that issue was found here How to disable command-Q for Quit?
This was all working ok for a couple of weeks, every now and then I press command+q and instead of quitting the application, my desktop colors would invert and so I would just press command+q again and my system would restore to normal colors.
Today this happened again, but it also screwed around with my VSCode as seen in the image above.
I have turned off the color inversion keyboard setting and I have rebooted the Mac, but the vscode issue has not resolved.
 You can change this by opening the Command Palette and searching for Preferences: Color Theme.

From your screenshots, it looks like the VS Code theme changed to High Contrast. You can change this by opening the Command Palette by pressing F1 or by clicking on View > Command Palette…, and searching for Preferences: Color Theme.

thanks that solved my issue


Update links to new location of readme.md in react-native-windows repo

PR #4731 in react-native-windows repo moved readme.md from the vnext folder to unify them.

Thanks! this also needs to be changed to remove the mention of vnext. But that's separate.


Upgrade to rspec-rails 3.2

Preparing for Rails 4.2 and Ruby 2.2 testing.

Also ignores appraisal lockfiles from git as per the suggestion from the documentation.

If there aren't any other .stub calls, this lgtm.


Accuracy when deployed on Kubernetes

CodeCarbon version: 2.3.4
Python version: 3.10.12
Operating System: Ubuntu 22.04 (Docker base)

Description
I have docker images that are used to train small ML models. These images are used to spin up containers on services such as Coreweave who use K8s for the same. I recently came to know about and added codecarbon to calculate the total resource usage. An example output (offline) is below:
{
  "timestamp": "2024-03-30T11:27:11",
  "project_name": "finetuning",
  "run_id": "84ad0f5d-5aab-4642-bd15-c6843671bf4c",
  "duration":<PHONE_NUMBER>4482727,
  "emissions": 0.019239630322990336,
  "emissions_rate": 0.00006592440033011917,
  "cpu_power":<PHONE_NUMBER>8414944,
  "gpu_power": 15.891167553168648,
  "ram_power":<PHONE_NUMBER>1359253,
  "cpu_energy": 0.015584842142308182,
  "gpu_energy": 0.012249018965878378,
  "ram_energy": 0.022895533826661152,
  "energy_consumed": 0.050729394934847696,
  "country_name": "United States",
  "country_iso_code": "USA",
  "region": null,
  "cloud_provider": "",
  "cloud_region": "",
  "os": "Linux-5.19.17-coreweave-x86_64-with-glibc2.35",
  "python_version": "3.10.12",
  "codecarbon_version": "2.3.4",
  "cpu_count": 128,
  "cpu_model": "AMD EPYC 7513 32-Core Processor",
  "gpu_count": 1,
  "gpu_model": "1 x NVIDIA RTX A5000",
  "longitude": null,
  "latitude": null,
  "ram_total_size":<PHONE_NUMBER>695801,
  "tracking_mode": "machine",
  "on_cloud": "N",
  "pue": 1
}

