Lib apparently not compiling properly on AndroidStudio 3.0 Canary 7

Hi again,
I just migrated to AS 3.0 beta to have more support with Room lib, but now your lib is not working anymore :/
Maybe it is a AS bug, not yours, but could you check this?
I didn't changed any validator property, just migrated to the last AS beta version (and obligatorily, gradle version to 4.1 and Android Plugin to 3.0.0-alpha7). It's printing the following:
****/ data binding error ****msg:Cannot find the setter for attribute 'app:validateEmpty' with parameter type boolean on android.support.design.widget.TextInputEditText..
Here is my xml:
 <android.support.design.widget.TextInputLayout
            android:id="@+id/tiXpto"
            android:layout_width="0dp"
            android:layout_height="wrap_content"
            android:layout_marginEnd="8dp"
            android:layout_marginRight="8dp"
            app:layout_constraintLeft_toLeftOf="parent"
            app:layout_constraintRight_toRightOf="parent"
            app:layout_constraintTop_toTopOf="parent">

            <android.support.design.widget.TextInputEditText
                android:id="@+id/edXpto"
                android:layout_width="match_parent"
                android:layout_height="wrap_content"
                android:layout_weight="1"
                android:hint="@string/add_xpto_name"
                android:inputType="textPersonName"
<EMAIL_ADDRESS>                android:textSize="16sp"
                app:validateEmpty="@{true}"
                app:validateEmptyAutoDismiss="@{true}"
                app:validateEmptyMessage="@{@string/field_is_required}"/>
        </android.support.design.widget.TextInputLayout>

Any help will be apreciatted.

Hi @JGeraldoLima , can you use in other canary versions?

I am having the same issue on 3.0.0-alpha8. Any ideas?

I am using 3.0.0-alpha9, and get the similar issue

Apparently It's a problem Gradle 3.0 has with older sources, for now you can copy the binding classes (DataBindings, ...) to your own project and it works.

Still doesn't work on Android Studio 3.0 Beta 3

Still doesnt't work on Android Studio 3.0 Beta 6, could not resolve the issue

Please use this solution until a stable version of Android Studio arrives:
implementation "com.github.Ilhasoft:data-binding-validator:master-SNAPSHOT"
As soon as a stable version arrives we will release a new version.

@danielsanfr I tried your solution, But it didn't change anything. The error is still there

Hi, today I was updating my version of  Android Studio to 3.0 and gradle to 4.1 and the ide report me this issue in compiling, seems these are stable versions. Can you solve this issue  for this stable versions?

Sorry for the delay guys :pensive:. Version 1.0.0 has now been released.


Cloud SQL DB should force SSL

[ ] The Cloud SQL database instance should require all connections to use SSL (require_ssl attribute).

Closed it as we are not planning to support GCP in short-term. And when we do - likely we'll file new issues based on AWS configuration.


Replace all-zero MAC address for 02:00:00:00:00:00

The motivation of this patch is to avoid potential problems because of using MAC addresses with special meanings. For instance, I recall a performance bug because of using a MAC address starting with '01:', which means multicast.
An all zero MAC address is a unicast globally administered address. According to [1], addresses with starting with '00:00:00' are reserved. I think is better to use one of the four family types of unicast locally administered MAC address available in the MAC address space: X2-XX-XX, X6-XX-XX, XA-XX-XX or XE-XX-XX. In this patch I picked 02:00:00:00:00:00.
[1] http://www.iana.org/assignments/ethernet-numbers/ethernet-numbers.xhtml

You can apply for an official MAC prefix, probably better than using random
addresses.

@alexandergall do you have strong feelings on this patch (affecting vpws.lua)?

The destination address in vpws.lua is just a dummy value that should never appear on the wire. It will be overweritten either by a statically configured address or the address discovered by nd_light.
Anyway, vpws.lua will be replaced by the l2vpn program that I'll push to the vpn branch soon.


Update the possible Kind values to include FHIR R4

A small update to allow for different Kind values as the Azure FHIR API will now support different versions of the service to be deployed.
Latest improvements:
MSFT employees can try out our new experience at OpenAPI Hub  - one location for using our validation tools and finding your workflow.

Contribution checklist:

[X ] I have reviewed the documentation for the workflow.
[X ] Validation tools were run on swagger spec(s) and have all been fixed in this PR.
[X] The OpenAPI Hub was used for checking validation status and next steps.

ARM API Review Checklist

[X] Service team MUST add the "WaitForARMFeedback" label if the management plane API changes fall into one of the below categories.
adding/removing APIs.
adding/removing properties.
adding/removing API-version.
adding a new service in Azure.

Failure to comply may result in delays for manifest application. Note this does not apply to data plane APIs.

[ ] If you are blocked on ARM review and want to get the PR merged urgently, please get the ARM oncall for reviews (RP Manifest Approvers team under Azure Resource Manager service) from IcM and reach out to them.
Please follow the link to find more details on API review process.

Automation for azure-sdk-for-python

Automation for azure-sdk-for-go

Can one of the admins verify this patch?


Cool project!

I just read the bit about Aurelias binding language being flexible and immediately wondered if there was a knockout plugin as someone that's been using Knockout for a few years ...and low and behold here it is.
Please excuse me for creating this as an issue but I just had to comment on what a cool project this was 👍
:)

Hi @MrChriZ ,
thanks for this very positive feedback!!!


WideCString/WideString => &str

Hi there,
this is actually more of a question than an issue but I'm very interested in your opinion. I have been using your WideCString type in a very small rust project and am facing the situation that I have to tranform a variable of type WideCString into a slice of type &str.
I can see various ways of doing so, specifically:

tranforming from WideCString => std::String (via to_string_lossy()) => &str
transforming from WideCString => &[u16] (via as_slice) => &str

I would be really interested in your perspective in this. What would be the best way to go?
For me this is not only a question of writing code that jst works. I'm currently learning rust and am really interested in writing "good" code (whatever that means). So, I'm trying to understand a little bit more than what I have to....
Thanks
Norbert

The main thing is to be aware of the string encoding, but in general, your best bet is definitely through WCString::to_string_lossy() if you know the string to be UTF-16, or mostly UTF-16. Because a wide string is going to be a sequence of u16 values and a regular Rust string is UTF-8 values, you're going to need to have an owned String somewhere along the way, you won't be able to go directly from a &[u16] slice to a &str. If you're not dealing with UTF-16 values, you'll have to use an external encoding crate to construct the String however.
If you're unsure, especially if your wide string comes from Windows, you probably have UTF-16, or at least malformed UTF-16, hence the possibility of a 'lossy' conversion. You can use WideCString::to_string() to detect and deal with malformed UTF-16, if needed.


sys/linux: use template based structure for USB descriptions

To allow future extensions of USB descriptions to fuzz particular USB
classes this patch changes the structure of USB descriptions to use
templates.
This will invalidate all existing USB corpus.

Codecov Report

Merging #1224 into master will decrease coverage by <.01%.
The diff coverage is 0%.

@@            Coverage Diff             @@
##           master    #1224      +/-   ##
==========================================
- Coverage   67.53%   67.53%   -0.01%
==========================================
  Files         120      120
  Lines       20890    20891       +1
==========================================
  Hits        14108    14108
- Misses       6113     6114       +1
  Partials      669      669

Impacted Files
Coverage Δ

sys/linux/init_vusb.go
0% <0%> (ø)
:arrow_up:

Continue to review full report at Codecov.

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LGTM


wget.exe could not download dependencies from GitHub on Windows.

The included wget.exe is too old to support TLS 1.1 and above on Windows.

Fixed in https://github.com/Microsoft/rDSN/pull/214


Ei 1221 payments sub orchestrator

Wasn't the purpose of this work to send clawbacks and payments for each legal entity in the same sub-orchestrator? All this change does it flips the problem around.

That's updated


Remove TaskrunMetrics Blank Identifier in CustomRun Reconciler to Avoid Redundant TaskRun Informer Register

Changes
This commit removes the blank identifier for taskrunMetrics in CustomRun reconciler so that to avoid having the redundant taskRun informer to be registered by init(). No functional changes.
/kind misc
prerequisite of #6444
Thanks to the pointers from @dibyom @lbernick ! 🙏

Submitter Checklist
As the author of this PR, please check off the items in this checklist:

[n/a] Has Docs if any changes are user facing, including updates to minimum requirements e.g. Kubernetes version bumps
[n/a] Has Tests included if any functionality added or changed
[x] Follows the commit message standard
[x] Meets the Tekton contributor standards (including functionality, content, code)
[x] Has a kind label. You can add one by adding a comment on this PR that contains /kind <type>. Valid types are bug, cleanup, design, documentation, feature, flake, misc, question, tep
[n/a] Release notes block below has been updated with any user facing changes (API changes, bug fixes, changes requiring upgrade notices or deprecation warnings)
[n/a] Release notes contains the string "action required" if the change requires additional action from users switching to the new release

Release Notes
NONE

/lgtm

/retest


Make timestamp optional

Fixes https://github.com/iMicknl/ha-tahoma/issues/671
Hi Donny! Could you perhaps temporarily merge this one in and release in your version? We haven't had time to integrate your work yet in our client + ha-tahoma version, thus this would be a good temporary solution.

