Request for --hide-ignored-files option

Currently files ignored via .xcovignore are not really ignored — they appear as 0% coverage.
For example:

+-----------------------------------+----+
|          xcov Coverage Report          |
+-----------------------------------+----+
                – snip ✂ –
| AFNetworking.framework            | 0% |
| OMGHTTPURLRQ.framework            | 0% |
+-----------------------------------+----+

However, I don't want to see these files at all.
Would be nice if there was a --hide-ignored-files option to completely remove this irrelevant stuff from the report.

Hey @getaaron ! Sorry for the delay in my reply. These are targets therefore you should be able to ignore them using the option exclude_targets. i.e.
    xcov(
      scheme: Lyst,
      workspace: Lyst.xcworkspace,
      output_directory: "./xcov_report",
      exclude_targets: "EasyPeasy.framework,AFNetworking.framework"
    )

The only_project_targets parameter might also address this particular situation.


fix: Handle multiple meta mutators cleanly

This applies each of the mutators before generating patches.

Verified manually too and seeing HTTPProxy on the control-plane


Link to enabling recycle bin for AD would be handy

It's only a web search away, but a quick link to where to go in Windows to enable the AD recycle bin would be very helpful to include here.
I'm connecting our domain, initially created on Server 2003 and migrated all the way through to modern servers, to Azure AD & Office 365 finally.  I've worked my way through things like using .local as the suffix (as suggested all those years ago) but then hit this suggestion to enable the recycle bin.
Thanks.

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

ID: fd5fd02e-6f34-8301-ac3d-023c8aa95fce
Version Independent ID: 8e12cb08-cd75-f52c-6e15-6b14a5adc3b3
Content: Azure AD Connect sync: Enable AD recycle bin
Content Source: articles/active-directory/hybrid/how-to-connect-sync-recycle-bin.md
Service: active-directory
GitHub Login: @billmath
Microsoft Alias: billmath

@billmath
Bill, could the steps to enable the On-Premise AD Recycle Bin be included in this document ?
Example: https://blogs.technet.microsoft.com/canitpro/2014/04/30/step-by-step-enabling-active-directory-recycle-bin-in-windows-server-2012-r2/

@IanYates Thank you for the feedback.
@neeleshray, yes it could but you would need to contact the author of the blog.  I don't have any way of directly updating this.  Thanks!
#please-close

@IanYates We will now proceed to close this thread. If there are further questions regarding this matter, please tag me in your reply. We will gladly continue the discussion and we will reopen the issue.

@bryanTrach-MSFT I understand not updating an authors blog, but this appears to be a standard Microsoft Docs website. It's even linked to via GitHub. Can't we get this updated?

Oh! I just realized the communication issue. @BryanTrach-MSFT, I think you thought @Neeleshray was asking to update the blog he linked. I believe he was simply asking that something similar to the CONTENT of that blog be insert on THIS page.
Most administrators know why they want this on, they just need the steps. You see, you do it once a year maybe, or once ever in your career. They know they need it on. (I just did it twice in 2 weeks, and I can't remember!).
So, updating this exact page to simply have the steps, not just an explanation of why you want to do it, would be fantastic.

@IanYates Can you please open a new feedback item? Feel free to reference this item if necessary.
To leave new feedback, navigate to the doc, and under the feedback section, select "this page." Thank you for your understanding.

This has not yet been addressed, and it looks like a dupe of https://github.com/MicrosoftDocs/azure-docs/issues/17523.

https://docs.microsoft.com/en-us/windows-server/identity/ad-ds/get-started/adac/introduction-to-active-directory-administrative-center-enhancements--level-100-#bkmk_enable_recycle_bin
The above link details how to enable the AD Recycle Bin and should be added to this document.


Add "select all matches" command

Similar to Sublime Text cmd+ctrl+g command which selects all the matches of current selection
http://gfycat.com/DazzlingMeagerErin

"editor.action.selectHighlights" is now working as I was expecting.


[stable/hadoop] How to access hdfs?

How to access hdfs by  kubectl port-forward on port 8020, please?

Check there
core-site.xml:
...
<property>
            <name>fs.defaultFS</name>
            <value>hdfs://{{ include "hadoop.fullname" . }}-hdfs-nn:9000/</value>
            <description>NameNode URI</description>
</property>

Port 9000 is used.


add failover script + split configmap from statefulset

I don't know if this may be useful for other people. I have created a pre-stop lifecycle which verifies if it is an actual master, and switches the service to its slave if so.
Also I have split the configmap from the statefulset to avoid having one big file.

I like the idea of automating the failover when a master pod shuts down. However, we're nearing a point where it makes more sense to tread into CRD domain and create an operator that manages the cluster.
I would also like to avoid this repo becoming a collection of scripts one might find useful, it mainly serves as an example on how to set up a stateful application inside Kubernetes. It's quite outdated too: a quick Google search on "redis cluster operator" shows a bunch of open source projects providing a far better setup compared to what I cooked up.


Fix for a buffer overflow when close code has not been received from the socket

I encountered the crash here where pointer only contained two bytes, [136, 39] and it was trying to read closeCode from outside the buffer. This should fix it.

Thanks!


This would be grateful

this will be added probably, dont put all your info in the title of your issue posts.


python3.pkgs.osmpythontools: 0.2.9 -> 0.3.0

Motivation for this change
Upstream release 0.3.0 (PyPI, Git tag)
Things done

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

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

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[x] Tested compilation of all pkgs that depend on this change using nix run nixpkgs.nixpkgs-review -c nixpkgs-review wip
[x] Tested execution of all binary files (usually in ./result/bin/)

(there are no executable files, as this is a library)

[ ] Determined the impact on package closure size (by running nix path-info -S before and after)
[ ] Ensured that relevant documentation is up to date
[x] Fits CONTRIBUTING.md.

Result of nixpkgs-review pr 113032 at a065dc54 run on x86_64-linux 1

2 packages built:

python37Packages.osmpythontools
python38Packages.osmpythontools

2 suggestions:

warning: missing-patch-comment
Please add a comment on the line above, explaining the purpose of this patch.
Near pkgs/development/python-modules/osmpythontools/default.nix:25:15:
   |
25 |   patches = [ ./remove-test-only-dependencies.patch ];
   |               ^

warning: unclear-gpl
gpl3 is a deprecated license, check if project uses gpl3Plus or gpl3Only and change meta.license accordingly.
Near pkgs/development/python-modules/osmpythontools/default.nix:58:5:
   |
58 |     license = licenses.gpl3;
   |     ^

Result of nixpkgs-review pr 113032 at a065dc54 run on aarch64-linux 1

3 packages built:

python37Packages.osmpythontools
python38Packages.osmpythontools
python39Packages.osmpythontools

2 suggestions:

warning: missing-patch-comment
Please add a comment on the line above, explaining the purpose of this patch.
Near pkgs/development/python-modules/osmpythontools/default.nix:25:15:
   |
25 |   patches = [ ./remove-test-only-dependencies.patch ];
   |               ^

warning: unclear-gpl
gpl3 is a deprecated license, check if project uses gpl3Plus or gpl3Only and change meta.license accordingly.
Near pkgs/development/python-modules/osmpythontools/default.nix:58:5:
   |
58 |     license = licenses.gpl3;
   |     ^

Going to squash when merging.

Going to squash when merging.

Squashed the 3 commits myself now. :slightly_smiling_face:


PSPKI v4.2.0 Module cannot find type [PKI.OCSP.OCSPRequest]

When running Get-EnterprisePKIHealthStatus with version 4.2.0 on PowerShell 5.1, it gives out this error.
DEBUG: Entering OCSP validation routine...
DEBUG: URL: http://ocsp.******.***/ocsp
New-Object : Cannot find type [PKI.OCSP.OCSPRequest]: verify that the assembly containing this type is loaded.
At C:\Program Files\WindowsPowerShell\Modules\PSPKI\4.2.0\Server\Get-EnterprisePKIHealthStatus.ps1:451 char:20
+             $req = New-Object PKI.OCSP.OCSPRequest $cert.Certificate
+                    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    + CategoryInfo          : InvalidType: (:) [New-Object], PSArgumentException
    + FullyQualifiedErrorId : TypeNotFound,Microsoft.PowerShell.Commands.NewObjectCommand