The container is limited to 4x CPU, 16 GB RAM, 1x GPU. I am aware that CPU/RAM counts/sizes can be reflective of the entire system (esp. on Linux) so I'm not concerned about that.
What I am wondering is if the accuracy of the power usage of the different components and the emissions is affected because of the same ?
e.g., Looking up on Google, the CPU above has a TDP of 200W. So, for using 4 cores, 188W seems a lot. Similar with RAM, 283W for 16GB RAM. Though, GPU stats seems to be correct. And the GPU power usage seems to be incorrect. In the actual logs, it updated correctly with the actual usage but in the final emissions, it seems to wrong.
Am I incorrect in thinking that the final_emissions is the average or the overall stats ?
Is there anything I can do to "correct" this ? If not, can I use those numbers and calculate the right values ?
The complete log:
  warnings.warn(
[codecarbon INFO @ 11:22:18] offline tracker init
Starting training
/opt/runtime/lib/python3.10/site-packages/accelerate/accelerator.py:432: FutureWarning: Passing the following arguments to `Accelerator` is deprecated and will be removed in version 1.0 of Accelerate: dict_keys(['dispatch_batches', 'split_batches', 'even_batches', 'use_seedable_sampler']). Please pass an `accelerate.DataLoaderConfiguration` instead:
dataloader_config = DataLoaderConfiguration(dispatch_batches=None, split_batches=False, even_batches=True, use_seedable_sampler=True)
  warnings.warn(
[codecarbon INFO @ 11:22:23] [setup] RAM Tracking...
[codecarbon INFO @ 11:22:23] [setup] GPU Tracking...
[codecarbon INFO @ 11:22:23] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 11:22:23] [setup] CPU Tracking...
[codecarbon INFO @ 11:22:23] Tracking Intel CPU via RAPL interface
[codecarbon INFO @ 11:22:24] >>> Tracker's metadata:
[codecarbon INFO @ 11:22:24]   Platform system: Linux-5.19.17-coreweave-x86_64-with-glibc2.35
[codecarbon INFO @ 11:22:24]   Python version: 3.10.12
[codecarbon INFO @ 11:22:24]   CodeCarbon version: 2.3.4
[codecarbon INFO @ 11:22:24]   Available RAM : 755.442 GB
[codecarbon INFO @ 11:22:24]   CPU count: 128
[codecarbon INFO @ 11:22:24]   CPU model: AMD EPYC 7513 32-Core Processor
[codecarbon INFO @ 11:22:24]   GPU count: 1
[codecarbon INFO @ 11:22:24]   GPU model: 1 x NVIDIA RTX A5000
[codecarbon INFO @ 11:22:35] Energy consumed for RAM : 0.001181 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:22:35] Energy consumed for all GPUs : 0.000637 kWh. Total GPU Power :<PHONE_NUMBER>7477933 W
[codecarbon INFO @ 11:22:35] Energy consumed for all CPUs : 0.000810 kWh. Total CPU Power :<PHONE_NUMBER>022706 W
[codecarbon INFO @ 11:22:35] 0.002628 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:22:39] Energy consumed for RAM : 0.001181 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:22:39] Energy consumed for all GPUs : 0.000881 kWh. Total GPU Power :<PHONE_NUMBER>5674938 W
[codecarbon INFO @ 11:22:39] Energy consumed for all CPUs : 0.000818 kWh. Total CPU Power :<PHONE_NUMBER>3791228 W
[codecarbon INFO @ 11:22:39] 0.002880 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:22:50] Energy consumed for RAM : 0.002361 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:22:50] Energy consumed for all GPUs : 0.001539 kWh. Total GPU Power :<PHONE_NUMBER>2241614 W
[codecarbon INFO @ 11:22:50] Energy consumed for all CPUs : 0.001626 kWh. Total CPU Power :<PHONE_NUMBER>819956 W
[codecarbon INFO @ 11:22:50] 0.005526 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:22:54] Energy consumed for RAM : 0.002361 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:22:54] Energy consumed for all GPUs : 0.001785 kWh. Total GPU Power :<PHONE_NUMBER>0786847 W
[codecarbon INFO @ 11:22:54] Energy consumed for all CPUs : 0.001626 kWh. Total CPU Power :<PHONE_NUMBER>722918 W
[codecarbon INFO @ 11:22:54] 0.005772 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:23:05] Energy consumed for RAM : 0.003541 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:23:05] Energy consumed for all GPUs : 0.002442 kWh. Total GPU Power :<PHONE_NUMBER>6394674 W
[codecarbon INFO @ 11:23:05] Energy consumed for all CPUs : 0.002403 kWh. Total CPU Power :<PHONE_NUMBER>3020192 W
[codecarbon INFO @ 11:23:05] 0.008386 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:23:09] Energy consumed for RAM : 0.003541 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:23:09] Energy consumed for all GPUs : 0.002687 kWh. Total GPU Power :<PHONE_NUMBER>0699567 W
[codecarbon INFO @ 11:23:09] Energy consumed for all CPUs : 0.002408 kWh. Total CPU Power :<PHONE_NUMBER>8359275 W
[codecarbon INFO @ 11:23:09] 0.008636 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:23:20] Energy consumed for RAM : 0.004721 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:23:20] Energy consumed for all GPUs : 0.003347 kWh. Total GPU Power :<PHONE_NUMBER>2371734 W
[codecarbon INFO @ 11:23:20] Energy consumed for all CPUs : 0.003204 kWh. Total CPU Power :<PHONE_NUMBER>4458245 W
[codecarbon INFO @ 11:23:20] 0.011273 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:23:24] Energy consumed for RAM : 0.004721 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:23:24] Energy consumed for all GPUs : 0.003595 kWh. Total GPU Power :<PHONE_NUMBER>9107558 W
[codecarbon INFO @ 11:23:24] Energy consumed for all CPUs : 0.003219 kWh. Total CPU Power :<PHONE_NUMBER>3781467 W
[codecarbon INFO @ 11:23:24] 0.011535 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:23:35] Energy consumed for RAM : 0.005901 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:23:35] Energy consumed for all GPUs : 0.004253 kWh. Total GPU Power :<PHONE_NUMBER>9166553 W
[codecarbon INFO @ 11:23:35] Energy consumed for all CPUs : 0.004038 kWh. Total CPU Power :<PHONE_NUMBER>9462683 W
[codecarbon INFO @ 11:23:35] 0.014193 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:23:39] Energy consumed for RAM : 0.005902 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:23:39] Energy consumed for all GPUs : 0.004505 kWh. Total GPU Power :<PHONE_NUMBER>1052025 W
[codecarbon INFO @ 11:23:39] Energy consumed for all CPUs : 0.004036 kWh. Total CPU Power :<PHONE_NUMBER>9519385 W
[codecarbon INFO @ 11:23:39] 0.014443 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:23:50] Energy consumed for RAM : 0.007082 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:23:50] Energy consumed for all GPUs : 0.005159 kWh. Total GPU Power :<PHONE_NUMBER>9322924 W
[codecarbon INFO @ 11:23:50] Energy consumed for all CPUs : 0.004802 kWh. Total CPU Power :<PHONE_NUMBER>489947 W
[codecarbon INFO @ 11:23:50] 0.017043 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:23:54] Energy consumed for RAM : 0.007082 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:23:54] Energy consumed for all GPUs : 0.005412 kWh. Total GPU Power :<PHONE_NUMBER>5723416 W
[codecarbon INFO @ 11:23:54] Energy consumed for all CPUs : 0.004817 kWh. Total CPU Power :<PHONE_NUMBER>9600733 W
[codecarbon INFO @ 11:23:54] 0.017311 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:24:05] Energy consumed for RAM : 0.008262 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:24:05] Energy consumed for all GPUs : 0.006066 kWh. Total GPU Power :<PHONE_NUMBER>0905812 W
[codecarbon INFO @ 11:24:05] Energy consumed for all CPUs : 0.005651 kWh. Total CPU Power :<PHONE_NUMBER>1379754 W
[codecarbon INFO @ 11:24:05] 0.019979 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:24:09] Energy consumed for RAM : 0.008262 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:24:09] Energy consumed for all GPUs : 0.006319 kWh. Total GPU Power :<PHONE_NUMBER>6397248 W
[codecarbon INFO @ 11:24:09] Energy consumed for all CPUs : 0.005678 kWh. Total CPU Power :<PHONE_NUMBER>5997192 W
[codecarbon INFO @ 11:24:09] 0.020259 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:24:20] Energy consumed for RAM : 0.009442 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:24:20] Energy consumed for all GPUs : 0.006972 kWh. Total GPU Power :<PHONE_NUMBER>0166227 W
[codecarbon INFO @ 11:24:20] Energy consumed for all CPUs : 0.006490 kWh. Total CPU Power :<PHONE_NUMBER>8297917 W
[codecarbon INFO @ 11:24:20] 0.022904 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:24:24] Energy consumed for RAM : 0.009442 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:24:24] Energy consumed for all GPUs : 0.007226 kWh. Total GPU Power :<PHONE_NUMBER>3215196 W
[codecarbon INFO @ 11:24:24] Energy consumed for all CPUs : 0.006510 kWh. Total CPU Power :<PHONE_NUMBER>3575464 W
[codecarbon INFO @ 11:24:24] 0.023179 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:24:35] Energy consumed for RAM : 0.010623 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:24:35] Energy consumed for all GPUs : 0.007878 kWh. Total GPU Power :<PHONE_NUMBER>0722248 W
[codecarbon INFO @ 11:24:35] Energy consumed for all CPUs : 0.007323 kWh. Total CPU Power :<PHONE_NUMBER>0197082 W
[codecarbon INFO @ 11:24:35] 0.025824 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:24:39] Energy consumed for RAM : 0.010623 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:24:39] Energy consumed for all GPUs : 0.008131 kWh. Total GPU Power :<PHONE_NUMBER>9263292 W
[codecarbon INFO @ 11:24:39] Energy consumed for all CPUs : 0.007321 kWh. Total CPU Power :<PHONE_NUMBER>067735 W
[codecarbon INFO @ 11:24:39] 0.026074 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:24:50] Energy consumed for RAM : 0.011803 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:24:50] Energy consumed for all GPUs : 0.008785 kWh. Total GPU Power :<PHONE_NUMBER>7698433 W
[codecarbon INFO @ 11:24:50] Energy consumed for all CPUs : 0.008121 kWh. Total CPU Power :<PHONE_NUMBER>313449 W
[codecarbon INFO @ 11:24:50] 0.028708 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:24:54] Energy consumed for RAM : 0.011803 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:24:54] Energy consumed for all GPUs : 0.009037 kWh. Total GPU Power :<PHONE_NUMBER>9427808 W
[codecarbon INFO @ 11:24:54] Energy consumed for all CPUs : 0.008117 kWh. Total CPU Power :<PHONE_NUMBER>1593166 W
[codecarbon INFO @ 11:24:54] 0.028958 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:25:05] Energy consumed for RAM : 0.012983 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:25:05] Energy consumed for all GPUs : 0.009691 kWh. Total GPU Power :<PHONE_NUMBER>669453 W
[codecarbon INFO @ 11:25:05] Energy consumed for all CPUs : 0.008899 kWh. Total CPU Power :<PHONE_NUMBER>0137837 W
[codecarbon INFO @ 11:25:05] 0.031573 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:25:09] Energy consumed for RAM : 0.012983 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:25:09] Energy consumed for all GPUs : 0.009944 kWh. Total GPU Power :<PHONE_NUMBER>7455456 W
[codecarbon INFO @ 11:25:09] Energy consumed for all CPUs : 0.008897 kWh. Total CPU Power :<PHONE_NUMBER>0314496 W
[codecarbon INFO @ 11:25:09] 0.031824 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:25:20] Energy consumed for RAM : 0.014163 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:25:20] Energy consumed for all GPUs : 0.010597 kWh. Total GPU Power :<PHONE_NUMBER>2837207 W
[codecarbon INFO @ 11:25:20] Energy consumed for all CPUs : 0.009687 kWh. Total CPU Power :<PHONE_NUMBER>4230418 W
[codecarbon INFO @ 11:25:20] 0.034447 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:25:24] Energy consumed for RAM : 0.014163 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:25:24] Energy consumed for all GPUs : 0.010850 kWh. Total GPU Power :<PHONE_NUMBER>1541042 W
[codecarbon INFO @ 11:25:24] Energy consumed for all CPUs : 0.009676 kWh. Total CPU Power :<PHONE_NUMBER>490736 W
[codecarbon INFO @ 11:25:24] 0.034690 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:25:35] Energy consumed for RAM : 0.015344 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:25:35] Energy consumed for all GPUs : 0.011502 kWh. Total GPU Power :<PHONE_NUMBER>034015 W
[codecarbon INFO @ 11:25:35] Energy consumed for all CPUs : 0.010454 kWh. Total CPU Power :<PHONE_NUMBER>7667594 W
[codecarbon INFO @ 11:25:35] 0.037300 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:25:35] Energy consumed for RAM : 0.015033 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:25:35] Energy consumed for all GPUs : 0.011513 kWh. Total GPU Power :<PHONE_NUMBER>175551 W
[codecarbon INFO @ 11:25:35] Energy consumed for all CPUs : 0.010244 kWh. Total CPU Power :<PHONE_NUMBER>461799 W
[codecarbon INFO @ 11:25:35] 0.036791 kWh of electricity used since the beginning.
/opt/runtime/lib/python3.10/site-packages/codecarbon/output.py:168: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.
  df = pd.concat([df, pd.DataFrame.from_records([dict(data.values)])])
[codecarbon INFO @ 11:25:50] Energy consumed for RAM : 0.016531 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:25:50] Energy consumed for all GPUs : 0.011830 kWh. Total GPU Power : 77.62553631713503 W
[codecarbon INFO @ 11:25:50] Energy consumed for all CPUs : 0.011266 kWh. Total CPU Power :<PHONE_NUMBER>6170003 W
[codecarbon INFO @ 11:25:50] 0.039626 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:26:05] Energy consumed for RAM : 0.017703 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:26:05] Energy consumed for all GPUs : 0.011948 kWh. Total GPU Power : 28.522841009919272 W
[codecarbon INFO @ 11:26:05] Energy consumed for all CPUs : 0.012077 kWh. Total CPU Power :<PHONE_NUMBER>0491823 W
[codecarbon INFO @ 11:26:05] 0.041728 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:26:23] Energy consumed for RAM : 0.019145 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:26:23] Energy consumed for all GPUs : 0.012036 kWh. Total GPU Power : 16.757284426890063 W
[codecarbon INFO @ 11:26:23] Energy consumed for all CPUs : 0.013043 kWh. Total CPU Power :<PHONE_NUMBER>439675 W
[codecarbon INFO @ 11:26:23] 0.044224 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:26:36] Energy consumed for RAM : 0.020095 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:26:36] Energy consumed for all GPUs : 0.012091 kWh. Total GPU Power : 16.46382340960936 W
[codecarbon INFO @ 11:26:36] Energy consumed for all CPUs : 0.013693 kWh. Total CPU Power :<PHONE_NUMBER>148626 W
[codecarbon INFO @ 11:26:36] 0.045879 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:26:51] Energy consumed for RAM : 0.021276 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:26:51] Energy consumed for all GPUs : 0.012159 kWh. Total GPU Power : 16.12618754811998 W
[codecarbon INFO @ 11:26:51] Energy consumed for all CPUs : 0.014516 kWh. Total CPU Power :<PHONE_NUMBER>7184404 W
[codecarbon INFO @ 11:26:51] 0.047951 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:27:06] Energy consumed for RAM : 0.022448 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:27:06] Energy consumed for all GPUs : 0.012224 kWh. Total GPU Power : 15.794729809961883 W
[codecarbon INFO @ 11:27:06] Energy consumed for all CPUs : 0.015288 kWh. Total CPU Power :<PHONE_NUMBER>3273098 W
[codecarbon INFO @ 11:27:06] 0.049960 kWh of electricity used since the beginning.
[codecarbon INFO @ 11:27:11] Energy consumed for RAM : 0.022896 kWh. RAM Power :<PHONE_NUMBER>1359253 W
[codecarbon INFO @ 11:27:11] Energy consumed for all GPUs : 0.012249 kWh. Total GPU Power : 15.891167553168648 W
[codecarbon INFO @ 11:27:11] Energy consumed for all CPUs : 0.015585 kWh. Total CPU Power :<PHONE_NUMBER>8414944 W
[codecarbon INFO @ 11:27:11] 0.050729 kWh of electricity used since the beginning.
/opt/runtime/lib/python3.10/site-packages/codecarbon/output.py:168: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.
  df = pd.concat([df, pd.DataFrame.from_records([dict(data.values)])])