Tnx :)


Observe

@amitu , except adding tests everything is done. i'm adding test cases to validate the data captured in context object

@amitu implemented all review comments

@jatinderjit  please review this.


working with this Endpoint

computerVision.Endpoint = "https://westcentralus.api.cognitive.microsoft.com";
see results: https://t.co/i5NuNeE4Vf

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

ID: bc1afe24-ffb4-7602-b809-b688a3757737
Version Independent ID: bdc9a3ae-f4d3-76c6-e5ec-e83b5cd36883
Content: Quickstart: Extract handwritten text - SDK, C# - Azure Cognitive Services
Content Source: articles/cognitive-services/Computer-vision/quickstarts-sdk/csharp-hand-text-sdk.md
Service: cognitive-services
Sub-service: computer-vision
GitHub Login: @PatrickFarley
Microsoft Alias: pafarley

@catafest Could you please provide more details about the issue? I see the endpoint has returned results for the image. Have you set the mode to Handwrittern?
Have you also tried other handwritten images with better quality for accurate results?

@catafest We hope you are able to test with above recommendations. We will now proceed to close this thread. If there are further questions regarding this matter, please tag @RohitMungi-MSFT in your reply. We will gladly continue the discussion and we will reopen the issue.


[Deploy] --> Domo Buzz

Service
Buzz
https://www.domo.com/buzz
Link to your repository
https://github.com/fieldaware/franz-plugin-domo-buzz


CI job for checking perf. of extensions just like in CLI repo

See https://github.com/Azure/azure-cli/blob/dev/tools/automation/verify/verify_module_load_times.py

add to S165.


Heads up that Mac mini Mid-2010 Works

Just wanted to provided a heads up that this chip (BCM94331PCIEBT4CAX) actually works in a Mid-2010 Mac mini. I looked everywhere on the interwebs for info on this and found some sites mentioning it and some sites (even this site) not mentioning it.

Thanks @nmajin for the info, did you install one yourself? Would you perhaps have a link to a guide or installation pics?
I'll update the compatibility table accordingly.

It is pretty straightforward if you follow the guide at iFixit and leave jumper (J0) on the BCM94331PCIEBT4CAX unconnected and J1 and J2 connected to the antennas just like the old board.
Guide: https://www.ifixit.com/Guide/Mac+Mini+Mid+2010+AirPort-Bluetooth+Board+Replacement/6402
Since the chip is a bit different, only one screw aligns correctly:

Add some electrical tape under the new chip so it is protected from anything that might short it, and some of the antennas had to be loosened to make it fit appropriately.


Some refactoring

I found some more time and refactored a few things, hope you don't mind.

Declare mapping between relative densities and their Lang strings only once.
Save game data when player leaves and something has changed.

lgtm, i will wait for a new release till the command changes are in if thats okay for you.


Change master -> main for qiskit-translations repo

Summary
Updated the qiskit-translations repo branch for the translatable strings push script
Details and comments
Fixes #

Thanks @SooluThomas! Please remember to create branches off of a fork in futures PRs


file_exists(): Unable to find the wrapper "phar"

Hi All,
Getting this error message in a Magento script using Kint5.0.1. I am sure Phar is configured in PHP (8.1) running on Apache2.  Tried Kint4 but the same thing
Warning: file_exists(): Unable to find the wrapper "phar" - did you forget to enable it when you configured PHP?  ..../kint5/kint.phar/init_phar.php on line 41
Fatal error: Uncaught Error: Class "Kint\CallFinder" not found in phar:///...../kint5/kint.phar/src/Kint.php:661 Stack trace: #0 phar:///....../kint5/kint.phar/src/Kint.php(449): Kint\Kint::getSingleCall() #1 phar:///...../kint5/kint.phar/src/Kint.php(552): Kint\Kint::getCallInfo() #2 ...../testShowProducts.php(32): Kint\Kint::dump() #3 {main} thrown in phar:///......../kint5/kint.phar/src/Kint.php on line 661
Any suggestions please.  I have hunted the internet to no avail so far for a solution (..... replaces the full path name for privacy)  -
Thanks very much.

Well first off, you should probably replace the path in your other stack frames too.
Anyway, phar is enabled (or disabled) at compile time in PHP, it's not something you can just "Turn on" and since the phar file wrapper is missing it looks like your PHP was compiled without it.
You can run phpinfo() in your script to see a bunch of compilation information. Under "Registered PHP Streams" phar should be present, and in the phar section it should be enabled all over

Thanks @jnvsor.
I did check phpinfo() before and Phar is enabled. See extract below,
Phar
Phar: PHP Archive support	enabled
Phar API version	1.1.1
Phar-based phar archives	enabled
Tar-based phar archives	enabled
ZIP-based phar archives	enabled
gzip compression	enabled
bzip2 compression	enabled
Native OpenSSL support	enabled
Phar based on pear/PHP_Archive, original concept by Davey Shafik.
Phar fully realized by Gregory Beaver and Marcus Boerger.
Portions of tar implementation Copyright (c) 2003-2009 Tim Kientzle.

Did you check "Registered PHP streams"? PHP is loading the phar fine, but the file_exists call in the autoloader is failing because the stream isn't registered for some reason (Which makes me wonder how it got there in the first place since the stub is requiring the autoloader through phar://)
But this makes no sense, if the phar stream really wasn't enabled then it shouldn't have been able to autoload far enough to cause the error... Can you try downloading the latest phar and see what that does? Maybe you just have a corrupt phar file. Since no-one else has this issue (And a failing autoloader would be rather important) I'm inclined to think the problem's on your end somewhere

Yes @jnvsor  I checked that:-
Registered PHP Streams | https, ftps, compress.zlib, php, file, glob, data, http, ftp, compress.bzip2, phar, zip
I don't think the Phar file is corrupt. I downloaded it from here yesterday. And as i say above the same thing happens with Kint 4.
I think the problem is an interaction with Magento (since the Magento 2.4 upgrade).
I added the statement
d('Dumped with Kint');
immediately after the include Kint statement
require_once (realpath(dirname(__FILE__)) . DS . 'kint5' . DS .'kint.phar');
and got this output:-
string (16) "Dumped with Kint"
Called from .../testShowProducts.php:20
So kint is working
Then a bit further down the script I initialise the Magento environment
$params = $_SERVER;
$bootstrap = Bootstrap::create(BP, $params);
$objectManager = $bootstrap->getObjectManager();
$state = $objectManager->get('Magento\Framework\App\State');
$state->setAreaCode('frontend');
kint::dump($state);

and the kint::dump($state) produces the error.

When you put it that way it makes perfect sense if magento is blowing away the phar autoloader. What happens if you include the phar after magento bootstraps?

Good idea - i will trry.....
Nope - same error.

So if you first include the phar and dump something right after that after your $state->setAreaCode call it still doesn't work?
Does phpinfo() still say phars are enabled after the magento bootstrap? Maybe it's disabling them for security or something

Exactly.
phpinfo() reports phar is enabled after the script runs.

Should have checked the stream handler: https://github.com/magento/magento2/issues/21973
So they deliberately disable the phar stream handler for security reasons. Apparently you can use stream_wrapper_restore to fix it

Ok great - well spotted! Thanks for your help. Will try that.
Surprised it's not come up here before because that dates back to Magento 2.3.1 in 2021


session.connect_cloud() doesn't work

Here's my code-
import scratchattach as sa
session = sa.login('x', 'x')
cloud = session.connect_cloud('1049536501')
That gives this error-
Traceback (most recent call last):
File "c:\Users\x\Desktop\py_work\scratchattachServer", line 6, in
cloud = session.connect_cloud('1049536501')
TypeError: Session.connect_cloud() takes 1 positional argument but 2 were given
In the example, there's only one argument, the project id. Why does it not like the new id? Where is the second one?
I'm using 0.4.2

In 0.4.2 you need to specify the ID with project_id .
session = sa.login('x', 'x')
cloud = session.connect_cloud(project_id='1049536501')
cloud.set_var("variable", "value")

Click here for more details.
We recommend updating Scratchattach.
pip install -U scratchattach

there are two arguments because this is a method of an object. The first parameter is self (passed automatically), and the second is the project id you passed in. however, in 0.4.2, the method only wants one positional argument (self), and a keyword argument (project_id), whose name must be explicitly passed as an argument, i.e. py session.connect_cloud(project_id=```1234)

update to the latest scratchattach version (v2.1.6). 0.4.2 is very outdated


Issue upgrading helm chart intel-device-plugins-gpu from v0.27.1 to v0.28.0

helm values
name: intel-device-plugin-gpu
sharedDevNum: 3
nodeFeatureRule: true

error
Invalid: NodeFeatureRule.nfd.k8s-sigs.io "intel-gpu-platform-labeling" is invalid: [spec.rules[1].labels: Invalid value: "null": spec.rules[1].labels in body must be of type object: "null", spec.rules[2].labels: Invalid value: "null": spec.rules[2].labels in body must be of type object: "null", spec.rules[3].labels: Invalid value: "null": spec.rules[3].labels in body must be of type object: "null"]

Same issue here

Thanks for reporting this. We'll look into it.

I wasn't able to reproduce this.
@mitchross or @onedr0p can you provide some details of the environment? For example versions for nfd, helm and k8s.

having the same issue, here's details of my environment: nfd 0.14.1, k8s (k3s): v1.28.2+k3s1, deployed with flux, using: helm-controller:v0.36.1, image-automation-controller:v0.36.1, image-reflector-controller:v0.30.0, kustomize-controller:v1.1.0, notification-controller:v1.1.0 and source-controller:v1.1.1.