The property 'URL' cannot be found on this object. Verify that the property exists and can be set.
At C:\Program Files\WindowsPowerShell\Modules\PSPKI\4.2.0\Server\Get-EnterprisePKIHealthStatus.ps1:452 char:13
+             $req.URL = $urlElement.Url
+             ~~~~~~~~~~~~~~~~~~~~~~~~~~
    + CategoryInfo          : InvalidOperation: (:) [], RuntimeException
    + FullyQualifiedErrorId : PropertyNotFound

This error does not happen with v3.4.x on Powershell 5.1.  I thought it was due to an error while upgrading so have installed the module on another computer which never had PSPKI before and give out the same error.
For reference
$PSVersionTable

Name                           Value
----                           -----
PSVersion                      5.1.19041.4412
PSEdition                      Desktop
PSCompatibleVersions           {1.0, 2.0, 3.0, 4.0...}
BuildVersion                   10.0.19041.4412
CLRVersion                     4.0.30319.42000
WSManStackVersion              3.0
PSRemotingProtocolVersion      2.3
SerializationVersion           <IP_ADDRESS>

Thanks for reporting! The fix is added and will be available in v4.3. For now, you can manually change Get-EnterprisePKIHealthStatus as in this commit: https://github.com/PKISolutions/PSPKI/commit/475e2ab6794bbbe52762f9baf8f1d32bc35c80c5


9302: tests with failure injection

Three more tests for CASSANDRA-9302, with failure injection.

+1


different behavior minified vs unminified, normalized result is not a number

When digging into "normalized result is not a number" exceptions (see #4863, #4801, etc.) I observe  different behavior between the minified and unminified versions where minified does not throw the exception and unminified does.
Example code taken from #4863 using Chrome 6x on Win 10 x64 w/ Cesium 1.44, 1.45, & 1.46:
`var viewer = new Cesium.Viewer('cesiumContainer');
var hierarchy = [ -180,90,-180,50,180,50,180,90];
viewer.entities.add({
polygon: {
hierarchy: new Cesium.PolygonHierarchy(Cesium.Cartesian3.fromDegreesArray(hierarchy)),
outline: true,
outlineColor: Cesium.Color.YELLOW,
fill: true,
//fill: false,
material: Cesium.Color.RED,
outlineWidth: 10
}
})`

This is by design.  The unminified build has additional runtime checks which can impact performance.  As a result the recommendation has always been to develop and test applications locally with the unminified version, and deploy the minified version.


Pivpn fails to install on blank ubuntu docker containers

PiVPN Issue Template

Console output of curl install.pivpn.io | bash

Console output of pivpn add or pivpn add nopass

Console output of pivpn debug

Issue
This is strange, but when I type curl -L https://install.pivpn.io | bash into a blank docker container with Ubuntu 16.04, it exits at installing packages. I'm not sure what is happening here. It looks like PiVPN isn't installing properly.

I've figured this out from #399 where I need to type dpkg --configure -a, then rerun the script again. I think this might be a problem with the install script. Maybe dpkg --configure -a could be inserted somewhere?

Cool @InnovativeInventor I will close this issue then as I already refferenced it in the the mentioned issue! this way we an track this all in one place ok?
Thanks a lot for your input ... maybe i will add that to the script when I have the time and if I check that is indeed a common solution for all users with the same kind of issue! =)


GPT models hang on large token generation.  Lower performance?

I am using a 3060 and a 3090 to split GPT models two ways including GPTJ and GPT Neo 2.7B.  When generating many tokens, say 500, the model hangs and either takes a abnormal amount of time to finish or does not finish. ( I kill it)  Generating 50 tokens does not have this issue.
During this issue, the 3090 memory is pinned to 100% while the 3060 stays low.

Subjectively, especially for GPTJ, the results, while not complete gibberish seem to be of lower quality.

Might this be a race condition between the two GPUs?


Fix inline video.

@krzyzanowskim brought it to my attention that videos don't play inline on mobile. We use the playsinline attribute on the video tag, but apparently video.js overrides that, so I add to also add it to the video.js config.

@stephencelis I think you are traveling this morning, so I'm going to go ahead and merge this. I think it's pretty straightforward.

Thanks for takin care of this!


Similar to issue#349, to run mnist keras sample, cluster stuck while feeding training data, exception "Timeout while feeding partition" raised after stuck for 600 seconds

Environment:

Python version 3.5
Spark version 2.2
TensorFlow version 1.12 gpu
TensorFlowOnSpark version 1.4.2
Cluster version Hadoop 2.7, yarn

Describe the bug:
Similar to issue#349, to run mnist keras sample, cluster stuck while feeding training data, exception raised "Timeout while feeding partition"
Logs:
root@master:/software/yahoo/tfos# ./train_keras_mnist_csv.sh
19/03/07 05:26:13 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Downloading hdfs:///user/root/TensorFlowOnSpark/examples/mnist/keras/mnist_mlp_estimator.py to /tmp/tmp3152022056050101843/user/root/TensorFlowOnSpark/examples/mnist/keras/mnist_mlp_estimator.py.
19/03/07 05:26:14 INFO spark.SparkContext: Running Spark version 2.2.0
19/03/07 05:26:14 INFO spark.SparkContext: Submitted application: mnist_mlp
19/03/07 05:26:14 INFO spark.SecurityManager: Changing view acls to: root
19/03/07 05:26:14 INFO spark.SecurityManager: Changing modify acls to: root
19/03/07 05:26:14 INFO spark.SecurityManager: Changing view acls groups to:
19/03/07 05:26:14 INFO spark.SecurityManager: Changing modify acls groups to:
19/03/07 05:26:14 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(root); groups with view permissions: Set(); users  with modify permissions: Set(root); groups with modify permissions: Set()
19/03/07 05:26:14 INFO util.Utils: Successfully started service 'sparkDriver' on port 38627.
19/03/07 05:26:14 INFO spark.SparkEnv: Registering MapOutputTracker
19/03/07 05:26:14 INFO spark.SparkEnv: Registering BlockManagerMaster
19/03/07 05:26:14 INFO storage.BlockManagerMasterEndpoint: Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information
19/03/07 05:26:14 INFO storage.BlockManagerMasterEndpoint: BlockManagerMasterEndpoint up
19/03/07 05:26:14 INFO storage.DiskBlockManager: Created local directory at /tmp/blockmgr-c871f126-c5ad-4557-8ff6-94f92a42a46d
19/03/07 05:26:14 INFO memory.MemoryStore: MemoryStore started with capacity 366.3 MB
19/03/07 05:26:14 INFO spark.SparkEnv: Registering OutputCommitCoordinator
19/03/07 05:26:14 INFO util.log: Logging initialized @2301ms
19/03/07 05:26:14 INFO server.Server: jetty-9.3.z-SNAPSHOT
19/03/07 05:26:14 INFO server.Server: Started @2341ms
19/03/07 05:26:14 INFO server.AbstractConnector: Started ServerConnector@32855c04{HTTP/1.1,[http/1.1]}{<IP_ADDRESS>:4040}
19/03/07 05:26:14 INFO util.Utils: Successfully started service 'SparkUI' on port 4040.
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@22ee411d{/jobs,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@3a6ca16a{/jobs/json,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@7c553d3f{/jobs/job,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@19034f49{/jobs/job/json,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@7955c667{/stages,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@5467b101{/stages/json,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@1e0d411d{/stages/stage,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@15655d20{/stages/stage/json,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@4eaadbdd{/stages/pool,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@37a6268c{/stages/pool/json,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@6b25ec77{/storage,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@4ab4e040{/storage/json,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@30eeb67d{/storage/rdd,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@10b0ecbe{/storage/rdd/json,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@4403e5d9{/environment,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@73274369{/environment/json,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@76a25bb4{/executors,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@77c80c3c{/executors/json,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@1cffb4e2{/executors/threadDump,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@7cefc63e{/executors/threadDump/json,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@44169fd6{/static,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@26fb722b{/,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@417899ac{/api,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@73e30fa2{/jobs/job/kill,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@7487caa2{/stages/stage/kill,null,AVAILABLE,@Spark}
19/03/07 05:26:14 INFO ui.SparkUI: Bound SparkUI to <IP_ADDRESS>, and started at http://<IP_ADDRESS>:4040
19/03/07 05:26:15 INFO client.RMProxy: Connecting to ResourceManager at master/<IP_ADDRESS>:8032
19/03/07 05:26:15 INFO yarn.Client: Requesting a new application from cluster with 2 NodeManagers
19/03/07 05:26:15 INFO yarn.Client: Verifying our application has not requested more than the maximum memory capability of the cluster (10000 MB per container)
19/03/07 05:26:15 INFO yarn.Client: Will allocate AM container, with 896 MB memory including 384 MB overhead
19/03/07 05:26:15 INFO yarn.Client: Setting up container launch context for our AM
19/03/07 05:26:15 INFO yarn.Client: Setting up the launch environment for our AM container
19/03/07 05:26:15 INFO yarn.Client: Preparing resources for our AM container
19/03/07 05:26:15 WARN yarn.Client: Neither spark.yarn.jars nor spark.yarn.archive is set, falling back to uploading libraries under SPARK_HOME.
19/03/07 05:26:16 INFO yarn.Client: Uploading resource file:/tmp/spark-a15b9378-0470-4bd1-ba17-b3832a553d18/__spark_libs__1802946680673561919.zip -> hdfs://master:9000/user/root/.sparkStaging/application_1551864161970_0029/__spark_libs__1802946680673561919.zip
19/03/07 05:26:17 INFO yarn.Client: Source and destination file systems are the same. Not copying hdfs:/user/root/mnist.npz#mnist.npz
19/03/07 05:26:17 INFO yarn.Client: Uploading resource file:/software/apache/spark/spark-2.2.0-bin-hadoop2.7/python/lib/pyspark.zip -> hdfs://master:9000/user/root/.sparkStaging/application_1551864161970_0029/pyspark.zip
19/03/07 05:26:17 INFO yarn.Client: Uploading resource file:/software/apache/spark/spark-2.2.0-bin-hadoop2.7/python/lib/py4j-0.10.4-src.zip -> hdfs://master:9000/user/root/.sparkStaging/application_1551864161970_0029/py4j-0.10.4-src.zip
19/03/07 05:26:17 INFO yarn.Client: Uploading resource file:/tmp/spark-a15b9378-0470-4bd1-ba17-b3832a553d18/__spark_conf__5445895715324259030.zip -> hdfs://master:9000/user/root/.sparkStaging/application_1551864161970_0029/spark_conf.zip
19/03/07 05:26:17 INFO spark.SecurityManager: Changing view acls to: root
19/03/07 05:26:17 INFO spark.SecurityManager: Changing modify acls to: root
19/03/07 05:26:17 INFO spark.SecurityManager: Changing view acls groups to:
19/03/07 05:26:17 INFO spark.SecurityManager: Changing modify acls groups to:
19/03/07 05:26:17 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(root); groups with view permissions: Set(); users  with modify permissions: Set(root); groups with modify permissions: Set()
19/03/07 05:26:17 INFO yarn.Client: Submitting application application_1551864161970_0029 to ResourceManager
19/03/07 05:26:17 INFO impl.YarnClientImpl: Submitted application application_1551864161970_0029
19/03/07 05:26:17 INFO cluster.SchedulerExtensionServices: Starting Yarn extension services with app application_1551864161970_0029 and attemptId None
19/03/07 05:26:18 INFO yarn.Client: Application report for application_1551864161970_0029 (state: ACCEPTED)
19/03/07 05:26:18 INFO yarn.Client:
client token: N/A
diagnostics: N/A
ApplicationMaster host: N/A
ApplicationMaster RPC port: -1
queue: default
start time:<PHONE_NUMBER>356
final status: UNDEFINED
tracking URL: http://master:8088/proxy/application_1551864161970_0029/
user: root
19/03/07 05:26:19 INFO yarn.Client: Application report for application_1551864161970_0029 (state: ACCEPTED)
19/03/07 05:26:19 INFO cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: ApplicationMaster registered as NettyRpcEndpointRef(spark-client://YarnAM)
19/03/07 05:26:19 INFO cluster.YarnClientSchedulerBackend: Add WebUI Filter. org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter, Map(PROXY_HOSTS -> slave2, PROXY_URI_BASES -> http://slave2:8088/proxy/application_1551864161970_0029), /proxy/application_1551864161970_0029
19/03/07 05:26:19 INFO ui.JettyUtils: Adding filter: org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter
19/03/07 05:26:20 INFO yarn.Client: Application report for application_1551864161970_0029 (state: RUNNING)
19/03/07 05:26:20 INFO yarn.Client:
client token: N/A
diagnostics: N/A
ApplicationMaster host: <IP_ADDRESS>
ApplicationMaster RPC port: 0
queue: default
start time:<PHONE_NUMBER>356
final status: UNDEFINED
tracking URL: http://master:8088/proxy/application_1551864161970_0029/
user: root
19/03/07 05:26:20 INFO cluster.YarnClientSchedulerBackend: Application application_1551864161970_0029 has started running.
19/03/07 05:26:20 INFO util.Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 34457.
19/03/07 05:26:20 INFO netty.NettyBlockTransferService: Server created on <IP_ADDRESS>:34457
19/03/07 05:26:20 INFO storage.BlockManager: Using org.apache.spark.storage.RandomBlockReplicationPolicy for block replication policy
19/03/07 05:26:20 INFO storage.BlockManagerMaster: Registering BlockManager BlockManagerId(driver, <IP_ADDRESS>, 34457, None)
19/03/07 05:26:20 INFO storage.BlockManagerMasterEndpoint: Registering block manager <IP_ADDRESS>:34457 with 366.3 MB RAM, BlockManagerId(driver, <IP_ADDRESS>, 34457, None)
19/03/07 05:26:20 INFO storage.BlockManagerMaster: Registered BlockManager BlockManagerId(driver, <IP_ADDRESS>, 34457, None)
19/03/07 05:26:20 INFO storage.BlockManager: Initialized BlockManager: BlockManagerId(driver, <IP_ADDRESS>, 34457, None)
19/03/07 05:26:20 INFO handler.ContextHandler: Started o.s.j.s.ServletContextHandler@1624c314{/metrics/json,null,AVAILABLE,@Spark}
19/03/07 05:26:21 INFO cluster.YarnSchedulerBackend$YarnDriverEndpoint: Registered executor NettyRpcEndpointRef(spark-client://Executor) (<IP_ADDRESS>:33898) with ID 1
19/03/07 05:26:21 INFO storage.BlockManagerMasterEndpoint: Registering block manager slave1:37461 with 2004.6 MB RAM, BlockManagerId(1, slave1, 37461, None)
19/03/07 05:26:22 INFO cluster.YarnSchedulerBackend$YarnDriverEndpoint: Registered executor NettyRpcEndpointRef(spark-client://Executor) (<IP_ADDRESS>:37784) with ID 2
19/03/07 05:26:22 INFO storage.BlockManagerMasterEndpoint: Registering block manager slave2:43783 with 2004.6 MB RAM, BlockManagerId(2, slave2, 43783, None)
19/03/07 05:26:22 INFO cluster.YarnClientSchedulerBackend: SchedulerBackend is ready for scheduling beginning after reached minRegisteredResourcesRatio: 0.8
args: Namespace(batch_size=100, cluster_size=2, epochs=1, images='mnist/csv/train/images', input_mode='spark', labels='mnist/csv/train/labels', mnist_npz='mnist.npz', model_dir='hdfs:///user/root/TensorFlowOnSpark/mnist_model', num_ps=1, output='predictions', steps=2000, tensorboard=True)
19/03/07 05:26:22 INFO memory.MemoryStore: Block broadcast_0 stored as values in memory (estimated size 289.6 KB, free 366.0 MB)
19/03/07 05:26:22 INFO memory.MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 23.6 KB, free 366.0 MB)
19/03/07 05:26:22 INFO storage.BlockManagerInfo: Added broadcast_0_piece0 in memory on <IP_ADDRESS>:34457 (size: 23.6 KB, free: 366.3 MB)
19/03/07 05:26:22 INFO spark.SparkContext: Created broadcast 0 from textFile at NativeMethodAccessorImpl.java:0
19/03/07 05:26:22 INFO memory.MemoryStore: Block broadcast_1 stored as values in memory (estimated size 289.6 KB, free 365.7 MB)
19/03/07 05:26:22 INFO memory.MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 23.6 KB, free 365.7 MB)
19/03/07 05:26:22 INFO storage.BlockManagerInfo: Added broadcast_1_piece0 in memory on <IP_ADDRESS>:34457 (size: 23.6 KB, free: 366.3 MB)
19/03/07 05:26:22 INFO spark.SparkContext: Created broadcast 1 from textFile at NativeMethodAccessorImpl.java:0
19/03/07 05:26:22 INFO mapred.FileInputFormat: Total input paths to process : 10
19/03/07 05:26:22 INFO mapred.FileInputFormat: Total input paths to process : 10
2019-03-07 05:26:22,967 INFO (MainThread-14378) Reserving TFSparkNodes w/ TensorBoard
2019-03-07 05:26:22,967 INFO (MainThread-14378) cluster_template: {'ps': range(0, 1), 'master': range(1, 2)}
2019-03-07 05:26:22,968 INFO (MainThread-14378) listening for reservations at ('<IP_ADDRESS>', 41155)
2019-03-07 05:26:22,968 INFO (MainThread-14378) Starting TensorFlow on executors
2019-03-07 05:26:22,972 INFO (MainThread-14378) Waiting for TFSparkNodes to start
2019-03-07 05:26:22,972 INFO (MainThread-14378) waiting for 2 reservations
19/03/07 05:26:23 INFO spark.SparkContext: Starting job: foreachPartition at /usr/local/lib/python3.5/dist-packages/tensorflowonspark/TFCluster.py:301
19/03/07 05:26:23 INFO scheduler.DAGScheduler: Got job 0 (foreachPartition at /usr/local/lib/python3.5/dist-packages/tensorflowonspark/TFCluster.py:301) with 2 output partitions
19/03/07 05:26:23 INFO scheduler.DAGScheduler: Final stage: ResultStage 0 (foreachPartition at /usr/local/lib/python3.5/dist-packages/tensorflowonspark/TFCluster.py:301)
19/03/07 05:26:23 INFO scheduler.DAGScheduler: Parents of final stage: List()
19/03/07 05:26:23 INFO scheduler.DAGScheduler: Missing parents: List()
19/03/07 05:26:23 INFO scheduler.DAGScheduler: Submitting ResultStage 0 (PythonRDD[8] at foreachPartition at /usr/local/lib/python3.5/dist-packages/tensorflowonspark/TFCluster.py:301), which has no missing parents
19/03/07 05:26:23 INFO memory.MemoryStore: Block broadcast_2 stored as values in memory (estimated size 21.5 KB, free 365.7 MB)
19/03/07 05:26:23 INFO memory.MemoryStore: Block broadcast_2_piece0 stored as bytes in memory (estimated size 15.2 KB, free 365.7 MB)
19/03/07 05:26:23 INFO storage.BlockManagerInfo: Added broadcast_2_piece0 in memory on <IP_ADDRESS>:34457 (size: 15.2 KB, free: 366.2 MB)
19/03/07 05:26:23 INFO spark.SparkContext: Created broadcast 2 from broadcast at DAGScheduler.scala:1006
19/03/07 05:26:23 INFO scheduler.DAGScheduler: Submitting 2 missing tasks from ResultStage 0 (PythonRDD[8] at foreachPartition at /usr/local/lib/python3.5/dist-packages/tensorflowonspark/TFCluster.py:301) (first 15 tasks are for partitions Vector(0, 1))
19/03/07 05:26:23 INFO cluster.YarnScheduler: Adding task set 0.0 with 2 tasks
19/03/07 05:26:23 INFO scheduler.TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, slave2, executor 2, partition 0, PROCESS_LOCAL, 4822 bytes)
19/03/07 05:26:23 INFO scheduler.TaskSetManager: Starting task 1.0 in stage 0.0 (TID 1, slave1, executor 1, partition 1, PROCESS_LOCAL, 4822 bytes)
19/03/07 05:26:23 INFO storage.BlockManagerInfo: Added broadcast_2_piece0 in memory on slave2:43783 (size: 15.2 KB, free: 2004.6 MB)
19/03/07 05:26:23 INFO storage.BlockManagerInfo: Added broadcast_2_piece0 in memory on slave1:37461 (size: 15.2 KB, free: 2004.6 MB)
2019-03-07 05:26:23,974 INFO (MainThread-14378) waiting for 2 reservations
2019-03-07 05:26:24,974 INFO (MainThread-14378) waiting for 2 reservations
2019-03-07 05:26:25,975 INFO (MainThread-14378) waiting for 2 reservations
2019-03-07 05:26:26,977 INFO (MainThread-14378) waiting for 1 reservations
2019-03-07 05:26:27,978 INFO (MainThread-14378) all reservations completed
2019-03-07 05:26:27,978 INFO (MainThread-14378) All TFSparkNodes started
2019-03-07 05:26:27,978 INFO (MainThread-14378) {'host': '<IP_ADDRESS>', 'executor_id': 1, 'addr': '/tmp/pymp-ouv7htjg/listener-nvgywg76', 'tb_pid': 0, 'task_index': 0, 'job_name': 'master', 'authkey': b'1\x03\x91\xff\x95\x1eAw\xbe\xc6\x93*\xfe\x0b\xbbz', 'port': 34517, 'tb_port': 0}
2019-03-07 05:26:27,979 INFO (MainThread-14378) {'host': '<IP_ADDRESS>', 'executor_id': 0, 'addr': ('<IP_ADDRESS>', 34537), 'tb_pid': 0, 'task_index': 0, 'job_name': 'ps', 'authkey': b'\xd0\xef@"\xf0\xabI\xb3\x8f\x00\xdaZ\xa8\xeb\xe0J', 'port': 43975, 'tb_port': 0}
2019-03-07 05:26:27,979 INFO (MainThread-14378) Feeding training data
19/03/07 05:26:28 INFO spark.SparkContext: Starting job: collect at PythonRDD.scala:458
19/03/07 05:26:28 INFO scheduler.DAGScheduler: Got job 1 (collect at PythonRDD.scala:458) with 10 output partitions
19/03/07 05:26:28 INFO scheduler.DAGScheduler: Final stage: ResultStage 1 (collect at PythonRDD.scala:458)
19/03/07 05:26:28 INFO scheduler.DAGScheduler: Parents of final stage: List()
19/03/07 05:26:28 INFO scheduler.DAGScheduler: Missing parents: List()
19/03/07 05:26:28 INFO scheduler.DAGScheduler: Submitting ResultStage 1 (PythonRDD[10] at RDD at PythonRDD.scala:48), which has no missing parents
19/03/07 05:26:28 INFO memory.MemoryStore: Block broadcast_3 stored as values in memory (estimated size 15.1 KB, free 365.6 MB)
19/03/07 05:26:28 INFO memory.MemoryStore: Block broadcast_3_piece0 stored as bytes in memory (estimated size 8.2 KB, free 365.6 MB)
19/03/07 05:26:28 INFO storage.BlockManagerInfo: Added broadcast_3_piece0 in memory on <IP_ADDRESS>:34457 (size: 8.2 KB, free: 366.2 MB)
19/03/07 05:26:28 INFO spark.SparkContext: Created broadcast 3 from broadcast at DAGScheduler.scala:1006
19/03/07 05:26:28 INFO scheduler.DAGScheduler: Submitting 10 missing tasks from ResultStage 1 (PythonRDD[10] at RDD at PythonRDD.scala:48) (first 15 tasks are for partitions Vector(0, 1, 2, 3, 4, 5, 6, 7, 8, 9))
19/03/07 05:26:28 INFO cluster.YarnScheduler: Adding task set 1.0 with 10 tasks
19/03/07 05:26:30 INFO scheduler.TaskSetManager: Starting task 0.0 in stage 1.0 (TID 2, slave1, executor 1, partition 0, NODE_LOCAL, 5481 bytes)
19/03/07 05:26:30 INFO scheduler.TaskSetManager: Finished task 1.0 in stage 0.0 (TID 1) in 7746 ms on slave1 (executor 1) (1/2)
19/03/07 05:26:30 INFO storage.BlockManagerInfo: Added broadcast_3_piece0 in memory on slave1:37461 (size: 8.2 KB, free: 2004.6 MB)
19/03/07 05:26:30 INFO storage.BlockManagerInfo: Added broadcast_0_piece0 in memory on slave1:37461 (size: 23.6 KB, free: 2004.6 MB)
19/03/07 05:26:31 INFO storage.BlockManagerInfo: Added broadcast_1_piece0 in memory on slave1:37461 (size: 23.6 KB, free: 2004.5 MB)
19/03/07 05:36:32 INFO scheduler.TaskSetManager: Starting task 1.0 in stage 1.0 (TID 3, slave1, executor 1, partition 1, NODE_LOCAL, 5481 bytes)
19/03/07 05:36:32 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 1.0 (TID 2, slave1, executor 1): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
File "/software/apache/hadoop/hadoop-2.7.7/tmp/nm-local-dir/usercache/root/appcache/application_1551864161970_0029/container_1551864161970_0029_01_000002/pyspark.zip/pyspark/worker.py", line 177, in main
process()
File "/software/apache/hadoop/hadoop-2.7.7/tmp/nm-local-dir/usercache/root/appcache/application_1551864161970_0029/container_1551864161970_0029_01_000002/pyspark.zip/pyspark/worker.py", line 172, in process
serializer.dump_stream(func(split_index, iterator), outfile)
File "/software/apache/spark/spark-2.2.0-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/rdd.py", line 2423, in pipeline_func
File "/software/apache/spark/spark-2.2.0-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/rdd.py", line 2423, in pipeline_func
File "/software/apache/spark/spark-2.2.0-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/rdd.py", line 2423, in pipeline_func
File "/software/apache/spark/spark-2.2.0-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/rdd.py", line 346, in func
File "/software/apache/spark/spark-2.2.0-bin-hadoop2.7/python/lib/pyspark.zip/pyspark/rdd.py", line 794, in func