Also tried it today with process tracking_mode. Besides the RAM, everything else seems to be similar to the above.
I'm mainly interested in the total emissions and energy used for the entire training (process) duration. The average power/energy will be nice to have but not necessary.
{
  "timestamp": "2024-03-31T13:05:42",
  "project_name": "finetuning",
  "run_id": "965fba31-6c53-4313-a8f4-7028837133de",
  "duration":<PHONE_NUMBER>585968,
  "emissions": 0.013126898727831899,
  "emissions_rate": 0.0000452831841981431,
  "cpu_power":<PHONE_NUMBER>6518426,
  "gpu_power": 16.64991510011033,
  "ram_power": 1.6509547233581543,
  "cpu_energy": 0.019036346739134652,
  "gpu_energy": 0.015457212018537003,
  "ram_energy": 0.00011831364604057935,
  "energy_consumed": 0.034611872403712225,
  "country_name": "United States",
  "country_iso_code": "USA",
  "region": null,
  "cloud_provider": "",
  "cloud_region": "",
  "os": "Linux-5.19.17-coreweave-x86_64-with-glibc2.35",
  "python_version": "3.10.12",
  "codecarbon_version": "2.3.4",
  "cpu_count": 128,
  "cpu_model": "AMD EPYC 7513 32-Core Processor",
  "gpu_count": 1,
  "gpu_model": "1 x NVIDIA RTX A5000",
  "longitude": null,
  "latitude": null,
  "ram_total_size":<PHONE_NUMBER>459473,
  "tracking_mode": "process",
  "on_cloud": "N",
  "pue": 1.25
}