As the error message is about label, I think it's about an empty key here: https://github.com/intel/helm-charts/blob/main/charts/gpu-device-plugin/templates/gpu.yaml#L61
As I haven't been able to reproduce this, if any of you can tweak a local chart and remove the empty "label", and try to upgrade again?

@tkatila I'll let others try this, unfortunately I don't have time earlier this week. But, you're right, here's a kustomize build diff for versions 0.27.1 and 0.28.0:
--- kubernetes HelmRelease: kube-system/intel-device-plugin-gpu GpuDevicePlugin: kube-system/intel-gpu-plugin

+++ kubernetes HelmRelease: kube-system/intel-device-plugin-gpu GpuDevicePlugin: kube-system/intel-gpu-plugin

@@ -1,14 +1,13 @@

 ---
 apiVersion: deviceplugin.intel.com/v1
 kind: GpuDevicePlugin
 metadata:
   name: intel-gpu-plugin
 spec:
-  image: intel/intel-gpu-plugin:0.27.1
-  initImage: intel/intel-gpu-initcontainer:0.27.1
+  image: intel/intel-gpu-plugin:0.28.0
   logLevel: 2
   sharedDevNum: 3
   resourceManager: false
   enableMonitoring: true
   preferredAllocationPolicy: none
   nodeSelector:
--- kubernetes HelmRelease: kube-system/intel-device-plugin-gpu NodeFeatureRule: kube-system/intel-gpu-platform-labeling

+++ kubernetes HelmRelease: kube-system/intel-device-plugin-gpu NodeFeatureRule: kube-system/intel-gpu-platform-labeling

@@ -0,0 +1,206 @@

+---
+apiVersion: nfd.k8s-sigs.io/v1alpha1
+kind: NodeFeatureRule
+metadata:
+  name: intel-gpu-platform-labeling
+spec:
+  rules:
+  - extendedResources:
+      gpu.intel.com/millicores<EMAIL_ADDRESS>+      gpu.intel.com/memory.max<EMAIL_ADDRESS>+      gpu.intel.com/tiles<EMAIL_ADDRESS>+    matchFeatures:
+    - feature: local.label
+      matchExpressions:
+        gpu.intel.com/millicores:
+          op: Exists
+        gpu.intel.com/memory.max:
+          op: Exists
+        gpu.intel.com/tiles:
+          op: Exists
+    name: intel.gpu.fractionalresources
+  - labels: null
+    labelsTemplate: |
+      {{ range .pci.device }}gpu.intel.com/device-id.{{ .class }}-{{ .device }}.present=true
+      {{ end }}
+    matchFeatures:
+    - feature: pci.device
+      matchExpressions:
+        class:
+          op: In
+          value:
+          - '0300'
+          - 0380
+        vendor:
+          op: In
+          value:
+          - '8086'
+    name: intel.gpu.generic.deviceid
+  - labels: null
+    labelsTemplate: gpu.intel.com/device-id.0300-{{ (index .pci.device 0).device }}.count={{
+      len .pci.device }}
+    matchFeatures:
+    - feature: pci.device
+      matchExpressions:
+        class:
+          op: In
+          value:
+          - '0300'
+        vendor:
+          op: In
+          value:
+          - '8086'
+    name: intel.gpu.generic.count.300
+  - labels: null
+    labelsTemplate: gpu.intel.com/device-id.0380-{{ (index .pci.device 0).device }}.count={{
+      len .pci.device }}
+    matchFeatures:
+    - feature: pci.device
+      matchExpressions:
+        class:
+          op: In
+          value:
+          - 0380
+        vendor:
+          op: In
+          value:
+          - '8086'
+    name: intel.gpu.generic.count.380
+  - labels:
+      gpu.intel.com/product: Max_1100
+    labelsTemplate: gpu.intel.com/device.count={{ len .pci.device }}
+    matchFeatures:
+    - feature: pci.device
+      matchExpressions:
+        class:
+          op: In
+          value:
+          - 0380
+        vendor:
+          op: In
+          value:
+          - '8086'
+        device:
+          op: In
+          value:
+          - 0bda
+    name: intel.gpu.max.1100
+  - labels:
+      gpu.intel.com/product: Max_1550
+    labelsTemplate: gpu.intel.com/device.count={{ len .pci.device }}
+    matchFeatures:
+    - feature: pci.device
+      matchExpressions:
+        class:
+          op: In
+          value:
+          - 0380
+        vendor:
+          op: In
+          value:
+          - '8086'
+        device:
+          op: In
+          value:
+          - 0bd5
+    name: intel.gpu.max.1550
+  - labels:
+      gpu.intel.com/family: Max_Series
+    matchFeatures:
+    - feature: pci.device
+      matchExpressions:
+        class:
+          op: In
+          value:
+          - 0380
+        vendor:
+          op: In
+          value:
+          - '8086'
+        device:
+          op: In
+          value:
+          - 0bda
+          - 0bd5
+          - 0bd9
+          - 0bdb
+          - 0bd7
+          - 0bd6
+          - 0bd0
+    name: intel.gpu.max.series
+  - labels:
+      gpu.intel.com/family: Flex_Series
+      gpu.intel.com/product: Flex_170
+    labelsTemplate: gpu.intel.com/device.count={{ len .pci.device }}
+    matchFeatures:
+    - feature: pci.device
+      matchExpressions:
+        class:
+          op: In
+          value:
+          - 0380
+        vendor:
+          op: In
+          value:
+          - '8086'
+        device:
+          op: In
+          value:
+          - 56c0
+    name: intel.gpu.flex.170
+  - labels:
+      gpu.intel.com/family: Flex_Series
+      gpu.intel.com/product: Flex_140
+    labelsTemplate: gpu.intel.com/device.count={{ len .pci.device }}
+    matchFeatures:
+    - feature: pci.device
+      matchExpressions:
+        class:
+          op: In
+          value:
+          - 0380
+        vendor:
+          op: In
+          value:
+          - '8086'
+        device:
+          op: In
+          value:
+          - 56c1
+    name: intel.gpu.flex.140
+  - labels:
+      gpu.intel.com/family: A_Series
+    matchFeatures:
+    - feature: pci.device
+      matchExpressions:
+        class:
+          op: In
+          value:
+          - '0300'
+        vendor:
+          op: In
+          value:
+          - '8086'
+        device:
+          op: In
+          value:
+          - 56a6
+          - 56a5
+          - 56a1
+          - 56a0
+          - '5694'
+          - '5693'
+          - '5692'
+          - '5691'
+          - '5690'
+          - 56b3
+          - 56b2
+          - 56a4
+          - 56a3
+          - '5697'
+          - '5696'
+          - '5695'
+          - 56b1
+          - 56b0
+    name: intel.gpu.a.series
+

I have this issue too. I had to roll back to 0.27.1 to get back up and running.

We haven't been able to reproduce this. @tkatila created a PR so if someone with the error could help test that. If it fixes the error, we can it released asap.
As a workaround, it's possible to install with nodeFeatureRule boolean set to false.

thanks @mythi. do you maintain a helm chart repo for pull requests, or what is the best way to test that PR out? sorry, I'm new to k8s/helm world.

@arthurgeek the best way to help with testing is to git clone @tkatila's repo for that fix PR and helm package/install the gpu chart as a local package

hey, we merged a potential fix. please re-open this issue if the problem still appears with 0.28.1-helm.0.

Confirmed that helm chart is working, thanks!


add static routes to frr plugin

Sometimes you might want to quickly set a route, blackhole some traffic, or create an interface route.

First of all, thank you, but, I have no idea if this get's merged as it would conflict with the logic of core features. This may create many support requests as  the daemon can't handle all events from changing routes, restarting services (/usr/local/etc/rc.XXX) etc.
Now to the patch, can you rename it to Static instead of FIXED? This sounds a bit misleading ;) The others are only upper case since they are protocol abbreviations. If this is really considered to get merged, it would be good to also add interface routes, not only gateway routes.

Understand that it might conflict with core functionality and should probably be used "at your own risk" Maybe add a disclaimer on the enable page?
I changed the naming from "fixed" to "staticd" didn't really like the idea of naming files and classes etc.. "static". I also broke out the UI into IPv4 and IPv6 tabs along with interface, distance, and blackhole under advanced.


Disability improvements

To allow disabled players to better enjoy games made with Escoria, we could provide some stuff:

Outlining items when focused (not only for disabled people)
Iterate over all items on screen (room focusable items, inventory items...)

Hi @StraToN.
Do you plan to have those features always on or give support for devs who what to implement them?
Thanks

Very good idea, @StraToN ❤
@stickgrinder I think we need to identify the places in the core plugin that are needed to support accessibility. Additionally, we'd need to make our stock GUIs accessible and add documentation for game devs, because in the end it's them that need to have game UI that supports a11y.
It would be awesome to have support from disabled players/gamedevs on this one to tell us, what they need. Like: Are screenreaders used to play games? Is Voiceover required?
I had a similar request over at Parrot to include contrast-friendly fonts. I added an example font for that and documented what need to be changed for developers, that want to include a11y support.

@stickgrinder

Do you plan to have those features always on or give support for devs who what to implement them?
Thanks

It is a complicated area. I am not too used to disability and sometimes I tend to rely on visual diseases. Game developers cannot "just use" something we did because it may not be coherent with the game style. And some of them may even not use them at all anyway. This their choice, but I believe if Escoria provides some elements in its core that can ease gamedev work on this topic, then maybe they'll agree to use them.
Whether game developers want to use them or not is not our concern (if it was, we'd just force it enabled). So to answer your question: I'd aim at giving support for devs who want to have these features in their game.