File "/usr/local/lib/python3.5/dist-packages/tensorflowonspark/TFSparkNode.py", line 423, in _train
raise Exception("Timeout while feeding partition")
Exception: Timeout while feeding partition
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:63)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)

Spark Submit Command Line:
#!/bin/bash
set environment variables (if not already done)
export USER=root
export LD_LIBRARY_PATH=${PATH}
export PYSPARK_PYTHON=python
export SPARK_YARN_USER_ENV="PYSPARK_PYTHON=python"
#export PATH=${PYTHON_ROOT}/bin/:$PATH
export QUEUE=default
set paths to libjvm.so, libhdfs.so, and libcuda*.so
export LIB_HDFS=$HADOOP_HOME/lib/native                                     # path to libhdfs.so, for TF acccess to HDFS
export LIB_JVM=$JAVA_HOME/jre/lib/amd64/server                              # path to libjvm.so
export LIB_CUDA=/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64    # for GPUs only
Launch the Spark cluster
export MASTER=yarn
export SPARK_WORKER_INSTANCES=2
export CORES_PER_WORKER=1
export TOTAL_CORES=$((${CORES_PER_WORKER}*${SPARK_WORKER_INSTANCES}))
export TFoS_HOME=hdfs:///user/${USER}/TensorFlowOnSpark
remove any old artifacts
hadoop fs -rm -r ${TFoS_HOME}/mnist_model
train
${SPARK_HOME}/bin/spark-submit
--master ${MASTER}
--executor-memory 4G
--conf spark.cores.max=${TOTAL_CORES}
--conf spark.task.cpus=${CORES_PER_WORKER}
--conf spark.executorEnv.JAVA_HOME="$JAVA_HOME"
--conf spark.dynamicAllocation.enabled=false
--conf spark.yarn.maxAppAttempts=1
--conf spark.executorEnv.LD_LIBRARY_PATH=$LIB_CUDA:$LIB_JVM:$LIB_HDFS
--driver-library-path=$LIB_CUDA
--archives hdfs:///user/${USER}/mnist.npz#mnist.npz
${TFoS_HOME}/examples/mnist/keras/mnist_mlp_estimator.py
--cluster_size ${SPARK_WORKER_INSTANCES}
--input_mode spark
--images mnist/csv/train/images
--labels mnist/csv/train/labels
--mnist_npz mnist.npz
--epochs 1
--model_dir ${TFoS_HOME}/mnist_model
--tensorboard

I met with the same problem. Instead, I use tensorflow

@witchoco can you view the executor logs for this failure?  During the job, you can use the Spark UI->Executors->stderr links.  After the job finishes, you can use yarn logs -applicationId <your_appId>. Also, were you able to run this example in a local spark standalone instance (per the original instructions)?

I have solved the same problem in tensorflow. The problem is caused by a bug in file 'mnist_dist.py'.

I have solved the same problem in tensorflow. The problem is caused by a bug in file 'mnist_dist.py'.
How did you solve it? I used to solve it by changing 'checkpoint_dir=logdir' to 'checkpoint_dir=None' in file 'mnist_dist.py'. But after that,the train model can't write to hdfs...

I have solved the same problem in tensorflow. The problem is caused by a bug in file 'mnist_dist.py'.
@bobzengscut
Could you please talk more about fixing the bug so that I can make it work? Thanks.

@JangNum @hfef7ui2 in which examples are you seeing this error?  Note that this bug specifically refers to the mnist/keras example, which does not have an mnist_dist.py file.  Also note that there are several other examples which have an mnist_dist.py file, so please refer to the specific example/file that you're attempting.

@leewyang I have met this "Timeout while feeding partition" error when running the mnist/spark example, just follow the "Run MNIST example" tutorial of this program. https://github.com/yahoo/TensorFlowOnSpark/wiki/GetStarted_YARN#run-distributed-mnist-training-using-feed_dict
/opt/spark-2.4.0-bin-hadoop2.7/bin/spark-submit \
--master yarn
--deploy-mode cluster
--executor-memory 5G
--py-files TensorFlowOnSpark/tfspark.zip,TensorFlowOnSpark/examples/mnist/spark/mnist_dist.py
--conf spark.yarn.maxAppAttempts=1 --archives hdfs:///user/hduser/Python.zip#Python TensorFlowOnSpark/examples/mnist/spark/mnist_spark.py
--images mnist/csv/train/images
--labels mnist/csv/train/labels
--mode train
--model mnist_model

I also have this problem.Does someone have work it out?

@downcastboy I'm going to reopen the other bug you filed and close this one since it's stale (and may be conflating different issues).


Adapt wording for required Android SDK for plugins

Solves https://github.com/flutter/flutter/pull/137115#discussion_r1388251047
Pre-launch Checklist

[x] I read the Contributor Guide and followed the process outlined there for submitting PRs.
[x] I read the Tree Hygiene wiki page, which explains my responsibilities.
[x] I read and followed the Flutter Style Guide, including Features we expect every widget to implement.
[x] I signed the CLA.
[x] I listed at least one issue that this PR fixes in the description above.
[x] I updated/added relevant documentation (doc comments with ///).
[x] I added new tests to check the change I am making, or this PR is test-exempt.
[ ] All existing and new tests are passing.

If you need help, consider asking for advice on the #hackers-new channel on Discord.

CC @reidbaker


[Bug]: time: invalid duration ""

Preflight Checklist

[x] I could not find a solution in the documentation, the existing issues or discussions
[ ] I have joined the ZITADEL chat

Environment
Self-hosted
Version
2.64.1
Database
PostgreSQL
Database Version
14
Describe the problem caused by this bug
I'm currently trying to make use of the REST /admin/v1/import endpoint to create oidc clients with a specified client_id. Unfortunately, I'm seeing an error which seems to persist even with the most minimal possible request body:
api-1           | INFO:zitadel.client:<-- application/json b'{"orgs": []}'
api-1           | INFO:zitadel.client:--> b'{"code":2, "message":"time: invalid duration \\"\\""}'

This would appear to indicate that Zitadel is attempting to parse the empty string as a duration value. I have tried using the export endpoint against a working instance, wiped the instance out, and still I get the same error trying to import the data.
To reproduce
Send an authenticated request to /admin/v1/import with the body {"orgs": []} (or with the contents of a request to the export endpoint)
Screenshots
No response
Expected behavior
No response
Operating System
Device: MacBook Pro (M3 Pro)
OS: MacOS 14.4 + Docker 4.34.3
Browser: httpx 0.27.0
Relevant Configuration
No response
Additional Context
No response

I am not sure, but from the error message it looks like a duration is not configured.
Looking at the api docs, we do have a timeout which you can configure in the request.
Could you try adding that?


Issue #8493 - Missing instructions in "Creating HA clusters with kube…

Fix #8493 (in clusters created according to the instructions kubelet, kube-controller-manager and kube-scheduler would connect to local IPs rather than the VIP, API server advertisedAddress pointing to local IPs, too).

change to kubeadm-init.yaml: configure advertiseAddress to the VIP
added section with instructions for configuring kubelet, kube-controller-manager and kube-scheduler to use the VIP

/cc @jbeda @timothysc @mattkelly

/assign @zacharysarah

/cc @mattkelly

/assign

@timothysc can you approve changes and provide lgtm? Then I can approve. Thanks.

/approve for doc review

@timothysc poke

@mbert I would fix the merge conflict myself, but since detiber has a couple of comments also, if you could respond and fix the merge conflict yourself that would be great. If you're not sure which version should go in, lmk. We've had a few oddnesses around exactly this place in this file. Thanks!

@Bradamant3 it looks like we have more than a merge problem here. Please take a look at the live documentation page:

I will take a closer look at this when at my box at work tomorrow. From what I see here I think we should first repair the page and then rebase my change.

OK @mbert after help all round in sig-docs, and with a few other formatting things still to be fixed on this page, #8663 is sorted and merged. Which means that the issue you note ^^ is fixed. Numbered lists are also fixed upstream. But there may be some other out-of-sync issues with other formatting; lmk if you have questions. There are still multiple other PRs in flight against this file; I've been trying to chain them appropriately, but I'm not sure I've always got it right and I apologize if I've inadvertently made things more difficult for you. Thanks for all your patience!

@Bradamant3 I have rebased and pushed my changes again. The result not only implements the PR's original purpose but also fixes the formatting issues.

re-adding lgtm per tech review; note that some formatting and list numbering issues remain in this file, but will be fixed in subsequent PRs. Need content here first.
/lgtm


Fix CI

The newly added test function "test_rb" in mc tests is specified for minio.
We have to remove it to work around.

@pwang7  Security audit can not be passed because rusoto is unmaintained now. Can we relax the limit of PR checks?


mssa.fit()出错

LoweringError: Failed at nopython (nopython mode backend)
Operands must be the same type, got (i64, i32)
File "Anaconda3\lib\site-packages\pymssa\optimized.py", line 226:
def incremental_component_reconstruction(trajectory_matrix,

components = np.zeros((P, N, rank))
^

[1] During: lowering "$0.7 = call $0.2($0.6, func=$0.2, args=[Var($0.6, C:\Users\Administrator\Anaconda3\lib\site-packages\pymssa\optimized.py (226))], kws=(), vararg=None)" at C:\Users\Administrator\Anaconda3\lib\site-packages\pymssa\optimized.py (226)

@xiaobai12321 thanks for submitting this. Unfortunately there is not enough information in this ticket to be able to reproduce the error you are seeing. Please follow the guidelines at:
https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports
to create a minimum working reproducer so that we can debug this issue further.

Probably a duplicate of https://github.com/numba/numba/issues/3910 and https://github.com/numba/numba/issues/5208.

Closing this issue due to lack of information. If more information becomes available please add it and reopen the issue. Thanks.


Add ZENGitHubApplicationNavigator

Navigate to the current Xcode directory in GitHub application

@zenangst thanks for your PR, but I don't think we should support Github application, it is not used by most people


Possible mistake in documentation of data-attribute?

In this section, we first introduce data-test-selector="post-title", but in the next example this becomes data-test-post-title. Is this a leftover from an older version (which I think it is, judging from the change history) or am I missing some piece?
I can make a PR for it, but I just wanted to make sure I'm not mistaken first.

Good catch! A PR is very welcome!
Can you also update the sentence in this section from … makes sure to remove all these data attributes in the … to … makes sure to remove all these data-test-* attributes in the …
Cheers.


fix：AnimatedImageView Highlight gif stop play

https://github.com/onevcat/Kingfisher/issues/1679

Do not worry about the tests. They are some GitHub runner issues.


Fix dead lock in setDataTTL method

Fix dead lock in setDataTTL method
JIRA:  https://issues.apache.org/jira/browse/IOTDB-2317

Coverage increased (+0.04%) to 67.584% when pulling 62c20c30156f94d0a2d6d5fe1b3882d3a3ff1903 on fix_ttl_dead_lock_xkf into 2ae5a52a354bc1a0c2f088767bbf4a2a763ec2dc on master.


console became sluggish with git 2.13

https://github.com/msys2/msys2/issues/33

Hey there! The link you posted seems to confirm a definite issue with Git on MSYS2, but since you've already posted an issue in MSYS2 proper, I'm not sure why you opened an issue here -- this repo is only for the package repository, and not Git or MSYS code itself.


Update version of rubies on Travis CI

Use latest version on Travis CI.
https://www.ruby-lang.org/en/news/2018/03/28/ruby-2-5-1-released/
https://www.ruby-lang.org/en/news/2018/03/28/ruby-2-4-4-released/
https://www.ruby-lang.org/en/news/2018/03/28/ruby-2-3-7-released/
https://www.ruby-lang.org/en/news/2018/03/28/ruby-2-2-10-released/