Complete log:
  warnings.warn(
[codecarbon INFO @ 13:00:51] offline tracker init
Starting training
/opt/runtime/lib/python3.10/site-packages/accelerate/accelerator.py:432: FutureWarning: Passing the following arguments to `Accelerator` is deprecated and will be removed in version 1.0 of Accelerate: dict_keys(['dispatch_batches', 'split_batches', 'even_batches', 'use_seedable_sampler']). Please pass an `accelerate.DataLoaderConfiguration` instead:
dataloader_config = DataLoaderConfiguration(dispatch_batches=None, split_batches=False, even_batches=True, use_seedable_sampler=True)
  warnings.warn(
[codecarbon INFO @ 13:00:54] [setup] RAM Tracking...
[codecarbon INFO @ 13:00:54] [setup] GPU Tracking...
[codecarbon INFO @ 13:00:54] Tracking Nvidia GPU via pynvml
[codecarbon INFO @ 13:00:54] [setup] CPU Tracking...
[codecarbon INFO @ 13:00:54] Tracking Intel CPU via RAPL interface
[codecarbon INFO @ 13:00:55] >>> Tracker's metadata:
[codecarbon INFO @ 13:00:55]   Platform system: Linux-5.19.17-coreweave-x86_64-with-glibc2.35
[codecarbon INFO @ 13:00:55]   Python version: 3.10.12
[codecarbon INFO @ 13:00:55]   CodeCarbon version: 2.3.4
[codecarbon INFO @ 13:00:55]   Available RAM : 755.442 GB
[codecarbon INFO @ 13:00:55]   CPU count: 128
[codecarbon INFO @ 13:00:55]   CPU model: AMD EPYC 7513 32-Core Processor
[codecarbon INFO @ 13:00:55]   GPU count: 1
[codecarbon INFO @ 13:00:55]   GPU model: 1 x NVIDIA RTX A5000
[codecarbon INFO @ 13:01:07] Energy consumed for RAM : 0.000004 kWh. RAM Power : 0.7472505569458008 W
[codecarbon INFO @ 13:01:07] Energy consumed for all GPUs : 0.000844 kWh. Total GPU Power :<PHONE_NUMBER>7489198 W
[codecarbon INFO @ 13:01:07] Energy consumed for all CPUs : 0.000976 kWh. Total CPU Power :<PHONE_NUMBER>4925484 W
[codecarbon INFO @ 13:01:07] 0.001824 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:01:11] Energy consumed for RAM : 0.001181 kWh. RAM Power :<PHONE_NUMBER>797302 W
[codecarbon INFO @ 13:01:11] Energy consumed for all GPUs : 0.000899 kWh. Total GPU Power :<PHONE_NUMBER>3395017 W
[codecarbon INFO @ 13:01:11] Energy consumed for all CPUs : 0.000787 kWh. Total CPU Power :<PHONE_NUMBER>0767266 W
[codecarbon INFO @ 13:01:11] 0.002867 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:01:22] Energy consumed for RAM : 0.000008 kWh. RAM Power : 0.7472877502441406 W
[codecarbon INFO @ 13:01:22] Energy consumed for all GPUs : 0.001988 kWh. Total GPU Power :<PHONE_NUMBER>6031692 W
[codecarbon INFO @ 13:01:22] Energy consumed for all CPUs : 0.001951 kWh. Total CPU Power :<PHONE_NUMBER>238832 W
[codecarbon INFO @ 13:01:22] 0.003947 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:01:26] Energy consumed for RAM : 0.002361 kWh. RAM Power :<PHONE_NUMBER>797302 W
[codecarbon INFO @ 13:01:26] Energy consumed for all GPUs : 0.001816 kWh. Total GPU Power :<PHONE_NUMBER>9661432 W
[codecarbon INFO @ 13:01:26] Energy consumed for all CPUs : 0.001556 kWh. Total CPU Power :<PHONE_NUMBER>15955 W
[codecarbon INFO @ 13:01:26] 0.005733 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:01:37] Energy consumed for RAM : 0.000012 kWh. RAM Power : 0.7472977638244629 W
[codecarbon INFO @ 13:01:37] Energy consumed for all GPUs : 0.003135 kWh. Total GPU Power :<PHONE_NUMBER>2076347 W
[codecarbon INFO @ 13:01:37] Energy consumed for all CPUs : 0.002945 kWh. Total CPU Power :<PHONE_NUMBER>1688984 W
[codecarbon INFO @ 13:01:37] 0.006091 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:01:41] Energy consumed for RAM : 0.003541 kWh. RAM Power :<PHONE_NUMBER>797302 W
[codecarbon INFO @ 13:01:41] Energy consumed for all GPUs : 0.002732 kWh. Total GPU Power :<PHONE_NUMBER>1568922 W
[codecarbon INFO @ 13:01:41] Energy consumed for all CPUs : 0.002351 kWh. Total CPU Power :<PHONE_NUMBER>741656 W
[codecarbon INFO @ 13:01:41] 0.008624 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:01:52] Energy consumed for RAM : 0.000016 kWh. RAM Power : 0.7472991943359375 W
[codecarbon INFO @ 13:01:52] Energy consumed for all GPUs : 0.004280 kWh. Total GPU Power :<PHONE_NUMBER>1210292 W
[codecarbon INFO @ 13:01:52] Energy consumed for all CPUs : 0.003912 kWh. Total CPU Power :<PHONE_NUMBER>4690667 W
[codecarbon INFO @ 13:01:52] 0.008208 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:01:56] Energy consumed for RAM : 0.004721 kWh. RAM Power :<PHONE_NUMBER>797302 W
[codecarbon INFO @ 13:01:56] Energy consumed for all GPUs : 0.003649 kWh. Total GPU Power :<PHONE_NUMBER>9416147 W
[codecarbon INFO @ 13:01:56] Energy consumed for all CPUs : 0.003128 kWh. Total CPU Power :<PHONE_NUMBER>5231454 W
[codecarbon INFO @ 13:01:56] 0.011498 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:02:07] Energy consumed for RAM : 0.000019 kWh. RAM Power : 0.7472991943359375 W
[codecarbon INFO @ 13:02:07] Energy consumed for all GPUs : 0.005434 kWh. Total GPU Power :<PHONE_NUMBER>1124793 W
[codecarbon INFO @ 13:02:07] Energy consumed for all CPUs : 0.004882 kWh. Total CPU Power :<PHONE_NUMBER>4811384 W
[codecarbon INFO @ 13:02:07] 0.010336 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:02:11] Energy consumed for RAM : 0.005902 kWh. RAM Power :<PHONE_NUMBER>797302 W
[codecarbon INFO @ 13:02:11] Energy consumed for all GPUs : 0.004566 kWh. Total GPU Power :<PHONE_NUMBER>6007867 W
[codecarbon INFO @ 13:02:11] Energy consumed for all CPUs : 0.003926 kWh. Total CPU Power :<PHONE_NUMBER>6239936 W
[codecarbon INFO @ 13:02:11] 0.014393 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:02:22] Energy consumed for RAM : 0.000023 kWh. RAM Power : 0.7472991943359375 W
[codecarbon INFO @ 13:02:22] Energy consumed for all GPUs : 0.006580 kWh. Total GPU Power :<PHONE_NUMBER>6345607 W
[codecarbon INFO @ 13:02:22] Energy consumed for all CPUs : 0.005918 kWh. Total CPU Power :<PHONE_NUMBER>1332965 W
[codecarbon INFO @ 13:02:22] 0.012521 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:02:26] Energy consumed for RAM : 0.007082 kWh. RAM Power :<PHONE_NUMBER>797302 W
[codecarbon INFO @ 13:02:26] Energy consumed for all GPUs : 0.005484 kWh. Total GPU Power :<PHONE_NUMBER>8021658 W
[codecarbon INFO @ 13:02:26] Energy consumed for all CPUs : 0.004738 kWh. Total CPU Power :<PHONE_NUMBER>9631926 W
[codecarbon INFO @ 13:02:26] 0.017304 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:02:37] Energy consumed for RAM : 0.000027 kWh. RAM Power : 0.7473006248474121 W
[codecarbon INFO @ 13:02:37] Energy consumed for all GPUs : 0.007727 kWh. Total GPU Power :<PHONE_NUMBER>2069915 W
[codecarbon INFO @ 13:02:37] Energy consumed for all CPUs : 0.006911 kWh. Total CPU Power :<PHONE_NUMBER>0207042 W
[codecarbon INFO @ 13:02:37] 0.014665 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:02:41] Energy consumed for RAM : 0.008262 kWh. RAM Power :<PHONE_NUMBER>797302 W
[codecarbon INFO @ 13:02:41] Energy consumed for all GPUs : 0.006401 kWh. Total GPU Power :<PHONE_NUMBER>1569874 W
[codecarbon INFO @ 13:02:41] Energy consumed for all CPUs : 0.005536 kWh. Total CPU Power :<PHONE_NUMBER>5104147 W
[codecarbon INFO @ 13:02:41] 0.020199 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:02:52] Energy consumed for RAM : 0.000031 kWh. RAM Power : 0.7473034858703613 W
[codecarbon INFO @ 13:02:52] Energy consumed for all GPUs : 0.008876 kWh. Total GPU Power :<PHONE_NUMBER>9092814 W
[codecarbon INFO @ 13:02:52] Energy consumed for all CPUs : 0.007907 kWh. Total CPU Power :<PHONE_NUMBER>1133254 W