Thanks  guys, all clear. This is a very good initiative, even considering that P&C games are probably a well suited genre for who suffers from disabilities, in that they don't usually require frantic interactions or fast motion.
Will definitely keep an eye on this.


Add missing registry mapping when generating Tinkerbell CP Spec

Issue #, if available:
Description of changes:
This PR adds registers a Secret Kind mapping to the control plane parse which seems to be missing when generating Tinker-bell CP Spec.
Testing (if applicable):
By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

/test all

/retest

/retest all

/retest

/lgtm

/approve


Erros with  imports on promisekit.h file (version 1.7)

I've got this errors when I try to compile on release:
- ERROR | xcodebuild:  /Users/matteo/Library/Developer/Xcode/DerivedData/App-agyylfaavsayemdgzozvlpmubnef/Build/Products/Release-iphonesimulator/PromiseKit/PromiseKit.framework/Headers/PromiseKit.h:44:9: error: 'NSNotificationCenter+PromiseKit.h' file not found with <angled> include; use "quotes" instead
- ERROR | xcodebuild:  /Users/matteo/Library/Developer/Xcode/DerivedData/App-agyylfaavsayemdgzozvlpmubnef/Build/Products/Release-iphonesimulator/PromiseKit/PromiseKit.framework/Headers/PromiseKit.h:50:9: error: 'NSURLConnection+PromiseKit.h' file not found with <angled> include; use "quotes" instead
- ERROR | xcodebuild:  /Users/matteo/Library/Developer/Xcode/DerivedData/App-agyylfaavsayemdgzozvlpmubnef/Build/Products/Release-iphonesimulator/PromiseKit/PromiseKit.framework/Headers/PromiseKit.h:59:9: error: 'UIActionSheet+PromiseKit.h' file not found with <angled> include; use "quotes" instead
- ERROR | xcodebuild:  /Users/matteo/Library/Developer/Xcode/DerivedData/App-agyylfaavsayemdgzozvlpmubnef/Build/Products/Release-iphonesimulator/PromiseKit/PromiseKit.framework/Headers/PromiseKit.h:62:9: error: 'UIAlertView+PromiseKit.h' file not found with <angled> include; use "quotes" instead
- ERROR | xcodebuild:  /Users/matteo/Library/Developer/Xcode/DerivedData/App-agyylfaavsayemdgzozvlpmubnef/Build/Products/Release-iphonesimulator/PromiseKit/PromiseKit.framework/Headers/PromiseKit.h:65:9: error: 'UIView+PromiseKit.h' file not found with <angled> include; use "quotes" instead
- ERROR | xcodebuild:  /Users/matteo/Library/Developer/Xcode/DerivedData/App-agyylfaavsayemdgzozvlpmubnef/Build/Products/Release-iphonesimulator/PromiseKit/PromiseKit.framework/Headers/PromiseKit.h:68:9: error: 'UIViewController+PromiseKit.h' file not found with <angled> include; use "quotes" instead

If I replace <angled> imports by "quotes" imports everything works fine but I don't know if it is a good solution. Can someone help me please?

You have not provided enough information for us to help you, Xcode version? PromiseKit version? How did you install PromiseKit? Etc.

I'm using Xcode 7.3 and PromiseKit v 1.7 installed via cocoapods 1.0
Errors occur only when I try to compile on release.
- ERROR | xcodebuild: ../Release-iphonesimulator/PromiseKit/PromiseKit.framework/Headers/PromiseKit.h:44:9: error: 'NSNotificationCenter+PromiseKit.h' file not found with <angled> include; use "quotes" instead
- ERROR | xcodebuild:  ../Release-iphonesimulator/PromiseKit/PromiseKit.framework/Headers/PromiseKit.h:50:9: error: 'NSURLConnection+PromiseKit.h' file not found with <angled> include; use "quotes" instead
- ERROR | xcodebuild:  ../Release-iphonesimulator/PromiseKit/PromiseKit.framework/Headers/PromiseKit.h:59:9: error: 'UIActionSheet+PromiseKit.h' file not found with <angled> include; use "quotes" instead
- ERROR | xcodebuild: ../Release-iphonesimulator/PromiseKit/PromiseKit.framework/Headers/PromiseKit.h:62:9: error: 'UIAlertView+PromiseKit.h' file not found with <angled> include; use "quotes" instead
- ERROR | xcodebuild:  ../Release-iphonesimulator/PromiseKit/PromiseKit.framework/Headers/PromiseKit.h:65:9: error: 'UIView+PromiseKit.h' file not found with <angled> include; use "quotes" instead
- ERROR | xcodebuild: ../Release-iphonesimulator/PromiseKit/PromiseKit.framework/Headers/PromiseKit.h:68:9: error: 'UIViewController+PromiseKit.h' file not found with <angled> include; use "quotes" instead

Thanks!

You're building at the command line with xcodebuild? Does the same happen in Xcode with the Archive option?

I'm running pod spec lint

I believe this may be a change in how CocoaPods specifies its import path since 1.0.

Closing manually since GitHub will not auto close commits not merged into master.

In case anyone is still interested, I fixed the issue by adding this lines in the bottom of my Podfile:
post_install do |installer|
	`find Pods -regex 'Pods/PromiseKit/objc/PromiseKit.h' -print0 | xargs -0 sed -i '' 's/\\(<\\)\\(.*\\)\\(>\\)/\\"\\2\\"/'`
end


The request was denied due to request throttling.

Current Version: 2.1.2
Current Behvaiour:
Error is coming, not receiving the product response. I have just created my Access key and Secret key to call Product Advertising API but I am receiving an error in response whenever I am calling the API from my local project. Error is,  "The request was denied due to request throttling. Please verify the number of requests made per second to the Amazon Product Advertising API."
I have verified and I found that I am not making multiple requests. I have used your sample code only. Also, I googled and came to know that after creating the Access and Secret key one has to wait for 48 hours. So do I need to wait for 48 hours or I am missing something else on this.
Any information on this would be of great help to me.
Expected behavior:
It should have returned the response where I have seen the product details
Code:
var authentication = new AmazonAuthentication("myAccessKey", "mySecretKey");
var client = new AmazonProductAdvertisingClient(authentication, AmazonEndpoint.IN, "jugaadhai-21");
var result = await client.SearchItemsAsync("canon eos");

As of January, 2019 – Amazon has now placed restrictions and limitations on who gets access to the API. Basically, you MUST have qualified sales attributed to API links within the previous trailing 30 days in order to prevent your API access from being revoked or limited (throttled).

As of January, 2019 – Amazon has now placed restrictions and limitations on who gets access to the API. Basically, you MUST have qualified sales attributed to API links within the previous trailing 30 days in order to prevent your API access from being revoked or limited (throttled).

@tinohager What does qualified sales means? In last month I made around 100$ and 241 items have been ordered using my Amazon associate. While generating Credentials for PA API it was written on that page "In order to qualify for requesting access to PA API, you will need an associate account, you will have to complete 3 qualifying sales in the first 180 days and you will have to comply with the Operating Agreement. Once your account is approved as an associate account, you will see a 'Request for PA API access' button below. You can click the button to get access to PA API."
Seeing this it seems like I am eligible, don't know what's missing or what I am doing wrong?

Have you try contact amazon over the contact form?

I have contacted them and the response which I received from them is not of much help.

After the above email from Amazon, I replied "I have attached one image in which I am not able to see PA-API transactions. Maybe it is because I have enabled PA API today only.
As you can see in the image, in the last 30 days we made somewhere around 100$. Am I still not qualified for using PA API?. Can you please check into my account and let me know."
After my above mail, last mail which I  received in that they were telling they are not equipped to provide any technical support or answer the queries related to Product Advertising API. They provided me some resources like the Getting started link, Scratchpad link, Detailed Documentation link, etc.
I am going to ask this question in the Amazon developer forum also. Let's see what I will get in response from there

Same issue: The request has not been correctly signed

@tinohager I wanted to let you know that API started working successfully by default. Somewhere I read it takes 48 hours once you activate your token key. So I used to daily open my project and check it and glad it worked. Your code is working fine buddy.
Thank you.


How to display i18n error message if user name has already been taken?

Based on what I found in the documentation, I am using the following code to set-up the additional field username:
if (Meteor.isServer) {
  Meteor.methods({
    "userExists": function(username) {
      check(username, String);
      return !!Meteor.users.findOne({
        username: username
      });
    },
  });
}

var pwd = AccountsTemplates.removeField('password');
AccountsTemplates.removeField('email');
AccountsTemplates.addFields([{
    _id: "username",
    type: "text",
    displayName: "username",
    required: true,
    minLength: 3,
    func: function(value) {
      if (Meteor.isClient) {
        var self = this;
        Meteor.call("userExists", value, function(err, userExists) {
          if (!userExists) {
            self.setSuccess();
          } else {
            self.setError(userExists);
          }
          self.setValidating(false);
        });
        return;
      }
      // Server
      return Meteor.call("userExists", value);
    }
  }, {
    _id: 'email',
    type: 'email',
    required: true,
    displayName: "email",
    re: /.+@(.+){2,}\.(.+){2,}/,
    errStr: 'Invalid email',
  },
  pwd
]);

The field shows up and works as expected. However, if I enter a user name that has already been taken, no error message is shown (although the dialog stays on-screen due to the error).
I am also using the softwarerero:accounts-t9n package for i18n and expected that the right internationalized error message would be picked if setError is just called with a true value, as described in the docs. Since this did not work, I also tried to set a string instead, and I also tried to set this string to one of the i18n keys in the accounts-t9n package, but none of these approaches made the error message appear.