Thx, I'll merge this after figuring out why travis is failing already (usually a file change in some deps)

Thx 4 comment, I'll try to check it if possible.


Negative acknowledge doesn't work with message_id

The docs state:
    def negative_acknowledge(self, message):
        """
        Acknowledge the failure to process a single message.

        When a message is "negatively acked" it will be marked for redelivery after
        some fixed delay. The delay is configurable when constructing the consumer
        with {@link ConsumerConfiguration#setNegativeAckRedeliveryDelayMs}.

        This call is not blocking.

        Parameters
        ----------

        message:
            The received message or message id.
        """

Specifically, that you can pass either the message or the message id into the function. However, I don't believe this is correct, and passing the message id does not work. To reproduce this issue, first run a local pulsar standalone instance, via
docker run -it -p 6650:6650 -p 8080:8080 --tmpfs /pulsar/data apachepulsar/pulsar:3.1.0 bin/pulsar standalone

And then run the following code:
import pulsar

client = pulsar.Client("pulsar://localhost:6650")
producer = client.create_producer("persistent://public/default/tmp_example")
consumer = client.subscribe("persistent://public/default/tmp_example", "sub", negative_ack_redelivery_delay_ms=10)
producer.send(b"hello")
while True:
    msg = consumer.receive()
    message_id = msg.message_id()
    print(msg, message_id)
    # consumer.negative_acknowledge(msg) # This works and causes redelivery
    consumer.negative_acknowledge(msg.message_id())  # This does not cause redelivery

When you pass in the message_id, no redeliveries occur. When you comment out the last line and swap to passing in the message as a whole, redeliveries occur.
Why using the message id matters: Our services consume the pulsar messages and convert them into non-pulsar structures (like pydantic objects or other python classes). We attach the message id to those objects so we can ack/nack them as needed without storing the entire original pulsar message
I suspect the general acknowledge method has the same bug in it.

Yeah it's a bug that acknowledge also has the same issue.
https://github.com/apache/pulsar-client-python/blob/bf8524a858eae1eced14a283bbe7dffdee534742/pulsar/__init__.py#L1508
We should check more types here.

Oh, it's not the issue with type checking. It's a regression that was introduced by https://github.com/apache/pulsar-client-python/pull/121.

I will push a fix ASAP and include it in the incoming 3.4.0 release.


Fixes a clippy issue in main raised by rustc 1.61.0

Fixes a clippy issue in main where an async method was called while holding
the DB MutexGuard.
https://rust-lang.github.io/rust-clippy/master/index.html#await_holding_lock

ACK b67237e


webpack-dev-server changeOrigin option?

It seems like changeOrigin is a valid option for the webpack-dev-server proxy settings though I don't see it documented anywhere.
https://webpack.js.org/configuration/dev-server/
Should this be documented?  I am unsure what it's exact purpose is.

So where/how did you find that changeOrigin is a valid option?

webpack-dev-server passes the proxy options to the http-proxy-middleware which is linked to and documented in the proxy section of the dev-server page:
https://webpack.js.org/configuration/dev-server#proxy
The changeOrigin option is documented in the other package in their README. If it's not documented well enough, I would open an issue over there. Also, if you want to highlight the relationship between the two packages a bit more then feel free to submit a PR here as well but we shouldn't re-document all options (i.e. linking out is the right way to go so we don't duplicate existing documentation).

I saw the changeOrigin option in one of the examples in the old webpack documentation.
https://webpack.github.io/docs/webpack-dev-server.html#proxying-local-virtual-hosts

I found that it was a valid option b/c my proxy would not work without it.  I initially did not see the link you mentioned, thanks for the insight.

Ah ok... yeah like I said if you wanted to submit a PR here I'd be happy to review but imo there's plenty of docs on the proxy option already and the link to http-proxy-middleware is good. Like I said if anything, I think the link should be highlighted more so that it's as clear as possible that these options are actually handled by another package.
Thanks for highlighting this though and definitely feel free to submit a PR. I'll keep my eyes out for anyone mentioning something similar (which would definitely indicate that link should be highlighted).

changeOrigin is a very important option, as you can see in http-proxy code source, it's change the host header, could be necessary according the targeted server configuration.
if (options.changeOrigin) {
    outgoing.headers.host =
      required(outgoing.port, options[forward || 'target'].protocol) && !hasPort(outgoing.host)
        ? outgoing.host + ':' + outgoing.port
        : outgoing.host;
  }

I also think changeOrigin should be documented, the "documentation" link in webpack-dev-server's github repo is https://webpack.js.org/configuration/dev-server/#devserver, which jump to webpack documentation.

But I can't find anything about "changeOrigin" there.

Seems like changeOrigin is sent to option.changeOrigin of http-proxy-middleware, which is deprecated based on their README.md
DEPRECATED!

那么你在哪里/如何发现这changeOrigin是一个有效的选择？

hello


Asynchronous chunk mesh building

As of b6e27616622781353556ea83338ac76e2d149846 we build block meshes asynchronously (not only in one stage of rendering one frame). This is already a great improvement in throughput, but we'd like to do the same for chunk meshes, using the same job queue system. This requires more work:

[ ] The inputs to SpaceMesh::compute() need to be able to be owned by the chunk mesh jobs rather than borrowed:

[ ] Avoid having the Space borrowed, by copying the needed data into a structure.
[ ] Make the VersionedBlockMeshes data available in some shareable form. (This raises interesting questions about letting the chunk jobs use the very latest results of block mesh jobs.)

[ ] Generalize the job queue to have both kinds of jobs.
[ ] Maybe: Merge block mesh updates and chunk mesh updates into one phase of execution instead of two. This is a maybe because it might be tricky to get usefully non-stale chunks out of this — I'm not sure.

Another potential strategy is to build parts of individual chunk meshes in parallel with rayon. SpaceMesh is not quite amenable to efficient parallel accumulation, because vertex indices must be remapped appropriately in the final mesh, but it still might be a win since vertices are significantly more expensive than indices, and iterating over empty space can be freely done in parallel.


On-the-fly derivations' extraction: duplicate derivations

When derivations are generated from the final version of the hyper-graph (i.e., when no new nodes or arcs can be added to it), no derivation duplicates occur (see also related issue #8).
This is not true in case of the on-the-fly derivation process.

There were two reasons for this behavior:

For a given NewArcs modification we were looking at all ingoing arcs corresponding to the target node, while only the arcs specified in the modification should be considered,
A single arc was sometimes emitted more than once, most likely due to the fact that a single Foot arc (corresponding to foot adjoin) can be created, in the current implementation, more than once.


[QUESTION/HELP] Restart cluster after reboot

Question / Where do you need Help?
Is it possible to fully stop the cluster and restart its state after some reboots?
Scope of your Question
I am unable to restart the cluster after a reboot.. I've also tried to restart the server from the docker cli but still fails..
(base) [alvaro@stealth k3s-k3d]$  k3d cluster list
NAME   SERVERS   AGENTS   LOADBALANCER
k3s    0/1       0/3      true
(base) [alvaro@stealth k3s-k3d]$  k3d cluster start k3s
INFO[0000] Starting cluster 'k3s'
INFO[0000] Starting servers...
INFO[0000] Starting Node 'k3d-k3s-server-0'
ERRO[0000] Failed to start node 'k3d-k3s-server-0'
FATA[0000] Failed to start server k3d-k3s-server-0: Error response from daemon: failed to create endpoint k3d-k3s-server-0 on network k3d-k3s: failed to add the host (veth9a05999) <=> sandbox (veth94b2262) pair interfaces: operation not supported
[ble: exit 1]

(base) [alvaro@stealth k3s-k3d]$  kubectl cluster-info

To further debug and diagnose cluster problems, use 'kubectl cluster-info dump'.
The connection to the server <IP_ADDRESS>:38003 was refused - did you specify the right host or port?

(base) [alvaro@stealth ~]$  docker ps -a
CONTAINER ID   IMAGE                      COMMAND                  CREATED        STATUS                      PORTS     NAMES
7603064b9272   rancher/k3d-proxy:v4.4.6   "/bin/sh -c nginx-pr…"   30 hours ago   Exited (137) 21 hours ago             k3d-k3s-serverlb
da0513cca65c   rancher/k3s:v1.21.1-k3s1   "/bin/k3s agent"         30 hours ago   Exited (1) 21 hours ago               k3d-k3s-agent-2
6c889d3a76c6   rancher/k3s:v1.21.1-k3s1   "/bin/k3s agent"         30 hours ago   Exited (1) 21 hours ago               k3d-k3s-agent-1
0f5fee523308   rancher/k3s:v1.21.1-k3s1   "/bin/k3s agent"         30 hours ago   Exited (1) 21 hours ago               k3d-k3s-agent-0
29e03a86fed8   rancher/k3s:v1.21.1-k3s1   "/bin/k3s server --t…"   30 hours ago   Exited (1) 21 hours ago               k3d-k3s-server-0

Is your question related to a specific version of k3d (or k3s)?

Please paste the output of k3d version here
(base) [alvaro@stealth k3s-k3d]$  k3d --version k3d version v4.4.6 k3s version v1.21.1-k3s1 (default)

Hi @alborotogarcia , thanks for opening this issue!
What are your system specs?
This looks like docker is having an issue there. Can you start the containers manually via docker start?
Potentially related Serverfault thread (related to kernel upgrades): https://serverfault.com/questions/738773/docker-failed-to-add-the-pair-interfaces-operation-not-supported
And a related issue on Moby: https://github.com/moby/moby/issues/27426
Are you on Arch maybe?

Hi @iwilltry42 yes I'm on Arch Linux, recently got some upgrades and after a reboot everything is fine.. my bad , thanks !


empty projet failing to render

It's probably an issue which could be fixed by exchanging on a forum, but as renderchan doesn't have a large community yet and it might help to have a public answer (instead of bothering privately the dev team), I prefer to ask here as an issue.
I try to create a renderchan project "from scratch". I picked the project.conf from the sources and create a .blend file from scratch including a "intro.svg.png" dependency as included image in the VSE.
At no point, whether calling it with --deps or without, the "intro.svg.png" dependency tried to trigger a file generation (I've dived into debugging step by step and at no point the filename is even considered to find out which module would be usable to generate the missing file)
For the sake of understanding how to start a new project in renderchan without relying blindly on the provided template, I'd like to know what is missing to trigger deps generation.
Thanks in advance
(Attached is the empty project attempt.)
renderchan_simple_proj.tar.gz

Want to back this issue? Post a bounty on it! We accept bounties via Bountysource.

Looking at it more in details, it may be related to the way resources are added in the .blend file
It should be the rendered file in ./render which is used and not a file in the same directory as the source file. Does that sound right ?