[codecarbon INFO @ 13:02:52] 0.016814 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:02:56] Energy consumed for RAM : 0.009443 kWh. RAM Power :<PHONE_NUMBER>797302 W
[codecarbon INFO @ 13:02:56] Energy consumed for all GPUs : 0.007319 kWh. Total GPU Power :<PHONE_NUMBER>6520013 W
[codecarbon INFO @ 13:02:56] Energy consumed for all CPUs : 0.006316 kWh. Total CPU Power :<PHONE_NUMBER>5520834 W
[codecarbon INFO @ 13:02:56] 0.023078 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:03:07] Energy consumed for RAM : 0.000035 kWh. RAM Power : 0.7473034858703613 W
[codecarbon INFO @ 13:03:07] Energy consumed for all GPUs : 0.010022 kWh. Total GPU Power :<PHONE_NUMBER>7540437 W
[codecarbon INFO @ 13:03:07] Energy consumed for all CPUs : 0.008880 kWh. Total CPU Power :<PHONE_NUMBER>1455744 W
[codecarbon INFO @ 13:03:07] 0.018937 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:03:11] Energy consumed for RAM : 0.010623 kWh. RAM Power :<PHONE_NUMBER>797302 W
[codecarbon INFO @ 13:03:11] Energy consumed for all GPUs : 0.008235 kWh. Total GPU Power :<PHONE_NUMBER>9804305 W
[codecarbon INFO @ 13:03:11] Energy consumed for all CPUs : 0.007103 kWh. Total CPU Power :<PHONE_NUMBER>997984 W
[codecarbon INFO @ 13:03:11] 0.025960 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:03:22] Energy consumed for RAM : 0.000039 kWh. RAM Power : 0.7473034858703613 W
[codecarbon INFO @ 13:03:22] Energy consumed for all GPUs : 0.011168 kWh. Total GPU Power :<PHONE_NUMBER>9628967 W
[codecarbon INFO @ 13:03:22] Energy consumed for all CPUs : 0.009831 kWh. Total CPU Power :<PHONE_NUMBER>0762765 W
[codecarbon INFO @ 13:03:22] 0.021037 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:03:26] Energy consumed for RAM : 0.011802 kWh. RAM Power :<PHONE_NUMBER>797302 W
[codecarbon INFO @ 13:03:26] Energy consumed for all GPUs : 0.009153 kWh. Total GPU Power :<PHONE_NUMBER>2081815 W
[codecarbon INFO @ 13:03:26] Energy consumed for all CPUs : 0.007875 kWh. Total CPU Power :<PHONE_NUMBER>0812245 W
[codecarbon INFO @ 13:03:26] 0.028830 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:03:37] Energy consumed for RAM : 0.000043 kWh. RAM Power : 0.74857234954834 W
[codecarbon INFO @ 13:03:37] Energy consumed for all GPUs : 0.012317 kWh. Total GPU Power :<PHONE_NUMBER>7864406 W
[codecarbon INFO @ 13:03:37] Energy consumed for all CPUs : 0.010828 kWh. Total CPU Power :<PHONE_NUMBER>4020802 W
[codecarbon INFO @ 13:03:37] 0.023188 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:03:41] Energy consumed for RAM : 0.012982 kWh. RAM Power :<PHONE_NUMBER>797302 W
[codecarbon INFO @ 13:03:41] Energy consumed for all GPUs : 0.010071 kWh. Total GPU Power :<PHONE_NUMBER>5717611 W
[codecarbon INFO @ 13:03:41] Energy consumed for all CPUs : 0.008664 kWh. Total CPU Power :<PHONE_NUMBER>957635 W
[codecarbon INFO @ 13:03:41] 0.031718 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:03:52] Energy consumed for RAM : 0.000047 kWh. RAM Power : 0.7485051155090332 W
[codecarbon INFO @ 13:03:52] Energy consumed for all GPUs : 0.013464 kWh. Total GPU Power :<PHONE_NUMBER>353972 W
[codecarbon INFO @ 13:03:52] Energy consumed for all CPUs : 0.011807 kWh. Total CPU Power :<PHONE_NUMBER>608062 W
[codecarbon INFO @ 13:03:52] 0.025318 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:03:56] Energy consumed for RAM : 0.014163 kWh. RAM Power :<PHONE_NUMBER>797302 W
[codecarbon INFO @ 13:03:56] Energy consumed for all GPUs : 0.010991 kWh. Total GPU Power :<PHONE_NUMBER>0907973 W
[codecarbon INFO @ 13:03:56] Energy consumed for all CPUs : 0.009432 kWh. Total CPU Power :<PHONE_NUMBER>3773656 W
[codecarbon INFO @ 13:03:56] 0.034585 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:04:05] Energy consumed for RAM : 0.014877 kWh. RAM Power :<PHONE_NUMBER>797302 W
[codecarbon INFO @ 13:04:05] Energy consumed for all GPUs : 0.011548 kWh. Total GPU Power :<PHONE_NUMBER>4422032 W
[codecarbon INFO @ 13:04:05] Energy consumed for all CPUs : 0.009920 kWh. Total CPU Power :<PHONE_NUMBER>1999332 W
[codecarbon INFO @ 13:04:05] 0.036345 kWh of electricity used since the beginning.
/opt/runtime/lib/python3.10/site-packages/codecarbon/output.py:168: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.
  df = pd.concat([df, pd.DataFrame.from_records([dict(data.values)])])
[codecarbon INFO @ 13:04:07] Energy consumed for RAM : 0.000051 kWh. RAM Power : 0.7462048530578613 W
[codecarbon INFO @ 13:04:07] Energy consumed for all GPUs : 0.014553 kWh. Total GPU Power :<PHONE_NUMBER>5331326 W
[codecarbon INFO @ 13:04:07] Energy consumed for all CPUs : 0.012783 kWh. Total CPU Power :<PHONE_NUMBER>1343655 W
[codecarbon INFO @ 13:04:07] 0.027387 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:04:22] Energy consumed for RAM : 0.000057 kWh. RAM Power : 1.2548003196716309 W
[codecarbon INFO @ 13:04:22] Energy consumed for all GPUs : 0.014896 kWh. Total GPU Power : 65.63594918902683 W
[codecarbon INFO @ 13:04:22] Energy consumed for all CPUs : 0.013801 kWh. Total CPU Power :<PHONE_NUMBER>4500802 W
[codecarbon INFO @ 13:04:22] 0.028753 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:04:37] Energy consumed for RAM : 0.000064 kWh. RAM Power : 1.2580332756042483 W
[codecarbon INFO @ 13:04:37] Energy consumed for all GPUs : 0.015019 kWh. Total GPU Power : 23.65649601202967 W
[codecarbon INFO @ 13:04:37] Energy consumed for all CPUs : 0.014796 kWh. Total CPU Power :<PHONE_NUMBER>271394 W
[codecarbon INFO @ 13:04:37] 0.029878 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:04:54] Energy consumed for RAM : 0.000073 kWh. RAM Power : 1.5729517936706543 W
[codecarbon INFO @ 13:04:54] Energy consumed for all GPUs : 0.015161 kWh. Total GPU Power : 23.752753694724493 W
[codecarbon INFO @ 13:04:54] Energy consumed for all CPUs : 0.015913 kWh. Total CPU Power :<PHONE_NUMBER>6718745 W
[codecarbon INFO @ 13:04:54] 0.031147 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:05:09] Energy consumed for RAM : 0.000087 kWh. RAM Power : 2.7783265113830566 W
[codecarbon INFO @ 13:05:09] Energy consumed for all GPUs : 0.015257 kWh. Total GPU Power : 18.331170484957525 W
[codecarbon INFO @ 13:05:09] Energy consumed for all CPUs : 0.016889 kWh. Total CPU Power :<PHONE_NUMBER>0280602 W
[codecarbon INFO @ 13:05:09] 0.032234 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:05:25] Energy consumed for RAM : 0.000108 kWh. RAM Power : 3.921996116638184 W
[codecarbon INFO @ 13:05:25] Energy consumed for all GPUs : 0.015356 kWh. Total GPU Power : 17.928908913098713 W
[codecarbon INFO @ 13:05:25] Energy consumed for all CPUs : 0.017953 kWh. Total CPU Power :<PHONE_NUMBER>2638104 W
[codecarbon INFO @ 13:05:25] 0.033417 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:05:41] Energy consumed for RAM : 0.000118 kWh. RAM Power : 1.9352631568908691 W
[codecarbon INFO @ 13:05:41] Energy consumed for all GPUs : 0.015451 kWh. Total GPU Power : 17.816804237108826 W
[codecarbon INFO @ 13:05:41] Energy consumed for all CPUs : 0.018970 kWh. Total CPU Power :<PHONE_NUMBER>6798623 W
[codecarbon INFO @ 13:05:41] 0.034538 kWh of electricity used since the beginning.
[codecarbon INFO @ 13:05:42] Energy consumed for RAM : 0.000118 kWh. RAM Power : 1.6509547233581543 W
[codecarbon INFO @ 13:05:42] Energy consumed for all GPUs : 0.015457 kWh. Total GPU Power : 16.64991510011033 W
[codecarbon INFO @ 13:05:42] Energy consumed for all CPUs : 0.019036 kWh. Total CPU Power :<PHONE_NUMBER>6518426 W
[codecarbon INFO @ 13:05:42] 0.034612 kWh of electricity used since the beginning.