I tried out different things, but it seems as if the setError() method is not working as expected. If I return a value from the func instead, it is displayed as an error message. But the async way using .setValidating() and setError() seems to be broken.

@derwaldgeist how are you setting negativeValidation and negativeFeedback flags? (see Form Fields Configuration)
the above code snippet should be enough to highlight the validation error on the input field, but it's not going to show any error in the error box.

Thanks for coming back on this. Both values (negativeValidation and negativeFeedback) are left to their defaults. Do I have to change something here? I did not notice any difference when I changed these values (I am using the Bootstrap version, BTW).


proton-pass: 1.17.5 -> 1.18.0

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://repology.org/project/proton-pass/versions.
meta.description for proton-pass is: Desktop application for Proton Pass
meta.homepage for proton-pass is: https://proton.me/pass
Updates performed

Version update

To inspect upstream changes
Impact
Checks done

built on NixOS
The tests defined in passthru.tests, if any, passed
found 1.18.0 with grep in /nix/store/ssfg507wzksai8aznjg564qybm9ggvx8-proton-pass-1.18.0
found 1.18.0 in filename of file in /nix/store/ssfg507wzksai8aznjg564qybm9ggvx8-proton-pass-1.18.0

Rebuild report (if merged into master) (click to expand)

2 total rebuild path(s)

2 package rebuild(s)

First fifty rebuilds by attrpath

proton-pass

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/ssfg507wzksai8aznjg564qybm9ggvx8-proton-pass-1.18.0 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A proton-pass https://github.com/r-ryantm/nixpkgs/archive/83df76b099432a9f68a7d9944403a480b1b12d71.tar.gz

Or:
nix build github:r-ryantm/nixpkgs/83df76b099432a9f68a7d9944403a480b1b12d71#proton-pass

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/ssfg507wzksai8aznjg564qybm9ggvx8-proton-pass-1.18.0
ls -la /nix/store/ssfg507wzksai8aznjg564qybm9ggvx8-proton-pass-1.18.0/bin

Pre-merge build results
We have automatically built all packages that will get rebuilt due to
this change.
This gives evidence on whether the upgrade will break dependent packages.
Note sometimes packages show up as failed to build independent of the
change, simply because they are already broken on the target branch.
Result of nixpkgs-review --extra-nixpkgs-config '{ allowInsecurePredicate = x: true; }' run on x86_64-linux 1

1 package built:

proton-pass

Maintainer pings
cc @massix @SebTM for testing.

Result of nixpkgs-review pr 322635 run on x86_64-linux 1

1 package built:

proton-pass


Issue 85

What type of PR is this?

Uncomment only one  /kind <> line, hit enter to put that in a new line, and remove leading whitespace from that line:
/kind new feature
/kind bug fix
/kind cleanup
/kind revert change
/kind design
/kind documentation
/kind enhancement

What this PR does / why we need it:
Adds Faroe release to documentation
Fixes grammer, typos and formatting issues
Which issue(s) this PR fixes:

Fixes #85
Test Report Added?:

Uncomment only one  /kind <> line, hit enter to put that in a new line, and remove leading whitespace from that line:
 /kind TESTED
/kind NOT-TESTED

Test Report:

Special notes for your reviewer:

@anvithks  : moved the changes from previous branch to this one.
@skdwriting @kumarashit  Please review .


Fix lodview issues

This PR does :

manage variables for set welcome text for dati-semtanci-lodview with kubernetes conf.
manage variable for set redirect link for dati-semantic-lodview on click to banner logo
manage variables for set internal/public sparql for dati-semantic-lodview

Fixes:36

teamdigitale/dati-semantic-lodview#26
teamdigitale/dati-semantic-lodview#36
teamdigitale/dati-semantic-lodview#37

cc: @ioggstream


Change TFT price to 10c on http://explorer.grid.tf/

Hi, as per request from Kristof, we need to change token price from 5c to 10c on http://explorer.grid.tf/.

yes indeed,

Explorers have been updated. New price is now reflected on the UI and used to calculate reservation costs


Add different icons for indent levels

This PR adds custom styles to override MkDocs defaults and enhance theme
Unordered list symbols added :

level 1 ul default is filled disc (bullet)
level 2 is hollow circle
level 3 is filled square

With this changes, nested list items look like this:


【求助】英伟达 L40 4卡无法微调通义千问2 72B INT4 模型

英伟达 L40 4卡无法微调通义千问2 72B INT4 模型。
帮忙指导下，8卡L40环境下，如何将  Qwen2-72B-Instruct-GPTQ-Int4 模型能微调跑通？是否可行，或者需要优化哪些参数？
相关环境信息及错误信息如下：
环境，8卡L40环境中，使用第4~7张GPU卡来微调。
1、GPU信息
nvidia-smi
Mon Aug 12 17:25:08 2024
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.104.05             Driver Version: 535.104.05   CUDA Version: 12.2     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  NVIDIA L40                     Off | 00000000:28:00.0 Off |                    0 |
| N/A   35C    P0              77W / 300W |  41499MiB / 46068MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
|   1  NVIDIA L40                     Off | 00000000:29:00.0 Off |                    0 |
| N/A   37C    P0              77W / 300W |  37812MiB / 46068MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
|   2  NVIDIA L40                     Off | 00000000:2C:00.0 Off |                    0 |
| N/A   39C    P0              82W / 300W |  37812MiB / 46068MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
|   3  NVIDIA L40                     Off | 00000000:31:00.0 Off |                    0 |
| N/A   39C    P0              77W / 300W |  37732MiB / 46068MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
|   4  NVIDIA L40                     Off | 00000000:A8:00.0 Off |                    0 |
| N/A   29C    P8              35W / 300W |     20MiB / 46068MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
|   5  NVIDIA L40                     Off | 00000000:A9:00.0 Off |                    0 |
| N/A   30C    P8              34W / 300W |     20MiB / 46068MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
|   6  NVIDIA L40                     Off | 00000000:AC:00.0 Off |                    0 |
| N/A   28C    P8              34W / 300W |     20MiB / 46068MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
|   7  NVIDIA L40                     Off | 00000000:B1:00.0 Off |                    0 |
| N/A   27C    P8              34W / 300W |     20MiB / 46068MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
+---------------------------------------------------------------------------------------+
| Processes:                                                                            |
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |
|        ID   ID                                                             Usage      |
|=======================================================================================|
|    0   N/A  N/A      7059      G   /usr/libexec/Xorg                             4MiB |
|    0   N/A  N/A   2311649      C   text-embeddings-router                     3610MiB |
|    0   N/A  N/A   2877274      C   python3                                   37848MiB |
|    1   N/A  N/A      7059      G   /usr/libexec/Xorg                             4MiB |
|    1   N/A  N/A   2888645      C   /usr/bin/python3                          37776MiB |
|    2   N/A  N/A      7059      G   /usr/libexec/Xorg                             4MiB |
|    2   N/A  N/A   2888646      C   /usr/bin/python3                          37776MiB |
|    3   N/A  N/A      7059      G   /usr/libexec/Xorg                             4MiB |
|    3   N/A  N/A   2888647      C   /usr/bin/python3                          37696MiB |
|    4   N/A  N/A      7059      G   /usr/libexec/Xorg                             4MiB |
|    5   N/A  N/A      7059      G   /usr/libexec/Xorg                             4MiB |
|    6   N/A  N/A      7059      G   /usr/libexec/Xorg                             4MiB |
|    7   N/A  N/A      7059      G   /usr/libexec/Xorg                             4MiB |
+---------------------------------------------------------------------------------------+
2、使用swift的docker镜像
docker run -d --name swift  -it --runtime nvidia --gpus all
--ipc=host
-v /root/dingtest/Qwen:/data
modelscope-registry.cn-hangzhou.cr.aliyuncs.com/modelscope-repo/modelscope:ubuntu22.04-cuda12.1.0-py310-torch2.3.0-tf2.16.1-1.16.0
bin/bash
3、微调的命令：
CUDA_VISIBLE_DEVICES=4,5,6,7
NPROC_PER_NODE=4
swift sft
--model_id_or_path /data/Qwen2-72B-Instruct-GPTQ-Int4
--model_type qwen2-72b-instruct-int4
--dataset alpaca-zh#500 alpaca-en#500 self-cognition#500
--max_length 1024
--learning_rate 1e-4
--output_dir output
--lora_target_modules ALL
--model_name 小黄 'Xiao Huang'
--model_author 魔搭 ModelScope
--deepspeed default-zero3
4、出错信息：
Detected kernel version 4.18.0, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher.
[INFO:swift] The SftArguments will be saved in: /output/qwen2-72b-instruct-int4/v1-20240812-172948/sft_args.json
[INFO:swift] The Seq2SeqTrainingArguments will be saved in: /output/qwen2-72b-instruct-int4/v1-20240812-172948/training_args.json
[INFO:swift] The logging file will be saved in: /output/qwen2-72b-instruct-int4/v1-20240812-172948/logging.jsonl
Using /root/.cache/torch_extensions/py310_cu121 as PyTorch extensions root...
Using /root/.cache/torch_extensions/py310_cu121 as PyTorch extensions root...
Using /root/.cache/torch_extensions/py310_cu121 as PyTorch extensions root...
Using /root/.cache/torch_extensions/py310_cu121 as PyTorch extensions root...
Detected CUDA files, patching ldflags
Emitting ninja build file /root/.cache/torch_extensions/py310_cu121/fused_adam/build.ninja...
/usr/local/lib/python3.10/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation.
If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].
warnings.warn(
Building extension module fused_adam...
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
ninja: no work to do.
Loading extension module fused_adam...
Time to load fused_adam op: 0.08309817314147949 seconds
Loading extension module fused_adam...
Loading extension module fused_adam...
Time to load fused_adam op: 0.10232162475585938 seconds
Time to load fused_adam op: 0.10274553298950195 seconds
Loading extension module fused_adam...
Time to load fused_adam op: 0.10145998001098633 seconds
Parameter Offload: Total persistent parameters: 49815552 in 1041 params
Train:   0%|                                                                                | 0/93 [00:00<?, ?it/s][rank2]: Traceback (most recent call last):
[rank2]:   File "/usr/local/lib/python3.10/site-packages/swift/cli/sft.py", line 5, in
[rank2]:     sft_main()
[rank2]:   File "/usr/local/lib/python3.10/site-packages/swift/utils/run_utils.py", line 27, in x_main
[rank2]:     result = llm_x(args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/swift/llm/sft.py", line 308, in llm_sft
[rank2]:     trainer.train(training_args.resume_from_checkpoint)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/swift/trainers/mixin.py", line 518, in train
[rank2]:     res = super().train(resume_from_checkpoint, *args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/transformers/trainer.py", line 1885, in train
[rank2]:     return inner_training_loop(
[rank2]:   File "/usr/local/lib/python3.10/site-packages/transformers/trainer.py", line 2216, in _inner_training_loop
[rank2]:     tr_loss_step = self.training_step(model, inputs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/transformers/trainer.py", line 3238, in training_step
[rank2]:     loss = self.compute_loss(model, inputs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/swift/trainers/trainers.py", line 183, in compute_loss
[rank2]:     outputs = model(**inputs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank2]:     return self._call_impl(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[rank2]:     return forward_call(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank2]:     ret_val = func(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 1846, in forward
[rank2]:     loss = self.module(*inputs, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank2]:     return self._call_impl(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1582, in _call_impl
[rank2]:     result = forward_call(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/peft/peft_model.py", line 1430, in forward
[rank2]:     return self.base_model(
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank2]:     return self._call_impl(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1582, in _call_impl
[rank2]:     result = forward_call(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/peft/tuners/tuners_utils.py", line 179, in forward
[rank2]:     return self.model.forward(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/transformers/models/qwen2/modeling_qwen2.py", line 1149, in forward
[rank2]:     outputs = self.model(
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank2]:     return self._call_impl(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1582, in _call_impl
[rank2]:     result = forward_call(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/transformers/models/qwen2/modeling_qwen2.py", line 1024, in forward
[rank2]:     layer_outputs = self._gradient_checkpointing_func(
[rank2]:   File "/usr/local/lib/python3.10/site-packages/swift/llm/utils/model.py", line 4843, in
[rank2]:     _old_checkpoint(*args, use_reentrant=use_reentrant, **kwargs))
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/_compile.py", line 24, in inner
[rank2]:     return torch._dynamo.disable(fn, recursive)(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 451, in _fn
[rank2]:     return fn(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/_dynamo/external_utils.py", line 36, in inner
[rank2]:     return fn(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/utils/checkpoint.py", line 494, in checkpoint
[rank2]:     ret = function(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank2]:     return self._call_impl(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1582, in _call_impl
[rank2]:     result = forward_call(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/transformers/models/qwen2/modeling_qwen2.py", line 745, in forward
[rank2]:     hidden_states = self.input_layernorm(hidden_states)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank2]:     return self._call_impl(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1571, in _call_impl
[rank2]:     args_result = hook(self, args)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank2]:     ret_val = func(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/parameter_offload.py", line 278, in _pre_forward_module_hook
[rank2]:     self.pre_sub_module_forward_function(module)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
[rank2]:     return func(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/parameter_offload.py", line 452, in pre_sub_module_forward_function
[rank2]:     param_coordinator.fetch_sub_module(sub_module, forward=True)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 451, in _fn
[rank2]:     return fn(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank2]:     ret_val = func(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
[rank2]:     return func(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/partitioned_param_coordinator.py", line 310, in fetch_sub_module
[rank2]:     self.__inflight_param_registry.pop(param).wait()
[rank2]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/partition_parameters.py", line 716, in wait
[rank2]:     handle.wait()
[rank2]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank2]:     ret_val = func(*args, **kwargs)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/partition_parameters.py", line 697, in wait
[rank2]:     param.data = instrument_w_nvtx(torch.cat)(partitions).view(param.ds_shape)
[rank2]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank2]:     ret_val = func(*args, **kwargs)
[rank2]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 MiB. GPU  has a total capacity of 44.32 GiB of which 3.44 MiB is free. Process 2095471 has 44.29 GiB memory in use. Of the allocated memory 41.76 GiB is allocated by PyTorch, and 1.65 GiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
[rank1]: Traceback (most recent call last):
[rank1]:   File "/usr/local/lib/python3.10/site-packages/swift/cli/sft.py", line 5, in
[rank1]:     sft_main()
[rank1]:   File "/usr/local/lib/python3.10/site-packages/swift/utils/run_utils.py", line 27, in x_main
[rank1]:     result = llm_x(args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/swift/llm/sft.py", line 308, in llm_sft
[rank1]:     trainer.train(training_args.resume_from_checkpoint)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/swift/trainers/mixin.py", line 518, in train
[rank1]:     res = super().train(resume_from_checkpoint, *args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/transformers/trainer.py", line 1885, in train
[rank1]:     return inner_training_loop(
[rank1]:   File "/usr/local/lib/python3.10/site-packages/transformers/trainer.py", line 2216, in _inner_training_loop
[rank1]:     tr_loss_step = self.training_step(model, inputs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/transformers/trainer.py", line 3238, in training_step
[rank1]:     loss = self.compute_loss(model, inputs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/swift/trainers/trainers.py", line 183, in compute_loss
[rank1]:     outputs = model(**inputs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank1]:     return self._call_impl(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[rank1]:     return forward_call(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank1]:     ret_val = func(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 1846, in forward
[rank1]:     loss = self.module(*inputs, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank1]:     return self._call_impl(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1582, in _call_impl
[rank1]:     result = forward_call(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/peft/peft_model.py", line 1430, in forward
[rank1]:     return self.base_model(
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank1]:     return self._call_impl(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1582, in _call_impl
[rank1]:     result = forward_call(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/peft/tuners/tuners_utils.py", line 179, in forward
[rank1]:     return self.model.forward(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/transformers/models/qwen2/modeling_qwen2.py", line 1149, in forward
[rank1]:     outputs = self.model(
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank1]:     return self._call_impl(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1582, in _call_impl
[rank1]:     result = forward_call(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/transformers/models/qwen2/modeling_qwen2.py", line 1024, in forward
[rank1]:     layer_outputs = self._gradient_checkpointing_func(
[rank1]:   File "/usr/local/lib/python3.10/site-packages/swift/llm/utils/model.py", line 4843, in
[rank1]:     _old_checkpoint(*args, use_reentrant=use_reentrant, **kwargs))
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/_compile.py", line 24, in inner
[rank1]:     return torch._dynamo.disable(fn, recursive)(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 451, in _fn
[rank1]:     return fn(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/_dynamo/external_utils.py", line 36, in inner