@zeograd Yes, it sounds like you might have the rendered files in the wrong place. Ideally, you should just be able to call renderchan intro.svg and it will render that file to the correct place and you can use it in any other projects from there. Unfortunately it seems like there's a bug with our Inkscape rendering module at the moment, so your svg file will only render properly if in Inkscape you go to Document Properties and set the custom size to a whole number with px units.

Indeed, the issue was with the location of the included file.
So, for future reference, a fresh new project workflow could be

copy the default project.conf in your project directory
create placeholder dependecy files (.svg, .sifz, ...)
render them (calling renderchan without option on them directly)
create a project wide .blend file referencing rendered placeholders (in ./render)

From then on, one can edit the placeholders and the .blend main file and call renderchan to have the project rendered with the latest version of all of those.
Thanks for confirming my misundertanding !

It's probably an issue which could be fixed by exchanging on a forum, but as renderchan doesn't have a large community yet ...

I agree, it would be nice to set up a community support forum at some point! After we will release version 1.0, perhaps.

So, for future reference, a fresh new project workflow could be ...

Yes, this is exactly how we do! It is a shame I still cannot find a time to write a full-featured tutorial. ^^ " Thanks for writing a hint here! ^^


Fix #282 roundtrip error of defaultdict with object and with nested

Fix #282

Awesome, thanks for the fix.  Brilliant!


docs(zh-cn): Reviewed No. 21 - Preprocessing sentence pairs (PyTorch)

#390

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint.


All Good, But Errors on !fix Command

Hello, I installed the new version 1.9.2. All commands run, stream and switch work. Only that! Fix doesn't work. I upload error picture. And I also had a picture from earlier version 1.6. and 1.7. and no problems with it. Does anyone have any idea where to look for errors?

Hello Dinli800,
Thank you for reporting this bug.
I am still working on this version, you can download the latest release here: https://github.com/715209/nginx-obs-automatic-low-bitrate-switching/releases .

Hi,
Thanks for the quick answer, I have now loaded Release 1.9.1, after "npm install --production" this version works again with all commands. Excellent! Only I noticed it is 1.9.0 not 1.9.1, should this download be like that?

Hello Dinli800,
Yes that was a mistake by me it is version v1.9.1. And yes just download the source code.


Add WgsDataReleaseTest study

Create a study named "WgsDataReleaseTest" to represent the n=79 samples Joe has been using as a test set for WGS data release resources.

MATCH (s:Study)-[:HAS_PARTICIPANT]->(p:Participant)-[:IS]->(:Person)
WHERE s.name = "WgsDataReleaseTestSmall"
RETURN COUNT(p)

COUNT(p)
79

Used script (fa4b012) to add participants to study.


Unable to pull/push image from harbor registry with nerdctl

Description
Unable to pull/push image from harbor registry with nerdctl
Pre-condition:

Configure the harbor and expose it via ingress: example harbor.app.com
register it in containerd host.toml file:
cat /etc/containerd/certs.d/harbor.app.com/hosts.toml
server = "https://harbor.app.com"

[host."https://harbor.app.com/kubernetes"]
capabilities = ["pull", "resolve", "push"]
ca = "/etc/containerd/certs.d/harbor.app.com/ca.crt"
Steps to reproduce the issue

try to login to harbor.app.com with nerdctl: sudo nerdctl login harbor.app.com
try to push an image to it:  sudo nerdctl push harbor.app.com/kubernetes/nginx:latest
try to pull an image from registry: sudo nerdctl pull harbor.app.com/kubernetes/hello-world:1.2

Describe the results you received and expected
Actual results:
nms@node-1:~$ sudo nerdctl login harbor.app.com
WARNING: Your password will be stored unencrypted in /root/.docker/config.json.
Configure a credential helper to remove this warning. See
https://docs.docker.com/engine/reference/commandline/login/#credentials-store
Login Succeeded
nms@node-1:~$ sudo nerdctl push harbor.app.com/kubernetes/nginx:latest
INFO[0000] pushing as a reduced-platform image (application/vnd.oci.image.index.v1+json, sha256:3c2fec5591022af849f07e55835e15ac66258716b508fa6f1b82a5b5291c998f)
index-sha256:3c2fec5591022af849f07e55835e15ac66258716b508fa6f1b82a5b5291c998f:    done           |++++++++++++++++++++++++++++++++++++++|
manifest-sha256:3d696e8357051647b844d8c7cf4a0aa71e84379999a4f6af9b8ca1f7919ade42: done           |++++++++++++++++++++++++++++++++++++++|
config-sha256:66f8bdd3810c96dc5c28aec39583af731b34a2cd99471530f53c8794ed5b423e:   done           |++++++++++++++++++++++++++++++++++++++|
layer-sha256:57b64962dd94d4818372adf30dc0e2ca4803c46d4f638b7712fe01a149c705c5:    done           |++++++++++++++++++++++++++++++++++++++|
layer-sha256:8cc1569e58f52d008e232130d8fca2411f417ea423305cd7d7b513fb96d22947:    done           |++++++++++++++++++++++++++++++++++++++|
layer-sha256:362f35df001b4bd6f8733cd4abe8e1493582782404fefc2393129a5dfb5e72df:    done           |++++++++++++++++++++++++++++++++++++++|
layer-sha256:bc0965b23a04fe7f2d9fb20f597008fcf89891de1c705ffc1c80483a1f098e4f:    done           |++++++++++++++++++++++++++++++++++++++|
layer-sha256:13e320bf29cd3ef51b06a3dfe259b2582d48be27a9ac4c6b7af6fbb99429d210:    done           |++++++++++++++++++++++++++++++++++++++|
layer-sha256:7b50399908e1c0958c409f3c844d61736fd41e37a58dca4832927715508dd3aa:    done           |++++++++++++++++++++++++++++++++++++++|
layer-sha256:650ee30bbe5efddbef9cc0245ba52b133d3c8897a6565faa6c5c87bc552b5305:    done           |++++++++++++++++++++++++++++++++++++++|
elapsed: 0.1 s                                                                    total:  913.0  (8.9 KiB/s)
FATA[0000] failed commit on ref "index-sha256:3c2fec5591022af849f07e55835e15ac66258716b508fa6f1b82a5b5291c998f": unexpected status from PUT request to https://harbor.app.com/kubernetes/v2/kubernetes/nginx/manifests/latest: 405 Not Allowed
nms@node-1:~$ sudo nerdctl pull harbor.app.com/kubernetes/hello-world:1.2
WARN[0000] reference for unknown type: text/html         digest="sha256:b6a377d90af951a0588dd82b1d02c6517ba29042f1f5136de1ebdb88df5b4602" mediatype=text/html size=785
FATA[0000] failed to unpack image on snapshotter overlayfs: unexpected media type text/html for sha256:b6a377d90af951a0588dd82b1d02c6517ba29042f1f5136de1ebdb88df5b4602: not found
nms@node-1:~$
What version of nerdctl are you using?
nms@node-1:~$ sudo nerdctl version
Client:
Version:       v2.0.2
OS/Arch:       linux/amd64
Git commit:    1220ce7ec2701d485a9b1beeea63dae3da134fb5
buildctl:
Version:      v0.18.1
GitCommit:    eb68885955169461d72dc2b7e6d084100fcaba86
Server:
containerd:
Version:      1.7.12
GitCommit:
runc:
Version:      1.2.2
GitCommit:    v1.2.2-0-g7cb36325
Are you using a variant of nerdctl? (e.g., Rancher Desktop)
None
Host information
However I have an external ubuntu machine where I have docker on it and harbor.app.com as insecure registry, and I am able to pull push images to that registry that runs on k8s cluster from where I use nerdctl trying to pull/push images.
nms@nfs:~$ docker push harbor.app.com/kubernetes/hello-world:1.2
The push refers to repository [harbor.app.com/kubernetes/hello-world]
ac28800ec8bb: Layer already exists
1.2: digest: sha256:d37ada95d47ad12224c205a938129df7a3e52345828b4fa27b03a98825d1e2e7 size: 524
nms@nfs:~$ cat /etc/docker/daemon.json
{
"insecure-registries": ["harbor.app.com"]
}
nms@nfs:~$

405 is Harbor refusing to serve the requests.
This is somewhat typical when the ingress rules are pointing to the wrong location IIRC.
Can you share how exactly you started and configured Harbor?
Also, can you re-run your nerdctl pull and push commands with the extra argument --debug-full
Thanks.


[embed] Consider removing support for hide-filter and don't hide-filter when the list is hidden

Previously, hide-filter was an option that was given because the filters took a lot of height for iframes. If we don't have pushback from partners, we should consider removing the ability to remove this as we don't have this issue anymore.
Furthermore, hide-list=true should not remove the filters. Again we did that because most partners were trying to save height but this is not an issue anymore.

This is done through: https://github.com/findthemasks/findthemasks/pull/896


UVI Request

--- UVI JSON ---
{
  "vendor_name": "Linux",
  "product_name": "Kernel",
  "product_version": "versions from  to before v5.10.77",
  "vulnerability_type": "unspecified",
  "affected_component": "unspecified",
  "attack_vector": "unspecified",
  "impact": "unspecified",
  "credit": "",
  "references": [
    "https://git.kernel.org/pub/scm/linux/kernel/git/stable/linux.git/commit/?id=693ecbe8f799405f8775719deedb1f76265d375a"
  ],
  "extended_references": [
    {
      "type": "commit",
      "value": "693ecbe8f799405f8775719deedb1f76265d375a",
      "note": "fixed"
    }
  ],
  "reporter": "joshbressers",
  "reporter_id": 1692786,
  "notes": "",
  "description": "usbnet: sanity check for maxpacket\n\nThis is an automated ID intended to aid in discovery of potential security vulnerabilities. The actual impact and attack plausibility have not yet been proven.\nThis ID is fixed in Linux Kernel version v5.10.77 by commit 693ecbe8f799405f8775719deedb1f76265d375a. For more details please see the references link."
}
--- UVI JSON ---

This issue has been assigned UVI-2021-1002056


Update Auth to use OAuth2

Using oauth2, as googlesheets4 does here, would tear down the very common barrier to entry for prospective users of finding, encrypting, and managing their API keys.

in the interim, could hotfix payloads to autoregister options, as this seems to be a consistent barrier to entry


Added ats_checking feature in resume suggestions

All checks have passed so merging it to release1.1.0


print to the log output when a workspace mapping fails

@ericsciple There was a discussion on this a week ago or so, this is just following through with the change.

@moswald why only change those 3 Debug() to Output()?
Will this causing noisy log for success case? if you think those information are critical, you can buffer them with StringBuilder and print the result only when not match.
Double check what the output looks like for hosted build, i remembered we did something special for hosted build with TFVC.

@TingluoHuang The scope of the change was just for failed mappings for Tfvc workspaces. These will only show if a candidate workspace has matched all the other requirements (name, machine, mapping count, etc).

@moswald i am going to resolve the conflict and merge it for you. #1652
i am in the process of releasing agents, i will include this PR in this release.

@TingluoHuang Thanks, I completely forgot about this PR.


Unhandled Exception: 'rights' (type: KeyError)

I see this error in master (4aa27f0c6bdf393090856a07c955a65b10841e74) version of this repository. Please let me know how to fix ?

Some information about my environment.
cat /etc/os-release
NAME="Pop!_OS"
VERSION="22.04 LTS"
ID=pop
ID_LIKE="ubuntu debian"
PRETTY_NAME="Pop!_OS 22.04 LTS"
VERSION_ID="22.04"
python3 --version
Python 3.10.6

Update it. You are literally using super-old code from one of first commits from 2020..


sct_deepseg is very slow

Example below:
sct_deepseg -i t2.nii.gz -task seg_mice_gm-wm_dwi
real	5m15.583s
user	4m43.707s
sys	0m32.558s

In comparison, sct_deepseg_sc takes . It would be worth investigating what is the source of the slowdown.
time sct_deepseg_sc -i t2.nii.gz -c t2
real	0m5.713s
user	0m11.626s
sys	0m1.802s

Note: this is task-dependent. For example, with another task, processing is much faster:
time sct_deepseg -i t2.nii.gz -task seg_sc_t2star
real	0m26.908s
user	0m24.258s
sys	0m4.236s

@charleygros is it because the task seg_mice_gm-wm_dwi includes a very large upsampling?

@charleygros is it because the task seg_mice_gm-wm_dwi includes a very large upsampling?

Yes, I believe this is exactly why: we are resampling to 0.1mm in the cross-sectional plane (because the training data was at this resolution).