Hello, can you provide a little more details about why you think the results are incorrect ?

Am I incorrect in thinking that the final_emissions is the average or the overall stats ?
Yes that is incorrect, the final emissions are computed from the sum of the consumption that you get for every interval

As you can see in the log Available RAM : 755.442 GB so we use this size for the estimation.
Same for the CPU, it is a 32 code AMD EPYC 7513 32-Core Processor so we monitor all of them.
What could help you is to use the code from https://github.com/mlco2/codecarbon/pull/316 than allows to monitor only the process that launch CodeCarbon.

I'm closing this PR, don't hesitate to re-open if you need more information.


Côte d’Ivoire Phone Number Fix

Description
Updates google-libphonenumber to 3.2.27
Other changes
Added a unit test in PhoneNumberInput.test.tsx for Côte d’Ivoire phone numbers.
Tested
Tested locally on iOS and with unit tests.
How others should test

Navigate to Connect your phone number select the Côte d’Ivoire flag - 🇨🇮
Observe correct place holder - 00 00 0 00000
Enter in a valid Côte d’Ivoire phone number e.g. 21 23 4 56789 and tap next.
Should begin phone verification - no need to complete but ensure that it starts.

Related issues

Fixes: Côte divoire 10 digit phone # instead of 8 digit #104

Backwards compatibility
Yes

Hey @MuckT we have verified the above task in Latest iOS TestFlight Build V:1.33.0 and updated the status in Test rails
Observation : Correct Place holder (000..) is seen and also user is able to proceed ahead for confirming phone number
Test Rail links:
iOS 14 : https://valoraapp.testrail.io/index.php?/tests/view/37178
Devices : iPhone 12(14.7.1)
Thanks.!

Hey @MuckT, we have verified the above task in Latest Android Internal Release Build V1.33.0 and updated the status in Test rails.
Test Rail link:
Android 12: https://valoraapp.testrail.io/index.php?/tests/view/37271
Device : Google Pixel 4a(12.0)
Thanks.!!


[UI] add multi value column in schema table

Add a new column in schema tabular view that checks if schema has singleValueField or not
singleValueField: false -> multivalue is True otherwise False
Before

After

@mayankshriv @xiangfu0

Codecov Report

Merging #11335 (3b033a2) into master (51da2f5) will decrease coverage by 53.59%.
Report is 2 commits behind head on master.
The diff coverage is n/a.

@@              Coverage Diff              @@
##             master   #11335       +/-   ##
=============================================
- Coverage     68.18%   14.59%   -53.59%
+ Complexity     6534      494     -6040
=============================================
  Files          2239     2165       -74
  Lines        120475   117318     -3157
  Branches      18230    17784      -446
=============================================
- Hits          82141    17119    -65022
- Misses        32496    98783    +66287
+ Partials       5838     1416     -4422

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Updated certificates + script

Replaces #30 and #34.  @shdunning @cmoore-redhat @karelhala please review.

Thank you for the PR @cben, sorry for such a late reply!


include link to WVD architecture

In the overview or requirements section it would be good to include a link to the WVD architectural guide which will emphasize the dependencies for WVD.  This would be especially useful for customers who are new to Azure.

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

ID: d2eeca14-80ef-c0b4-2719-80ceb286ba3d
Version Independent ID: b7d3df23-3158-2807-eecc-73e7230c2033
Content: What is Windows Virtual Desktop? - Azure
Content Source: articles/virtual-desktop/overview.md
Service: virtual-desktop
GitHub Login: @Heidilohr
Microsoft Alias: helohr

@pnwnightowl Thank you for the feedback!  We are investigating this and will get back to you shortly.

@pnwnightowl A PR has been submitted to the document author for review based on your suggestion.