[rank1]:     return fn(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/utils/checkpoint.py", line 494, in checkpoint
[rank1]:     ret = function(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank1]:     return self._call_impl(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1582, in _call_impl
[rank1]:     result = forward_call(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/transformers/models/qwen2/modeling_qwen2.py", line 745, in forward
[rank1]:     hidden_states = self.input_layernorm(hidden_states)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank1]:     return self._call_impl(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1571, in _call_impl
[rank1]:     args_result = hook(self, args)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank1]:     ret_val = func(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/parameter_offload.py", line 278, in _pre_forward_module_hook
[rank1]:     self.pre_sub_module_forward_function(module)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
[rank1]:     return func(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/parameter_offload.py", line 452, in pre_sub_module_forward_function
[rank1]:     param_coordinator.fetch_sub_module(sub_module, forward=True)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 451, in _fn
[rank1]:     return fn(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank1]:     ret_val = func(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
[rank1]:     return func(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/partitioned_param_coordinator.py", line 310, in fetch_sub_module
[rank1]:     self.__inflight_param_registry.pop(param).wait()
[rank1]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/partition_parameters.py", line 716, in wait
[rank1]:     handle.wait()
[rank1]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank1]:     ret_val = func(*args, **kwargs)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/partition_parameters.py", line 697, in wait
[rank1]:     param.data = instrument_w_nvtx(torch.cat)(partitions).view(param.ds_shape)
[rank1]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank1]:     ret_val = func(*args, **kwargs)
[rank1]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 MiB. GPU  has a total capacity of 44.32 GiB of which 3.44 MiB is free. Process 2095470 has 44.29 GiB memory in use. Of the allocated memory 41.76 GiB is allocated by PyTorch, and 1.65 GiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
[rank0]: Traceback (most recent call last):
[rank0]:   File "/usr/local/lib/python3.10/site-packages/swift/cli/sft.py", line 5, in
[rank0]:     sft_main()
[rank0]:   File "/usr/local/lib/python3.10/site-packages/swift/utils/run_utils.py", line 27, in x_main
[rank0]:     result = llm_x(args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/swift/llm/sft.py", line 308, in llm_sft
[rank0]:     trainer.train(training_args.resume_from_checkpoint)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/swift/trainers/mixin.py", line 518, in train
[rank0]:     res = super().train(resume_from_checkpoint, *args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/transformers/trainer.py", line 1885, in train
[rank0]:     return inner_training_loop(
[rank0]:   File "/usr/local/lib/python3.10/site-packages/transformers/trainer.py", line 2216, in _inner_training_loop
[rank0]:     tr_loss_step = self.training_step(model, inputs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/transformers/trainer.py", line 3238, in training_step
[rank0]:     loss = self.compute_loss(model, inputs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/swift/trainers/trainers.py", line 183, in compute_loss
[rank0]:     outputs = model(**inputs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[rank0]:     return forward_call(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank0]:     ret_val = func(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 1846, in forward
[rank0]:     loss = self.module(*inputs, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1582, in _call_impl
[rank0]:     result = forward_call(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/peft/peft_model.py", line 1430, in forward
[rank0]:     return self.base_model(
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1582, in _call_impl
[rank0]:     result = forward_call(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/peft/tuners/tuners_utils.py", line 179, in forward
[rank0]:     return self.model.forward(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/transformers/models/qwen2/modeling_qwen2.py", line 1149, in forward
[rank0]:     outputs = self.model(
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1582, in _call_impl
[rank0]:     result = forward_call(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/transformers/models/qwen2/modeling_qwen2.py", line 1024, in forward
[rank0]:     layer_outputs = self._gradient_checkpointing_func(
[rank0]:   File "/usr/local/lib/python3.10/site-packages/swift/llm/utils/model.py", line 4843, in
[rank0]:     _old_checkpoint(*args, use_reentrant=use_reentrant, **kwargs))
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/_compile.py", line 24, in inner
[rank0]:     return torch._dynamo.disable(fn, recursive)(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 451, in _fn
[rank0]:     return fn(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/_dynamo/external_utils.py", line 36, in inner
[rank0]:     return fn(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/utils/checkpoint.py", line 494, in checkpoint
[rank0]:     ret = function(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1582, in _call_impl
[rank0]:     result = forward_call(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/transformers/models/qwen2/modeling_qwen2.py", line 745, in forward
[rank0]:     hidden_states = self.input_layernorm(hidden_states)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank0]:     return self._call_impl(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1571, in _call_impl
[rank0]:     args_result = hook(self, args)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank0]:     ret_val = func(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/parameter_offload.py", line 278, in _pre_forward_module_hook
[rank0]:     self.pre_sub_module_forward_function(module)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
[rank0]:     return func(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/parameter_offload.py", line 452, in pre_sub_module_forward_function
[rank0]:     param_coordinator.fetch_sub_module(sub_module, forward=True)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 451, in _fn
[rank0]:     return fn(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank0]:     ret_val = func(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
[rank0]:     return func(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/partitioned_param_coordinator.py", line 310, in fetch_sub_module
[rank0]:     self.__inflight_param_registry.pop(param).wait()
[rank0]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/partition_parameters.py", line 716, in wait
[rank0]:     handle.wait()
[rank0]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank0]:     ret_val = func(*args, **kwargs)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/partition_parameters.py", line 697, in wait
[rank0]:     param.data = instrument_w_nvtx(torch.cat)(partitions).view(param.ds_shape)
[rank0]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank0]:     ret_val = func(*args, **kwargs)
[rank0]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 MiB. GPU
[rank3]: Traceback (most recent call last):
[rank3]:   File "/usr/local/lib/python3.10/site-packages/swift/cli/sft.py", line 5, in
[rank3]:     sft_main()
[rank3]:   File "/usr/local/lib/python3.10/site-packages/swift/utils/run_utils.py", line 27, in x_main
[rank3]:     result = llm_x(args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/swift/llm/sft.py", line 308, in llm_sft
[rank3]:     trainer.train(training_args.resume_from_checkpoint)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/swift/trainers/mixin.py", line 518, in train
[rank3]:     res = super().train(resume_from_checkpoint, *args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/transformers/trainer.py", line 1885, in train
[rank3]:     return inner_training_loop(
[rank3]:   File "/usr/local/lib/python3.10/site-packages/transformers/trainer.py", line 2216, in _inner_training_loop
[rank3]:     tr_loss_step = self.training_step(model, inputs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/transformers/trainer.py", line 3238, in training_step
[rank3]:     loss = self.compute_loss(model, inputs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/swift/trainers/trainers.py", line 183, in compute_loss
[rank3]:     outputs = model(**inputs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank3]:     return self._call_impl(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[rank3]:     return forward_call(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank3]:     ret_val = func(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 1846, in forward
[rank3]:     loss = self.module(*inputs, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank3]:     return self._call_impl(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1582, in _call_impl
[rank3]:     result = forward_call(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/peft/peft_model.py", line 1430, in forward
[rank3]:     return self.base_model(
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank3]:     return self._call_impl(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1582, in _call_impl
[rank3]:     result = forward_call(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/peft/tuners/tuners_utils.py", line 179, in forward
[rank3]:     return self.model.forward(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/transformers/models/qwen2/modeling_qwen2.py", line 1149, in forward
[rank3]:     outputs = self.model(
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank3]:     return self._call_impl(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1582, in _call_impl
[rank3]:     result = forward_call(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/transformers/models/qwen2/modeling_qwen2.py", line 1024, in forward
[rank3]:     layer_outputs = self._gradient_checkpointing_func(
[rank3]:   File "/usr/local/lib/python3.10/site-packages/swift/llm/utils/model.py", line 4843, in
[rank3]:     _old_checkpoint(*args, use_reentrant=use_reentrant, **kwargs))
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/_compile.py", line 24, in inner
[rank3]:     return torch._dynamo.disable(fn, recursive)(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 451, in _fn
[rank3]:     return fn(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/_dynamo/external_utils.py", line 36, in inner
[rank3]:     return fn(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/utils/checkpoint.py", line 494, in checkpoint
[rank3]:     ret = function(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank3]:     return self._call_impl(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1582, in _call_impl
[rank3]:     result = forward_call(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/transformers/models/qwen2/modeling_qwen2.py", line 745, in forward
[rank3]:     hidden_states = self.input_layernorm(hidden_states)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[rank3]:     return self._call_impl(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1571, in _call_impl
[rank3]:     args_result = hook(self, args)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank3]:     ret_val = func(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/parameter_offload.py", line 278, in _pre_forward_module_hook
[rank3]:     self.pre_sub_module_forward_function(module)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
[rank3]:     return func(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/parameter_offload.py", line 452, in pre_sub_module_forward_function
[rank3]:     param_coordinator.fetch_sub_module(sub_module, forward=True)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 451, in _fn
[rank3]:     return fn(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank3]:     ret_val = func(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
[rank3]:     return func(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/partitioned_param_coordinator.py", line 310, in fetch_sub_module
[rank3]:     self.__inflight_param_registry.pop(param).wait()
[rank3]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/partition_parameters.py", line 716, in wait
[rank3]:     handle.wait()
[rank3]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank3]:     ret_val = func(*args, **kwargs)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/runtime/zero/partition_parameters.py", line 697, in wait
[rank3]:     param.data = instrument_w_nvtx(torch.cat)(partitions).view(param.ds_shape)
[rank3]:   File "/usr/local/lib/python3.10/site-packages/deepspeed/utils/nvtx.py", line 15, in wrapped_fn
[rank3]:     ret_val = func(*args, **kwargs)
[rank3]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 MiB. GPU  has a total capacity of 44.32 GiB of which 3.44 MiB is free. Process 2095472 has 44.29 GiB memory in use. Of the allocated memory 41.83 GiB is allocated by PyTorch, and 1.66 GiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
Train:   0%|          | 0/93 [00:08<?, ?it/s]
E0812 17:31:13.756000<PHONE_NUMBER>36992 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: 1) local_rank: 0 (pid: 8189) of binary: /usr/local/bin/python
Traceback (most recent call last):
File "/usr/local/bin/torchrun", line 8, in
sys.exit(main())
File "/usr/local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/init.py", line 347, in wrapper
return f(*args, **kwargs)
File "/usr/local/lib/python3.10/site-packages/torch/distributed/run.py", line 879, in main
run(args)
File "/usr/local/lib/python3.10/site-packages/torch/distributed/run.py", line 870, in run
elastic_launch(
File "/usr/local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 132, in call
return launch_agent(self._config, self._entrypoint, list(args))
File "/usr/local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 263, in launch_agent
raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
/usr/local/lib/python3.10/site-packages/swift/cli/sft.py FAILED
Failures:
[1]:
time      : 2024-08-12_17:31:13
host      : 3f84365aced2
rank      : 1 (local_rank: 1)
exitcode  : 1 (pid: 8190)
error_file: <N/A>
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[2]:
time      : 2024-08-12_17:31:13
host      : 3f84365aced2
rank      : 2 (local_rank: 2)
exitcode  : 1 (pid: 8191)
error_file: <N/A>
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[3]:
time      : 2024-08-12_17:31:13
host      : 3f84365aced2
rank      : 3 (local_rank: 3)
exitcode  : 1 (pid: 8192)
error_file: <N/A>
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
Root Cause (first observed failure):
[0]:
time      : 2024-08-12_17:31:13
host      : 3f84365aced2
rank      : 0 (local_rank: 0)
exitcode  : 1 (pid: 8189)
error_file: <N/A>
traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html