Thank you for your insights @charleygros. I am still wondering if processing time can be improved. More specifically: does the slowness come from the resampling or the DP part?

The DL model is certainly heavier than the other models you mentioned (bigger field of view as input, deeper model in terms of layers), which could slow down the model loading.
I do think that the resampling then 3d Nib reconstruction (ie downsampling) slows the process down.
SOmething else I am considering: use the onnx model (instead of the pt version). I'm adding this to my investigations (w AP flipped data).


Notes on docs

I've gone through everything in readthedocs that isn't the API. These are my observations.
Introduction

[ ] We should change pip install pbjam to pip install pbjam –user

Session

[ ] Since this is the quickstart guide, we should add a couple of comments into the first sell, specifically on the make_plots and path parameters explaining exactly what they do.

[ ] On that note, we should showcase what the output looks like, maybe by reading it in as a pandas dataframe and printing the head.

[ ] It would be neat if we added a little sentence or two about the star this notebook looks at with a hyperlink to the paper we take the numax, deltanu and teff from. Gives new users a foothold.

[ ] We should delete the empty bottom cell to make it a little tidier :)

[ ] We should expand the acronym HMC to Hamiltonian Monte Carlo (HMC), as theres no hyperlink to an explanation.

All the hyperlinks work a-ok.
Star

[ ] In the first paragraph of ‘preparing the data’, the lightkurve.periodogram appears as a funky hyperlink that doesn’t go anywhere.

[ ] There is a cell, lc0.plot(), which should show the plot underneath it but doesn’t.

[ ] We should

import warnings
warnings.filterwarnings(‘ignore’)

To avoid that annoying AstropyDepricationWarning popping up in our nice example.

[ ] We should add a note when using pg.flatten() that this is sub-optimal compared to a fit to the granulation background.

[ ] Pg.plot() should show a plot, ideally.

[ ] When calling pb.star, add a note that we’re not using the path parameter and that therefore our data will save in our working directory.

[ ] ‘The next step is to fit asymptotic’ should be ‘The next step is to fit an asyptotic’ or ‘The next step is to fit the asymptotic (with reference here)’

[ ] Still a citation needed for glitches.

[ ] When calling pb.peakbag, specify that star.f and star.s are the frequency and power of our periodogram.

[ ] Remove the last empty cell to make it look tidier :)

Hyperlinks work a-ok.

Advanced

[ ] We should turn off warnings

[ ] Top between cells 10 and 11, it’s should be its.

[ ] Between the first two equations in the asy_peakbag section theres a broken latex command.

[ ] Earlier in the epsilon section, you say that we will explain what the epsilon parameter is later. In the asy_peakbag section where you note the asymptotic relation and explain the parameter epsilon, I would add a little line that says ‘…is commonly referred to as an offset, and is the parameter we calculated using the epsilon function above’ or something to that effect.

[ ] After the equation for mode height there is a broken latex command.

[ ] Cell 28 has an error output at the moment

[ ] In the second paragraph of the peakbag section theres an ‘inn’ which should be ‘in’.

[ ] In the following paragraph theres a typo ‘develope’.

[ ] If we’re being pedantic (and why note), pymc3 should be PyMC3 in all instances.

[ ] There’s still a TODO in here!

[ ] Theres a typo ‘perfrect’

[ ] There’s a typo ‘differnet’

[ ] I would add a dashed line at the 0 mark in cell 35, but looks like this section isn’t fully complete yet :)

Help & Contact

[ ] We should add my email to the Help & Contact.

Done with comments! As for the level of the content in the Advanced notebook (which looks sick, btw), we should give it to somebody with statistics skill but no involvement in this program to see if they can follow. Alex is a good shout, or perhaps Bill.

Thanks for the comments Oli, I don't have power on my laptop (forgot adapter at airbnb)
I'll fix session and star tomorrow.

Bill had the following comments:

[ ] Front page:   Tweak first line to “… oscillation spectra of solar-like oscillators.”
[ ] “… with much fewer priors in place” Than what?
[ ] Straight-forward à straightforward (more than one instance)
[ ] Use guide: shown in the example below à shown in the examples below
[ ] API: PBJam is can -> PBJam can

Bill also said:

This is then confusing: “This allows for a more accurate model of the spectrum of frequencies, than the heavily parameterized models like the asymptotic relation.”, because the preceding paragraph says PBJam fits the asymptotic relation; I understand it’s the mode ID that is based on the asymptotic relation, not the actual bagging. Needs a tweak to the wording just to be clear (I had to re-read a couple of times before the difference hit home).

[ ] Tweak wording to reflect this.

Great job everyone - I think we have done all we can here for now.  I'm closing and we can make new issues as problems occur.
Thanks everyone - sterling work!


api: fix cors comment

I didn't find magical code convert the RuntimeFractionalPercent to 100/HUNDRED.
I have a messy test case in #6570 to verify but that test breaks many other things.
Signed-off-by: Yuchen Dai<EMAIL_ADDRESS>

@dschaller PTAL if you have a sec.

@dschaller I appreciate your reasoning!
Your original comment is subtle but correct. Abandon this PR.


I can't run any script?

Hi, i get this error every time:
2016-07-08 02:11:50 [boto] DEBUG: Retrieving credentials from metadata server.
2016-07-08 02:11:51 [boto] ERROR: Caught exception reading instance data
Traceback (most recent call last):
  File "/usr/local/lib/python2.7/dist-packages/boto/utils.py", line 211, in retry_url
    r = opener.open(req, timeout=timeout)
  File "/usr/lib/python2.7/urllib2.py", line 429, in open
    response = self._open(req, data)
  File "/usr/lib/python2.7/urllib2.py", line 447, in _open
    '_open', req)
  File "/usr/lib/python2.7/urllib2.py", line 407, in _call_chain
    result = func(*args)
  File "/usr/lib/python2.7/urllib2.py", line 1228, in http_open
    return self.do_open(httplib.HTTPConnection, req)
  File "/usr/lib/python2.7/urllib2.py", line 1198, in do_open
    raise URLError(err)
URLError: <urlopen error timed out>
2016-07-08 02:11:51 [boto] ERROR: Unable to read instance data, giving up

This is full log:
/home/jan/Documents/frontera/examples/scrapy_recording/scrapy_recording/spiders/recorder.py:29: ScrapyDeprecationWarning: SgmlLinkExtractor is deprecated and will be removed in future releases. Please use scrapy.linkextractors.LinkExtractor
  RegexLinkExtractor(allow=ALLOWED_RE),
2016-07-08 02:11:49 [scrapy] INFO: Scrapy 1.0.3 started (bot: scrapy_frontier)
2016-07-08 02:11:49 [scrapy] INFO: Optional features available: ssl, http11, boto
2016-07-08 02:11:49 [scrapy] INFO: Overridden settings: {'NEWSPIDER_MODULE': 'scrapy_recording.spiders', 'CONCURRENT_REQUESTS_PER_DOMAIN': 2, 'CONCURRENT_REQUESTS': 256, 'RETRY_ENABLED': False, 'SPIDER_MODULES': ['scrapy_recording.spiders'], 'HTTPCACHE_ENABLED': True, 'BOT_NAME': 'scrapy_frontier', 'DOWNLOAD_TIMEOUT': 20, 'COOKIES_ENABLED': False, 'SCHEDULER': 'frontera.contrib.scrapy.schedulers.recording.RecorderScheduler', 'LOGSTATS_INTERVAL': 10}
2016-07-08 02:11:49 [scrapy] INFO: Enabled extensions: CloseSpider, TelnetConsole, LogStats, CoreStats, SpiderState
2016-07-08 02:11:49 [py.warnings] WARNING: /usr/local/lib/python2.7/dist-packages/frontera/contrib/scrapy/schedulers/recording.py:5: ScrapyDeprecationWarning: Module `scrapy.log` has been deprecated, Scrapy now relies on the builtin Python library for logging. Read the updated logging entry in the documentation to learn more.
  from scrapy import log

2016-07-08 02:11:50 [boto] DEBUG: Retrieving credentials from metadata server.
2016-07-08 02:11:51 [boto] ERROR: Caught exception reading instance data
Traceback (most recent call last):
  File "/usr/local/lib/python2.7/dist-packages/boto/utils.py", line 211, in retry_url
    r = opener.open(req, timeout=timeout)
  File "/usr/lib/python2.7/urllib2.py", line 429, in open
    response = self._open(req, data)
  File "/usr/lib/python2.7/urllib2.py", line 447, in _open
    '_open', req)
  File "/usr/lib/python2.7/urllib2.py", line 407, in _call_chain
    result = func(*args)
  File "/usr/lib/python2.7/urllib2.py", line 1228, in http_open
    return self.do_open(httplib.HTTPConnection, req)
  File "/usr/lib/python2.7/urllib2.py", line 1198, in do_open
    raise URLError(err)
URLError: <urlopen error timed out>
2016-07-08 02:11:51 [boto] ERROR: Unable to read instance data, giving up
2016-07-08 02:11:51 [scrapy] INFO: Enabled downloader middlewares: HttpAuthMiddleware, DownloadTimeoutMiddleware, UserAgentMiddleware, DefaultHeadersMiddleware, MetaRefreshMiddleware, HttpCompressionMiddleware, RedirectMiddleware, ChunkedTransferMiddleware, DownloaderStats, HttpCacheMiddleware, SchedulerDownloaderMiddleware
2016-07-08 02:11:51 [scrapy] INFO: Enabled spider middlewares: HttpErrorMiddleware, OffsiteMiddleware, RefererMiddleware, UrlLengthMiddleware, DepthMiddleware, SchedulerSpiderMiddleware
2016-07-08 02:11:51 [scrapy] INFO: Enabled item pipelines:
2016-07-08 02:11:51 [scrapy] INFO: Spider opened
2016-07-08 02:11:51 [py.warnings] WARNING: /usr/local/lib/python2.7/dist-packages/frontera/contrib/scrapy/schedulers/recording.py:65: ScrapyDeprecationWarning: log.msg has been deprecated, create a python logger and log through it instead
  log.msg('Starting recorder', log.INFO)

2016-07-08 02:11:51 [scrapy] INFO: Starting recorder
2016-07-08 02:11:51 [scrapy] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min)
2016-07-08 02:11:51 [scrapy] DEBUG: Telnet console listening on <IP_ADDRESS>:6024
2016-07-08 02:11:51 [scrapy] DEBUG: Redirecting (302) to <GET https://diffeo.com/> from <GET http://diffeo.com>
2016-07-08 02:11:51 [scrapy] DEBUG: Crawled (200) <GET https://diffeo.com/> (referer: None) ['cached']
2016-07-08 02:11:51 [scrapy] INFO: Closing spider (finished)
2016-07-08 02:11:51 [py.warnings] WARNING: /usr/local/lib/python2.7/dist-packages/frontera/contrib/scrapy/schedulers/recording.py:83: ScrapyDeprecationWarning: log.msg has been deprecated, create a python logger and log through it instead
  log.msg('Finishing recorder (%s)' % reason, log.INFO)

2016-07-08 02:11:51 [scrapy] INFO: Finishing recorder (finished

I tested on examples/scrapy_recording and examples/general-spider.
I have started db-worker but I don't think that this could be the problem.
Any idea? Btw. I think frontera is a bit buggy. I had to fix some frontera code in graph manager importing.

Hi @Bundas, it looks like your code is somehow interacts with boto. You didn't posted your configs, so I can't say where the problem is exactly, but I can assume you're trying to read seeds from s3 bucket and URL isn't accessible. So recommendation is to check my assumption, if it's wrong then post your Scrapy and Frontera settings files.
graph manager and scrapy_recording are quite untouched components for a long time, so it's probable there are some problems, please don't hesitate to submit PRs if you think your patches worth merging.

can we close that @Bundas ?


[SPARK-31242][SQL][TEST] mergeSparkConf in WithTestConf should also respect spark.sql.legacy.sessionInitWithConfigDefaults

What changes were proposed in this pull request?

Make mergeSparkConf in WithTestConf respects spark.sql.legacy.sessionInitWithConfigDefaults.
Why are the changes needed?

Without the fix, conf specified by withSQLConf can be reverted to original value in a cloned SparkSession.  For example, you will fail test below without the fix:
withSQLConf(SQLConf.CODEGEN_FALLBACK.key -> "true") {
  val cloned = spark.cloneSession()
  SparkSession.setActiveSession(cloned)