@pnwnightowl The documentation should be updated shortly.  We are going to close this issue as resolved but if you have any additional questions about the documentation, please tag me in your reply and we would be happy to continue the conversation.


Report JSDoc syntax errors

Note that JSDoc syntax errors are only reported for javascript files with // @ts-check turned on. Typescript files don't report these errors because Typescript only uses Jsdoc for documentation — it seems wrong to report syntax errors on parts of Jsdoc that aren't also being checked.
Fixes #13371

I thought the travis failures on this PR were due to node-stable upgrading to Node 8.

The build error I looked at was for node 6--stable is passing. It looks like tslint is now checking es5.d.ts and finding lots of lint, specifically badly formatted jsdoc. But I think that is unrelated to this change, which only adds errors to js files when checkjs is on.

Maybe --exclude is being ignored by something in the pipeline now? There is an explicit exclude for es5.d.ts.

Yep, this is a bug in tslint 5.4.0 that is fixed in 5.4.1:
https://github.com/palantir/tslint/issues/2852
https://github.com/palantir/tslint/pull/2853

Ah, thanks for investigating!


Alexey-Ben meeting 2019-03-11

Updates from last week

FoRTE

Code for reproducibly adding UMBS PFTs to PEcAn (i.e. not point-and-click in PEcAn database web interface)
Had to wrap my head around recent PEcAn updates that broke my current workflow
Tested ED "switches" on short runs. With minor ED code revisions, all of them work and seem to produce slightly different output (as expected).

Other

Frontiers paper final revisions submitted
RSE peer review
EFI abstract

Goals for this week

FoRTE

Run longer ED simulations (10-20 years) with switches to see if output is reasonable
Plot parameter distributions based on available trait data. Look for more literature constraints.

Hector

Develop code for running sensitivity analysis for global Hector given input parameter sets

Other

PLoS One peer review

Discussion topics

EFI abstract
BK email about Hector

FoRTE data package


Use Google Tag Manager

Use the Google Tag Manager used by ngrok.com.

Our tag manager loads JS (from Olark and Hubspot) in the page without requiring us to update our site.
Our tag works on ngrok.com and the current /docs
When we try to load the same thing on docusaurus, the Tag Manager is loaded, but the nested JS not.

To reproduce:

Change docusaurus.config.js with our tag manager id:

Build and then run the site preview (according to Docusaurus, tag manager runs only in production builds)

npm run build
npm run serve

done


Archive ...?

Last update in June 2016, I guess this repo isn't under active maintenance and was replaced by nitro's mono-repository I guess.
Correct me if I'm wrong @ernscht

you are right, thanks - will archive this and similar outdated repos soon.


New icon: cgm life

[x] I have carefully read and followed CONTRIBUTING document.

URL of the site:
https://cgmlife.com/

Proof of the Aegis-compatible 2FA:
https://www.cgm.com/_Resources/Persistent/e54a3ab2e1ef1bb5c570553ab99ce862d39a704a/CGM CONNECTION Multi-factor Authentication Instructions 030524.pdf

Logo / icon info:
extracted from logo main website: https://cgmlife.com

Background color info:
it's from the logo (#f5a067)

same here, instead of the orignal orange use the #f8c18c from our palette, thanks!


remove workspace delegate

motivation: SwiftPMWorkspace is not actually using the workspace delegate, remove redundant code
changes: remove BuildSettingProviderWorkspaceDelegate

@swift-ci please test


delete account and associated data

User story
As a user, I want to delete my account, so I can have my data all removed from Climate mind.
Acceptance criteria

When I delete my account, then my user account is removed from the users table in the database and I can no longer login.  database that can be deleted without making conversations I had with other users disappear or cause errors for those users.
Conversation data in the database that has been shared with other users does not get deleted as this has been consented to share already
endpoint is /user-account and DELETE
endpoint requires Authorization header and X-Session-Id header.
endpoint requires currentPassword in Body.
endpoint responses include 200 "Account deleted"
new endpoint documentation is included in the stoplight specs

This issue is just for deleting the user account and not any other associated data. A separate issue/ user story will need to be made for deleting all associated data without generating errors for other users. And when do that consideration will need to be given for situation where a conversation was linked for user a account and user b account (if user B already has an account) and then either user A or user B deletes their account:

When I delete my account, then all associated data with my account is deleted from the database that can be deleted without making conversations I had with other users disappear or cause errors for those users.
Conversation data in the database that has been shared with other users does not get deleted as this has been consented to share already


[Feature] Add support for Redis as an alternative caching option

Currently, our application uses Momento for caching. We would like to extend the caching functionality to support Redis as well, allowing the app to dynamically choose between Momento and Redis based on environment variables.
Expected Behavior:

If the environment variable MOMENTO_KEY is present, the app should use Momento for caching.
If the environment variable REDIS_URL is present (and MOMENTO_KEY is absent), the app should use Redis for caching.
If neither environment variable is present, or the default cache configuration (REDIS) should be used.

Technical Details:

The app should prioritize Redis over Momento when both environment variables (MOMENTO_KEY and REDIS_URL) are available.
Update the configuration logic to support both caching systems.

Additional Notes:

Update documentation to reflect the new Redis support and how to configure either caching system.
Ensure backward compatibility with existing Momento configurations.

@riazosama do you plan to use upstash for redis or any other option????

@riazosama do you plan to use upstash for redis or any other option????

We plan to use redis deployed on our own EC2 or server.

ok
i've added the necessary configuration in my PR


fix(docs): Use external link icon only in main content

The external link icon was decorating every link on the site, but links outside the main content shouldn't be decorated, because it's very visually distracting. For example:

With this change the icon will still display on links in the main articles, but not in the site UI itself.

Thanks for the review, @RishhiB!


SOCKS proxy support

Coverage increased (+6.37%) to 98.04% when pulling 1346eb7e832e8ae0b8589669e5aca958ba42ab1e on marthjod:master into b5f4f8a5bee724d25b2da12b072bfe81340ede56 on nmesstorff:master.


Speed up CPU sorting

Proposed changes
Sorting on the CPU was using a stable sort, which is not the default in numpy/torch and was therefore quite a bit slower. Switching to std::sort speeds up sorting of a 64x128x1024 matrix 1.1x to 4.2x depending on the sort axis (best of 10 runs on M1 pro):
           device    lib  axis     t_ms   speedup
-------------------------------------------------
   before     cpu    mlx     0  1263.40
   after      cpu    mlx     0   373.36      3.3x

   before     cpu    mlx     1   957.94
   after      cpu    mlx     1   228.17      4.2x

   before     cpu    mlx     2   255.36
   after      cpu    mlx     2   277.79      1.1x

This is how mlx compares to NumPy and Pytorch (note that the latter is multithreaded, so not really a fair comparison):
  device    lib  axis    t_ms
-----------------------------
     cpu    mlx     0  373.36
     cpu     np     0  226.97
     cpu  torch     0   52.12

     cpu    mlx     1  228.17
     cpu     np     1  237.17
     cpu  torch     1   43.99

     cpu    mlx     2  277.79
     cpu     np     2  299.10
     cpu  torch     2   53.27

Checklist
Put an x in the boxes that apply.

[x] I have read the CONTRIBUTING document
[x] I have run pre-commit run --all-files to format my code / installed pre-commit prior to committing changes
[x] I have added tests that prove my fix is effective or that my feature works
[x] I have updated the necessary documentation (if needed)

Great!