尝试过 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True 配置这个环境变量，还是会出现 GPU 显存不足。

NPROC_PER_NODE=4
是4路DDP，改为2或者1试试
如果仍然OOM，请重开本issue


Made an update to the logic in the config provider to group the logic…

… into chunks and also so that the .env file is the second step in processing rather then the last.

Codecov Report

Merging #196 into master will increase coverage by 0.21%.
The diff coverage is 90%.

@@            Coverage Diff             @@
##           master     #196      +/-   ##
==========================================
+ Coverage   39.22%   39.44%   +0.21%
==========================================
  Files          84       84
  Lines        2822     2832      +10
  Branches      529      529
==========================================
+ Hits         1107     1117      +10
  Misses       1597     1597
  Partials      118      118

Impacted Files
Coverage Δ

src/DebugConfigurationProvider.ts
31.91% <90%> (+5.19%)
:arrow_up:

Continue to review full report at Codecov.

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Unable to upload a new app tar.gz

Hello,
When I try to upload a new app code using this extension, it says "App install failed" - without any error code/text. So I am unable to figure out what the error is. Is there a way to figure out why the app installation is failing? any logs or something

Hi! Thanks for opening an issue - what method of app installation are you using, out of the 3 methods the app offers?
https://splunk.github.io/vscode-extension-splunk-soar/user-guide/tutorial-basics/install-a-local-app/
Are you on the latest version of the extension?


500 "attempt to write a readonly database" error caused by "PRAGMA schema_version"

I've not been able to replicate this myself yet, but I've seen log files from a user affected by it.
File "/usr/local/lib/python3.11/site-packages/datasette/views/base.py", line 89, in dispatch_request
await self.ds.refresh_schemas()
File "/usr/local/lib/python3.11/site-packages/datasette/app.py", line 371, in refresh_schemas
await self._refresh_schemas()
File "/usr/local/lib/python3.11/site-packages/datasette/app.py", line 386, in _refresh_schemas
schema_version = (await db.execute("PRAGMA schema_version")).first()[0]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/datasette/database.py", line 267, in execute
results = await self.execute_fn(sql_operation_in_thread)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/datasette/database.py", line 213, in execute_fn
return await asyncio.get_event_loop().run_in_executor(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/concurrent/futures/thread.py", line 58, in run
result = self.fn(*self.args, **self.kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/datasette/database.py", line 211, in in_thread
return fn(conn)
^^^^^^^^
File "/usr/local/lib/python3.11/site-packages/datasette/database.py", line 237, in sql_operation_in_thread
cursor.execute(sql, params if params is not None else {})
sqlite3.OperationalError: attempt to write a readonly database

That's running the official Datasette Docker image on https://fly.io/ - it's causing 500 errors on every page of their site.

I thought it might relate to the "defensive mode" issue described here:

https://github.com/simonw/sqlite-utils/issues/235

But I have since determined that the Datasette official Docker image does NOT run anything in defensive mode, so I don't think it's related to that.

Asked on the SQLite Forum if anyone has seen this before: https://sqlite.org/forum/forumpost/793a2ed75b

Here's the relevant code:
https://github.com/simonw/datasette/blob/5890a20c374fb0812d88c9b0ef26a838bfa06c76/datasette/app.py#L422-L437
This function is called on almost every request (everything that subclasses BaseView at least - need to remember that for the refactor in #2053 etc).
https://github.com/simonw/datasette/blob/5890a20c374fb0812d88c9b0ef26a838bfa06c76/datasette/views/base.py#L101-L103
It uses PRAGMA schema_version as a cheap way to determine if the schema has changed, in which case it needs to refresh the internal schema tables.
This was already the cause of a subtle bug here:

#1231

Here's a potential workaround: when I store the schema versions, I could also score an MD5 hash of the full schema (select group_concat(sql) from sqlite_master). When I read the schema version with PRAGMA schema_version I could catch that exception and, if I see it, I could calculate that MD5 hash again as a fallback and use that to determine if the schema has changed instead.
The performance overhead of this needs investigating - how much more expensive is md5(... that SQL query result) compared to just PRAGMA schema_version, especially on a database with a lot of tables?

Here's a much better chart, which shows that MD5 performance unsurprisingly gets worse as the number of tables increases while schema_version remains constant:

I tightened up the benchmark (it was measuring the time taken to create the tables too) and got this:

I tried deploying the fix you submitted, but still getting the same errors. I can past the logs here if needed, but I really don't see anything new in them.


Support tagged lookups on VPC & Subnets

For systems NOT using the default vpc (e.g. using the terraform vpc module), there are often public and private subnets created.  This means 6 subnets 2 per AZ, which breaks this module.  One thought is to add a variable
variable "subnet_tags" {
##   Tier = "Private"

}

and modify main.tf to do
data "aws_subnet_ids" "default" {
  vpc_id = "${data.aws_vpc.default.id}"
  tags = "${var.subnet_tags}"
}

Then apply similar logic to the aws_vpc block

Assuming that Terraform treats an empty tags value the same as no value at all, I'm definitely in favor of this change!

:)  NULL != 0 != "" != [] != {} :)

Haha, yep. I even filed a bug about it: https://github.com/hashicorp/terraform/issues/14037

https://github.com/hashicorp/terraform-aws-vault/pull/39 :)

#39 Adds support for tagged lookups on the main "example", but not on the vault-cluster module, which is where I think would be more valuable, since the main example is not one-size-fits-all. Plus I don't think examples are supposed to be considered production-ready anyway (or at least they should be considered less production-ready than modules). I'll open an issue for it.

@patoarvizu vpc_id in the vault-cluster module is just a variable. It's up to the client depending on it as a module to set it.  Either through a data lookup or similar.  The main is an example implementation of how to do so.  In theory, you could pass a set of filters or tags instead of the vpc_id but that starts to complicate the module.  This way you can do any of the available options.


feature request: support for whitelist networks

Not sure if this is the best way to discuss a blocktrail feature request.. but would be nice if blocktrail supports networks in whitelist..

We get a "Server Response: {"code":0,"msg":"Unable to co-sign transction due to IP whitelist restrictions"}" maybe because of lack of network syntax support on whitelist.
and btw, error message has a typo :)


Node.js 12 actions are deprecated.

Hi
Getting warning from the workflow.
Node.js 12 actions are deprecated. For more information see: https://github.blog/changelog/2022-09-22-github-actions-all-actions-will-begin-running-on-node16-instead-of-node12/. Please update the following actions to use Node.js 16<EMAIL_ADDRESS>Please help to fix

Use Gamesight/slack-workflow-status@master  instead of<EMAIL_ADDRESS>to disable the warning

new release @ v1.2.0 now uses node16 and should remove those deprecation notifications.


Button to remove repeating tags

Hey there,
Because of editing mistakes or when you are using several Auto-Taggers on a Dataset it's quite likely to get duplicate tags.
Right now I can't think of an Extension that checks for those and deletes the duplicates.
It would be great if you could include this functionality.

Thank you!


Automated Package Upgrade

:tada: This PR is included in version 7.7.399 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


Update README.md

[ ] Removes reference to Istanbul as if it were a future HF
[ ] Adds muirGlacier to the active HF list

I already did some similar updates along the v1.5.0 release PR, not sure if it is worth to update this PR along. I didn't add any note on Berlin though.

Alright, closing this one.


Canvas ist empty at only one image

if wie have only one image at source, the canvas is empty...
I fill the source by PHP and sometimes only one image is displayed.

please fill in more information. A jsfiddle example would be great, or at least your setup code.

my Setup:

i can't reproduce the problem that you describe
https://jsfiddle.net/giniedp/n35L3nxf/
your code looks fine for spritespin. However

you don't have to escape the slash in the file name
you probably might want to add a leading "/" to make it an absolute file path.

hmmm...?


What is the reason for dividing block_size by 28?

I was going through the dumper logic, and couldn't understand why block_size is divided by 28? I understand the 24 bytes being subtracted is page header, but couldn't gather from Postgres docs on what the logic for that might be.
https://github.com/rueian/pgcapture/blob/f79a2714cce43fe0a176834a27e22303d1004ae2/pkg/dblog/dumper.go#L112

Hi @unarmedcivilian,
According to the https://www.postgresql.org/docs/13/storage-page-layout.html#PAGE-TABLE:
After subtracting the page header, the remaining space are occupied by the ItemIdData and Items
Each ItemId is 4 bytes and each Item has a HeapTupleHeaderData which is 23 bytes and actual data which is at least 1 byte.
Therefore the query divides the remaining space by (4+23+1) to get all possible ctids.

Thank you @rueian


Update downward-api-volume-expose-pod-information.md

The pod spec puts the downward api files into /etc/podinfo, not directly in /etc. Updated docs to reflect this fact.

^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
For 1.10 Features: set Milestone to 1.10 and Base Branch to release-1.10
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
NOTE: After opening the PR, please un-check and re-check the "Allow edits from maintainers" box so that maintainers can work on your patch and speed up the review process. This is a temporary workaround to address a known issue with GitHub.>
Please delete this note before submitting the pull request.

/assign @bradtopol

/assign

/assign @bradtopol

/approve