  assert(SQLConf.get.getConf(SQLConf.CODEGEN_FALLBACK) === true)
}

Does this PR introduce any user-facing change?

No.
How was this patch tested?

Added tests.

Test build #120314 has started for PR 28014 at commit 7bf6e76.

Merged build finished. Test PASSed.

Test PASSed.
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Test PASSed.

cc @cloud-fan @jose-torres

Test build #120314 has finished for PR 28014 at commit 7bf6e76.

This patch fails due to an unknown error code, -9.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test FAILed.

Test FAILed.
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Test FAILed.

retest this please

Test build #120319 has started for PR 28014 at commit 7bf6e76.

Merged build finished. Test PASSed.

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Test PASSed.

Test build #120332 has started for PR 28014 at commit c37fc77.

Test build #120319 has finished for PR 28014 at commit 7bf6e76.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test PASSed.

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Test PASSed.

Test build #120332 has finished for PR 28014 at commit c37fc77.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test PASSed.

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Test PASSed.

thanks, merging to master/3.0!

thanks!


Not working on android with firefox??

I tried going to your test page:
https://chalda-pnuzig.github.io/SimpleSearchableSelect/demo/
on an android device. When I used chrome in an enhanced multiselect, my matches were displayed in a
horizontally scrolling line of pills along the bottom of the page and I could select it by clicking.
When I did the same with firefox, there was nothing displaying the matches. Any ideas?

Apparently a known bug: https://bugzilla.mozilla.org/show_bug.cgi?id=1535985

On firefox if I click on the input and then click it again the datalist appears:


igv: 2.14.1 -> 2.15.1

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://repology.org/metapackage/igv/versions.
meta.description for igv is: "A visualization tool for interactive exploration of genomic datasets"
meta.homepage for igv is: "https://www.broadinstitute.org/igv/"
meta.changelog for igv is: ""
Updates performed

Version update

To inspect upstream changes
Impact

Checks done (click to expand)

built on NixOS
The tests defined in passthru.tests, if any, passed
found 2.15.1 with grep in /nix/store/8841wvxv1g8a3sdvhdbpbwnkh9cxl2j1-igv-2.15.1
found 2.15.1 in filename of file in /nix/store/8841wvxv1g8a3sdvhdbpbwnkh9cxl2j1-igv-2.15.1

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

1 total rebuild path(s)

1 package rebuild(s)

First fifty rebuilds by attrpath
igv

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/8841wvxv1g8a3sdvhdbpbwnkh9cxl2j1-igv-2.15.1 \
  --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 igv https://github.com/r-ryantm/nixpkgs/archive/0b00111782afd70b6215d2b1310b3e18595c4c05.tar.gz

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/8841wvxv1g8a3sdvhdbpbwnkh9cxl2j1-igv-2.15.1
ls -la /nix/store/8841wvxv1g8a3sdvhdbpbwnkh9cxl2j1-igv-2.15.1/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 run on x86_64-linux 1

1 package built:

igv

Maintainer pings
cc @mimame for testing.

@ofborg eval


keybase.pub returns 404 for existing file (intermittently)

For example: https://yan12125.keybase.pub/arch-repo/yan12125-testing/yan12125-testing.db is sometimes 200 and sometimes 404.

I got no more 404 errors for existing files. I presume this is fixed and can be closed?

Yep thanks.


not working

If I enter a level, it keeps saying "Head into a level to start!".
Can someone fix this for me?
Thanks.

Download latest version
On Tue, 10 May 2022 at 16:54, andrei1010gaming @.***>
wrote:

If I enter a level, it keeps saying "Head into a level to start!".
Can someone fix this for me?
Thanks.
—
Reply to this email directly, view it on GitHub
https://github.com/decoder0007/PosBor/issues/3, or unsubscribe
https://github.com/notifications/unsubscribe-auth/AMASUCJ7JT652WOBXS2YUB3VJKBD7ANCNFSM5VSCEY5Q
.
You are receiving this because you are subscribed to this thread.Message
ID: @.***>

What other mods do you have installed?
On Tue, 10 May 2022 at 16:57, andrei1010gaming @.***>
wrote:

@decoder0007 https://github.com/decoder0007 already did
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https://github.com/decoder0007/PosBor/issues/3#issuecomment-1122585739,
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You are receiving this because you were mentioned.Message ID:
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gdshare
invisible dual bugfix
run info
betterinfo
betteredit
Mega Hack v7
(my mods)

nvm i fixed it with deleting mods

It’s run info
On Wed, 11 May 2022 at 13:08, andrei1010gaming @.***>
wrote:

nvm i fixed it with deleting mods
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Use wazero based SQLite bindings.

Since you're using wazero to avoid cgo in #3027 and #3042 I though you might want to consider using my wazero based SQLite bindings: github.com/ncruces/go-sqlite3.
They're no where near as battle tested as #3040, so feel free to close this.

@ncruces Appreciate the pull request. I actually switched from mattn/go-sqlite3 to modernc.org/sqlite a few days in https://github.com/sqlc-dev/sqlc/pull/3040. That removes our cgo dependency for now.

Sure, makes sense.
If you ever feel like it's worth it to consolidate dependencies, now you know it exists.


DNA synthesis/DNA replication question

Hullo!
Looking at the annotation of replicative polymerases.
The current structure of the ontology means we want to annotate with:
GO:0006261 	DNA-dependent DNA replication
we have to remember to also co-annotate with:
GO:0090592 	DNA synthesis involved in DNA replication
so that it can be found under
DNA biosynthetic process
and
DNA replication
As many of these mutants are lethal, there is a lot of in vitro experiments - and so not many chances to annotate the experimental work with
GO:1904860 | DNA biosynthetic process involved in mitotic DNA replication
which "bags" both branches.
There may be a very good reason why not, but any chance of a:
DNA synthesis involved in DNA-dependent DNA replication??

Adding to this, if one were to annotate to
-mitochondrial DNA replication
we have to remember to co-annotate with a biosynthesis branch term:

I think "mitochondrial DNA replication" could go under biosynthesis.
The reason for the difference in nuclear replication is that not all replication is biosynthetic. I can't remember why (@mah11 will know). To me now this seems odd but I think it is that some of the subprocesses are not biosynthetic processes (possibly something to do with primer degradation during removal caused TPVs?).
If this is the case, i can't think of any immediate reason why "mitochondrial DNA replication" cannot go directly under "DNA synthesis involved in DNA replication" (giving it the DNA biosyntheic process parent) , because it's all equivalent to "leading strand synthesis"

The reason for the difference in nuclear replication is that not all replication is biosynthetic

No; it's that DNA replication involves more than just DNA synthesis.
The same may be true for mitochondrial DNA replication, at least in some systems. I don't know it well, but a brief search suggests that different mechanisms exist, e.g.
https://academic.oup.com/jb/article/164/3/183/5040786
http://www.biochemsoctrans.org/content/45/2/513

I still think this is odd. To all intents and purposes DNA replication is a biosynthetic process. Which "parts" are not biosynthesis?

primers are made of RNA

Got it. So DNA replication is part of "cellular biosynthetic process", but not part_of DNA biosynthesis.

So the "involved in" might be a good fudge?
e.g.
DNA synthesis involved in DNA-dependent DNA replication
DNA synthesis involved inmitochondrial DNA replication
It would be helpful to users coming from a top-down query point-of-view.

So DNA replication is part of "cellular biosynthetic process",

I don't know the intended scope of that grouping term, so I'm not in a position to comment.

In these cases I think it is clearer if the terms are worded
DNA-dependent DNA replication, DNA synthesis
this matches
GO:0006269    DNA replication, synthesis of RNA primer
and it is clearer that this is a sub-part of the process.
To me,
DNA synthesis involved in DNA-dependent DNA replication
just looks confusing....

i agree that this term isn't great and could at turn users off: DNA synthesis involved in DNA-dependent DNA replication

As long as the inheritance works, I don't mind!

@vanaukenk, others: any more views/progress on this one?
I'm particularly keen to have "mitochondrial DNA replication (GO:0006264)" put under the "DNA biosynthetic process (GO:0071897)" branch (see Val's comment above).
Thanks, Steven

@sjm41
As @hattrill suggested, how about we create the new term, 'DNA synthesis involved in mitochondrial DNA replication' and position it in the ontology as follows:
is_a DNA biosynthetic process (GO:0071897)
part_of mitochondrial DNA replication (GO:0006264)

DNA synthesis involved in mitochondrial DNA replication (GO:new)

and defined as:
"Any DNA biosynthetic process that is involved in mitochondrial DNA replication."
We could use Midori's two reviews above as definition xrefs, but I'm happy to add more papers if you have some from your curation.

Thanks @vanaukenk - this approach sounds good.
But wouldn't the new term be a is_a child of "DNA synthesis involved in DNA replication" (GO:0090592) rather than "DNA biosynthetic process" (GO:0071897)?
(see Helen's screenshot in her second post above).
Then the new term would be a 'sister' term to the existing "DNA biosynthetic process involved in mitotic DNA replication" (GO:1904860).
On that note, it would be good to use the same wording for these two sister terms  - e.g. use "DNA synthesis involved in..." for both.

@sjm41
Yes, you're right about the more granular parent, and the wording for all of the terms should be the same, although it looks like we have both versions throughout this part of the ontology with some terms having synonyms and not others.
@ukemi - do you have opinions on which language should prevail: 'DNA biosynthetic process' vs 'DNA synthesis' ?

It's kind of a toss-up. I think the community uses DNA synthesis more that biosynthesis, but to keep internally consistent in the ontology with other terms, biosynthesis would be more appropriate. Our general rule is to use what is used by the community and then make a synonym for people who are searching across the ontology.

Pubmed:
"DNA synthesis" ~45,500
"DNA biosynthesis" ~34,000

Thanks, @ukemi
For these child terms, I'll go with "DNA synthesis" and make sure all of the appropriate synonyms are there.


[type:fix] Fix the wrong request type

Fixes #4974
Make sure that:

[x] You have read the contribution guidelines.
[ ] You submit test cases (unit or integration tests) that back your changes.
[x] Your local test passed ./mvnw clean install -Dmaven.javadoc.skip=true.

Codecov Report

Merging #4975 (ff867c2) into master (a6a56cf) will increase coverage by 0.01%.
Report is 5 commits behind head on master.
The diff coverage is 0.00%.

@@             Coverage Diff              @@
##             master    #4975      +/-   ##
============================================
+ Coverage     63.93%   63.95%   +0.01%
- Complexity     8528     8541      +13
============================================
  Files          1208     1208
  Lines         35899    35903       +4
  Branches       3217     3218       +1
============================================
+ Hits          22953    22961       +8
+ Misses        11095    11091       -4
  Partials       1851     1851

Files Changed
Coverage Δ

.../java/org/apache/shenyu/admin/utils/HttpUtils.java
35.35% <0.00%> (-1.37%)
:arrow_down:

... and 4 files with indirect coverage changes
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