@nicolov Thanks for the PR!
We chose std::stable_sort to be consistent in results with the GPU (which does a stable sort) and also to make sure that the order of elements in the sort forward is the same as the order we consider in sort backward (the sort vip uses an argsort which also does a stable sort). As such, going to std::sort without also producing / saving the indices at the same time like Pytorch does would make getting the correct vjp difficult

Given @jagrit06 comments about the VJP/JVP it seems like it will be difficult to switch to this. Still I am somewhat surprised the stable sort is so much slower (4x!)... I wonder if we could write a faster one 🤔 ..
@nicolov up to you if you want to investigate further or close this for now.

@nicolov what's the status of this? Should we close it

Yes, let’s close it for now.


change license and notice for more standardized

@tianxiaoliang

Coverage increased (+0.01%) to 66.3% when pulling bd42c03ff110055a1a470913db70cd02420d0be1 on alec-z:master into 1a99ab41f7ea0ffb5c0bf8c7049e0df25924f0cf on go-chassis:master.


made all widgets scalable (needed for High-DPI-displays)

I chose cvui for an image processing project where high-dpi displays may be used (as they are common nowadays). On a display with 180 DPI or more, the widgets look tiny and the text becomes unreadable. Only text() and printf() did support scaling, as they consist only of text. Now all other widgets - including EnhancedWindow - can be scaled analogous to text() and printf(). The internal geometry of all widgets is automatically adapted consistent to their new parameter theFontSize (for example the height of the title bar of a window and dozens of other small things). The size of a widget as defined by the user is not changed.
The samples main-app and ui-enhanced-window-component both now include a cvui::counter which the user can use to change the scaling of the user interface. In my (closed-source) application, instead of a cvui::counter I query the display DPI to define the scaling, so the whole application always has the same physical dimensions on a display, independent from its pixel density.
I think everything works fine. I didn′t care about the Python part, though.

This is outstanding, thank you very much for such a contribution! I am organizing my job schedule for 2020 to accommodate a few hours of work on open source projects every week. I will include cvui on that budged too.
Since this is a significantly large PR, I will need time to review it. Thanks again and I look forward to seeing it incorporated into the lib.

Thank you for your positive response! I am looking forward to see my commits in your repo. I added two other commits. In the first, I moved EnhancedWindow.h from the corresponding example project to a path next to cvui.h. There are two samples requiring EnhancedWindow.h and for projects who like to use it (like mine), it looks odd to have a dependency on an example.
In the second, I introduced support for colored buttons and counters, because I need colors in my project. With the new argument theInsideColor one can specify the fill color of a button. The other three colors that are used to paint buttons are automatically derived from it, so that they match the original default colors if theInsideColor is the DEFAULT_BUTTON_COLOR 0x424242. I modified the example main-app so it shows one colored button and counter.


Dupe Bug with Roost

When the Roost output is full and the progress bar is maxed out, and then you start outputting, the progress bar never resets, and it keeps putting more and more resources into the output without needing to wait https://s.dinnerbeef.com/gOXe5/hufIBEkE60.mp4/raw
Version: 1.18.2-1.0.7

huh, will fix tomorrow


No Files in the latest version

I believe it means after I do gem install, no files are downloaded into my local gem

Should be fixed in 1.1.6, sorry for the inconvenience.


Remove specific file restriction

Closes #196

@sophie-cluml, @jinjoolee07
We have three options:

Allow extensions starting with a . and validate the input to exclude invalid ones.
Allow extensions starting without a . and validate the input to exclude invalid ones.
Allow any extensions and automatically add a . if necessary.

In any case, documentation will be required.
By the way, should we validate the input to ensure it does not include spaces and exclude such cases?


how can i update the bulletin after it was presented

how can i update the bulletin image after it the bulletin was presented

If you use the BLTNPageItem, you can access the image property and change the image from there.


Question about PDEEPoseController's PD Gains

In ManiSkill's PDEEPoseController, the Kp and Kd gains appear to be defined with respect to the joints, rather than for translation and rotation separately, as in some other EE pose controllers. Is there a specific conversion or relationship between these joint-level gains and the EE translation/rotation gains?
https://github.com/haosulab/ManiSkill/blob/61076748d9e2c7254b1863220615c120f5919d7f/mani_skill/agents/controllers/pd_ee_pose.py#L138-L141

Currently we don't have other kinds of EE controllers with PD specified on translation/rotation. This would involve modifying the inverse kinematics solver essentially which can get complicated.

Thank you! I might give this a try, though I'm unsure about the difficulty yet. But since we can calculate the Jacobian, this should be possible?


chat history from previous day is no available.

Describe the bug
Chats/Conversations from previous days are not searchable nor visible.
Link to the Bolt URL that caused the error
https://bolt.new/
Steps to reproduce

go to https://bolt.new/
login with github username and password
view the left side panel
only option is to create a new chat or conversation, search through prior chats (which isn't functional because there is not history to search)

Expected behavior
expected to see prior chat history and conversations to reference and go back to
Screen Recording / Screenshot
No response
Platform

OS: macOS
Browser: Chrome
Version: 130.0.6723.117 (Official Build) (64-bit)

Additional context
No response

Hi @stevendean,
Engineering recently released an update for chat persistence and you should be able to see your chat history going forwards. Please let us know if you continue to have problems with this. Appreciate your patience and the team continues to make improvements!

Building on this @endocytosis , I just had a chat probably 5-6 messages long, purchased a subscription when my tokens ran out, and came back to the app to find the chat reverted to the first message I sent.

Can I expect that chat to come back or should I just try to re-do it?
I actually downloaded the code right before upgrading to the subscription, is there any way I can upload it back into bolt.new or is that not the best move?

Thanks!


Fix for target port detection msg during edit

Fixes
Fixes RHTAPBUGS-140
Description
Fixes an issue where a message is shown that the target port was not detected when editing the component settings
Type of change

[x] Bugfix

/cc @christianvogt

/lgtm
/approve

/retest


Simplify fabric8 config data location resolver

@ryanjbaxter  ready to be looked at, totally forgot to tag you. thank you.


[WIP] Default Topology Spread constraints

Temporary placeholder
Enhancement issue: kubernetes/enhancements#1258

/sig scheduling

/milestone 1.18

👋 Please rebase this PR on dev-1.18 in order to avoid merge conflicts.
Feel free to /hold cancel after you've rebased.
/hold

/hold cancel

/assign @Huang-Wei

/lgtm

/assign @sftim

Hi @alculquicondor
We are very close to the docs final deadline i.e All 1.18 enhancements docs should be in ready to merge state by Monday 16th March. Please make sure to complete the docs reviews before the deadline.
Thanks!

/lgtm
Thanks @alculquicondor

Thanks a lot for your reviews @sftim . Anything missing to get the approval?

@VineethReddy02 happy to see this merged?


Minor: add example for creating SchemaDescriptor

Which issue does this PR close?

Closes #.
Rationale for this change
While workign on https://github.com/apache/arrow-rs/pull/6840 I found it very fiddly to understand to make a SchemaDescriptor in an example
It would have been nice to have an example in the docs. Let's add one
What changes are included in this PR?
Add an example of creating SchemaDescriptor in the docs

Are there any user-facing changes?
Just docs, no behavior changes

Thank you for the reviews @etseidl and @tustvold